India Clinical Epidemiology Network, Chennai
Department of Biostatistics, Christian Medical College, Vellore
Institute of Child Health, Egmore, Chennai
Department of Medicine, King George Medical College, Lucknow, India
IndiaSAFE Steering Committee
Correspondence: Dr Shuba Kumar, Social Scientist and Manager, India Clinical Epidemiology Network, No. 58 Venkatratnam Nagar, Adayar, Chennai - 600 020, India. Tel: +91 44 24422477; fax: +91 44 24455378; e-mail: indiaclen{at}touchtelindia.net
Declaration of interest None. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To determine the association of domestic spousal violence with poor mental health.
Method In a household survey of rural, urban non-slum and urban slum areas from seven sites in India, the population of women aged15-49 years was sampled using probability proportionate to size. The Self Report Questionnaire was used to assess mental health status and a structured questionnaire elicited spousal experiences of violence.
Results Of 9938 women surveyed, 40% reported poor mental health. Logistic regression showed that women reporting `any violence' - `slap', `hit', `kick' or `beat' (OR 2.2, 95% CI 2.0-2.5) - or `all violence' - all of the four types of physically violent behaviour (OR 3.5, 95% CI 2.94-3.51) - were at increased risk of poor mental health.
Conclusions Findings indicate a strong association between domestic spousal violence and poor mental health, and underscore the need for appropriate interventions.
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INTRODUCTION |
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METHOD |
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Previous studies have estimated the prevalence of domestic violence against women in Bangladesh and rural India at 20-50% (Schuler et al, 1996; Jejeebhoy, 1998). Assuming a prevalence of 40%, at a precision of 2% with a 95% confidence interval and a 15% withdrawal rate, the sample size in each stratum was estimated at a minimum of 3200 women respondents. At each of the seven sites in the study, only two of three different strata (rural, urban slum, urban non-slum) were selected.
Each study site purposively selected potential blocks, localities and slums based on easy accessibility. Using the probability proportionate to size method, nearly eight to ten villages (in rural areas) or streets (in urban areas) were selected for each study site. When selecting households from urban slum areas, the field team randomly selected paths and enumerated all households located along those paths. If they failed to obtain the requisite sample size fixed for that particular area, they turned right and moved along the new path, repeating the manoeuvre until the required sample size was achieved. In urban non-slum areas, all households located on a single street were included; if there happened to be a building with more than three floors, then one floor alone was randomly selected and all flats on that floor were included. For the rural areas, a junction of some central point was identified. One line was selected from each compass direction and all households along that line were included. If the number of households fell short of the requisite sample size then the field team proceeded to the next line and continued with the process of selection.
Eligibility criteria
Women aged 15-49 years, with at least one resident child below 18 years of
age, were eligible. As the main study also assessed child abuse, the presence
of a resident child was an essential criterion for participation.
Consequently, childless women were excluded from the study. Women aged 50
years and over and those not residing with their husbands for the past 12
months were also excluded. The interviews were conducted in privacy after
obtaining the woman's informed consent.
Instruments
Spousal violence against women
A structured interview schedule was developed to assess physical spousal
violence. These behaviours were assessed over the whole span of the woman's
marriage. The instrument broadly elicited information on household
characteristics, social status of woman's parental family
vis-à-vis that of her husband's family, lifetime experiences
of family violence, and childhood history of family violence. To ensure
comparability between the different study regions, the instrument was
translated into the local language (Hindi, Marathi, Tamil or Malayalam) and
then back-translated into English. All the back-translations were thoroughly
checked to ensure that the meaning of the original English language version
was retained. An intensive joint training session was conducted for the
research staff from all sites. Interrater reliability assessment found an
intraclass correlation coefficient of 0.75.
Mental health status
The Self Report Questionnaire (SRQ;
Sen, 1987;
Srinivasan & Suresh,
1990), a standardised instrument, was administered to measure the
mental health status of the participating women. This is a 20-item
questionnaire requiring `yes/no' responses, and screens for the presence of
anxiety and depressive disorders. The SRQ has been standardised in India in
two separate studies (Sen,
1987; Srinivasan & Suresh,
1990). Patients who scored 7 or more on the SRQ were designated as
having `poor' mental health and those with a score below 7 were designated as
being `normal'.
Definitions of violence
Spousal violence was grouped into three categories:
The violent behaviour could have occurred at any time during the woman's marriage.
Socio-economic status
In assessing socio-economic status, proxy indicators such as toilet
facilities and ownership of household appliances and of vehicles were used.
