Census Tract Patterns and Contextual Social Determinants of Health Associated With COVID-19 in a Hispanic Population From South Texas: A Spatiotemporal Perspective (vol 7, e29205, 2021)

被引:1
作者
Bauer, Cici [1 ]
Zhang, Kehe [1 ]
Lee, Miryoung [2 ]
Fisher-Hoch, Susan [2 ]
Guajardo, Esmeralda [3 ]
McCormick, Joseph [2 ]
de la Cerda, Isela [2 ]
Fernandez, Maria E. [4 ]
Reininger, Belinda [5 ]
Bauer, Cici [1 ]
机构
[1] Univ Texas Hlth Sci Ctr Houston, Sch Publ Hlth, Dept Biostat & Data Sci, 1200 Pressler St, Houston, TX 77030 USA
[2] Univ Texas Hlth Sci Ctr Houston, Sch Publ Hlth, Dept Epidemiol Human Genet & Environm Sci, Brownsville, TX USA
[3] Cameron Cty Publ Hlth, San Benito, TX USA
[4] Univ Texas Hlth Sci Ctr Houston, Sch Publ Hlth, Dept Hlth Promot & Behav Sci, Houston, TX 77030 USA
[5] Univ Texas Hlth Sci Ctr Houston, Sch Publ Hlth, Dept Hlth Promot & Behav Sci, Brownsville, TX USA
基金
美国国家卫生研究院;
关键词
Bayesian; COVID-19; Health inequity; Social determinants of health; Spatial pattern; Underserved population;
D O I
10.2196/32870
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Previous studies have shown that various social determinants of health (SDOH) may have contributed to the disparities in COVID-19 incidence and mortality among minorities and underserved populations at the county or zip code level. Objective: This analysis was carried out at a granular spatial resolution of census tracts to explore the spatial patterns and contextual SDOH associated with COVID-19 incidence from a Hispanic population mostly consisting of a Mexican American population living in Cameron County, Texas on the border of the United States and Mexico. We performed age-stratified analysis to identify different contributing SDOH and quantify their effects by age groups. Methods: We included all reported COVID-19–positive cases confirmed by reverse transcription–polymerase chain reaction testing between March 18 (first case reported) and December 16, 2020, in Cameron County, Texas. Confirmed COVID-19 cases were aggregated to weekly counts by census tracts. We adopted a Bayesian spatiotemporal negative binomial model to investigate the COVID-19 incidence rate in relation to census tract demographics and SDOH obtained from the American Community Survey. Moreover, we investigated the impact of local mitigation policy on COVID-19 by creating the binary variable “shelter-in-place.” The analysis was performed on all COVID-19–confirmed cases and age-stratified subgroups. Results: Our analysis revealed that the relative incidence risk (RR) of COVID-19 was higher among census tracts with a higher percentage of single-parent households (RR=1.016, 95% posterior credible intervals [CIs] 1.005, 1.027) and a higher percentage of the population with limited English proficiency (RR=1.015, 95% CI 1.003, 1.028). Lower RR was associated with lower income (RR=0.972, 95% CI 0.953, 0.993) and the percentage of the population younger than 18 years (RR=0.976, 95% CI 0.959, 0.993). The most significant association was related to the “shelter-in-place” variable, where the incidence risk of COVID-19 was reduced by over 50%, comparing the time periods when the policy was present versus absent (RR=0.506, 95% CI 0.454, 0.563). Moreover, age-stratified analyses identified different significant contributing factors and a varying magnitude of the “shelter-in-place” effect. Conclusions: In our study, SDOH including social environment and local emergency measures were identified in relation to COVID-19 incidence risk at the census tract level in a highly disadvantaged population with limited health care access and a high prevalence of chronic conditions. Results from our analysis provide key knowledge to design efficient testing strategies and assist local public health departments in COVID-19 control, mitigation, and implementation of vaccine strategies. ©Cici Bauer, Kehe Zhang, Miryoung Lee, Susan Fisher-Hoch, Esmeralda Guajardo, Isela de la Cerda, Isela de la Cerda, Maria E Fernandez, Belinda Reininger.
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Bauer C, 2021, JMIR PUBLIC HLTH SUR, V7, DOI 10.2196/29205