A modeling study suggests that the majority of COVID-19 adult hospitals nationwide are due to at least one of four pre-existing conditions: obesity, hip-strain, diabetes. 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 Turald University’s Gerald J. and Dorothy R. Friedman School of Nutritional Science and Policy, used mathematical simulation to estimate the number and proportion of COVID-19 national hospitals could be banned if Americans did not. suffers from four major cardiometabolic conditions. All conditions have been strongly associated in other studies with an increased risk of adverse outcomes with COVID-19 infection.
“While newly authorized COVID-19 vaccines will ultimately reduce infections, we have a long way to go to get to that point. Our findings call for interventions to find out the improving cardiometabolic health will reduce hospitalization, morbidity, and health care sequences from COVID-19, ”said Dariush Mozaffarian, lead author and dean of the Friedman School. “We know that changes in the quality of a diet alone, even without weight loss, quickly improve metabolic health within just six to eight weeks. It is essential to test lifestyles like this. for the reduction of COVID-19 infections, both for this and future pandemics. “
The researchers estimated that among the total 906,849 COVID-19 hospitals that occurred in U.S. adults as of November 18, 2020:
- 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) were due to heart failure.
Epidemiologically, the appropriate proportion represents the percentage of COVID-19 hospitals that could be excluded without the four conditions. In other words, the study found that the people may still have been infected but may not have had a hard enough clinical course to go to the hospital. When numbers for the four conditions were combined, the model suggests that 64% (575,419) of COVID-19 hospitals may have been excluded. A 10% reduction in the national frequency of all conditions, when combined, could prevent approximately 11% of all COVID-19 hospitalizations, according to the model.
The four scenarios were selected based on other published research from around the world showing that each is an independent predictor of adverse outcomes, including hospitalization, among people with COVID-19. The specific risk estimates for each condition from a published multivariate model included 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 hospitals nationally; distributions of these hospitals by age, sex, and ethnicity; and the estimated distribution of the underlying comorbidities among adults with COVID-19 disease. They then estimated the proportions and numbers of COVID-19 cases that became severe enough to require hospitalization as a result of the presence of one or more of the conditions.
“Medical providers should educate patients who may be at risk for severe COVID-19 and consider promoting lifestyle protective measures, such as improved dietary quality and physical activity, to promote cardiometabolic health. It is also important that providers are aware of the health inequalities. People with these conditions often struggle, “said first author Meghan O’Hearn, a doctoral candidate at the Friedman School.
The model estimated that differences in COVID-19 hospitals were due to age and race / ethnicity as a result of the four conditions. For example, it was estimated that approximately 8% of COVID-19 hospitals among adults under 50 were due to diabetes, compared to approximately 29% of COVID-19 hospitals among those of age 65 and older. In contrast, obesity had an equally devastating effect on COVID-19 hospitals across age groups.
At any age, COVID-19-capable hospitals had all four conditions higher in Black adults than in white adults and generally higher for diabetes and obesity in Hispanic adults than in adults. bright. For example, among adults aged 65 and over, diabetes was estimated to cause approximately 25% of COVID-19 hospitals among white adults, versus approximately 32% among Black adults, and approximately on 34% among Hispanic adults.
When the four conditions were assessed together, the proportion of appropriate hospitals was highest in Black adults of all ages, followed by Hispanics. For example, among young adults aged 18–49 years, the four conditions together were estimated to cause approximately 39% of COVID-19 hospitalizations among white adults, as opposed to 50% among Black adults. .
“National data show that Black and Hispanic Americans are suffering the worst outcomes from COVID-19. Our findings support the need to prioritize vaccine circulation, good nutrition, and measures another prevention for people with cardiometabolic disorders, especially among the groups most affected by health differences, “Mozaffarian said. “Policies aimed at reducing the incidence of these four cardiometabolic conditions among Black and Hispanic Americans must be part of any state or national policy debate aimed at reducing health differences from COVID-19. “
Data
The model used existing data from a number of sources. Hospitals by age, gender, ethnicity and ethnicity came from the CDC’s COVID-NET system, which monitors COVID-19 hospitals in 14 participating states. Data on COVID-19 national hospitals came from the COVID Administration Project, a voluntary organization that collects data from all 50 states on the COVID-19 revolution in the U.S. These two datasets were combined to estimate COVID-19 hospitals nationally by population. subgroups. The data on the national distribution of the four conditions came from the most recent Health and Nutrition Examination Survey (NHANES), a national representative study in which participants receive medical and laboratory tests. Data on the association between COVID-19 hospitals and each of the four conditions came from a study of factors associated with hospital admission among people with COVID-19 in New York City.
Restrictions
The authors note that equivalence does not equate to cause, and that the modeling approach does not confirm reductions in the four COVID-19 hospital settings. Hypotheses were based on limited available data on the prevalence of cardiometabolic conditions among US COVID-19 infected adults, the demographic breakdown of COVID-19 hospitals nationally, and the strongest evidence to date on links between cardiometabolic conditions and adverse COVID outcomes -19.
Authors
Additional authors of the study are Frederick Cudhea and Renata Micha at the Friedman School, and Junxiu Liu, a graduate pupil at the Friedman School at the time of the study, is now an assistant professor at the Icahn School of Medicine at Mount Sinai.