Development, testing and comparison of novel lifestyle-based prediction models for risk of coronary heart disease.

ABSTRACT: Prediction of coronary heart disease (CHD) risk through standard equations relying on laboratory-based clinical markers has proven challenging and needs advancement. This study aims to derive and cross-validate novel CHD-risk prediction models based on lifestyle behaviours including wearables and polygenic risk scores (PRS), with comparison to the established Pooled Cohort Equations (PCE) and Systematic COronary Risk Evaluation 2 (SCORE2). This study included 291,151 white British individuals of UK Biobank. Cox regression was applied to derive Lifestyle-Based Model (LBM) for CHD-risk prediction incorporating age, sex, body mass index, dietary intake score (0-3; derived from self-reported food types), smoking status, and physical activity (wearable-device-derived Euclidean Norm Minus One).

SUBMITTER: Shi Q 

PROVIDER: S-EPMC12541051 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature