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Suicide is among the leading causes of death worldwide.
1
Yet, basic
data on the prevalence and risk factors for suicide and its
immediate precursors – suicidal ideation, plans and attempts –
are unavailable in many countries around the world, particularly
those that are less developed.
2
Most studies of suicidal thoughts
and behaviours (hereafter ‘suicidal behaviours’) have been
conducted within individual Western, high-income countries
3–6
and it is not known whether prevalence estimates and risk factors
identified in such studies generalise beyond these countries.
Recent studies in several low- and middle-income countries such
as China and India suggest the occurrence of suicidal behaviours
may differ markedly from high-income countries. For instance,
this work suggests that gender and the presence of mental dis-
orders play less of a role in the occurrence of suicidal behaviours
in low- and middle-income countries.
7,8
Data on suicidal
behaviours collected cross-nationally would provide a unique
opportunity to evaluate the consistency of prevalence estimates
and risk factors for these important outcomes, and would greatly
inform research, policy, and treatment efforts more broadly aimed
at understanding and preventing suicide around the world.
1,9
The purpose of the current study was to estimate the cross-
national prevalence of suicidal behaviours and to examine risk
factors for these outcomes using data from the World Health
Organization (WHO) World Mental Health (WMH) Survey
Initiative.
10
Several studies have provided valuable information
about suicidal behaviours across several countries.
5,11,12
The
current study extends prior work by conducting a more
thorough examination of suicidal behaviours, using more
consistent assessment methods across sites, and represents the
largest, most representative examination of suicidal behaviours
ever conducted.
Method
Respondent samples
The WMH surveys were carried out in 17 countries: Africa
(Nigeria, South Africa); the Americas (Colombia, Mexico, USA);
Asia and the Pacific (Japan, New Zealand, Beijing and Shanghai
in the People’s Republic of China); Europe (Belgium, France,
Germany, Italy, The Netherlands, Spain, Ukraine);
13
and the
Middle East (Israel, Lebanon). The World Bank
14
classifies China,
Colombia, Lebanon, Mexico, Nigeria, South Africa and Ukraine as
less developed or low- and middle-income countries, and all other
survey countries as high-income countries. All surveys were con-
ducted face-to-face by trained lay interviewers among multi-stage
household probability samples (described in the online Table
DS1). The total sample size was 84 850, w ith individual country
sample sizes ranging from 2372 in The Netherlands to 12 992 in
New Zealand. The weighted average response rate across all
countries was 71.1%.
Procedures
All respondents completed a Part I interview that contained core
diagnostic assessments, including the assessment of suicidal
behaviours. All Part I respondents who met criteria for any dis-
order and a subsample of approximately 25% of the remainder
of the respondents were administered a Part II interview that
assessed potential correlates and disorders of secondary interest
(n=48 427). Data were weighted to adjust for this differential
sampling of Part II respondents, differential probabilities of
98
Cross-national prevalence and risk factors
for suicidal ideation, plans and attempts
Matthew K. Nock, Guilherme Borges, Evelyn J. Bromet, Jordi Alonso, Matthias Angermeyer,
Annette Beautrais, Ronny Bruffaerts, Wai Tat Chiu, Giovanni de Girolamo, Semyon Gluzman,
Ron de Graaf, Oye Gureje, Josep Maria Haro, Yueqin Huang, Elie Karam, Ronald C. Kessler,
Jean Pierre Lepine, Daphna Levinson, Maria Elena Medina-Mora, Yutaka Ono, Jose
´
Posada-Villa
and David Williams
Background
Suicide is a leading cause of death worldwide; however, the
prevalence and risk factors for the immediate precursors to
suicide – suicidal ideation, plans and attempts – are not well-
known, especially in low- and middle-income countries.
Aims
To report on the prevalence and risk factors for suicidal
behaviours across 17 countries.
Method
A total of 84 850 adults were interviewed regarding suicidal
behaviours and socio-demographic and psychiatric risk
factors.
Results
The cross-national lifetime prevalence of suicidal ideation,
plans, and attempts is 9.2% (s.e.=0.1), 3.1% (s.e.=0.1), and
2.7% (s.e.=0.1). Across all countries, 60% of transitions from
ideation to plan and attempt occur within the first year after
ideation onset. Consistent cross-national risk factors included
being female, younger, less educated, unmarried and having
a mental disorder. Interestingly, the strongest diagnostic risk
factors were mood disorders in high-income countries but
impulse control disorders in low- and middle-income
countries.
Conclusion
There is cross-national variability in the prevalence of suicidal
behaviours, but strong consistency in the characteristics and
risk factors for these behaviours. These findings have
significant implications for the prediction and prevention of
suicidal behaviours.
Declaration of interests
None. Funding detailed in Acknowledgements.
The British Journal of Psychiatry (2008)
192, 98–105. doi: 10.1192/bjp.bp.107.040113
selection within households, and to match samples to population
socio-demographic distributions.
Standardised interviewer training procedures, WHO transla-
tion protocols for all study materials, and quality control pro-
cedures for interviewer and data accuracy that have been
consistently employed across all WMH countries are described
in more detail elsewhere.
10,15,16
Informed consent was obtained
before beginning interviews in all countries. Procedures for
obtaining informed consent and protecting individuals were
approved and monitored for compliance by the institutional
review boards of organisations coordinating surveys in each country.
Measures of suicidal behaviours
Suicidal ideation, plans and attempts were assessed using Version
3.0 of the WHO Composite International Diagnostic Interview
(CIDI).
16
The computer-assisted WMH–CIDI (for Windows)
was used in countries where it was financially and logistically pos-
sible to do so; elsewhere, the paper-and-pencil version was used.
Based on evidence that reports of such potentially embarrassing
behaviours are higher in self-administered than interviewer-
administered surveys,
17
these questions were printed in a self-
administered booklet and referred to by letter (e.g. ‘Did experience
C ever happen to you?’; in booklet, ‘C=You attempted suicide’). If
the respondent was unable to read, the interviewer read these
items aloud (19.5% of all instances). Interviews assessed the life-
time presence and age-of-onset of each outcome.
Risk factors for suicidal behaviours
Interviews also examined three sets of risk factors for suicidal
behaviours: socio-demographics, characteristics of suicidal behav-
iours and temporally prior DSM–IV mental disorders (i.e. those
with an onset prior to the first onset of suicidal ideation). The
socio-demographic factors included gender, age/cohort, edu-
cation, employment history, and marital history. Characteristics
of suicidal behaviours included age-of-onset of ideation, time
since onset of ideation, presence of a suicide plan and time since
onset of plan. Respondent disorders were assessed using the WHO
CIDI.
16
The assessment included DSM–IV mood, anxiety, impulse
control and substance use disorders. Prior studies using clinical
reappraisal interviews have found CIDI diagnoses to have good
concordance with blinded diagnoses based on the Structured
Clinical Interview for DSM–IV
18
in probability subsamples of
respondents from the surveys in France, Italy, Spain and the
USA.
