# The Relationship Between Dynamic Changes in the Insulin Resistance–Related Indices and Metabolic Syndrome in Middle‐Aged and Elderly Population

## TL;DR

This study examines how changes in insulin resistance indices predict metabolic syndrome in middle-aged and elderly people.

## Contribution

The study identifies TyG–BMI and Mets-IR as better predictors of metabolic syndrome and highlights the importance of dynamic changes in these indices.

## Key findings

- TyG–BMI and Mets-IR showed larger predictive value for metabolic syndrome.
- Nonlinear associations were found between TyG–BMI, TG/HDL-c, and Mets-IR with metabolic syndrome.
- High variability patterns in insulin resistance indices increase the risk of metabolic syndrome.

## Abstract

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.

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.

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.

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.