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Correlates of Sexually Transmitted Infections Among South African Women Using Individual- and Community-Level Factors: Results from Generalized Additive Mixed Models

  • Handan WandEmail author
  • Natashia Morris
  • Reshmi Dassaye
  • Tarylee Reddy
  • Gita Ramjee
Original Paper

Abstract

South Africa has the highest burden of human immunodeficiency virus (HIV) infections in the world. There is also growing evidence that an individual’s risk of contracting HIV is increased by the presence of other sexually transmitted infections (STIs). The primary objective of this study was to examine the association between the prevalence of STIs in a cohort of South African women who enrolled in HIV prevention trials (2002–2012). The current study linked the individual factors with the community-level characteristics using geo-referencing. These multi-level data were analyzed in generalized additive mixed models settings. In the multivariate logistic regression model, younger age (odds ratio [OR] 4.30, 95% CI 3.20, 5.77 and OR 2.72, 95% CI 2.02, 3.66 for age < 25 and 25–29, respectively); being single/not cohabiting (OR 4.57, 95% CI 3.18, 6.53), two + sex partners (OR 1.46, 95% CI 1.18,1.80); parity < 2 (OR 2.04, 95% CI 1.53, 2.72), parity = 2 (OR 1.85, 95% CI 1.37, 2.48), and using injectables (contraceptive) (OR 1.53, 95% CI 1.13, 2.06) were all significantly associated with increased prevalence of STIs. Women who resided in the communities with high proportions of female headed-households were also significantly at higher risk for STIs (OR 1.20, p = .0025). Because these factors may reflect characteristics of the larger groups who share similar cultural norms and social environments, they can provide considerable insight into the spread of STIs. Prevention strategies based on individual and community-level drivers of STIs are likely to be the most effective means of targeting and reaching those at greatest risk of infection. This strategy has the potential to play a significant role in the epidemic’s trajectory.

Keywords

Generalized additive models Individual-level and population-level risk factors Sexually transmitted infection 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Handan Wand
    • 1
    Email author
  • Natashia Morris
    • 2
  • Reshmi Dassaye
    • 3
  • Tarylee Reddy
    • 2
  • Gita Ramjee
    • 2
  1. 1.Kirby InstituteUniversity of New South WalesKensingtonAustralia
  2. 2.Biostatistics UnitSouth African Medical Research CouncilDurbanSouth Africa
  3. 3.HIV Prevention Research UnitSouth African Medical Research CouncilWestvilleSouth Africa

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