Aims: Previous studies have shown that eGDR and TyG, as indicators of insulin resistance (IR), were key risk factors for cardiovascular disease (CVD). Our study further explored the relationship between eGDR change and new-onset CVD, and compared the predictive value of eGDR change, eGDR and TyG.
Materials and methods: A total of 2895 participants without CVD at baseline from the China Health and Retirement Longitudinal Study (CHARLS) were included, using K-means clustering and cumulative eGDR to measure eGDR change between 2012 and 2015. Cox and restricted cubic splines (RCS) regression models assessed the relationship between eGDR change and new-onset CVD. The predictive value of TyG, eGDR and eGDR change for outcomes was evaluated using receiver operating characteristic (ROC) curves, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).
Results: During a mean follow-up of 4.42 years, 581 CVD cases occurred, including 389 heart disease cases and 249 stroke cases. Participants with consistently low eGDR had a higher new-onset CVD risk (HR: 2.51, 95%CI: 2.04-3.09). A stepwise increase of outcomes was observed with the increased cumulative eGDR (p for trend <0.001). Further analysis showed the correlation between cumulative eGDR and outcomes was linear. Compared to eGDR and TyG, cumulative eGDR exerted greater predictive effect as evaluated by area under curve, IDI and NRI.
Conclusions: Sustained low eGDR was related to an increased risk of new-onset CVD in middle-aged and elderly population. Continuous monitoring of eGDR significantly enhances the accuracy of new-onset CVD risk stratification, which may reduce the incidence of new-onset CVD.
Keywords: CHARLS; K‐means clustering; cardiovascular diseases; estimated glucose disposal rate change; insulin resistance.
© 2025 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.