Covid-19: risk factors for severe disease and death

Jordan, Rachel; Adab, Peymané; Cheng, Kar Keung

doi:10.1136/bmj.m1198

Cited by 1,529 publications

(1,479 citation statements)

References 14 publications

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“…Recent work has primarily focused on patient demographics, underlying health comorbidities, social disparities in healthcare access and quality, and environmental variables such as pollution to identify potential risk factors and vulnerable populations. [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] However, while these previous studies have examined the effects of these domains on COVID-19 spread independently, some do not control for the potentially confounding interactions between variables. In this study, we sought to investigate COVID-19 prevalence and mortality in all U.S. counties through a more comprehensive framework that accounts for effects of county-level macroeconomic, demographic, environmental, health status, and healthcare access variables.…”

Section: Discussionmentioning

confidence: 99%

“…Recent studies have pointed to the fact that, compared to the general population of the United States, Black Americans have been shown to suffer from increased rates of chronic medical comorbidities such as cardiovascular disease, diabetes mellitus, hypertension, obesity, and chronic respiratory disease, all of which have been shown to convey increased risk of SARS-CoV-2 infection and lead to worse outcomes. [18][19][20] Studies have also cited inequities in structural variables, which manifest in the disproportionate number of Black Americans who suffer from poverty, reside in densely packed areas with more environmental hazards, have decreased access to healthy food sources, and lack healthcare coverage and access. 31 In our comprehensive multivariate analysis, we were able to control for these potentially confounding variables; however, after doing so, our data continue to demonstrate a disproportionate number of COVID-19 cases and deaths in counties with large Black populations in the United States.…”

Section: Impact Of Racementioning

confidence: 99%

“…4,5 Previous studies have examined the effects of various risk factors on spread of COVID-19 including patient demographics, 6,7 social determinants of health, 8 environmental variables, [9][10][11][12][13][14][15] housing, 16,17 and underlying health conditions. [18][19][20] Identifying risk factors allows public health officials to determine populations at greater risk and development targeted public health interventions. Ultimately, this may help "flatten the curve" of cases and avoid overwhelming the health care system.…”

Section: Introductionmentioning

confidence: 99%

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Multivariate Analysis of Factors Affecting COVID-19 Case and Death Rate in U.S. Counties: The Significant Effects of Black Race and Temperature

Hannah

Durbin

et al. 2020

Preprint

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Objectives : Coronavirus disease-19 has spread rapidly around the world, and many risk factors including patient demographics, social determinants of health, environmental variables, underlying health conditions, and adherence to social distancing have been hypothesized to affect case and death rates. However, little has been done to account for the potential confounding effects of these factors. Using a large multivariate analysis, this study illuminates modulators of COVID-19 incidence and mortality in U.S. counties while controlling for risk factors across multiple domains.Methods : Data on COVID-19 and various risk factors in all U.S. counties was collected from publicly available data sources through April 14, 2020. Counties with at least 50 COVID-19 cases were included in case analyses and those with at least 10 deaths were included in mortality models. The 661 counties meeting inclusion criteria for number of cases were grouped into quartiles and comparisons of risk factors were made using t-tests between the highest and lowest quartiles. Similar comparisons for 217 counties were made for above average and below average deaths/100,000. Adjusted linear and logistic regression analyses were performed to evaluate the independent effects of factors that significantly impacted cases and deaths.Results : Univariate analyses demonstrated numerous significant differences between cohorts for both cases and deaths. Risk factors associated with increased cases and/or deaths per 100,000 included increased GDP per capita, decreased social distancing, increased age, increased percent Black, decreased percent Hispanic, decreased percent Asian, decreased health, increased poverty, increased diabetes, increased coronary heart disease, increased physical inactivity, increased alcohol consumption, increased tobacco use, and decreased access to primary care. Multivariate regression analyses demonstrated Black race is a risk factor for worse COVID-19 outcome independent of comorbidities, poverty, access to health care, and other mitigating factors. Lower daily temperatures was also an independent risk factor in case load but not deaths.Conclusions : U.S. counties with a higher proportion of Black residents are associated with increased COVID-19 cases and deaths. However, the various suggested mechanisms, such as socioeconomic and healthcare predispositions, did not appear to drive the effect of race in our model. Counties with higher average daily temperatures are also associated with decreased COVID-19 cases but not deaths. Several theories are posited to explain these findings, including prevalence of vitamin D deficiency. Additional studies are needed to further understand these effects.

