The Relationship Between Dynamic Changes in the Insulin Resistance-Related Indices and Metabolic Syndrome in Middle-Aged and Elderly Population.

Background: Insulin resistance is the central pathogenesis of metabolic syndrome. Insulin resistance-related indices have been shown to identify the metabolic syndrome. The present study aims to explore the predictive value of four insulin resistance-related indices for the metabolic syndrome and the association between dynamic changes in these indices and the metabolic syndrome. Methods: 3,526 participants aged ≥ 45 years were enrolled from the China Health and Retirement Dynamic Study. After a 4-year follow-up, 761 participants developed metabolic syndrome. The receiver operating characteristic curve was used to evaluate the predictive value. The restricted cubic spline was used to explore the presence of a nonlinear relationship between indices and metabolic syndrome. Logistic regression was used to analyze the dynamic changes in insulin resistance indices in the metabolic syndrome. Results: TyG-BMI and Mets-IR have larger AUC. TyG-BMI, TG/HDL-c, and Mets-IR exhibit a nonlinear association with the metabolic syndrome. Participants with low-high and high-high variability patterns have an increased risk of metabolic syndrome. For TG/HDL-c, the high-low pattern is also associated with a higher risk of developing metabolic syndrome. Conclusions: TyG-BMI and Mets-IR could be better indices for predicting metabolic syndrome in middle-aged and elderly populations. For individuals with indices below the cutoff points, it is advisable to avoid an increase in IR-related indices to prevent metabolic syndrome. A dynamic variety of insulin resistance-related indices could predict a higher risk of the incidence of metabolic syndrome.