Critical Reflection

Word counts

It is an important academic and practical skill to be able to communicate succinctly. It is expected that students will adhere to the word limits and not exceed the prescribed limit by more than 2000 words including in-text citations and the reference list. Except in previously approved circumstances, appendices should not be included to accommodate extra words. All text included in the assessment will be included in the word count (as determined by Turnitin).

Assessment : Critical Reflection ( Essay)

Word limit / length 2000 words

Overview

PLEASE GO TO: CONSENSUS STATEMENT, www.equallywell.org.au

In 2017 the National Mental Health Commission launched “Equally Well”, which they say aims to improve quality of life of people living with mental illness by providing equal access to quality health care. By championing physical health as a priority, Equally Well ultimately aims to reduce the life expectancy gap that exists between people living with a mental illness and the general population. Some seventy state, territory and federal organisations endorsed a national consensus statement.

The National Consensus commences with an assumption that “providing equity of access to quality health care” will bridge the life expectancy gap between people living with mental illness and the general population.

This critical reflection is designed to show that you can review the individual, social and symptomatic-generated influences on consumer’s physical wellbeing.

PLEASE GO TO: CONSENSUS STATEMENT, www.equallywell.org.au

Learning outcomes

This assessment task is aligned to the following learning outcomes:

1. Appraise the range of barriers that consumers have to achieving physically healthy lifestyles

Assessment details

Write a critical reflection which critiques the ‘Equally Well’ campaign. Provide the following in your writing:

1. An outline of the evidence that people with mental illness do not currently enjoy “equity of access” to quality health care.

2. Reference to the literature on determinants of health and wellbeing outline factors, other than access to health care, which may contribute to poor physical health in people diagnosed with mental illness.

3. Include in your discussion a justification for why nutrition, exercise-based interventions, and pharmacological treatments should be provided to people diagnosed with mental illness.

Assessment rubric

Criterion;

Introduction & Conclusion : (10%)

Excellent introduction. Clear and succinct. Outstandingly written conclusion.

Presentation of arguments and evidence that people with mental illness do not enjoy “equity of access” to quality health care: (30%)

Key arguments described. Erudite description of key hypothesised concepts (e.g. diagnostic overshadowing) and extant evidence of inequitable access outlined across a range of health care settings

Outline factors other than access to health care which may contribute to poor physical health in people diagnosed with mental illness:

(50%)

Both logic and empirical data are presented in support of arguments for specific determinants of health contributing to poor physical health in people diagnosed with mental illness. An understanding of the intertwined aetiology of physical, mental and social problems is clearly articulated.

Writing, grammar and referencing: (10%)

Clear, crisp and coherent style. Very well organised. Free of grammar and spelling errors. All citations follow required style.

Currie et al. BMC Health Services Research 2014, 14:404
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RESEARCH ARTICLE Open Access

Examining the relationship between health-related
need and the receipt of care by participants
experiencing homelessness and mental illness
Lauren B Currie*, Michelle L Patterson, Akm Moniruzzaman, Lawrence C McCandless and Julian M Somers

Abstract

Background

: People experiencing homelessness and mental illness face multiple barriers to care. The goal of this study
was to examine the association between health service use and indicators of need among individuals experiencing
homelessness and mental illness in Vancouver, Canada. We hypothesized that those with more severe mental illness
would access greater levels of primary and specialist health services than those with less severe mental illness.

Methods

: Participants met criteria for homelessness and current mental disorder using standardized criteria (n = 497).
Interviews assessed current health status and involvement with a variety of health services including specialist, general
practice, and emergency services. The 80th percentile was used to differentiate ‘low health service use’ and ‘high health
service use’. Using multivariate logistic regression analysis, we analyzed associations between predisposing, enabling
and need-related factors with levels of primary and specialist health service use.

Results

: Twenty-one percent of participants had high primary care use, and 12% had high use of specialist services.
Factors significantly (p ≤ 0.05) associated with high primary care use were: multiple physical illnesses [AOR 2.74 (1.12,
6.70]; poor general health [AOR 1.68 (1.01, 2.81)]; having a regular family physician [AOR 2.27 (1.27, 4.07)]; and negative
social relationships [AOR 1.74 (1.01, 2.99)]. Conversely, having a more severe mental disorder (e.g. psychotic disorder)
was significantly associated with lower odds of high service use [AOR 0.59 (0.35, 0.97)]. For specialist care, recent history
of psychiatric hospitalization [AOR 2.53 (1.35, 4.75)] and major depressive episode [AOR 1.98 (1.11, 3.56)] were associated
with high use, while having a blood borne infectious disease (i.e., HIV, HCV, HBV) was associated with lower odds of high
service use.

Conclusion

s: Contrary to our hypotheses, we found that individuals with greater assessed need, including more
severe mental disorders, and blood-borne infectious diseases had significantly lower odds of being high health
service users than those with lower assessed needs. Our findings reveal an important gap between levels of
need and service involvement for individuals who are both homeless and mentally ill and have implications for
health service reform in relation to the unmet and complex needs of a marginalized sub-population. (Trial registration:
ISRCTN57595077 and ISRCTN66721740).

Keywords: Homelessness, Health services, Unmet need, Mental illness

Background
In Canada and throughout the developed world, home-
lessness is a significant social issue that demands the at-
tention of our public institutions. A staggering proportion
of those experiencing homelessness are also experiencing
mental disorders, demanding high levels of health care

* Correspondence: clauren@sfu.ca
Faculty of Health Sciences, Simon Fraser University, 8888 University Drive,
Burnaby V5A 1S6, BC, Canada

© 2014 Currie et al.; licensee BioMed Central L
Commons Attribution License (http://creativec
reproduction in any medium, provided the or
Dedication waiver (http://creativecommons.or
unless otherwise stated.

service to meet the needs of these individuals [1,2]. Previ-
ous research has concluded that inadequate services are
available for people experiencing homelessness and men-
tal illness, often due to competing priorities, barriers to
treatment access, and poor discharge planning and follow-
up [3,4]. However, little is known about the association be-
tween varying complexities of need (e.g., type of mental
disorder, multiple mental disorders, co-morbid conditions,

td. This is an Open Access article distributed under the terms of the Creative
ommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and
iginal work is properly credited. The Creative Commons Public Domain
g/publicdomain/zero/1.0/) applies to the data made available in this article,

http://www.controlled-trials.com/ISRCTN57595077/housing+first

http://www.controlled-trials.com/ISRCTN66721740/housing+first

mailto:clauren@sfu.ca

http://creativecommons.org/licenses/by/4.0

http://creativecommons.org/publicdomain/zero/1.0/

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substance use, criminal justice system involvement) and
levels of health service use.
Individuals experiencing homelessness and mental ill-

ness are a heterogeneous population requiring varying
levels of health and social supports. Discontinuity be-
tween services for people with complex needs (e.g., con-
current disorders), poor psychiatric follow-up, an absence
of low-barrier treatment options, stigma, and discrimin-
ation each contribute to high levels of unmet need within
this population [5-7]. Previous research has shown that
homeless individuals underuse outpatient services and, as
a result, rely heavily on emergency department visits and
inpatient stays to address both physical and mental ill-
nesses [3,8,9]. In response, researchers and service pro-
viders have called for the reorientation of health and
social services to a more individualized and client-
centered approach [3,4,10,11]. A challenge in advocat-
ing for such service reorientation is the lack of empirical
research describing the distinct needs of subgroups within
the homeless mentally ill population [12]. In order to ori-
ent services in a manner that best addresses the needs of
different individuals, it is important to identify the factors
associated with different levels of health service use and
unmet need.
A challenge to understanding discontinuities in health

service use is identifying the unique and diverse needs of
this population and matching individuals with differing
levels of care. The Gelberg-Andersen Behavioural Model
for Vulnerable Populations offers a framework to help
identify factors associated with health service use with
the aim of improving healthcare access and delivery
[13-15]. Previous research using this model has shown
that, among homeless individuals, there are specific
characteristics that can help to predict and explain ser-
vice involvement, and are categorized as predisposing,
enabling, and need-related factors. Predisposing factors
include individual characteristics, (e.g., age, gender ethni-
city, education, history of homelessness), and are associ-
ated with commonly observed demographic trends in
health seeking behaviour. Enabling factors are com-
prised of systemic and structural considerations such
as having a regular family physician, social support, or
access to health care, and exert an influence via the
availability and accessibility of health care services. Fi-
nally, need-related factors consist of perceived and ob-
jective medical need and include mental and physical
health status, severity and type of illness, and substance
use [13,14,16].
However, this model has not been applied to a sample

of homeless individuals wherein all participants also
have a mental disorder, with or without a concurrent
substance use disorder [13-15]. Furthermore, previous
applications of the Gelberg-Andersen model have pri-
marily been in the context of the American healthcare

system, where structural aspects of funding have an im-
portant bearing on access to healthcare.
Existing research suggests that individuals experien-

cing more complex mental disorders, such as psychotic
disorders, require a higher level of service compared to
individuals with less severe mental disorders [15,17]. It is
therefore hypothesized that individuals with more com-
plex needs, including those experiencing more severe
mental disorders, multiple comorbidities and concurrent
disorders will have a greater number of encounters with
both primary and specialist health care than individuals
with less complex needs.
By examining factors shown to be associated with dif-

ferent levels of service use, we can help to identify gaps
in the current service landscape, and target services to
address areas of unmet need. Guided by the Gelberg-
Andersen model, the purpose of this research is to
examine the association between level of health service
use with predisposing, enabling, and need-related factors
among a sample of participants experiencing homeless-
ness and mental illness in Vancouver, Canada. The em-
pirically derived Gelberg-Andersen model will be used
as a framework for this analysis with the goal of identify-
ing potential discontinuities in care and opportunities
for intervention.

Methods
Data source and sample
Data were drawn from baseline interviews for the full
sample (n = 497) of participants enrolled in the Vancou-
ver At Home (VAH) study. Participants recruited to the
VAH study met inclusion criteria for recent homeless-
ness and current mental illness as assessed through the
use of standardized assessment measures administered
in person by trained interviewers [18]. Participants were
recruited from over 40 different community and institu-
tional agencies, representing roughly 13 different types
of services [18]. Referral sources included homeless shel-
ters, drop-in centres, homeless outreach teams, hospi-
tals, community mental health teams, and criminal justice
programs. Prospective participants were contacted directly
by research team members or were referred to the VAH
research team by agency staff. Final eligibility was con-
firmed with an in-person screening interview. Approxi-
mately 800 individuals were assessed for eligibility.
Among those, roughly 300 were excluded due to: ineli-
gibility (n ~ 200); being eligible, but losing contact follow-
ing screening (n = 100); declining to participate (n = 3);
and not being able to complete the baseline interview
(n = 3) [18]. All participants were at least 19 years of
age and provided written, informed consent prior to
participating in the study.
VAH is a longitudinal study, consisting of two ran-

domized control trials (RCTs) investigating housing and

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supports for people experiencing homelessness and men-
tal illness [18]. With the RCT design participants were
randomly assigned to one of 5 different study arms each
consisting of approximately 100 participants. Sample size
calculations were performed prior to recruitment to en-
sure sufficient power to perform outcome analysis be-
tween groups. Sample sizes of 100 participants per arm
were determined based on effect size estimates of 0.5
for major outcome variables, power of 0.80 (β = 0.20)
[18,19]. Analyses presented in the current study con-
sider only baseline data from the full sample of VAH
participants prior to randomization. The study is part
of a Canadian multi-centre project which took place
from October 2009 – March 2013 [19].

Predisposing, enabling and need factors
Data concerning socio-demographic characteristics, health
service use, housing histories, mental illness, substance
use and quality of life were collected through a series of
self-report questionnaires and categorized into the do-
mains of predisposing, enabling or need-related factors.
The selection of explanatory variables and categorization
into the three different domains followed the procedures of
previous investigators [13,16] and the guidelines for imple-
menting the Andersen-Newman and Gelberg-Andersen
models [13-15].

Predisposing factors
Predisposing factors included sociodemographic char-
acteristics as follows: gender (male/female), age [Youth
(<25); 25–44; and > 44], education (incomplete high
school; graduated high school), marital status (single/
never married; married/partnered; separated/widowed/
divorced), and whether they had a child 18 years or
younger (yes/no). Self-reported ethnicity was catego-
rized as: Caucasian, Aboriginal and Other. Housing
status was assessed based on shelter use in the past
6 months (yes/no), lifetime duration of homelessness
(1–3 years; >3 years); longest single period of home-
lessness (1 year; >1 year), and current housing status
(absolutely homeless versus precariously housed) (See
Goering et al. [19]). Criminal justice involvement was
assessed in terms of having been in jail in the past
6 months (yes/no).

Enabling factors
Personal and social resources were categorized as enab-
ling factors including: having a regular family physician
(yes/no) and having a place to go to seek health care
(yes/no). Unmet need was assessed by asking partici-
pants if, in the past year, they felt they needed health
care but did not receive it (yes/no). Social resources
were assessed in terms of the type and quality of social
relationships, including general feelings about family,

types of daily activities, the amount of time spent with
other people, and the people they interact with socially
(Quality of Life Interview-20 [20]).

Need factors
Need related factors included variables concerning phys-
ical and mental health. Physical health was assessed
through self-reported physical illness including: blood-
borne infectious diseases (HIV, Hepatitis C and/or Hepa-
titis B), chronic illnesses (heart disease, cancer, COPD,
etc.) history of head injury (yes/no), and having multiple
physical illnesses (≥2). General health was evaluated on
a five-point Likert scale ranging from excellent to poor.
Responses were dichotomized as positive (excellent/very
good/good) or negative (fair/poor) perceived health. Mental
disorders, substance dependence and alcohol dependence
were assessed using the MINI International Neuropsychi-
atric Interview [21]. Mental disorders were dichotomized
into clusters of less severe form (major depressive episode,
panic disorder, post-traumatic stress disorder) and severe
form (mood disorder with psychotic features, psychotic dis-
order, and manic or hypomanic episode). Multiple mental
disorders were assessed as meeting criteria for two or more
(≥2) disorders.

Definition of high and low health service use
Service use was evaluated based on the frequency of
past-month primary health care (family doctor, nurse,
dentist, or pharmacist) or specialist health care (special-
ist physician, psychologist, psychiatrist, addiction worker
or mental health worker) visits. The 80th percentile was
used to define two groups whereby two or fewer visits
(<3) for each type of service in the past month were cat- egorized as ‘low health service use’ and three or more visits (≥3) were categorized ‘high health service use’.

Statistical analysis
Pearson’s Chi-square tests were used to conduct pair-
wise comparisons between predisposing, enabling and
need-related baseline characteristics, among low and
high service use groups for both primary and specialist
health care providers. Bivariate and multivariate logistic
regression analyses were used to estimate baseline asso-
ciations between various predisposing, enabling and
need-related factors and levels of primary and specialist
health care. Variables were selected using the Gelberg-
Andersen framework for the regression analysis. We
used a significance level of p ≤ 0.10 to select variable for
inclusion in the multivariable logistic regression analyses.
Stepwise logistic regression (backwards elimination) was
used to select variables for the final multivariable model.
Odds ratios and 95% confidence intervals obtained
through logistic regression were reported as effect sizes.
All reported p-values were 2-sided. SPSS v21 software was

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used to conduct all statistical analyses. Institutional
review and ethics approval was provided by Simon
Fraser University’s Office of Research Ethics, under the
application entitled “Research Demonstration Project on
Housing and Mental Health in Vancouver, BC”, applica-
tion number 2009 s0231.

Results
Sample characteristics
The median age of participants (n = 497) was 41 years,
and the majority were male (73%), born in Canada (87%),
of European (57%) or Aboriginal (15%) decent, and met
criteria for absolute homelessness (78%). The median
duration of lifetime homelessness was 36 months and
the median age of first homelessness was 28 years. Most
participants were single and never married (70%), un-
employed (96%), and 41% had not completed high
school [18].
The most prevalent mental disorders in the sample

were psychotic disorder (53%) and major depressive epi-
sode (40%), followed by post-traumatic stress disorder
(PTSD) (26%), panic disorder (21%) and (hypo) manic
episode (19%). Half (52%) of participants met criteria for
two or more mental disorders. Substance dependence
was observed among 58% of participants and alcohol de-
pendence among 24%, with 28% of the sample reporting
poly-drug use (two or more types) and 29% reporting
daily illicit drug use [22]. Physical illnesses, including in-
fectious and chronic conditions, were highly prevalent,
with most participants (81%) reporting having two or
more physical illnesses including the presence of hepa-
titis C among 30% of participants [18].
In the month prior to recruitment, 49% of participants

reported being seen by a health service provider and
27% by a psychiatrist. Historically, 53% of participants
had been hospitalized for a mental illness two or more
times in the preceding five-years, and 12% had been hos-
pitalized for more than 6 months in the same time
period. In the preceding 6 months, the majority of par-
ticipants (58%) had visited an emergency room and 40%
had arrived at a hospital via ambulance.

Health service use – past month
In order to examine the nature of health service use
among participants, visits were categorized as primary
care or specialist care visits. For primary care, 393 (79%)
participants were categorized as low use (<3 visits) and 103 (21%) as high use (≥3 visits). For specialist care, 437 (88%) were categorized as low use (<3 visits) and 60 (12%) as high use (≥3 visits). Univariate associations between the outcome (levels of

service use) and predictor variables are presented in Tables 1,
2 and 3, sorted by primary and specialist health service use.
Within the primary health service use category, none of the

observed associations between predisposing factors and
levels of service use were significant at the p < 0.05 level; while the only predisposing variables significant at the p ≤ 0.10 level were ethnicity, marital status and having children under 18 years. Within the specialist health service use cat- egory, age at enrolment and being ‘hospitalized two or more times for a mental illness in the past 5 years’ were signifi- cantly associated with level of specialist health service use (p < 0.05). These variables as well as education level and duration of longest single period of homelessness, were included in multivariable regression analyses. Table 2 presents the results of chi-square tests for en-

abling factors. All variables pertaining to health care ac-
cess were significantly associated with past month health
service use in the primary care category (p < 0.05), and were included in the regression model. In the specialist care category, only ‘having a regular place to go for health care’ was significant at the p < 0.05 level. Mea- sures related to quality of life were assessed for inclusion in the regression models. For primary care, both ‘feelings about family in general’ and ‘feelings about the things done with other people’ were significantly associated with levels of service use and thus included in the re- gression model (p < 0.05). In the specialist care category, none of the variables were significantly associated with level of service use and only ‘feeling about the amount of time spent with other people’ was selected for inclu- sion in the regression model (p ≤ 0.10). Several need-related factors were significantly associ-

ated with levels of service use (see Table 3). In the spe-
cialist health service use category, only major depressive
episode and blood-borne infectious disease were signifi-
cantly associated with level of service use at the p < 0.05 level and no additional variables were included at the p ≤ 0.10 level. Tables 4 and 5 present the results of univariate and

multi-variable logistic regression analyses. Unadjusted odds
ratios are included for all variables that met the threshold
for inclusion in the logistic regression analysis (p ≤ 0.10).
For primary health service use (Table 4), having two or
more physical illnesses, reporting poor general health, hav-
ing a regular family physician, and feeling ‘horrible’ about
the ‘things that they do with others’ were all significantly
associated with high primary health service use. By con-
trast, participants with more severe mental disorders were
significantly less likely to have high primary health service
use than those without severe mental disorders. Ethnicity,
having a regular location for seeking health services, self-
assessed unmet health care need, current substance de-
pendence, and blood-borne infectious diseases were not
significantly associated with level of health service use in
the final regression model.
In the specialist care category (Table 5), having been

hospitalized for a mental illness at least 2 or more times

Table 2 Univariate comparisons of enabling characteristics, by primary and specialist health service use

Variable Primary health service use Specialist health service use

All
N (%)

Low use
(<3 visits) N (%)

High use
(≥3 visits)
N (%)

P value Low use
(<3 visits) N (%)

High use
(≥3 visits)
N (%)

P value

Regular Family Physician 320 (65) 241 (61) 79 (78) 0.002 277 (64) 43 (72) 0.217

Regular place to go for health care 394 (81) 304 (79) 90 (88) 0.031 341 (80) 54 (90) 0.053

Needed health care but didn’t receive it (past year) 209 (43) 155 (41) 54 (53) 0.026 189 (44) 20 (35) 0.154

Feelings about family in general 199 (43) 147 (41) 52 (54) 0.013 176 (43) 23 (40) 0.595

Feelings about things you do with other people 117 (25) 80 (21) 37 (37) 0.001 101 (24) 16 (27) 0.607

Feelings about amount of time spent with other people 151 (31) 116 (30) 35 (35) 0.341 138 (33) 13 (22) 0.119

Feelings about people seen socially 136 (28) 104 (27) 32 (32) 0.337 120 (28) 16 (27) 0.792

Bolded p-values indicate significance at p ≤ 0.10.

Table 1 Univariate comparisons of predisposing characteristics, by primary and specialist health service use

Variable Primary health service use Specialist health service use
All
N (%)
Low use
(<3 visits) N (%) High use (≥3 visits) N (%) P value Low use (<3 visits) N (%) High use (≥3 visits) N (%) P value

Male gender 358 (73) 288 (74) 70 (69) 0.292 316 (73) 43 (72) 0.830

Age at enrolment visit

Youth 36 (7) 28 (7) 8 (8) 0.889 27 (6) 9 (15) 0.031

25-44 years 280 (57) 224 (57) 56 (54) 253 (58) 28 (47)

> 44 years 180 (36) 141 (36) 31 (38) 157 (36) 23 (38)

Ethnicity

Aboriginal 77 (15) 61 (16) 16 (16) 0.068 71 (16) 6 (10) 0.433

Caucasian 279 (56) 212 (54) 67 (65) 245 (56) 35 (58)

Other 140 (28) 120 (31) 20 (19) 121 (28) 19 (32)

Education (≤Grade 8) 76 (15) 62 (16) 14 (14) 0.840 65 (15) 11 (18) 0.093

Single marital status 342 (70) 278 (72) 64 (62) 0.067 301 (70) 42 (70) 0.939

Have children (under 18) 122 (25) 89 (23) 33 (32) 0.059 108 (25) 14 (25) 0.920

Hospitalized for mental illness (>6 months) in past 5 years 57 (12) 49 (13) 8 (8) 0.164 49 (11) 8 (13) 0.666

Hospitalized for mental illness (>2 times) in past 5 years 253 (53) 206 (54) 47 (47) 0.190 213 (50) 40 (71) 0.003

Worked continuously at least one year in the past 322 (65) 257 (66) 65 (63) 0.597 280 (65) 43 (72) 0.275

Jail in last 6 months 68 (14) 53 (14) 15 (15) 0.777 06 (14) 8 (13) 0.933

Shelter in last 6 months 143 (29) 113 (29) 30 (29) 0.941 127 (29) 16 (27) 0.701

Duration of homelessness in lifetime

1-3 Years 256 (52) 208 (54) 48 (47) 0.197 223 (52) 34 (57) 0.474

3 Years Plus 234 (48) 179 (46) 55 (53) 208 (48) 26 (43)

Duration of homelessness -longest single period

1 Year 246 (50) 190 (49) 56 (54) 0.330 210 (49) 36 (60) 0.102

1 Year Plus 245 (50) 198 (51) 47 (46) 221 (51) 24 (40)

Age of first homelessness (<25 years) 214 (44) 166 (43) 48 (47) 0.427 191 (44) 23 (38) 0.381

Housing Status (Absolutely Homeless) 388 (78) 313 (80) 75 (73) 0.135 342 (78) 23 (38) 0.780

Bolded p-values indicate significance at p ≤ 0.10.

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Table 3 Univariate comparisons of need-related characteristics, by primary and specialist health service use

Variable Primary health service use Specialist health service use
All
N (%)
Low use
(<3 visits) N (%) High use (≥3 visits) N (%) P value Low use (<3 visits) N (%) High use (≥3 visits) N (%) P value

Major Depressive Episode 199 (40) 147 (37) 52 (51) 0.016 168 (38) 31 (52) 0.050

Manic or Hypomanic Episode 97 (20) 80 (20) 17 (17) 0.380 84 (19) 13 (22) 0.654

Post Traumatic Stress Disorder (PTSD) 129 (26) 93 (24) 36 (35) 0.021 113 (26) 16 (27) 0.901

Panic Disorder 104 (21) 80 (20) 24 (23) 0.513 91 (21) 13 (22) 0.880

Mood Disorder with Psychotic Features 84 (17) 68 (17) 16 (16) 0.698 73 (17) 11 (18) 0.758

Psychotic Disorder 263 (53) 218 (56) 44 (43) 0.021 236 (54) 27 (45) 0.190

Suicidality (moderate/high) 168 (34) 128 (33) 40 (39) 0.232 144 (33) 24 (40) 0.234

Multiple mental disorders (≥2) 240 (48) 179 (46) 61 (59) 0.013 207 (47) 33 (55) 0.267

Less severe cluster of mental disorder 264 (53) 194 (49) 70 (68) 0.001 230 (53) 34 (57) 0.557

Severe cluster of mental disorder 363 (73) 299 (76) 63 (61) 0.002 318 (73) 45 (75) 0.715

Alcohol dependence 121 (24) 95 (24) 26 (25) 0.822 104 (24) 17 (28) 0.443

Substance dependence 288 (58) 217 (55) 71 (69) 0.012 257 (59) 31 (52) 0.293

Any physical illness 453 (91) 355 (90) 98 (95) 0.122 398 (91 55 (92) 0.880

Blood-borne Infectious diseases (HIV/HCV/HBV) 157 (32) 113 (29) 44 (43) 0.009 145 (34) 12 (20) 0.042

Multiple physical illness (≥2) 402 (81) 306 (78) 96 (93) 0.000 353 (81) 49 (82) 0.870

Head injury 270 (56) 211 (56) 58 (57) 0.830 234 (55) 36 (62) 0.322

General Health (fair/poor) 235 (48) 171 (44) 64 (62) 0.001 211 (48 24 (40) 0.222

Bolded p-values indicate significance at p ≤ 0.10.

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in the past 5 years and current major depressive episode
were associated with high specialist service use, while
having a blood-borne infectious disease was associated
with lower odds of high specialist health service use.
Age at enrolment was the only variable significant in
univariate regression analyses at the p ≤ 0.05 level that
was not present in the final regression model.

Discussion

Contrary to our hypothesis, the application of the
Gelberg-Anderson model within our sample of home-
less mentally ill individuals revealed that those with
greater assessed need, including severe mental disor-
ders and blood-borne infectious diseases, accessed
health services at significantly lower levels than those
with lower assessed needs. The burden of illness in our
sample was extremely high. More than half of partici-
pants met criteria for psychotic disorder, and over
eighty-percent reported having multiple chronic phys-
ical illnesses. It was hypothesized that individuals with
more severe mental disorders, multiple co-morbidities,
and concurrent disorders, would have used health ser-
vices at a higher frequency than those with less severe
conditions. Further, based on findings from previous
research using the Gelberg-Andersen model, it was ex-
pected that need-related factors would be strongly as-
sociated with higher levels of service use [15].

High health service use was defined as three or more
visits in the past month, for both primary care and spe-
cialist visits. As such, 21% of participants accessed pri-
mary health services three or more times in the past
month, while only 13% of participants accessed high
levels of specialist health services. The vast majority of
participants accessed primary or specialist services two or
fewer times in the past month. This finding is consistent
with other literature identifying that a small proportion of
individuals tend to account for a disproportionately high
amount of service use [23,24]. While the 80th percentile of
the number of health services visits was chosen in order
to define the outcome variable, it is important to note
that even the median level of two visits in the past
month is considerably greater than the number of
health care visits per month that would be observed in
the general population [25].
The frequency of service use was considered inde-

pendently in the categories of primary care and specialist
health service use for the purpose of differentiating be-
tween primary health services accessed by the individual
(i.e., family physician, nurse, dentist, etc.), versus special-
ized referral-based health service use (i.e., specialist phys-
ician, psychiatrist, psychologist, etc.). In both categories,
as expected, a greater number of need-related factors were
significantly associated with level of service use than the
other Gelberg-Andersen domains. Variables shown to be

Table 5 Unadjusted and adjusted odds ratios for associations between predictor variables and levels of service use for
specialist health care visits (≥3 visits)

Outcome variable Unadjusted OR
(95% CI)

P value Adjusted OR
(95% CI)*

P value

Predisposing Factors

Age at enrolment visit

Youth 0.33 (0.14, 0.78) 0.011

25-44 years 0.44 (0.18, 1.05) 0.065

> 44 years

Education (≤Grade 8) 0.63 (0.37, 1.09) 0.097

Hospitalized for mental illness (>2 times) in past 5 years 2.48 (1.35, 4.56) 0.004 2.53 (1.35, 4.75) 0.004

Enabling Factors

Regular place to go for health care 2.32 (0.97, 5.57) 0.059

Needed health care but didn’t receive it (past year) 0.66 (0.37, 1.17) 0.159

Feelings about amount of time spent with other people 0.60 (0.31, 1.15) 0.122

Need Factors

Major Depressive Episode 1.71 (1.00, 2.94) 0.052 1.98 (1.11, 3.56) 0.021

Blood-borne Infectious diseases (HIV/HCV/HBV) 0.51 (0.26, 0.99) 0.045 0.48 (0.24, 0.97) 0.042

*Adjusted odds ratios and confidence intervals are only shown for variables that remained significant in the final logistic regression model.
Bolded p-values indicate significance at p < 0.05.

Table 4 Associations between predictor variables and high primary health service use (≥3 visits)

Outcome variable Unadjusted OR
(95% CI)
P value Adjusted OR
(95% CI)*
P value
Predisposing Factors
Ethnicity

Aboriginals 1.57 (0.76, 3.25) 0.221

Caucasian 1.90 (1.10, 3.28) 0.022

Other

Single marital status 1.53 (0.97, 2.41) 0.069

Have children (under 18) 1.58 (0.98, 2.55) 0.061

Enabling Factors

Regular Family Physician 2.17 (1.31, 3.60) 0.003 2.27 (1.27, 4.07) 0.006

Regular place to go for health care 2.02 (1.06, 3.88) 0.034

Needed health care but didn’t receive it (past year) 1.64 (1.06, 2.55) 0.027

Feelings about family in general 1.77 (1.13, 2.78) 0.014

Feelings about things you do with other people 2.23 (1.39, 3.59) 0.001 1.74 (1.01, 2.99) 0.047

Need Factors

Multiple mental disorders (≥2) 1.74 (1.12, 2.70) 0.014

Less severe cluster of mental disorder 2.18 (1.38, 3.44) 0.001

Severe cluster of mental disorder 0.50 (0.31, 0.78) 0.003 0.59 (0.35, 0.97) 0.039

Substance dependence 1.80 (1.13, 2.86) 0.013

Blood-borne Infectious diseases (HIV/HCV/HBV) 1.82 (1.16, 2.84) 0.009

Multiple physical illness (≥2) 3.90 (1.75, 8.71) 0.001 2.74 (1.12, 6.70) 0.027

General Health (fair/poor) 2.12 (1.36, 3.31) 0.001 1.68 (1.01, 2.81) 0.047

*Adjusted odds ratios and confidence intervals are only shown for variables that remained significant in the final logistic regression model after backwards elimination.
Bolded p-values indicate significance at p < 0.05.

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significantly associated with higher levels of health service
use in previous studies such as substance use and female
gender were non-significant in our models. It is possible
that non-significant results observed for certain predictor
variables could be due to small sample sizes within these
cells. All individuals included in these analyses were re-
cruited on the basis of current homelessness status and
therefore it was not possible to show a relationship be-
tween homelessness and level of service use. However,
previous studies using the Gelberg-Andersen framework
have shown homelessness to be significantly associated
with high service use compared to housed individuals, and
thus these findings are understood in the context of
higher average service use [15,26].

Primary health care visits
In the primary health care visit category, none of the
predisposing factors were found to be significantly asso-
ciated with level of health service use. Having a regular
family physician, and negative feelings about ‘the things
you do with other people’ were enabling factors associ-
ated with significantly greater odds of high service use.
It is intuitive that participants who have regular family
physicians would have higher levels of service use than
those who do not have a regular family physician, as this
is suggestive of health seeking behaviour. Feeling “hor-
rible” about one’s social interactions may suggest a lack
of positive social support and therefore an increased reli-
ance on external sources, such as health services to meet
needs.
Of the three need-related factors found to be signifi-

cantly associated with level of service use, having mul-
tiple physical illnesses and reporting fair or poor general
health were associated with higher levels of service use,
supporting the hypothesis that people with poorer phys-
ical health ought to be accessing health services more
frequently. Conversely, having a more severe mental dis-
order was associated with significantly lower likelihood
of high health service use. This finding of lower health
service use among those with more severe mental disor-
ders (i.e. psychotic and bipolar disorder) is troubling and
suggests possible gaps or barriers in the health system
resulting in inadequate care for homeless individuals
with more complex mental health challenges. The nature
of such mental disorders can be such that individuals
may not seek help when they need it due to stigma, mis-
trust in the medical system, negative past experiences,
dissatisfaction with the prescription of medication with-
out adequate psychological counseling and negative expe-
riences with medication side-effects. This finding supports
previous research that individuals experiencing homeless-
ness and mental illness face barriers to service use [27,28]
and suggests that, in Vancouver, those with the most com-
plex needs are particularly underserved.

Specialist health care visits
The predisposing factor of hospitalization for a mental
illness (>2 times) in the past 5 years was associated with
higher levels of specialist health service use, suggesting
that personal histories of specialized tertiary psychiatric
care can help to explain increased levels of specialist
care in the present. No enabling factors were signifi-
cantly associated with specialist health service use. The
only other factors associated with specialist health ser-
vice use were need-related factors. Major depressive
episode was associated with higher levels of specialist
service use, suggesting that individuals with depression
are likely to be referred to and make use of specialist
services, including being seen by a psychiatrist or other
mental health professional. Having a psychotic disorder,
or more severe mental disorder, was not significantly asso-
ciated with either high or low levels of specialist health
care use. Given the difficulty in treating individuals with
severe mental disorders and the limited availability of spe-
cialists, it is possible that this finding of non-significance
may be related to the fact that such individuals are more
likely to be turned away from specialist services or inad-
equately followed [29]. Finally, having a blood-borne infec-
tious disease (i.e., HIV, HCV, or HBV) was associated with
significantly lower specialist health service use, which may
suggest that individuals with these conditions are under-
served by specialist health care providers, or that these
conditions can be successfully managed by primary health
care providers.

Strengths and limitations
The Gelberg-Andersen framework guided the selection
of variables to be included in analyses and provided a
useful means of organization into the three domains of
predisposing, enabling and need-related factors. The var-
iables available through the VAH study were defined in
ways consistent with previous studies using the Gelberg-
Andersen framework, and were relatively complete in
scope to populate the three domains. Analyzing health
service use within this framework enabled comparison
between previously established findings that also used
this framework and highlighted differences between our
sample and those studied elsewhere. Our results repre-
sent the first application of the Gelberg-Andersen frame-
work to a homeless mentally ill cohort in Canada.
Limitations include the fact that the data used were

based on self-reported past-month service use and thus
were subject to recall bias whereby individuals may have
had difficulty accurately recalling the exact frequency
and nature of all health services contacts. As well, partic-
ipants may over or underreport certain types of service
use due to social desirability bias or perceptions of
stigma. Individuals experiencing homelessness and men-
tal illness tend to be a ‘hard to reach’ and heterogeneous

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population and therefore it is difficult to generalize find-
ings beyond our current sample. Further the cross-
sectional design of this particular study does not allow
us to make any direct causal inference about the asso-
ciation between level of need and service use. Efforts
were made to ensure that as many established Gelberg-
Andersen variables were included, however, certain vari-
ables might not have been included or may have been
defined differently in comparison to previous studies.
Additionally, inconsistencies between previous studies
in the categorization of certain variables (i.e. substance
use) within the three different Gelberg-Andersen do-
mains, underscores the importance of judgment when
placing particular variables into the three categories
that comprise the model. While the overall sample size
of the study allowed sufficient power to reduce the
probability for a Type II error in the primary analysis,
it is possible that the sample sizes for certain predictor
variables (i.e. Aboriginal status) were not sufficiently
large to establish a statistically significant.

Conclusion
The current study found that homeless individuals with
more severe mental disorders and blood borne infectious
diseases had significantly lower odds of using high levels
of primary and specialist health services respectively,
despite evidence of need. Our results raise important
questions concerning the adequacy of services available
to homeless individuals who experience severe mental
disorders. Insufficient involvement in community care
may contribute to the further worsening of health and
the high use of hospital services in this population. Strat-
egies to better connect individuals experiencing home-
lessness with indicated services in the context of public,
private and mixed models of health care delivery need to
be developed to be responsive to individuals complex
and unique needs.

Abbreviations

AOR: Adjusted odds ratio; COPD: Chronic obstructive pulmonary disease;
HBV: Hepatitis: B; HCV: Hepatitis C; HIV: Human immunodeficiency virus;
RCT: Randomized control trial; VAH: Vancouver At Home.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

LC conducted field interviews, designed this study and led development of
the manuscript. MP supervised field research and contributed to the writing
of the manuscript. AM carried out the primary statistical analyses. LM
contributed to the statistical analyses and also contributed to the
manuscript. JS was principal investigator, contributed to the research design
and the writing of the manuscript. All authors read and approved the final
manuscript.

Acknowledgments

This research was funded by a grant to Simon Fraser University from Health
Canada and the Mental Health Commission of Canada. The VAH Research
Team would like to extend special thanks to the participants, service

providers and field research team members. The authors also thank the At
Home/Chez Soi project collaborative.

Received: 20 February 2014 Accepted: 15 September 2014
Published: 18 September 2014

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doi:10.1186/1472-6963-14-404
Cite this article as: Currie et al.: Examining the relationship between
health-related need and the receipt of care by participants
experiencing homelessness and mental illness. BMC Health Services
Research 2014 14:404.

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Abstract
Background
Methods
Results
Conclusions
Background
Methods
Data source and sample
Predisposing, enabling and need factors
Predisposing factors
Enabling factors
Need factors
Definition of high and low health service use
Statistical analysis
Results
Sample characteristics
Health service use – past month
Discussion
Primary health care visits
Specialist health care visits
Strengths and limitations
Conclusion
Abbreviations
Competing interests
Authors’ contributions
Acknowledgments
References

8
SEXUAL HEALTH IN

MENTAL HEALTH PRACTICE
JO BATES

Learning outcomes

By the end of this chapter you should be able to:

• Consider the concept of sexual health
• Identify some of the most prevalent sexually transmitted infections (STIs),

including signs and symptoms, treatment and prevention
• Discuss contraceptive methods, including their advantages and disadvantages
• Explore the role of the mental health practitioner in facilitating good sexual

health

INTRODUCTION

This chapter will introduce the concept of sexual health and relate this specifically
to the needs of clients with mental health problems. Sexual health is a broad,
diverse, multifaceted and challenging area of health care and the term ‘sexual
health’ often means different things to different people. Some may immediately
think of illness and infections such as sexually transmitted infections (STIs) and
human immunodeficiency virus (HIV), whereas others may think of contraception
or women’s health, including cervical smears and breast screening. Indeed, sexual
health does include these topics, but it also includes much more than that.

Sexual health is holistic, involving the whole person in both body and mind and
affecting each and every one of us throughout our lifespan, whether we are ill or not.

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 111

Good sexual health is essential to good general health and to our sense of wellbe-
ing and quality of life, whether we choose to be sexually active or not. There are
many definitions of sexual health and the one below is offered by the Department of
Health (DH) (2001: 7):

Sexual health is an important part of physical and mental health. It is a key part
of our identity as human beings together with the fundamental human rights
to privacy, a family life and living free from discrimination. Essential elements of
good sexual health are equitable relationships and sexual fulfilment with access
to information and services to avoid the risk of unintended pregnancy, illness or
disease.

While this definition shows the importance of sexual health to our identity, it is
focused largely on the prevention of illness, infections and unintended pregnancy. A
further definition from the World Health Organization (WHO) (2012) takes a more
holistic view in that it sees sexual health as:

a state of physical, mental and social well-being in relation to sexuality. It requires
a positive and respectful approach to sexuality and sexual relationships, as well
as the possibility of having pleasurable and safe sexual experiences, free of coer-
cion, discrimination and violence.

Essentially, as stated by Quinn and Browne (2009), sexuality and sexual health are vital
components of our life, playing a key role in the overall quality of life and in our general
wellbeing. World Association for Sexual Health (1999) go on to advocate that sexual
health involves sexual rights that are a basic human given and these are as follows:

• The right to sexual freedom
• The right to sexual autonomy, sexual integrity and safety of the sexual body
• The right to sexual privacy
• The right to sexual equality
• The right to sexual pleasure
• The right to emotional sexual expression
• The right to sexually associate freely
• The right to make free and responsible reproductive choices
• The right to sexual information based on scientific inquiry
• The right to comprehensive sexuality education
• The right to sexual health care

While sexual health is an important aspect of life, it is an issue that is often over-
looked in health care practice. Several studies have shown that nurses do not discuss
sexual matters with their clients for a variety of reasons, most commonly a lack of
knowledge, conservative attitudes, fear of offending clients and embarrassment
(McCann 2003; Brown et al. 2008; Matevosyan 2009; Quinn and Browne 2009).
Other factors, such as lack of time, fear of being perceived as encouraging sex and

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS112

the perceived risk of creating emotional turmoil, have also been found to hinder
some nurses discussing sexual matters with their clients (Brown et al. 2008).
Johnson et al. (2002) add that wider health professionals are also reluctant to dis-
cuss sexual issues, largely due to a belief that such matters are personal, thus rein-
forcing that sexual health is a neglected area of health care.

To compound this, Wakley et al. (2003) report that clients are also reluctant to
discuss sexual matters, stating similar reasons to that of health care profession-
als, such as being embarrassed and feeling ill at ease. In addition, clients state that
they feel humiliated, ashamed, are worried about being judged and of having their
partner present, unease about their sexuality and concerns about confidentiality.
Furthermore, McCann (2003) and Higgins et al. (2006) found that clients are often
unaware that their illness or treatment may have consequences in relation to their
sexual health, thus suggesting a lack of knowledge that appears currently to be
shared with the health professional.

Given the reluctance of both health professionals and clients to discuss sexual health,
it is unsurprising that this is a commonly neglected area of practice, but with poten-
tially long-term consequences to both physical and mental health the situation needs
to change. It is imperative, therefore, that all health professionals who work with peo-
ple with mental health disorders feel confident to at least bring up the topic of sexual
health with their clients and that they also have a basic knowledge of this sensitive and
important area of health care. Being an expert is not a requirement of addressing this
topic; indeed, taking that first step of initiating a discussion could well make all the dif-
ference. Before going further, consider the issues raised in Action Learning Point 8.1.

Action Learning Point 8.1

Consider the following;

• Do you talk to clients/patients about sexual health issues?
• If not what stops you?
• What level of knowledge do you have in relation to sexual health?
• Do you need to develop this knowledge further?

SEXUAL HEALTH AND INDIVIDUALS WITH
MENTAL HEALTH PROBLEMS

There is evidence to suggest that individuals with mental health problems are at an
increased risk of poorer sexual health when compared with the general population. In
particular, the risk of contracting STIs and HIV is higher than in the general popula-
tion, as is the possibility of having an unintended pregnancy (Rosenberg et al. 2001;
Brown et al. 2006; Carey et al. 2007; Brown et al. 2008; and Matevosyan 2009).

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 113

According to Farr et al. (2010), 20% of women with mental distress do not
use contraception, or when they do, they use contraception that is less effective.
An unfortunate consequence of unintended pregnancy in a woman with a mental
health disorder is a potential worsening of their condition, resulting in adverse out-
comes for both mother and baby (Farr et al. 2010). In relation to STIs, research by
Matevosyan (2009) showed that 34% of patients with an STI also had a co-morbid
mental health disorder. While both of these studies were conducted in the USA, and
may not therefore be generalised to other countries or populations, it certainly pre-
sents food for thought.

Chronic illnesses, which include many of the mental health disorders, can also have
a significant impact on an individual’s (and consequently their partner’s) sexual health
as these affect libido, self-image and general physical and psychological wellbeing.
This in turn can influence decision-making and choice (Warner et al. 1999). An exam-
ple is the documented assertion that people with a mental health disorder are more
likely to engage in risk-taking behaviour such as having sex at a young age, having
unprotected sex, engaging multiple partners who may themselves be in a high-risk
group, injecting drug use and sex trading (Rosenberg et al. 2001; Brown et al. 2008;
Quinn and Brown 2009).

There are also further considerations in relation to the vulnerability of individuals
with a mental health problem, starting with the proposal that they are at increased
risk of experiencing periods of homelessness, social disadvantage and poverty, all
lifestyle issues that can add to their potential for vulnerability to sexual health prob-
lems (Drake et al. 1991; Berkman and Kawachi 2000; Carey et al. 2007). Treatment
for mental health disorders can also cause side-effects linked to sexual dysfunction
and, conversely, the condition itself may cause an array of sexual problems, all of
which impact on general health and wellbeing, but more specifically on sexual health
and wellbeing.

SEXUALLY TRANSMITTED INFECTIONS (STIs)
STIs are infections contracted via sexual contact with another person and are caused
by bacteria, viruses or protozoa. The long-term consequences of undiagnosed and
untreated STIs are serious and sometimes fatal, and they present a major public
health problem in the world today (Adler 2004). STIs have been known about for
centuries, with some well-known individuals from history acquiring STIs. Today
STIs are still often associated with stigma and shame because of the nature of how
they are contracted and this stigma can present a huge barrier to individuals access-
ing treatment (Bannerman and Proom 2009). Additionally, the risk of contracting
an STI or HIV is linked with the type of sexual activity and number of partners, and
the risk increases the more sexual partners a person has (Wakley et al. 2003). How-
ever, it is important to recognise that an individual may only have sexual contact
with one person but if that person has an STI or HIV then there is the potential for
cross-infection. Remember that not everyone with an STI has had sexual contact
with multiple partners.

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS114

The long-term consequences of untreated STIs can be devastating. Chlamydia,
for example, may be asymptomatic but can result in symptoms such inter-menstrual
bleeding and pelvic inflammatory disease in women, which in turn can cause ectopic
pregnancies and infertility. In men, the infection may result in urethral discharge,
proctitis, conjunctivitis and reactive arthritis (Richens 2004). The World Health
Organization (2000) describe STIs as falling into one of four groups:

• Viral infections (including HIV, acquired immune deficiency syndrome (AIDS), herpes sim-
plex 1 and 2, human papilloma virus (HPV), hepatitis B and others)

• Bacterial infections (including chlamydia, syphilis, gonorrhoea, trichomonas, garde-
nerella and others)

• Yeast infections (including candidiasis and others)
• Infestations (including pubic crabs, scabies and others).

An understanding of the common STIs, routes of transmission and signs and symp-
toms is invaluable for health care professionals.

• Chlamydia – The most commonly diagnosed STI in young men (age 20–24) and women
(age 16–19) in England, Wales and Northern Ireland. It can be transmitted from one
mucous membrane to another, e.g. throat, eyes and anus, by close physical contact.
Chlamydia can also be transmitted from mother to baby during labour.

Signs and symptoms: Asymptomatic in up to 80% of women and 50% of men; women may
also experience post-coital bleeding, inter-menstrual bleeding, vaginal discharge, pelvic
inflammatory disease; both genders may experience genital inflammation and swelling,
sore throat, pain on urination and lower abdominal pain.

Treatment: Oral antibiotics

• Gonorrhoea – Transmitted by close physical contact from one mucous membrane to
another. Easily transmitted via vaginal, oral and anal sex. Can be transmitted from
mother to baby.

Signs and symptoms: Up to 50% of cases in women and 10% in men will be
asymptomatic; symptoms include genital discharge, lower abdominal pain and pain on
urination.

Treatment: Oral antibiotics

• Syphilis – The primary route of transmission is via sexual contact but syphilis can also be
transmitted from mother to child. If untreated, it leads to a systemic disease with a vari-
ety of clinical complications which over time may be fatal.

Signs and symptoms: Painless ulcer (chancre) at site of exposure (usually genitals,
perianal area or mouth), skin rash and systemic illness.

Treatment: Treated with antibiotics via intramuscular (IM) injection preferably, but can
be treated with oral antibiotics.

• HIV – Viral infection transmitted via sexual contact, blood to blood (e.g. needlestick injury
or infected blood products being transfused), mother to baby. It can take up to three

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 115

months for antibodies to appear in the blood following infection with the virus. This is
called the ‘window period’. Testing for HIV antibodies should therefore take place at time
of exposure and then be repeated three months later.

Signs and symptoms: Upon initial infection the following signs and symptoms may occur
(although they often go unnoticed or are put down to having a cold or feeling ‘off colour’
as most people will recover within 2–4 weeks): high temperature, fatigue, skin rash,
myalgia, headaches, sore throat, mouth ulcers, swollen lymph glands, nausea, diarrhoea,
weight loss, night sweats, oral thrush, cough (not an exhaustive list). If the virus remains
undetected (many people will be asymptomatic), it will over a period of time start to
damage the immune system of the infected person. They will then become susceptible to
infections such as oral thrush, vaginal thrush, gastro-intestinal infections resulting in
diarrhoea, pulmonary infections, herpes simplex infections, skin cancer and pneumonia
(not an exhaustive list).

Treatment: At this point in time there is no cure for HIV or AIDS, although modern drug
treatments have greatly improved both the quality and length of life for those infected
with the virus.

• Genital warts – Many types of warts have been detected (over 100) and they are caused
by the human papilloma virus (HPV). Certain strains cause genital and perianal warts, and
some strains have been associated with cervical cancer.

Signs and symptoms: Single or multiple fleshy growths which are painless and may or
may not be itchy; can cause psychological distress as they may reoccur.

Treatment: Various treatments available.

• Genital herpes (herpes simplex virus HSV) – HSV 1 usually affects the lips and mouth area.
HSV 2 usually affects the ano-genital area. It is, however, possible to transfer both types
so that HSV 1 is found in the genital area and HSV 2 is found in the mouth and lips.
Transmitted by skin-to-skin contact with a herpes lesion (blister), such as during kissing,
oral sex or other sexual contact. Mother to baby transmission can occur.

Signs and symptoms: For both men and women the infection may cause tingling, burning
or itching sensation; small fluid filled blisters appear at the site of infection which are very
painful; in the genital region the blister may make passing urine painful, sometimes
resulting in urinary retention which requires catheterisation and hospital admission; can
cause pyrexia and myalgia and flu-like symptoms.

Treatment: Various treatments for the symptoms are available and analgesia may also be
required during an outbreak.

• Hepatitis B – Can be transmitted by sexual contact, via blood and blood products and
from mother to baby.

Signs and symptoms: May be asymptomatic in the acute phase for some people; can
cause flu-like symptoms, lethargy, diarrhoea, fever, loss of appetite and weight loss,
nausea and vomiting, jaundice of the skin, itchy skin, upper right-sided abdominal
pain.

Treatment: Referral to a doctor is required for monitoring of the condition. Immunisation
against the infection is available.

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS116

• Hepatitis C – Transmitted via IV drug use, infected blood and blood products, body pierc-
ing and tattoos with unclean needles. Transmission via sexual activity and from mother
to baby carries a lower risk.

Signs and symptoms: Over 80% of people are asymptomatic but the following may occur:
tiredness, nausea.

Treatment: Referral to a doctor is required for monitoring of the condition. No
immunisation is currently available (Richens 2004; Peate 2005; Bannerman and Proom
2009).

THE ROLE OF THE MENTAL HEALTH
PRACTITIONER

Appropriate awareness and knowledge of sexual health are a prerequisite of
quality care for people with mental health problems. Strategies include the
incorporation of sexual health within a systematic physical health assessment
(discussed further in Chapter 2) and the promotion of effective contraception
and safer sex.

SEXUAL HEALTH ASSESSMENT
The most important thing that a mental health professional can do to enhance
the sexual wellbeing of their clients is to engage them in a discussion regarding
their sexual health. It is imperative not to stereotype people according to race,
gender, sexual activity, age or illness, but to assess each person’s risk on an indi-
vidual basis. While mental health practitioners are well versed in communication
and engagement strategies, they are unlikely to feel equipped to discuss sexual
health issues as few health professionals receive training in this potentially delicate
art. The core skills, however, remain unchanged and so mental health profession-
als should feel confident in employing their existing proficiency in relationship
development and complement these with some key prompt questions specifically
focused on sexual health.

If the discussion is part of a formal assessment, it may feel more comfortable to
tell the client that sexual health is part of the holistic approach and that the ques-
tions that are about to be asked are standard for everybody. To break the ice, ask-
ing whether the client is in a sexual relationship currently can be a good starting
point, followed by enquiring whether they, or their partner, are having any sexual
difficulties. If the client appears willing to discuss this, then asking whether they are
satisfied with their sex life and whether they have any sexual concerns they would
like to discuss are good open questions that can elicit information and encourage
discussion. Once the client has started to open up, the aim will be to take a fuller
sexual history with a question such as ‘Would you mind telling me about your sexual
history?’ With an added prompt such as ‘Perhaps your first sexual experience?’ or

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 117

‘Could you tell me how many partners you’ve had?’ This may identify negative and/
or abusive experiences and, while the mental health practitioner should be aware
of and sensitive to this, it does not have to negate continuing with the assessment.
Instead, clinical judgement will need to be applied.

When taking a sexual history it is important to consider both past and present
circumstances and questions should be aimed at identifying sexual behaviours and
orientation, sexual difficulties or concerns, sexually transmitted diseases, contracep-
tion methods and alcohol and drug use (prescribed and recreational). Whether safe
sex has and is still being practised is a key area for exploration and an excellent lead
into the promotion of sex education.

Where the discussion of sexual health falls outside a formal assessment, perhaps
in a routine visit or a conversation on a ward, the practitioner may want to think
about initiating the conversation by asking clients how they are finding their medica-
tion and whether they have experienced any disruption to their sexual functioning as
a result. Similarly, where clients are using drugs or alcohol, it may be appropriate to
ask if these have had any impact on their experience or behaviour in relation to sex.
In both situations the fact that sexual ill-health can be a consequence can provide a
rationale to the client for initiating the conversation, which will also help normalise
anything the client may wish to raise.

Many STIs have common presenting signs and symptoms which should act as a
trigger to indicate that a client should be advised to attend a sexual health screen-
ing unit. There is no suggestion that mental health professionals conduct physi-
cal examinations; rather, they are encouraged to be attuned to the cues that may
indicate a need for referral. These cues could include vaginal discharge and pos-
sibly (but not always) vaginal discomfort and irritation, genital ulceration and
urethral discharge (Adler 2004). Discharge from the penis in men is abnormal
and requires further investigation, whereas in women some vaginal discharge
is normal. However, if the vaginal discharge becomes offensive in smell, itchy,
more purulent or changes from what is considered normal by the woman, this
will require further investigation (Bannerman and Proom 2009). It is helpful to
remember that in many cases STIs co-exist together so if a person is infected with
one STI, they will need to be fully screened as it may be that they are also infected
with another STI as well.

SEXUAL HEALTH PROMOTION AND
CONTRACEPTION

Health promotion is an important part of any health professional’s role. Indeed,
professionals will be familiar with the Ottawa Charter, which states that ‘Health
promotion is the process of enabling people to increase control over and to improve
their health’ (World Health Organization 1986: 1).

This is an apt definition when considering the purpose of sexual health promo-
tion. Ultimately, the aim is to equip individuals with knowledge and skills to take

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS118

control over the sexual health choices they make. This should be delivered in a
non-judgemental and supportive way by health professionals who have at least a
basic understanding of sexual health matters, have the ability to communicate effec-
tively with others and be self-aware (Ingram-Fogel 1990, cited in Rowe et al. 2009).
The latter is particularly important given the wide array of sexual preferences in
terms of sexuality and sexual behaviours (promiscuity, fetishes) which you may
encounter. In order to enhance your own self-awareness, it is therefore important
that you take some time to consider your beliefs and values and Action Learning
Point 8.2 will assist with this.

Action Learning Point 8.2

• Do you have any strongly held beliefs and values about sex and sexual behaviour?
• If so, what are these and how did you come to hold these beliefs?
• Do you make assumptions about a person’s sexual identity and sexual preference?

Most of us tend to assume that most people are heterosexual or ‘straight’ when in
fact this may not be the case. Burrows (2011) states that in the UK it is estimated
that between 0.3% and 10% of the population report as being lesbian, gay or
bisexual (LGB). Indeed, people who are LGB suffer health inequalities due to factors
such as social exclusion, inappropriately designed services and lack of awareness
among health professionals (Burrows 2011). When considering people with mental
health problems this is likely to be compounded even more. A small way in which
a difference can be made in relation to becoming more inclusive is to consider the
language you use. For example, when dealing with a woman do you refer to her
husband? If so, unless you know otherwise, this is making assumptions. First, does
the woman have a partner or is she single? Second, if she does have a partner is that
person male or female? Try to use words such as ‘your partner’. If assumptions are
made about a person’s sexuality and sexual preferences it is very difficult for them
to correct that assumption as they may be unsure and even fearful of the reaction
and response they may get.

When promoting sexual health with clients it is also extremely important that the
mental health practitioner is able to be non-judgemental. To do so you may need to
put aside your beliefs and values and focus on maximising the sexual wellbeing of
your client. This may not be easy and can cause emotional conflict for some. If this
is the case for you, then you should seek help and support yourself in order that
you can resolve any personal issues to enable you to work more effectively in your
professional role.

Encouraging men and women to use an effective method of contraception,
facilitating access to contraception and contraceptive services is an extremely

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 119

important part of sexual health care. This has the dual aim of protecting against
STIs and preventing unplanned pregnancies, thus enabling people to choose when
and if to reproduce.

There are many factors to consider when advising about contraception for
women with a mental health disorder. For example, St Johns’ Wort is a herbal
preparation available in many pharmacies, chemists and herbal stores and is used
to help alleviate low mood. However, it can interfere with the Combined Oral
Contraceptive pill (COC) commonly known as ‘the pill’ and the Progestogen Only
Pill (POP), commonly known as the ‘mini pill’, potentially affecting their efficacy
(Guillebaud and Macgregor 2009; Glasier and Gebbie 2008; Bekaert and White
2006). Break through bleeding (BTB), or spotting bleeding as it is sometimes called,
can be a disadvantage of progestogen-only methods of contraception such as the
mini pill and Depo Provera, and this may not be well tolerated in some women with
a mental health disorder (Matevosyan 2009). When considering contraception it is
important to note that only condoms protect against the transmission of STIs and
HIV, and only if they are used correctly each time the person has sex. Therefore
health professionals should take the opportunity to discuss the use of condoms
even if the person is using a hormonal method of contraception such as the COC.
The hormonal method will protect against unintended pregnancy and condoms will
protect against STIs and HIV.

There are a range of Medical Eligibility Criteria (MEC) developed by the World
Health Organization (2012) to assist and guide health professionals when advising
and prescribing methods of contraception (2012). Contraceptive methods are cat-
egorised according to the presence of specific illnesses or conditions. Contraception
is considered in terms of whether the advantages of using the method outweigh the
risks of taking it. Those eligible should not have a condition for which there is a
restriction for the use of the contraceptive method, or the theoretical or proven risks
usually outweigh the advantages of using the method. The contraceptive method
should not be used if this represents an unacceptable health risk or where the advan-
tages of using the method generally outweigh the theoretical or proven risks (WHO
2012). In the UK, they have been adopted and adapted by the Faculty of Family
Planning and Reproductive Health Care in 2006 and are referred to as the UKMEC
(French 2009).

Mental health practitioners cannot be expected to be expert in contraception, but
it is helpful to have a basic understanding of the contraceptive methods available
and their advantages and disadvantages. It is important that you encourage both
men and women to seek expert advice, especially if they are taking any form of
medication and/or have any medical conditions. Table 8.1 outlines common
contraceptive methods and their advantages and disadvantages. It is also important
to reiterate that the majority of contraceptive devices do not protect against STIs
and, as such, clients should always be advised to use condoms in addition to their
chosen method of contraception.

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS120

Contraceptive
method Advantages Disadvantages

Male condom
85–98%
effective

Widely and easily available
The only contraceptive method
that protects against STIs and
HIV when used correctly and
consistently.
Available over the counter or via
the internet.
Available in various colours,
flavours, sizes, etc.
There are no medical side effects.

Some people say it interferes with the
spontaneity of sex and some men report
feelings of reduced sensation.
Latex sensitivity can occur – alternative
non-latex condoms must be used for
people with a latex allergy.

Female
condom
79–95%
effective

Reduced sensation is less likely
for the male.
An effective method that is
controlled by the woman.
Available over the counter or via
the internet.
Protects against STIs.
Made of strong polyurethane so
there is reduced risk of splitting
when compared with the male
condom.

Not suitable for women who dislike
touching their genitalia.
Unattractive appearance.
Can be noisy during sex.
Penetration can sometimes occur
outside the condom and sometimes the
condom may be pushed up into the
vagina.

Diaphragm
84–94%
effective

Woman controlled.
Can be used by women who
are breastfeeding.
Spermicide use provides
additional vaginal lubrication.
Gives some protection against
pelvic inflammatory disease.
Gives protection against pre-
malignant disease and
carcinoma of the cervix.
Reusable.
Can be inserted up to several
hours before intercourse.
No hormonal side-effects.

Latex sensitivity can occur.
Risk of toxic shock syndrome if the
diaphragm is left in situ over a prolonged
period.
Not suitable for women who dislike
touching their genitalia.
Needs to be refitted if the woman gains
or loses 7lbs of weight and also
following childbirth and pelvic surgery.
Requires insertion before intercourse.
Spermicide can be messy.
Initial fitting must be carried out by a
trained doctor or nurse.
Does not protect against STIs and HIV.
May cause some loss of sensation for
the woman and also some discomfort.
Increased risk of urinary tract infections.
Must be motivated to continue using this
method.

Combined Oral
Contraceptive
pill (COC),
commonly

Highly effective if taken correctly
and consistently.
Regulates menstruation so
periods can be predicted.

Not suitable for all women therefore
expert advice should be sought
Does not protect against STIs and HIV.

Table 8.1 Common contraceptive methods

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 121

Contraceptive
method Advantages Disadvantages

known as the
pill, 92–99%
effective

Reduces PMT symptoms,
bleeding and menstrual pain.
Provides protection against
ovarian, endometrial and bowel
cancer.
Reduces ovarian cysts.
Nearly 100% reversible.
Does not interfere with sex.

Side-effects can include: break through
bleeding (BTB) or ‘spotting’ bleeding,
nausea, breast tenderness and mood
changes, headaches, migraines, weight
gain, depression, reduced libido.
Efficacy may be affected by some
medicines such as St John’s Wort, some
anticonvulsants, some antibiotics and
some antiretrovirals.
There may be a slight increase in risk
of breast cancer, although this is
uncertain.
There may be an increased risk of
thrombosis and stroke for some women
– this risk increases if the woman
smokes and is over 35 years old.
Long-term use of the COC (over 8
years) may slightly increase the risk of
cervical cancer.

Progestogen
Only Pill (POP)
commonly
known as ‘the
mini pill’
96–99% efficacy
with consistent
use

Does not contain oestrogen and
may therefore be suitable for
women who are unable to take
the COC.
Effective method of
contraception if taken correctly
and consistently.
Can be used by women who
are breastfeeding.
Does not interfere with sex.

Although the POP is very safe, there
are a few women for whom the POP
is not suitable, therefore expert
advice should be sought
Must be taken within a 3-hour margin every
24 hours (Cerazette 12-hour margin).
Ovarian cysts and risk of ectopic
pregnancy in conception does occur.
Some women report weight gain, acne,
breast tenderness, spotting, bleeding
and erratic bleeding patterns.
Does not protect against STIs and HIV.

Progestogen
only injection
(Long-Acting
Reversible
Contraception
[LARC])
99–100%
efficacy

Highly effective method of
contraception.
Does not contain oestrogen and
may therefore be suitable for women
who are unable to take the COC.
Does not interfere with sex.
Need to have a repeat injection
every 12 weeks so do not have
to remember to take a pill daily
Protects against pelvic infection
and cancer of the uterus.
Not affected by other medicines.

Not suitable for all women therefore
expert advice should be sought
Have to wait at least 12 weeks for the
effects of the injection to subside.
Need to return to health provider for
repeat injection every 12 weeks.
Reported side-effects include weight gain,
spotting, irregular bleeding, mood
changes, breast tenderness and loss of
libido.
Delay in return of fertility from a few
months up to 18 months on stopping
the injection.

(Continued)

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Contraceptive
method Advantages Disadvantages

Can be used by women who
are breastfeeding.
Some women will have no
bleeding which can be seen as
an advantage.

Does not protect against STIs and HIV.
There is a possible link between the
progestogen injection and an increased
risk of osteoporosis.

Intra-Uterine
System (IUS)
known as the
Mirena Coil and
Intra-Uterine
Device (IUD)
commonly
known as ‘the
coil’)
Both methods
are LARCs
97–99% efficacy

Both devices are highly effective
methods of contraception.
Long-lasting between three and
five years depending on device
used.
Does not interfere with sex.
Can be used by women who
are breastfeeding.
Does not contain oestrogen and
therefore may be suitable for
women who are unable to take
the COC.
Fully reversible on removal.
Mirena coil can be used to treat
heavy and painful periods.

Needs insertion by a qualified doctor or
nurse.
Insertion may be uncomfortable for
some women.
Small risk of uterine perforation.
The IUD may increase menstrual blood
loss.
There may be some progestogen side-
effects with the Mirena coil, such as
spotting bleeding.
Does not protect against STIs and HIV.

Progestogen
implant known
as Implanon
and Nexplanon
Efficacy >99%
It is a LARC
method

Highly effective method of
contraception.
Long-acting (three years).
Fully reversible on removal
Does not contain oestrogen and
may therefore be suitable for
women who are unable to take
the COC.
Does not interfere with sex.
Can be used by women who
are breastfeeding after six
weeks following the birth.
No evidence that it affects bone
mineral density.

Needs insertion and removal by a
qualified doctor or nurse.
Small risk of complications following
insertion, such as infection, bruising,
bleeding and scarring.
Sometimes may be difficult to remove.
Possible side-effects, including weight
gain, headaches, breast tenderness,
altered bleeding pattern, such as
spotting bleeding.
Does not protect against STIs and HIV.

Emergency
contraception
‘the morning after
pill’ (pill containing
progestogen;
only known as
Levonelle in the
UK)

Safe method for when other
methods have not been taken
correctly or not used.

Can cause nausea and vomiting.
Does not protect against STIs and HIV.
May alter bleeding pattern.

Table 8.1 (Continued)

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SEXUAL HEALTH IN MENTAL HEALTH PRACTICE 123

Before moving on to the conclusion, utilise the information from this chapter to
consider the following case study.

Clara

Clara is a 34 year-old married lady who works part-time as a clerical worker and has
two young children. She was diagnosed with manic depression in her early twenties
but despite having had long periods of remission she has also had several short but
intense periods of mania, some of which have led to brief hospital admissions. Clara
has recently experienced her most severe period of mania yet, and during your visit to
her home today she has become very upset. Clara explains that during this period she
stayed away from home for five nights with people she had recently met at a party.
She is distraught as she recalls that she was highly promiscuous during this time and
had sexual encounters with a number of different men. Clara’s primary concern is the
potential damage this may do to her marriage and she is struggling to decide what to
disclose to her husband. She rebuffs your suggestion that she visit her GP or sexual
health centre as she feels embarrassed.