Toilet facilities inside the home rather than outside were considered to be an
indication of higher socioeconomic status. Similarly, possession of a greater
number of household appliances, such as a refrigerator, gas or electric stove,
television and air conditioner, and ownership of a vehicle, were also
considered an indication of higher socio-economic status.
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RESULTS |
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Socio-demographic characteristics
The average age of the respondents was 31 years (s.d.=6.9). Rates of
non-literacy were higher among rural (40%) and urban slum (32%) dwellers,
whereas higher education levels were more common among urban non-slum (31%)
dwellers. A third of women in rural areas were employed, predominantly in
agriculture, in contrast to only 22% of women in urban slum and urban non-slum
areas. Most of the women were married (96%); the remainder were recently
widowed, separated or divorced.
Seventeen per cent of women in urban non-slum areas reported having toilet facilities outside their home, in contrast to 43% from the urban slum areas and 32% from the rural areas. Similarly, 49% of women living in urban non-slum areas reported owning a vehicle, in contrast to 17% and 15% from the urban slum and rural areas respectively. This indicated that women from the rural and urban slum areas lived in greater poverty.
Socio-demographic characteristics and mental health status
More women from urban slum areas (48%) and rural areas (44%) had poor
mental health compared with those from urban non-slum areas (23%).
Table 1 relates the mental
health status of the women to various socio-demographic characteristics. There
was a significant (P=0.001) increase in the proportion of women with
poor mental health with an increase in age, suggesting the presence of
probable anxiety and depression. Women aged 40-49 years living in the rural
(50%) and urban slum (60%) areas constituted the greatest proportion in this
category. An increase in the number of years of education was associated with
a reduction in the proportion of women with poor mental health, a pattern that
was statistically significant (P=0.001) and consistent across all
three residential strata. Mental morbidity in women who had 12 years or more
of education was 20% in rural areas, 25% in urban slum areas and 10% in urban
non-slum areas, in contrast to 40%, 50% and 39% respectively in non-literate
women from these three types of area.
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Difference in employment status between the woman and her husband also emerged as significantly associated with poor mental health in the women (P=0.001). The mental health of the woman was less likely to be poor in instances where husbands held jobs of higher status and income compared with that of their wives (rural, 39%; urban slum, 43%; urban non-slum, 21%). However, the prevalence of poor mental health was increased almost three-fold when the woman's job and income status was at a higher level than that of her husband (rural, 69%; urban slum, 71%; urban non-slum, 54%).
Other spousal and family characteristics and mental health
The consumption of alcohol by the husband was found to be significantly
(P=0.001) associated with the mental health status of the woman
(Table 2).
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Among women whose husbands abstained from alcohol, 39% of rural respondents, 41% of urban slum respondents and 20% of urban non-slum respondents had poor mental health. In contrast, a far greater proportion of women whose husbands were reported as being regularly drunk had poor mental health: rural 64%, urban slum 73%, urban non-slum 48%. Severe harassment by in-laws was also found to be significantly associated (P=0.001) with poor mental health status. Of women who reported experiencing severe harassment by their in-laws, 74%, 80% and 71% from the rural, urban slum and urban non-slum areas respectively had poor mental health. Even those who reported moderate harassment from their in-laws presented with higher rates of poor mental health. With respect to social support, the less the support the higher were the rates of poor mental health, which was also consistent across all three survey strata. Women who reported harsh physical punishment during childhood also had higher rates of poor mental health (P=0.001). Similarly, a greater percentage of women who reported having witnessed as children their father beating their mother also scored high on the SRQ (P=0.001). Both these findings were consistent across all sites.
Physically violent behaviours and mental health
Table 3 shows the
distribution of physically violent behaviours and the prevalence of poor
mental health. Each of the four types of physically violent behaviour was
significantly associated with greater prevalence of poor mental health. For
all four behaviours the risk was a little over twofold. Experience of any one
of the four physically violent behaviours also doubled the relative risk of
poor mental health, compared with women who had not reported any physical
spousal violence.
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A logistic regression analysis of factors associated with poor mental health revealed several (Table 4): women who experienced dowry harassment (OR 1.71, 95% CI 1.56-1.92) or harsh physical punishment during childhood (OR 1.41, 95% CI 1.27-1.57), witnessed their father beating their mother (OR 1.31, 95% CI 1.17-1.46), whose husbands regularly consumed alcohol (OR 2.2, 95% CI 1.9-2.55) and who had experienced any one of the four types of physically violent behaviour (OR 2.23, 95% CI 2.0-2.49) were all at increased risk of poor mental health. Similarly, after adjusting for the above hypothesised and confounding variables (in separate analyses), this risk increased when the woman was subjected to `multiple violence' (OR 2.6, 95% CI 2.3-2.9) or `all violence' (OR 3.5, 95% CI 2.9-3.5). In contrast, presence of more household appliances (OR 0.9, 95% CI 9-0.9), high-school education for both the woman and her husband (OR 0.9, 95% CI 0.9-0.9) and more social support (OR 0.8, 95% CI 0.7-0.8) served to protect the woman against mental morbidity.
