Journal of the American Heart Association · 2025
Disparities in Geographic Access to Cardiac Rehabilitation Among Socially Vulnerable Communities.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Chen Edward W, Wu Wen-Chih, Han Ling, Gandhi Parul U, Bastian Lori A, Brandt Cynthia A, Mattocks Kristin M, Oen-Hsiao Joyce, Varghese Merilyn S
Аннотация
BACKGROUND: There is a dearth of research examining geographic disparities in access to cardiac rehabilitation (CR). We evaluated whether disparities in geographic access to CR exist among socially vulnerable communities, using the Social Vulnerability Index (SVI).
METHODS: Among 3113 US counties, we investigated relationships between SVI and number of hospitals with CR per 100 000 adults, modeled with SVI as a linear variable, and SVI and distance to the nearest county with CR facilities, modeled using spline terms for SVI. We used multivariable zero-inflated negative binomial regression modeling adjusted for county population, CR eligibility, percentage without health insurance, metropolitan status, and availability of existing health care infrastructure. We explored whether these relationships changed in the context of rurality.
RESULTS: After adjustment, as SVI increased by 1 percentile, number of hospitals with CR per 100 000 adults decreased by 1.2% (P<0.001). For distance to CR, individual spline terms were not significant in our adjusted model; however, the overall predicted distance to CR increased as SVI increased. When stratified by metropolitan status, these relationships not only persisted but also intensified in rural counties. As SVI increased by 1 percentile, the odds of a county containing a CR facility decreased by 0.9% in metropolitan counties (P=0.002) versus 2.2% in rural counties (P<0.001).
CONCLUSION: More socially vulnerable communities experienced worse geographic access to CR facilities. This access disparity intensified in rural communities. Our findings call for reducing barriers to CR access among socially vulnerable and rural communities, potentially through virtual or hybrid models of CR.
METHODS: Among 3113 US counties, we investigated relationships between SVI and number of hospitals with CR per 100 000 adults, modeled with SVI as a linear variable, and SVI and distance to the nearest county with CR facilities, modeled using spline terms for SVI. We used multivariable zero-inflated negative binomial regression modeling adjusted for county population, CR eligibility, percentage without health insurance, metropolitan status, and availability of existing health care infrastructure. We explored whether these relationships changed in the context of rurality.
RESULTS: After adjustment, as SVI increased by 1 percentile, number of hospitals with CR per 100 000 adults decreased by 1.2% (P<0.001). For distance to CR, individual spline terms were not significant in our adjusted model; however, the overall predicted distance to CR increased as SVI increased. When stratified by metropolitan status, these relationships not only persisted but also intensified in rural counties. As SVI increased by 1 percentile, the odds of a county containing a CR facility decreased by 0.9% in metropolitan counties (P=0.002) versus 2.2% in rural counties (P<0.001).
CONCLUSION: More socially vulnerable communities experienced worse geographic access to CR facilities. This access disparity intensified in rural communities. Our findings call for reducing barriers to CR access among socially vulnerable and rural communities, potentially through virtual or hybrid models of CR.