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Background <p>Previous 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.</p> Objective <p>This 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.</p> Methods <p>We 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).</p> Results <p>Among the study population, 1530 participants (16.70%) developed CMM. Cox regression analysis indicated significant associations of obesity indices and the TyG index with CMM (<i>P</i> &lt; 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 (<i>P</i> &lt; 0.001).</p> Conclusion <p>Our 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.</p>

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

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  • 发表日期：

    2025年11月12日

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  • Yan Wang,
  • Haonan Wang,
  • Xinyao Liu,
  • Junhui Zhang

摘要

Background

Previous 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.

Objective

This 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.

Methods

We 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).

Results

Among 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).

Conclusion

Our 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.