19,20
Statistical analysis
Cross-tabulations were used to estimate lifetime prevalence of sui-
cidal ideation, plans and attempts. Discrete-time survival analysis
with person-year as the unit of analysis and including both stable
(e.g. gender) and time-varying (e.g. marital history) covariates
21
was used to study retrospectively assessed risk factors for the first
onset of each suicidal behaviour. Discrete-time survival analysis
uses each year of life of each respondent as a separate observation,
so that a sample of 100 000 respondents with an average age of 30
years would be treated as 3 million separate records. Each record is
coded for the respondent’s stable characteristics (e.g. gender), the
respondent’s age at the time of the observational record (e.g. the
20th year of a respondent’s life who was age 45 years at the time
of interview), values on the time-varying predictors as of that year
of life (e.g. whether or not the respondent was still a student, had
ever been married, and had ever been employed as of age 20), and
values on the outcomes as of that year (e.g. whether or not the
respondent had ever made a suicide attempt and, if so, whether
this was the year of the respondent’s first lifetime attempt). The
data file was analysed to compare person-years for all respondents
that had never had the outcome of interest v. the year of first onset
of the outcome using a logistic regression modelling approach and
controlling for person-year (i.e. age at the time of the observa-
tional record) as well as for the predictors. Logistic regression
coefficients were converted to odds ratios (ORs) for ease of
interpretation and 95% confidence intervals (CIs) are also
reported and have been adjusted for design effects. Continuous
variables were divided into categories to minimise effects of
extreme values. Standard errors (s.e.) and significance tests were
estimated using the Taylor series method
22
using SUDAAN
software
23
(for UNIX) to adjust for the effects of weighting and
clustering. Multivariate significance was evaluated using Wald
w
2
-tests based on design-corrected coefficient variance–covariance
matrices. Statistical significance was evaluated using two-tailed
0.05-level tests.
Results
Prevalence
The estimated lifetime prevalence of suicidal ideation, plan and
attempt in the overall cross-national sample is 9.2% (s.e.=0.1),
3.1% (s.e.=0.1) and 2.7% (s.e.=0.1), respectively (online Table
DS2). Among suicide ideators, the conditional probability of ever
making a suicide plan is 33.6% (s.e.=0.7) and of ever making a
suicide attempt is 29.0% (s.e.=0.6). The probability of attempt
among ideators with a plan is 56.0% (s.e.=1.2) but only 15.4%
(s.e.=0.6) among those without a plan (online Table DS3).
Within-country prevalence estimates show substantial varia-
bility, with the cross-national estimate outside the 95% CI in 13
of the 17 countries for suicidal ideation, and 12 of the 17 for
suicide plans and attempts. Prevalence estimates in low- and
middle-income countries are similar to those in high-income
countries for: suicidal ideation (3.1–12.4% v. 3.0–15.9% respec-
tively), suicide plan (0.9–4.1% v. 0.7–5.6% respectively) and
suicide attempt (0.7–4.7% v. 0.5–5.0% respectively). Although
prevalence estimates varied cross-nationally, the conditional
probability of suicide plan and attempt among ideators is more
consistent across countries, with the cross-national estimate out-
side the 95% CI in only 5 of the 17 countries for plans, 7 of 17
countries for attempts, 9 of 17 countries for unplanned attempts,
and 4 of 17 countries for planned attempts.
Socio-demographic factors
In the cross-national sample, risk of each suicidal behaviour is
significantly related to being female, younger age, having fewer
years of formal education, and before ever being married (Table
1). The ORs of these predictors are fairly modest in magnitude
(OR=1.3–3.1) with the exception of age. Age is inversely related
to risk of each suicidal behaviour, with ORs increasing as age
decreases (50–64 years, OR=2.6–3.4; 35–49 years, OR=4.2–5.6;
18–34 years, OR=9.5–12.4). Employment history is unrelated to
suicidal behaviours. Notably, the relations between the socio-
demographic risk factors and suicidal behaviours are attenuated
when predicting suicide plans and attempts among ideators (Table
2), suggesting the relations between these socio-demographic
factors and suicide plans and attempts are due primarily to their
association with suicidal ideation.
Within-country findings are very similar to those in the
pooled sample. For example, a dominant sign pattern exists for
female gender and risk of the three main outcomes of suicidal
ideation, plan and attempt (i.e. 47 of the 51 ORs across the 17 sep-
arate countries are 1.0 or greater) and 57% of the within-country
99
Prevalence and risk factors for suicidal behaviours
Nock et al
ORs for gender are significant at the 0.05 level. Odds ratios for
female gender are always 1.0 or greater for suicidal ideation, and
are less than 1.0 in only two instances for suicide plan (Japan
0.9, Nigeria 0.9) and two instances for attempt (Colombia 0.9,
Nigeria 0.8), none being statistically significant. Similarly, the
strong relation between age and risk of suicidal behaviours is
consistent across 16 of the 17 countries (in Japan the highest risk
of each outcome is in the 35–49 years cohort), with 88% of the
within-country ORs for the youngest cohort significant at the
0.05 level. Results are similar but less consistently significant in
within-country analyses for education, employment and marital
history given the relatively small effect sizes for these relations.
Characteristics of suicidal behaviours as risk factors
Suicide ideators within each country were classified into terciles
based on age-of-onset of suicidal ideation to examine the relation
between age-of-onset and risk of transition from ideation to plans
and attempts. Analyses revealed that earlier age-of-onset is sig-
nificantly associated with greater risk of suicide plan and attempt
among those with ideation (Table 2). Importantly, the transition
from suicidal ideation to first onset of plan or attempt is extremely
elevated within the first year of onset of ideation (OR=117.4–
123.1), and decreases substantially thereafter (OR=1.5–4.4).
Among ideators, having a suicide plan is associated with a signif-
icantly higher risk of making an attempt (OR=7.5), although the
odds of making an unplanned attempt within the first year after
onset of ideation are just as high (OR=174.6) as the odds of
making an attempt within the first year after onset of a plan
(OR=168.4). Thus, whether a plan is present or not, the highest
risk of suicide attempt is in the first year after onset of ideation.
Examination of age-of-onset curves reveals that across all 17
countries the risk of first onset of suicidal ideation increases
sharply during adolescence and young adulthood (online Fig.
DS1). These curves separate in the mid-teens to early 20s, with
several countries (Japan, New Zealand, USA) showing an earlier
increase in risk of suicidal ideation, while other countries have a
sharp increase in risk later in life (Israel, Mexico, Spain, Ukraine).
Conditional age-of-onset curves show that the rapid transitions
from ideation to attempt (online Fig. DS2) occur within the first
year of onset of ideation more than 60% of the time across all 17
countries. The same pattern was observed for the transitions from
ideation to plan and plan to attempt across all countries.
Mental disorders as risk factors
In the cross-national sample, the presence of a prior mental dis-
order is associated with significantly increased risk of suicidal
behaviours, even after controlling for socio-demographic factors,
characteristics of suicidal behaviours, and countr y of residence
(Tables 3 and 4). Relations are strongest across both high-, and
low- and middle-income countries for mood disorders
(OR=3.4–5.9) and impulse-control disorders (OR=3.3–6.5),
followed by anxiety disorders (OR=2.8–4.8) and substance use
disorders (OR=2.8–4.6). Importantly, associations between
mental disorders and suicidal behaviours are attenuated when pre-
dicting plans and attempts among ideators, with ORs decreasing
to 1.0–2.1 across all categories. Among ideators, the risk of making
an attempt is highest for those with substance use and impulse-
control disorders, suggesting that these disorders are most strongly
associated with acting on suicidal thoughts when they are present.