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DISCUSSION |
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Poverty, education, domestic spousal violence and poor mental health
Women who were poor and those who were less educated were also found to be
at increased risk of poor mental health. Other studies have also shown that
women living in poverty are disproportionately affected. These women are faced
with enormous social, physical and economic stresses, which in association
with the experience of domestic violence are likely to increase their
vulnerability to mental morbidities (Patel
et al, 1999). Heise
(1998) postulated that poverty
probably acts as a marker for a variety of social conditions that combine to
increase the risk of violence faced by women. Women in better jobs than their
husbands were also found to be at risk of poor mental health, a feature that
is not unique to India. Counts et al
(1992) found that where women
have a higher economic status they are seen as having sufficient power to
change traditional gender roles, and it is at this point that violence is at
its highest.
An interesting finding was that higher levels of education of both the woman and her husband acted as a protective buffer against poor mental health, suggesting the important part education could play in reducing violence against women and thereby mental disorder. This implies that higher levels of education engender better skills in coping with and dealing with stressful situations. Studies have indeed shown that low academic achievement was one of the risk factors predicting physical abuse of partners by men in New Zealand (Moffitt & Caspi, 1999).
Alcohol, dowry, domestic violence and poor mental health
Regular alcohol consumption by the husband, harassment by the in-laws,
exposure to harsh physical discipline during childhood and witnessing father
beating the mother during childhood were other factors that were strongly
associated with increased risk of poor mental health, all of which have been
well documented (Black et al,
1999). Alcohol has consistently emerged as a risk marker for
partner violence that is especially consistent across a range of settings
(McCauley et al,
1995). Many researchers believe that alcohol operates as a
situational factor, increasing the likelihood of violence by reducing
inhibitions, clouding judgement and impairing an individual's ability to
interpret cues (Flanzer,
1993).
Harassment by in-laws on issues related to dowry, which emerged as a risk factor for poor mental health in this study, is particularly characteristic of the Indian setting. The dowry has been in existence for many years and has been the subject of much debate as well as legislative action (Agnes, 1992). Despite efforts, this age-old practice continues to survive and has been a significant factor that has driven many women to suicide (Kumari, 1989).
Social support, childhood experiences or violence and poor mental health
The beneficial effects of social support have been acknowledged. In this
study the mental health status of women who reported having good social
support was better than that of those who reported poor social support. Coker
et al (2003) found
that higher levels of emotional support can modify the effect of intimate
partner violence on health, and suggested that interventions to increase
emotional and social support to women victims of violence might reduce the
negative consequences to mental and physical health.
Published studies have provided fairly strong evidence of long-term psychological effects on women who remember violence between their parents. Such women were diagnosed as having low self-esteem, depression and poor social competence (Silveryn et al, 1995). Further, women who experienced physical or sexual abuse in childhood also experienced ill health with regard to physical functioning and psychological well-being more frequently than other women (McCauley et al, 1995). The results from our study clearly echo these findings. The statistically strong association that emerged between witnessing father beating mother during childhood and poor mental health, as well as between exposure to childhood violence and poor mental health during the woman's adult years, provide compelling evidence of the long-term and deleterious effects of violence.
Study limitations
The cross-sectional design of our study precluded the ability to establish
the causal effect of violence in leading to poor mental health. The sample was
restricted to women under 50 years, a decision that was based on the belief
that women over that age were likely to have better crisis management skills
than younger women and therefore were likely to experience less domestic
spousal violence. This limited the ability to generalise the study's findings
to a wider cross-section of older women. Further, all assessments were based
on self-reports by respondents, and are likely to be gross underestimates.
Despite these limitations, this study is one of the largest population-based
studies in India that has provided valuable data on domestic violence and
established the strong association between domestic spousal violence and poor
mental health. It also provides substantive evidence of the need to classify
domestic violence as a major public health problem. An effective preventive
programme that could eliminate physical domestic violence could hope to
achieve a reduction of 41% (population attributable fraction) in the
prevalence of poor mental health in the total population, a fact that
underscores the need for culturally acceptable and sustainable intervention
strategies to deal with this social malaise.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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REFERENCES |
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Received for publication December 23, 2003. Revision received October 12, 2004. Accepted for publication October 13, 2004.