Evidence map›Paper›PMID 40883802›Full record

ArticleLipids in health and disease2025

Association between the metabolic score for insulin resistance trajectory and new-onset metabolic syndrome: a retrospective cohort study based on health check-up data in China.

Jianan Song, Su Yan, Youxiang Wang, Peimeng Zhu, Suying Ding, Jingfeng Chen

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In one paragraph

Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jianan SongHealth Management Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Su YanHenan Provincial Center for Disease Control and Prevention, Zhengzhou, Henan, 450052, China.
Youxiang WangHealth Management Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Peimeng ZhuHealth Management Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Suying DingHealth Management Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Jingfeng ChenHealth Management Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China. fccjfchen@zzu.edu.cn.ORCID http://orcid.org/0009-0005-2898-1490

Funding

China Postdoctoral Science Foundation 2022M722900Collaborative Innovation Project of Zhengzhou City XTCX2023006Henan Province Key Scientific Research Projects of Universities 25A320073Henan province science and technology research project 242102311099National Natural Science Foundation of China 72101236Nursing team project of the First Affiliated Hospital of Zhengzhou University HLKY2023005
6 · The paper itself

Abstract

backgroundThe Metabolic Score for Insulin Resistance (METS-IR) is a novel biomarker for evaluation of insulin resistance (IR). Emerging evidence suggests this metric may be able to predict the onset of metabolic syndrome (MetS). The aim of this study was to determine whether there is a correlation between sustained METS-IR values and the future risk of MetS.

methodsData for 3,750 individuals who attended a tertiary hospital in Zhengzhou for a health check-up between 2017 and 2022 were analyzed. The METS-IR was used to evaluate IR. A latent class trajectory model was created by dividing the subjects into high-stability and low-stability categories based on three consecutive years of data. The incidence of MetS between 2020 and 2022 was calculated using the Kaplan-Meier method and Cox regression modeling.

resultsOver a median follow-up of 2.13 years, we identified 430 cases of MetS (11.47%). The incidence rate was 35.48% in the high-stability group and 8.32% in the low-stability group (P < 0.001). Multivariate Cox regression, controlling for sex, age, hypertension status, diabetes status, and serum uric acid, low-density lipoprotein cholesterol, and gamma-glutamyl transferase levels, revealed that the risk of MetS was significantly higher in the high-stability group (hazard ratio [HR] = 4.77, 95% confidence interval [CI]: 3.714-6.126, P < 0.001). Stratified analysis by age showed that the risk of MetS was also significantly higher in individuals aged < 45 years (HR = 6.202, 95% CI: 4.312-8.921) and in those aged ≥ 45 years (HR = 3.89, 95% CI: 2.720-5.566) in the high-stability group. Receiver operating characteristic (ROC) curve analysis showed that the trajectory of METS-IR could predict MetS. The respective areas under the ROC curve for the 1-year, 2-year, and 3-year risk of MetS were 0.575, 0.641, and 0.628. Sensitivity analyses showed that an elevated METS-IR value was associated with an increased risk of new-onset MetS.

conclusionsIn this study, there was a significant correlation between the METS-IR value and the future risk of MetS. METS-IR measurement over time may allow early detection of individuals at high risk of MetS, which would lessen the impact of chronic disease.

Indexed as

Insulin ResistanceMetabolic SyndromeAdultBiomarkersChinaCholesterol, LDLFemalegamma-GlutamyltransferaseHumansIncidenceMaleMiddle AgedProportional Hazards ModelsRetrospective StudiesRisk FactorsUric AcidBiomarkersCholesterol, LDLgamma-GlutamyltransferaseUric AcidCohort studyInsulin resistanceMetabolic syndromeRisk factors

Identifiers

PMID40883802
PMCPMC12395968

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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.