ArticleJournal of global health2025
Small area geographic variation in girl and boy child marriage in India: a district-level longitudinal analysis, 2016 and 2021.
Article in Journal of global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Sustainable Development Goal (SDG) target 5.3 aims to 'eliminate all harmful practices, such as child, early, and forced marriage'. India is a signatory to the SDGs and tracks this indicator to measure national progress. Geographic inequity in the change in the district-level prevalence of child marriage over time in India has not been previously explored. Methods: We used data from the National Family Health Survey (NFHS) in India from 2016 (NFHS-4) and 2021 (NFHS-5). We aligned districts to be consistent over time. We included 720 districts for girls and 716 for boys. We used a four-level logistic regression model to partition the total variation of boy (<21 years) and girl child marriage (<18 years) in each year. We computed a precision-weighted prevalence of girl and boy child marriage, as well as within-district variation, using standard deviation measures. Results: Across districts, the average prevalence of child marriage decreased from 22.65% to 18.89% among girls and from 16.17% to 13.57% among boys. Inequality across districts in the prevalence of girl and boy child marriage decreased between 2016-21, and there was a negative association between district prevalence in 2016 and the change in district prevalence between 2016-21. There was a positive correlation between the difference in prevalence in boy (r = 0.72; P < 0.001) and girl (r = 0 · 60; P < 0.001) child marriage and the change in standard deviation across districts, indicating increasing inequality in the worst-performing districts. Conclusions: We provide new insight into recent progress and setbacks in eliminating child marriage across India. We found considerable district-level heterogeneity and clustering of poorly performing districts, coupled with increasing local inequality, especially within the worst-performing districts. Intervention and policy may be more effective if informed by local inequality.
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