Demographic Determinants and Geographical Variability of COVID-19 Vaccine Hesitancy in Underserved Communities: Cross-sectional Study.
Demographic Determinants and Geographical Variability of COVID-19 Vaccine Hesitancy in Underserved Communities: Cross-sectional Study.
复制标题
DOI：
10.2196/34163
复制
发表时间：
2023-04-27
影响因子：
8.5
通讯作者：
Il'yasova, Dora
中科院分区：
文献类型：
--
作者：
Matas, Jennifer L.;Landry, Latrice G.;Lee, LaTasha;Hansel, Shantoy;Coudray, Makella S.;Mata-McMurry, Lina, V;Chalasani, Nishanth;Xu, Liou;Stair, Taylor;Edwards, Christina;Puckrein, Gary;Meyer, William;Wiltz, Gary;Sampson, Marian;Gregerson, Paul;Barron, Charles;Marable, Jeffrey;Akinboboye, Olakunle;Il'yasova, Dora
关键词：
新冠肺炎的住院和死亡对服务不足和少数族裔人群的影响不成比例，他们强调，疫苗接种迟迟不及时可能是这些人群中一个特别重要的公共卫生风险因素。这项研究旨在表征服务不足的不同人群中新冠肺炎疫苗的迟疑性。少数民族和农村冠状病毒洞察研究从加利福尼亚州、中西部(伊利诺伊州/俄亥俄州)、佛罗里达州和路易斯安那州的联邦合格卫生中心招募了一名方便的成年人(年龄≥18，N=3735)，并收集了2020年11月至2021年4月的基线数据。疫苗犹豫不决状态被定义为对“如果有冠状病毒疫苗，你会接种吗？”这一问题的回答是“不”或“未决定”。(“是”归类为毫不犹豫)。横断面描述性分析和Logistic回归模型检验了年龄、性别、种族/民族和地理位置对疫苗迟疑率的影响。使用公布的县级数据计算了研究县对普通人群的预期疫苗迟疑估计。使用卡方检验评估每个地区内与人口统计特征的粗略关联。主要影响模型包括年龄、性别、种族/民族和地理区域，以估计调整后的优势比(OR)和95%的顺位。地理和每个人口统计特征之间的交互作用在不同的模型中进行了评估。不同地理区域的疫苗犹豫变异性最强：加利福尼亚州，27.8%(范围25.0%-30.6%)；中西部，31.4%(范围27.3%-35.4%)；路易斯安那州，59.1%(范围56.1%-62.1%)；佛罗里达州，67.3%(范围64.3%-70.2%)。对总人口的预期估计较低：9.7%(加利福尼亚州)、15.3%(中西部)、18.2%(佛罗里达州)和27.0%(路易斯安那州)。人口统计模式也因地理位置而异。年龄分布呈倒U形，在佛罗里达州(n=88，80.0%)和路易斯安那州(n=54，79.4%；P<；0.05)，25-34岁年龄段患病率最高。在中西部(n=110，36.4%比n=48，23.5%)、佛罗里达(n=458，71.6%比n=195，59.3%)和路易斯安那州(n=425，66.5%比n=172，46.5%；P<；0.05)，女性比男性更犹豫不决。在加利福尼亚州和佛罗里达州发现了种族/民族差异，非西班牙裔黑人参与者的患病率最高(n=86，45.5%)，佛罗里达州的拉美裔参与者(n=567，69.3%)的患病率最高(P<；0.05)，但中西部和路易斯安那州没有。主效应模型证实了年龄与年龄呈U型相关：与年龄25-34岁的相关性最强(OR 2.29，95%CI 1.74-3.01)。按照粗略分析发现的模式，性别和种族/族裔与该区域的统计相互作用是显著的。与加州男性相比，佛罗里达州(OR=7.88，95%CI 5.96~10.41)和路易斯安那州(OR=6.09，95%CI 4.55~8.14)与女性的相关性最强。与加州的非西班牙裔白人参与者相比，佛罗里达州的西班牙裔参与者(OR=11.18，95%CI 7.01-17.85)和路易斯安那州的黑人(OR=8.94，95%CI 5.53-14.47)的相关性最强。然而，在加利福尼亚州和佛罗里达州观察到了最强的种族/民族差异：这两个地区的种族/民族之间的OR值分别相差4.6倍和2倍。这些发现突显了当地背景因素在推动疫苗迟疑及其人口统计模式中的作用。
COVID-19 hospitalizations and deaths disproportionately affect underserved and minority populations, emphasizing that vaccine hesitancy can be an especially important public health risk factor in these populations. This study aims to characterize COVID-19 vaccine hesitancy in underserved diverse populations. The Minority and Rural Coronavirus Insights Study (MRCIS) recruited a convenience sample of adults (age≥18, N=3735) from federally qualified health centers (FQHCs) in California, the Midwest (Illinois/Ohio), Florida, and Louisiana and collected baseline data in November 2020-April 2021. Vaccine hesitancy status was defined as a response of “no” or “undecided” to the question “Would you get a coronavirus vaccine if it was available?” (“yes” categorized as not hesitant). Cross-sectional descriptive analyses and logistic regression models examined vaccine hesitancy prevalence by age, gender, race/ethnicity, and geography. The expected vaccine hesitancy estimates for the general population were calculated for the study counties using published county-level data. Crude associations with demographic characteristics within each region were assessed using the chi-square test. The main effect model included age, gender, race/ethnicity, and geographical region to