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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Acquir Immune Defic Syndr. Author manuscript; available in PMC Dec 13, 2012.
Published in final edited form as:
PMCID: PMC3521617
NIHMSID: NIHMS378583

Intimate Partner Violence Functions as both a Risk Marker and Risk Factor for Women’s HIV Infection: Findings from Indian Husband-Wife Dyads

Abstract

Context and Objective

Female victims of intimate partner violence (IPV) consistently demonstrate elevated STI/HIV prevalence. IPV is thought to function indirectly as a marker of abusive men’s elevated STI/HIV infection and/or directly via facilitating transmission to wives. The present examination utilizes a nationally representative sample of married Indian couples to test these mechanisms and determine whether 1) abusive husbands demonstrate higher HIV infection prevalence compared with non-abusive husbands, and 2) the risk of wives’ HIV infection based on husbands’ HIV infection varies as a function of their exposure to IPV.

Design, Setting and Participants

The Indian National Family Health Survey-3 (NFHS-3) was conducted across all Indian states in 2005-2006. Analyses were limited to 20,425 husband-wife dyads which provided both IPV data and HIV test results.

Analyses

Logistic regression models estimated the odds ratios and 95% confidence intervals to evaluate the following associations: 1) husband’s HIV acquisition outside the marital relationship based on their perpetration of IPV and 2) wives’ HIV infection based on husbands’ HIV infection, as a function of their IPV exposure.

Results

One-third (37.4%) of wives experienced IPV; 0.4% of husbands and 0.2% of wives were HIV infected. Compared with non-abusive husbands, abusive husbands demonstrated increased odds of HIV acquisition outside the marital relationship in adjusted models (AOR=1.91; 95% CI 1.11, 3.27). Husband HIV infection was associated with increased HIV risk among wives; this risk was elevated sevenfold in abusive relationships in adjusted models (AOR =7.22; 95% CI 1.05, 49.88).

Conclusions

Findings provide the first empirical evidence that abused wives face increased HIV risk based both on the greater likelihood of HIV infection among abusive husbands, as well elevated HIV transmission within abusive relationships. Thus, IPV appears to function both as a risk marker and as a risk factor for HIV among women, indicating the need for interwoven efforts to prevent both men’s sexual risk and IPV perpetration.

Background

The global HIV epidemic is rapidly “feminizing”.1, 2 Increasing numbers of women are HIV infected worldwide,1 and within the Indian context women account for an estimated 40% of cases among 2.5 million people living with HIV/AIDS3. Limited pre-marital and extra-marital sexual behavior among Indian women4, 5 renders heterosexual transmission from husbands the dominant infection pathway for wives.5-7 High levels of intimate partner violence (IPV) victimization are consistently documented in South Asia,8-12 with an estimated 1 in 3 women victimized across their lifetime.4 Such victimization is increasingly considered relevant to women’s STI/HIV risk in this region12-14 and elsewhere.15, 16 A growing body of evidence demonstrates elevated STI/HIV prevalence among abused women,17-21 including recent findings from a national sample of Indian women illustrating greater HIV infection prevalence based on exposure to abuse from husbands.22 These data have prompted international attention to the possible mechanisms by which IPV and STI/HIV may relate,23 however these theories remain untested to date.

Prior research highlights elevated sexual risk behaviors and STI prevalence among abusive men,12, 13, 16, 24, 25 bolstering the hypothesis that abusive men are more likely than nonabusive individuals to contract STI/HIV and may subsequently transmit infection to female partners. Thus, abused women’s increased STI/HIV prevalence may reflect greater likelihood of STI/HIV exposure, rendering IPV a risk marker for their male partners’ STI/HIV infection. IPV may also increase women’s STI/HIV risk more directly by providing enhanced opportunity for STI/HIV transmission. Potential mechanisms by which abuse may facilitate STI/HIV transmission include women’s limited negotiation capacity to refuse sex or use condoms, 26-28 and the potential for physical trauma (i.e., tearing or lacerations) in situations of forced sex.29 While IPV cannot lead to STI/HIV in the absence of pathogen exposure, abuse may serve to enhance transmission in the presence of male partner STI/HIV,21 rendering IPV a direct transmission risk factor. If determined to both a marker of abusive male partners’ elevated STI/HIV infection prevalence and to mechanistically enhance STI/HIV transmission, IPV may be considered to pose “double jeopardy” to women, i.e., limited control over sexual relationships with male partners more likely to be HIV-infected.

