1. Trajectory patterns of metabolic syndrome severity score and risk of type 2 diabetes
- Author
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Atieh Amouzegar, Mohammadjavad Honarvar, Safdar Masoumi, Davood Khalili, Fereidoun Azizi, and Ladan Mehran
- Subjects
Diabetes ,Metabolic syndrome ,Risk ,Trajectory ,Growth mixture model ,Cardio metabolic risk factors ,Medicine - Abstract
Abstract Background The available evidence indicates that the severity of metabolic syndrome tends to worsen progressively over time. We assessed the trajectory of age and sex-specific continuous MetS severity score (cMetS-S) and its association with the development of diabetes during an 18-year follow-up. Methods In a prospective population-based Tehran Lipid and Glucose Study, 3931 eligible participants free of diabetes, aged 20–60 years, were followed at three-year intervals. We examined the trajectories of cMetS-S over nine years using latent growth mixture modeling (LGMM) and subsequent risks of incident diabetes eight years later. The prospective association of identified trajectories with diabetes was examined using the Cox proportional hazard model adjusting for age, sex, education, and family history of diabetes, physical activity, obesity (BMI ≥ 30 kg/m2), antihypertensive and lipid-lowering medication, and baseline fasting plasma glucose in a stepwise manner. Results Among 3931 participants, three cMetS-S trajectory groups of low (24.1%), medium (46.8%), and high (29.1%) were identified during the exposure period. Participants in the medium and high cMetS-S trajectory classes had HRs of 2.44 (95% CI: 1.56–3.81) and 6.81 (95% CI: 4.07–10.01) for future diabetes in fully adjusted models, respectively. Normoglycemic individuals within the high cMetS-S class had an over seven-fold increased risk of diabetes (HR: 7.12; 95% CI: 6.05–12.52). Conclusion Although most adults exhibit an unhealthy metabolic score, its severity usually remains stable throughout adulthood over ten years of follow-up. The severity score of metabolic syndrome has the potential to be utilized as a comprehensive and easily measurable indicator of cardiometabolic dysfunction. It can be employed in clinical settings to detect and track individuals at a heightened risk of developing T2DM, even if their glucose levels are normal.
- Published
- 2023
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