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

被引:32
作者
Tian, Ting [1 ]
Zhang, Jingwen [1 ]
Hu, Liyuan [1 ]
Jiang, Yukang [1 ]
Duan, Congyuan [1 ]
Li, Zhongfei [5 ]
Wang, Xueqin [2 ,3 ]
Zhang, Heping [4 ]
机构
[1] Sun Yat Sen Univ, Sch Math, 135 Xingang Xi Rd, Guangzhou 510275, Guangdong, Peoples R China
[2] Capital Univ Econ & Business, Sch Stat, 121 Zhangjialukou, Beijing 100070, Peoples R China
[3] Univ Sci & Technol China, Sch Management, 96 Jinzhai Rd, Hefei 230026, Anhui, Peoples R China
[4] Yale Univ, Sch Publ Hlth, 60 Coll St, New Haven, CT 06520 USA
[5] Sun Yat Sen Univ, Sch Management, 135 Xingang Xi Rd, Guangzhou 510275, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Adverse health factors; County-level confirmed and deaths; Race; ethnicity; Segregation index; Physical environment; SLEEP; TIME;
D O I
10.1186/s40249-020-00786-0
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
BackgroundThe 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.MethodsUsing 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.ResultsA 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.ConclusionsThe 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
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页数:8
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