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County-level association of COVID-19 mortality with 2020 United States presidential voting
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-weighte...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society for Public Health. Published by Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451615/ https://www.ncbi.nlm.nih.gov/pubmed/34416573 http://dx.doi.org/10.1016/j.puhe.2021.06.011 |
Sumario: | 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. |
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