To date, little work has begun to disentangle these two distinct vulnerabilities. Understanding the mechanisms underpinning abused women’s elevated STI/HIV, i.e., whether IPV functions as a marker of abusive men’s HIV risk and/or facilitates transmission, is critical for designing effective HIV prevention interventions. The India National Family Health Survey 3 (NFHS-3) represents the first national, population-based data on HIV status, sexual risk and IPV for husband-wife dyads. The data thus offer empirical strength in HIV assessment while maximizing inferences to the general population. The present analysis seeks to extend prior findings from these data indicating elevated HIV infection prevalence among abused women22 by estimating 1) the association of IPV with husbands HIV acquisition outside the marital relationship (i.e., IPV as a risk marker for an HIV-infected husband), and 2) the extent to which IPV may modify the risk to the wives from HIV-infected husbands (i.e., IPV as an HIV transmission mechanism or risk factor).

Methods

Design, Setting and Sample

The national, population-based India National Family Health Survey-3 (NFHS-3) was conducted in all 29 states of India by the International Institute for Population Sciences (IIPS) and Macro International from November 2005 to August 2006. The NFHS is referred to as the ‘Demographic Health Survey’ or ‘DHS’ in other national contexts, and is conducted regularly in many countries to obtain population-based estimates of major health threats. The NFHS involves confidential questionnaires administered verbally to male and female participants separately; surveys were bilingual within each state, i.e., each question was available in English and the principal language of the state. The nationally representative household-based sample for the NFHS-3 was created via a stratified, multistage cluster strategy. Within each state, two-stage (rural areas) and three-stage (urban areas) procedures identified 3,850 primary sampling units (PSUs) comprised of one or more villages in rural areas, and census enumeration blocks within wards in urban areas; PSU selection probability was proportional to size. Within each PSU, household enumeration generated the sampling frame for systematic selection of households. Trained research assistants conducted household-based recruitment and obtained written informed consent immediately prior to survey data collection. These procedures identified 131,596 eligible women ages 15-49, of which 124,385 completed the survey (response rate 95%; 124,385/131,596), and 85,373 eligible men ages 15-54 of which 74,369 completed the survey (response rate 87.1%; 74,369/85,373).4The study protocol did not explicitly sample husband-wife dyads, rather, male participants’ responses were matched to those of their married female partners to create a sample of husband-wife dyads (n=39,257) subsequent to data collection. Further details concerning the NFHS-3 procedures are available elsewhere.4

The analytic sample was limited to husband-wife dyads for whom both HIV testing and IPV survey data were available; separate procedures selected subsets of participants for these two components. HIV testing was conducted for a systematically selected subset of participants. The 3% (3,896/124,385) of female participants and 5% (3,971/74,369) of male participants from the state of Nagaland were not included in HIV testing due to local opposition. Of the remaining female participants, 49% (58,202/120,489) were selected for HIV testing of whom 91% (52,853/58,202) participated. Of the remaining male participants, 79% (55,311/70,398) were selected for HIV testing of whom 91% (50,093/55,311) participated. Among the matched husband-wife dyads, 67% (26,230/39,257) contained HIV test results for both husband and wife.

The analytic sample was further restricted to dyads in which the wife was systematically selected to complete the IPV assessment. Of 26,230 husband-wife dyads linked with HIV data, 78% (20,433/26,230) had IPV data and thus were included in the sample. The final sample size was 20,425 husband-wife dyads, following exclusion of 8 dyads based on incomplete exposure (IPV) data or reportedly never having had sexual intercourse.

Measures

Demographics including age, religion, and education were assessed via single self-reported items on both the men’s and women’s surveys. A relative index of household wealth was calculated based on interviewer-observed assets (e.g., ownership of consumer items); the resulting score was divided into quintiles. Self-reported lifetime number of sexual partners, lifetime history of condom use for contraceptive purposes (reported on both men and women’s survey), and male circumcision (obtained via men’s survey) were considered as sexual risk covariates.

