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Exploring the associations between intimate partner violence and women’s
mental health: Evidence from a population-based study in Paraguay
Kanako Ishida
a
,
*
, Paul Stupp
a
, Mercedes Melian
b
, Florina Serbanescu
a
, Mary Goodwin
a
a
Division of Reproductive Health, Centers for Disease Control and Prevention, 4770 Buford Hwy, NE Mail stop K-23, Atlanta, GA 30341, USA
b
Paraguayan Center for Population Studies (Centro Paraguayo de Estudios de Población eCEPEP), Asunción, Paraguay
article info
Article history:
Available online 15 September 2010
Keywords:
Paraguay
Intimate partner violence
Child abuse
Sexual abuse
Mental health
Common mental disorders
Suicidal ideation
Latin America
Women
abstract
Using a nationally representative sample from the 2008 Paraguayan National Survey of Demography and
Sexual and Reproductive Health, we examine the association between emotional, physical, and sexual
intimate partner violence (IPV) and mental health among women aged 15e44 years who have ever been
married or in a consensual union. The results from multivariate logistic regression models demonstrate
that controlling for women’s socioeconomic and marital status and history of childhood abuse and their
male partners’unemployment and alcohol consumption, IPV is independently associated with an
increased risk for common mental disorders (CMD) and suicidal ideation measured by the Self Reporting
Questionnaire (SRQ-20). IPV variables substantially improve the explanatory power of the models,
particularly for suicidal ideation. Emotional abuse, regardless of when it occurred, is associated with the
greatest increased risk for CMD whereas recent physical abuse is associated with the greatest increased
risk for suicidal ideation. These findings suggest that efforts to identify women with mental health
problems, particularly suicidal ideation, should include screening for the types and history of IPV
victimization.
Published by Elsevier Ltd.
Introduction
Although largely neglected by global health policy (Patel, 2007),
mental disorders are estimated to constitute 14% of the global
burden of disease and disability (Prince et al., 2007). Women are
about 1.5e3.0 times more likely than men to experience depres-
sion, the single most common mental distress (Kuehner, 2003).
Women’s higher risk for mental health problems has been attrib-
uted to the burden of childbearing and childrearing roles, as well as
to social and economic disadvantages associated with female
gender (WHO & UNFPA, 2009). Mental health status among
mothers has been closely linked with the health and survival of
their children. Evidence from developing countries has shown that
children whose mothers suffer from mental disorders are at
a higher risk for low birth weight (Patel & Prince, 2006), malnu-
trition (Harpham, Huttly, De Silva, & Abramsky, 2005), and other
developmental problems (Walker et al., 2007).
Intimate partner violence (IPV) is another significant problem
associated with gender. The prevalence of IPV against women has
been increasingly documented and recognized as an important
public health issue worldwide (Garcia-Moreno, Jansen, Ellsberg,
Heise, & Watts, 2006). Results from a growing body of work in
developing countries have consistently shown a significant asso-
ciation between IPV against women and women’s mental health
(Ellsberg, Jansen, Heise, Watts, & Garcia-Moreno, 2008; Kumar,
Jeyaseelan, Suresh, & Ahuja, 2005; Patel et al., 2006; Pillai,
Andrews, & Patel, 2008). This evidence is important given that
lack of attention to the psychosocial contexts of mental health
problems among female patients has been cited as one cause of an
overreliance on psychotropic medication in the treatment of these
problems (Fischbach & Herbert, 1997). This overreliance on medi-
cation may, in turn, have led to an increase in the frequency and
chronicity of violence against women and mental health problems
attributable to such violence. However, a review of past literature
on mental health outcomes and IPV victimization among women
reveals a substantial overlap in their determinants, indicating
a need to test whether an independent association exists between
IPV victimization and poor mental health outcomes, or whether the
association is explained by common causal factors.
This analysis controls for women’s socioeconomic and marital
status, their history of childhood violence, and characteristics of
their male partners to investigate whether IPV is independently
associated with poor mental health outcomes. Our research
extends upon and complements earlier research from developing
countries in two other ways. First, it is based on a nationally
*Corresponding author. Tel.: þ1 404 906 4929.
E-mail address: kishida@cdc.gov (K. Ishida).
Contents lists available at ScienceDirect
Social Science & Medicine
journal homepage: www.elsevier.com/locate/socscimed
0277-9536/$ esee front matter Published by Elsevier Ltd.
doi:10.1016/j.socscimed.2010.08.007
Social Science & Medicine 71 (2010) 1653e1661
representative sample of women of reproductive age from
Paraguay, unlike most previous studies on mental health, which
used health facility data for a subpopulation of women with health
care needs, such as those who are pregnant. These studies thus may
be biased in that socioeconomic status has been shown to be
positively associated with health care utilization (Fisher, Mello, &
Izutsu, 2009) and it may also be correlated with the risk for
violence or mental disorders. Second, we compare and contrast the
associations between IPV victimization and two measures of poor
mental health status: common mental disorders (CMD) and
suicidal ideation, using the Self Reporting Questionnaire (SRQ-20).
We also distinguish timings and typesdemotional, physical, and
sexualdof IPV. We aim to shed more light on mechanisms through
which IPV affects women’s mental health and provide important
programmatic implications.
