ArticlePDF AvailableLiterature Review

Global Burden of Post-traumatic Stress Disorder and Major Depression in Countries Affected by War Between 1989 and 2019: A Systematic Review and Meta-analysis

BMJ Global Health

July 2021

DOI:10.1136/bmjgh-2021-006303

License
CC BY-NC 4.0

Authors:

Thole Hoppen

University of Münster

Stefan Priebe

Queen Mary, University of London

Inja Vetter

University of Münster

Nexhmedin Morina

University of Münster

Objective: Extensive research has demonstrated high prevalences of posttraumatic stress disorder (PTSD) and major depression (MD) in war-surviving populations. However, absolute estimates are lacking, which may additionally inform policy making, research and health care. We aimed at estimating the absolute global prevalence and disease burden of adult survivors of recent wars (1989-2019) affected by PTSD and/or MD. Methods: We conducted a systematic literature search and meta-analysis of interview-based epidemiological surveys assessing the prevalence of PTSD and/or MD in representative samples from countries with a recent war history (1989-2019). Drawing on the war definition and geo-referenced data of the Uppsala Conflict Database Program and population estimates of the United Nations for 2019, we extrapolated the meta-analytic results to absolute global numbers of affected people. Drawing on Disability Adjusted Life Years (DALYs) data of the Global Burden of Diseases Study 2019, we further calculated the PTSD-and MD-associated DALYs. Results: Twenty-two surveys (N = 15,420) for PTSD, 13 surveys for MD (N = 9,836) and six surveys on the comorbidity of PTSD and MD (N = 1,131) were included. Random effects meta-analyses yielded point prevalences of 26.51% for PTSD and 23.31% for MD. Of those affected by PTSD, 55.26% presented with comorbid MD. Prevalence rates were not significantly associated with war intensity and length, time since war, response rate or survey quality. The extrapolation yielded 316 million adult war-survivors globally who suffered from PTSD and/or MD in 2019. War-survivors were almost exclusively living in LMICs and carried a burden of 3,127,089 and 4,114,663 DALYs associated with PTSD and MD, respectively. Conclusions: Since LMICs lack sufficient funding and qualified professionals to provide evidence-based psychological treatments for such large numbers of affected people, alternative and scalable strategies using existing resources in primary care and communities are required. Research is required to assist upscaling.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart of study selection. MD, major depression; PTSD, post-traumatic stress disorder. Medizin. Protected by copyright.

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Forest plots for point prevalence of post-traumatic stress disorder (top) and major depression (bottom).

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Extrapolation to absolute prevalence and associated disease burden, as measured by DALYs

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HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

Global burden of post- traumatic stress

disorder and major depression in

countries affected by war between 1989

and 2019: a systematic review and meta-

analysis

Thole H Hoppen ,1 Stefan Priebe,2 Inja Vetter,1 Nexhmedin Morina1

Original research

To cite: HoppenTH, PriebeS,

VetterI, etal. Global burden

of post- traumatic stress

disorder and major depression

in countries affected by war

between 1989 and 2019: a

systematic review and meta-

analysis. BMJ Global Health

2021;6:e006303. doi:10.1136/

bmjgh-2021-006303

Handling editor Seye Abimbola

►Additional supplemental

material is published online only.

To view, please visit the journal

online (http:// dx. doi. org/ 10.

1136/ bmjgh- 2021- 006303).

Received 13 May 2021

Accepted 20 July 2021

1Institute of Psychology,

University of Münster, Münster,

Germany

2Unit for Social and Community

Psychiatry, Queen Mary

University of London, London,

Correspondence to

Dr Thole H Hoppen;

thoppen@ uni- muenster. de

employer(s)) 2021. Re- use

permitted under CC BY- NC. No

commercial re- use. See rights

and permissions. Published by

BMJ.

ABSTRACT

Objective Extensive research has demonstrated high

prevalences of post- traumatic stress disorder (PTSD)

and major depression (MD) in war- surviving populations.

However, absolute estimates are lacking, which

may additionally inform policy making, research and

healthcare. We aimed at estimating the absolute global

prevalence and disease burden of adult survivors of

recent wars (1989–2019) affected by PTSD and/or MD.

Methods We conducted a systematic literature search

and meta- analysis of interview- based epidemiological

surveys assessing the prevalence of PTSD and/or MD in

representative samples from countries with a recent war

history (1989–2019). Drawing on the war denition and

geo- referenced data of the Uppsala Conict Database

Programme and population estimates of the United

Nations for 2019, we extrapolated the meta- analytic

results to absolute global numbers of affected people.

Drawing on disability- adjusted life years (DALYs) data of

the Global Burden of Diseases Study 2019, we further

calculated the PTSD- associated and MD- associated

DALYs.

Results Twenty- two surveys (N=15 420) for PTSD,

13 surveys for MD (N=9836) and six surveys on

the comorbidity of PTSD and MD (N=1131) were

included. Random effects meta- analyses yielded point

prevalences of 26.51% for PTSD and 23.31% for MD.

Of those affected by PTSD, 55.26% presented with

comorbid MD. Prevalence rates were not significantly

associated with war intensity and length, time since

war, response rate or survey quality. The extrapolation

yielded 316 million adult war- survivors globally who

suffered from PTSD and/or MD in 2019. War- survivors

were almost exclusively living in low/middle- income

countries (LMICs) and carried a burden of 3 105 387

and 4 083 950 DALYs associated with PTSD and MD,

respectively.

Conclusions Since LMICs lack sufcient funding and

qualied professionals to provide evidence- based

psychological treatments for such large numbers of

affected people, alternative and scalable strategies using

existing resources in primary care and communities are

required. Research is required to assist upscaling.

INTRODUCTION

Meta- analyses demonstrate high preva-

lence rates of post- traumatic stress disorder

(PTSD) and major depression (MD) in

Key questions

What is already known?

►Several meta- analyses of epidemiological surveys have

demonstrated high prevalences of post- traumatic stress

disorder (PTSD) and major depression (MD) in war-

surviving populations.

►However, absolute global estimates of prevalence and

disease burden are lacking.

►Estimates in absolute numbers may inform policy mak-

ing, research and healthcare beyond percentages.

What are the new ndings?

►In this systematic review and meta- analysis that includ-

ed 41 surveys, random effects meta- analyses yielded a

point prevalence of 26.51% for PTSD and 23.31% for

MD.

►Of those affected by PTSD, 55.26% presented with co-

morbid MD.

►The extrapolation yielded about 316 million adult war

survivors who experienced PTSD and/or MD in 2019

residing in 43 war- ridden countries with a war histo-

ry between 1989 and 2019 (almost exclusively low/

middle- income countries (LMICs)).

►PTSD and MD were associated with about 3 million and

4 million disability- adjusted life years, respectively.

What do the new ndings imply?

