Objective To investigate the association between 8 insulin resistance (IR) surrogate markers and incident atherosclerotic cardiovascular disease (ASCVD) in population with cardiovascular-kidney-metabolic syndrome (CKM) of stages 0-3, and to identify the surrogate marker with the best predictive performance.

Methods A study was conducted on 20121 community residents classified as CKM stages 0-3 from the Chengdu cohort of the China Multi-Ethic Cohort. A Cox proportional hazards model was used to calculate hazard ratios (HRs) between each IR surrogate marker and incident ASCVD. Cubic spline regression was employed to explore the dose-response relationships between these markers and incident ASCVD. The relative relationships between different markers and incident ASCVD were examined through the ratio of HRs (RHRs). Time-dependent area under the receiver operating characteristic curve (TDAUC) and Uno's C-statistic were calculated to compare the predictive performance of each marker for incident ASCVD. Based on the PREVENT equation components and the 8 surrogate markers under analysis, random forest feature selection was used to determine the contribution of each marker to accurate prediction.

Results During a follow-up period of 82741.93 person-years, 1447 incident cases of ASCVD were recorded, with an incidence density of 17.49 per 1000 person-years. Association analyses indicated that the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL) and the TyG/(TG/HDL) index were not associated with incident ASCVD (P > 0.05). The TyG index combined with obesity measurement parameters emerged as a reliable predictor of ASCVD incidence. The most promising indicator, TyG index with waist-to-height ratio (TyG_WHtR), exhibited an inverted J-shaped association with incident ASCVD (P for nonlinearity = 0.045; TDAUC = 0.640; C = 0.634), while the TyG index with body mass index (TyG_BMI), waist circumference (TyG_WC), and waist-to-hip ratio (TyG_WHR) showed positive linear associations (all P for trend < 0.05), with relatively lower predictive performance (C = 0.564, 0.588, and 0.598, respectively). Although both the TyG index and the metabolic score for insulin resistance (METS-IR) were associated with increased ASCVD risk (TyG: Q2 vs. Q1, HR = 1.23 and Q4 vs. Q1, HR = 1.24; METS-IR: P for non-linearity = 0.045), they exhibited poor predictive performance for incident ASCVD.

Conclusion The TyG index combined with obesity measurement parameters is an ideal IR surrogate marker for predicting incident ASCVD in populations with stages 0-3 CKM. Monitoring these markers will facilitate the prevention and control of cardiovascular diseases in CKM populations.