Racial and Ethnic Disparities in Financial Barriers Among Overweight and Obese Adults Eligible for Semaglutide in the United States.
Daisy S MasseyYuntian LiuHarlan M KrumholzPublished in: Journal of the American Heart Association (2022)
Background Semaglutide holds the promise for weight loss and risk reduction. Less is known about racial and ethnic disparities in financial barriers among the semaglutide-eligible population. Methods and Results We conducted a cross-sectional analysis of adults aged 18 years or older using data from the National Health and Nutrition Examination Survey 2015 to 2020. We analyzed adults eligible for semaglutide based on Food and Drug Administration labeling and assessed financial barriers and social determinants of health among the eligible population overall and by race and ethnicity. A total of 13 711 adults were included in the final analysis. In 2015 to 2020, 51.1% (48.3%-53.2%) of US adults (≈43.3 million) met the Food and Drug Administration eligibility criteria for semaglutide. The percentage of adults eligible for semaglutide was highest among Black adults (56.6% [54.2%-59.1%]), followed by Hispanic adults (55.0% [52.8%-57.3%]). Among adults eligible for semaglutide, 11.9% (10.1%-13.6%) were uninsured, 13.3% (12.1%-14.5%) lacked a usual source of care, 33.6% (30.2%-36.9%) had low family income, and 38.9% (36.5%-41.3%) lacked higher education. Compared with White individuals, significantly larger proportions of Black and Hispanic individuals were uninsured, lacked a usual source of care, had low family income, or lacked higher education ( P <0.001 for all). Conclusions Many Americans who were eligible for semaglutide were likely to be unable to afford the medication. Among the eligible population, a larger proportion of Black and Hispanic adults had financial barriers than other subgroups.
Keyphrases
- healthcare
- affordable care act
- weight loss
- physical activity
- mental health
- quality improvement
- emergency department
- type diabetes
- bariatric surgery
- machine learning
- big data
- drug administration
- young adults
- pain management
- risk assessment
- climate change
- deep learning
- health insurance
- health information
- adverse drug
- middle aged
- breast cancer risk