►The number of war survivors experiencing PTSD and/or

MD creates a massive mental health burden, which is

primarily borne by LMICs.

►Tailored approaches for LMICs contexts are necessary to

address the presented vast mental health burden.

►Low- cost and scalable solutions that build on available

resources are recommended as well as multidisciplinary

research to guide evidence- based upscaling.

►The ndings generally illustrate the importance of

peace- building and maintenance.

Medizin. Protected by copyright. on July 28, 2021 at Univ.- & Landesbibliothek, Zweigbibliothekhttp://gh.bmj.com/BMJ Glob Health: first published as 10.1136/bmjgh-2021-006303 on 28 July 2021. Downloaded from

2HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

BMJ Global Health

war- affected populations with pooled estimates ranging

from 15.3% to 30.6% for PTSD and 10.8% to 30.8% for

MD.1–4 However, there is a lack of prevalence estimates

and disease burden estimates in absolute numbers.

Such absolute estimates are important for three major

reasons. First, war affects large populations globally:

between 1989 and 2019, about one- sixth of the global

population have experienced war within their country

of residence.5 6 Second, absolute numbers add clarity

to the scope of war- related mental health burdens and,

as such, inform policy making, healthcare and research

beyond relative estimates. Third, countries with a recent

history of war are almost exclusively low/middle- income

countries (LMICs) with limited healthcare resources.7

Absolute estimates may reveal particular challenges for

mental healthcare in LMICs settings and inform tailored

approaches. All previous meta- analyses partly or exclu-

sively involved specific populations precluding extrapola-

tions to general war- surviving populations.

Against this background, we aimed to estimate the

absolute global number of war survivors with PTSD and/

or MD, as well as the absolute associated disease burden.

For this, we conducted a systematic literature search and

meta- analysis on high- quality epidemiological surveys

conducted in countries with a history of war within their

own territory between 1989 and 2019, and extrapolated

results to absolute numbers and the associated disability-

adjusted life years (DALYs) as a measure of disease

burden.

METHODS

Denition of war and war-aficted country

We used the definition of war and geo- referenced

war- data from the Uppsala Conflict Data Programme

(UCDP) from the Department of Peace and Conflict

Research of the Uppsala University.5 The UCDP supplies

geo- referenced war data from 1989 to 2019. Based on the

geo- referenced data, we classified war in four countries

(ie, India, Israel, Russia and Ukraine) as regional rather

than nationally distributed (see https:// ucdp. uu. se/)

which was relevant for the accuracy of extrapolations,

which are described in more detail elsewhere.6

Systematic literature search

Up until September 2017, we relied on our previous

systematic literature search with identical search strategy,2

which we pre- registered in the PROSPERO database (ID:

CRD42016032720; https://www. crd. york. ac. uk/ pros-

pero/ display_ record. php? RecordID= 32720). However,

for the present report, we excluded surveys that were not

representative of general populations. A new systematic

literature search was conducted in Medline, PsycINFO

and PTSDpubs between 1 August 2017 up until 15 January

2021 (see detailed search strategy in online supplemental

eList 1). We conducted the systematic review according

to the Preferred Reporting Items for Systematic Reviews

and Meta- Analyses (PRISMA) guidelines.8 Two authors

(THH, IV) independently conducted all search steps

(eg, duplicate detection, title and abstract screen, full-

text screen) as well as all following steps (eg, data extrac-

tion, risk of bias assessment); regular meetings between

three authors (THH, IV and NM) were held to discuss

disagreements. Inclusion and exclusion criteria were set

to maximise representativeness of general war surviving

populations and, therefore, to allow for extrapolations.

Epidemiological surveys were eligible if they met all of

the following inclusion criteria: (1) conducted after

the first year of war in a country with a history of war

between 1989 and 2019 as defined by the UCDP; (2)

using a random sampling technique to draw a represent-

ative sample from the general population; (3) including

at least 50 participants; (4) at least 80% of the partici-

pants were aged 18 years or older and (5) PTSD and/

or MD were measured with a (semi- )structured interview

based on the diagnostic criteria reported in any version

of the Diagnostic and Statistical Manual for Mental Disor-

ders (DSM) or the International Statistical Classification

of Diseases (ICD). There were no restrictions in terms

of language or population (other than the mentioned

inclusion criteria). In line with the inclusion criterion 2,

surveys were excluded if they were conducted in an area

with particularly high or low war intensity as compared

with the rest of the country, indicated by geo- referenced

UCDP data, or if surveys involved help- seeking popula-

tions. We also reviewed relevant secondary literature

(see PRISMA flow chart; figure 1)1 4 6 9 10 as well as refer-

ence lists of eligible articles. Since all relevant data were

reported in the eligible surveys, no contact with authors

of primary literature was necessary.

Coding of survey information

The main outcome was the point prevalence of PTSD,

MD and their comorbidity. We further extracted relevant

data for the planned moderator analyses (see later).

Quality assessment

We assessed the quality of included surveys with a scale

that we had developed previously.2 The scale is based on

the recommendations reported in the Strengthening

the Reporting of Observational Studies in Epidemiology

guidelines and related meta- analyses,11–13 and consists of

six quality items (see online supplemental eTable 1). Two

authors (THH, IV) independently rated the quality of

included trials on the applicable items with 73% agree-

ment. All disagreements were solved through discussions

between three authors (THH, IV and NM). A quality sum

score of percentage of the possible sum score was created

for each survey since they differed on the number of

applicable quality items.

Meta-analysis

We conducted random effects meta- analyses on Freeman-

Tukey double arcsine transformed prevalence propor-

tions using the inverse variance method.14 We used the

packages meta (V.4.16-2)15 and metafor (V.2.4-0)16 in R

HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303 3

BMJ Global Health

(V.3.6.1).17 To calculate 95% CIs for individual studies

in the forest plots, we used the Agresti- Coull interval.18

Q- statistics and the I²-statistics were calculated to get an

estimate of homogeneity in effect sizes. The latter indi-

cates the degree of heterogeneity in percentages. We esti-

mated the between- study variance by calculating τ²-sta-

tistics via the restricted maximum likelihood method.19

To analyse the potential effects of outliers, we defined

outliers as prevalence proportions that were at least 3.3

SD above or below the pooled prevalence proportion

and aimed to supply outlier- adjusted results.20 To analyse

potential publication bias, we visually inspected funnel

plots and performed Egger’s test of asymmetry.21 As

recommended,22 we did this only in the presence of at

least 10 independent estimates. In case of detected asym-

metry, we used the trim and fill method, which supplies

asymmetry- adjusted results by introducing additional

hypothetical studies.23 To statistically control for effects

of potentially moderating variables (ie, total war deaths,

war deaths per 100.000 population, total conflict- related

deaths, conflict- related deaths per 100.000, war lengths

in years, years since end of war and conduct of survey,

response rate, quality of survey, mean age, % females, %

in a relationship, % in employment and continent) on

prevalence proportions, we planned to perform univar-

iate mixed- method meta- regressions if enough inde-

pendent surveys reported on the given information (ie,

k≥10).19 Data on country- specific war intensity, conflict

intensity and war length (accumulative for 1989–2019)

was retrieved from the UCDP (https:// ucdp. uu. se/).