Background: mental health and violence
Here, we review the existing literature on the associations
between mental health and four potential determinants of poor
mental health outcomesdwomen’s socioeconomic and marital
status, their male partners’unemployment and alcohol consump-
tion, and women’s history of violence victimization as a childdand
between IPV victimization and these four key covariates. We
particularly highlight how these covariates may be linked to the
risk of IPV victimization, thereby potentially explaining the asso-
ciation between mental health and IPV.
Socioeconomic status
As an important health policy theme, the nexus between
poverty and burden of both mental and physical diseases has been
increasingly investigated. Findings from most recent studies
suggest that this association is even stronger in low- and middle-
income countries, particularly those undergoing rapid economic
growth and experiencing widening economic disparities, than in
developed countries (Patel, 2007). In a review of 11 studies from
less-developed countries, Patel and Kleinman (2003) argue that
stress factors associated with poverty, including financial insecu-
rity, stigmatization, and discrimination, may at least partially
explain the greater vulnerability of the poor to psychiatric disor-
ders. However, it is also argued that other individual characteristics,
such as being older, female, widowed, and in poor physical health,
are more important determinants of mental health than poverty
per se (Das, Do, Friedman, McKenzie, & Scott, 2007).
Although the same factors associated with povertydmaterial
deprivation and financial stressdhave been hypothesized to be key
determinants of IPV, empirical evidence for their association with
IPV has been mixed (Krahé, Bieneck, & Möller, 2005). Recent studies
find more consistently protective effects of educational attainment
(Bates, Schuler, Islam, & Islam, 2004; Flake, 2005) than higher
economic status measured by household wealth (Yount, 2005). Yet
the risk of IPV in many other less-developed countries shows no
associations with either educational attainment or economic status
according to recent cross-national studies by Hindin, Kishor and
Ansara (2008) and Kishor and Johnson (2006). In addition, the
effects of these socioeconomic indicators may depend on whether
violence is physical or sexual (Koenig, Stephenson, Ahmed,
Jejeebhoy, & Campbell, 2006), suggesting the complexity of the
association between socioeconomic status and the risk for IPV.
Marital status
Union dissolution has been commonly identified as one conse-
quence of IPV (Ellsberg, Winkvist, Peña, & Stenlund, 2001) and
a risk factor for poor mental health (Bierman, Fazio, & Milkie, 2009).
However, the linkage among mental health, IPV, and consensual
marital status, a common alternative to marriage in Latin America
(Castro Martin, 2002), has been less studied. The informal “trial
marriage”nature of consensual unions, marked by either or both
partners’lower level of investment in the relationship (Nock,1995)
and heightened sexual jealousy (Wilson & Daly, 2001), may make
women in such unions more vulnerable to both IPV (Flake, 2005)
and poor mental health. Study results demonstrate a higher risk for
depression among women in consensual unions than among their
married counterparts (Brown, Bulanda, & Lee, 2005) and that this
risk differential is not fully attributable to social selection, that is,
a tendency of less mentally healthy women to be in consensual
unions (Marcussen, 2005).
Male partner’s unemployment and alcohol consumption
Unemployment and alcohol consumption among women’s male
partners may simultaneously increase women’s risk for IPV and
poor mental health. Hindin, Kishor, and Ansara (2008) and Kishor
and Johnson (2006) both concluded that alcohol consumption by
a male partner is a risk factor for IPV in all less-developed countries
that they studied. Although neither study found male partners’
unemployment to be significantly associated with their violent
behavior at home, results from some ethnographic studies in Latin
America suggest that failure to satisfy the breadwinning role may
prompt men to use alcohol and violence to reconstruct their
masculine identity (Fuller, 2000). The effects of a partner’s alcohol
consumption and unemployment on women’s mental health have
not been well explored; however, similar to the effects of poverty,
both factors may adversely affect women’s mental health by
increasing financial stress in the household.
Experience of violence during childhood
Several recent studies from less-developed countries have
found that experiences of violence during childhood, including
witnessing physical violence by the father against the mother,
consistently increases the risk for violence victimization later in life
(Flake, 2005; Gage, 2005; Hindin et al., 2008; Koenig et al., 2006;
Yount & Carrera, 2006; Yount & Li, 2008). Growing evidence,
although overwhelmingly from developed countries, has demon-
strated similarly long-lasting adverse effects of childhood abuse on
victims’mental health during adolescence and adulthood (Fletcher,
2009; Pillai et al., 2008; Schilling, Aseltine, & Gore, 2008), including
an increased risk for suicide (Dube et al., 2001; Johnson et al., 2002).
However, the extent to which being a victim of childhood violence
has direct consequence on mental health or mediated by IPVdthe
association between childhood violence victimization and poor
mental health outcomes may be explained by their respective
association with IPVdneeds to be clarified.
