Risk factors associated with mortality of COVID-19 in 3125 counties of the United States

Abstract Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in t...

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Main Authors: Ting Tian, Jingwen Zhang, Liyuan Hu, Yukang Jiang, Congyuan Duan, Zhongfei Li, Xueqin Wang, Heping Zhang
Format: Article
Language:English
Published: BMC 2021-01-01
Series:Infectious Diseases of Poverty
Subjects:
Online Access:https://doi.org/10.1186/s40249-020-00786-0
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spelling doaj-308f4ae279c5474bb287e1e6782a1ae42021-01-10T12:55:59ZengBMCInfectious Diseases of Poverty2049-99572021-01-011011810.1186/s40249-020-00786-0Risk factors associated with mortality of COVID-19 in 3125 counties of the United StatesTing Tian0Jingwen Zhang1Liyuan Hu2Yukang Jiang3Congyuan Duan4Zhongfei Li5Xueqin Wang6Heping Zhang7School of Mathematics, Sun Yat-Sen UniversitySchool of Mathematics, Sun Yat-Sen UniversitySchool of Mathematics, Sun Yat-Sen UniversitySchool of Mathematics, Sun Yat-Sen UniversitySchool of Mathematics, Sun Yat-Sen UniversitySchool of Management, Sun Yat-Sen UniversitySchool of Statistics, Capital University of Economics and BusinessSchool of Public Health, Yale UniversityAbstract Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. Methods Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal–Wallis tests were used in our statistical analysis. Results A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19. Graphic abstracthttps://doi.org/10.1186/s40249-020-00786-0Adverse health factorsCounty-level confirmed and deathsRace/ethnicitySegregation indexPhysical environment
collection DOAJ
language English
format Article
sources DOAJ
author Ting Tian
Jingwen Zhang
Liyuan Hu
Yukang Jiang
Congyuan Duan
Zhongfei Li
Xueqin Wang
Heping Zhang
spellingShingle Ting Tian
Jingwen Zhang
Liyuan Hu
Yukang Jiang
Congyuan Duan
Zhongfei Li
Xueqin Wang
Heping Zhang
Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
Infectious Diseases of Poverty
Adverse health factors
County-level confirmed and deaths
Race/ethnicity
Segregation index
Physical environment
author_facet Ting Tian
Jingwen Zhang
Liyuan Hu
Yukang Jiang
Congyuan Duan
Zhongfei Li
Xueqin Wang
Heping Zhang
author_sort Ting Tian
title Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
title_short Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
title_full Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
title_fullStr Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
title_full_unstemmed Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
title_sort risk factors associated with mortality of covid-19 in 3125 counties of the united states
publisher BMC
series Infectious Diseases of Poverty
issn 2049-9957
publishDate 2021-01-01
description Abstract Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. Methods Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal–Wallis tests were used in our statistical analysis. Results A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19. Graphic abstract
topic Adverse health factors
County-level confirmed and deaths
Race/ethnicity
Segregation index
Physical environment
url https://doi.org/10.1186/s40249-020-00786-0
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