• What are the risks to Clara’s sexual health?
• Identify the steps you could take to ensure she receives the optimum care at this time?

Answer guide:

1 Clara is at risk of having contracted an STI. The long-term consequences of
undiagnosed and untreated STIs are serious and sometimes fatal, so it is vital that
any STI is diagnosed and treated as soon as possible. In addition, Clara is of child-
bearing age and there is a risk that she may be pregnant.

2 It is vitally important that you, as her mental health practitioner, are open and
willing to discuss this sensitive issue with Clara and every attempt should be made
to encourage her to attend a sexual health screening clinic. This may be achieved
by highlighting the anonymity of the service, educating her about the importance
of early diagnosis and the availability of effective treatments for many infectious
conditions, facilitating access and possibly even accompanying her on her visit.
However, if this is unsuccessful, then you could assess Clara for the presence of
common signs and symptoms of an STI, such as inter-menstrual bleeding, vaginal
discharge, genital inflammation and swelling, vaginal ulceration or rash, genital
itching, pain on urination and lower abdominal pain. In addition, Clara should be
encouraged to take a pregnancy test and may benefit from having the details of a
pregnancy advisory service. She should also be strongly encouraged to use a barrier
method of contraception until an STI has been ruled out so that she does not risk
passing an infection on to her husband. Clara should be made aware of the how to
access a sexual health screening service in case she changes her mind at a later
date. Lastly, it may be possible to liaise with Clara’s family GP, with her consent, to
consider the possibility of Clara taking a course of broad-spectrum antibiotics.

CA
SE STU

D
Y

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS124

CONCLUSION

Good sexual health is a basic human given yet so many people fail to experience
this. Both body and mind can be affected by sexual ill-health, yet it is an often over-
looked aspect of health care practice. While a variety of reasons have been offered
for this, reluctance on the part of the health professional is undoubtedly key, with
personal discomfort and a lack of knowledge being at the core of the problem.
Addressing this reluctance must, however, be a priority for mental health practitioners
as the increased risk of sexual ill-health to individuals with mental health problems
adds yet another vulnerability to an already disadvantaged group. By promoting
sexual wellbeing, mental health practitioners have the opportunity to enhance the
overall health of their clients, while being attuned to the signs of sexual ill-health
will facilitate access to appropriate sexual health services.

USEFUL RESOURCES

At the time of writing in the UK we recommend the following resources:

World Health Organization – www.who.int/
HIV and Aids information – www.avert.org.uk
Marie Stopes International – www.mariestopes.org.uk
International Planned Parenthood Federation – www.ippf.org/en

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Collins, E., Drake, M., & Deacon, M. (Eds.). (2013). The physical care of people with mental health problems : A guide for best practice. SAGE Publications.
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8 volume 36 | number 1 January/February 2011

2ndOPINION
PRO
Writing for the PRO position: Wanda Montalvo, MSN, RN, ANP

I
n my opinion, poverty is a major
contributing factor to the twin
tower epidemic of childhood

obesity and type 2 diabetes mellitus
(T2DM). Between 1963 and 1970,
the rate of obesity among children
and adolescents was 4.0%. By the
year 2000, the rate almost quadru-
pled to 15.5% (Bloomgarden,
2004). According to the CDC, in
the last two decades the United
States has experienced increased
rates of T2DM in children and
adolescents, with obesity being
identified as one of the major con-
tributors. Although childhood
obesity is known to be a major risk
for the development of diabetes
(along with other contributing
factors such as eating high-calorie
foods, lack of exercise, and family
history), poverty plays a key, but
often overlooked, role.

Studies have shown that older
non-Hispanic white children in the
8 to 16 age group in families with
low incomes were significantly
more likely to be overweight than
children in families with high in-
come (Alaimo, Olson, & Frongillo,
2001). People living in the lowest
socioeconomic status (SES) cate-
gories with less than a high school
diploma had an excess risk (2.4
times that of higher SES catego-
ries) of diabetes-related mortality
(Saydah & Lochener, 2010). The
poorest income groups are the ones
most likely to be obese and thus at
risk for developing diabetes.

Food insecurity due to uncertain
availability of nutritionally ade-
quate foods and socioeconomic
constraints impact families in the
lowest SES. Clearly, there is an im-
portant link between a family’s
income level and a child’s health

and well-being. Current strategies to reduce childhood obesity and diabetes
recommend raising clinical awareness about the disease, developing standard
definitions, and assessing and improving the quality of care among children
and adolescents diagnosed with T2DM. Unless we focus on poverty, however,
this epidemic will not be alleviated. Awareness of the disease is not enough.
Recently New York City has taken a strong policy position in increasing
the population’s awareness of foods being ordered in all fast food and other
restaurants by requiring that use of trans fats be reduced in restaurant food
preparation and that calorie counts on menus must be posted in all food estab-
lishments. Yet, New York City still shows a variance of diabetes among different
socioeconomic groups, especially among ethnic minorities with less than a high
school diploma.

It is time to broaden our efforts toward learning how to combat poverty if we
are ever going to hope to reduce obesity and diabetes in children. In the 2000
recommendations of
the American Academy
of Pediatrics, it was sug-
gested that social scien-
tists be integrated into
pediatric research be-
cause of the complexity
of the combined issues
of race/ethnicity, gen-
der, and SES on child
health status. As the
U.S. economic recession
pushes more families
into unemployment and
lower SES, both school lunch programs and emergency food assistance have
increased by 18%, highlighting the burden of poverty. Addressing poverty as
essential in improving children’s lives and health is crucial. If inequalities in
SES cause inequalities in health status, it is our job to change this. As nurses, we
need to think beyond the clinical indicators and advocate for changes in socio-
economic policies that will reduce income inequality and thus diabetes and
obesity in children.

Wanda Montalvo is the Clinical Director of NYS Health Diabetes Campaign,
NY State Health Foundation, New York, NY.

References

Alaimo, K., Olson, C. M., & Frongillo, E. A. (2001). Low family income and food insufficiency in rela-
tion to overweight in US children: Is there a paradox? Archive Pediatric Adolescent Medicine,
155(10), 1161–1167.

Bloomgarden, Z. T. (April 2004). Type 2 diabetes in the young: The evolving epidemic. Diabetes
Care, 27(4), 998–1010. doi 10.2337/diacare.27.4.998

Saydah, S., & Lochener, K. (2010). Socioeconomic status and risk of diabetes-related mortality in
the U.S. Public Health Reports, 125(3), 377–388.

Is Poverty the Root Cause of the Epidemic of
Type 2 Diabetes Mellitus in Children?

Children in families with low income
are signifi cantly more likely to be
overweight than children in families
with high income, and people living
in the lowest SES categories have an
excess risk (2.4 times that of higher
SES categories) of diabetes-related
mortality.

Copyright © 2010 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

January/February 2011 MCN 9

Writing for the CON position: Xxx

Second Opinion columns are coordinated
by Kathleen Leask Capitulo and Heidi
VonKoss Krowchuk. Dr. Capitulo can be
reached via e-mail at: DrKatieRN@
hotmail.com. Dr. Krowchuk can be reached
via e-mail at: Heidi_Krowchuk@uncg.edu.2ndOPINION

CON Coordinated by Kathleen Leask Capitulo, DNSc, RN, FAAN
Writing for the CON position: Melissa Capitulo, BSN, RN

W
hy is pediatric type 2 dia-
betes (T2DM) an epi-
demic? In my opinion,

the root causes are not just poverty,
but rather multifactorial: poor nu-
tritional education, changing di-
etary patterns, increased sedentary
lifestyles, obesity, genetics, family
histories of diabetes, poor socio-
economic status (SES), high body
mass index (BMI), and insulin re-
sistance syndrome. This global
epidemic is evidenced by the tri-
pling of people with diabetes since
1985 (Bloomgarden, 2004).

A major contributing factor to
this public health problem is nutri-
tion: what children eat. The Ameri-
can diet has changed over the past
25 years. For many families, fast
foods and high-calorie drinks have
replaced home cooking and milk.
In the current economic recession
many families find it cheaper to buy
fast food or junk food, rather than
prepare healthy and organic foods.
Increased amounts of simple car-
bohydrates have contributed to
higher insulin resistance and obesi-
ty, resulting in increased T2DM in
children.

Exercise plays an important role
in the prevention and treatment of
T2DM by decreasing weight, and
lowering BMI and insulin resis-
tance. As schools so often cut phys-
ical education and extracurricular
activities to make more time prepar-
ing for testing, children are less
active. The increased use of video
games and computers has contrib-
uted to a sedentary lifestyle for chil-
dren. Exercise, alone, however, has
not been found to decrease T2DM,
but when combined with diet and a
healthy lifestyle, it is effective
(Hayes & Kriska, 2008).

Obesity in children has tripled in the last 47 years leading to increased inci-
dence of T2DM, hypertension, behavioral and musculoskeletal, and behavior
diseases. Obesity in children leads to obesity in adulthood with the concomitant
risks of cardiovascular disease, hypertension, hyperinsulinemia, hypercholester-
olemia, and colon cancer. Some interventions have been successful in altering
these patterns. Sepulveda, Tait, Zimmerman, and Edington (2010) have shown
that web-based, voluntary intervention program giving parents incentives to
promote healthy lifestyles, including food management, increased physical activ-
ity, family dinners, and decreased children’s screen time (time on the computer
or video games). Results of the intervention program included increases in
healthy behaviors such as increased physical activity, increased consumption of
fruit and vegetables, and family dinners.

Genetics also plays a role in the development of T2DM in children. The inci-
dence of T2DM is significantly higher in Native American children, particularly in
the Pima Indians of Arizona where the incidence is 50.9 per 1,000. Overall, Native
American populations
in the United States have
a rate of 4.5 per 1,000.
In some populations,
however, diabetes has a
low incidence such as in
Italy, where a study of
710 obese children in
Italy showed that only
0.2% developed T2DM
(Bloomgarden, 2004).

T2DM is a growing
epidemic and health concern, but not just because of poverty. Increased con-
sumption of simple carbohydrates and fast food, decreased physical activity and
a sedentary lifestyle, obesity, and genetics all play a role. Healthcare providers
should focus on prevention through education of children, families, and schools
about healthy lifestyle behaviors, and on early detection, particularly in high-risk
populations such as children with obesity and a family history of T2DM. With-
out early detection and treatment, future generations will be challenged by the
health and economic costs of increasing numbers of adults with T2DM. ✜

Melissa Capitulo is a Staff Nurse, Pediatrics, Winthrop University Hospital,
Mineola, NY.
DOI:10.1097/NMC.0b013e3181fbaf1f

References
Bloomgarden, Z. (April 2004). Type 2 diabetes in the young: The evolving epidemic. Diabetes Care,

27(4), 998–1010. doi 10.2337/diacare.27.4.998
Hayes, C., & Kriska, A. (2008). Role of physical activity in diabetes management and prevention.

Journal of the American Dietetic Association, 108(4 Suppl. 1), S19–S23. doi: 10.1016/j.
jada.2008.01.016

Sepulveda, M. J., Tait, F., Zimmerman, E., & Edington, D. (2010). Impact of childhood obesity on
employers. Health Affairs, 29(3), 513–521. doi: 10.1377/hlthaff.2009.0737

T2DM is a growing epidemic and
health concern, but not just because
of poverty. Increased consumption
of simple carbohydrates and fast
food, decreased physical activity
and a sedentary lifestyle, obesity,
and genetics all play a role.

Copyright © 2010 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

INVITED REVIEW

Nutrition in early life and the programming of adult
disease: a review
S. C. Langley-Evans

School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, UK

Keywords

cardiovascular disease, foetal programming,

metabolic syndrome, obesity, pregnancy,

weaning.

Correspondence

S. C. Langley-Evans, School of Biosciences,

University of Nottingham, Sutton Bonington

Campus, Loughborough LE12 5RD, UK.

Tel.: +44 (0)115 9516139

Fax: +44 (0)115 9516122

E-mail: simon.langley-evans@Nottingham.ac.uk

How to cite this article

Langley-Evans S.C. (2015) Nutrition in early life

and the programming of adult disease: a review.

J Hum Nutr Diet. 28 (Suppl. 1), 1–14

doi:10.1111/jhn.12212

Abstract

Foetal development and infancy are life stages that are characterised by

rapid growth, development and maturation of organs and systems. Variation

in the quality or quantity of nutrients consumed by mothers during preg-

nancy, or infants during the first year of life, can exert permanent and pow-

erful effects upon developing tissues. These effects are termed

‘programming’ and represent an important risk factor for noncommunica-

ble diseases of adulthood, including the metabolic syndrome and coronary

heart disease. This narrative review provides an overview of the evidence-

base showing that indicators of nutritional deficit in pregnancy are associ-

ated with a greater risk of type-2 diabetes and cardiovascular mortality.

There is also a limited evidence-base that suggests some relationship

between breastfeeding and the timing and type of foods used in weaning,

and disease in later life. Many of the associations reported between indica-

tors of early growth and adult disease appear to interact with specific geno-

types. This supports the idea that programming is one of several cumulative

influences upon health and disease acting across the lifespan. Experimental

studies have provided important clues to the mechanisms that link nutri-

tional challenges in early life to disease in adulthood. It is suggested that

nutritional programming is a product of the altered expression of genes that

regulate the cell cycle, resulting in effective remodelling of tissue structure

and functionality. The observation that traits programmed by nutritional

exposures in foetal life can be transmitted to further generations adds

weight the argument that heritable epigenetic modifications play a critical

role in nutritional programming.

Introduction

Research over a period of several decades has identified

associations between anthropometric measurements at

birth and disease in later life (Barker, 2006; Langley-

Evans & McMullen, 2010; Gluckman et al., 2011). The

epidemiological studies describing such associations have

led to the assertion that factors in the maternal environ-

ment influencing growth and development can also alter

tissue function, such that adult physiology reflects the

early-life experience. Work with experimental models

has confirmed that nutrition in early life has the capac-

ity to permanently establish physiological and meta-

bolic states that effectively determine the risk of diseases

that occur with ageing (Langley-Evans & McMullen,

2010).

The evidence linking nutrition in early life to health in

adulthood now forms a cornerstone of health promotion

and public health nutrition programmes globally. A 2009

report recognised and promoted the importance of foetal

and early-life nutrition and its relationship with lifelong

health. This report found compelling evidence for a role

of early-life nutrition in setting the risk of conditions

including coronary heart disease, type-2 diabetes, osteo-

porosis, asthma, lung disease and some forms of cancer

(British Medical Association, 2009). These findings were

further backed by the 2011 report of the UK Scientific

Advisory Committee on Nutrition, which recommended

1ª 2014 The British Dietetic Association Ltd.

Journal of Human Nutrition and Dietetics

a strategy to promote, protect and support breastfeeding

and to optimise the diets and body composition of young

women (Scientific Advisory Committee on Nutrition,

2011). In 2012, the WHO published global targets and

recommendations for the nutrition of mothers, infants

and young children with the aim of reducing the preva-

lence of low birth weight (World Health Organization,

2012).

The concept of early-life programming

The term ‘programming’, originally coined by Lucas

(1991), is used to describe the process by which exposure

to specific environmental stimuli or insults, during criti-

cal phases of development, can trigger adaptations that

result in permanent changes to the physiology of the

organism (Gluckman & Hanson, 2004; Gluckman et al.,

2011). In other words, when a developing foetus or infant

is subject to external challenge, the physiological adapta-

tions that occur to ensure survival may leave behind a

permanent memory of that exposure.

Programming is a consequence of the plasticity of cells

and tissues during development, which permits the devel-

oping embryo or foetus to respond to their current envi-

ronment. For most types of cell, plasticity is a short-lived

characteristic that is a feature only of the embryonic and

foetal stages. In some cell types, the adaptive capacity

remains present throughout life. For example, the human

immune system can respond to infection by a previously

unencountered pathogen and the B-lymphocytes that dif-

ferentiate during that response remain available to com-

bat any subsequent infection by that organism

(Gluckman et al., 2011). The majority of tissues retain

plasticity only during the periods of embryonic and foetal

development. As a result, these are considered to be the

critical developmental phases during which perturbation

of normal processes and hence programming of human

health and disease by nutrition may occur.

A key process through which the environment encoun-

tered during early life may determine lifelong physiologi-

cal and metabolic function, and hence disease risk, is

likely to be through the remodelling of organs and tissues

(Langley-Evans, 2009). All tissues have a structure that

relates to their function, with functional units that are

required to mediate physiological function. For example,

in the pancreas, the functional unit required for mainte-

nance of insulin synthesis and secretion is the islet. Simi-

lar to most human systems, the pancreas is fully formed

by the time of birth and the number of islets is set in ute-

ro (Snoeck et al., 1990). Subtle developmental exposures

that result in fewer islets being formed may have no

immediate impact upon pancreatic function but make an

age-related decline in metabolic regulation more likely. As

described below, the same principle applies to other

organs and tissues (Langley-Evans et al., 1999) and,

hence, factors that determine the quality of the intrauter-

ine environment can modify tissue structure and are

effectively risk factors for noncommunicable diseases of

adulthood.

A diverse range of different stimuli operating during

development may have a programming effect. This review

describes the programming effects of the nutritional envi-

ronment encountered in early life. In addition, any envi-

ronmental factor that might impact upon foetal growth

should be regarded as a potential programming influence,

including smoking, severe psychological trauma, maternal

infection or pharmacological agents (Seckl & Meaney,

2004; Yehuda et al., 2005; Salmasi et al., 2010; Schmiege-

low et al., 2013).

The timing of exposure to potential programming

stimuli may be critical in determining the outcome of the

event. Greatest sensitivity will occur during the periods of

most rapid growth and maturation. For example, the kid-

ney may be most vulnerable during the phase of nephro-

genesis (Langley-Evans et al., 1999). The brain, which has

a critical period of development early in human gestation,

may remain vulnerable for much longer because extensive

growth and development of neural pathways and linkages

extends well into childhood (Plagemann et al., 2000).

Longer periods of exposure may be expected to have an

impact upon a greater range of organs and systems.

Nutritional programming during foetal
development

Some of the earliest indications of a relationship between

the intrauterine environment and later health were pro-

vided by ecological studies that showed simple correla-

tions between place of birth and the risk of death from

coronary heart disease and between the risk of death in

infancy and coronary heart disease mortality (Barker &

Osmond, 1987; Osmond et al., 1990). These early indica-

tions were given extra weight through retrospective

cohort studies based upon a population from Hertford-

shire, UK. Records from 16 000 men and women born in

Hertfordshire between 1911 and 1930 included weight at

birth and weight at age 1 year. It was found that,

although mortality rates for all causes were unrelated to

size at birth or in infancy, lower birthweight was associ-

ated with increased coronary mortality (Barker et al.,

1989). Follow-ups of men aged 64–75 years in this cohort
indicated inverse associations between weight at birth and

blood pressure (Barker et al., 1990), type-2 diabetes

(Hales et al., 1991) and the insulin resistance syndrome

(Barker et al., 1993). A number of similar studies indi-

cated inverse relationships between lower birthweight

2 ª 2014 The British Dietetic Association Ltd.

Early life – later disease S. C. Langley-Evans

(but within the normal population range) and disease

outcomes. In one of the largest of these studies, the US

Nurses Health Study, Curhan et al. (1996) collected data

on birthweight from 70 297 women and found that,

among full-term singletons, and after adjustment for

adult body mass index, the risks of coronary heart disease

and stroke were both related to weight at birth (relative

risk estimate 0.85 per kg increase in birth weight). A

lower weight at birth was also associated with higher

blood pressure in adult life. In addition to studies show-

ing relationships between birthweight and disease risk in

adults, a number of reports indicated that disease markers

are elevated in young children subsequent to low birth-

weight (Bavdekar et al., 1999).

Birthweight is not the only measureable feature at birth

that is related to later health and disease. Thinness at

birth (measured as ponderal index; weight/length
3
) has

been found to be inversely related to risk of type-2 diabe-

tes and glucose intolerance. Eriksson et al. (1999, 2001)

have reported extensively upon two populations born in

Helsinki, Finland (1924–33 and 1933–44). Follow-ups of
these cohorts confirmed that stroke and coronary heart

disease mortality were greater with low birthweight. Thin-

ness at birth was also related to risk of coronary heart

disease death type-2 diabetes and metabolic syndrome if

body mass index was high in later childhood (Eriksson

et al., 1999, 2001). Large head circumference in propor-

tion to body length is also a potential disease marker

(Carrington & Langley-Evans, 2006) and, together, these

observations suggest that factors constraining truncal

growth in utero also bring about a programming effect

upon the developing organs, which permanently perturbs

function and redundancy of systems in the face of ageing.

Observations that intrauterine factors were related to

disease in adulthood were explained by the initiators of

the programming hypothesis in terms of deficits in

maternal nutrition. It was argued that, in the early part

of the 20th Century when the Hertfordshire and Helsinki

cohorts were born, the main drivers of poor pregnancy

outcome were poverty and associated undernutrition and

infectious disease among young women. This argument

received some weight with the observation that placental

size was also related to disease outcomes. In children,

blood pressure was positively associated with placental

weight (Moore et al., 1996) and follow-ups of a cohort of

50-year-old men and women found that highest blood

pressure was associated with lower birthweight and a lar-

ger placenta (Barker et al., 1990). Because the placenta is

the primary determinant of nutritional supply to the foe-

tus, it was reasoned that nutritional deficit or excess

could alter the foetal : placental ratio with irreversible

consequences for organ structure (Godfrey et al., 1991).

Animal studies also indicated that lower birthweight was

a frequent outcome of maternal undernutrition (Woodall

et al., 1996). In sheep, maternal undernutrition also

results in placental enlargement, a response that is inter-

preted as an adaptation to maximise transfer of nutrients

from mother to foetus (McCrabb et al., 1991).

To some extent, this argument remains accepted within

the field, although it has to be recognised that measures

of infant anthropometry at birth or placental size are only

crude proxies for nutritional exposure during pregnancy.

However, there are very few studies that have the capacity

to offer more meaningful measures in the context of

long-term health. Where such information is available,

the effects are often small or difficult to interpret. In the

winter of 1944–1945, western Holland was subject to a
famine of approximately 6 months in duration [at the

height of the famine, the adult ration was 2.09–
2.51 MJ day

–1
(500–600 kcal day–1)] because of the

blockade of food supplies by Nazi forces (Roseboom

et al., 2001, 2011). As a result of the duration of the fam-

ine, some pregnant women were affected over the final

stages of pregnancy, whereas others were undernourished

in early pregnancy. Birth weights among babies affected

by famine in late gestation were approximately 250 g

lower than those of babies born before or conceived after

the famine (Lumey, 1992; Roseboom et al., 2001).

For mothers who experienced the famine in the first

trimester of gestation, the babies were heavier at birth

than the norm for the population. Over a number of fol-

low-ups considering health outcomes for the famine

babies compared to contemporaries born before or after

the famine, it was shown that exposure to famine in early

gestation was associated with a greater prevalence of cor-

onary heart disease and raised circulating lipids, as well as

with raised concentrations of blood clotting factors and

more obesity compared to those not exposed to the fam-

ine (Ravelli et al., 1976, 1999, 2000; Roseboom et al.,

2001). Individuals who had suffered exposure to the fam-

ine during mid-gestation were more likely to exhibit

impaired renal function as adults (Painter et al., 2005)

and exposure to famine during late gestation was associ-

ated with glucose intolerance and type-2 diabetes (de

Rooij et al., 2006a; de Rooij et al., 2007).

A study conducted in a small number of children dem-

onstrated a relationship between maternal iron status and

adiposity and offspring blood pressure (Godfrey et al.,

1994). Blood pressure was also an outcome reported by

Project Viva, a US prospective cohort study following the

children of women whose nutritional status had been

measured in detail in the period before and during preg-

nancy. Gillman et al. (2003) reported that maternal cal-

cium supplementation during pregnancy reduced blood

pressure in 6-month-old infants. Project Viva also identi-

fied an association between higher maternal vitamin D

3ª 2014 The British Dietetic Association Ltd.

S. C. Langley-Evans Early life – later disease

intake and lower risk of childhood asthma among 3-year-

old children (Camargo et al., 2007). The same cohort

showed that babies born to women who gained excessive

weight in pregnancy were more likely to be obese in

childhood (Oken et al., 2009). Normia et al. (2013)

reported that, in a small cohort of mother–child (4-year-
old) pairs, higher maternal carbohydrate intake was asso-

ciated with higher childhood systolic blood pressure and

higher childhood systolic blood pressure was noted in off-

spring exposed to lowest or highest tertiles of maternal

fat intake during pregnancy. A longer-term follow up of

Scots aged in their 40s for whom maternal food intake

data were available also provided evidence that maternal

intake could be a driver of intrauterine programming

(Campbell et al., 1996). Adult blood pressure was associ-

ated with maternal intakes of animal protein and sugars,

although the relationship was complex and nonlinear.

The epidemiological approaches to investigating the

relationships between events in foetal life and outcomes

60–70 years later are inevitably subject to criticism.
Clearly, there is no scope for a randomised controlled

trial in this area and, although there are a number of

ongoing prospective cohort studies, it is inevitable that

the literature relies upon retrospective cohorts and case–
control studies. These are prone to unadjusted confound-

ing and generally are reliant on poor proxy markers of

nutrition in pregnancy. A single measure of weight at

birth reveals little about the experience of the foetus in

utero and cannot provide any indication of whether

growth was constrained, or what factors were limiting. As

demonstrated by the Dutch Hunger Winter studies,

undernutrition at different stages of gestation may have

varying effects upon final birthweight, including an

increased size at birth (Lumey, 1992; Roseboom et al.,

2001). Moreover, among populations in developed coun-

tries, the correlation between maternal intake and birth

weight is poor (Godfrey et al., 1996; Langley-Evans &

Langley-Evans, 2003). The actual nutritional environment

encountered by the foetus is far more complex, reflecting

maternal intake, stores, maternal activity, placental func-

tion and rate of foetal growth. A meta-analysis by Huxley

et al. (2002) identified a high influence of measurement

and publication bias in the literature linking foetal growth

to cardiovascular disease but, importantly, other robust

systematic reviews and meta-analyses have confirmed

relationships between birth anthropometry and the risk of

type-2 diabetes and chronic kidney disease (Whincup

et al., 2008; White et al., 2009).

Given the unavoidable issues with epidemiology in this

area, much of the research designed to investigate the

mechanistic basis of programming, and to confirm the

association between physiological and metabolic function

in adulthood and nutrition during foetal life, has been

reliant on experimental animal studies. It is most striking

that, across a diverse range of species, including rodents,

sheep and nonhuman primates, there are solid relation-

ships between maternal nutritional status and blood pres-

sure, feeding behaviour, adiposity and glucose

homeostasis (Langley-Evans, 2013). The animal evidence

suggests that apparently very different nutritional insults

during pregnancy (e.g. iron deficiency and maternal over-

feeding) can elicit essentially the same outcomes in the

resulting adult offspring (Langley-Evans et al., 1996;

Gambling et al., 2003; Samuelsson et al., 2008). Not only

does this confirm the biological plausibility of the pro-

gramming hypothesis, but it also suggests that a limited

number of common mechanisms may link nutritional

‘stressors’ to development changes that result in later

disease.

Nutritional programming during infancy

The early studies of nutritional programming identified

growth over the first year of life as an indicator of disease

in adulthood. For example, Hales et al. (1991) reported

that, in addition to birthweight, weight at 1 year was sig-

nificantly related to glucose intolerance and beta-cell dys-

function in 64-year-old men. Such studies have not been

longitudinal in nature and so, in that study, it was not

clear whether the smaller 1-year-olds were also the small

newborns, or whether they represented a group who had

failed to thrive after birth. However, data of this nature

have been regarded as generally supportive of nutritional

programming occurring during early infancy. Other stud-

ies argue that the key driver of programmed disease is the

combination of poor early growth with rapid catch-up

growth in infancy and childhood (Eriksson et al., 1999,

2001; Forsen et al., 1999).

Nutrition in the earliest stage of infancy is provided

solely as milk, which may be human milk delivered by

breastfeeding or formula milk from bottle feeding. There

is a large amount of literature available describing the

longer-term health benefits of breastfeeding, providing

evidence suggesting that disease risk is programmed dur-

ing this period (if we accept that human milk is optimal

for growth and development and formula milk is not). A

positive effect of breast-feeding on cognitive function is

widely reported (Evenhouse & Reilly, 2005) and breast-

feeding appears likely to protect against some immune-

related diseases later in life, such as type-1 diabetes

(EURODIAB, 2002) and inflammatory bowel disease (Kle-

ment et al., 2004). There is significant literature detailing

the benefits of breastfeeding in preventing atopic disease

in children with a family history (Gdalevich et al., 2001).

However, the literature on breastfeeding and later health

is plagued by methodological difficulties, being heavily

4 ª 2014 The British Dietetic Association Ltd.

Early life – later disease S. C. Langley-Evans

dependent upon observational studies with self-report of

breastfeeding behaviour, and subject to the effects of con-

founding factors (Schack-Nielsen & Michaelsen, 2007).

There is limited convincing evidence that the window

for nutritional programming extends any further into

infancy. The World Health Organization recommends

exclusive breastfeeding until 6 months of age and contin-

ued breastfeeding until 2 years of age or beyond. After

6 months, appropriate complementary foods should be

introduced, although some argue that this is too late for

infants in developed countries where the risk of water- or

food-borne infection is low (Fewtrell, 2011). In develop-

ing countries, early or inappropriate complementary feed-

ing may lead to malnutrition and poor growth but, in

countries where obesity is a greater public health concern

than malnutrition, the relationship between mode of

feeding, growth and longer-term health is unclear.

A systematic review of the literature (Pearce et al.,

2013) investigating the relationship between the timing of

the introduction of complementary feeding and obesity

or being overweight during childhood found that intro-

ducing complementary foods at ≤4 months was associated
with a higher body mass index (BMI) in childhood.

However, this was largely reflected in lean mass and there

was no strong evidence of earlier weaning being associ-

ated with greater adiposity. It is possible that effects of

complementary food may interact with earlier nutritional

experience. The responses of formula-fed infants to early

weaning may differ from those of breastfed babies (Przyr-

embel, 2012). There is evidence that the mode of feeding

before weaning influences flavour preferences in infants.

These effects of exposure to either breast milk (and the

exposure to flavours in the maternal diet) or formula

may affect food choices and health in later life. (Trabulsi

& Mennella, 2012).

In addition to the timing of introduction of comple-

mentary feeding, the nature of the foods used in weaning

have been considered as potential determinants of child-

hood obesity or being overweight. The systematic review

of Pearce & Langley-Evans (2013) found some evidence

of an association between high protein intakes at

2–12 months of age and higher BMI or body fatness in
childhood. Higher energy intake during complementary

feeding was also associated with a higher BMI in child-

hood. Adherence to dietary guidelines during weaning

was associated with a higher lean mass, although consum-

ing specific foods or food groups made no difference to

childhood BMI.

Although the early nutritional environment may have

some limited effects on adiposity in childhood, the

longer-term relationship to health in adulthood is

unclear. There is strong evidence indicating that a degree

of the risk of adult obesity and being overweight is

related to being overweight in childhood, a phenomenon

known as tracking (Freedman et al., 2001). It is likely that

the strongest determinant of weight and fat mass tracking

is genetics rather than diet, however, and it is also appar-

ent that childhood obesity has no strong independent

effect upon risk of either cardiovascular disease or meta-

bolic disorders (Lloyd et al., 2010, 2012). These are heav-

ily influenced only by adult adiposity.

Data from robust longitudinal cohort studies suggest

that there is no strong relationship between breastfeeding

and the risk of coronary heart disease in adulthood (Mar-

tin et al., 2004; Rich-Edwards et al., 2004). In the Caer-

philly study of more than 2500 middle-aged men, Martin

et al. (2005) reported that breastfeeding was associated

with an increased risk of coronary heart disease mortality.

This was not coinsidered to be causal because there was

no relationship between mortality and the duration of

breastfeeding. Although mortality from heart disease is

not explained by feeding in infancy, there are weak but

significant associations between breastfeeding and risk

factors for heart disease. Adults who were breastfed have

lower blood pressure and lower total cholesterol than

those who were formula fed (Owen et al., 2002, 2003).

The systematic review of Arenz et al. (2004) suggested

that breastfeeding was protective against obesity in child-

hood, with a longer duration of breastfeeding having a

greater effect. A further review by Owen et al. (2005),

however, concluded that the protective effect was likely

to be heavily confounded and did not persist into

adulthood.

Disease risk across the lifespan

The most robust research linking early-life nutrition to

disease in adulthood demonstrates associations between

diet during pregnancy and the risk of cardiovascular dis-

ease, the metabolic syndrome and type-2 diabetes. These

are conditions that develop with ageing, typically mani-

festing in the fifth decade of life. The determinants of risk

at any stage of life are not simple interactions of the indi-

vidual with his/her environment at that particular point

in time. They are in fact the products of cumulative

exposures across the whole lifespan. The environment

encountered at each stage of life, from the periconceptual

period through to senescence, modifies the individual

response to nutrients and other challenges at successive

stages.

Primarily, the risk of most noncommunicable disease is

determined by genetic factors, with numerous single nucle-

otide polymorphisms (SNPs) accounting for significant

risk of coronary heart disease, obesity, type-2 diabetes

and cancer (Norheim et al., 2012). For example, the

C677T polymorphism of methyl-tetrahydrofolate reductase

5ª 2014 The British Dietetic Association Ltd.

S. C. Langley-Evans Early life – later disease

(MTHFR) is associated with the risk of cardiovascular dis-

ease (McNulty et al., 2012) and colorectal cancer (Sohn

et al., 2009) and the apo E4 variant of apolipoprotein E is

associated with atherosclerosis and Alzheimer’s disease

(Kofler et al., 2012; Hauser & Ryan, 2013). These gene

variants rarely provide a simple predisposition to disease.

This is largely because most disease states are not mono-

genic in origin, as well as there being a degree of gene–
environment or gene–nutrient interactions in the aetiology
of disease. Again, taking the C677T polymorphism of

MTHFR, it is clear that, with an adequate folate status, any

association of the TT variant with cardiovascular disease is

removed and that, for colorectal cancer, a positive folate

balance decreases risk with respect to the TT genotype

(Homocysteine Studies Collaboration, 2002; Kim et al.,

2012). Abarin et al. (2012) reported that, among girls car-

rying a SNP of FTO, which is normally associated with

higher BMI in adolescence, exclusive breastfeeding negated

the effect of the high-risk allele.

Throughout life, the pathways that lead from any given

genetic predisposition will be modified by both nutrition-

related and non-nutritional factors. The effects of multi-

ple protective or harmful SNPs are also modified by their

interactions with each other and by epigenetic factors that

ultimately control the expression of these ‘disease’ genes;

for example, silencing their expression through DNA

methylation (Jaenisch & Bird, 2003). At any given life

stage, the expression of the genotype is dependent upon

nutritional-signals that play a regulatory role. At the epi-

genetic level, this essentially comprises the B vitamins,

although nutritional status also influences gene expression

via transcription factors such as the peroxisome prolifera-

tor activated receptors (PPARs) or nuclear receptors.

Although nutritional exposures at all stages of life can

modify the disease pathway, the fact that early-life pro-

gramming can alter tissue function and responsiveness to

environmental cues means that nutritional exposures

occurring early in life are able to determine how an indi-

vidual will respond to nutritional signals that come later

in life (Fig. 1). To some extent, this is demonstrated by

some of the epidemiology that describes the association

between foetal growth and adult disease. Studies by Phil-

lips and colleagues showed that, although insulin resis-

tance was greater in 50-year-olds who had been relatively

thin at birth, the influence of this marker of early growth

was greater in individuals who were overweight or obese

in adulthood (Phillips et al., 1994). Similarly, the studies

of the Helsinki cohort showed that women who devel-

oped coronary heart disease had been born small but had

gained weight and increased BMI more rapidly in child-

hood (Forsen et al., 1999). Overall, their increased disease

risk was the product of cumulative nutritional factors at

different life stages.

Underpinning all of the interactions between nutri-

tional or non-nutritional exposures across the lifespan is

the influence of genotype upon disease risk. A body of

evidence favours the concept that nutritional program-

ming provides a layer of risk-modification between the

genotype and later lifestyle behaviours (Fig. 1). A range

of studies have reported that birthweight modulates the

normally observed relationships between specific gene

polymorphisms and disease. The PP variant of the

Pro12Ala SNP of the PPAR-gamma2 gene is associated

with an increased risk of type-2 diabetes. Eriksson et al.

(2002) reported that this association was present only in

individuals who had been of lower weight at birth, show-

ing that an interaction exists between programming influ-

ences and the genotype. This may be regarded in two

ways, with the inferences that programming only occurs

in individuals with a susceptible genotype (i.e. because

birthweight did not predict diabetes in individuals with-

out the PP variant) or that the effect of genotype is only

expressed in individuals subject to adverse programming,

with both being equally valid. de Rooij et al. (2006b) fol-

lowed up individuals from the Dutch Hunger Winter

cohort and found that the effects of the Pro12Ala SNP on

glucose homeostasis varied with the timing of exposure

to famine in utero. However, in contrast to the work of

Eriksson et al. (2002), it was the Ala variant that

increased the risk of type-2 diabetes, although only in

those exposed to famine during mid-gestation.

There are other examples of interactions between early

life factors and genotype. The K121Q SNP of plasma cell

glycoprotein 1 is implicated in development of type-2 dia-

betes, with the Q allele increasing insulin resistance. In the

study by Kubaszek et al. (2004), 121Q increased the risk of

hypertension, type-2 diabetes and insulin resistance,

although only in adults who had been of lower weight at

birth. Lips et al. (2007) followed up individuals from the

Hertfordshire cohort to examine the relationship between

early growth, genotype and bone health. Their study found

that, among women, the 11 genotype of the calcium-sens-

ing receptor CASRV3 polymorphism was associated with

higher lumbar spine bone mineral density within the low-

est birthweight tertile. The opposite was observed among

individuals in the highest birthweight tertile.

Given that the risk of developing cardiovascular disease

or the metabolic syndrome in adulthood is determined by

factors interacting across the lifespan, including powerful

effects of genotype and dietary exposures at all stages of

life, the fact that it is possible to detect any influence of

foetal growth-related factors at all is remarkable. The per-

sistence of early-life events as influences upon the

response to nutritional challenges in adulthood is a testa-

ment to the likely strength of early-life programming

effects upon the development of organs and systems.

6 ª 2014 The British Dietetic Association Ltd.

Early life – later disease S. C. Langley-Evans

Transgenerational effects of nutrition in
pregnancy

Current thinking in the developmental programming area

is that disease arises as a result of a mismatch between

the prenatal and postnatal environment. This is supported

by evidence demonstrating that rapid catch-up growth

following prenatal growth restriction is the strongest pre-

dictor of the metabolic syndrome. In populations under-

going economic and nutritional transition from poor to

relatively affluent status (e.g. India, China, South Africa),

an explosion of obesity, type-2 diabetes and cardiovascu-

lar disease is expected as a result of such a mismatch.

Although rapid improvements in maternal nutrition in

such countries may be expected to lessen the importance

of nutritional programming as a contributor to the over-

all disease burden, it is argued that transgenerational

effects may occur, whereby the consequences of deficits in

maternal nutrition in pregnancy are ultimately transmit-

ted to grandchildren. This means that, across the globe,

nutritional/economic transition may represent a sharp

decline in malnutrition-related disease, to be followed by

half a century of unavoidable metabolic disease.

Pembrey (1996) proposed that an transgenerational

feed-forward control loop exists, linking the growth and

health of an individual with the nutrition of their grand-

parents. This form of control would be likely to involve

some genomic imprinting of genes, which are then passed

on to subsequent generations. The outcome of such

imprinting would be very long-term health consequences

for populations that are exposed to either undernutrition

or over-nutrition at some stage in their history. The com-

plexity of the epidemiological studies that would be nec-

essary to investigate transgenerational programming in

human populations largely precludes such work.

Studies of individuals exposed to the Dutch famine

indicate that undernutrition of women during pregnancy

influenced the nutrition of their daughters and subse-

quently had an impact upon the birthweight of their

grandchildren. Veenendaal et al. (2013) reported that the

grandchildren of women who were pregnant during the

famine had greater neonatal adiposity and poor health in

later life. Women who were exposed to famine in utero

were themselves more likely to give birth to low birth

weight children (Lumey, 1992), which suggests a grand-

maternal influence upon foetal growth and development.

Health Disease

Genome

Epigenome

Nutritional
environment

Non-dietary
exposures

Smoking

Social class

Infection

Stress

In utero

Infancy

Childhood

Adult

Ef
fe

ct
s

ar
e

cu
m

u
la

ti
ve

Effects are interactive

Figure 1 Disease risk is the product of cumulative risk factors across the lifecourse. Primarily, the risk of most noncommunicable disease is

determined by genetic factors, with numerous polymorphisms accounting for significant risk of coronary heart disease, obesity, type-2 diabetes

and cancer. The effects of protective or harmful polymorphisms may be modified by their interactions with each other and epigenetic factors that

control the expression of these ‘disease’ genes. Throughout life, the pathways which lead from any given genetic predisposition will be modified

by non-nutritional factors. Nutritional exposures at all stages of life also modify the disease pathway. Exposures that occur early in life are able,

through programming, to determine how an individual will respond to nutritional signals in later life.

7ª 2014 The British Dietetic Association Ltd.

S. C. Langley-Evans Early life – later disease

Transgenerational effects are not necessarily the product

of deficits only in maternal nutrition. Bygren et al. (2001)

have reported that the grandchildren of men who were

overfed in the prepubertal growth period had a signifi-

cantly shorter lifespan. Davis et al. (2008) reported that

childhood BMI correlated strongly with grandparental

BMI, irrespective of parental BMI. This has been inter-

preted as the transgenerational transmission of obesity,

although BMI also reflects lean mass and any relation-

ships could reflect family behaviours as much as a biolog-

ical transmission.

Transgenerational programming, the physiological

response of offspring across two or more generations, has

been previously noted in studies of animals. Beach &

Hurley (1982)assessed immune function in the offspring

of mice fed a zinc deficient diet in pregnancy. Immuno-

suppression was severe and persisted into a third genera-

tion following the initial nutritional insult before

resolving. More recently, Drake et al. (2005) have

reported that the treatment of pregnant rats with dexa-

methasone in pregnancy, an intervention known to retard

foetal growth and programme hypertension and glucose

intolerance in the offspring, produces effects on glucose

homeostasis that persist for two generations. Maternal

high fat feeding elicited a sex-specific insulin resistant

phenotype in second- and third-generation mice offspring

(Zambrano et al., 2005).

At the present time, it is likely that the observed pro-

gramming of physiology, metabolism, health and disease

is in part a product of the maternal environment signal-

ling to the foetal epigenome. This is an issue of major sig-

nificance because epigenetic marks, although sensitive to

environment and ageing, may be stably inherited by any

future offspring. This allows potential for a nutritional

insult in one pregnancy to have effects over several genera-

tions. Feeding a low-protein diet to rats during pregnancy

programmed blood pressure and nephron number over

two generations. Importantly, transmission occurred via

the male as well as the female line, which is strongly sug-

gestive of an influence of the epigenome (Harrison &

Langley-Evans, 2009). This opens up the possibility that

paternal, as well as maternal, nutritional status may be an

important determinant of disease risk. This would radi-

cally change the way that we think about optimising nutri-

tional status in the peri-conceptual period.

Mechanistic considerations

The evidence to link early-life nutrition (in particular

maternal nutritional status in pregnancy) with disease in

later life is overwhelming. The challenge is to utilise this

information for the development of novel approaches to

public health, or other interventions, to prevent and treat

disease. To be able to even put in place simple measures

such as advice for optimising nutrition in the peri-con-

ceptual period requires an understanding of the mecha-

nisms that explain how nutritional programming occurs.

The animal experiments suggesting that even relatively

mild perturbations of dietary quality during can bring

about altered function in the ageing offspring are a cause

for caution. Any ill-considered intervention in humans

could have far-reaching, transgenerational consequences.

As described above, the most likely mechanism that

allows a possibly transient nutritional insult, acting during

early life, to exert a lasting effect upon physiological func-

tion, decades later, involves changes to the structure of

organs and tissues during their phases of growth, differen-

tiation and maturation (Fig. 2). This tissue remodelling is

typified by observations of the effects of undernutrition

and growth restraint upon the kidney in both animals and

humans. Nephrons are the functional units of the kidney,

being the sites of blood filtration and urine formation. In

the human kidney, nephron number is determined before

birth and is hypervariable between individuals, ranging

between 300 000 and 10 00 000 nephrons per kidney

(Mackenzie & Brenner, 1995). Nephron number is an

important marker of the likelihood of chronic kidney dis-

ease because nephrons are progressively lost with ageing.

It is argued that a lower starting number is associated with

an earlier loss of functional capacity.

Autopsy studies strongly suggest an association between

nephron number and birthweight (Hughson et al., 2003)

and investigations of Australian aboriginal populations

suggest that poverty is a driver of lower nephron number

and disease (Singh & Hoy, 2004). Animal studies confirm

that nephron number is extremely sensitive to maternal

undernutrition and can be constrained by food restric-

tion, protein restriction or iron deficiency during nephro-

genesis (Langley-Evans et al., 1999; Swali et al., 2011).

There is also evidence of remodelling being associated

with maternal nutritional insults in the brain (Plagemann

et al., 2000) and pancreas (Snoeck et al., 1990) but only

in animals.

The conditions that appear to be programmed in utero

are exclusively diseases that have their onset in middle-

age or the later years. This suggests that key features of

tissue remodelling are the depletion of functional reserve,

as illustrated in the case of the kidney above, and a sus-

ceptibility to more rapid loss of functional units. There

are numerous examples in animal studies that suggest a

greater susceptibility to oxidative injury and senescence in

the offspring of mothers that were undernourished in

pregnancy (Jennings et al., 2000; Langley-Evans & Sculley,

2005, 2006; Tarry-Adkins et al., 2013).

Remodelling of tissues is not a simple response to a

lack of substrate, or endocrine signals from mother to

8 ª 2014 The British Dietetic Association Ltd.

Early life – later disease S. C. Langley-Evans

foetus indicating a sub-optimal environment. The process

inevitably involves changes in these signals, eliciting

changes in gene expression that impact upon tissue devel-

opment. The programming literature now contains innu-

merable reports of long-term gene expression changes in

response to an early-life insult; for example, altered

expression of the genes involved in hepatic glucose han-

dling following intrauterine exposure to maternal over-

feeding in the rat (Erhuma et al., 2007; Bayol et al.,

2010). In humans, there are fewer such reports and, in

most cases, it is impossible to ascribe causal relationships

between gene expression and outcome. For example, D�ıaz

et al. (2013) reported that placental expression of pre-adi-

pocyte factor 1 was inversely correlated with infant fat

mass at age 1 year. Similarly Lewis et al. (2012) reported

that placental expression of Pleckstrin homology-like

domain family A2 was related to bone mass in 4-year-old

children. These studies provide potentially useful predic-

tive biomarkers for disease but do not cast significant

light on how maternal nutritional status elicits program-

ming responses. The state of research in humans in this

context is far less advanced and convincing than the envi-

ronment–polymorphism interactions described above.
Although of interest in terms of exploring how longer-

term disease states are driven by early-life nutrition, these

reports do not provide a strong basis for determining the

initial drivers of programming. It is likely that, in the face

of intrauterine nutrient excess or deficit, a number of

changes occur in gene expression that are very short-term

but sufficient to perturb tissue development irreversibly.

There is emerging evidence to suggest that genes control-

ling the cell cycle and DNA replication (hence the prolif-

eration phases of organ development) may be particularly

susceptible to influences of maternal undernutrition

(Fig. 2) (Swali et al., 2011, 2012).

Although other potential mechanisms cannot be ignored,

influences of epigenetic factors (e.g. DNA methylation and

histone modifications) are considered to play an important

role in developmental programming of disease (Burdge

et al., 2007). DNA methylation provides an important

mechanism for gene silencing, whereas modifications of

histone proteins can either allow gene transcription or

silence expression (Jaenisch & Bird, 2003). Environmental

challenges in early life, including under- or over-nutrition,

are likely to affect DNA methylation significantly because,

during the very early phases of embryo development, DNA

methylation is extensively reprogrammed. Differences in

methylation were found at the IGF2 locus between individ-

uals exposed to the Dutch famine and their unexposed sib-

lings (Heijmans et al., 2008). A rapidly increasing body of

evidence from both animal and human studies show that

the epigenome is sensitive to nutrition during foetal and

adult life (Sharif et al., 2007; Sinclair et al., 2007; Lillycrop

et al., 2008; Bogdarina et al., 2010).

Effects of early nutrition upon the epigenome are likely

to have a number of significant effects upon later health

and wellbeing. First, epigenetic marks control gene

expression and this means that even transient nutritional

Mature tissue with functional units Mature tissue with fewer functional units

Smaller mature tissue with fewer
functional units

P
ro

lif
er

at
io

n
D

if
fe

re
n

ti
at

io
n

Insult during cell proliferation
limits tissue growth and
functional capacity

Insult during cell
differentiation limits functional
capacity of the mature tissue

Figure 2 The basis of tissue remodelling. The development of tissues depends on an ordered pattern of cell proliferation from early progenitor

cells, with later differentiation of the tissue precursors to form the specialised cell types and functional units responsible for tissue function. Tissue

development is therefore associated with waves of cell division, apoptosis and differentiation to achieve the mature structure. Remodelling of

tissues will occur if environmental factors, including signals of less than optimal nutrition, impact upon the proliferation and differentiation

phases, resulting in tissues that are smaller (or of normal size) but with fewer functional structures and hence limited capacity to withstand age-

related degeneration.

9ª 2014 The British Dietetic Association Ltd.

S. C. Langley-Evans Early life – later disease

exposures could leave an epigenetic memory within cells,

which will then govern how genes are expressed in

response to further environmental cues. Second, the state

of the epigenome is not entirely stable throughout life. As

epigenetic drift occurs, patterns of gene expression within

tissues can change and this has been linked to certain

cancers and Alzheimer’s disease (Fraga & Esteller, 2007;

Wang et al., 2008). The nature of age-related drift may be

partly mediated by early-life events and the state of the

epigenome in infancy. Finally, it is assumed that changes

to the epigenome may be heritable and this could explain

why programming effects of nutrition can persist over

several generations and be passed down the male line.

Conclusions

Although heavily reliant on findings from retrospective

cohort studies and experiments with animals, there is an

overwhelming body of evidence to demonstrate that

nutritional influences encountered during early life have a

lasting impact upon health and well-being. The potential

impact of these findings for public health is huge because

pregnancy and early infancy represent windows of oppor-

tunity during which parents are most willing to adopt

lifestyle changes that could have health implications

across multiple generations. There is a need for greater

understanding of the processes involved in early-life pro-

gramming to refine advice given to women who are preg-

nant or planning a pregnancy and mothers with young

children. The recognition that lifestyle factors impacting

upon health are operant from the moment of conception

has profound implications for the way in which we

regard the aetiology of disease and should be a factor

incorporated into any future use of genomic or epige-

nomic information as a basis for personalised nutritional

advice.

Conflict of interests, source of funding and
authorship

The author declares he has no conflicts of interest.

No funding is declared.

The author critically reviewed the manuscript and

approved the final version submitted for publication.

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Early life – later disease S. C. Langley-Evans

COMMONWEALTH OF AUSTRALIA

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Course of Study:
(MHNS6004) Physical Health Care in Mental Health

Title of work:
European psychiatric/mental health nursing in the 21st Century; a
person-centred evidence-based approach (2018)

Section:
The withdrawn or recalcitrant client pp. 1–15

Author/editor of work:
Santos, José Carlos; Cutcliffe, John R.

Author of section:
R Lakeman

Name of Publisher:
Springer

The withdrawn or recalcitrant client

By Richard Lakeman DNSci

This is an early draft and adaptation of Lakeman, R. (in press, 2018). The withdrawn or
recalcitrant client. In Santos, J. & Cutcliffe, J.R. (Eds). European Psychiatric / Mental Health
Nursing in the 21st Century. London: Springer

Reprinted for Southern Cross University with permission from the author – In this paper the term
‘health professional’ is used instead of nurse

There are few groups who raise the anxiety of health professionals more than those

who don’t improve as expected, who don’t follow recommendations or who fail to

engage with them in a respectful or cooperative way. Main (1957, p. 129) suggested

that the sufferer who frustrates a keen therapist by failing to improve is always in

danger of meeting primitive human behaviour disguised as treatment. He observed

that nurses would only give a sedative when they were unable to stand the patient’s

problems without anxiety, impatience, guilt, anger or despair; whatever their

justification for the treatment. Today the reluctant, recalcitrant or a-motivated service

user is at risk of coercion and increasingly desperate and frequently non-evidence

based treatment measures. An armoury of long acting ‘depot’ medications, other

dangerous medications and ECT may be imposed on individuals who fail to improve

at the pace expected of them, often perpetuating a cycle of further resistance and

reluctance to engage with the health care system.

Assessment and the seeds of resistance
People who fail to follow health care advice, who are seen to lack motivation or who

actively resist caregivers are often labelled as resistant or reluctant. For the most

part, resistance and social withdrawal are best understood as functions of the

dynamics between people. People tend to resist what they fear, what they don’t

want, and what is imposed on them. Yalom (1992, p.220) tentatively proposes

“perhaps symptoms are messengers of meaning and will vanish only when their

message is comprehended”. Health professionals need to consider what symptoms

mean. As a first example, problems with drive and motivation may be part of

recognised disorders but this does not render those symptom meaningless; often

people diagnosed and treated for mental illness have quite understandable reasons

for resisting the well-meaning ministrations of treatment teams. It is worth

familiarising yourself with some of the disorders that are thought to impact on

motivation and drive.

Withdrawal and amotivation as symptoms
Social withdrawal and amotivation have long been considered part of a range of

disorders and syndromes (see table 1). In neurology, amotivation falls on a

continuum from apathy or indifference at one end, aboulia or a lack of will or initiative

in the middle and at the extreme pole, akinetic mutism (an absence of movement

and speech). Treating the primary cause where possible, optimising the person’s

physical well-being, reducing medications that aggravate amotivational symptoms,

understanding and remediating cognitive deficits and creating an enriched positive

environment are important treatment considerations. At the extreme end of the

continuum pharmacological treatments may be introduced as part of treatment e.g.

activating antidepressants, dopamine agonists and stimulants, in addition to

specialist neuropsychological treatments (Marin and Wilkosz, 2006).

Neurological disorders

 Frontal lobe

o Frontotemporal dementia

o Anterior cerebral artery infarction

o Ruptured anterior communicating artery

o Tumour

o Hydrocephalus

o Trauma

 Right hemisphere

o Right middle cerebral artery infarction

 Cerebral white matter

o Ischemic white matter disease

o Multiple sclerosis

o Binswanger’s encephalopathy

o HIV

 Basal ganglia

o Parkinson’s disease

o Huntington’s disease

o Progressive supra-nuclear palsy

o Carbon monoxide poisoning

 Diencephalon

o Degeneration or infarction of thalamus

o Wernicke-Korsakoff disease

 Amygdala

o Klüver-Bucy syndrome

 Multifocal disease

o Alzheimer’s disease (apathy may be mediated by damage to prefrontal

cortex, parietal cortex, amygdala)

Medical disorders

 Apathetic hyperthyroidism

 Hypothyroidism

 Pseudohypoparathyroidism

 Lyme disease

 Wilson’s disease

 Chronic fatigue syndrome

 Testosterone deficiency

 Debilitating medical conditions (e.g., malignancy, renal or heart failure)

Drug-induced conditions

 Neuroleptics, especially typical neuroleptics

 Selective serotonin reuptake inhibitors

 Marijuana dependence

 Stimulant (cocaine, amphetamine) withdrawal

 Cocaine-related subcortical strokes

Socioenvironmental effects (lack of reward, loss of incentive, lack of perceived control)

 Role change

 Institutionalism

Environmental effects

 Motor vehicle accident

 Falls (particularly among elderly)

 Sports-related injury

 Combat-related injury

Table 1: Conditions associated with apathy, abulia, and akinetic mutism.

Reproduced from Marin and Wilkosz (2005, p. 382).

In psychiatry degrees of amotivation may be part of common syndromes such as

depression and psychosis, and may be exacerbated by common pharmacological

treatments (particularly the major tranquilisers). Bleuler who first coined the term

schizophrenia suggested that the most prominent symptoms could be categorised as

the “4 As” i.e. problems with Associations between thoughts, Ambivalence, Affect

and Autism. Although debates continue about what were the more important

symptoms of Bleuler’s definition and in particular the importance of dissociation and

splitting (see Moskowitz and Heim, 2011), Bleuler recognised that some people with

this complex syndrome of heterogeneous symptoms withdraw from the world and

become preoccupied with their inner experience (autism). More recently distinctions

have been made between negative symptoms (an absence or diminishment of

functioning), positive symptoms (reflecting an excess) and cognitive symptoms

(Marneros, Andreasen and Tsuang, 2012). Positive symptoms (which include

delusions and hallucinations) are generally considered more amenable to treatment,

and social withdrawal and cognitive problems are generally considered to be more

disabling and resistant to pharmacological treatments. Avolition is the term used to

describe a general decrease in the motivation to initiate and perform self-directed

purposeful activities which is sometimes observed in people who may be diagnosed

with schizophrenia.

Carpenter, Heinrichs and Alphs (1985) note the importance of distinguishing

between what they call “secondary” negative symptoms from those that appear

persistent. For example they note that some negative symptoms are associated with

dramatic exacerbations of psychosis during which time people tend to try and

dampen down external stimuli to prevent being overwhelmed. Negative symptoms

may also be secondary to the use of neuroleptic drugs (which traditionally have been

very tranquilising and induce states similar to Parkinson’s disease). Negative

symptoms may also be a response to unstimulating environments (a feature of

impoverished community settings as well as traditional total institutions). More

recently it has been noted that negative symptoms may not cluster together so neatly

and unsurprisingly are inconsistently responsive to pharmacotherapy (Erhart, Marder

and Carpenter, 2006). Regardless of cause however, apathy and amotivation appear

to be the most important predictor of poor functional outcomes in research involving

people diagnosed with schizophrenia (Fervaha et al, 2013).

What may be considered a contentious part of one syndrome may sometimes be

considered an essential feature of others. Anhedonia for example is the loss of

enjoyment in activities previously found enjoyable. This concept is central to notions

of depression, although depression too is an amorphous syndrome with multiple

possible causes. People diagnosed with schizophrenia often report anhedonia, but

they have been found to enjoy activities “in the moment” as much as people without

this diagnosis (Strauss, 2013). Where they may differ is in the anticipation of

pleasurable experiences (if people don’t anticipate that an activity is likely to be

pleasurable, their motivation to do it is reduced). There is some evidence that

negative thoughts about one’s ability to successfully perform goal-directed behaviour

can prevent behaviour initiation, engagement and anticipatory pleasure (Campellone

et al, 2016). Beck et al (1979) famously observed that depression can be

characterised as holding negative beliefs about oneself, the world and the future

(known as the cognitive triad of depression). From this model the remedy is to assist

the person to adopt more reasonable, realistic thoughts about themselves and the

world, and reduce ruminations and thinking which are predictive of bad outcomes.

Finally fatigue or tiredness, chronic pain and indeed chronic stress can sap people’s

drive and motivation and can contribute to depression and hopelessness.

Resistance
Resistance connotes a more active stance on the part of people to not move forward

or do what is needed (at least as perceived by therapists). Traditionally resistance

was understood as an effort to repress anxiety-provoking insights and memories,

and later was ascribed to a reluctance to accept the interpretation of the therapist. In

other words resistance is an attempt to control anxiety and it is more or less

functional, and necessary for mental health. Resistance can be a function of people’s

stage of development. For example it is a natural part of adolescence to resist the

direction and control of adults and to identify more strongly with peer groups. This

pushing against parental or adult authority assists in the process of identity formation

and is arguably essential to enable the young person to leave the comfort of home.

Resistance however can be reflected in distorted thinking, a failure to see the best

way forwards, an unwillingness to change and sometimes in overt opposition to the

health professional or helping process. Generally speaking when engaging with a

person in a therapeutic conversation, topics that appear to engender resistance and

shifts in affect should be carefully noted and attended to. Sometimes the

communication can be quite overt – “Don’t go there”, the subtext being that this topic

is potentially too anxiety-provoking right now. The health professional may use this

moment to make an empathic comment e.g. they can see or sense that this topic

causes some discomfort and ask the person whether they would prefer to discuss it

at a later time.

The notion of resistance as a feature of the psychology of the individual (whether

unconscious or an actively chosen behaviour) can be useful. However, this view can

obscure the more commonly encountered reasons for resistance, which are more to

do with the dynamics or relationships between people. A view which considers

interpersonal dynamics invites the health professional or therapist to consider how

their own behaviour may influence the behaviour of the other/s (see for example

table 2). It can be empowering to “reframe” resistance as a health professional or

therapist issue: it is widely recognised that one cannot change clients, whereas one

can change how one interacts with them.

 Resistance occurs when the health professional fails to recognise that all

clients are ambivalent about change.

 Resistance sometimes occurs when the health professional wants more for

clients than clients want for themselves. In this sense, resistance can be a

values clash between the health professional and the clients in which the

health professional’s values are overly present.

 Resistance occurs when the health professional’s goals clash with the client’s.

 Resistance is a result of the health professional being too intent on his / her

own agenda.

 Resistance occurs when the health professional or therapist is going too fast.

 Resistance occurs when the health professional does not know what to do.

 Resistance occurs when the health professional asks the wrong question or

makes a poorly worded or unacceptable statement which to the client is

unfathomable and unrealisable.

 Resistance is anything the client does that makes the health professional

uncomfortable.

 Resistance occurs when the health professional fails to cooperate with the

client.

 Whenever you feel that your client is being resistant, you must also be

resisting your client’s position. From this perspective you are being resistant.

When considered in this context, resistance is a nursing problem.

Table 2: Resistance as a health professional problem. Adapted with permission from

Reproduced from Mitchell (2012, p. 8).

Trauma and learned helplessness
Childhood abuse, neglect and trauma have been found to play causal roles in

depression, anxiety disorders, post-traumatic stress disorder, eating disorders,

substance abuse, personality disorders, dissociative disorders and psychosis (Read,

Mosher and Bentall, 2004). The greater the number of adverse childhood

experiences a person is exposed to, the more likely they are to engage in risk taking

behaviour, have poor health maintenance behaviours, become ill from a range of

often preventable diseases and die prematurely (Felitti et al, 1998). Not surprisingly

people exposed to trauma early in their lives, particularly when they do not

experience secure, warm and consistent attachment to a caregiver, subsequently

have a great deal of difficulty trusting people and sustaining relationships with others

(Pearlman and Courtois, 2005). The relationships people have with health

professionals may also be tenuous – why should people trust health professionals or

other relative strangers when the person’s experience of their primary care-givers or

others in authority has been a failure to protect, inconsistency and sometimes

abuse?

The person’s experience of health and welfare systems may also exacerbate a

sense of powerlessness and mistrust, and a feeling that relationships with helpers

are shallow, coercive and uncaring. Watkins (2001, p.133) suggests that it is not

surprising that people with “severe mental health problems” are unwilling to engage

with mental health services, given there is sometimes a “legacy of distrust” founded

on dealings with statutory agencies, traumatising experiences of past

hospitalisations, enforced treatment and experiences of discrimination and racism in

their past dealings with health professionals. The experience of having to tell a story

multiple times or having to see multiple health professionals before engaging with a

primary therapist can be psycho-noxious for someone with attachment-trauma.

Health professionals need to be alert to the impact of early attachment experiences,

trauma and people’s experience of engagement with the health care system and

anticipate that many people will not conform to a compliant or acquiescent patient

role.

Health professionals may need to earn the trust of people they work with through

demonstrating unconditional positive regard (Rogers, 1957) and engaging in a

certain kind of respectful, “containing” relationship which individuals may not expect

or have experienced before. Indeed, purposefully doing the unexpected is a tool to

deal with resistance. As Mitchell (2012, p.37) notes, “… socially typical responses

are, by and large ineffective in creating therapeutic movement. Typical responses

beget typical reactions…”. Responding to hostility, blaming, anger or expressions of

hopelessness (which might ordinarily elicit rejection or defensive behaviour) with

compassion, curiosity, empathy and hope may not only help build an alliance, they

may also be inherently therapeutic.

Early research examining what happens to both animals and humans when exposed

to repeated traumatic events over which they have little control elucidated the

concept of ‘learned helplessness’ (Mikulincer, 2013). Over time people in essence

give up trying to change their situation or resist what they perceive as being beyond

their control. They become apathetic and a-motivated. Resistance can be a highly

adaptive response to situations of abuse or injustice, yet people often don’t engage

in health affirming behaviour because they don’t perceive that it will make a

difference. This can in part explain highly institutionalised behaviour. The kind of

resistance often seen in response to coercive care might also be considered a

natural, if not healthy response.

The Coerced or Involuntary Client
In many parts of Europe and the Western World a large proportion of people who

use tertiary mental health services experience coercion to receive assessment or

treatment at some point in their journey. Police (sometimes in conjunction with

mental health co-responders), ambulance, paramedics and emergency services staff

frequently compel people to be assessed by mental health professionals. All

Western countries have legislation to enable such compulsory assessment and

treatment. People who have committed crimes may also be compelled to submit to

therapy including those who have committed sexual offences or who have been

identified as having problems with illicit drugs or alcohol. Not surprisingly people tend

to resist (often quite actively through anger and sometimes violence) the deprivation

of their liberty and treatment or care imposed on them.

Regardless of their legal status people may perceive that they have little choice in

their treatment or care, or about important decisions in their lives. The perception of

coercion and perception of choice are pivotal to the dynamics that may play out

between the individual and health providers. Some people who are legally required

to engage in treatment may have no perception of coercion at all, and others may

welcome help and treatment regardless of perceived legal pressure. Others may not

be subject to any legal order but fear that if they don’t comply they will be compelled

to go to hospital, lose entitlements (e.g. housing or pensions) or lose valued support.

People’s fears and perceptions around coercion need to be explored.

People may come to accept the need for coercion, particularly when they have been

engaged in dangerous behaviour but they often assert that coercive processes could

have been undertaken in a more considerate manner (Sibitz et al, 2011). In many

instances health professionals have little choice but to work with people compelled to

be involved with their service and they may be required to enforce treatment plans in

which they have little personal investment and with which they don’t agree. This

unique dynamic has rarely been explored. A useful strategy to build relationships

and to minimise conflict around coercion is for health professionals to acknowledge

this shared position with the client, being honest about what aspects of care or

treatment are non-negotiable and being clear about what choices are available.

Honesty, transparency and maximising choice are critical ingredients of recovery

orientated practices (Lakeman, 2010) and programmes such as Safewards aimed at

reducing conflict and containment measures (Bowers et al, 2015).

Motivation and readiness for change
People may appear resistant or fail to adhere to treatment plans because they are

not ready to change; or more particularly, health care providers are not in step with

their stage of readiness. Motivational interviewing (MI) encompasses a range of

theories about change; it articulates ways to identify readiness and practices to

assist in shifting people towards making positive changes in their life. It is based on

an understanding that people are often ambivalent about change and may present

with conflicting emotions and thoughts about taking a particular course of action.

