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10.1192/bjp.bp.111.096370Access the most recent version at DOI:
2012, 200:364-373.BJP
Seena Fazel and Katharina Seewald
review and meta-regression analysis
Severe mental illness in 33 588 prisoners worldwide: systematic
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There are over 10 million prisoners worldwide,
1
a population that
has been growing by about 1 million per decade. In 2008, the USA
had the largest number of people imprisoned at 2.3 million and
the highest rate per head of population (at 756 per 100 000 people
compared with a median of 145 per 100 000 worldwide), and
China, Russia, Brazil and India had more than a quarter of a
million prisoners each.
1
It has been widely reported that
prisoners have elevated rates of psychiatric disorders compared
with the general population, including for psychosis, depression,
personality disorder and substance misuse, which are risk factors
for elevated suicide rates,
2,3
premature mortality on release from
prison
4
and increased reoffending rates.
5,6
It is estimated that
suicide rates within prison are increased four to five times
7
and
deaths within the first week of release 29-fold higher
8
than rates
in the general population. Further, a recent review found that
reoffending rates are increased by 40% in offenders with psychotic
disorders compared with non-mentally ill offenders.
5
A previous systematic review estimated that the prevalence of
psychosis was typically 4% in prisoners of both genders, and that
of major depression was 10% in men and 12% in women.
9
How-
ever, this review is now a decade old, and, as many psychiatric
institutions have continued to reduce their bed numbers,
10
a
number of commentators have suggested that rates of severe
mental illness have been increasing over time in prisoners,
11
although empirical evidence in support of this is inconsistent
12
and experts have suggested that measures introduced by the World
Health Organization and other international humanitarian
agencies have improved prison care.
13
In addition, there has been
no review, to our knowledge, of the mental health of prisoners in
low–middle-income countries, although the vast majority of
prisoners now live in such countries.
1
As there is a substantial
body of new evidence,
14
we have conducted a new systematic
review and meta-analysis of the prevalence of psychosis and major
depression, and used subgroup analyses and meta-regression to
explore possible sources of heterogeneity between studies. We
hypothesise that there has been an increase in the rates of
psychosis and major depression over time, and that low–middle-
income countries have higher prevalences of these conditions
due to their less resourced community and prison healthcare
services.
15
Method
We identified publications estimating the prevalence of psychotic
disorders (including psychosis, schizophrenia, schizophreniform
disorders, manic episodes) and major depression among prisoners
that were published between 1 January 1966 and 31 December
2010. For the period 1 January 1966 to 31 December 2000,
methods are described in a previous systematic review conducted
by one of the authors (S.F.).
9
For the update and expanded review,
from 1 January 2001 to 31 December 2010, we used the following
databases: PsycINFO, Global Health, MEDLINE, Web of Science,
PubMed, National Criminal Justice Reference Service, EMBASE,
OpenSIGLE, SCOPUS, Google Scholar, scanned references and
corresponded with experts in the field (Fig. 1). Key words used
for the database search were the following: mental*, psych*,
prevalence, disorder, prison*, inmate, jail, and also combinations
of those. Non-English language articles were translated. We
followed PRISMA criteria.
16
364
Severe mental illness in 33 588 prisoners
worldwide: systematic review and meta-
regression analysis
Seena Fazel and Katharina Seewald
Background
High levels of psychiatric morbidity in prisoners have been
documented in many countries, but it is not known whether
rates of mental illness have been increasing over time or
whether the prevalence differs between low–middle-income
countries compared with high-income ones.
Aims
To systematically review prevalence studies for psychotic
illness and major depression in prisoners, provide summary
estimates and investigate sources of heterogeneity between
studies using meta-regression.
Method
Studies from 1966 to 2010 were identified using ten
bibliographic indexes and reference lists. Inclusion criteria
were unselected prison samples and that clinical examination
or semi-structured instruments were used to make DSM or
ICD diagnoses of the relevant disorders.
Results
We identified 109 samples including 33 588 prisoners in
24 countries. Data were meta-analysed using random-effects
models, and we found a pooled prevalence of psychosis of
3.6% (95% CI 3.1–4.2) in male prisoners and 3.9% (95% CI
2.7–5.0) in female prisoners. There were high levels of
heterogeneity, some of which was explained by studies in
low–middle-income countries reporting higher prevalences of
psychosis (5.5%, 95% CI 4.2–6.8; P=0.035 on meta-
regression). The pooled prevalence of major depression
was 10.2% (95% CI 8.8–11.7) in male prisoners and 14.1%
(95% CI 10.2–18.1) in female prisoners. The prevalence of
these disorders did not appear to be increasing over time,
apart from depression in the USA (P=0.008).
Conclusions
High levels of psychiatric morbidity are consistently reported
in prisoners from many countries over four decades. Further
research is needed to confirm whether higher rates of
mental illness are found in low- and middle-income nations,
and examine trends over time within nations with large
prison populations.
Declaration of interest
None.