Domestic violence in Paraguay
Paraguay has had a moderately high IPV prevalence that is
comparable to that of other Latin American countries (24e47%,
Kishor & Johnson, 2006). Since the 1990s, legislative and judicial
systems in Latin America have taken significant steps toward
reducing levels of domestic violence. In 1994, Latin America
became the first region to draft and approve a regional convention
on the prevention, punishment, and eradication of violence against
women, commonly known as the “Convention of Belém do Pará”
(Macaulay, 2005). Paraguay ratified the convention and promul-
gated a civil law that offers protection to IPV victims and later penal
codes against the perpetration of IPV. However, assistance for IPV
K. Ishida et al. / Social Science & Medicine 71 (2010) 1653e16611654
victims in Paraguay is limited because of a lack of services and
training of personnel and poor enforcement of laws, compounded
by the prevailing poverty among women and their economic
dependence on men (Arrúa de Sosa, 2005). Moreover, a substantial
proportion of women maintain traditional perspectives on gender
roles and have a permissive attitude toward IPV (CEPEP, 2009). No
previous study of the mental health consequences of IPV or the
magnitude of mental health problems at the national level has been
conducted in Paraguay.
Data and methods
Data
This study is based on data from the 2008 Paraguayan National
Survey of Demography and Sexual and Reproductive Health
(Encuesta Nacional de Demografía y Salud Sexual y Reproductiva;
ENDSSR), conducted by the Paraguayan Center for Population
Studies (Centro Paraguayo de Estudios de Población; CEPEP), with
technical assistance from the U.S. Centers for Disease Control and
Prevention. The survey employed a multi-stage cluster sample
based on the 2002 census tracts: a total of 384 census tracts were
randomly selected; a number of households, proportional to the
size of the population, were randomly selected from each cluster,
and one woman aged 15e44 years was randomly selected from
each household for the interview. The individual response rate was
95.1%, and the final, nationally representative sample consists of
6540 women. Data were collected with a standardized question-
naire in face-to-face, household interviews conducted from June
through October 2008. The portion of the interview concerning IPV
was done for 4409 women who have ever been in either a marital
or a consensual union and only when privacy was secured, and
prior to the interview, the respondents were told that their infor-
mation would be handled with discretion. The details of the survey
can be found elsewhere (CEPEP, 2009). Sampling weight is applied
throughout the analysis to correct for unequal probabilities of
selection for survey participation due to complex multi-stage
sample design.
Measures of mental health
The 2008 ENDSSR included SRQ-20 developed by the World
Health Organization (WHO) in the 1980s as a screening tool for
CMD in primary care settings (WHO, 1994). CMD include depres-
sion, anxiety, irritability, poor memory/concentration, and somatic
complaints such as insomnia, fatigue, and headache. Since then, the
SRQ-20 has been translated into different languages, validated
locally, and used across cultures, including in Latin America
(Ludermir & Lewis, 2005). SRQ-20 has been shown to be compa-
rable with the General Health Questionnaire (GHQ-12) in Latin
America (Araya, Wynn, & Lewis, 1992; Mari & Williams, 1985).
Positive responses to the 20 items are added up to range from
0 to 20, and to maximize its predictive ability for clinically signifi-
cant mental disorders, we use a cut-point based on psychiatric
diagnoses in previous studies from Paraguay (Míguez, Pecci, &
Garrizosa, 1992), Chile (Vicente, Vielma, Rioseco, & Medina, 1994),
and Colombia (Lima, Pai, & Santacruz, 1991), and classify women
with at least 8 symptoms in the past four weeks as being at risk for
CMD.
1
Using this cut-point, 27.8% of women, who have ever been
married or in a consensual union, are categorized as potentially
having CMD.
In addition to women’s CMD risk, we consider their suicidal
ideation, captured by a single question in the SRQ-20, “Has the
thought of ending your life been on your mind (Ha tenido la idea de
quitarse la vida)?”While CMD is intended to capture the general
poor mental health status with multiple dimensions, suicidal
ideation alone captures a potentially severe and distinct form of
mental health problems and the risk for actual self-harm. Among
ever-in-union women, 3.1% reported suicidal ideation.
Measures of IPV
The survey also collected information on IPV experienced by
respondents during their lifetime and in the 12 months prior to the
interview based on the conflict tactic scales (Strauss, 1979), which
have been widely used in demographic and reproductive health
surveys across cultures. For this study, “intimate partner”was
defined as a current or former partner in either a consensual or
a marital union, and IPV was classified as being either emotional,
physical, or sexual. Emotional violence is determined by at least one
affirmative response when asked whether or not their male part-
ners had insulted them or made them feel bad about themselves;
humiliated them in front of others; done something to scare or
intimidate them; or threatened to hurt them or others that are
important to them. Physical violence is determined by at least one
affirmative response when asked whether or not they had been
slapped in the face; pushed; cornered; hit with a fist or an object;
kicked; dragged; threatened with a pistol, knife, or other objects;
strangled; burned; or had their hair pulled or an object thrown at
them. Sexual violence is defined as having been forced to have
sexual relations against their will, either as a result of physical force
or out of fear. In order to examine whether the mental health
consequences of IPV are immediate, long-lasting, or both, we use
two mutually exclusive time frames: within the previous 12
months (current) and more than 12 months ago (past).
Other key covariates and descriptive statistics
Table 1 lists key independent variables considered in the study.
Educational attainment is categorized into five groups, ranging
from incomplete primary or less to complete secondary or above.