The primary exposure, IPV, was assessed via self-report in accordance with World Health Organization (WHO) recommendations30 and based on the Conflict Tactics Scale.31 Lifetime IPV victimization was indicated by a positive answer to any of the following 8 items pertaining to experiences at the hands of their current husband: “push you, shake you, or throw something at you”, “slap you”, “punch you with a fist or something harmful”, “kick, drag or beat you up”, “try to choke or burn you on purpose”, “threaten or attack you with a knife, gun, or any other weapon”, “physically force you to have sexual intercourse with him even when you did not want to” or “force you to perform any sexual acts that you did not want to”. The assessment was administered only when privacy could be ensured. Items demonstrated adequate internal consistency reliability with Cronbach’s alpha =0.76 for the current sample. Wives’ reports of victimization served as a proxy for husbands’ IPV perpetration in analyses pertaining to husbands.

HIV infection was assessed via collection and testing of dried blood spots (DBS) pending a separate written informed consent. HIV test results were linked to participant survey data via unique barcodes thus eliminating the need for individual identifiers and preserving anonymity of test results. Consistent with WHO/UNAIDS guidelines for population-based HIV seroprevalence assessment,32 a sequential multiple testing protocol was followed whereby all positive results and 5% of negative results diagnosed via the first ELISA (Microlisa by J. Mitra) were tested with a second ELISA (Enzaid-Span 3 by Span Diagnostics); the Innolia Western Blot kit was used for non-matching results. The SRL Ranbaxy laboratory provided HIV antibody testing and compilation of results. An external quality control lab at the National AIDS Control Organization (NACO) in Pune, India validated a subsample of test results. All study procedures were approved by the ORC MACRO Institutional Review Board; the Harvard School of Public Health Human Subjects Committee deemed analyses exempt given the anonymous nature of the data.

Analysis

Prevalence estimates of IPV perpetration/victimization based on wives’ reports of husband behavior and husband and wife HIV infection were calculated. Differences in IPV and HIV based on demographics and sexual risk behavior were assessed separately for husbands and wives via Wald chi-square analyses; significance for all analyses was set at p<0.05.

Assessment of the extent to which IPV represents a marker for husband’s HIV infection was conducted via logistic regression models which estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association of IPV perpetration with husband’s HIV infection. To maximize clarity and empirical strength in assessing the extent to which IPV perpetration related to husband’s acquisition of HIV infection outside the marital relationship, this analysis was restricted to husbands whose wives were not infected with HIV, i.e., those husbands who could not have acquired HIV via their wives (n=20,358). The model was subsequently adjusted for husbands’ sexual risk covariates (i.e., lifetime sex partners, lifetime condom use, circumcision) as well as husbands’ potential demographic confounders (i.e., age, education, household wealth). Religion was not included as a covariate given its collinearity with circumcision. OR and AOR estimates generated via logistic regression were evaluated for statistical significance based on 95% CIs not crossing 1.0.

Assessment of the extent to which HIV infection among wives related to husband HIV infection, and whether this effect varied based on the presence of IPV (i.e., IPV as a transmission risk factor), was conducted via logistic regression models which first estimated AORs and 95% CIs for associations of husband HIV infection with wives’ HIV infection using the full analytic sample. Covariates included wives’ sexual risk behaviors (i.e., lifetime number of sexual partners, lifetime condom use) and wives’ potential demographic confounders (i.e., age, education, women’s religion, and household wealth). The adjusted model was then stratified by presence of IPV in the marital relationship, i.e., IPV present (n=7,147) and IPV not present (n=13,278). The final model utilized the full analytic sample and included an indicator term reflecting exposure to both IPV and male partner HIV, while controlling for IPV. AOR estimates generated were evaluated for statistical significance based on 95% CIs not crossing 1.0. To maximize statistical power, missing data were imputed as the referent as follows for all multivariate analyses: missing education data were coded as having no education (8 husbands, 1 wife), missing condom use data were coded as having never used condoms (24 husbands, 30 wives), missing information on number of lifetime sex partners were coded as having had 1 partner (48 husbands, 40 wives), and 158 husbands with unknown circumcision status were classified as uncircumcised. Sensitivity analyses indicated that no effect estimate was modified by 1% or more based on these procedures. All analyses were conducted in STATA to accommodate the complex design of the NFHS-3; the ‘svyyset’ command was used to accommodate potential non-independence of responses within PSUs and all analyses were weighted for non-response using the nationally representative men’s and women’s HIV testing weights standardized to the analytic sample.