The British Journal of Psychiatry (2012)
200, 364–373. doi: 10.1192/bjp.bp.111.096370
Review article
Inclusion criteria were the: (a) study population was sampled
from a general prison population; (b) diagnoses of the relevant
disorders were made by clinical examination or by interviews
using validated diagnostic instruments; (c) diagnoses met
standardised diagnostic criteria for psychiatric disorders based
on the ICD or the DSM; (d) prevalence rates were provided for
the relevant disorders in the previous 6 months.
In order to include unselected, representative and generalisable
prison samples we only selected studies that conducted a diagnostic
interview with a general prison population. We excluded those
studies that used a screening tool before conducting the diagnostic
interview
6,17,18
(as this may lead to an underestimate if the
screening tool had poor sensitivity or overestimates if the tool
had poor specificity). We also excluded sampled selected
populations, for example by offence type
19,20
(as there is evidence
that selecting some offender groups may also lead to over-
estimates, which is particularly the case for murder and attempted
murder
21
), or age group
22
(including solely juvenile prisoners
23
or
prisoners who were in healthcare settings
24
). For example, one
study that used a screening tool to identify mentally ill prisoners
and was excluded reported a prevalence of 32% for schizophrenia.
25
Studies that did not separate sentenced from remand prisoners
in their report
26
and duplicates were excluded. In this update,
we did not include personality disorder due to the high hetero-
geneity reported in the previous work.
9
For substance misuse
and post-traumatic stress disorder, there are more recent
reviews
27,28
and a substantial body of new work has not emerged
since their publication.
29
Data extraction
We extracted information on the year of interview, geographical
location, gender, remand/detainee (including jail inmates) or
sentenced prisoner, average age, method of sampling, sample size,
participation rate, type of interviewer, diagnostic instrument,
diagnostic criteria (ICD v. DSM), numbers diagnosed with
psychotic disorders (ICD-10: F20.xx–F29.xx, F30.xx; DSM-IV:
293.xx, 295.xx), and major depression (ICD-10, F 32.xx, F33.xx;
DSM-IV: 296.2x, 296.3x). Where there was schizophrenia and
other psychotic disorders reported separately, we combined them
to produce a single prevalence. For one publication,
30
we collated
‘De
´pression endoge
`ne-Me
´lancolie’, ‘Etat de
´pressif chronique’ and
‘Sympto
ˆmes psychotiques contemporains des e
´pisodes thymiques’
as indicating major depression. The data from each of the
identified publications were subdivided into four samples (men
v. women, remand/detainee v. sentenced prisoners). In contrast
to our previous review, we included data on low–middle-income
countries
31
and whether the clinical diagnostic interview was
conducted within 2 weeks of arrival into the prison (which may
influence prevalence rates and also provides an estimate of mental
health needs on reception to prison). For the update, we examined
rates of comorbidity with substance misuse. The data extraction
was done by two researchers independently (K.S. and K.W.). For
further clarification about specific studies, we corresponded
directly with the authors of the studies.
Data analysis
We analysed sources of heterogeneity by subgroup and meta-
regression analysis using dichotomous and continuous variables.
The year that the interview was conducted and the average age
of the prisoners were analysed as continuous variables. Sample size
and response rate were analysed as both dichotomous and
continuous variables. As the median of reported response rates
was 81%, we defined ‘low’ as 480% v. ‘high’ as 480%). The
following were analysed only as dichotomous variables: gender,
prisoner type (detainees/remand v. sentenced prisoners),
reception status (interviewed in the first 2 weeks of reception v.
the rest), type of interviewer (psychiatrist v. non-psychiatrist),
diagnostic instrument (clinical examination v. semi-structured
interview using a diagnostic tool) and classification criteria
(ICD v. DSM). Geographical location was analysed as low–
middle-income v. high-income country.
31
We included the US
studies within the high-income country group. Also, we
conducted an additional separate analysis of US studies (v. rest
of world and v. rest of high-income countries) for three reasons:
first, there are over 2 million prisoners there (around a fifth of
the world prisoner population); second, they constituted 30% of
the included studies in the review; and third, mentally
disordered prisoners in the USA are less likely to be diverted
because of judicial and legal reasons, and hence this may
contribute to higher prevalence rates.
6
We used a recent method for further examination of hetero-
geneity, which involves removing up to four outliers and testing
whether this reduces I
2
values to below 50%, and then
investigating in more detail the study characteristics of these
outliers.
32
We calculated pooled prevalence estimates and their 95%
confidence intervals and transformed the zero cells to 0.5 in order
to calculate prevalences as per standard methods.
33
Meta-analyses
for prevalences were conducted by gender and prisoner status. We
measured the heterogeneity between studies with Cochran’s Q
(reported with a chi-squared value and P-value) and the I
2
statistic (with 95% confidence intervals)
34
and used random-
effects models for summary statistics as heterogeneity was high
(I
2
475%).
