Evidence mapPaperPMID 40898229Full record

ArticleCardiovascular diabetology2025

The association between triglyceride glucose-waist height ratio index and cardiometabolic multimorbidity among Chinese middle-aged and older adults: a national prospective cohort study.

Longyan Lv, Ping Zhang, Xuerui Chen, Yan Gao

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Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

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16citing papers in PubMed
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3 · Its place in the literature

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16 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Longyan LvFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province 250355, China.
Ping ZhangFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province 250355, China.
Xuerui ChenFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province 250355, China.
Yan GaoDepartment of General Medicine, the 960th Hospital of People's Liberation Army Joint Logistics Support Force, NO.25 Shifan Road, Jinan, Shandong 250031, People's Republic of China. gaoyantianyu74@163.com.ORCID https://orcid.org/0000-0003-0279-0790

Funding

The 2023 PLA General Logistics Department Health Care Special Project 23BJZ45
6 · The paper itself

Abstract

backgroundCardiometabolic multimorbidity (CMM) imposes a progressively severe health burden worldwide. Triglyceride-glucose (TyG) index and waist-to-height ratio (WHtR), as indicators of insulin resistance and central adiposity, respectively, have been shown to be strongly associated with CMM. However, there is currently a lack of research combining the two for CMM risk assessment. This study aims to investigate the relationship between TyG-WHtR index and CMM.

methodsThis prospective cohort study analyzed data from Chinese adults aged ≥ 45 years participating in the 2011-2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). We employed the Kaplan-Meier curves, multivariable Cox regression analysis, and restricted cubic spline (RCS) to examine the relationship between the TyG-WHtR index and the risk of CMM. Time-dependent receiver operating characteristic (ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were utilized to evaluate predictive performance. Additionally, subgroup analyses and sensitivity tests were conducted to assess the robustness of the findings.

resultsDuring a median follow-up of 9 years, 413 (9.4%) of the 4393 participants developed CMM. Multivariable Cox regression analysis revealed progressively higher risks of CMM across increasing TyG-WHtR quartiles. Compared to participants in the lowest quartile (Q1) of the TyG-WHtR index, the hazard ratios (HRs) and 95% confidence intervals (CIs) for those in quartiles Q2, Q3, and Q4 were 1.75 (1.18-2.6), 2.33 (1.58-3.43), and 3.13 (2.08-4.7), respectively. Consistently, elevated cumulative TyG-WHtR independently increased CMM risk. The RCS analysis indicated a positive linear relationship between the TyG-WHtR index and the incidence of CMM. Moreover, both baseline and cumulative TyG-WHtR significantly improved reclassification metrics (NRI/IDI) and discriminative ability (AUC). Sensitivity analyses corroborated these primary findings.

conclusionThis study suggests that TyG-WHtR independently predicts CMM risk. The linear dose-response relationship highlight the potential utility of TyG-WHtR in early risk assessment and prevention strategies for CMM.

Indexed as

Blood GlucoseTriglyceridesWaist-Height RatioAgedAge FactorsBiomarkersCardiometabolic Risk FactorsChinaEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedMultimorbidityPredictive Value of TestsBiomarkersBlood GlucoseTriglyceridesCardiometabolic multimorbidity (CMM)CHARLSTriglyceride glucose-waist height ratio index (TyG-WHtR)

Identifiers

PMID40898229
PMCPMC12406543

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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.