Results

Prevalence and Correlates of IPV and HIV Infection among Husbands

The prevalence of IPV against wives among married Indian couples was 37.4% (95% CI 36.1, 38.7), and 0.4% (95% CI 0.3, 0.5) of husbands were HIV infected (Table 1). IPV perpetration prevalence inversely related to educational attainment (p<0.001) and household wealth (p<0.001), and varied across husbands’ religious groupings with Muslim men demonstrating the highest prevalence (40.9%, p<0.001). Fewer than 1 in 5 husbands (18.3%) reported more than one sexual partner in their lifetime. IPV perpetration was more prevalent among such husbands (42.8% vs. 36.1%, p<0.001), and among those never having used condoms (40.0% vs. 30.6%, p<0.001). Husbands with more than one lifetime sex partner also demonstrated elevated HIV prevalence (0.7% vs. 0.3%, p=0.013).

Table 1
Sample demographics, HIV risk factors and associations with IPV perpetration and HIV infection among Indian husbands (n=20,425)

Prevalence of HIV Infection and correlates of IPV victimization and HIV among Wives

Among wives, IPV victimization prevalence inversely related to educational attainment (<0.001) and household wealth (p<0.001; Table 2). Muslim wives demonstrated the highest victimization prevalence relative to other religious groupings (41.0%, p<0.001). IPV victimization was more prevalent among wives having had multiple sex partners (54.8% vs. 37.2%, p<0.001) and those who had never used condoms (38.3% vs. 33.1%, p<0.001). The prevalence of HIV among wives was 0.2% (95% CI 0.1, 0.3); HIV infection varied by religious groupings and was most prevalent among Hindu wives (0.2%, p=0.028).

Table 2
Sample demographics, HIV risk factors and associations with IPV victimization and HIV infection among Indian wives (n=20,425)

Associations of IPV Perpetration with Husband’s HIV Infection Acquired Outside Marital Relationship

Among husbands whose wives were not HIV infected (i.e., husbands who were not at risk for HIV acquisition from their wives, n=20,358), the odds of HIV infection were significantly elevated based on IPV perpetration (OR 1.94; 95% CI 1.02, 3.69, Table 3). The association of IPV perpetration with husbands HIV infection persisted after controlling for husbands’ demographic factors and sexual risk covariates (AOR 1.91; 95% CI 1.11, 3.27).

Table 3
Associations of IPV perpetration and sexual covariates with HIV infection among Indian husbands whose wives are not HIV infected (n=20,358)a

Associations of Husband HIV and Wives’ HIV Infection, as a Function of IPV

Among all couples, husbands’ HIV infection was associated with their wives’ HIV infection after accounting for wives’ demographics and sexual risk covariates (AOR 740.40; 95% CI 308.08, 1777.42, p<0.001; Table 4). In analyses stratified by presence of IPV in the relationship, husband HIV infection related to wife HIV infection within both abusive (AOR 4610.88; 95% CI 858.96, 24751.04, p<0.001) and non-abusive (AOR 544.97; 95% CI 198.38, 1497.09, p<0.001) strata. In the final model, a multiplicative interaction term quantified the magnitude of the difference in these effect estimates. In the presence of an interaction term representing exposure to both husband HIV infection and IPV, the main effects for each component of the interaction term are interpreted as the odds of wives’ HIV in the referent group for each component of the interaction term, i.e., the main effect of husband HIV infection (AOR 539.13; 95% CI 198.19, 1466.58, p<0.001) is interpreted as the effect of husband HIV infection in the absence of IPV. A significant multiplicative interactive effect of exposure to both husband HIV and IPV on wives’ HIV was detected, whereby the odds of wives’ HIV infection based on husbands’ HIV infection increased seven-fold in the presence of IPV (AOR 7.22; 95%CI 1.05, 49.88, p=0.045) over the odds of wives’ HIV infection based on exposure to husband HIV in the absence of IPV. No associations were detected between wives’ sexual risk behaviors and their HIV infection status.

