Dose-Response Relationship Between the Triglyceride-Glucose Index and Metabolic Syndrome Risk in Patients With Type 2 Diabetes: A Cross-Sectional Analysis of 1,560 Cases

Feng ChenZixue GuRong Peng^*

• School of Basic Medical Sciences ＆ School of Nursing, Chengdu University, Chengdu, China

Background The triglyceride-glucose (TyG) index, as a novel biomarker for assessing insulin resistance, may possess predictive value for metabolic syndrome (MS) in patients with type 2 diabetes mellitus (T2DM). However, its dose-response relationship requires further investigation. Therefore, this cross-sectional study aimed to examine the association between the TyG index and MS, along with their dose-response relationship, in a T2DM population. Methods This cross-sectional study enrolled patients with T2DM from a tertiary hospital in Chengdu between January 2018 and December 2023. Participants were stratified into quartiles (Q1-Q4) based on TyG index levels. We employed multivariable logistic regression to analyze associations between TyG index and MS and its components. Predictive performance was evaluated using receiver operating characteristic (ROC) curve analysis, while restricted cubic spline analysis was utilized to examine the dose-response relationship between TyG index and MS.This study included a total of 1,560 patients with T2DM. With increasing TyG index levels, patients were significantly younger, had lower HDL-C levels, higher rates of current alcohol consumption, and elevated BMI, TG, TC, LDL-C and FPG values (all P<0.05). The prevalence of MS, overweight/obesity and dyslipidemia also progressively increased with higher TyG quartiles (all P<0.05). Pearson correlation analysis showed the TyG index was positively correlated with BMI, TG, TC, LDL-C and FPG (all P<0.001), while negatively correlated with HDL-C (P<0.001). After adjusting for confounding factors, multivariate logistic regression analysis revealed that compared with the Q1 group, the Q4 group had a significantly higher risk of MS (OR=26.994), overweight/obesity and dyslipidemia (all P<0.001). The area under the curve (AUC) for TyG index in predicting MS was 0.793,with a sensitivity of 0.864 and a specificity of 0.611. Furthermore, a nonlinear dose-response relationship was observed between TyG index and MS, with MS risk increasing progressively when TyG index exceeded 9.31. Conclusion The TyG index serves as an independent predictor of MS risk in patients with T2DM, demonstrating a significant dose-response relationship with MS.