Evidence map›Paper›PMID 40672596›Full record

ArticleAmerican journal of translational research2025

Nonlinear relationship between TyG index and the risk of non-alcoholic fatty liver disease in Chinese population: a cross-sectional study.

Tuo Han, Bao'e Yan, Jing Xiao, Xiyu Gao, Ying Li, Qian Wang, Chunyan Zhang, Yan Zhang

Abstract read
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Article in American journal of translational research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing 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

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Tuo HanDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Bao'e YanDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Jing XiaoDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Xiyu GaoDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Ying LiDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Qian WangDepartment of Health Management, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Chunyan ZhangDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.
Yan ZhangDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University Xi'an 710004, Shaanxi, The People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is insufficient evidence on the link between the triglyceride-glucose index (TyG) and non-alcoholic fatty liver disease (NAFLD) in the Chinese population. This study aims to investigate the association between TyG and the risk of NAFLD.

methodsA cross-sectional study was conducted with 994 participants who underwent health examinations. Demographic information, blood biochemistry profiles, and ultrasonics results were collected. Logistic regression and restricted cubic spline (RCS) analysis was used to assess the nonlinear relationship between TyG and NAFLD risk. Subgroup analysis was performed to examine possible interaction effects.

resultsOverall, 31.2% (n = 314) of the general population had NAFLD. Age, male gender, BMI, blood pressure, alanine aminotransferase, fasting blood glucose, uric acid, triglycerides and TyG levels were associated with NAFLD. RCS analysis showed a significant nonlinear dose-response relationship between TyG index and NAFLD. The risk of developing NAFLD increases significantly with a higher TyG index. This association persists even after adjustment for relevant risk factors [odds ratio (OR): 4.70, 95% CI 3.24 to 6.83]. Furthermore, compared to the lowest quartile of TyG (Q1), the NAFLD risk of subjects in the Q2, Q3, and Q4 quartiles increased 1.53, 3.84, and 16.07 times, respectively (P for trend < 0.001). Furthermore, statistically significant interactions were observed between TyG index and gender, BMI, and hypertension in predicting NAFLD risk (P < 0.05).

conclusionsThis study highlights the impact of an elevated TyG index on the risk of developing NAFLD. Elevated TyG levels may serve as a risk factor for NAFLD in the Chinese population.

Indexed as

hypertensioninsulin resistanceNon-alcoholic fatty liver diseasesex differencetriglyceride-glucose index

Identifiers

PMID40672596
PMCPMC12261141

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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.