Sex partner concurrency, geographic context, and adolescent sexually transmitted infections.
ABSTRACT Geographic areas characterized by a high prevalence of sexually transmitted infections (STIs) are critical to the maintenance and persistence of STIs within populations. Sex partner concurrency has been shown to be associated with increased risk for individual-level STIs.
The objectives of this study were to determine whether gonorrhea rate per census block group and sex partner concurrency independently and interactively are associated with a current bacterial STI among adolescents.
Face-to-face interviews and urine testing for Chlamydia trachomatis and Neisseria gonorrhoeae were conducted among female, sexually active, 14- to 19-year-olds presenting for reproductive clinic care between August 2000 and June 2002.
Gonorrhea rate per census block group and sex partner concurrency were not independently but were interactively associated with a current bacterial STI. Among participants with a main sex partner who practiced concurrency, living in high-prevalence geographic areas was significantly associated with a current bacterial STI.
The results suggest that geographic context may moderate an adolescent sex partner's behaviors. The research adds to the basic understanding of sexually transmitted disease transmission and acquisition in a high-prevalence inner-city setting.
Piel 09/2005; 20(7):331-337. DOI:10.1016/S0213-9251(05)72297-8
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ABSTRACT: Spatial analyses of HIV/AIDS related outcomes are growing in popularity as a tool to understand geographic changes in the epidemic and inform the effectiveness of community-based prevention and treatment programs. The Urban Health Study was a serial, cross-sectional epidemiological study of injection drug users (IDUs) in San Francisco between 1987 and 2005 (N = 29,914). HIV testing was conducted for every participant. Participant residence was geocoded to the level of the United States Census tract for every observation in dataset. Local indicator of spatial autocorrelation (LISA) tests were used to identify univariate and bivariate Census tract clusters of HIV positive IDUs in two time periods. We further compared three tract level characteristics (% poverty, % African Americans, and % unemployment) across areas of clustered and non-clustered tracts. We identified significant spatial clustering of high numbers of HIV positive IDUs in the early period (1987-1995) and late period (1996-2005). We found significant bivariate clusters of Census tracts where HIV positive IDUs and tract level poverty were above average compared to the surrounding areas. Our data suggest that poverty, rather than race, was an important neighborhood characteristic associated with the spatial distribution of HIV in SF and its spatial diffusion over time.International Journal of Environmental Research and Public Health 04/2014; 11(4):3937-55. DOI:10.3390/ijerph110403937 · 1.99 Impact Factor
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ABSTRACT: This study examined temporal and spatial relationships between neighborhood drug markets and gonorrhea among census block groups from 2002 to 2005. This was a spatial, longitudinal ecologic study. Poisson regression was used with adjustment in final models for socioeconomic status, residential stability and vacant housing. Increased drug market arrests were significantly associated with a 11% increase gonorrhea (adjusted relative risk (ARR) 1.11; 95% CI 1.05, 1.16). Increased drug market arrests in adjacent neighborhoods were significantly associated with a 27% increase in gonorrhea (ARR 1.27; 95% CI 1.16, 1.36), independent of focal neighborhood drug markets. Increased drug market arrests in the previous year in focal neighborhoods were not associated with gonorrhea (ARR 1.04; 95% CI 0.98, 1.10), adjusting for focal and adjacent drug markets. While the temporal was not supported, our findings support an associative link between drug markets and gonorrhea. The findings suggest that drug markets and their associated sexual networks may extend beyond local neighborhood boundaries indicating the importance of including spatial lags in regression models investigating these associations.Health & Place 06/2013; 23C:128-137. DOI:10.1016/j.healthplace.2013.06.002 · 2.44 Impact Factor