Evidence map›Paper›PMID 33109219›Full record

ArticleLipids in health and disease2020

Association between triglyceride glucose-body mass index and non-alcoholic fatty liver disease in the non-obese Chinese population with normal blood lipid levels: a secondary analysis based on a prospective cohort study.

Yaling Li, Rui Zheng, Jie Li, Shuyi Feng, Li Wang, Zhiming Huang

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 pooled it
7.4field-weighted citation impact, top 2% of its field
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

35 citing papers in PubMed, 4 syntheses or guidelines pooled it, 70 citations in OpenAlex.

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  13. Association of Lipid and Blood Glucose Profiles with MASLD Among Young Adults.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025
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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

6 authors at 1 institution in 1 country.

Yaling LiDepartment of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang Province, China.
Rui ZhengDepartment of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang Province, China.
Jie LiDepartment of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang Province, China.
Shuyi FengDepartment of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang Province, China.
Li WangDepartment of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang Province, China.
Zhiming HuangDepartment of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang Province, China. wzfyyhzm@163.com.ORCID http://orcid.org/0000-0002-1378-2983
Wenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBoth triglyceride glucose-body mass index (TyG-BMI) and non-alcoholic fatty liver disease (NAFLD) are linked to insulin resistance (IR). Prospective studies linking TyG-BMI to NAFLD have been limited by short follow-up. This study investigated the longitudinal association between TyG-BMI and NAFLD occurrence in the non-obese Chinese individuals.

methodsThis study determined TyG-BMI at baseline and the incidence of NAFLD at follow-up and performed a post hoc analysis of a prospective cohort study that involved assessing the risk of NAFLD in non-obese Chinese residents from January 2010 to December 2014. The incidence of NAFLD during the 5-year follow-up was identified as the endpoint. Cox proportional hazards regression analysis was used to evaluate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the incidence of NAFLD. Receiver operating characteristic (ROC) curve analysis was conducted to estimate the predictive power of TyG-BMI and its components for NAFLD. Subgroup analysis was performed to better understand other factors that may affect the association between TyG-BMI and NAFLD to identify potential special populations.

resultsDuring the follow-up period, 841 (8.61%) of 9767 non-obese subjects who met the screening criteria were diagnosed with NAFLD. After confounding factors were fully adjusted for, the HR of NAFLD was 3.09 (95% CI 2.63-3.63) per standard deviation (SD) increase in TyG-BMI. Furthermore, TyG-BMI had a strong predictive value (area under ROC = 0.85; 95% CI 0.84-0.86) for the incidence of NAFLD, with a specificity of 0.73 and sensitivity of 0.82. Additionally, in the male population, each SD increase in TyG-BMI was linked to an increased risk of NAFLD (HR = 2.85, 95% CI 2.30-3.53), but the risk was higher in the female population (HR = 3.58, 95% CI 2.80-4.60). Gender and TyG-BMI interacted significantly with NAFLD incidence (P < 0.0001).

conclusionIn the normolipidaemic and non-obese subset of the Chinese population, an increase in TyG-BMI is related to an increased incidence of NAFLD. TyG-BMI may have clinical significance in identifying groups at high risk of NAFLD.

Indexed as

Body Mass IndexAdultAsian PeopleBlood GlucoseChinaFemaleHumansIncidenceLipidsLongitudinal StudiesMaleMiddle AgedNon-alcoholic Fatty Liver DiseaseObesityProspective StudiesRisk FactorsBlood GlucoseLipidsTriglyceridesAssociationBody mass indexFasting plasma glucoseInsulin resistanceNon-alcoholic fatty liver diseaseSecondary analysisTriglycerideTriglyceride glucose body mass index

Identifiers

PMID33109219
PMCPMC7592551
OpenAlexW3096400159

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.