Devakumar et al. Confl Health (2021) 15:74 https://doi.org/10.1186/s13031-021-00410-4 R E S E A R C H Mental health of women and children experiencing family violence in conflict settings: a mixed methods systematic review Delan Devakumar1*, Alexis Palfreyman1, Amaran Uthayakumar‑Cumarasamy2, Nazifa Ullah3, Chavini Ranasinghe3, Nicole Minckas1, Abhijit Nadkarni4,5, Sian Oram6, David Osrin1 and Jenevieve Mannell1 Abstract Background: Armed conflict has significant impacts on individuals and families living in conflict‑affected settings globally. Scholars working to prevent violence within families have hypothesised that experiencing armed conflict leads to an increase in family violence and mental health problems. In this review, we assessed the prevalence of family violence in conflict settings, its association with the mental health of survivors, moderating factors, and the importance of gender relations. Methods: Following PRISMA guidelines, we systematically reviewed quantitative and qualitative studies that assessed the prevalence of family violence and the association between family violence and mental health problems, within conflict settings (PROSPERO reference CRD42018114443). Results: We identified 2605 records, from which 174 full text articles were screened. Twenty‑nine studies that reported family violence during or up to 10 years after conflict were eligible for inclusion. Twenty one studies were quantitative, measuring prevalence and association between family violence and mental health problems. The stud‑ ies were generally of high quality and all reported high prevalence of violence. The prevalence of violence against women was mostly in the range of 30–40%, the highest reported prevalence of physical abuse being 78.9% in Bosnia and Herzegovina. For violence against children, over three‑quarters had ever experienced violence, the highest preva‑ lence being 95.6% in Sri Lanka. Associations were found with a number of mental health problems, particularly post‑ traumatic stress disorder. The risk varied in different locations. Eight qualitative studies showed how men’s experience of conflict, including financial stresses, contributes to their perpetration of family violence. Conclusions: Family violence was common in conflict settings and was associated with mental health outcomes, but the studies were too heterogenous to determine whether prevalence or risk was greater than in non‑conflict settings. The review highlights an urgent need for more robust data on perpetrators, forms of family violence, and mental health outcomes in conflict‑affected settings in order to help understand the magnitude of the problem and identify potential solutions to address it. © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you giv ...

1. Devakumar et al. Confl Health (2021) 15:74
https://doi.org/10.1186/s13031-021-00410-4
R E S E A R C H
Mental health of women and children
experiencing family violence in conflict settings:
a mixed methods systematic review
Delan Devakumar1*, Alexis Palfreyman1, Amaran
Uthayakumar‑ Cumarasamy2, Nazifa Ullah3,
Chavini Ranasinghe3, Nicole Minckas1, Abhijit Nadkarni4,5,
Sian Oram6, David Osrin1 and Jenevieve Mannell1
Abstract
Background: Armed conflict has significant impacts on
individuals and families living in conflict‑ affected settings
globally. Scholars working to prevent violence within families
have hypothesised that experiencing armed conflict
leads to an increase in family violence and mental health
problems. In this review, we assessed the prevalence of
family violence in conflict settings, its association with the
mental health of survivors, moderating factors, and the
importance of gender relations.
Methods: Following PRISMA guidelines, we systematically
reviewed quantitative and qualitative studies that
assessed the prevalence of family violence and the association
between family violence and mental health problems,
within conflict settings (PROSPERO reference
CRD42018114443).
Results: We identified 2605 records, from which 174 full text

2. articles were screened. Twenty‑ nine studies that
reported family violence during or up to 10 years after conflict
were eligible for inclusion. Twenty one studies were
quantitative, measuring prevalence and association between
family violence and mental health problems. The stud‑
ies were generally of high quality and all reported high
prevalence of violence. The prevalence of violence against
women was mostly in the range of 30–40%, the highest reported
prevalence of physical abuse being 78.9% in Bosnia
and Herzegovina. For violence against children, over
three‑ quarters had ever experienced violence, the highest
preva‑
lence being 95.6% in Sri Lanka. Associations were found with a
number of mental health problems, particularly post‑
traumatic stress disorder. The risk varied in different locations.
Eight qualitative studies showed how men’s experience
of conflict, including financial stresses, contributes to their
perpetration of family violence.
Conclusions: Family violence was common in conflict settings
and was associated with mental health outcomes,
but the studies were too heterogenous to determine whether
prevalence or risk was greater than in non‑ conflict
settings. The review highlights an urgent need for more robust
data on perpetrators, forms of family violence, and
mental health outcomes in conflict‑ affected settings in order to
help understand the magnitude of the problem and
identify potential solutions to address it.
© The Author(s) 2021. Open Access This article is licensed
under a Creative Commons Attribution 4.0 International
License, which
permits use, sharing, adaptation, distribution and reproduction
in any medium or format, as long as you give appropriate credit
to the
original author(s) and the source, provide a link to the Creative

3. Commons licence, and indicate if changes were made. The
images or
other third party material in this article are included in the
article’s Creative Commons licence, unless indicated otherwise
in a credit line
to the material. If material is not included in the article’s
Creative Commons licence and your intended use is not
permitted by statutory
regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy
of this
licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
The Creative Commons Public Domain Dedication waiver
(http:// creat iveco
mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data
made available in this article, unless otherwise stated in a credit
line to the data.
Introduction
Rates of family violence and mental ill health are hypoth-
esised to be higher in areas of armed conflict than in
non-conflict-affected settings [1], but the extent of the
risks and their associations have not been systematically
assessed.
Open Access
*Correspondence: [email protected]
1 Institute for Global Health, University College London,
London WC1N
1EH, UK
Full list of author information is available at the end of the
article
http://creativecommons.org/licenses/by/4.0/
http://creativecommons.org/publicdomain/zero/1.0/

4. http://creativecommons.org/publicdomain/zero/1.0/
http://crossmark.crossref.org/dialog/?doi=10.1186/s13031-021-
00410-4&domain=pdf
Page 2 of 19Devakumar et al. Confl Health (2021) 15:74
Family violence, including violence against women
(VAW) from intimate partners or other household mem-
bers and violence against children, is prevalent across
the world and has adverse implications for physical and
mental health [2]. The WHO multi-country study on
women’s health and domestic VAW, showed that lifetime
prevalence of physical and sexual abuse by an intimate
partner ranges from 15 to 71% [3]. Rates of child abuse
vary by type of abuse, definition and location. ‘Base-case
estimates’ from 96 countries suggested at least 50% prev-
alence of exposure to violence in the last year, equating to
approximately 500 million children aged 2–17 years [4].
A systematic review of 55 studies estimated the preva-
lence of sexual violence to be 8–31% in girls and 3–17%
in boys [5]. Sexual violence in particular is associated
with a long-term increased risk of mental and physical
illness [6].
Reports from conflict settings indicate increased rates
of VAW and physical and sexual abuse of children by
both men and women [7–9]. For example, in a study of
child soldiers from Sierra Leone, 44% reported having
been raped [10]. There are a number of possible reasons
for this. The social and economic conditions that lead to
conflict at a societal level may also result in increases in
family violence. Catani et al. propose that the ‘cycle of
violence’ model, in which violence is transmitted inter-
generationally within a family [11], can also apply to
conflict situations in which external violence leads to vio-

5. lence within the family [12]. The mechanisms by which
this may occur are multiple. Conflict may normalise vio-
lence in a society, increase substance abuse, and affect
education, income, family composition, and gender atti-
tudes [13–15].
In addition to violence, mental disorders are common
in conflict, due to both the conflict itself and the family
violence. Women and children living in conflict-affected
settings are at increased risk of developing depressive,
anxiety, and psychotic disorders [16, 17]. The prevalence
of mental disorders in conflict-affected populations is
substantially higher than in the average population: 15.4%
for post-traumatic stress disorder (PTSD) and 17.3% for
depression, versus 7.6% for any anxiety disorder includ-
ing PTSD and 5.3% for any mood disorder including
depressive disorders [18, 19].
There remains a gap in knowledge on the prevalence of
family violence in conflict-affected areas and its mental
health consequences. Greater understanding is needed
of why and how family violence may result in an increase
in mental disorders in conflict-exposed populations.
This review was designed to explicitly investigate links
between family violence occurring at an individual level
(within families), and broader forms of violent armed
conflict occurring within communities. We included
both quantitative and qualitative research to both enu-
merate the problem and explore the reasons why armed
conflict is associated with mental ill-health, expanding
our conceptual understanding of the underlying causes.
Our review had four objectives. First, to investigate the
prevalence of family violence, including violence against
women and children, in conflict-affected areas. Second,
to describe the risk of mental disorder among women

6. and children who had experienced or witnessed family
violence in conflict-affected areas. Third, to examine how
the association of family violence with mental health in
women and children is moderated by the type of conflict,
the gender of the perpetrator, and the type of violence.
Finally, to understand the ways in which gender rela-
tions, as a well-recognised risk factor for violence against
women and children [20], influence the mental health of
women and children who experience or witness family
violence.
Methods
Design
We conducted a mixed-methods systematic review. The
protocol was registered prospectively with PROSPERO
(CRD42018114443) and reporting follows PRISMA
guidelines [21].
Search strategy
We searched the following databases: EMBASE, Inter-
national Bibliography of Social Sciences, MEDLINE
(PubMed), PsycINFO, Scopus, SciELO, Social Policy
and Practice, Sociology database, Global Index Medi -
cus, Online Library of Dignity, Web of Science, Cochrane
Library, CINAHL Plus, and regional databases (LILACS,
African Journals online, Latin America & Iberia Database
(ProQuest), Middle East & Africa Database (ProQuest)).
Studies were imported into Endnote and duplicates
removed. The search was restricted to articles in English,
Arabic, Spanish, Portuguese, and French, with no date
restrictions. Database searches were complemented by
reference list screening and citation tracking of included
materials in Web of Science and Google Scholar.
Search terms
The search strategy (Additional file 1: Appendix) was

7. designed with the support of a librarian and included
terms related to (1) women and children, (2) family vio-
lence, (3) mental disorders, and (4) conflict-affected
areas. Terms describing conflict-affected areas were
compiled using a list of countries and territories in
which armed conflicts were recorded before 2018, using
the Uppsala Conflict Data of the International Peace
Research Institute and the Heidelberg Institute for Inter-
national Conflict Research. We used the Uppsala Institute
Page 3 of 19Devakumar et al. Confl Health (2021) 15:74
interstate and intrastate definitions of conflict: “An armed
conflict is a contested incompatibility that concerns gov-
ernment and/or territory where the use of armed force
between two parties, of which at least one is the govern-
ment of a state, results in at least 25 battle-related deaths
in one calendar year”; and “A conflict between a govern-
ment and a non-governmental party, with no interference
from other countries” [22].
Inclusion criteria
Population and setting: Our review included adult
women (aged 18 years or older), and male or female chil-
dren (aged under 18 years). If the study sample included
men aged 18 or older, reports were only included if 90%
were under 18. We did not include facility-based studies
in the assessment of prevalence due to the risk of selec-
tion bias, but chose to include school studies to reflect
the universal right to education. We included studies up
to 10 years post-conflict to capture the ongoing effects of
war. Type of study: We included primary research using
qualitative (e.g. individual interviews, focus group inter -
views) or quantitative (e.g. cohort, case–control, cross-

