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Association between triglyceride-glucose derived indices with cardiometabolic multimorbidity: Findings from the

Yi Liu1,2,3, Dongze Li1,2,3, Jing Yu1,2,3

  • 1West China School of Nursing, Sichuan University/Department of Emergency Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Plos One
|December 30, 2025
PubMed

Insights

Triglyceride-glucose body mass index (TyG-BMI) effectively predicts cardiometabolic multimorbidity (CMM) risk. This index, combining insulin resistance and adiposity, offers valuable insights for early risk stratification.

Area of Science:

  • Cardiovascular Research
  • Metabolic Syndrome Studies
  • Public Health & Epidemiology

Background:

  • Cardiometabolic multimorbidity (CMM), encompassing diabetes mellitus (DM), stroke, and coronary heart disease (CHD), presents a significant global health challenge.
  • High mortality, reduced function, and increased healthcare costs are linked to CMM.
  • The predictive value of insulin resistance (IR) surrogates, like triglyceride-glucose (TyG) indices with anthropometrics, for CMM is not fully understood.

Purpose of the Study:

  • To quantify the association between TyG-derived indices and incident CMM.
  • To evaluate the predictive performance of various TyG-based markers for CMM risk.

Main Methods:

  • Utilized multivariate logistic regression analysis on Atherosclerosis Risk in Communities (ARIC) study data.
  • Employed restricted cubic spline modeling to investigate nonlinear associations.
  • Assessed diagnostic accuracy using receiver operating characteristic (ROC) curve analysis (area under the curve [AUC] values).

Main Results:

  • Triglyceride-glucose body mass index (TyG-BMI) showed the strongest association with CMM risk (OR: 1.61 per SD; 5.67-fold higher risk in the highest quartile).
  • TyG-BMI demonstrated the highest predictive performance (AUC: 0.684).
  • Nonlinear relationships were observed for TyG-BMI and TyG-waist-to-height ratio; linear trends for TyG and TyG-waist circumference.

Conclusions:

  • TyG-BMI is a robust predictor of CMM risk, reflecting combined insulin resistance and adiposity.
  • The observed nonlinear risk suggests threshold-dependent mechanisms.
  • TyG-BMI is valuable for early CMM risk stratification.
Abstract

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