Ambivalent people met with highly directive or coercive demands for change from

health professionals often ‘dig in’ and resist change even further. Consider for

example, smoking cessation – most people are aware of the potential dangers of

smoking yet rarely does a health professional telling them they ‘should’ stop lead to a

commitment to changing behaviour. Resistance always arises when there is a

mismatch between the health professional’s or therapist’s aspirations for behavioural

change (ABCs) and the person’s – most commonly when the health professional’s

ABCs are high for change in particular area and the person’s are low (e.g. the health

professional believes the person should exercise more and eat less junk food,

whereas the person does not perceive this as important). The health professional

may ineffectually attempt to manipulate, persuade or cajole the person to change.

Conversely the person may have a high ABC on one issue where the health

professional’s is low (e.g. the person believes they need a medical intervention to

reduce weight whereas the health professional believes they should make lifestyle

changes). Such a clash of agendas needs to be worked through to prevent an

unproductive struggle and emphasise the importance of negotiating mutually

agreeable goals to progress.

People vary in their desire for change, perceived ability or confidence to make

changes, specific reasons for making changes, and perceptions of need for change

(consider the acronym DARN). As illustrated in table 3, the health professional can

ask questions and listen for talk about change. Note that individuals will vary in the

intensity of their desire, their confidence, how pressing their reasons and how

compelling their perceived need for change. They may for example desire something

greatly but have a low confidence in their capability to achieve it. Their ambivalence

may be expressed in statements such as “I really want to give up smoking [desire]

but I really don’t think I can [ability]”. Additionally, expressions of commitment to

change suggest a greater likelihood of actually making change, and taking actual

steps towards change may suggest that a person is ready to make change.

Change Talk Statements about… Questions to elicit change talk

Desire Preference for change:
“I want to…”
“I would like to…”
“I wish…”

“Why would you want / like / wish /
hope.… ?”
How important is this to you?

Ability Capability:
“I could…”
“I can…”
“I might be able to…”

“How would you do it, if you decided to?”
“What are you able to do?”
“What could you do?

Reasons Arguments for change:
“I would feel better if…”
“I would have more…
if…”

“What are your three best reasons for
…?”
“Why would you make this change?”
“What would be some benefits of
change?”

Need Feeling obliged to
change:
“I ought to…”
“I have to…”
“I should…”

“How important is it to you…?”
“How much do you need to…?”

Commitment The likelihood of
change:
“I am going to…”
“I will…”
“I intend to…”

“What do you think you will do?”
“What if anything do you intend to do?”

Taking Steps Action taken: “What have you done already?”
“What would be a first step for you”

“I actually went out
and…”
“I cut down…”

Table 3: Assessing motivation through listening and asking about change talk.

Source: Adapted from Rollnick et al (2008).

Responding to resistance and recalcitrant behaviour
Just as numerous theoretical lenses can be employed for understanding resistant or

difficult behaviour, so too many different approaches may considered in determining

how best to respond. Health professionals who work with people with complex needs

ought to develop and maintain a “tool box”/set of useful psychotherapeutic skills.

Education and supervised practice in solution focused and strengths based therapies

(See for example: Ungar, 2015), positive psychology and motivational interviewing

(See for example Rollnick et al, 2008 and DiClemente and Prochaska, 1998) will be

particularly useful. The following are a precis of some general principles to consider

when working with resistant clients.

Build an alliance

The capacity to work productively with someone using any set of skills depends a

great deal on the quality of the relationship that is formed between health

professional and person. Rogers (1957) famously observed that the necessary and

sufficient conditions for personality growth of clients in therapy were: congruence on

the part of the therapist, communication to the client of the therapist’s empathic

understanding, and unconditional positive regard. As has been noted, prior adverse

experience (of the patient, the health professional or both), conflicting goals and

resistant behaviour sometimes make it difficult to establish or sustain an ideal

relationship.

Trotter (2015) suggests that when working with involuntary clients (of all kinds) what

has been emphatically demonstrated to work are role clarification, reinforcing and

modelling pro-social values, collaborative problem solving, cognitive behavioural

strategies and providing a service in an integrated way. Developing the relationship,

through appropriate use of empathy, humour, the communication of optimism,

judicious use of self-disclosure, working with family and peers, and employing

principles of case management have all been found to be somewhat helpful.

Clarifying with the person what the health professional’s role is from the outset and

revisiting that periodically is helpful in building a working alliance. This is particularly

true when the health professional may have multiple roles in relation to the person.

The health professional needs to be clear with what services or tasks they may be

mandated to provide and which are negotiable.

Modelling unconditional positive regard, and maintaining a friendly, concerned and

professional countenance may be taken as a given. As important are modelling how

to contain anxiety and strong emotions, and to deal with inevitable ruptures that may

occur in the relationship. Sometimes service users may express overt hostility or

anger towards the health professional, be unable to regulate their emotions or

arouse fear and anxiety in caregivers. The health professional needs to learn to

contain these strong emotions in a similar way to that of a good-enough parent who

calmly soothes an infant experiencing distress. This skill of emotional containment

has recently been conceptualised as pivotal in the care and treatment of people with

personality disorders (Goodwin, 2005). It is now widely recognised that interpersonal

environments characterised by high expressed emotion (i.e. over involvement,

critical comments and hostility) contribute to a worsening of problematic behaviours

in a wide range of mental health presentations (van Audenhove and Van Humbeeck,

2003). Health professionals need to learn to moderate and contain their own

responses to distress and distressing behaviour (reduce expressed emotion) and

model how to solve problems.

Be motivational

Motivational interviewing involves some core skills that might be considered

universally good practice in the helping field e.g. Resisting the righting reflex,

Understanding the person’s motivation, Listening and Empowering (Rollnick et al,

2008). MI involves reaching agreement on a focus and setting an agenda, and

emphasises the “spirit” of the approach. Conversations exploring and building

motivation to change progress through exchanging information, asking useful

questions, listening reflectively and sometimes using structured approaches (e.g.

eliciting the pros and cons about a particular behaviour). Summarising progress,

returning to agenda setting, or considering the next step are part of the iterative

process.

People rarely benefit from being told that something is wrong with them, nor do they

respond well to being told what to do. A first principle in motivational interviewing is

“Resisting the righting reflex”. That is, to avoid correcting another’s course, giving

unsolicited advice or over-using direction. People have a natural tendency to resist

persuasion (no matter how well motivated). If the health professional or others argue

for change (e.g. “You ought to do…”) then the person is likely to argue against

change. Whilst there may be an occasional need to confront, inform or announce a

different viewpoint, these strategies ought to be used the least and undertaken with

great care and often with permission.

Health professionals will be well acquainted with communicating empathically (e.g.

“You feel… [identifying the correct emotion and intensity]… when or because…

[identifying accurately the trigger]”) (Egan, 2013) or using selective reflection to

enable deeper exploration about a topic of interest. A motivational form of reflection

involves selectively reflecting the change talk (illustrated in table 3) and / or the

person’s ambivalence. The goal (and natural tendency of the person) is for them to

then argue for change or a different behaviour.

Being motivational also means understanding what motivates and drives specific

individuals; understanding their values and aspirations, and whether they are

motivated primarily by intrinsic or extrinsic rewards. Where people may appear high

on desire but low on other aspects of motivation then the health professional may

need to negotiate the provision of incentives. A longstanding and robust principle of

behavioural psychology is that behaviour that is followed by positive consequences

is likely to be repeated. Providing incentives or rewards for meeting specific

behavioural goals (e.g., verified abstinence), has a strong evidence base in drug use

(Carroll and Onken, 2005) and increasingly direct incentives are proving to be useful

to secure adherence to many health treatments of importance to public health.

However, few things motivate individuals more than the praise, attention and

approval of peers and trusted people. Therefore, praise people often and

acknowledge their struggles and achievements.

Be ecological / solution focused

A tradition and tendency of health and welfare services has been the identification of

problems. Service users frequently develop or have reinforced a perception that they

are at fault and need fixing. Often however, the person’s problematic behaviour is a

response to contexts beyond their control. As Ungar (2015, p.66) notes “Individuals

are not to blame for the strategies they use to cope in contexts that deny them

choices”. An ecological approach to problems emphasises the development and

mobilisation of skills in navigation and negotiation (see table 4) to identify and

evaluate internal and external resources available to them and help people influence

which resources they receive, by whom, how, when and where. Emphasising the

idea of resourcing the person to deal with the world rather than fixing them goes a

long way to avoiding conflict and positions the health professional as an ally in

coping. Giving people something they want or need is a shortcut to building a

relationship. Indeed, whether or not people perceive they got something of value

from their first encounter with a health professional may well influence the trajectory

of the relationship from that time forward.

Being solution focused is in part a way of being as well as encompassing a set of

techniques. An elegant and respectful way to demonstrate being solution focused is

to judiciously attempt to reframe deficit and negative talk, statements about what

people don’t want into a desire for a solution, a more positive frame or a statement

about what people want.

e.g. “I really hate that doctor… he never listens to me” [person]

“You would feel warmer towards your doctor if you had more opportunities to be

heard” [health professional]

e.g. “I find it so hard to get out of bed right now” [person]

“You would like to have more energy in the mornings” [health professional]

The classic solution focused question which can elicit aspirations for positive goal

setting is the ‘miracle question’. Have the person imagine or anticipate at some point

in time in the future (the next day when they wake up, or in a year’s time) that their

problems are resolved (and they don’t need to know how it happened). Ask them to

describe how it would be and what they would be doing. A variation of this approach

can also be used with families or others in the network (Seikulla et al, 2006) – what

they imagine things might be like and how they might help people get there.

Clarify and set Meaningful Goals

People don’t tend to resist what they really want. Often people may want something

from the relationship but not always what is being offered. Early in the relationship it

is important to negotiate meaningful goals. Goal setting will proceed from an evolving

understanding of the person, their context and the resources available to them.

Where the individual’s goals appear to be discordant with the health professional or

the health team it is necessary to find some common ground. The aforementioned

miracle question can be helpful to identify areas to aspire to. It is important to explore

the person’s motivation to attain a particular goal. Goal setting involves a

commitment of one or more people to do something. As well as being specific,

meaningful, action-orientated, realistic and with a clear time frame (“SMART”) the

health professional may need to assist the person to determine who needs to do

what, and to identify motivational rewards or contingencies if the steps are not

intrinsically motivating in themselves.

Navigation Skills:

 Make resources available – Help the person identify internal and external

resources.

 Make resources accessible – Discuss how the person can access resources.

 Explore barriers to change – Discuss the barriers to change and what

resources are most likely to address which barriers.

 Build bridges to new services and supports – Discuss supports that are

available and build bridges to make new resources available and

accessible.

 Ask what is meaningful – Explore which resources are the most meaningful

given the person’s culture and context.

 Keep solutions as complex as the problems they solve – Explore solutions

that are as complex (multi-systemic) as the problems they address.

 Find allies – Explore possible allies who can help the client access resources

and put new ways of coping into practice.

 Ask whether coping strategies are adaptive or maladaptive – Explore the

solutions that the person is using to cope in challenging contexts and the

consequences of the choices the person is making.

 Explore the person’s level of motivation – Discuss with the person their level

of motivation to implement preferred solutions.

 Advocate – Advocate with, or on the behalf of, the person, or show the person

how to advocate independently to make resources more available and

accessible.

Negotiation Skills:

 Thoughts and feelings – Explore the person’s thoughts and feelings about

what brought the client into contact with the helping system.

 Context – Explore the context in which problems occur, and the conditions

that sustain them.

 Responsibility – Discuss who has responsibility to change patterns of coping

that are causing problems for the person, and/or for others in the person’s life.

 Voice – Help the person’s voice be heard when they name the people and

resources necessary to make life better.

 New names – When appropriate offer new names and descriptions for

problems and explore the new meanings for the person.

 Fit – Enable the person to choose one or more descriptions of the problem

that fit with how they see the world.

 Resources – Work together to find the internal and external resources to help

the person put new solutions into practice.

 Possibilities – Enable the person to experience possibilities for change that

are more numerous than expected.

 Performance – Identify times when the person is performing new ways of

coping and discuss who will notice the changes.

 Perception – Help the person find ways to communicate to others that they

have changed or are doing better than expected.

Table 4: 20 Skills for ecological practice. Adapted from Unger (2015)

Engage allies

An ecological approach acknowledges that people are part of a social system that is

an integral part of a person’s life and is a necessary resource for a person’s well-

being. Health professionals are part of that system and whilst a fundamental goal is

to be an ally to the person, the health professional also needs to mobilise other

social resources. The health professional ought to negotiate who needs to be

involved and what roles they need to assume. Consider for example, someone who

needs to lose weight. Some people may need information (and referral to a dietitian),

some may need a coach (a referral to an exercise physiologist) or a companion to

attend an exercise class with, whilst others might need a family intervention. All

forms of family therapy and solution focused therapy acknowledge that the solutions

to problems or the resources to solve them are largely within the social group.

A sense that a team is working together to find solutions is a powerfully and

reassuring idea. It is perhaps one of the critical ingredients of programmes such as

assertive community treatment (the most evidenced based programme for people

with complex mental health needs) and is fundamental to innovative new

programmes such as open dialogue (Lakeman, 2014). Readers will note Ungar’s

(2015) list of negotiation skills (table 4) end with having the person’s voice heard and

their improvement witnessed by others. This involvement, witnessing and

engagement with others is a powerful motivator of positive behaviour and

connectedness with others is perhaps the lynchpin of mental health. People need the

opportunity to share their successes, help others and be needed by a social group.

Engaging peer support and encouraging people to be peer supporters is a sound

motivational strategy.

Lastly, health professionals need to remain engaged with allies themselves. When

enmeshed in clinical roles it is sometimes hard to see the forest (dynamics) for the

trees (behaviours). Clinical supervision or at least open dialogue with others who are

able to identify the dynamics involved in interactions, able to model the kind of

containing presence that health professionals need to model, and enrich the health

professional’s toolbox of solution focused strategies are essential to developing

effective practice with the recalcitrant or highly resistant client.

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72 Abstracts / Psychoneuroendocrinology 83S (2017) 1–89

Symposium 19: The impact of prenatal and postnatal stress in
childhood on hypothalamic-pituitary-adrenal function,
proinflammatory markers, and mental health in adolescence
and adulthood
Time: Saturday, 09/Sep/2017: 10:30 am–12:00 pm
Session Chair: Mark A. Ellenbogen

A 10-year longitudinal study of cumulative
stress in childhood, the cortisol response at
awakening, and depressive symptoms in the
offspring of parents with bipolar disorder

Mark A. Ellenbogen 1,∗,
Claire-Dominique Walker 2, Sheilagh Hodgins 3

1 Centre for Research in Human Development,
Concordia University, Canada
2 Douglas Mental Health University Institute and
McGill University, Canada
3 Department of Psychiatry, Université de Montréal,
Canada
E-mail address: mark.ellenbogen@concordia.ca
(M.A. Ellenbogen).

Background: The offspring of parents with bipolar disorder
(OBD), relative to control offspring, are at high risk for developing
affective disorders and have elevated daytime cortisol levels. It is
possible that these changes to the hypothalamic-pituitary-adrenal
(HPA) axis in the OBD occur in response to prenatal and postnatal
stress and adversity in the environment. According to the cumu-
lative stress hypothesis, stress-sensitive physiological systems are
altered by exposure to multiple adversities, irrespective of the type.
We tested whether cumulative stress exposure in childhood medi-
ates the relationship between risk status (having a parent with
bipolar disorder) and the cortisol response following awakening
(CAR) in young adulthood. We also tested whether an elevated CAR
response in the OBD was related to the development of depressive
symptoms.

Methods: The sample (19.3 ± 3.4 years) consisted of 58 OBD and
60 offspring of parents with no affective disorder (controls). Cumu-
lative stress was measured as an index of exposure to obstetric
complications and other stress-related risk factors in parents.

Results: Bootstrapping analyses revealed that the cumulative
stress in childhood significantly mediated the relationship between
risk status and an elevated CAR in young adulthood (CI: 0.02–0.22).
A sequential multiple mediation model demonstrated significant
pathways from risk status to cumulative stress, from cumulative
stress to an elevated CAR, and from an elevated CAR to depressive
symptoms in young adulthood (CI: 0.01–0.18).

Conclusions: These findings highlight the role of cumulative
stress as a putative mechanism leading to the development of affec-
tive disorders through HPA dysfunction.

http://dx.doi.org/10.1016/j.psyneuen.2017.07.432

Prenatal maternal stress predicts cortisol stress
response and child behavior problems at ages 4
and 13: Project Ice Storm

Suzanne King 1,2,∗, Erin Yong Ping 3,
Guillaume Elgbeili 2, David P. Laplante 2

1 McGill University, Canada
2 Douglas Mental Health University Institute, Canada
3 Concordia University, Canada
E-mail address: suzanne.king@mcgill.ca (S. King).

Background: Studying associations between prenatal maternal
stress (PNMS) and the hypothalamic-pituitary-adrenal (HPA) axis
in humans is problematic given ethical constraints against assign-
ing stressors to pregnant women. Yet, it is important to increase
understanding of the fetal origins of HPA axis development in
children, and subsequent links to mental health. Natural disasters
provide varying degrees of hardship to the population, often in
quasi-random ways.

Method: In June 1998 we recruited women who were pregnant
during the January 1998 Quebec Ice Storm and assessed their objec-
tive exposure and their subjective distress (PTSD symptoms). When
their children were 4 years old (n = 34) we sampled salivary cortisol
before and after vaccination, and at age 13 (n = 45) before and after
the Trier Social Stress Test. Mothers rated their children’s behavior
problems with the Child Behavior Checklist (CBCL).

Results: At age 4, objective and subjective PNMS interacted
to explain variance in cortisol: the lowest cortisol response was
in children of mothers who were either over-reactors or under-
reactors to their objective exposure. Lower cortisol and higher
subjective PNMS explained greater internalizing (R2 = .30) and
externalizing (R2 = .34) problems. At age 13, greater objective
exposure predicted higher acute cortisol response. More severe
externalizing problems were associated with more severe subjec-
tive PNMS and lower acute cortisol response (R2 = .21); associations
were not significant for internalizing problems.

Conclusions: Different aspects of PNMS predict child HPA axis
in different ways at different ages, and failure to mount an HPA axis
response predicts more severe behavior problems in childhood and
adolescence.

http://dx.doi.org/10.1016/j.psyneuen.2017.07.433

Interaction of childhood maltreatment and
polymorphisms of the FKBP5 gene on the
cortisol response to stress in adolescents

Raegan Mazurka 1,∗,
Katherine E. Wynne-Edwards 2, Kate L. Harkness 1

1 Queen’s University, Canada
2 University of Calgary, Canada
E-mail address: r.mazurka@queensu.ca
(R. Mazurka).

Background: Childhood maltreatment is associated with
increased risk for psychopathology as well as differences in the
neurobiological stress response. An additional factor associated
with neuroendocrine functioning and increased psychopathology
risk is polymorphisms within the FKBP5 gene. In this preliminary
investigation, we examined the gene-environment interaction of
childhood maltreatment and variation in the FKBP5 gene on the
cortisol response to the Trier Social Stress Test.

Methods: Our sample consisted of 90 depressed and non-
depressed adolescents (11–21 years). We assessed HPA axis
function by measuring salivary cortisol over the Trier Social Stress

http://crossmark.crossref.org/dialog/?doi=10.1016/j.psyneuen.2017.07.432&domain=pdf

mailto:mark.ellenbogen@concordia.ca

dx.doi.org/10.1016/j.psyneuen.2017.07.432

http://crossmark.crossref.org/dialog/?doi=10.1016/j.psyneuen.2017.07.433&domain=pdf

mailto:suzanne.king@mcgill.ca

dx.doi.org/10.1016/j.psyneuen.2017.07.433

http://crossmark.crossref.org/dialog/?doi=10.1016/j.psyneuen.2017.07.434&domain=pdf

mailto:r.mazurka@queensu.ca

42 PRACTICAL NEUROLOGY MARCH 2016

E X P E R T
O P I N I O N

L
ithium is an alkali metal naturally found in minerals
and seawater. Compounds of lithium salts, most com-
monly lithium carbonate, have been used for medicinal

purposes since the 19th century. Historically, lithium has
been used to treat a range of diseases, including gout and
hypertension, but currently it is primarily used to treat
bipolar disorder.1 In bipolar disorder, it is a common adjunct
mood stabilizer for patients prone to manic episodes or sui-
cide. With an estimated one to three percent of the world’s
population suffering from bipolar disorder, lithium’s use is
widespread.2 Although widely used, lithium has a narrow
therapeutic window and toxic levels can lead to a variety
of systemic symptoms which confer significant morbidity.
Ahead, we will review the pharmacology of lithium, outline
its use in modern medicine, and discuss severe lithium neu-
rotoxicity in order to highlight its presentation, diagnosis,
and treatment.

MECHANISM OF ACTION
Most commonly used in the treatment of bipolar disor-

der, lithium may also be used in refractory depression and
schizophrenia or as an adjunct mood stabilizer. A recent
meta-analysis also showed that lithium might play an impor-
tant role in reducing suicide in those with a mood disorder.3

Although Lithium’s specific mechanism of action as utilized
to treat psychiatric disorders has not been entirely elucidat-
ed and remains partially unknown, several hypotheses exist.
For example, some evidence points to lithium being syner-
gistic with serotonin neurotransmission. One study showed
that serotonin uptake and release by neurons in rat raphe
nuclei were enhanced by greater than 20 percent with the
addition of lithium when compared to controls.4 In addition
to mediating neurotransmission and release, much of lithi-
um’s therapeutic action may be related to a reduction in the

oxidative stress associated with recurrent episodes of both
mania and depression. Lithium has been shown to reduce
both neuronal apoptosis and autophagy, while at the same
time increasing neural protective proteins. Glutamate and
dopamine neurotransmission is thought to be augmented
by lithium, aiding in its effect on mood stabilization.5

The main inhibitory neurotransmitter, GABA, plays an
essential role in regulating both dopamine and glutamine.
GABA levels are known to be decreased in those with bipo-
lar disorder and low GABA levels lead to excitotoxicity,
which is counteracted by lithium, contributing to its neu-
roprotective properties. Additionally, lithium also enhances
the release of several neuroprotective proteins.

PATHOPHYSIOLOGY
As previously mentioned, lithium toxicity is not uncom-

mon due to its narrow therapeutic index. Lithium toxicity
presents with a variety of clinical manifestations including
renal dysfunction, neurologic dysfunction, gastrointestinal
symptoms, cardiac manifestations, and endocrine abnor-
malities. The mechanism for injury on each system is not
completely known.

The most common complication of chronic lithium inges-
tion is nephrogenic diabetes insipidus (DI), which can be
seen in as many as 20 percent of patients on lithium.6 Due
to lithium’s renal excretion, any change in the glomerular
filtration rate will affect serum lithium concentrations; for
example, renal dysfunction, hyponatremia, NSAIDs, and
diuretics can directly cause an increase in lithium levels.6
The half life of lithium is approximately 29 hours,7 but when
the drug approaches toxic levels it can impair excretion by
reducing the GFR by as much as 0-5mL/min within the first
year alone.6 Lithium accumulates in the collecting tubules
and interferes with the ability of ADH to increase water

Lithium Toxicity:
A Review of Pathophysiology,
Treatment, and Prognosis
By Erica Altschul, DO, Craig Grossman, MD, Renee Dougherty DO, MS,
Rahul Gaikwad, MD, Vina Nguyen, MD, Joshua Schwimmer, MD, Edward Merker, MD,
and Steven Mandel, MD

E X P E R T
O P I N I O N

MARCH 2016 PRACTICAL NEUROLOGY 43

permeability,6 leading to a drop in urinary concentrating
ability by 15 percent over time.8 This is usually observed
early on in the course of lithium ingestion and is reversible,
but if lithium doses are not adjusted over time the dam-
age can become irreversible.6 In addition, lithium competes
with sodium and potassium channels interfering with ion
transport in neurons, ultimately altering neurotransmitter
activity. Serotonin and acetylcholine effects are increased,
dopamine effects are diminished, and cyclic adenosine
5-monophosphate cannot accumulate.6 The changes of
neurotransmitter activity are thought to cause the severe
neurological sequelae of lithium toxicity. Neurotoxicity of
lithium can persist despite falling serum levels of lithium.
This is likely due to Lithium’s ability to accumulate in the
cerebral white matter.7

Lithium toxicity can also develop because of drug
interactions, such as atypical and typical antipsychotic.
Occasionally, lithium toxicity can be mistaken for other
syndromes associated with antipsychotic use. As stated
previously, lithium increases serotonin metabolites in the
CSF. Lithium toxicity in combination with SSRIs may lead
to a serotonin-like syndrome. A similar mechanism is seen
with neuroleptic malignant syndrome given the synergistic
effects lithium has on neuroleptic drugs.9 In a meta analysis
of lithium toxicity, one case presented with increased pulse
rate, blood pressure, and temperature in a patient consum-
ing a combination of lithium and a neuroleptic drug.9 It is
important to consider polypharmacy as a contributor to the
development of lithium toxicity.

PRESENTATION
The effects of lithium toxicity are diverse and varied: from

a mild hand tremor to a comatose state, from nausea and
vomiting to bradycardia and hypotension. While lithium
toxicity can affect almost every system, the scope of this
paper will focus mainly on the neurological side effects.
There is no typical age or direct correlation with gender to
indicate a predisposition for a patient to develop toxicity,
though it has been seen in more females than males.9 While
one would assume the higher dose of lithium would more
commonly result in toxicity, most cases have been seen in
patients on less than 2,000 mg/day and no study has been
able to prove a direct correlation between serum lithium
levels and the severity of neurotoxicity. It is thought that
severe intoxication occurs with levels less than 3 mEq/L
and greater 5 mEq/L can be fatal, but in one meta-analysis
most cases of toxicity occurred with serum levels below
1.5mEq/L.9

Most patients with lithium toxicity only experience mild
neurological side effects, such as a hand tremor. As toxicity
becomes more severe, patients develop pyramidal, extra-
pyramidal, and cerebellar signs. Severe intoxication can

lead to seizures, stupor, and coma with a 10 percent risk of
permanent neurologic effects, especially cerebellar dysfunc-
tion.6 The more common cerebellar signs seen with lithium
toxicity include ataxia and other gait abnormalities, myoc-
lonus, hyperreflexia, and dysarthria.7,9 Disorientation, altered
consciousness, and acute delirium is associated with acute
lithium neurotoxicity.9 Some patients have presented with
seizure-like activity and EEG changes do occur, mainly mani-
fested as diffuse slowing. Patients with prior EEG abnormali-
ties are thought to be at increased risk for neurotoxicity.7
Given the wide variety of clinical presentations, a grading
system has been developed to determine the severity of
lithium induced neurotoxicity (Table 1).10

There are three main types of lithium toxicity: acute,
acute on chronic, and chronic. Acute is considered in any
patient who is lithium naïve and consumes a large amount
of lithium at once, acute on chronic is seen in patients who
have been on chronic lithium and overdose, while chronic
toxicity is a slow accumulation of lithium in patients who
have a decreased ability to excrete the drug due to the its side
effects.10 The severity of disease has been shown to have cor-
relation with the type of lithium toxicity, with chronic toxicity
resulting in the highest incidence of severe disease.

The longer symptoms persist, the greater concern for
prognosis. If symptoms persist for more than two months
after cessation of lithium, the patient is at an increased
risk for developing permanent neurotoxicity. Irreversible
neurotoxicity has the same clinical manifestations as
reversible neurotoxicity, but results in demyelination of
the cerebellum and loss of purkinje fibers.9 Some authors
believe that patients with pre-existing brain pathology are
at an increased risk for developing neurotoxicity, since the
brain tissue has an increased affinity for lithium as well as a
decreased ability to clear intracellular levels of lithium.9

TREATMENT
The standard treatment strategy of lithium toxicity gen-

erally involves stabilization by primary survey, cessation of
lithium administration or any medications that may reduce
lithium elimination, hydration, gastrointestinal decontami-

TABLE 1. AMDISEN RATING SCALE
FOR THE ASSESSMENT OF LITHIUM TOXICITY

(SEVERITY RATING)

0 No clinical signs or symptoms

1 Mild (nausea, vomiting, tremor, hyperreflexia, agitation,
weakness, and ataxia)

2 Moderate (stupor, rigidity, hypertonia, and hypotension)

3 Severe (myoclonus, cardiovascular collapse, seizure, and
coma)

44 PRACTICAL NEUROLOGY MARCH 2016

E X P E R T
O P I N I O N

nation, and enhanced elimination via extracorporeal treat-
ments of enteral treatments. However, due to the relatively
long time course involved in lithium poisoning after presen-
tation, it is not unreasonable in certain non-life threatening
cases to choose a conservative course of action, while moni-
toring serum lithium levels and renal function, so that treat-
ment can be adjusted as necessary. Regardless of the level of
toxicity, patients should be admitted for hospitalization; the
level of acuity is dependent on the severity of the symptoms.
In severe situations, for example when seizure or altered
mental status is present, the patient should be admitted to
an intensive care unit for further management.

Once lithium toxicity is suspected, a primary survey should
be rapidly conducted to carefully assess the patient’s airway
and breathing. After the patient’s airway and breathing are
stabilized, the primary concern should be restoring volume by
administering intravenous normal saline; a patient in a hypo-
volemic state seems to benefit the most from this, as many
will experience a large decrease in total body fluid as a direct
result of polyuria and concomitant central and nephrogenic
diabetes insipidus secondary to lithium use.11 Hydration also
promotes the renal excretion of lithium. Total volume resusci-
tation should be at least two to three liters, assuming normal
cardiac function. Sodium levels should be monitored closely,
as hypernatremia may occur when large amounts of normal
saline are administered.

It is essential to discontinue any form of lithium therapy
once a diagnosis of toxicity has been made. Additionally,
certain medications are known to decrease the renal excre-
tion of lithium; these drugs include thiazide diuretics,
angiotensin converting enzyme inhibitors, and non-steroidal
anti-inflammatory drugs. Although diuretics may be the
causative agent for lithium toxicity, the use of loop diuret-
ics, such as furosemide or amiloride, may be beneficial. Loop
diuretics have the benefit of augmenting the fractional
lithium clearance, while decreasing the absorption of lithium
in the proximal convoluted tubule. However, due to the side
effect profile of these agents, including the risk of electrolyte
disorders and dehydration, most researchers do not cur-
rently recommend this form of therapy.12

The next step in treatment is decontamination. There
are two forms of this therapy that have been investigated
for use in lithium toxicity, one being activated charcoal and
the second being whole bowel irrigation (WBI). Activated
charcoal is administered via nastrogastric tube and acts by
restricting the absorption of most toxins; however this form
of treatment does not bind lithium ions and has been found
to have little effect on outcomes of lithium poisoning.13 WBI
restricts lithium absorption, while decreasing the bioavail-
ability of the toxin, and removing residual lithium from the
gastrointestinal tract.14 These forms of treatment may be
best suited for individuals in the early phase of acute poison-

ing, when lithium is still being absorbed, in comparison to
chronic lithium toxicity, which is not nearly as dependent
on acute levels of lithium found in the gut.15

In more chronic lithium toxicity or in acute toxicity that
does not respond to decontamination, the goal would be
enhanced elimination. The purpose of this treatment modal-
ity is to augment lithium clearance, decrease the severity of
the intoxication, and potentially prevent chronic sequela
from developing. The two main modalities that are available
currently are extracorporeal treatments, normally utilizing
hemodialysis (HD) or hemofiltration, and enteral treatments,
using sodium polystyrene sulfate (SPS); extreme caution must
be exercised when using SPS, as there is a high risk of hypo-
kalemia with use.16 The decision to perform hemodialysis is
often dependent on the serum lithium levels, as well as the
patient’s clinical condition and renal function. Some research-
ers have suggested hemodialysis is appropriate in any patient
with a lithium level greater than 6mEq/L; a chronic lithium
user who has a lithium level greater than 4mEq/L; any patient
with renal insufficiency, severe neurologic compromise, or
hemodynamic instability with a lithium level greater than 2.5-
4mEq/L; any patient with a lithium level less than 2.5mEq/L
with concurrent ESRD or who fails to reach lithium level less
than 1mEq/L after 30 hours.13 However, there is no universally
accepted guideline for initiating hemodialysis, and it is often
at the discretion of the nephrologist and/or intensivist. Also of
note, HD works to clear serum (extracellular) lithium from the
body, but has no role in clearing intracellular lithium stores;
this is of particular importance when HD is discontinued, as
serum lithium levels may eventually rebound to levels seen
prior to the initiation of HD.17

PROGNOSIS
The prognosis of patients with lithium intoxication varies,

ranging from no residual sequela to long lasting neurologic
deficits. The spectrum of prognosis does not seem depen-
dent on the treatment modalities, as case reports suggest
that neurologic deficits may be seen following the most
aggressive forms of therapy, including hemodialysis.18 Most
cases of intoxication will have total recovery of all neuro-
logic function after resolution of the acute phase of toxicity;
only a small percentage of individuals will go on to exhibit
some form of neurologic deficit or dysfunction.19 The most
concerning long-term deficit or dysfunction of lithium
toxicity is the Syndrome of Irreversible Lithium-Effectuated
Neurotoxicity (SILENT), a constellation of neuropsychiatric
symptoms that follows lithium toxicity and may remain
long after serum lithium levels return to normal, with a
minimum persistence of at least two months. Characterized
by brainstem dysfunction, cerebellar dysfunction, extrapyra-
midal symptoms and cognitive impairment, the symptoms
of SILENT are thought to represent attenuated versions of

E X P E R T
O P I N I O N

MARCH 2016 PRACTICAL NEUROLOGY 45

more severe deficits present during the initial phases of tox-
icity. Additionally, researchers have suggested the possibility
of visual and auditory perceptual disturbances, as well.20
Case reports suggest that severe cases of SILENT syndrome
may persist for years, with cerebellar symptoms being the
most frequently reported; these symptoms include truncal
ataxia, gait ataxia, and clumsiness involving motor activity.
Furthermore, case reports suggest that pyramidal signs have
a greater chance of complete resolution in comparison to
cerebellar signs, with ataxia persisting the longest.21 Risk fac-
tors for persistent neurologic dysfunction include presence
of fever during intoxication; rapid correction of hyponatre-
mia or lithium levels; high serum lithium levels on presenta-
tion; coexisting illnesses, such as epilepsy, acute gastroenteri-
tis, or chronic kidney disease; and concomitant use of other
drugs, such as antipsychotics or epileptic agents.22

Of note, it is important to monitor thyroid function fol-
lowing lithium intoxication, as hypothyroidism is a common
phenomenon that occurs concurrently with lithium use,
affecting approximately 20 percent of lithium users, and
may be exacerbated during times of intoxication.23

Lithium is concentrated in the thyroid gland three to four
times more than in plasma.24 It inhibits release of preformed
thyroid hormone by alteration in tubulin polymerization
and also by inhibition of the stimulatory effect of TSH on
the cAMP pathway.25 The incidence of goiter with lithium
treatment is estimated to be 30 percent to 55 percent,
while the prevalence of hypothyroidism with lithium treat-
ment ranges between six percent and 52 percent. Lithium
has been associated with rare case of hyperthyroidism as
well. One report noted that 20 percent of Lithium-treated
patients have antithyroid antibodies, compared with 7.5
percent without Lithium treatment.26 The same study
observed increased B-cell activity and a decreased ratio of
suppressor to cytotoxic T-cells, as well.

CONCLUSION
Despite the diverse presentation of lithium toxicity, it

remains a common drug to treat a multitude of psychiat-
ric disorders. Given its prevalence in the community, it is
important to recognize the initial presentation of lithium
toxicity as further progression can cause development of
permanent neurologic disorders and severe renal dysfunc-
tion. Finally, always consider drug interactions, especially
with other antipsychotic medications as well as nephrotoxic
agents, particularly since the combination of these drugs
with lithium increases the risk of toxicity. n

Erica Altschul, DO is an Internal Medicine Resident at Lenox
Hill Hospital in New York.

Craig Grossman, MD is an Internal Medicine Resident at
Lenox Hill Hospital.

Renee Dougherty, DO, MS is an Internal Medicine Resident
at Lenox Hill Hospital.

Rahul Gaikwad, MD is an Internal Medicine Resident at
Lenox Hill Hospital.

Vina Nguyen, MD is an Internal Medicine Resident at Lenox
Hill Hospital.

Joshua Schwimmer, MD is Assistant Professor of Medicine,
Hofstra Northwell School of Medicine; Nephrologist, Lenox Hill
Hospital

Edward Merker, MD is Associate Director of Endocrinology
and Associate Clinical Professor of Medicine (Endocrinology)
and Geriatrics at Icahn School of Medicine at Mt. Sinai
Hospital.

Steven Mandel, MD is a Clinical Professor of Neurology at
Lenox Hospital and Hofstra NorthWell School of Medicine.

1. R. Oruch, M. A. Elderbi, H. A. Khattab, I. F. Pryme, and A. Lund, “Lithium: a review of pharmacology, clinical uses, and
toxicity,” European Journal of Pharmacology, vol. 740, pp. 464–473, 2014.
2. Marmol F. Lithium: bipolar disorder and neurodegenerative diseases Possible cellular mechanisms of the therapeutic
effects of lithium. Prog Neuropsychopharmacol Biol Psych. 2008;32:1761–1771. doi: 10.1016/j.pnpbp.2008.08.012.
3. Cipriani, A.; Hawton, K.; Stockton, S.; Geddes, JR. (2013). “Lithium in the prevention of suicide in mood disorders:
updated systematic review and meta-analysis.”. BMJ 346: f3646.
4. Scheuch, K.; Höltje, M.; Budde, H.; Lautenschlager, M.; Heinz, A.; Ahnert-Hilger, G.; Priller, J. (2010). “Lithium modulates
tryptophan hydroxylase 2 gene expression and serotonin release in primary cultures of serotonergic raphe neurons”. Brain
Research 1307: 14�21.
5. Malhi GS (2013). “Potential mechanisms of action of lithium in bipolar disorder. Current understanding.”. CNS Drugs
27 (2): 135–53.
6. Alexander MP, Farag YM, Mittal BV, Rennke HG, Singh AK. Lithium toxicity: A double-edged sword.Kidney Int.
2008;73:233–7
7. Gill, J., Singh, H. and Nugent, K. (2003), Acute Lithium Intoxication and Neuroleptic Malignant Syndrome. Pharmaco-
therapy, 23: 811–815. doi: 10.1592/phco.23.6.811.32179
8. McKnight RF, Adida M, Budge K, Stockton S, Goodwin GM, Geddes JR. Lithium toxicity profile: a systematic review and
meta-analysis. Lancet. 2012;379(9817):721–728
9. Netto I, Phutane VH. Reversible Lithium Neurotoxicity: Review of the Literature.The Primary Care Companion for CNS
Disorders. 2012;14(1):PCC.11r01197. doi:10.4088/PCC.11r01197.
10. Ivkovic A, Stern TA. Lithium-induced neurotoxicity: clinical presentations, pathophysiology, and treatment.Psychoso-
matics. 2014;55:296–302. doi: 10.1016/j.psym.2013.11.007
11. McLean M MD, Sherwin H MD, Madabhushi V, et al: Case Review: A 17-Year Old Female Patient with a Lithium
Overdose. Air Medical Journal 2015; 34(4): 162-165.
12. Eyer F MD, Pfab R MD, Felgenhauer N MD, et al: Lithium Poisoing: Pharmacokinetics and Clearance During Different
Therapeutic Measures. Journal of Clinical Psychopharmacology 2006; 26(3): 325-330.
13. (7 & 3) Lee YC, Lin JL, Lee SL, et al: Outcome of patients with lithium poisoning at a far-east poison center. Human and
Experimental Toxicology 2010: 528-534.
14. Meertens JH, Jagernath DR, Eleveld DJ, et al: Hemodialysis followed by continuous venovenous hemofiltration in
lithium intoxication, a model and a case. European Journal of Internal Medicine 2009; 20: 70-73.
15. Deguigne M, Hamel J, Boels D and Harry P: Lithium Poisoning: the value of early digestive tract decontamination.
Clinical Toxicology 2013; 51(4): 243-248.
16. Roberts D and Gosselin S: Variability in the Management of Lithium Poisoning. Seminars in Dialysis 2014; 27(4):
390-394.
17. (8)Ivkovic A MD and Stern T MD: Lithium-Induced Neurotoxicity: Clinical Presentations, Pathophysiology, and Treat-
ment. Psychosomatics 2014; 55(3): 296-302.
18. (9)Von Hartitzsch B, Hoenich N, Leigh RJ, et al: Permanent Neurological Sequale Despite Hemodialysis for Lithium
Intoxication. British Medical Journal 1972; 4: 757-759.
19. (10)Nguyen, Lilly. Lithium II: Irreversible Neurotoxicity After Lithium Intoxication. Journal of Emergency Nursing 2008;
34(4): 378-379.
20. (11) Feldman W, Besterman A, Yu JP, et al: Persistent Perceptual Disturbances After Lithium Toxicity: A Case Report
and Discussion. Psychosomatics 2015; 56(3): 306-310.
21. (12)Lang E and Davis S: Lithium Neurotoxicity: the development of irreversible neurological impairment despite
standard monitoring of serum lithium levels. Journal of Clinical Neuroscience 2002; 9(3): 308-309.
22. (13) Porto F, Leite M, Fontenelle L, e al: The Syndrome of Irreversible Lithium-Effectuated Neurotoxicity (SILENT):
One-year follow-up of a single case. Journal of the Neurological Sciences 2009; 277: 172-173.
23. (14)Lazarus JH: Lithium and Thyroid. Best Practice and Research Clinical Endocrinology and Metabolism 2009; 23:
723-733.
24. Lazarus,JH.Endocrine and Metabolic Effects of Lithium.New York and London, Plenum Medical Book Company, 1986.
Lithium and the thyroid gland: pp. 99-124.
25. Perrild H, Hegedus L, Basstrup PC,Kayser L,Kastberg S. Thyroid function and ultrasonically determined thyroid size in
patients receiving long-term Lithium treatment. Am. J Psychiatry 1990: 147: 1518-21.
26. Wilson R,McKillop JH,Crocket GT,Pearson C,Jenkins C, Burns F et al.The effect of lithium therapy on parameters thought
to be involved in the development of autoimmune disease. Clin Endocrin 1991: 34:357-61.

62

Australian Prescriber Vol. 26 No. 3 2003

Serotonin syndrome

Michael Hall, Clinical Pharmacology/Toxicology Registrar, and Nick Buckley,
Associate Professor, Department of Clinical Pharmacology and Toxicology, The
Canberra Hospital, Canberra

SYNOPSIS

Serotonin syndrome is a toxic state caused mainly by
excess serotonin within the central nervous system. It
results in a variety of mental, autonomic and
neuromuscular changes, which can range in severity
from mild to life-threatening. Most cases are
self-limiting. Severe serotonin syndrome is nearly always
caused by a drug interaction involving two or more
‘serotonergic’ drugs, at least one of which is usually a
selective serotonin reuptake inhibitor or monoamine
oxidase inhibitor. Management involves withdrawal of
the offending drugs, aggressive supportive care and
occasionally serotonin antagonists such as
cyproheptadine. Treatment of the condition for which
the serotonergic drugs were prescribed should be
reviewed.

Index words: selective serotonin reuptake inhibitors, drug
interactions, cyproheptadine.

(Aust Prescr 2003;26:62–3)

Introduction

The treatment of depression in Australia has evolved greatly
over the last two decades. Tricyclic antidepressant use is
decreasing, while the use of selective serotonin reuptake
inhibitors (SSRIs) is increasing. In 2001, prescriptions for
SSRIs outnumbered those for tricyclics by two to one.1 Other
new antidepressants with serotonergic properties are also
being introduced. Although SSRIs and the other ‘atypical’
antidepressants are generally regarded as having lower toxicity
than tricyclics, minor toxic effects are common, and serious
toxicity can occur.

Serotonin syndrome refers to a drug-induced syndrome that is
characterised by mental, autonomic and neuromuscular changes.
It is not an idiosyncratic adverse reaction, but a dose-related
range of toxic symptoms that are largely attributable to increasing
serotonin concentrations in the central nervous system. Serotonin
syndrome was first described in 1955, but during the 1990s
reports became increasingly common, as the signs, symptoms,
and precipitants became more widely recognised. Although
severe cases have been reported with an overdose of a single
drug, they usually only occur with a combination of two or more
‘serotonergic’ drugs (even when each is at a therapeutic dose),
presumably leading to an excessive rise in serotonin
concentrations. The true incidence of serotonin syndrome is
unknown, because of a lack of large case series, a wide spectrum
of symptoms and variations in the definition.

Pathophysiology

Serotonin (5-hydroxytryptamine, 5-HT) is synthesised from
the amino acid tryptophan. It has central and peripheral effects
and there are at least seven different types of serotonin
receptors. Centrally, serotonin acts as a neurotransmitter with
influences on mood, sleep, vomiting and pain perception.
Depression is often associated with low concentrations of
serotonin. Peripherally, the primary effect of serotonin is on
muscles and nerves. The majority of serotonin is synthesised
and stored in the enterochromaffin cells of the gut where it
causes contraction of gastrointestinal smooth muscle. Serotonin
is also stored in platelets and promotes platelet aggregation. It
also acts as an inflammatory mediator.

The pathophysiology of serotonin syndrome remains poorly
understood. It is thought to result from stimulation of the
5-HT

1A
and 5-HT

2
receptors, and the drug classes implicated

in serotonin syndrome reflect this theory. These include serotonin
precursors, serotonin agonists, serotonin releasers, serotonin
reuptake inhibitors, monoamine oxidase inhibitors (MAOIs)
and some herbal medicines (Table 1). Commonly used migraine
medications such as sumatriptan and dihydroergotamine are
also regarded as ‘serotonergic’ drugs. There are isolated case
reports of mild/moderate serotonin syndrome associated with
these drugs. Most cases will involve either an SSRI or an MAOI
and at least one other medication. Generally, drugs with two
different mechanisms of action on serotonin must be present for
a severe serotonin syndrome to develop.

Table 1

Drugs implicated in severe serotonin syndrome*

Drug Mechanism

L-Tryptophan Serotonin precursor

Selective serotonin reuptake inhibitors Inhibit serotonin reuptake

Tricyclic antidepressants Inhibit serotonin reuptake

Monoamine oxidase inhibitors (A>B) Inhibit metabolism of 5-HT

Pethidine Serotonin agonist

Tramadol Inhibits serotonin reuptake

LSD Partial serotonin agonist

Buspirone Partial serotonin agonist

Amphetamines and anorectics ↑ 5-HT release & ↓ reuptake

Atypical antidepressants Various

St John’s wort All of the above?

Lithium Unknown

* Note: Interactions are more severe between drugs with
different mechanisms of increasing serotonin.

63

Australian Prescriber Vol. 26 No. 3 2003

Some other drugs may cause serotonin syndrome although
how this happens remains unclear. Drugs with effects on
catecholamines, tryptamine and dopamine may have secondary
effects on serotonin release or reuptake.

Diagnosis

The diagnosis of serotonin syndrome is purely clinical. It is
based upon recognising a varied combination of signs and
symptoms in the presence of selected ‘serotonergic’
medications. The diagnosis should not be made without
identifying a cause. Serotonin syndrome most commonly
occurs after a dose increase (or overdose) of a potent
serotonergic drug or shortly after a second drug is added.
Some of the drugs involved have very long half-lives
(e.g. fluoxetine) and may have been ceased weeks before.
There may be a history of recent overdose or use of illicit
drugs, particularly ecstasy, amphetamines or cocaine. Herbal
medicines may be implicated (St John’s wort, ginseng,
S-adenosyl-methionine).

The clinical features of serotonin syndrome are highly variable,
reflecting the spectrum of toxicity (Table 2). The onset can be
dramatic or insidious. The most useful features in the diagnosis
of serotonin syndrome are hyperreflexia and clonus
(inducible/spontaneous/ocular). However, many patients
taking SSRIs may display one or more of the clinical features
without gross toxicity.

Investigations are generally unhelpful in the diagnosis of
serotonin syndrome, but may assist in treatment and in ruling
out a differential diagnosis. The white cell count is often
mildly raised and elevations in creatine kinase levels may
occur.

The differential diagnosis includes neuroleptic malignant
syndrome, dystonic reactions, encephalitis, tetanus, thyroid
storm and sepsis, as well as poisoning by anticholinergic
drugs, amphetamines, cocaine, lithium, MAOIs, salicylates
and strychnine. Serotonin syndrome can also be confused with
the withdrawal of antidepressant treatment.2 Serotonin
syndrome and the other agitated deliriums share many clinical
features, but clonus, hyperreflexia and flushing are the most
specific signs.

Time course/complications

In most cases, serotonin syndrome is a self-limiting condition
and will improve on cessation of the offending drugs. Mild to
moderate cases usually resolve in 24–72 hours. In severe cases
patients require intensive care as the syndrome may be
complicated by severe hyperthermia, rhabdomyolysis,
disseminated intravascular coagulation and/or adult respiratory
distress syndrome.

Treatment

Recognising the possibility of serotonin syndrome and diligent
supportive care are the mainstays of treatment. All patients
with moderate or severe serotonergic symptoms should be
admitted to hospital. Those with hyperthermia should be

admitted to an intensive care unit. All serotonergic medications
should be ceased, and care taken that other precipitants are not
inadvertently administered. Intravenous hydration is given, to
ensure an adequate output of urine. Careful monitoring of
temperature, pulse, blood pressure and urine output is required.
Aggressive cooling techniques may be required for
hyperthermia. This may involve cool water sprays, ice packs,
and even paralysis and ventilation. Benzodiazepines may be
used to control seizures and muscle hyperactivity. Specific
treatment of hypertension is usually not required.

Serotonin antagonists have been used in management of
moderate to severe serotonin syndrome. Cyproheptadine
is possibly the most promising drug.3 The initial dose is
4–8 mg orally. This may be repeated in two hours. If no
response is seen after 16 mg it should be discontinued. If there
is a response then it may be continued in divided doses up to
32 mg/day (e.g. up to 8 mg four times daily). Other drugs that
have been suggested include chlorpromazine and propranolol,
but these have more contraindications and adverse effects.

After the patient has recovered reconsider the ongoing treatment
of the condition for which the serotonergic drug was prescribed.

Prevention

The prevention of serotonin syndrome involves awareness of
the toxic potential of serotonergic drugs. The manufacturer’s
advice about washout periods should be carefully considered
when switching antidepressants and patients should also be
educated about possible drug interactions.

E-mail: michael.hall@act.gov.au

R E F E R E N C E S

1. Data produced by Drug Utilisation Sub-Committee, Pharmaceutical
Benefits Branch, Health Access and Financing Division, Commonwealth
Department of Health and Ageing, Canberra, 2002.

2. Tiller JWG. Medicinal mishaps: serotonin states. Aust Prescr 1998;21:63.
3. Chan BS, Graudins A, Whyte IM, Dawson AH, Braitberg G, Duggin GG.

Serotonin syndrome resulting from drug interactions. Med J Aust
1998;169:523-5.

F U R T H E R R E A D I N G

Gillman PK. The serotonin syndrome and its treatment. J Psychopharmacol
1999;13:100-9.

Gillman PK. Serotonin syndrome: history and risk. Fundam Clin Pharmacol
1998;12:482-91.

Conflict of interest: none declared

Table 2

Clinical features of serotonin syndrome

Cognitive Confusion, agitation, hypomania,
hyperactivity, restlessness

Autonomic Hyperthermia, sweating, tachycardia,
hypertension, mydriasis, flushing, shivering

Neuromuscular Clonus (spontaneous/inducible/ocular),
hyperreflexia, hypertonia, ataxia, tremor

Hypertonia and clonus are always symmetrical and are often
much more dramatic in the lower limbs.

52 World Psychiatry 10:1 – February 2011

A number of reviews and studies have shown that people
with severe mental illness (SMI), including schizophrenia, bi-
polar disorder, schizoaffective disorder and major depressive
disorder, have an excess mortality, being two or three times as
high as that in the general population (1-21). This mortality
gap, which translates to a 13-30 year shortened life expectancy
in SMI patients (4,5,22-27), has widened in recent decades
(11,28-30), even in countries where the quality of the health
care system is generally acknowledged to be good (11). About
60% of this excess mortality is due to physical illness (27,31).

Individuals with SMI are prone to many different physi-
cal health problems (Table 1). While these diseases are also
prevalent in the general population, their impact on indi-
viduals with SMI is significantly greater (31,32).

Although many factors contribute to the poor physical
health of people with SMI (33), the increased morbidity and
mortality seen in this population are largely due to a higher
prevalence of modifiable risk factors, many of which are re-
lated to individual lifestyle choices (31). However, this is not
the whole story. It seems that the somatic well being of peo-
ple with a (severe) mental illness has been neglected for de-
cades (15), and still is today (7,34-39,40,41). There is in-
creasing evidence that disparities not only in health care

Physical illness in patients with severe mental disorders.
I. Prevalence, impact of medications and disparities
in health care

WPA EDUCATIONAL MODULE

Marc De Hert1, cHristopH U. correll2, JUlio BoBes3, Marcelo cetkovicH-BakMas4, Dan coHen5,
itsUo asai6, JoHan DetraUx1, sHiv GaUtaM7, Hans-JUrGen Möller8, DaviD M. nDetei9,
JoHn W. neWcoMer10, ricHarD UWakWe11, stefan leUcHt12
1University Psychiatric Center, Catholic University Leuven, Leuvensesteenweg 517, 3070 Kortenberg, Belgium; 2Albert Einstein College of Medicine, Bronx, NY, USA;
3Department of Medicine – Psychiatry, University of Oviedo-CIBERSAM, Spain; 4Department of Psychiatry, Institute of Cognitive Neurology, and Department
of Psychiatry, Institute of Neurosciences, Favaloro University Hospital, Buenos Aires, Argentina; 5Department of Epidemiology, University of Groningen,
The Netherlands; 6Japanese Society of Transcultural Psychiatry; 7Psychiatric Centre, Medical College, Jaipur, India; 8Department of Psychiatry, University of Munich,
Germany; 9University of Nairobi and Africa Mental Health Foundation, Nairobi, Kenya; 10Department of Psychiatry, Washington University School of Medicine,
St. Louis, MO, USA; 11Faculty of Medicine, Nnamdi Azikiwe University, Nnewi Campus, Nigeria; 12Department of Psychiatry and Psychotherapy, Technische
Universität München, Munich, Germany

The lifespan of people with severe mental illness (SMI) is shorter compared to the general population. This excess mortality is mainly due
to physical illness. We report prevalence rates of different physical illnesses as well as important individual lifestyle choices, side effects
of psychotropic treatment and disparities in health care access, utilization and provision that contribute to these poor physical health
outcomes. We searched MEDLINE (1966 – August 2010) combining the MeSH terms of schizophrenia, bipolar disorder and major depres-
sive disorder with the different MeSH terms of general physical disease categories to select pertinent reviews and additional relevant
studies through cross-referencing to identify prevalence figures and factors contributing to the excess morbidity and mortality rates. Nu-
tritional and metabolic diseases, cardiovascular diseases, viral diseases, respiratory tract diseases, musculoskeletal diseases, sexual
dysfunction, pregnancy complications, stomatognathic diseases, and possibly obesity-related cancers are, compared to the general popu-
lation, more prevalent among people with SMI. It seems that lifestyle as well as treatment specific factors account for much of the in-
creased risk for most of these physical diseases. Moreover, there is sufficient evidence that people with SMI are less likely to receive
standard levels of care for most of these diseases. Lifestyle factors, relatively easy to measure, are barely considered for screening; baseline
testing of numerous important physical parameters is insufficiently performed. Besides modifiable lifestyle factors and side effects of
psychotropic medications, access to and quality of health care remains to be improved for individuals with SMI.

Key words: Physical illness, severe mental illness, bipolar disorder, depression, schizophrenia, psychotropic medication, health disparities

(World Psychiatry 2011;10:52-77)

access and utilization, but also in health care provision con-
tribute to these poor physical health outcomes (33-39). A
confluence of patient, provider, and system factors has cre-
ated a situation in which access to and quality of health care
is problematic for individuals with SMI (31). This is not to-
tally surprising as we are today in a situation in which the
gaps, within and between countries, in access to care are
greater than at any time in recent history (42). Therefore, this
growing problem of medical comorbidities and premature
death in people with SMI needs an urgent call to action.

This paper highlights the prevalence of physical health
problems in individuals with SMI. Furthermore, contributing
factors are considered that impact on the physical health of
these people, such as psychotropic medications (antipsychot-
ics, antidepressants and mood stabilizers), individual lifestyle
choices (e.g., smoking, diet, exercise), psychiatric symptoms,
as well as disparities in the health care. This is a selective,
rather than a systematic review of clinical data on physical
health problems in people with SMI, as we did not include
all physical diseases. We searched MEDLINE (1966 – August
2010) for epidemiological, morbidity and mortality data on
the association between physical illnesses and schizophre-
nia, bipolar disorder and major depressive disorder. We com-

WPA1_2011_52_77.indd 52 02/02/11 11:45

53World Psychiatry 10:1 – February 2011

bined the MeSH terms of these psychiatric disorders with the
different MeSH terms of major general physical disease cat-
egories. We included pertinent reviews to identify prevalence
figures and factors contributing to the excess morbidity and
mortality rates. Reference lists of reviews were searched
for additional relevant studies. Moreover, if necessary to ob-
tain more specific information, for some of the general phys-
ical disease categories (e.g., respiratory diseases), we also
used specific physical illnesses as a search term.

PhysIcal dIseases lInKed to sMI

and/or

PsychotroPIc treatMent

obesity

Obesity is becoming a significant and growing health crisis,
affecting both developed and developing countries (43,44).
People with obesity have shorter life spans and are at in-
creased risk for a number of general medical conditions,
including type 2 diabetes mellitus, DM (relative risk, RR >3),
cardiovascular disease, CVD (RR >2-3), dyslipidemia (RR
>3), hypertension (RR >2-3), respiratory difficulties (RR >3),
reproductive hormone abnormalities (RR >1-2) and certain
cancers (e.g., colon) (RR >1-2) (22,45-49,50).

Several methods are available to assess overweight and
obesity. Body mass index (BMI) is a direct calculation
based on height and weight (kg/m2). A BMI ≥25 kg/m2
corresponds to overweight, a BMI ≥30 kg/m2 to obesity
(31). BMIs ≥30kg/m2 are known to shorten life expectancy
(48,51). However, based on evidence for higher morbidity
and mortality risk at BMIs below 30 Kg/m2 in Asian popu-

lations, the threshold for the definition of overweight in
these populations is modified to a BMI ≥23 Kg/m2 and the
threshold for obesity to a BMI ≥25 Kg/m2. Waist circumfer-
ence (WC), measuring abdominal or central adiposity, is
emerging as a potentially more valid and reliable predictor
of risk for CVD, type 2 DM, and other metabolic risk-re-
lated conditions, compared with BMI (31). Accumulating
evidence argues that lower cutoff points for WC should be
used for Asians, as this population is prone to obesity-re-
lated morbidity and mortality at shorter WCs (52-56). The
International Diabetes Federation (IDF) provides sex-and
race-specific criteria in defining WC to identify people
with central obesity, thus adjusting this criterion to make
it also useful in non-Caucasian populations (Table 2).
However, long-term prospective studies are still required
to identify more reliable WC cut points for different ethnic
groups, particularly for women (57).

Obesity in SMI patients

SMI and obesity overlap to a clinically significant extent
(45). Increasing evidence suggests that persons with SMI are,
compared to the general population, at increased risk for
overweight (i.e., BMI =25-29.9, unless Asian: BMI =23-24.9),
obesity (i.e., BMI ≥30, unless Asian: BMI ≥25) and abdomi-
nal obesity (see Table 2) (63-75), even in early illness phase
and/or without medication (76-78). The risk of obesity in
persons with SMI, however, varies by diagnosis. People with
schizophrenia have a 2.8 to 3.5 increased likelihood of being
obese (79). Several Canadian and US studies reported rates
of obesity (BMI ≥30) in patients with schizophrenia of 42-
60% (63,79,80). On the other hand, those with major depres-

Table 1 Physical diseases with increased frequency in severe mental illness (from 15)

Disease category Physical diseases with increased frequency

Bacterial infections and mycoses

Viral diseases

Neoplasms

Musculoskeletal diseases

Stomatognathic diseases
Respiratory tract diseases
Urological and male genital diseases
Female genital diseases and pregnancy complications
Cardiovascular diseases

Nutritional and metabolic diseases

Tuberculosis (+)
HIV (++), hepatitis B/C (+)
Obesity-related cancer (+)
Osteoporosis/decreased bone mineral density (+)
Poor dental status (+)
Impaired lung function (+)
Sexual dysfunction (+)
Obstetric complications (++)
Stroke, myocardial infarction, hypertension, other cardiac and vascular
diseases (++)
Obesity (++), diabetes mellitus (+), metabolic syndrome (++),
hyperlipidemia (++)

(++) very good evidence for increased risk, (+) good evidence for increased risk

Table 2 Ethnicity-specific cutoff values of waist circumference indicating abdominal obesity (see 57-62)

European, sub-Saharan Africans, Mediterranean
and Middle Eastern populations

South Asians, Chinese, and ethnic South
and Central Americans

Japanese Northern
Americans

Men ≥94 cm ≥90 cm ≥90 cm ≥102 cm

Women ≥80 cm ≥80 cm ≥82-85 cm ≥88 cm

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54 World Psychiatry 10:1 – February 2011

sion or bipolar disorder have a 1.2 to 1.5 increased likelihood
of being obese (BMI ≥30) (44,69,70,81,82). Clinical research
has suggested that up to 68% of treatment-seeking bipolar
disorder patients are overweight or obese (83). One study
found an obesity rate (BMI ≥30) of 57.8% among those with
severe depression (84).

In patients with SMI, as in the general population, obe-
sity is associated with lifestyle factors (e.g., lack of exercise,
poor diet), but also with illness-related (negative, disorgan-
ized and depressive symptoms) and treatment-related fac-
tors, including weight liability of certain psychotropic
agents. Adverse effects, such as sedation, should also be
considered as potential contributors to weight gain in addi-
tion to, still not fully elucidated, medication induced effects
on appetite and food intake (45,73,50,85-87).

Obesity and psychotropics

Weight gain during acute and maintenance treatment of
patients with schizophrenia is a well established side effect of
antipsychotics (AP), affecting between 15 and 72% of patients

(26,50,77,88-98). There is growing evidence for similar effects
in patients with bipolar disorder (65,83,99). There is a hierar-
chy for risk of weight gain with AP that has been confirmed in
different studies and meta-analyses (88,92,100-106). Weight
gain is greatest with clozapine and olanzapine (107,108),
while quetiapine and risperidone have an intermediate risk.
Aripiprazole, asenapine, amisulpride and ziprasidone have
little effect on weight. A recent systematic review of random-
ized, placebo controlled trials of novel AP in children and

adolescents (<18 years old) identified the same hierarchy for risk of weight gain for this vulnerable population (109). Among the conventional AP, so-called low-potency agents, such as chlorpromazine and thioridazine, have a higher risk than high-potency drugs, such as haloperidol (110-112). No agent, however, should be considered as truly weight-neutral, as the proportion of individuals experiencing ≥7% weight gain is greater with any atypical AP than with placebo (92), and all AP have been found to cause significant weight gain in AP- naïve or first-episode patients (113-115). Even amisulpride, ziprasidone and low-dose haloperidol demonstrated notable weight gain of 9.7 kg, 4.8 kg and 6.3 kg respectively at endpoint in a 12-month trial of AP in first-episode patients (102). Equal- ly, antidepressants (AD) such as paroxetine (116), and mood stabilizers, such as lithium and valproate (117-119), have been associated with weight gain (Table 3).

The high interindividual variability in medication-induced
weight gain suggests that genetic factors influence the risk to
gain weight (50,122). Studies of genetic predictors of weight
gain under AP therapy have mainly but not exclusively (131)
focused on HTR2C (132-135) and LEPR (135,136) gene
polymorphisms. Although the results are promising, the role
of genetic factors in predicting this severe side effect remains
an option for the future.

Metabolic syndrome

Obesity is also associated with the metabolic syndrome
(MetS), a clustering of abnormalities that confers a 5-6-fold

Table 3 Weight gain liability of psychotropic agents used in SMI (see 45,63-65,87,95,99,104,120,121-130)

Drug class Weight loss Relatively weight neutral Weight gain

Antidepressants Bupropion
Fluoxetine

Citalopram
Duloxetine

Escitalopram
Nefazodone

Sertraline
Venlafaxine

Substantial
Amitriptyline
Imipramine
Mirtazapine

Intermediate
Nortriptyline
Paroxetine

Anticonvulsants/
Mood stabilizers

Topiramate
Zonisamide

Lamotrigine
Oxcarbazepine

Substantial
Lithium

Valproate

Intermediate
Carbamazepine

Gabapentin

Antipsychotics Aripiprazole (in pre-treated individuals)
Molindone (in pre-treated individuals)
Ziprasidone (in pre-treated individuals)

Amisulpride
Aripiprazole
Asenapine

Fluphenazine
Haloperidol
Lurasidone

Perphenazine
Ziprasidone

Substantial
Chlorpromazine

Clozapine
Olanzapine

Intermediate
Iloperidone
Quetiapine
Risperidone
Thioridazine

Zotepine

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55World Psychiatry 10:1 – February 2011

increased risk of developing type 2 DM and a 3-6 fold in-
creased risk of mortality due to coronary heart disease (137-
144).

There is also evidence supporting the hypothesis that the
MetS or components of the MetS may be important etio-
logic factors for certain cancers (e.g., colon cancer) (145,146).

Although some controversy exists whether the MetS is a
true syndrome (57,147-149), and despite differences in spe-
cific criteria among the definitions (Table 4), there is agree-
ment that the major characteristics of the syndrome include
central obesity, hypertension, dyslipidemia, glucose intoler-
ance or insulin resistance (45,137,150). Studies show large
variations in prevalence estimates of the MetS across defini-
tions, countries or regions, gender, ethnicity, and age groups
(137). Countries in North and South America (151-154)
reported a relatively higher prevalence than other countries
or regions in the world (137).

MetS in SMI patients

The MetS is highly prevalent among treated patients with
schizophrenia. Depending on used MetS criteria, gender,
ethnicity, country, age groups and AP treatment, percentages
vary considerably (between 19.4% and 68%) (155-167).
However, there is little debate that people with schizophre-
nia exhibit a higher MetS prevalence than their peers in the
general population across the world (168). MetS rates in
patients with bipolar disorder and schizoaffective disorder
have been reported to be 22-30% (143,169,170) and 42%
(171), respectively.

Table 5 summarizes the potential of various AP medica-
tion to cause or exacerbate the metabolic syndrome. Never-
theless, lifestyle and behavioral patterns (smoking, physical
inactivity, dietary habits) also play important roles in the
prevalence of the MetS in SMI populations (118,168,176).