Since there was more than one survey for some coun-

tries which experienced multiple wars (Rwanda, Kosovo,

Democratic Republic of the Congo, and Palestine for

PTSD; Rwanda and Kosovo for MD), we merged cases

and non- cases per country for these specific moderator

analyses. Some planned moderator analyses (interven-

tion utilisation, non- war- related trauma history) were

precluded since these variables were either not assessed

or assessed too heterogeneously (differences in defining

and assessing mean number of traumatic events per

trauma type, breadth of assessed trauma history) to allow

for the planned moderator analyses.

Population estimates, extrapolation and income groups

For all nationally distributed wars, we relied on popula-

tion estimates of the Population Division of the Depart-

ment of Economic and Social Affairs (DESA) of the

United Nations.24 Since people who were very young

during war might not be able to remember exposure

to war- related events,25 we only extrapolated data on

adults who were at least 6 years old at the time of the war.

Countries where only specific regions were affected by

war were: India (Punjab, Nagaland, Kashmir, Assam and

Manipur), Ukraine (Donetsk People’s Republik, Kharkiv

Oblast, Luhansk People’s Republic, Zaporizhzhia Oblast

and Dnipropetrovsk Oblast), Israel (Gaza strip and West

Bank) and Russia (Chechnya). For regional wars, we

relied on national consensus data and World Bank popu-

lation data since DESA does not supply age- grouped

regional population estimates. Definitions of LMICs

were based on the World Bank classifications (ie, gross

national income per capita of less than US$12 536).26

Disease burden estimate

To estimate the associated disease burden of the global

number of war survivors with PTSD and MD, we replied

on country- specific DALYs estimates published in the last

iteration of the Global Burden of Diseases (GBD) study;

the GBD 2019.27 Since the GBD 2019 does not report

on PTSD data separately, the estimate for all anxiety

disorders was used. Total country DALYs for PTSD and

all anxiety disorders were retrieved, divided by the total

country population and subsequently multiplied by the

retrieved number of adult war survivors.

RESULTS

Article synthesis

The PRISMA flowchart in figure 1 shows an overview of

the survey synthesis. Of the initial 3989 records identi-

fied, 74 full texts remained after the title and abstract

Figure 1 Preferred Reporting Items for Systematic Reviews

and Meta- Analyses owchart of study selection. MD, major

depression; PTSD, post- traumatic stress disorder.

4HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

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screen for eligibility. After thorough screening of the 74

full texts, a total of 20 eligible publications were included

in the present meta- analysis reporting on 22 independent

surveys (N=15 420) for PTSD from 12 countries and 3

continents, 13 independent surveys (N=9836) for MD

from 9 countries and 3 continents, and 6 independent

surveys (N=1131) for PTSD and comorbid MD from 6

countries and 2 continents.

Characteristics of included studies

An overview of the characteristics of included surveys is

provided in table 1. On average, surveys assessed PTSD

and/or MD 6.88 years (weighted mean; SD=5.88) after

the end of warfare. War intensity and lengths varied

considerably across countries. Survey response rates were

high with a weighted mean of 88.91% (SD=11.10). Most

surveys used mental health professionals as interviewers

who were trained for the purpose of the survey. The most

frequently used interview measure was the Mini Inter-

national Neuropsychiatric Interview28 for both PTSD

and MD. Quality of surveys was moderate overall with a

weighted mean of 34.92% (SD=10.94) of the maximum

attainable quality sum scores. None of the included

surveys involved a formal psychometric validation of

translated measures.

Meta-analytic results

Prevalence of PTSD and MD

Figure 2 shows forest plots of prevalence of PTSD and

MD in the included surveys. Random effects models

yielded a pooled point prevalence of 26.51% (k=22,

95% CI 22.17 to 31.10) for PTSD. Heterogeneity was

large (I2=98%, Q=1057.13, p<0.001). No statistical

outliers were observed. The funnel plot (see online

supplemental eFigure 1) and Egger’s test of asymmetry

(t=0.77, p=0.453) did not indicate publication bias. For

MD, the random effects model yielded a pooled point

prevalence of 23.31% (k=13, 95% CI 18.55 to 28.42) with

large heterogeneity (I2=96.1%, Q=310.72, p<0.001). No

statistical outliers were observed. Again, the funnel plot

(see online supplemental eFigure 2) and Egger’s test

of asymmetry (t=0.77, p=0.457) did not indicate publi-

cation bias. For the comorbidity between PTSD and

MD, the random effects model yielded a pooled point

prevalence of 55.26% (k=6, 95% CI 42.11 to 68.05) with

large heterogeneity (I2=95.6%, Q=113.39, p<0.001; see

the corresponding forest plot in online supplemental

eFigure 3). No statistical outliers were observed. We used

pooled point prevalence in the extrapolation to absolute

numbers.

Moderator results

In the meta- regressions on prevalence of PTSD and MD,

none of the analysed potential moderators was found to

be significantly related (see online supplemental eTable

2). Meta- regressions for comorbidity point prevalence

were precluded (k<10).

Extrapolation to absolute numbers and DALYs

Table 2 shows point prevalence estimates for PTSD, MD

and their comorbidity per country as well as globally.

We estimate that a total of 854 653 860 adult war survi-

vors were alive in 2019 and resided in one of 43 coun-

tries which experienced at least one war between 1989

and 2019. Of these, 849 754 461 were residing in LMICs.

Based on the meta- analytic summary of epidemiological

surveys, the extrapolation yielded that, in 2019, about

227 million adult war survivors globally experienced

PTSD (95% CI 189 476 761 to 265 797 350) and about

199 million experienced MD (95% CI 158 538 291 to 242

892 627). Based on the meta- analytic results on comor-

bidity point prevalence, about 110 million (95% CI 83

891 464 to 135 569 084) adult war survivors globally

experienced comorbid PTSD and MD. Consequently,

about 315 699 683 adult war survivors globally expe-

rienced PTSD and/or MD in 2019 in 43 war- afflicted

countries. Of these, 313 889 900 were residing in LMICs.

Only two countries affected by war (Kuwait and Croatia)

were considered high- income. Extrapolations to disease

burden are also provided in table 2. When the GBD

2019 results are taken as a reference, the extrapolations

yielded 3 127 089 PTSD- associated DALYs and 4 114 663

MD- associated DALYs across 43 war- affected countries, of

which 3 105 387 (PTSD) and 4 083 950 (MD) were located

in LMICs.

