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ASSOCIATIONS BETWEEN COVID-19 VACCINE HESITANCY AND SOCIOSPATIAL FACTORS IN NYC TRANSIT WORKERS 50 YEARS AND OLDER
Innov Aging ; 6(Suppl 1):457, 2022.
Article in English | PubMed Central | ID: covidwho-2188950
ABSTRACT
This analysis aimed to investigate how age, race/ethnicity, and geographical location contributed to vaccine hesitancy in a sample of New York City (NYC) Metropolitan Transit Authority (MTA) workers. Transport Workers Union, Local 100 members completed online surveys in August 2020 about their COVID-19 history, workplace protections and policies, fear of COVID-19 exposure, vaccination attitudes, and sociodemographic and health characteristics. We conducted univariate and bivariate analyses, followed by multivariate logistic regression, to determine the association between respondent age (younger than 50 vs. 50+) and vaccine hesitancy (willing vs. unwilling/unsure). We also produced spatial visualizations to examine these factors by participants' zip codes. Of 645 respondents, 59% were 50 years or older, 53% were non-White, and 71% expressed vaccine hesitancy. MTA workers ages 50+ were 46% less likely to be vaccine hesitant than their younger counterparts (OR 0.64;95% CI 0.42, 0.97). Compared to Whites, non-Whites (OR 3.95;95% 2.44, 6.39) and those who did not report their race (OR 3.10;95% CI 1.87, 5.12) were significantly more likely to be vaccine hesitant. Those who were not concerned about contracting COVID-19 in the community had 1.83 greater odds (95% CI 1.12, 2.98) of being vaccine hesitant than those who were concerned. Spatial visualizations revealed that the oldest respondents tended to reside in Queens. Zip codes with high vaccine hesitancy were clustered in Brooklyn, where non-White respondents tended to reside. The trends observed in COVID-19 vaccine hesitancy based on race and age persist in a population of high risk, non-healthcare essential workers.

Full text: Available Collection: Databases of international organizations Database: PubMed Central Topics: Vaccines Language: English Journal: Innov Aging Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: PubMed Central Topics: Vaccines Language: English Journal: Innov Aging Year: 2022 Document Type: Article