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Multilevel analysis identifies social and individual factors affecting HIV testing uptake in young women.
Background Human immunodeficiency virus (HIV) disproportionately affects young Nigerian women, yet testing uptake remains suboptimal. This study identified individual- and community-level determinants of HIV testing among this demographic to guide targeted healthcare interventions. Methods A secondary analysis of the 2024 Nigeria Demographic and Health Survey (NDHS) was conducted ( N = 14,634, ages 15-24). Multilevel logistic regression models were applied to account for the hierarchical data structure, with Model III (the full model containing both individual and community-level covariates) demonstrating the best fit based on Akaike information criterion and Bayesian information criterion. Results The prevalence of HIV testing among young women in Nigeria was 21.3%. The multilevel logistic regression analysis revealed that key individual-level factors significantly associated with higher odds of HIV testing included advanced age category, higher educational status, higher wealth index, high individual media exposure, comprehensive HIV knowledge, and a history of sexually transmitted infections. Additionally, marital status was a strong predictor, with married and formerly married women exhibiting significantly higher odds of testing compared to their never-married peers. At the community level, living in communities with high community-level HIV knowledge and high community wealth significantly boosted testing practice. The intraclass correlation coefficient in the null model indicated that 19.0% of the total variance in HIV testing practice was attributable to community-level factors, confirming a notable neighborhood effect. Conclusion HIV testing practices among young Nigerian women are multidimensionally shaped by a prominent “neighborhood effect” alongside individual socioeconomic and marital status. To bridge the current implementation gap in Nigeria, clinical and public health interventions must transition toward decentralized, community-based testing models that intentionally reach out to younger, never-married, and socioeconomically disadvantaged women.
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Derse et al. (2026) studied this question.
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