Study suggests that COVID-19 hospitalizations could have been prevented without four common, existing conditions. Credit: Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy at Tufts University
The model indicates a higher risk based on race and age, and provides insights to reduce the impact of diseases.
A modeling study indicates a majority of adults COVID-19 hospitalizations nationwide can be attributed to at least one of four existing conditions: obesity, high blood pressure, diabetes, and heart failure, in that order.
The study, published today (February 25, 2021) in the Journal of the American Heart Association (JAHA) and led by researchers at the Gerald J. and Dorothy R. Friedman School of Nutritional Science and Policy at Tufts University, used a mathematical simulation to estimate the number and proportion of national COVID-19 hospitalizations that could be prevented if Americans do not. suffers from four major cardiometabolic conditions. Each condition has been strongly linked in other studies to an increased risk of poor outcomes with COVID-19 infection.
‘While newly authorized COVID-19 vaccines will ultimately reduce infections, we have a long way to go. Our findings call for interventions to determine whether improving cardiometabolic health will reduce COVID-19 hospitalizations, diseases, and healthcare types, ”said Dariush Mozaffarian, principal and dean of Friedman School. ‘We know that changes in dietary quality alone, even without weight loss, rapidly improve metabolic health in just six to eight weeks. It is essential to test such lifestyle approaches to reduce serious COVID-19 infections, both for this pandemic and future pandemics that are likely to come. ”
According to the researchers, among the 906,849 total COVID-19 hospitalizations that occurred on November 18, 2020 in U.S. adults:
- 30% (274 322) were due to obesity;
- 26% (237,738) were due to hypertension;
- 21% (185,678) were due to diabetes; and
- 12% (106 139) can be attributed to heart failure.
In epidemiological terms, the attributable ratio represents the percentage of COVID-19 hospitalizations that could have been prevented in the absence of the four conditions. In other words, the study found that individuals may still be infected, but that they may not have had a serious clinical course to require hospitalization. When the numbers for the four conditions were added together, the model indicates that 64% (575,419) of the COVID-19 hospitalizations could have been prevented. A 10% decrease in the national incidence of each condition, when combined, can occur according to the model approximately 11% of all COVID-19 hospitalizations.
The four conditions were selected based on other published research from around the world showing that each is an independent predictor of serious outcomes, including hospitalization, among people infected with COVID-19. The specific risk estimates for each condition were from a published multivariate model in which more than 5,000 COVID-19 patients were diagnosed earlier in the New York City pandemic. The researchers used other national data to model the number of COVID-19 hospitalizations nationally; the distribution of these hospitalizations according to age, sex and race; and the estimated distribution of the underlying comorbidities among adults infected with COVID-19. They then estimated the ratios and numbers of COVID-19 cases that became serious enough to require hospitalization due to the presence of one or more of the conditions.
‘Medical providers should educate patients who may be at serious risk for COVID-19 and should consider promoting preventative lifestyle measures, such as improved dietary quality and physical activity, to improve overall cardiometabolic health. It is also important that providers be aware of the health differences that people with these conditions often experience, ‘says first author Meghan O’Hearn, a doctoral candidate at the Friedman School.
The model estimated that age and race / ethnicity resulted in inequalities in COVID-19 hospitalizations due to the four conditions. For example, approximately 8% of COVID-19 hospitalizations among adults younger than 50 years are estimated to be due to diabetes, compared with approximately 29% of COVID-19 hospitalizations under age 65 and older. In contrast, obesity has an equally detrimental impact on COVID-19 hospitalizations in different age groups.
At any age, COVID-19 hospitalizations attributable to all four conditions were higher in black adults than in white adults, and generally higher for diabetes and obesity in Hispanic adults than in white adults. For example, among adults 65 years and older, it is estimated that diabetes causes about 25% of COVID-19 hospitalizations among white adults, compared to about 32% among black adults and about 34% among Hispanic adults.
When the four conditions were combined, the percentage of attributable hospitalizations was highest in black adults of all ages, followed by Spanish. For example, among young adults aged 18-49 years, it is estimated that the four conditions together cause about 39% of COVID-19 hospitalizations among white adults, compared to 50% among black adults.
‘National data shows that black and Hispanic Americans have the worst results from COVID-19. Our findings support the need to prioritize the distribution of vaccines, good nutrition and other preventative measures for people with cardiometabolic conditions, especially among groups most affected by health inequalities, “said Mozaffarian.” Policies aimed at reducing the incidence of these four cardiometabolic conditions among black and Hispanic Americans should be part of any state or national policy discussion aimed at reducing health inequalities in COVID-19. “
Data
The model used existing data from different sources. Hospitalizations by age, gender, race, and ethnicity come from the CDC’s COVID-NET system, which tracks COVID-19 hospitalizations in 14 participating states. Data on national COVID-19 hospitalizations comes from The COVID Tracking Project, a voluntary organization that collects data from all 50 states on the COVID-19 outbreak in the US. These two data sets were combined to estimate COVID-19 hospitalizations at the national level by population. subgroups. The data on the national distribution of the four conditions come from the most recent National Health and Nutrition Examination Survey (NHANES), a nationally representative study in which participants undergo medical examinations and laboratory tests. Data on the association between COVID-19 hospitalizations and each of the four conditions came from a study on factors related to hospitalization among people with COVID-19 in New York City.
Restrictions
The authors note that association does not equate to causality, and that the modeling approach does not prove that reduction of the four conditions would reduce COVID-19 hospitalizations. Assumptions were based on limited available data on the distribution of cardiometabolic conditions among COVID-19-infected American adults, the demographic breakdown of COVID-19 hospitalizations nationally, and the strongest evidence to date on the association between cardiometabolic conditions and poor COVID- 19 outcomes.
Authors
Additional authors on the study are Frederick Cudhea and Renata Micha at Friedman School, and Junxiu Liu, a postdoctoral fellow at Friedman School at the time of the study, now assistant professor at Icahn School of Medicine at Mount Sinai .
Funding
The work was supported by two grants from the National Institute of Health’s National Heart, Lung, and Blood Institute (R01HL130735 and R01HL115189). The content is the sole responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. See the study for conflicts of interest.
Quotation
O’Hearn, M., Liu, J., Cudhea, F., Micha, R., & Mozaffarian, D. (2021). COVID-19 Hospitalizations Attributed to Cardiometabolic Conditions in the United States: A Comparative Risk Assessment Analysis. Journal of the American Heart Association.