Evidence map›Paper›PMID 40589514›Full record

ArticleFrontiers in endocrinology2025

Association of triglyceride glucose index with incident diabetes among individuals with normal fasting triglycerides and fasting plasma glucose values: a general population-based retrospective cohort study.

Yongchao Wang, Tiantian Cheng, Tie Zhang, Rubing Guo, Liang Ma, Wei Zhao

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Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yongchao WangDepartment of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China.
Tiantian ChengDepartment of Traditional Chinese Medicine Dermatology, Chaoyang District Taiyanggong Community Health Service Center, Beijing, China.
Tie ZhangDepartment of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China.
Rubing GuoSchool of Public Health, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Liang MaDepartment of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China.
Wei ZhaoDepartment of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The triglyceride glucose (TyG) index has been proposed as a reliable surrogate marker for insulin resistance. Previous studies have demonstrated a significant positive association between the TyG index and diabetes risk. However, whether this association persists among individuals with normal fasting triglyceride (TG) and fasting plasma glucose (FPG) levels remains unclear. This study aims to evaluate the relationship between the TyG index and diabetes in this specific population utilizing a large-scale population-based dataset. Methods: A total of 155,337 subjects (74,622 males and 80,715 females) were included in this retrospective cohort study. The TyG index was calculated using the formula: ln [TG (mg/dL) × GLU (mg/dL)/2]. Cox regression analyses were utilized to estimate hazard ratios (HR) and 95% confidence intervals (CI). A generalized additive model (GAM), combined with smooth curve fitting, was employed to investigate potential nonlinear associations. Subgroup analyses were stratified by age, sex, body mass index, and family history of diabetes. Results: During a 3.13-year mean follow-up, 1127 subjects (0.73%) developed diabetes. After adjusting for confounding variables, subjects in the highest quartile of baseline TyG index exhibited an increased risk of diabetes compared to those in the lowest quartile (adjusted HR: 3.80; 95% CI: 2.41-5.99; P for trend < 0.001). Furthermore, a nonlinear threshold association was identified, with an inflection point at a TyG index value of 8.41. For subjects with a TyG index greater than 8.41, the adjusted HR was 15.33 (95% CI: 7.3-32.2, P < 0.001). Subgroup analysis revealed a stronger positive correlation in individuals aged <60 years. Discussion: This large-scale study demonstrates a robust independent association between the TyG index and diabetes risk in individuals with normal FPG and TG levels. Our findings suggest that a TyG index exceeding 8.41 correlates with a progressively higher risk of diabetes development. These results collectively suggest the TyG index could serve as a clinically relevant predictor of diabetes incidence in this population.

Indexed as

Blood GlucoseDiabetes MellitusDiabetes Mellitus, Type 2FastingTriglyceridesAdultAgedBiomarkersFemaleFollow-Up StudiesHumansIncidenceInsulin ResistanceMaleMiddle AgedPrognosisBiomarkersBlood GlucoseTriglyceridescohort studydiabetesinflection pointrisk factorstriglyceride glucose index

Identifiers

PMID40589514
PMCPMC12206639

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.