35,36
The I
2
is an estimate of the proportion of the total
variation across studies that is beyond chance. In situations with
high between-study heterogeneity, the use of random-effects
365
Severe mental illness in prisoners worldwide
Searching in databases
PsychINFO, Global Health, MEDLINE,
Web of Science, PubMed, National
Criminal Justice Reference Service,
EMBASE, OpenSIGLE, SCOPUS,
Google Scholar
n
46000
Records screened
n
=158
Abstracts screened
n
=82
Full-text articles
n
=60
25 publications
included in final meta-analysis
Publications before
2001 excluded
n
45800
Duplicates and reviews
excluded, title screened for
inclusion criteria
(e.g. offence type,
age group), removed:
n
=76
Removed because screening
revealed exclusion criteria
(e.g. prison setting, specific
mental disorder):
n
=22
Exclusion after full-text
screening for inclusion criteria
(e.g. priod of diagnoses,
breakdown for mood disorders)
and author correspondence:
n
=35
6
6
6
6
7
7
7
7
Fig. 1 Flow diagram showing the different steps involved
in searching for relevant publications (2001–2010).
Fazel & Seewald
models is recommended as it produces study weights that
primarily reflect the between-study variation and thus provide
close to equal weighting. Univariate and multivariate meta-
regression analyses were used to explore possible sources of
heterogeneity among studies.
37
Factors in univariate meta-
regression with P-values of 50.1 were included in the final model.
We also conducted a test of funnel plot asymmetry (Egger’s test)
for publication bias using the publication (rather than the sample)
as the unit of measurement. A funnel plot is a plot of the
estimated prevalence against the sample size of the included
studies. Egger’s test can reveal a symmetric or asymmetric funnel
plot. The latter indicates the existence of a significant publication
bias or a systematic heterogeneity between studies.
38
All analyses
were done in STATA statistical software, version 11.1 on Windows.
Results
Study characteristics
The final data-set consisted of 81 publications, 56 based on the
previous review from the period 1966–2001
39–94
and 25 new ones
(online Table DS1).
30,95–118
These publications provided data on
109 samples that included a total of 33 588 prisoners. Of these,
28 361 (84.4%) were male. The overall weighted mean age was
30.5 years. The studies were conducted in 24 different countries,
8 of which are classified as low–middle-income countries:
Brazil,
108
Dubai,
93
India,
95,109
Iran,
96
Kuwait,
92
Malaysia,
116
Mexico
97
and Nigeria.
91
There were 72 studies from high-income countries. There were
25 studies from the USA,
41,48,51,52,54–57,59,62–64,67,73,75,76,79,82,83,85–
88,104,112
3 from Canada,
42,72,80
5 from Australia,
40,50,60,61,99
and
1 from New Zealand.
44
The remaining studies were conducted
in Europe including eight in England and Wales,
45,53,69,70,78,89,
90,106
six in Ireland,
71,84,100,102,105,115
three in Scotland,
43,47,49
and a number in The Netherlands,
46,74,81,98
Finland,
58,65,66
Germany,
101,113,114
Denmark,
39,94
Italy,
107,117
Greece,
103,118
Austria,
110
France,
30
Norway,
77
Spain
111
and Sweden.
68
Nine studies reported results from interviews carried out
within 2 weeks of arrival into the prison,
98–100,102,104,106,110,112,115
two of them without giving information about the prisoner type
(remand/detainee or sentenced).
99,115
Psychotic illnesses
We identified 99 samples from 74 studies that reported
rates of psychotic illnesses and included a total of 30 635
prisoners.
30,39–51,53–57,59–63,65–87,89–92,94–96,98,100–118
Overall, we
calculated a random-effects pooled prevalence of 3.6% (95% CI
3.1–4.2) in male prisoners (1120 of 26 814 individuals), and
3.9% (95% CI 2.7–5.0) in female prisoners (182 of 3821
individuals) (Table 1). There was significant heterogeneity among
these studies in the male (w
2
= 416, P50.0001, I
2
= 83%, 95% CI
79–86) and female prisoners (w
2
= 86, P50.0001, I
2
= 68%, 95%
CI 54–79).
There was a significant difference in the prevalences in
low–middle-income countries (5.5%, 95% CI 4.2–6.8) compared
with high-income countries (3.5%, 95% CI 3.0–3.9) (Fig. 2),
confirmed by meta-regression (b= 0.0204, s.e.(b) = 0.0095,
P= 0.035) (Table 2). We did not find any difference in prevalences
between male and female prisoners, between detainees/remand
and sentenced prisoners, and no statistically significant change
in prevalence over time (b=70.0001, s.e.(b) = 0.0002, P= 0.84)
(Fig. 3). When we looked specifically at US studies (17 samples),
there also appeared to be no change over time (b=70.0006,
s.e.(b) = 0.0005, P= 0.24). There was evidence of an asymmetric
funnel plot (Egger’s test, t= 239.32, s.e.(t) = 0.0044, P50.001).
Major depression
We identified 54 publications that reported rates of major depression
in 20 049 prisoners.
