Association of various insulin resistance surrogate indices with aging acceleration and future risk of cardiovascular disease in individuals with cardiovascular-kidney-metabolic syndrome stages 0–3: insights from CHARLS 2011–2020 data
Shu-Shu Han, Qin Liu, Zhiming Zeng, Ying Li, Ping-wei Li, Fang-Xiao Cheng, Pian Zhong, Jiang-Bo Li
Abstract
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome imposes a substantial global health burden, with most adults clustered in early stages 0-3. Insulin resistance (IR), as a core manifestation of metabolic dysfunction, is thought to play a pivotal role in CKM progression and cardiovascular disease (CVD) development, but the relative impact of diverse IR surrogates and the mediating role of biological ageing acceleration remain unclear. METHOD: This prospective analysis included 6318 participants with CKM syndrome stages 0-3 from the China Health and Retirement Longitudinal Study (CHARLS). We evaluated twelve insulin resistance surrogates in relation to incident CVD using multivariable-adjusted logistic regression, restricted cubic splines (RCS), and quantile-based models. Mediation analyses assessed whether biological aging acceleration mediated the association between IR indices and new-onset CVD. RESULTS: 1231 (19.5%) of 6318 participants with CKM stages 0-3 developed new-onset CVD. All IR surrogates demonstrated significant associations with CVD risk, with elevated TyG-derived indices, METS-IR, CTI, and TG/HDL-C showing positive associations whereas eGDR exhibited an inverse relationship (all P-trend < 0.05). RCS analyses revealed nonlinear relationships for METS-IR, CTI, and eGDR. Significant modification effects were observed by biological ageing acceleration, gender, and CKM stage. Mediation analyses indicated that biological aging acceleration accounted for 14.9-16.4% of the TyG-ABSI-CVD association and 1.3-4.2% of other IR-CVD relationships. CONCLUSIONS: Multiple IR surrogate indices independently predict cardiovascular disease in CKM stages 0-3, with biological aging acceleration mediating this association. Integrating these measures into risk stratification could enable early identification and targeted intervention for high-risk individuals.