Association of Triglyceride-Glucose-Frailty Index with Cardiovascular Disease and All-Cause Mortality Incidence in Individuals with Cardiovascular-Kidney-Metabolic Syndrome Stages 0–3: A Nationwide Prospective Cohort Study

Background: Both the triglyceride-glucose (TyG) index and frailty are associated with cardiovascular disease (CVD) incidence and all-cause mortality, yet the combined impact of the TyG-Frailty Index (TyGFI) remains insufficiently explored, particularly in individuals with cardiovascular-kidney-metabolic (CKM) syndrome stages 0–3. Methods: This study included middle-aged and elderly adults from the China Health and Retirement Longitudinal Study (CHARLS). The outcomes were the incidence of CVD and all-cause mortality. Multivariable Cox proportional hazards models, Kaplan–Meier curves, and restricted cubic spline (RCS) analyses were used to assess the association between TyGFI and the incidence of CVD and mortality. The predictive performance of different indices was compared using receiver operating characteristic (ROC) curves. Subgroup analyses were employed to assess the influence of different sociodemographic and clinical characteristics. Mediation analysis was conducted to evaluate whether age mediates the association between TyGFI and the outcomes. Results: This study included 6207 individuals for CVD and 6386 individuals for all-cause mortality in CKM syndrome stages 0–3. In the fully adjusted models, TyGFI was significantly associated with increased risks of CVD (HR = 1.25, 95% CI: 1.18–1.33) and all-cause mortality (HR = 1.39, 95% CI: 1.18–1.63). Participants in the highest TyGFI quartile faced more risk of CVD incidence (HR = 2.02, 95% CI: 1.69–2.42) and death (HR = 2.67, 95% CI: 1.33–5.38) compared to those in the lowest quartile. RCS analysis revealed a significant non-linear association between TyGFI and CVD and a linear association with all-cause death. ROC analysis indicated that TyGFI had the stronger predictive ability for CVD. Mediation analysis showed that age mediated the effect of TyGFI on both CVD occurrence (mediation proportion = 9.81%) and mortality (mediation proportion = 32.45%). Subgroup and sensitivity analyses confirmed the robustness of the findings. Conclusions: The findings suggest that TyGFI is a strong predictor of CVD risk and mortality in individuals with CKM syndrome stages 0–3, and age may serve as a mediating factor. These findings hold important clinical significance for enhancing the early identification and prevention of cardiovascular and fatal events in middle-aged and elderly populations.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2026-05-28
DOI
https://doi.org/10.3390/jcm15114156
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association of Triglyceride-Glucose-Frailty Index with Cardiovascular Disease and All-Cause Mortality Incidence in Individuals with Cardiovascular-Kidney-Metabolic Syndrome Stages 0–3: A Nationwide Prospective Cohort Study

Daoliang Zhang, Xingsheng Ye, Wenjie Peng, Miaomiao Yang et al.
Journal of Clinical Medicine
Diabetes, Cardiovascular Risks, and Lipoproteins
article

Association of Triglyceride-Glucose-Frailty Index with Cardiovascular Disease and All-Cause Mortality Incidence in Individuals with Cardiovascular-Kidney-Metabolic Syndrome Stages 0–3: A Nationwide Prospective Cohort Study

Daoliang Zhang, Xingsheng Ye, Wenjie Peng, Miaomiao Yang, Yuanqi Chen
article en

Abstract

Background: Both the triglyceride-glucose (TyG) index and frailty are associated with cardiovascular disease (CVD) incidence and all-cause mortality, yet the combined impact of the TyG-Frailty Index (TyGFI) remains insufficiently explored, particularly in individuals with cardiovascular-kidney-metabolic (CKM) syndrome stages 0–3. Methods: This study included middle-aged and elderly adults from the China Health and Retirement Longitudinal Study (CHARLS). The outcomes were the incidence of CVD and all-cause mortality. Multivariable Cox proportional hazards models, Kaplan–Meier curves, and restricted cubic spline (RCS) analyses were used to assess the association between TyGFI and the incidence of CVD and mortality. The predictive performance of different indices was compared using receiver operating characteristic (ROC) curves. Subgroup analyses were employed to assess the influence of different sociodemographic and clinical characteristics. Mediation analysis was conducted to evaluate whether age mediates the association between TyGFI and the outcomes. Results: This study included 6207 individuals for CVD and 6386 individuals for all-cause mortality in CKM syndrome stages 0–3. In the fully adjusted models, TyGFI was significantly associated with increased risks of CVD (HR = 1.25, 95% CI: 1.18–1.33) and all-cause mortality (HR = 1.39, 95% CI: 1.18–1.63). Participants in the highest TyGFI quartile faced more risk of CVD incidence (HR = 2.02, 95% CI: 1.69–2.42) and death (HR = 2.67, 95% CI: 1.33–5.38) compared to those in the lowest quartile. RCS analysis revealed a significant non-linear association between TyGFI and CVD and a linear association with all-cause death. ROC analysis indicated that TyGFI had the stronger predictive ability for CVD. Mediation analysis showed that age mediated the effect of TyGFI on both CVD occurrence (mediation proportion = 9.81%) and mortality (mediation proportion = 32.45%). Subgroup and sensitivity analyses confirmed the robustness of the findings. Conclusions: The findings suggest that TyGFI is a strong predictor of CVD risk and mortality in individuals with CKM syndrome stages 0–3, and age may serve as a mediating factor. These findings hold important clinical significance for enhancing the early identification and prevention of cardiovascular and fatal events in middle-aged and elderly populations.

Journal of Clinical MedicineVol. 15(11)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Twelfth Guangzhou City People's Hospital (CN), Fu Wai Hospital (CN)
Good health and well-being
Openalex Percentile: Top 6%
Diabetes, Cardiovascular Risks, and Lipoproteins
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.