The spatial and temporal association of neighborhood drug markets and rates of sexually transmitted infections in an urban setting.

Health Place

Center for Child and Community Health Research (CCHR), Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, MD 21224, USA.

Published: September 2013

AI Article Synopsis

  • This study analyzed the connection between neighborhood drug markets and gonorrhea rates from 2002 to 2005, using a statistical method called Poisson regression.
  • Results showed that an increase in drug market arrests was linked to an 11% rise in gonorrhea cases, with even higher increases of 27% when considering arrests in neighboring areas.
  • The findings suggest that while past drug arrests in the same neighborhood didn't impact gonorrhea rates, the influence of drug markets may stretch beyond local areas, highlighting the importance of considering broader spatial factors in research.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845497PMC
http://dx.doi.org/10.1016/j.healthplace.2013.06.002DOI Listing

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