8. sectional studies, or baseline data from experimental or
quasi-experimental studies) research designs. Where
quantitative studies were reported in more than one pub-
lication, the one with the largest sample was selected for
inclusion. Exposures: We included family violence against
women or children. The definition of family violence,
adapted from the United Nations definition of violence
against women [23] was the intentional use of physi-
cal force or power by an intimate partner, ex-partner or
parent that results in physical, sexual or mental harm
or suffering to women and/or children. This includes
threats of violence, sexual coercion, psychological abuse
and arbitrary deprivation of liberty. Family violence is
an overarching term that includes intimate partner vio-
lence and child abuse, perpetuated by family members.
Studies of children who witness violence against women
in the home in addition to experiencing direct violence
themselves were included. The comparator group for
quantitative studies was no exposure to family violence.
Outcomes: Our primary outcome was mental disorder,
defined in accordance with the International Classifica-
tion of Diseases and Related Health Problems (ICD-11)
or Diagnostic and Statistical Manual of Mental Disor-
ders, 5th Edition (DSM-V) criteria. Articles were eligible
if mental disorder was assessed using either a validated
diagnostic or screening instrument, diagnosed by a cli-
nician, or self-reported by participants. The secondary
outcomes included were mental and social wellbeing of
women experiencing family violence and children experi -
encing or witnessing family violence.
Exclusion criteria
Population and setting: We excluded soldiers and war
veterans, refugees and asylum seekers who had moved
away from the conflict setting. Soldiers and war veter-
ans were considered to be too different a population

9. who had experienced combat directly. Type of study: We
excluded opinion pieces and editorials, dissertations or
theses, policy papers, reviews, general reports that did
not introduce new evidence from a specific study, and
conference abstracts. Exposures: Other forms of violence
against women and children were beyond the scope of
the review; for example, peer bullying, violence by per-
petrators other than intimate partners, ex-partners, or
family members, female genital mutilation or cutting, or
child labour or marriage.
Screening
Titles and abstracts were screened independently by two
reviewers (CR, NU) from 2nd June 2019. Full texts were
screened from 31st July 2019. Data extraction began on
1st September 2019 and was completed by January 2020.
Disagreement was resolved by discussion and no papers
were discussed with a third reviewer. Each full text was
then independently reviewed by two authors (two of AP,
AU-C, CR, DD, NU, JM). Disagreement was resolved by
discussion. One author was contacted for missing data,
but did not respond.
Quality assessment
Two reviewers assessed each article (qualitative articles
by AP and JM, with disagreements decided by DD; quan-
titative articles by A-UC and DD) for quality using the
Joanna Briggs Institute checklists [24]. Discrepancies in
scoring were discussed between the reviewing authors.
Analyses
Quantitative studies: We used descriptive statistics to
summarise information about the study characteristics,
samples, and methods. Ninety-five percent confidence
intervals were reported for all measures of prevalence
and risk ratios where available. Meta-analysis was not

10. conducted due to study heterogeneity.
Qualitative analysis: We conducted a thematic analy-
sis of selected articles and used NVIVO 12 to organise
the data. All articles were read multiple times by two
reviewers (AP, JM) to identify initial codes related to the
associations between family violence and mental health
and the influence of gender relations (Additional file 1:
Appendix), drawing on the accounts of both research
participants and the article’s authors. AP and JM dis-
cussed these codes to arrive at a consensus and collabo-
ratively developed a final codebook. One reviewer (JM)
Page 4 of 19Devakumar et al. Confl Health (2021) 15:74
then went through each article in detail, systematically
extracting all relevant quotes. As a descriptive account
of the current literature on this topic, further theoreti-
cal interpretation beyond a descriptive analysis was not
needed.[25].
Results
Studies included
We identified 2603 records, of which 1682 were dupli -
cates (Fig. 1). Of the 173 full-text articles retrieved, 29
studies conducted between 1994 and 2017 in 13 coun-
tries were included (Additional file 1: Appendix). Reasons
for exclusion were mostly due to the study not including
family violence or not being a full research paper (Addi -
tional file 1: Appendix).
The quantitative papers described violence against
women and violence against children. We included 14
quantitative studies of violence against women in con-

11. flict from 11 countries (five in Africa, five in Asia, one
in Europe). All were cross-sectional, with the exception
of one cohort study [26]. The sample sizes for women
within these studies ranged from 80 to 2196 individuals
(Table 1). The types of violence included varied. Eleven
studies focused on intimate partner violence (IPV). The
other studies had broader definitions including violence
from other members of the family and other forms of vio-
lence (Table 1).
We included eight studies of violence against children
in conflict-affected countries. All were from Asia except
one from Uganda. All were school-based samples except
two that were community-based [27, 28], which were
the smallest (n = 149 [27]) and largest (n = 513 [28]).
Six studies were cross-sectional and two were cohorts
(Table 2).
Eight qualitative studies were included [29–36], pre-
senting research from six countries: Côte d’Ivoire (2),
Timor-Leste (2), Colombia (1), Uganda (1), Demo-
cratic Republic of the Congo (1), and Sri Lanka (1).
Fig. 1 PRISMA flow chart
Page 5 of 19Devakumar et al. Confl Health (2021) 15:74
Ta
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52. w
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53. at
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55. ta
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N
=
1
56
8
(n
) =
9

56. 03
15
+
N
o
n
‑ v
u
ln
er
ab
le
a
n
d
vu
ln
er
ab
le
in
d

57. iv
id
u
‑
al
s
w
er
e
se
le
ct
ed
**
IP
V
fr
o
m
p
ar
tn
er
o

58. r
sp
o
u
se
K
in
ya
n
d
a
(2
01
6)
[4
8]
U
g
an
d
a
U
n

59. kn
o
w
n
In
te
rs
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
st
u
d
y
N

60. =
1
11
0
(n
) =
6
94
14
+
R
es
id
en
t
o
f t
h
e
4
su
b
‑ c

61. o
u
n
ti
es
, w
it
h
in
th
e
ag
e
ra
n
g
e
o
f
14
+
,
co

62. n
ve
rs
an
t
w
it
h
t
h
e
It
es
o
t
la
n
‑
g
u
ag
e
an
d

63. w
o
u
ld
u
n
d
er
st
an
d
t
h
e
su
rv
ey
Ph
ys
ic
al
, e
m

64. o
ti
o
n
al
/
p
sy
ch
o
lo
g
ic
al
a
n
d
se
xu
al
v
io
le

65. n
ce
fr
o
m
p
ar
tn
er
o
r
sp
o
u
se
Page 6 of 19Devakumar et al. Confl Health (2021) 15:74
Ta
b
le
1
(
co

66. n
ti
n
u
ed
)
A
u
th
o
r
C
o
u
n
tr
y
St
u
d
y
se
tt
in

67. g
(u
rb
an
/r
u
ra
l)
N
at
u
re
o
f c
o
n
fl
ic
t
St
u
d
y

68. d
es
ig
n
Sa
m
p
le
s
iz
e
(n
)
A
g
e
o
f s
am
p
le
Pa
rt
ic

69. u
la
r
g
ro
u
p
o
f
fo
cu
s
Ty
p
e
o
f V
io
le
n
ce
an
d

70. R
o
le
o
f
p
er
p
et
ra
to
r
R
ee
s
(2
01
6)
[4
5]
Ti
m
o
r‑

71. Le
st
e
Fa
ci
lit
y‑
b
as
ed
In
tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al

72. st
u
d
y
(n
) =
1
67
2
<
1
5
to
>
3
5
Pr
eg
n
an
t
w
o

73. m
en
in
se
co
n
d
t
ri
m
es
te
r
IP
V
fr
o
m
p
ar
tn
er

74. Sh
u
m
an
(2
01
6)
[3
0]
C
ô
te
d
’Iv
o
ire
U
rb
an
In
tr
as
ta
te

75. C
ro
ss
‑ s
ec
ti
o
n
al
st
u
d
y
(n
) =
8
0
18
+
W
o
m

76. en
fr
o
m
t
h
e
g
en
er
al
p
o
p
u
la
ti
o
n
IP
V
fr
o
m

77. p
ar
tn
er
Sr
is
ka
n
d
ar
aj
ah
(2
01
5)
[4
1]
Sr
i L
an
ka
U
n

78. kn
o
w
n
In
tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
st
u
d
y
N

79. =
5
69
(n
) =
1
22
37
.6
(5
.6
)
Pa
re
n
ts
o
f p
ri
m
ar
y
sc
h

80. o
o
l c
h
ild
re
n
Ph
ys
ic
al
, e
m
o
ti
o
n
al
/
p
sy
ch
o
lo

81. g
ic
al
, s
ex
u
al
vi
o
le
n
ce
a
n
d
IP
V
fr
o
m
h
u

82. sb
an
d
U
st
a
(2
00
8)
[5
0]
Le
b
an
o
n
Fa
ci
lit
y‑
b
as
ed
In

83. tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
st
u
d
y
(n
) =
3
10
15
–7

84. 2;
3
6.
20
(1
0.
60
)
W
o
m
en
fr
o
m
t
h
e
g
en
er
al
p
o

85. p
u
la
ti
o
n
IP
V
an
d
d
o
m
es
ti
c
vi
o
‑
le
n
ce
fr
o

86. m
h
u
sb
an
d
o
r
fa
m
ily
m
em
b
er
s
Vi
n
ck
(2
01
3)
[3

87. 8]
Li
b
er
ia
Ru
ra
l a
n
d
u
rb
an
In
tr
as
ta
te
C
ro
ss
‑ s
ec
ti

88. o
n
al
st
u
d
y
N
=
4
50
1
(n
) =
2
19
6
35
.4
Li
b
er
ia

89. n
a
d
u
lt
s
IP
V
fr
o
m
p
ar
tn
er
o
r
sp
o
u
se
* T
h
e

90. st
u
d
y
in
cl
u
d
ed
w
o
m
en
re
ce
iv
in
g
p
sy
ch
ia
tr
ic

91. t
re
at
m
en
t.
Th
es
e
w
o
m
en
w
er
e
ex
cl
u
d
ed
fr
o
m

92. o
u
r a
n
al
ys
is
**
V
u
ln
er
ab
le
in
d
iv
id
u
al
s
d
efi
n

93. ed
a
s
’A
p
er
so
n
w
h
o
h
ad
a
n
y
o
f t
h
e
fo
llo
w
in

94. g
c
h
ar
ac
te
ri
st
ic
s:
w
id
o
w
ed
, d
iv
o
rc
ed
, o
r s
ep
ar

95. at
ed
; l
iv
in
g
in
a
n
in
te
rn
al
ly
d
is
p
la
ce
d
p
er
so
n

96. s
ca
m
p
; w
o
m
en
w
h
o
h
ad
s
u
ff
er
ed
s
ex
u
al
to
rt

97. u
re
; s
in
g
le
m
o
th
er
s;
o
rp
h
an
s;
o
u
t
o
f s
ch
o

98. o
l y
o
u
th
; c
h
ild
/a
d
o
le
sc
en
t
m
o
th
er
s;
w
o
m
en

99. a
n
d
a
d
o
le
sc
en
t
g
ir
ls
w
it
h
o
u
t
an
y
so
u
rc

100. e
o
f l
iv
el
ih
o
o
d
(m
ai
n
ly
la
ck
o
f a
cc
es
s
to
a
ra
b

101. le
la
n
d
);
h
av
in
g
a
m
en
ta
l h
ea
lt
h
p
ro
b
le
m
; s
u

102. rv
iv
o
r o
f i
n
ti
m
at
e
p
ar
tn
er
v
io
le
n
ce
; a
n
d
s
u

103. rv
iv
o
rs
o
f r
ec
en
t
fa
m
in
es
o
r fl
o
o
d
s
Page 7 of 19Devakumar et al. Confl Health (2021) 15:74
Ta
b