DISCUSSION

Main ndings

We aimed to estimate the absolute global number of

war survivors with PTSD and/or MD and the associ-

ated disease burden in countries that experienced

warfare within their own territory between 1989 and

2019. Extrapolation informed by meta- analysis yielded

about 316 million adult survivors of war experiencing

PTSD and/or MD globally. Almost all war survivors of

recent wars reside in LMICs carrying a global accumu-

lated burden of 3 million PTSD- associated DALYs and 4

million MD- associated DALYs.

Strengths and limitation

We estimated the absolute global number of war survivors

with PTSD and/or MD by conducting an up- to- date and

comprehensive systematic literature search. We maxim-

ised validity of extrapolations by only including interview-

based epidemiological data from random general popu-

lation samples. The extrapolations to absolute numbers

may enable professionals from various disciplines to

better grasp the burden of PTSD and MD on survivors

of war and guide decision making to ultimately improve

mental health of survivors.

Our study also has several limitations. The meta-

analyses relied on only 41 surveys. This primarily reflects

the current state of literature on war survivors that has

mostly focused on refugees or other special war- surviving

populations rather than general populations.29 In fact,

HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303 5

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Table 1 Characteristics of eligible epidemiological surveys included in the meta- analysis

Publication Country

Years

since

war*

War- related

deaths

1989–2019†

(per 100.000)

Conict- related

deaths 1989–

2019 ‡

Lengths

of war(s)

in years

1989–2019 N

Random

sampling

technique used

Response

rate in %

PTSD

assessment

Expertise and

training of

interviewers

Quality of

survey in

%§

Ayazi et al53 Sudan 5 51 837

(118.22)

93 133 20 1200 Multistage

random cluster

sampling

95 NA MINI Local health

personnel, 9 days

of training

41.67

Canetti et al54 Palestine 0 1708 (33.48) 1710 1 1196 Stratied

3- stage cluster

random

sampling

62.9 PSS- I NA Trained

interviewers

not otherwise

specied

25.00

de Jong et al55 Algeria 6 18 920

(43.15)

21 153 6 653 Random sample

of population

based on

governmental

registries

76.7 CIDI NA n.r. 25.00

Palestine 0 s.a. s.a. s.a. 585 4- stage random

sampling

strategy

98 CIDI NA n.r. 33.33

Eytan et al56 Kosovo 2 1898 (106.10) 2847 2 996 Random

sampling

from eight

municipalities

93 MINI NA Local

psychosocial

counsellors,

trained by

authors

41.67

Fodor et al57 Rwanda 17 6749 (52.11) 516 805 1 465 Probability

proportional to

size sampling

based on

census data

96 NA MINI Experienced

Rwandan college

graduates,

1 week of training

50.00

Johnson et al58 Liberia 4 3048 (60.26) 23 245 1 1661 Combination

of systematic

random

sampling and

40×40 cluster

sampling

98.2 PSS- I NA Liberian public

health graduates

and community

health workers,

several days of

training

41.67

Johnson et al59 DRC 0 28 637

(31.97)

114 888 7 989 Systematic

cluster sampling

strategy

98.9 PSS- I NA Experienced

Congolese

interviewers,

several days of

training

58.33

Madianos et al60 Palestine 0 s.a. s.a. s.a. 916 Multistage

sample in four

areas of West

Bank

92 SCID SCID Second author

(native to West

Bank), training

through pilot

interviews

50.00

Continued

6HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

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Publication Country

Years

since

war*

War- related

deaths

1989–2019†

(per 100.000)

Conict- related

deaths 1989–

2019 ‡

Lengths

of war(s)

in years

1989–2019 N

Random

sampling

technique used

Response

rate in %

PTSD

assessment

Expertise and

training of

interviewers

Quality of

survey in

%§

Morina and Ford61 Kosovo 6 s.a. s.a. s.a. 102 Random sample

of civilians,

random walk

technique

81 MINI MINI Psychology

students trained

by the rst author

25.00

Morina et al62 Kosovo 6 s.a. s.a. s.a. 84 Random walk

technique in the

region of Drenica

90 MINI NA Psychology

students trained

by the rst author

41.67

Morina et al63 Kosovo 8 s.a. s.a. s.a. 163 Random walk

technique in

different regions

90.1 MINI MINI Psychology

students trained

by the rst author

31.25

Mugisha et al64 Uganda 7 9970 (21.80) 17 034 3 2361 Multistage

sampling,

random

selection

of parishes

from selected

subcounties

n.r. MINI MINI Psychiatric

nurses trained for

this study

18.75

Munyandamutsa

et al65

Rwanda 14 s.a. s.a. s.a. 962 Multistage

random

sampling

procedure

n.r. MINI MINI Psychologists,

social workers

and physicians,

20 hours of

training

18.75

Priebe et al66 Croatia 13 3091 (31.98) 1478 1 727 Multistage

probabilistic

sampling frame

and random-

walk technique

70 MINI MINI Trained

mental health

professionals or

trainees

31.25

Kosovo 8 s.a. s.a. s.a. 648 Multistage

probabilistic

sampling frame

and random-

walk technique

91 MINI MINI Trained

mental health

professionals or

trainees

43.75

Serbia 13 5806 (66.45) 7267 3 637 Multistage

probabilistic

sampling frame

and random-

walk technique

70.1 MINI MINI Trained

mental health

professionals or

trainees

31.25

Bosnia and Herze-

govina

13 13 440

(409.65)

26 333 4 640 Multistage

probabilistic

sampling frame

and random-

walk technique

85 MINI MINI Trained

mental health

professionals or

trainees

43.75

Table 1 Continued

Continued

HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303 7

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Publication Country

Years

since

war*

War- related

deaths

1989–2019†

(per 100.000)

Conict- related

deaths 1989–

2019 ‡

Lengths

of war(s)

in years

1989–2019 N

Random

sampling

technique used

Response

rate in %

PTSD

assessment

Expertise and

training of

interviewers

Quality of

survey in

%§

Rieder et al67 Rwanda 16 s.a. s.a. s.a. 172 Random

sampling in

Muhanga district

n.r. PSS- I NA Experienced local

bachelor- level

psychologists

16.67

Rugema et al68 Rwanda 17 s.a. s.a. s.a. 917 Two- stage

random

sampling

99.8 MINI MINI Experienced

clinical

psychologists,

several days of

training

31.25

Schaal et al69 ** Rwanda 15 s.a. s.a. s.a. 112 Random

community

sample of Butare

and Kigali

97 PSS- I NA Masters- level

and clinical

psychologists,

extensive

previous training

41.67

Somasundaram and

Sivayokan70

Sri Lanka 4 61 265

(286.11)

65 628 15 98 Random

sampling

procedure in a

suburb of Jaffna

97 SIQ SIQ Trained medical

students

31.25

Veling et al71 DRC 0 s.a. s.a. s.a. 93 Balanced

sampling to

12 quarters of

Bunia

n.r. CIDI NA Trained local

interviewers

25.00

Yasan et al72 Turkey 9.8 26 981

(31.99)

28 611 9 708 Random

sampling of

regions in

Diyarbakir,

proportionate

sample of

residents

98.3 CAPS NA Final- year

psychology

students trained

by psychiatry

professors

41.67

Summary (ie, sum or

weighted/unweighted

mean (SD) or most

prevalent option)

countries+Palestine

from 3 continents

6.88

(5.88)

Total: 17 813

(18 807)¶

Per 100.000:

99.48

(112.16)

70 779 (133,300)¶ 3.92 (4.83)¶ 17 085 (Multistage)

random

sampling

procedure

88.91

(11.10)

MINI MINI Mental health

professionals

with specic

training for the

used interview

34.92

(10.94)

*Timespan in years between the end of war and the time the respective survey was conducted.

