Key result
Hong-Mainous index outperforms poverty rate alone in predicting high county-level CVD burden.
Why the study?
Social determinants of health are linked to health conditions, but multivariate measures to estimate community risk of morbidity or mortality were lacking.
Does the HM-CVD index score accurately predict county-level cardiovascular disease mortality compared to other area-level indexes?
Cross-Sectional (n=3,026)
Does the HM-CVD index score accurately predict county-level cardiovascular disease mortality compared to other area-level indexes?
Effect estimate: AUC 0.851 (95% CI 0.829-0.872)
Absolute Event Rate: 0.851% vs 0.808%
p-value: p=<0.001
A novel county-level social determinants of health index score accurately predicts cardiovascular disease mortality burden and outperforms existing area-level socioeconomic indices.
May aid county-level CVD burden identification; hypothesis-generating for SDOH indices, pending prospective validation.
PURPOSE Social determinants of health (SDoH) have been linked to a variety of health conditions, but there are no multivariate measures of these determinants to estimate the risk of morbidity or mortality in a community. We developed a score derived from multivariate measures of SDoH that predicts county-level cardiovascular disease (CVD) mortality. METHODS Using county-level data from 3,026 US counties, we developed a score considering variables of neighborhood socioeconomic status, food/lifestyle environment, and health care resource availability and accessibility to predict the 3-year average (2015-2017) age-adjusted county-level mortality rate for all CVD. We used one 50% random sample to develop the score and the other to validate the score. A Poisson regression model was developed to estimate parameters of variables while accounting for intrastate correlation. RESULTS The index score was based on 7 SDoH factors: percentage of the population of minority (nonwhite) race, poverty rate, percentage of the population without a high school diploma, grocery store ratio, fast-food restaurant ratio, after-tax soda price, and primary care physician supply. The area under the curve for the development and validation groups was similar, 0.851 (95% CI, 0.829-0.872) and 0.840 (95% CI, 0.817-0.863), respectively, indicating excellent discriminative ability. The index had better predictive performance for CVD burden than other area-level indexes: poverty only (area under the curve= 0.808, P <.001); the Centers for Disease Control and Prevention’s Social Vulnerability Index (CDC-SVI) (area under the curve =0.786, P <.001); and the Agency for Healthcare Research and Quality’s Socioeconomic Status (AHRQ-SES) index (area under the curve =0.835, P = .03). CONCLUSIONS Our validated multivariate SDoH index score accurately classifies counties with high CVD burden and therefore has the potential to improve CVD risk prediction for vulnerable populations and interventions for CVD at the county level.
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Hong et al. (2020) conducted a cross-sectional in Cardiovascular disease (n=3,026). Hong-Mainous CVD (HM-CVD) index vs. Poverty rate was evaluated on Predictive performance (AUC) for high county-level CVD burden (AUC 0.851, 95% CI 0.829-0.872, p=<0.001). The Hong-Mainous cardiovascular disease index demonstrated excellent discriminative ability (AUC 0.851) and outperformed poverty rate alone (AUC 0.808) in predicting high county-level CVD burden.
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