The research team, led by Sanjiv Singh of the University of Petroleum and Energy Studies together with Jayantika Chakraborty and Sampurna Kundu, drew on the fifth round of the National Family Health Survey, conducted between 2019 and 2021. After applying the survey’s complex sampling weights and restricting the analysis to ever-married women aged 15 to 49 who completed the domestic violence module, the final weighted sample comprised 53,965 women. The outcome measure was a composite binary indicator capturing whether a respondent had experienced at least one act of physical, sexual, or emotional violence from her current or most recent husband at any point during the marriage, following the World Health Organization’s definition of intimate partner violence.

At the national level, the prevalence of intimate partner violence stood at 31.40 percent, consistent with the survey’s headline figure that 31.3 percent of married women aged 18 to 49 have experienced spousal violence. But the geographic contrast was dramatic. Kerala, India’s most educated state, reported a prevalence of roughly 12 percent, while Bihar, among the least educated, reported 42.6 percent. That nearly fourfold gap between two states within a single democracy frames the study’s central question: how much of the difference can be explained by the characteristics of women themselves, and how much by the normative and institutional environments they inhabit?

The statistical architecture of the study was correspondingly layered. Binary logistic regression estimated the associations between education, employment, and empowerment and the odds of reported violence, with interaction terms testing whether empowerment moderated those associations. Empowerment was measured using the SWPER global index, a validated tool for low- and middle-income countries built on three domains: attitudes toward wife-beating, social independence, and decision-making autonomy, each classified as low, medium, or high. The model showed adequate explanatory strength, with a likelihood ratio chi-square of 8677.36 and a pseudo R-squared of 0.1292. To probe the Kerala-Bihar gap, the team applied Fairlie decomposition, a nonlinear extension of the Blinder-Oaxaca technique that partitions a prevalence difference into the contributions of individual covariates. Generalized structural equation modelling added a test of whether empowerment mediates the pathway from education to violence.

The regression results confirmed the protective gradient for education. Compared with women who had no formal education, those with primary, secondary, and higher education had progressively lower odds of reporting intimate partner violence, with adjusted odds ratios of 0.83, 0.74, and 0.58 respectively. Husbands’ education mattered too: women whose husbands held higher education had 26 percent lower odds of reporting violence nationally. But in Bihar, women’s own education lost statistical significance, a pattern the authors read as evidence that the value of a structural resource depends on the normative conditions surrounding it. In Kerala, where female literacy is near-universal, education could not even be retained in the state model.

Employment told a different and darker story. Working women had higher odds of reported violence in every setting: non-working women had 13 percent lower odds nationally, 24 percent lower in Bihar, and 38 percent lower in Kerala. The pattern echoes what researchers call the male backlash hypothesis, in which a woman’s economic activity is perceived as a challenge to patriarchal authority and provokes retaliatory control. Earlier work in urban India had identified both a backlash effect and a so-called female guilt channel, in which working women are more likely to justify violence against themselves. The new analysis also found that when husbands were unemployed, their wives reported 22 percent lower odds of violence nationally, underscoring that the employment-violence link is relational rather than simply individual.

Two risk factors towered over everything else. Husbands’ alcohol consumption more than doubled the odds of intimate partner violence in all three settings, with adjusted odds ratios of 2.45 nationally, 2.58 in Bihar, and 2.44 in Kerala; among employed husbands who drank, the odds approached four times the reference nationally and reached 6.39 in Bihar. Childhood exposure to inter-parental violence was nearly as potent: women who had witnessed violence between their parents were more than three times as likely to experience partner violence themselves, with odds ratios of 3.09 nationally, 3.36 in Bihar, and 3.98 in Kerala. These findings highlight the intergenerational transmission of violence and suggest that substance-use interventions and early childhood programs could serve as critical entry points for prevention.

The empowerment results were the study’s most puzzling and, the authors argue, its most revealing. Relative to the most empowered women, those in the lowest categories of decision-making autonomy and of rejection of wife-beating had significantly lower odds of reporting violence, with odds ratios as low as 0.54 and 0.66 nationally. The most plausible interpretation is not that empowerment causes violence, but that empowerment changes disclosure. Women who internalize wife-beating as justified may set a higher threshold for recognizing and naming an act as violence in a survey, while women with greater marital authority may both recognize coercion more readily and, consistent with the backlash account, encounter more of it. Social independence behaved differently, declining in prevalence as independence rose, and it was the second-largest contributor to the Kerala-Bihar gap after women’s education.