104. le
2
S
tu
d
y
ch
ar
ac
te
ri
st
ic
s
Vi
o
le
n
ce
a
g
ai
n
st

105. c
h
ild
re
n
A
u
th
o
r
C
o
u
n
tr
y
St
u
d
y
se
tt
in
g

106. (u
rb
an
/r
u
ra
l)
N
at
u
re
o
f c
o
n
fl
ic
t
R
es
ea
rc
h

107. d
es
ig
n
Sa
m
p
le
s
iz
e
(n
)
A
g
e
o
f s
am
p
le
Pa
rt
ic

108. u
la
r
g
ro
u
p
o
f
fo
cu
s
Ty
p
e
o
f v
io
le
n
ce
a
n
d

109. ro
le
o
f p
er
p
et
ra
to
r
C
at
an
i (
20
08
) [
12
]
Sr
i L
an
ka

110. Sc
h
o
o
l‑
b
as
ed
In
tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
s
tu

111. d
y
29
6
9–
15
; 1
2.
2
St
u
d
en
ts
Ph
ys
ic
al
a
b
u
se
, s
ex

112. u
al
ab
u
se
a
n
d
e
m
o
ti
o
n
al
ab
u
se
in
cl
u
d

113. in
g
w
it
‑
n
es
si
n
g
IP
V
b
et
w
ee
n
p
ar
en
ts
, f
ro

114. m
fa
m
ily
m
em
b
er
C
at
an
i (
20
09
) [
40
]
A
fg
h
an
is
ta

115. n
Sc
h
o
o
l‑
b
as
ed
, u
rb
an
In
te
rn
at
io
n
al
is
ed
in
tr

116. as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
s
tu
d
y
28
7
7–
15
; G
ir
ls
1

117. 1.
8
(1
.6
)
Bo
ys
1
0.
9
(1
.7
).
C
o
m
‑
b
in
ed
m
ea
n
: 1

118. 1
St
u
d
en
ts
Ph
ys
ic
al
v
io
le
n
ce
(f
am
‑
ily
v
io
le
n
ce

119. d
efi
n
ed
as
b
ei
n
g
e
xp
o
se
d
t
o
p
h
ys
ic
al
, e

120. m
o
ti
o
n
al
o
r
se
xu
al
a
b
u
se
o
r
w
it
n
es
si
n

121. g
IP
V
) f
ro
m
fa
m
ily
m
em
b
er
in
cl
u
d
‑
in
g
s
ib
lin

122. g
Fa
yy
ad
(2
01
7)
[4
7]
Le
b
an
o
n
Sc
h
o
o
l‑
b
as
ed
, p
er

123. i‑
u
rb
an
In
tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
s
tu
d
y
25
2

124. 14
.7
(1
.7
)
A
d
o
le
sc
en
ts
fr
o
m
g
ra
d
es
7
t
o
1

125. 2
w
h
o
ex
p
er
ie
n
ce
d
a
t
le
as
t
o
n
e
w
ar
e
ve

126. n
t
Ph
ys
ic
al
v
io
le
n
ce
(f
am
ily
v
io
le
n
ce
) f
ro
m

127. p
ar
en
ts
a
n
d
fa
m
ily
O
’L
ea
ry
(2
01
8)
[2
7]
A
fg
h
an
is

128. ta
n
C
o
m
m
u
n
it
y‑
b
as
ed
,
ru
ra
l a
n
d
u
rb
an
In
te

129. rn
at
io
n
al
is
ed
in
tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
s
tu

130. d
y
14
9
12
–1
8;
1
4.
6
C
h
ild
re
n
li
vi
n
g
in
K
ab
u

131. l
Ph
ys
ic
al
a
b
u
se
(d
o
m
es
ti
c
vi
o
le
n
ce
a
n
d

132. n
eg
le
ct
) f
ro
m
p
ar
en
ts
Pa
n
te
r‑
Br
ic
k
(2
01
1)
[4

133. 3]
A
fg
h
an
is
ta
n
Sc
h
o
o
l‑
b
as
ed
In
te
rn
at
io
n
al
is

134. ed
in
tr
as
ta
te
C
o
h
o
rt
s
tu
d
y
23
4
11
–1
6;
1
3.
5

135. (1
.5
1)
St
u
d
en
ts
Ph
ys
ic
al
v
io
le
n
ce
(d
o
m
es
ti
c

136. vi
o
le
n
ce
)
fr
o
m
fa
m
ily
m
em
b
er
s
Pa
n
te
r‑
Br
ic

137. k
(2
01
5)
[4
2]
A
fg
h
an
is
ta
n
Sc
h
o
o
l‑
b
as
ed
In
te

138. rn
at
io
n
al
is
ed
in
tr
as
ta
te
C
o
h
o
rt
s
tu
d
y
33
1

139. 11
–1
6
St
u
d
en
ts
in
g
ra
d
es
5–
10
Ph
ys
ic
al
v
io
le
n

140. ce
(d
o
m
es
ti
c
vi
o
le
n
ce
)
fr
o
m
u
n
kn
o
w
n
g

141. ro
u
p
s
Sa
ile
(2
01
6)
[2
8]
U
g
an
d
a
C
o
m
m
u
n
it
y‑

142. b
as
ed
In
te
rs
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
s
tu
d
y
51
3
6–

143. 13
; 8
.7
9
(S
D
1
.2
9)
C
h
ild
re
n
a
tt
en
d
in
g
se
co
n

144. d
‑ g
ra
d
e
Ph
ys
ic
al
(f
am
ily
v
io
‑
le
n
ce
e
.g
. e
xp
er
ie

145. n
ci
n
g
an
d
w
it
n
es
si
n
g
p
h
ys
ic
al
an
d
v
er

146. b
al
d
o
m
es
ti
c
vi
o
le
n
ce
) f
ro
m
fa
m
ily
m
em
b
er

147. Sr
is
ka
n
d
ar
aj
ah
(2
01
5)
[4
1]
Sr
i L
an
ka
Sc
h
o
o
l‑
b

148. as
ed
In
tr
as
ta
te
C
ro
ss
‑ s
ec
ti
o
n
al
s
tu
d
y
35
9
7–
11

149. . M
=
9
.2
(S
D
1
.0
)
Pr
im
ar
y
sc
h
o
o
l
ch
ild
re
n
a
n

150. d
t
h
ei
r
p
ar
‑
en
ts
. T
am
il
fa
m
ili
es
Ph
ys
ic
al
, e
m
o

151. ti
o
n
al
/
p
sy
ch
o
lo
g
ic
al
a
n
d
se
xu
al
v
io
le
n

152. ce
(E
xp
o
‑
su
re
t
o
fa
m
ily
v
io
le
n
ce
an
d
IP
V
) f
ro

153. m
P
ar
en
ts
Page 8 of 19Devakumar et al. Confl Health (2021) 15:74
Five reports focused exclusively on family violence per -
petrated against women, two on violence by mothers
against their children, and one on both forms of fam-
ily violence. Only one report discussed VAW by family
members other than the husband. Seven reports used
interviews or focus groups and one used a question-
naire. Terms such as depression, anxiety, post-trau-
matic stress disorder, or suicidal ideation were rarely
used. As such, mental health problems were coded as
anything that discussed a psychological symptom or
negative feelings, including stress, fear, worry, unhappi -
ness, or concern.
We summarise below the results according to our four
objectives, including the qualitative and quantitative
results together.
1. Prevalence of family violence in conflict-affected
areas
The prevalence of family violence and associations with
mental health are shown in Tables 3 (for women) and 4
(for children). Amongst women, the prevalence of vio-
lence varied, but exposure to domestic violence in both

154. conflict and post-conflict settings was common. The
highest prevalence was a study from Bosnia and Herze-
govina, where 78.9% of women reported physical abuse
and 96.1% psychological abuse [37]. Commonly, how-
ever, reports of IPV were in the region of 30–40%. Life-
time experience of IPV was reported at 37.7%[38] from
Liberia, 44.6% for those who had 2–4 trauma exposures
in a study from Afghanistan [13], and 49.8%in a study
from rural Côte d’Ivoire [39]. High prevalence was also
reported for exposure to IPV within the last 12 months
(24.4% [38], 25.1% [13] and 29.7% [39]). No obvious dif-
ference was seen by country or region of the world.
The prevalence of violence against children varied but
in all cases violence was very common. Lifetime experi-
ence of violence was reported at 77% from Afghanistan
[40], 88.9% from Uganda [28], and 83.8% and 95.6%
in studies from Sri Lanka[12, 41] Similar high preva-
lences were reported for recent or ongoing violence over
the last year (27% [42], 47% [43] and 71% [27]) and last
month (35.2% [40], 64.2% [12] and 71.6% [41]). Where
the mean number of events was measured, children had
experienced 5.3 [12] or witnessed 4.3 [40] family violence
events.
2. Risk of mental health problems among women and
children who have experienced or witnessed family
violence
Nearly all the studies found associations between fam-
ily violence and adverse mental health among women
(Table 3). Depression and PTSD were commonly meas-
ured outcomes.
Six studies estimated the association between family

155. violence and mental health outcomes in children. Across
all studies, associations were found between family vio-
lence and mental ill-health.
Post‑ traumatic stress disorder
Gupta et al. [16] found a non-significant positive associa-
tion between IPV and PTSD (OR 1.6 (95% CI 0.9, 2.6) in
Côte d’Ivoire. Johnson et al. [44] found that in the DRC
43.9% (95% CI 34.7, 53.0) of women not affected by IPV
had PTSD, compared with 77.2% (95% CI 66.8, 87.7)
who were affected by IPV. A dose–response relationship
between compound exposures of violence and likelihood
of PTSD was reported by Rees et al. [45], whereby severe
combined physical and psychological abuse was associ-
ated with the greatest risk of PTSD (OR 3.24, 95% CI 1.90,
5.50). These findings were comparable with those found
in Afghanistan. Jewkes et al. [13] reported that, of women
who had no exposure to trauma, 1.35% had PTSD. Of
women with one trauma exposure 1.7% had PTSD, and
with 2–4 trauma exposures 1.65% had PTSD (p < 0.0001).
Umubyeyi et al.[46] noted strong positive associations
between different forms of violence exposure and PTSD
in Rwanda: physical (aOR 3.16; 95% CI 1.67, 5.95), sexual
(aOR 4.20; 95% CI 2.22, 7.95), psychological (aOR 2.97;
95% CI 1.62–5.45).
In children, studies from Sri Lanka [12], Afghanistan
[40, 42, 43], Lebanon [47] and Uganda [28] all showed
increases in PTSD associated with family violence. In
comparable studies, Catani et al. [12] and Catani et al.
[40] showed that exposure to war predicted family vio-
lence and PTSD symptoms, and a correlation between
family violence and PTSD. Similarly, Fayyad et al. found
higher PTSD scores (as measured by the Child Revised
Impact of Events Scale (CRIES)) in children who had
experienced or witnessed family violence [47].

156. Other mental health problems
Umubyeyi et al. [46] found associations between major
depressive episode and physical (aOR 4.63; 95% CI
2.57, 8.32), sexual (aOR 5.49; 95% CI 2.94, 10.25), and
psychological violence (aOR 5.59; 95% CI 3.19, 9.80).
As was the case with PTSD, a dose–response relation-
ship between compound exposures of violence and
likelihood of depression was observed. In Afghani-
stan, Jewkes et al. [13] found that, of women who had
no exposure to trauma, 12.1% reported depression;
with one trauma exposure, 16.2% reported depres-
sion; and of women who had 2–4 trauma exposures;
17.1% reported depression (p < 0.0001). In Bosnia and
Herzegovina, Avdibegovic et al. [37] found that 76%
Page 9 of 19Devakumar et al. Confl Health (2021) 15:74
Ta
b
le
3
V
io
le
n
ce
a
g

157. ai
n
st
w
o
m
en
re
su
lt
s
A
u
th
o
r
Pr
ev
al
en
ce
o
f f
am

158. ily
v
io
le
n
ce
Pr
ev
al
en
ce
o
f a
m
en
ta
l h
ea
lt
h
p
ro
b
le

159. m
Ev
id
en
ce
o
f a
ss
o
ci
at
io
n
b
et
w
ee
n
fa
m
ily
v
io
le

160. n
ce
an
d
m
en
ta
l h
ea
lt
h
p
ro
b
le
m
A
vd
ib
eg
o
vi
c

161. (2
00
6)
[3
7]
Bo
sn
ia
a
n
d
H
er
ze
g
o
vi
n
a
78
.9
%
e
xp

162. er
ie
n
ce
d
p
h
ys
ic
al
a
b
u
se
, 6
0.
5%
e
xp
er
i‑
en
ce
d

163. s
ex
u
al
a
b
u
se
a
n
d
9
6.
1%
e
xp
er
ie
n
ce
d
p
sy
ch

164. o
‑
lo
g
ic
al
a
b
u
se
G
en
er
al
n
eu
ro
ti
ci
sm
m
ea
su
re

165. d
b
y
C
o
rn
el
l I
n
d
ex
t
es
t
w
as
h
ig
h
in
2
6
an
d

166. m
o
d
er
at
e
in
3
0
o
u
t
o
f 7
6
su
rv
i‑
vo
rs
o
f d
o
m

167. es
ti
c
vi
o
le
n
ce
76
%
o
f p
ar
ti
ci
p
an
ts
e
xp
er
ie
n
ci

168. n
g
d
o
m
es
ti
c
ab
u
se
h
ad
sy
m
p
to
m
s
o
f n
eu
ro

169. si
s
G
en
er
al
le
ve
ls
o
f n
eu
ro
si
s =
4
3%
(I
Q
R
25
.3
, 6
2.

