Dynamic reversibility of biological aging and risk of cardiovascular disease and stroke: a longitudinal cohort study

Abstract Background Aging status, indexed by biological age acceleration (BAacc), is closely associated with cardiovascular disease (CVD). However, transitioning from reactive healthcare to predictive, preventive, and personalised medicine (PPPM/3PM) requires elucidating how longitudinal, dynamic transitions in aging status impact incident CVD risk. Methods We analyzed 4,756 participants from the China Health and Retirement Longitudinal Study. Biological age was calculated using the Klemera-Doubal method (KDM). KDM-BAacc was measured at Wave 1 (baseline) and Wave 3 (follow-up) to derive multidimensional dynamic metrics: change groups, K-means clusters, aging rates, cumulative burden, and extreme phenotypes. Wave 2 was excluded from baseline calculations due to the absence of blood biomarker collection. Incident CVD (stroke and heart disease) was ascertained over a median 9.13-year follow-up. Cox models were adjusted for sociodemographic, lifestyle, and clinical risk factors. Results Compared to sustained acceleration, reversing aging status (“accelerated to non-accelerated”) significantly lowered risks of composite CVD (HR: 0.72, 95% CI: 0.59–0.89) and stroke (HR: 0.46, 95% CI: 0.33–0.64). Consistent protective effects were observed in “high-to-low” cluster trajectories. Conversely, the “Rapid aging” phenotype (sustained highest quartile) nearly doubled stroke risk (HR: 1.97) versus the “Anti-aging” group. Faster aging rates (≥ 1) were associated with a 32% increased stroke risk, demonstrating a linear dose-response relationship. Notably, associations with heart disease were attenuated after adjusting for comorbidities. Conclusions Biological aging is dynamically reversible, and reversing KDM-BAacc significantly mitigates CVD and stroke risks. For routine medical application, we recommend integrating longitudinal KDM-BAacc profiling into annual primary care check-ups. Crucially, these findings strongly support the paradigm shift from reactive medical services to PPPM/3PM. By identifying reversible suboptimal health prior to disease onset, this predictive tool enables targeted prevention and personalised interventions based on individual aging trajectories, decisively surpassing conventional generalized approaches.