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Background <p>The composite indicator (TyG-CVAI), constructed by combining the triglyceride-glucose index and the Chinese visceral adiposity index, can quantify the combined pathogenic effects of insulin resistance and visceral obesity. However, an in-depth exploration of the long-term longitudinal evolution trajectories, cumulative exposure burden of TyG-CVAI, and its nonlinear association with the risk of cardiovascular disease (CVD) subtypes is still lacking. This study aims to prospectively evaluate the dynamic evolution pattern of TyG-CVAI and its predictive value for incident CVD, stroke, and heart disease.</p> Methods <p>Based on the Kailuan prospective cohort, this study included 32,841 participants without CVD prior to the 2012 baseline. Using data from four repeated measurements between 2006 and 2012, the longitudinal evolution trajectories of TyG-CVAI were identified through the K-means clustering algorithm, and its cumulative exposure burden (cumTyG-CVAI) was calculated. Multivariable Cox proportional hazards regression models were utilized to evaluate its association with incident CVD and its subtypes after 2012, and its dose-response relationship and predictive accuracy were assessed using restricted cubic splines (RCS) and receiver operating characteristic (ROC) curves.</p> Results <p>During a median follow-up of 6.9 years, a total of 3,212 incident CVD events were recorded. Longitudinal analysis identified three distinct evolutionary trajectories: low, moderate, and high. After fully adjusting for confounding factors, compared with the low trajectory group, the high trajectory group faced the highest risk of incident total CVD (HR 1.837, 95% CI 1.588–2.126), stroke (HR 1.919, 95% CI 1.672–2.203), and heart disease (HR 2.260, 95% CI 1.827–2.796). For each standard deviation (SD) increase in cumulative TyG-CVAI, the risks of the aforementioned outcomes significantly increased by 29.2%–34.1%, respectively. RCS analysis showed that TyG-CVAI was positively and linearly correlated with the risk of stroke, while exhibiting a significant nonlinear threshold effect with the risks of total CVD (cumulative inflection point: 4683.98) and heart disease (cumulative inflection point: 4828.73). ROC analysis confirmed that the cumulative TyG-CVAI (AUC: 0.624–0.655) provided incremental improvements in predictive performance compared with single baseline measurements and traditional single or composite metabolic indices (all <i>P</i> &lt; 0.05).</p> Conclusions <p>The dynamic elevation of TyG-CVAI and its long-term cumulative burden are independent predictors of incident CVD, stroke, and heart disease. Compared to single baseline assessments and traditional static indicators, cumulative TyG-CVAI demonstrates improved risk stratification value for cardiovascular risk, highlighting the clinical utility of integrating longitudinal metabolic monitoring into routine cardiovascular screening. Furthermore, this index shows a nonlinear threshold effect with heart disease and a linear correlation with stroke, highlighting the clinical value of integrating longitudinal metabolic monitoring into routine cardiovascular stratification to achieve precise prevention.</p>

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Trajectories, cumulative burden of the dynamic triglyceride glucose-Chinese visceral adiposity index, and risk of incident cardiovascular diseases: a large prospective cohort study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月30日

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  • Ao Men Lu,
  • Qian Xu,
  • Yun Tao Wu

摘要

Background

The composite indicator (TyG-CVAI), constructed by combining the triglyceride-glucose index and the Chinese visceral adiposity index, can quantify the combined pathogenic effects of insulin resistance and visceral obesity. However, an in-depth exploration of the long-term longitudinal evolution trajectories, cumulative exposure burden of TyG-CVAI, and its nonlinear association with the risk of cardiovascular disease (CVD) subtypes is still lacking. This study aims to prospectively evaluate the dynamic evolution pattern of TyG-CVAI and its predictive value for incident CVD, stroke, and heart disease.

Methods

Based on the Kailuan prospective cohort, this study included 32,841 participants without CVD prior to the 2012 baseline. Using data from four repeated measurements between 2006 and 2012, the longitudinal evolution trajectories of TyG-CVAI were identified through the K-means clustering algorithm, and its cumulative exposure burden (cumTyG-CVAI) was calculated. Multivariable Cox proportional hazards regression models were utilized to evaluate its association with incident CVD and its subtypes after 2012, and its dose-response relationship and predictive accuracy were assessed using restricted cubic splines (RCS) and receiver operating characteristic (ROC) curves.

Results

During a median follow-up of 6.9 years, a total of 3,212 incident CVD events were recorded. Longitudinal analysis identified three distinct evolutionary trajectories: low, moderate, and high. After fully adjusting for confounding factors, compared with the low trajectory group, the high trajectory group faced the highest risk of incident total CVD (HR 1.837, 95% CI 1.588–2.126), stroke (HR 1.919, 95% CI 1.672–2.203), and heart disease (HR 2.260, 95% CI 1.827–2.796). For each standard deviation (SD) increase in cumulative TyG-CVAI, the risks of the aforementioned outcomes significantly increased by 29.2%–34.1%, respectively. RCS analysis showed that TyG-CVAI was positively and linearly correlated with the risk of stroke, while exhibiting a significant nonlinear threshold effect with the risks of total CVD (cumulative inflection point: 4683.98) and heart disease (cumulative inflection point: 4828.73). ROC analysis confirmed that the cumulative TyG-CVAI (AUC: 0.624–0.655) provided incremental improvements in predictive performance compared with single baseline measurements and traditional single or composite metabolic indices (all P < 0.05).

Conclusions

The dynamic elevation of TyG-CVAI and its long-term cumulative burden are independent predictors of incident CVD, stroke, and heart disease. Compared to single baseline assessments and traditional static indicators, cumulative TyG-CVAI demonstrates improved risk stratification value for cardiovascular risk, highlighting the clinical utility of integrating longitudinal metabolic monitoring into routine cardiovascular screening. Furthermore, this index shows a nonlinear threshold effect with heart disease and a linear correlation with stroke, highlighting the clinical value of integrating longitudinal metabolic monitoring into routine cardiovascular stratification to achieve precise prevention.