Introduction Sociodemographic factors and chronic conditions associated with coronavirus disease 2019 (COVID-19) among persons with substance use disorder (PWSUD) are not well understood. We identified risk factors associated with COVID-19 among PWSUD with hospital visits. Methods Using the Premier Healthcare Database Special COVID-19 Release, we conducted a case-control study using ICD-10-CM codes to identify PWSUD aged 12 years and older with hospital visits for any reason during April–December 2020. Multivariable logistic regression was used to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) to identify factors associated with COVID-19 diagnosis among PWSUD (age, sex, race/ethnicity, U.S. Census Region, urban/rural classification, insurance payor type, comorbidities, and substance use disorder [SUD] type), and then stratified by SUD type. Results From April-December 2020, 18,298 (1.3%) of 1,429,154 persons with SUD in the database had a COVID-19 diagnosis. Among PWSUD, opioid use disorder (OUD; aOR=1.24, 95% CI=1.18-1.32), alcohol use disorder (AUD; aOR=1.16, 95%CI=1.11-1.22), cocaine or other stimulant use disorder (COUD; aOR=1.28, 95% CI=1.22-1.34), and multiple SUDs (aOR=1.20, 95%CI=1.15-1.26) were associated with higher odds of COVID-19, as were comorbidities such as chronic lower respiratory disease (aOR=1.32, 95% CI=1.26-1.37), chronic hepatitis (aOR=1.45, 95% CI=1.34-1.57), and diabetes (aOR=1.78, 95% CI=1.71-1.86). Conclusions Among a sample of PWSUD, OUD, AUD, COUD, multiple SUDs, and associated comorbidities were associated with COVID-19 diagnosis. Integration of COVID-related care, care of other comorbidities, and SUD treatment may benefit PWSUD. Future studies are needed to better understand COVID-19 prevention in this population and to reduce disparities among subpopulations at increased risk.

Background While overall opioid prescribing has been decreasing in the United States, the rates of prescribing at the county level have been variable. Previous studies show that social determinants of health (the social and economic conditions in which we live) may play a role in opioid prescribing; however, researchers have not examined this relationship across US counties. This cross-sectional study seeks to determine whether county-level sociodemographic characteristics (e.g., economic, housing, social environment, healthcare environment, and population characteristics) are associated with county level differences in opioid dispensing. Methods Data from 2,881 counties in the United States from 2017 to 2018 were used for this study. Opioid dispensing was measured using morphine milligram equivalents (MME) per capita. Spatial error models were used to measure the association between county-level sociodemographic characteristics and MME per capita while adjusting for spatial correlation between neighboring counties. Results In the adjusted model, counties with a higher percentage of people below the poverty line, with less than a 4-year college degree, and without health insurance were associated with higher MME dispensed per capita, as were counties with higher percentages of families headed by a single parent, persons separated or divorced, and those with disabilities. Conversely, minority race/ethnicity and rural population were associated with lower opioid dispensing. Conclusions County-level sociodemographics can differ in their association with opioid dispensing, hence examining which county-level factors help in improving opioid prescribing, and implementing overdose prevention strategies that tackle these factors is important.

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