170. 3)
,
A
n
xi
et
y
=
6
4%
(I
Q
R
36
.0
, 7
3.
0)
, P
h
o
b
ia
=

171. 5
7%
(I
Q
R
29
.0
,
86
.0
),
D
ep
re
ss
io
n
=
5
0%
(I
Q
R
0.

172. 0,
8
6.
0)
, O
b
se
ss
iv
e
–
co
m
p
u
ls
iv
e
te
n
d
en
ci
es

173. =
5
0%
(I
Q
R
17
.0
, 6
7.
0)
G
u
p
ta
(2
01
4)
[1
6]
C
ô
te

174. d
’Iv
o
ire
W
o
m
en
e
xp
er
ie
n
ci
n
g
li
fe
ti
m
e
IP
V:
2

175. 6.
5%
Pa
st
y
ea
r
IP
V:
2
3.
4%
O
f t
h
e
w
o
m
en
w
h
o
e

176. xp
er
ie
n
ce
d
n
o
IP
V,
9
.2
%
h
ad
p
ro
b
ab
le
P
TS
D

177. O
f t
h
e
w
o
m
en
w
h
o
e
xp
er
ie
n
ce
d
IP
V
w
it
h
in

178. t
h
e
lif
et
im
e,
b
u
t
n
o
t
w
it
h
in
t
h
e
p
as
t
ye

179. ar
1
2.
3%
h
ad
p
ro
b
ab
le
P
TS
D
22
.1
%
o
f t
h
e
w
o

180. m
en
w
h
o
e
xp
er
ie
n
ce
d
p
as
t
ye
ar
h
ad
p
ro
b
ab

181. le
P
TS
D
A
d
ju
st
ed
O
R,
fo
r
lif
et
im
e
IP
V
p
ri
o
r
to

182. t
h
e
p
as
t
ye
ar
a
n
d
PT
SD
=
1
.6
(9
5%
C
I 0
.9
, 2
.6

183. )
Fo
r
p
as
t
ye
ar
IP
V
an
d
P
TS
D
=
3
.1
(9
5%
C
I 1
.8
, 5

184. .3
)
H
ea
th
(2
01
2)
[2
6]
Pa
le
st
in
e
A
t
18
m
o
n
th
fo
llo

185. w
u
p
: 2
3.
8%
re
p
o
rt
ed
b
ei
n
g
in
su
lt
ed
, 2
0.
4%
p

186. u
sh
ed
/s
h
o
ve
d
, 1
4.
4%
t
h
re
at
en
ed
,
an
d
1
8.
3%
h

187. it
H
o
ss
ai
n
(2
01
4)
[3
9]
C
ô
te
d
’Iv
o
ire
IP
V
am
o
n
g

188. e
ve
r‑
p
ar
tn
er
ed
: 2
9.
1%
re
p
o
rt
ed
li
fe
‑ t
im
e
se
xu
al

189. v
io
le
n
ce
, 1
4.
9%
in
t
h
e
la
st
1
2
m
o
n
th
s
38
.4
%

190. re
p
o
rt
ed
li
fe
‑ t
im
e
p
h
ys
ic
al
v
io
le
n
ce
, 2
0.
9%
in

191. th
e
la
st
1
2
m
o
n
th
s
23
.9
%
re
p
o
rt
ed
s
ev
er
e

192. lif
e
‑ t
im
e
p
h
ys
ic
al
v
io
le
n
ce
.
11
.6
%
in
t
h
e
la

193. st
1
2
m
o
n
th
s
49
.8
%
re
p
o
rt
ed
li
fe
‑ t
im
e
p
h
ys

194. ic
al
a
n
d
/o
r
se
xu
al
vi
o
le
n
ce
. 2
9.
7%
in
t
h
e
la

195. st
1
2
m
o
n
th
s
Je
w
ke
s
(2
01
8)
[1
3]
A
fg
h
an
is
ta
n

196. Pa
st
1
2
m
o
n
th
s
p
h
ys
ic
al
IP
V:
O
f t
h
e
w
o
m
en

197. w
h
o
h
ad
n
o
e
xp
o
su
re
t
o
t
ra
u
m
a,
1
7.
7%
re

198. p
o
rt
ed
IP
V,
o
f t
h
o
se
w
h
o
h
ad
1
t
ra
u
m
a
ex

199. p
o
su
re
; 2
7.
6%
re
p
o
rt
ed
IP
V,
an
d
fo
r
th
o
se
w
h

200. o
h
ad
2
–4
t
ra
u
m
a
ex
p
o
su
re
s,
2
5.
1%
re
p
o
rt

201. ed
IP
V
(p
=
0
.0
06
)
Li
fe
ti
m
e
p
h
ys
ic
al
r
is
k
IP
V:

202. O
f t
h
e
w
o
m
en
w
h
o
h
ad
n
o
e
xp
o
su
re
t
o
t

203. ra
u
m
a;
2
8.
1%
re
p
o
rt
ed
li
fe
ti
m
e
IP
V,
a
m
o
n
g

204. w
o
m
en
w
h
o
h
ad
1
t
ra
u
m
a
ex
p
o
su
re
,
47
.0
%

205. re
p
o
rt
ed
li
fe
ti
m
e
IP
V,
a
n
d
fo
r
th
o
se
w
h
o
h

206. ad
2–
4
tr
au
m
a
ex
p
o
su
re
s,
4
4.
6%
re
p
o
rt
ed
li
fe

207. ti
m
e
IP
V
(p
<
0
.0
00
1)
D
ep
re
ss
io
n
: O
f t
h
e
w
o

208. m
en
w
h
o
h
ad
n
o
e
xp
o
su
re
t
o
tr
au
m
a;
1
2.
05

209. %
re
p
o
rt
ed
d
ep
re
ss
io
n
. O
f t
h
e
w
o
m
en
w
it
h

210. 1
t
ra
u
m
a
ex
p
o
su
re
1
6.
25
%
re
p
o
rt
ed
d
ep
re
ss

211. io
n
,
an
d
o
f t
h
e
w
o
m
en
w
h
o
h
ad
2
–4
t
ra
u
m

212. a
ex
p
o
su
re
s,
17
.1
%
re
p
o
rt
ed
d
ep
re
ss
io
n
(p
<

213. 0
.0
00
1)
PT
SD
: O
f t
h
e
w
o
m
en
w
h
o
h
ad
n
o
e
xp
o

214. su
re
t
o
t
ra
u
m
a
1.
35
%
h
ad
P
TS
D
. O
f t
h
e
w
o
m

215. en
w
it
h
1
t
ra
u
m
a
ex
p
o
su
re
1
.7
%
h
ad
P
TS
D
. O

216. f t
h
e
w
o
m
en
w
h
o
h
ad
2
–4
tr
au
m
a
ex
p
o
su
re

217. s
1.
65
%
h
ad
P
TS
D
(p
<
0
.0
00
1)
Jo
h
n
so
n
(2
01
0)
[4

218. 4]
D
em
o
cr
at
ic
R
ep
u
b
lic
o
f C
o
n
g
o
30
.5
%
re
p
o

219. rt
ed
IP
V.
O
f t
h
is
g
ro
u
p
, 9
6%
re
p
o
rt
ed
p
h
ys
ic

220. al
IP
V
an
d
8
.5
%
re
p
o
rt
ed
s
ex
u
al
IP
V
21
.4
%
re
p

221. o
rt
ed
s
u
b
st
an
ce
a
b
u
se
. 4
1.
9%
h
ad
M
D
D
,
54
.0

222. %
h
ad
P
TS
D
, 2
7.
3%
h
ad
s
u
ic
id
al
id
ea
ti
o
n
a
n
d

223. 16
.8
%
re
p
o
rt
ed
a
s
u
ic
id
e
at
te
m
p
t
20
.5
%
(9

224. 5%
C
I 1
2.
0,
2
9.
0)
o
f w
o
m
en
a
ff
ec
te
d
b
y
IP
V
su
ff

225. er
ed
fr
o
m
s
u
b
st
an
ce
a
b
u
se
, 6
4.
9%
(9
5%
C
I 5
2.
3,

226. 77
.5
) s
u
ff
er
ed
fr
o
m
M
D
D
, 7
7.
2%
(9
5%
C
I 6
6.
8,
8

227. 7.
7)
su
ff
er
ed
fr
o
m
P
TS
D
, 4
2.
4%
(9
5%
C
I 2
8.
9,
5
6.

228. 0)
s
u
ff
er
ed
fr
o
m
s
u
ic
id
al
id
ea
ti
o
n
, a
n
d
3

229. 3.
1%
(9
5%
C
I 2
2.
9,
4
3.
4)
re
p
o
rt
ed
a
s
u
ic
id
e
at

230. te
m
p
t
Page 10 of 19Devakumar et al. Confl Health (2021)
15:74
Ta
b
le
3
(
co
n
ti
n
u
ed
)
A
u
th
o

231. r
Pr
ev
al
en
ce
o
f f
am
ily
v
io
le
n
ce
Pr
ev
al
en
ce
o
f a
m
en

232. ta
l h
ea
lt
h
p
ro
b
le
m
Ev
id
en
ce
o
f a
ss
o
ci
at
io
n
b
et

233. w
ee
n
fa
m
ily
v
io
le
n
ce
an
d
m
en
ta
l h
ea
lt
h
p
ro
b

234. le
m
K
an
e
(2
01
8)
[5
1]
Ir
aq
36
.3
%
d
o
m
es
ti
c
vi
o
le

235. n
ce
, 2
.4
%
s
ex
u
al
a
ss
au
lt
D
ep
re
ss
io
n
: H
PS
‑ 2
5
M

236. =
1
.5
4
(S
D
0
.5
4)
p
<
0
.0
00
1,
Po
st
‑ t
ra
u
m
at
ic

237. s
tr
es
s:
H
TS
M
=
1
.2
4
(S
D
0
.5
0)
p
<
0
.0
00
1
Li

238. n
ea
r
R
eg
re
ss
io
n
B
et
a
C
o
effi
ci
en
t
fo
r
d
o
m
es

239. ti
c
vi
o
le
n
ce
a
n
d
d
ep
re
ss
io
n
0
.3
0
(p
<
0
.0
00

240. 1)
; a
n
d
a
n
xi
et
y
(p
<
0
.0
5)
N
o
a
ss
o
ci
at
io
n
w

241. it
h
p
o
st
‑ t
ra
u
m
at
ic
s
tr
es
s
K
in
ya
n
d
a
(a
) (
20

242. 13
) [
49
]
U
g
an
d
a
34
.5
%
re
p
o
rt
ed
e
xp
o
su
re
t
o

243. IP
V
14
.7
%
re
p
o
rt
ed
p
ro
b
le
m
d
ri
n
ki
n
g
, 4
7.
9%

244. re
p
o
rt
ed
d
ep
re
ss
iv
e
d
is
o
rd
er
K
in
ya
n
d
a
(2

245. 01
6)
[4
8]
U
g
an
d
a
44
.9
%
re
p
o
rt
ed
a
n
y
fo
rm
o
f I

246. P
V
7.
8%
re
p
o
rt
ed
s
ex
u
al
IP
V
22
.9
%
re
p
o
rt
ed
p

247. h
ys
ic
al
IP
V
44
.2
%
re
p
o
rt
ed
p
sy
ch
o
lo
g
ic
al
IP
V

248. A
d
ju
st
ed
O
R
fo
r
p
ro
b
ab
le
m
aj
o
r
d
ep
re
ss
iv
e

249. d
is
o
rd
er
:
p
h
ys
ic
al
IP
V
1.
41
(9
5%
C
I 0
.9
6,
2
.0
7)

