The research team set out to solve a stubborn methodological problem. Although leading causal frameworks of intimate partner violence have long conceptualized patriarchy as a structural-level driver of abuse, most empirical studies have been forced to rely on individual-level proxy measures—such as a woman’s own attitudes toward wife-beating, or her husband’s controlling behavior. Those proxies conflate what a person believes with the social architecture surrounding her, making it difficult to isolate the independent contribution of structural patriarchy itself. To get around this, the team turned to a validated composite measure known as the India Patriarchy Index, or IPI, which quantifies patriarchy at the structural level across geographic units, allowing researchers to ask whether the society a woman lives in predicts her risk of violence above and beyond her own characteristics.

The data source was India’s National Family Health Survey, specifically the fifth round, known as NFHS-5, a nationally representative household survey conducted under the auspices of the International Institute for Population Sciences and India’s Ministry of Health and Family Welfare. The analytic sample included 61,180 women aged 18 to 49 who were asked about their experiences of violence at the hands of a male partner in the preceding 12 months. The survey captures multiple distinct forms of abuse: emotional violence, physical violence, and sexual violence. This granularity matters, because different forms of violence may respond to different drivers, and interventions designed to prevent one form may not automatically protect against another.

The statistical approach was deliberately rigorous. The researchers used survey-weighted mixed effects logistic regression models, a technique that accounts for the hierarchical structure of the data—women nested within districts—and adjusts for the complex survey design that makes NFHS estimates representative of the national population. Crucially, the models did not simply compare raw rates of violence across districts. Instead, they adjusted for an extensive battery of potential confounders spanning other social stratification systems, including caste, religion, and household wealth, as well as attitudinal and behavioral indicators and a full set of socio-demographic characteristics. This adjustment strategy is what allows the analysis to disentangle structural patriarchy from other structural and individual-level determinants of violence—many of which, such as gender attitudes, have historically been used as stand-ins for patriarchy itself.

The headline result is striking. Compared with women living in districts with lower levels of structural patriarchy, women in districts with the highest levels of structural patriarchy had 1.9 times the odds of reporting experience of intimate partner violence of any type. In statistical terms, the adjusted odds ratio was 1.92, with a 95 percent confidence interval of 1.58 to 2.34. Because that entire interval sits well above 1.0, the association is unlikely to be a statistical fluke. The researchers also found a positive linear pattern, meaning that risk rose steadily across the spectrum of structural patriarchy rather than appearing only at the extreme end—a dose-response relationship that strengthens the case for a genuine association.

Importantly, the team disaggregated their models by the type of violence reported, examining any IPV, emotional-only violence, physical-only violence, sexual-only violence, and the experience of all forms simultaneously. This disaggregation reflects a growing recognition in the field that intimate partner violence is not a monolith. Emotional abuse, physical assault, and sexual coercion can have different etiologies, different correlates, and different consequences for survivors. By modeling each form separately, the study provides a more textured picture of how structural patriarchy relates to the full landscape of abuse, rather than collapsing everything into a single binary outcome.

What makes this study methodologically distinctive is the way it separates levels of analysis. The intraclass correlation coefficient—a statistic that quantifies how much of the variation in an outcome occurs between clusters rather than within them—plays a key role in this kind of multilevel modeling, and the mixed effects framework allowed the researchers to partition variance in violence risk across individual and district levels. The researchers also examined the spatial patterning of patriarchy using Local Indicators of Spatial Association, or LISA, a technique borrowed from spatial statistics that identifies geographic clustering of high and low values on a map. Together, these tools let the team describe where structural patriarchy concentrates in India and test whether that concentration translates into measurable differences in women’s safety.

The study’s intellectual lineage is also notable. The authors acknowledge Siegfried Gruber and Mikołaj Szołtysek, whose development of the original Patriarchy Index in the European context laid the groundwork for the India-specific adaptation used here. That index approach represents a conceptual shift: rather than treating patriarchy as an attitude to be surveyed, it treats it as a measurable property of social systems, assembled from indicators that capture how power, resources, and authority are distributed between men and women across a population. Applying such an index to a survey as large and methodologically mature as NFHS-5 allows researchers to test structural theories of violence at a scale that was previously impractical.

The implications for policy are significant. The authors argue that their findings underscore the need for district-level planning in violence prevention, and for the use of structural indicators alongside individual- and couple-level gender norms transformative programming. In practical terms, this means that programs aimed at changing the attitudes and behaviors of individual couples—valuable as they are—may be insufficient if the surrounding social structure continues to concentrate power and normalize male authority. India’s national health and rights initiatives, the study suggests, should incorporate structural measures of patriarchy when targeting resources and designing interventions, so that prevention strategies are calibrated to the structural realities of each district rather than applied uniformly across a vast and heterogeneous country.

The research also carries a broader message for global public health. Intimate partner violence affects millions of women worldwide, and the field has made enormous progress in cataloging its individual-level risk factors, from exposure to violence in childhood to alcohol use and economic dependency. But this study demonstrates that the social structures within which individuals are embedded carry independent predictive weight. A woman’s risk of being beaten, coerced, or humiliated by her partner depends in part on how patriarchal her district is—after accounting for her caste, her religion, her wealth, her own attitudes, and her personal circumstances. That is a sobering conclusion, but also an actionable one: if structures can be measured, they can be monitored, compared, and ultimately changed. The study, a secondary analysis of publicly available data that received ethical exemption from the University of California San Diego Institutional Review Board, was supported by the Bill & Melinda Gates Foundation and the National Institute on Alcoholism and Alcohol Abuse, with no funder involvement in design, analysis, or interpretation. As India and other countries confront the scale of gender-based violence, the evidence points toward a prevention agenda that operates at every level—from the couple, to the community, to the structure of society itself.

Subject of Research: The association between structural-level patriarchy and intimate partner violence in India using the India Patriarchy Index and national demographic and health survey data.

Article Title: Examining the association between structural-level patriarchy and intimate partner violence: evidence from India’s national demographic and health survey

Article References: Barker, K. M., Patwardhan, V., Chokhandre, P., Singh, A., Singh, A., & McDougal, L. (2026). Examining the association between structural-level patriarchy and intimate partner violence: evidence from India’s national demographic and health survey. International Journal for Equity in Health. https://doi.org/10.1186/s12939-026-03010-x

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03010-x

Keywords: intimate partner violence, patriarchy, India, National Family Health Survey, gender norms, domestic violence, structural determinants, public health, multilevel modeling, district-level planning, gender equity, NFHS-5