30,39,42,44–46,48,50–54,58,60–62,64,71,73,75–77,79–83,87–
93,96–108,110,111,113–116,118
Overall, 10.2% (95% CI 8.8–11.7) of male
prisoners (1686 of 16 021 individuals) and 14.1% (95% CI 10.2–
18.1) of female prisoners (605 of 4028) were diagnosed with major
depression (Fig. 4). There was significant heterogeneity among
these studies in males (w
2
= 541, P50.0001, I
2
= 91%, 95% CI
89–93) and also in females (w
2
= 307, P50.0001, I
2
= 93%, 95%
CI 90–94). Even after the exclusion of four outliers in both gen-
ders, the I
2
remained above 50%.
There was no significant difference in the prevalence of
depression between men and women. However, there appeared
to be higher prevalences in those studies using DSM criteria and
in low–middle-income countries, confirmed on univariate meta-
regression (Table 2). Whereas there was no evidence for rates of
major depression changing over time in the non-US samples,
the prevalence of depression appeared to be increasing over time
in the US samples, of which there were 17 from 1970 to 2010
(b= 0.0038, s.e.(b) = 0.0013, P= 0.008) (Fig. 5).
In a multivariate meta-regression analysis combining both
income group and classification criteria, the finding of a higher
prevalence rate in low–middle-income countries remained
significant only for women prisoners and was based on a single
Mexican study.
97
In the US studies, multivariate meta-regression
was not possible as all the samples that reported information on
classification criteria used DSM criteria. However in the non-US
and high-income samples, classification criteria still remained
significant when income group was included in the model
and DSM studies reported higher prevalences of depression
(b= –0.0645, s.e.(b) = 0.0282, P= 0.026). There was evidence of
an asymmetric funnel plot (t= 27.78, s.e.(t) = 0.0452, P50.001).
Comorbidity
There were five publications since 2001 that reported rates of
comorbidity in prisoners.
96,97,99,102,107
These rates ranged from
20.4 to 43.5% in those with any mental disorder who had
comorbid substance misuse, from 13.6 to 95.0% in prisoners with
psychotic illnesses with comorbid substance misuse, and 9.2 to
82.5% in individuals with mood disorders and major depression
with concurrent substance misuse.
Discussion
Main findings
We report a systematic review of the prevalence of psychosis and
depression in prisoners based on 109 separate samples (from 81
366
Table 1 Pooled prevalances for psychosis and major
depression in prisoners
Variable
Psychosis, %
(95% CI)
Major depression, %
(95% CI)
Overall 3.7 (3.2–4.1) 11.4 (9.9–12.8)
Gender of inmates
Male 3.6 (3.1–4.2) 10.2 (8.8–11.7)
Female 3.9 (2.7–5.0) 14.1 (10.2–18.1)
Prisoner status
Sentenced prisoners 3.7 (3.0–4.2) 10.5 (8.8–12.1)
Remand prisoners (detainees) 3.5 (4.2–6.8) 12.3 (9.5–15.1)
Country
Low/middle income 5.5 (4.2–6.8) 22.5 (10.6–34.4)
High income 3.5 (3.0–3.9) 10.0 (8.7–11.2)
Severe mental illness in prisoners worldwide
publications) based on 33 588 prisoners. In addition, we have, for
the first time to our knowledge, reviewed research in low- and
middle-income countries (based on 5792 prisoners) and employed
meta-regression analyses to explore sources of heterogeneity
between studies. In particular, we have examined whether rates
of mental illness in prisoners have been increasing over time.
Our main findings were that rates of psychosis in prisoners
were significantly higher in low- and middle-income countries
than in high-income ones (5.5% in low–middle- v. 3.5% in high-
income nations). Contrary to expert opinion,
119
there were no
significant differences in rates of psychosis and depression
between male and female prisoners or between detainees (or
remand) and sentenced prisoners. In the 17 US samples included,
there appeared to be an increasing prevalence of depression over
the 31 years covered by these particular studies (1974–2005). In
addition, we found no differences in depression rates between
men and women, detainees (or remand) and sentenced prisoners,
or other study characteristics that may have explained hetero-
geneity. The overall prevalences of 3.7% of male and female
prisoners with a psychotic illness, and 11.4% with major
depression have not materially changed since a 2002 review based
on 56 publications of mental illness.
9
In contrast to one of our initial hypotheses, we did not find an
increase in rates of psychosis and depression over time. The
reasons for this are unclear but improvements in psychiatric care
in prison, increased diversion of mentally disordered offenders
from prison to hospital, and better living conditions may have
contributed.
120
The role of international organisations, over the
past two decades, in improving prison health has also been
suggested to have a played a part.