†Number of war- related death (ie, state- based violence) in the respective country with a history of war between 1989 and 2019 as dened by Uppsala Conict Data Programme (UCDP).5 Retrieved from: https://ucdp.uu.se/.

‡Number of all conict- related death (ie, state- based violence+non- state violence+one- sided violence) in the respective country with a history of war between 1989 and 2019 as dened by the UCDP.

§As assessed with Strengthening the Reporting of Observational Studies in Epidemiology criteria.11

¶To calculate these unweighted means and SDs, country- specic data were considered once per country.

**Only representative sample included.

CAPS, Clinician- Administered PTSD Scale; CIDI, Composite International Diagnostic Interview; DRC, Democratic Republic of Congo; MD assessment, used (semi- )structured interview based on Diagnostic and Statistical

Manual of Mental Disorders (DSM) or International Statistical Classication of Diseases (ICD) diagnostic criteria to assess major depression; MINI, Mini International Neuropsychiatric Interview; n, included amount of

subjects in the given survey; NA, not applicable; n.r., not reported; PSS- I, Post- traumatic Symptom Scale Interview; PTSD assessment, used (semi- )structured interview based on Diagnostic and Statistical Manual of Mental

Disorders (DSM) or International Statistical Classication of Diseases (ICD) diagnostic criteria to assess post- traumatic stress disorder; s.a., see intensity/lengths of war for the respective country above; SCID, Structured

Clinical Interview for DSM- IV; SIQ, Stress Impact Questionnaire.

Table 1 Continued

8HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

BMJ Global Health

the current literature base on interview- based randomly

sampled surveys covers only 12 countries (and Palestine)

and for the remaining 30 war- affected countries such

samples are currently lacking. Therefore, our summary

of the available literature might not be generalisable to

countries with lacking data. On the notion of generalis-

ability to countries with lacking data, it is worthwhile to

check whether countries with available data may differ

from countries without such data in terms of war- intensity.

As can be seen in table 1, countries with available data

bewailed on average 17 813 war- related deaths from

1989 to 2019 (SD=18 807) which translates into 99.48

war- related deaths per 100.000 population (SD=112.16).

Whereas countries with missing data on average bewailed

40 042 (SD=71 980) or 183.17 per 100.000 population

(SD=339.65). Across all 43 war- afflicted countries, an

average of 33 322 (SD=61 593) individuals or 155.97 per

100.000 (SD=288.95) died due to war events. This demon-

strates that the war- afflicted countries with available data

are somewhat below average in terms of war- intensity.

The performed moderator analyses did not yield signifi-

cant differences in prevalence rates across 12 war- affected

countries (plus Palestine) despite varying degrees of war-

intensity and war- length (see online supplemental eTable

2). This finding may be unexpected, since higher inten-

sity of trauma has been shown to relate to higher risk and

prevalences of PTSD generally30 and also in the context

of war trauma31 and genocide such as the Holocaust.32

Therefore, the results of this moderator analysis should

be interpreted with caution as a dose–response relation-

ship between war intensity and prevalences of trauma-

related disorders appears plausible.31

Also related to the issue of limited data and generalis-

ability, extrapolative accuracy is naturally restrained. Due

Figure 2 Forest plots for point prevalence of post- traumatic stress disorder (top) and major depression (bottom).

HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303 9

BMJ Global Health

Table 2 Extrapolation to absolute prevalence and associated disease burden, as measured by DALYs

Country

Last war-

affected

year for the

given country

(1989–2019)

Total

population

of adult war

survivors (2019)

Absolute prevalence of war survivors with

PTSD (95% CI)

PTSD-

associated

DALYs

Absolute prevalence of war survivors

with MD (95% CI)

MD-

associated

DALYs

Absolute prevalence of war survivors

with PTSD+MD

El Salvador 1989 2 483 500 658 376 (550 592 to 772 369) 10,262 578 904 (460 689 to 705 811) 12 636 319 902 (243 776 to 393 944)

Mozambique 1991 6 686 071 1 772 477 (1 482 302 to 2 079 368) 20 387 1 558 523 (1 240 266 to 1 900 181) 30 377 861 240 (656 294 to 1 060 575)

Kuwait 1991 2 317 732 614 431 (513 841 to 720 815)11 450 540 263 (429 939 to 658 699)16 877 298 550 (227 505 to 367 649)

Croatia 1991 2 581 667 684 400 (572 356 to 802 898)10 251 601 787 (478 899 to 733 710)13 836 332 547 (253 412 to 409 516)

Myanmar 1992 22 181 071 5 880 202 (4 917 543 to 6 898 313) 86 017 5 170 408 (4 114 589 to 6 303 860) 36 527 2 857 167 (2 177 259 to 3 518 462)

Peru 1992 14 322 678 3 796 942 (3 175 338 to 4 454 353) 80 362 3 338 616 (2 656 857 to 4 070 505) 39 573 1 844 919 (1 405 891 to 2 271 928)

Georgia 1993 2 464 257 653 275 (546 326 to 766 384) 5 733 574 418 (457 120 to 700 342) 12 726 317 424 (241 888 to 390 892)

Azerbaijan 1994 5 508 694 1 460 355 (1 221 277 to 1 713 204) 13 963 1 284 077 (1 021 863 to 1 565 571) 19 722 709 581 (540 725 to 873 814)

Bosnia-

Herzegovina

1995 2 236 056 592 778 (495 734 to 695 413) 8 519 521 225 (414 788 to 635 487) 9 678 288 029 (219 488 to 354 693)

Tajikistan 1996 3 523 143 933 985 (781 081 to 1 095 697) 7757 821 245 (653 543 to 1 001 277) 10 380 453 820 (345 826 to 558 857)

Congo 1998 2 191 526 580 974 (485 861 to 681 565) 7030 510 845 (406 528 to 622 832) 15,489 282 293 (215 117 to 347 630)

Serbia 1999 6 352 650 1 684 088 (1 408 383 to 1 975 674) 22 395 1 480 803 (1 178 417 to 1 805 423) 28 139 818 292 (623 566 to 1 007 686)

