The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level

Abstract

Background 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 whether other environmental and socioeconomic factors might play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality and COVID-19 mortality across U.S. counties. Methods Data from 3142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). Results After controlling for covariates, counties with higher rates of opioid-related mortality 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 Particulate Matter (PM2.5) exposure also saw significantly higher rates of COVID-19 mortality. Analyses revealed rural counties, counties with higher percentages of non-Hispanic whites, and counties with increased average maximum temperatures are significantly associated with lower mortality rates from COVID-19. Conclusions This study indicates need for public health efforts in hard hit COVID-19 regions to also focus prevention efforts on overdose risk among people who use opioids. Future studies using individual-level data are needed to allow for detailed inferences.

Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review

“…14 out of 164 papers included this criterion in their analysis on state, county, and city scales. The result of our review showed that the urban population in France ( Pilkington et al, 2021 ; Tchicaya et al, 2021 ), Iran ( Ramírez-Aldana et al, 2020 ), Bangladesh ( Alam, 2021 ), and the US ( Qeadan et al, 2021 ) increased the number of cases. However, reports from Italy ( Perone, 2021 ), the Netherlands ( Boterman, 2020 ), and China ( Chu et al, 2021 ) found an insignificant effect of urbanization on COVID-19 spread.…”

“…On the county scale , income just appeared in the papers conducted in the US and the results seem to be contrasting. Regarding COVID-19 incidence, income was a strong and significant predictor ( Qeadan et al, 2021 ; Wheaton and Kinsella Thompson, 2020 ; Wang et al, 2021 ; Mollalo et al, 2020 ). Wheaton and Kinsella Thompson (2020) discuss that as socializing and other face-to-face activities of residents are elastic to income, there are higher cases in wealthier households.…”

“…The highest number of papers that included population density in their analysis is on the county scale (as shown in Table 1 ). About 63 % of documents on this scale found population density as a driving force of COVID-19 spread ( Wong and Li, 2020 ; Kim et al, 2021 ; Aw et al, 2021 ; Jo et al, 2021 ; Qeadan et al, 2021 ; Q. Li et al, 2021 ; Lee et al, 2021 ). It is worth mentioning that 17 out of 27 of these papers were conducted in the US.…”

Similar COVID-19 incidence to the general population in people with opioid use disorder receiving integrated outpatient clinical care

“…Moreover, they are at increased risk of COVID-19, and its more serious complications, due to a number of reasons ( Wang et al, 2021a ; Qeadan et al, 2021 ). Overcrowded living facilities such as shelters for the homeless, prisons, and densely-populated neighborhoods are high-risk environments for coronavirus transmission ( Wang et al, 2020 ; Kinner et al, 2020 ).…”

Impacts of Built Environment on Risk of Women’s Lung Cancer: A Case Study of China

“…ESCAPE (European study of cohorts for air pollution effects) also found the risk of all types of lung cancer increased by 22% with a 10 μg/m 3 increase in PM10 and lung adenocarcinoma by 18% with a 5 μg/m 3 increase in PM2.5 [ 11 , 12 ]. In a cross-sectional COVID-19 study, Qeadan F. et al even found that higher average daily PM2.5 exposure is positively associated with higher county-level COVID-19 mortality rates based on data of 3142 counties across the U.S. [ 13 ]. This is not the only cause; a meta-analysis for the risk factors of Chinese lung cancer rate from 2006 to 2016 revealed air pollutants, history of respiratory disease, smoking and alcohol abuse are the most important risk factors [ 14 ].…”