121
367
Low/middle income
Fido & al-Jabally (1993)
92
Agbahowe et al (1998)
91
Arnab et al (2009)
95
Assadi et al (2006)
96
Ponde et al (2011)
108
Zahari et al (2010)
116
Sharma et al (2010)
109
Subtotal: I
2=
52.3%, P= 0.050
High income
Hurwitz & Christiansen (1983)
94
Bluglass (1966)
43
Joukamaa (1995)
65
Robins & Reiger (1991)
79
Neighbors et al (1987)
73
Hyde & Seiter (1987)
62
Gunn et al (1991)
55
Motiuk & Porporino (1992)
72
Roesch (1995)
80
Teplin (1994)
86
Teplin et al (1996)
87
Joukamaa (1993)
66
Davidson et al (1995)
49
DiCataldo et al (1995)
51
Maden et al (1994)
70
Birmingham et al (1996)
41
Brooke et al (1996)
45
Powell et al (1997)
75
(male, sentenced)
Powell et al (1997)
75
(male, remand/detainee)
Parsons et al (2001)
106
Simpson et al (1999)
83
(male, sentenced)
Simpson et al (1999)
83
(male, remand/detainee)
Watzke et al (2006)
114
Duffy et al (2006)
102
Falissard et al (2006)
30
Curtin et al (2009)
100
(male, sentenced)
Curtin et al (2009)
100
(male, remand/detainee)
Trestman et al (2007)
112
Gunter et al (2008)
104
Piselli et al (2009)
107
Vicens et al (2011)
111
Alevizopoulus & Igoumenou (in press)
118
19 smaller studies (male, sentenced)
16 smaller studies (male, remand/detainee)
10 smaller studies (female, sentenced)
15 smaller studies (female, remand/detainee)
Subtotal: I
2=
87.5%, P= 0.000
Overall: I
2=
88.2%, P= 0.000
ES (95% CI) % WeightStudy ID
0.05 (0.00–0.09) 1.09
0.04 (0.00–0.08) 1.33
0.06 (0.05–0.06) 2.77
0.03 (0.01–0.05) 2.29
0.06 (0.04–0.08) 2.14
0.09 (0.06–0.11) 1.81
0.07 (0.02–0.11) 1.19
0.05 (0.04–0.07) 12.63
0.03 (0.01–0.05) 2.29
0.02 (0.00–0.04) 2.41
0.03 (0.02–0.04) 2.64
0.05 (0.03–0.07) 2.35
0.04 (0.02–0.07) 2.15
0.03 (0.02–0.05) 2.40
0.02 (0.01–0.03) 2.80
0.04 (0.03–0.04) 2.74
0.05 (0.03–0.06) 2.45
0.04 (0.03–0.06) 2.48
0.04 (0.03–0.05) 2.64
0.02 (0.00–0.03) 2.44
0.01 (0.00–0.03) 2.60
0.06 (0.04–0.09) 2.13
0.02 (0.00–0.03) 2.45
0.04 (0.03–0.06) 2.37
0.05 (0.03–0.06) 2.45
0.03 (0.02–0.05) 2.54
0.02 (0.01–0.03) 2.58
0.11 (0.08–0.14) 1.62
0.03 (0.02–0.04) 2.54
0.04 (0.02–0.05) 2.33
0.00 (70.00–0.01) 2.82
0.03 (0.02–0.05) 2.35
0.09 (0.06–0.11) 2.00
0.03 (0.01–0.04) 2.29
0.05 (0.03–0.08) 1.96
0.01 (0.00–0.03) 2.56
0.03 (0.01–0.05) 2.16
0.02 (0.00–0.03) 2.48
0.04 (0.03–0.06) 2.46
0.03 (0.01–0.04) 2.50
0.04 (0.03–0.05) 2.75
0.06 (0.05–0.07) 2.66
0.06 (0.04–0.08) 2.34
0.04 (0.02–0.05) 2.65
0.04 (0.03–0.04) 87.37
0.04 (0.03–0.04) 100.00
7
77
777
7
7
777
7
7
777
7
7
7
77
77
7
7
77
77
777
77
77
77
777
7
7
0 0.02 0.04 0.06 0.08 0.1 0.12
Fig. 2 Meta-analysis of the prevalence of psychotic illnesses in prisoners by country group (low–middle income
v.
high income).
Weights are from random-effects analysis. Smaller studies: n5250. ES, prevalence.
Fazel & Seewald
Implications
Three main implications arise from these findings. First, the
substantial burden of treatable psychiatric morbidity is confirmed
by these findings. One in seven prisoners has depression or
psychosis, and treatment may confer additional benefits such as
reducing the risks of suicide
3
and self-harm
122
within custody,
and suicide
123,124
and drug-related deaths on release
4
as well as
reoffending.
5,6
As reoffending rates are high (at 50% in the USA
and UK within 2 years of release),
125,126
treatment of prisoners
may have a potentially large impact on public safety. In this
context, the lack of good-quality treatment evidence remains
concerning.
127
The role of diversion away from prison at early
stages of the criminal process and other collaborations between
mental health and the justice system is underscored by our
findings,
18,128,129
particularly as repeat incarcerations are associated
with mental illness.
6
Second, the higher prevalence of psychosis in prisoners in low-
and middle-income countries is notable as rates of imprisonment
are increasing in more of these countries than in high-income
ones,
1
and possibly faster; also service provision is likely to be
worse. Health services in such countries can potentially use the
estimates reported in this review in developing prison medical
services, particularly in countries where resources are unlikely to
allow for local prevalence studies to be conducted. In poorer
countries, the role of explicit mental health budgets in ongoing
health programmes could be considered, particularly for
marginalised populations such as prisoners.
