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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

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Shou-lin Wu

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Open access Jul 2026

Cumulative triglyceride-glucose-body mass index exposure and cardiovascular disease risk: findings from the Kailuan study

Background The relationship between cumulative triglyceride-glucose-body mass index (TyG-BMI) exposure and the risk of cardiovascular disease (CVD) has been unclear. This study investigated the association between cumulative TyG-BMI exposure and the risk of CVD in the Chinese population using data from the large-scale, prospective community-based Kailuan Study. Methods The Kailuan Study included 47,577 individuals without a history of CVD or cancer who underwent health examinations in 2006, 2008, and 2010. Cumulative TyG-BMI exposure was calculated as the weighted sum of the mean TyG-BMI for each time interval (value × time). Participants were stratified into four groups based on the cumulative TyG-BMI exposure quartile. Cox proportional hazards regression models were established to calculate hazard ratios and 95% confidence intervals for evaluation of the relationship between cumulative TyG-BMI exposure and risk of CVD. The area under the receiver operating characteristic (ROC) curve was calculated to compare the predictive power of cumulative TyG-BMI, TyG, and BMI for CVD. Results A total of 3,514 incident cardiovascular events occurred during a median follow-up of 10 years. The risk of CVD increased with increasing cumulative TyG-BMI exposure quartile. After adjusting for potential confounders, Cox regression analysis yielded respective hazard ratios (95% confidence intervals) of 1.32 (1.18–1.49), 1.33 (1.18–1.49), and 1.44 (1.29–1.62) for the Q2, Q3, and Q4 groups in comparison with the Q1 group. The subgroup analysis showed a significant interaction between cumulative TyG-BMI index and age or hypertension, but there was no interaction between sex, Diabetes mellitus and cumulative TyG-BMI index. The restricted cubic spline analysis revealed a significant non-linear relationship between cumulative TyG-BMI index and the risk of CVD. The area under the ROC curve (AUC) of cumulative TyG-BMI was 0.6047, demonstrating modestly higher discriminative performance than TyG (AUC: 0.5602) and BMI (AUC: 0.5612). Conclusions High cumulative TyG-BMI exposure is associated with an increased risk of CVD. The TyG-BMI value may help to identify individuals at high risk of developing CVD.

Peng Fu, Yuxian Wang, Kuangyi Wu et al. · 0 citations
Open access Aug 2026

Cumulative lipid–inflammatory indices and the risk of cardiometabolic multimorbidity: a prospective cohort study

Background Cardiometabolic multimorbidity (CMM) has become a major global public health challenge. Although dyslipidemia and chronic low-grade inflammation are known to contribute to cardiometabolic diseases, their long-term cumulative combined effects on the risk of CMM remain poorly understood. This study aimed to evaluate the associations of cumulative lipid-inflammatory indices with incident CMM in a large prospective cohort. Methods A total of 25,376 participants from the Kailuan cohort were included and followed up until December 31, 2023. Nine cumulative lipid-inflammatory exposure indices were constructed via trapezoidal area-under-the-curve calculation using repeated measurements from 2006 to 2010. The primary outcome was incident CMM, defined as the concurrence of at least two cardiometabolic diseases including type 2 diabetes, ischemic heart disease and stroke. Multivariable Cox regression, restricted cubic spline analyses, competing-risk models, and subgroup analyses were applied. Results During a median follow-up of 13.0 years, 481 incident CMM events were documented. All nine cumulative lipid-inflammatory indices were independently and positively associated with an elevated risk of CMM in a dose-response manner. Incorporating these indices into conventional risk model improved risk reclassification and discriminatory ability. Conclusions Elevated cumulative lipid-inflammatory indices are associated with a higher risk of incident CMM. These composite markers may serve as auxiliary indicators for preliminary risk stratification, while causal relationships cannot be confirmed based on this observational cohort alone.

Li-Jun Meng, Haibo Gao, Jing Yang et al. · 0 citations