The decomposition analysis quantified the state contrast. Women’s education explained 8.69 percent of the Kerala-Bihar difference in prevalence, the social independence domain 7.89 percent, exposure to parental violence 4.24 percent, husbands’ education 3.10 percent, and women’s employment 2.31 percent. Two characteristics, attitudes toward violence and husbands’ working status, contributed in the opposite direction, though neither reached statistical significance. Crucially, all measured factors together explained only about 18 percent of the gap, leaving the large residual to unmeasured contextual forces: governance quality, community gender norms, access to legal and health services, alcohol regulation, and state-level differences in the recognition and reporting of violence.

The authors are careful about what their cross-sectional design cannot establish. Causal ordering is unknown, employment may be endogenous to violence, and self-reported prevalence is almost certainly conservative, particularly where violence is normatively accepted. Still, the policy implications are pointed. Education and employment alone will not reduce violence without parallel shifts in household power and community norms; alcohol harm-reduction and primary care offer practical screening gateways; and breaking the intergenerational cycle demands interventions that reach children exposed to domestic violence. State-specific strategies, the study concludes, must pair individual empowerment with gender-transformative structural change, because the same resource can carry entirely different consequences under different normative regimes.

Subject of Research: Associations of women's education, employment, and empowerment with intimate partner violence in India

Article Title: Interrupting the violence: intersecting associations of education, employment, and empowerment with intimate partner violence in India

Article References: Singh, S., Chakraborty, J., & Kundu, S. (2026). Interrupting the violence: intersecting associations of education, employment, and empowerment with intimate partner violence in India. SN Social Sciences, 6(10), Article 494. https://doi.org/10.1007/s43545-026-01799-6

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01799-6

Keywords: intimate partner violence, India, NFHS-5, women's empowerment, education, employment, SWPER index, Kerala, Bihar, male backlash, decomposition analysis, gender norms

Stunting, defined as height-for-age falling more than two standard deviations below the benchmarks set by the World Health Organization’s child growth standards, is not simply a matter of being small. It reflects months or years of inadequate nutrition, repeated infection, and chronic stress during the most sensitive window of human development. Its consequences cascade: stunted children face elevated risks of cognitive impairment, weakened immunity, poorer school performance, and reduced adult earning capacity. That is why international health agencies treat stunting reduction as a central yardstick for progress on nutrition and equity.

The research team drew on two large, nationally representative household surveys: the 2016 South African Demographic and Health Survey, which measured 1,468 children under five, and the 2023 Lesotho Demographic and Health Survey, covering 1,574 children. Because these surveys combine standardized anthropometric measurements with detailed household records of income, education, residence, and maternal health, they allow researchers to place every measured child on a national socioeconomic spectrum, a powerful but data-hungry form of epidemiological mapping.

The headline numbers are sobering. In Lesotho, 35.6 percent of children under five were stunted, with a 95 percent confidence interval of 32.6 to 38.7 percent. South Africa fared somewhat better at 27.4 percent, with a confidence interval of 24.3 to 30.7 percent. These figures persist at high levels despite years of national nutrition programs, school feeding schemes, and social grants, suggesting that broad interventions alone are not reaching the households where growth failure begins.

The study’s methodological core lies in how it quantifies inequality. The team used the Erreygers corrected concentration index, a refinement of the standard concentration index designed to handle bounded health outcomes and produce more reliable rankings. In both countries the index was negative and statistically significant: −0.1442 in South Africa and −0.1818 in Lesotho, each at p less than 0.001. A negative value in this framework signals pro-poor inequality, meaning stunting is concentrated among children from poorer households rather than spread evenly across the wealth distribution.

The concentration curves make the pattern vivid. When children are ranked from poorest to richest and cumulative stunting is plotted against cumulative population, the curves for both countries sag above the diagonal of equality, showing that the poorest children accumulate a disproportionate share of the stunting burden. In Lesotho the deviation was even steeper than in South Africa, indicating that the wealth gradient in undernutrition is more pronounced in the smaller, mountainous kingdom.