Disparities in health care

The proportion of SMI patients not receiving tests for as-
sessing metabolic risk factors, even for factors relatively
simple and easy to measure, such as obesity and blood pres-
sure, is high (141,177-181). At present, neither psychiatrists
nor primary care physicians carefully screen or monitor pa-
tients receiving AP medication for metabolic risk factors
(173). Even after FDA (Food and Drug Administration) and
ADA (American Diabetes Association)/APA (American
Psychiatric Association) recommendations for novel AP, the
frequency of baseline glucose and lipid testing showed little
change. Several large-scale pharmacoepidemiologic studies
of individuals initiating a novel AP (with non-psychiatric
large control groups) reported low mean baseline metabolic
testing rates, varying between 8% and less than 30% (181-
183) and follow-up assessments done in only 8.8% of pa-
tients. Likewise, most children starting treatment with novel

AP do not receive recommended glucose and lipid screen-
ing. In a related study in children receiving AP treatment,
similarly low metabolic monitoring rates were found (184).
The MetS remains, thus, widely underdiagnosed and under-
treated among patients with SMI.

diabetes mellitus

Three to four percent of the world’s population have DM,
which leads to a markedly increased risk of blindness, renal
failure, amputation and cardiovascular disease, and reduces
life expectancy by 10 or more years. Currently, 70% of peo-
ple with DM live in developing countries, and while DM is
increasing across the world, its greatest increase will be in
these countries. By 2030 more than 80% of people with DM
will live in developing countries (195).

There are well-defined biological and behavioral risk fac-
tors for type 2 DM (195). The most important of these are
overweight and obesity (RR: 4.10-17.5)(196), particularly
abdominal obesity, and physical inactivity (RR: 1.12-2.18)
(196-205). Other behavioral risk factors include certain di-
etary patterns (over and above any effect on obesity), such
as diets low in whole grains and other sources of fibre, as
well as smoking (206).

Identifying people at high risk of DM is important be-
cause it has been demonstrated that intensive interventions
in this group can reduce the incidence of DM. In individuals
at high risk, a combination of moderate weight loss, in-
creased physical activity and dietary advice can lead to a
60% reduction in DM incidence (207,208).

DM in SMI patients

Evidence suggests that the prevalence of DM in people
with schizophrenia as well as in people with bipolar disor-
der and schizoaffective disorder is 2-3 fold higher compared
with the general population (103,209-216). The risk of DM
in people with depression or depressive symptoms is 1.2-2.6
times higher compared to people without depression (217-
225).

The reason for the increased risk of DM in SMI patients
is multifactorial and includes genetic and lifestyle factors as
well as disease and treatment specific effects. An increase in
well-established DM risk factors in these patients partially
accounts for much of the increased risk (16,226). However,
additional factors (disease, treatment) are important as well,
and research suggests that, compared to the general popula-
tion, the prevalence of DM in schizophrenia patients is 4 to
5 times higher in different age groups (15-25: 2% vs. 0.4%;
25-35: 3.2% vs. 0.9%; 35-45: 6.1% vs. 1.1%; 45-55: 12.7%
vs. 2.4%; 44-65: 25% vs. 5.8%) (227).

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56 World Psychiatry 10:1 – February 2011

DM and psychotropic medications

Atypical AP seem to have a stronger diabetogenic risk
than conventional AP (96,228,229), the risk being 1.3 fold
higher in people with schizophrenia taking atypical AP com-
pared with those receiving conventional AP (230). However,
the risk of DM-related adverse events differs between atypi-

cal AP. Of the atypical AP, specifically olanzapine (231-234)
and clozapine (232,234,235) and, to a lesser extent, quetiap-
ine (236) and risperidone (237), are associated with an in-
creased risk of DM (80) in people who have schizophrenia
or bipolar disorder (238,239). A recent large-scale pharma-
coepidemiologic study (including 345,937 patients who pur-
chased antipsychotics and 1,426,488 unexposed individuals)

Table 4 Working definitions of the MetS (see 57,185-194)

Criteria WHO
(1998,1999)

EGIR
(1999)

NCEP ATP III
(2001,2004)

AACE/ACE
(2003)

IDF
(2005)

IDF & AHA/NHLBI
(2009)

Required factor IGT, IFG or DM type
2, and/or insulin

resistance

plus any 2 or more
of the following

Insulin resistance or
hyperinsulinemia

plus any 2 of the
following

None

but any 3 or more
of the following

At least one of the
specified risk

factors (e.g., obesity,
sedentary lifestyle,

age>40)

plus 2 or more
of the following

Central obesity

plus any 2 of the
following
None
but any 3 or more
of the following

Additional factors

Obesity Waist-to-hip ratio
>0.90 (men)

Waist-to-hip ratio
>0.85 (women)

and/or BMI>30 kg/m2

WC≥94 cm (men)
WC≥80 cm (women)

WC≥102 cm (men)
WC≥88 cm (women)

BMI>25 kg/m2 or
WC>102 cm (men)

WC>89 cm (women)
(10-15% lower for

non-Caucasians)

Elevated WC and
country-specific

definitions as defined
by the IDF and AHA/

NHLBI until more
data are available

Triglycerides

HDL – cholesterol

≥150 mg/dL (≥1.7
mmol/L)

and/or

<35 mg/dL (<0.9 mmol/L) (men)

<39 mg/dL (<1.0 mmol/L) (women)

>177 mg/dL (>2.0
mmol/L)

<40 mg/dL (<1.0 mmol/L)

(men and women)
or on dyslipidemia

Rx

≥150 mg/dL
(≥1.7 mmol/L)
or on elevated
triglycerides Rx

<40 mg/dL (<1.03 mmol/L)(men)

<50 mg/dL (<1.29 mmol/L) (women) or on reduced HDL-

cholesterol Rx

>150 mg/dL

<40 mg/dL (men) <50 mg/dL (women)

≥150 mg/dL
(≥1.7 mmol/L) or
on lipid abnorma-

lity Rx

< 40 mg/dL (<1.03 mmol/L)

(men)
<50 mg/dL

(<1.29 mmol/L) (women) or on lipid

abnormality Rx

≥150 mg/dL (≥1.7
mmol/L) (Rx for ele-
vated triglycerides is

an alternate indicator)

<40 mg/dL (<1.0 mmol/L)(men) <50 mg/dL

(<1.3 mmol/L)(women) (Rx for reduced

HDL-cholesterol is an
alternate indicator)

Blood pressure ≥160/90 mm Hg
(later modified as
≥140/90 mm Hg)

≥140/90 mm Hg
or on hypertension

Rx

≥130/85 mm Hg
or on hypertension

Rx

>130/85 mm Hg ≥130/85 mm Hg
or on

antihypertensive Rx

≥130/85 mm Hg
(antihypertensive Rx in

a patient with a histo-
ry of hypertension is

an alternate indicator)

Glucose IGT, IGF (≥110 mg/dL)
(≥6.1 mmol/L),
or DM type 2

IGT or IFG
(≥110 mg/dL)
(≥6.1 mmol/L)
(but not DM)

≥110 mg/dL
(≥6.1 mmol/L)
(includes DM)

(later modified as
≥100 mg/dL) (≥5.6

mmol/L) or on
elevated glucose Rx

110-125 mg/dl ≥100 mg/dL (≥5.6
mmol/L) or pre-

viously diagnosed
type 2 DM

≥100 mg/dL
(≥5.6 mmol/L)
(Rx of elevated

glucose is an alternate
indicator)

Other Microalbuminuria
(urinary albumin

excretion rate
≥20 mg/min or albumin:

creatinine ratio
≥20 mg/g)

(later modified
as ≥30 mg/g)

WHO: World Health Organization; EGIR: European Group for the Study of Insulin Resistance; NCEP ATP III: National Cholesterol Education Program Expert
Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III); AACE/ACE: American Association of Clinical
Endocrinologists/American College of Endocrinology; IDF: International Diabetes Federation; AHA/NHLBI: American Heart Association/National Heart, Lung,
and Blood Institute; IGT: impaired glucose tolerance; IFG: impaired fasting glucose; DM: diabetes mellitus; BMI: body mass index; WC: waist circumference; Rx:
treatment; HDL: high-density lipoprotein.

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57World Psychiatry 10:1 – February 2011

found low to moderate, but significantly increased rates of
incident DM compared with the general population for clo-
zapine (RR=1.45), olanzapine (RR=1.29) and risperidone
(RR=1.23). Rates increased two or more times with ziprasi-
done and sertindole. Aripiprazole, amisulpride and quetiap-
ine did not have a significantly increased rate (240).

In the only study to date in first-episode patients, DM
development was promoted in patients with schizophrenia
by initial treatment with olanzapine (hazard ratio, HR=1.41)
and mid-potency conventional AP (HR=1.60), as well as by
current treatment with low-potency conventional AP (odds
ratio, OR=1.52), olanzapine (OR= 1.44) and clozapine
(OR=1.67). Current aripiprazole treatment reduced DM risk
(OR= 0.51) (241). An analysis of the FDA’s DM-related ad-
verse events database (ranging from new-onset hyperglyce-
mia to life-threatening ketoacidosis), found the following
adjusted reporting ratios for DM relative to all drugs and
events: olanzapine 9.6 (9.2-10.0); risperidone 3.8 (3.5-4.1);
quetiapine 3.5 (3.2-3.9); clozapine 3.1 (2.9-3.3); ziprasidone
2.4 (2.0-2.9); aripiprazole 2.4 (1.9-2.9); haloperidol 2.0 (1.7-
2.3) (242). However, a systematic review of 22 prospective,
randomized, controlled trials found no difference in the in-
cidence of glycaemic abnormalities between placebo co-
horts and AP medication cohorts, as well as no significant
difference between any of the AP medications studied in
terms of their association with glycaemic abnormalities
(243). Although the latter analysis was restricted to mostly
short-term trials, this inconsistency of findings suggests that
medication effects interact with patient, illness, cohort and
study-specific factors.

AD may also increase the risk of DM, probably partly due
to side effects such as sedation, increased appetite, and
weight gain (244-248). However, although increasing, spe-
cific data on the risk of DM associated with the use of AD
are sparse. Given the heterogeneity and small sample sizes
of the few currently available studies, it is unclear whether
or not specific AD themselves may increase the risk of DM.
Nevertheless, it seems that an increased risk of DM is associ-
ated with the concurrent use of tricyclic AD and serotonin

reuptake inhibitors (SSRIs) (OR=1.89) (249), the long-term
use of both tricyclic AD (incidence rate ratio, IRR=1.77) and
SSRIs (IRR=2.06) in at least moderate daily doses (250), as
well as the use of AD medication in high-risk patients (251).

Furthermore, although understudied, certain mood stabi-
lizers, especially valproate, have been associated with an
elevated risk for the development of insulin resistance
(252,253), conferring a risk for DM, which is possibly re-
lated to weight gain (254), and/or fatty liver infiltration
(255), but also to valproate itself (256).

Disparities in health care

There is evidence that diabetes patients with mental health
conditions are less likely to receive standard levels of diabe-
tes care (35,257,258). In the Clinical Antipsychotic Trials of
Intervention Effectiveness (CATIE) schizophrenia study,
non-treatment rate for DM was 45.3% (35). One study
(n=76,799), examining the impact of mental illness on DM
management, found the unadjusted OR to be 1.24 (1.22-
1.27) for no hemoglobin A(1c) testing, 1.25 (1.23-1.28) for no
low-density lipoprotein cholesterol testing, 1.05 (1.03-1.07)
for no eye examination, 1.32 (1.30-1.35) for poor glycemic
control, and 1.17 (1.15-1.20) for poor lipaemic control (257).
Despite clear guidance and a high prevalence of undiagnosed
DM, screening rates for metabolic abnormalities in people
with SMI remain low, which may lead to prolonged periods
of poor glycaemic control (259-263). Delayed diagnosis re-
sults in prolonged exposure to raised blood glucose levels,
which can, among other things, cause visual impairment and
blindness, damage to kidneys with the potential consequence
of renal failure, and nerve damage (264).

diabetic ketoacidosis

Although diabetic ketoacidosis (DKA), a potentially fatal
condition related to infection, trauma, myocardial infarction
or stroke (265), occurs most often in patients with type 1
DM, it may be the first obvious manifestation of type 2 DM.
Symptoms include: increased thirst and urination, nausea
and vomiting, abdominal pain, poor appetite, unintended
weight loss, lethargy, confusion and coma.

The incidence of DKA is nearly (266) or more (267) than
10-fold greater in those with schizophrenia compared to the
general population. Cases of DKA have been reported with
the atypical AP clozapine (235,268), olanzapine (233,269),
quetiapine (236), risperidone (237), aripiprazole (270-272)
and ziprasidone (242). However, not all atypical AP appear
to have the same propensity to cause this complication
(273). The incidence of DKA for each atypical AP over a
7-year period was as follows: clozapine, 2.2%; olanzapine,
0.8%; and risperidone, 0.2% (267). However, higher inci-
dence rates for clozapine and olanzapine can be due to re-
porting and detection biases (more DKA cases may be re-

Table 5 Approximate relative likelihood of metabolic distur-
bances with AP medication (172-175)

Medication MetS

Chlorpromazine
Clozapine

Olanzapine
Quetiapine
Amisulpride
Iloperidone
Risperidone
Sertindole
Asenapine

Aripiprazole
Haloperidol
Lurasidone

Perphenazine
Ziprasidone

High (?, limited data)
High
High

Moderate
Mild

Mild (?, limited data)
Mild
Mild

Low (?, limited data)
Low
Low

Low (?, limited data)
Low
Low

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58 World Psychiatry 10:1 – February 2011

ported for these agents since doctors in general are more
careful about clozapine and olanzapine and therefore detect
and report such cases with these agents more frequently).
Within the class of conventional AP, cases of DKA have
been reported with chlorpromazine (274,275), but no such
cases have been reported for other conventional AP. The
mortality of reported cases of DKA varies between 15.4%
and 48% (233,235-237), which is up to ten times higher than
the 4% rate in the general population (276).

cardiovascular diseases

The term cardiovascular diseases (CVD) refers to any dis-
ease that affects the cardiovascular system. Coronary heart
disease and cerebrovascular disease are the principal com-
ponents of CVD and make the largest contribution to its
global burden (277,278). CVD accounts for 17.1 million or
29% of total worldwide deaths (279). While there are down-
ward trends in CVD mortality in most developed countries
due to successful secondary prevention, the mortality rates
in developing countries are rising (280). A staggering 82%
of worldwide CVD deaths take place in developing coun-
tries (279). Global trade and food market globalization have
led to a transition toward a diet that is energy dense and
nutrient poor. The resultant increases in obesity are accom-
panied by physical inactivity. In addition, tobacco consump-
tion is increasing at alarming rates in developing countries
(281). Finally, people in developing countries have less ac-
cess to effective and equitable health care services which
respond to their needs (279).

The conventional risk factors for CVD are smoking, obe-
sity, hypertension, raised blood cholesterol and DM. Many
other factors increase the risk of CVD, including unhealthy
diet, physical inactivity and low socioeconomic status (282,
283). Table 6 shows the summary prevalence of CVD risk
factors in developed and developing countries, based on the
World Health Organization (WHO) comparative risk factor
survey data. The risk of late detection of CVD risk factors
and consequent worse health outcomes is higher among
people from low socioeconomic groups due to poor access

to health care. This gradient exists in both rich and poor
countries (284,285).

CVD in SMI patients

The preponderance of evidence suggests that patients
with major depression, bipolar disorder and schizophrenia
are at significantly higher risk for cardiovascular morbidity
and mortality than are their counterparts in the general pop-
ulation (2,9,11,23,28,29,287-295). Moreover, in SMI pa-
tients, CVD is the commonest cause of death (2,25,33,
218,289,290,296-300).

The prevalence of CVD in people with schizophrenia and
bipolar disorder is approximately 2- to 3-fold increased, par-
ticularly in younger individuals (5,16,25,29,297,299,301,302).
A recent review of all published larger (>100 patients) studies
between 1959 and 2007 found the mortality risk for CVD to
be 35% to 250% higher among persons with bipolar spectrum
disorders compared to the general population (6). People with
depression have a 50% greater risk of CVD (22). Besides the
fact that depression is an independent risk factor for aggravat-
ing morbidity and mortality in coronary heart disease (303),
the main factor mediating the link between depression and
coronary events seems to be lack of physical activity (304).

The aetiology of this excess CVD is multifactorial and
likely includes genetic and lifestyle factors as well as disease
specific and treatment effects (16). People with SMI have
significantly higher rates of several of the modifiable risk
factors compared with controls. They are more likely to be
overweight or obese, to have DM, hypertension, or dyslip-
idemia and to smoke (25,95,229,178,305-308). The excess
CVD mortality associated with schizophrenia and bipolar
disorder is widely attributed to the 1-5 fold RR of the modi-
fiable CVD risk factors in this group of patients compared
with the general population (Table 7).

Coronary heart disease in SMI patients

Coronary heart disease refers to the failure of coronary

Table 6 Economic development and risk factors for cardiovascular disease in WHO subregions (see 280,286)

Poorest countries in Africa, America,
South-East Asia, Middle East

Better-off countries in America, Europe,
South-East Asia, Middle East, Western Pacific

Developed countries of Europe,
North America, Western Pacific

Mean body mass index 19.9 – 26.0 22.9 – 26.0 23.4 – 26.9

Physical inactivity (% with
no physical activity)

11 – 23 15 – 24 17 – 20

Low fruit and vegetable
intake: average intake

per day (grams)

240 – 360 190 – 350 290 – 450

Blood pressure (mean
systolic pressure mmHg)

125 – 133 124 – 133 127 – 138

Mean cholesterol (mmol/L) 4.8 – 5.1 4.6 – 5.8 5.1 – 6.0

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59World Psychiatry 10:1 – February 2011

circulation to supply adequate circulation to cardiac muscle
and surrounding tissue, a phenomenon that can result in a
myocardial infarction. During the 21st century, coronary
heart disease will remain the leading cause of death in de-
veloped countries, will become the leading cause of death in
developing countries, and therefore, will emerge as the lead-
ing cause of death in the world (25). The risk of coronary
heart disease seems to be 2-3.6-fold higher in patients with
schizophrenia (25,299). One large study found that the ten-
year coronary heart disease risk was significantly elevated in
male (9.4% vs. 7.0%) and female (6.3% vs. 4.2%) patients
who have schizophrenia compared to controls (p=0.0001)
(101). People with bipolar disorder have a 2.1 fold higher
risk (299). The RR of myocardial infarction in people with
major affective disorder was found to be 1.7 to 4.5 (310-313).
Depression is an even stronger risk factor for cardiac events
in patients with established coronary heart disease: prospec-
tive studies have shown that depression increases the risk of
death or nonfatal cardiac events approximately 2.5-fold in
patients with coronary heart disease (314).

Cerebrovascular disease in SMI patients

Cerebrovascular disease is a group of brain dysfunctions
related to disease of the blood vessels supplying the brain,
and can result in a cerebrovascular accident or stroke. The
risk of cerebrovascular accident seems to be 1.5 to 2.9 fold
higher in patients with schizophrenia (40,41,299,302,315,
316) and 2.1 to 3.3 fold higher in patients with bipolar dis-
order (299,317). The RR of developing cerebrovascular ac-
cident for patients with major affective disorder was found
to be 1.22 to 2.6 (318,319). Obesity, DM, CVD as well as
depressive symptoms are recognized as risk factors for cere-
brovascular accident (317,320).

CVD and psychotropics

In addition to weight gain and obesity related mecha-
nisms, there appears to be a direct effect of AP that contrib-
utes to the worsening of CVD risk (96,97,121,321). A recent
publication demonstrated that atypical AP D

2
antagonism

could have a direct effect on the development of insulin re-
sistance (322). Evidence was found that higher AP doses
predicted greater risk of mortality from coronary heart dis-
ease and cerebrovascular accident (299).

Overall, SSRIs appear safe in cardiac populations, with
few cardiac side effects (287,311), while studies have found
an increased risk of adverse cardiac events in patients using
tricyclic AD (311,323,324). Tricyclic AD commonly increase
heart rate by over 10%, induce orthostatic hypotension, slow
cardiac conduction, and increase the risk of arrhythmias. Al-
though it can have some cardiac conduction effects, in gen-
eral, lithium can be safely used in cardiac patients (287).

Sudden cardiac death and psychotropics

Patients with schizophrenia have been reported to be three
times as likely to experience sudden cardiac death as indi-
viduals from the general population (325,326). In patients
with AP monotherapy, a similar dose-related increased risk
of sudden cardiac death was found for both conventional and
atypical AP, with adjusted RRs of 1.31 vs. 1.59 (low dose,
chlorpromazine equivalents <100mg), 2.01 vs. 2.13 (moder- ate dose, chlorpromazine equivalents 100-299mg) and 2.42 vs. 2.86 (high dose, chlorpromazine equivalents ≥300mg), respectively (327). In large epidemiological studies, a dose dependent increased risk of sudden cardiac death has been identified in current users of tricyclic AD (328).

There is a consensus that QTc values >500 msec, or an
absolute increase of 60 msec compared with drug-free base-
line, puts a patient at significant risk of torsade de pointes,
ventricular fibrillation and sudden cardiac death (94,329,
330). Most AP and some AD may be associated with QTc
prolongation (331). Patients using AP have higher rates of
cardiac arrest or ventricular arrhythmias than controls, with
ratios ranging from 1.7 to 5.3 (332-335). AP associated with
a greater risk of QTc prolongation include pimozide, thio-
ridazine and mesoridazine among the conventional AP
(94,335,336) and sertindole and ziprasidone among the
atypical AP (94,337). However, the largest randomized study
to date (n=18,154) did not find a statistically significant dif-
ference in the risk of sudden cardiac death between ziprasi-
done and olanzapine treated patients with schizophrenia

Table 7 Estimated prevalence and relative risk (RR) of modifiable risk factors for cardiovascular disease in schizophrenia and bipolar
disorder compared to the general population (see 4,305,309)

Modifiable risk factors Schizophrenia Bipolar disorder

Prevalence (%) RR Prevalence (%) RR

Obesity
Smoking
Diabetes mellitus
Hypertension
Dyslipidemia
Metabolic syndrome

45-55
50-80
10-15
19-58
25-69
37-63

1.5-2
2-3
2-3
2-3
#5
2-3

21-49
54-68
8-17

35-61
23-38
30-49

1-2
2-3

1.5-3
2-3
#3
2-3

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60 World Psychiatry 10:1 – February 2011

(338,339). Similarly, another large randomized study
(n=9,858) observed no significant differences between
sertindole and risperidone recipients in cardiac events, in-
cluding arrhythmias, requiring hospitalization. However,
cardiac mortality in general was higher with sertindole
(337). These large randomized studies, which focused on a
low incidence serious side effect, suffer from the problem
that they did not enrich samples for cardiac risk, so that they
lack power and, possibly, generalizability. Cases of torsade
de pointes have been reported with thioridazine, haloperi-
dol, ziprasidone, olanzapine, and tricyclic AD. Although
SSRIs have been associated with QTc prolongation, no cases
of torsade de pointes have been reported with the use of
these agents. There are no reported cases of lithium-induced
torsade de pointes (328).

Disparities in health care

SMI patients have the highest CVD mortality but the least
chance of receiving many specialized interventions or circu-
latory medications. Evidence suggests that people with
schizophrenia are not being adequately screened and treat-
ed for dyslipidemia (up to 88% untreated) and hypertension
(up to 62% untreated) (35,306,340-343). The care of these
patients shows a significant deficit in the monitoring of cho-
lesterol values and the prescription of statins (25,35,40,344).
They also have low rates of surgical interventions, such as
stenting and coronary artery bypass grafting (40,41,291,
297,345). A poorer quality of medical care contributes to
excess mortality in older people with mental disorders after
heart failure (346). Another important barrier is the lack of
seeking medical care by SMI patients themselves, even dur-
ing acute cardiovascular syndromes (25).

Viral diseases

Patients with SMI are at increased risk for a variety of
chronic viral infections, of which the most serious are the
diseases associated with human immunodeficiency virus
(HIV) and hepatitis C virus.
HIV positivity

The prevalence of HIV positivity in people with SMI is
generally higher than in the general population, but varies
substantially (1.3-23.9%) (347-370). The high frequency of
substance abuse, sexual risk behaviors (e.g., sex without a
condom, trading sex for money and drugs), and a reduced
knowledge about HIV-related issues contribute to this high
HIV prevalence (364,371-376). Therefore, it is important
that patients with SMI are tested for HIV (377). However,
studies investigating HIV testing rates among individuals
with a SMI indicate that fewer than half of these patients
(percentages ranging from 17% to 47%) have been tested in
the past year (378-394).

Since many patients with SMI are exposed to atypical AP,
which have been associated with metabolic abnormalities,
and since patients infected with HIV and on highly active
antiretroviral therapy may also develop metabolic abnor-
malities, this group of patients is at particularly high risk for
developing MetS and ultimately CVD (395).

Hepatitis

Across different continents, markedly elevated rates of
hepatitis virus infection have been reported in persons with
SMI compared to the general population (364,396-403).
The largest study to date found prevalence rates of hepatitis
B virus (23.4%) and hepatitis C virus (19.6%) in SMI pa-
tients to be approximately 5 and 11 times the overall esti-
mated population rates for these infections. Overall, an es-
timated 20-25% of persons with SMI are infected with
hepatitis C virus (360,404-407).

The most common transmission routes for persons with
SMI are drug-use behaviors and sexual behaviors related to
drug use (404-406). Therefore, especially patients with SMI
and substance use disorders (including dependency) should
have routine screening and treatment for hepatitis C virus
infection to prevent associated morbidity and mortality
(400,407,408). Interventions exist that are specifically de-
signed to facilitate integrated infectious disease program-
ming in mental health settings for people with SMI and to
overcome provider- and consumer-level barriers at a modest
and specified cost (409). A recent study showed that the as-
signment of people with SMI to the “STIRR” (Screening,
Testing, Immunization, Risk reduction counseling, medical
treatment Referral) intervention had high levels (over 80%)
of participation and acceptance of core services (testing for
hepatitis C, immunization against hepatitis, knowledge
about hepatitis) (407).

respiratory tract diseases

Up until 50 years ago, respiratory diseases, such as pneu-
monia and tuberculosis, accounted for the majority of deaths
amongst people with SMI who lived in institutions (2). To-
day, respiratory diseases are still more prevalent in people
with SMI (8,410-417).

Tuberculosis

Studies consistently show a higher incidence of tubercu-
losis among patients with schizophrenia compared with the
general population (422-426). In some countries, tuberculo-
sis still occurs so frequently that mental hospitals have spe-
cial wards for people with both tuberculosis and schizophre-
nia (15). If untreated, up to 65% of people with active tuber-
culosis will die of the disease. However, chemotherapy is

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61World Psychiatry 10:1 – February 2011

effective and the vast majority of people with drug-suscepti-
ble forms of tuberculosis are cured if properly treated (427).

Pneumonia

A nationwide, population-based study found schizophre-
nia to be associated with a 1.37 times greater risk of acute
respiratory failure and a 1.34-fold greater risk of mechanical
ventilation (428). Filik et al (414) found that people with
SMI have a higher prevalence of angina and respiratory
symptoms and impaired lung function when compared with
the general population. Significant barriers to prompt and
appropriate medical care for pneumonia still persist for pa-
tients who have schizophrenia (428).

Chronic obstructive pulmonary disease

The prevalence of chronic obstructive pulmonary dis-
ease, i.e. chronic bronchitis and emphysema, is significantly
higher among those with SMI than comparison subjects
(429-433). In a study of 200 outpatients in the US, 15% of
those with schizophrenia and 25% of those with bipolar
disorder had chronic bronchitis, and 16% of people with
schizophrenia and 19% of people with bipolar disorder had
asthma. These rates were significantly higher than those of
the matched controls from the general population. The au-
thors also found that, even when smoking was controlled for
as a confounder, both people with schizophrenia and bipo-
lar disorder were more likely to suffer from emphysema
(430). Although the association remains unclear, a higher
incidence of chronic obstructive pulmonary disease in the
past two decades has been associated with the side effects of
phenothiazine conventional AP (434).

cancer

Cancer risk in SMI patients

Given that obesity and unhealthy lifestyle behaviors are
known risk factors for a number of cancer types (149,435-
438), one would expect to see higher cancer rates in patients
with SMI. However, studies exploring the relationship be-
tween SMI and all cancer types together have shown con-
flicting results (30,439). Some studies have demonstrated a
decreased cancer risk in schizophrenia (440-448). On the
other hand, other studies found an increased (9,21,28,449-
451) or no different (292,419,452,453) overall risk of cancer
in patients with schizophrenia compared to the general
population. In the population of bipolar spectrum disorders,
deaths from cancer are not higher (8,288,416,417,454-456)
or only slightly elevated (417,418,456) compared with the
general population, despite the higher number of risk factors
for cancer (such as obesity) in this population. This discrep-

ancy of results may be a result of various confounding fac-
tors that could artificially lower the rates of diagnosed and
reported cancer in SMI populations. For example, people
with SMI are less likely to receive routine cancer screening
(457-460). Furthermore, patients with SMI have a shorter
life expectancy, so they may die from cardiovascular reasons
before reaching the expected age of death from cancer (30).
Another tentative hypothesis is that AP have antitumour
properties (448) or that the disease itself has a possible pro-
tective effect, including a tumor suppressor gene or en-
hanced natural killer cell activity (461,462). Nevertheless, a
problem with most of the existing data base analyses is that
etiologically disparate cancer types were lumped together.
An important analysis of cause-specific excess deaths asso-
ciated with underweight, overweight, and obesity in the gen-
eral population found that obesity was associated with an
increased mortality from cancers considered obesity-related
but not with mortality from other cancers (463).

Cancer risk and psychotropics

Because of the possible, but still controversial, role of pro-
lactin in breast cancer, the assumption has been made that
exposure to prolactin-raising dopamine antagonists could
result in breast cancer. The current study database on AP
and breast cancer risk is very limited (464). The majority of
the studies in which the risk of breast cancer has been inves-
tigated in patients treated with conventional AP (465-468)
did not uncover an increased risk of breast cancer, an excep-
tion being the cohort study by Wang et al (469).

Musculoskeletal diseases

Osteoporosis in SMI patients

Schizophrenia, schizoaffective states, major depression
and bipolar disorder are known to be associated with low
bone mineral density (BMD) (470). In comparison with the
general population, untreated patients with schizophrenia
appear to have an increased risk of developing osteoporosis.
On the one hand, this is because of the disease itself, on the
other hand, because of risk factors related to their lifestyle
(e.g., smoking, reduced physical activity, alcohol abuse,
vitamin D and calcium deficiency, polydipsia) (470-476). Al-
though the association between depression and loss of BMD
has been reported inconsistently, most studies have found
low BMD in patients with depressive symptoms or major
depressive disorder (477-483). Two recent meta-analyses
confirmed that depression is associated with low BMD and
should be considered as an important risk factor for osteo-
porosis, although this increased risk may be mediated by AD
(484,485). However, physiologic changes and the adoption
of poor health behaviors are two prominent ways in which
depression is hypothesized to directly affect BMD (486).

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62 World Psychiatry 10:1 – February 2011

Osteoporosis and psychotropics

Although it has been suggested that raised prolactin lev-
els provoked by AP medication can lead to an increased
risk of osteoporosis in patients with schizophrenia (471,
487), clinical data implicating AP-induced hyperprolac-
tinemia as a possible major risk factor for bone loss are
limited and contradictory (488,489). Some studies (490-
493) found a relationship between the use of prolactin-rais-
ing medication and low BMD in patients with chronic
schizophrenia, while others (474,489,494-498) failed to
find a relationship between prolactin, AP and osteoporosis.
Nevertheless, the available data seem to indicate that hy-
perprolactinemia with associated hypogonadism may be a
risk factor (488), leading to bone mineral loss in women as
well as men (499).

The majority of studies directly examining the relation-
ship between AD and BMD in humans report that the use
of these medications is associated with low BMD (486).
However, this finding seems to be restricted to the SSRI
class of AD (500-502).

Data describing the epidemiology of osteoporotic fracture
and psychotropics in patients with SMI are limited. Regard-
ing AP, conflicting results exist (503). Some of these studies
have reported higher prevalence rates of osteoporotic frac-
tures in patients with chronic schizophrenia, entirely or
partly independent of the use of AP (504,505). Other studies
(506-510) have found significant increases (OR=1.2-2.6) in
the risk of fractures associated with AP. For AD, a dose-re-
sponse relationship was observed for fracture risk (504,508).
SSRIs seem to be associated with the highest adjusted odds
of osteoporotic fractures (OR=1.5) (504,505, 508). A meta-
analysis showed a 33% increased risk of fractures with SSRIs
compared to non-SSRI AD. The RR of fractures in this meta-
analysis was 1.60 for AD and 1.59 for AP (511). Although
lithium has a potentially negative impact on bone metabo-
lism (470), it is associated with lower fracture risk (OR=0.6)

and, thus, seems to be protective against fractures (504,505).

Urological, male/female genital diseases
and pregnancy complications

Sexual dysfunction in SMI patients

Sexual dysfunction in SMI patients has received little at-
tention from clinicians (512,513). This low awareness has a
significant negative impact on patients’ satisfaction with
treatment, adherence, quality of life and partner relation-
ships (450). Although there are relatively few systematic in-
vestigations concerning sexual disorders in schizophrenia
(514), sexual dysfunction in schizophrenia is, compared to
normal controls, estimated to be more frequent (515-519)
and to affect 30-80% of women and 45-80% of men (512,515,
520-523). This dysfunction can be secondary to the disease
itself and to comorbid physical disorders, or be an adverse

event of AP (520,524,525). Sexual dysfunction is also a com-
mon symptom of depression (526-530). Up to 70% of pa-
tients with depression may have sexual dysfunction (466).
Approximately 25% of patients with major depression may
experience problems with erection or lubrication (531).

Patients with SMI are likely to engage in high-risk sexual
behavior, putting them at risk of sexually transmitted dis-
eases. However, findings suggest that sexual health educa-
tion for these people tends to produce a reduction in sexual
risk behavior (532).

Sexual dysfunction and psychotropics

Psychotropic drugs are associated with sexual dysfunc-
tion (514). To date, only few studies (534-547) have directly
compared the sexual functioning associated with different
atypical AP. These studies suggest that the relative impact of
AP on sexual dysfunction can be summarized as: paliperi-
done = risperidone > haloperidol > olanzapine ≥ ziprasi-
done > clozapine ≥ quetiapine > aripiprazole (503,520,536).
Conventional AP cause less sexual dysfunction than risper-
idone but more than the other novel AP (520,522).

AD therapy (except for mirtazapine, nefazodone and bu-
propion) frequently induces or exacerbates sexual dysfunc-
tion, which occurs in approximately 50% of patients (548).
Although sexual dysfunction has been reported with all
classes of AD (549), SSRIs are associated with higher rates
(550-552). Published studies suggest that between 30% and
60% of SSRI-treated patients may experience some form of
treatment-induced sexual dysfunction (553,554).

Pregnancy complications, SMI and psychotropics

There is an extensive literature reporting an increased oc-
currence of obstetric complications among women who
have schizophrenia (15). During pregnancy, it is important
to evaluate the safety of psychotropic drugs. Most women
with a SMI cannot stop taking their medication, as this
would interfere with their activities of daily living, especially
taking care of an infant (555). There is a paucity of informa-
tion, with a lack of large, well designed, prospective com-
parative studies during pregnancy. However, no definitive
association has been found up to now between the use of AP
during pregnancy and an increased risk of birth defects or
other adverse outcomes (555,556). Among AD, SSRIs and,
possibly, serotonin and noradrenaline reuptake inhibitors
(SNRIs) have been associated with preterm labor, respira-
tory distress, serotonin rebound syndrome, pulmonary hy-
pertension and feeding problems in the neonate (557-559).
Furthermore, a number of mood stabilizers have been as-
sociated with fetal malformations, including carbamazepine
and valproate (560,561). Current evidence seems to suggest
that Fallot’s tetralogy is not considerably elevated with lith-
ium compared to the rate in the general population (560).

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63World Psychiatry 10:1 – February 2011

stomatognathic diseases

Oral health in SMI patients

Dental health has been consistently found to be poor in
people with SMI (562-573). A study using an overall dental
status index (DMF-T) in chronically hospitalized patients
with mental disorders (mostly schizophrenia) found a mean
score of 26.74 (out of a possible 32), one of the highest re-
ported in the literature (571). According to another study,
only 42% of patients with schizophrenia brush their teeth
regularly (at least twice a day) (573). This poor dental health
leads to functional difficulties. In one large study (n=4,769),
34.1% of the patients with SMI reported that oral health
problems made it difficult for them to eat (572).

Factors which influence oral health include: type, sever-
ity, and stage of mental illness; mood, motivation and self-
esteem; lack of perception of oral health problems; habits,
lifestyle (e.g., smoking), and ability to sustain self-care and
dental attendance; socio-economic factors; effects of medi-
cation (dry mouth, carbohydrate craving); and attitudes and
knowledge of dental health teams concerning mental health
problems (569,574).

Oral health and psychotropics

AP, AD and mood stabilizers all cause xerostomia (575).
This reduction in salivary flow changes the oral environment
and leads to caries, gingivitis and periodontal disease (576).

Disparities in health care

Oral health status is a frequently disregarded health issue
among SMI patients (498), with low rates of dental examina-
tion within the past 12 months (569,577-579). In one study
of a mixed psychiatric population, 15% had not been to a
dentist in the last 2 years (579), while in another only 31% of
schizophrenia patients had visited a dentist during a three
year period (577). In the latter study, non-adherence to an-
nual dental visits was predicted by substance abuse diagnosis,
involuntary legal status, living in an institution, admission to
a psychiatric facility for a minimum of 30 days, and male
gender, whereas clozapine treatment, novel AP treatment, at
least monthly outpatient visits, and age > 50 years were as-
sociated with a lower risk for inappropriate dental care.

Taken together, these findings confirm the urgent need for
an intervention program to improve oral health outcomes
among patients with SMI, by facilitating access to dental
care and addressing modifiable factors such as smoking and
medication side effects (571,572), especially because oral
diseases are preventable and social inequity in oral health
avoidable (580). Moreover, improving dental health status
and care are relevant, as poor dental status is associated with
endocarditis and reduces social and work opportunities.

other physical health conditions in people with sMI

This review is by no means exhaustive. We speculate that
perhaps most medical illnesses occur with greater frequency
in SMI, which in itself serves as a vulnerability factor (587).

Haematological diseases, which may in themselves be
primary problems in patients with SMI, have frequently
been described in the literature as potential serious compli-
cations of psychotropic medications. AP (e.g., clozapine,
haloperidol, olanzapine, phenothiazines, quetiapine, ris-
peridone, ziprasidone), AD (e.g., amitriptyline, clomip-
ramine, imipramine) as well as lithium are associated with
blood dyscrasias. Clozapine (approximately 0.8%) and phe-
nothiazines (chlorpromazine approximately 0.13%) are the
most common causes of drug-related neutropenia/agranu-
locytosis. AD are rarely associated with agranulocytosis.
With appropriate management, the mortality from drug-in-
duced agranulocytosis in Western countries is 5-10% (be-
fore the use of antibiotics this percentage was 80%) (582).

Some physical conditions, although important, are rarely
studied, underreported and not systematically assessed. Al-
though a common side effect of AP that can be severe and
lead to serious consequences and even death, constipation
has been given relatively little attention. The most reported
complications of this physical condition are paralytic ileus,
faecal impaction, bowel obstruction and intestine/bowel
perforations. Constipation has most widely been reported
for clozapine, although it can be associated with other AP
as well. Prevalence of constipation in randomized controlled
trials for different AP is: zotepine 39.6%, clozapine 21.3%,
haloperidol 14.6% and risperidone 12% (583). Next to med-
ication effects, lifestyle and diet factors can contribute to the
occurrence of constipation in people with SMI (sedentary
life, low physical activity, diet low in fibre, limited fluid in-
take) (584). Clinicians should actively and systematically
screen and monitor symptoms and possible complications
of constipation (585-588).

conclUsIons

In summary, many physical disorders have been identified
that are more prevalent in individuals with SMI. In addition
to modifiable lifestyle factors and psychotropic medication
side effects, poorer access to and quality of received health
care remain addressable problems for patients with SMI.
Greater individual and system level attention to these physi-
cal disorders that can worsen psychiatric stability, treatment
adherence, and life expectancy as well as quality of life will
improve outcomes of these generally disadvantaged popula-
tions worldwide. The barriers to somatic monitoring and
interventions in persons with SMI will be summarized in the
second part of this educational module, where monitoring
and treatment guidelines as well as recommendations at the
system level (state and health care institutions) and individ-
ual level (clinicians, patients, family) will be provided.

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64 World Psychiatry 10:1 – February 2011

acknowledgements

The production of this educational module is part of the
WPA Action Plan 2008-2011 and has been supported by the
Lugli Foundation, the Italian Society of Biological Psychia-
try, Pfizer and Bristol Myers Squibb.

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ARTICLE

Full text free online at nps.org.au/australianprescriber

Switching and stopping antidepressants

SUMMARY
Switching from one antidepressant to another is frequently indicated due to an inadequate
treatment response or unacceptable adverse effects. All antidepressant switches must be carried
out cautiously and under close observation.

Conservative switching strategies involve gradually tapering the first antidepressant followed by
an adequate washout period before the new antidepressant is started. This can take a long time
and include periods of no treatment with the risk of potentially life-threatening exacerbations
of illness.

Clinical expertise is needed for more rapid or cross-taper switching as drug toxicity, including
serotonin syndrome, may result from inappropriate co-administration of antidepressants. Some
antidepressants must not be combined.

Antidepressants can cause withdrawal syndromes if discontinued abruptly after prolonged use.
Relapse and exacerbation of depression can also occur. Gradual dose reduction over days to
weeks reduces the risk and severity of complications.

antidepressants soon after starting and many more
only partially adhere to treatment.6

Withdrawing antidepressants
If used for longer than six weeks, all antidepressants
have the potential to cause withdrawal syndromes if
they are stopped or rapidly reduced (with the possible
exception of agomelatine). As a result many patients
believe that antidepressants are addictive. This is not
the case as abusive and compulsive use, tolerance and
drug seeking do not occur with antidepressant drugs.
Withdrawal syndromes occur with many drugs (such
as corticosteroids) when used long term.

The usual recommended period for antidepressant
dose reduction is a minimum of four weeks.2 However,
abrupt cessation may at times be unavoidable on
clinical grounds. The time frame for dose reduction
also depends on individual risk for withdrawal
symptoms, patient preference and experience during
withdrawal, and drug characteristics such as half-life
(Table 1).

Previous withdrawal symptoms and anxiety when
starting antidepressant treatment are predictors
of future discontinuation problems. Some patients
experience little discomfort despite abrupt cessation,
while others are severely affected. In a minority,
withdrawal symptoms are not diminished by
extending the duration of dose taper. These patients
may prefer rapid cessation and a briefer withdrawal
period. Many will not experience symptoms in the
early part of withdrawal (which could proceed
more rapidly) but develop severe symptoms in the

Introduction
Antidepressant drugs are indicated for the treatment
of depression, anxiety disorders (including panic and
social phobia), obsessive compulsive disorder and
post-traumatic stress disorder. There are over 20
antidepressants currently available in Australia. These
can be divided into 13 clinically relevant groups, which
differ substantially in their pharmacodynamic and
pharmacokinetic characteristics.

Up to two-thirds of patients with major depression
fail to respond to their first antidepressant drug. After
assuring correct diagnosis, optimal dose, duration and
adherence to treatment, a change of antidepressant
drug is indicated.1 A patient is unlikely to respond if
there has been no improvement after three to four
weeks on an adequate dose of antidepressant.2
About a quarter of patients switched to a second
antidepressant can be expected to achieve remission.3
There is no evidence that switching between classes
of antidepressants is more effective than switching
within a class.4 Unacceptable adverse effects from
antidepressants, such as sexual dysfunction and
weight gain, may also necessitate a change of
therapy.5 Switching from one antidepressant to
another is a common clinical challenge.

Withdrawal of an antidepressant is also indicated after
an episode of depression has been adequately treated
– usually six to nine months after recovery from a
single episode. Serious physical illness, pregnancy
and surgery may also be reasons for stopping
antidepressant therapy. Up to a third of patients stop

Nicholas Keks
Director1

Adjunct professor2

Judy Hope
Deputy director1

Senior lecturer2

Simone Keogh
Psychiatrist and senior
fellow1

1 Centre for Mental Health
Education and Research
Delmont Private Hospital
2 Monash University
Melbourne

Keywords
antidepressant, drug
interaction, drug
withdrawal, serotonin
syndrome

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austprescr.2016.039

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first antidepressant to minimise withdrawal symptoms
then start a washout period equivalent to five half-
lives of the drug (Table 1). This does not apply to
irreversible monoamine oxidase inhibitors where a
specified long period of washout is mandatory (see
Table 3). Five half-lives equates to about five days
for most SSRIs except fluoxetine, which can still be
significantly active five or more weeks after cessation.
The second antidepressant is then introduced
according to the starting dose recommendations.

later stages (when dose reduction may need to be
more gradual).

Withdrawal symptoms
Withdrawal symptoms generally begin within
hours to days of dose reduction, depending on the
characteristics of the particular drug.7 Withdrawing
selective serotonin reuptake inhibitors (SSRIs) and
serotonin noradrenaline reuptake inhibitors (SNRIs)
tends to cause flu-like symptoms, nausea, lethargy,
dizziness, ataxia, ‘electric shock’ sensations, anxiety,
irritability, insomnia and vivid dreams. The symptoms
can be extremely disabling for some patients.

Venlafaxine is associated with the most severe
withdrawal effects. Paroxetine is also troublesome
while fluoxetine rarely causes withdrawal symptoms
(especially if the dose is under 40 mg) due to the long
half-life of the parent drug and its active metabolite
(about 7 days). Withdrawal of tricyclic antidepressants
can cause nausea, headache, abdominal pain,
diarrhoea, lethargy, anxiety, insomnia and vivid
dreams. It is unlikely that withdrawal symptoms will
occur after cessation of low-dose tricyclics used in
pain treatment. Withdrawing irreversible monoamine
oxidase inhibitors such as tranylcypromine is
particularly troublesome. It often causes agitation,
irritability, mood disorders, dreams, cognitive
impairment and occasionally psychosis and delirium.

Relapse and exacerbation
Stopping antidepressants can also result in relapse
or exacerbation of the psychiatric illness. Relapse
of depressive symptoms (including suicidal ideation
and self-harm) and recurrence of panic attacks and
severe anxiety can all occur with dose reduction
and cessation. Such exacerbations can cause life-
threatening behaviours in high-risk patients, and
antidepressant withdrawal must be a carefully
considered decision made by the well-informed
patient, often their family, and the prescriber. Avoid
stopping an antidepressant abruptly – withdrawal
over weeks to months (if possible) reduces the risk
of relapse.2

Switching strategies
A number of strategies are available for switching
between antidepressants (Table 2).6,8 Close
clinical observation and caution is required with
all approaches, as some patients may respond
idiosyncratically and serious complications can
occur. Individual patient factors and illness factors
may require considerable modification of a
switching strategy.

The most conservative strategy, with the lowest risk of
drug interactions, is to gradually taper the dose of the

Table 1 Approximate half-lives of
antidepressants

Antidepressant Approximate half-life
(days)

citalopram 1.5

escitalopram 1.5

paroxetine 1.0

sertraline 1.1–1.3

fluoxetine 4–16*

fluvoxamine 0.6

vortioxetine 2.4–2.8

agomelatine 0.04–0.08

desvenlafaxine 0.4

duloxetine 0.5

venlafaxine 0.6†

mianserin 0.9–2.5

mirtazepine 0.8–1.6‡

reboxetine 0.5

amitriptyline 0.2–1.9

imipramine 0.2–1.3

nortriptyline 0.8–2.3

doxepin 0.4–1.0

dothiepin 2.1

trimipramine 0.6–1.6

clomipramine 0.6–2.5

moclobemide 0.08

phenelzine see below§

tranylcypromine see below§

* fluoxetine plus active metabolite norfluoxetine
† venlafaxine plus active metabolite des

venlafaxine

‡ a longer half-life (up to 65 hours) has occasionally

been recorded and a shorter half-life is sometimes
seen in young men

§ biological activity persists for 14–21 days

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Switching and stopping antidepressants

there will be a considerable risk of withdrawal
symptoms and drug interactions. A cross-taper
strategy, where the first antidepressant dose is
reduced while the second antidepressant is introduced
at a low dose and gradually increased, can be done
safely with only some antidepressants (Table 3).

Switching between specific
antidepressants
Table 3 lists generalised guidelines for switching
patients from one antidepressant to another.2, 8-10 The
recommendations are applicable to any switching
strategy. Circumstances where only a conservative
strategy can be used are identified. Table 3 also states
when antidepressants should not be co-administered
or tapered at the same time.

Serotonin syndrome
As many antidepressants have serotonergic activity,
serotonin syndrome can occur during antidepressant
switching. While the syndrome may cause mild

The dose is usually tapered over four weeks, similar
to the minimum period required for antidepressant
discontinuation. However, the time frame may need to
be modified depending on patient factors.

As the conservative switch can take quite a long time
and usually includes at least several days where the
patient is not on an antidepressant, a compromise
strategy is the moderate switch. Here the washout
period can generally be shortened to about two days.
The risk of drug interactions is increased with this
approach, but is still quite low. The conservative and
moderate switch techniques are both suitable for
general practice.

Direct and cross-taper switch methods can also be
used but considerable expertise is necessary (Table 2).
Some patients will require admission to hospital. A
direct switch – one drug is stopped and another drug
is commenced the next day at the usual therapeutic
dose – can be used when switching between some
SSRIs, SNRIs and tricyclic antidepressants. However,

Table 2 Techniques for switching from one antidepressant to another 6

Method Comment

Conservative switch:

• the first antidepressant is gradually reduced and stopped

• there follows a drug-free washout interval of five half-lives
of the first antidepressant

• the new antidepressant is started according to its dose
recommendation

Most appropriate for general practice. The risk of drug
interactions is very low but discontinuation symptoms
may occur.

Moderate switch:

• the first antidepressant is gradually reduced and stopped

• there follows a drug-free washout interval of 2–4 days

• the new antidepressant is started at a low dose

Also recommended for use in general practice. The risk
of drug interactions is low but discontinuation symptoms
may occur.

Direct switch:

• the first antidepressant is stopped

• the second antidepressant is started the next day at the
usual therapeutic dose

Quick and simple but discontinuation symptoms are likely
depending on the second antidepressant. The risk of
drug interactions is substantial, depending on the second
antidepressant. Method requires clinical expertise and is
only feasible in selected instances, such as swapping from
one short half-life SSRI to another.

Cross-taper switch:

• the first antidepressant is gradually reduced and stopped

• the second antidepressant is introduced at a low dose at
some stage during the reduction of the first antidepressant,
so that the patient is taking both antidepressants
simultaneously

• the dose of the second antidepressant is increased to
the therapeutic dose when the first antidepressant has
been stopped

Frequently used for patients with high risk from illness
relapse but there is risk of drug interactions and increased
adverse effects from combined medications. Only feasible
in selected instances. Requires clinical expertise.

Note: Above strategies do not apply to monamine oxidase inhibitors, for which strict recommendations must be followed
(Table 3)

SSRI selective serotonin reuptake inhibitor

Adapted from reference 6

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tricyclic antidepressant due to inhibition of tricyclic
antidepressant metabolism by fluoxetine. Early signs
of tricyclic antidepressant toxicity include drowsiness,
tachycardia and postural hypotension.

When changing from irreversible monoamine oxidase
inhibitors (phenelzine and tranylcypromine) to all
other antidepressants, with the possible exception of
agomelatine, an adequate washout of two to three
weeks is mandatory.

Conclusion

Switching antidepressants involves drug cessation,
which may cause withdrawal symptoms and relapse
or exacerbation of the psychiatric illness. Gradual
antidepressant withdrawal reduces the risk of
complications. If the washout period is not long
enough (defined by half-life of the drug), introducing
a new antidepressant can cause drug interactions
leading to toxicity, particularly serotonin syndrome.
Switching from one antidepressant to another
requires careful observation and caution.

Conflict of interest: none declared

symptoms such as nervousness, agitation, tremor,
diaphoresis, shivering, mydriasis, hyperreflexia
and diarrhoea, in more severe cases tachycardia,
hyperthermia, hypertension, myoclonus, muscular
rigidity and delirium can occur. Convulsions, organ
system failure and death may follow. Prevention
through minimising interactions between potent
serotonergic drugs is critical.11

The only significant interaction for agomelatine is
with fluvoxamine (Table 3). Vortioxetine (an SSRI with
possible other serotonergic effects) can interact with
a variety of antidepressants. Caution is required for
switching and the prescriber should consult relevant
drug information before proceeding. The same
caution applies to duloxetine (Table 3).

Fluoxetine is a particular challenge for switching
because of its long half-life. Serotonin syndrome can
occur if clomipramine, fluvoxamine or monoamine
oxidase inhibitors are introduced before an adequate
washout of fluoxetine, which can take five or more
weeks. Tricyclic antidepressants can be introduced
at a low dose after fluoxetine withdrawal. However,
the low dose needs to be continued for several
weeks to avoid cardiotoxic plasma concentrations of

Fava GA, Gatti A, Belaise C, Guidi J, Offidani E. Withdrawal
symptoms after selective serotonin reuptake inhibitor
discontinuation: a systematic review. Psychother Psychosom
2015;84:72-81. http://dx.doi.org/10.1159/000370338

FURTHER READING

1. Little A. Treatment-resistant depression. Am Fam Physician
2009;80:167-72.

2. Taylor D, Paton C, Kapur S, editors. The Maudsley prescribing
guidelines in psychiatry. 11th ed. London: Wiley Blackwell; 2015.

3. Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA,
Stewart JW, Warden D, et al. Acute and longer-term
outcomes in depressed outpatients requiring one or
several treatment steps: a STAR*D report. Am J Psychiatry
2006;163:1905-17. http://dx.doi.org/10.1176/ajp.2006.163.11.1905

4. Souery D, Serretti A, Calati R, Oswald P, Massat I,
Konstantinidis A, et al. Switching antidepressant class does
not improve response or remission in treatment-resistant
depression. J Clin Psychopharmacol 2011;31:512-6.
http://dx.doi.org/10.1097/JCP.0b013e3182228619

5. Keks NA, Hope J, Culhane C. Management of antidepressant-
induced sexual dysfunction. Australas Psychiatry
2014;22:525-8. http://dx.doi.org/10.1177/1039856214556323

6. Jefferson JW. Strategies for switching antidepressants
to achieve maximum efficacy. J Clin Psychiatry
2008;69 Suppl E1:14-8.

7. Schweitzer I, Maguire K. Stopping antidepressants.
Aust Prescr 2001;24:13-5. http://dx.doi.org/10.18773/
austprescr.2001.008

8. Luft B. Antidepressant switching strategies. Graylands
Hospital Drug Bulletin 2013;20:1-4.

9. Psychotropic Expert Group. Therapeutic Guidelines:
psychotropic. Version 7. Melbourne: Therapeutic Guidelines
Limited; 2013.

10. Procyshyn RM, Bezchlibnyk-Butler KZ, Jeffries JJ, editors.
Clinical handbook of psychotropic drugs. 21st ed. Boston:
Hogrefe Publishing; 2015.

11. Buckley NA, Dawson AH, Isbister GK. Serotonin syndrome.
BMJ 2014;348:g1626. http://dx.doi.org/10.1136/bmj.g1626

REFERENCES

http://www.nps.org.au/australianprescriber

http://dx.doi.org/10.1159/000370338

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=19621857&dopt=Abstract

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=19621857&dopt=Abstract

http://dx.doi.org/10.1176/ajp.2006.163.11.1905

http://dx.doi.org/10.1097/JCP.0b013e3182228619

http://dx.doi.org/10.1177/1039856214556323

http://www.ncbi.nlm.nih.gov/pubmed/18494539

http://www.ncbi.nlm.nih.gov/pubmed/18494539

http://www.ncbi.nlm.nih.gov/pubmed/18494539

http://dx.doi.org/10.18773/austprescr.2001.008

http://dx.doi.org/10.18773/austprescr.2001.008

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Switching and stopping antidepressants

Table 3 Guidelines for switching between specific antidepressants 2,8-10

TO→

↓FROM

citalopram

escitalopram

paroxetine

sertraline

(SSRIs)

fluoxetine fluvoxamine vortioxetine agomelatine

desvenlafaxine

duloxetine

venlafaxine

(SNRIs)

citalopram
escitalopram
paroxetine
sertraline
(SSRIs)

taper drug, start
alternative SSRI
at low dose*

taper and stop
drug, then start
fluoxetine at
10 mg§

taper and stop
drug, then start
fluvoxamine at
50 mg§

taper drug, start
vortioxetine at
5 mg*

taper drug, start
agomelatine*

taper drug, then
start SNRI at low
dose*

fluoxetine stop fluoxetine
(or taper if dose
>40 mg/day),
wait 7 days for
washout, then
start above SSRI
at low dose†§

stop fluoxetine
(or taper if dose
>40 mg/day),
wait 14 days for
washout, then
start fluvoxamine
at 50 mg†§

stop fluoxetine
(or taper if dose
>40 mg/day),
wait 7 days for
washout, then
start vortioxetine
at 5 mg†§

stop fluoxetine
(or taper if dose
>40 mg/day),
start agomelatine

taper and stop
fluoxetine,
wait 7 days for
washout, then
start SNRI at low
dose†§

fluvoxamine taper and stop
fluvoxamine, then
start above SSRI
at low dose§

taper and stop
fluvoxamine, then
start fluoxetine at
10 mg§

taper and stop
fluvoxamine, start
vortioxetine at
5 mg§

taper and stop
fluvoxamine,
wait 7 days
for washout,
then start
agomelatine§

taper and stop
fluvoxamine, then
start SNRI at low
dose§

vortioxetine taper
vortioxetine, start
above SSRI at low
dose*

taper and stop
vortioxetine,
start fluoxetine at
10 mg§

taper and stop
vortioxetine, start
fluvoxamine at
50 mg§

taper
vortioxetine, start
agomelatine at
25 mg*

taper
vortioxetine, start
SNRI at low dose*

agomelatine stop agomelatine,
then start above
SSRI

stop agomelatine,
then start
fluoxetine

stop agomelatine,
then start
fluvoxamine*

stop agomelatine,
then start
vortioxetine

stop agomelatine,
then start SNRI

desvenlafaxine
duloxetine
venlafaxine
(SNRIs)

taper SNRI, start
above SSRI at low
dose*

taper and stop
SNRI, start
fluoxetine at
10 mg§

taper and stop
SNRI, start
fluvoxamine at
50 mg§

taper SNRI, start
vortioxetine at
5 mg*

taper SNRI, start
agomelatine*

taper SNRI, start
alternative SNRI
at low dose*

mianserin

mirtazepine

taper drug, start
above SSRI*

taper drug, start
fluoxetine*

taper drug, start
fluvoxamine*

taper drug, start
vortioxetine*

taper drug, start
agomelatine*

taper drug, start
SNRI*

reboxetine taper reboxetine,
start above SSRI*

taper reboxetine,
start fluoxetine*

taper reboxetine,
start fluvoxamine
at 50 mg*

taper reboxetine,
start vortioxetine
at 5 mg*

taper reboxetine,
start agomelatine*

taper reboxetine,
start SNRI at low
dose*

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mianserin

mirtazapine

reboxetine

amitriptyline

imipramine

nortriptyline

doxepin

dothiepin

trimipramine

(TCAs)

clomipramine moclobemide

phenelzine

tranylcypromine

(MAOIs)

taper drug, then start
above drug at low
dose*

taper drug, start
reboxetine*

taper SSRI, start
above drug at
low dose (usually
25 mg)*

taper and stop
drug, then start
clomipramine at
25 mg§

taper and stop drug
for 7 days washout
before starting
moclobemide at
low dose§

taper and stop drug
for 7 days washout
before starting MAOI
at low dose§

stop fluoxetine
(or taper if dose
>40 mg/day), start
above drug at low
dose

stop fluoxetine
(or taper if dose
>40 mg/day), start
reboxetine at 4 mg

stop fluoxetine
(or taper if dose
>40 mg/day), wait
14 days for washout,
then start above
drug at 25 mg and
continue low dose for
further 3 weeks‡

stop fluoxetine
(or taper if dose
>40 mg/day),
wait 14 days for
washout, then start
clomipramine at
25 mg and continue
this dose for further
3 weeks‡

stop fluoxetine
(or taper if dose
>40 mg/day), then
wait 5–6 weeks
for washout
before cautiously
commencing low-
dose moclobemide§

stop fluoxetine
(or taper if dose
>40 mg/day), then
wait 5–6 weeks
for washout
before cautiously
commencing low-
dose MAOI§

taper and stop
fluvoxamine, then
start above drug at
low dose§

taper fluvoxamine,
start reboxetine at
4 mg*

taper fluvoxamine,
start above drug at
25 mg*

taper and stop
fluvoxamine, start
clomipramine at
25 mg§

taper and stop
fluvoxamine, wait
7 days for washout
before cautiously
commencing low-
dose moclobemide§

taper and stop
fluvoxamine, wait
7 days for washout
before cautiously
commencing low-
dose MAOI§

taper vortioxetine,
start above drug at
low dose*

taper vortioxetine,
start reboxetine*

taper vortioxetine,
start above drug at
low dose (usually
25 mg)*

taper and stop
vortioxetine, start
clomipramine at
25 mg§

taper and stop
vortioxetine for
14 days washout
before starting
moclobemide at
low dose§

taper and stop
vortioxetine for
21 days washout
before starting
MAOI at low dose
cautiously§

stop agomelatine,
then start above
drug

stop agomelatine,
then start reboxetine

stop agomelatine,
then start above
drug at low dose
(usually 25 mg)*

stop agomelatine,
then start
clomipramine

stop agomelatine,
then start
moclobemide

stop agomelatine,
then start MAOI

taper SNRI, start
above drug at low
dose*

taper SNRI, start
reboxetine at 4 mg*

taper SNRI, start
above drug at
25 mg*

taper SNRI, start
clomipramine at
25 mg*

taper and stop
SNRI, wait 7 days
for washout
before cautiously
commencing low-
dose moclobemide§

taper and stop
SNRI, wait 7 days
for washout
before cautiously
commencing low-
dose MAOI§

taper drug, start
drug above at low
dose*

taper drug, start
reboxetine at 4 mg*

taper drug, start
above drug at
25 mg*

taper drug, start
clomipramine at
25 mg*

taper and stop
drug, wait 7 days
for washout
before cautiously
commencing low-
dose moclobemide§

taper and stop
drug, wait 14 days
for washout
before cautiously
commencing low-
dose MAOI§

taper reboxetine,
start above drug*

taper reboxetine,
start above drug at
25 mg*

taper reboxetine,
start clomipramine at
25 mg*

taper and stop
reboxetine, then wait
7 days for washout
before cautiously
commencing low-
dose moclobemide§

taper and stop
reboxetine, then wait
7 days for washout
before cautiously
commencing low-
dose MAOI§

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Switching and stopping antidepressants

Table 3 Guidelines for switching between specific antidepressants 2,8-10 (continued)

TO→
↓FROM
citalopram
escitalopram
paroxetine
sertraline
(SSRIs)

fluoxetine fluvoxamine vortioxetine agomelatine desvenlafaxine

duloxetine
venlafaxine
(SNRIs)
amitriptyline
imipramine
nortriptyline
doxepin
dothiepin
trimipramine
(TCAs)

taper first drug
and start above
drug at low dose*

taper and
stop first drug
before starting
fluoxetine§

taper drug, start
fluvoxamine at
50 mg*

taper drug, start
vortioxetine at
5 mg*
taper drug, start
agomelatine*

taper drug, start
SNRI at low dose*

clomipramine taper and stop
clomipramine,
then start above
SSRI at low dose§

taper and stop
clomipramine,
then start
fluoxetine at
10 mg§

taper and stop
clomipramine,
then start
fluvoxamine at
50 mg§

taper and stop
clomipramine,
then start
vortioxetine at
5 mg§

taper
clomipramine,
start
agomelatine*

taper and stop
clomipramine,
then start SNRI at
low dose§

moclobemide taper and stop
moclobemide,
then wait
24 hours for
washout before
starting above
drug§

taper and stop
moclobemide,
then wait
24 hours
for washout
before starting
fluoxetine§

taper and stop
moclobemide,
then wait
24 hours
for washout
before starting
fluvoxamine§

taper and stop
moclobemide,
then wait
24 hours
for washout
before starting
vortioxetine§

taper
moclobemide,
start agomelatine

taper and stop
moclobemide,
then wait
24 hours for
washout before
starting SNRI§

phenelzine
tranylcypromine
(MAOIs)

taper and stop
MAOI, then
wait 14 days for
washout before
starting above
drug§

taper and stop
MAOI, then
wait 14 days
for washout
before starting
fluoxetine§

taper and stop
MAOI, then
wait 14 days
for washout
before starting
fluvoxamine§

taper and stop
MAOI, then
wait 14 days
for washout
before starting
vortioxetine§

taper and stop
MAOI, start
agomelatine*

taper and stop
MAOI, then
wait 14 days for
washout before
starting SNRI§

Taper means gradual dose reduction, with lowering by increments every few days, usually over a period of 4 weeks, modified by patient experience,
drug, illness and other factors.

All switches from one antidepressant to another may result in serious complications. Switches must be undertaken cautiously and under close observation.

The recommendations in this table are based on clinical experience, product information, empirical evidence and recommendations from other
guidelines. It may be necessary to modify the switching process depending on patient, illness and interacting drug variables, determined by the patient’s
clinical progress. In appropriate circumstances expert prescribers may use less conservative switch strategies if justified by harm–benefit considerations
arising from factors such as illness severity.

MAOI monoamine oxidase inhibitor SNRI serotonin noradrenaline reuptake inhibitor
TCA tricyclic antidepressant SSRI selective serotonin reuptake inhibitor

An enlarged poster version of this
Switching-antidepressants table has been
inserted in the current issue of Australian
Prescriber. Extra copies are available
on request.

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mianserin
mirtazapine

reboxetine amitriptyline

imipramine
nortriptyline
doxepin
dothiepin
trimipramine
(TCAs)

clomipramine moclobemide phenelzine

tranylcypromine
(MAOIs)

taper drug, start
above drug at low
dose*

taper drug, start
reboxetine at 4 mg*

taper first drug, start
alternative TCA at
25 mg*

taper drug, start
clomipramine
cautiously at 25 mg*

taper and stop
drug, then wait
7 days for washout
before starting
moclobemide§

taper and stop
drug, then wait 14
days (21 days for
imipramine) before
starting MAOI§

taper clomipramine,
then start above
drug at low dose*

taper clomipramine,
then start reboxetine
at 4 mg*

taper clomipramine,
then start drug at
25 mg*

taper and stop
clomipramine,
then wait 7 days
for washout
before starting
moclobemide§

taper and stop
clomipramine, then
wait 21 days for
washout before
starting MAOI§

taper and stop
moclobemide, then
wait 24 hours for
washout before
starting above drug§

taper and stop
moclobemide, then
wait 24 hours for
washout before
starting reboxetine§

taper and stop
moclobemide, then
wait 24 hours for
washout before
starting above drug§

taper and stop
moclobemide,
then wait 24 hours
for washout
before starting
clomipramine§

taper and stop
moclobemide, then
wait 24 hours for
washout before
starting MAOI§

taper and stop MAOI,
then wait 14 days
for washout before
starting above drug§

taper and stop MAOI,
then wait 14 days
for washout before
starting reboxetine§

taper and stop MAOI,
then wait 14 days
for washout before
starting above drug§

taper and stop
MAOI, then wait
21 days for washout
before starting
clomipramine§

taper and stop MAOI,
start moclobemide
while maintaining
MAOI dietary
restrictions for
14 days§

taper and stop
MAOI, wait 14 days
for washout before
starting other MAOI§

* A washout period of 2–5 half-lives (most frequently 2–5 days) between cessation of previous drug and the introduction of a new drug is the safest
switching strategy from the point of view of drug interactions. In the indicated instances a washout period is not essential if switching is carried out
cautiously and under close observation, and clinical considerations such as illness severity support harm–benefit considerations. Cautious cross taper
(when the dose of the first drug is being reduced and the dose of the second drug is being increased at the same time so that the patient is taking
both antidepressants) may be used in the indicated instances if appropriate and safe.

