Biological Age Acceleration as a Marker of Chronic Kidney Disease: A Population-Based Study

Chronic kidney disease (CKD) remains a major global health concern. Biological age (BA), which reflects the functional state of multiple physiological systems, may capture aging-related vulnerability more effectively than chronological age. This study evaluated whether acceleration in BA—estimated by the Klemera–Doubal method (KDM)—is linked to CKD in a nationally representative Chinese cohort. The original number of participants was 17,708. Data were drawn from 6,830 participants in the baseline wave of the China Health and Retirement Longitudinal Study (CHARLS). KDM-based BA acceleration (KDM-BAacc) was calculated as the residual from regressing biological age on chronological age and categorized into quartiles. CKD was identified from self-reported physician diagnoses. Logistic regression models with stepwise adjustment for sociodemographic, lifestyle, and clinical factors were applied to examine the association. Each interquartile range increase in KDM-BAacc was linked with markedly higher odds of CKD (OR = 2.13, 95% CI: 1.68–2.70, p  < 0.001). Participants in the top quartile of acceleration exhibited a risk of CKD that was over three times greater compared to those in the bottom quartile (OR = 3.10, 95% CI: 1.99–4.85). Restricted cubic spline models supported a steady, approximately linear increase in CKD risk across the entire spectrum of BA acceleration ( p for non-linearity = 0.758). Subgroup analyses showed consistency across demographic strata, with significant interactions observed for smoking history, education level, and sleep duration. Sensitivity analyses yielded consistent results. KDM-derived biological age acceleration is a strong, independent, and linearly increasing risk factor for CKD, suggesting that BA may hold substantial value for CKD risk prediction and early identification.