130
Our report does
not provide information on the causes of higher prisoner rates
of psychosis in low- and middle-income nations but possibilities
include fewer opportunities and services for diverting offenders
to health services, a stronger relationship between mental illness
and criminality, and different sociocultural factors that mean
more mentally ill people end up in prison. Poorer legal represen-
tation for the mentally ill may be one such factor. The increased
comorbidity with opioid use in prisoners found in some countries
and that form part of the illegal drug trade may be another.
96
A final implication from this review is that, although inter-
nationally the prevalence of depression does not appear to be
increasing in prisoners, in the USA, which has the largest prison
368
Table 2 Meta-regression analyses of sources of heterogeneity in the prevalence of psychosis and major depression in prisoners
Psychosis Major depression
Variable and study characteristic
a
bs.e.(b)Pbs.e.(b)P
Gender of inmates: male v. female 0.0016 0.063 0.800 0.0323 0.0222 0.151
Mean age of inmates (continuous) 70.0009 0.0009 0.334 0.0011 0.0033 0.735
Year of study (continuous) 50.0001 0.0003 0.889 0.0015 0.0013 0.340
Country
Low/middle v. high income 0.0204 0.0095 0.035 0.1157 0.0318 0.001
USA v. rest of the world 0.0007 0.0060 0.902 70.0043 0.0241 0.859
Within the USA, over time 70.0006 0.0005 0.241 0.0038 0.0013 0.008
Prisoner status: sentenced prisoners v. detainees 0.0025 0.0038 0.504 0.0136 0.0159 0.396
On reception: first 2 weeks of reception v. rest 70.0016 0.0058 0.778 70.0131 0.0241 0.588
Participation rate
Continuous 70.0184 0.0333 0.585 70.0778 0.0998 0.441
Low (480%) v. high (480%) 72.637 3.0964 0.400 70.2786 1.1458 0.809
Sample size
Continuous 50.0001 0.0000 0.337 50.0001 0.0000 0.577
4500 v. 4500 0.0088 0.0062 0.156 70.0147 0.0275 0.594
Interviewer: psychiatrist v. other 70.0015 0.0053 0.784 0.0199 0.0231 0.391
Diagnostic criteria: ICD v. DSM 70.0021 0.0055 0.706 70.0590 0.025 0.021
Significant associations (P50.05) are in bold.
a. For comparisons the reference category is given first.
0.15 –
0.1 –
0.05 –
0–
0.15 –
0.1 –
0.05 –
0–
1960 1970 1980 1990 2000 2010
Year of interview
1970 1980 1990 2000 2010
Year of interview
Prevalence of psychotic illnessPrevalence of psychotic illness
(a)
(b)
Fig. 3 Prevalence of psychotic illness in prisoners over time in
(a) individual studies from all countries (including the USA) and
(b) studies conducted in the USA only.
The size of the circles is proportional to the sample size of each study.
Severe mental illness in prisoners worldwide
population worldwide, the rate of depression appears to have been
increasing over time. This was not found for psychosis in
prisoners internationally or in the USA, which may be partly
because the incidence of psychotic disorders has not increased
in the general population either.
131
In relation to increased
depression in US prisoners, further work could investigate the
possible contributions of the closure of large psychiatric hospitals,
the provision of community care, the funding of mental
health and the reported increase in major depression rates in
the general population.
132
Whatever the causes, the US houses
more than three times more mentally ill people in prison than
in all psychiatric hospitals,
133
and undertreatment for mental
illness in US prisons exacerbates these problems.
134
Simple
measures, including having policies and guidelines for the
transfer of severely mentally ill people to psychiatric hospitals,
training of prison staff and discharge planning, may improve these
rates.
133
Strengths and limitations
The high levels of heterogeneity between the studies are to be
expected as the studies were conducted by different groups in a
large variety of prisons using differing methods,
135
and this may
simply reflect real differences in prevalences over time and by
region. This may also be an explanation for the asymmetric funnel
plots we reported in addition to possible publication bias.
38
Also,
publication bias may explain the small number of studies in low-
and middle-income countries, and such bias is thought to
contribute in all mental health research from these countries.
