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Activity spaces among injection drug users in San Francisco
Martinez, AN., Lorvick, J., & Kral, A. (2014). Activity spaces among injection drug users in San Francisco. International Journal of Drug Policy, 25(3), 516-524. https://doi.org/10.1016/j.drugpo.2013.11.008
BACKGROUND: Representations of activity spaces, defined as the local areas within which people move or travel in the course of their daily activities, are unexplored among injection drug users (IDUs). The purpose of this paper is to use an activity space framework to study place and drug user health. METHODS: Data for this analysis is from an epidemiological study of street-recruited IDUs in San Francisco (N=1084). Study participants reported geographic intersections of where they most often slept at night, hung out during the day, and used drugs during a 6 month time period. We used GIS software to construct and map activity space routes of street-based network paths between these intersections. We further identified if syringe exchange program (SEP) locations intersected with, participant activity space routes. We used logistic regression to estimate associations between activity space variables and HIV serostatus, syringe sharing, and non-fatal overdose, after adjusting for individual and Census tract covariates. RESULTS: Mean activity space distance for all participants was 1.5miles. 9.6% of participants had a SEP located along their activity space. An increase in activity space distance was associated with a decrease in odds of being HIV positive. An increase in residential transience, or the number of different locations slept in by participants in a 6 month time period, was associated with higher odds of syringe sharing. Activity space distance was not independently associated with overdose or syringe sharing. DISCUSSION: Research that locates individuals in places of perceived importance is needed to inform placement and accessibility of HIV and overdose prevention programs. More attention needs to be given to the logistics of collecting sensitive geospatial data from vulnerable populations as well as how to maximize the use of GIS software for visualizing and understanding how IDUs interact with their environment