New Research Reveals Pandemic’s Unequal Impact On Childhood Obesity Rates

by | Jul 1, 2025

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A new nationally representative study published in Annals of Internal Medicine reveals that while overall childhood obesity rates in the United States remained largely unchanged during the COVID-19 pandemic, Black children and adolescents experienced a significant and disproportionate increase in obesity prevalence.

Researchers from Beth Israel Deaconess Medical Center and Harvard Medical School analyzed data from more than 17,500 U.S. children and adolescents aged 2–19 using the National Health and Nutrition Examination Survey (NHANES) covering 2011 through August 2023. The overall obesity rate rose modestly from 20.3% before the pandemic to 22.0% during 2021–2023.

However, the prevalence of obesity among Black youth surged from 22.4% before the pandemic to 35.8% during the pandemic period—a 10.4 percentage point increase not seen in other racial or ethnic groups. In comparison, rates among Mexican American youth rose slightly from 26.4% to 28.1%, Other Hispanic youth from 24.0% to 25.9%, and White youth from 17.4% to 18.2%. Among Asian youth, obesity rates declined slightly from 10.6% to 9.9%. None of these changes were statistically significant.

The study suggests that Black children and adolescents may have faced heightened exposure to risk factors such as reduced opportunities for physical activity, food insecurity, and increased stress linked to family economic hardship during the pandemic.

The authors emphasize the need for public health and policy interventions to prevent and manage rising childhood obesity, especially among minoritized populations disproportionately affected by the social and economic impacts of COVID-19.

The research was supported by the National Institutes of Health and the American Heart Association. The full study, titled “Obesity Prevalence Among Children and Adolescents in the United States, 2011 to 2023,” is available in Annals of Internal Medicine.

This report was prepared with the assistance of AI.

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