136
Our approach to this was to identify causes of heterogeneity,
and two possible explanations were found. In depression, we
found that studies using DSM criteria had higher rates than those
using ICD criteria. Although such differences have occasionally
been found in community studies, and a lower congruence
between the two diagnostic systems for depression diagnoses
compared with some other psychiatric disorders has also been
369
Low/middle income
Fido & al-Jabally (1993)
92
Ghubash & El-Rufaie (1997)
93
Agbahowe et al (1998)
91
Bermu
´dez et al (2007)
97
Assadi et al (2006)
96
Zahari et al (2010)
116
Ponde et al (2011)
108
Subtotal: I
2=
98.0%, P= 0.000
High income
Neighbors et al (1987)
73
Hyde & Seiter (1987)
62
Roesch (1995)
80
Jordan et al (1996)
64
Teplin et al (1996)
87
DiCataldo et al (1995)
51
Brinded et al (1999)
44
Brooke et al (1996)
45
Powell et al (1997)
75
(male, remand/detainee)
Powell et al (1997)
75
(male, sentenced)
Parsons et al (2001)
106
Simpson et al (1999)
83
(male, sentenced)
Simpson et al (1999)
83
(male, remand/detainee)
Watzke et al (2006)
114
Duffy et al (2006)
102
Butler & Allnutt (2003)
99
(male, sentenced)
Butler & Allnutt (2003)
99
(male, sentenced)
a
Falissard et al (2006)
30
Curtin et al (2009)
100
(male, sentenced)
Curtin et al (2009)
100
(male, remand/detainee)
Gunter et al (2008)
104
Piselli et al (2009)
107
Vicens et al (2011)
111
Alevizopoulus & Igoumenou (in press)
118
13 smaller studies (male, sentenced)
10 smaller studies (male, remand/detainee)
8 smaller studies (female, sentenced)
12 smaller studies (female, remand/detainee)
Subtotal: I
2=
91.0%, P= 0.000
Overall: I
2=
94.7%, P= 0.000
Study ID ES (95% CI) % Weight
0.14 (0.07–0.22) 2.02
0.13 (0.08–0.19 2.40
0.21 (0.13–0.29) 1.93
0.62 (0.55–0.68) 2.21
0.29 (0.24–0.34) 2.57
0.13 (0.09–0.16) 2.84
0.86 (0.04–0.08) 3.01
0.23 (0.11–0.34) 16.97
0.13 (0.10–0.16) 2.82
0.07 (0.04–0.09) 2.99
0.10 (0.08–0.12) 3.01
0.11 (0.09–0.13) 3.00
0.14 (0.12–0.16) 3.03
0.09 (0.06–0.11) 2.96
0.14 (0.13–0.16) 3.04
0.10 (0.08–0.12) 3.01
0.08 (0.06–0.11) 2.97
0.12 (0.10–0.14) 2.98
0.14 (0.10–0.17) 2.81
0.06 (0.04–0.08) 3.04
0.10 (0.07–0.13) 2.91
0.03 (0.01–0.05) 3.04
0.05 (0.03–0.07) 3.02
0.05 (0.03–0.07) 3.02
0.13 (0.11–0.16) 2.97
0.18 (0.15–0.21) 2.85
0.06 (0.03–0.09) 2.94
0.05 (0.02–0.07) 2.98
0.17 (0.12–0.21) 2.62
0.06 (0.03–0.09) 2.93
0.08 (0.06–0.10) 3.02
0.04 (0.03–0.06) 3.04
0.13 (0.12–0.15) 3.05
0.09 (0.08–0.11) 3.07
0.11 (0.08–0.13) 2.94
0.12 (0.10–0.15) 2.99
0.10 (0.08–0.11) 83.03
0.12 (0.10–0.14) 100.00
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
0 0.5 0.1 0.15 0.2 0.25 0.3 0.35
Fig. 4 Meta-analysis of the prevalence of major depression in prisoners by country group (low–middle income
v.
high income).
Weights are from random-effects analysis. Smaller studies: n5250. ES, prevalence. a. On early reception.
Fazel & Seewald
reported,
137
particular reasons for this difference in prisoners
are unclear. Possibilities include that in the diagnostic systems,
fatigability is included in the core criteria for depression in ICD,
but it is an associated (rather than a core) feature in DSM. In
addition, it may be that the distinction between melancholic
and non-melancholic forms of depression
138
is more important
in prisoners as the overlap between sadness and clinical depression
is more difficult to determine.
The strengths of this review include the large number of
samples and prisoners included, and therefore the ability to
examine prevalences by clinically relevant subgroups with some
degree of precision. However, we identified only eight studies in
low- and middle-income countries, and our findings should be
interpreted with caution. Furthermore, we have examined
heterogeneity using subgroup analyses and meta-regression, which
allowed us to investigate dichotomous and continuous variables
such as age, sample size and the date when the study was
conducted. One of the limitations of the review is that there
may be other explanations for the heterogeneity that we did not
test, such as comorbidity with other mental disorders, but
systematic data on this were lacking. Furthermore, the statistical
power of testing trends within nations was limited, and even
our findings on US trends were based on 17 studies.
Avenues for future research
A number of research implications arise from this review. First,
studying the epidemiology of mental illness and criminality in
low- and middle-income countries and how it compares with
high-income countries may provide some reasons for the
difference in psychosis prevalence. A recent review found no such
studies in low- and middle-income countries.
139
More research
into the treatment of mentally ill prisoners and the most effective
models of service delivery is pressing, and further comparison of
novel approaches needs closer examination.
140
Future prison
surveys should include information on comorbidity and
psychiatric history, suicide attempts within custody, treatment
received in prison and adherence to treatment, and length of
custody. In addition, the relationship between mental illness in
prisoners and recidivism rates needs further examination.
