Geographic variation in COVID-19 vulnerability by legal immigration status in California: a prepandemic cross-sectional study.
Geographic variation in COVID-19 vulnerability by legal immigration status in California: a prepandemic cross-sectional study.
复制标题
COVID-19中的地理差异是加利福尼亚州法律移民身份的脆弱性：一项横断面的横断面研究。
DOI：
10.1136/bmjopen-2021-054331
复制
发表时间：
2022-05-24
期刊：
影响因子：
2.9
通讯作者：
Aqua, Jasmine Ko
中科院分区：
文献类型：
--
作者：
Sohn, Heeju;Aqua, Jasmine Ko
通过合法移民身份和居住地量化加州居民的COVID-19脆弱性。横断面人口代表性调查数据的二次数据分析。加州健康访谈调查（2015-2020,n=128 528）限制版的所有成年受访者。按合法移民身份和人口普查地区划分的COVID-19相对社会脆弱性指数跨越六个领域：社会经济脆弱性；人口与残疾；少数民族地位和语言障碍；住宅密度高；流行病学风险;以及获得医疗服务的机会。居住在南加州城市地区（洛杉矶，奥兰治，圣地亚哥-帝国）的无证移民由于低社会经济地位，高语言障碍，高住房密度和低护理机会而具有特别高的脆弱性。圣华金谷是弱势移民群体和美国出生人口的家园，他们患严重COVID-19的人口和流行病学风险最高。缓解公共卫生危机的干预措施必须明确考虑移民在社会脆弱性和排他性的州和联邦安全网政策方面的双重劣势。
To quantify COVID-19 vulnerabilities for Californian residents by their legal immigration status and place of residence. Secondary data analysis of cross-sectional population-representative survey data. All adult respondents in the restricted version of the California Health Interview Survey (2015–2020, n=128 528). Relative Social Vulnerability Indices for COVID-19 by legal immigration status and census region across six domains: socioeconomic vulnerability; demography and disability; minority status and language barriers; high housing density; epidemiological risk; and access to care. Undocumented immigrants living in Southern California’s urban areas (Los Angeles, Orange, San Diego-Imperial) have exceptionally high vulnerabilities due to low socioeconomic status, high language barriers, high housing density and low access to care. San Joaquin Valley is home to vulnerable immigrant groups and a US-born population with the highest demographic and epidemiological risk for severe COVID-19. Interventions to mitigate public health crises must explicitly consider immigrants’ dual disadvantage from social vulnerability and exclusionary state and federal safety-net policies.
登录
查看更多内容
影响因子：
13.8
作者：
Casanova FO;Hamblett A;Brinkley-Rubinstein L;Nowotny KM
通讯作者：
Nowotny KM
影响因子：
13.8
作者：
Galletly CL;Lechuga J;Dickson-Gomez JB;Glasman LR;McAuliffe TL;Espinoza-Madrigal I
通讯作者：
Espinoza-Madrigal I
影响因子：
3.5
作者：
Hall, Matthew
通讯作者：
Hall, Matthew
影响因子：
5.4
作者：
Asad, Asad L.;Clair, Matthew
通讯作者：
Clair, Matthew
影响因子：
3.8
作者：
Clark, Eva;Fredricks, Karla;Weatherhead, Jill
通讯作者：
Weatherhead, Jill