Assessing the impact of insulin resistance trajectories on cardiovascular disease risk using longitudinal targeted maximum likelihood estimation

作者：Yaning Feng, Liangying Yin, Haoran Huang, Yongheng Hu, Sitong Lin · 发表于：Cardiovascular Diabetology · 年份：2025 · DOI：10.1186/s12933-025-02651-6 · 被引用次数：19 · 研究领域：Diabetes, Cardiovascular Risks, and Lipoproteins、Advanced Causal Inference Techniques、Nutritional Studies and Diet

BACKGROUND: Cardiovascular disease (CVD) is closely associated with Insulin Resistance (IR). However, there is limited research on the relationship between trajectories of IR and CVD incidence, considering both time-invariant and time-varying confounders. We employed advanced causal inference methods to evaluate the longitudinal impact of IR trajectories on CVD risk. METHODS: The data for this study were extracted from a Chinese nationwide cohort, named China Health and Retirement Longitudinal Study (CHARLS). Triglyceride-glucose (TyG) index and TyG body mass index (BMI) were used as surrogate markers for IR, and their changes were recorded as exposures. Longitudinal targeted maximum likelihood estimation (LTMLE) was used to study how dynamic shifts in IR trajectories (i.e., increase, decrease, etc.) influence long-term CVD risk, adjusting for both time-invariant and time-varying confounders. RESULTS: A total of 3,966 participants were included in the analysis, with 2,152 (54.3%) being female. The average age at baseline was 58.28 years. Over the course of a 7-year follow-up period, 499 (12.6%) participants developed CVD. Four distinct trajectories of TyG index and TyG-BMI were identified: low stable, increasing, decreasing, and high stable. LTMLE analyses revealed individuals in the 'high stable' and 'increasing' groups had a significantly higher risk of developing CVD compared to those in the 'low stable' group, while the 'decreasing' group showed no significant differences...