Associations between neighborhood‐level factors and opioid‐related mortality: A multi‐level analysis using death certificate data. (3rd June 2020) - Flores, Michael William; Lê Cook, Benjamin; Mullin, Brian; Halperin‐Goldstein, Gabriel; Nathan, Aparna; Tenso, Kertu; Schuman‐Olivier, Zev
Abstract: Aim: To identify associations between opioid‐related mortality and neighborhood‐level risk factors. Design: Cross‐sectional study. Setting: Massachusetts, USA. Participants: Using 2011–14 Massachusetts death certificate data, we identified opioid‐related ( n  = 3089) and non‐opioid‐related premature deaths ( n  = 8729). Measurements: The independent variables consisted of four sets of neighborhood‐level factors: (1) psychosocial, (2) economic, (3) built environment and (4) health‐related. At the individual level we included the following compositional factors: age at death, sex, race/ethnicity, marital status, education, veteran status and nativity. The primary outcome of interest was opioid‐related mortality. Findings: Multi‐level models identified number of social associations per 10 000 [odds ratio (OR) = 0.84, P  = 0.002, 95% confidence interval (CI) = 0.75–0.94] and number of hospital beds per 10 000 (OR = 0.78, P  < 0.001, 95% CI = 0.68–0.88) to be inversely associated with opioid‐related mortality, whereas the percentage living in poverty (OR = 1.01, P  = 0.008, 95% CI = 1.00–1.01), food insecurity rate (OR = 1.21, P  = 0.002, 95% CI = 1.07–1.37), number of federally qualified health centers (OR = 1.02, P  = 0.028, 95% CI = 1.02–1.08) and per‐capita morphine milligram equivalents of hydromorphone (OR = 1.05, P  = 0.003, 95% CI = 1.01–1.08) were positively associated with opioid‐related mortality. Conclusions: Opioid‐related deaths between 2011 and 2014 in the state of Massachusetts appear to be positively associated with the percentage living in poverty, food insecurity rate, number of federally qualified health centers and per‐capita morphine milligram equivalents of hydromorphone, but inversely associated with number of social associations per 10 000 and number of hospital beds per 10 000.