Results also show a strong dose–response relationship between the
number of mental disorders present and the risk of suicidal
behaviours.
In within-country analyses, the presence of any mental dis-
order is associated with significantly increased risk in each of
the 17 countries. The ORs for these analyses are quite stable, with
only three countries differing significantly from the cross-national
estimate for any outcome. Specifically, Israel is above the cross-
national estimate for ideation, plan, and attempt, Italy is above the
estimate for attempt, and Germany is below the estimate for
ideation. The strong dose–response relationship between number
100
Table 1 Socio-demographic risk factors for first onset of suicide-related outcomes: pooled analysis (
n
¼48 427).
Ideation Plan Attempt
Socio-demographic factor OR 95% CI OR 95% CI OR 95% CI
Gender
Female 1.4* 1.3 to 1.4 1.4* 1.3 to 1.6 1.7* 1.5 to 1.9
w
2
1
83.0** 41.8** 75.7**
Age, years
a
18–34 9.5* 8.1 to 11.0 10.3* 8.0 to 13.3 12.4* 9.1 to 16.8
35–49 4.2* 3.7 to 4.9 4.3* 3.4 to 5.6 5.6* 4.1 to 7.5
50–64 2.6* 2.2 to 3.0 2.7* 2.1 to 3.4 3.4* 2.4 to 4.7
w
2
3
1139.6** 454.5** 417.0**
Education
b
Student 2.6* 2.2 to 3.0 2.5* 1.9 to 3.3 2.6* 2.0 to 3.4
Low 2.0* 1.8 to 2.3 2.0* 1.7 to 2.5 3.1* 2.5 to 3.9
Low/medium 1.3* 1.2 to 1.5 1.4* 1.2 to 1.7 1.8* 1.4 to 2.3
Medium 1.4* 1.2 to 1.6 1.5* 1.2 to 1.8 1.7* 1.4 to 2.1
w
2
4
233.4** 67.9** 119.1**
Ever employed
No 0.9 0.8 to 1.0 0.9 0.7 to 1.1 0.9 0.7 to 1.1
w
2
1
2.7 1.6 2.0
Ever married
No 1.3* 1.2 to 1.5 1.3* 1.1 to 1.5 1.4* 1.2 to 1.7
w
2
1
40.0** 14.2** 17.9**
Results are based on multivariate discrete-time survival models with person-year as the unit of analysis; see the text for a description. Each model controls for person-year.
a. Referent category: 65+ years.
b. Referent category: high education.
*
P
50.005; **
P
50.01, two-sided test.
Prevalence and risk factors for suicidal behaviours
of disorders and risk of suicidal behaviours is also consistent
across all 17 countries.
Within-country analyses examining the relationship between
each of the four disorder categories and the three primary suicidal
behaviours also are largely consistent with those in the pooled
cross-national sample, with only 3 of 204 ORs (1.5%) less than
1.0, and 92.5% of ORs significant at the 0.05 level. The greatest
variability among countries is in the relation between mood dis-
order and suicidal behaviours. Seven countries have ORs signifi-
cantly higher than the cross-national estimate (Belgium, China,
Germany, Israel, Italy, Japan and Nigeria), with two countries
(Colombia, France) below the cross-national estimate.
Analyses revealed an interesting pattern regarding low- and
middle-income v. high-income countries. In high-income coun-
tries the presence of a mood disorder is the strongest predictor
of suicidal ideation, plan and attempt (Table 3; 9 of 10 countries
show this pattern). However, in low- and middle-income
countries the presence of an impulse-control disorder is a stronger
predictor than mood disorder (Table 4; 5 of the 6 countries in
which impulse-control disorders were examined). Thus, although
the presence of mental disorders in general, and comorbidity in
particular, are consistently strong predictors of suicidal behaviours
cross-nationally, there are notable differences in the type of
disorder most strongly predictive of suicidal behaviours.
Discussion
The results of this study provide valuable and previously unavail-
able information about the prevalence and risk factors of suicidal
behaviours around the world. Our results show that although
there is substantial variability in the prevalence of suicidal
behaviours cross-nationally, there are important cross-national
consistencies in the prevalence and risk factors for suicidal
behaviours. Most notably, across all countries examined, 60% of
the transitions from suicidal ideation to first suicide attempt
101
Table 2 Socio-demographic risk factors for first onset of suicide-related outcomes among ideators: po oled analysis.
Plan (n=6872)
a
Attempt (n=6872)
a
Attempt without a lifetime
plan (n=4239)
a
Attempt with a lifetime plan
(n=2633)
b
Socio-demographic factor OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Gender
Female 1.1 1.0 to 1.3 1.3* 1.1 to 1.5 1.4* 1.1 to 1.7 1.3* 1.0 to 1.6
w
2
1
2.1 12.6** 8.0** 5.3*
Age, years
c
18–34 1.4* 1.0 to 1.9 1.8* 1.2 to 2.7 2.0* 1.1 to 3.6 1.6 0.9 to 2.7
35–49 1.2 0.9 to 1.7 1.8* 1.3 to 2.7 2.1* 1.2 to 3.7 1.6 0.9 to 2.7
50–64 1.2 0.9 to 1.5 1.6* 1.1 to 2.3 1.8* 1.0 to 3.2 1.5 0.9 to 2.5
w
2
3
4.5 11.3** 7.6 3.1
Education
d
Student 1.0 0.8 to 1.3 1.1 0.8 to 1.5 1.1 0.7 to 1.8 1.1 0.8 to 1.6
Low 1.0 0.8 to 1.3 1.9* 1.4 to 2.5 2.2* 1.4 to 3.5 1.6* 1.1 to 2.4
Low/medium 1.1 0.9 to 1.4 1.4* 1.1 to 1.9 1.6* 1.0 to 2.6 1.2 0.9 to 1.7
Medium 1.1 0.9 to 1.4 1.3 1.0 to 1.7 1.6 1.0 to 2.5 1.1 0.8 to 1.5
w
2
4
1.9 29.5** 24.5** 10.8*
Ever employed
No 1.0 0.8 to 1.2 0.9 0.8 to 1.1 0.9 0.6 to 1.2 1.0 0.8 to 1.4
w
2
1
0.2 0.6 1.0 0.1
Ever married
No 1.0 0.9 to 1.2 1.2 1.0 to 1.5 1.0 0.7 to 1.3 1.2 0.9 to 1.6
w
2
1
0.0 2.9 0.0 2.0
Age of onset of ideation
e
Early 1.3* 1.0 to 1.6 2.2* 1.7 to 2.9 2.9* 1.9 to 4.4 1.8* 1.2 to 2.6
Middle 1.2* 1.0 to 1.5 1.5* 1.2 to 1.9 1.6* 1.1 to 2.2 1.5* 1.1 to 2.0
w
2
2
5.0 32.2** 27.3** 10.4**
Years since onset of ideation
f
0 117.4* 87.9 to 156.8 123.1* 92.9 to 162.9 174.6* 100.9 to 302.1 – –
1–5 3.3* 2.4 to 4.5 4.4* 3.2 to 5.9 6.2* 3.4 to 11.2 – –
6–10 1.8* 1.2 to 2.6 1.5 1.0 to 2.1 1.5 0.6 to 3.4 – –
w
2
3
2207.2** 2521.0** 873.6** – –
Have a plan
Yes – – 7.5* 6.4 to 8.7 – – – –
w
2
1
– – 650.2** – – – –
Years since onset of plan
f
0 – – – – – – 168.4* 106.6 to 266.1
1–5 – – – – – – 5.0* 3.1 to 8.0
6–10 – – – – – – 1.6 0.9 to 3.0
w
2
3
– – – – – – 1126.1**
Results are based on multivariate discrete-time survival models with person-year as the unit of analysis; see the text for a description. –, indicates that the variable is not used as a
predictor in the model.
