To evaluate the associations between lipid-related metabolic indicators and incident type 2 diabetes mellitus (T2DM).
A diabetes family cohort study of 3,726 participants was conducted in Taizhou from May to October 2021 to track incident T2DM cases. Lipid metabolism indicators included triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride-glucose (TyG) and its related indices, Chinese Visceral Adiposity Index (CVAI), and homeostasis model assessment of insulin resistance (HOMA-IR). Mixed-effects Cox proportional hazards models, within-family Cox models, and quartile analyses were performed to examine the associations between these indicators and incident T2DM.
Among 1,257 participants without diabetes at baseline, 68 developed incident T2DM during the average follow-up of 3.92 years. Higher levels of TyG (HR = 1.758, 95% CI: 1.182–2.616), TyG-BMI (HR = 1.007, 95% CI: 1.002–1.013), TyG-WHtR (HR = 2.108, 95% CI: 1.468–3.027), TyG-WC (HR = 1.005, 95% CI: 1.003–1.007), CVAI (HR = 1.013, 95% CI: 1.006–1.020), and HOMA-IR (HR = 1.195, 95% CI: 1.038–1.376) were significantly associated with an increased risk of incident T2DM, whereas traditional lipid indicators showed no significant associations. These findings were consistent in within-family analyses. Furthermore, dose-response relationships were observed between TyG, TyG-WHtR, TyG-WC, CVAI and incident T2DM.
In conclusion, TyG-related indices, CVAI, and HOMA-IR were significantly associated with incident T2DM in this diabetes family-based cohort. These composite indicators may be useful for the early identification of high-risk individuals and for informing targeted prevention strategies.
Not applicable.
Haowei Li, Yilu Huang, Donghui Yang et al.· BMC Endocrine Disorders· 0 citations
Using period analysis, the most up-to-date 5-year RS for CC, EC, and OC in Taizhou, Eastern China is provided, and sustained survival improvements over the past 15 years for these cancers are found, providing epidemiological support for optimizing local gynecological cancer screening, treatment and targeted cancer control policies.