Evidence map›Paper›PMID 41013277›Full record

ArticleBMC cardiovascular disorders2025

The additive effect of cardiopulmonary fitness and triglyceride-glucose index on the risk of metabolic syndrome.

Mengyi Li, Shiqi Wang, Hanbin Li, Wen Zhong, Hongxin Cheng, Quan Wei, Lu Wang

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mengyi Li *Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
Shiqi Wang *Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
Hanbin Li *Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
Wen ZhongRehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
Hongxin ChengRehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
Quan WeiRehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China. weiquan@scu.edu.cn.
Lu WangRehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, PR China. wanglu0823@scu.edu.cn.

Funding

China Postdoctoral Science Foundation 2023M732443National Key R&D Program of China 2023YFC3603800, 2023YFC3603801National Natural Science Foundation of China 82202793, 82172534, 82372574, 82202792Natural Science Foundation of Sichuan Province 2023NSFSC1494Noncommunicable Chronic Diseases-National Science and Technology Major Project 2024ZD0526000
6 · The paper itself

Abstract

backgroundMetabolic syndrome (MetS) is a cluster of risk factors including increased triglycerides, insulin resistance, and hypertension, posing increasing public health challenges. Both cardiorespiratory fitness (CRF) and the Triglyceride-Glucose (TyG) index have been associated with MetS risk independently. However, their combined predictive value remains unclear. This study aims to assess the combined influence of CRF and TyG index on MetS risk in a survey sample.

methodsData from 3742 participants in the National Health and Nutrition Examination Survey (NHANES) in year cycle of 1999-2004 were analyzed. Logistic regression and restricted cubic spline (RCS) analyses were used to evaluate the associations of CRF and TyG index with MetS risk. Subgroup analyses by different CRF, TyG, and disease conditions were conducted to explore interaction effects across different populations. Sensitivity analysis was implemented to verify the robustness of the results. Predictive value was assessed using net reclassification improvement (NRI), integrated discrimination improvement (IDI), and area under the curve (AUC) of receiver operating characteristic (ROC) curve.

resultsLogistic regression showed that impaired CRF was associated with a 73% higher risk of MetS (Odds Ratio (OR) 1.73; 95% Confidence Interval (CI), 1.23-2.42), while elevated TyG index was associated with a 6.84-fold increased risk (OR 6.84; 95% CI, 2.71-17.29). The combination of impaired CRF and high TyG index showed the highest risk of MetS (OR 11.99; 95% CI, 3.79-37.98). In sensitivity analysis, the results remained similar. Subgroup and interaction analyses further confirmed these findings, showing consistent results across demographic groups and under various analytical conditions. The combined use of CRF and TyG index significantly enhanced the predictive performance (AUC 0.871; 95% CI, 0.856-0.886) and improved model classification capabilities (NRI 0.393; 95% CI, 0.309-0.476; IDI 0.020; 95% CI, 0.014-0.025).

conclusionsThis study reveals that CRF and TyG index independently predict MetS risk, while their combination demonstrates superior predictive accuracy compared to using either parameter alone. These findings indicate that integrating both CRF and TyG into clinical practice may improve early detection and preventive strategies for MetS.

Indexed as

Blood GlucoseCardiorespiratory FitnessMetabolic SyndromeTriglyceridesAdultAgedBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedNutrition SurveysPredictive Value of TestsRisk AssessmentRisk FactorsBiomarkersBlood GlucoseTriglyceridesCardiorespiratory fitnessMetabolic syndromeNHANESTriglyceride-Glucose index

Identifiers

PMID41013277
PMCPMC12466076

What Socratic holds

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LicenceCC BY-NC-ND
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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.