† Fluoxetine may still cause interactions 5 or 6 weeks after cessation (especially from higher doses) due to long half-life of drug and active metabolite.
‡ Fluoxetine is likely to continue to elevate TCA concentrations for several weeks.
§ Co-prescription of the two antidepressants in this instance is not recommended.

Adapted from references 2, 8–10

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Journal of the American College of Cardiology Vol. 56, No. 14, 2010
© 2010 by the American College of Cardiology Foundation ISSN 0735-1097/$36.00
P

QUARTERLY FOCUS ISSUE: PREVENTION/OUTCOMES

Metabolic Syndrome

The Metabolic Syndrome and Cardiovascular Risk

A Systematic Review and Meta-Analysis

Salvatore Mottillo, BSC,*† Kristian B. Filion, PHD,*‡§ Jacques Genest, MD,� Lawrence Joseph, PHD,‡§
Louise Pilote, MD, MPH, PHD,‡§¶ Paul Poirier, MD, PHD,†† Stéphane Rinfret, MD, MSC,‡‡
Ernesto L. Schiffrin, MD, PHD,** Mark J. Eisenberg, MD, MPH*‡

Montreal and Sainte-Foy, Quebec, Canada

Objectives We sought to conduct a systematic review and meta-analysis of the cardiovascular risk associated with the met-
abolic syndrome as defined by the 2001 National Chole

sterol

Education Program (NCEP) and 2004 revised Na-
tional Cholesterol Education Program (rNCEP) definitions.

Background Numerous studies have investigated the cardiovascular risk associated with the NCEP and rNCEP definitions of
the metabolic syndrome. There is debate regarding the prognostic significance of the metabolic syndrome for
cardiovascular outcomes.

Methods We searched the Cochrane Library, EMBASE, and Medline databases through June 2009 for prospective observa-
tional studies investigating the cardiovascular effects of the metabolic syndrome. Two reviewers extracted data,
which were aggregated using random-effects models.

Results We identified 87 studies, which included 951,083 patients (NCEP: 63 studies, 497,651 patients; rNCEP: 33
studies, 453,432 patients). There was little variation between the cardiovascular risk associated with NCEP and
rNCEP definitions. When both definitions were pooled, the metabolic syndrome was associated with an in-
creased risk of cardiovascular d

isease

(CVD) (relative risk [RR]: 2.35; 95% confidence interval [CI]: 2.02 to 2.73),
CVD mortality (RR: 2.40; 95% CI: 1.87 to 3.08), all-cause mortality (RR: 1.58; 95% CI: 1.39 to 1.78), myocardial
infarction (RR: 1.99; 95% CI: 1.61 to 2.46), and str

oke

(RR: 2.27; 95% CI: 1.80 to 2.85). Patients with the meta-
bolic syndrome, but without diabetes, maintained a high cardiovascular risk.

Conclusions The metabolic syndrome is associated with a 2-fold increase in cardiovascular outcomes and a 1.5-fold increase
in all-cause mortality. Studies are needed to investigate whether or not the prognostic significance of the meta-
bolic syndrome exceeds the risk associated with the sum of its individual components. Furthermore, studies are
needed to elucidate the mechanisms by which the metabolic syndrome increases cardiovascular risk. (J Am
Coll Cardiol 2010;56:1113–32) © 2010 by the American College of Cardiology Foundation

ublished by Elsevier Inc. doi:10.1016/j.jacc.2010.05.034

P
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he metabolic syndrome affects approximately one-quarter
f North Americans and has become a leading health
oncern due to its link to cardiovascular disease (1). Ever
ince the metabolic syndrome was described by Reaven in
988 (2), a number of definitions have been published by
rganizations including the National Cholesterol Education

rom the *Divisions of Cardiology and Clinical Epidemiology, Jewish General
ospital/McGill University, Montreal, Quebec, Canada; †Faculty of Medicine,
niversity of Montreal, Montreal, Quebec, Canada; ‡Department of Epidemiology,
iostatistics and Occupational Health, McGill University, Montreal, Quebec, Can-
da; §Division of Clinical Epidemiology, McGill University Health Center, Mon-
real, Quebec, Canada; �Division of Cardiology, McGill University Health Center,

ontreal, Quebec, Canada; ¶Division of Internal Medicine, McGill University
ealth Center, Montreal, Quebec, Canada; **Division of Internal Medicine, Jewish
eneral Hospital, Montreal, Quebec, Canada; ††Faculty of Pharmacy, Laval Hos-

ital, Quebec Heart and Lung Institute, Sainte-Foy, Quebec, Canada; and the

‡Clinical and Interventional Cardiology, Multidisciplinary Cardiology Department,
aval Hospital, Quebec Heart and Lung Institute, Sainte-Foy, Quebec, Canada. This a

rogram (NCEP) (3), the International Diabetes Federa-
ion (4), and the World Health Organization (5), among
thers. Of these, the 2001 Third Report of the NCEP’s
dult Treatment Panel has emerged as the most widely
sed definition, primarily because it provides a relatively
imple approach for diagnosing the metabolic syndrome by

ork is supported by the Canadian Institutes of Health Research (CIHR grant
umber 82918). Mr. Mottillo is supported by a Canadian Cardiovascular Outcomes
esearch Team (CCORT) summer studentship funded through a CIHR Team
rant in Cardiovascular Outcomes Research. Dr. Genest is on the Speakers’ Bureau

or Merck and AstraZeneca. Dr. Joseph is a Chercheur-National of the Fonds de la
echerche en Santé du Québec (FRSQ). Dr. Pilote is a Chercheur-National of the
RSQ. Dr. Poirier is a Senior Physician-Scientist of the FRSQ. Dr. Rinfret is a

unior Physician-Scientist of the FRSQ. Dr. Schiffrin holds a Canada Research Chair
n Vascular and Hypertension Research. Dr. Eisenberg is a Chercheur-National of the
RSQ. All other authors have reported that they have no relationships to disclose.

Manuscript received February 11, 2010; revised manuscript received May 10, 2010,

ccepted May 13, 2010.

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1114 Mottillo et al. JACC Vol. 56, No. 14, 2010
The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

employing easily measurable risk
factors (3,6). Specifically, the
NCEP defines the metabolic
syndrome as having 3 or more of
the following 5 cardiovascular
risk factors: 1) central obesity
(waist circumference: men �102
cm; women �88 cm); 2) elevated
triglycerides (�150 mg/dl); 3

)

diminished high-density lipo-
protein (HDL) cholesterol (men
�40 mg/dl; women �50 mg/dl);
4) systemic hypertension (�130/
�85 mm Hg); and 5) elevated
fasting glucose (�110 mg/dl). In
2004, this NCEP definition was
revised (rNCEP) by lowering the
threshold for fasting glucose to
�100 mg/dl in concordance with
American Diabetes Association
criteria for impaired fasting glu-

ose (7). Also, thresholds for central obesity were lowered
rom strictly �102 cm in men and 88 cm in women to
reater than or equal to these values. Finally, the rNCEP
efinition includes patients being treated for dyslipidemia,
yperglycemia, or systemic hypertension.
The value of the metabolic syndrome as a predictor of

ardiovascular risk has been met with much debate. In 2005,
he American Diabetes Association and the European
ssociation for the Study of Diabetes issued a joint state-
ent summarizing the issues surrounding the metabolic

yndrome (8). In this statement, they underscore the need to
dentify the cardiovascular risk associated with the metabolic
yndrome. A large number of observational studies have
een carried out to investigate this risk, and there is a need
o synthesize the results of these studies. Two previous
eta-analyses investigating the metabolic syndrome only

ncluded studies published prior to 2005 and did not
nvestigate the rNCEP definition (9,10). Since then, 71
tudies have been published that used the NCEP and
NCEP definitions to investigate the cardiovascular effects
f the metabolic syndrome. Thus, our objective was to carry
ut a systematic review and meta-analysis to estimate the
ardiovascular risk associated with the metabolic syndrome
ccording to the NCEP and rNCEP definitions in the
eneral population and the subpopulations of men, women,
nd patients without type 2 diabetes mellitus.

ethods

ata sources and searches. We systematically searched
he Cochrane Library, EMBASE, and Medline databases
hrough June 2009 using the following key words: all-cause
ortality, cardiovascular risk, cardiovascular disease, cardio-

ascular mortality, fatal myocardial infarction (MI), meta-

Abbreviations
and Acronyms

BMI � body mass index

CI � confidence interval

CVD � cardiovascular
disease

HDL � high-density
lipoprotein

HR � hazard ratio

LDL � low-density
lipoprotein

MI � myocardial infarction

NCEP � National
Cholesterol Education
Program

rNCEP � revised National
Cholesterol Education
Program

RR � relative risk

olic syndrome, National Cholesterol Education Program w

dult Treatment Panel III, nonfatal MI, revised National
holesterol Education Program Adult Treatment Panel III,

troke, and syndrome X. References from published pro-
pective studies, relevant reviews, and previous meta-
nalyses were hand searched for additional studies not
dentified in the database search.
tudy selection. Eligible studies: 1) were prospective, ob-
ervational studies; 2) stratified patients based on the pres-
nce or absence of the metabolic syndrome using the NCEP
r rNCEP definitions; 3) reported cardiovascular outcomes
nd/or all-cause mortality; 4) reported outcomes as count
ata, or as relative risk (RR) or hazard ratio (HR) with a
orresponding measure of variance; and 5) were published in
he English language. Studies investigating more than 1
ardiovascular outcome or more than 1 definition of the
etabolic syndrome were also eligible for inclusion. Studies

ot meeting these criteria were excluded.
ata extraction. Two reviewers independently extracted

ata using standardized data extraction forms. Disagree-
ents were resolved by consensus or, when necessary, by a

hird reviewer. Reviewers extracted information on study
esign, including the duration of follow-up, the setting, and
he number of participants with and without the metabolic
yndrome according to each definition. Extracted baseline
articipant characteristics included age, sex, mean blood
ressure, body mass index (BMI), cholesterol, triglycerides,
aist circumference, and the prevalence of cardiovascular
isease (CVD), type 2 diabetes mellitus, systemic hyperten-
ion, obesity, and smoking. Reviewers extracted the follow-
ng outcomes: all-cause mortality, CVD, CVD mortality,

I, and stroke. Outcomes data presented as count data,
onadjusted risk estimates (RR or HR) with corresponding
easures of variance, or multivariable adjusted risk esti-
ates were extracted for participants with and without the
etabolic syndrome. The variables included in the multi-

ariable models were also extracted. In addition, when
vailable, outcomes were extracted for different subpopula-
ions, which included men, women, and patients without
ype 2 diabetes mellitus.

ata synthesis and analysis. We synthesized the results of
ncluded studies using random-effects meta-analyses, and
ynthesized results are presented as RRs with corresponding
5% confidence intervals (CIs). Heterogeneity was assessed
sing I2 statistics. We only conducted these meta-analyses
or studies that reported outcomes as count data; studies that
eported outcomes as risk estimates only (HR and RR) were
xcluded from these analyses. In the general population, we
stimated the cardiovascular risk associated with the NCEP,
odified NCEP, the rNCEP, and modified rNCEP defini-

ions of the metabolic syndrome separately. The modified
CEP and modified rNCEP definitions typically used mea-

urements of BMI (typically, BMI �30 kg/m2 or BMI
anging from �25 to 27 kg/m2 for Asian populations) instead
f waist circumference to define central obesity.

We also assessed the cardiovascular risk when all definitions

ere pooled. With the pooled definitions, we determined the

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1115JACC Vol. 56, No. 14, 2010 Mottillo et al.
September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

isk in the general population, in men, in women, and in
atients without type 2 diabetes mellitus. Pooled analyses were
onducted for the following 5 outcomes: 1) all-cause mortality;
) CVD; 3) CVD mortality; 4) MI; and 5) stroke. For each
utcome, a meta-analysis was performed to summarize the
verall effects across all relevant studies.

We reported risk estimates (HR and RR) in tables as part
f our systematic review. We classified nonadjusted risk
stimates and risk estimates adjusting exclusively for age
nd/or sex as “least adjusted.” In contrast, risk estimates
djusting for any cardiovascular risk factor (i.e., smoking
tatus, low-density lipoprotein [LDL] cholesterol, and
hysical activity) were classified as “most adjusted.” The

ength of follow-up varied considerably between studies.
herefore, we conducted a sensitivity analysis in which we

tratified studies using the median length of follow-up. In
ddition, funnel plots were constructed and visually assessed
or the possible presence of publication bias. All analyses
ere conducted using MIX software version 1.7 (11,12).

esults

earch results and study inclusion. A total of 3,162
otentially relevant studies were identified in our initial

iterature search (Fig. 1). After screening the abstracts of
hese studies, the full-length papers of 189 studies were
etrieved and assessed for eligibility. Of the retrieved stud-
es, a total of 87 met our inclusion criteria and were included
n our systematic review (Tables 1 to 5). The remaining 102
tudies were excluded either because they did not use the
CEP or rNCEP definitions of the metabolic syndrome to

tratify patients (n � 68), they used a cross-sectional study

Figure 1 Flow Diagram of Studies Included in the Systematic R

NCEP � National Cholesterol Education Program; rNCEP � revised National Chole

esign (n � 31), or they did not report any cardiovascular m

utcomes (n � 3). No additional studies were identified
hrough our hand search of references from published
tudies, relevant reviews, and previous meta-analyses.

All included studies were published since 2002, had
ample sizes ranging from 76 to 124,513 patients, and had
ollow-up durations ranging from 1.0 to 32.7 years (Online
ables 1 to 4). The prevalence of the metabolic syndrome in

hese studies ranged from 1% in a study of women without
ype 2 diabetes mellitus (13) and 78% in a study of patients
ith type 2 diabetes mellitus (14). There were also varia-

ions in the mean values for each of the 5 components of the
etabolic syndrome: 1) BMI ranged from 22 to 33 kg/m2;

) fasting glucose ranged from 82 to 196 mg/dl; 3) HDL
holesterol ranged from 37 to 64 mg/dl; 4) triglycerides ranged
rom 88 to 199 mg/dl; and 5) systolic blood pressure ranged
rom 117 to 174 mm Hg. Many studies followed specific
ubpopulations, accounting for much of the variability. In
articular, several studies reported outcomes for men (28
tudies; n � 172,548), women (24 studies; n � 164,768), and
articipants without diabetes (17 studies; n � 172,367).
Of the 87 studies (n � 951,083) included in our system-

tic review, 43 reported all-cause mortality data (n �
36,864) (Table 1), 19 reported CVD (n � 116,202)
Table 2), 38 reported CVD mortality (n � 407,350)
Table 3), 12 reported MI (n � 29,470) (Table 4), and 26
eported stroke (n � 126,633) (Table 5). A total of 38
tudies investigated the NCEP definition (n � 345,560)
Online Table 1), and 26 studies investigated the rNCEP
efinition (n � 433,808) (Online Table 2). In addition, 25
tudies investigated the modified NCEP definition (n �
52,091) (Online Table 3), and 7 studies investigated the

Education Program.

eview

sterol

odified rNCEP definition (n � 19,624) (Online Table 4).

M

1116 Mottillo et al. JACC Vol. 56, No. 14, 2010
The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

etS Studies Reporting the Incidence of All-Cause MortalityTable 1 MetS Studies Reporting the Incidence of All-Caus

e Mortality

First Author, Year (Ref. #)* Population n Me

tS (%)

Follow-Up

(yrs)
Effect

Measure

Risk of All-Cause Mortality†
(95% C

I)

All-Cause
Mortality (%)

Least Adjusted Most Adjusted
MetS
Group

Non-MetS
Group

NCEP definition‡

Benetos et al., 2008 (33) Pts without CVD 84,730 9.6 4.7§ HR — 1.63 (1.38–1.93) —

—

Butler et al., 2006 (14) General population 3,035 38.5 6.0� RR 1.02 (0.85–1.22) — 14.5 1

4.2

Men 1,473 — 6.0� RR — — 15.9 19.0
Women 1,562 — 6.0� RR — — 13.4 9.0
Pts with T2DM 461 77.9 6.0� RR 0.71 (0.48–1.06) — 18.1 25.5
Pts without T2DM 2,562 31.6 6.0� RR 0.95 (0.76–1.17) — 12.9 13.6

Dekker et al., 2005 (34) Men 615 19.0 11.0� HR 1.98 (1.28–3.05) — — —
Women 749 25.8 11.0� HR 1.18 (0.72–1.94) — — —

Guize et al., 2007 (35) General population 60,754 10.3 3.6§ HR — 1.79 (1.35–2.38) — —
Hillier et al., 2005 (36) Elderly women with no T2DM 921 27.1 12.2§ HR — 1.30 (1.00–1.70) — —
Hong et al., 2007 (37) Pts with atherosclerosis 14,699 — 9.0§ RR — 1.39 (1.22–1.58) 9.6

5.9

Men with atherosclerosis 6,389 32.4 9.0§ RR — 1.57 (1.31–1.89) 10.2

8.0

Women with atherosclerosis 8,310 29.1 9.0§ RR — 1.22 (1.02–1.47) 9.2 4.3

Hunt et al., 2004 (28) General population 2,107 9.4 12.7§ HR 1.47 (1.13–1.92) — — —
Subjects with CVD 1,947 — 12.7§ HR 1.06 (0.71–1.58) — — —

Katzmarzyk et al., 2005 (38) Nonobese men 7,505 4.7 10.0§ RR — 0.92 (0.53–1.60) 3.98 2.24
Overweight men 9,048 19.8 10.2§ RR — — 3.52 2.21
Obese men 2,620 61.1 10.2§ RR — — 3.44 2.45

Katzmarzyk et al., 2006 (39) Men 20,789 19.7 11.0§ RR 1.46 (1.23–1.74) 1.36 (1.14–1.62) 4.5 2.7
Lakka et al., 2002 (40) Middle-aged men 707 15.0 12.0¶ RR 1.67 (0.95–2.92) 1.67 (0.91–3.08) — —
Langenberg et al., 2006 (41) General population 2,118 — 20.0� HR — 1.43 (1.24–1.65) 71.5 58.8

Men 977 16.9 20.0� HR — 1.44 (1.18–1.76) 74.5 65.8
Women 1,141 15.1 20.0� HR — 1.46 (1.19–1.80) 68.6 5

3.0

Mancia et al., 2007 (42) General population 2,013 16.2 12.3� HR 2.39 (1.79–3.18) 1.37 (1.02–1.84) 20.2 9.2
Marroquin et al., 2004 (43) Women with CAD 147 42.2 3.5¶ HR — 4.93 (1.02–23.76) 14.5 2.11

Women without CAD 362 34.5 3.5¶ HR — 1.41 (0.32–6.32) 3.2 3.5
Women with T2DM without CAD 340 30.3 3.5¶ RR 2.20 (0.60–8.04) — 7.8 3.5

Monami et al., 2008 (44) Pts with T2DM 1,716 67.1 4.7§ HR 1.36 (1.10–1.69) — — —
Pannier et al., 2008 (45) Normotensive pts 34,577 4.5 4.7§ HR — 1.09 (0.68–1.75) — —

Hypertensive pts 26,447 17.7 4.7§ HR — 1.40 (1.13–1.74) — —
Ramkumar et al., 2007 (46) Pts with moderate CKD 710 48.9 9.0� HR — 1.40 (1.01–1.94) — —
Sundstrom et al., 2006 (47) 70-year-old men 1,221 24.1 32.7� HR 1.58 (1.24–2.01) 1.26 (0.95–1.66) — —
Takeno et al., 2008 (48) Pts with AMI 461 37.3 1.5¶ HR — 1.27 (0.54–3.04) — —
Wang et al., 2007 (49) Elderly without T2DM 1,025 42.7 13.5¶ HR 1.13 (0.93–1.37) 1.08 (0.89–1.31) — —

Elderly men without T2DM — — 13.5¶ HR — 1.08 (0.82–1.42) — —
Elderly women without T2DM — — 13.5¶ HR — 1.08 (0.83–1.40) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 42.6 3.2¶ HR 1.45 (1.17–1.80) 1.43 (1.14–1.78) — —
Zambon et al., 2009 (51) Elderly 2,910 39.0 4.4§ HR 1.30 (1.11–1.54) — — —

Elderly men 1,174 25.6 4.4§ HR 1.26 (0.99–1.60) — — —
Elderly women 1,736 48.1 4.4§ HR 1.33 (1.06–1.68) — — —

Modified NCEP definition#

Chen et al., 2006 (52) Pts with renal disease and ACS 76 76.3 18.1§ RR 2.82 (0.72–11.09) — 31.4 11.1
Feinberg et al., 2007 (53) Pts with ACS, without T2DM 1,060 33.9 1.0� HR — 1.96 (1.18–3.24) 8.9 4.6
Kasai et al., 2006 (54) Pts who underwent PCI 748 42.5 12.0§ HR — 1.34 (0.88–2.05) 13.5 10.5
Levantesi et al., 2005 (55) Pts post-MI 8,245 37.0 3.5� RR 1.15 (0.99–1.33) 1.29 (1.10–1.51) 8.5 7.4
Malik et al., 2004 (56) General population 4,576 37.1 13.3§ HR — 1.40 (1.19–1.66) — —

Subjects with T2DM 4,056 29.0 13.3§ HR — 1.17 (0.96–1.42) — —
Nigam et al., 2006 (57) General population 24,358 13.5 12.6§ HR 1.23 (1.16–1.29) 1.21 (1.14–1.29) — —
Sundstrom et al., 2006 (47) 50-year-old-men 2,322 17.4 32.7� HR 1.67 (1.45–1.93) 1.36 (1.17–1.58) — —

70-year-old-men 1,221 23.1 32.7� HR 1.52 (1.19–1.94) 1.20 (0.90–1.59) — —
Thomas et al., 2007 (58) General population 2,863 17.5 8.5§ RR 3.03 (2.00–4.59) — 7.0 2.3

Revised NCEP definition*

*

Benetos et al., 2008 (33) Pts without CVD 84,730 16.5 4.7§ HR — 1.32 (1.13–1.53) — —
Davis et al., 2007 (59) Subjects with type 1 diabetes 127 41.7 11.0§ HR — 0.74 (0.32–1.74) — —
Guize et al., 2007 (35) General population 60,754 17.7 3.6§ HR — 1.46 (1.14–1.88) — —
Hildrum et al., 2009 (60) Age 40–59 yrs 3,789 28.0 7.9§ HR 2.06 (1.35–3.13) 2.14 (1.40–3.29) — —

Age 60–74 yrs 1,973 47.0 7.9§ HR 1.10 (0.90–1.36) 1.14 (0.92–1.41) — —
Age 75–89 yrs 986 57.0 7.9§ HR 1.05 (0.88–1.25) 1.05 (0.87–1.26) — —

Huang et al., 2008 (61) Men 58,771 — 8.0� RR 2.09 (1.90–2.30) 1.21 (1.09–1.34) 4.7 2.3
Women 65,742 — 8.0� RR 4.33 (3.85–4.88) 1.30 (1.12–1.49) 4.4

4.1

Pts without T2DM without CVD 117,045 — 8.0� RR — 1.04 (0.94–1.15) 3.1 1.4

Kajimoto et al., 2008 (62) Pts with T2DM who underwent CABG 274 65.3 10.5§ HR 0.84 (0.56–1.27) — — —
Pts without T2DM who underwent CABG 909 40.9 10.5§ HR 1.34 (1.03–1.74) — — —

Katzmarzyk et al., 2006 (39) Men 20,789 26.9 11.0§ RR 1.41 (1.21–1.67) 1.31 (1.11–1.54) 4.2 2.6
Lee et al., 2008 (63) Men 2,787 24.3 14.1§ HR 3.20 (2.50–4.10) 1.40 (1.10–1.80) 16.8 6.3

Women 2,912 21.4 14.1§ HR 5.00 (3.50–6.90) 1.80 (1.30–2.60) 11.7 2.7

(continued on next page)

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1117JACC Vol. 56, No. 14, 2010 Mottillo et al.
September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

ome studies investigated more than 1 cardiovascular out-
ome or more than 1 definition of the metabolic syndrome.
he metabolic syndrome and cardiovascular risk. The

ssociation between the metabolic syndrome and cardiovas-
ular risk was similar for the NCEP and rNCEP definitions
Table 6). Specifically, the metabolic syndrome as defined
y the NCEP definition was associated with an increase in
isk for all-cause mortality (RR: 1.54; 95% CI: 1.29 to 1.84;
2 � 84%; 95% CI: 73% to 91%) similar to that of the
etabolic syndrome as defined by the rNCEP definition

RR: 1.63; 95% CI: 1.30 to 2.04; I2 � 95%; 95% CI: 92%
o 97%). There was also little variation in cardiovascular risk
etween the modified NCEP and modified rNCEP defini-
ions compared with the original NCEP definition. Overall,
hen studies investigating all definitions were pooled, the
etabolic syndrome was associated with an increase in the

isk for CVD (RR: 2.35; 95% CI: 2.02 to 2.73; I2 � 64%;
5% CI: 39% to 79%), CVD mortality (RR: 2.40; 95% CI:
.87 to 3.08; I2 � 81%; 95% CI: 72% to 88%), all-cause
ortality (RR: 1.58; 95% CI: 1.39 to 1.78; I2 � 89%; 95%
I: 85% to 92%), MI (RR: 1.99; 95% CI: 1.61 to 2.46; I2 �
0%; 95% CI: 0% to 73%), and stroke (RR: 2.27; 95% CI:
.80 to 2.85; I2 � 88%; 95% CI: 82% to 91%) (Table 6,
igs. 2 to 6). The point estimates for cardiovascular risk

ontinuedTable 1 Continued

First Author, Year (Ref. #)* Population n Me

Lopes et al., 2008 (64) Pts with CAD 589
Pts with CAD with T2DM —
Pts with CAD without T2DM —

Mozaffarian et al., 2008 (65) Elderly 4,258
Noto et al., 2008 (66) General population 685

Men —
Women —

Saito et al., 2009 (67) Men 12,412
Women 21,639

Simons et al., 2007 (68) Elderly men 1,233
Elderly women 1,572

Wassink et al., 2008 (50) Pts with CV risk factor 3,196
Pts with CV risk factor without T2DM 2,472

Wen et al., 2008 (69) Elderly men 5,761
Elderly women 4,786

Modified revised NCEP definition#

Hsu et al., 2008 (70) Men 4,888

Women 6,170
Kasai et al., 2008 (71) Pts without T2DM who underwent PCI 450
Niwa et al., 2007 (72) Men 914

Women 1,262
Tanomsup et al., 2007 (73) Men 2,545
Wang et al., 2007 (49) Elderly without T2DM 1,025

Elderly men without T2DM 648
Elderly women without T2DM 377

Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and
djusting for any cardiovascular risk factor or component of the metabolic syndrome (i.e., smoking
aving 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumferen

ipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); and 4) hypertension (�130
Median follow-up. #The modified NCEP and modified revised NCEP definitions use measurements
evised NCEP definition uses a lower cutoff for elevated fasting glucose of �100 mg/dl.

ACS � acute coronary syndrome; AMI � acute myocardial infarction; BMI � body mass index
ardiovascular; CVD � cardiovascular disease; HR � hazard ratio; MetS � metabolic syndrome; MI
ntervention; Pts � patients; RR � relative risk; T2DM � type 2 diabetes mellitus.

ere consistently higher in women compared with men, (

specially for all-cause mortality (RR: 1.86; 95% CI: 1.37 to
.52; I2 � 91%; 95% CI: 85% to 94% for women vs. RR:
.42; 95% CI: 1.16 to 1.74; I2 � 90%; 95% CI: 81% to 94%
or men).

A small number of studies reported outcomes for patients
ithout type 2 diabetes mellitus. However, even in the

bsence of type 2 diabetes mellitus, the metabolic syndrome
as still associated with an increased risk of CVD mortality

RR: 1.75; 95% CI: 1.19 to 2.58; I2 � 68%; 95% CI: 8% to
9%), MI (RR: 1.62; 95% CI: 1.31 to 2.01; I2 � 0%; 95%
I: 0% to 90%), and stroke (RR: 1.86; 95% CI: 1.10 to
.17; I2 � 89%; 95% CI: 56% to 97%). The confidence
nterval for our assessment of the effect of the metabolic
yndrome on all-cause mortality in this subpopulation was
nconclusive (RR: 1.32; 95% CI: 0.65 to 2.67; I2 � 87%;
5% CI: 47% to 97%). Finally, there were an insufficient
umber of studies investigating patients with type 2 diabetes
vailable to pool these data.
ensitivity analyses. In sensitivity analyses, we assessed the
otential impact of follow-up duration on our results. These
ensitivity analyses showed that studies with longer
ollow-up times had risk estimates that were similar to those
ith shorter follow-up times. Specifically, in studies with a

ollow-up time that was longer than the median duration

Follow-Up
(yrs)

Effect
Measure

Risk of All-Cause Mortality†
(95% CI)
All-Cause
Mortality (%)
Least Adjusted Most Adjusted
MetS
Group
Non-MetS
Group

2.0� HR — 2.50 (1.15–5.47) — —
2.0� HR — 1.06 (0.38–2.91) — —
2.0� HR — 3.57 (1.38–9.19) — —

15.0� HR 1.31 (1.19–1.43) 1.22 (1.11–1.34) 53.1 47.9
15.0� HR — 1.00 (0.81–1.24) 25.6 23.7
15.0� HR — 0.95 (0.61–1.47) 18.8 19.6
15.0� HR — 1.04 (0.82–1.32) 28.0 28.2
12.3� HR 1.07 (0.94–1.23) 1.06 (0.92–1.23) — —
12.3� HR 1.23 (1.05–1.44) 1.22 (1.03–1.43) — —
16.0� HR 1.60 (1.37–1.86) 1.53 (1.30–1.79) 66.7 52.8
16.0� HR 1.43 (1.23–1.67) 1.35 (1.15–1.59) 51.3 3

9.4

3.2¶ HR 1.43 (1.15–1.78) 1.40 (1.12–1.75) — —
3.2¶ HR 1.36 (1.05–1.76) 1.34 (1.03–1.74) — —
8.0� RR 1.24 (1.08–1.42) 1.18 (1.02–1.36) — —
8.0� RR 1.27 (1.05–1.54) 1.15 (0.94–1.40) — —

4.7§ HR 1.05 (0.87–1.28) — — —
4.7§ HR 1.46 (1.19–1.80) — — —
12§ HR 0.90 (0.45–1.79) 0.88 (0.42–1.85) — —

12.5§ HR 1.05 (0.60–1.82) 1.13 (0.64–1.98) 17.1 15.3
12.5§ HR 1.24 (0.39–3.95) 1.31 (0.41–4.18) 13.6 6.2
17.0� HR — 1.60 (1.23–2.09) — —
13.5¶ HR 1.10 (0.91–1.33) 1.08 (0.88–1.28) — —
13.5¶ HR — 1.05 (0.80–1.37) — —
13.5¶ HR — 1.09 (0.83–1.43) — —

imates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates
terol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as
n �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density
m Hg); and 5) elevated fasting glucose (�110 mg/dl). §Mean follow-up. �Maximum follow-up.

typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The

� coronary artery bypass graft; CAD � coronary artery disease; CI � confidence interval; CV �
cardial infarction; NCEP � National Cholesterol Education Program; PCI � percutaneous coronary

tS (%)

52.3
—
—

35.0
22.9
12.4
31.5
—
—

31.1
34.1
50.1
—

45.6
54.4

22.0
28.0
2

8.7

9.0
1.7

19.3
51.3
—
—

risk est
, choles
ce: me

/�85 m
of BMI (

; CABG

12.3 years), the risk for CVD mortality associated with the

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1118 Mottillo et al. JACC Vol. 56, No. 14, 2010
The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

etabolic syndrome (RR: 2.62; 95% CI: 1.56 to 4.38; I2 �
8%; 95% CI: 80% to 93%) was similar to the risk in studies
ith a follow-up time shorter than the median duration

RR: 2.23; 95% CI: 1.74 to 2.86; I2 � 65%; 95% CI: 30%
o 82%).

Some studies also reported outcomes for patient popula-

etS Studies Reporting the Incidence of CVDTable 2 MetS Studies Reporting the Incidence of CVD

First Author, Year (Ref. #)* Population n MetS (%)

NCEP definition‡

Andreadis et al., 2007 (74) Pts with hypertension 1,007 4

2.1

Dekker et al., 2005 (34) Men 615 19.0

Women 749 25.8

Jeppesen et al., 2007 (75) General population 2,135 19.2

Resnick et al., 2003 (76) American Indians
without T2DM

2,283 35.0

Sattar et al., 2008 (77) Elderly (age 70–82 yrs)
without T2DM

4,812 27.7

Elderly (age 60–79 yrs)
men without T2DM

2,737 2

7.2

Wilson et al., 2005 (78) Men 1,549 22.5

Women 1,774 14.9

Modified NCEP definition#

Guzder et al., 2006 (79) Pts with T2DM 428 82.5

Hwang et al., 2009 (80) Men 1,761 21.7

Women 674 11.4

Kokubo et al., 2008 (81) Men 2,492 18.0

Elderly men — —

Women 2,840 20.7

Elderly women — —

Ninomiya et al., 2007 (82) Men 1,050 20.6

Women 1,402 29.9

Schillaci et al., 2004 (83) Hypertensive pts 1,742 34.0

Song et al. 2007 (84) Women with BMI
�25 kg/m2

13,526 4.3

Women with BMI
25–29.9 kg/m2

7,834 14.1

Women with BMI
�30 kg/m2

4,266 31.4

Takeuchi et al., 2005 (85) Men 780 25.3

Worm et al., 2009 (86) HIV-infected pts 23,202 4.4

Revised NCEP definition**

Ingelsson et al., 2007 (87) Pts without T2DM 1,830 31.8

Liu et al., 2007 (88) General population 30,378 18.2

Meigs et al., 2007 (89) Pts without insulin
resistance

2,104 16.2

Pts with insulin
resistance

699 63.0

Vaccarino et al., 2008 (90) Women received CA
angiography

652 60.0

Wand et al., 2007 (91) HIV-infected pts 881 8.5

Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and
djusting for any cardiovascular risk factor or component of the metabolic syndrome (i.e., smoking
aving 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumferen

ipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85
ollow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (ty
CEP definition uses a lower cutoff for elevated fasting glucose of �100 mg/dl.
CA � coronary artery; HIV � human immunodeficiency virus; other abbreviations as in Table 1.

ions with cardiovascular risk factors (systemic hypertension, t

therosclerosis, or a history of CVD). Our sensitivity
nalysis showed that studies of subjects without these risk
actors had risk estimates for CVD mortality (RR: 2.36;
5% CI: 1.79 to 3.1; I2 � 84%; 95% CI: 75% to 89%)
onsistent with those obtained in our primary analysis (RR:
.40; 95% CI: 1.87 to 3.08; I2 � 81%; 95% CI: 72%

-Up
s)

Effect
Measure

Risk of CVD† (95% CI)
CVD (%)

Least Adjusted Most Adjusted
MetS
Group
Non-MetS
Group

§ HR 1.75 (1.15–2.66) — 11.8 8.1

� HR 1.91 (1.31–2.79) 1.64 (1.11–2.44) — —

� HR 1.68 (1.11–2.55) 1.17 (0.73–1.87) — —

§ HR — 1.86 (1.39–2.45) — —

¶ HR 1.35 (1.13–1.62) 1.11 (0.79–1.56) — —

¶ HR 1.07 (0.86–1.32) — — —

¶ HR 1.27 (1.04–1.56) — — —

� RR 2.88 (1.99–4.16) — 17.9 4.9

� RR 2.25 (1.31–3.88) — 7.7 2.6

¶ HR 1.27 (0.72–2.23) 2.05 (1.13–3.74) — —

¶ RR 2.02 (1.38–2.95) — 10.0 4.9

¶ RR 5.17 (2.59–10.31) — 15.6 3.0

HR 1.70 (1.23–2.34) 1.75 (1.27–2.41) 12.3 6.5

HR 1.67 (1.16–2.40) 1.73 (1.20–2.48) — —

HR 1.93 (1.35–2.77) 1.90 (1.31–2.77) 9.5

3.2

HR 1.78 (1.19–2.66) 1.70 (1.12–2.59) — —

� HR 1.93 (1.38–2.70) 1.86 (1.32–2.62) 23.2 13.0

� HR 1.68 (1.22–2.33) 1.70 (1.22–2.36) 17.0 7.9

¶ HR — 1.73 (1.25–2.38) — —

§ RR 2.58 (1.88–3.53) 2.40 (1.71–3.37) 7.9 2.2

§ RR 2.92 (2.24–3.79) — 7.1 2.4

§ RR 2.32 (1.71–3.15) — 6.1 2.6

� HR — 2.23 (1.14–4.34) 11.7 6.7

§ RR 2.89 (2.34–3.59) 0.94 (0.69–1.27) — —

¶ RR 2.08 (1.47–2.93) — 10.2 4.9

� HR — 2.01 (1.73–2.33) — —

¶ RR 1.40 (1.00–2.10) 1.30 (0.90–1.90) 10.6 6.1

¶ RR 2.01 (1.28–3.15) — 17.1 8.5

§ RR 2.44 (1.51–3.92) 1.81 (1.10–2.99) — —

� HR — 2.56 (0.86–7.60) — —

imates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates
terol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as
n �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density
); and 5) elevated fasting glucose (�110 mg/dl). §Median follow-up. �Maximum follow-up. ¶Mean
BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised

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1119JACC Vol. 56, No. 14, 2010 Mottillo et al.
September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

Funnel plots suggest that mild publication bias may be
resent (data not shown).

iscussion

ur systematic review and meta-analysis was designed to
stimate the cardiovascular risk associated with the meta-
olic syndrome as defined by the NCEP and rNCEP
efinitions. Our literature search was designed to include all
rospective studies investigating the NCEP and rNCEP
efinitions, thereby allowing us to include a large number of
tudies (87 studies; n � 951,083).

Overall, the metabolic syndrome was associated with a
-fold increase in risk of CVD, CVD mortality, and stroke,
nd a 1.5-fold increase in risk of all-cause mortality. Thus,
atients with the metabolic syndrome were at higher risk for
ardiovascular outcomes than for all-cause mortality, al-
hough these patients were at elevated risk for either

Figure 2 The Metabolic Syndrome and the Relative Risk for All

I2 � 89%; 95% confidence interval (CI): 85% to 92%. ACS � acute coronary syndro
MI � myocardial infarction; PCI � percutaneous coronary intervention; Pts � patie

utcome compared with those without this syndrome. The h

etabolic syndrome was also associated with an approxi-
ate 2-fold increase in risk for MI. There was little

ariation in cardiovascular risk between the NCEP and
NCEP definitions, which principally differ in their thresh-
ld for impaired fasting glucose (�110 mg/dl vs. �100
g/dl, respectively). The modified NCEP and modified

NCEP definitions also showed little variation compared
ith the original NCEP definition; these definitions only
iffer in their measurement of central obesity (use of BMI
ersus waist circumference, respectively).

The pathophysiological mechanism by which the meta-
olic syndrome increases cardiovascular risk remains under
ebate (15). Earlier definitions by the World Health Orga-
ization (5) and the European Group for the Study of
nsulin Resistance (16) emphasize the independent role of
nsulin resistance as the underlying component of the

etabolic syndrome. Insulin resistance progresses toward

e Mortality

AD � coronary artery disease; MetS � metabolic syndrome;
R � relative risk; T2DM � type 2 diabetes mellitus.

-Caus

me; C
nts; R

yperinsulinemia and hyperglycemia, thus triggering pe-

MetS Studies Reporting the Incidence of CVD MortalityTable 3 MetS Studies Reporting the Incidence of CVD Mortality

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of CVD Mortality† (95% CI) CVD Mortality (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group

NCEP definition‡
Benetos et al., 2008 (33) Pts without CVD 84,730 9.6 4.7§ HR — 2.05 (1.28–3.28) — —
Butler et al., 2006 (14) General population 3,035 38.5 6.0� RR 1.37 (0.98–1.92) — 5.13 3.75

Men 1,473 — 6.0� — — — 6.2 5.5
Women 1,562 — 6.0� — — — 4.4 1.9
Pts with T2DM 461 77.9 6.0� RR 0.77 (0.38–1.53) — 7.5 9.8
Pts without T2DM 2,562 31.6 6.0� RR 1.19 (0.79–1.81) — 4.1 3.4

DECODE study, 2007 (92) Men without T2DM age 50–69 yrs 2,790 26.5 10.0� RR 1.48 (1.02–2.14) — 5.55 3.75
Dekker et al., 2005 (34) Men 615 19.0 11.0� HR 2.25 (1.16–4.34) — — —

Women 749 25.8 11.0� HR 0.76 (0.32–1.83) — — —
Hillier et al., 2005 (36) Elderly women with no T2DM 921 27.1 12.2§ HR — 1.60 (1.10–2.30) — —
Hunt et al., 2004 (28) General population 2,107 9.4 12.7§ HR 2.53 (1.74–3.67) — — —

Subjects with CVD 1,947 — 12.7§ HR 2.01 (1.13–3.57) — — —
Katzmarzyk et al., 2005 (38) Nonobese men 7,505 4.7 10.2§ RR 3.74 (1.68–8.32) 1.60 (0.71–3.61) 1.99 0.53

Overweight men 9,048 19.8 10.2§ RR 2.14 (1.35–3.41) — 1.51 0.7
Obese men 2,620 61.1 10.2§ RR 1.33 (0.67–2.63) — 1.56 1.18

Katzmarzyk et al., 2006 (39) Men 20,789 19.7 11.4§ RR 2.03 (1.54–2.69) 1.79 (1.35–2.37) 1.93 0.8
Lakka et al., 2002 (40) Men 707 15.0 11.6§ RR 2.08 (0.93–4.65) 2.27 (0.96–5.36) — —
Langenberg et al., 2006 (41) General population 2,118 — 20.0� HR — 1.50 (1.23–1.83) 38.0 29.1

Men 977 16.9 20.0� HR — 1.28 (0.95–1.71) 32.7 33.7
Women 1,141 15.1 20.0� HR — 1.18 (1.38–2.39) 43.0 25.3

Maggi et al., 2006 (93) Men 1,359 31.4 4.0� HR 3.35 (1.35–8.30) 1.12 (1.09–1.16) — —
Women 1,724 59.5 4.0� HR 1.06 (0.63–1.39) 0.82 (0.56–1.19) — —

Mancia et al., 2007 (42) General population 2,013 16.2 12.3� HR 3.27 (1.97–5.41) 1.71 (1.02–2.85) 7.3 2.4
Monami et al., 2008 (44) Pts with T2DM 1,716 67.1 4.7§ HR 1.82 (1.24–2.68) — — —
Solymoss et al., 2009 (94) Pts with �50% stenosis of CA 876 53.0 12.6§ HR 1.43 (0.97–2.11) 1.42 (0.96–2.10) — —
Sundstrom et al., 2006 (47) 70-year-old men 1,221 24.1 32.7� HR 2.01 (1.41–2.85) 1.43 (0.95–2.17) — —
Wang et al., 2007 (49) Elderly without T2DM 1,025 42.7 13.5¶ HR 1.43 (1.12–1.84) 1.35 (1.05–1.74) — —

Elderly men without T2DM — — 13.5¶ HR — 1.43 (1.00–2.03) — —
Elderly women without T2DM — — 13.5¶ HR — 1.27 (0.89–1.82) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 42.6 3.2¶ HR 1.71 (1.31–2.24) 1.65 (1.25–2.17) — —
Zambon et al., 2009 (51) Elderly 2,910 39.0 4.4§ HR 1.36 (1.03–1.78) — — —

Elderly men 1,174 25.6 4.4§ HR 1.51 (0.98–2.33) — — —
Elderly women 1,736 48.1 4.4§ HR 1.27 (0.90–1.79) — — —

(continued on next page)

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ContinuedTable 3 Continued

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure
Risk of CVD Mortality† (95% CI) CVD Mortality (%)
Least Adjusted Most Adjusted MetS Group Non-MetS Group

Modified NCEP definition#
Chen et al., 2006 (52) Pts with renal disease and ACS 76 73.7 18.2§ — — — 24.0 0.0
de Simone et al., 2007 (95) Hypertensive subjects 8,243 19.3 10.0� HR — 1.73 (1.38–2.17) — —
Kasai et al., 2006 (54) Pts who underwent PCI 748 28.7 12§ RR 2.70 (1.28–5.70) — 6.3 2.3
Malik et al., 2004 (56) General population 4,576 37.1 13.3§ HR — 1.82 (1.40–2.37) — —

Subjects with T2DM 4,056 29.0 13.3§ HR — 1.65 (1.10–2.47) — —
Nigam et al., 2006 (57) General population 24,358 13.5 12.6§ HR 1.26 (1.19–1.35) 1.22 (1.14–1.31) — —
Nakatani et al., 2007 (96) Japanese pts with AMI 3,858 42.7 2.0¶ HR — 1.08 (0.62–1.90) — —
Sundstrom et al., 2006 (47) 50-year-old men 2,322 17.4 32.7� HR 2.21 (1.82–2.68) 1.59 (1.29–1.95) — —

70-year-old men 1,221 23.1 32.7� HR 2.11 (1.49–3.00) 1.55 (1.02–2.35) — —
Thomas et al., 2007 (58) General population 2,863 17.5 8.5§ RR 6.12 (2.99–12.51) — 3.4 0.6

Revised NCEP definition**
Benetos et al., 2008 (33) Pts without CVD 84,730 16.5 4.7§ HR — 1.64 (1.08–2.50) — —
Davis et al., 2007 (59) Subjects with type 1 diabetes 127 41.7 11.0§ HR 1.37 (0.40–4.74) — — —
Hildrum et al., 2009 (60) Age 40–59 yrs 3,789 28.0 7.9§ HR 3.97 (2.00–7.88) 3.95 (1.96–7.97) — —

Age 60–74 yrs 1,973 47.0 7.9§ HR 1.07 (0.82–1.39) 1.09 (0.83–1.43) — —
Age 75–89 yrs 986 57.0 7.9§ HR 1.12 (0.90–1.40) 1.11 (0.89–1.39) — —

Huang et al., 2008 (61) Men 58,771 — 8.0� RR 3.17 (2.56–3.93) 1.77 (1.40–2.24) 1.2 0.4
Women 65,742 — 8.0� RR 7.46 (5.55–10.02) 1.69 (1.19–2.42) 1.0 0.1
Pts without T2DM and CVD 117,045 — 8.0� RR — 1.68 (1.32–2.16) 0.7 0.2

Hunt et al., 2007 (97) Men without T2DM 1,940 15.6 15.5§ RR 3.38 (1.95–5.85) — 5.1 1.5
Women without T2DM 2,532 19.4 15.5§ RR 1.81 (1.17–2.81) — 7.2 4.0

Kajimoto et al., 2008 (62) Nondiabetic pts who had CABG 909 40.9 10.5§ HR 2.31 (1.36–3.92) — — —
Diabetic pts who had CABG 274 65.3 10.5§ HR 0.75 (0.41–1.36) — — —

Katzmarzyk et al., 2006 (39) Men 20,789 26.9 11.4§ RR 1.89 (1.44–2.47) 1.67 (1.27–2.19) 1.7 0.8
Lee et al., 2008 (63) Men 2,787 24.3 14.1§ HR 6.70 (4.30–10.40) 3.00 (1.90–4.80) 8.1 1.4

Women 2,912 21.4 14.1§ HR 7.40 (4.00–13.80) 2.10 (1.10–4.00) 4.3 0.7
Mozaffarian et al., 2008 (65) Elderly 4,258 35.0 15.0� RR 1.51 (1.29–1.76) — — —
Noto et al., 2008 (66) General population 685 22.9 15.0� HR 1.33 (0.96–1.83) — 10.6 7.8

Men — 12.4 15.0� HR 1.45 (0.83–2.52) — 11.8 7.6
Women — 31.5 15.0� HR 1.31 (0.88–1.93) — 10.2 7.9

Saito et al., 2009 (67) Men 12,412 — 12.3¶ HR 1.61 (1.16–2.23) 1.41 (0.99–2.02) — —
Women 21,639 — 12.3¶ HR 1.46 (1.00–2.13) 1.44 (0.98–2.11) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 50.1 3.2¶ HR 1.69 (1.28–2.22) 1.61 (1.22–2.14) — —
Pts with CV factor without T2DM 2,472 — 3.2¶ HR 1.55 (1.12–2.14) 1.49 (1.07–2.08) — —

Wen et al., 2008 (69) Elderly men 5,761 45.6 8.0� RR 1.70 (1.28–2.23) 1.45 (1.07–1.96) — —
Elderly women 4,786 54.4 8.0� RR 1.86 (1.21–2.84) 1.66 (1.05–2.60) — —

Modified revised NCEP definition#
Espinola-Klein et al., 2007 (98) Pts with CAD 811 43.0 6.7¶ HR — 2.50 (1.60–3.80) 18.4 7.4
Hsu et al., 2008 (70) Men 4,888 22.0 4.7§ HR — 1.40 (0.96–2.04) — —

Women 6,170 28.0 4.7§ HR — 1.85 (1.25–2.73) — —
Niwa et al., 2007 (72) Men 914 9.0 12.5§ HR 1.67 (0.65–4.34) 1.84 (0.68–4.96) 6.1 3.7

Women 1,262 1.7 12.5§ HR 1.12 (0.15–8.39) 1.31 (0.17–9.96) 4.5 2.03
Wang et al., 2007 (49) Elderly without T2DM 1,025 51.3 13.5¶ HR 1.37 (1.07–1.77) 1.31 (1.02–1.69) — —

Elderly men without T2DM 648 — 13.5¶ HR — 1.32 (0.93–1.87) — —
Elderly women without T2DM 377 — 13.5¶ HR — 1.29 (0.89–1.87) — —

*Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and risk estimates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates adjusting for any cardiovascular risk factor or component of the
metabolic syndrome (i.e., smoking, cholesterol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as having 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumference: men �102 cm; women �88
cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density lipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85 mm Hg); and 5) elevated fasting glucose (�110 mg/dl). §Mean follow-up. �Maximum follow-up. ¶Median
follow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised NCEP definition uses a lower cutoff for elevated fasting glucose
of � 100 mg/dl.

Abbreviations as in Tables 1 and 2.

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MetS Studies Reporting the Incidence of MITable 4 MetS Studies Reporting the Incidence of MI

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of MI† (95% CI) MI (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group
NCEP definition‡

Butler et al., 2006 (14) General population 3,035 38.5 6.0§ HR — 1.51 (1.12–2.05) 9.1 5.7

Men 1,473 — 6.0§ HR — — 12.1 8.1

Women 1,562 — 6.0§ HR — — 6.8 3.1

Pts with T2DM 461 77.9 6.0§ RR 0.95 (0.52–1.74) — 11.1 11.8

Pts without T2DM 2,562 31.6 6.0§ RR 1.51 (1.11–2.04) — 8.2 5.4

Girman et al., 2004 (99) Pts without T2DM 1,991 20.6 5.4¶� HR 1.49 (1.21–1.83) — — —

Pts without T2DM 3,188 46.0 5.0§ HR 1.49 (0.99–2.25) — — —

Holvoet et al., 2004 (100) Elderly 3,033 37.8 5.0§ RR 1.91 (1.35–2.72) 1.97 (1.35–2.86) 5.6 2.9

Solymoss et al., 2009 (94) Pts with �50% stenosis of CA 204 53.0 12.6¶ HR 2.36 (1.00–5.57) 2.25 (0.93–5.43) — —

Takeno et al., 2008 (48) Pts with AMI 461 37.3 1.5� HR — 0.84 (0.23–2.70) — —

Thorn et al., 2009 (101) Pts with type 1 diabetes 2,474 — 5.7� HR 2.61 (1.90–3.59) 1.85 (1.32–2.59) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 42.6 3.2� HR 1.54 (1.16–2.04) 1.61 (1.21–2.15) — —

Modified NCEP definition#

Chen et al., 2006 (52) Pts with renal disease and ACS 76 76.3 18.1¶ HR — — 16.0 0.0

Kasai et al., 2006 (54) Pts who underwent PCI 748 28.7 12¶ RR 1.35 (0.70–2.61) — 5.4 4.0

Kokubo et al., 2008 (81) Men 2,492 18.0 — HR 2.09 (1.30–3.37) 2.12 (1.31–3.43) 5.8 2.6

Women 2,840 20.7 — HR 2.68 (1.41–5.10) 2.77 (1.44–5.32) 3.6 0.8

Revised NCEP definition**

Nilsson et al., 2007 (102) Pts without T2DM 5,047 20.7 10.7¶ RR 1.99 (1.47–2.69) — 5.8 2.9

Men without T2DM 3,008 26.0 10.7¶ RR 1.87 (1.30–2.67) — 8.7 4.6

Women without T2DM 2,039 17.0 10.7¶ RR 1.48 (0.82–2.68) — 2.7 1.8

Noto et al., 2008 (66) General population 685 22.9 15.0§ HR — 1.91 (1.28–2.83) 7.5 3.9

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 50.1 3.2� HR 1.60 (1.20–2.14) 1.68 (1.25–2.26) — —

Pts with CV factor without T2DM 2,472 — 3.2� HR 1.57 (1.12–2.20) 1.65 (1.16–2.34) — —

*Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and risk estimates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates adjusting for any cardiovascular risk factor or component of the
metabolic syndrome (i.e., smoking, cholesterol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as having 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumference: men �102 cm; women �88
cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density lipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85 mm Hg); and 5) elevated fasting glucose (�110 mg/dl). §Maximum follow-up. �Median follow-up. ¶Mean
follow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised NCEP definition uses a lower cutoff for elevated fasting glucose
of �100 mg/dl.

Abbreviations as in Tables 1 and 2.
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1123JACC Vol. 56, No. 14, 2010 Mottillo et al.
September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

ipheral vasoconstriction and sodium retention. Hepatic
roduction of very low-density lipoprotein also increases,

eading to hypertriglyceridemia, low HDL cholesterol, ele-
ated apolipoprotein B, elevated small LDL cholesterol, and
onsequently, atherosclerosis. As a result of these lipid
mbalances, individuals with the metabolic syndrome typi-
ally exhibit a prothrombotic and proinflammatory state
15,17). More recent definitions by the NCEP (3), rNCEP
7), and the International Diabetes Federation (4) empha-
ize central obesity as the underlying component. Adipo-
ytes secrete mediators including TNF-�, leptin, adiponec-
in, and resistin, which lead to insulin resistance. In these
efinitions, it is postulated that central obesity causes
ystemic hypertension and dyslipidemia independently and
hrough the induction of insulin resistance.

Regardless of which definition is used, insulin resistance
nd central obesity are postulated to be the key components
f the metabolic syndrome, and both lead to glucose
ntolerance and dysglycemia. Consequently, even a small
hange in the fasting glucose threshold may have an
mportant impact on the associated cardiovascular risk. For
his reason, there has been considerable debate over the
mpact of lowering the fasting glucose threshold from �110
o �100 mg/dl. We therefore carried out a meta-analysis of
he cardiovascular risk associated with the rNCEP defini-

Figure 3 The Metabolic Syndrome and the Relative Risk for CV

I2 � 64%; 95% CI: 39% to 79%. BMI � body mass index; CVD � cardiovascular d

ion in addition to the original NCEP definition. s

Previous meta-analyses showed that the metabolic syn-
rome was associated with higher cardiovascular risk in
omen relative to men (9,10). In our meta-analysis, the
oint estimates for cardiovascular risk were consistently
igher in women compared with men. However, patient-

evel data are needed to confirm this finding. The mecha-
isms explaining a potentially higher cardiovascular risk in
omen with the metabolic syndrome are unclear; however,

everal theories have been postulated (18 –20). First, central
diposity tends to be more pronounced in women post-
enopause than in men, and thus may be linked to a higher

isk of cardiovascular disease (18). Second, the cholesterol
rofile is different in women compared with men. HDL
holesterol decreases post-menopause and LDL cholesterol
ncreases post-menopause, with LDL particles becoming
enser, and therefore, more atherogenic (19). Third, there is
vidence that elevated triglycerides are more highly associ-
ted with coronary artery disease in women than in men. In
meta-analysis, it was shown that an increase in triglycer-

des of 18 mg/dl was associated with a 76% increased
ardiovascular risk in women compared with a 32% in-
reased risk in men (20). Finally, several studies have
uggested a number of other unique risk factors that may be
esponsible for a stronger association between the metabolic

; other abbreviations as in Figure 2.

D
isease

yndrome and cardiovascular risk in women. These risk

MetS Studies Reporting the Incidence of StrokeTable 5 MetS Studies Reporting the Incidence of Stroke

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of Stroke† (95% CI) Stroke (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group
NCEP definition‡

Boden-Albala et al., 2007 (103) General population 3,297 44.0 6.4§ HR — 1.50 (1.10–2.20) — —

Men 1,220 38.0 6.4§ HR — 1.10 (0.60–1.90) — —

Women 2,077 48.0 6.4§ HR — 2.00 (1.30–3.10) — —

Hsia et al., 2003 (104) Women with angiographic disease 397 61.2 2.8§ RR 1.90 (0.52–6.91) — 3.7 1.9

McNeill et al., 2005 (105) Men 6,881 23.7 11.0§ RR 1.28 (0.87–1.89) — 2.2 1.7

Women 5,208 22.7 11.0§ RR 5.45 (3.92–7.59) — 7.4 1.4

Qiao et al., 2009 (106) Men without CAD and T2DM 4,041 — 21.0� HR 1.30 (0.92–1.83) — — —

Women without CAD and T2DM 3,812 — 21.0� HR 2.30 (1.36–1.90) — — —

Solymoss et al., 2009 (94) Pts with �50% stenosis of CA 876 53.0 12.6§ HR 1.67 (1.18–2.37) 1.68 (1.18–2.39) — —

Thorn et al., 2009 (101) Pts with type 1 diabetes 2,474 — 5.7¶ HR 1.94 (1.25–3.02) 1.51 (0.94–2.44) — —

Vlek et al., 2008 (107) Hypertensive pts without T2DM 1,815 42.7 3.9§ HR 1.36 (0.85–2.16) — — —

Wang et al., 2008 (108) Elderly without T2DM 991 42.1 13.8¶ HR 1.62 (1.17–2.24) — — —

Wassink et al.,2008 (50) Pts with CV risk factor 3,196 42.6 3.2¶ HR 1.66 (1.10–2.49) 1.73 (1.13–2.65) — —

Modified NCEP definition#

Chen et al. 2006 (109) Men 725 45.5 10.4§ HR 5.80 (2.00–16.50) — 9.1 1.0

Women 831 58.7 10.4§ HR 2.50 (0.70–8.40) — 7.7 0.7

Chien et al., 2007 (110) General population 3,507 24.2 9.0¶ HR — 2.05 (1.45–2.91) — —

Hwang et al., 2009 (80) Men 1,761 21.7 8.7§ RR 1.35 (0.80–2.25) — 5.0 3.7

Women 674 11.4 8.7§ RR 4.98 (2.23–11.13) — 11.7 2.4

Iso et al., 2007 (111) Men 3,813 — 18.3¶ HR 1.90 (1.30–2.80) 2.00 (1.30–3.10) — —

Women 5,646 — 18.3¶ HR 1.40 (1.00–2.10) 1.50 (1.00–2.30) — —

Kokubo et al., 2008 (81) Men 2,492 18.0 — HR 1.52 (0.99–2.34) 1.58 (1.02–2.43) 6.5 4.0

Women 2,840 20.7 — HR 1.70 (1.09–2.64) 1.62 (1.02–2.58) 6.0 2.5

Koren-Morag et al., 2005 (112) Pts with CAD without T2DM 10,784 34.3 8.1� RR 1.44 (1.18–1.76) — 4.3 3.0

Men with CAD without T2DM 8,844 — 8.1� RR 1.31 (1.05–1.64) — 4.2 3.2

Women with CAD without T2DM 1,903 — 8.1� RR 2.09 (1.28–3.42) — 4.8 2.3

Kurl et al., 2006 (113) Men without T2DM 1,264 9.0 14.3§ RR 2.00 (1.01–3.95) 2.39 (1.17–4.89) — —

Ninomiya et al., 2007 (82) Men 1,050 20.6 14.0� HR 2.04 (1.33–3.14) 1.92 (1.23–2.98) 14.4 7.6

Women 1,402 29.9 14.0� HR 1.43 (0.99–2.08) 1.50 (1.03–2.19) 11.9 6.6

Song et al., 2007 (84) Women with BMI �25 kg/m2 13,256 4.3 10.0¶ RR 1.35 (0.74–2.45) 1.24 (0.64–2.39) 2.1 1.0

Women with BMI 25–29.9 kg/m2 7,834 4.3 10.0¶ RR 2.07 (1.23–3.47) — 1.7 0.8

Women with BMI �30 kg/m2 4,266 4.3 10.0¶ RR 1.79 (0.96–3.32) — 1.3 0.8

Takahashi et al., 2007 (13) Women without T2DM 726 1.1 6.4§ RR — 23.1 (2.7–19.6) — —

Takeuchi et al., 2005 (85) Men 780 25.3 6.0� RR — 1.61 (1.26–2.06) — —

Wannamethee et al., 2005 (114) Men 5,228 25.5 20.0� RR 1.51 (1.20–1.91) — 7.6 5.0

(continued on next page)
1
1

2
4

M
ottillo
et
al.
JACC
Vol.56,No.14,2010
The
M
etabolic
Syndrom
e
and
C
ardiovascular
R
isk
Septem
ber28,2010:1113–32

ContinuedTable 5 Continued

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure
Risk of Stroke† (95% CI) Stroke (%)
Least Adjusted Most Adjusted MetS Group Non-MetS Group
Revised NCEP definition**

Nilsson et al., 2008 (102) Pts without T2DM 5,047 20.7 10.7§ RR 2.47 (1.83–3.34) — 6.4 2.6

Men without T2DM 3,008 26.0 10.7§ RR 2.10 (1.39–3.18) — 7.0 3.3

Women without T2DM 2,039 17.0 10.7§ RR 2.71 (1.75–4.19) — 5.9 2.2

Noto et al., 2008 (66) General population 685 22.9 15.0� HR 1.44 (0.94–2.19) — 6.8 3.5

Qiao et al., 2009 (106) Men without CAD and T2DM 4,041 — 21.0� HR 1.13 (0.81–1.58) — — —

Women without CAD and T2DM 3,812 — 21.0� HR 2.08 (1.24–3.51) — — —

Rodriguez-Colon et al., 2009 (115) General population 14,993 39.0 9.0� RR 2.45 (1.96–3.08) 2.24 (1.78–2.82) 3.2 1.3

Men 6,732 39.0 9.0� RR 1.98 (1.47–2.67) 2.11 (1.56–2.85) 3.7 1.9

Women 8,261 39.0 9.0� RR 3.27 (2.29–4.67) 2.41 (1.69–3.49) 2.9 1.1

Simons et al., 2007 (68) Elderly men 1,233 31.1 16.0� HR 1.43 (1.07–1.92) 1.31 (0.96–1.77) 70.1 15.8

Elderly women 1,572 34.1 16.0� HR 1.53 (1.17–2.01) 1.37 (1.04–1.82) 17.0 12.2

Wang et al., 2008 (108) Elderly without T2DM 991 50.8 13.8¶ HR 1.52 (1.10–2.11) — — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 50.1 3.2¶ HR 1.75 (1.15–2.66) 1.77 (1.14–2.75) — —

Pts with CV factor without T2DM 2,472 — 3.2¶ HR 1.88 (1.18–2.99) 1.96 (1.21–3.18) — —

Wild et al., 2009 (116) General population 762 34.7 15.0� RR 2.61 (1.52–4.48) — 4.2 11.0

Modified revised NCEP definition#

Chen et al., 2006 (109) Men 709 48.6 10.4§ HR 8.20 (2.00–34.30) — 8.9 0.7

Women 850 57.3 10.4§ HR 2.60 (0.60–11.30) — 6.8 0.6

*Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and risk estimates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates adjusting for any cardiovascular risk factor or component of the
metabolic syndrome (i.e., smoking, cholesterol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as having 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumference: men �102 cm; women �88
cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density lipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85 mm Hg); and 5) elevated fasting glucose (�110 mg/dl). §Mean follow-up. �Maximum follow-up. ¶Median
follow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised NCEP definition uses a lower cutoff for elevated fasting glucose
of �100 mg/dl.

Abbreviations as in Tables 1 and 2.
1
1

2
5

JACC
Vol.
56,
No.
14,
2010
M
ottillo
et
al.
Septem
ber
28,
2010:1113–32
The
M
etabolic
Syndrom
e
and
C
ardiovascular
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isk

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1126 Mottillo et al. JACC Vol. 56, No. 14, 2010
The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

actors include polycystic ovary syndrome (21), hormonal
ontraceptive use (22–24), and gestational diabetes (25).

Our results also suggest that the metabolic syndrome
aintains its prognostic value for cardiovascular outcomes

n the absence of type 2 diabetes mellitus. Some experts have
uggested that the reason the metabolic syndrome is asso-
iated with an increase in cardiovascular risk is because most
atients with the metabolic syndrome also have type 2
iabetes mellitus (8). However, after synthesizing the results
f studies conducted in patients without type 2 diabetes
ellitus, the metabolic syndrome remained associated with
high cardiovascular risk, ranging from RR: 1.62 (95% CI:
.31 to 2.01; I2 � 0%; 95% CI: 0% to 90%) for MI, to RR:
.86 (95% CI: 1.10 to 3.17; I2 � 89; 95% CI: 56% to 97%)
or stroke. The risk for all-cause mortality in patients
ithout type 2 diabetes mellitus (RR: 1.32; 95% CI: 0.65 to
.67; I2 � 87; 95% CI: 47% to 97%) was accompanied by a
ide and therefore inconclusive confidence interval because

his analysis involved only 2 studies (n � 3,622 patients).
ore studies are needed to confirm whether or not the
etabolic syndrome is prognostic in this population.
Our systematic review allowed us to identify an important

ap in the literature. The prognostic importance of the
etabolic syndrome, compared with that of the sum of its

ndividual components (obesity, systemic hypertension, el-
vated fasting glucose, elevated triglycerides, and low HDL
holesterol), has repeatedly been challenged (8,26,27). In a
ohort study of 2,815 patients, the risk of CVD mortality
ssociated with the metabolic syndrome as defined by the
CEP definition (HR: 2.53; 95% CI: 1.74 to 3.67) was

imilar to the risk associated with impaired fasting glucose
HR: 2.87; 95% CI: 1.96 to 4.20) and systemic hypertension
HR: 1.71; 95% CI: 1.15 to 2.54) (28). Furthermore, in a
ystematic review of 7 clinical trials (n � 3,459), the
etabolic syndrome as defined by the NCEP definition was

o longer an independent predictor of atherosclerotic plaque
rogression after adjustment for its individual components
29). Despite these studies, there remains debate as to
hether or not the metabolic syndrome provides a syner-
istic effect that increases its association with cardiovascular
isk. Of the 87 studies included in our systematic review,
nly 5 reported risk estimates that were adjusted for at least
component of the metabolic syndrome (Online Table 5).
f these 5 studies, 3 adjusted for obesity, 3 adjusted for

ystemic hypertension, and 1 adjusted for fasting glucose.
here is a need for prospective studies that investigate the

isk associated with the metabolic syndrome independent of
he risk of its individual components in order to establish
hether or not the metabolic syndrome adds any prognostic

ignificance.
Our results allow us to confirm the strong association of

he 2001 NCEP definition of the metabolic syndrome with
ardiovascular risk. Furthermore, to our knowledge, no
revious meta-analyses have been conducted to establish the
ardiovascular risk associated with the 2004 rNCEP defi-

nition. We recommend that health care workers use theSu
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1127JACC Vol. 56, No. 14, 2010 Mottillo et al.
September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

Figure 4 The Metabolic Syndrome and the Relative Risk for CVD Mortality

I2 � 81%; 95% CI: 72% to 88%. Abbreviations as in Figure 2.

