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. 2025 Aug 4;24(1):318.
doi: 10.1186/s12933-025-02880-9.

Predictive value of the combined triglyceride-glucose and frailty index for cardiovascular disease and stroke in two prospective cohorts

Yi-Chang Zhao #  1   2   3   4 , Shi-Qi Wu #  1   2   3   4 , Jia-Kai Li  1   2   3   4 , Zhi-Hua Sun  1   2   5   4 , Bi-Kui Zhang  1   2   3   4 , Rao Fu  1   2   3   4 , Miao Yan  6   7   8   9
Affiliations

Predictive value of the combined triglyceride-glucose and frailty index for cardiovascular disease and stroke in two prospective cohorts

Yi-Chang Zhao et al. Cardiovasc Diabetol. .

Abstract

Background: The triglyceride-glucose (TyG) index is a validated surrogate for insulin resistance, while frailty reflects cumulative physiological decline. The combined impact of TyG-Frailty Index (TyGFI) has not been adequately explored. This study aimed to investigate the association between TyGFI and the risk of cardiovascular disease (CVD) and stroke.

Methods: A total of 5448 participants from the China Health and Retirement Longitudinal Study (CHARLS) and 1139 participants from the U.S. National Health and Nutrition Examination Survey (NHANES) were included. Multivariable logistic regression models were used to estimate associations with CVD and stroke, adjusting for demographic, clinical, and lifestyle covariates. Restricted cubic spline (RCS) and subgroup analyses were employed to examine dose-response relationships and interaction effects.

Results: Higher TyGFI levels were associated with older age, adverse metabolic parameters, and increased prevalence of hypertension, diabetes, and dyslipidemia. In fully adjusted models, the highest TyGFI quartile was significantly associated with increased risks of CVD (CHARLS: OR 15.09, 95% CI 9.65-23.60; NHANES: OR 4.98, 95% CI 2.04-12.19) and stroke (CHARLS: OR 21.12, 95% CI 6.44-69.23; NHANES: OR 12.98, 95% CI 2.58-65.17), with consistent dose-response trends confirmed by RCS analyses. Subgroup analyses further demonstrated the robustness of these associations across diverse demographic and clinical strata.

Conclusions: TyGFI is a strong and independent predictor of CVD and stroke in two nationally representative cohorts. By integrating metabolic and functional risk dimensions, TyGFI provides a more comprehensive risk stratification tool, with significant implications for early identification and prevention of cardiovascular events in aging populations.

Keywords: Cardiovascular disease; Frailty index; Population-based cohort; Stroke; Triglyceride-glucose index.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The China Health and Retirement Longitudinal Study was approved by the Ethics Review Committee of Peking University. The National Health and Nutrition Examination Survey were approved by the National Center for Health Statistics ethics review board. Written informed consent was obtained from all participants. Informed consent was obtained from each subject in these two cohorts. Consent for publication: This manuscript is not currently under consideration for publication elsewhere, and the work reported will not be submitted for publication elsewhere until a final decision has been made as to its acceptability by the journal. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flow diagram of participant selection from the CHARLS and NHANES cohorts. This figure illustrates the stepwise selection of study participants from the 2011 wave of the CHARLS and from the 2001–2011 cycles of the U.S. NHANES. Participants were excluded if they were younger than 45 years, had a history of stroke or CVD, or had missing values for serum triglyceride or glucose. The final eligible samples in each cohort were then divided into four groups (Quartiles 1–4) based on the distribution of the variable of interest (e.g., TyG index). The numbers shown under each box represent the sample size remaining at each stage of inclusion and exclusion
Fig. 2
Fig. 2
Multivariable logistic regression results and restricted cubic spline curves of the association between TyG-FI and CVD risk in the CHARLS and NHANES cohorts. A A forest plot from the CHARLS cohort showing the results of multivariable logistic regression analyses for CVD as the outcome. It displays the adjusted OR, 95% CI, and p-values across four different models. B A forest plot from the NHANES cohort showing the results of multivariable logistic regression analyses for CVD as the outcome. It similarly displays the OR, 95% CI, and p-values across four different models. C A dose–response curve from the CHARLS cohort based on RCS analysis, illustrating the relationship between TyG-FI and CVD risk. The shaded area represents the 95% confidence interval. D A dose–response curve from the NHANES cohort based on RCS analysis, illustrating the relationship between TyG-FI and CVD risk. The shaded area represents the 95% confidence interval
Fig. 3
Fig. 3
Multivariable logistic regression results and restricted cubic spline curves of the association between TyG-FI and stroke risk in the CHARLS and NHANES cohorts. A A forest plot from the CHARLS cohort showing the results of multivariable logistic regression analyses for stroke as the outcome. It displays the adjusted OR, 95% CI, and p-values across four different models. B A forest plot from the NHANES cohort showing the results of multivariable logistic regression analyses for stroke as the outcome. It similarly displays the OR, 95% CI, and p-values across four different models. C A dose–response curve from the CHARLS cohort based on RCS analysis, illustrating the relationship between TyG-FI and stroke risk. The shaded area represents the 95% confidence interval. D A dose–response curve from the NHANES cohort based on RCS analysis, illustrating the relationship between TyG-FI and stroke risk. The shaded area represents the 95% CI
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