Association between the triglyceride-glucose index and silent myocardial infarction in the general population
Abstract
Abstract This study aimed to explore the relationship between the triglyceride-glucose (TyG) index and silent myocardial infarction (SMI) in the general population, with a focus on elucidating potential links and contributing to the understanding of risk factors for undetected cardiac events. This prospective cohort study was carried out within a community-based population, using data from the Atherosclerosis Risk in Communities study in the United States. The dataset included information on demographics, cardiovascular risk factors, blood lipids, liver and kidney function, and other variables. Participants were categorized into four quartiles based on their TyG index scores. Cox regression analysis was used to examine the relationship between the different ranges of TyG indices and SMI. In total, 14,211 community residents were enrolled and followed up for 36 years. Among them, 7,316 (51.48%) developed SMI. TyG index measurements were divided into quartiles: Q1 (≤ 8.26), Q2 (8.26–8.62), Q3 (8.62–9.02), and Q4 (≥ 9.02). Restricted cubic spline curves indicated that higher TyG indices correlated with a greater risk of SMI. Results of the Kaplan–Meier analysis suggested that participants with a higher TyG index had a lower cumulative survival rate for SMI (P < 0.001). Through multivariate Cox regression analysis, the TyG index was identified as an independent predictor of SMI risk (P < 0.001). Further stratified analyses reinforced the link between the TyG index and the risk of SMI, demonstrating its consistent influence across diverse population subsets. Mediation analysis revealed significant effects of hypertension, diabetes, body mass index and sex on SMI risk. The overall effect sizes ranged from 1.77 to 1.95, with direct effects accounting for 52.7–99.6% and mediation effects ranging from 0.4 to 47.3%. In the general population, the TyG index as an independent predictor of SMI risk, emphasizing its importance in cardiovascular disease assessment.
Article Details
Authors (11)
Min Dai
Dongze Li
Jing Yu
Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
Yi Liu
Qin Zhang
State Key Laboratory of Chemo and Biosensing, College of Biology, College of Chemistry and Chemical Engineering
Wei Zhang
Yan Zhong
Zhi Wan
Menglin Tang
Yongli Gao
Li Rao
Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction, Ministry of Education, College of Chemistry, Central China Normal University, 152 Luoyu Road, Wuhan 430079, P. R. China