Cross-sectional association between ZIP code-level gentrification and homelessness among a large community-based sample of people who inject drugs in 19 US cities

• Authors: Sabriya Linton, Emory University; Hannah Cooper, Emory University; Mary Kelley, Emory University; Conny C. Karnes, Emory University; Zev Ross, ZevRoss Spatial Analysis; Mary E. Wolfe, Emory University; Samuel R. Friedman, National Development and Research Institutes; Don Des Jarlais, Mount Sinai Beth Israel; Salaam Semaan, Centers for Disease Control and Prevention; Barbara Tempalski, National Development and Research Institutes; Catlainn Sionean, Centers for Disease Control and Prevention; Elizabeth DiNenno, Centers for Disease Control and Prevention; Cyprian Wejnert, Centers for Disease Control and Prevention; Gabriella Paz-Bailey, Emory University
• Journal Title: BMJ Open
• Volume: Volume 7, Number 6
• Publisher: BMJ Publishing Group: Open Access | 2017-06-20, Pages e013823-e013823
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1136/bmjopen-2016-013823
• Subjects: Health Sciences, Public Health; Health Sciences, Epidemiology; Biology, Virology
• Keywords: Science & Technology; Life Sciences & Biomedicine; Medicine, General & Internal; General & Internal Medicine; NEW-YORK-CITY; BEHAVIORAL SURVEILLANCE SYSTEM; STREET-INVOLVED YOUTH; FRANCISCO BAY AREA; ANGELES SKID-ROW; HIV RISK; HOUSING STATUS; LOS-ANGELES; NEIGHBORHOOD DEPRIVATION; USERS IDUS; Public health; Epidemiology; HIV; AIDS; Substance misuse

Abstract

Background Housing instability has been associated with poor health outcomes among people who inject drugs (PWID). This study investigates the associations of local-level housing and economic conditions with homelessness among a large sample of PWID, which is an underexplored topic to date. Methods PWID in this cross-sectional study were recruited from 19 large cities in the USA as part of National HIV Behavioral Surveillance. PWID provided self-reported information on demographics, behaviours and life events. Homelessness was defined as residing on the street, in a shelter, in a single room occupancy hotel, or in a car or temporarily residing with friends or relatives any time in the past year. Data on county-level rental housing unaffordability and demand for assisted housing units, and ZIP code-level gentrification (eg, index of percent increases in non-Hispanic white residents, household income, gross rent from 1990 to 2009) and economic deprivation were collected from the US Census Bureau and Department of Housing and Urban Development. Multilevel models evaluated the associations of local economic and housing characteristics with homelessness. Results Sixty percent (5394/8992) of the participants reported homelessness in the past year. The multivariable model demonstrated that PWID living in ZIP codes with higher levels of gentrification had higher odds of homelessness in the past year (gentrification: adjusted OR=1.11, 95% CI=1.04 to 1.17). Conclusions Additional research is needed to determine the mechanisms through which gentrification increases homelessness among PWID to develop appropriate community-level interventions.