Mireille Guay, Aubrey Maquiling, Ruoke Chen, Valérie Lavergne, Donalyne-Joy Baysac, Jackie Kokaua, Catherine Dufour, Eve Dubé, Shannon E MacDonald, Nicolas L Gilbert
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Logistic regression models were fitted using sociodemographic factors as explanatory variables and vaccination status (unvaccinated vs at least one dose) or vaccination intent (unlikely versus likely or already vaccinated) as outcomes. To account for vaccine prioritization groups, multiple regression models were adjusted for province of residence, age, Indigenous identity and health care worker status.</p><p><strong>Results: </strong>Seniors with a lower household income (less than $60,000) and those living in smaller communities (fewer than 100,000 inhabitants) had higher odds of being unvaccinated. Among Canadian adults, the odds of being unlikely to get vaccinated were higher for males (adjusted odds ratio [AOR] 1.3), individuals younger than 60 (AOR between 3.3 and 5.1), non-health care workers (AOR 3.3), those with less than a high school education (AOR 3.4) or a household income of less than $30,000 (AOR 2.7) and individuals who do not identify as South Asian, Chinese, Black, Filipino, Arab, Latin American, Southeast Asian, West Asian, Korean or Japanese (AOR 1.7).</p><p><strong>Interpretation: </strong>COVID-19 vaccine uptake (80%) and vaccination intent (95%) were high among Canadians; however, relative disparities were observed among specific groups. Continued efforts targeted toward these groups are essential in reducing potential inequity in access or service provision.</p>","PeriodicalId":49196,"journal":{"name":"Health Reports","volume":"33 12","pages":"37-54"},"PeriodicalIF":2.7000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sociodemographic Disparities in COVID-19 Vaccine Uptake and Vaccination Intent in Canada.\",\"authors\":\"Mireille Guay, Aubrey Maquiling, Ruoke Chen, Valérie Lavergne, Donalyne-Joy Baysac, Jackie Kokaua, Catherine Dufour, Eve Dubé, Shannon E MacDonald, Nicolas L Gilbert\",\"doi\":\"10.25318/82-003-x202201200004-eng\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>This study's objective was to examine sociodemographic disparities in COVID-19 vaccine uptake and vaccination intent in the Canadian provinces by identifying factors associated with vaccine uptake in seniors prioritized for vaccination at the time of the survey and vaccination intent in all adults.</p><p><strong>Data and methods: </strong>A cross-sectional survey of Canadian adults was conducted in all provinces from mid-April to mid-May 2021. In addition to sociodemographic characteristics, respondents (n=10,678) provided information on their COVID-19 vaccination status or their intent to get vaccinated. Logistic regression models were fitted using sociodemographic factors as explanatory variables and vaccination status (unvaccinated vs at least one dose) or vaccination intent (unlikely versus likely or already vaccinated) as outcomes. To account for vaccine prioritization groups, multiple regression models were adjusted for province of residence, age, Indigenous identity and health care worker status.</p><p><strong>Results: </strong>Seniors with a lower household income (less than $60,000) and those living in smaller communities (fewer than 100,000 inhabitants) had higher odds of being unvaccinated. 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Sociodemographic Disparities in COVID-19 Vaccine Uptake and Vaccination Intent in Canada.
Introduction: This study's objective was to examine sociodemographic disparities in COVID-19 vaccine uptake and vaccination intent in the Canadian provinces by identifying factors associated with vaccine uptake in seniors prioritized for vaccination at the time of the survey and vaccination intent in all adults.
Data and methods: A cross-sectional survey of Canadian adults was conducted in all provinces from mid-April to mid-May 2021. In addition to sociodemographic characteristics, respondents (n=10,678) provided information on their COVID-19 vaccination status or their intent to get vaccinated. Logistic regression models were fitted using sociodemographic factors as explanatory variables and vaccination status (unvaccinated vs at least one dose) or vaccination intent (unlikely versus likely or already vaccinated) as outcomes. To account for vaccine prioritization groups, multiple regression models were adjusted for province of residence, age, Indigenous identity and health care worker status.
Results: Seniors with a lower household income (less than $60,000) and those living in smaller communities (fewer than 100,000 inhabitants) had higher odds of being unvaccinated. Among Canadian adults, the odds of being unlikely to get vaccinated were higher for males (adjusted odds ratio [AOR] 1.3), individuals younger than 60 (AOR between 3.3 and 5.1), non-health care workers (AOR 3.3), those with less than a high school education (AOR 3.4) or a household income of less than $30,000 (AOR 2.7) and individuals who do not identify as South Asian, Chinese, Black, Filipino, Arab, Latin American, Southeast Asian, West Asian, Korean or Japanese (AOR 1.7).
Interpretation: COVID-19 vaccine uptake (80%) and vaccination intent (95%) were high among Canadians; however, relative disparities were observed among specific groups. Continued efforts targeted toward these groups are essential in reducing potential inequity in access or service provision.
Health ReportsPUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
7.30
自引率
4.00%
发文量
28
期刊介绍:
Health Reports publishes original research on diverse topics related to understanding and improving the health of populations and the delivery of health care. We publish studies based on analyses of Canadian national/provincial representative surveys or Canadian national/provincial administrative databases, as well as results of international comparative health research. Health Reports encourages the sharing of methodological information among those engaged in the analysis of health surveys or administrative databases. Use of the most current data available is advised for all submissions.