To examine individual‐ and community‐level factors associated with racial/ethnic differences in individuals’ opioid prescription use.
Outpatient opioid prescription utilization and demographic, socioeconomic, and health characteristics from a nationally representative sample of the US noninstitutionalized civilian population obtained from 2013‐2016 Medical Expenditure Panel Survey (MEPS) data and combined with 2012‐2016 American Community Survey data and 2015 Health Area Resources File data.
We use the Oaxaca‐Blinder decomposition method to disaggregate racial/ethnic differences in prescription opioid utilization into differences explained by underlying predisposing, enabling and need characteristics, and unexplained differences.
We use restricted‐use geographic identifiers to supplement the MEPS data with information on community characteristics and local health care resources.
The average annual rate of any outpatient opioid prescription use was higher for non‐Hispanic whites (15.8%; standard errors [SE]: 0.3) than for non‐Hispanic blacks and Hispanics by 1.4 percentage points (SE: 0.5) and 6.2 percentage points (SE: 0.4), respectively. The smaller difference between non‐Hispanic blacks and whites is not explained by the differences in the risk factors, while almost all the difference between Hispanics and non‐Hispanic whites can be explained by the differences in the means of the risk factors. The differences in the prevalence of pain, the rate of being United States‐born, and the racial/ethnic composition of the community explain 2.4 (SE: 0.2), 1.4 (SE: 0.3), and 1.9 (SE: 0.4) percentage‐point differences, respectively. Pain prevalence explains the difference regardless of opioid potency, while foreign‐born status and community racial/ethnic composition explain the difference in higher‐potency opioid utilization only.
This study underscores the importance of accounting for both individual and community characteristics when investigating patterns in opioid use. Our results could assist policy makers in tailoring strategies to promote safer and more effective pain management based on individual and community characteristics.
Data Collection/Extraction Methods