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Section: Discussionmentioning

confidence: 99%

Section: Impact Of Racementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multivariate Analysis of Factors Affecting COVID-19 Case and Death Rate in U.S. Counties: The Significant Effects of Black Race and Temperature

Hannah

Durbin

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Men in these groups appear to be at higher risk. Chronic obstructive pulmonary disease (COPD), cardiovascular disease and hypertension are strong predictors of admission to intensive care 23,24 …”

Section: Coronaviruses In Manmentioning

confidence: 99%

COVID‐19: a brief history and treatments in development

Chaplin¹

2020

Prescriber

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“…[1,2] These recommendations are mainly based on studies from the Wuhan region of China and Italy, and generally show that once infected, individuals with at least one of these prognostic factors are more likely to go on to generate severe disease and a resulting higher risk of mortality. [3][4][5][6][7][8] Governments around the world have, therefore, recommended that individuals with at least one of these factors self-isolate for prolonged periods of time to not only reduce the risk contracting severe COVID-19, but also prevent any sudden increase in demand for critical care in hospitals, which could overwhelm health systems. If the pandemic developed to affect a large proportion of the population, then critical care capacity could become saturated.…”

Section: Introductionmentioning

confidence: 99%

Burden and prevalence of prognostic factors for severe covid-19 disease in sweden

Gémes

Talbäck

Modig

et al. 2020

Preprint

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Objectives: Describe the burden and prevalence of prognostic factors of severe COVID-19 disease at national and county level in Sweden. Design: Cross sectional studySetting: Sweden Participants: 9,624,428 individuals living in Sweden on 31st December 2014 and alive on 1st January 2016 Main outcome measures: Burden and prevalence of prognostic factors for severe COVID-19 based on the guidelines from the World Health Organization and European Centre for Disease Prevention and Control, which are age 70 years and older, cardiovascular disease, cancer, chronic obstructive pulmonary disease, severe asthma, and diabetes. Prognostic factors were identified based on records for three years before 1 st January 2016 from the Swedish National Inpatient and Outpatient Specialist Care Register, Prescribed Drug Register, and Cancer Register.Results: 22.1% of the study population had at least one prognostic factor for severe COVID-19 (2,131,319 individuals), and 1.6% had at least three factors (154,746 individuals). The prevalence of underlying medical conditions in the whole study population ranged from 0.8% with chronic obstructive pulmonary disease (78,516 individuals) to 7.4% with cardiovascular disease (708,090 individuals), and the county specific prevalence of at least one prognostic factor ranged from 19.2% in Stockholm (416,988 individuals) to 25.9% in Kalmar (60,005 individuals). Conclusions:The prevalence of prognostic factors for severe COVID-19 disease will aid authorities in optimally planning healthcare resources during the ongoing pandemic. Results can also be applied to underlying assumptions of disease burden in modelling efforts to support COVID-19 planning. This information is crucial when deciding appropriate strategies to mitigate the pandemic and reduce both the direct mortality burden from the disease itself, and the indirect mortality burden from potentially overwhelmed health systems.

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Covid-19: risk factors for severe disease and death

Abstract: A long list is emerging from largely unadjusted analyses, with age near the top

Cited by 1,529 publications

References 14 publications

Multivariate Analysis of Factors Affecting COVID-19 Case and Death Rate in U.S. Counties: The Significant Effects of Black Race and Temperature

Multivariate Analysis of Factors Affecting COVID-19 Case and Death Rate in U.S. Counties: The Significant Effects of Black Race and Temperature

COVID‐19: a brief history and treatments in development

Burden and prevalence of prognostic factors for severe covid-19 disease in sweden

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