Systematic identification of correlates of HIV infection: an X-wide association study AIDS Patel, C. J., Bhattacharya, J., Ioannidis, J. A., Bendavid, E. 2018; 32 (7): 933–43


Better identification of at-risk groups could benefit HIV-1 care programmes. We systematically identified HIV-1 risk factors in two nationally representative cohorts of women in the Demographic and Health Surveys.We identified and replicated the association of 1415 social, economic, environmental, and behavioral factors with HIV-1 status. We used the 2007 and 2013-2014 surveys conducted among 5715 and 15?433 Zambian women, respectively (688 shared factors). We used false discovery rate criteria to identify factors that are strongly associated with HIV-1 in univariate and multivariate models of the entire population, as well as in subgroups stratified by wealth, residence, age, and past HIV-1 testing.In the univariate analysis, we identified 102 and 182 variables that are associated with HIV-1 in the two surveys, respectively (79 factors were associated in both). Factors that were associated with HIV-1 status in full-sample analyses and in subgroups include being formerly married (adjusted OR 2007, 2.8, P?

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