Abstract
Background
Insulin resistance is the central pathogenesis of metabolic syndrome. The ratio of triglyceride/high-density lipoprotein cholesterol, the metabolic score of insulin resistance, and the triglyceride glucose index in conjunction with body mass index have been verified as surrogate indices of insulin resistance and shown to be used in identifying the metabolic syndrome. Remnant cholesterol is a newly proposed indicator that potentially correlates with insulin resistance. The present study aims to explore the predictive value of the above 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 4 years’ follow-up, 761 participants developed metabolic syndrome. Logistic regression was used to analyze the association of the indexes with the occurrence of metabolic syndrome. The impact of dynamic changes in these indices on the metabolic syndrome was explored furthermore. The receiver operating characteristic curves was used to evaluate the predictive value. The restricted cubic spline was used to explore the presence of a nonlinear relationship between different indices and metabolic syndrome.
Results
The increase in the four insulin resistance indices is significantly associated with an increased risk of metabolic syndrome. Compared with the other three indices, TyG-BMI has a better predictive ability for the metabolic syndrome (AUC = 0.703). Participants with low-high and high-high variability patterns have an increased risk of metabolic syndrome compared with participants consistently low levels of the index during follow-up. For TG/HDL-c, the high-low pattern is also associated with a higher risk of developing metabolic syndrome. For TyG-BMI, METS-IR, and RC, the high-low pattern of change do not increase the risk of metabolic syndrome.
Conclusions
TyG-BMI could be a better index for predicting the occurrence of metabolic syndrome in middle-aged and elderly population. Dynamic variety of these indexes, including TG/HDL-c, METS-IR, TyG-BMI, and RC could predict the risk of the incidence of metabolic syndrome. Monitoring the dynamic changes in the above insulin resistance indices could contribute to prevent the occurrence of metabolic syndrome in middle-aged and elderly populations.