ArticleNutrition & metabolism2024
Triglyceride-glucose index predicts all-cause mortality, but not cardiovascular mortality, in rural Northeast Chinese patients with metabolic syndrome: a community-based retrospective cohort study.
Article in Nutrition & metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Evaluation of the effect of baseline predictors on the incidence of metabolic syndrome in middle-aged and elderly individuals: a population-based cohort study in Southwest Iran.Diabetology & metabolic syndrome · 2026Article
- The prognostic significance of cholesterol, high-density lipoprotein and glucose (CHG) index in evaluating all-cause mortality risk in metabolic dysfunction-associated steatotic liver disease (MASLD) individuals: evidence from two cohort studies.Cardiovascular diabetology · 2026Article
- Review
- Nonlinear relationship between triglyceride-glucose index and cardiovascular mortality with competing risk analysis on populations aged 18-80 years.BMC cardiovascular disorders · 2025Article
- Emergency risk stratification using the TyG index: a multi-center cohort study on nonlinear association with 28-day mortality among critically ill patients transferred from the ED to the ICU.Frontiers in medicine · 2025Article
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6 authors.
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Abstract
backgroundMetabolic syndrome (MetS) includes a group of metabolic irregularities, including insulin resistance (IR), atherogenic dyslipidemia, central obesity, and hypertension. Consistent evidence supports IR and ongoing low-grade inflammation as the main contributors to MetS pathogenesis. However, the association between the triglyceride-glucose (TyG) index and mortality in people with MetS remains uncertain. The objective of this study was to examine the correlation between the baseline TyG index and all-cause and cardiovascular (CV) mortality in rural Northeast Chinese individuals with MetS.
methodsFor the Northeast China Rural Cardiovascular Health Study, 3918 participants (mean age, 55 ± 10; 62.4% women) with MetS at baseline were enrolled in 2012-2013 and followed up from 2015 to 2017. The TyG index was calculated using the equation TyG index = ln [fasting TG (mg/dL) × fasting glucose (mg/dL)/2] and subdivided into tertiles [Q1(< 8.92); Q2 (8.92-9.36); Q3 (≥ 9.36)]. Multivariate Cox proportional hazards models were developed to examine the correlations between mortality and the baseline TyG index.
resultsDuring a median of 4.66 years of follow-up, 196 (5.0%) all-cause deaths and 108 (2.8%) CV disease-related deaths occurred. The incidence of all-cause mortality was significantly different among TyG index tertiles of the overall population (P = 0.045). Kaplan-Meier analysis demonstrated a significantly increased risk of all-cause mortality in rural Chinese patients with a higher TyG index (log-rank P < 0.05). After adjusting for possible confounders, Cox proportional hazard analysis revealed that the TyG index could effectively predict all-cause mortality (HR for the third vs. first tertile of TyG was 1.441 [95% confidence interval, 1.009-2.059]), but not CV mortality, in rural Chinese patients with MetS.
conclusionsThe TyG index is an effective predictor of all-cause mortality in rural Chinese patients with MetS. This indicates that the TyG index may be useful for identifying rural Chinese individuals with MetS at a high risk of death.
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