Combined effect of triglyceride glucose-body mass index and hypertension on new-onset stroke: evidence from the China health and retirement longitudinal study

Objective: The aim of this study is to investigate the combined impact of the triglyceride glucose-body mass index (TyG-BMI) and hypertension on the risk of stroke among the middle-aged and older adult population in China.

Methods: This study included 6,922 participants aged 45 and above from the China Health and Retirement Longitudinal Study, utilizing a multivariate Cox proportional hazards regression model to explore the relationship between TyG-BMI, hypertension, and the incidence of new-onset stroke events, as well as conducting Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) analyses to evaluate the predictive utility of TyG-BMI.

Results: During a 7-year follow-up period, a total of 401 stroke events were recorded. Compared to patients with lower TyG-BMI (TyG-BMI < 199.74) levels and non-hypertension, those with elevated TyG-BMI levels and non-hypertension had an adjusted hazard ratio (HR) and 95% confidence intervals (95%CI) were 1.47 (1.05-2.05). The adjusted HR and 95%CI for the group with lower TyG-BMI levels and hypertension was 2.99 (2.17-4.12), and for those with elevated TyG-BMI levels and hypertension, the adjusted HR and 95%CI was 3.49 (2.63-4.62). In a multivariate Cox proportional hazards regression model, the combination of elevated TyG-BMI levels and hypertension, treated as routine variables, was still significantly associated with the risk of stroke. NRI and IDI analyses showed significant improvements in risk prediction with the inclusion of TyG-BMI. Furthermore, in all subgroup analyses conducted, individuals with elevated TyG-BMI levels and hypertension nearly exhibited the highest risk for incident stroke.

Conclusion: Our study reveals that the combined effect of TyG-BMI and hypertension may increase the risk of incident stroke in the middle-aged and older adult Chinese population. TyG-BMI correlates with comorbid conditions and enhances traditional risk assessment. Future research will require validation through larger sample sizes or diverse populations to further confirm this finding.