250. , p
sy
ch
o
lo
g
ic
al
IP
V
0.
97
(9
5%
C
I 0
.6
8,
1
.3
9)
, s
ex
u

251. al
IP
V
2.
15
(9
5%
C
I 1
.0
9,
4.
23
)
R
ee
s
(2
01
6)
[4
5]

252. T
im
o
r‑
Le
st
e
30
.6
%
re
p
o
rt
ed
s
ev
er
e
p
sy
ch
o
lo

253. g
ic
al
a
b
u
se
(t
h
re
at
‑
en
in
g
, i
n
ti
m
id
at
io
n
a

254. n
d
c
o
n
tr
o
lli
n
g
)
6.
2%
re
p
o
rt
ed
p
h
ys
ic
al
a

255. b
u
se
o
n
ly
19
.5
%
re
p
o
rt
ed
c
o
m
b
in
ed
s
ev
er
e

256. p
sy
ch
o
lo
g
ic
al
a
n
d
p
h
ys
ic
al
a
b
u
se
19
.7
%

257. m
et
t
h
e
EP
D
S
th
re
sh
o
ld
fo
r
d
ep
re
ss
iv
e
sy
m
p

258. to
m
s,
5
.7
%
fo
r
PT
SD
s
ym
p
to
m
s
an
d
6
.3
%
fo
r
p

259. sy
ch
o
lo
g
ic
al
d
is
tr
es
s
A
d
ju
st
ed
O
R
fo
r
IP
V
an

260. d
D
ep
re
ss
io
n
E
PD
S:
S
ev
er
e
p
sy
ch
o
lo
g
ic
al
a
b

261. u
se
1
.6
1
(9
5%
C
I 1
.1
7,
2
.2
3)
. P
h
ys
ic
al
ab
u
se
2

262. .2
7
(9
5%
C
I 1
.3
7,
3
.7
7)
. S
ev
er
e
p
sy
ch
o
lo
g
ic
al

263. an
d
p
h
ys
ic
al
a
b
u
se
4
.3
(9
5%
C
I 3
.1
2,
5
.9
6)
A
d

264. ju
st
ed
O
R
fo
r
IP
V
an
d
P
TS
D
: S
ev
er
e
p
sy
ch
o
lo
g

265. ic
al
ab
u
se
1
.2
6
(9
5%
C
I 0
.7
1,
2
.2
4)
. P
h
ys
ic
al
a

266. b
u
se
2
.2
0
(9
5%
C
I 0
.9
6,
5
.0
4)
. S
ev
er
e
p
sy
ch
o

267. lo
g
ic
al
a
n
d
p
h
ys
ic
al
a
b
u
se
3.
24
(9
5%
C
I 1
.9

268. 0,
5
.5
0)
A
d
ju
st
ed
O
R
fo
r
IP
V
an
d
P
sy
ch
o
lo
g
ic

269. al
D
is
tr
es
s
(K
es
‑
sl
er
‑ 1
0
in
d
ic
e)
: S
ev
er
e
p
sy
ch

270. o
lo
g
ic
al
a
b
u
se
1
.0
9
(9
5%
C
I 0
.5
9,
2
.0
3)
. P
h

271. ys
ic
al
a
b
u
se
2
.0
8
(9
5%
C
I 0
.8
7,
5
.0
1)
.
Se
ve
re
p

272. sy
ch
o
lo
g
ic
al
a
n
d
p
h
ys
ic
al
a
b
u
se
5
.3
2
(9
5%

273. C
I
3.
20
, 8
.8
7)
Sh
u
m
an
(2
01
6)
[3
0]
C
o
te
d
’Iv
o
ire

274. 53
.6
%
re
p
o
rt
ed
e
xp
o
su
re
t
o
p
h
ys
ic
al
, s
ex
u
al

275. o
r
em
o
‑
ti
o
n
al
IP
V
in
t
h
e
p
as
t
ye
ar
. O
f t
h
e

276. ty
p
es
o
f v
io
le
n
ce
,
46
.4
%
re
p
o
rt
ed
e
m
o
ti
o
n

277. al
IP
V,
2
1.
7%
re
p
o
rt
ed
s
ex
u
al
IP
V
an
d
1
7.
4%
re

278. p
o
rt
ed
p
h
ys
ic
al
IP
V.
2
9%
re
p
o
rt
ed
p
h
ys
ic
al

279. a
n
d
/o
r
se
xu
al
IP
V
in
p
as
t
ye
ar
A
m
o
n
g
p
ar
tn

280. er
ed
w
o
m
en
o
n
ly
1
4.
5%
re
p
o
rt
ed
b
ei
n
g
p
u

281. sh
ed
, s
h
o
ve
d
, k
ic
ke
d
o
r
d
ra
g
g
ed
. 1
3%
re
p
o

282. rt
ed
b
ei
n
g
s
la
p
p
ed
, h
av
in
g
s
o
m
et
h
in
g
t
h

283. ro
w
n
at
t
h
em
o
r
b
ei
n
g
h
it
w
it
h
s
o
m
et
h

284. in
g
. 1
5.
9%
re
p
o
rt
ed
b
ei
n
g
fo
rc
ed
t
o
h
av
e
se

285. x
as
re
su
lt
o
f t
h
re
at
s
o
r
in
ti
m
id
at
io
n
, 1
1.
6%
re

286. p
o
rt
ed
b
ei
n
g
p
h
ys
ic
al
ly
fo
rc
ed
to
h
av
e
se
x,

287. 3
6.
2%
re
p
o
rt
ed
b
ei
n
g
fr
ig
h
te
n
ed
o
r
h
u
m
ili

288. at
ed
10
.9
%
fa
ce
d
m
en
ta
l h
ea
lt
h
re
p
er
cu
ss
io
n
s
(u

289. n
d
efi
n
ed
)
Sr
is
ka
n
d
ar
aj
ah
(2
01
5)
[4
1]
Sr
i L
an
ka
70

290. .3
%
re
p
o
rt
ed
IP
V
in
t
h
e
p
as
t
ye
ar
, 3
.4
(S
D
4
.2

291. ) I
P
V‑
re
la
te
d
e
ve
n
ts
in
t
h
e
p
as
t
ye
ar
27
.9
%
o

292. f m
o
th
er
s
m
et
c
ri
te
ri
a
fo
r
a
d
ia
g
n
o
si
s
o
f P

293. TS
D
U
st
a
(2
00
8)
[5
0]
Le
b
an
o
n
27
%
re
p
o
rt
ed
a
t

294. le
as
t
o
n
e
in
ci
d
en
t
o
f d
o
m
es
ti
c
ab
u
se
d
u
ri

295. n
g
c
o
n
fli
ct
. 1
3%
re
p
o
rt
ed
a
t
le
as
t
o
n
e
in
ci

296. d
en
ce
p
er
p
et
ra
te
d
b
y
a
h
u
sb
an
d
o
r
o
th
er
fa

297. m
ily
m
em
b
er
C
o
rr
el
at
io
n
b
et
w
ee
n
n
eg
at
iv
e

298. m
en
ta
l h
ea
lt
h
s
co
re
a
n
d
d
o
m
es
ti
c
vi
o
le
n

299. ce
d
u
ri
n
g
c
o
n
fli
ct
: 0
.2
1
p
<
0
.0
01
C
o
rr
el
at

300. io
n
b
et
w
ee
n
n
eg
at
iv
e
m
en
ta
l h
ea
lt
h
s
co
re
a
n

301. d
d
o
m
es
ti
c
vi
o
le
n
ce
a
ft
er
c
o
n
fli
ct
: 0
.1
4

302. p
<
0
.0
1
Page 11 of 19Devakumar et al. Confl Health (2021)
15:74
Ta
b
le
3
(
co
n
ti
n
u
ed
)
A
u
th
o

303. r
Pr
ev
al
en
ce
o
f f
am
ily
v
io
le
n
ce
Pr
ev
al
en
ce
o
f a
m
en

304. ta
l h
ea
lt
h
p
ro
b
le
m
Ev
id
en
ce
o
f a
ss
o
ci
at
io
n
b
et

305. w
ee
n
fa
m
ily
v
io
le
n
ce
an
d
m
en
ta
l h
ea
lt
h
p
ro
b

306. le
m
Vi
n
ck
(2
01
3)
[3
8]
Li
b
er
ia
A
m
o
n
g
a
d
u
lt
w

307. o
m
en
, 3
7.
7%
(9
5%
C
I,
34
.9
, 4
0.
5)
re
p
o
rt
ed
li
fe
ti

308. m
e
ex
p
o
su
re
t
o
in
ti
m
at
e
‑ p
ar
tn
er
p
h
ys
ic
al

309. v
io
le
n
ce
. 2
4.
4%
(9
5%
C
I 2
2.
1,
2
6.
9)
re
p
o
rt
ed
in

310. ci
d
en
ce
o
f i
n
ti
m
at
e
‑ p
ar
tn
er
p
h
ys
ic
al
v
io
le
n

311. ce
o
ve
r
a
o
n
e
‑ y
ea
r
re
ca
ll
p
er
io
d
W
o
m
en
w
er

312. e
3.
3
ti
m
es
m
o
re
li
ke
ly
t
h
an
m
en
t
o
re
p
o
rt

313. h
av
in
g
e
xp
er
ie
n
ce
d
a
s
ev
er
e
b
ea
ti
n
g
b
y
a

314. sp
o
u
se
o
r
p
ar
tn
er
18
.8
%
re
p
o
rt
ed
P
TS
D
s
ym
p

315. to
m
s
17
.6
%
re
p
o
rt
ed
d
ep
re
ss
io
n
s
ym
p
to
m
s

316. C
I,
C
o
n
fid
en
ce
In
te
rv
al
; C
M
D
, C
o
m
m
o
n
M
en
ta

317. l H
ea
lt
h
D
is
o
rd
er
s;
C
TS
, C
o
n
fli
ct
T
ac
ti
cs
S
co
re

318. ; E
PD
S,
E
d
in
b
u
rg
h
D
ep
re
ss
io
n
S
ca
le
, G
A
D
, G
en

319. er
al
is
ed
A
n
xi
et
y
D
is
o
rd
er
; H
PS
-2
5,
H
o
p
ki
n
s

320. Sy
m
p
to
m
C
h
ec
kl
is
t-
25
; H
TS
, H
ar
va
rd
Tr
au
m
a
Sc

321. al
e;
IQ
R,
In
te
rq
u
ar
ti
le
ra
n
g
e;
M
D
D
, M
aj
o
r D
ep
re

322. ss
iv
e
D
is
o
rd
er
; O
R,
O
d
d
s
ra
ti
o
; S
D
, S
ta
n
d
ar

323. d
D
ev
ia
ti
o
n
; S
R
Q
-2
0,
S
el
f-
R
ep
o
rt
in
g
Q
u
es

324. ti
o
n
n
ai
re
-2
0
Page 12 of 19Devakumar et al. Confl Health (2021)
15:74
Ta
b
le
4
V
io
le
n
ce
a
g
ai
n