Household wealth status is constructed based on a weighted sum of
household assets and amenities, such as refrigerators, TV sets, and
toilet facilities, and the type of materials used for roofing and
flooring in respondents’homes to capture the long-term accumu-
lation of wealth, where the weight is derived from principal
components analysis (Filmer & Pritchett, 2001). The sample is
stratified into five quintiles ranging from lowest to highest. Current
marital status is categorized into four groups: currently in a marital
union, currently in a consensual union, previously in a union
(currently separated, divorced, or widowed), and never in either
type of union. Consensual unions are as common as marital unions
in Paraguay with 24.8% and 29.1% in each category. Male partner’s
unemployment is not common, occurring only to 2.3% of women in
a union. Male partner’s alcohol consumption is categorized into
three levels based on its frequency observed in the last 12 months
of the union, and 18.3% drank “daily or weekly”(1e7 times per
week), 44.0%, “monthly”(1e3 times per month), and 37.7%, “less
than monthly”(<1 time per month). Variables for childhood
violence are constructed as dichotomous indicators of whether or
not respondents have ever been physically or sexually abused by
a non-partner, including family members, and whether or not they
have ever witnessed violence perpetrated by their father against
their mother, before the age of 15 years. Physical abuse is captured
by a question: “Have you ever been hit or maltreated physically by
someone, including family member?”Sexual abuse is defined as
1
In the sensitivity analysis, the results (not shown) were robust to various cut-
points (from 5/6 to 11/12) to define potential CMD.
K. Ishida et al. / Social Science & Medicine 71 (2010) 1653e1661 1655
having been raped, kissed, or forced to undress or perform sexual
acts against their will or as having had private body parts touched.
Witnessing parental violence is common, occurring to 23.9% of all
women who have ever been in a union, followed by physical
violence victimization with 20.5%. Child sexual abuse was experi-
enced by 1.8% of ever-in-union women in the sample.
Analytic approach
We conduct our analysis in two steps. We first investigate the
association between each type of current IPV (physical, emotional,
and sexual) and potentially overlapping risk factors for mental
health problems: women’s socioeconomic status, their marital
status (marital or consensual union), their male partners’unem-
ployment and alcohol consumption status, and whether they are
victims of, or witnesses to, violence as a child, using multivariate
logistic regression models. The sample for this step of our analysis
consists of 3934 women who are currently in a union; we exclude
women who are separated, divorced, or widowed at the time of the
survey because information about the timing of the union disso-
lution or death of the spouse is not available. Subsequently, after
presenting bivariate associations between IPV and the two indica-
tors of mental healthdCMD risk and suicidal ideation, we use
multivariate logistic regression models to estimate adjusted odds
ratios for the association between each of these risk factors and
mental health status. For this step, we use the full sample of 4409
women who have ever been in a union. We have three modelsdIPV
only (Model 1), the aforementioned four covariates only (Model 2),
and both IPV and the four covariates (Model 3). In order to inves-
tigate whether IPV is independently associated with mental health
outcomes, we compare Models 1 and 3 in the strength and signif-
icance of the association between IPV and mental health outcomes
in order to determine the extent to which the association can be
explained by the four covariates. We also use the log-likelihood
ratio test and the Bayesian Information Criterion (BIC) statistics
(Raftery, 1995) to assess the significance and size of the increased
explanatory power between Models 2 and 3.
For the second series of logistic regression models, the odds
ratios are based on Y
*
-standardized coefficients, which we calculate
by fixing the variance of the latent Yvariable, in order to facilitate
the comparisons of the coefficients among nested logistic regres-
sion models. This is because the coefficient estimates may other-
wise change even when variables added to the model are not
correlated with variables that are already in the model (Mare,
2006). A Y
*
-standardized coefficient indicates the expected
change expressed in standard deviations of the latent outcome
variable for a one-unit change in a given independent variable.
M-plus version 5.2 (Muthén & Muthén, 1998e2007) is used for the
analysis.
Results
Intimate partner violence
Emotional abuse is the most common type of IPV reported by
women who have ever been in a union: 36.0% reported having
experienced emotional violence at some time in their life, and 18.4%
reported having experienced it in the previous 12 months (Table 2).
The comparative figures for current physical and sexual violence are
6.7% and 3.3%, respectively.
Table 3 shows the correlates of IPV victimization experienced
in the last 12 months in adjusted odds ratios based on multivariate
logistic regression models. Neither women’s educational attain-
ment nor their household wealth quintile is significantly associ-
ated with risk for any type of violence. Women in a consensual
union are at a significantly higher risk for emotional and physical
IPV than legally married women as expected (ORs: 1.27 for
emotional and 1.78 for physical violence). Unemployment of
a male partner is also a significant risk factor for both emotional
and physical violence (ORs: 0.29 for emotional violence and 0.21
for physical violence). Women whose male partners drank at least
once a week are at the greatest risk for all three types of violence
(ORs: 4.16 for emotional, 5.95 for physical, and 6.02 for sexual
violence). Male partner’s drinking on a monthly basis is associated
with a significantly, but lesser increased risk for emotional and
physical violence. Finally, experiences of physical violence and
witnessing parental violence during childhood are similarly
important risk factors for all types of current IPV victimization;
however, childhood sexual violence is not significantly associated
with risk for any type of IPV.