a. Model controls for years since onset of ideation.
b. Model controls for years since onset of plan.
c. Referent category: 65+ years.
d. Referent category: high education.
e. Referent category: late.
f. Referent category: 11+ years
*
P
50.05; **
P
50.01, two-sided test.
Nock et al
occurred within the first year of ideation onset. Moreover, con-
sistent cross-national risk factors included female gender, younger
age, fewer years of education, unmarried status and the presence
of a mental disorder, with psychiatric comorbidity significantly
increasing risk. Interestingly, the strongest diagnostic risk factors
were mood disorders in high-income countries, but impulse-
control disorders in low- and middle-income countries.
Limitations
Several important limitations should be borne in mind when in-
terpreting these results. First, although the overall response rate
was at an acceptable level, response rates varied across countries
and in some cases were below commonly accepted standards.
We controlled for differential response using post-stratification
adjustments, but it is possible that response rates were related to
the presence of suicidal behaviours or mental disorders, which
could have biased cross-national comparisons. Also, although
surveys in most countries included nationally representative
samples, several surveys (e.g. China, Japan) focused on specific
urban areas and so findings from those surveys may not generalise
to all regions of those countries. A related limitation is that
although we examined suicidal behaviours across 17 countries,
several countries/regions with high rates of suicide, such as India
and South East Asia, were not included.
24
The inclusion of data
from additional countries/regions in future work will significantly
enhance our understanding of the factors influencing suicidal
behaviours further.
Second, data were based on retrospective self-report of the
occurrence and timing of suicidal behaviours, and thus may be
subject to underreporting and biased recall. We also did not
collect information from third-party informants to validate re-
spondent reports. On balance, several systematic reviews have
demonstrated that adults can recall past experiences with suffi-
cient accuracy to provide valuable information,
25,26
and such data
are especially useful when prospective data are not available,
27
as
in the current case. Another limitation is that there may be cul-
tural differences in the willingness to report on suicidal behaviours
and in the interpretation of questions about DSM–IV mental
disorders. Our results must be viewed w ith these limitations in
mind.
Third, several mental disorders were not adequately assessed
in the WMH surveys for various reasons. A few DSM–IV disorders
were not assessed in some surveys because they were believed to
have low relevance or they were excluded from analyses owing
to an insufficient number of cases, such as impulse-control dis-
orders in Nigeria. In some cases, disorders were not adequately
assessed owing to skip logic errors, such as bipolar disorder and
substance use disorders in the European Study of the Epidemiol-
ogy of Mental Disorders surveys.
10
Schizophrenia and other non-
affective psychoses were not included in any WMH survey because
previous validation studies showed they are overestimated in
lay-administered interviews like the CIDI.
28
These exclusions are
unfortunate because prior research clearly indicates that bipolar
and substance use disorders are strongly associated with suicidal
behaviours,
3,6
suggesting that schizophrenia and suicidal behav-
iours share unique prevalence patterns and are strongly related
in low- and middle-income countries;
29
thus, the current study
might have provided important information in this regard. The
measurement of these disorders and the explanation of their
relationship to suicidal behaviours in both high-income and
low- and middle-income countries is one of the most important
tasks for future work on this topic.
Fourth, this initial study included only a limited range of risk
factors for suicidal behaviour. Factors such as individual Axis I
and Axis II disorders, and traumatic life events were not examined
102
Table 3 High-income countries: DSM–IV disord ers as risk factors for first onset of suicide-rela ted outcomes (pooled analysis).
Total sample (n=32 921) Among ideators
Ideation Plan Attempt
Plan
(n=5017)
Attempt
(n=5017)
Attempt without
a lifetime plan
(n=3189)
Attempt with
a lifetime plan
(n=1828)
Disorder category OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Any anxiety
disorders
{,a
3.4* 3.2 to 3.7 4.5* 3.9 to 5.1 4.8* 4.1 to 5.5 1.6* 1.3 to 1.8 1.5* 1.3 to 1.8 1.3* 1.0 to 1.7 1.6* 1.2 to 2.0
Any mood
disorders
{,a,b
4.7* 4.2 to 5.2 5.8* 4.9 to 6.9 5.9* 5.0 to 7.1 1.5* 1.3 to 1.8 1.3* 1.1 to 1.6 1.3 0.9 to 1.7 1.2 0.9 to 1.5
Any impulse-
control
disorders
§,c
3.3* 2.8 to 3.8 3.6* 2.8 to 4.6 4.2* 3.3 to 5.4 1.4* 1.0 to 1.9 1.5* 1.1 to 2.1 1.5* 1.0 to 2.3 1.5* 1.0 to 2 .2
Any substance
use disorders
#,a,b
2.8* 2.5 to 3.2 4.1* 3.4 to 4.9 4.2* 3.5 to 5.1 1.9* 1.6 to 2.4 1.6* 1.2 to 2.1 1.9* 1.3 to 2.7 1.4 1.0 to 1.9
Any disorders
a
4.1* 3.8 to 4.5 5.8* 5.0 to 6.8 6.4* 5.4 to 7.6 1.6* 1.4 to 1.9 1.6* 1.3 to 1.9 1.5* 1.1 to 1.9 1.6* 1.2 to 2 .1
Exactly one
disorder
a
1.0 0.9 to 1.1 0.9 0.7 to 1.1 0.8 0.7 to 1.1 0.8 0.6 to 1.0 0.8 0.6 to 1.1 0.7 0.4 to 1.1 0.9 0.6 to 1.3
Exactly two
disorders
a
2.1* 1.9 to 2.4 1.9* 1.5 to 2.2 1.9* 1.5 to 2.3 0.9 0.7 to 1.1 1.0 0.7 to 1.3 1.2 0.8 to 1.8 0.8 0.6 to 1.2
Three or more
disorders
a
6.1* 5.6 to 6.6 8.6* 7.4 to 10.0 8.9* 7.7 to 10.3 2.0* 1.7 to 2.4 1.8* 1.5 to 2.1 1.7* 1.3 to 2.1 1.8* 1.4 to 2.3
High-income countries include USA, Belgium, France, Germany, Italy, The Netherlands, Spain, Israel, Japan and New Zealand. Results are based on multivariate discrete-time survival
model. Each model controls for person-year, countries and the socio-demographic variables from Table 1.