325. st
c
h
ild
re
n
re
su
lt
s
A
u
th
o
r
Pr
ev
al
en
ce
o
f f
am
ily

326. v
io
le
n
ce
Pr
ev
al
en
ce
o
f a
m
en
ta
l h
ea
lt
h
p
ro
b
le
m

327. Ev
id
en
ce
o
f a
ss
o
ci
at
io
n
b
et
w
ee
n
fa
m
ily
v
io
le
n

328. ce
a
n
d
m
en
ta
l h
ea
lt
h
p
ro
b
le
m
C
at
an
i (
20
08

329. ) [
12
]
Sr
i L
an
ka
95
.6
%
re
p
o
rt
ed
a
t
le
as
t
o
n
e
fa

330. m
ily
v
io
le
n
ce
e
ve
n
t
ty
p
e
ev
er
. 6
4.
2%
in
t
h
e
la

331. st
m
o
n
th
C
h
ild
re
n
e
xp
er
ie
n
ce
d
o
r
w
it
n
es
se

332. d
5
.3
(S
D
=
3
.2
)
vi
o
le
n
t
ev
en
t
ty
p
es
. 6
8.
8%
o

333. f c
h
ild
re
n
re
p
o
rt
ed
b
ei
n
g
b
ea
te
n
w
it
h
a
n

334. o
b
je
ct
. 1
8%
o
f c
h
ild
re
n
h
ad
s
u
ff
er
ed
at
le
as
t

335. o
n
e
in
ju
ry
b
ec
au
se
o
f t
h
e
vi
o
le
n
t
tr
ea
tm
en
t,

336. an
d
1
0%
o
f t
h
em
n
ee
d
ed
m
ed
ic
al
t
re
at
m
en
t.
55
.4

337. %
re
p
o
rt
ed
h
av
in
g
w
it
n
es
se
d
o
th
er
fa
m
ily
m

338. em
b
er
s
b
ei
n
g
h
it
4.
3%
re
p
o
rt
ed
h
av
in
g
e
xp
er

339. ie
n
ce
d
o
r
w
it
n
es
se
d
a
t
le
as
t
o
n
e
in
ci
d
en

340. t
o
f s
ex
u
al
a
b
u
se
o
r
se
xu
al
v
io
le
n
ce
at
h
o

341. m
e
PT
SD
: 3
0.
4%
(2
8.
5%
b
o
ys
; 3
2.
6%
g
ir
ls
);
M
aj
o
r

342. D
ep
re
ss
iv
e
D
is
o
rd
er
: 1
9.
6%
;
Pa
st
s
u
ic
id
al
it
y:

343. 2
2.
6%
; C
u
rr
en
t
su
ic
id
al
id
ea
ti
o
n
: 1
7.
2%
Ex
p
o
su

344. re
t
o
w
ar
p
re
d
ic
te
d
fa
m
ily
v
io
le
n
ce
(p
<
0
.0
01

345. )
Ex
p
o
su
re
t
o
fa
m
ily
v
io
le
n
ce
p
re
d
ic
te
d
P
TS

346. D
s
ym
p
to
m
s
(p
<
0
.0
01
)
C
at
an
i (
20
09
) [
40
]
A
fg

347. h
an
is
ta
n
77
%
(7
1.
3%
g
ir
ls
, 8
1.
3%
b
o
ys
) r
ep
o
rt
ed

348. a
t
le
as
t
o
n
e
ty
p
e
o
f f
am
ily
v
io
le
n
ce
e
ve
n
t

349. ev
er
. 3
5.
2%
in
t
h
e
la
st
m
o
n
th
C
h
ild
re
n
w
it
n

350. es
se
d
o
n
a
ve
ra
g
e
4.
3
vi
o
le
n
t
ev
en
t
ty
p
es

351. w
it
h
in
fa
m
ily
(m
ea
n
b
o
ys
=
5
.0
, g
ir
ls
: 3
.5
)
23
.2

352. %
h
ad
e
ve
r
w
it
n
es
se
d
o
th
er
fa
m
ily
m
em
b
er
s
b

353. ei
n
g
h
it
. 3
1.
5%
h
ad
w
it
n
es
se
d
t
h
ei
r
m
o
th

354. er
b
ei
n
g
b
ea
te
n
b
y
th
e
fa
th
er
41
.6
%
c
h
ild
re
n

355. re
p
o
rt
ed
b
ei
n
g
b
ea
te
n
b
y
th
ei
r
fa
th
er
.
59
.9

356. %
c
h
ild
re
n
re
p
o
rt
ed
b
ei
n
g
b
ea
te
n
b
y
m
o
th

357. er
. 1
1%
ch
ild
re
n
s
u
ff
er
ed
a
t
le
as
t
o
n
e
in
ju
ry

358. (b
ru
is
es
, b
le
ed
in
g
an
d
b
ro
ke
n
b
o
n
es
)
14
.1
%

359. a
n
d
2
6.
1%
o
f t
h
e
b
o
ys
fu
lfi
lle
d
a
ll
D
SM
‑
IV
c

360. ri
te
ri
a
fo
r
p
ro
b
ab
le
P
TS
D
Ex
p
o
su
re
t
o
w
ar
p

361. re
d
ic
te
d
fa
m
ily
v
io
le
n
ce
in
g
ir
ls
(p
<
0
.0
01
) b

362. u
t
n
o
t
b
o
ys
C
o
rr
el
at
io
n
b
et
w
ee
n
fa
m
ily
v

363. io
le
n
ce
a
n
d
P
TS
D
(p
<
0
.0
1)
Fa
yy
ad
(2
01
7)
[4
7]
Le

364. b
an
o
n
Pr
ev
al
en
ce
o
f v
io
le
n
ce
in
t
h
e
o
ve
ra
ll
g

365. ro
u
p
n
o
t
g
iv
en
38
%
o
f t
h
e
st
u
d
en
ts
h
ad
p
o

366. st
‑ w
ar
m
en
ta
l h
ea
lt
h
p
ro
b
‑
le
m
s
as
m
ea
su
re
d
b

367. y
th
e
SD
Q
p
lu
s
im
p
ac
t
va
ri
ab
le
36
%
h
ad
a
C
RI
ES

368. s
co
re
a
b
o
ve
3
0
(P
TS
D
)
D
eg
re
e
o
f w
ar
e
xp
o
su

369. re
w
as
a
s
ig
n
ifi
ca
n
t
p
re
d
ic
to
r
o
f
b
o
th
S
D

370. Q
(O
R
1.
42
; 9
5%
C
I 1
.1
2–
1.
80
) a
n
d
C
RI
ES
(O
R
1.
41
; 9

371. 5%
C
I 1
.1
1–
1.
80
)
St
ra
ti
fie
d
b
y
SD
Q
s
co
re
(L
o
w
S

372. D
Q
s
co
re
g
ro
u
p
=
n
o
p
ro
b
le
m
; H
ig
h
o
r
b

373. o
rd
er
lin
e
SD
Q
s
co
re
=
p
o
st
w
ar
p
ro
b
le
m
)
Pa

374. re
n
ts
h
it
: L
o
w
S
D
Q
s
co
re
g
ro
u
p
=
2
%
p
ar
en

375. ts
h
it
; h
ig
h
SD
Q
s
co
re
=
1
3.
7%
(p
=
<
0
.0
01
)
Pa

376. re
n
ts
h
it
e
ac
h
o
th
er
: L
o
w
S
D
Q
s
co
re
g
ro
u
p

377. =
2
%
p
ar
en
ts
h
it
; h
ig
h
S
D
Q
s
co
re
=
1
1.
6%
(p

378. =
0
.0
01
)
Fa
ce
d
fa
m
ily
v
io
le
n
ce
: L
o
w
S
D
Q
s
co

379. re
g
ro
u
p
=
1
7.
5%
p
ar
en
ts
h
it
; h
ig
h
S
D
Q
s
co

380. re
=
3
7.
4%
(p
=
0
.0
01
)
St
ra
ti
fie
d
b
y
C
RI
ES
s
co
re

381. (C
RI
ES
<
3
0
=
n
o
t
in
d
ic
at
in
g
PT
SD
; ≥
3
0
in
d

382. ic
at
in
g
P
TS
D
)
Fa
m
ily
v
io
le
n
ce
: C
RI
ES
<
3
0
=
1

383. 9.
8%
; C
RI
ES
≥
3
0
=
3
5.
2%
(p
v
al
u
e
=
0
.0
13
)
O

384. ’L
ea
ry
(2
01
8)
[2
7]
A
fg
h
an
is
ta
n
71
%
o
f r
ep
o
rt
ed
s

385. o
m
e
le
ve
l o
f p
h
ys
ic
al
v
io
le
n
ce
A
t
h
o
m
e:
3
6.

386. 2%
w
er
e
h
it
o
r
h
u
rt
, 8
6.
1%
s
cr
ea
m
ed
a
t
ag
g
re

387. ss
iv
el
y,
7
0%
c
al
le
d
n
am
es
, 7
0.
7%
w
er
e
p
u
sh
ed
,

388. g
ra
b
b
ed
o
r
ki
ck
ed
; n
o
c
h
ild
re
p
o
rt
ed
s
ex
u
al

389. a
b
u
se
Page 13 of 19Devakumar et al. Confl Health (2021)
15:74
Ta
b
le
4
(
co
n
ti
n
u
ed
)
A
u
th
o

390. r
Pr
ev
al
en
ce
o
f f
am
ily
v
io
le
n
ce
Pr
ev
al
en
ce
o
f a
m
en

391. ta
l h
ea
lt
h
p
ro
b
le
m
Ev
id
en
ce
o
f a
ss
o
ci
at
io
n
b
et

392. w
ee
n
fa
m
ily
v
io
le
n
ce
a
n
d
m
en
ta
l h
ea
lt
h
p
ro

393. b
le
m
Pa
n
te
r‑
Br
ic
k
(2
01
1)
[4
3]
A
fg
h
an
is
ta
n
Fa
m

394. ily
v
io
le
n
ce
w
as
re
p
o
rt
ed
in
4
7%
b
y
at
le
as
t
o
n

395. e
in
fo
rm
an
t
o
ve
r
th
e
p
re
vi
o
u
s
ye
ar
11
.5
%
fa
m

396. ily
‑ l
ev
el
v
io
le
n
ce
(s
ev
er
e
p
h
ys
ic
al
b
ea
ti
n
g
s)

