Association between the cumulative average triglyceride glucose-body mass index and cardiovascular disease incidence among the middle-aged and older population: a prospective nationwide cohort study in China

医学 体质指数 累积发病率 内科学 逻辑回归 入射(几何) 风险因素 人口 队列研究 人口学 队列 环境卫生 物理 社会学 光学
作者
Fadong Li,Li Wang,Boqun Shi,Shuaifeng Sun,Shen Wang,Shuo Pang,Xiaofan Wu
出处
期刊:Cardiovascular Diabetology [Springer Nature]
卷期号:23 (1) 被引量:6
标识
DOI:10.1186/s12933-023-02114-w
摘要

Abstract Background Findings from earlier research have established that insulin resistance (IR) is implicated in atherosclerosis progression, representing a noteworthy risk factor for cardiovascular disease (CVD). Recently, the triglyceride glucose-body mass index (TyG-BMI) has been introduced as a straightforward and robust alternative indicator for early detection of IR. Nevertheless, there is a scarcity of studies that have examined the capability of TyG-BMI for predicting incident CVD. Consequently, the core objective of this study was to determine whether the cumulative average TyG-BMI correlated with CVD incidence. Methods All data was sourced from the China Health and Retirement Longitudinal Study (CHARLS). The exposure was the cumulative average TyG-BMI, determined by the average of TyG-BMI values for the baseline and follow-up investigations (Wave 1 in 2011, Wave 3 in 2015, respectively). The calculation of TyG-BMI involved a combination of triglyceride, fasting blood glucose, and body mass index. The primary outcome was incident CVD. Logistic regression analyses as well as restricted cubic spline (RCS) regression analyses were performed for examining the association between the cumulative average TyG-BMI and CVD incidence. Results In all, 5,418 participants were enrolled in our analysis, with 2,904 (53.6%) being female, and a mean (standard deviation, SD) age of 59.6 (8.8) years. The mean (SD) cumulative average TyG-BMI among all participants was 204.9 (35.7). Totally, during a 4-year follow-up, 543 (10.0%) participants developed CVD. The fully adjusted logistic regression analysis revealed a significant association between the cumulative average TyG-BMI and incident CVD [odds ratio (OR), 95% confidence interval (CI): 1.168, 1.040–1.310, per 1 SD increase]. The RCS regression analysis displayed a positive, linear association of the cumulative average TyG-BMI with CVD incidence (P for overall = 0.038, P for nonlinear = 0.436). Conclusions Our study revealed a noteworthy correlation between the cumulative average TyG-BMI and incident CVD among the middle-aged and older population. The cumulative average TyG-BMI emerges as a valuable tool that may enhance the primary prevention and treatment of CVD.
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