Table 2
Prevalence of IPV.
Type of IPV Weighted %
Last 12 months More than 12 months ago only Ever
Emotional 18.4 17.6 36.0
Physical 6.7 11.2 17.9
Sexual 3.3 5.6 8.9
Any kind of violence 19.5 19.2 38.7
N¼4409 (women ever-in-union).
Table 1
Distribution of selected characteristics.
Variable Weighted % Unweighted n
Educational attainment in years
0e5 18.2 915
6 23.3 1085
7e11 23.0 1021
12 15.7 632
13þ19.7 756
Total 100.0 4409
Household wealth quintile
Lowest 21.5 1207
2nd 20.6 957
3rd 21.2 878
4th 19.5 745
Highest 17.3 622
Total 100.0 4409
Marital status
Married 47.4 2075
In consensual union 40.4 1859
Previously in union 12.3 475
Total 100.0 4409
Partner’s unemployment
a
2.3 1710
Partner’s alcohol consumption
a
Daily/weekly 18.3 752
Monthly 44.0 1704
Less than monthly 37.7 1478
Total 100.0 3934
Childhood violence
Victim of physical violence 20.5 859
Victim of sexual violence 1.8 70
Witnessed parental violence 23.9 993
N¼4409 (women ever-in-union).
a
N¼3934 (women currently in union).
K. Ishida et al. / Social Science & Medicine 71 (2010) 1653e16611656
Mental health
We find initial support for associations between IPV and CMD
risk and between IPV and suicidal ideation in the bivariate analysis
as shown in Table 4. All types of IPV, particularly sexual violence,
are significantly and positively associated with CMD risk, regardless
of timing of the abusive episodes. Significant and positive associ-
ations are also found between all types of current IPV and past
sexual abuse and suicidal ideation.
Finally, the results of the three multivariate logistic regression
models of each measure of mental health status are presented in
Table 5. First, we examine the odds ratios for IPV, comparing those
in Models 1 and 3 to estimate the degree to which other covariates
explain the association between IPV victimization and mental
health outcomes. Model 1 for CMD risk shows that all types of IPV,
regardless of the timing of violent episodes, significantly increase
the risk for CMD. The introduction of other key covariates only
slightly decreases the odds ratios, and most of them remain
significant in Model 3, suggesting that a large portion of the asso-
ciation between IPV and CMD risk is independent of these cova-
riates. The odds ratios for both current and past emotional (1.6 for
current and 1.3 for past violence) and sexual (1.5 for current and 1.3
for past violence) violence in Model 3 are larger than those for
physical violence, and current episodes of violence victimization
have slightly but consistently larger odds ratios than past episodes
for all types of violence.
Model 1 for suicidal ideation shows that all types of current IPV
and sexual abuse experienced in the past significantly increase the
risk for suicidal ideation. The strength of these associations persists
in Model 3 with odds ratios for current physical violence (1.9) and
current and past sexual violence (1.4 each), remaining significant,
suggesting that, similar to the findings for CMD risk, the effects of
IPV victimization on suicidal ideation are largely independent of
other key covariates. Unlike the pattern of associations with CMD
risk and consistently with the bivariate results, the only significant
odds ratios for past IPV are those for sexual violence, suggesting
that this form of abuse has not only an immediate but also long-
lasting effect on women’s suicidal ideation.
Subsequently, we assess the changes in the overall fit of the
models. The results of log-likelihood tests show a significant
improvement of the model fit between Models 2 and 3 for both
CMD risk and suicidal ideation, but particularly for suicidal idea-
tion. While BIC statistics generally increase with the number of
covariates added to the model, they decrease from Model 2 to
Model 3 for both mental health status. Again, the reduction of the
BIC is particularly large for suicidal ideation than for CMD risk
(171 and 2141, respectively). These results suggest that intro-
duction of IPV variables substantially increases the explanatory
power of the model, highlighting the significance of the association
between IPV and women’s mental health status.
Finally, we shift our attention to the associations between other
covariates and mental health outcomes, particularly comparing
Models 2 and 3 in their strength and significance in order to
determine the extent to which IPV may also act as a mediator of
these associations. First, adverse effects of low educational attain-
ment and low household wealth quintile on the CMD risk are linear
and particularly strong and significant at lowest thresholds (0e5
years of schooling and lowest household wealth quintile) in both
Models 2 and 3. The almost identically-sized ORs in these two
multivariate models are consistent with the lack of significance of
these variables as the determinants of IPV victimization, as shown
Table 3
Odds ratios and 95% confidence intervals from logistic regression models of three
types of IPV experienced in last 12 months.
