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Sexual network position and risk of sexually transmitted infections
  1. Caroline M Fichtenberg (cfichten{at}jhsph.edu)
  1. Johns Hopkins University, United States
    1. Stephen Q Muth (sqmuth{at}earthlink.net)
    1. Quintus-ential Solutions, United States
      1. Beth Brown (brownb{at}obgyn.ucsf.edu)
      1. University of California, San Francisco, United States
        1. Nancy S Padian (npadian{at}rti.org)
        1. RTI International, United States
          1. Thomas A Glass (tglass{at}jhsph.edu)
          1. Johns Hopkins Bloomberg School of Public Health, United States
            1. Jonathan M Ellen (jellen{at}jhmi.edu)
            1. Johns Hopkins School of Medicine, USA

              Abstract

              Objectives: A population-based sexual network study was used to identify sexual network structures associated with sexually transmitted infection (STI) risk, and to evaluate the degree to which addition of network-level data furthers the understanding of STI risk.

              Methods: Participants (N=655) were from the baseline and 12 month follow-up waves of a 2000-2001 population-based longitudinal study of sexual networks among urban African American adolescents. Sexual network position was characterized as the interaction between degree (number of partners) and 2-reach centrality (number of partners’ partners), resulting in the following five positions: confirmed dyad, unconfirmed dyad, periphery of non-dyadic network, center of star-like network, and center of non-star network. STI risk was measured as laboratory-confirmed infection with gonorrhea and/or chlamydia.

              Results: Logistic regression with generalized estimating equations showed that being in the center of a sexual network component increased the odds of infection at least six-fold compared to being in a confirmed dyad. Individuals with only one partner were at nearly five-fold increased risk if their partner was connected to others. Measuring network position using only individual-level information led to two-fold underestimates of the associations between STI risk and network structure.

              Conclusions: These results demonstrate the importance of using sexual network data to fully capture the probability of exposure to an infected partner.

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