In summary, prison provides a unique public health
opportunity to treat mental illnesses that otherwise may not be
treated in the community. Almost all prisoners return to their
communities of origin, and effective treatment of mentally ill
prisoners will have potentially substantial public health benefits
and possibly reduce reoffending rates.
Seena Fazel, MD, Department of Psychiatry, University of Oxford, Warneford
Hospital, UK; Katharina Seewald, Bsc, Department of Psychiatry, University of
Oxford, Warneford Hospital, UK and Department of Psychology, University of
Konstanz, Germany
Correspondence: Seena Fazel, University Department of Psychiatry, Warneford
Hospital, Oxford OX3 7JX, UK. Email: seena.fazel@psych.ox.ac.uk
First received 10 May 2011, final revision 12 Dec 2011, accepted 17 Jan 2012
Funding
K.S. was funded by the German Friedrich-Ebert Stiftung.
Acknowledgements
We thank S. Agbahowe, H. Andersen, L. Birmingham, R. Bland, G. Cote, M. Davidson,
B. Denton, R. Ghubash, J. Haapsalo, H. Herrman, W. Hurley, K. Jordan, M. Joukamaa,
T. Maden, D. Mohan, B. Morentin, W. Narrow, K. Northrup, T. Powell, K. Rasmussen,
C. Schoemaker, N. Singleton, C. Smith and G. Walters for kindly providing additional data
from their studies for the initial review. We are grateful to T. Butler, B. Falissard,
H. Kennedy, M. Pereira Ponde
´, M. Piselli and R. Quartesan, C. E. von Schoenfeld,
R. Trestman and V. Tort for providing further information about their studies for the update.
In addition, K. Abram, D. Black, C. James, O. Nielssen, M. I. da Rosa and K. Wada helpfully
responded to queries. We are grateful to J. Baillargeon for comments on a previous draft.
Kat Witt assisted as the second data extractor.
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Table DS1 Update: Details of included Studies since 2001
Study Year of
interview
Country Income group Sampling Instrument Diagnostic criteria Psychiatric
Interviewer
Mean age
(years)
Participation Rate
(%)
Alevizopoulus, 2010 2010 Greece High Systematic ISPI DSM N26.9 Not stated
Arnab, 2009 2001 India Low-middle Not stated SCID DSM-IV Y 34.8 Not stated
Assadi, 2006 2002 Iran Low-middle Stratified random SCID DSM-IV Y32.7 88
Bermudez, 2009 2001 Mexico Low-middle Convenience MINI DSM-IV N 30.6 Not stated
Bulten,2009 2009 Netherlands High Simple random MINI DSM-III-R N30.4 81
Butler, 2005 2001 Australia High Consecutive CIDI DSM-IV N 29.6 85
Curtin, 2009 2004 Ireland High Consecutive SADS-L ICD-10 N29.8 92
Dudeck, 2009 2006 Germany High Not stated SCID DSM-IV Y 31.2 Not stated
Duffy, 2006 2001 Ireland High Systematic SADS-L ICD-10 Y37.1 64
Falissard, 2006 2003 France High Stratified random MINI DSM-IV Y 37 63
Fotiadou, 2004 2001 Greece High Systematic MINI DSM-IV N36.5 85
Gunter, 2008 2005 US High Simple random MINI DSM-IV N 31.1 Not stated
Linehan, 2009 2002 Ireland High Stratified random SADS-L ICD-10 N29.6 70
Parsons, 2001 1998 UK High Population SADS-L ICD-10 N 28.1 89
Piselli, 2009 2005 Italy High Consecutive SCID DSM-IV Y35.5 72
Ponde, 2010 2006 Brazil Low-middle Not stated MINI DSM-IV N 33 Not stated
Sharma, 2010 2010 India Low-middle Simple random Clinical interview Not stated NNot stated Not stated
Stompe, 2010 2008 Austria High Consecutive SCAN ICD-10 NNot stated Not stated
Trestman, 2007 2004 US High Systematic SCID DSM-IV N32 Not stated
Vicens, 2011 2007 Country High Simple random SCID DSM-IV NNot stated 90
von Schoenfeld, 2006 2003 Germany High Not stated SCID DSM-IV N34 82
Watzke, 2006 2000 Germany High Not stated SCAN ICD-10 Y31.6 Not stated
Wright, 2006 2002 Ireland High Population SADS-L ICD-10 Y27.4 76
Zahari, 2010 2009 Malaysia Low-middle Stratified random SCID DSM-IV Y35 Not stated
Zoccali, 2008 2003 Italy High Population SCID DSM-III-R Y35.8 Not stated
CIDI = Composite International Diagnostic Interview ; ISPI = Iowa Structured Psychiatric Interview; MINI =Mini-International Neuropsychiatric Interview ; SADS-L = Schedule for Affective Disorders and Schizophrenia; SCAN = Schedules
for Clinical Assessment in Neuropsychiatry; SCID = Structured Clinical Interview for DSM-IV
DSM-IV = Diagnostic and Statistical Manual of Mental Disorders (by the American Psychiatric Association),
ICD-10 = International Statistical Classification of Diseases and Related Health Problems (by the World Health Organization)