Table 4
Associations of husband HIV infection and IPV victimization with HIV among Indian wives (n=20,425)a

Discussion

Our findings from this first population-based investigation of the effect of IPV on HIV among husband-wife dyads indicate that abusive husbands increase their wives’ HIV risk in the Indian context via two distinct, yet convergent, pathways, specifically abusive husbands’ heightened risk of HIV infection and heightened risk of infection transmission in the presence of IPV. Compared with non-abusive husbands, abusive husbands demonstrated almost twice the odds of acquiring HIV outside their marital relationship. This finding supports concerns that abusive men are more likely to acquire HIV and subsequently introduce infection into their marital relationships; thus, IPV may be considered a risk marker for wives’ HIV infection via abusive husband’s greater odds of HIV infection. Moreover, compared to wives’ exposure to their husbands’ HIV infection in the absence of violence, wives’ exposure to both IPV and husbands’ HIV heightened their odds of contracting HIV sevenfold. This evidence supports the hypothesis that IPV may facilitate HIV transmission from an infected partner, rendering IPV a risk factor (i.e., direct mechanism) for women’s HIV infection. Taken together, these results support the hypothesis that abused women’s elevated HIV prevalence reflects their being subject to “double jeopardy”, i.e., abused women are more likely to have an HIV-infected male partner, with whom HIV transmission may be enhanced based on abuse in the relationship.

These findings advance previous efforts devoted to understanding both elements of abused women’s double jeopardy for HIV infection, with prior work informing the mechanisms likely responsible. Current evidence that abusive men are more likely to acquire HIV outside of the marital relationship (i.e., IPV as a risk marker for HIV) advances prior investigations across diverse settings demonstrating elevated sexual risk behavior and self-reported STI among abusive men12, 13, 16, 24 by confirming these findings via utilization of laboratory testing for HIV among a population-based sample. Analyses restricted to the sample of husbands to those whose wives were not HIV infected afforded greater empirical clarity than previously possible in testing hypotheses that abusive husbands are at greater risk for acquiring HIV outside the marital relationship and subsequently introducing it to their wives. Both men’s IPV perpetration and their sexual risk behavior are increasingly considered to stem from a common source, specifically socially sanctioned norms of masculinity that prioritize sexual entitlement and multiple partnering, and physical and sexual domination of female partners. 15, 33,34 As such, the India National Aids Control Organization (NACO) has recognized social norms endorsing men’s sexual entitlement and power over women as a factor in women’s HIV vulnerability.35 Supporting the import of modifying such factors, recent efforts targeting the intersection of men’s sexual risk and abusive behavior have been demonstrated effective in reducing both men’s violence perpetration and incident STI in the African context;36 similar efforts underway in India should be prioritized as they hold promise in modifying masculinity norms to reduce both IPV and HIV/STI.34

Current evidence of facilitated HIV transmission to female partners in the presence of IPV (i.e., IPV as a risk factor), similarly advances the current state of knowledge. Use of matched husband-wife dyads with integrated HIV test results allowed assessment of the differential impact of wives’ exposure to their husbands’ HIV across violent and non-violent relationships, with women whose husbands were violent suffering approximately seven times the risk of becoming infected with HIV based on exposure to their husband’s infection. Prior work suggests a number of mechanisms for women’s greater likelihood of HIV infection based on exposure to husband HIV in the presence of violence. The role of unwanted sex and subsequent physical trauma (i.e., tearing or lacerations)23, 29 associated with IPV is likely critical in increasing opportunity for infection transmission. Cultural norms dictate low levels of sexual communication between spouses concerning sexuality among this population generally;27 abused women’s limited ability to negotiate or refuse sex in the face of violence, coupled with unwanted sex obtained via physical force and a range of coercive tactics,13,26, 27,35, 37 likely facilitate trauma and HIV transmission. Qualitatively riskier sexual practices, e.g., anal sex, found more common among male IPV perpetrators38 may also constitute an enhanced transmission mechanism within abusive relationships. While condom use was relatively rare within the current sample of married couples, evidence from India of violence in response to condom requests by wives26, 27 suggests that abused women’s limited ability to negotiate condom use (e.g., in the context of wives’ knowledge of his HIV infection or suspicion of extramarital sexual risk behavior) may increase risk of HIV transmission, even within this low-use setting. Further investigations using husband-wife dyads as the unit of analysis across other national and high-risk contexts are recommended to advance the empirical basis for these hypothesized mechanisms and clarify the present findings.

