Dataset Information

County-level association of COVID-19 mortality with 2020 United States presidential voting.

ABSTRACT:

Objective

The objective of this study was to assess the association between United States county-level COVID-19 mortality and changes in presidential voting between 2016 and 2020.

Study design

The study design is a county-level ecological study.

Methods

We analysed county-level population-weighted differences in partisan vote change, voter turnout and sociodemographic and health status characteristics across pre-election COVID-19 mortality quartiles. We estimated a population-weighted linear regression of the 2020-2016 Democratic vote change testing the significance of differences between quartiles of COVID-19 mortality, controlling for other county characteristics.

Results

The overall change in the 2020-2016 Democratic vote was +2.9% but ranged from a +4.3% increase in the lowest mortality quartile counties to +0.9% in the highest mortality quartile counties. Change in turnout ranged from +9.1% in the lowest mortality counties to only +6.2% in highest mortality counties. In regression estimates, the highest mortality quartile was associated with a -1.26% change in the Democratic 2020-2016 vote compared with the lowest quartile (P < 0.001).

Conclusions

Higher county-level COVID-19 mortality was associated with smaller increases in Democratic vote share in 2020 compared with 2016. Possible explanations to be explored in future research could include fear of in-person voting in heavily Democratic, high-mortality counties, fear of the economic effects of perceived Democratic support for tighter lockdowns and stay-at-home orders and general exhaustion that lowered political participation in hard-hit counties.

SUBMITTER: Parzuchowski AS

PROVIDER: S-EPMC9451615 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Publications

County-level association of COVID-19 mortality with 2020 United States presidential voting.

Parzuchowski A S AS Peters A T AT Johnson-Sasso C P CP Rydland K J KJ Feinglass J M JM

Public health 20210623

<h4>Objective</h4>The objective of this study was to assess the association between United States county-level COVID-19 mortality and changes in presidential voting between 2016 and 2020.<h4>Study design</h4>The study design is a county-level ecological study.<h4>Methods</h4>We analysed county-level population-weighted differences in partisan vote change, voter turnout and sociodemographic and health status characteristics across pre-election COVID-19 mortality quartiles. We estimated a populati ...[more]

PMID: 34416573

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Project description:BackgroundCoronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics.Methods and findingsIn this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.ConclusionsIn this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

Dataset Information

County-level association of COVID-19 mortality with 2020 United States presidential voting.

Objective

Study design

Methods

Results

Conclusions

Publications

County-level association of COVID-19 mortality with 2020 United States presidential voting.

Similar Datasets

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