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Prescription opioid poisoning across urban and rural areas: identifying vulnerable groups and geographic areas
Author(s) -
Cerdá Magdalena,
Gaidus Andrew,
Keyes Katherine M.,
Ponicki William,
Martins Silvia,
Galea Sandro,
Gruenewald Paul
Publication year - 2017
Publication title -
addiction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.424
H-Index - 193
eISSN - 1360-0443
pISSN - 0965-2140
DOI - 10.1111/add.13543
Subject(s) - medicine , demography , medical prescription , pharmacy , injury prevention , relative risk , poison control , rural area , rate ratio , occupational safety and health , confidence interval , environmental health , geography , population , family medicine , pathology , sociology , pharmacology
Aims To determine (1) whether prescription opioid poisoning (PO) hospital discharges spread across space over time, (2) the locations of ‘hot‐spots’ of PO‐related hospital discharges, (3) how features of the local environment contribute to the growth in PO‐related hospital discharges and (4) where each environmental feature makes the strongest contribution. Design Hierarchical Bayesian Poisson space–time analysis to relate annual discharges from community hospitals to postal code characteristics over 10 years. Setting California, USA. Participants Residents of 18 517 postal codes in California, 2001–11. Measurements Annual postal code‐level counts of hospital discharges due to PO poisoning were related to postal code pharmacy density, measures of medical need for POs (i.e. rates of cancer and arthritis‐related hospital discharges), economic stressors (i.e. median household income, percentage of families in poverty and the unemployment rate) and concentration of manual labor industries. Findings PO‐related hospital discharges spread from rural and suburban/exurban ‘hot‐spots’ to urban areas. They increased more in postal codes with greater pharmacy density [rate ratio (RR) = 1.03; 95% credible interval (CI) = 1.01, 1.05], more arthritis‐related hospital discharges (RR = 1.08; 95% CI = 1.06, 1.11), lower income (RR = 0.85; 95% CI = 0.83, 0.87) and more manual labor industries (RR = 1.15; 95% CI = 1.10, 1.19 for construction; RR = 1.12; 95% CI = 1.04, 1.20 for manufacturing industries). Changes in pharmacy density primarily affected PO‐related discharges in urban areas, while changes in income and manual labor industries especially affected PO‐related discharges in suburban/exurban and rural areas. Conclusions Hospital discharge rates for prescription opioid (PO) poisoning spread from rural and suburban/exurban hot‐spots to urban areas, suggesting spatial contagion. The distribution of age‐related and work‐place‐related sources of medical need for POs in rural areas and, to a lesser extent, the availability of POs through pharmacies in urban areas, partly explain the growth of PO poisoning across California, USA.