Independent variable Type of IPV
Emotional Physical Sexual
Educational attainment in years [ref. 13þ]
0e5 0.87 1.21 1.08
(0.57e1.34) (0.61e2.43) (0.45e2.60)
6 0.85 1.16 0.99
(0.58e1.25) (0.54e2.47) (0.42e2.38)
7e11 1.11 1.60 1.24
(0.78e1.59) (0.85e3.00) (0.55e2.79)
12 1.19 0.88 1.24
(0.81e1.76) (0.42e1.86) (0.52e2.97)
Household wealth quintile [ref. highest]
Lowest 1.13 1.03 1.96
(0.68e1.88) (0.50e2.13) (0.72e5.32)
2nd 0.82 0.69 0.98
(0.54e1.24) (0.35e1.37) (0.37e2.62)
3rd 1.03 0.86 1.41
(0.70e1.52) (0.44e1.66) (0.58e3.42)
4th 1.15 0.76 0.86
(0.82e1.62) (0.38e1.55) (0.32e2.34)
In consensual union 1.27*1.78** 1.15
(1.02e1.58) (1.26e2.50) (0.75e1.76)
Partner’s unemployment 3.47*** 4.73*** 2.14
(1.99e6.04) (2.42e9.26) (0.73e6.31)
Partner’s alcohol consumption [ref. less than monthly]
Daily/weekly 4.16*** 5.95*** 6.02***
(3.19e5.42) (3.83e9.25) (3.17e11.44)
Monthly 1.87*** 1.99** 1.66
(1.47e2.36) (1.28e3.10) (0.88e3.14)
Childhood violence
Victim of physical violence 2.54*** 2.58*** 2.20***
(2.04e3.18) (1.90e3.52) (1.39e3.47)
Victim of sexual violence 1.42 0.91 1.82
(0.74e2.74) (0.28e2.98) (0.58e5.71)
Witnessed parental violence 1.80*** 2.05*** 2.14***
(1.42e2.27) (1.47e2.88) (1.41e3.26)
N¼3934 (women currently in union).
*p<0.05; **p<0.01; ***p<0.001.
All models are adjusted for age, language spoken at home, current pregnant/post-
partum status, having at least one surviving child, employment status, and urban
residence. All figures are weighted.
Table 4
% with CMD risk and suicidal ideation by IPV with 95% confidence intervals.
IPV % with CMD risk % with suicidal
ideation
Last 12 months
Emotional Yes 47.1 (42.9e51.3) 8.5 (6.4e11.1)
No 23.4 (21.8e25.2) 1.9 (1.4e2.6)
p<0.001 p<0.001
Physical Yes 55.5 (49.0e61.9) 16.6 (12.1e22.3)
No 25.8 (24.1e27.5) 2.2 (1.7e2.8)
p<0.001 p<0.001
Sexual Yes 64.0 (54.9e72.2) 16.5 (10.7e24.7)
No 26.6 (24.9e28.3) 2.7 (2.1e3.4)
p<0.001 p<0.001
More than 12 months ago only
Emotional Yes 36.5 (32.6e40.7) 3.3 (2.1e5.2)
No 25.9 (32.6e40.7) 3.1 (2.5e3.9)
p<0.001 p¼0.799
Physical Yes 43.8 (38.2e49.6) 4.0 (2.4e6.5)
No 25.8 (24.1e27.5) 3.0 (2.4e3.8)
p<0.001 p¼0.293
Sexual Yes 52.0 (44.5e59.4) 7.5 (4.5e12.3)
No 26.3 (24.6e28.1) 2.9 (2.3e3.6)
p<0.001 p<0.001
Total 27.8 (26.1e29.5) 3.1 (2.6e3.8)
N¼4409 (women ever-in-union) Significant associations are shaded. All figures are
weighted.
K. Ishida et al. / Social Science & Medicine 71 (2010) 1653e1661 16 57
Table 5
Odds ratios and 95% confidence interval from logistic regression models of CMD risk and suicidal ideation.
Independent variable CMD risk Suicidal ideation
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
IPV
Last 12 months
Emotional 1.64*** 1.58*** 1.42*1.32
y
(1.40e1.91) (1.35e1.86) (0.93e2.17) (0.87e2.01)
Physical 1.26*1.17
y
2.05*** 1.86***
(1.00e1.60) (0.93e1.49) (1.32e3.20) (1.19e2.91)
Sexual 1.60*** 1.47** 1.51*1.43*
(1.18e2.16) (1.09e2.00) (1.00e2.30) (0.95e2.16)
More than 12 months ago only
Emotional 1.36*** 1.32*** 1.28 1.18
(1.14e1.61) (1.11e1.56) (0.77e2.11) (0.72e1.95)
Physical 1.21*1.14 1.11 1.05
(0.97e1.50) (0.92e1.41) (0.71e1.72) (0.67e1.64)
Sexual 1.39** 1.25*1.58** 1.39*
(1.07e1.81) (0.96e1.64) (1.08e2.31) (0.95e2.05)
Other
Educational attainment in years [ref. 13þ]
0e5 1.34*** 1.34*** 1.38 1.32
(1.06e1.70) (1.07e1.69) (0.71e2.69) (0.66e2.64)
6 1.29** 1.30** 1.17 1.13
(1.03e1.61) (1.05e1.62) (0.61e2.28) (0.58e2.21)
7e11 1.23** 1.20*1.36 1.21
(1.01e1.51) (0.98e1.47) (0.71e2.61) (0.63e2.33)
12 1.167** 1.18 1.12 1.06
(0.94e1.46) (0.92e1.51) (0.59e2.12) (0.57e1.99)
Household wealth quintile [ref. highest]
Lowest 1.53*** 1.49*** 1.03 1.00
(1.19e1.95) (1.17e1.90) (0.62e1.70) (0.59e1.69)
2rd 1.54*** 1.55*** 1.03 1.10
(1.24e1.91) (1.25e1.92) (0.62e1.51) (0.66e1.83)
3rd 1.39*** 1.38*** 0.96 0.97
(1.13e1.71) (1.13e1.69) (0.62e1.51) (0.62e1.50)
4th 1.25** 1.23** 0.88 0.89
(1.02e1.53) (1.01e1.50) (0.55e1.41) (0.55e1.43)
Marital Status [ref. married]
In consensual unions 1.10
y
1.04 1.30*1.20
(0.96e1.25) (0.91e1.18) (0.96e1.76) (0.88e1.63)
Previously in unions 1.08 0.97 1.75** 1.28
(1.09e1.71) (0.85e1.11) (1.00e3.06) (0.73e2.22)
Partner’s unemployment 1.27
y
1.11 1.22 1.03
(0.90e1.80) (0.77e1.58) (0.59e2.50) (0.45e2.33)
