Link between triglyceride-glucose-body mass index and future stroke risk in middle-aged and elderly chinese: a nationwide prospective cohort study

• Published in: Cardiovascular diabetology 2024-02, Vol.23 (1), p.81-81, Article 81
• Main Authors: Shao, Yuankai, Hu, Haofei, Li, Qiming, Cao, Changchun, Liu, Dehong, Han, Yong
• Format: Article
• Language: English
• Subjects: Age; Aged; Biomarkers; Blood Glucose; Blood pressure; Body Mass Index; China - epidemiology; Cholesterol; Chronic illnesses; Cohort analysis; Diabetes; Disease control; Disease prevention; Fatalities; Glucose; Health risks; Hemoglobin; High density lipoprotein; Humans; Hypertension; Insulin resistance; Interviews; Kidney diseases; Longitudinal Studies; Middle Aged; Missing data; Non-linear association; Older people; Prospective Studies; Questionnaires; Regression analysis; Risk Factors; Smooth curve fitting; Stroke; Stroke - diagnosis; Stroke - epidemiology; Triglyceride glucose-body mass index; Triglycerides; Variables
• ISSN: 1475-2840; 1475-2840
• DOI: 10.1186/s12933-024-02165-7

Current literature is deficient in robust evidence delineating the correlation between the triglyceride glucose-body mass index (TyG-BMI) and the incidence of stroke. Consequently, this investigation seeks to elucidate the potential link between TyG-BMI and stroke risk in a cohort of middle-aged and senior Chinese individuals. This study employs longitudinal data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, encompassing 8,698 participants. The CHARLS cohort was assembled using a multistage probability sampling technique. Participants underwent comprehensive evaluations through standardized questionnaires administered via face-to-face interviews. Our analytic strategy involved the application of Cox proportional hazards regression models to investigate the association between TyG-BMI and the risk of stroke. To discern potential non-linear relationships, we incorporated Cox proportional hazards regression with smooth curve fitting. Additionally, we executed a battery of sensitivity and subgroup analyses to validate the robustness of our findings. Our study utilized a multivariate Cox proportional hazards regression model and found a significant correlation between the TyG-BMI and the risk of stroke. Specifically, a 10-unit increase in TyG-BMI corresponded to a 4.9% heightened risk of stroke (HR = 1.049, 95% CI 1.029-1.069). The analysis also uncovered a non-linear pattern in this relationship, pinpointed by an inflection point at a TyG-BMI value of 174.63. To the left of this inflection point-meaning at lower TyG-BMI values-a 10-unit hike in TyG-BMI was linked to a more substantial 14.4% rise in stroke risk (HR 1.144; 95% CI 1.044-1.253). Conversely, to the right of the inflection point-at higher TyG-BMI values-each 10-unit increment was associated with a smaller, 3.8% increase in the risk of stroke (HR 1.038; 95% CI 1.016-1.061). In the middle-aged and elderly Chinese population, elevated TyG-BMI was significantly and positively associated with stroke risk. In addition, there was also a specific non-linear association between TyG-BMI and stroke (inflection point 174.63). Further reduction of TyG-BMI below 174.63 through lifestyle changes and dietary control can significantly reduce the risk of stroke.