Triglyceride–glucose body roundness index and risks of incident cardiovascular disease and cardiometabolic multimorbidity: evidence from prospective cohorts in China and England

Cardiovascular disease (CVD) and cardiometabolic multimorbidity (CMM) impose substantial health burdens. The triglyceride–glucose body roundness index (TyG-BRI) integrates metabolic dysfunction reflected by TyG with body-shape information reflected by BRI, but its associations with incident CVD and CMM and its comparative predictive performance across populations remain uncertain. We included 8,747 participants free of CVD or CMM at baseline, comprising 6,496 from CHARLS and 2,251 from ELSA. TyG-BRI was evaluated continuously and by quartiles. Among 5,721 participants with two measurements, K-means clustering identified low, intermediate, and high two-wave level groups. Cohort-stratified Cox models and restricted cubic splines assessed associations. Four-year Cox models developed in CHARLS were externally evaluated in ELSA and compared with models incorporating TyG, BRI, TyG-BMI, or TyG-WC. Competing-risk and sensitivity analyses assessed robustness. During follow-up, 1,401 participants developed CVD and 1,151 developed CMM. Compared with the lowest TyG-BRI quartile, the highest quartile was associated with higher risks of CVD (HR, 1.666; 95% CI, 1.424–1.949) and CMM (HR, 3.958; 95% CI, 3.260–4.805). Corresponding HRs comparing the high with the low two-wave level group were 1.678 (95% CI, 1.400–2.011) and 3.354 (95% CI, 2.765–4.070). The association was approximately linear for CVD but nonlinear for CMM and was stronger for CMM among participants aged < 60 years after multiple-testing correction. Findings were generally consistent in competing-risk and sensitivity analyses. In ELSA, TyG-BRI had modest discrimination for CVD (AUC, 0.598) and better discrimination for CMM (AUC, 0.701). For CMM, it improved discrimination over the Base model and BRI, although TyG-WC had the highest AUC. Updating the baseline hazard substantially improved calibration. Higher TyG-BRI was associated with incident CVD and, more strongly, CMM across baseline and repeated assessments. TyG-BRI may provide complementary information on cardiometabolic risk but remains a candidate marker requiring further population-specific validation and recalibration.

Authors

Institutions

Publication Details

Journal
BMC Cardiovascular Disorders
Published
2026-09-21
DOI
https://doi.org/10.1186/s12872-026-06681-0
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
article

Triglyceride–glucose body roundness index and risks of incident cardiovascular disease and cardiometabolic multimorbidity: evidence from prospective cohorts in China and England

Tianyu She, Jingru Bi, Wenxin Li, Yilin Pan
BMC Cardiovascular Disorders
Diabetes, Cardiovascular Risks, and Lipoproteins
article

Triglyceride–glucose body roundness index and risks of incident cardiovascular disease and cardiometabolic multimorbidity: evidence from prospective cohorts in China and England

Tianyu She, Jingru Bi, Wenxin Li, Yilin Pan
article en

Abstract

Cardiovascular disease (CVD) and cardiometabolic multimorbidity (CMM) impose substantial health burdens. The triglyceride–glucose body roundness index (TyG-BRI) integrates metabolic dysfunction reflected by TyG with body-shape information reflected by BRI, but its associations with incident CVD and CMM and its comparative predictive performance across populations remain uncertain. We included 8,747 participants free of CVD or CMM at baseline, comprising 6,496 from CHARLS and 2,251 from ELSA. TyG-BRI was evaluated continuously and by quartiles. Among 5,721 participants with two measurements, K-means clustering identified low, intermediate, and high two-wave level groups. Cohort-stratified Cox models and restricted cubic splines assessed associations. Four-year Cox models developed in CHARLS were externally evaluated in ELSA and compared with models incorporating TyG, BRI, TyG-BMI, or TyG-WC. Competing-risk and sensitivity analyses assessed robustness. During follow-up, 1,401 participants developed CVD and 1,151 developed CMM. Compared with the lowest TyG-BRI quartile, the highest quartile was associated with higher risks of CVD (HR, 1.666; 95% CI, 1.424–1.949) and CMM (HR, 3.958; 95% CI, 3.260–4.805). Corresponding HRs comparing the high with the low two-wave level group were 1.678 (95% CI, 1.400–2.011) and 3.354 (95% CI, 2.765–4.070). The association was approximately linear for CVD but nonlinear for CMM and was stronger for CMM among participants aged < 60 years after multiple-testing correction. Findings were generally consistent in competing-risk and sensitivity analyses. In ELSA, TyG-BRI had modest discrimination for CVD (AUC, 0.598) and better discrimination for CMM (AUC, 0.701). For CMM, it improved discrimination over the Base model and BRI, although TyG-WC had the highest AUC. Updating the baseline hazard substantially improved calibration. Higher TyG-BRI was associated with incident CVD and, more strongly, CMM across baseline and repeated assessments. TyG-BRI may provide complementary information on cardiometabolic risk but remains a candidate marker requiring further population-specific validation and recalibration.

BMC Cardiovascular Disorders
Capital Medical University (CN), Nankai University (CN), Chinese PLA General Hospital (CN), Integrated Chinese Medicine (China) (CN), Beijing Anzhen Hospital (CN)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 11%
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.