Figure 5 The Metabolic Syndrome and the Relative Risk for MI

I2 � 40%; 95% CI: 0% to 73%. Abbreviations as in Figure 2.

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1128 Mottillo et al. JACC Vol. 56, No. 14, 2010
The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

etabolic syndrome as a diagnostic tool for identifying
atients who are at risk for cardiovascular events. There is
n urgent need to develop and implement prevention and
reatment strategies, such as lifestyle programs, diets, and
harmacotherapies to reduce the prevalence of the meta-
olic syndrome and its associated cardiovascular risk
30,31).
revious studies. Two previous meta-analyses, which in-
luded studies published prior to 2005, investigated the
ardiovascular risk associated with the metabolic syndrome
9,10). An additional 71 studies investigating the NCEP
nd rNCEP definitions have been published since the
onduct of these meta-analyses, and these studies were
ncluded in our meta-analysis (32). We also established
he cardiovascular risk associated with the rNCEP defi-
ition of the metabolic syndrome, which was only re-

eased in 2004 (7). Finally, we confirmed that there was
ittle variation in cardiovascular risk between the modi-
ed NCEP and rNCEP definitions compared with the

Figure 6 The Metabolic Syndrome and the Relative Risk for Str

I2 � 88%; 95% CI: 82% to 91%. Abbreviations as in Figures 2 and 3.

riginal NCEP definition. v

The 2 previous meta-analyses concluded that the meta-
olic syndrome nearly doubled the risk of cardiovascular
vents. We obtained consistently higher point estimates for
ardiovascular outcomes (RR �2) and showed that the risk
or CVD, CVD mortality, and stroke exceeds that of
ll-cause mortality. However, there remains a need for
uture studies to investigate the cardiovascular risk associ-
ted with the metabolic syndrome after its individual com-
onents have been adjusted for.
tudy limitations. Our meta-analysis has a number of
otential limitations. The inclusion of observational cohort
tudies in our meta-analysis presented challenges beyond
hose typically encountered in meta-analyses of randomized
ontrolled trials. First, of the 87 studies included in our
aper, only 34 studies reported count data that we pooled.
he remaining 53 studies only reported risk estimates (RR
r HR), which were not included in our pooled analyses.
owever, we included these 53 studies in tables as part of

ur systematic review. Second, the length of follow-up

oke

aried considerably between studies. However, in a sensi-

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1129JACC Vol. 56, No. 14, 2010 Mottillo et al.
September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

ivity analysis, we stratified studies by the length of
ollow-up and found that studies with longer follow-up
imes had risk estimates that were similar to those in studies
ith shorter follow-up times. There was also some hetero-
eneity in baseline patient characteristics, such as the
nclusion of patients with atherosclerosis, systemic hyper-
ension, or a history of CVD. Due to the presence of
otential heterogeneity between studies, data were analyzed
sing random-effects models, which incorporate both
ithin- and between-study variability. In addition, we

onducted a sensitivity analysis in which we restricted our
nalyses to studies of subjects without systemic hyperten-
ion, atherosclerosis, or cardiovascular disease. The results
f these analyses are consistent with those of our primary
nalysis. A third potential limitation was the limited num-
er of studies available to estimate the cardiovascular risk
ssociated with the metabolic syndrome in our subgroup
nalyses of men, women, and patients without type 2
iabetes mellitus. We could not conduct meta-regression
nalyses to estimate the effect of these covariates on the
etabolic syndrome– cardiovascular risk association since

he number of studies investigating these subgroups was
mall. A fourth limitation includes the inherent assumptions
f meta-analysis. We were limited to data reported in
ublished articles and did not have access to individual
atient-level data. Access to patient-level data would have
een particularly helpful for our subgroup analyses. Fifth,
isual assessment of funnel plots suggests that mild publi-
ation bias may be present. Publication bias is an inherent
imitation to virtually all meta-analyses. Finally, our meta-
nalysis was limited to studies published in English. How-
ver, �5% of studies identified in our literature search were
ublished in a language other than English, and their
xclusion is unlikely to substantially affect the conclusions of
ur meta-analysis.

onclusions

he metabolic syndrome is associated with a 2-fold increase in
isk for CVD, CVD mortality, MI, and stroke, and a 1.5-fold
ncrease in risk for all-cause mortality. There is little variation
n risk between the NCEP and rNCEP definitions of the

etabolic syndrome. There is also little variation in risk for the
odified NCEP and rNCEP definitions compared with the

riginal NCEP definition. In addition, our results indicate that
atients with the metabolic syndrome, but without type 2
iabetes mellitus, are still at high risk for CVD mortality, MI,
nd stroke. We therefore suggest that the metabolic syndrome
oes not require type 2 diabetes mellitus in its definition in
rder to be closely associated with cardiovascular risk. Our
ystematic review identified an important gap in the literature;
tudies are needed to investigate whether or not the prognostic
ignificance of the metabolic syndrome exceeds the risk asso-
iated with the sum of its individual components. We recom-
end that health care workers use the metabolic syndrome to

dentify patients who are at particularly high risk for cardio-

ascular complications. The prevention and reduction of the
etabolic syndrome is essential to reduce cardiovascular dis-

ase and to extend life in the adult population.

cknowledgments
he authors would like to thank Tara Dourian, Yevgeniya
izina, and Susan Wakil for their help with data abstraction.

eprint requests and correspondence: Dr. Mark J. Eisenberg,
epartment of Medicine, Divisions of Cardiology and Clinical
pidemiology, Sir Mortimer B. Davis Jewish General Hospital,
cGill University, 3755 Cote Ste Catherine, Suite H-421.1, Montreal,
uebec H3T 1E2, Canada. E-mail: mark.eisenberg@mcgill.ca.

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ey Words: cardiovascular disease y cardiovascular risk y meta-analysis
metabolic syndrome y mortality y National Cholesterol Education

rogram.

APPENDIX

or supplementary tables, please see the online version of this article.

The Metabolic Syndrome and Cardiovascular Risk
Methods
Data sources and searches
Study selection
Data extraction
Data synthesis and analysis
Results
Search results and study inclusion
The metabolic syndrome and cardiovascular risk
Sensitivity analyses
Discussion
Previous studies
Study limitations
Conclusions
Acknowledgments
REFERENCES
APPENDIX

C l i n i c a l r e s e a r c h

Metabolic syndrome in psychiatric patients:
overview, mechanisms, and implications
Brenda W. J. H. Penninx, PhD; Sjors M. M. Lange, MD

Introduction

Psychiatric patients have a greater risk of prema-
ture all-cause mortality than the general population.
Epidemiological studies show that the life expectancy
of patients with major psychiatric disorders is reduced
by 7 to 24 years.1 Psychiatric illness takes a toll at least
as great as the 8-year difference exacted by heavy
smoking.1 About 60% of the excess mortality observed

Copyright © 2018 AICH – Servier Research Group. All rights reserved 63 www.dialogues-cns.org

Keywords: abdominal obesity; bipolar disorder; cardiovascular disease; depres-
sion; dyslipidemia; metabolic syndrome; review; schizophrenia

Author affiliations: Department of Psychiatry, VU University Medical
Center & GGZ InGeest, Amsterdam, The Netherlands

Address for correspondence: Brenda W. J. H. Penninx, VU University Medi-
cal Center, Oldenaller 1, Amsterdam, The Netherlands
(email: b.penninx@vumc.nl)

Psychiatric patients have a greater risk of premature mortality, predominantly due to cardiovascular diseases (CVDs).
Convincing evidence shows that psychiatric conditions are characterized by an increased risk of metabolic syndrome
(MetS), a clustering of cardiovascular risk factors including dyslipidemia, abdominal obesity, hypertension, and hy-
perglycemia. This increased risk is present for a range of psychiatric conditions, including major depressive disorder
(MDD), bipolar disorder (BD), schizophrenia, anxiety disorder, attention-deficit/hyperactivity disorder (ADHD), and
posttraumatic stress disorder (PTSD). There is some evidence for a dose-response association with the severity and
duration of symptoms and for a bidirectional longitudinal impact between psychiatric disorders and MetS. Associa-
tions generally seem stronger with abdominal obesity and dyslipidemia dysregulations than with hypertension.
Contributing mechanisms are an unhealthy lifestyle and a poor adherence to medical regimen, which are prevalent
among psychiatric patients. Specific psychotropic medications have also shown a profound impact in increasing
MetS dysregulations. Finally, pleiotropy in genetic vulnerability and pathophysiological mechanisms, such as those
leading to the increased central and peripheral activation of immunometabolic or endocrine systems, plays a role
in both MetS and psychiatric disorder development. The excess risk of MetS and its unfavorable somatic health con-
sequences justifies a high priority for future research, prevention, close monitoring, and treatment to reduce MetS
in the vulnerable psychiatric patient.
© 2018, AICH – Servier Research Group Dialogues Clin Neurosci. 2018;20:63-72.

C l i n i c a l r e s e a r c h

in psychiatric patients is due to physical comorbidities,
predominantly cardiovascular diseases (CVDs).2 In-
deed, the CVD risk, but also that of the related comor-
bidities of diabetes, stroke, and obesity, has proven to
be significantly increased in a multitude of psychiatric
conditions, including depression,3 schizophrenia,4 bipo-
lar disorder (BD),5 and anxiety disorder.6
To assist clinicians in identifying and treating pa-
tients at an increased risk of CVD, the concept of meta-
bolic syndrome (MetS) was introduced. MetS is defined
by a combination of abdominal obesity (also known as
central obesity), high blood pressure, low high-density
lipoprotein cholesterol (HDL-C), elevated triglycer-
ides, and hyperglycemia. MetS indicates a preclinical
state for the development of CVD and diabetes.7 Vari-
ous definitions for MetS have been proposed and are
all aimed at being easy to use in clinical settings and
all share similar diagnostic thresholds.8 However, ab-
dominal obesity is central to the MetS definition of the
International Diabetes Federation, whereas it is not a
mandatory criterion in the MetS definition of the Na-
tional Cholesterol Education Program (NCEP) Adult
Treatment Panel III.8 One should be aware that MetS
is a heterogeneous concept: hypertension, dyslipidemia,
and hyperglycemia are highly comorbid and intercor-
related, but their pathophysiologies do not necessarily
overlap. However, as a prevalent condition and predic-
tor of CVD across racial, gender, and age groups, MetS
provides the opportunity to identify high-risk popula-
tions and prevent the progression of some major causes
of morbidity and mortality.
In line with an increased cardiovascular mortality
risk, a recent meta-analysis showed that the prevalence
of MetS is 58% higher in psychiatric patients than in
the general population.2 This increased prevalence is
seen independently of the MetS definition used and is
consistently observed for each of the MetS components,
although to a lesser extent in hypertension. The risk of
MetS was similarly elevated in those with schizophre-
nia, BD, and major depressive disorder (MDD), which
suggests that MetS is a general comorbidity seen in
different psychiatric patient groups. Consequently, it
is likely that in large part, general, nonspecific disease
mechanisms contribute to the MetS–psychiatric disease
comorbidity. Below we describe the current evidence
base of MetS dysregulations in various individual psy-
chiatric conditions. Mechanisms inherent to psychiatric
disorders that contribute to an increased MetS risk are

then discussed. We conclude by describing clinical im-
plications and future directions.

MetS and major depression

Pan et al systematically reviewed 29 cross-sectional
studies involving 155 333 subjects and found depres-
sion (either defined through self-reported symptoms
or a psychiatric disorder) and MetS to be modestly as-
sociated (adjusted odds ratio [OR]=1.34).9 In the ap-
proximately 3000 subjects in the Netherlands Study of
Depression and Anxiety conducted among psychiatric
patients, we confirmed an association between ma-
jor depression and MetS and showed evidence for a
dose-response association between the two.10 Prospec-
tive evidence is scarce but does confirm a bidirectional
relationship, with depression predicting the onset of
MetS, and MetS predicting the onset of depression over
time.9 The most consistent evidence exists between de-
pression and obesity-related components (abdominal
obesity, low HDL-C, hypertriglyceridemia), whereas
associations with hyperglycemia and hypertension are
confirmed less frequently.11 Three longitudinal studies
among depressed patients found that a combination of
multiple metabolic dysregulations contributes to the
sustained chronicity of depression.12–14 Once both are
present, MetS abnormalities may contribute to patients
maintaining a depressed state.
To what extent does antidepressant utilization con-
tribute to an increased MetS risk among depressed
individuals? Several studies have illustrated that an-
tidepressants have an impact on (subtle) metabolic
dysregulations. There is consistent evidence that an-
tidepressant medications, especially tricyclic antide-
pressants (TCAs) and serotonin and norepinephrine
reuptake inhibitors (SNRIs), increase cardiac vagal con-
trol,11,15 which contributes to elevated systolic and dia-
stolic blood pressure and hypertension among medica-
tion users.16 Autonomic activity differences diminished
when antidepressant medication use was stopped.15 In
a meta-analysis of treatment trials, Serretti and Man-
delli17 evaluated short-term weight change after anti-
depressant treatment. Amitriptyline, mirtazapine, and
paroxetine were associated with a greater risk of weight
gain. In contrast, weight loss seems to occur with fluox-
etine and bupropion, although the effect of fluoxetine
appears to be limited to the acute phase of treatment.
Other compounds were found to have a transient or

64

Metabolic syndrome in psychiatric patients – Penninx and Lange Dialogues in Clinical Neuroscience – Vol 20 . No. 1 . 2018

negligible effect on body weight in the short term. It is
important to indicate that—despite some detrimental
metabolic impact—a favorable impact of antidepres-
sant use on body weight has been illustrated. Hannes-
tad and colleagues18 meta-analyzed 22 studies and
found that antidepressants, mainly selective serotonin
reuptake inhibitors (SSRIs), reduced cytokine levels
during treatment.
In a 6-year observational study with three assess-
ment waves, antidepressant use was consistently asso-
ciated with metabolic dysregulation at all assessment
waves, and it exerted a negative, longitudinal impact on
subsequent metabolic health.19 Compared with antide-
pressant nonusers, TCA use was associated with lower
HDL-C, and the use of most types of antidepressants
(TCA, SSRI, SNRI) was associated with higher waist
circumference, triglycerides, and a number of MetS
abnormalities. Effect sizes observed were somewhat
stronger for TCA use than for use of SSRIs and SN-
RIs, particularly for waist circumference. As this study
also included drug-naive depressed patients, it could
illustrate that both symptom severity and antidepres-
sant use exerted independent effects on MetS and that
patients without antidepressant medication have an in-
creased MetS risk. Finally, it is important to point out
that the prevalence of MetS abnormalities may partly
depend on the depression symptom profile. Recent
studies point more toward MetS abnormalities in de-
pressed persons with many atypical, neurovegetative
symptoms, including hyperphagia, hypersomnia, lack of
energy, and leaden paralysis.11,20,21

MetS and bipolar disorder

In line with observations on MDD, MetS prevalence
has been found to be higher in BD. In a study among
972 younger bipolar and unipolar depressed patients
in a current depressive episode, both patient groups
showed a comparably higher MetS prevalence than
population controls.22 Patients had higher body mass
index (BMI), higher levels of glucose, total cholester-
ol, low-density-lipoprotein cholesterol (LDL-C), and
lower HDL-C levels, but did not differ in hypertension
from healthy controls. Other studies have indicated that
the increased MetS risk extends to BD patients who are
not in a current depressive episode. Vancampfort et al
meta-analyzed 37 studies involving around 7000 BD pa-
tients and found an overall MetS rate of 37.3%.23 When

compared with general population groups, BD patients
had 1.98-times higher MetS rates.
Vancampfort’s meta-analysis also investigated the
role of clinical characteristics.23 As five studies investi-
gated patients with bipolar 1 disorder (BD-1), and oth-
ers concerned mixed or unspecified diagnostic groups, it
was possible to compare MetS risks. The BD-1 patients
had a significantly lower risk of MetS. However, as the
mixed or unspecified diagnostic groups were older on
average, this result could simply reflect age differences.
Six of the included studies in the meta-analysis23 also
reported MetS prevalence in BD patients using antipsy-
chotic medication compared with antipsychotic-free BD
patients. BD patients using antipsychotic medication
were at a significantly 1.72 times greater risk of MetS
relative to antipsychotic-free patients. Individual stud-
ies that directly compared BD patients on medication
with those using placebo or no medication confirm the
role of medication on metabolic dysregulations. A me-
ta-analysis demonstrated that patients receiving lithium
gained more weight than those receiving a placebo.24
Similarly, in a pooled analysis of placebo-controlled tri-
als in patients with acute mania associated with BD-1,
olanzapine, quetiapine, risperidone, and valproic acid
were all associated with greater weight gain than the
placebo.25 As most studies examined BD patients on
psychotropic medications, there is not much literature
on the MetS risk in drug-naive BD patients. However,
some recent studies do suggest that the increased MetS
risk extends to drug-naive BD patients.22,26,27

MetS and schizophrenia

Also in schizophrenia, CVD is the leading cause of
death.28 Vancampfort’s meta-analysis found schizophre-
nia patients to have a significantly higher risk of abdom-
inal obesity (OR=4.43), hypertension (OR=1.36), low
HDL-C (OR=2.35), hypertriglyceridemia (OR=2.73),
and MetS (OR=2.35).29 Metabolic disturbances in
schizophrenia do increase with illness duration30 and
with age.31 Schizoaffective disorder has shown slightly
higher rates of MetS than has schizophrenia.32
Quite a number of studies have been dedicated to
the contribution of antipsychotics to MetS dysregula-
tions. In particular, second-generation antipsychotics
have been shown to cause weight gain, abdominal obe-
sity, lipid and glucose metabolism alterations, and insu-
lin resistance,33 which are side effects that lead to high

65

C l i n i c a l r e s e a r c h

66

rates of medication discontinuation. Second-generation
antipsychotics associated with extensive weight gain
are also the ones associated with most metabolic al-
terations, with weight gain reported in up to 72% of all
antipsychotic-receiving patients.34 However, some stud-
ies have reported metabolic alterations to occur even
without weight gain.28 The antipsychotics clozapine
and olanzapine have the highest weight gain potential
through the dysregulation of adipose tissue homeosta-
sis.35 A common target of all antipsychotics is the dopa-
mine D

2
receptor, located in the brain where dopamine

has an effect on food intake and body weight, as well as
in the body where dopamine impacts insulin-producing
β-cells of the pancreas.36 Pathways through oxidative
stress reactions,35 altered ghrelin and leptin release,35
dysfunctions in the autonomic nervous system activ-
ity,37 inflammatory35 and other signaling pathways (eg,
those involving dopamine, histamine, serotonin, mus-
carinic mechanisms, cannabinoids, and adiponectin)35
have also been implicated as important contributing
processes leading to MetS comorbidity with the use of
antipsychotics.35

Controversial results have been reported on wheth-
er schizophrenia itself confers an inherent risk for met-
abolic alterations or whether the impact is solely due
to antipsychotic use. Some individual studies could not
detect metabolic alterations in first-episode, drug-naive
patients,30 but these nonsignificant findings could also
be due to small sample sizes, low severity, and short
disease duration. In fact, several recent findings clearly
point toward metabolic alterations due to schizophre-
nia itself, in the absence of medication and chronic (be-
havioral) alterations. Glucose homeostasis,38 waist:hip
ratio,31 and visceral fat31 have been shown to be altered
from illness onset and also in the absence of antipsy-
chotic use. Others reported MetS alterations in at-risk
populations who do not have schizophrenia themselves,
such as in family members and in ultra-high-risk groups
for psychosis.30

MetS and other psychiatric disorders

Anxiety is part of a symptom continuum ranging from
a comorbid symptom to a full-blown separate diagno-
sis. Both sides of this continuum seem to have influence
on MetS risk,39 although reported associations are not
always robust.40,41 Within-study comparisons of associa-
tions between anxiety and depression with MetS found

similar,19 as well as weaker,40,41 associations for anxiety.
A recent meta-analysis summarizing 18 cross-section-
al studies examining MetS risk in persons with high
anxiety found a weak, but significantly increased risk
(OR=1.07).42 The two longitudinal studies in this meta-
analysis could not confirm a prospective association. In
a medical records analysis,43 patients with anxiety had
higher cardiometabolic risks: diabetes (OR=1.31), hy-
pertension (OR=1.21), hyperlipidemia (OR=1.25), and
obesity (OR=1.09).44 These odds, although significant,
are still slightly lower than those found for some other
psychiatric conditions.
Several studies have examined the prevalence of
MetS in patients with posttraumatic stress disorder
(PTSD). A meta-analysis of nine studies compared
MetS across 9673 PTSD patients with 6852 controls.45
The pooled MetS prevalence in PTSD patients was
38.7%. In comparison with matched general population
controls, patients with PTSD had a 1.82-times higher
risk for MetS.45 This risk was found to be consistent
across geographical regions and populations (war vet-
erans or not).
Personality disorders (PD), and in particular border-
line PD, are associated with multiple cardiovascular risk
factors, but the inherent impact of PD itself on MetS
risk has not yet been examined. The use of second-gen-
eration antipsychotics in PD is common practice and co-
morbid psychiatric disorders are prevalent, making PD
patients a group vulnerable to MetS abnormalities.46 A
lack of data is also an issue for obsessive compulsive
disorder. An Italian study of 104 patients found MetS to
be present in 21.2% of cases, but the confidence interval
encompassed that of the general population estimate.47

A recent meta-analysis showed that 1 out of 5 pa-
tients (21.5%) with alcohol-use disorders (AUDs) had
MetS.48 The prevalence of MetS was found to be espe-
cially high in patients with high psychiatric comorbidity.
An important moderator for the MetS risk in AUDs is
chronic liver disease, which has a profound influence on
lipid metabolism. Heroin and methadone users showed
a MetS prevalence of 29.5% with exposure time to
methadone use as a significant predictor of MetS.49
Drugs themselves, for instance (meth)amphetamine,
have an important influence on glucose metabolism,
have immunosuppressive or proinflammatory proper-
ties, and are cardiotoxic.49 For drug- and alcohol-depen-
dence disorders, studies including a healthy reference
group are necessary to indicate more precisely to what

Metabolic syndrome in psychiatric patients – Penninx and Lange Dialogues in Clinical Neuroscience – Vol 20 . No. 1 . 2018

67

extent these disorders increase the overall MetS risk
when compared with the general population.
Even childhood developmental disorders have
been related to some extent to MetS dysregulations, al-
though large-scale studies examining the entire concept
of MetS are absent. A medical record study indicated
that children with autism spectrum disorders are at an
increased risk of obesity and obesity-related disorders
(OR=1.85).50 This study also indicated that autistic pa-
tients may be at risk partly because they are commonly
using antipsychotics, antidepressants, or antiepileptics
for extended periods of time.50 Whereas hardly any re-
search has been done in children with attention-deficit/
hyperactivity disorder (ADHD), some reports in adults
indicate that ADHD may involve an increased BMI
and alterations in lipid profiles, although findings seem
inconsistent51,52 and well-powered studies are lacking.

Mechanisms connecting MetS and
psychiatric disorders

How may we explain the increased MetS risk in per-
sons with a psychiatric disorder? As illustrated above,
the use of psychotropic medications can partly contrib-
ute to the observed increased MetS risk in psychiatric
patients. However, it is also clear that the increased risk
of MetS is present in patient groups using very different
types of treatments and also extends to patients not on
treatment. Consequently, the increased MetS risk is also
very likely to be inherent to the presence of psychiatric
disease itself. Considering that the increased MetS risk
is seen in various different psychiatric patient popula-
tions, it is likely that general (nonspecific) mechanisms
are in play. Some important potential connecting mech-
anisms are discussed below.

Poorer lifestyle and medical care

General factors predisposing psychiatric patients to
MetS include unhealthy lifestyle choices such as smok-
ing, excessive alcohol intake, poor sleep hygiene, physi-
cal inactivity, and unhealthy nutritional patterns, which
are all more common in different psychiatric patient
groups.11,35 These are known behavioral risk factors that
contribute to poorer cardiovascular health and an in-
creased risk of MetS. Various individual studies examin-
ing MetS in psychiatric patients have often attempted to
adjust for basic lifestyle factors such as smoking habits

and activity patterns. When doing so, MetS associations
are generally not much reduced. However, it is notori-
ously difficult to fully quantify the impact of lifestyle in
psychiatric patients, as it can only be partly captured us-
ing self-report information, and therefore residual con-
founding likely exists. Considering the huge impact of
lifestyle on MetS, and the fact that psychiatric patients
generally live unhealthier lives across many aspects,
poor lifestyle plays a role in the psychiatric disorder–
MetS association. In addition, the reduced likelihood
of psychiatric patients receiving standard (optimal) lev-
els of medical care likely contributes to an unhealthier
metabolic profile among psychiatric patients.53

Central and peripheral immune, metabolic, and
endocrine dysregulations

Accumulating evidence suggests that different psychi-
atric patient groups share inherent pathophysiological
features of dysregulated homeostasis systems, includ-
ing the hypothalamic-pituitary-adrenal (HPA)-axis and
inflammatory response. These pathophysiological fea-
tures all have links to MetS development as well.
Regarding the HPA-axis, disturbances of glucocor-
ticoid sensitivity accompanied with a systemic cortisol
action is a well-recognized characteristic in patients
with stress-related disorders.54 HPA-axis hyperactiva-
tion determines visceral fat accumulation via increased
lipid storage and adipogenesis.55 This glucocorticoid-
mediated effect is amplified in abdominal adipose tis-
sue expressing a high density of glucocorticoid recep-
tors. Hypercortisolemia induces lipolysis, the release of
fatty acids, and synthesis of very-low-density lipopro-
tein (VLDL), resulting in hypertriglyceridemia.
White adipose tissue, especially in the abdominal
area, is an active endocrine organ producing inflamma-
tory cytokines and hormones (eg, leptin) and, therefore,
a major contributor to pathogenic immunometabolic
responses in the central nervous system, as well as in
the rest of the body. Cytokines produced peripherally
can access the brain—either directly crossing the blood-
brain barrier through saturable active transport sys-
tems or indirectly via microglia activation—and result
in decreased neurogenesis in emotion-regulating brain
structures.56 Cytokines also catalyze the synthesis of
kynurenine from tryptophan, resulting in the reduced
synthesis of serotonin and increased synthesis of trypto-
phan catabolites, which perturb neurotransmission and

C l i n i c a l r e s e a r c h

68

lead to neuronal damage.57 The activation of a proin-
flammatory response stimulates the release of lipids in
the bloodstream, resulting in a reduction in HDL-C and
phospholipids and an increase in triglycerides. Both the
sustained HPA-axis and inflammatory activation may
affect insulin sensitivity and alter glucose metabolism
acting directly on pancreatic β-cells.
Other linking pathophysiological mechanisms may
also be relevant. For instance, the leptin-melanocortin
pathway has an important role in lipid and glucose ho-
meostasis, as it is a key neuroendocrine regulator of
energy homeostasis. This pathway has also been shown
to play a role in mood regulation through the enhance-
ment of neurogenesis and neuroplasticity in hippo-
campal and cortical structures and the modulation of
HPA-axis and immune system activity.58 In addition,
higher levels of oxidative and nitrosative stress could be
a further linking mechanism, as these have been shown
to be involved in both the development of psychiatric
diseases and metabolic dysregulations.59 In sum, various
immunometabolic and endocrine homeostasis systems
show bidirectional interplay with both psychiatric and
somatic health, and dysregulations in these may con-
tribute to a psychiatric disorder–MetS comorbidity.

Shared genetic vulnerability

The last decade has given rise to large-scale studies in
which genome-wide association studies (GWAs) and
candidate gene studies have identified genetic variants
that are associated with CVD, MetS dysregulations,
and psychiatric disorders. A recent review60 revealed 24
pleiotropic genes that seem to be shared between mood
disorders and cardiometabolic conditions. These genes
included among others CACNA1D (encoding calcium
voltage-gated channel subunit a1 D), FTO (encoding fat
mass and obesity-associated protein), BDNF (encoding
brain-derived neurotrophic factor), POMC (encoding
proopiomelanocortin), and IGF1 (encoding insulin-like
growth factor 1). A pathway analysis revealed shared
genetic pathways involving corticotropin-releasing hor-
mone signaling, axonal guidance signaling, serotonin
and dopamine receptors signaling, circadian rhythm
signaling, and leptin signaling. Further confirmation for
the overlap in mood disorders and MetS-relevant genes
comes from observations that genome-wide genetic
risk scores for obesity and inflammation are associated
with a significantly increased risk of MDD, especially

those with neurovegetative symptoms.61 Similarly, a
recent review article found robust and multiple-study
evidence for fat mass and obesity associated genes (in-
cluding FTO), leptin genes, MTHFR (encoding methy-
lenetetrahydrofolate reductase), and serotonin recep-
tor 2C genes to be involved in the pathogenesis of both
MetS and schizophrenia.62 These recent studies clearly
suggest that the MetS–psychiatric disorder comorbid-
ity may partly arise from a shared genetic vulnerability
involving pathophysiological processes that impact on
metabolic as well as mental health.

Gut microbiome alterations

The gut is colonized by trillions of microorganisms col-
lectively called the microbiome. It is increasingly clear
that this microbiome plays a critical role in many as-
pects of health, including metabolism, immunity, and
even neurobiology. Consequently, it is possible that
commensal bacteria are also a connecting factor to
both metabolic and psychiatric health. The penetration
of bacteria across the gut epithelium may modulate a
range of neurotrophins and proteins involved in brain
development and plasticity, resulting in chronic low-
grade inflammation, which further induces MetS.63,64
This research area is currently growing at a rapid rate
and will teach us more about the importance of micro-
biome alterations as an underlying mechanism for the
MetS comorbidity in psychiatric patients.

Clinical implications and future perspectives

The abovementioned evidence that MetS is more prev-
alent among psychiatric patients indicates the relevance
of considering the diagnosis and treatment of MetS si-
multaneously with the management of psychiatric con-
ditions. Such simultaneous treatment could decelerate
the somatic consequences of MetS, but possibly also the
progression of psychiatric conditions, as MetS has been
associated with a more chronic and progressive disease
course. For some psychotropic medications, such as an-
tidepressants and mood stabilizers, there is evidence
that MetS dysregulations are predictive of treatment
resistance.12,65 This may even suggest that the reduction
in MetS prevalence could potentially improve the re-
sponse to psychotropic medications; however, this point
deserves future confirmatory research. Overall, the
clinical evaluation and treatment of MetS in psychiatric

Metabolic syndrome in psychiatric patients – Penninx and Lange Dialogues in Clinical Neuroscience – Vol 20 . No. 1 . 2018

69

patients is very worthwhile both for somatic and mental
health of patients.
One obvious question is how to best prevent and
treat MetS in psychiatric patients. Figure 1 summarizes
the main risk factors for MetS comorbidity in psychiat-
ric patients and the potential (future) clinical implica-
tions that could be considered to prevent or reduce the
impact of MetS risk. As described above, it is important
to be aware of specific psychotropic medications that
raise the MetS risk more than others and to be able to
adapt the prescription of a particular medication to the
cardiovascular risk profile of patients. This is especially
important in patients who are already at an increased
risk due to obesity or preexisting somatic conditions.
Dose reduction or the switching of antipsychotic medi-
cation has proven to be safe and beneficial.66 Evidence
has been reported for concomitant metformin and
statin use to be effective in the treatment of antipsy-
chotic-induced weight gain and metabolic adversities.67
In addition, adequate monitoring of MetS and its po-
tential deterioration during treatment is necessary in
order to provide timely treatments when clinically rel-
evant MetS deterioration occurs. Multiple studies have
reported considerable underdiagnosis and undertreat-

ment of somatic comorbidity in psychiatric patients.68,69
Early detection, identifying high-risk patients, and
early treatment based on existing somatic guidelines
should be part of daily practice. Another obvious route
to prevent or improve the risk of MetS is by directly
modifying the lifestyle of psychiatric patients. Lifestyle
interventions, changing sedentary lifestyle behavior,
and reducing smoking have been shown to improve de-
pressive and psychotic symptom severity70,71 and favor-
ably affect metabolic parameters and cardiorespiratory
status.72,73 A pilot trial indicated that subjects with BD,
MDD, and schizophrenia who underwent a program of
dietary changes, exercise, and modules of wellness had
a lower waist circumference and better mental health.74
Lifestyle-improving programs could and should be-
come much more integrated and accessible in standard
clinical practice.
Scientific research is currently exploring novel types
of interventions that could help reduce the combination
of MetS dysregulations as well as psychiatric symptoms.
One novel route is through adjunctive anti-inflammato-
ry agents such as nonsteroidal anti-inflammatory drugs
(NSAIDs) or N-acetylcyteine, which may have direct
symptom-reducing effects in psychiatric patients or

improve efficacy of psycho-
tropic medication. Such first
evidence exists for patients
with BD,75 depression76 and
schizophrenia.77 This proof-
of-concept evidence shows
that additional, more robust
studies evaluating immuno-
modulating agents for larger
groups of psychiatric patients
are merited. A second novel
route of intervention may
be targeting the gut-brain
axis. Animal research pro-
vided first evidence that the
broad-scale alteration of the
microbiome via use of selec-
tive dietary microbial growth
substrates, or prebiotics, may
directly affect the expres-
sion of brain-relevant pro-
teins such as brain-derived
neurotrophic factor (BDNF)
and N-methyl-d-aspartic acid

Risk factors for MetS dysregulation

Genetics

Immuno-metabolic dysregulations
• immune alterations
• HPA-axis dysregulations
• leptin-melanocortin alterations
• microbiome alterations

Lifestyle risk factors
• physical inactivity
• smoking
• excessive alcohol intake
• poor sleep hygiene
• unhealthy nutritional patterns

Psychiatric care
• medication side effects
• treatment discontinuation
• symptom profiles

Somatic care
• undertreatment
• underdiagnosis
• poor access to health care

Potential clinical implications

Early risk assessment

Immunometabolic modifications
• anti-inflammatory medication
• use of prebiotics

Lifestyle modifications
• quit smoking
• alcohol abuse treatment
• physical exercise programs
• dietary guidance

Psychiatric care modifications
• dose modification
• switching medication
• adequate symptom treatment

MetS risk assessment
• early detection
• regular screening
• adequate treatment through guidelines

Better
mental
and
metabolic
health

Figure 1. Risk factors for metabolic syndrome dysregulations in psychiatric patients (left box) and the poten-
tial (future) clinical implications needed to minimize the unfavorable impact of these risk factors
(middle box). HPA-axis, hypothalamic-pituitary-adrenal axis; MetS, metabolic syndrome

C l i n i c a l r e s e a r c h

(NMDA) as well as on various metabolic processes in-
cluding insulin resistance and inflammation.63 In line
with this, the administration of probiotics in healthy
women improved brain connectivity and emotional
processing and reduced stress.63 Studies targeting the
gut-brain axis in psychiatric patients are ongoing and
will show us whether this is an efficacious route to im-
prove both MetS and psychiatric health outcomes for
the future.

Conclusion

The risk of MetS is increased in a range of psychiatric
patients. This increased risk is due to an intricate com-
bination of pathways acting synergistically and having
a negative effect on the course of psychiatric diseases.
MetS changes in psychiatric disorders could be caus-
al, consequential, or due to an underlying same set of

causes. A likely multitude of factors interact, includ-
ing iatrogenic effects of psychotropic medication, an
unhealthy lifestyle, poorer medical care of psychiatric
patients, and genetic and pathophysiological vulner-
ability. Because of the adverse consequences of MetS
on somatic as well as psychiatric outcomes, coordinated
pharmacological interventions managing mental health
and metabolic dysregulations coupled with behavioral
approaches may help lessen the disease burden. Treat-
ing psychiatric disorders and MetS simultaneously is
merited in order to enhance treatment outcomes for
both conditions. Future research is required to further
our understanding of underlying mechanisms and the
effectiveness of such interventions. o

Disclosure/Acknowledgments: BP has received research funding (not re-
lated to contents of current paper) from Jansen Research and Boehringer
Ingelheim. SL has nothing to disclose.

70

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El síndrome metabólico en pacientes
psiquiátricos: análisis, mecanismos y
consecuencias

Los pacientes psiquiátricos tienen un mayor riesgo de
mortalidad prematura, principalmente por enfermeda-
des cardiovasculares (ECVs). Existe evidencia convincen-
te que muestra que las condiciones psiquiátricas están
caracterizadas por un aumento del riesgo del síndrome
metabólico (SMet), un conjunto de factores de riesgo
cardiovascular que incluyen dislipidemia, obesidad ab-
dominal, hipertensión e hiperglicemia. Este riesgo au-
mentado se presenta en diversas condiciones psiquiátri-
cas como trastorno depresivo mayor (TDM), trastorno
bipolar (TB), esquizofrenia, trastorno de ansiedad, tras-
torno por déficit de atención con hiperactividad (TDAH)
y trastorno por estrés postraumático (TEPT). Al parecer
existe alguna evidencia de una asociación dosis-res-
puesta entre la gravedad y duración de los síntomas y
el impacto longitudinal bidireccional entre los trastor-
nos psiquiátricos y el SMet. En general las asociaciones
parecen más potentes con la obesidad abdominal y la
dislipidemia que con la hipertensión. Los mecanismos
que contribuyen a esto son un estilo de vida poco sa-
ludable y una pobre adherencia al tratamiento médico,
condiciones que son prevalentes entre los pacientes psi-
quiátricos. Los medicamentos psicotrópicos específicos
también han demostrado un impacto importante en el
aumento de las fallas en la regulación del SMet. Por úl-
timo, la pleiotropía en la vulnerabilidad genética y los
mecanismos fisiopatológicos, como los que conducen a
una mayor activación central y periférica de los sistemas
inmunometabólico y endocrino, tienen un papel tanto
en el desarrollo del SMet como del trastorno psiquiátri-
co. El riesgo aumentado del SMet y las consecuencias
desfavorables en la salud somática justifican una priori-
dad alta para la investigación, prevención, monitoriza-
ción estricta y tratamiento para reducir a futuro el SMet
en el paciente psiquiátrico vulnerable.

Analyse, mécanismes et implications du syndrome
métabolique chez les patients psychiatriques

Les patients psychiatriques ont un risque plus élevé de
mortalité prématurée, surtout en raison des maladies
cardiovasculaires (MCV). D’après des données convain-
cantes, les troubles psychiatriques se caractérisent par
un risque augmenté de syndrome métabolique (SM), un
ensemble de facteurs de risque cardiovasculaire com-
prenant une dyslipidémie, une obésité abdominale, une
hypertension et une hyperglycémie. Dans ces troubles
psychiatriques, on trouve le trouble dépressif caracté-
risé (TDC), le trouble bipolaire (TB), la schizophrénie, le
trouble anxieux, le trouble déficit de l’attention/hype-
ractivité (TDAH) et le trouble de stress post-traumatique
(TSPT). Il semble exister une association dose-réponse
entre la sévérité et la durée des symptômes et l’impact
longitudinal bidirectionnel entre les troubles psychia-
triques et le SM. Ces associations paraissent générale-
ment plus fortes avec l’obésité abdominale et les dyslipi-
démies qu’avec l’hypertension. Un mode de vie malsain
et une mauvaise adhésion au traitement médical, fré-
quents chez les patients psychiatriques, y participent.
Les traitements psychotropes spécifiques influent for-
tement sur l’augmentation des dysrégulations du SM.
Enfin, la pléiotropie de la vulnérabilité génétique et des
mécanismes physiopathologiques, comme de ceux qui
augmentent l’activation centrale et périphérique des
systèmes endocriniens ou immunométaboliques, joue
un rôle dans le développement à la fois du SM et des
troubles psychiatriques. Ce risque majoré de SM et ses
conséquences négatives sur la santé somatique justi-
fient une priorité élevée pour la recherche, la préven-
tion, la surveillance étroite et le traitement afin de dimi-
nuer dans l’avenir le SM chez les patients psychiatriques
vulnérables.

Susanne Stanley &
Jonathan Laugharn

e

Clinical Guidelines for the Physical
Care of Mental Health Consumer

s

Report

“People with mental illness remain one of
the most marginalised groups in society”

(Lawrence, Holman & Jablensky,

2

001, p.1

)

The Clinical Guidelines for the Physical Care of Mental
Health Consumers project was instigated in February
of

20

09 by the former Western Australian Department
of Health – Mental Health Division, in response to the
alarming morbidity and mortality rates, from common
physical health disorders in the mentally ill.

This report represents

12

months of effort in compiling
both national and international literature and research.
The result is the development of evidence-based clinical
guidelines and protocols addressing the assessment
and ongoing monitoring of the physical health of people
with a mental illness.

Consultation and feedback on the first draft of the Clinical
Guidelines package was sought across the health
sector in Western Australia. An invited Reference Group
discussion was held, and feedback from general health
and mental health service representatives, consumers
and carers was obtained.

The Clinical Guidelines for the Physical Care of Mental
Health Consumers package affords a preventative,
best-practice framework for mental health services, and
facilitates effective coordination of care between health
providers, and with mental health consumers.

I would like to thank Dr Steve Patchett, Dr Rowan
Davidson, Dr Elizabeth Moore, Neil Guard, and the many
health service representatives, consumers and carers
for their commitment to improved physical health for
people with a mental illness.

Finally, I would like to commend the authors of this report
for their work and dedication to this important initiative.
We look forward to the continued support provided
to this project by the newly formed WA Mental Health
Commission.

Aleksandar Janca

Winthrop Professor and Head
School of Psychiatry and Clinical Neurosciences

University of Western Australia

Foreword

© Copyright 20

10

. Community, Culture and Mental Health Unit,
School of Psychiatry and Clinical Neurosciences and The University
of Western Australia. All rights reserved. Except in accordance
with the provisions of the Copyright Act 19

6

8

(Cth), and the grant
of permission below, no part of the content of this publication may
be reproduced, stored or transmitted in any form without the prior
written permission of the Community, Culture and Mental Health Unit,
School of Psychiatry and Clinical Neurosciences or The University of
Western Australia.

This Publication was produced with generous financial assistance of
the Mental Health Commission of the State Government of Western
Australia. The Government of Western Australia is granted a non-
exclusive irrevocable non-transferable license to use the contents of
this publication for any non-commercial purpose.

Enquiries concerning this report should be directed to:
Community, Culture and Mental Health Unit
The University of Western Australia
School of Psychiatry and Clinical Neurosciences
Fremantle Hospital, W Block, L6, 1 Alma Street, Fremantle WA 6

16

0

Stanley, S. & Laugharne, J. (2010). Clinical guidelines for the physical
care of mental health Consumers. Community, Culture and Mental
Health Unit, School of Psychiatry and Clinical Neurosciences,
The University of Western Australia. Perth: The University of
Western Australia.

1 Background InformatIon 2

2 factors affectIng the PhysIcal health
of mental health consumers

3

2.1 Medication Effects 3

2.1.1 Antidepressants 3
2.1.2 Anxiolytics

4

2.1.3 Mood Stabilisers/Anticonvulsants 4
2.1.4 Antipsychotics 4

2.2 Lifestyle 5
2.2.1 Exercise 5
2.2.2 Diet 5
2.2.3 Tobacco Smoking 6
2.2.4 Cholesterol 6
2.2.5 Dental 7

2.3 Physical Disorders 7
2.3.1 HIV/AIDS and STI’s 7
2.3.2 Hepatitis C 8
2.3.3 Cancer 8
2.3.4 Irritable Bowel Syndrome/Gastrointestinal Dysfunction 9
2.3.5 Type II Diabetes 9
2.3.6 Cardiovascular Disease 10
2.3.7 Respiratory Disease 11

2.4 Alcohol & Illicit Drug Use 12
2.4.1 Alcohol 12
2.4.2 Other Illicit Substances 12

2.5 Psychosocial 13
2.5.1 Familial Relationships

14

2.5.2 Community Involvement 15
2.5.3 Socio-Economic Status and Employment 16
2.5.4 Culture/Religion 17

3 clInIcal guIdance and monItorIng Protocols 19

3.1 Inpatient/Outpatient and Community Physical
Health Care 19

3.2 Distinct Populations 21

3.2.1 People Over 65 Years of Age 21
3.2.2 Children/Adolescents 21
3.2.3 Aboriginal and Torres Straight Islanders

22

3.2.4 Pregnancy 22
3.2.5 People with Intellectual Disabilities 23
3.2.6 People from Culturally and Linguistically Diverse
Backgrounds (CALD) 23

4 collaBoratIon and PartnershIPs

24

5 references 25

6 BIBlIograPhy 31

7 aPPendIces

32

Appendix 1 – Clinical Algorithm – Metabolic Syndrome 32

Appendix 2 – Screening Forms

34

Table of Contents

The Duty to Care report on preventable physical
illness in mental health consumers (Lawrence,
Holman & Jablensky, 2001) demonstrated markedly
elevated rates of a range of physical disorders.

As a consequence, people with a severe mental illness
are 2.5 times more likely to die from preventable physical
illness than people in the general population.

This awareness of high ill health and mortality rates led to
the 2004 Who is your GP? report (HealthRight Advisory
Group, WA Office of Mental Health), advocating that
mental health professionals take more responsibility for
the physical health of their patients.

In February 2009 the Western Australian Department
of Health – Mental Health Division, commissioned
a review of both national and international literature
to identify existing research, clinical guidelines and
protocols addressing the physical health of mental
health consumers.

A systematic search using multiple data bases from a
variety of disciplines adhered to the specific inclusion
criteria of; 1) a focus on physical conditions occurring
in people with a mental health diagnosis, 2) currency of
publications and research, 3) evidence-based studies,
and 4) adult samples. Exclusion criteria included papers
on expert opinion, and research that did not focus
upon clinical or patient-relevant outcomes (adhering to
the National Health and Medical Research Council’s
(NHMRC, ) ‘relevance of the evidence’ principle). Older
studies were included based on relevance to the topic
and the dearth of research in specific areas.

The literature review to follow is not exhaustive, but
aims to identify significant differences in physical health
between the general population and mental health
consumers. These differences highlight areas requiring
examination and ongoing monitoring, and allow for the
development of a physical health assessment package
for use in clinical and community settings with mental
health consumers.

“Of the 16 million Australians aged 16–85 years,
almost half (45% or 7.3 million) had a lifetime
mental disorder, i.e. a mental disorder at some
point in their life”

(Australian Bureau of Statistics – ABS, 2007a).

Background Information 21

2

The following investigation will cover five major
dimensions; medication, alcohol and illicit
drug use, physical disorders (pre-existing or
developing), lifestyle, and psychosocial factors.
These dimensions reveal an holistic approach to the
complex and interactive factors associated with the
poor physical health of people with a mental illness.

One of the most prevalent health issues found in mental
health consumers is that of the metabolic syndrome.
Once thought to be primarily evident in people diagnosed
with psychoses and mood disorders, the metabolic
syndrome is now shown to be relatively common across
all mental health diagnoses. Metabolic syndrome is
related to several of the dimensions considered here –
medication use, lifestyle factors, psychosocial factors
and comorbid physical illness are all relevant.

The metabolic syndrome is a recognised cluster of
features predictive of both cardiovascular disease and
type 2 diabetes (Barnes et al., 2008). Central obesity,
glucose intolerance/insulin resistance, hypertension,
and dyslipidemia characterise the syndrome, yet only
a small number of consumers are regularly screened
(Meyer & Stahl, 2009; Taylor et al., 2005). Waterreus and
Laugharne (2009) have recently developed an algorithm
to assist clinicians in screening of the metabolic
syndrome, highlighting waist circumference, blood
pressure, fasting lipids, and fasting blood glucose.

Psychotropic medication is the first line of treatment for
mental illness in the Western world and, unfortunately,
the side-effects of drugs can be quite detrimental to the
physical health of consumers (Schwartz et al., 2004;
White, Gray & Jones, 2009; Zimmermann et al., 2003).
This is compounded by risk factors such as smoking
and a lack of exercise (Morris et al., 2006; Porter &
Evans, 2008), and alcohol and illicit drug use (Hilton,
2007). Existing or developing physical conditions such
as hepatitis C and B or gastrointestinal complaints can
then hinder efforts to provide adequate health care,
and psychosocial supports are needed to ensure that
consumers and clinicians are effective in addressing
health problems.

2.1 MeDiCATioN effeCT

S

The severity of known medication side effects is often
downplayed, evidenced by the inadequacies in physical
health screening for mental health consumers (Barnes
et al., 2008). Informative literature on adverse drug
reactions is generally presented in reports of clinical
drug trials, individual cases, or drug safety monitoring,
and studies are typically short-term in duration.

Voluntary reporting of side effects often depends
upon the practicing clinician’s vigilance, awareness
and initiative. In this respect, “adverse events may be
under diagnosed or not reported and, when they are
reported, they usually serve as no more than a warning
of a possible adverse reaction” (Edwards & Anderson,
1999, p.512). Poor health and increased risk of mortality
can arise from any of the four major categories of
psychotropic medications; antidepressants, anxiolytics,
mood stabilizers / anticonvulsants, and antipsychotics.

As new drugs are introduced onto the market, research
on contraindicated medications needs to be continually
updated to keep practitioners informed of best practices
and adverse effects, along with the strict monitoring
of side effects that patients experience, and informing
patients of foodstuffs and beverages that will adversely
interact with medications.

2.1.1 Antidepressants

Antidepressant medications, commonly used for
depressive and anxiety disorders (American Society of
Health-System Pharmacists, 2009; NAMI, 2009), can be
divided into several different classes; Selective Serotonin
Reuptake Inhibitors (SSRI’s), Tricyclics, Monoamine
Oxidase Inhibitors (MAOI’s), Serotonin and Noradrenaline
Reuptake Inhibitors (SNRI’s), and Reversible Inhibitors of
Monoamine Oxidase A (RIMA’s).

All have a number of common side effects such as
nausea, diarrhoea, dizziness, tremor, headaches,
dependence/withdrawal reactions (Edwards &
Anderson, 1999), sexual dysfunction (Cohn & Rickels,
1989), and hyperglycemia (Yamada, Sugimoto & Inoue,
1999). Fatalities occur through more serious issues
such as Serotonin Syndrome (Prator, 2006), weight
gain leading to type 2 diabetes (Schwartz et al., 2004;
Zimmermann et al., 2003), and cardiotoxicity (American
Society of Health System Pharmacists, 2009).

Marked weight gain is related to many physical health
issues such as type 2 diabetes and cardiovascular
disease, and is common with antidepressants,
particularly tricyclics (Zimmerman, 2003). SSRI’s were
thought to induce weight loss rather than weight gain
and, as such, have generally been overlooked. More
recently, it has been shown that weight loss can occur
during the first few weeks of drug administration, but
over the long term, weight gain is a typical result.

Drugs in other classes such as isocarboxazid (MAOI) and
mirtazapine (NaSSA) are also associated with moderate
to marked weight gain over time.

Factors Affecting the
Physical Health of Mental Health Consumers2

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 3

2.1.2 Anxiolytics

Anxiolytics such as benzodiazepines are widely
prescribed for the treatment of anxiety disorders, insomnia
and epilepsy (Barnes et al., 2008; NAMI, 2009). Sedation,
rebound anxiety on withdrawal, risk of dependence, light-
headedness, impairment of psychomotor performance
and memory, confusion, and cognitive impairment are all
listed as side effects for this class of drugs.

Due to the central nervous system side effects,
benzodiazepines have also been associated with
workplace injuries and traffic accidents (Choy, 2007).
Long half-life benzodiazepines (e.g. diazepam and
chlordiazepoxide) are not recommended in the elderly
as falls and excessive sedation may occur (Mort &
Aparasu, 2002).

Long-term users (four months or longer) account for
the majority of anxiolytics and hypnotics taken, and
efficacy is uncertain (Griffiths & Weerts, 1997). Long-
term risks involved with the use of these drugs suggest
lowered cognitive functioning, some of which may not be
reversible, and may represent a cumulative drug effect
(e.g. psychomotor speed, speed of cognitive processing
and verbal memory) (Barker, Greenwood, Jackson &
Crowe, 2004; Choy, 2007).

Barker et al. (2004) conducted a meta-analysis
examining all available research on the cognitive effects
of long-term benzodiazepine use. They found consistent
impairment in all cognitive domains for long-term users
(minimum use of 12 months) when compared to control
subjects. The small number of studies and, at times, lack
of methodological vigour suggests a need for further
research in this area.

Other benzodiazepine effects reported in the literature
are treatment-emergent depression, paradoxical
reactions (i.e. behavioural disinhibition, anxiety,
insomnia), and delirium.

2.1.3 Mood Stabilisers/Anticonvulsants

Medications categorised as mood stabilisers

/

anticonvulsants are generally used in the treatment of
bipolar disorder, anxiety and seizures (Barnes et al.,
2008; NAMI, 2009). Along with issues such as nausea,
vomiting, diarrhoea, weight gain, sedation, and tremor
(American Society of Health-System Pharmacists, 2009;
NAMI, 2009), tolerance/dependence can develop with
these medications (Zimmermann et al., 2003).

Some medications such as valproic acid, carbamazepine,
and lithium carbonate can lead to severe, even fatal

consequences (Zimmermann et al., 2003). These
include hepatoxicity, alopecia, pancreatitis, severe skin
reactions, thrombocytopenia, involuntary movements,
toxicity – renal impairment or failure, cardiac arrhythmias,
and long term issues such as cognitive impairment and
moderate to marked weight gain (American Society
of Health-System Pharmacists, 2009; Mental Illness
Fellowship Victoria, 2003; NAMI, 2009; Zimmermann et
al., 2003).

Newer anticonvulsants looking to avoid the severe
effects of older drugs are associated with their own side
effects that need to be monitored such as hepatic (liver)
failure and aplastic anaemia with felbamate (Ortinski &
Meader, 2004).

Bootsma et al. (2009) evaluated discontinuation due
to drug side effects in 1066 inpatients and outpatients
who had been treated with lamotrigine (336 patients),
levetiracetam (

30

1 patients), and topiramate (429
patients). The most commonly reported side effects
for lamotrigine were dizziness (14.9%), positive mood
disorders (e.g. agitation, aggression, hyperirritability)
(11.7%), rash (10.6%), and sleepiness (6.4%) or
sleeplessness (7.4%). For levetiracetam the most
common complaints dealt with positive mood disorders
(13.8%), tiredness (13.8%), negative mood disorders
(depression, apathy) (13.1%), and sleepiness (8.5%).
Finally, people taking topiramate reported many more
negative effects such as mental slowing (27.8%),
word-finding difficulties (dysphasia) (15%), positive and
negative mood disorders (13.2% and 5.7% respectively),
gastrointestinal complaints (10.6%), paresthesia (7.5%),
appetite loss (7%), skin complaints (6.6%), weight
loss (6.2%), headaches (5.7%), and dizziness (5.3%).
Overall, adverse drug events resulted in discontinuation
for 35.9% of people taking topiramate, 22.5% of people
prescribed levetiracetam, and 15.5% of people taking
lamotrigine.

2.1.4 Antipsychotics

Atypical antipsychotic medications were introduced
to lower the incidence of extrapyramidal symptoms
such as Parkinsonism and tardive dyskinesia, yet it is
becoming increasingly evident that they are associated
with metabolic disturbances such as cardiovascular
disease and type 2 diabetes.

Many of the physical health problems related to
antipsychotic medications are similar to those cited
for mood stabilisers and antidepressants. Generally
prescribed for schizophrenia, antipsychotics have
been increasingly used for treating bipolar disorder,

4

anxiety and depression (Schwartz et al., 2004).
Metabolic disturbances leading to type 2 diabetes and
cardiovascular disease are markedly elevated when
compared to the general population. The prevalence of
metabolic syndrome among people taking antipsychotic
medications in Australia is high, affecting approximately
19% to 29% of adults (Zimmet, Alberti & Shaw, 2005).

Typical or first generation antipsychotics such as
chlorpromazine, haloperidol, and loxapine are
associated with extrapyramidal side effects such as
tardive dyskinesia, and impaired cognitive functioning
(Kiraly, Gunning & Leiser, 2008). The newer atypical (or
second generation) antipsychotics are associated with
adverse metabolic affects such as moderate to marked
weight gain, glucose intolerance and type 2 diabetes,
and hyperlipidemia.

Clozapine shows the greatest weight gain (McIntyre et
al., 2005; Zimmermann et al., 2007), and cardiotoxic
adverse effects such as myocarditis, cardiomyopathy, and
pericarditis (Layland, Liew & Prior, 2009). Disturbances
in glucose homeostatic mechanisms are also found
with olanzapine, zotepine, quetiapine, chlorpromazine,
thioridazine, perphenazine, trifluoperazine, risperidone,
clopenthixol, and sulpride associated with moderate to
marked weight gain (Zimmermann et al., 2007).

Many antipsychotic medications have also been linked with
QT interval prolongation, adverse cardiac effects (John,
Koloth, Dragovic & Lim, 2009; Kiraley et al., 2008; Marder
et al., 2004; Schwartz et al., 2004; Zimmermann et al.,
2003), and antipsychotic –induced hyperprolactinaemia
causing sexual dysfunction, fertility problems, and bone
mineral density reduction (Montejo, 2008).

2.2 LifeSTyLe

Major lifestyle factors are often outlined when citing
determinants of poor physical health in people with a
mental illness. A lack of exercise, poor diet, and smoking
tobacco (Elmslie et al., 2001; Osborn, Nazareth & King,
2007; O’Sullivan, Gilbert & Ward, 2006; Porter & Evans,
2008; Soundy, Faulkner & Taylor, 2007) have been
identified as unhealthy behaviours leading to chronic
disease and mortality, along with high cholesterol levels
(Jow, Yang & Chen, 2006; Ojala et al., 2008; Troisi,
2009), and poor dental hygiene (Dickerson et al., 2003;
Sjogren & Nordstrom, 2000).

2.2.1 exerci

se

Low levels of physical activity have been reported in
Australia, with around 70% of the population exercising

at low to sedentary levels (ABS, 2006). Low levels of
physical activity in people with a mental illness have
been reported in many studies (Elmslie et al., 2001;
Porter & Evans, 2008; Soundy, Faulkner & Taylor, 2007).
This is supported by a study in which people with bipolar
disorder were twice as likely to not engage in physical
activity at all as compared to a matched control group,
reasoned to be due to the known sedating effects of
medications (Elmslie et al., 2001). Jerome et al. (2009)
examined levels of exercise and found that people with
mental health issues tend to engage in sporadic physical
activity rather than sustained physical activity.

An in-depth, qualitative study conducted in 2007
(Soundy et al., 2007) suggests that walking is the most
common form of exercise undertaken, and that people
with mental health problems are more physically active
than commonly thought. The authors found that patients
were receptive to the promotion of physical activity, but
were ambivalent about engaging in physical exercise.
Barriers such as a lack of social support, poor social
skills, poor self-image, and coping with current emotional
issues tend to prevent behaviour change and adoption
of a healthier lifestyle.

2.2.2 Die

t

For people with mental health disorders, a major factor
contributing to obesity is often thought to be diets high
in saturated fat (Jerome et al., 2009; Porter & Evans,
2008). Poor dietary habits in the mentally ill though, are
not conclusively supported by the literature.

Stokes and Peet (2004) conducted a pilot study of 20
patients diagnosed with schizophrenia. They used a
seven day weighed intake method along with patient diet
histories supplied by nursing staff. Results suggested
that patients had diets high in sugars and saturated fats.

Osborn et al. (2007) found that people with a psychotic
disorder had diets low in fibre, but when compared to
a matched sample, there was no difference in levels of
saturated or total unsaturated fat intake between the two
groups. This finding was similar to that of a New Zealand
study, although the latter study also found that sucrose
levels (particularly those derived from non-alcoholic
beverages such as sweetened drinks, cakes etc.) were
higher in people taking antipsychotic medications
(Elmslie et al., 2001).

Finally, in the USA Strassnig, Brar and Ganguli (2003)
examined a 24 hour diet recall of 146 outpatients with
schizophrenia. They then compared this with the general
population using the Third National Health and Nutrition

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 5

Examination Survey. Dietary choices were no different
to the general population as the relative percentage
of calories derived from proteins, carbohydrates and
fats were similar between groups. There were also no
differences in cholesterol or fibre intake between groups.
In general though, people with schizophrenia tended to
eat more than people in the general population.

2.2.3 Tobacco Smokin

g

The Australian Bureau of Statistics (2008) data indicate
that for the 2007-2008 period, 20% of Australian adults
smoked cigarettes. Figures for smoking prevalence for
people with a mental illness vary, but they are significantly
higher than prevalence rates for the general population.
In a large American study (over 100,000 people with a
mental illness) overall tobacco smoking rates of around
39% (Morris, Giese, Turnbull, Dickinson & Johnson-
Nagel, 2006) were found. Lower overall rates have been
established in Australia.

The 2007 National Survey of Mental Health and Wellbeing
(SMHWB) (ABS, 2007a) found that for people who had
identified as having a mental disorder within the past 12
months, 32.4% smoked tobacco. Diaz et al. (2009) found
that 66% of people with bipolar disorder, 74% of people with
schizophrenia, and 57% of people with major depression
smoke tobacco. Strine et al. (2008) investigated tobacco
smoking prevalence in anxiety and depression. Tobacco
smoking rates for people with a diagnosis in their lifetime
of anxiety were approximately

26

%, similar to depression
at 25.5%. Figures were higher for comorbid diagnoses of
anxiety and depression at around 37%.

Morris et al. (2006) conducted a statewide population
survey of all people with a mental illness within the public
mental health system. They found that males were more
likely to smoke tobacco than females, and that people
with a diagnosis of bipolar disorder, schizophrenia,
or schizoaffective disorder were more likely to smoke
tobacco than people with other diagnoses. Finally, they
also found differences between ethnic groups with
Asian people, Pacific Islanders and Hispanics less likely
to smoke tobacco than whites, African Americans or
American Indians.

When considering ‘quit smoking’ programmes within
the mental health system, care needs to be taken.
Hilton (2007, p.221) cautions that “abstinence from
nicotine inhibits liver enzyme production, which can
significantly increase levels of prescribed medication”.
For example, lithium levels need to be monitored as
they could fall, whereas clozapine levels could rise and
become toxic. Monitoring blood levels before and during

smoking cessation is advised. The potential interactions
of psychotropic drugs with drugs prescribed to aid
cessation is also an issue for clinicians to be mindful of.

2.2.4 Cholesterol

Second generation antipsychotic medications such
as olanzapine and clozapine are associated with
dyslipidemia, a physical health condition that manifests
abnormal concentrations of lipids or lipoproteins in the
blood (Ojala et al., 2008). Dyslipidemia is noted through
high serum levels of Total Cholesterol (TC), low serum
levels of High-Density Lipoprotein Cholesterol (HDL-C),
and high Low-Density Lipoprotein Cholesterol (LDL-C)
and Triglyceride (TG) levels. Ojala (2008) suggests that
statins can be used to effectively lower TC, LDL-C and
TG levels in people taking antipsychotic medications.

Levels of leptin, a hormone thought to speed up the
body’s metabolism and suppress appetite, have been
assessed along with Total Cholesterol levels in patients
with schizophrenia and patients with major depressive
disorder (Jow et al., 2006). Low TC and leptin levels
were found in people with major depression, whereas
high TC and leptin levels were found in people with
schizophrenia. An association was found between the
length of illness in schizophrenia and mean leptin and
TC levels, possibly suggesting that the longer a person
takes antipsychotic medications the higher their leptin
and TC levels become.

High cholesterol levels are a major risk factor of coronary
heart disease, and Walldius and Jungner (2004) suggest
that TC and LDL-C levels may not be the best indicators
of coronary artery disease. Some people who manage to
dramatically reduce their TC and LDL-C levels still go on
to develop cardiovascular disease. In order to reduce this
risk, physicians need to aim for higher concentrations of
apolipoprotein A1 (apoA1) (the major protein component
of high density lipoprotein (HDL) in plasma) and HDL-C,
as these components of lipoproteins appear to have
better predictive value.

The effects of medication on cholesterol levels have
been indicated to differ between races. Daumit et al.
(2008) assessed 1125 patients with a diagnosis of
schizophrenia over an

18

month period. They were
randomly assigned to receive treatment with olanzapine,
quetiapine, risperidone, perphenazine or ziprasidone.
The double-blind study found an interaction between
race and treatment. For Caucasians, HDL-C levels
decreased when patients were taking olanzapine or
quetiapine, but increased significantly when taking
perphenazine. For hispanics, HDL-C levels decreased

6

when taking olanzapine or perphenazine, but increased
when taking ziprasidone.

2.2.5 Dental

Oral health is generally poor in people with mental illness
(Burchell et al., 2006; Dickerson et al., 2003; Sjogren &
Nordstrom, 2000). They are less likely to report visits
to the dentist or to a dental hygienist, yet their needs
for dental services are great (Dickerson et al., 2003;
Griffiths et al., 2000). In examining the oral health status
of psychiatric patients, Sjogren and Nordstrom (2000)
found that people experienced problems such as a bad
odour coming from their mouth, ulcerated, bleeding
and/or inflamed mucous membranes, lips or gums,
decayed and/or fractured teeth, calculus on teeth, and
an absence of saliva. Results of their study showed that
patients in long-term psychiatric care displayed worse
oral health status than people in short-term (shorter than
three months) psychiatric care.

Burchell et al. (2006) cite reasons such as personal
neglect, other medical conditions, poor nutrition,
low income, the consumption of sugary foods and
drinks, and medication effects such as dry mouth
(causing xerostomia). Xerostomia increases the risk of
periodontal disease, dental caries, and oral infections
(e.g. generalised stomatitis, candidiasis, glossitis, etc.)
(Griffiths et al., 2000).

Difficulties in treating this client group include the need
for breaks during treatment, the complexity of treatment,
unpredictable behaviour, and medical histories that are
difficult to obtain resulting in additional consultation with
health professionals from other areas (Burchell et al.,
2006; Griffiths et al., 2000). Dickerson et al. (2003) cite
some perceived barriers from the clients’ perspective as
a lack of transport and affordability.