Limitations of the current study include the inability to establish a temporal relationship based on the cross-sectional nature of the study, thus incident and secondary infections among concordant husband-wife dyads cannot be disentangled. While the analyses were based on a conceptual framework positing that husbands may be more likely to introduce HIV to the relationship, it is not possible to rule out the possibility that wives introduced HIV infection within concordant couples, although this appears unlikely based on the current findings that wives’ sexual risk was not associated with their HIV infection. Low levels of prior HIV testing in this sample4 suggests that the majority of participants were unaware of their HIV status at the time of testing, limiting concerns that IPV could have been caused by HIV disclosure.39, 40 Although procedures entailing multiple testing and external quality control enhanced the precision of HIV assessment, misclassification is possible and the low prevalence of HIV renders analyses sensitive to potential misclassification. While potential misclassification could limit the precision of estimates, misclassification is not likely to be differential relative to IPV, thus minimizing bias. The IPV assessment was dichotomized for ease in interpretation; further investigation is needed to evaluate the extent to which patterns identified may vary across severity levels and types (i.e., physical and sexual) violence. The self-reported nature of sexual risk behaviors by both male and female participants renders these measures imprecise.

The findings from this population-based study of IPV and HIV in India bolster the hypothesis that abused women face “double jeopardy,” i.e., compounded risk for HIV infection based on both abusive husbands’ greater likelihood of HIV infection and facilitated HIV transmission within abusive relationships. Patterns identified likely extend to other STIs that, while treatable, demonstrate higher population prevalence within the Indian context and elsewhere.25, 41, 42 The current evidence that IPV serves both as a risk marker for greater likelihood of HIV infection and as a direct HIV transmission mechanism serves to echo calls for simultaneous modification of men’s sexual risk behavior and reduction of violence perpetration against female partners both within South Asia and elsewhere.12, 15 As IPV may function to facilitate HIV transmission, the reduction of men’s sexual risk in the absence of reducing their abuse of female partners may fall critically short of stemming the secondary transmission of HIV and other STIs. Given evidence that over one in three women face abuse at the hands of their husbands both in the current sample and worldwide,43 the need for prevention to stem the interwoven threats of IPV and HIV to women’s health and well-being cannot be overstated.

Acknowledgements

Support for the creation of this article was provided to Dr. Decker via the Harvard University Center for AIDS Research (HU CFAR NIH/NIAID fund P30-AI060354).