*Odds ratio (OR) significant at the 0.05 level, two-sided test.
{
Panic, agoraphobia, generalised anxiety, specific phobia, social phobia, post-traumatic stress, and adult separation anxiety disorders.
{
Major depressive, dysthymic, and bipolar disorders.
§
Intermittent explosive, attention-deficit/hyperactivity, conduct, and oppositional defiant disorders.
#
Alcohol/illicit drug misuse or dependence.
a. Assessed in the Part II sample.
b. New Zealand assessed in the Part I sample.
c. Assessed only in the Part II sample with age range 18–44 years.
Prevalence and risk factors for suicidal behaviours
in this study. Also excluded were potential protective factors such
as treatment utilisation and social support. The investigation of
these and other factors remain important directions for future
research.
Clinical implications and future research
These limitations notwithstanding, several important findings
from this study warrant more detailed comment. Perhaps the
most impor tant finding of this study is that there is strong
cross-national consistency for several key risk factors for suicidal
behaviours. Female gender, young age, and low educational attain-
ment have been identified as risk factors for suicidal behaviours in
prior studies,
3,6
and the current findings suggest these risk factors
may be universal. Future research is needed to determine whether
risk of suicidal behaviours is occurring at higher rates among
young people, or whether people simply become less likely to
report on earlier suicidal behaviour with age, due to forgetting
or re-interpretation of these earlier events.
Risk of suicide plans and attempts was also highest within the
first year of ideation and when suicidal ideation had an earlier age-
of-onset. Remarkably, 60% of the transitions from ideation to
attempt – as well as from ideation to plan and plan to attempt
– occur within the first year of onset of ideation and this result
is consistent across all 17 countries. Few studies have examined
the probability and speed of transition from ideation to plans
and attempts, and this information can be especially useful to
healthcare providers. Another important finding is that the strong
relationship observed between mental disorders and suicide plans
and attempts diminishes when controlling for ideation. Thus,
although mental disorders are strong risk factors for suicidal
behaviours, factors beyond the mere presence of mental disorders
explain the transition from ideation to plans and attempts.
Several recent studies have suggested that mental disorders
are less important in the occurrence of suicidal behaviours in
low- and middle-income countries relative to high-income coun-
tries. Whereas studies in high-income countries suggest that
490% of those who die by suicide have a diagnosable mental dis-
order and 460% have a mood disorder in particular,
30
rates in
low- and middle-income countries have been suggested to be as
low as 60% and 35% respectively.
7
Our results indicate that when
the same assessment methods are used cross-nationally, mental
disorders are as predictive of suicidal behaviours in low- and
middle-income countries as they are in high-income countries,
and that comorbidity is an important predictor across all coun-
tries. Notably though, impulse-control disorders were stronger
predictors than mood disorders in most low- and middle-income
countries. The fact that mood and impulse-control disorders have
the strongest associations with suicidal behaviours is consistent
with prior work highlighting the importance of depressed mood
and impulsiveness in the suicidal process,
31
and extends these
findings cross-nationally. The reason for the difference in the
importance of impulse-control disorders between high-income
and low- and middle-income countries is unclear and awaits
further examination.
Future research must examine factors that might explain the
variability in prevalence and must also develop more complex risk
and protective models that take into account both common and
specific factors for each country/region. From a practical perspec-
tive, the similarities observed between low- and middle-income
and high-income countries suggest equivalent resources should
be devoted to studying and preventing suicidal behaviours in these
countries. Currently, resources devoted to the treatment of mental
disorders in general, and to suicide prevention in particular,
9
are
lacking in many low- and middle-income (and high-income)
countries.
7,10
It is important to note, however, that more
103
Table 4 Low- and middle-income cou ntries: DSM–IV disorders as risk factors for first onset of suicid e-related outcomes (pooled
analysis).
Total sample (n=15 506) Among ideators
Ideation Plan Attempt
Plan
(n=1855)
Attempt
(n¼1855)
Attempt without
a lifetime plan
(n=1050)
Attempt with
a lifetime plan
(n=805)
Disorder category OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Any anxiety
disorders
{,a
2.8* 2.4 to 3.2 3.6* 2.8 to 4.5 3.5* 2.8 to 4.3 1.5* 1.2 to 1.9 1.2 0.9 to 1.5 1.1 0.7 to 1.6 1.3 0.9 to 1.8
Any mood
disorders
{,a
3.4* 2.8 to 4.1 5.5* 4.4 to 6.9 4.7* 3.6 to 6.0 2.1* 1.6 to 2.9 1.0 0.8 to 1.4 0.8 0.5 to 1.3 1.2 0.8 to 1.9
Any impulse-
control
disorders
§,b
4.4* 3.5 to 5.5 6.5* 4.8 to 8.8 6.3* 4.6 to 8.5 2.1* 1.5 to 2.9 1.6* 1.1 to 2.4 1.4 0.8 to 2.6 2.3* 1.3 to 4.2
Any substance
use disorders
#,a
2.9* 2.3 to 3.7 4.2* 3.0 to 5.9 4.6* 3.5 to 6.3 1.8* 1.1 to 2.8 1.4* 1.0 to 2.0 1.2 0.6 to 2.5 1.6 1.0 to 2.5
Any disorders
a
3.6* 3.1 to 4.1 5.4* 4.4 to 6.7 5.3* 4.2 to 6.6 1.8* 1.4 to 2.4 1.4* 1.1 to 1.7 1.2 0.8 to 1.7 1.6* 1.1 to 2.3
Exactly one
disorder
a
1.4* 1.1 to 1.7 1.0 0.8 to 1.3 1.2 0.9 to 1.6 0.7* 0.5 to 1.0 0.9 0.7 to 1.3 0.9 0.5 to 1.6 1.0 0.6 to 1.6
Exactly two
disorders
a
2.8* 2.3 to 3.5 3.7* 2.9 to 4.7 3.1* 2.4 to 4.1 1.5* 1.1 to 2.1 1.1 0.8 to 1.6 0.9 0.5 to 1.5 1.0 0.6 to 1.7
Three or more
disorders
a
5.9* 4.9 to 7.2 10.0* 7.7 to 12.9 9.2* 7.4 to 11.6 2.5* 1.9 to 3.3 1.5* 1.1 to 2.1 1.6* 1.0 to 2.6 1.8* 1.2 to 2.7
Low- and middle-income countries include Colombia, Mexico, Ukraine, Lebanon, Nigeria, South Africa and People’s Republic of China. Results are based on multivariate
discrete-time survival model. Each model controls for person-year, countries and the socio-demographic variables from Table 1.
*Odds ratio (OR) significant at the 0.05 level, two-sided test.
{
Panic, agoraphobia, generalised anxiety, specific phobia, social phobia, post-traumatic stress, and adult separation anxiety disorders.
