Evidence map›Paper›PMID 33397470›Full record

ArticleInfectious diseases of poverty2021

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

Ting Tian, Jingwen Zhang, Liyuan Hu, Yukang Jiang, Congyuan Duan, Zhongfei Li, Xueqin Wang, Heping Zhang

Abstract read
In one paragraph

Article in Infectious diseases of poverty, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  13. Spatial Risk Factors for Pillar 1 COVID-19 Excess Cases and Mortality in Rural Eastern England, UK.Risk analysis : an official publication of the Society for Risk Analysis · 2022
    Article
  14. COVID-19 and Agricultural Workers: A Descriptive Study.Journal of immigrant and minority health · 2022
    Article
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  16. Article
  17. Long-term exposure to PMEnvironment international · 2022
    Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ting TianSchool of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Jingwen ZhangSchool of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Liyuan HuSchool of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Yukang JiangSchool of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Congyuan DuanSchool of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Zhongfei LiSchool of Management, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Xueqin WangSchool of Statistics, Capital University of Economics and Business, 121 Zhangjialukou, Huaxiang Fengtai District, Beijing, 100070, China. hawkingwang@gmail.com.
Heping ZhangSchool of Public Health, Yale University, 60 College Street, New Haven, CT, 06520-8034, USA. heping.zhang@yale.edu.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

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.

Indexed as

AgedCluster AnalysisCOVID-19FemaleHumansMaleMortalityPandemicsPrevalencePublic HealthRace FactorsRisk FactorsSARS-CoV-2Sex FactorsSocioeconomic FactorsStatistics, NonparametricAdverse health factorsCounty-level confirmed and deathsPhysical environmentRace/ethnicitySegregation index

Identifiers

PMID33397470
PMCPMC7780082

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.