Affiliation:
1. Stanford University School of Medicine Stanford CA
2. Division of Cardiovascular Medicine and the Cardiovascular Institute Stanford University School of Medicine Stanford CA
3. Department of Medicine Stanford University School of Medicine Stanford CA
4. Department of General Internal Medicine Bern University HospitalUniversity of Bern Switzerland
5. Department of Pediatrics Stanford University School of Medicine Stanford CA
6. Department of Management Science and Engineering Stanford University School of Engineering Stanford CA
Abstract
Background
Persistent racial/ethnic disparities in cardiovascular disease (CVD) mortality are partially explained by healthcare access and socioeconomic, demographic, and behavioral factors. Little is known about the association between race/ethnicity‐specific CVD mortality and county‐level factors.
Methods and Results
Using 2017 county‐level data, we studied the association between race/ethnicity‐specific CVD age‐adjusted mortality rate (AAMR) and county‐level factors (demographics, census region, socioeconomics, CVD risk factors, and healthcare access). Univariate and multivariable linear regressions were used to estimate the association between these factors;
R
2
values were used to assess the factors that accounted for the greatest variation in CVD AAMR by race/ethnicity (non‐Hispanic White, non‐Hispanic Black, and Hispanic/Latinx individuals). There were 659 740 CVD deaths among non‐Hispanic White individuals in 2698 counties; 100 475 deaths among non‐Hispanic Black individuals in 717 counties; and 49 493 deaths among Hispanic/Latinx individuals across 267 counties. Non‐Hispanic Black individuals had the highest mean CVD AAMR (320.04 deaths per 100 000 individuals), whereas Hispanic/Latinx individuals had the lowest (168.42 deaths per 100 000 individuals). The highest CVD AAMRs across all racial/ethnic groups were observed in the South. In unadjusted analyses, the greatest variation (
R
2
) in CVD AAMR was explained by physical inactivity for non‐Hispanic White individuals (32.3%), median household income for non‐Hispanic Black individuals (24.7%), and population size for Hispanic/Latinx individuals (28.4%). In multivariable regressions using county‐level factor categories, the greatest variation in CVD AAMR was explained by CVD risk factors for non‐Hispanic White individuals (35.3%), socioeconomic factors for non‐Hispanic Black (25.8%), and demographic factors for Hispanic/Latinx individuals (34.9%).
Conclusions
The associations between race/ethnicity‐specific age‐adjusted CVD mortality and county‐level factors differ significantly. Interventions to reduce disparities may benefit from being designed accordingly.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Cardiology and Cardiovascular Medicine
Cited by
7 articles.
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