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Opposing views: associations of political polarization, political party affiliation, and social trust with COVID-19 vaccination intent and receipt.
- Source :
- Journal of Public Health; Mar2023, Vol. 45 Issue 1, p36-39, 4p
- Publication Year :
- 2023
-
Abstract
- Introduction Political polarization has increased in the USA within recent years. Studies have shown Republicans are less likely to accept COVID-19 vaccinations than Democrats; however, little is known regarding the association between COVID-19 vaccination acceptance and political polarization. Methods We used data from a nationally-representative survey of 1427 participants conducted between 9 February 2021 and 17 February 2021. We estimated multivariate-adjusted odds ratios for COVID-19 vaccination intent and receipt according to perceived political polarization (measured as the perceived size of the ideological gap between Democrats and Republicans), political party affiliation, and social trust, controlling for demographic and socioeconomic factors. Results Among participants perceiving high levels of polarization, Republicans (versus Democrats) reported a 90% lower odds of vaccination intent (OR = 0.10 [0.05, 0.19], P  < 0.001). Participants with high (versus low) social trust and low perceived polarization had a 2-folder higher vaccination intent (OR = 2.39 [1.34, 4.21], P  = 0.003); this association was substantially weaker in the high perceived polarization group. Conclusions High perceived levels of political polarization appear to magnify the decrease in the odds of receiving the COVID-19 vaccine and the intent to get vaccinated among Republicans versus Democrats. Political polarization may further attenuate the protective associations of high social capital with vaccination. [ABSTRACT FROM AUTHOR]
- Subjects :
- VACCINATION
CONFIDENCE intervals
PRACTICAL politics
COVID-19 vaccines
ATTITUDE (Psychology)
CROSS-sectional method
MULTIVARIATE analysis
SOCIAL capital
SOCIOECONOMIC factors
DESCRIPTIVE statistics
POLITICAL participation
DATA analysis software
ODDS ratio
LOGISTIC regression analysis
DEMOGRAPHY
TRUST
Subjects
Details
- Language :
- English
- ISSN :
- 17413842
- Volume :
- 45
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Journal of Public Health
- Publication Type :
- Academic Journal
- Accession number :
- 162442601
- Full Text :
- https://doi.org/10.1093/pubmed/fdab401