Geography deepens the divide. In South Africa, stunted children were significantly more likely to live in rural areas than in urban ones, with the analysis yielding a coefficient of 0.1015 at p less than 0.05. This rural penalty likely reflects a constellation of disadvantages: longer distances to clinics and markets, higher food prices for staple goods, limited access to clean water and sanitation, and thinner coverage of early childhood services. In a country with one of the most developed economies in Africa, the persistence of rural nutritional deficits underscores how uneven development can be.

To move beyond description, the researchers deployed multivariable decomposition analysis, a technique borrowed from economics that splits an observed inequality into the contributions of its underlying factors. The results pointed to three dominant levers: maternal educational attainment, household wealth, and rural residence. Mothers with more education, the analysis implies, tend to have better access to nutritional knowledge, health services, and economic resources, all of which protect against growth faltering. Household wealth operates through food security, housing quality, and healthcare access, while rurality compounds both.

The authors argue that the findings carry direct policy weight. Strengthening integrated nutrition and social protection policies, they conclude, is critical to achieving equitable improvements in child nutritional outcomes in both countries. In practice, that means pairing food and micronutrient programs with investments in girls’ and women’s schooling, deepening child support grants and other cash-transfer systems, and deliberately targeting rural and remote communities where the burden is heaviest. Universal approaches that treat all children alike, the data suggest, will leave the poorest behind.

For a region where stunting remains stubbornly high despite decades of intervention, the study reframes the problem: this is not merely a question of food supply but of social structure. Until the economic gradient in childhood nutrition is flattened, the tallest children in South Africa and Lesotho will, in a statistical sense, keep growing up on the wealthier side of the line. The research, published open access in Discover Social Science and Health, gives policymakers a precise map of where and among whom the next generation’s growth potential is being lost, and a measured argument for why equity must move to the center of the nutrition agenda.

Subject of Research: Socio-economic inequalities in childhood stunting among children under five in South Africa and Lesotho

Article Title: Socio-economic inequalities in childhood stunting among children under five years in South Africa and Lesotho

Article References: Sello, M., Musonda, E., Mubita, A., Fikani, N., & Phiri, M. (2026). Socio-economic inequalities in childhood stunting among children under five years in South Africa and Lesotho. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00491-7

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00491-7

Keywords: childhood stunting, South Africa, Lesotho, socio-economic inequality, malnutrition, concentration index, decomposition analysis, maternal education, household wealth, rural health, child nutrition, demographic and health surveys

The research, conducted by Susanta Sen, Asif Ali, Amit Banerjee, and Namita Chakma of the Department of Geography at The University of Burdwan in West Bengal, drew on two rounds of India’s National Family Health Survey: the fourth round, conducted in 2015–16 with 122,955 women, and the fifth round, conducted in 2019–21 with 118,700 women. The analysis focused on women aged 20 to 24 years, the standard age group used to assess child marriage prevalence under international indicators, since these women had passed beyond the age at which a legal marriage before 18 could have occurred. By comparing the two survey rounds, the researchers were able to track both the level of child marriage and the distribution of that practice across the wealth spectrum over roughly a five-year interval.

To measure inequality rigorously, the team employed the Erreygers Concentration Index, a widely used summary measure in health equity research that captures whether a health or social outcome is systematically concentrated among richer or poorer groups. A negative value of the index indicates that the outcome is concentrated among the economically disadvantaged. In both survey rounds, the Erreygers Concentration Index for child marriage was negative and statistically significant, confirming that the burden of marrying before 18 falls disproportionately on girls from poorer households. The index moved from −0.281, with a 95 percent confidence interval of −0.289 to −0.273, in the fourth round to −0.257, with a 95 percent confidence interval of −0.265 to −0.249, in the fifth round, indicating a modest narrowing of wealth-related inequality but no fundamental change in its direction or magnitude.

The absolute picture tells a similarly nuanced story. The absolute gap in child marriage prevalence between the poorest and richest groups narrowed from 20.65 percentage points in NFHS-4 to 19.04 percentage points in NFHS-5. Yet the relative measure moved in the opposite direction: the ratio of child marriage prevalence among the poor compared with the non-poor actually increased, from 2.07 to 2.20. This combination of a shrinking absolute gap and a widening relative gap is a classic pattern in epidemiology and social statistics, arising when prevalence declines faster in absolute terms among groups that already have lower baseline levels. In practical terms, even though fewer girls overall are marrying as children, a girl born into a poor household today remains substantially more exposed to the risk of early marriage than one born into affluence, and in relative terms that exposure has grown.