References

1. Quinn TC, Overbaugh J. HIV/AIDS in women: an expanding epidemic. Science. 2005 Jun 10;308(5728):1582–1583. [PubMed]
2. Wingood GM. Feminization of the HIV epidemic in the United States: major researchfindings and future research needs. J Urban Health. 2003 Dec;80(4 Suppl 3):iii67–76. [PMC free article] [PubMed]
3. National AIDS Control Organization UNGASS Country Progress Report 2008 India. NACO; Delhi: 2008.
4. IIPS and Macro International India National Family Health Survey(NFHS-3) 2005-06. International Institute for Population Sciences (IIPS) and Macro International Inc.; Deonar, Mumbai and Calverton, Maryland [USA]: 2007.
5. Mehta SH, Gupta A, Sahay S, et al. High HIV prevalence among a high-risk subgroup ofwomen attending sexually transmitted infection clinics in Pune, India. J Acquir Immune Defic Syndr. 2006;41(1):75–80. [PubMed]
6. Gangakhedkar RR, Bentley ME, Divekar AD, et al. Spread of HIV infection in marriedmongamous women in India. JAMA. 1997;278(23):2090–2092. [PubMed]
7. Newmann S, Sarin P, PKumarasamy N, et al. Marriage, monogamy and HIV: a profile of HIV-infected women in south India. Int J STD AIDS. 2000;11(4):250–253. [PubMed]
8. Bates LM, Schuler SR, Islam F, Islam MK. Socioeconomic factors and processes associated wtih domestic violence in rural Bangladesh. International Family Planning Perspectives. 2004;30(4):190–199. [PubMed]
9. Koenig MA, Stephenson R, Ahmed S, Jejeebhoy SJ, Campbell J. Individual and contextual determinants of domestic violence in North India. Am J Public Health. 2006 Jan;96(1):132–138. [PubMed]
10. Kumar S, Jeyaseelan L, Suresh S, Ahuja RC. Domestic violence and its mental health correlates in Indian women. Br J Psychiatry. 2005 Jul;187:62–67. [PubMed]
11. Naved RT, Azim S, Bhuiya A, Persson LA. Physical violence by husbands: Magnitude, disclosure and help-seeking behavior of women in Bangladesh. Soc Sci Med. 2006 Jan 19;62(12):2917–2929. [PubMed]
12. Silverman JG, Decker MR, Kapur NA, Gupta J, Raj A. Violence against wives, sexualrisk and sexually transmitted infection among Bangladeshi men. Sex Transm Infect. 2007 Jun;83(3):211–215. [PMC free article] [PubMed]
13. Martin SL, Kilgallen B, Tsui AO, Maitra K, Singh KK, Kupper LL. Sexual behaviors and reproductive health outcomes: associations with wife abuse in India. Jama. 1999 Nov 24;282(20):1967–1972. [PubMed]
14. Stephenson R. Human immunodeficiency virus and domestic violence: the sleeping giants of Indian health? Indian J Med Sci. 2007 May;61(5):251–252. [PubMed]
15. Dunkle KL, Jewkes R. Effective HIV prevention requires gender-transformative work with men. Sex Transm Infect. 2007 Jun;83(3):173–174. [PMC free article] [PubMed]
16. Raj A, Santana C, La Marche A, Amaro H, Cranston K, Silverman JG. Perpetration of partner violence associated with sexual risk behaviors among young adult men. Am J Public Health. 2006;96(10):1873–1878. [PubMed]
17. Chandrasekaran V, Krupp K, George R, Madhivanan P. Determinants of domestic violence among women attending an human immunodeficiency virus voluntarycounseling and testing center in Bangalore, India. Indian J Med Sci. 2007 May;61(5):253–262. [PubMed]
18. Decker MR, Silverman JG, Raj A. Dating violence and sexually transmitted disease/HIV testing and diagnosis among adolescent females. Pediatrics. 2005 Aug;116(2):e272–276. [PubMed]
19. Dunkle KL, Jewkes RK, Brown HC, Gray GE, McIntryre JA, Harlow SD. Gender-based violence, relationship power, and risk of HIV infection in women attending antenatalclinics in South Africa. Lancet. 2004 May 1;363(9419):1415–1421. [PubMed]
20. Wingood GM, DiClemente RJ, Raj A. Adverse consequences of intimate partner abuse among women in non-urban domestic violence shelters. Am J Prev Med. 2000 Nov;19(4):270–275. [PubMed]
21. Decker MR, Miller E, Kapur NA, Gupta J, Raj A, Silverman JG. Intimate partner violence and sexually transmitted disease symptoms in a national sample of married Bangladeshi women. Int J Gynaecol Obstet. 2008;100(1):18–23. [PubMed]
