Multilevel modeling of county-level excessive alcohol use, rurality, and COVID-19 case fatality rates in the US

PLoS One. 2021 Jun 17;16(6):e0253466. doi: 10.1371/journal.pone.0253466. eCollection 2021.


Objective: Reports of disparities in COVID-19 mortality rates are emerging in the public health literature as the pandemic continues to unfold. Alcohol misuse varies across the US and is related to poorer health and comorbidities that likely affect the severity of COVID-19 infection. High levels of pre-pandemic alcohol misuse in some counties may have set the stage for worse COVID-19 outcomes. Furthermore, this relationship may depend on how rural a county is, as access to healthcare in rural communities has lagged behind more urban areas. The objective of this study was to test for associations between county-level COVID-19 mortality, pre-pandemic county-level excessive drinking, and county rurality.

Method: We used national COVID-19 data from the New York Times to calculate county-level case fatality rates (n = 3,039 counties and county equivalents; October 1 -December 31, 2020) and other external county-level data sources for indicators of rurality and health. We used beta regression to model case fatality rates, adjusted for several county-level population characteristics. We included a multilevel component to our model and defined state as a random intercept. Our focal predictor was a single variable representing nine possible combinations of low/mid/high alcohol misuse and low/mid/high rurality.

Results: The median county-level COVID-19 case fatality rate was 1.57%. Compared to counties with low alcohol misuse and low rurality (referent), counties with high levels of alcohol and mid (β = -0.17, p = 0.008) or high levels of rurality (β = -0.24, p<0.001) demonstrated significantly lower case fatality rates.

Conclusions: Our findings highlight the intersecting roles of county-level alcohol consumption, rurality, and COVID-19 mortality.

MeSH terms

  • Alcoholism / epidemiology*
  • Alcoholism / physiopathology
  • COVID-19 / epidemiology*
  • COVID-19 / mortality
  • COVID-19 / virology
  • Comorbidity
  • Geography
  • Health Status Disparities
  • Humans
  • Models, Theoretical
  • Multivariate Analysis
  • Pandemics / prevention & control
  • Risk Factors
  • Rural Population / statistics & numerical data*
  • SARS-CoV-2 / isolation & purification*
  • SARS-CoV-2 / physiology
  • Severity of Illness Index
  • Socioeconomic Factors
  • Survival Rate
  • United States / epidemiology
  • Urban Population / statistics & numerical data*

Grant support

The authors received no specific funding for this work.