Interpretable prediction of coronary heart disease risk in adults over 50 with accelerated aging using 45 dietary nutrients.

Abstract

Background: The relationship between dietary nutrient intake and coronary heart disease (CHD) risk among older adults with accelerated aging remains inadequately understood.

Methods: This study analyzed data from seven cycles of the National Health and Nutrition Examination Survey (NHANES) conducted in the United States between 2005 and 2018. Weighted Quantile Sum (WQS) regression was employed to evaluate the association between dietary nutrient mixtures and CHD risk in individuals aged 50 and older with accelerated aging. Additionally, six machine learning models were developed, with SHAP and LIME algorithms applied to assess the contribution of individual nutrients to CHD risk.

Results: In the fully adjusted model, dietary nutrient mixtures were inversely associated with CHD risk in older adults experiencing accelerated aging (adjusted OR = 0.90, 95% CI: 0.81-0.99, p = 0.048). Both SHAP and LIME analyses consistently identified vitamin B12 and lutein + zeaxanthin as protective nutrients, independent of demographic adjustments.

Conclusion: Among adults aged 50 and older with accelerated aging, higher intake of specific dietary nutrients was associated with reduced CHD risk. Of the machine learning models tested, the random forest algorithm demonstrated the strongest predictive performance. SHAP and LIME analyses jointly highlighted vitamin B12 and lutein + zeaxanthin as key contributors to the reduced CHD risk in this high-risk population.