TY - JOUR
T1 - Describing the changing relationship between opioid prescribing rates and overdose mortality
T2 - A novel county-level metric
AU - Hall, Eric W.
AU - Bradley, Heather M.
AU - Jones, Jeb
AU - Rosenberg, Eli S.
AU - Lopman, Ben
AU - Sullivan, Patrick S.
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/8/1
Y1 - 2021/8/1
N2 - Background and Aims: In the United States, the rate of drug overdose death has more than tripled over the past two decades, a trend that is often attributed to changes in opioid prescribing practices. We developed a novel, longitudinal metric to summarize the relationship between prescription opioid prescribing practices and drug overdose mortality and to assess if longitudinal changes in that relationship differ by characteristics of place. Methods: We constructed a single county-level measure of overdose deaths per 100,000 opioid prescriptions annually from 2006 to 2018. We used latent profile analysis to classify all U.S. counties into classes based on demographic and socioeconomic characteristics and fit a mixed Poisson log-linear model to quantify temporal changes in our measure by county-type classes. Results: Latent profile analysis resulted in 7 classes with high separation between classes (overall entropy = 0.916). Across all groups, the average number of overdose deaths per opioid prescription remained steady from 2006 to 2011 and increased from 2012–2018. The largest increases were in the high GDP (average annual change: 18.1 %, 95 %CI: 17.5, 18.6) and high education classes (16.6 %, 95 %CI: 16.0, 17.1). Conclusions: This novel summary metric enhances our understanding of the shift in overdose mortality and the role of geography and place characteristics.
AB - Background and Aims: In the United States, the rate of drug overdose death has more than tripled over the past two decades, a trend that is often attributed to changes in opioid prescribing practices. We developed a novel, longitudinal metric to summarize the relationship between prescription opioid prescribing practices and drug overdose mortality and to assess if longitudinal changes in that relationship differ by characteristics of place. Methods: We constructed a single county-level measure of overdose deaths per 100,000 opioid prescriptions annually from 2006 to 2018. We used latent profile analysis to classify all U.S. counties into classes based on demographic and socioeconomic characteristics and fit a mixed Poisson log-linear model to quantify temporal changes in our measure by county-type classes. Results: Latent profile analysis resulted in 7 classes with high separation between classes (overall entropy = 0.916). Across all groups, the average number of overdose deaths per opioid prescription remained steady from 2006 to 2011 and increased from 2012–2018. The largest increases were in the high GDP (average annual change: 18.1 %, 95 %CI: 17.5, 18.6) and high education classes (16.6 %, 95 %CI: 16.0, 17.1). Conclusions: This novel summary metric enhances our understanding of the shift in overdose mortality and the role of geography and place characteristics.
KW - County
KW - Drug overdose mortality
KW - Opioid prescriptions
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U2 - 10.1016/j.drugalcdep.2021.108761
DO - 10.1016/j.drugalcdep.2021.108761
M3 - Article
C2 - 34051545
AN - SCOPUS:85106403679
SN - 0376-8716
VL - 225
JO - Drug and Alcohol Dependence
JF - Drug and Alcohol Dependence
M1 - 108761
ER -