Evidence map›Paper›PMID 41998634›Full record

ArticleBMC endocrine disorders2026

Association of TyG index and obesity indicators with cognitive function: a cross - sectional study from Chinese health check-up centers.

Jiapei Wei, Xucheng Wu, Liantian Chen, Yincun Wang, Yanjie Zhao, Liming Zhang, Xingqi Cao, Liying Chen, Xuan Ge, Yangzhen Lu and 2 more

Abstract read
In one paragraph

Article in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

1 citing paper in PubMed.

  1. Review
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

12 authors.

Jiapei WeiDepartment of General Practice, Dongyang People's Hospital, 60 Wuning West Road, Dongyang, Zhejiang, 322100, China.
Xucheng WuCenter for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Liantian ChenCenter for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Yincun WangCenter for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Yanjie ZhaoCenter for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Liming ZhangCenter for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Xingqi CaoDepartment of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Liying ChenDepartment of General Practice, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Xuan GeHealth Management Center, Dongyang People's Hospital, 60 Wuning West Road, Dongyang, 322100, China.
Yangzhen LuDepartment of General Practice, Dongyang People's Hospital, 60 Wuning West Road, Dongyang, Zhejiang, 322100, China.
Zuyun LiuCenter for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Health, Zhejiang Key Laboratory of Intelligent Preventive Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China. Zuyun.liu@outlook.com.
Hui ShentuDepartment of General Practice, Dongyang People's Hospital, 60 Wuning West Road, Dongyang, Zhejiang, 322100, China. sthdyrmyy@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhether the triglyceride-glucose index (TyG) and its derived indices [TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), TyG-weight-adjusted waist index (TyG-WWI), TyG-a body shape index (TyG-ABSI)] are associated with cognitive function remains unclear, particularly in middle-aged populations.

methodsA total of 876 participants (mean age 49.4 ± 13.3 years) were recruited. The TyG and its related indices were computed and divided into quartiles (Q1-Q4). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), Digit Symbol Substitution Test (DSST), and Auditory Verbal Learning Test (AVLT, including immediate recall [AVLT-3] and delayed recall [AVLT-5]). Multivariable linear regression models adjusted for demographic, lifestyle, and clinical covariates (Model 2) were used to assess associations. Restricted cubic spline (RCS) models were applied to explore non-linear relationships.

resultHigher TyG index quartiles were generally associated with lower cognitive scores, although associations were attenuated compared to models adjusted for age and sex only. Specifically, participants in the highest quartile (Q4) of TyG-WHtR had a 0.97 point lower MoCA score (95% CI: -1.89, -0.06) and a 1.53 point lower DSST score (95% CI: -2.97, -0.10) compared to Q1. Among the TyG-obesity indices, TyG-WHtR and TyG-WC showed consistent and significant associations with MoCA and DSST scores, while TyG-WWI and TyG-ABSI showed weaker or non-significant associations across cognitive domains. These associations were generally more pronounced in females and participants aged < 60 years. RCS analyses indicated approximately linear inverse associations for most indices, with a threshold effect observed for TyG-WWI.

conclusionsElevated TyG and its obesity-related indices, particularly TyG-WHtR, are associated with poorer cognitive function in healthy middle-aged Chinese adults. These findings highlight the potential utility of integrating metabolic and anthropometric indicators into early risk assessment for cognitive decline. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Blood GlucoseBody Mass IndexCognitionObesityTriglyceridesAdultChinaCross-Sectional StudiesFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisWaist CircumferenceWaist-Height RatioBlood GlucoseTriglyceridesCognitive functionEarly risk detectionMetabolismObesityTriglyceride-glucose index

Identifiers

PMID41998634
PMCPMC13224721

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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 OpenQuestion graph.