A modeling study suggests a majority of adult COVID-19 hospitalizations nationwide are attributable to at least one of four pre-existing conditions: obesity, hypertension, diabetes, and heart failure, in that order.
The study, published today in the Journal of the American Heart Association (JAHA) and led by researchers at the Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy at Tufts University, used a mathematical simulation to estimate the number and proportion of national COVID-19 hospitalizations that could have been prevented if Americans did not suffer from four major cardiometabolic conditions. Each condition has been strongly linked in other studies to increased risk of poor outcomes with COVID-19 infection.
“While newly authorized COVID-19 vaccines will eventually reduce infections, we have a long way to go to get to that point. Our findings call for interventions to determine whether improving cardiometabolic health will reduce hospitalizations, morbidity, and health care strains from COVID-19,” said Dariush Mozaffarian, lead author and dean of the Friedman School. “We know that changes in diet quality alone, even without weight loss, rapidly improve metabolic health within just six to eight weeks. It’s crucial to test such lifestyle approaches for reducing severe COVID-19 infections, both for this pandemic and future pandemics likely to come.”
The researchers estimated that, among the 906,849 total COVID-19 hospitalizations that had occurred in U.S. adults as of November 18, 2020:
- 30% (274,322) were attributable to obesity;
- 26% (237,738) were attributable to hypertension;
- 21% (185,678) were attributable to diabetes; and
- 12% (106,139) were attributable to heart failure.
The four conditions were chosen based on other published research from around the world showing each is an independent predictor of severe outcomes, including hospitalization, among people infected with COVID-19. The specific risk estimates for each condition were from a published multivariable model involving more than 5,000 COVID-19 patients diagnosed in New York City earlier in the pandemic. The researchers used other national data to model the number of COVID-19 hospitalizations nationally; the distributions of these hospitalizations by age, sex, and race; and the estimated distribution of the underlying comorbidities among adults infected with COVID-19. They then estimated the proportions and numbers of COVID-19 cases that became severe enough to require hospitalization owing to the presence of one or more of the conditions.
The authors note that association does not equal causation, and the modeling approach does not prove reductions in the four conditions will reduce COVID-19 hospitalizations. Assumptions were based on limited available data on the cardiometabolic condition distribution among COVID-19 infected U.S. adults, the demographic breakdown of COVID-19 hospitalizations nationally, and the strongest evidence to date on links between cardiometabolic conditions and poor COVID-19 outcomes.
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