Cholesterol, high-density lipoprotein, and glucose index versus triglyceride–glucose index in predicting cardiovascular disease risk: a cohort study

Cardiovascular disease (CVD) represents a significant global health challenge, characterized by high incidence rates and substantial morbidity and mortality. A newer index, the Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index, has been proposed as a potential diagnostic tool for metabolic disorders but has not been investigated for its ability to predict CVD risk. This study aims to evaluate the predictive efficacy of the CHG index in comparison to the well-established Triglyceride-Glucose (TyG) index.

In this cohort study, 6249 adults aged 45 and older were recruited from the CHARLS database, with data collected from 2011 to 2020. CVD events were tracked over a nine-year follow-up. The TyG and CHG indices were calculated, and their relationships with CVD risk were assessed using univariate and multivariate Cox regression models. Additionally, restricted cubic spline (RCS) analysis was performed to further explore these associations. Receiver operating characteristic (ROC) analysis was conducted to compare the predictive performance of both indices, and subgroup analysis evaluated their applicability in different populations.