Abstract
BACKGROUND AND AIM: The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclear whether COVID-19 and opioid use outcomes may be related, and the extent to which environmental factors, such as particulate matter (PM2.5) and temperature, play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality, environmental factors, and COVID-19 mortality across U.S. counties. METHODS: Data from 3,142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020 as well as the number of opioid overdoses per 100,000 persons. PM2.5 exposure data was derived from the Environmental Protection Agency’s Air Quality System Downscaler model; median household income; health statuses relating to smoking, excessive drinking, access to places of physical activity, and diabetes; unemployment status; and rural status were obtained from the County Health Rankings database. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). RESULTS:In multivariable models, counties with higher rates of opioid overdose per 100,000 persons were found to be significantly associated with higher rates of COVID-19 mortality (aMRR: 1.0134; 95% CI [1.0054, 1.0214]; P=0.001). Counties with higher average daily PM2.5 exposure also saw significantly higher rates of COVID-19 mortality (aMRR: 1.0695; 95% CI [1.0194, 1.220]), while counties with higher maximum average temperature was associated with lower mortality (aMRR: 0.9784; 95% CI [0.9682, 0.9889]). CONCLUSIONS:In an ecological study of US counties, we found that higher rates of opioid overdose and higher PM2.5 levels were associated with higher rates of COVID-19 mortality. KEYWORDS: Air pollution, Temperature, Pharmaceuticals, Infectious diseases, Socio-economic factors
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