DOI: 10.1161/circ.148.suppl_1.12414 ISSN: 0009-7322

Abstract 12414: Aggregated Data Masks Racial and Ethnic Disparities in Cardiometabolic Disease Prevalence

Alain Koyama, Kai Bullard, Yoshihisa Miyamoto, Ryan Saelee, Sandra Jackson, Meda Pavkov, Fang Xu, Stephen Onufrak
  • Physiology (medical)
  • Cardiology and Cardiovascular Medicine

Background: Although data disaggregation can unmask important differences in health disparities among subgroups, prevalence of cardiometabolic diseases among disaggregated racial and ethnical subgroups in the United States is inadequately characterized.

Research Question: How does prevalence of diagnosed cardiometabolic diseases among US adults vary by racial and ethnic subgroups?

Methods: A total of 3,970,904 US adults aged ≥18 years were identified from the Behavioral Risk Factor Surveillance System, 2013-2021. Prevalence of each cardiometabolic disease (diabetes, myocardial infarction, angina or coronary heart disease [CHD], stroke) was based on self-reported diagnosis by a healthcare professional, adjusting for age, sex, and survey year.

Results: Adjusted prevalence of diabetes was 10.9% (95% confidence interval: 10.8-11.0%) in the total population, ranging from 9.1% (9.0-9.1%) among Non-Hispanic (NH) White adults, to approximately 16% among NH American Indian/Alaska Native, NH Black, and NH Pacific Islander adults. Diabetes prevalence was 11.5% (11.0-12.0%) for the aggregated NH Asian category, but ranged from 6.3% (4.7-8.4%) in the Vietnamese subgroup to 15.2% (13.8-16.8%) in the Filipino subgroup. Additional adjusted overall prevalences were myocardial infarction 4.3% (4.3-4.3%), angina or CHD 4.1% (4.1-4.2%), and stroke 3.2% (3.1-3.2%). Within the Hispanic subgroups, reported prevalence of angina or CHD ranged from 3.1% (2.3-4.0%) to 6.3% (6.0-6.6%) among Cuban and Puerto Rican subgroups, respectively.

Conclusion: Prevalence of diagnosed cardiometabolic diseases varied considerably among racial and ethnic subgroups, highlighting the utility of data disaggregation in accurate characterization of health disparities within specific racial and ethnic populations. Such data can be used to better tailor disease prevention programs to disproportionately-affected subpopulations.

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