estimate adjusted odds ratios (ORs) and 95% CIs. Interactions between geography and each demographic characteristic were evaluated in separate models. The strongest vaccine hesitancy variability was by geographic region: California, 27.8% (range 25.0%-30.6%); the Midwest, 31.4% (range 27.3%-35.4%); Louisiana, 59.1% (range 56.1%-62.1%); and Florida, 67.3% (range 64.3%-70.2%). The expected estimates for the general population were lower: 9.7% (California), 15.3% (Midwest), 18.2% (Florida), and 27.0% (Louisiana). The demographic patterns also varied by geography. An inverted U-shaped age pattern was found, with the highest prevalence among ages 25-34 years in Florida (n=88, 80.0%,) and Louisiana (n=54, 79.4%; P<.05). Females were more hesitant than males in the Midwest (n= 110, 36.4% vs n= 48, 23.5%), Florida (n=458, 71.6% vs n=195, 59.3%), and Louisiana (n= 425, 66.5% vs. n=172, 46.5%; P<.05). Racial/ethnic differences were found in California, with the highest prevalence among non-Hispanic Black participants (n=86, 45.5%), and in Florida, with the highest among Hispanic (n=567, 69.3%) participants (P<.05), but not in the Midwest and Louisiana. The main effect model confirmed the U-shaped association with age: strongest association with age 25-34 years (OR 2.29, 95% CI 1.74-3.01). Statistical interactions of gender and race/ethnicity with the region were significant, following the pattern found by the crude analysis. Compared to males in California, the associations with the female gender were strongest in Florida (OR=7.88, 95% CI 5.96-10.41) and Louisiana (OR=6.09, 95% CI 4.55-8.14). Compared to non-Hispanic White participants in California, the strongest associations were found with being Hispanic in Florida (OR=11.18, 95% CI 7.01-17.85) and Black in Louisiana (OR=8.94, 95% CI 5.53-14.47). However, the strongest race/ethnicity variability was observed within California and Florida: the ORs varied 4.6- and 2-fold between racial/ethnic groups in these regions, respectively. These findings highlight the role of local contextual factors in driving vaccine hesitancy and its demographic patterns.
登录
查看更多内容
DOI：
10.15585/mmwr.mm6915e3
发表时间：
2020-04-17
期刊：
MMWR. Morbidity and mortality weekly report
影响因子：
--
作者：
Garg S;Kim L;Whitaker M;O'Halloran A;Cummings C;Holstein R;Prill M;Chai SJ;Kirley PD;Alden NB;Kawasaki B;Yousey-Hindes K;Niccolai L;Anderson EJ;Openo KP;Weigel A;Monroe ML;Ryan P;Henderson J;Kim S;Como-Sabetti K;Lynfield R;Sosin D;Torres S;Muse A;Bennett NM;Billing L;Sutton M;West N;Schaffner W;Talbot HK;Aquino C;George A;Budd A;Brammer L;Langley G;Hall AJ;Fry A
通讯作者：
Fry A
影响因子：
13.8
作者：
Padamsee TJ;Bond RM;Dixon GN;Hovick SR;Na K;Nisbet EC;Wegener DT;Garrett RK
通讯作者：
Garrett RK
影响因子：
3.7
作者：
Doherty IA;Pilkington W;Brown L;Billings V;Hoffler U;Paulin L;Kimbro KS;Baker B;Zhang T;Locklear T;Robinson S;Kumar D
通讯作者：
Kumar D
DOI：
10.1007/s40615-020-00833-4
发表时间：
2020-09-01
影响因子：
3.9
作者：
Abedi, Vida;Olulana, Oluwaseyi;Zand, Ramin
通讯作者：
Zand, Ramin
影响因子：
16.6
作者：
Nguyen LH;Joshi AD;Drew DA;Merino J;Ma W;Lo CH;Kwon S;Wang K;Graham MS;Polidori L;Menni C;Sudre CH;Anyane-Yeboa A;Astley CM;Warner ET;Hu CY;Selvachandran S;Davies R;Nash D;Franks PW;Wolf J;Ourselin S;Steves CJ;Spector TD;Chan AT;COPE Consortium
通讯作者：
COPE Consortium