Evidence map›Paper›PMID 41219986›Full record

ArticleArchives of public health = Archives belges de sante publique2025

Improving cardiometabolic multimorbidity prediction with a composite obesity-TyG index: a study of middle-aged and older adults in CHARLS.

Yan Wang, Haonan Wang, Xinyao Liu, Junhui Zhang

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Article in Archives of public health = Archives belges de sante publique, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yan WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China.
Haonan WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China.
Xinyao LiuThe Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, P. R. China.
Junhui ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical University, No.1, Section 1, Xianglin Rd, Longmatan District, Luzhou, Sichuan, 646000, P. R. China. zjh960500@swmu.edu.cn.

Funding

General Project of Humanities and Social Sciences Research of the Ministry of Education (Planning Fund Project) Grant No. 24YJAZH217Sichuan Provincial Science and Technology Plan Key R&D Project Grant No. 2024YFFK0348
6 · The paper itself

Abstract

backgroundPrevious studies have demonstrated the importance of obesity and insulin resistance in increasing the risk of cardiovascular and metabolic diseases. However, few studies have demonstrated the association between visceral fat and cardiometabolic multimorbidity (CMM). In addition, the interaction of visceral fat and insulin resistance on CMM and the predictive value of the combination of the two remain incompletely understood.

objectiveThis study aims to investigate the relationships among novel obesity indices, the TyG index, and the CMM and to evaluate the predictive value of composite indices that combine obesity indices with the TyG index for CMM risk, thereby providing a basis for developing refined and multidimensional intervention strategies.

methodsWe used data from the China Health and Retirement Longitudinal Study (CHARLS), including baseline information collected in 2011 and follow-up data gathered in 2015 and 2018, which included 9162 participants. The associations between the obesity indices, TyG and CMM were investigated via Cox regression models, Kaplan-Meier curves, the MacKinnon product distribution method, interaction effect analyses, ROC analysis and related indicators (NRI, IDI).

resultsAmong the study population, 1530 participants (16.70%) developed CMM. Cox regression analysis indicated significant associations of obesity indices and the TyG index with CMM (P < 0.001). TyG mediated over 20% of the associations between obesity indices and CMM. The interaction effects between obesity indices and TyG on CMM were the most significant. The CVAI showed the best predictive performance among the obesity indices in this study, and the combination of obesity indices and the TyG index showed enhanced prediction performance for CMM (P < 0.001).

conclusionOur study demonstrated that the composite index constructed by combining novel obesity indices with TyG significantly improved the accuracy of predicting CMM risk in middle-aged and elderly individuals, underscoring the critical role of maintaining a healthy weight and enhancing insulin sensitivity in the prevention of CMM.

Indexed as

Cardiometabolic multimorbidityInsulin resistanceObesity indicesType 2 diabetes

Identifiers

PMID41219986
PMCPMC12606983

What Socratic holds

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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.