Beyond describing the inequality, the study’s central methodological contribution lies in its use of regression-based decomposition analysis, a technique that partitions the observed concentration index into contributions attributable to individual socio-demographic characteristics. Rather than simply noting that child marriage correlates with poverty, decomposition analysis quantifies how much of the measured inequality each factor statistically explains. The results were striking in their consistency: educational attainment dominated the explained component of wealth-related inequality in both survey rounds, accounting for 77.06 percent in NFHS-4 and 77.41 percent in NFHS-5. In other words, differences in schooling levels between rich and poor women are by far the largest statistical driver of why early marriage clusters among the disadvantaged.

The composition of the remaining explained inequality shifted over time in ways that offer clues about the changing social landscape. In the fourth survey round, place of residence, meaning the divide between urban and rural areas, was the second-largest contributor to wealth-related inequality in child marriage. By the fifth round, however, the contribution of mass media exposure had risen substantially, overtaking residential location as a key explanatory factor. This shift suggests that access to information, whether through television, radio, newspapers, or increasingly digital channels, has become a more salient axis of inequality as connectivity spreads unevenly across Indian society. It also implies that the messages, norms, and alternatives that media exposure conveys about marriage, gender roles, and women’s life courses play a measurable role in shaping when and whether girls marry.

The study also documented substantial variation across India’s states and Union Territories, underscoring that child marriage is not a uniform national phenomenon but one embedded in highly diverse regional contexts of culture, economy, and policy implementation. States differ enormously in baseline prevalence, in the steepness of the wealth gradient, and in the pace of change between the two survey rounds. This heterogeneity means that a single national policy lever, applied uniformly, is unlikely to produce equitable results. Regions where the wealth gradient is steepest may require intensively targeted approaches, while regions with lower but persistent prevalence may benefit more from broad norm-change campaigns and enforcement of existing legal prohibitions on marriage below the age of 18.

The public health significance of these findings extends well beyond the institution of marriage itself. Child marriage is internationally recognized as a driver of adverse outcomes including early pregnancy, elevated maternal and infant mortality risks, interrupted schooling, restricted economic agency, and increased vulnerability to domestic violence. When the burden of child marriage concentrates among the poorest girls, it functions as a mechanism through which poverty and disadvantage reproduce themselves across generations. The study’s conclusion that reductions in overall prevalence have not been matched by equivalent reductions in socioeconomic inequality echoes a broader theme in development research: aggregate progress can mask persistent, and sometimes widening, disparities that demand explicit equity-oriented policy attention.

The authors point toward a set of policy directions grounded in their decomposition results. Because education explains such an overwhelming share of the inequality, interventions that support girls’ secondary education, reduce the economic pressures that push families to withdraw daughters from school, and keep adolescents enrolled through the years when marriage decisions are typically made stand out as the highest-leverage options. The growing contribution of mass media exposure suggests that improving access to information, and using media channels deliberately to shift social norms around early marriage, could complement educational investments. The researchers also highlight strengthening social protection for economically disadvantaged households and explicitly prioritizing the poorest families in programmatic targeting, since the data confirm that the risk of child marriage remains most intense at the bottom of the wealth distribution.

Ultimately, the study delivers a message that is both encouraging and cautionary. India has made genuine progress: child marriage prevalence declined measurably between 2015–16 and 2019–21, and the concentration index softened slightly. But the persistence of a large absolute wealth gap, the rise in the poor-to-non-poor prevalence ratio, and the stark regional differences all indicate that the finish line remains distant for the girls whom the practice continues to touch most directly. As India and the global community pursue the elimination of child marriage under international development goals, this research argues that success should be judged not only by how far national averages fall, but by how quickly the gap closes for those at the bottom, where the consequences of marrying too young are felt most severely.

Subject of Research: Wealth-related socioeconomic inequality in child marriage among young women in India

Article Title: Wealth-related inequality in child marriage in India using decomposition analysis

Article References: Sen, S., Ali, A., Banerjee, A., & Chakma, N. (2026). Wealth-related inequality in child marriage in India using decomposition analysis. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00488-2

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00488-2

Keywords: child marriage, India, wealth inequality, Erreygers Concentration Index, decomposition analysis, National Family Health Survey, girls' education, mass media exposure, social protection, public health, NFHS-5, socioeconomic disparity