Intimate partner violence and HIV testing during antenatal care: A latent class analysis to identify risk factors for HIV infection in mothers and their children in the United Republic of Tanzania
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Public Health & EpidemiologyAbstract
Intimate partner violence has adverse effects on mother’s overall health and prevention of mother to child HIV transmission. To identify and examine subgroups of mothers experiencing intimate partner violence and the likelihood of HIV testing during antenatal care, we conducted a latent class analysis using data from the Tanzania Demographic and Health Survey 2010 (N = 2,809). Intimate partner violence included mother’s experiences with partners’ controlling behaviors, as well as emotional, physical, and sexual violence. The outcome was mother’s accepting HIV testing offered during their antenatal care visit. Covariates included mother’s level of education, rural/urban residence, and prevention of mother to child HIV transmission talk during antenatal care visit. The latent class analysis indicated a three-class solution was the best model and identified the following profiles: mothers with no experience of intimate partner violence (61% of sample) with a 90.5% likelihood of HIV testing; mothers with moderate levels of intimate partner violence (26%) with an 84.7% likelihood of testing; and mothers with extreme levels of intimate partner violence (13%) with an 82% likelihood of testing. An auxiliary multinomial logistic regression with selected covariates was conducted to further differentiate IPV profiles, where mothers with extreme levels of intimate partner violence had 57% increased odds [95%CI:1.06–2.33, p = .023] of living in rural areas compared to mothers with no experience of intimate partner violence. Our person-centered methodological approach provided a novel model to understand the impact of multiple intimate partner violence risk factors on antenatal care HIV testing to identify mothers in need of interventions and their children at highest for parent to child HIV transmission. Our model allows person-centered interventional designs tailored for the most at-risk subgroups within a population.
Publication informationOriginally published in PLOS Global Public Health on 2022-08-12. Original DOI: 10.1371/journal.pgph.0000831.
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This work is made available under the CC0 1.0 public domain dedication.