Objective: To more accurately predict women at greatest risk for HIV, we conducted an individually-matched case control study using data from women who attended an urban health clinic in Atlanta, GA to identify risk factors associated with HIV seroconversion.
Methods: We obtained data from women who sought care at Fulton County Board of Health Sexual Health Clinic between 2011 and 2016. Cases were women who seroconverted before 2018 but after having at least one clinician assisted visit (CAV) with the clinic prior to their date of HIV diagnosis. Controls were women who visited the clinic in this same time frame but remained HIV negative. Controls were individually matched to cases in a 2:1 matching ratio on race, age at first CAV (± one year of age), and date of first CAV (± three calendar months). Clinical characteristics and risk factors between cases and controls were compared using Chi-square and Fisher’s exact tests. Bivariate and multivariate conditional logistic regression were performed to develop a model for predicting probability of HIV seroconversion. We evaluated our predictive model using the global null hypothesis.
Results: Having a history of gonorrhea, multiple gonorrhea episodes, a history of syphilis, a greater number of sex partners in the past 2 months, anal sex, history of injection drug or crack cocaine use, a history of exchanging drugs/money for sex, and heterosexual sex with more than one sex partner in the last month were independently associated with HIV seroconversion. After conducting backward selection from a fully adjusted model, the predictors that remained in the model were: having a history of syphilis, anal sex, and injection drug or crack cocaine use. We obtained the following formula: ln(odds HIV seroconversion)= 1.596 (history of syphilis) + 1.073 (anal sex) + 3.459 (injection drug or crack cocaine use). Women having all of those risk factors were six times more likely to seroconvert than similar women without any of those factors.
Conclusion: Our results offer clinical insights into which women are most at-risk for HIV, and therefore best candidates for initiating HIV prevention interventions like pre-exposure prophylaxis (PrEP) for HIV within a HIV “hotspot” in the South.
Table of Contents
Table of Contents
Background/Literature Review 1
Study design and population 4
Statistical analysis 5
Future Directions 13
Table 1. 19
Table 2. 22
Figures and Figure Legends 23
Figure 1. 23
About this Master's Thesis
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