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

Abstract

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.

Positive Correlation Between Heavy Alcoholic Drinking and SARS-Cov-2 Non-Infection Rate

“…It is reasonable to suppose that all three events (inhaled, exhaled, direct contact) concur with the final finding in a synergistic way. Our findings match those showing that US counties with high alcohol consumption and high rurality experienced a significantly lower COVID-related mortality rate [ 8 ]. Interestingly, the significance of the Cochran-Armitage trend test supports our hypothesis that frequency matters more than the absolute quantity of ingested EtOH.…”

“…Indeed, the document released by WHO [ 6 ] is merely divulgation and does not bring any evidence supporting the section "general myths about alcohol and COVID-19" but simply affirms that "there is no evidence that drinking alcohol offers any protection against COVID-19 or has a positive effect on the course and outcomes of any infectious disease". Now, if this might have been acceptable in 2020, at present, the evidence showed by Pro et al [ 8 ] should lead to a selective update, at least. Particularly, the RCT from the Spanish group [ 12 ] found a faster and higher - even not significative - reduction of the viral load in the EtOH-treated patient's group versus controls.…”

“…The negative impact of alcohol drinking on health in the time of the COVID-19 pandemic has been discussed extensively [ 7 ]. However, an opposite report found that US counties with high alcohol consumption and high rurality experienced a significantly lower COVID-related mortality rate [ 8 ].…”

Alcohol Use and the Risk of Communicable Diseases

“…Studies on the association between alcohol use and the incidence and severity of COVID-19 have yielded mixed results. While some studies have found associations, in particular for heavy drinkers [178][179][180] or people with AUDs [181], other studies have demonstrated that alcohol use per se was not necessarily associated with the incidence of COVID-19 or with a more severe course of the disease [182][183][184]. This is in line with the postulated pathways described above, which mainly report effects for heavy drinking and/or in people with AUDs (see also [185][186][187]).…”

Aging in Rural Communities

“…One such measure is the Index of Relative Rurality (IRR) [49], which is calculated using population size, population density, distance to nearest metropolitan area, and percent urban population. The IRR has been used in several recent studies on health and aging, including health services utilization [50], geographic inequities in healthcare providers [51], availability of hospice care [52], opioid prescribing patterns [53], obesity [54], and COVID-19-related outcomes [55,56].…”