Algeria 1999 24 441 969 6 479 566 (5 418 785 to 7 601 452) 108 133 5 697 423 (4 533 985 to 6 946 408) 147 708 3 148 396 (2 399 185 to 3 877 096)

Sierra Leone 1999 3 129 883 829 732 (693 895 to 973 394) 10 829 729 576 (580 593 to 889 513) 15 341 403 164 (307 224 to 496 476)

Kosovo 1999 915 361 242 662 (202 936 to 284 677) NA 213 371 (169 799 to 260 146) NA 117 909 (89 850 to 145 199)

Ethiopia 2000 44 350 185 11 757 234 (9 832 436 to 13 792 908) 121 905 10 338 028 (8 226 959 to 12,604,323) 194 816 5 712 794 (4 353 344 to 7 035 028)

Eritrea 2000 1 428 785 378 771 (316 763 to 444 352) 8 864 333 050 (265 040 to 406 061) 14 143 184 043 (140 247 to 226 640)

Angola 2001 11 202 755 2 969 850 (2 483 651 to 3 484 057) 33 302 2 611 362 (2 078 111 to 3 183 823) 68 513 1 443 039 (1 099 645 to 1 777 032)

Burundi 2002 5 293 042 1 403 185 (1 173 467 to 1 646 136) 15 802 1 233 808 (981 859 to 1 504 283) 24 527 681 802 (519 557 to 839 606)

Liberia 2003 2 463 836 653 163 (546 232 to 766 253) 7550 574 320 (457 042 to 700 222) 11 837 317 369 (241 846 to 390 825)

Uganda 2004 19 435 624 5 152 384 (4 308 878 to 6 044 479) 57 787 4 530 444 (3 605 308 to 5 523 604) 122 373 2 503 523 (1 907 770 to 3 082 967)

Russia

(regional)

2004 959 727 254 424 (212 771 to 298 475) 3091 223 712 (178 029 to 272 754) 4,676 123 623 (94 205 to 152 236)

India (regional) 2005 53 366 769 14 147 530 (11 831 413 to 16 597 065) 152 752 12 439 794 (9 899 536 to 15 166 836) 265 286 6 874 230 (5 238 397 to 8 465 280)

Colombia 2005 35 348 853 9 370 981 (7 836 841 to 10 993 493) 156 309 8 239 818 (6 557 212 to 10 046 144) 102 122 4 553 323 (3 469 787 to 5 607 196)

Nepal 2005 17 553 695 4 653 485 (3 891 654 to 5 459 199) 55 365 4 091 766 (3 256 210 to 4 988 760) 125 913 2 261 110 (1 723 043 to 2 784 447)

Chad 2006 6 934 582 1 838 358 (1 537 397 to 2 156 655) 19 251 1 616 451 (1 286 365 to 1 970 808) 33 647 893 251 (680 688 to 1 099 995)

Rwanda 2009 7 004 398 1 856 866 (1 552 875 to 2 178 368) 22 281 1 632 725 (1 299 316 to 1 990 650) 40 235 902 244 (687 541 to 1 111 069)

Sri Lanka 2009 15 326 238 4 062 986 (3 397 827 to 4 766 460) 63 630 3 572 546 (2 843 017 to 4 355 717) 50 174 1 974 189 (1 504 399 to 2 431 118)

Israel (regional) 2014 5 840 055 1 548 199 (1 294 740 to 1 816 257) 22 332 1 361 317 (1 083 330 to 1 659 744) 39 874 752 264 (573 251 to 926,376)

South Sudan 2014 5 828 199 1 545 056 (1 292 112 to 1 812 570) 19 525 1 358 553 (1 081 131 to 1 656 374) 22 909 750 736 (572 087 to 924 495)

Pakistan 2015 130 645 594 34 634 147 (28 964 128 to 40 630 780) 382 665 30 453 488 (24 234 758 to 37 129 478) 581 982 16 828 597 (12 823 964 to 20 723 599)

Continued

10 HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

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Country

Last war-

affected

year for the

given country

(1989–2019)

Total

population

of adult war

survivors (2019)

Absolute prevalence of war survivors with

PTSD (95% CI)

PTSD-

associated

DALYs

Absolute prevalence of war survivors

with MD (95% CI)

MD-

associated

DALYs

Absolute prevalence of war survivors

with PTSD+MD

Ukraine

(regional)

2015 9 172 307 2 431 579 (2 033 500 to 2 852 587) 30 410 2 138 065 (1 701 463 to 2 606 770) 68 580 1 181 495 (900 339 to 1 454 953)

Sudan 2016 23 446 328 6 215 622 (5 198 051 to 7 291 808) 98 386 5 465 339 (4 349 294 6 663 446) 132 072 3 020 146 (2 301 454 to 3 719 163)

Turkey 2016 60 057 715 15 921 300 (13 314 795 to 18 677 949) 267 749 13 999 453 (11 140 706 to 17 068 403) 378 125 7 736 098 (5 895 170 to 9 526 628)

Iraq 2017 70 339 201 18 646 922 (15 594 201 to 21 875 492) 384 721 16 396 068 (13 047 922 to 19 990 401) 409 203 9 060 467 (6 904 384 to 11 157 524)

Philippines 2017 42 632 563 11 301 892 (9 451 639 to 13 258 727) 184 410 9 937 650 (7 908 340 to 12 116 174) 121 384 5 491 546 (4 184 745 to 6 762 571)

DR Congo 2018 22 520 461 5 970 174 (4 992 786 to 7 003 863) 71 413 5 249 519 (4 177 546 to 6 400 315) 144 335 2 900 884 (2 210 573 to 3 572 298)

Afghanistan 2019 19 791 367 5 246 691 (4 387 746 to 6 155 115) 83 888 4 613 368 (3 671 299 to 5 624 707) 119 476 2 549 347 (1 942 689 to 3 139 397)

Somalia 2019 7 433 691 1 970 671 (1 648 049 to 2 311 878) 24 977 1 732 793 (1 378 950 to 2 112 655) 43 406 957 542 (729 679 to 1 179 166)

Yemen 2019 16 284 148 4 316 928 (3 610 196 to 5 064 370) 76 436 3 795 835 (3 020 709 to 4 627 955) 113 562 2 097 578 (1 598 426 to 2 583 066)

Libya 2019 4 619 825 1 224 716 (1 024 215 to 1 436 766) 24 878 1 076 881 (856 978 to 1 312 954) 34 089 595 085 (453 475 to 732 818)

Syria 2019 11 163 348 2 959 404 (2 474 914 to 3 471 801) 51 859 2 602 176 (2 070 801 to 3 172 624) 58 620 1 437 963 (1 095 776 to 1 770 781)

Nigeria 2019 102 874 311 27 271 980 (22 807 235 to 31 993 911) 282 463 23 980 002 (19 083 185 to 29 236 879) 379 778 13 251 349 (10 097 979 to 16 318 391)

Total n.a. 854 653 860 226 568 738 (189 476 761 to 265 797 350) 3 127 089 199 219 815(158 538 291 to 242 892 627) 4 114 663 110 088 870 (83 891 464 to 135 569 084)

LMICs only

total

n.a. 849 754 461 225 269 908 (188 390 564 to 264 273 637) 3 105 387 198 077 765 (157 629 453 to 241 500 218) 4 083 950 109 457 773 (83 410 547 to 134 791 919)

Bold indicates that the respective war- affected country is a high- income country.

