Neighborhood Socioeconomic Environment and Sexual Network Position

Rates of sexually transmitted infections (STIs) are strongly associated with neighborhood poverty; however, the mechanisms responsible for this association remain unclear. Using a population-based study of sexual networks among urban African American adolescents, we tested the hypothesis that poverty, unemployment, and the sex ratio drive STI rates by affecting sexual network structure. Participants were categorized as being in one of three network positions that had previously been found to be strongly linked to infection with chlamydia and gonorrhea: being in a confirmed dyad (i.e., a monogamous pair), being connected to a larger network through one partner, and being in the center of a larger network. We found that only poverty was statistically significantly associated with sexual network position. Residing in the poorest third of neighborhoods was associated with 85% decreased odds of being in confirmed dyads. There was no association of sexual network position with neighborhood employment. Living in a neighborhood with an unequal number of young men and women appeared to be associated with a higher likelihood of being in a confirmed dyad; however, the differences were not statistically significant. These results suggest that poverty may impact STI rates by shaping sexual network structure, but we did not find any evidence that this association operates through unemployment or the sex ratio.

[1]  K. Holmes,et al.  Avoiding risky sex partners: perception of partners’ risks v partners’ self reported risks , 2003, Sexually transmitted infections.

[2]  D. Massey.  American Apartheid: Segregation and the Making of the Underclass , 1993 .

[3]  K. Holmes,et al.  Sociodemographic distribution of gonorrhea incidence: implications for prevention and behavioral research. , 1991, American journal of public health.

[4]  Adaora A Adimora,et al.  Contextual factors and the black-white disparity in heterosexual HIV transmission. , 2002, Epidemiology.

[5]  J. M. Oakes,et al.  The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology. , 2004, Social science & medicine.

[6]  David R. Holtgrave,et al.  Social Capital as a Predictor of Adolescents' Sexual Risk Behavior: A State-Level Exploratory Study , 2003, AIDS and Behavior.

[7]  J. Wildgen,et al.  "Broken windows" and the risk of gonorrhea. , 2000, American journal of public health.

[8]  Mitchell B. Chamlin,et al.  Unemployment, Economic Theory, and Property Crime: A Note on Measurement , 2000 .

[9]  J. Santelli,et al.  Neighborhood context and sexual behaviors among adolescents: findings from the national longitudinal study of adolescent health. , 2005, Perspectives on sexual and reproductive health.

[10]  H. White.  Maximum Likelihood Estimation of Misspecified Models , 1982 .

[11]  V. Sadock.  The Social Organization of Sexuality: Sexual Practices in the United States , 1995 .

[12]  A. Ghani,et al.  The Role of Sexual Partnership Networks in the Epidemiology of Gonorrhea , 1997, Sexually transmitted diseases.

[13]  K. Brewster.  Neighborhood context and the transition to sexual activity among young black women , 1994, Demography.

[14]  S V Subramanian,et al.  Race/ethnicity, gender, and monitoring socioeconomic gradients in health: a comparison of area-based socioeconomic measures--the public health disparities geocoding project. , 2003, American journal of public health.

[15]  D R Holtgrave,et al.  Social capital, poverty, and income inequality as predictors of gonorrhoea, syphilis, chlamydia and AIDS case rates in the United States , 2003, Sexually transmitted infections.

[16]  P. Kilmarx,et al.  The social ecology of syphilis. , 1999, Social science & medicine.

[17]  R. Royall.  Model robust confidence intervals using maximum likelihood estimators , 1986 .

[18]  R. Rothenberg,et al.  The geography of gonorrhea. Empirical demonstration of core group transmission. , 1983, American journal of epidemiology.

[19]  W. Wilson.  The truly disadvantaged : the inner city, the underclass, and public policy , 1988 .

[20]  N. Adler,et al.  What you don't know can hurt you: perceptions of sex-partner concurrency and partner-reported behavior. , 2004, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[21]  S Q Muth,et al.  Sexual network position and risk of sexually transmitted infections , 2009, Sexually Transmitted Infections.

[22]  W. Wilson.  When Work Disappears: The World of the New Urban Poor , 1996 .

[23]  A. Adimora,et al.  Concurrent Sexual Partnerships Among Women in the United States , 2002, Epidemiology.

[24]  S V Subramanian,et al.  Monitoring Socioeconomic Inequalities in Sexually Transmitted Infections, Tuberculosis, and Violence: Geocoding and Choice of Area-Based Socioeconomic Measures—The Public Health Disparities Geocoding Project (US) , 2003, Public health reports.

[25]  K. Holmes,et al.  Do People Really Know Their Sex Partners?: Concurrency, Knowledge of Partner Behavior, and Sexually Transmitted Infections Within Partnerships , 2004, Sexually transmitted diseases.

[26]  M. S. St. Louis,et al.  Sociodemographic factors and the variation in syphilis rates among US counties, 1984 through 1993: an ecological analysis. , 1997, American journal of public health.

[27]  N. Krieger,et al.  Socioeconomic differences in sexually transmitted disease rates among black and white adolescents, San Francisco, 1990 to 1992. , 1995, American journal of public health.

[28]  Adaora A Adimora,et al.  Social context, sexual networks, and racial disparities in rates of sexually transmitted infections. , 2005, The Journal of infectious diseases.

[29]  James C. Thomas,et al.  Social structure, race, and gonorrhea rates in the southeastern United States. , 2003, Ethnicity & disease.