A novel glucose–lipid metabolism–related indicator and its association with metabolic dysfunction–associated fatty liver disease: a cross–sectional study based on a health check–up population

Objective This study aimed to investigate the association between a novel glucose–lipid metabolic indicator, the cholesterol, high density lipoprotein, and glucose (CHG) index, and the prevalence of metabolic dysfunction–associated fatty liver disease (MAFLD), as well as to evaluate its discriminative ability. Methods This single–center cross–sectional study included 166,647 adults who underwent a health examination at the Health Management Center of the First Affiliated Hospital of Chongqing Medical University between July 2022 and March 2025. Multivariable logistic regression models were used to assess the association between the CHG index and the prevalence of MAFLD. Restricted cubic spline (RCS) functions were applied to explore potential nonlinear relationships. Receiver operating characteristic (ROC) curve analysis was used to compare the discriminative ability of the CHG index, triglyceride-glucose (TyG) index, and fatty liver index (FLI), and differences in AUCs were assessed using the DeLong test. Subgroup analyses were performed to assess its stability across different populations. Sensitivity analyses were performed to further examine the association between the CHG index and MAFLD. Results A total of 166,647 participants were included, comprising 85,643 men (51.4%) and 81,004 women (48.6%), with an overall prevalence of MAFLD of 33.7%. The CHG index was significantly higher in participants with MAFLD than in those without (5.42 ± 0.34 vs. 5.05 ± 0.31; P < 0.001). In the fully adjusted model, the CHG index was positively associated with MAFLD (per SD increase in the CHG index: OR = 2.35, 95% CI: 2.31–2.39, P < 0.001; Q4 vs Q1: OR = 8.64, 95% CI: 8.21–9.10, P < 0.001, P for trend < 0.001). Threshold effect analysis demonstrated a nonlinear association between the CHG index and MAFLD (inflection point K = 5.54, P for nonlinearity < 0.001). ROC analysis showed that the CHG index had good discriminatory ability for MAFLD (AUC = 0.810, 95% CI: 0.807-0.812), although its performance was lower than that of the TyG index and FLI. Subgroup analyses showed significant interactions between the CHG index and age, sex, and body mass index (BMI) (all P for interaction < 0.001), with stronger associations observed among females, younger participants, and those with lower BMI. Sensitivity analyses showed similar results. Conclusion The CHG index was positively associated with MAFLD and showed good discriminatory ability in this large Chinese health check-up population. Although its performance was lower than that of the TyG index and FLI, it may still serve as a simple and accessible metabolic indicator for identifying individuals at higher risk of MAFLD in primary healthcare and health screening settings.