Article Text

other Versions

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


              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.

              Statistics from

              Request permissions

              If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

              Linked Articles

              • Whistlestop tour
                Jackie A Cassell