Partner’s alcohol consumption [ref. less than monthly]
Daily/weekly 1.22** 1.02*1.34*1.01
(1.04e1.42) (0.87e1.20) (0.94e1.92) (0.67e1.52)
Monthly 0.94 0.88 0.87 0.82
(0.82e1.07) (0.77e1.01) (0.63e1.21) (0.59e1.15)
Childhood violence
Physical violence 1.33*** 1.19*** 1.63*** 1.40*
(1.16e1.51) (1.03e1.37) (1.17e2.29) (0.96e2.05)
Sexual violence 1.44*1.28 1.09 1.06
(0.97e2.14) (0.86e1.90) (0.51e2.31) (0.50e2.24)
Witnessed parental violence 1.18** 1.10
y
1.03 0.89
(1.03e1.35) (0.95e1.26) (0.74e1.42) (0.64e1.25)
Test of model fit
Log-likelihood 2425 2450 2349 523 1558 507
Contrast/F: (3)e(1) 76*** 16*
Contrast/F: (3)e(2) 101*** 1051***
Sample-size adjusted BIC statistics 4949 5052 4881 1144 3338 1197
Contrast/BIC: (3)e(1) 103 3684
Contrast/BIC: (3)e(2) 171 2141
N¼4409 (women ever-in-union).
y
p<0.10; *p<0.05; **p<0.01; ***p<0.001.
All models are adjusted for age, language spoken at home, current pregnant/postpartum status, having at least one surviving child, employment status, and urban residence.
Odds ratios are based on Y
*
-standardized coefficients. All figures are weighted.
K. Ishida et al. / Social Science & Medicine 71 (2010) 1653e16611658
in Table 3, and suggest that both low educational attainment and
household wealth quintile have independently positive effects on
CMD riskdthat is, adverse effects on mental health. Being in
a consensual union, male partner’s unemployment, frequent
drinking, and three types of violence experienced as a child are all
risk factors in Model 2 as expected, although being in a consensual
union and male partner’s unemployment are only marginally
significant. The size and significance of these coefficients are
reduced in Model 3 with IPV variables, suggesting that their
adverse effects on mental health are partly explained by their
positive effects on women’s risk for IPV as shown in Table 2.
However, male partner’s frequent drinking and physical violence
during childhood remain significant risk factors for CMD even after
IPV is added; thus they are also independent of IPV.
Neither educational attainment nor household wealth quintile is
significantlyassociated with suicidal ideation in either Model 2 or 3,
suggesting that the risk for suicidal ideation is not limited to specific
socioeconomic groups. Model 2 demonstrates that women in
a consensualunion or previously ina union are at significantlygreater
risk for suicidalideation than those ina marital union; however, these
adverse effects are reduced and no longer significant in Model 3 with
IPV variables. This indicates that the observed increased risk for
suicidal ideation among formerly married women is at least partly
explained by their increased risk for IPV victimization. We find no
significant effect of male partner’s employment status on women’s
risk for suicide ideation in either Model 2 or 3. On the otherhand, an
increased riskfor suicidal ideation among womenwith partners who
drank daily or weekly in Model 2 disappear in Model 3, suggesting
that virtually all its negative association between mental health and
partner’s frequent drinking is attributable to the former’s positive
association with IPV victimization. Finally, the significant adverse
effect of physical violence experienced as a child reducesin the size in
the final model, suggesting that the adverse effect of childhood
physical violence is partially explained by its positive effect on IPV.
However, it continues to be a significant and independent risk factor
for suicidal ideation.
Discussion and conclusions
No population-based study has ever existed to examine the
association between IPV victimization and mental health problems
in a developing country setting. This study demonstrated that IPV
victimization is significantly associated with Paraguayan women’s
poor mental health status measured by the risk of CMD and suicidal
ideation. The introduction of covariatesdwomen’s socioeconomic
and marital status and history of childhood violence victimization
and their partner’scharacteristicsddid not substantially change
the strength and significance of the IPVepoor mental health asso-
ciation, highlighting the independence of this association.
