Evidence mapPaperPMID 39865224Full record

ArticleBMC endocrine disorders2025

Triglyceride-glucose index in predicting the risk of new-onset diabetes in the general population aged 45 years and older: a national prospective cohort study.

Yingqi Shan, Qingyang Liu, Tianshu Gao

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Article in BMC endocrine disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

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10citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yingqi ShanGraduate School of Liaoning, University of Traditional Chinese Medicine, Shenyang, Liaoning, 110033, China.
Qingyang LiuDepartment of Endocrinology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110033, China. qingyang-tcm@163.com.
Tianshu GaoDepartment of Endocrinology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110033, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveInsulin resistance (IR) is often present in diabetes, which imposes a heavy burden on the prevention and treatment of diabetes. Triglyceride glucose index (TyG) is simple, reliable and reproducible in detecting IR, and has great advantages in predicting the risk of diabetes. The aim of this study was to analyze the potential association between TyG and the risk of diabetes in Chinese middle-aged and older adults using a prospective cohort study design.

methodsThis study used longitudinal data from five waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, 2018, and 2020, involving 5886 participants. We used Cox proportional risk regression modeling to investigate the association between TyG index and the risk of new-onset diabetes, and decision tree analysis to identify high-risk groups for diabetes. Finally, ROC curves were applied in order to construct a predictive model for diabetes.

resultsA total of 1054 (17.9%) participants developed diabetes throughout the 9-year follow-up. Our study utilized a multivariate Cox proportional risk regression model and found a significant correlation between TyG index and diabetes risk. The analysis also revealed a nonlinear relationship between TyG index and diabetes risk.Receiver Operating Characteristic(ROC) curve analysis showed that the Area under the curve(AUC) area of TyG index in predicting the risk of new-onset diabetes was 0.652 (P < 0.05).

conclusionsTyG index can be used as a risk factor for predicting new-onset diabetes in the middle-aged and elderly population in China. In addition, there was a nonlinear relationship between TyG index and diabetes. Improving insulin resistance by regulating glucose and lipid metabolism plays an important role in the primary prevention of diabetes.

Indexed as

BiomarkersBlood GlucoseDiabetes MellitusDiabetes Mellitus, Type 2TriglyceridesAgedChinaFemaleFollow-Up StudiesHumansInsulin ResistanceLongitudinal StudiesMaleMiddle AgedPrognosisProspective StudiesBiomarkersBlood GlucoseTriglyceridesAged 45years and olderCHARLS databaseChort studyNew-onset diabetesTriglyceride-glucose index

Identifiers

PMID39865224
PMCPMC11765927

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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 Socratic graph.