Association and predictive values of nine biological age measures for cardiovascular disease mortality: screening and validation from two prospective cohort studies.

Abstract

Biological age (BA) reflects the aging process more accurately than chronological age. This study aimed to evaluate the associations and predictive values of nine BA measures for mortality outcomes. BA measures were developed using data from the Yixing Cohort Study (YCS; N = 4,128) and externally validated in the Jurong Cohort Study (JCS; N = 16,652). Dose-response relationships between the clinical indices and all-cause death were assessed using restricted cubic spline analysis. Statistically significant predictors were then integrated into BA estimates using nine different algorithms. The difference between BA and chronological age, termed delta age (DA), was calculated, and its association with mortality outcomes was assessed using Cox proportional hazards models. The hazard ratios (HRs) of the association of the nine DAs with mortality were greater for CVD death than all-cause death, with the DA derived from the Klemera and Doubal Method 2 (KDM2) showing the strongest association with CVD death (YCS: HR(95% CI) = 1.325 (1.060-1.656); JCS: HR(95% CI) = 1.167(1.101-1.236); P < 0.05) and all-cause death (YCS: HR(95% CI) = 1.203(1.075-1.346); JCS: HR(95% CI) = 1.089 (1.050-1.129); P < 0.05). Incorporating KDM2-based DA into the traditional risk factors model significantly improved the prediction of CVD death, as reflected by net reclassification improvement (YCS: NRI = 7.9%; JCS: NRI = 9.1%; P < 0.001) and integrated discrimination improvement (YCS: IDI = 0.4%; JCS: IDI = 0.7%; P < 0.001). Our findings support that KDM2-based aging measures could serve as a complementary tool for identifying people at high risk of CVD events and all-cause death.