# Combined effect of triglyceride-glucose index and glucose disposal rate on cardio-cerebrovascular disease

**Authors:** Hongfei Yang, Chao Sun, Ya Li, You Zhou, Rui Wang, Yingxue Li

PMC · DOI: 10.1371/journal.pone.0342154 · PLOS One · 2026-02-06

## TL;DR

This study explores how combining two markers of insulin resistance improves prediction of cardio-cerebrovascular disease risk.

## Contribution

The study introduces the combined use of TyG index and eGDR for predicting cardio-cerebrovascular disease outcomes.

## Key findings

- High TyG and low eGDR groups showed significantly increased disease risk compared to the reference group.
- TyG and eGDR have synergistic predictive value for cardio-cerebrovascular disease.
- Multiplicative interaction between TyG and eGDR was significant, but additive interaction was not.

## Abstract

The triglyceride-glucose index and estimated glucose disposal rate serve as notable surrogate markers of insulin resistance, demonstrating established links to cardio-cerebrovascular disease. However, their combined prognostic value in predicting cardio-cerebrovascular disease outcomes remains unexplored. The current investigation examined the interaction between the TyG (triglyceride–glucose index) index and eGDR (estimated glucose disposal rate) concerning the danger of cardiovascular disease within a clinical population.

This investigation employed data sourced from the China Health and Retirement Longitudinal Study (CHARLS). The median TyG index and eGDR scores were used to stratify the participants into 4 categories: low TyG/high eGDR, high TyG/high eGDR, low TyG/low eGDR, and high TyG/low eGDR. Clinical characteristics across groups were systematically compared. Cox proportional hazards regression models evaluated the distinct and interconnected associations of the TyG index and eGDR with the risk of cardio-cerebrovascular disease, with multiplicative and additive interaction effects subsequently assessed through formal interaction analysis.

The final study cohort comprised 7,330 participants, with 1,336 individuals (18.2%) developing cardio-cerebrovascular disease during the 9-year follow-up. Stratification using median thresholds (TyG: 8.59; eGDR: 10.55 mg/kg/min) yielded four groups: low TyG/high eGDR (n = 2,991), high TyG/high eGDR (n = 1,375), low TyG/low eGDR (n = 1,372), and high TyG/low eGDR (n = 2,292). Multivariable-adjusted Cox regression analyses revealed markedly increased risks of cardio-cerebrovascular disease among the various exposure groups when contrasted with the low TyG/high eGDR reference: high TyG/high eGDR (HR: 1.31, 95%CI: 1.10–1.57, p< 0.05), low TyG/low eGDR (HR: 1.54, 95%CI: 1.29–1.84, p< 0.05), and high TyG/low eGDR (HR: 1.55, 95%CI: 1.31–1.82, p< 0.05). Interaction analysis revealed significant multiplicative effects between TyG and eGDR but no evidence of additive interaction.

The TyG index and eGDR demonstrate independent associations with cardio-cerebrovascular disease risk, while their combined assessment reveals synergistic predictive capacity. Combined assessment of the two allows for further accurate stratification of the population based on insulin resistance and improved prediction of cardio-cerebrovascular disease.

## Full-text entities

- **Genes:** INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, SERPINE1 (serpin family E member 1) [NCBI Gene 5054] {aka PAI, PAI-1, PAI1, PLANH1}, RENBP (renin binding protein) [NCBI Gene 5973] {aka RBP, RNBP}
- **Diseases:** type 1 and type 2 diabetes (MESH:D003924), HEC (MESH:D044903), CHARLS (OMIM:603663), cerebral vascular diseases (MESH:D014652), cardiovascular mortality (MESH:D003643), hypertension (MESH:D006973), CAPI (MESH:C000719218), obesity (MESH:D009765), CVD (MESH:D002318), diabetes (MESH:D003920), angina (MESH:D000787), arterial stiffness (MESH:C566112), visceral adiposity (MESH:D007418), very-low-density lipoprotein (MESH:D001851), IR (MESH:D007333), cardio-cerebrovascular disease (MESH:D002561), stroke (MESH:D020521), dyslipidemia (MESH:D050171), CHD (MESH:D003327), heart disease (MESH:D006331), cancer (MESH:D009369), adipokine dysregulation (MESH:D021081), thrombosis (MESH:D013927), heart failure (MESH:D006333), chronic inflammation (MESH:D007249), cardiac insufficiency (MESH:D000309), atherosclerosis (MESH:D050197), adiposity (MESH:D018205), hyperglycemia (MESH:D006943), metabolic dysfunction (MESH:D008659), myocardial fibrosis (MESH:D005355)
- **Chemicals:** UA (MESH:D014527), oxygen (MESH:D010100), creatinine (MESH:D003404), TG (MESH:D014280), glucose (MESH:D005947), alcohol (MESH:D000438), reactive oxygen species (MESH:D017382), NO (MESH:D009569), blood glucose (MESH:D001786), free fatty acids (MESH:D005230), advanced glycation end-product (MESH:D017127), CCVD (-), urea nitrogen (MESH:C530477), cholesterol (MESH:D002784)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12880699/full.md

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12880699/full.md

## References

40 references — full list in the complete paper: https://tomesphere.com/paper/PMC12880699/full.md

---
Source: https://tomesphere.com/paper/PMC12880699