22. Silverman JG, Decker MR, Saggurti N, Balaiah D, Raj A. Intimate partner violence and HIV infection among married Indian women. Jama. 2008 Aug 13;300(6):703–710. [PubMed]
23. WHO Violence Against Women and HIV/AIDS: Critical Intersections - Intimate Partner Violence and HIV/AIDS. WHO; Geneva: 2004.
24. Dunkle KL, Jewkes RK, Nduna M, et al. Perpetration of partner violence and HIV risk behaviour among young men in the rural Eastern Cape, South Africa. AIDS. 2006;20(16):2107–2114. [PubMed]
25. Schensul SL, Mekki-Berrada A, Nastasi BK, Singh R, Burleson JA, Bojko M. Men’s extramarital sex, marital relationships and sexual risk in urban poor communities in India. J Urban Health. 2006 Jul;83(4):614–624. [PMC free article] [PubMed]
26. Go VF, Sethulakshmi CJ, Bentley ME, et al. When HIV-prevention messages and gender norms clash: The impact of domestic violence on women’s HIV risk in the slums of Chennai, India. AIDS and Behavior. 2003;7(3):263–272. [PubMed]
27. Sivaram S, Johnson S, Bentley ME, et al. Sexual health promotion in Chennai, India: Key role of communication among social networks. Health Promotion International. 2005;20(4):327–333. [PubMed]
28. Wingood GM, DiClemente RJ. The effects of an abusive primary partner on the condom use and sexual negotiation practices of African-American women. Am J Public Health. 1997 Jun;87(6):1016–1018. [PubMed]
29. Slaughter L, Brown CR, Crowley S, Peck R. Patterns of genital injury in female sexual assault victims. Am J Obstet Gynecol. 1997 Mar;176(3):609–616. [PubMed]
30. WHO Putting women first: Ethical and safety recommendations for research on domestic violence against women. WHO, Department of Gender and Women’s Health; Geneva: 2001.
31. Straus MA, Hamby SL, Boney-McCoy S, Sugarman DB. The Revised Conflict Tactics Scales (CTS2) J Family Issues. 1996;17(3):283–316.
32. WHO/UNAIDS Guidelines for measuring national HIV prevalence in population-based surveys. WHO/UNAIDS; Geneva: 2005.
33. Santana MC, Raj A, Decker MR, La Marche A, Silverman JG. Masculine gender roles associated with increased sexual risk and intimate partner violence perpetration among young adult men. J Urban Health. 2006 Jul;83(4):575–585. [PMC free article] [PubMed]
34. Verma RK, Pulerwitz J, Mahendra V, et al. Challenging and changing gender attitudes among young men in Mumbai, India. Reprod Health Matters. 2006 Nov;14(28):135–143. [PubMed]
35. National AIDS Control Organization [Accessed];India Scenario: Women. 2008 May 20; http://www.nacoonline.org/Quick_Links/Women/
36. Jewkes R, Nduna M, Levin J, et al. Impact of stepping stones on incidence of HIV and HSV-2 and sexual behaviour in rural South Africa: cluster randomised controlled trial. Bmj. 2008;337:a506. [PMC free article] [PubMed]
37. Chhabra S. Sexual violence among pregnant women in India. J Obstet Gynaecol Res. 2008 Apr;34(2):238–241. [PubMed]
38. Raj A, Reed E, Santana MC, et al. Intimate partner violence perpetration, risky sexual behavior and STI/HIV diagnosis among heterosexual African American men. American Journal of Men’s Health. In press. [PubMed]
39. Gaillard P, Melis R, Mwanyumba F, et al. Vulnerability of women in an African setting: lessons for mother-to-child HIV transmission prevention programmes. Aids. 2002 Apr 12;16(6):937–939. [PubMed]
40. Temmerman M, Ndinya-Achola J, Ambani J, Piot P. The right not to know HIV-test results. Lancet. 1995 Apr 15;345(8955):969–970. [PubMed]
41. Garg S, Singh MM, Nath A, et al. Prevalence and awareness about sexually transmitted infections among males in urban slums of Delhi. Indian J Med Sci. 2007 May;61(5):269–277. [PubMed]
42. Ray K, Bala M, Bhattacharya M, Muralidhar S, Kumari M, Salhan S. Prevalence of RTI/STI agents and HIV infection in symptomatic and asymptomatic women attending peripheral health set-ups in Delhi, India. Epidemiol Infect. 2007 Dec 17;:1–9. [PubMed]
43. Garcia-Moreno C, Jansen HA, Ellsberg M, Heise L, Watts CH. Prevalence of intimate partner violence: findings from the WHO multi-country study on women’s health anddomestic violence. Lancet. 2006 Oct 7;368(9543):1260–1269. [PubMed]