{
Major depressive, dysthymic, and bipolar disorders.
§
Intermittent explosive, attention-deficit/hyperactivity, conduct, and oppositional defiant disorders.
#
Alcohol/illicit drug misuse or dependence.
a. Assessed in the Part II sample.
b. Assessed only in the Part II sample with age range 18–44 years.
Nock et al
treatment alone is not the answer. Several recent studies have
highlighted that despite significant increases in service utilisation
among suicidal individuals, the rates of suicidal ideation, plans
and attempts have remained virtually unchanged.
4
Moreover,
although several different forms of treatment have proven effective
at decreasing the likelihood of making suicide attempts, psycho-
social treatments have proven less effective at decreasing the
likelihood of death by suicide.
32
Improvements in our ability to
predict and prevent suicidal behaviours and suicide deaths are
clearly needed, and require that we continue to identify the risk
and protective factors that influence such behaviours. In addition,
we need to develop more sophisticated methods for synthesising
and using the information obtained about such factors.
Matthew K. Nock, PhD, Department of Psychology, Harvard University,
Massachusetts, USA, Guilherme Borges, PhD, Department of Epidemiology, National
Institute of Psychiatry and Universidad Autonoma Metropolitana, Mexico City, Mexico,
Evelyn J. Bromet, PhD, Department of Psychiatry, State University of New York,
Stony Brook, USA, Jordi Alonso, MD, PhD, Health Services Research Unit, Institut
Municipal d’Investigacio Medica IMIM, Barcelona, Spain, Matthias Angermeyer, MD,
University of Leipzig, Department of Psychiatry, Leipzig, Germany, Annette
Beautrais, PhD, Christchurch School of Medicine & Health Sciences, New Zealand,
Ronny Bruffaerts, PhD, Department of Neurosciences and Psychiatry, University
Hospitals, Gasthuisberg, Belgium, Wai Tat Chiu, AM, Department of Health Care
Policy, Harvard Medical School, Boston, Massachusetts, USA, Giovanni de
Girolamo, MD, Department of Mental Health, AUSL di Bologna, Bologna, Italy,
Semyon Gluzman, MD, Ukrainian Psychiatric Association, Kyiv, Ukraine, Ron de
Graaf, PhD, Netherlands Institute of Mental Health and Addiction, Utrecht, The
Netherlands, Oye Gureje, MD, PhD, FRCPsych, Department of Psychiatry, University
College Hospital, Ibadan, Nigeria, Josep Maria Haro, MD, MPH, PhD, Sant Joan de
Deu-SSM, Barcelona, Spain, Yueqin Huang, MPH, MD, PhD, Institute of Mental
Health, Peking University, People’s Republic of China, Elie Karam, MD, Department
of Psychiatry and Psychology, St George Hospital University Medical Center, Beirut,
Lebanon, Ronald C. Kessler, PhD, Department of Psychology, Harvard University,
Massachusetts, USA, Jean Pierre Lepine, MD, Hospital Fernand Widal, Paris, France,
Daphna Levinson, PhD, Research and Planning, Mental Health Services, Ministry of
Health, Jerusalem, Israel, Maria Elena Medina-Mora, PhD, Department of
Epidemiology, National Institute of Psychiatry and Universidad Autonoma
Metropolitana, Mexico City, Mexico, Yutaka Ono, MD, Keio University, Tokyo, Japan,
Jose
´
Posada-Villa, MD, Colegio Mayor de Cundinamarca University, Saldarriaga
Concha Foundation, Bogota, Colombia, David Williams, PhD, MPH, Harvard
University School of Public Health, Boston, Massachusetts, USA.
Correspondence: Mat thew K. Nock, PhD, Department of Psycholo gy, Harvard
University, 33 Kirkland Street, 1280 Cambridge, MA 02138, USA. Email:
nock@wjh.h arvard.ed u
First received 7 May 2007, final revision 7 Oct 2007, accepted 27 Nov 2007
Acknowledgements
The surveys included in this report were carried out in conjunction with the World Health
Organization WHO World Mental Health (WMH) Survey Initiative. We thank the WMH staff
for assistance with instrumentation, fieldwork, and data analysis. These activities were
supported by the United States National Institute of Mental Health (NIMH; R01MH077883,
R01MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation,
the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the
Fogarty International Center (FIRCA R01-TW006481), the Pan American Health Organization
(PAHO), Eli Lilly, Ortho-McNeil Pharmaceutical, GlaxoSmithKline, and Bristol-Myers Squibb. A
complete list of WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/.
The Chinese World Mental Health Survey Initiative is supported by the Pfizer Foundation.
The Colombian National Study of Mental Health is supported by the Ministry of Social
Protection, with supplemental support from the Saldarriaga Concha Foundation. The
European Study of the Epidemiology of mental Disorders project is funded by the European
Commission (contracts QLG5-1999-01042; SANCO 2004123), the Piedmont Region, Italy,
Fondo de Investigacio
´
n Sanitaria, Instituto de Salud Carlos III, Spain FIS 00/0028, Ministerio
de Ciencia y Tecnologı
´a,
Spain (SAF 2000-158-CE), Departament de Salut, Generalitat de
Catalunya, Spain (RETICS RD06/0011 REM-TAP Network), and other local agencies and by
an unrestricted educational grant from GlaxoSmithKline. The Israel National Health
Survey is funded by the Ministry of Health with support from the Israel National Institute
for Health Policy and Health Services Research and the National Insurance Institute of
Israel. The World Mental Health Japan Survey is supported by the Grant for Research on
Psychiatric and Neurological Diseases and Mental Health (H13-SHOGAI-023, H14-TOKUBETSU-
026, H16-KOKORO-013) from the Japan Ministry of Health, Labour and Welfare. The
Lebanese National Mental Health Survey is supported by the Lebanese Ministry of Public
Health, the WHO (Lebanon), the Fogarty International Center and anonymous private
donations to Institute for Development, Research, Advocacy and Applied Care, Lebanon,
and unrestricted grants from Janssen Cilag, Eli Lilly, GlaxoSmithKline, Roche, and Novartis.
The Mexican National Comorbidity Survey is supported by The National Institute of
Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science
and Technology (CONACyT-G30544-H), with supplemental support from the PAHO. Te Rau
Hinengaro: The New Zealand Mental Health Survey is supported by the New Zealand
Ministry of Health, Alcohol Advisory Council, and the Health Research Council. The Nigerian
Survey of Mental Health and Wellbeing is supported by the WHO (Geneva and Nigeria) and
the Federal Ministry of Health, Abuja, Nigeria. The South Africa Stress and Health Study is
supported by the US NIMH (R01-MH059575) and National Institute of Drug Abuse (NIDA)
with supplemental funding from the South African Department of Health and the University
of Michigan. The Ukraine Comorbid Mental Disorders during Periods of Social Disruption
study is funded by the US NIMH (RO1-MH61905). The US National Comorbidity Survey
Replication is supported by the NIMH (U01-MH60220) with supplemental support from
the NIDA, the Substance Abuse and Mental Health Services Administration, the Robert
Wood Johnson Foundation (grant 044708), and the John W. Alden Trust. R.C.K., as principal
investigator, had full access to all of the data in the study and takes responsibility for the
integrity of the data and the accuracy of the data analysis.
