Evidence map›Paper›PMID 40038642›Full record

ArticleBMC public health2025

The association between derived TyG index and the risk of heart failure in the elderly population: a prospective cohort study from 2017 to 2023.

Xinyang Dui, Xin Chen, Linlin Zhu, Xinyue Han, Tianpei Ma, Liang Lv, Guoyue Huang, Lin Hu, Jinyu Xiao, Zhuoma Diji and 7 more

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Xinyang Dui *Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Xin Chen *Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Linlin Zhu *Department of Toxic Nephrology, West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Xinyue HanDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Tianpei MaDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Liang LvDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Guoyue HuangThe Johns Hopkins University, Bloomberg School of Public Health, Baltimore, USA.
Lin HuDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Jinyu XiaoDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Zhuoma DijiDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Nan YangDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Mengjie HuDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Jiaqiang LiaoDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Mengyu FanDepartment of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Xia JiangWest China Institute of Preventive and Medical Integration for Major Diseases, Sichuan University, Chengdu, Sichuan, China.
Tao Zhang *Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China. statzhangtao@scu.edu.cn.
Jiayuan Li *Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China. lijiayuan73@163.com.

Funding

Chengdu Science and Technology Program 2024-YF05-01784-SNNational Key Research and Development Program of China 2020YFC2006505Sichuan Provincial Science and Technology Support Program 2024ZYD0102, 2025YFHZ0069
6 · The paper itself

Abstract

backgroundDiabetes and obesity are established risk factors for heart failure(HF). Although the TyG (triglyceride-glucose) index serves as a sensitive marker for identifying insulin resistance, there is a lack of comprehensive evidence regarding whether its integration with obesity indices can enhance the predictive capacity for HF. This prospective cohort study is designed to explore the correlation between TyG indices in conjunction with obesity indices (TyG-body mass index, or TyG-BMI; TyG-waist circumference, or TyG-WC; TyG-waist circumference-to-height ratio, or TyG-WHtR) and the risk of HF.

methodsBetween 2017 and 2023, the study employed a prospective cohort study design to investigate all older adults aged 60 years and above who completed at least twice periodical health examinations in the National Basic Public Health Service at the Hongguang Community Health Service Center. The association between TyG and its derived indices (TyG-BMI; TyG-WC; TyG-WHtR) and the risk of HF was assessed by Cox modelling, as well as their longitudinal trajectories fitted using a group-based trajectory model.

resultsA total of 7,335 people participated in the study. During an average follow-up period of 2.97 years, 229 participants were eventually diagnosed with HF. Findings showed that individuals with a TyG-BMI less than 142 or greater than or equal to 169, TyG-WC greater than or equal to 614, and TyG-WHtR greater than or equal to 3.85 had a higher risk of developing HF, with hazard ratios (HR) and 95% confidence intervals (CIs) of 1.17 (1.15, 2.55), 1.45 (1.06. 1.98), 1.54 (1.09, 2.18) and 1.33 (1.01, 1.75). In terms of trajectories, the three derived indexes exhibited relatively stable fluctuations. Specifically, among men, those with low-level fluctuations in the TyG-BMI trajectory had a hazard ratio of 2.37 for HF compared to those with a medium-level wave.Compared to individuals whose TyG-WHtR levels fluctuate around 3.71 over five years, those with TyG-WHtR levels approaching 3.29 and steadily decreasing face an 80% higher risk of developing HF. However, there was no such difference observed in women.

conclusionThis study demonstrates a difference in the risk of HF among populations with varying levels of TyG combined with obesity indicators. In addition, persistently low and decreasing levels of TyG-WHtR also indicate an increased risk of developing HF. These biomarkers can be used as effective practical tools for identifying those at high risk of developing HF in the community's older population.

Indexed as

Blood GlucoseHeart FailureAgedAged, 80 and overBiomarkersBody Mass IndexFemaleHong KongHumansMaleMiddle AgedObesityProspective StudiesRisk AssessmentRisk FactorsWaist CircumferenceBiomarkersBlood GlucoseDerived TyG indexHeart failureProspective cohort study

Identifiers

PMID40038642
PMCPMC11877815

What Socratic holds

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LicenceCC BY
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Registered trials

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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.