Associations of community socioeconomic factors and opioid use disorder across an urban-to-rural spectrum in Pennsylvania: an electronic health record-based case-control study.

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Bibliographic Details
Title: Associations of community socioeconomic factors and opioid use disorder across an urban-to-rural spectrum in Pennsylvania: an electronic health record-based case-control study.
Authors: Poulsen, Melissa N. (AUTHOR), Nordberg, Cara M. (AUTHOR), DeWalle, Joseph (AUTHOR), Reeder, Meghann (AUTHOR), Berrettini, Wade (AUTHOR), Schwartz, Brian S. (AUTHOR)
Source: Social Psychiatry & Psychiatric Epidemiology. Nov2025, Vol. 60 Issue 11, p2639-2651. 13p.
Subjects: Socioeconomic factors, Opioid abuse, Medical records, Disease risk factors, Public health, Urban fringe, Case-control method
Geographic Terms: Pennsylvania
Abstract: Purpose: To elucidate the role of community socioeconomic conditions in creating opioid-related risk environments, we assessed community-level socioeconomic measures in association with opioid use disorder (OUD) across a diverse geography. Methods: We conducted a case-control study using medical records (2012–2020) from a Pennsylvania health system to identify cases of OUD (n = 14,674) and controls (n = 58,696; frequency-matched on age, sex, year, medical record duration). Residential addresses were used to assign community-level measures: community socioeconomic deprivation (CSD), high proportional housing costs (HPHC), population in service occupations (PSO), and community credit score (CCS). Logistic regression analyzed associations of community type (city census tracts [CCT], boroughs, townships) and community socioeconomic features (stratified by community type) with OUD, adjusting for demographics and individual-level socioeconomic status. Results: CCT or borough (versus township) residence was associated with higher OUD odds. CSD, HPHC, and CCS were associated with OUD across community types; PSO was only associated in CCTs. The highest (versus lowest) level of CSD was associated (odds ratio, 95% CI) with higher OUD odds among individuals in townships (1.18 [1.03, 1.36]), boroughs (1.34 [1.09, 1.63]), and CCTs (1.46 [1.13, 1.88]). "Good" (versus "high fair") CCS was associated with lower odds in townships (0.78 [0.71, 0.86]), boroughs (0.56 [0.41, 0.77]), and CCTs (0.73 [0.44, 1.22]). Conclusion: Findings indicate poor community socioeconomic conditions are related to higher OUD risk, highlight the value of research regarding opioid-related risk environments, and suggest structural and policy interventions, such as vocational training and rent subsidies, as important for addressing the root causes of OUD. [ABSTRACT FROM AUTHOR]
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Database: Psychology and Behavioral Sciences Collection
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