BACKGROUND: Atherosclerotic cardiovascular disease remains a leading cause of morbidity and mortality worldwide. Established risk equations guide prevention but rely mainly on static, clinic-based variables and incompletely capture physical activity, sedentary behavior, and cardiorespiratory fitness.
METHODS: This narrative review synthesizes evidence from epidemiological studies, clinical trials, and methodological frameworks on the roles of physical activity, sedentary behavior, and cardiorespiratory fitness (CRF) in cardiovascular risk prediction, with emphasis on digital phenotyping, mechanistic exercise physiology, and multimodal clinical prediction models.
RESULTS: Cardiorespiratory fitness reflects integrated physiological reserve and is strongly associated with cardiovascular and all-cause outcomes. Cardiopulmonary exercise testing extends fitness assessment by identifying mechanisms of exercise limitation, including cardiac, ventilatory, autonomic, pulmonary vascular, and peripheral contributors. Wearable technologies provide longitudinal, real-world measures of physical activity and sedentary behavior that complement static clinical risk factors. Multimodal models integrating electronic health records, electrocardiography, imaging, wearable signals, and exercise testing may support more personalized and actionable risk stratification. However, the current evidence base remains limited by insufficient external and prospective validation, incomplete calibration reporting, limited decision-analytic evaluation, and inadequate assessment of subgroup performance and equity.
CONCLUSIONS: Physical activity and cardiorespiratory fitness should be considered clinically relevant and modifiable phenotypes in contemporary cardiovascular risk prediction. Future models should prioritize standardized measurement, mechanistic validation of digital phenotypes, calibration, external validation, subgroup evaluation, workflow feasibility, and prospective evidence of clinical utility before widespread implementation.