DALYs, disability- adjusted life years; LB, lower bound; MD, major depression; NA, data on Kosovo not available; n.a., not applicable; PTSD, post- traumatic stress disorder; UB, upper bound.

Table 2 Continued

HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303 11

BMJ Global Health

to the general scarcity of data, we had to rely on pooled

prevalences of PTSD and MD for extrapolations. In the

light of varying degrees of war intensity and lengths as

well as more general country- specific differences, such

an approach is limited. However, the CIs for the pooled

PTSD and MD prevalences were fairly narrow (22.17%

to 31.10% and 18.55% to 28.42%, respectively) indi-

cating fairly similar prevalences of PTSD and MD across

the included surveys from 12 war- affected countries (plus

Palestine) from three continents. Similarly, the moder-

ator analysis on pooled prevalences by continent did not

yield significant differences in PTSD prevalences across

the three war- afflicted continents (ie, Africa, Asia and

Europe). Surveys on MD were too scarce to allow for

this moderator analysis. As more data accumulates, more

fine- grained meta- analyses and, consequently, more fine-

grained extrapolations will become possible.

Another potential limitation is that the current liter-

ature base exclusively covers cross- sectional surveys and

lacks longitudinal data on remission from PTSD and MD.

In their summary of the World Mental Health (WMH)

Surveys, Kessler et al reported that remission of war-

related PTSD would steeply increase about 6 years after

exposure. The remission rate was reported to rise from

about 20% at 5 years after war to about 70% at 6 years

after war.33 In our review, the mean time between war and

the assessment of disorders across all included surveys

was 6.88 years. In our moderator analyses (see online

supplemental eTable 2), the number of years between

the end of the (last) war and the conduct of the survey

was not found to be related to prevalence rates. This

finding is at odds with previous research as illustrated by

the above- mentioned summary of the WMH surveys. Yet,

several factors might explain why remission rates may be

dampened in post- war settings. Besides war- trauma, non-

war- related traumatic experiences and difficult socioeco-

nomic conditions may also influence the development

and maintenance of PTSD and MD.34 35 Socioeconomic

risk factors are more prevalent in LMICs with a history

of war as compared with the countries included in the

WHM surveys which were mostly high- income countries.

Furthermore, individuals with mental disorders in LMICs

are less likely to receive appropriate healthcare,36–38 and

PTSD as well as MD, if left untreated, may follow a chronic

course.39 40 However, while remission rates post- conflict

might be dampened in war- ridden LMICs for various

reasons, a degree of remission is still to be expected

particularly over several decades as illustrated by long-

term epidemiological data on WWII survivors.41–43 There-

fore, null findings more probably boil down to a lack of

longer- term data rather than lacking remissions per se.

Another potential limitation concerns heterogeneity

in outcomes based on different nosology. We included

surveys that conducted diagnostic interviews based on

any ICD or DSM iteration, which use different criteria for

defining PTSD and MD. Finally, this study estimates the

disease burden for PTSD. Since the GBD 2019 does not

report on PTSD DALYs separately, all anxiety disorder

DALYs had to be used. The presented estimate, therefore,

may overestimate or underestimate the PTSD- associated

DALYs. The GBD study has already announced that it

will report data on PTSD separately in coming iterations,

which will allow for more accurate extrapolations.

Comparison with the literature

The pooled PTSD and MD prevalences are slightly

lower than reported prevalences in most meta- analyses

on these conditions in war- surviving populations (ie,

≥30%).3 4 29 In our previous meta- analyses, we found

similarly high prevalences (ie, 24%–26% for PTSD and

23%–27% for MD).2 6 However, recent estimates by the

WHO are considerably lower with 15.3% for PTSD and

10.8% for MD.1 As mentioned before, all previous meta-

analyses partly or exclusively involved specific popula-

tions (eg, refugees, bereaved individuals) and precluded

extrapolations to general war- surviving. Furthermore,

related meta- analyses included self- report- based data.1

Self- report- based measures of PTSD (eg, PTSD CheckList

– Civilian Version) and MD (eg, Patient Health Question-

naire – 9) either are not validated for LMICs or have poor

psychometric properties in LMICs.44 To our knowledge,

we performed the first meta- analysis that exclusively

included representative interview- based data and, there-

fore, allowed for more valid extrapolations. We aimed at

estimating the absolute prevalence and disease burden

of PTSD and MD in war- afflicted countries, irrespective

of assumptions about their aetiology. The elevated prev-

alences of PTSD and MD in war- surviving populations

are not to be mistaken as solely caused by war- related

trauma. The aetiologies of PTSD and MD are complex

and, besides war experiences, non- war- related traumatic

experiences, psychological stressors and aversive social

conditions can play a role in the development and main-

tenance of PTSD and MD. However, independently of

the precise aetiology of the disorders, the reported preva-

lences reflect the extent of the total burden and the need

for help due to PTSD and MD in war- surviving popula-

tions.

Clinical, policy and research implications

In theory, effective psychological interventions for

both youth and adult survivors of mass conflict do

exist.38 45 However, most LMICs lack the resources in

terms of both funding and qualified staff to provide

evidence- based psychological treatments for all affected

war survivors.36 37 46 While the allocation of financial and

human resources for mental healthcare should surely

increase,36 47 other approaches than specialised treat-

ments are needed to address the mental health needs of

survivors of war. For this, mental healthcare should be

as much as possible integrated into the overall response

to healthcare following wars. This may include strength-

ening of primary care to address mental disorders in

primary care, task- sharing of psychosocial interventions

with trained non- professional individuals, involving

families and informal carers, using digital platforms to

12 HoppenTH, etal. BMJ Global Health 2021;6:e006303. doi:10.1136/bmjgh-2021-006303

BMJ Global Health

facilitate the delivery of interventions, and the develop-

ment and implementation of community- based inter-

ventions.48–52 All these options may benefit from more

systematic research to inform public health policies and

practice.

CONCLUSIONS

The effects of exposure to war place a large mental health

burden on the affected countries. An extrapolation from

relative prevalence of PTSD and MD to absolute numbers

suggests that hundreds of millions adult war survivors

globally are affected. Countries with a recent history of

war are almost exclusively LMICs. These countries lack

the resources to provide specialised treatments for most

of the affected war survivors. Therefore, alternative strat-

egies—such as low- cost and technology- based interven-

tions that build on existing resources—should be brought

forward to meet the high burden of war- related mental

disorders. The presented results generally illustrate the

importance of peace- building and maintenance.

Twitter Thole H Hoppen @HoppenDr

Contributors THH and NM designed the study. THH and IV conducted the

systematic literature search and data extraction. THH conducted the statistical

analyses. THH wrote the manuscript. NM, SP and IV commented on and contributed

to the manuscript.

Funding The authors have not declared a specic grant for this research from any

funding agency in the public, commercial or not- for- prot sectors.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement All data analysed in this meta- analysis and in the

extrapolations is published and publically available.

Supplemental material This content has been supplied by the author(s). It has

not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been

peer- reviewed. Any opinions or recommendations discussed are solely those

of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and

responsibility arising from any reliance placed on the content. Where the content

includes any translated material, BMJ does not warrant the accuracy and reliability

of the translations (including but not limited to local regulations, clinical guidelines,

terminology, drug names and drug dosages), and is not responsible for any error

and/or omissions arising from translation and adaptation or otherwise.

Open access This is an open access article distributed in accordance with the

Creative Commons Attribution Non Commercial (CC BY- NC 4.0) license, which

permits others to distribute, remix, adapt, build upon this work non- commercially,

and license their derivative works on different terms, provided the original work is

properly cited, appropriate credit is given, any changes made indicated, and the

use is non- commercial. See:http:// creativecommons. org/ licenses/ by- nc/ 4. 0/.

ORCID iD

Thole HHoppen http:// orcid. org/ 0000- 0002- 6050- 8696

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Supplemental content

eList 1. Search Strategy

eTable 1. Quality Assessment

eFigure 1. Funnel Plot – Meta-analysis on PTSD Point Prevalences

eFigure 2. Funnel Plot – Meta-analysis on MD Point Prevalences

eFigure 3. Forest Plot – Meta-analysis on Comorbidity Point Prevalences (PTSD + MD)

eTable 2. Moderator Results

BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance

Supplemental material placed on this supplemental material which has been supplied by the author(s) BMJ Global Health

doi: 10.1136/bmjgh-2021-006303:e006303. 6 2021;BMJ Global Health, et al. Hoppen TH

eList 1. Search Strategy

1) Depression (TI depress* OR AB depress* OR SU depress*) OR (TI MDD OR AB

MDD OR SU MDD)

2) PTSD (TI posttraumatic stress OR AB posttraumatic stress OR SU posttraumatic

stress) OR (TI post-traumatic stress OR AB post-traumatic stress OR SU post-traumatic

stress) OR (TI posttraumatic syndrome* OR AB posttraumatic syndrome* OR SU

posttraumatic syndrome*) OR (TI post-traumatic syndrome* OR AB post-traumatic

syndrome* OR SU post-traumatic syndrome*) OR (TI PTSD OR AB PTSD OR SU

PTSD)

3) General mental health (TI mental health OR AB mental health OR SU mental

health) OR (TI mental disorders OR AB mental disorders OR SU mental disorders)

4) War survivors (TI genocide OR AB genocide OR SU genocide ) OR ( TI holocaust

OR AB holocaust OR SU holocaust) OR (TI war* OR AB war* OR SU war*) OR (TI

mass conflict* OR AB mass conflict* OR SU mass conflict*) OR (TI post-conflict*

OR AB post-conflict* OR SU post-conflict*) OR (TI political conflict* OR AB political

conflict* OR SU political conflict*) OR (TI armed conflict* OR AB armed conflict*

OR SU armed conflict*) OR (TI terrorism OR AB terrorism OR SU terrorism) OR (TI

torture OR AB torture OR SU torture) OR (TI persecution OR AB persecution OR SU

persecution) OR (TI civilian* OR AB civilian* OR SU civilian*) OR (TI ethnic

cleansing OR AB ethnic cleansing OR SU ethnic cleansing)

Combined search (TI OR AB OR SU): 1 OR 2 OR 3 AND 4

BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance

Supplemental material placed on this supplemental material which has been supplied by the author(s) BMJ Global Health

doi: 10.1136/bmjgh-2021-006303:e006303. 6 2021;BMJ Global Health, et al. Hoppen TH

eTable 1. Quality Assessment

Bias type

High quality (score=2)

Moderate quality (score=1)

Poor quality (score=0)

1. Selection (sample

population)

Random or probability sampling

Special population (all shared something in common, e.g. torture)

Mixed sampling (convenience sampling, snowballing, advertisement, non-

randomized etc.)

Sample selection ambiguous and sample

unlikely to be representative.

2. Selection (participation rate)

High response rate (>85%).

Moderate response rate (70–85%).

Low response rate (<70%) or not reported

3a. Reported psychometric quality

of PTSD measurement:

language in which it is used in this

study

High (good results on validity and reliability

reported)

Medium (only reliability data provided, yet no data on validity; or psychometric data

are in the medium range, e.g., reliability lower than 0.70)

No report, or

Low (e.g., only internal consistency reported; or

general statement that psychometrics are good)

4a. Reported psychometric quality

of PTSD measurement:

for original version of instrument if

in different language (e.g. English)

High (good results on validity and reliability

reported)

Medium (only reliability data provided, yet no data on validity; or psychometric data

are in the medium range, e.g., reliability lower than 0.70)

No report, or

Low (e.g., only internal consistency reported; or

general statement that psychometrics are good)

3b. Reported psychometric quality

of MD measurement:

language in which it is used in this

study

High (good results on validity and reliability

reported)

Medium (only reliability data provided, yet no data on validity; or psychometric data

are in the medium range, e.g., reliability lower than 0.70)

No report, or

Low (e.g., only internal consistency reported; or

general statement that psychometrics are good)

4b. Reported psychometric quality

of MD measurement:

for original version of instrument if

in different language (e.g. English)

High (good results on validity and reliability

reported)

Medium (only reliability data provided, yet no data on validity; or psychometric data

are in the medium range, e.g., reliability lower than 0.70)

No report, or

Low (e.g., only internal consistency reported; or

general statement that psychometrics are good)

BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance

Supplemental material placed on this supplemental material which has been supplied by the author(s) BMJ Global Health

doi: 10.1136/bmjgh-2021-006303:e006303. 6 2021;BMJ Global Health, et al. Hoppen TH

5. Training in the use of the

psychiatric interview

High quality in training:

interviewers were extensively trained by

experienced professionals while applying the

interview in question with potential study

participants

Moderate quality in training:

interviewers were trained by experienced professionals but no interview sessions

with potential study participants were applied or reported

Low quality in training:

No training was used or reported

6. Interrater-reliability (IRR)

High IRR (>85%).

Moderate IRR (70–85%).

No IRR reported, or

Low IRR (<70%).