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105
Word pictures of depression: anhedonia
Sharon McConville
I have never been a particularly hedonistic type of person, but for me, the following illustration is useful in summing up my experience
of anhedonia:
‘The sun is shining brilliantly and the sky is a cloudless azure. Everything looks pristine. The trees and bushes appear velvety, like
model vegetation on a model railway set, and the lines of the buildings are sharp like the edges of neatly-wrapped parcels. My friends
are excited because they have planned to watch a movie which is being projected on to the cliff face at Cavehill, and it is a perfect
evening for such an adventure. I have a ticket but I have decided not to go. It is cloudy and dark in my inner world and I do not have
the energy left to construct a bridge which I can cross into this bright parallel reality. Sometimes I can do it; sometimes I can mentally
detach myself from the gloom and live for a time in the glow created by the people around me, like a candle which does not quite
smoulder out because it is relit using the flame of others which burn more strongly. This is an excursion which I would ordinarily enjoy:
the film is one which I would like to see; the people are friends with whom I am comfortable; I would like to be outside in a beautiful
setting with panoramic views; and the novelty value of marrying Hollywood commercialism with the stark majesty of nature appeals
to me. Tonight, I know that I could not concentrate on any film; I am intimidated by the thought of having to interact with a number of
different people, taking into account their different needs and the differing expectations which they have of me; and I crave silence
and space unmarred by noisy crowds.’
The British Journal of Psychiatry (2008)
192, 105. doi: 10.1192/bjp.192.2.105
1
The British Journal of Psychiatry (2008)
192, 98–105. doi: 10.1192/bjp.bp.107.040113
Table DS1 Sample characte ristics.
Sample size
Country Survey Sample characteristics
a
Field dates
Age,
years Part I Part II
Part II and
age 444
b
Response
rate
c
Belgium ESEMeD Stratified multistage clustered probability sample of
individuals residing in households from the national
register of Belgium residents. NR
2001–02 18+ 2419 1043 486 50.6
Colombia NSMH Stratified multistage clustered area probability sample
of household residents in all urban areas of the country
(~73% of the total national population)
2003 18–65 4426 2381 1731 87.7
France ESEMeD Stratified multistage clustered sample of working
telephone numbers merged with a reverse directory (for
listed numbers). Initial recruitment was by telephone,
with supplemental in-person recruitment
in households with listed numbers. NR
2001–02 18+ 2894 1436 727 45.9
Germany ESEMeD Stratified multistage clustered probability sample of
individuals from community resident registries. NR
2002–03 18+ 3555 1323 621 57.8
Italy ESEMeD Stratified multistage clustered probability sample of
individuals from municipality resident registries. NR
2001–02 18+ 4712 1779 853 71.3
Israel NHS Stratified multistage clustered area probability sample o f
household residents. NR
2002–04 21+ 4859 – – 72.6
Japan WMHJ
2002–2003
Un-clustered two-stage probability sample of individuals
residing in households in four metropolitan areas
(Fukiage, Kushikino, Nagasaki, Okayama)
2002–03 20+ 2436 887 282 56.4
Lebanon LEBANON Stratified multistage clustered area probability sample
of household residents. NR
2002–03 18+ 2857 1031 595 70.0
Mexico M–NCS Stratified multistage clustered area probability sample
of household residents in all urban areas of the country
(~75% of the total national population)
2001–02 18–65 5782 2362 1736 76.6
Netherlands ESEMeD Stratified multistage clustered probability sample
of individuals residing in households that are listed
in municipal postal registries. NR
2002–03 18+ 2372 1094 516 56.4
New Zealand NZMHS Stratified multistage clustered area probability
sample of household residents. NR
2004–05 16+ 12992 7435 4242 73.3
Nigeria NSMHW Stratified multistage clustered area probability sample
of households in 21 of the 36 states in the country,
representing 57% of the national population. The
surveys were conducted in Yoruba, Igbo, Hausa and
Efik languages.
2002–03 18+ 6752 2143 1203 79.3
PRC Beijing B–WMH Stratified multistage clustered area probability sample
of household residents in the Beijing metropolitan area
2002–03 18+ 2633 914 307 74.8
PRC Shanghai S–WMH Stratified multistage clustered area probability sample of
household residents in the Shanghai metropolitan area
2002–03 18+ 2568 714 263 74.6
South Africa SASH Stratified multistage clustered area probability sample
of household residents. NR
2003–04 18+ 4315 – – 87.1
Spain ESEMeD Stratified multistage clustered area probability sample
of household residents. NR
2001–02 18+ 5473 2121 960 78.6
Ukraine CMDPSD Stratified multistage clustered area probability sample
of household residents. NR
2002 18+ 4725 1720 541 78.3
USA NCS–R Stratified multistage clustered area probability sample
of household residents. NR
2002–03 18+ 9282 5692 3197 70.9
ESEMeD, European Study of the Epidemiology of Mental Disorders; NR, nationally representative; NSMH, Colombian National Study of Mental Health; NHS, Israel National Health
Survey; WMHJ, World Mental Health Japan Survey; LEBANON, Lebanese Evaluation of the Burden of Ailments and Needs of the Nation; M–NCS, Mexico National Comorbidity Survey;
NZMHS, New Zealand Mental Health Survey; NSMHW, Nigerian Survey of Mental Health and Wellbeing; PRC, People’s Republic of China; B–WMH, Beijing World Mental Health Survey;
S–WMH, Shanghai World Mental Health Survey; SASH, South Africa Health Survey; CMDPSD, Comorbid Mental Disorders During Periods of Social Disruption; NCS–R, US National
Comorbidity Survey Replication.
a. Most WMH surveys are based on stratified multistage clustered area probability household samples in which samples of areas equivalent to counties or municipalities in the USA
were selected in the first stage followed by one or more subsequent stages of geographical sampling (e.g. towns within counties, blocks within towns, households within blocks) to
arrive at a sample of households, in each of which a listing of household members was created and one or two people were selected from this listing to be interviewed. No substitution
was allowed when the originally sampled household resident could not be interviewed. These household samples were selected from census area data in all countries other than
France (where telephone directories were used to select households) and The Netherlands (where postal registries were used to select households). Several WMH surveys (Belgium,
Germany, Italy) used municipal resident registries to select respondents without listing households. The Japanese sample is the only totally un-clustered sample, with households
randomly selected in each of the four sample areas and one random respondent selected in each sample household. Nine of the 15 surveys are based on NR household samples, while
two others are based on NR household samples in urbanised areas (Colombia, Mexico).
b. All countries, with the exception of Nigeria, PRC Beijing, PRC Shanghai, and Ukraine (which were age restricted to 439 years) were age restricted to 444 years.
c. Calculated as the ratio of the number of households in which an interview was completed to the number of households originally sampled, excluding from the denominator
households known not to be eligible either because of being vacant at the time of initial contact or because the residents were unable to speak the designated languages of the
survey.