397. Fa
m
ily
v
io
le
n
ce
(s
ev
er
e
b
ea
ti
n
g
) w
as
a
ss
o
ci
at

398. ed
w
it
h
an
in
cr
ea
se
in
S
D
Q
(p
=
<
0
.0
1)
a
n
d
C

399. RI
ES
(p
=
<
0
.0
5)
sc
o
re
s
b
u
t
n
o
t
d
ep
re
ss
io

400. n
(D
SR
S)
Fo
r
SD
Q
, s
co
re
s
in
cr
ea
se
d
b
y
1.
85
p
o
in

401. ts
(C
I 0
.0
3,
3
.6
6)
w
it
h
t
ra
u
m
at
ic
b
ea
ti
n
g
s

402. an
d
1
.2
6
p
o
in
ts
(C
I 0
.5
0,
2
.0
3)
w
it
h
a
fa
m
ily

403. m
em
b
er
w
h
o
is
v
io
le
n
t
at
h
o
m
e
Pa
n
te
r‑
Br
ic

404. k
(2
01
5)
[4
2]
A
fg
h
an
is
ta
n
27
%
re
p
o
rt
d
o
m
es
ti

405. c
vi
o
le
n
ce
in
t
h
e
la
st
y
ea
r
M
en
ta
l h
ea
lt
h
w
as

406. m
ea
su
re
d
a
t
tw
o
t
im
ep
o
in
ts
T
1
an
d
T2
. M
ea
n

407. s
co
re
s
at
e
ac
h
t
im
e
p
o
in
t
w
er
e:
C
RI
ES
: T
1
=

408. 8
.0
; T
2
=
5
.9
D
SR
S:
T
1
=
9
.5
; T
2
=
7
.3
SD
Q
:T
1
=

409. 9
.0
; T
2
=
9
.4
A
d
ju
st
ed
O
R:
4
.8
4
(p
<
0
.0
1)
s
tr

410. es
so
r
o
f d
o
m
es
ti
c
vi
o
le
n
ce
ca
u
si
n
g
s
u
st

411. ai
n
ed
d
is
tr
es
s
Sa
ile
(2
01
6)
[2
8]
U
g
an
d
a
88
.9
%
w

412. er
e
ex
p
o
se
d
t
o
a
t
le
as
t
o
n
e
ev
en
t
fr
o
m
t

413. h
e
fa
m
ily
v
io
le
n
ce
s
p
ec
tr
u
m
. M
ea
n
n
u
m
b
er

414. o
f f
am
ily
vi
o
le
n
ce
a
d
ve
rs
e
ev
en
ts
=
3
.8
5
(S
D

415. =
3
.3
3)
77
%
e
xp
er
ie
n
ce
d
b
ei
n
g
h
it
w
it
h
a
n

416. o
b
je
ct
53
%
e
xp
er
ie
n
ce
d
a
ct
s
o
f v
er
b
al
a
b
u

417. se
42
%
w
er
e
th
re
at
en
ed
38
%
re
p
o
rt
ed
t
o
h
av
e
w

418. it
n
es
se
d
o
th
er
fa
m
ily
m
em
b
er
s
b
ei
n
g
b
ea
te
n

419. , p
u
n
ch
ed
, o
r
ki
ck
ed
Se
ve
re
p
h
ys
ic
al
m
al
tr
ea
tm
en

420. t:
15
%
w
er
e
p
u
n
ch
ed
o
r
ki
ck
ed
o
n
t
h
e
b
o
d

421. y
3%
w
er
e
b
u
rn
t
w
it
h
h
o
t
w
at
er
o
r
a
ci
g
ar

422. et
te
o
n
p
u
rp
o
se
4%
o
f c
h
ild
re
n
w
er
e
th
re
at
en
ed

423. t
o
b
e
ki
lle
d
PT
SD
=
3
.3
–7
.2
%
D
ep
re
ss
io
n
=
2

424. 6.
3–
38
.2
%
A
d
ju
st
ed
m
o
d
el
fo
r
th
e
as
so
ci
at
io
n

425. b
et
w
ee
n
fa
m
ily
vi
o
le
n
ce
a
n
d
m
en
ta
l h
ea
lt
h

426. o
u
tc
o
m
es
:
SD
Q
=
b
et
a
co
effi
ci
en
t
0.
24
(p
<
0
.0

427. 01
)
C
D
I s
co
re
(d
ep
re
ss
io
n
s
ym
p
to
m
s)
=
b
et
a
co

428. effi
ci
en
t
0.
17
(p
<
0
.0
01
)
U
PI
D
s
co
re
(P
TS
D
) =
b

429. et
a
co
effi
ci
en
t
0.
11
(p
<
0
.0
5)
M
ed
ia
ti
o
n
p
at
h
w

430. ay
s
M
o
d
el
a
ss
es
si
n
g
t
h
e
eff
ec
t
si
ze
o
f t
ra
u

431. m
at
ic
e
xp
o
su
re
le
ad
in
g
t
o
fa
m
ily
v
io
le
n
ce
t

432. o
c
h
ild
p
sy
ch
o
p
at
h
o
lo
g
y:
SD
Q
=
0
.1
7
(9
5%
C

433. I 0
.1
0,
0
.2
7)
C
D
I s
co
re
(d
ep
re
ss
io
n
s
ym
p
to
m
s)
=

434. 0
.0
7
(9
5%
C
I 0
.0
2,
0.
12
)
U
PI
D
s
co
re
(P
TS
D
) =
0

435. .0
6
(9
5%
C
I ‑
0.
01
, 0
.1
5)
M
o
d
el
a
ss
es
si
n
g
t
h
e

436. eff
ec
t
si
ze
o
f t
ra
u
m
at
ic
e
xp
o
su
re
le
ad
in
g
t
o

437. fa
m
ily
v
io
le
n
ce
t
o
c
h
ild
p
sy
ch
o
p
at
h
o
lo
g
y,

438. m
ed
ia
te
d
b
y
p
er
ce
iv
ed
m
at
er
n
al
c
ar
e:
SD
Q
=

439. 0
.0
7
(9
5%
C
I 0
.0
3,
0
.1
1)
C
D
I s
co
re
(d
ep
re
ss
io
n
s

440. ym
p
to
m
s)
=
0
.0
4
(9
5%
C
I 0
.0
2,
0.
07
)
U
PI
D
s
co

441. re
(P
TS
D
) =
0
.0
4
(9
5%
C
I 0
.0
1,
0
.0
8)
Sr
is
ka
n
d
ar
aj

442. ah
(2
01
5)
[4
1]
Sr
i L
an
ka
83
.8
%
re
p
o
rt
ed
a
t
le
as
t
o

443. n
e
ev
en
t
o
f v
ic
ti
m
is
at
io
n
at
h
o
m
e
an
d
7
1.

444. 6%
t
h
at
t
h
e
vi
o
le
n
ce
w
as
in
t
h
e
la
st
m
o
n

445. th
,
76
.9
%
w
er
e
sl
ap
p
ed
o
n
b
o
d
y,
a
rm
s
o
r
le

446. g
s,
4
4.
8%
h
it
w
it
h
h
ar
d
o
b
je
ct
s,
3
7.
3%
t
h

447. re
at
en
ed
v
er
b
al
ly
, 1
2.
8%
h
ad
a
t
le
as
t
o
n
e
in

448. ju
ry
, 5
%
n
ee
d
ed
m
ed
ic
al
t
re
at
m
en
t
M
ea
n
n
u
m

449. b
er
o
f i
n
ti
m
at
e
p
ar
tn
er
v
io
le
n
ce
e
ve
n
ts
fo
r

450. th
e
m
o
th
er
is
3
.4
in
t
h
e
p
as
t
ye
ar
Ex
p
o
su
re
t

451. o
m
as
s
tr
au
m
a
ev
en
ts
w
as
a
ss
o
ci
at
ed
w
it
h
vi

452. ct
im
is
at
io
n
o
f t
h
e
ch
ild
b
y
b
o
th
t
h
e
m
o
th
er

453. a
n
d
t
h
e
fa
th
er
C
D
I,
C
h
ild
D
ep
re
ss
io
n
In
ve
n

454. to
ry
; C
I,
co
n
fid
en
ce
in
te
rv
al
; C
RI
ES
, C
h
ild
R
ev
is
ed
Im

455. p
ac
t
o
f E
ve
n
ts
S
ca
le
. S
co
re
o
f 3
0
o
r m
o
re
in
d
ic

456. at
es
P
TS
D
; D
SR
S,
D
ep
re
ss
io
n
S
el
f R
at
in
g
S
ca
le
; O

457. R,
O
d
d
s
ra
ti
o
; S
D
Q
, S
tr
en
g
th
s
an
d
D
iffi
cu
lt
ie

458. s
Q
u
es
ti
o
n
n
ai
re
; U
PI
D
, U
PI
D
, U
n
iv
er
si
ty
o
f C

459. al
ifo
rn
ia
a
t
Lo
s
A
n
g
el
es
P
TS
D
R
ea
ct
io
n
In
d
ex

460. fo
r D
SM
-I
V
Page 14 of 19Devakumar et al. Confl Health (2021)
15:74
‘domicile’ (community-based sample) participants
experiencing domestic abuse had symptoms of neu-
rosis according to the Cornell Index. 17.1% of women
who had 2–4 trauma exposures reported depression
compared with 12.0% of women who had no exposure
to trauma in Afghanistan.
In children, the association with depression was less
consistent, though often not measured. Strengths and
Difficulties Questionnaire (SDQ) scores, which meas-
ure a range of psychosocial outcomes, were also higher
in the studies from Lebanon [47] and Afghanistan [42].
Panter-Brick found increases in SDQ score with trau-
matic beatings and family violence at home [43], and
those who had sustained distress compared to the low
distress group (measured by CRIES) had an increased
risk (adjusted OR 4.84) of living in a family with ongo-
ing stressful domestic violence [42]. Saile et al. exam-
ined the pathway between conflict, family violence and
mental health in children. They found small changes in
SDQ scores, depression symptoms and PTSD [28].
Women’s perspectives on armed conflict or how

461. their experiences of conflict may have affected their
mental health were reported in relation to financial
stress and their concerns about the care of their chil -
dren. For instance, women participating in focus group
discussions in Côte d’Ivoire reported that financial
stress made them lose interest in having sex with their
husbands, to which some husbands might respond
with sexual violence:
When the woman is not at ease… you know, there
is no money to properly take care of the children,
she is preoccupied and she does not feel like hav-
ing sex so it happens that the man rapes her [36].
Another study of returned female combatants in
Northern Uganda explored the stresses women felt
about the care of their children when they returned
from situations in which they had been abducted and
forced to marry combatants:
When I had just returned from the bush with my
children, I used to have lots of thoughts [worries]
on how I will look after the children in case of
sickness since their father is not there [34].
Rees et al.[29] uniquely explored the use of violence
by women as a result of the armed conflict in Timor-
Leste, with the concept of ‘explosive anger’ as an expla-
nation for high rates of violence against children.
3. Variation of the association of family violence with
mental health by type of conflict, sex of perpetrator,
type of violence
Type of conflict
In the quantitative studies, we were unable to directly

462. answer our question as to whether the association
between family violence and changes in mental health
differed by type of conflict. Only the three studies from
Uganda were interstate [28, 48, 49]. No discernable differ -
ence could be seen between these and the intrastate con-
flicts (Democratic Republic of Congo [44], Côte d’Ivoire
[16, 30, 39], Lebanon [47, 50], Liberia [38], Palestine [26]
and Sri Lanka [12, 41]), or the internationalised intrastate
conflicts (Afghanistan [13, 27, 40, 43], Bosnia and Herze-
govina [37] and Iraq [51]).
The qualitative studies also did not engage with this
concept and there were no comparative case studies in
the review.
Sex of perpetrator
Limited data were available on the prevalence of female-
perpetrated family violence, and we were unable to assess
whether the association between family violence and
mental health problems varied according to the sex of the
perpetrator. The majority of studies measuring violence
against women focused on male spouses in the context
of heterosexual married relationships. Two studies, Usta
et al. [50] and Hossain et al. [39], defined domestic vio-
lence as including violence from family members. In
rural Côte d’Ivoire, Hossain et al. [39] demonstrated the
lifetime prevalence of sexual violence from female per -
petrators including female family members was 0.1%.
Among women, lifetime prevalence of physical violence
from female family members was 8.9%; prevalence of life-
time physical violence from male family members was
also 8.9%.
Type of violence
We were unable to assess whether the association
between family violence and mental health problems var-

463. ied according to type of violence; only one study provided
suitably disaggregated data. Umubyeyi et al. [46] found
that PTSD and generalised anxiety disorder (GAD) were
most strongly associated with sexual violence (PTSD
aOR 4.20 (95% CI 2.22, 7.95); GAD aOR 6.37 (95% CI
3.45,11.79)), followed by physical (PTSD aOR 4.70 (95%
CI 2.65, 8.35); GAD aOR 3.16 (95% CI 1.67,5.95)) and
psychological violence (PTSD aOR 4.34 (95% CI 2.54,
7.43); GAD aOR 2.97 (95% CI 1.62, 5.45)). Physical vio-
lence was more closely associated with suicide risk fol -
lowed by psychological violence and sexual violence.
Major depressive episode showed the strongest associa-
tion with psychological violence, followed by sexual vio-
lence, and physical violence.
Page 15 of 19Devakumar et al. Confl Health (2021)
15:74
4. Impact of gender norms on the mental health of
women and children experiencing family violence
The conflict-related triggers identified in qualitative
articles, such as financial stress and alcohol use, were
explained by both authors and study participants as
rooted in gender norms. In situations of conflict, men
may not be able to fulfill their socially-expected roles
such as providing financially for the household [35],
and in some cases women become the main household
providers [30]. This has indirect impacts on the mental
health of women and children by increasing men’s stress
and sense of insecurity in ways that increase family vio-
lence [29, 30, 35].
Guruge et al. explained how the use of violence by men

