The study suggests that hospitalizations for COVID-19 could have been prevented without four pre-existing common conditions. Credit: Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy at Tufts University
The model suggests greater risk based on race and age, offers ideas for reducing the impact of the disease.
A modeling study suggests a majority of adults COVID-19 hospitalizations across the country are attributed to at least one of the four pre-existing conditions: obesity, hypertension, diabetes and heart failure, in that order.
The study, published today (February 25, 2021) in the American Heart Association Journal (JAHA) and led by researchers from the School of Nutrition Science and Policy Gerald J. and Dorothy R. Friedman at Tufts University, used a mathematical simulation to estimate the number and proportion of national hospitalizations for COVID-19 that could have been avoided if Americans do not suffer from four main cardiometabolic conditions. Each condition has been strongly associated in other studies with an increased risk of poor results with COVID-19 infection.
“Although the newly authorized COVID-19 vaccines will eventually reduce infections, we have a long way to go to reach that point. Our findings require interventions to determine whether improving cardiometabolic health will reduce COVID-19 hospitalizations, morbidity and health strains, ”said Dariush Mozaffarian, principal author and dean of the Friedman School. “We know that only changes in diet quality, even without weight loss, rapidly improve metabolic health in just six to eight weeks. It is crucial to test these lifestyle approaches to reduce serious COVID-19 infections, both for this pandemic and for future pandemics to come ”.
The researchers estimated that, among the total of 906,849 hospitalizations for COVID-19 that occurred in adults in the U.S. on November 18, 2020:
- 30% (274,322) were attributable to obesity;
- 26% (237,738) were attributable to hypertension;
- 21% (185,678) were attributed to diabetes; and
- 12% (106,139) were attributable to heart failure.
In epidemiological terms, the attributable proportion represents the percentage of admissions for COVID-19 that could have been avoided in the absence of the four conditions. In other words, the study found that individuals may still have been infected, but may not have had a clinical course severe enough to require hospitalization. When the numbers for the four conditions were combined, the model suggests that 64% (575,419) of COVID-19 hospitalizations may have been avoided. A 10% reduction in the national prevalence of each condition, when combined, could prevent about 11% of all admissions for COVID-19, according to the model.
The four conditions were chosen based on other research published worldwide, 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 involving more than 5,000 COVID-19 patients diagnosed in New York City at the beginning of the pandemic. The researchers used other national data to model the number of COVID-19 hospitalizations nationally; the distribution of these hospitalizations by age, sex and race; and the estimated distribution of underlying comorbidities among adults infected with COVID-19. Then, they estimated the proportions and number of COVID-19 cases that became severe enough to require hospitalization due to the presence of one or more of the conditions.
“Medical service providers should educate patients who may be at risk for severe COVID-19 and consider promoting preventive lifestyle measures, such as better quality of diet and physical activity, to improve overall cardiometabolic health. It is also important that health professionals are aware of the health disparities that people with these conditions often face, ”said first author Meghan O’Hearn, a doctoral candidate at Friedman School.
The model estimated that age and race / ethnicity resulted in disparities in hospitalizations for COVID-19 due to the four conditions. For example, about 8% of hospitalizations for COVID-19 among adults under 50 were estimated to be due to diabetes, compared with about 29% of hospitalizations for COVID-19 among those 65 and over. In contrast, obesity had an equally damaging impact on hospitalizations for COVID-19 in all age groups.
At any age, hospitalizations for COVID-19 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 aged 65 and over, diabetes has been estimated to cause about 25% of hospitalizations for COVID-19 among white adults, against about 32% among black adults and about 34% among Hispanic adults.
When the four conditions were considered combined, the proportion of attributable hospitalizations was highest in black adults of all ages, followed by Hispanics. For example, among young adults aged 18 to 49, the four conditions together were estimated to cause about 39% of hospitalizations for COVID-19 among white adults, against 50% among black adults.
“National data show that blacks and Hispanic Americans are suffering the worst results of COVID-19. Our results support the need to prioritize the distribution of vaccines, good nutrition and other preventive measures for people with cardiometabolic conditions, particularly among the groups most affected by health disparities, ”said Mozaffarian. “Policies aimed at reducing the prevalence of these four cardiometabolic conditions among blacks and Hispanic Americans should be part of any state or national policy discussion aimed at reducing COVID-19 health disparities.”
Data
The model used existing data from several sources. Hospitalizations by age, sex, race and ethnicity came from the CDC’s COVID-NET system, which tracks COVID-19 hospitalizations in 14 participating states. The data on national hospitalizations for COVID-19 came from The COVID Tracking Project, a voluntary organization that collects data from all 50 states on the COVID-19 outbreak in the USA. These two sets of data were combined to estimate COVID-19 hospitalizations nationwide by subgroup population. The data on the national distribution of the four conditions came from the most recent National Health and Nutrition Examination Survey (NHANES), a nationally representative study in which participants undergo medical and laboratory tests. The data on the association between COVID-19 hospitalizations and each of the four conditions came from a study on factors associated with hospitalization among people with COVID-19 in New York City.
Limitations
The authors note that the association is not equal to causality, and the modeling approach does not prove that reductions in the four conditions will reduce hospitalizations for COVID-19. The assumptions were based on the limited data available on the distribution of cardiometabolic condition among US adults infected with COVID-19, the demographic analysis of COVID-19 hospitalizations at the national level and the strongest evidence to date on the links between cardiometabolic conditions and poor outcomes of COVID-19.
Authors
Other authors of 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 an assistant professor at the Icahn School of Medicine on Mount Sinai.
Financing
This work was supported by two awards from the National Institutes 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 opinion of the National Institutes of Health. See the study for conflicts of interest.
Quote
O’Hearn, M., Liu, J., Cudhea, F., Micha, R., & Mozaffarian, D. (2021). COVID-19 hospitalizations attributable to cardiometabolic conditions in the USA: a comparative analysis of risk assessment. American Heart Association Journal.