2
Table DS 2 Lifetime prevalence of su icide-related out comes i n the World Mental Health surveys of the total sample (
n
¼84 850).
Ideation Plan Attempt
% s.e. s.d. n % s.e. s.d. n % s.e. s.d. n
The Americas
Colombia 12.4
a
0.7 46.6 587 4.1
a
0.4 26.6 204 4.7
a
0.4 26.6 224
Mexico 8.1
b
0.5 38.0 488 3.2 0.3 22.8 192 2.7 0.3 22.8 166
USA 15.6
a
0.5 48.2 1462 5.4
a
0.3 28.9 507 5.0
a
0.2 19.3 469
Europe
Belgium 8.4 0.9 44.3 209 2.7 0.4 19.7 77 2.5 0.4 19.7 66
France 12.4
a
0.7 37.7 391 4.4
a
0.4 21.5 143 3.4 0.4 21.5 115
Germany 9.7 0.7 41.7 347 2.2
b
0.3 17.9 78 1.7
b
0.3 17.9 64
Italy 3.0
b
0.3 20.6 144 0.7
b
0.1 6.9 33 0.5
b
0.1 6.9 26
Netherlands 8.2 0.6 29.2 223 2.7 0.5 24.4 78 2.3 0.3 14.6 64
Spain 4.4
b
0.3 22.2 272 1.4
b
0.2 14.8 84 1.5
b
0.2 14.8 80
Ukraine 8.2
b
0.5 34.4 389 2.7 0.3 20.6 126 1.8
b
0.2 13.7 80
Africa and the Middle East
Israel 5.5
b
0.3 20.9 268 1.9
b
0.2 13.9 93 1.4
b
0.2 13.9 66
Lebanon 4.3
b
0.6 32.1 117 1.7
b
0.4 21.4 39 2.0
b
0.3 16.0 54
Nigeria 3.2
b
0.2 16.4 237 1.0
b
0.1 8.2 70 0.7
b
0.1 8.2 46
South Africa 9.1 0.7 46.0 394 3.8 0.4 26.3 171 2.9 0.3 19.7 140
Asia and the Pacific
China 3.1
b
0.2 14.4 160 0.9
b
0.2 14.4 42 1.0
b
0.2 14.4 49
Japan 10.9
a
0.5 24.7 264 2.1
b
0.3 14.8 50 1.9
b
0.3 14.8 48
Oceania
New Zealand 15.9
a
0.5 56.5 2212 5.6
a
0.3 33.9 814 4.6
a
0.3 33.9 688
Total 9.2 0.1 29.1 8164 3.1 0.1 29.1 2801 2.7 0.1 29.1 2445
a. The lower end of the 95% CI of the estimate is above the prevalence estimate for the total sample.
b. The upper end of the 95% CI of the estimate is below the prevalence estimate for the total sample.
Table DS 3 Lifetime prevalence of suici de-related out comes in the W orld Mental H ealth surveys among ideators.
Plan Attempt Attempt without a lifetime plan Attempt with a lifetime plan
% s.e. s.d. n % s.e. s.d. n % s.e. s.d. n % s.e. s.d. n
The Americas
Colombia 33.2 2.6 63.0 204 37.8
a
2.6 63.0 224 22.7
a
3.2 62.6 77 68.3
a
3.5 50.0 147
Mexico 39.0
a
2.7 59.6 192 33.8 2.7 59.6 166 16.3 2.6 44.7 48 61.3 4.8 66.5 118
USA 34.5 1.6 61.2 507 31.8 1.4 53.5 469 19.9
a
1.4 43.3 185 54.4 3.1 69.8 284
Europe
Belgium 32.2 3.4 49.2 77 29.4 4.3 62.2 66 12.2 3.4 39.1 16 65.7 7.0 61.4 50
France 35.9 3.1 61.3 143 27.2 2.9 57.3 115 14.2 3.1 48.8 40 50.4 4.6 55.0 75
Germany 22.1
b
2.5 46.6 78 17.4
b
2.2 41.0 64 4.0
b
1.3 21.3 14 64.7 5.8 51.2 50
Italy 24.6
b
4.0 48.0 33 18.2
b
4.5 54.0 26 8.2
b
3.0 31.6 10 48.8 11.2 64.3 16
Netherlands 33.4 4.6 68.7 78 27.6 3.5 52.3 64 12.0 3.2 38.5 18 58.6 7.4 65.4 46
Spain 33.1 3.8 62.7 84 33.9 3.1 51.1 80 14.4 3.4 46.6 23 73.3
a
5.8 53.2 57
Ukraine 32.9 2.5 49.3 126 21.5
b
2.7 53.3 80 13.4 2.3 37.3 32 38.2
b
5.0 56.1 48
Africa & the Middle East
Israel 35.3 3.2 52.4 93 25.0 2.9 47.5 66 8.3
b
2.1 27.8 15 55.5 5.5 53.0 51
Lebanon 38.4 5.0 54.1 39 46.4
a
5.2 56.2 54 30.1
a
6.3 55.6 25 72.4
a
6.9 43.1 29
Nigeria 30.1 3.6 55.4 70 20.9
b
3.0 46.2 46 1.9
b
0.9 11.6 3 64.8 7.2 60.2 43
South Africa 41.7
a
2.3 45.7 171 31.7 2.6 51.6 140 11.2 2.3 34.3 33 60.5 4.5 58.8 107
Asia and the Pacific
China 29.5 4.6 58.2 42 32.3 4.9 62.0 49 26.1
a
4.7 51.1 28 47.1 10.0 64.8 21
Japan 18.8
b
2.6 42.2 50 17.0
b
2.5 40.6 48 8.8
b
2.1 30.7 21 52.1 7.0 49.5 27
Oceania
New Zealand 35.1 1.4 65.8 814 28.8 1.3 61.1 688 16.6 1.4 52.3 241 51.2 2.2 62.8 447
Total 33.6 0.7 63.2 2801 29.0 0.6 54.2 2445 15.4 0.6 43.9 829 56.0 1.2 63.5 1616
a. The lower end of the 95% CI of the estimate is above the prevalence estimate for the total sample.
b. The upper end of the 95% CI of the estimate is below the prevalence estimate for the total sample.
3
Fig. DS1 Cumulative age-of-onset distribution for suicide ideation in each country
Fig. DS2 Conditional, cumulative speed of transition from ideation to attempt in each country
10.1192/bjp.bp.107.040113Access the most recent version at DOI:
2008, 192:98-105.BJP
Levinson, Maria Elena Medina-Mora, Yutaka Ono, José Posada-Villa and David Williams
Gureje, Josep Maria Haro, Yueqin Huang, Elie Karam, Ronald C. Kessler, Jean Pierre Lepine, Daphna
Beautrais, Ronny Bruffaerts, Wai Tat Chiu, Giovanni de Girolamo, Semyon Gluzman, Ron de Graaf, Oye
Matthew K. Nock, Guilherme Borges, Evelyn J. Bromet, Jordi Alonso, Matthias Angermeyer, Annette
plans and attempts
Cross-national prevalence and risk factors for suicidal ideation,
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