Changes in the triglyceride glucose-body mass index estimate the risk of stroke in middle-aged and older Chinese adults: a nationwide prospective cohort study

Abstract

Abstract Background Stroke was reported to be highly correlated with the triglyceride glucose-body mass index (TyG-BMI). Nevertheless, literature exploring the association between changes in the TyG-BMI and stroke incidence is scant, with most studies focusing on individual values of the TyG-BMI. We aimed to investigate whether changes in the TyG-BMI were associated with stroke incidence. Methods Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), which is an ongoing nationally representative prospective cohort study. The exposures were changes in the TyG-BMI and cumulative TyG-BMI from 2012 to 2015. Changes in the TyG-BMI were classified using K-means clustering analysis, and the cumulative TyG-BMI was calculated as follows: (TyG-BMI2012 + TyG-BMI2015)/2 × time (2015–2012). Logistic regressions were used to determine the association between different TyG-BMI change classes and stroke incidence. Meanwhile, restricted cubic spline regression was applied to examine the potential nonlinear association of the cumulative TyG-BMI and stroke incidence. Weighted quantile sum regression was used to provide a comprehensive explanation of the TyG-BMI by calculating the weights of FBG, triglyceride-glucose (TG), and BMI. Results Of the 4583 participants (mean [SD] age at baseline, 58.68 [9.51] years), 2026 (44.9%) were men. During the 3 years of follow-up, 277 (6.0%) incident stroke cases were identified. After adjusting for potential confounders, compared to the participants with a consistently low TyG-BMI, the OR for a moderate TyG-BMI with a slow rising trend was 1.01 (95% CI 0.65–1.57), the OR for a high TyG-BMI with a slow rising trend was 1.62 (95% CI 1.11–2.32), and the OR for the highest TyG-BMI with a slow declining trend was 1.71 (95% CI 1.01–2.89). The association between the cumulative TyG-BMI and stroke risk was nonlinear (Passociation = 0.017; Pnonlinearity = 0.012). TG emerged as the primary contributor when the weights were assigned to the constituent elements of the TyG-BMI (weight2012 = 0.466; weight2015 = 0.530). Conclusions Substantial changes in the TyG-BMI are independently associated with the risk of stroke in middle-aged and older adults. Monitoring long-term changes in the TyG-BMI may assist with the early identification of individuals at high risk of stroke.