Importantly, drug interactions may occur between
psychotropic medications and drugs commonly used for
oral health conditions (Griffiths et al., 2000). Many result
in enhanced sedation, and some produce abnormal
responses such as increased heart rate and blood
pressure. Dental teams must take these factors into
account during treatment, along with other psychotropic
drug effects such as dyskinesia and dystonia, which pose
problems for denture construction and interfere with the
wearing of dentures for mental health consumers.

2.3 PHySiCAL DiSorDerS

Physical health disorders that people with a mental
illness may have (pre-existing) or may acquire after they

receive a diagnosis and treatment can adversely affect
both physical health and continuing treatment regimes.
A 2007 report by the ABS suggests that 11.7% of the
population, or 1.9 million Australians, had both a physical
condition and a mental health disorder at the time of
data collection (ABS, 2007a).

2.3.1 HiV/AiDS and STi’s

The prevalence rates of Human Immunodeficiency
Virus (HIV), Acquired Immune Deficiency Syndrome
(AIDS) and Sexually Transmitted Infections (STI’s) are
elevated amongst people with mental illness (McKinnon,
Cournos & Herman, 2002; Meade & Sikkema, 2007;
Mijch et al., 2006). Little research has been conducted
in Australia to determine prevalence rates of HIV among
the mentally ill, but Meade and Sikkema (2007) give a US
seroprevalence rate ranging from 1.7% to 5% for people
with a mental illness as compared to 0.6% in the general
population of the US.

An Australian study gave a rate of 17.6% of the HIV-
positive population in Victoria as having a mental
disorder, where the most common conditions were
affective disorder and substance dependence/abuse
(Mijch et al., 2006). According to McKinnon et al. (2002),
the HIV risk of different mental disorders is predominantly
based on assumption rather than evidence, with the
majority of the small number of studies that have been
conducted finding no relationship between being
sexually active and diagnosis and a few finding a
relationship with schizophrenia but not bipolar disorder.
Positive symptomology does appear to result in greater
sexual activity, and sex trading is more likely with people
diagnosed with schizophrenia than other diagnoses.

Davidson et al. (2000) assessed sexual risk behaviours
in 234 outpatients in Melbourne community mental
health clinics. They found that 43% of mentally ill men
and 51% of mentally ill women gave reports of sexual
activity over the past 12 months as compared to 72%
of men and 73% of women in the general population
of Australia. Multiple sex partners (three or more) were
reported by 32% of mentally ill men and 10% of mentally
ill women for the past 12 months. Despite the apparent
lower rates of sexual activity in people with a mental
illness as compared to the general population, risk
factors such as unprotected sex, sex trading (trading sex
for money, drugs or other goods) and illicit drug use are
more common in self-reported behaviours, resulting in
HIV/AIDS and other STI’s (Meade & Sikkema, 2007).

Interestingly, in Meade and Sikkema’s study (2007),
social support emerged as both a preventative factor

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 7

and a risk factor. The more social support a mentally ill
person had, the more likely they were to engage in sex
trading and have multiple sexual partners, but the less
likely they were to have unprotected sex. Senn and Carey
(2009) conducted a literature search for years up to 2007
investigating HIV testing rates for people with a mental
illness. Findings were varied ranging from 17% to 47%
of people who had been tested in the past year of each
study the authors reviewed, and people who engaged in
high risk sexual behaviour or drug use appeared to be
most likely to be tested.

2.3.2 Hepatitis B and

C

Like HIV and STI’s, prevalence rates of the hepatitis B
and C viruses are higher among people with a psychiatric
disorder as compared to the general population
(Rosenberg et al., 2001). Both hepatitis B and C are
major causes of liver disease, such as cirrhosis and
hepatocellular carcinoma (which develops 10 to 30
years after the person is initially infected), and while a
vaccination is available for hepatitis B, none exists for
hepatitis C. In the US, prevalence rates for hepatitis C
in mental health patients have been described as 11
times higher (19.6%) than rates in the general population
(Dinwiddie, Shicker & Newman, 2003). Australian studies
examining the prevalence of hepatitis C in mental health
consumers are scarce.

Lacey, Ellen, Devlin, Wright and Mijch (2007) evaluated
prevalence, risk behaviours and testing rates among 71
psychiatric inpatients of Alfred Hospital in Melbourne
between August 2002 and January 2003. Of interest
in this study was that one of the criteria for admittance
was that participants did not have a known hepatitis
C infection. From their sample, the authors obtained a
prevalence rate of 19.4% as compared to approximately
1% of the general Australian population (Department of
Health and Ageing, 2008). Drug-taking behaviours and
multiple sexual partners emerged as the most common
risk factors (Lacey et al., 2007).

Goldberg and Seth (2008) examined 108 people with
schizophrenia spectrum disorder, a psychotic disorder
or bipolar disorder to assess hepatitis C screening and
follow-up practices. Previous testing of hepatitis C was
reported by 32% of the sample, and there were low rates
of immunization. At baseline 31% of people in this study
tested positive, with 18 new cases identified. At the six
month follow-up, of those new cases, only nine people
reported receiving an hepatitis C specific medical follow-
up. These findings seem surprising in view of the fact
that people within the mental health system already have

contact with health service providers. Rifai et al. (2006)
found that despite receiving a referral for treatment once
hepatitis C had been confirmed, only 33% of people
actually received treatment. Reasons for this were
nonadherence to treatment, psychiatric symptoms, and
the presence of illicit drugs or alcohol – 11% of their
sample died during the study and all of those people had
a comorbid alcohol use disorder. The interaction of drugs
during treatment does need to be taken into account, and
this study found that interferon-α in combination with
ribavirin can be safely administered to psychiatric patients.

2.3.3 Cancer

There appears to be conflicting research on cancer
incidence and mortality in people with mental illness.
Most studies, though, suggest that while many incidence
rates are similar to those of the general population,
mortality rates are much higher (Kisely et al., 2008;
Lawrence et al., 2000; Levav et al., 2009).

A population-based record-linkage study conducted
in Nova Scotia, Canada, examined data from 247,344
people who had been in contact with health services
for psychiatric problems between the years 1995 and
2001 (Kisely et al., 2008). It found that the incidence
was higher than that in the general population for most
cancers. Exceptions were ovarian cancer in females,
prostate and colorectal cancer in males, and skin
melanoma and bladder cancer in both sexes where
similar incidences were found between mental health
patients and the general population. Overall, the authors
found that cancer mortality rates were 70% higher in
male and 59% higher in female mental health patients
when compared to the general population. In men, the
highest cancer mortality rate was for cancers of the brain
and for women it was cancer of the uterus.

Lawrence et al. (2000) conducted a population-based
linkage study in Western Australia examining data from
172,932 mental health patients. They found no difference
in the incidence of cancers in psychiatric patients as
compared to the general population. A much higher
incidence of cancers of the brain were found, although
further investigation revealed that the majority of these
cases were of older people and possibly resulted from
a misdiagnosis of symptoms as psychiatric disorders
rather than brain tumours. The study showed a 40%
higher cancer mortality rate in males and a 20% higher
cancer mortality rate in females when compared to the
general population.

The higher rates of tobacco smoking found in people with
a mental illness (ABS, 2007) suggest that there should

8

be a higher incidence of lung cancer. Evidence for this
is mixed as the Canadian study found both incidence
and mortality to be higher in a mental health population
as compared to the general population (Kisley et al.,
2008), whereas the Western Australian study found
similar incidence but raised mortality levels for lung
cancer (Lawrence et al., 2000). According to a separate
study, the highest cancer mortality rates for people with
schizophrenia were shown to be lung cancer for men
and breast cancer for women (Tran et al., 2009).

Reasons for increased cancer mortality rates have been
put down to delays in detection or initial presentation,
and difficulties in communication or accessing physical
health care, along with lifestyle issues such as tobacco
smoking (Kisely et al., 2008; Lawrence et al., 2000).
These delays in cancer detection could also be
responsible for similar incidence rates between mental
health consumers and the general population. It could
be that incidence is actually higher amongst mental
health consumers, but due to the lack of physical health
screening, the different types of cancer are not identified.

2.3.4 irritable Bowel Syndrome/
Gastrointestinal Dysfunctio

n

Irritable bowel syndrome is characterised by abdominal
discomfort or pain, bloating, and diarrhoea and/or
constipation (Talley, 2006). The incidence of irritable
bowel syndrome in western populations is around 10-
15%. For mental illness populations it is somewhat
higher. A study examining irritable bowel syndrome
symptomology and anxiety and depressive disorders
found rates of 25.8% for people with generalised anxiety
disorder, 21.7% for people diagnosed with panic disorder,
25% for people with major depressive disorder, 16% for
people with obsessive-compulsive disorder, and 11.4%
for people diagnosed with social anxiety disorder (Gros
et al., 2009). Research on schizophrenia has also found
a much higher prevalence rate of 19.5% when compared
to a matched control sample of 2.5% (Gupta et al., 1997).

A contentious disorder, irritable bowel syndrome has
often been dismissed as a non-organic problem or rather,
a psychological problem (Heitkemper & Jarrett, 2001). It
is now thought to result from hypersensitivity in the bowel
wall, and has been cited as a neurological bowel disease
(Talley, 2001), and tends to affect women more so than
men. This then leads to a disruption of typical intestinal
muscle functioning. Tally cites evidence of central
dysregulation, serotonin dysregulation, inflammatory
bowel disease, and bacterial overgrowth in detailing
the pathophysiology of the disorder (Talley, 2006). Of

interest to mental health is serotonin dysregulation,
where people who display constipation-predominant
irritable bowel syndrome show a reduction in levels
of plasma serotonin, yet these levels are increased in
people who experience diarrhoea. As 95% of the body’s
serotonin resides in the gut, “an up or down regulation
of the serotonin-norepinephrine system could result in
alternating dominance of the signalling pathways, and
hence fluctuating symptoms” (Talley, 2001, p.2062).

Karling et al. (2007) found that SSRI’s (49%) and
benzodiazepines (38%) were more commonly taken
among people with a diagnosis of depression who had
low irritable bowel symptom scores (as determined
by the Gastrointestinal Symptom Rating Scale for
irritable bowel syndrome). They also found a strong
association between symptoms of irritable bowel
syndrome and symptoms of anxiety and depression.
Patients in remission showed an equivalent frequency of
gastrointestinal symptoms to the comparison group of
physically and mentally healthy subjects.

The authors did not state the levels or types of
medications patients in remission were taking (if at
all), although a meta-analysis conducted by Jackson
et al. (2000) found that subtherapeutic doses of
antidepressant medications in treating irritable bowel
syndrome appeared to be more effective than higher
dose trials. Karling et al. (2007) concluded that there
was an association between symptoms of irritable bowel
syndrome and symptoms of anxiety and depression.
It may be suggested then that the more physical
discomfort and pain a person experiences, the more
anxious and emotionally distressed a person becomes.

2.3.5 Type ii Diabet

es

Type 2 diabetes occurs when either the pancreas does
not produce sufficient insulin, or cells become resistant to
insulin. Causal factors have been linked to both genetics
and environmental issues such as high blood pressure,
a lack of exercise and poor diet which, in turn, result
in a person becoming overweight or obese (Diabetes
Australia, 2009). The ABS (2008) outlines a rising trend in
Australia, with 3.5% of the general population reporting
that they had been diagnosed with diabetes (88% had
type 2 diabetes) in 2004/2005 to 4% in 2007/2008. The
actual figure is likely to be higher in 2009, particularly
as many cases remain undiagnosed (ABS, 2008;
Diabetes Australia, 2009). Blood glucose control and a
healthy lifestyle can prevent type 2 diabetes and in many
cases, can improve complications associated with this
condition.

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 9

The prevalence of diabetes is much higher in consumers
of mental health services than in the general population,
and elevated levels of blood glucose can be associated
with the administration of psychotropic medications..
Cohen et al. (2006) found that of 200 patients diagnosed
with schizophrenia or schizo-affective disorder, 7% had
hyperglycemia and 14.5% had diabetes. Measurements
of fasting glucose in all patients, regardless of prescribed
antipsychotic medication, showed a significant increase
in prevalence as compared to the general population.
Levels of risk appear to increase again when more
than one atypical antipsychotic is prescribed, or when
quetiapine, clozapine, olanzapine or risperidone are
used when compared to people receiving typical
antipsychotics alone (Citrome et al., 2004).

Basu and Meltzer (2006) highlight patterns in diabetes
mellitus in relation to typical and atypical antipsychotic
medications. They suggest that in the pre-atypical
antipsychotics era (1979 to 1989) and short-term post-
atypical antipsychotics era (1990 to 1995) the occurrence
of diabetes in people with a diagnosis of schizophrenia
was similar to that of the general population. By 2001,
approximately 70% of patients in the US were prescribed
the newer, atypical medications. Between 1996 and the
year 2001 there was a 0.7% increase per year in diabetes
mellitus in patients diagnosed with schizophrenia.
Saddichha et al. (2008) conducted a randomized, double
blind controlled prospective study in people diagnosed
with first episode schizophrenia. They too found that
problems have emerged with second generation
pharmacotherapy, where antipsychotic treatment had
led to the development of diabetes mellitus in 10.1% of
patients within six weeks. They suggest that “… the
presence of treatment-emergent glucose intolerance
and frank diabetes mellitus” is a direct result of atypical
antipsychotic medication (Saddichha et al., 2008, p.342).

There is also increasing awareness of the effects
of antidepressants on blood glucose regulation.
Serotonin (5-HT) contributes to glucose regulation,
and medications such as fluoxetine and fluvoxamine
have been shown to induce hyperglycemia through an
inhibition of insulin release (Yamada, Sugimoto & Inoue,
1999). Increased risk of developing type 2 diabetes
according to antidepressant medication has been given
at 44% for tricyclics alone, 38% for SSRI’s alone, 49%
when administered multiple antidepressants, and 60%
if tricyclics are taken concurrently with SSRI’s (Brown,
Majumdar & Johnson, 2008).

Andersohn, Schade, Suissa and Garbe (2009) conducted
a large observational study of over 160,000 patients

diagnosed with depressive disorder between 1990 and
2005. They found that with long-term use (24 months),
tricyclic and SSRI antidepressants given in moderate to
high daily doses increase the risk of diabetes by 84%.
Other antidepressants such as SNRI’s increase the risk
of diabetes by 80%.

Assessment of blood glucose levels may need to take
sex differences into account. Magliano et al., (2008)
found that men with impaired glucose tolerance were
more likely to progress to diabetes than women as men
have higher fasting plasma glucose. This is despite
more women showing impaired glucose tolerance than
men. They also found that women with impaired fasting
glycemia were more likely to develop diabetes as women
have a higher 2-h plasma glucose than men. Again, this
is despite more men revealing higher levels of impaired
fasting glycemia. The authors suggest that these sex
differences may result from measurement issues where
a fixed glucose load is used rather than adjusting for
average height differences between men and women.

2.3.6 Cardiovascular Disease

Cardiovascular diseases, or diseases of the circulatory
system, account for 36% of all deaths in Australia, with
stroke and ischaemic heart disease being the two most
common causes (ABS, 2006a). In 2004/2005, 3.5 million
people (18%) in Australia reported having a long-term
cardiovascular condition. High blood pressure was
most commonly reported – 11% of people.

Key risk factors include dyslipidemia (an abnormal
concentration of fatty acids, oils, waxes, triglycerides
and sterols in the blood), obesity, smoking, hypertension
(high blood pressure), and hyperglycemia (high blood
sugar) (Newcomer, 2007).

Increased levels of morbidity and mortality from
cardiovascular disease can be seen in people with a
diagnosed mental illness when compared to the general
population (Newcomer, 2007). In addition to the above-
mentioned risk factors, research has also examined
treatment effects for people with a mental illness. Slordal
and Spigset (2006) examined research on non-cardiac
drugs that are identified as being associated with the
development or worsening of heart failure. Tricyclic
antidepressants have well recognised effects on blood
pressure, heart rate, and cardiac rhythm, and there is
also a suspected direct effect on cardiac contractility.
The effects of SSRI’s are unclear and mixed at best, and
generally thought to have little influence upon myocardial
function.

10

In 2009, Whang et al. examined this further in a cohort of
63,469 female nurses. The study covered a span of nine
years, and the authors found an elevated risk of sudden
cardiac death associated with antidepressant use in
women who had no baseline cardiovascular disease and
antidepressant use prior to the commencement of the
study. This elevated risk was not associated with severity
of depressive symptoms, and possible proarrhythmic
effects were implicated. By the year 2000, 61% of these
women were taking SSRI’s and 39% were taking other
antidepressants, and a secondary analysis conducted
on data between 2000 and 2004 found that both SSRI
use and other antidepressant use were associated with
increased risk for sudden cardiac death.

Antipsychotic medications also have well-known
effects associated with cardiovascular disease. Slordal
and Spigset (2006) cite myocarditis/cardiomyopathy
(inflammation and/or disorder of the heart muscle) to
be associated with both typical (e.g. chlorpromazine,
fluphenazine, and haloperidol) and atypical (e.g.
clozapine and risperidone) antipsychotics.

Ray et al. (2001) conducted a retrospective cohort
study of 481,744 people, investigating the risk of sudden
cardiac death among antipsychotic users who had
no evidence of a life-threatening non-cardiac illness.
Typical antipsychotics such as haloperidol, thioridazine,
chlorpromazine, thiothixene showed at least a 60%
greater incidence of sudden cardiac death at a moderate
dose (> 100mg thioridazine or its equivalent) than the
incidence for sudden cardiac death in non-users.

The CATIE schizophrenia study, conducted between
2001 and 2004, examined data on 1125 people who had
been taking psychotropic medication for an average of 14
years before entering the study (Daumit et al., 2008). The
baseline risk of cardiac heart disease ranged from 8.1 to
9.1% across all antipsychotic medications. Patients were
randomly assigned to receive olanzapine, quetiapine,
risperidone, perphenazine, or ziprasidone (added to the
study in 2002). Despite the already established baseline
risk, after only a few months exposure cardiovascular
heart disease risk showed significant changes across
antipsychotic medications. Patients taking olanzapine
and quetiapine resulted in the highest risk, whereas
ziprasidone, risperidone, and perphenazine were
associated with a lower overall risk. In addition, 36%
of people prescribed quetiapine, ziprasidone, or
olanzapine showed an increase in their blood pressure
as compared to 27% of people prescribed risperidone or
perphenazine. Ethnic differences were also found, with
HDL levels significantly increased for caucasians taking

perphenazine, whereas HDL levels were significantly
increased for non-caucasians taking ziprasidone.

2.3.7 respiratory Disease

Respiratory disease accounted for 8.4% (11,577 people)
of all registered deaths in Australia in 2007 (ABS, 2007b).
The majority of these deaths were from chronic lower
respiratory diseases (or Chronic Obstructive Pulmonary
Disease – COPD) (4.2%) such as asthma, bronchitis
and emphysema. There is little reliable information on
the prevalence of COPD, but a 12 country international
study examining prevalence rates of COPD found that
in Australia, 10.8% of people suffered COPD symptoms
(Buist et al., 2007). Approximately 11% of Australian
adults (15% of children) have asthma (Asthma Foundation
Australia, 2009), and almost 1 in 5 people over 40 years
of age have COPD (Lung Foundation, 2009).

As a large number of people with a mental illness smoke
tobacco (see 2.2.3 Tobacco Smoking), it is likely that
respiratory disorders would be more prevalent in this
population. Kendrick (1996) interviewed 101 people with
long-term mental illness (two years or more) and found
prevalence rates of 20.8% for cough and daily sputum,
23.8% for shortness of breath, and 10.8% for wheezing.
New Zealand study evaluated prevalence rates of a
number of physical health conditions in people diagnosed
with a mental illness across ethnic groups. Respiratory
disease and mood disorders were evident in 13.9% of
Maori people, 17.9% of Pacific Islanders, and 10.3% of
people from other ethnicities (British and European).
Respiratory disease and anxiety disorders were found
in 21.6% of Maori people, 17.8% of Pacific Islanders,
and 18.3% of people from other ethnic backgrounds. It
appears then that the prevalence of respiratory disease
is much higher in people with a mental illness than in the
general population, and certain ethnic groups may be
more likely to present with respiratory health problems
than others.

Frith, Esterman, Crocket and James (2004) examined

28

3 patients who smoked cigarettes (identified as the
most important risk factor for COPD) and displayed
respiratory symptoms. Only nine of these patients
had been diagnosed with COPD despite the authors’
findings that 31% met diagnostic criteria for COPD. They
suggest that COPD is often mistaken for asthma, or is
simply unrecognised.

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 11

2.4 ALCoHoL & iLLiCiT DrUG USe

Illicit drug use is a major issue when assessing the physical
health of mental health consumers. Although it is a legal
substance, alcohol will be included in this section as it is
often associated with mental illness. Other substances
such as amphetamines, cannabis, cocaine, ecstasy,
hallucinogens, heroin, inhalants and anabolic steroids are
also prevalent and poly-drug use is common. Through the
use of licit and illicit drugs, physical health often deteriorates,
and comorbid drug use and resulting physical conditions
can cause difficulties in management (Hilton, 2007).

From 2006 to 2007 Australian law enforcement officers
seized 5,443 kgs of stimulants (e.g. amphetamines),
4,782 kgs of cannabis, 647kgs of cocaine, and 86kgs of
heroin, arresting over 82,300 people on drug offences
(Australian Crime Commission, 2009). The quantity of
illicit drugs seized nationally is rising in all areas, with
amphetamine-type stimulants increasing in weight by
320%, heroin by 192%, cocaine by 1300% and other
drugs such as steroids increasing in weight by 63%
from 2005/06 to 2006/07. In Australia, cannabis is still
the most widely used illicit drug, accounting for 69%
of all national drug arrests. In 2004, around 84% of the
population had consumed alcohol in the past 12 months
(Australian Institute of Health and Welfare, 2007), and
38% of Australians 14 years of age and over had used
an illicit drug at some point in their lives.

Substance use disorders are often comorbid with
mental illness, in particular, psychotic disorders (Jane-
Llopis & Matytsina, 2006). There is some evidence for
the self-medication hypothesis in that many people
prefer particular substances over others in an attempt
to alleviate particular emotional problems they may be
experiencing (Khantzian, 2003; Suh et al., 2008), while
other theories posit that the emotional problems occur
after the person starts abusing licit and illicit substances.

Hambrecht and Hafner (1996) suggest that bidirectional
causality is probable, as there is evidence for both
and, at times, drug abuse and symptomology emerge
simultaneously. In their study of 232 people diagnosed
with schizophrenia, they found that 24% of people
abused alcohol and 14% of people abused drugs, twice
the rate of abuse found in their matched control sample.
The temporal order given for those people abusing
alcohol or drugs revealed that 32.7% of people had an
alcohol problem at least one year before (commonly
more than five years before) the first symptoms of
schizophrenia appeared, 18.2% of people had an
alcohol disorder and the first symptoms of schizophrenia

appear at the same time (within the same month), and
49.1% of people developed an alcohol disorder after
the first symptom of schizophrenia appeared. For drug
abuse, 27.5% of people abused drugs before the first
symptoms of schizophrenia appeared, for 34.6% drug
abuse and schizophrenia appeared concurrently, and
for 37.9% of people drug abuse occurred after the first
symptoms of schizophrenia appeared. This suggests
that alcohol and drugs may play a major role in inducing
psychosis, but they may also be used in an attempt to
alleviate emotional distress.

2.4.1 Alcohol

Alcohol consumption rates in Australia see 21% of
people drinking at a level that poses a high risk to their
health (ABS, 2008). When broken down into specific
age groups, the highest level of reported risk in drinking
behaviours was seen in the 25yrs to 34yrs age group for
males, and the 45yrs to 64yrs age group for females.

Alcohol use disorders are often associated with anxiety
disorders, and relapse rates following treatment are
difficult to predict (Kushner et al., 2006; Kushner et al.,
2009). It has been suggested that more often than not,
the anxiety disorder precedes the alcohol disorder and,
therefore, should be treated first. An opposite temporal
direction is seen with depression, with a recent review
of the literature suggesting that alcohol disorders often
precede depression (Jane- Llopis & Matytsina, 2006).

Chronic health complications can be seen with long-
term alcohol abuse. Liver dysfunction can typically
occur, along with possible brain damage (Hilton, 2007).
Wernicke’s encephalopathy, a degenerative brain
condition, results from vitamin B1 (thiamine) deficiency,
and failure to treat this can in turn, result in the irreversible
damage of Korsakoff’s syndrome. Dependence and
withdrawal symptoms such as delirium tremens and
seizures can also occur, and detoxification for moderate
to severe symptoms needs close monitoring.

Oral, throat and oesophageal cancers have also been
associated with chronic alcohol consumption (Australian
Institute of Health & Welfare, 2005), and alcohol abuse
can also affect the metabolism of prescription drugs,
resulting in cardiotoxicity, sedation, and lowering of the
seizure threshold (Hilton, 2007).

2.4.2 other illicit Substances

Substance use disorders are often comorbid with
psychotic disorders (Lambert et al., 2005; Tucker, 2009).
Lambert et al. (2005) evaluated 643 patients aged from 15

12

to 19 years who entered the Early Psychosis Prevention
and Intervention Centre (EPPIC) between 1998 and
2000. They found that 74.1% of people presenting with
early episode psychosis had a lifetime prevalence of
substance use disorder, 61.6% at baseline. Of the 385
people experiencing a first episode psychosis who also
had a baseline substance use disorder, 70.6% had
cannabis-related disorders, 16.4% had polysubstance
use, and 13% used other substances such as opiates,
alcohol or amphetamines.

Of note, a review of this research suggests professional
unease with the concept of ‘drug-induced psychosis’
(Tucker, 2009). Crebbin et al. (2009) found little difference
in levels of violence and hospitalisation between a
drug-induced psychosis group and a first-episode
schizophrenia group who were also illicit drug users. One
third of the drug-induced psychosis group went on to
develop a schizophrenia-spectrum disorder. In a review
of longitudinal studies on cannabis use and psychosis,
Degenhardt and Hall (2006) found that regular cannabis
use was a strong predictor of the reporting of symptoms
of psychosis, and an increased risk of schizophrenia
emerged.

The physiological effects of amphetamines and related
drugs such as ecstasy and cocaine tend to be quite
similar, although some drugs are addictive whereas
others such as ecstasy are not (Kalant, 2001). Acute
effects such as muscular tension, bruxism (teeth
grinding), jaw clenching, restlessness of the legs, and
increased body temperature tend to occur when the
drug is taken. Two to three days after taking the drug,
pain and stiffness in the lower back, headache, nausea,
dry mouth, blurred vision, loss of appetite, insomnia, and
a fluctuating heart rate and blood pressure tend to follow.
For some people, hyperactivity, inability to focus, mild
hallucinations, depersonalisation, and anxiety can occur.
Longer-term use or residual effects can result in serotonin
neurotoxicity, impairments of memory, decision making,
information processing, greater impulsivity, panic
attacks, recurrent paranoia, and psychotic episodes.
Major physical toxicity (hepatic, cardiovascular, cerebral,
and hyperpyrexic) and even death can result.

McKetin et al. (2008) found that methamphetamine users
tended to show poorer physical health if they injected the
drug, were long-term users (10 years or more), or had
impaired mental health (e.g. an anxiety or depressive
disorder). People who were engaged in polydrug use e.g.
heroin or pharmaceutical opioids such as prescription
analgesics or methadone, and benzodiazepines or
antidepressants also showed poorer physical health.

The physical health risk from opioids such as heroin are
considerably lower than other drugs (Kalant, 2001). Much
of the physical harm produced by heroin is caused from
unsterilized needles, needle swapping (e.g. HIV/AIDS,
hepatitis C), the intravenous use of drug preparations
intended for oral use only (i.e. respiratory death occurring
from overdose), and abscesses and cellulitis which tend
not to reoccur once drug injection has ceased (Kalant,
2001; Williamson et al., 2008).

Poor physical health can also result from the lifestyle
and psychosocial factors with which drug addiction is
associated, such as poverty, tobacco smoking, and poor
nutrition. In a 24 month longitudinal study of 615 heroin
users in Australia, the only significant predictor of physical
health status was the amount of time spent in residential
rehabilitation (Williamson et al., 2008). Residential
rehabilitation provides the basic requirements for good
health such as stable accommodation and regular meals
which are generally lacking in the lives of heroin addicts.

Anabolic steroids are known performance enhancers,
and although they are considered to be controlled
substances in countries such as Australia, they are
readily available for non-medicinal purposes via
e-mail orders and the internet from other countries
(Kicman, 2008). The most commonly used steroids
in sport are stanozolol, nandrolone, testosterone, and
methandienone, and veterinary medications such as
trenbolone and boldenone have also been used to
enhance performance.

Significant changes in anxiety, aggression, and sexual
behaviour have been noted, primarily due to irregular
serotonergic and GABAergic transmission (Clark
& Henderson, 2003). Cardiovascular events (e.g.
myocardial infarction, stroke, sudden cardiac death),
cholesterol dysregulation (e.g. high LDL levels, low HDL
levels, low apolipoprotein-1 levels), impaired liver function,
liver tumours and jaundice, hypomania and depression
are among the many adverse effects prominent in the
abuse of anabolic steroids (Kicman, 2008).

2.5 PSyCHoSoCiA

L

The links between physical and mental health are well
established, and have been shown to be bidirectional.
People with poor physical health often show lower
levels of mental well-being (Kendall-Tackett, 2009;
Thomas, 2008). For example, weight gain can seriously
impair social relationships through stigmatisation.
Alternatively, people with poor mental health tend to
have more physical health issues than people with

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 13

better mental health (Lawrence et al., 2001; Osborn et
al., 2007). Family and intimate relationships, community
involvement and friendships, socio-economic status
and employment, and culture and religion can all impact
upon the physical health of mental health consumers.

Coping resources and processes affect both mental
and physical health, and social support is viewed as a
key factor in a person’s management of stressful events
(Taylor & Stanton, 2007). Social support can generally be
defined as the provision or receipt of emotional support,
intimacy, affection, appraisal and affirmation (Hale et
al., 2005). In some cases though, social and emotional
support are considered separate entities, with the latter
term reserved for feelings and emotions and the former
term referring to relationships and interaction in general.

The connection between social and emotional support
and physical health has been widely researched, with
findings revealing that the lower the levels of emotional
and social support, the higher the levels of physical and
mental distress (e.g. anxiety and depressive symptoms)
(Strine, Chapman, Balluz & Mokdad, 2008). To this end,
the provision of social supports for people experiencing
health problems is vital.

Jacobson (1986) encourages consideration of the types
and timing of social supports linked to the process
of coping with psychological and physical health
problems. Stressful situations occur in the form of
crises, transition, and deficiencies. A crisis is a situation
which occurs suddenly and is of limited duration. It is
severely threatening to the person’s well-being, and
results in marked emotional arousal. Transition is where
a person goes through a time of change, both personal
and relational. This involves a shift in meaning, resulting
in changes to the person’s way of thinking about
themselves and the world around them. Deficiency is
defined by chronically excessive demands and a lack
of resources to meet those demands. The association
between these three kinds of stressful situations is not
necessarily linear, as Jacobson suggests. For example,
there will be individual differences in the amount of time
it takes to typically progress from one situation to the
next, some situations may not occur (e.g. transition and/
or deficiency after a crisis), certain situations may occur
simultaneously, or a person may start with a deficiency
that over time develops into a crisis.

Figure 1 links stressful situations with appropriate types
and timing of supports. Support for a person experiencing
distress may be given via emotional (i.e. fostering feelings
of comfort, care, and security), cognitive (i.e. information,

knowledge, advice), and/or material means (goods and
services) (Jacobson, 1986). Although the receipt of
support engenders coping and eases stress, it is the timing
of these supports that also determine their effectiveness
and perceived helpfulness.

Emotional support for a person in crisis allows the
expression of feelings – fear, anxiety, emotional distress.
On the other hand, a person going through a transitional
period in their life would find information helpful, assisting
them with decision making and personal direction.
Finally, a person experiencing a deficiency (e.g. housing
and homelessness) would greatly benefit from material
supports (e.g. rent assistance, hostel accommodation).

2.5.1 familial relationships

Social and emotional support is associated with a
reduced risk of morbidity, mental illness, and mortality,
and affects the way in which people cope with stressful
events and situations (Uchino, 2006; Strine et al., 2008).
The structure and functions of interpersonal relationships
reveal how social support provides two distinct pathways
of influence upon physical health.

A behavioural pathway facilitates healthy activities such
as good nutrition, not smoking, and exercise, whereas a
psychological pathway facilitates areas such as positive
mood states or feelings of control (Uchino, 2006).
Both pathways are linked together and influence each
other. For example, a stressed person may reduce their
exercise routine due to other pressures in their life, yet
exercise may assist in reducing the amount of stress
the person feels. Both pathways also have a reciprocal
influence on social support processes e.g. psychological
distress may influence perceptions of support, and
these perceptions may negatively contribute to social
interactions.

Taking a lifespan approach, Uchino (2009) suggests that
children who experience more parental support and less
familial conflict tend to develop a ‘positive psychosocial
profile’. That is, their levels of perceived support, control,
and self-esteem are higher, thus enabling them to cope
with life stressors in a more effective, flexible and proactive
manner. This is supported by earlier research, where
perceptions of close social support from significant others,
family, and friends equates to lower levels of depressive
symptoms, hassles, and substance abuse (Jackson,
2006). These people also tend to have a healthier diet,
show better adaptive care-seeking behaviours, and for
women, higher levels of physical exercise.

14

Hale, Hannum and Espelage (2005) examined the
relationship between social support and physical health.
The authors found that women reported higher levels
of social intimacy such as closeness, emotional self-
disclosure, warmth and validation, and more physical
symptoms of ill health than men did. Men who reported
higher levels of belonging (i.e. connection to groups)
tended to report fewer physical symptoms of ill health.
This association between feelings of belonging and
physical symptoms of ill health was not found with
women. Rather, women who reported higher levels of
belonging and self-disclosure tended to report better
overall health perceptions, yet no association was found
with the reporting of physical health symptoms.

The importance of family networks and social supports
cannot be understated. Yet appropriate supports for
patient needs may not always be provided. Fleury et
al. (2008) examined this in 186 outpatients diagnosed
with schizophrenia or delusional disorder. For patients
in contact with their family, 37% had physical health
problems. Despite familial contact, 61% reported a need
for daytime activities and social company, 31% revealed
a need for intimate relationships, and 33% had a need for
sexual expression. No help was obtained from relatives
or services in regard to their health for 10.5% of people,
social needs (31%), or information and utilities (31%).
Patients not in contact with family reported a similar
percentage of physical health problems (35%), a lower
need for daytime activities (44%), a slightly lower need
for social company (50%), a similar need for intimate
relationships (26%), and a much lower need for sexual
expression (14%). No help was received from relatives or
services in relation to health for 10.6% of people, social
needs (42%), or information and utilities (27%). This
suggests that despite contact with family, many people
with mental health issues do not receive adequate
supports from either their family or relevant services. It
also shows that needs for intimacy and sexual expression
are not necessarily being met, regardless of whether the
person is in contact with their family or not.

Fan et al. (2007) investigated sexual functioning and
quality of life in patients with a diagnosis of schizophrenia.
They found high rates of sexual impairment (desire/
interest, frequency of desire, sexual arousal, orgasm,
sexual pleasure) across clozapine, olanzapine, and
typical antipsychotic groups. Overall, 60% of men and
80% of women had impaired sexual functioning.

A review of the sexual side effects of SSRI’s and other
medications reveals sexual impairment in 24% to 73% of
people (Schweitzer, Maguire & Ng, 2009). The authors

explain the large variation to be dependent upon the
sensitivity of the measure, concluding that it is likely
that at least half of the people taking SSRI’s experience
some form of sexual side effect. Other medication
groups that can have adverse sexual side effects are
benzodiazepines, antipsychotics, mood stabilisers,
antihypertensives, antiepileptics, prostate medications,
and recreational drugs.

Effective treatment strategies need to address issues
such as perceptions of close emotional and social
support, intimacy, and sexual dysfunction, and how this
may impact upon the physical health of patients. Family
contact in itself is not enough as the supports given may
not meet the needs of the person.

2.5.2 Community involvement

Hale et al. (2005) advised that a sense of belonging
impacts upon physical symptoms and perceived
overall physical health. Belonging is not restricted to
intimate relationships, but can also apply to community
engagement and group activities, where a connection to
others and having someone to talk to appears to protect
people against physical symptoms of ill health.

A qualitative evaluation of a heath programme aimed at
reducing obesity in people with severe mental illnesses
found that material supports to access fitness facilities,
cognitive supports to facilitate understanding of food
and nutrition, and emotional supports to develop new
friendships provided the most benefit to participants
(Shiner et al., 2008). Kindness, being in a non-
stigmatizing environment, and having others listen to
them allowed participants to gain self-confidence and
develop new social skills.

emotional Suppo

rt


Cris

is

Transition


Cognitive Support

Deficiency


Material Support

Figure 1. Types and timing of supports in stressful situations
(adapted from Jacobson, 1986, p.254).

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 15

The advantages provided by the receipt of social support
can also be seen in the provision of social support. That
is, the mental and physical health of people with a severe
mental illness can benefit greatly by providing assistance
to others who also have mental health concerns (Bracke,
Christiaens & Verhaeghe, 2008).

Bracke et al. (2008, p.453) suggest that mental health
services should provide a balance in the receipt and
provision of peer support. A peer support network
affords a crucial resource that a person can turn to in their
time of need. It offers them the opportunity to redefine
or interpret their experiences in accordance with others
who have had similar experiences. It offers a sense of
belonging, love, care, and self-worth. The reciprocal
nature of peer support also enhances feelings of self-
worth, self-esteem, belonging, and personal and social
competence. It affords the person the acknowledgement
of their ability to problem-solve, and hence, enhances
coping skills and the recovery process.

Davidson et al. (2006) adds that the availability of peer
supporters enhances the credibility of the service
provider in that the peers offering support drew upon
their own experiences of mental illness in order to
engage and assist others. It may be then, that the peer
supporter’s alliance with the support service engenders
understanding and acceptance of the client’s distress,
lending credence to the service provider’s ability to offer
effective treatment.

A 12 month peer support trial was undertaken in Western
Australia to improve the physical health of people with
a mental illness (Bates, Kemp & Isaac, 2008). Peer
supporters assisted clients to find a GP, increase their
physical activity levels (walking), lose weight, link up with
community exercise services, quit smoking, and change
their diet by adopting healthier eating habits. The peer
supporters themselves showed improvement in their
own physical and mental health, increased confidence
and self-esteem, and some also managed to stop
smoking. Pre-trial concerns expressed by clinicians
were alleviated, as peer supporters showed a high level
of professionalism by maintaining confidentiality and
responsibility in their roles. Clinicians could clearly see
that the mental health of peer supporters had improved
rather than deteriorated. A number of barriers to the
success of the trial were noted, such as the rigidity
of the organisational culture of mental health, and the
insufficient training and insecurity of clinical staff resulting
in a lack of understanding and staff reluctance to promote
peer support. By the end of the trial clinicians saw the
importance of attending to the physical health needs of

their clients, and how this improvement promoted better
mental health and recovery.

2.5.3 Socio-economic Status
and employment

The overwhelming majority of the main indicators
of health status (e.g. self-rated health, functional
impairments, disease-specific morbidity, and mortality)
are inversely associated with Socio-Economic Status
(SES) (Schnittker & McLeod, 2005). For example,
cardiovascular disease is more pronounced in low
socioeconomic areas, with 5.2% of people reporting a
stroke, heart and/or vascular disease as compared to
2.7% of people in higher socioeconomic groups. Death
rates from cardiovascular disease for low SES areas
are 20% higher than the more prosperous areas (ABS,
2006).

Unfortunately, low SES has a consistently negative
relationship to mental illness (Hudson, 2005). That is,
the lower a person’s SES, the higher their risk of mental
illness. In examining links between SES and mental
illness during young adulthood, Miech et al. (1999)
found high prevalence rates of anxiety and antisocial
disorders but surprisingly, not depressive disorders in
low SES areas. Educational attainment, and therefore
future prosperity, was not affected by anxiety and
depressive disorders, but antisocial disorders showed a
high risk of failure in educational pursuits. These results
concerning depression don’t necessarily hold for people
later in life though. Koster et al. (2006) reveal that low
education or income levels result in a 50% increased
risk of depression in older adults (aged 55yrs to 85yrs).
Psychosocial factors such as self-efficacy and social
networks tended to be lower and smaller than those of
people from higher SES areas.

A low SES also affects the affordability of medications
and essential health services. Rising medication costs
and changes in co-payments under the Australian
Pharmaceutical Benefits Scheme has seen a variation
in the scripts being filled by patients (Hynd et al.,
2008). No change or an increase was observed in the
dispensing of psychotropic medications, yet decreases
in medications dealing with physical health side effects
such as insulin, statins, and anti-Parkinson’s drugs are
worrying. A significant decrease in dispensing to people
on social security payments suggests a greater potential
for adverse health outcomes in people with mental
health problems.

16

While employment generates greater affordability,
employment is beneficial to health in many other ways.
A recent study on psychoses and employment found
unemployment to be associated with more negative
symptoms and a poorer quality of life (Turner et al.,
2009). Interestingly, people involved in non-labour force
work such as students, homemakers, trainees, retirees
and volunteers were more like the employed group than
the unemployed group in regards to symptoms, quality
of life, and functioning. These associations suggest that
negative symptoms in psychosis may disable people
to the extent that they cannot be gainfully employed.
Alternatively, it also suggests that engaging in activity of
some sort, whether paid or unpaid, is more beneficial
than having no purposeful work at all, and may possibly
alleviate some of the negative symptoms of psychosis.

2.5.4 Culture/religion

Living in a society that is in complete contrast to the
values and belief systems of a person or group can be
highly stressful and challenging. Differences between
religious and cultural beliefs, values and meaning,
and practices and customs can result in alienation,
discrimination and abuse, serving to isolate the person
or group from the rest of society. “Culture includes,
but is not restricted to, age or generation; gender;
sexual orientation; occupation and socioeconomic
status; ethnic origin or migrant experience; religious or
spiritual belief; and disability” (Nursing Council of New
Zealand, 2009, p.4). Individuals belong to and identify
with many different groups. Culture then, is not static
but continuously evolving, resulting in diversity not only
between cultures but within cultures.

Multiculturalism and religious diversity highlight the need
to incorporate culture and religion into the understanding,
treatment and support of mental and physical health.
The need to respect and consider the views of a client
embodies the realisation that different people require
different therapeutic assistance. It is essential then, to
employ an holistic approach which takes into account
the social, emotional, spiritual, and cultural wellbeing
of the person and the community as a whole (Pyett,
Wapless-Crowe & van der Sterren, 2008).

Language

Communication and understanding are often hindered
through language barriers. The Office of Multicultural
Interests in WA (2008) note that 27.1% of WA’s population
were born overseas, with 49.2% of people having at least
one parent born in a country other than Australia, and

11.4% of WA’s population speak a language other than
English at home. In WA, diversity is highlighted through
the identification of over 100 religious faiths, and around
270 different languages. The proportion of people who
were born overseas and did not speak English very well
(or not at all) was 5% as compared to the Australian total
of 10%. As many people do not speak English well, the
use of interpreters enables better communication and
understanding between client and practitioner. In many
cases though, the client may prefer to have a family
member to assist with their understanding and expression.

The Self and Family

Notions of the interconnectedness of self and family differ
throughout the world. Hofstede (1984) introduced the one
dimensional structure of individualism versus collectivism,
where cultures emphasising autonomy (western) were
compared to cultures that emphasise dependence (non-
western). This line of thinking was furthered by Markus
and Kitayama (1991), proposing independent and
inter-dependent self-construals. Sato (2001) offers two
self-systems – autonomy and relatedness. In western
cultures, high levels of autonomy and moderate levels
of relatedness are valued. It is believed that individuals
require a strong sense of control, achievement,
competence, agency, independence, uniqueness, and
separateness from others to maintain emotional/mental
health. People in collectivistic (primarily non-western)
cultures tend to place greater value upon relatedness,
with only moderate levels of autonomy needed to
maintain emotional/mental health. Collectivistic cultures
emphasise communion, affiliation, connectedness,
harmonious relationships, interdependence, and
sociality. Fusion with others and emotional attachment
throughout life results in a strong sense of unity and is
essential to ensure well-being.

The lack of importance placed upon relatedness in
western cultures may be quite detrimental to the physical
and mental well-being of people who do not hold those
same values. For example, indigenous Australians hold
very strong beliefs of kinship, community, and spirituality
(O’Brien, Boddy & Hardy, 2007). Diagnosis and treatment
must be meaningful and relevant to the person and their
significant others. Therefore, the clinician must engage not
only the ill person, but their family, extended family, and in
many cases, their community as well. Issues of relatedness
may also arise within western cultures as, although a
person may be raised within an individualistic society, their
personal values and indeed their family’s values may align
more strongly with relatedness than with autonomy.

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 17

Mental/Physical Health Ideology and Treatment

Values and beliefs also differ between people and cultures
on notions of mental and physical illness. Individual
variation within cultures suggests that no universal
explanation of mental illness can be applied to an entire
cultural group (Tyson & Flaskerud, 2009). Individuals and
groups consider emotions, thoughts and behaviours
within the context of their own society when making
determinations of who is and who is not mentally ill.

Western medical explanations and treatments for illness
may not carry the same meaning or relevance for people
from other cultures. For example, practicing Muslims
focus their attention on the soul, and although caring for
the body is viewed by Muslim people as essential, it is
secondary to the soul (Haque, 2004). Treatment then may
incorporate balance, or restoring the flow of energy in the
person’s social, familial, personal and spiritual life (Tyson
& Flaskerud, 2009). In multicultural societies, groups
and individuals tend to blend (to differing extents) both
modern and traditional explanations and understandings
of illness, which are influenced by their political, social,
economic, medical, and religious experience.

Health treatments and supports may also differ between
communities. Definitions of support are dependent
upon beliefs surrounding autonomy, dependency and
reciprocity, and these beliefs in turn, shape the way
in which people and groups give, receive, accept or
reject support (Jacobson, 1986). Culturally adapted
interventions and supports allow insight into the lived
experience of physical and mental illness, and provide
alternative methods of assisting people in need.

An example of this is Motivational Care Planning (MCP),
designed for indigenous Australians with mental illness
living in remote communities (Nagel, Robinson, Condon
& Trauer, 2009). This particular intervention focused on
understanding and incorporating local perspectives of
mental health through collaboration. The importance
of family, a story-telling approach, and traditional and

cultural activities emerged for this particular group of
people, and MCP revealed improved outcomes when
compared to ‘treatment as usual’. Importantly, these
gains were sustained over an 18 month period.

Cultural Safety

Egalitarian practices where all people are treated
equally regardless of their culture can actually work to
disempower minority cultures as they do not recognise
differences between or within cultures (Australian
Government Department of Health and Ageing – AGDHA,
2004; Haswell-Elkins, Sebasio, Hunter & Mar, 2007).

Cultural awareness is viewed as a ‘first step’ in the
understanding of difference, where people learn about
cultural groups, behaviours, rituals and practices other
than their own (Nguyen, 2008). However, it doesn’t
acknowledge diversity within groups, or indeed,
that culture is dynamic and in a process of continual
change. Notions of cultural sensitivity go one step
further in that they accept the legitimacy of differences
in the experiences and realities of others (e.g. historical,
political, economic, emotional, social), yet it still asserts
one world view over another, and doesn’t provide clients
with control and power over their own mental and
physical health.

Cultural Safety, on the other hand, is a safe environment
for people where there is no denial, assault or challenge
to their identity or needs (Williams, 1998). Cultural Safety
deals with the process of collaboration – shared respect,
meaning, knowledge and experience – where people
learn together with dignity, and actually listen to each
other. Ball (2008) gives five principles that generate
Cultural Safety (see Table 1).

The resulting cultural competence of the integration of
Cultural Safety into mental and physical health practice
ensures that behaviours, attitudes and policies come
together and work effectively in a system, agency or
among health professionals (Nguyen, 2008).

Table 1. The five principles of Cultural Safety.

Protocols Addresses cultural forms of engagement (e.g. informed consent/permission), seeking and sharing cultural knowledge.

Personal
Knowledge

Being mindful of your own cultural identity, socio-historic location/power in relation to the client, and personal
ideology and commitment to ways of conceptualising mental health and well-being, sharing personally relevant
information creates equity and trust.

Partnerships Sharing knowledge versus ‘telling’, collaborative practice where those seeking help share in the problem solving
versus expert/authority models.

Process Ensuring equity and dignity, negotiating goals and activities, talking less and listening more, frequent checking to
ensure that proposed solutions fit with the client’s values, preferences and lifestyle.

Positive
Purpose

Building on strengths and avoiding negative labelling, ensuring confidentiality, being accountable, doing no harm,
making it matter and ensuring real benefits.

3
18

The physical health assessment and ongoing monitoring
of mental health consumers involves collaboration and
partnership between mental and physical health staff
and consumers. The literature review revealed five major
domains of physical health prevalent for mental health
consumers. Within these domains, key components for
assessment were identified:

1) Medication effects – antipsychotics, antidepressants,
anxiolytics, mood stabilisers

2) Lifestyle issues – exercise, diet, smoking, dental,
cholesterol

3) Pre-existing or developing physical conditions –
including HIV/AIDS and STI’s, hepatitis C and B,
cancer, irritable bowel syndrome, type 2 diabetes,
cardiovascular disease, respiratory disease

4) Alcohol and Illicit drug use – alcohol, other substances

5) Psychosocial issues – familial relationships, social/
community involvement, Socio-Economic Status
and employment, culture and religion

The ongoing monitoring of these key areas of health
ensures equality of health care across Australia’s diverse
population. The intricacies of the monitoring process can
be eased through the guidance and application of a user-
friendly, time-efficient, cost-effective, and informative
assessment package based upon best practice
methodology. Coordination of services involving mental
health clinicians, general practitioners and physicians at
the local level is crucial.

3.1 iNPATieNT / oUTPATieNT
AND CoMMUNiTy PHySiCAL
HeALTH CA

re

The assessment protocols proposed here take a
biopsychosocial approach to physical health assessment.
The Clinical Guidelines for the Physical Health Screening
of Mental Health Consumers package can be used and/
or adapted for inpatient, outpatient, or community care
situations. This package serves as an aid to mental health
clinicians and GP’s in the physical care of mental health
consumers. It focuses on screening and monitoring,
not specific treatments, which should be carried out by
qualified clinicians In order to assess the key dimensions
of physical health for mental health consumers, three
avenues of investigation are to be take

n:

• Medication monitoring

• Physical investigations, and

• Lifestyle and psychosocial assessment

Each of these areas requires specific tools that have
been either sourced or developed for the Clinical
Guidelines package. A clinical algorithm wall chart
for monitoring metabolic syndrome in mental health
consumers starts off the package, giving indices and
monitoring recommendations for waist circumference,
blood pressure, fasting lipids, and fasting blood glucose1
(see Appendix 1). This represents the basic physical
assessment to be conducted. In order for an informative,
individualised assessment to occur, a general screening
form2 (see Appendix 2) is provided, where all consumer
results are noted. This screening form spans a time
period of 24 months, allowing for an initial baseline
measurement and an overall view of the consumer’s
physical health to reveal any changes that may be
occurring over time.

Each major category of medication (and sometimes
individual medications) will require specific tests. Working
in collaboration, the monitoring of consumer medication
and physical health examinations and investigations
are to be directed and conducted by the consumer’s
psychiatrist and/or general practitioner. To this end, the
general screening form lists the tests needed for each
medication/medication category.

A second screening form has also been provided
which outlines additional tests required for specific
medications, and a third and separate screening form
has been provided for clozapine. In the case of multiple
medications being prescribed, the Psychiatrist/GP
selects the general screening form plus the additional
screening form. The main results are placed upon
the general form and specific medication tests for the
second drug that are not covered on the first form need
to be highlighted and monitored on the second form.

The physical examination/investigation conducted by
the consumer’s GP should take note of existing and/
or developing physical health conditions common for
mental health consumers. These include conditions
such as Irritable Bowel Syndrome and gastrointestinal
complaints, and cardiovascular disease. A Clinician
Handbook is included which provides evidence-based
information on specific medical tests and side-effects
for each category of medication (including the normative
ranges for each test), common physical conditions
occurring significantly more often in mental health
consumers as compared to the general population,

1 Taken from Waterreus & Laugharne (2009). Screening for the metabolic syndrome in patients
receiving antipsychotic treatment: a proposed Algorith

m

2 Adapted from the PaRK Mental Health Service Screening Protocols –
Shymko, Muldoon & Bruton (2009)

Clinical Guidance and Monitoring Protocols3

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 19

and a brief overview of lifestyle, alcohol and illicit drug
issues, and psychosocial issues. Findings relevant to the
physical examination/investigation should be noted on
the general screening form.

The Psychosocial Assessment booklet (colour-coded
to match the general medication screening forms) can be
completed by the psychiatrist, the GP, a mental health nurse
or a case worker. The booklet includes tools assessing
the dimensions of lifestyle (exercise3 and diet4, smoking2,
dental5, sexual activity6), illicit drug use (alcohol use7 and
dependence8, other drug use9 and dependence10), and
psychosocial aspects (culture/religion11, psychosocial
supports12).

3 Adapted from Lifescripts – Department of Health & Ageing (2008)

4 Adapted from World Health Organisation (2004)

5 Adapted from Griffiths et al. (2000) – Oral health care for people with mental health problems:
Guidelines and recommendations

6 Adapted in part from Ware & Sherbourne (1992) – Medical Outcomes Study (MOS)
Sexual Functioning Scale

7 AUDIT – Babor, de la Fuente, Saunders, & Grant (1992)

8 SADQ-C – Stockwell, Sitharan, McGrath & Lang (1994)

9 DAST – Skinner (1982)

10 SDS – Gossop, Darke, Griffiths, Hando, Powis, Hall & Strang (1995)

11 Based on notions of Autonomy and Relatedness (Sato, 2001), and Cultural Safety (Williams, 1998)

12 Based on Jacobson’s (1986) ‘types and timing of social supports’, and the
MOS Social Support Survey developed by Sherbourne and Stewart (1991)

The cultural/religious/spirituality component has been
placed at the front of the booklet to allow the assessor
to first develop rapport and gain understanding of the
consumer’s point of view. The psychosocial supports
assessment has been placed at the end of the booklet
enabling an evaluation of what kinds of supports will
be needed to ensure successful monitoring of physical
health (e.g. someone to offer emotional support, getting
to the doctor, etc.), and encourage positive change.
These surveys can be completed by either the consumer
or the assessor, and the results are to be placed on the
general screening form.

In essence, the Clinical Guidelines package provides
an over-arching, individualised, evidence-based
evaluation of each consumer’s physical health status. It
is recommended that wherever possible, assessment
is conducted within 48hrs of the consumer’s first
presentation to the mental health service, and that the
initial assessment results be used as a baseline from
which to monitor ongoing health status.

20

3.2 DiSTiNCT PoPULATioNS

The physical health care of distinct groups of people
within the mental health population may require additional
consideration in regard to the issues that they face. The
resulting treatment plan should make allowances for
issues such as age, ethnicity, pregnancy, and disability.

3.2.1 People over 65 years of Age

The physical healthcare of consumers who are older
persons should be adjusted accordingly, as older persons
more frequently suffer from interrelated medical, psychiatric
and social issues. The initial assessment should have
particular focus upon physical health (NSW Department
of Health, 2009, p.23-25). It should be remembered that
older persons are particularly at risk of problems related to:

a) Falls

b) Multiple medication use

c) Malnutrition

d) Pressure areas (if they have reduced mobility)

e) Musculo-skeletal limitations and pain

f) Constipation

g) Cancer (Lawrence et al., 2000)

Assessment and management must take this into
account. Additional challenges to obtaining an accurate
and complete history may exist in some older people.
These may include hearing or visual impairment, memory
impairment, and minimisation of symptoms or conditions
due to perceived social attitudes or in order to please the
health staff. Consent to examination and treatment can
also be a complex issue with the elderly.

In new presentations and in relapse of established illness
in older persons, it is important to take delirium into
account and to communicate closely with community
practitioners. The possibility of elder abuse should also
be considered in situations of trauma.

3.2.2 Children/Adolescents

At initial assessment of a child or adolescent consumer,
physical examination may include developmental
assessment and specific issues such as screening for
sensory deficit in developmental delay (NSW Department
of Health, 2009, p.23-25). It is also important to be
aware of potential issues, such as physical or sexual
abuse, and to remain alert for physical signs. Particular
considerations when conducting a physical examination
of children or adolescents include:

a) Organisation – having a planned approach and
ensuring equipment is in good working order and
close to hand will help children and adolescents to feel
confident and enable the examination to go smoothly.

b) Flexibility – this is a critical element in the physical
examination of children and adolescents and should be
adopted in the overall care and treatment of this group.
For example, the presence of a parent or the use of a
doll (to explain a procedure) may be appropriate.

c) Safety – be careful of fittings and equipment in the
examination area. Reviewing the environment from a
‘child’s perspective’ (i.e. below adult eye level) may
assist in this process.

d) Communication – explaining what is happening in
age-appropriate language and reassuring the child
or adolescent is vital. Obtaining feedback from
them to assess their understanding of procedures
is recommended and is likely to improve their
co-operation.

e) Privacy – younger children may prefer the parent/
carer to be in the room but modesty will still be
important; older children are often extremely
sensitive about their bodies and may prefer privacy
while taking a history and/or conducting a physical
examination – this should be respected and will
foster a more relaxed atmosphere.

In Western Australia, the 1996 Mental Health Act (MHA)
“…does not specifically address minors but applies to
everyone, regardless of age. Whenever possible and
where appropriate, legal guardians should be involved
in the decision-making process when a minor is referred
under the MHA” (WA Department of Health, 2009, p.2).

If there are circumstances that make it unclear if the
involvement of a young person’s parents or guardians
is safe or practical, consultation with Child Protection
Services should be sought. In circumstances where the
consumer is a young person for whom the Minister or
Director-General of Community Services has parental or
care responsibility, a Department of Community Services
caseworker should participate in the planning process.

Health staff should be familiar with the key objectives
within Our Children Our Future: A framework for Child
and Youth Health Services in Western Australia 2008-
2012 (WA Department of Health, 2008).

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 21

3.2.3 Aboriginal and Torres Strait islanders

The specific historical, cultural, spiritual and social issues
of Aboriginal people must be taken into consideration
when identifying and addressing their physical health
needs (NSW Department of Health, 2009, p.23-25).

Many chronic diseases within the Aboriginal and Torres
Strait Islander population such as diabetes, hypertension,
cardiovascular disease and chronic renal failure are
significantly more prevalent than for the general population
(National Aboriginal Community Controlled Health
Organisation – NACCHO, 2005). As a consequence, life
expectancy is much lower. For example, the average life
expectancy of an Aboriginal or Torres Strait Islander male
is almost 21 years lower than that expected for all males
in Australia – 56 years as compared to 76.6 years (ABS,
2001).

Many Aboriginal people’s contact with government
services may have been negative, which can cause
suspicion and mistrust. This may be acutely important
for Aboriginal people with mental health problems and
disorders. It is recommended that mental health staff
dealing with Aboriginal consumers should familiarise
themselves with the National Aboriginal Community
Controlled Health Organisation/Royal Australian
College of General Practitioners’ National Guide to a
Preventive Health Assessment in Aboriginal People,
available online at:

www.racgp.org.au/aboriginalhealthunit/nationalguide

Another recent source is the Third Edition (2007) of
Murray and Couzos, Aboriginal Primary Health Care.

Physical examination and care and treatment of physical
health needs should reflect the key principles for working
with Aboriginal communities, including:

a) Services working in partnership

b) Holistic approach to mental health

c) Flexibility

d) Accessibility of services

e) Ability to follow people across areas

f) Respect and sensitivity for indigenous people

g) Involvement of family and others in care

h) Treating an individual as part of a family and the
community

i) Provision of education and training

j) Illness prevention

Health staff should liaise with specialist Aboriginal health
representatives in their area (e.g. Aboriginal Mental
Health Workers or Aboriginal Medical Services) to ensure
that their approach to providing physical health care for
Aboriginal consumers is consistent with the needs of the
local Aboriginal community.

The process should also:

a) Provide the consumer and family with relevant 24-
hour contact numbers for assistance

b) Identify community liaison contact(s) who can
engage additional support for the consumer such as
extended family, elders and community members.

c) Ensure actions are taken to resolve precipitating
events and other life stressors

d) Refer the consumer to Aboriginal health or medical
services whenever possible

e) Enquire as to whether the consumer wishes for family
to be present at the time of physical examination

3.2.4 Pregnancy

If a consumer is pregnant, it is critical that her physical
health is monitored and any health issues or disease
identified early (NSW Department of Health, 2009, p.23-
25). Health staff should also:

a) Carefully weigh the potential risks and benefits of any
medication the consumer may currently be taking
and discuss these findings and treatment alternatives
with the consumer.

b) Ensure the consumer is connected with antenatal
services and assist with booking if required.

c) With the consumer’s consent, liaise with appropriate
maternity services (perinatal psychiatrist/perinatal
mental health coordinator).

After the birth, early childhood nurses can provide, or
facilitate access to, psychosocial support, guidance and
monitoring of the infant’s progress. If there are concerns
about the health and safety of the child, consideration
may need to be given to reporting concerns of prenatal
risk of harm.

22

3.2.5 People with intellectual Disabilities

Cognitive and communication difficulties can make it
hard for people with intellectual disability to recognise
and communicate pain or other symptoms of ill health
(NSW Department of Health, 2009, p.23-25). Involving
family members or other support workers will support
the identification of health issues and the provision of a
medical history. However, these support people may be
unaware of symptoms, and an accurate history may be
difficult to obtain. It should also be noted that:

a) Physical examination may be difficult due to anxiety or
challenging behaviours in the person with intellectual
disability

b) The combination of difficulties with communication,
accurate history taking and physical examination may
mean that assessments are lengthy, so adequate
time should be allocated for this

c) There is a risk of ‘diagnostic overshadowing’, where
physical or behavioural symptoms may be ascribed
to the intellectual disability, and a physical or mental
health disorder overlooked as a result

The specific medical conditions and risk factors that
prevalence studies have identified occur more frequently
in people with intellectual disability should be considered.
The International Association for the Scientific
Study of Intellectual Disability (IASSID) has made
recommendations for the detection and management
of these conditions in people with intellectual disability
(2002) (see www.iassid.org).

The IASSID Health Guidelines for Adults recommend
action in the following areas:

Dental health
Sensory impairments
Nutrition
Constipation
epilepsy
Thyroid disease
Gastro-oesophageal reflux disease and H.pylori
osteoporosis
Medication review
immunisation status
Physical activity and exercise
Comprehensive health assessments
Genetics
Women’s health

3.2.6 People from Culturally and Linguistically
Diverse Backgrounds (CALD)

Physical care and examinations for consumers from
Culturally and Linguistically Diverse Backgrounds
(CALD) requires a culturally sensitive approach (NSW
Department of Health, 2009, p.23-25).

Health professionals should be aware of their own values
and beliefs. It is recommended that, when working
cross-culturally, staff approach CALD consumers with
sensitivity and respect for the social context of the
consumer’s problems. It is important to understand the
personal meaning of the illness for the consumer, their
family, and their community. The process should take
into account the following factors:

a) Lack of proficiency in English

b) Impeded access to health services due to language
difficulties and cultural expectations

c) Lack of awareness of available community services

d) Stressors experienced during the process of
adapting to mainstream Australian culture

CALD consumers and their families should have access
to interpreter services to facilitate the treatment planning
process where appropriate, including three-way
telephones or conference phones for use with telephone
interpreters. Health staff should refer to the WA Charter
of Multiculturalism (2004).

Where complex or unknown cultural dynamics are
involved, cultural advice should be sought from the
Multicultural Services Centre of Western Australia Inc.
(MSCWA) (see www.mscwa.com.au/).

Clinical Guidelines for the Physical Care of Mental Health Consumers: Report 23

Consultation and collaboration across the health
sector has been an important part of the process in
developing these Guidelines.

Once the first draft of the Clinical Guidelines for the
Physical Care of Mental Health Consumers assessment
and monitoring package was complete, each key
stakeholder was sent a Clinical Guidelines package.

Feedback on this package was sought through reference
group consultation, and if attendance was not possible,
stakeholders were able to make comment via other
means (e.g. email, post, phone).

Specific mental health group representation and
feedback was gathered from consumers and carers,
general practitioners, GP liaison officers, nursing staff
and nurse practitioners, psychiatrists and psychologists.

A diverse range of general health service representatives
were also consulted in the feedback process.

Service providers represented:

Dental Health WA

Department of Health, WA

fremantle Hospital

GP Network, WA

Great Southern Mental Health Services

Healthright

Health Networks Branch, Department of Health WA

infant, Child, Adolescent and youth Mental Health
Service, Graylands Hospital

Multicultural Services, South Metropolitan Area
Health Service

office of the Chief Psychiatrist, WA

ParK Mental Health Service

Personal Helpers & Mentors Program, Albany

rural Clinical School of Western Australia

State forensic Mental Health Service, WA

Statewide Mental Health Governance & Performance

Community, Culture & Mental Health Unit,
The University of Western Australia

Western Australian Country Health Service

From the consultation process, three key areas of
concern emerged. Firstly, general complaints of a lack
of standardisation across services for physical health
assessment of mental health consumers were received.
For example, it is not currently known what each service
is screening for (if at all), or how often this is occurring.
In this respect, stakeholders were pleased that Clinical
Guidelines had been developed and were almost ready
to be initiated.

A second point of concern was how to implement the
Clinical Guidelines and achieve consistency across
clinics. It was suggested that each clinic may need to
develop a management plan, dependent upon issues
such as staffing levels and available services (e.g.
regional areas may experience difficulties accessing
some services). Also, success will depend in part upon
coordination between health professionals to prevent
repetition of screening or failure to screen.

The third issue raised during consultation was the
sustainability of the Clinical Guidelines. A built-in review
mechanism would be needed for all dimensions,
particularly the medication testing and normative ranges
as new research findings may warrant change.

Detailed feedback was also received on the structure
of information in each component of the package.
Changes and adaptations were made to the first draft,
allowing for a better fit with the practicalities of physical
health assessment of mental health consumers. In
general, feedback was overwhelmingly positive and
many people looked forward to the introduction of the
Clinical Guidelines package on the basis that it would
have a positive impact on the physical health care of
mental health consumers.

Collaboration and Partnerships4

24

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Appendix 1 – Clinical Algorithm for monitoring metabolic syndrome in mental health patients

Appendices7

32

Appendix 2 – Screening Forms

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Community, Culture and Mental Health Unit
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L6, W Block, Alma Street
Fremantle, WA 6160

Tel +61 8 9431 3467
Fax +61 8 9431 3407
Web www.psychiatry.uwa.edu.au/research/community-culture

CRICOS Provider Code: 00126G

1

0

PRESCRIBING IN MENTAL
HEALTH PRACTICE – THE

BALANCING ACT
BEN GREEN

Learning outcomes:

By the end of this chapter you should be able to:

• Discuss the potential impact of psychiatric pharmacology on the physical health of
individuals with mental health problems

• Consider the potential impact of medical prescribing on the mental health of such
individuals

• Reflect on the role of the mental health practitioner in medication management

INTRODUCTION

Psychiatric prescribing undoubtedly has a major role in the treatment of mental
health conditions, alleviating symptoms, assisting recovery and enabling people
with such conditions to gain the stability they need for rehabilitation and psycho-
therapy. Nevertheless, such prescribing benefits can also incur a cost in terms of
adverse effects, from drowsiness to coronary heart disease. This chapter addresses
the effects on physical health caused by the prescription of psychiatric drugs and,
conversely, mental health problems associated with medical prescribing. Some of the

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 141

main physical problems associated with psychiatric prescribing will also be consid-
ered, including side-effects, drug safety and drug–drug interactions. The chapter
finally discusses the means by which psychiatric prescribing can best be monitored
and managed more safely.