464. becomes a means of maintaining a sense of power and
control in the face of the instability brought on by con-
flict, which threatened gender norms that men rely upon
for their identity and sense of security:
With death, disappearances, disability and loss of
traditional sources of livelihood (such as fishing)
affecting many men, women in war-affected areas
of Sri Lanka have taken on being the breadwinner
and head of household roles, and have become more
active in their communities. When there is a disrup-
tion of established social relationships and roles in
war and post-war contexts, men are known to use
violence as means of re-exerting control and power
to maintain roles that are consistent with social
norms. [35]
Related to this, economic instability often opens up
new opportunities for women to earn, which men may
feel threatened by, contributing to their use of violence
[29, 30, 35]. Shuman et al., for example, discussed how
change in women’s roles arose in Côte d’Ivoire as an
underlying cause of family violence:
In post-crisis Côte d’Ivoire, economic opportunities
are scarce and in some cases, women have become
the financial providers for their families. While
women welcomed opportunities to have more con-
trol over resources in their relationships, they also
described being perceived as a threat by their part-
ners. Among men, this perceived loss of control and
traditional gender responsibilities was discussed as
an underlying cause of all forms of IPV. [30]
The stress reported by men was also highlighted as a
reason for their increased drinking behaviour. In Côte

465. d’Ivoire, Northern Uganda and Sri Lanka, instability and
financial problems arising from the conflict were seen as
triggers for problematic drinking by men, which contrib-
uted in turn to increased episodes of violence[34–36].
The qualitative data also support the impact of gen-
der norms on the mental health of women and children
experiencing violence directly through their experi-
ence of violence-related stigma. [29, 30]. Sexual violence
was frequently described as especially stigmatising for
women. For instance, Annan and Brier’s study of women
abducted by the Lord’s Resistance Army in Northern
Uganda described the lower status of women who return
to their communities as women who had been ‘married’
or sexually abused. They described how the fear of this
stigma drives women to agree to be married either to vio-
lent men or as second wives, which is attached to lower
status in the household, in turn increasing the risk of
violence:
While polygamous marriages are common, women
as second wives are seen to have less power in house-
holds than first wives. One social worker observed
that women’s insecurities about social status com-
bined with economic pressures to push them into
relationships faster than their peers – some entering
negative relationships, confirming their insecurities
about having less value than other women. [29]
Annan and Brier (2010) also argued that forced mar-
riage as part of armed conflict may have similar long-
term psychological impacts on women as childhood
experiences of violence, with similar consequences for
difficult relationships with men in adulthood.
The qualitative results predominantly related to vio-

466. lence against women, but one study, Kohli et al. (2015),
highlighted how the stigmatisation of violence against
women has affected the mental health of children by con-
tributing to social isolation in South Kivu, DRC:
Further, participants described how living in an
unstable and violent household negatively affected
children’s interaction with community members, as
the entire family could become isolated and disre-
spected in the community. Male and female partici-
pants in this study described households with IPV
as unable to progress or have stability in their lives.
[31]
Study quality
Quality assessments for both quantitative and qualitative
studies are in the Additional file 1: Appendix. Overall,
there was a low risk of bias in most of the quantitative
studies. Bias existed in identifying and dealing with con-
founding, which we assessed as high or unclear in seven
studies [30, 37, 40, 45, 48, 50]. Sampling criteria were
defined in all studies, with most adopting a version of
random sampling. In some, for example O’Leary et al.
Page 16 of 19Devakumar et al. Confl Health (2021)
15:74
[27], purposive sampling was used, leading to a likely
bias.
The qualitative studies were generally of high quality,
with the exception of the categories of cultural and theo-
retical positionality and reflexivity, for which we felt that
all studies were lacking.

467. Discussion
Conflict has a pervasive impact on people and societies.
Conflict-related violence is well documented, but less
well known is how exposure to armed conflict and its
social and economic consequences can influence family
violence and mental health problems. Our results pro-
vided evidence that family violence is common and is
associated with poor mental health outcomes, but varia-
bility in outcomes and measurement meant that we were
not able to support or refute the hypothesis that the prev-
alence increases in conflict settings nor that it changes
the association with mental disorders.
Worldwide, approximately one in three women have
survived physical or sexual violence, but the prevalence
varies greatly by location. By WHO region, lifetime prev-
alence of physical or sexual intimate partner violence is
highest in the Pacific (Melanesia 51%, Micronesia 41%,
Polynesia 39%), South Asia (35%) and sub-Saharan Africa
(33%) [52]. According to a recent WHO report, many
countries with a recent history of armed conflict, includ-
ing Afghanistan and Papua New Guinea, have some of
the highest prevalences of physical and sexual IPV (46%
and 51%, respectively), but data from conflict settings
remain poor [52]. Our review found similar proportions,
but the studies varied widely, most likely representing
actual differences in prevalence, but also methodologi -
cal issues such as study design, data availability, and tools
used.
Studies of violence against children showed the almost
ubiquitous presence of violence. It is estimated that one
billion children have suffered from violence in the pre-
ceding year [4]. A systematic review by Hillis et al. from
96 countries (n = 38) summarised the prevalence of vio-

468. lence over the past year in any country. In Africa, Asia
and North America, approximately half to two-thirds of
children suffered violence. Prevalence in Latin America,
Oceania, and Europe was a little lower, mostly at around
one-third[4]. Direct comparison is limited as the coun-
tries included in the review by Hillis et al. did not over-
lap with ours, with the exception of Uganda, where they
reported data from a randomised controlled trial [53].
Studies in our review reported recent violence at a simi -
lar prevalence in the studies from Afghanistan. The tw o
Sri Lankan studies appeared to show a higher prevalence,
reporting 64.2% [12] and 71.6% [41] in the past month
alone. Amongst Violence Against Children and Youth
Surveys (VACS) studies, only one country – Uganda –
has comparable data [54]. This study reported a similar
prevalence of lifetime family violence (59% against girls
and 68% against boys). Conflicts themselves vary and the
impact on individual families is different. Other factors
may also affect health. For example, in a study from Sri
Lanka, the population also experienced the Indian Ocean
tsunami [12].
The finding of an association between violence and
mental health problems is not new [55, 56], and was
reported in approximately half the studies of violence
against women in our review. The studies were not ame-
nable to meta-analysis, nor could comparisons be drawn
readily with non-conflict settings. The most consist-
ent association was with PTSD. This may be due to an
increased risk of PTSD, as has been commonly shown
in conflict-affected populations, but may also reflect a
bias in the topics that are researched. For studies that
included suicide risk and substance use as additional
outcome measures, the association between exposure
to family violence and prevalence broadly followed the

469. dose–response relationship observed for PTSD.
Amongst studies of violence against children, consist-
ent associations were found between family violence and
symptoms of mental health problems. Three studies con-
structed structural equation models to explore associa-
tions [13, 26, 28]. Heath et al. [26] and Jewkes et al. [13]
treated violence and mental health problems (PTSD and
depression) as co-outcomes and did not examine the
association between the two. Jewkes et al. showed the
importance of household wealth and previous childhood
trauma [13]. Saile et al.[28] proposed maternal care as a
mediating factor that could reduce adverse mental health
symptoms.
Armed conflict can challenge dominant masculinities
that cast men as providers and heads of family in ways
that contribute to perpetration of family violence [31, 33,
36]. Gender norms undermine women’s mental health
during conflict by contributing to shame and stigma
associated with experiencing both sexual violence and
family violence more broadly, and this can also contrib-
ute to the social isolation of children [31]. However, the
same destabilising effects of armed conflict can also give
women new economic opportunities and contribute to
their economic and social empowerment [29, 30, 35].
Strengths and limitations
The main strengths of the review included its robust
search strategy, its use of dual reviewers, and analysis
and synthesis of both quantitative and qualitative data.
The review protocol was prospectively registered and
the reporting followed established standards. Limita-
tions should, however, be noted. Studies were highly

470. Page 17 of 19Devakumar et al. Confl Health (2021)
15:74
heterogeneous and meta-analysis could not be conducted
and pooled estimates of the association between expo-
sure to family violence and mental health problems could
not be calculated. Violence is likely to have been under-
reported, and the extent of under-reporting and other
biases in data collection would vary between studies and
settings. Although a standardised approach for research
on violence against children has been advocated (the
Violence Against Children and Youth Surveys (VACS)),
the studies included in the review did not follow this
approach. Variation in outcomes would in part be due
to the definitions used, with no set definition of family
violence being accepted [57]. Our definition of family
violence resulted in the inclusion of studies of violence
against women and violence against children, but rarely
was family violence explicitly defined within the studies.
Although we found consistent evidence of association
between exposure to family violence and mental health
problems for both adults and children, we can make lim-
ited inferences regarding causality due to the predomi-
nance of cross-sectional studies within the review. It is
possible that both family violence and changes in mental
health are outcomes of exposure to conflict, as described
by Heath et al. [26] and Jewkes et al. [13], and reverse
causality may occur [58].
In reviewing the qualitative studies, two forms of mal-
treatment of women (and children) not captured by our
search terms are potentially salient for women’s mental
health and could be rationalised under a broader concep-
tualisation of family violence. First, rejection and neglect

471. following women and children’s return from conflict-
related assault or time embedded with conflict groups
affects their ability to reintegrate into family life, with
implications for mental health. Second, sexual violence
by combatants to entrap girls and women into forced
unions could be viewed as initiating acts of both intimate
partnerships and IPV.
Conclusions
Our systematic review showed that family violence was
common in conflict settings and was associated with
mental health outcomes. However, we were unable to
determine whether prevalence or risk was greater than in
non-conflict settings. This gap in the review stems from a
lack of comparable data and reiterates the need for stand-
ardised measurement of both violence against women
and violence against children. It also draws attention to
the need to break down existing silos between research
on violence affecting women and that affecting children
to build a more comprehensive picture of the overlapping
risks and mental health outcomes of violence within fam-
ilies [59]. A far more robust understanding of the impacts
of armed conflict on families and their experiences of
violence is urgently needed to develop comprehensive
support systems in conflict-affected settings.
Supplementary Information
The online version contains supplementary material available at
https:// doi.
org/ 10. 1186/ s13031‑ 021‑ 00410‑ 4.
Additional file 1: PRISMA checklist, search terms, coding
framework for
qualitative papers and quality assessments.

472. Acknowledgements
None.
Authors’ contributions
The work was conceived by DD, JM and NM. Database
searching by CR and
NU. Data extraction and reporting by AN, AP, AU‑ C, CR, DD,
NU and JM. Articles
were assessed for quality by AP, AU‑ C, DD, JM. The
manuscript was read and
edited by all authors. All authors read and approved the final
manuscript.
Funding
This review was funded by the National Institute for Health
Research (Ref
17/63/47).
Availability of data and materials
Data sharing is not applicable to this article as no datasets were
generated or
analysed during the current study.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Institute for Global Health, University College London,

473. London WC1N 1EH,
UK. 2 Hull University Teaching Hospitals NHS Trust, Hull,
UK. 3 UCL Medical
School, 74 Huntley Street, London, UK. 4 London School of
Hygiene and Tropi‑
cal Medicine, London, UK. 5 Sangath, Porvorim, India. 6
King’s College London,
London, UK.
Received: 10 June 2021 Accepted: 23 September 2021
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