Substantial improvement of explanatory power by IPV underlined
the importance of IPV in identifying women with poor mental
health status, particularly suicidal ideation, for which IPV, along
with childhood physical abuse, are the only significant risk factors
in a broad range of variables considered for this study.
While these findings of significant IPVepoor mental health
association are broadly consistent with past non-population-based
studies from other developing countries (Ellsberg et al., 2008;
Kumar et al., 2005; Patel et al., 2006; Pillai et al., 2008), we also
identified several important differences by type and timing of
abusive episodes in the associations between IPV victimization and
the two mental health indicators in Paraguay as in other
studies conducted in developed countries (Bonomi et al., 2006;
Pico-Alfonso et al., 2006). While emotional and sexual abuse
experienced both within 12 months and priorto 12 months ago had
the strongest positive effects on the risk of CMD, physical and
sexual violence were the most important risk factors for suicidal
ideation, with sexual violence having a long-lasting adverse effect.
Results of an auxiliary analysis by type of sexual violence showed
that sexual intercourse engaged in out of fear was strongly asso-
ciated with risk for CMD but not with risk for suicidal ideation,
whereas physically forced sexual intercourse was strongly associ-
ated with suicidal ideation, but not with risk for CMD. In sum, abuse
that evokes fear of the partner has a positive effect on women’s risk
for general depression and anxiety while abuse that involved
physical force increases suicidal ideation. An important avenue for
future research would be a more systematic examination of the
association between the type of violence and other measures of
mental health status and across cultures for a solid conclusion.
More detailed information on violence about timing, frequency,
and severity of abusive acts may be useful.
This study also identified other important determinants of poor
mental health outcomes, notably low socioeconomic status
measured by educational attainment and household wealth quintile
for CMD risk and exposure toviolence during childhood for CMD risk
and suicidal ideation. Virtually all portions of the adverse effects of
low educational attainment and household poverty on the CMD risk
were independent of IPV. These effects were linear, with women in
the lowest status based on both the socioeconomic indicators
demonstrating the greatest risk for CMD. The socioeconomic
gradients of mental health that we found in Paraguay are similar
with the results from countries in Africa, Asia, and Latin America in
the Patel and Kleiman’s study (2003). While poverty may be an
important contributing factor for mental health problems, mental
illness may also hinder academic achievement and perpetuate or
even aggravate poverty. The strong association between mental
health and socioeconomic status is likely to be the product of an
interaction between the two factors. On the other hand, no such
socioeconomic gradients were found for suicidal ideation, suggest-
ing that suicide risk is not limited to a specific socioeconomic
stratum. In addition, while the adverse effects of being in a consen-
sual union and male partner’s frequent drinking were almost
entirely explained by their positive effects on IPV victimization,
physical violence experienced as a child notonly increases the risk of
IPV, but also is associated with poor mental health outcomes,
independently of IPV, highlighting its long-lasting adverse effect.
The data and findings of this study have some limitations.
Conflict tactic scales used to capture IPV in the 2008 ENDSSR are
specific and designed to minimize respondents’subjectivity.
However, normative response bias (the tendency of survey
respondents to underreport potentially stigmatizing experiences)
may have resulted in the underestimation of the prevalence of IPV.
The same bias may have resulted in the underreporting of suicidal
ideation and other SRQ-20 items, particularly because the survey
questionnaire was not self-administered, but filled out by inter-
viewers during face-to-face interviews with respondents. Further-
more, similar to past studies from both developed and less-
developed countries alike, the cross-sectional nature of the data did
not allow us to exclude the possibility that women with symptoms
of CMD were more likely to perceive marital conflicts more nega-
tively and recall episodes of abuse than those without such
symptoms. To determine the causal relationship between IPV
victimization and CMD risk, future research should analyze
psychosomatic conditions and episodes of IPV collected at multiple
time points. Finally, data on IPV were restricted to women who
have ever been in a union; we suggest that future studies of mental
health consequences of IPV victimization include never-married
women in dating relationships.
Despite these limitations, our population-based study high-
lighted the differential associations between IPV and poor mental
health by the type and timing of IPV and measures of mental health
K. Ishida et al. / Social Science & Medicine 71 (2010) 1653e1661 1659
at the national level and present several important policy recom-
mendations. We strongly suggest that women who are screened for
psychiatric disorders should be asked about their history of IPV.
Additionally, in conjunction with a recent study showing a close
link between suicidal ideation and suicide attempts across cultures
(Nock et al., 2008), psychiatric conditions of women with a recent
episode of abuse, that is physical in particular including forced
sexual intercourse, need to be closely monitored to prevent
potential self-harm. Finally, in addition to the recent legislative
progress in passing laws that criminalize abusive acts occurring
within the home in Paraguay, further programmatic efforts are
necessary to address social norms related to gender roles and to
promote early detection and prevention of IPV.
Acknowledgement
The authors thank Takashi Izutsu for providing expert advice
and Julio Galeano, Claudina Zavattiero, Marco Castillo, Edgar Tullo,
and Esmilce Gonzáles for facilitating our data access. A version of
this study was presented at the 2010 meetings of the Population
Association of America, Dallas. The findings and conclusions in this
report are those of the authors and do not necessarily represent
the official position of the Centers for Disease Control and
Prevention.
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