Abstract
The aim of the current study is to examine factors related to opioid overdose deaths within the framework of social disorganization theory. We identify county-level factors related to overdose deaths among a series of measures related to economic (unemployment, health insurance coverage, and poverty) and socio-structural (prescribed opioid pills, racial heterogeneity, drug arrest rate, county rurality, and Appalachian location) disadvantage. Using panel data on counties in the United States drawn from five major, federal-level datasets, we perform a series of stepwise mixed-effects models to examine the relationships between economic and social markers of structural disadvantage and opioid-involved overdose deaths between the years 2006 and 2012. The proportion of poverty, unemployment, Appalachia, and pills prescribed are associated with increased opioid overdose deaths over time. A series of interactions illustrate that markers of disadvantage, including opioid prescriptions, often operate in tandem to exacerbate opioid overdose deaths. Based on standardized coefficients, the most predictive factor related to opioid overdose deaths is the volume of opioid pill prescriptions in a county on a year-to-year basis. Overall, this study emphasizes the utility of criminological theory in policy-related work focused on the opioid crisis. Our work also highlights the need for federal agencies to release data already collected on opioid pills to further our understanding of how to combat the opioid crisis.
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This research was supported in part by the Center for Family and Demographic Research, Bowling Green State University, which has core funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2CHD050959).
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Confer, L.M., Kuhl, D. & Boman, J.H. The Influence of Community Disadvantage and Opioid Pill Prescriptions on Overdose Deaths in American Counties. Am J Crim Just 48, 1295–1319 (2023). https://doi.org/10.1007/s12103-023-09737-5
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DOI: https://doi.org/10.1007/s12103-023-09737-5