Epidemiological studies repeatedly show that most people with mental health
problems are not diagnosed and are not treated (by counselling, psychotherapies or
prescribed drugs). Even so, the scale of prescribing of psychiatric drugs is huge and
increasing, with primary care physicians calling on their use in about 50% of the
cases of mental health problems they identify (Linden et al. 1999).

Some countries have tried to address this by using psychological therapies as
first-line options for anxiety and depression and yet the trend for prescribing
persists. Outside any discussion of the relative therapeutic values of the various
treatment options, it is prudent to note that roughly 10% of all health service
expenditure, in the UK, is on medicines and the cost of prescribing rose more
than tenfold between 1980 and 2007 (Office of Health Economics 2009). The
huge scope of psychiatric prescribing is worth considering for various reasons,
but key to this chapter is the fact that there are many physical implications of
these medicines and with their increased use such implications are becoming
more prevalent.

PSYCHIATRIC PRESCRIBING FOR INDIVIDUALS
WITH MENTAL HEALTH PROBLEMS

THE DRUGS DO WORK!
Before embarking on what will be a dauntingly long list of the negative aspects of
psychiatric prescribing, it is worth considering briefly whether the positive aspects
outweigh the negative. In short, do the benefits outweigh the risks? On balance,
I believe the benefits far outweigh the risks, but there will be counter-arguments,
sometimes forceful and well-reasoned. Other counter-arguments are sometimes
philosophical or perhaps overly optimistic regarding the severe and pervasive nature
of mental illness.

One way to consider the impact of the twentieth-century advances in psychiatric
pharmacology is to reflect on the consequences of severe mental illness (SMI) prior
to the introduction of first-generation antipsychotic medication in the 1950s. During
this time the long-term nature of SMI, together with the relatively low frequency of
spontaneous recovery, led to a progressive accumulation of patients in asylums. In
1870 there were 27,109 psychiatric beds in England and Wales. In 1910 there were
97,580 (Gregory 2004). At the start of the National Health Service (NHS) in 1948
over half of all NHS beds were psychiatric beds (Figure 10.1). However, something
happened to reverse this expansion. The bed numbers peaked at 148,100 in 1954
(Gregory 2004). Thereafter there was a rapid and persistent decline in bed numbers
so that in 2007 (when the UK population was 60,943,912), there were only 20,000

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS142

or so psychiatric beds. This is a similar number to the late 1800s when the popula-
tion was about 17 million or a third of that in 2007 (Green 2009).

The fall in psychiatric bed occupancy starting in the 1950s pre-dates any political
move towards community care and is based upon the efficacy of a new class of
drugs (the dopamine blockers), antipsychotics such as chlorpromazine (first synthe-
sised in 1950 and first used in psychiatry in 1952) and others such as haloperidol
(1958) and levomepromazine (1959) (Green 2004).

It was the success of these drugs which enabled patients to be discharged from the
psychiatric hospitals back into the community. Sometimes the effects were remark-
ably quick. Hospital records from this time include case histories where patients
admitted for decades were able to be discharged after weeks on the new drugs.

The argument can thus be made for the dramatic efficacy of psychiatric medication
in the treatment of mental illness. For the first time in millennia, humankind has had
the means to treat mental illness and alleviate suffering, preventing the need for the
incarceration of the majority of mentally ill people. Without the use of such drugs we
arguably might require an asylum-building programme of unthinkable proportions.

1

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Figure 10.1 Public psychiatric bed numbers in England and Wales 1850–2007 (peak in
1954) (Green 2009)

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 143

Having made the public health case for psychiatric medication, we must now
turn to the individual’s experiences of such drugs, which are not always completely
positive. It can be argued that some adverse physical effects are infinitely preferable
to decades of in-patient care for schizophrenia, or years of severe depression, but to
inform such an argument we must first increase our awareness of the extent of the
physical effects of some medications.

WHAT IS THE COST TO PHYSICAL HEALTH?
All medicines are associated with side-effects or adverse effects. These are difficult
to classify. Some of the effects are predictable, based upon the drug’s known phar-
macology, and others are somewhat unpredictable or idiosyncratic. Those working
in mental health care should consider the relative advantages of medication as well
as the prevalence and severity of any negative side-effects. Unfortunately, psychiatric
medication exposes individuals with a mental health problem to a wide a range of
serious physical health conditions, such as diabetes (see Chapter 3) and cardiovas-
cular problems (see Chapter 4), while also causing physical adverse effects which
can impact on the individual’s daily functioning. A drug like chlorpromazine, for
instance, is thought to derive its main antipsychotic effects from blocking dopamine
receptors in the brain (D2 receptors), but it also affects other receptors, such as his-
tamine. Its effects on histamine receptors cause the drowsiness associated with the
drug. In one way the sedation is an unwanted or adverse effect. In another sense,
for overactive and disturbed patients with insomnia this side-effect becomes a
desired effect. We can also predict its Parkinsonian-like side-effects (tremor and
muscle rigidity) from its effects on cholinergic receptors, and its tendency to cause
postural hypotension on its effects on adrenergic receptors. Its more unpredictable
or idiosyncratic effects are less easy to predict from pharmacology and are derived
from experience with the drug over many years – such as the photosensitive skin
suffered by people who take chlorpromazine (and a consequent need for topical
sun-blocking agents).

One of the key problems faced by individuals with mental health problems when
taking medicines is that their complaints about them are often attributed to their
underlying illness. No one can know every side-effect of a drug and even the litera-
ture does not always record them all. This can lead to problems when the health pro-
fessional discounts the individual’s experience. I shudder with embarrassment and
hesitate to disclose that as a student I found it difficult to credit a young woman’s
account of lactation on an antipsychotic and a male patient’s complaint that on an
antipsychotic he was ‘firing blanks’ when he masturbated. A little more experience
talking to clients and reading about psychopharmacology taught me the error of
my ways! New drugs are also sometimes marketed without all the side-effects being
known. Again, listening to the client is key. Shortly after paroxetine was marketed
in the 1990s I noted that it was a very good antidepressant and very good at allay-
ing anxiety, but I also had clients telling me, after some time on the drug, that they
felt very tearful if they failed to take the medication for a few days. Some described

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS144

towering rages; others described ‘electric zap sensations’ or ‘a series of images over-
lapping when I turn my head’. You can see how easy it might be to assume these
were symptoms of illness. The pharmaceutical company was not much help in iden-
tifying these experiences. It was only when dozens of clients described these symp-
toms and doctors started talking together about them that the unusual descriptions
gathered value as descriptions of withdrawal effects.

THE PHYSICAL IMPACT OF PSYCHIATRIC
MEDICATION

The relationship between physical and mental health is complex and psychiatric
medication has been implicated as a causative factor in a wide range of adverse
physical effects and conditions.

WEIGHT GAIN
While effective against psychosis, many of our current antipsychotic drugs promote
weight gain, and in such clients there appears to be a higher incidence of weight-related
disorders such as diabetes and coronary heart disease. In particular, second-generation
antipsychotic medication, once enthusiastically endorsed by pharmaceutical companies
and agencies such as the National Institute for Health and Clinical Excellence (NICE),
have now been found to promote weight gain, especially clozapine and olanzapine
(Tschoner et al. 2009). For example, the body mass increase with these can be a
significant (25% +) long-term increase. Over 10 weeks’ treatment with clozapine,
Allison et al. (2009) found that the average service user put on 4.45 kg; with olan-
zapine this was 4.15kg; and with risperidone it was 2.15 kg.

Weight gain is not confined to antipsychotics. Many antidepressants, if used long
term, also stimulate weight gain and this too is associated with the development of
metabolic syndrome (Andersohn et al. 2009). Implicated antidepressants include
amitriptyline, paroxetine and mirtazapine.

Apart from the physical risks associated with these complications, patients do
not like an altered appearance, as can be seen in Hamer and Haddad’s (2007) study
where 73% of patients reported concern about weight gain. This was particularly
prevalent in women and a consequent effect on compliance was noted.

In view of these problems, guidelines now state the need for prescribers to con-
sider physical health factors such as diabetes, or family history of diabetes, and
conduct relevant tests before embarking on antipsychotic therapy. A cautionary
note should be sounded about the use of antipsychotic drugs outside their intended
field. Sometimes, because of the side-effect of sedation, antipsychotics can be used
as sleeping tablets or as anxiolytics. This kind of use can be legitimate, but it is also
off licence – that is, neither the pharmaceutical company nor the state regulatory
bodies would readily sanction the use of the drug for off licence uses. This leaves the

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 145

client in a position of being able, in the event of an adverse reaction, to recover dam-
ages from the prescriber only, rather than from the usually wealthier pharmaceuti-
cal company. For instance, a prescriber could find themselves sued for prescribing
olanzapine to a client with anxiety disorder who later developed diabetes, especially
without ensuring the client had been through the necessary screening for diabetes
risks beforehand.

There are many ways of minimising weight gain and some of the key consider-
ations are outlined below:

• Consider antipsychotics that are least associated with weight gain, particularly in clients
with a family history of cardiac problems and/or diabetes

• Recent research has noted the possibility of using metformin in treating olanzapine-
induced weight gain (Praharaj 2011), although switching antipsychotics would seem more
practical than exposing a client to two drugs where a single alternative might do

• Dietary education/modification, for example healthy eating programmes
• Exercise programmes, coaching and training, such as referral on prescription schemes
• Weight monitoring programmes, examples of which can be found in Chapter 11

METABOLIC SYNDROME AND DIABETES
The link between a metabolic syndrome of obesity and insulin resistance and schizo-
phreniform illness has been appreciated for some time. In 1897 Henry Maudsley (of
the Maudsley Hospital, London) noted ‘diabetes is a disease which often shows itself
in families where insanity prevails’ (Green 2009). This basic link between schizophre-
nia and a metabolic syndrome is explored in Chapter 3 but its relevance to this
particular chapter is in the fact that antipsychotic drugs often increase weight, as
outlined above, which consequently increases not only the risk of metabolic syn-
drome and diabetes but also that of cardiovascular diseases (Allison et al. 2009).

CARDIOVASCULAR DISEASES
For individuals with mental health problems the risk of developing cardiovascular
disease is two to three times greater than that of the general population, depending
on where in the world the person lives (Hennekens et al. 2005; Filik et al. 2006).
Part of the reason for this increased risk is again the increase in weight as a result
of some of the medications, but it is also wider than this. Chapter 4 investigates
cardiovascular disease in more detail but it is worth considering here the risk of
postural hypotension, which can be a side-effect of some antidepressants and anti-
psychotics. It is related to alpha-1 blockade, which is produced by drugs like chlor-
promazine, amitriptyline, venlafaxine and others.

Postural hypotension (or orthostatic hypotension) involves a drop of 10–20 mmHg
in systolic blood pressure on changing of posture from sitting to standing, which may
lead to dizziness, fainting sensations and falls (and thus to hip fractures in the elderly).

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS146

The management of postural hypotension includes monitoring the service user’s
blood pressure on a regular basis. Being alert to complaints of dizziness is also
important, as is acting on these by checking blood pressure both while the client is
sitting and standing.

If postural hypotension is present, consider using an alternative drug – especially
in older patients who might fall. Until the old drug is replaced, give a full explana-
tion about the risks of sudden movements to both the client and their family/carers,
and advise them about standing up gradually, and avoiding triggers such as high
temperature environments, heavy meals and prolonged periods of standing still.

Also worthy of discussion is adult sudden death syndrome, which some clients may
be exposed to due to the impact of psychiatric medication on the cardiovascular system.
This is linked with drugs that can delay the repolarisation of heart muscle – measured
on ECG by a QTc prolongation beyond 420 ms. This is seen in all antipsychotics,
although Glassman and Bigger (2001) report that with first-generation antipsychot-
ics the risk of sudden death syndrome is almost three times greater, although this is
still very rare. Various risk factors are associated with sudden death syndrome and
antipsychotics, including organic psychiatric disorder, hypertension, high body mass
index, smoking and history of a myocardial infarction. Particularly risky antipsychotics
for prolonging QTc on ECG are thioridazine and haloperidol. Various medical drugs
are also associated with sudden death syndrome, including amiodarone (ironically this
is an anti-arrhythmic).

An effective means of managing the risk of adult sudden death syndrome is tack-
ling associated risks such as hypertension, weight reduction and smoking cessation
in combination with informed prescribing. As a guideline, prescribers are advised
to use low-risk drugs at the lowest effective dose. Monitoring baseline and regular
ECGs looking for QTc prolongation will also facilitate early detection and treatment.
Before moving on, take this opportunity to consider Action Learning Point 10.1.

Action Learning Point 10.1

• Discuss with your team how they routinely monitor ECG changes in clients on
antipsychotics.

CANCER
There is a small body of literature which considers the possibility of a carcinogenic
risk associated with psychiatric medication. In the USA, the Food and Drug
Administration (FDA) requires extensive animal testing to determine the carcino-
genic potential of drugs. For instance, drug information in the USA refers to the
potential of, say, a very high dose of risperidone to induce pituitary adenomas in
mice. The relevance to humans is not clearly established. Such tumours are thought
to be related to prolonged dopamine D2 antagonism and hyperprolactinaemia.

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 147

Hyperprolactinaemia occurs in about 40% of women on antipsychotics (excluding
clozapine) (Bushe et al. 2008). It is probable that this area of research will grow in
future years.

There is concern that some antipsychotic drugs can interfere with chemotherapy
regimes. For instance, chemotherapy can affect the bone marrow and so can clo-
zapine. Opinion is somewhat divided on whether clozapine therapy should be sus-
pended during chemotherapy, but the limited evidence suggests continuation is not
problematic (Goulet and Grignon 2008). Research is ongoing, however. See Chapter 6
for further information relating to the management of cancer.

SEXUAL SIDE-EFFECTS
Chapter 8 explores the sexual health of individuals with mental health problems.
Here consideration will be given specifically to the effects of medication on sexual
functioning.

Sexual side-effects (SSEs) of medication affect a person’s quality of life and lead
to poor compliance. Sexual side-effects may be experienced by about 43% of cli-
ents on antipsychotics (Wallace 2001). SSEs with antipsychotics can include loss of
libido due to hyperprolactinaemia, erectile failures (e.g. 40% of men had difficulty
in achieving and maintaining erection with chlorpromazine) and ejaculatory fail-
ures (e.g. total inhibition of ejaculation or even retrograde ejaculation) and priapism
(painful prolonged erection of the penis or clitoris).

Selective serotonin reuptake inhibitors (SSRI) antidepressants can delay ejacula-
tion in males so fluoxetine is sometimes used for treating premature ejaculation.
The side-effect of delayed ejaculation/climax in males can be unpleasant for some
couples and welcomed by others. The antidepressant clomipramine has been linked
to complete anorgasmia. Clients frequently discontinue medication as a result of
SSEs, which highlights the need for mental health practitioners to incorporate sexual
health into their assessment and care. Unfortunately the research evidence indicates
that professionals generally fail to even ask about SSEs. Most psychiatrists (77%)
surveyed in a recent study, for instance, only explored the topic of SSEs when they
were cued by clients (Singh et al. 2010). Sexual function can, of course, be compro-
mised by psychiatric illness itself and by physical illness.

BLOOD DYSCRASIA
Blood dyscrasia is an abnormality of the blood and generally implies some disorder
in the production of blood cell components, for instance insufficient erythrocytes
(anaemia) or insufficient platelets (thrombocytopenia).

Clozapine, used in treatment resistant schizophrenia, can affect bone marrow
function leading to reduced white cell production or even agranulocytosis (a more
profound reduction of white cells which can become permanent). At the start of
clozapine therapy, blood counts should therefore be monitored weekly.

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS148

Other drugs, like carbamazepine, chlorpromazine and zuclopenthixol, can also
impair white cell production and mental health practitioners should be alert for
the signs of infection in any client prescribed these drugs. They should also ensure
that a white cell blood count is carried out in the event that they do develop an
infection.

HYPERPROLACTINAEMIA
Prolactin is a hormone secreted by the pituitary gland. Various drugs, including
antipsychotics, can trigger higher blood prolactin levels. Dopamine blockade by
some antipsychotics leads to more prolactin. High levels of prolactin can cause
infertility in women, through disturbance of, or absence of, the normal menstrual
cycle. Hyperprolactinaemia can lead to lactation, amenorrhoea, gynaecomastia,
vaginal dryness and hirsutism. Hyperprolactinaemia also occurs in men taking anti-
spychotics and may lead to loss of libido or erectile dysfunction. Of all the antipsy-
chotics, quetiapine is probably least likely to cause this side-effect.

A recent study found hyperprolactinaemia in a third of patients on antipsychotics,
mainly in females (47.3% and 17.6% in males) and was associated with all antip-
sychotics except clozapine (Bushe et al. 2008). The highest prevalence rates were
found with amisulpride and risperidone. Long-term hyperprolactinaemia has been
linked to osteoporosis, bone fractures, pituitary tumours and breast cancer (Bushe
et al. 2008). An awareness of these side-effects should enable those engaged in the
care of individuals with a mental illness to seek early treatment for their clients. In
addition, consideration should be given to reducing the dose of the medication and
also to switching it to a prolactin sparing antipsychotic. Now take a look at Action
Learning Point 10.2.

Action Learning Point 10.2
• Discuss with your team what efforts they make to routinely detect hyperprolactinaemia.
• What measures do they take to tackle the long-term consequences of hyper-

prolactinaemia?

MOVEMENT DISORDERS
Among the most common side-effects of psychiatric medication is a change to the
client’s gait, posture and movement. These are frequently distressing to clients, are
stigmatising and target them for unwanted attention by others. Extrapyramidal
symptoms (EPSES) are motor side-effects usually caused by antipsychotics acting on
the dopamine system. They include drug-induced Parkinsonism, a dopamine-blockade-
related side-effect which can include limb and hand tremor, abnormal gait, ‘cog-
wheel’ or ratchet-like muscle tone, and mask-like faces – relieved by oral procyclidine

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 149

or an equivalent. In addition, an unpleasant inner restlessness called akathisa can be
observed by the client’s abnormal walking or pacing about or fidgeting when seated.
This inner agitation is so upsetting it can lead to thoughts of suicide or violence.

Dystonia can present as a sudden (acute dystonia) or late (tardive dystonia) per-
sistent muscle contraction or spasm. The dystonia is often seen with first-generation
antipsychotics like haloperidol (dystonia is also seen with the anti-emetic drug
metoclopramide – Maxolon). Such dystonias are usually seen in the neck (30%),
tongue (17%), jaw (15%), or as an oculogyric crisis (in which the eyes roll back,
and neck arches) 6%, and as opisthotonus (body arching) in 3.5% (Swett 1975).
Acute dystonia is involuntary and very frightening for the client. The management
is by administration of procyclidine, which may need to be repeated. The drug that
precipitated the dystonia should be avoided thereafter.

Finally, tardive dyskinesia occurs in 5–30% of patients treated with long-term
first-generation antipsychotics (Kane et al. 1988) and involves repetitive, involun-
tary movements without purpose. These may consist of any of the following: move-
ment of the lips and tongue, such as grimacing, lip smacking, lip pursing, sticking
out of the tongue; rapid blinking; ‘fluttering’ of the fingers; rapid movements of the
arms; truncal movements – twisting of the trunk of the body; toe tapping; and mov-
ing the leg up and down. Some historical descriptions of these kinds of movements
in clients with schizophrenia pre-date the development of antipsychotics, so there
is debate as to whether they are side-effects of medication or something to do with
the central nervous system disease that is schizophrenia. Also tardive dyskinesia has
been found in up to 14% of first-degree relatives of people with schizophrenia – that
is to say, tardive dyskinesia is found in relatives who have never had antipsychotics
(McCreadie et al. 2003).

Agencies like NICE initially recommended switching patients to new antipsychot-
ics to avoid tardive dyskinesia. However, subsequent experience with the drugs has
shown that second-generation antipsychotics are also associated with tardive dys-
kinesia. The clinical antipsychotic trials of intervention effectiveness (CATIE trial),
for instance, found that 4.5% of patients on quetiapine and 2.2% of patients on
risperidone developed tardive dyskinesia (Miller et al. 2008).

Abnormal movements can be measured and monitored using instruments like the
Abnormal Involuntary Movement Scale (AIMS) (Munetz and Benjamin 1988) and
Extrapyramidal Symptom Rating Scale (ESRS) (Simpson and Angus 1970).

Catatonia is a profound generalised condition where patients may hold rigid
poses for hours and will seemingly be oblivious to any external stimuli. It has been
described since the 1870s and although it may be classified as a reaction to medi-
cation by some, it is still of uncertain aetiology. It can be treated with hydration,
benzodiazepines and electroconvulsive therapy (ECT).

Neuroleptic malignant syndrome (NMS) is an idiosyncratic reaction to a variety
of medications, including antipsychotics, antidepressants and lithium. It occurs
in about 0.5% of those taking antipsychotics (Adnet et al. 2000). Its aetiology is
somewhat uncertain and may be a variant of a condition described many years
ago called lethal catatonia. NMS is traditionally held to be a reaction to medica-
tion. It is associated with raised temperature, increased muscle tone, delirium and

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS150

autonomic instability. It is associated with raised creatine phosphokinase blood
levels. It has a mortality of about 10–15% and is a medical emergency (Adnet
et al. 2000). In the event of NMS, medical help should be sought immediately.
Medication should be stopped and on later re-introduction the client must be
monitored very closely.

SEDATION
Psychiatric drugs which affect histaminergic neuroreceptors, like tricyclic anti-
depressants and some antipsychotics, can be sedating. This is useful in control-
ling behavioural disturbance and also in tackling insomnia. Sedation is also seen
to a lesser or greater extent with many other psychiatric drugs, including the
newer antidepressant and antipsychotics. Such sedation affects vigilance and the
ability to respond quickly and appropriately when using machinery or driving
and so clients need warning about this problem. Reassurance should, however,
be given that sedation is often at its worst in the first couple of weeks and that
after this point many people will develop a tolerance and the sedative effects will
become less. Where sedation persists, the possibility of reducing the dose should
be considered along with the potential for splitting the dose between morning
and evening. Thought should also be given to the need for the sedative effect as
switching to a less sedative drug may be an option. Please refer to Action Learn-
ing Point 10.4

Action Learning Point 10.4
• Look up the side-effects of the psychiatric medication for one of your clients.

What physical health conditions are they at potential risk of and how is this being
managed?

THE ROLE OF THE MENTAL HEALTH
PRACTITIONER

MINIMISING THE COST THROUGH EFFECTIVE
MEDICATION MANAGEMENT
Despite the potential controversy surrounding psychiatric medication, it is still
widely regarded as one of the major therapeutic tools available to mental health
professionals. Unfortunately, the lack of service users’ adherence to medication is a
long-standing and global concern (World Health Organization 2003), and how best
to encourage engagement in such an approach has therefore drawn wide interest.
Two of the main influences on non-adherence are proposed to be adverse side-effects

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 151

and a lack of collaborative care, which has led to the suggestion that any attempts
to enhance adherence should include strategies aimed at minimising adverse effects
and maximising service user involvement (World Health Organization 2003).

Concordance is the term used to describe these combined aims, and is an approach
that recognises the adverse effects of medication – regarding non-adherence as a
legitimate and understandable response from the service user. The MHP’s role in
such circumstances is to discuss the reasons for non-adherence with the service user
and in doing so take the opportunity to assess for the presence of adverse effects.

Medication assessments can be undertaken at many points throughout the care
process but it is useful at the initial assessment to take some historical information
about previous experiences of medication in order to identify any potential physical
effects. Asking directly about the physical health of the individual’s family could also
identify a predisposition to some of the physical conditions associated with psychi-
atric medication. This can then be factored into any treatment decisions made. The
use of standardised and validated assessment tools is also advocated as an additional
tool for assessment, with the intention of reducing the MHPs reliance on the service
users’ self-report and introducing a more objective measure (Jones and Jones 2005).
There are many available but a commonly adopted tool is the Liverpool University
Neuroleptic Rating Scale (LUNSERS) (Day et al. 1995) and the recommendation is
to continue to use these tools to monitor changes throughout treatment. If you are
working in a rehabilitation service or depot service, then you can use one of these
with service users every 3–6 months to monitor for the presence of the adverse
effects outlined. This would be a prompt to monitor ECG changes, the development
of abnormal involuntary movements (AIMs), and so on. For suggestions on what to
include if devising a tool for your own service, see Box 10.1.

Box 10.1 Suggestions for Devising an Assessment Tool
Suggested headings would be:

Weight, BMI, waist circumference, blood pressure, heart rate and rhythm, temperature,
anticholinergic side-effects, EPSEs, AIMs, excess sedation, prolactin levels, creatine
kinase levels, sexual function, diabetes symptoms, glucose levels, HBA1 levels, liver
function tests, lipid levels, ECG, full blood count.

There are general best practice principles to follow when it comes to medication man-
agement, many of which have already been adopted in the previous discussions on
minimising adverse effects. However, the following guidance focuses particularly on the
collaborative nature of the process and starts with an open, honest discussion about the
medication that has been prescribed, including both the beneficial effects and the potential
negatives associated with that particular medication. It is the latter that MHPs tend to shy
away from, which is understandable given that this information may prevent an individual

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS152

from taking a potentially very beneficial medication. However, it is actually the lack of
preparation for these negative effects that is of most concern to service users, thus ensur-
ing that it is paramount to give sufficient information (Gray et al. 2005).

Asking service users what knowledge they already have of the medication can be a
good opening to the discussion and can also be a good way of identifying any miscon-
ceptions or lack of understanding. These can then be used as the basis for introducing
education around the signs and symptoms of the potential adverse effects, and it is worth
considering providing the information in written form so that it can be taken away and
referred back to at a later date. Both service users and their family and carers should be
involved in these discussions, and all involved in the care should be encouraged to take a
proactive approach in the monitoring and reporting of any such symptoms. Monitoring
is also a key role for the MHP, who should be aware of the medication regimes of indi-
vidual service users in order to check for any signs and symptoms of adverse effects.

Should any adverse effects become apparent, the care of the individual should be
reviewed. It is recommended that thought be given to the medication and whether
any changes to this would be beneficial and possible (as outlined under the different
adverse effects) and also that lifestyle changes are considered. The provision of health
promotion advice in relation to lifestyle choices and changes is a developing role for
MHPs and more guidance on this can be found in Chapter 11. However, it is worth
reinforcing at this point that the provision of such advice can be empowering for
service users as it allows them to collaborate fully in their care and affords them the
opportunity to take some control over their own health and wellbeing. Take a look at
the case study of Sinita below for an example of medication management in practice.

Sinita
Sinita, aged 45, has a history of recurrent depression and was admitted to hospital in
a very agitated state. While there it was decided that her antidepressant would be
changed to amitriptyline, as all previous antidepressants had failed to provide lasting
improvement. Sinita, however, was reluctant to comply and it was only when asked
about this that the MHP was able to identify that Sinita thought that the medication
would make her ‘like a zombie’. It seems that others on the ward had told her that
the heavy sedative effects would render her unable to do or feel anything and this
had understandably made her hesitant. The MHP took the opportunity to inform
Sinita about the potential side-effects of the medication, honestly acknowledging the
sedative effect but pointing out that this would assist with her feelings of agitation.
The other potential side-effects were then discussed (principally weight gain and
metabolic syndrome) and Sinita was informed that there were ways in which these
could be managed. The benefits of the medication were finally reinforced before a
summary of the information was written down and given to Sinita.

The following day the MHP met with Sinita and her family to further discuss the
medication and an agreement was made that she would take this if she and her family
could be involved in the monitoring and management of the adverse effects. Further
meetings were therefore arranged to facilitate more education around the signs and
symptoms of potential effects and to discuss potential lifestyle changes.

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 153

AWARENESS OF INTERACTIONS WITH
OTHER DRUGS
The greater the number of medications a client is taking the higher is the risk of
a serious drug interaction and MHPs are advised to have an awareness of the
potential for this. Many individuals with mental health problems will be pre-
scribed psychiatric medication which may increase their risk of physical health
problems, leading to further prescribed medications. Should these medications
cause side-effects, yet more medication may be used in an attempt to address
them and the outcome may well be polypharmacy and a significantly increased
risk of drug interactions.

Interactions can arise where there is competition for the bodily systems that elimi-
nate drugs from the body. For instance, most drugs are metabolised by the liver.
Therefore clients taking multiple medications may be putting their liver under con-
siderable strain. Furthermore, some drugs, such as carbamazepine, may increase the
rate at which the liver metabolises other medications. This has the potential to lower
the serum levels of these other drugs and lead to breakthrough symptoms such as
psychosis or depression. Service users prescribed medicines that can affect liver func-
tion should be monitored for changes in their Liver Function Tests (LFTs).

A section at the back of the British National Formulary (BNF) (2010: Appendix 1)
details the most important known interactions between various drugs. The section in
the September 2010 BNF is closely printed and nearly 90 pages long, indicating the
complexity and number of potential interactions. It is therefore impossible to summa-
rise them all and each service user has to be thought about individually in terms of their
age, sex, weight, physical state of health and other medications. Table 10.1 lists some
examples of interactions. Before moving on, think about Action Learning Point 10.5.

Action Learning Point 10.5

• Audit the number of prescribed drugs that each of the clients in your care is on. What
is the mean number of medications? Could this be safely reduced? If so how?

• What would be the potential risks and benefits of reducing the number of medica-
tions for each client?

Physical health medication Mental health medication Effects of interaction

Ibuprofen, aspirin and other
non-steroidal anti-inflammatory
drugs

Lithium

SSRI antidepressants and
venlafaxine

Lithium toxicity

Increased risk of bleeding

Table 10.1 Common drug–drug interactions

(Continued)

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS154

AWARENESS OF THE PSYCHOLOGICAL EFFECTS
OF PHYSICAL HEALTH MEDICATION
Given the propensity for physical illness in individuals with mental health prob-
lems, a further area of consideration for MHPs is the psychological effects of
physical health medication. Several of these medications can cause symptoms of
depression, anxiety and even psychosis and in such instances it is not uncommon
for individuals to acquire new diagnoses or extra treatments they do not need. It is
therefore important that MHPs are alert to the possibility that new psychological

Physical health medication Mental health medication Effects of interaction

ACE inhibitors (used in
hypertension)

Antipsychotics, beta-
blockers and MAOIs

Hypotension

Amiodarone (anti-arrhythmic) Lithium, amisulpride and
other antipsychotics

Arrhythmias

Anticonvulsants SSRIs, tricyclics,
carbamazepine, haloperidol,
olanzapine, quetiapine,
risperidone, Fluoxetine,
mirtazapine, paroxetine

Lower fit threshold
Impact on the concentration
of psychiatric and/or
anticonvulsant medication

Anaesthetics Tricyclic antidepressants Arrythmia and hypotension

Diuretics (used to treat heart
failure, liver cirrhosis,
hypertension and certain
kidney diseases)

Tricyclics Hypotension

Lithium Increased risk of lithium
toxicity

Oestrogens (in oral
contraceptives and HRT)

Tricyclics Impair antidepressant effect

Lamotrigine Reduce serum levels of
lamotrigine

Thyroid hormones Antidepressants Enhanced effect

Antifungals Aripiprazole, quetiapine
alprazolam and midazolam

Increases concentration of
psychiatric medication

Pimozide Arrthymias

Histamine antagonists (used
for oesophageal reflux)

Citalopram, mirtazapine,
imipramine, chlorpromazine
and benzodiazepines

Increases concentration of
psychiatric medication

Methyldopa (antihypertensive) MAOIs, anxiolytics and
hypnotics.

Hypotension

Metoclopramide (anti-emetic) Antipsychotics Increased risk of
Extrapyramidal Side Effects

Table 10.1 (Continued)

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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 155

symptoms, or a worsening of existing symptoms, may be a result of medication
that has been prescribed for the service user’s physical health and that they liaise
with the care team if they suspect that medical prescribing is having a psychological
effect. Table 10.2 identifies a range of physical health medication and the potential
psychological side-effects and Harry’s case illustrates how such effects may present
in practice.

Harry

Harry, a 72 year-old man, was under the care of the mental health team for long-
standing moderate anxiety. Over the past two months it had been noted that his
anxiety had become significantly worse and that he had also been demonstrating
signs of profound low mood and agitation. After discussion at a case review, the
suggestion was made that Harry start cognitive behavioral therapy (CBT) and
perhaps a course of antidepressants, but after discussion with Harry about his
current medication it was revealed that he had been started on amiodarone, for
an irregular heartbeat, 10 weeks before. Knowing that amiodarone is associated
with depression, agitation and anxiety, the MHP referred Harry to the psychiatrist
for a medication review and, rather than embark upon CBT or an antidepressant,
the amiodarone was stopped and an alternative substituted. The depression and
agitation resolved within a week or so and his anxiety returned to a moderate level
without any further treatment being required.

Medication Prescribed for Psychological effects

Propranolol Hypertension Depression, bad dreams

Simvastatin Hypercholesterolaemia Depression, tiredness

Amiodarone Rhythm disturbances Depression, psychosis

Aminophyline Chronic Obstructive Pulmonary
Disease

Anxiety, panic

Salbutamol Asthma Anxiety, panic

Corticosteroids Asthma, rheumatoid arthritis Depression, psychosis, delirium,
mania

Methotrexate Chemotherapy, psoriasis,
rheumatoid arthritis

Depression

Omeprazole Acid reflux Depression

Isotretinoin Acne Depression, suicidal ideation

Penicillins Antibiotics Depression, agitation

Oral contraceptives Contraception Depression

Table 10.2 Psychological effects of some medicines prescribed for physical health

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THE PHYSICAL CARE OF PEOPLE WITH MENTAL HEALTH PROBLEMS156

SAFETY IN PREGNANCY
A final consideration is the potential adverse effects of prescribed medication on an
unborn child, which is an area that tends to cause some anxiety for all involved in
the care team. As with the sections above, the intention here is to assist in increasing
the MHP’s knowledge and awareness.

Seven per cent of mothers in their childbearing years suffer mental illness (NICE
2007). This, combined with the fact that 50–60% of pregnancies are generally
‘unplanned’ (NICE 2007), means that for many weeks the expectant mother may be
potentially unaware of her pregnancy and consequently be unwittingly exposing her
unborn child to psychotropic drugs.

The first step in facing this problem is an awareness of the risk. First trimester
exposure is associated with abnormal organ formation and third trimester expo-
sure is linked to withdrawal effects in the neonate – for example, the withdrawal
seen with some antidepressants and antipsychotics. It should also be borne in
mind that following birth babies may encounter any drugs that are secreted in
breast milk.

Unfortunately, no drug can be deemed wholly safe. This means that a policy
of avoiding drugs during pregnancy (especially in the first trimester) is the wisest
course unless the risks posed to the mother by any relapse are severe and probable.

The following points are worth considering in planning an approach for
women with mental health problems in their childbearing years. No guarantees
about safety are available and there is a relative lack of research and certainty
in this area.

When considering antidepressants, tricyclics are relatively safe in terms of any risk
of malformations, but if used in the third trimester can lead to withdrawal symptoms
in the neonate. There is less certainty about SSRIs and malformations. In relation
to antipsychotics, phenothiazines are associated with a small risk of malformations,
while haloperidol and olanzapine are considered safer. The mood stabiliser lithium
is definitely associated with foetal cardiac abnormalities such as Fallot’s Tetralogy,
while valproate and carbamazepine are associated with neural tube defects. Finally,
phenytoin is associated with facial cleft defects. To avoid problems with psychiatric
drugs in pregnancy the following suggestions are made:

• In women of childbearing years prescribe drugs which are safer – just in case these
patients become pregnant.

• Advise potentially fertile women with long-term mental health problems of the risks of
medication and pregnancy and encourage planned pregnancies following discussion
with the care team.

• Weigh up risks of using no medication during pregnancy or switching drugs to ones less
associated with risk.

• Use scanning or other imaging for embryos exposed to potentially damaging drugs – this
might lead to consideration of prenatal surgery for vascular abnormalities, neural tube
defects or, sadly, termination in some cases.

• Folic acid supplements (used for neural tube defect prophylaxis).

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Collins, E., Drake, M., & Deacon, M. (Eds.). (2013). The physical care of people with mental health problems : A guide for best practice. SAGE Publications.
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PRESCRIBING IN MENTAL HEALTH PRACTICE – THE BALANCING ACT 157

CONCLUSION

After the daunting array of adverse effects and problems associated with the medica-
tion listed above the reader would be forgiven for wondering about the wisdom of
prescribing any medication for mental health problems. There is without doubt a
cost to the physical health of individuals who are prescribed these medications, but
there is also a clear advantage – improved mental health. Despite the recent growth
of psychotherapies, medication remains a major therapeutic tool, so it seems that
MHPs are faced with a dilemma: whether to prioritise mental over physical health.

Perhaps the answer is to balance both, treating the psychological aspects while
managing the physical. There are many ways that MHPs can minimise the adverse
physical effects of psychotropic medication, but one of particular relevance to this
topic is medication concordance. By taking a collaborative approach to minimis-
ing the potentially harmful effects of mental health prescribing, the service user is
afforded the opportunity to take some control over their own health and wellbeing,
which will not only enhance the chances of adherence for mental health treatment,
but also that which is physical.

USEFUL RESOURCES

At the time of writing in the UK we recommend the following resources:

National Prescription Centre – www.npc.co.uk
British National Formulary – http://bnf.org/bnf/index.htm
Royal Pharmaceutical Society for Great Britain – www.rpharms.com/home/home.asp
Association of British Pharmaceutical Industries – www.abpi.org.uk/Pages/default.aspx
Association for Nurse Prescribing – http://anp.org.uk/
Drug Tariff Online – www.drugtariff.com/
Electronic Medicines Compendium – www.medicines.org.uk/emc/
Medicines and Healthcare Products Regulatory Agency – www.mhra.gov.uk/index.htm
www.nelm.nhs.uk/en/ – National Electronic Library for Medicines

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Collins, E., Drake, M., & Deacon, M. (Eds.). (2013). The physical care of people with mental health problems : A guide for best practice. SAGE Publications.
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Assignment 2 – “Critical Reflection”

There is a clear link between mental illness and poor physical health outcomes, leading to premature death and a lower quality of life for people with a mental illness (Productivity Commission, 2020). In Australia, four out of every five persons with a mental illness will have co-morbid physical health issues. Compared to the general population, people with a mental illness encompass approximately one-third of all avoidable deaths, are two times more likely to have cardiovascular disease, respiratory disease, metabolic syndrome, and five times more likely to smoke (National Mental Health Commission, 2016). Furthermore, the economic cost of physical health care for people with a mental illness is estimated to be 0.9%GDP in Australia, or $15billion per year (National Mental Health Commission, 2016). Despite being sicker than the general population, people with a severe mental illness, such as schizophrenia, access healthcare services much less, contributing to overall poor health outcomes (Royal Australian and New Zealand College of Psychiatrists, 2015).

As a means of addressing this health inequity, the National Mental Health Commission developed the “Equally Well” consensus, which aims to bridge the gaps in health disparity between mental health and physical health. It attempts to do this by the introduction of 48 actions that are aimed at developing person-centred, effective, equitable and coordinated healthcare (Productivity Commission, 2020). These actions aimed at mental health providers and GP’s, attempt to address a complex issue that is multifactorial through several suggested interventions.

Equally well works on the premise that people with a mental illness suffer the consequences of health inequity. In Australia, all residents have access to Medicare which enables equal access to healthcare regardless of any variables in their presentation or circumstance, this is defined as health equality (Botero et al., 2013). However, equity in health refers to providing tailored healthcare to individuals (Botero et al., 2013); for example, despite having Medicare provisions, people may not have transport to get to the health care that they require. This inequity in healthcare extends to many vulnerable populations across the country, including people with a severe mental illness.

The cause of inequity in mental health concerning poor physical health outcomes is complex and multifactorial and extends further than a simplistic view of lack of access to appropriate services; whilst access to services is valid, the complexities extend much further than this. Moreover, it is essential to note that not all mental illness are created equal. There is a greater health inequity for those with a serious mental illness or SMI, illnesses such as schizophrenia, major depression, and bipolar affective disorder (Young et al., 2017), compared to those with lower acuity illnesses such as mild to moderate depression and anxiety. This is due to several factors, but one worthwhile pointing out is the nature of these illnesses; all of them have aa affective or negative symptom component, which predominantly affects energy and motivation, causing people to be withdrawn and isolative (Gyllensten et al., 2020; Royal Australian and New Zealand College of Psychiatrists, 2015). This leads to poorer health outcomes because they are less likely to engage in initial treatment and ongoing follow up. Additionally, for someone with a severe mental illness, comprehending healthcare advice may be extremely difficult when experiencing auditory hallucinations, intrusive thoughts, or other cognitive deficits (De Hert et al., 2011). These diagnostic features of severe mental illnesses already set a footing for poor physical health outcomes.

Sickel et al. (2019) outline the impact of stigma, including self-stigma and other internal negative self-talk such as poor self-esteem, as a factor in help-seeking behaviours that can prevent someone with mental health issues from seeking assistance for their physical health. Moreover, when people with a severe mental illness do present for physical health issues, the focus remains on their mental health issues despite their presenting problem, or their physical health symptoms are attributed to part of their mental health presentation; this is termed “diagnostic overshadowing” (Berry et al., 2020; Royal Australian and New Zealand College of Psychiatrists, 2015) and is another barrier that contributes to the healthcare inequity for people with a severe mental illness.

There are also environmental conditions that affect the physical health of people with a serious mental illness, such as poor housing or homelessness, institutionalisation, limited income, and limited socialisation directly impact health (Collins et al., 2013). Collins et al. (2013) suggest that contributing factors to poor physical health in people with a serious mental illness are threefold: lifestyle factors, environmental factors, and illness-related factors. These factors play a role in preventing someone with a serious mental illness seek initial and ongoing treatment for physical health issues.

Additionally, people with a serious mental illness are often treated with medications with side effects that affect their physical health, people prescribed antipsychotic medications are at higher risk of developing metabolic syndrome as a result of side effects of these medications. Metabolic syndrome is a cluster of symptoms such as increases in weight, BMI, blood glucose levels, lipids and triglycerides, and hypertension (Berry et al., 2020). This risk is twofold; the medications used to treat the severe mental illness can lead to adverse physical health effects, leading to medication non-adherence, creating a two times burden on the patient and healthcare system. Additionally, fear of relapse and an increase in psychotic symptoms can lead to reluctance to change medications instead of a treatment that has fewer physical health effects (Berry et al., 2020).

Furthermore, mental health medications also have high potential to cause other side effects, known as extrapyramidal side effects that present similar to Parkinson’s symptoms and include involuntary muscle movements and spasms, muscle stiffness, tremors and restlessness, which further impairs the ability to engage effectively in physical health interventions, limits mobility, and perpetuates ongoing stigma and feelings of judgement (Firth et al., 2019). All of these medication effects can prevent someone with a serious mental illness from seeking further healthcare treatment for several reasons, such as fear of additional side effects and fear of judgement from side effects; additionally, these medication effects already lay the grounds for poorer physical health outcomes (Firth et al., 2019).

Lastly, health literacy plays a role in seeking adequate physical health. Health literacy refers to the innate ability to navigate the health care system, including locating, comprehending and conveying health information, seeking appropriate care, and making critical, up-to-date healthcare choices (Keleher & Hagger, 2007). The inequity is that health literacy is assumed for all Australians this is not considered in delivering advice and treatment options, leading to poor treatment adherence and preventing further engagement in treatment (Keleher & Hagger, 2007).

Furthermore, modifiable lifestyle factors are also a risk factor for poor physical health and precipitant for poor physical health outcomes in people with mental illness, these include sedentary lifestyle, smoking, poor diet and nutrition, alcohol and illicit substance misuse, and dysregulated sleep patterns (Berry et al., 2020; Gyllensten et al., 2020). The aetiology of these factors needs to be understood to put in place successful interventions. These causes can include intergenerational and childhood trauma, learnt behaviours, lack of education, low income and poverty, unemployment, and social exclusion (National Mental Health Commission, 2016). All of these lead to poorer physical health outcomes and increased financial strain, which reinforces the cycle of poverty and disadvantage (Productivity Commission, 2020).

Nevertheless, people with a serious mental illness still require physical health interventions, more so than the general population. So, the question remains, how do we achieve this? The “equally well” campaign attempts to address this question through suggested interventions and actions each health service can make to reduce the risk of physical health issues and promote more positive outcomes (National Mental Health Commission, 2016).

Modifiable lifestyle factors are primarily targeted in physical health interventions and considered to be first-line interventions for improving physical health issues for people with a serious mental illness (Firth et al., 2019), these lifestyle interventions include smoking cessation interventions, building physical activity by improving fitness and improving quality of diet (Firth et al., 2019). There have been several interventions in the past that have attempted to tackle this and improve the physical health of the overall population. It is widely recognised that early intervention during the first episode or prodromal stage of severe mental illness is core in developing healthy lifestyle changes (Royal Australian and New Zealand College of Psychiatrists, 2015).

The Royal Australian and New Zealand College of Psychiatrists (2015) report that referral for physical activity interventions such as diet and exercise coaching should be incorporated into routine screening and first phase interventions with regular evaluations and ongoing monitoring. Improving the physical health competency of mental health professionals is also addressed as pertinent to improve physical health outcomes for people with a severe mental illness (Young et al., 2017). Nevertheless, multidisciplinary approaches to physical activity coaching have been proven efficacious as a collaborative approach that empowers the individual and builds self-management of physical health, including mentoring, ongoing support, education, and collaborative, interactive activities (Royal Australian and New Zealand College of Psychiatrists, 2015; Watkins et al., 2020). Nutritional coaching is also an important factor; one that has been efficacious is ongoing coaching and diet support that includes shopping, budgeting, meal planning and cooking skills (Watkins et al., 2020).

There are times when additional medications are warranted to prevent further decline in physical health. The introduction of anti-hyperglycaemic agents, antihypertensive agents, and statins are often required to avoid further health deterioration and the introduction of other pharmacological interventions to assist with weight loss such as metformin (De Hert et al., 2011). Furthermore, pharmacological interventions can assist in side effect management, such as anticholinergic medications to reduce extrapyramidal side effects, or medications to assist in smoking cessation such as “Champix”, or medicine to assist with substance abstinence such as methadone, or benzodiazepines to assist with alcohol withdrawal (Firth et al., 2019). Certainly, these pharmacological interventions play a role in treating the symptoms of physical health issues for people with a mental illness, however, early intervention and treating the underlying cause through nutrition, diet and exercise interventions provide better patient outcomes (Firth et al., 2019).

Moreover, the effects of building health literacy, improving nutrition and exercise support lead to flow-on effects that link to barriers of health inequality. Participation in physical health interventions and subsequent health benefits such as weight loss is linked to improved self-esteem, improved mood, increased feelings of hope for a positive future, and improved energy and motivation (Watkins et al., 2020).

Addressing the health inequity for people with a severe mental illness is a complex issue that requires a multidisciplinary and multifaceted approach. Whilst there have been some great initiates across the country to address this health gap, the problem remains, and interventions predominantly do not occur or occur at sub-optimal levels. Indeed, building-specific program interventions into health policies and providing adequate training and resources to health care services is vital in bridging the barriers that contribute to the gap in health. The Equally Well Campaign is a great starting point for health services in raising awareness and competence in assessing, responding, and providing a holistic model of care to patients with mental health and physical health issues.

References

Berry, A., Drake, R. J., & Yung, A. R. (2020). Examining healthcare professionals’ beliefs and actions regarding the physical health of people with schizophrenia. BMC health services research, 20(1), 771-771.

https://doi.org/10.1186/s12913-020-05654-z

Botero, A. M. C., Valencia, M. M. A., & Jaime, C. F. (2013). Social and health equity and equality: The need for a scientific framework. 7, 10-17.

Collins, E., Drake, M., & Deacon, M. (2013). The Physical Care of People with Mental Health Problems : A Guide For Best Practice. SAGE Publications.

http://ebookcentral.proquest.com/lib/scu/detail.action?docID=4714347

De Hert, M., Cohen, D., Bobes, J., Cetkovich-Bakmas, M., Leucht, S., Ndetei, D. M., Newcomer, J. W., Uwakwe, R., Asai, I., Moeller, H.-J., Gautam, S., Detraux, J., & Correll, C. U. (2011). Physical illness in patients with severe mental disorders. II. Barriers to care, monitoring and treatment guidelines, plus recommendations at the system and individual level. World Psychiatry, 10(2), 138-151.

https://doi.org/10.1002/j.2051-5545.2011.tb00036.x

Firth, J., Siddiqi, N., Koyanagi, A., Siskind, D., Rosenbaum, S., Galletly, C., Allan, S., Caneo, C., Carney, R., Carvalho, A., Chatterton, M., Correll, C., Curtis, J., Gaughran, F., Heald, A., Hoare, E., Jackson, S., Kisely, S., Lovell, K., & Stubbs, B. (2019). The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness. The Lancet Psychiatry, 6, 675-712.

https://doi.org/10.1016/S2215-0366(19)30132-4

Gyllensten, A. L., Ovesson, M. N., Hedlund, L., Ambrus, L., & Tornberg, Å. (2020). To increase physical activity in sedentary patients with affective – or schizophrenia spectrum disorders – a clinical study of adjuvant physical therapy in mental health. Nordic journal of psychiatry, 74(1), 73-82.

https://doi.org/10.1080/08039488.2019.1669706

Keleher, H., & Hagger, V. (2007). Health Literacy in Primary Health Care. Australian Journal of Primary Health – AUST J PRIM HEALTH, 13.

https://doi.org/10.1071/PY07020

National Mental Health Commission. (2016). Equally Well Consensus Statement: Improving the physical health and well being of people living with mental illness in Australia. NMHC.

https://www.equallywell.org.au/wp-content/uploads/2018/12/Equally-Well-National-Consensus-Booklet-47537

Productivity Commission. (2020). Mental Health: Inquiry Report. A. Government.

https://www.pc.gov.au/inquiries/completed/mental-health/report/mental-health

Royal Australian and New Zealand College of Psychiatrists. (2015). Keeping Body and Mind Together: Improving the physical health and life expectancy of people with serious mental illness.

Sickel, A. E., Seacat, J. D., & Nabors, N. A. (2019). Mental health stigma: Impact on mental health treatment attitudes and physical health. Journal of health psychology, 24(5), 586-599.

https://doi.org/10.1177/1359105316681430

Watkins, A., Denney‐Wilson, E., Curtis, J., Teasdale, S., Rosenbaum, S., Ward, P. B., & Stein‐Parbury, J. (2020). Keeping the body in mind: A qualitative analysis of the experiences of people experiencing first‐episode psychosis participating in a lifestyle intervention programme. International journal of mental health nursing, 29(2), 278-289.

https://doi.org/10.1111/inm.12683

Young, S. J., Praskova, A., Hayward, N., & Patterson, S. (2017). Attending to physical health in mental health services in Australia: a qualitative study of service users’ experiences and expectations. Health and Social Care in the Community, 25(2), 602-611.

https://doi.org/10.1111/hsc.12349

Assessment 2 Example 2

The ‘Equally Well’ campaign – is it enough?

The Equally Well campaign aims to improve the physical health and wellbeing of Australians living with mental illness through a commitment to six key principles and numerous subsidiary actions, with a particular focus on equity of access to healthcare (National Mental Health Commission (NMHC), 20

1

6). While Equally Well is to be commended for the breadth of its ambition in tackling these challenges, an equivalent level of commitment to addressing the social determinants of health, and to shifting entrenched societal attitudes to persons living with mental illness, will be required if long term improvements are to be achieved.

Australian and international studies have repeatedly shown that people living with mental illness have poorer physical health than the general population (NMHC, 2016). Life expectancy is up to 30% less for people living with mental illness, with the majority of premature deaths relating to illnesses such as cancer, diabetes, respiratory and cardiovascular disease (NMHC, 2016). Many of these diseases are of a chronic nature and adversely impact quality of life for many years prior to death (NMHC, 2016). A higher rate of disease implicates a higher need for quality healthcare, but in practice people living with mental illness are significantly less likely than the general population to access the care they require (NHMC, 2016).

A well-educated person with strong social support, comfortable housing and no financial pressures will often postpone seeking help for health problems due to fear around diagnosis or unwillingness to prioritise their own health (Byrne, 2008). For this socially advantaged person, a “high degree of persistence, tenacity and confidence” will nonetheless be required to obtain high quality care for complex conditions (The Royal Australian and New Zealand College of Psychiatrists (RANZCP), 2015, p. 14). For a person living with mental illness, these barriers are even more challenging and are further compounded by a range of additional factors.

A person living with mental illness is less likely to have an existing relationship with a regular doctor and more likely to lack trust in the medical system, often as a result of past trauma (Corscadden et al., 2019). Their mental illness may impair their ability to recognise symptoms of disease and their motivation to seek advice (Lerbaek et al., 2021). When the person attends an appointment, aspects of their mental illness such as anxiety and agitation may heighten the challenge of dealing with long waiting periods, a stressful physical environment and disrespectful staff attitudes (Gedik et al., 2020).

Diagnostic overshadowing, whereby the clinician overlooks or dismisses physical health concerns by misattributing them to mental illness, presents a further impediment for the person with mental illness, and is considered a significant contributing factor to 35% of people living with mental illness having an undiagnosed physical health issue (Geiss et al., 2017; Lerbaek et al., 2021). Clinician bias is a significant contributor to diagnostic overshadowing, with many clinicians dismissive of the person’s insight into their own condition (Lerbaek et al., 2021).

The consequences of this attitudinal bias are apparent throughout diagnosis, treatment and ongoing support. Standard health screening is less likely to be provided to a person with mental illness, and even if a diagnosis is made, the same level of treatment, referral and ongoing support may not be offered (Roberts, 2019). This failure to listen and respond appropriately to a person living with mental illness breeds a “culture of hopelessness and low expectations” and further inhibits the willingness of those persons to report their symptoms (RANZCP, 2015, p. 5). As a result, physical health worsens, opportunities for early intervention are lost, disease becomes chronic, care needs become more complex, clinicians have their negative biases reinforced through encountering serious physical health conditions in advanced stages that have not been adequately addressed, disadvantage in access to healthcare is further entrenched, and thus the cycle continues.

Diagnostic overshadowing has also been attributed to the tendency of practitioners to focus only on their own area of specialty, itself arguably a product of the distinction between mental and physical health which permeates the healthcare system (Lerbaek et al., 2021; Roberts, 2019). At the primary care level, some general practitioners will actively avoid dealing with patients living with mental illness, or conversely will focus exclusively on addressing mental health issues (Nankivell et al., 2013). In emergency departments, the complexity of presentations attributable to multiple causes, time pressures and clinicians’ fear of dysregulated patient behaviours can further exacerbate this problem (Geiss et al., 2017). Geiss et al. (2017) illustrate this by reference to presentation of a patient with elevated temperature, high heart rate and agitation, which would generally be interpreted as delirium suggestive of an underlying infection. Notwithstanding the high mortality rate associated with this presentation, where a person has been diagnosed as having a psychiatric disorder the same symptoms are likely to be attributed to mental illness, increasing the potential for further clinical decline.

While Equally Well recognises the need to promote standardised physical assessments and monitoring for people with mental illness, this must be combined with a shift in clinician mindset in order to be effective (NHMC, 2016). Such reform will be difficult to achieve while undergraduate medical degrees continue to treat mental health as a peripheral issue, and while clinicians continue to view people living with mental illness as a separate category of person, warranting a lesser degree of care and respect (Gedik et al., 2020).

A person’s health is closely linked to the social and environmental conditions of their life, in particular their socioeconomic, housing, employment and educational status (Australian Institute of Health & Welfare (AIHW), 2020). In addition to directly impacting health, these social determinants have an indirect effect due to their influence on behavioural and biomedical risk factors (AIHW, 2020). As a result, social determinants “interact with and amplify other barriers” to accessing quality healthcare, exacerbating the burden of disease (Nankivell et al., 2013, p. 446).

Adverse life circumstances have been shown to have long term effects on behavioural and psychological pathways, and to trigger epigenetic changes, elevating the risk of mental and physical health disorders (Roberts, 2019). People with mental illness are more likely to experience poverty, unemployment, housing problems and lack of social support and, conversely, people experiencing adverse social circumstances are more likely to experience mental illness (Roberts, 2019). A person living in poverty is more likely to suffer poor nutrition due to limited access to healthy foods, low levels of education and employment, inadequate housing, violence and trauma, and in turn poor nutrition increases the likelihood of obesity, cardiovascular disease and type 2 diabetes (Roberts, 2019).

For a person living in poverty with a serious mental illness, higher healthcare needs do not equate to higher access to care (Corscadden et al., 2019). Financial pressures impact the person’s ability to pay medical fees, fund treatments and travel to appointments (Corscadden et al., 2019). The person may lack the resources to make online appointments, and for those experiencing homelessness the lack of a fixed address or Medicare card can add a further layer of complexity. People living with homelessness, long-term unemployment and poverty are less likely to have good health literacy, and less likely to enjoy social support networks which might otherwise facilitate overcoming these barriers (Corscadden et al., 2019).

Prior experience of stigma with respect to their mental health or socioeconomic status may further inhibit a person’s willingness to engage with the health system (Happell et al., 2018). Social exclusion harms self-esteem, and it is difficult for a person who is marginalised to have faith in their society (Schout et al., 2011). Yet latent distrust in the system is too often cemented by the marginalised person’s experience of diagnostic overshadowing and substandard care when they do seek to engage with healthcare providers.

While Equally Well includes acknowledgement of the relevance of social determinants of health to equity of healthcare access, without a parallel detailed commitment specific to addressing underlying social inequities and promoting healthy living environments on a societal scale, the success of the Equally Well initiatives is likely to be curtailed (NHMC, 2016). For example, there is strong evidence that prioritising housing, together with clinical and psychological support, has a lasting positive impact on a person’s health and wellbeing (AIHW, 2020). Unless Equally Well can be matched by a similar commitment to evidence-based practice in housing policy, the uphill battle to effect positive change in health outcomes will likely continue.

A shift away from a purely biomedical approach focused on pharmacological treatments, towards interventions which encompass lifestyle changes such as nutrition and exercise, is recognised by Equally Well as another critical aspect of improving the physical health of people living with mental illness (NHMC, 2016). There is a misplaced perception amongst clinicians that people living with mental illness are disinterested in lifestyle changes (Happell et al., 2012). A person is less likely to be offered the same information about lifestyle options as a person without mental illness, despite the likelihood that their need for lifestyle guidance is greater (Lerbaek et al., 2021). This unwillingness to acknowledge the capabilities of a person living with mental illness further exacerbates the tendency to view their challenges through a purely biomedical lens rather than as a product of their broader social context (Schout & de Jong, 2017). The tendency to blame an individual for their lifestyle choices overlooks that social determinants are generally not a matter of choice, and again highlights the need for significant attitudinal shift to accompany the specifics of Equally Well.

The importance of providing lifestyle prescriptions to persons living with mental illness is heightened by the iatrogenic effects of many medications for psychiatric disorders (Schout & de Jong, 2017). In particular, common antipsychotic medications are known to cause adverse metabolic effects, yet persons already at higher risk of metabolic disease as a result of the social determinants of health are still prescribed these treatments with no regard to boarder health consequences (RANZCP, 2015).

Evidence is growing that nutrition plays a key role in mental health, particularly with respect to the link with chronic inflammation and the potential of healthy diets to modify some potential side effects of psychiatric medications (Teasdale et al., 2020). While research has focused primarily on interactions with depression and anxiety, early indications are that nutritional interventions may also be beneficial in treatment of disorders involving psychosis (Teasdale et al., 2020). While the biological pathways that mediate these interactions are not fully understood, there is sufficient evidence to support guidance on dietary improvement being included as a standard aspect of psychiatric care, as recognised by Equally Well (NHMC, 2016). Of equivalent importance is prescribing physical exercise, which has been demonstrated to assist with emotional dysregulation, psychomotor agitation, anxiety and depression (NHMC, 2016; Tomasi et al., 2019).

For lifestyle guidance offered to people living with mental illness to be effective, it is essential to tailor the support to address the specific challenges (such as socioeconomic disadvantage) which are likely to make adherence to dietary and exercise interventions more difficult. Facilitating participation in mainstream physical health activities may be a means of linking people living with mental illness with the broader community and helping address social isolation. Where lifestyle interventions can be integrated with development of a sense of community and connection, there will likely be greater potential for successful long term change.

Equally Well is an ambitious and necessary step towards improving the physical health and wellbeing of people living with mental illness in Australia. However, to achieve its outcomes it must be combined with a parallel commitment to addressing the upstream systemic issues affecting entrenched social determinants of health. Moreover, this must be accompanied by a societal shift in attitudes towards persons with mental illness: a shift away from negative assumptions and disrespectful attitudes towards a greater recognition of shared commonalities, and a willingness to embrace community with no ‘us and them’.

References

Adan, R., van der Beek, E., Buitelaar, J., Cryan, J., Hebebrand, J., & Higgs, S. et al. (2019). Nutritional psychiatry: towards improving mental health by what you eat. European Neuropsychopharmacology, 29(12), 1321-1332. https://doi.org/10.1016/j.euroneuro.2019.10.011

Australian Institute of Health & Welfare. (2020). Australia’s health 2020: data insights. Canberra: AIHW.

Byrne, S. (2008). Healthcare Avoidance. Holistic Nursing Practice, 22(5), 280-292. https://doi.org/10.1097/01.hnp.0000334921.31433.c6

Corscadden, L., Callander, E., & Topp, S. (2019). Disparities in access to healthcare in Australia for people with mental health conditions. Australian Health Review, 43(6), 619. https://doi.org/10.1071/ah17259

Ewart, S., Bocking, J., Happell, B., Platania-Phung, C., & Stanton, R. (2016). Mental health consumer experiences and strategies when seeking physical healthcare. Global Qualitative Nursing Research, 3, 233339361663167. https://doi.org/10.1177/2333393616631679

Gedik, M., Partlak Günüşen, N., & Çelik Ince, S. (2020). Experiences of individuals with severe mental illnesses about physical health services: a qualitative study. Archives of Psychiatric Nursing, 34(4), 237-243. https://doi.org/10.1016/j.apnu.2020.04.004

Geiss, M., Chamberlain, J., Weaver, T., McCormick, C., Raufer, A., & Scoggins, L. et al. (2017). Diagnostic overshadowing of the psychiatric population in the emergency department: physiological factors identified for an early warning system. Journal of the American Psychiatric Nurses Association, 24(4), 327-331. https://doi.org/10.1177/1078390317728775

Happell, B., Platania-Phung, C., Bocking, J., Ewart, S., Scholz, B., & Stanton, R. (2018). Consumers at the centre: interprofessional solutions for meeting mental health consumers’ physical health needs. Journal of Interprofessional Care, 33(2), 226-234. https://doi.org/10.1080/13561820.2018.1516201

Happell, B., Scott, D., & Platania-Phung, C. (2012). Perceptions of barriers to physical healthcare for people with serious mental illness: a review of the international literature. Issues in Mental Health Nursing, 33(11), 752-761. https://doi.org/10.3109/01612840.2012.708099

Lerbaek, B., McCloughen, A., Lauritsen, M., Aagaard, J., Nordgaard, J., & Jørgensen, R. (2020). Barriers and possible solutions to providing physical healthcare in mental healthcare: a qualitative study of Danish key informants’ perspectives. Issues in Mental Health Nursing, 42(5), 463-472. https://doi.org/10.1080/01612840.2020.1823537

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Roberts, R. (2019). The physical health of people living with mental illness: a narrative literature review. Charles Sturt University. https://www.equallywell.org.au/wp-content/uploads/2019/06/Literature-review-EquallyWell

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1

IMPORTANT INFORMATION; ASSIGNMENT GUIDELINE

Please take time to read the unit assessment guide with further details surrounding the requirements.

The first assessment task had you research the available physical health programs out there, their aims, what they offer and how they go about doing it. This is a really good springboard to get you thinking about why it is that despite having these programs out there, and being one of the countries with the best life expectancies/ health outcomes, there remains such a disparity between the life expectancy of someone with a mental illness vs one without. This leads to this assessment task.

Equity vs equality

Equity vs equality mean two very different things. I would suggest that you take some time to research what these mean and how these terms influence the health of such a population as those with a mental illness.

Consider the following:

As much as Australia boasts it has services that are tailored to an individual’s needs, unfortunately, this is not the reality. The health system somewhat relies on an idealistic society where by one has adequate health literacy, adequate education, adequate income, knowledge of how to access services, knowledge of such services, adequate transport to get to services and allocated appointments etc etc. Throw a dash of chaos in there and acknowledge the disruption of one’s determinants of health that is commonly experienced by people with a mental illness and what happens then?

The breakdown:

Point 1. An outline of the evidence that people with mental illness do not currently enjoy

“equity of access” to quality health care.

This is about what we currently know about the physical health of those with mental illness. What do the stats say?

Point 2. Reference to the literature on determinants of health and wellbeing outline factors,

other than access to health care, which may contribute to poor physical health in

people

diagnosed with mental illness.

This point feeds back to point 1. Why is it that people with MI have poorer physical health? This is closely aligned with your readings……

 

Point 3. Include in your discussion a justification for why nutrition, exercise-based

interventions, and pharmacological treatments should be provided to people

diagnosed with mental illness.

As is states, why is it those interventions should be provided in relation to what you have said in part 1 and 2.

Point three asks you to include in your discussion a justification for why nutrition, exercises-based interventions and pharmacological treatments should be provided to people diagnosed with a mental illness. You need to justify why these should be provided- ie what is the benefit of one having support/ services for their nutrition? What does the evidence say in relation to this? BUT, you need to consider this in relation to the barriers they may face. 

If I give you an example: 

We know there are high rates of diabetes in those with mental illness which can be associated with many of the social determinants listed earlier and then some. If we are discussing the concept of nutrition in relation to this- healthy diet = less chance of developing diabetes but also improves the trajectory of the condition if one already has such a diagnosis. So, if we consider say, someone who is homeless who has a mental illness, chances are their diet isn’t going to be great right? because they likely don’t have an income, can’t go shopping to get supplies to cook a healthy meal, don’t have access to cook a healthy meal etc etc. So, if support or services were provided which tackled this issue, we would hopefully see either reduction in prevalence or a lessened negative impact of such a condition and better physical health. 

That example is really simplified down and perhaps optimistic in its outcomes, but hopefully gives you an idea of what is being sought. It is about justifying why these services should be provided. 

The finer details:

I suggest you stick to the 2000 word limit provided as the more words you use, chances are the task is not succinctly written as it could be which will impact your grades.

· Yes, you need a formal introduction and conclusion.

· Yes, you can use headings- it will help you structure your work.

· References are needed to support your work, keep them as recent as possible.

There are two examples uploaded in the assessment 2 folder under Assessment tasks and submissions. Please have a look at these. Again, you must not copy these as that will constitute academic misconduct. We are simply providing these to help guide you in the right direction.