ArticleBMC medicine2025
A social determinants-based county-level cardiovascular mortality index to identify high-risk counties in the USA.
Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Trends and widening inequities in cardiovascular-kidney-metabolic involvement in cardiovascular mortality: A national spatiotemporal analysis, 2014-2023.Clinical medicine (London, England) · 2026Article
- National trends and county-level geographic disparities in mortality from operationally defined cardiovascular-kidney-metabolic stages 4 and 4b in the United States.Frontiers in cardiovascular medicine · 2026Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSocial determinants of health (SDOH) contribute significantly to geographical variations in cardiovascular disease (CVD) mortality in the USA. We aimed to develop and evaluate a SDOH-related social cardiovascular mortality index (SCMI) as a population-level tool for public health surveillance and planning to identify US counties at risk of high CVD mortality. We also sought to identify the leading SDOH-related variables associated with CVD mortality across US counties.
methodsWe used public registry data from 3141 US counties and applied machine learning techniques to screen 158 SDOH-related variables (centered around 2019), identifying 15 key determinants of total CVD mortality (2018-2020) to develop the SCMI, a composite score ranging from 0.00 to 100.00. We validated SCMI by comparing its predictive performance with social vulnerability index (SVI) for future total CVD mortality (2019-2021) in 1000 bootstrap resamples, based on R
resultsCounties in the highest SCMI quintile (80.01-100.00), reflecting the most disadvantaged community conditions, had on average 202.55 more predicted total CVD deaths per 100,000 population than those in the lowest quintile (0.00-20.00) (p < 0.001). SCMI consistently outperformed SVI in predicting future total CVD mortality, with higher R
conclusionsOur novel SDOH-based SCMI consistently outperformed SVI in predicting US counties at risk of high CVD mortality. The identified leading county-level SDOH variables need further evaluation as potentially modifiable targets for community interventions. Our findings can improve county-level cardiovascular risk stratification and support efforts to mitigate geographical variations in cardiovascular mortality in the USA.
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