Insulin Resistance Markers Predict New-Onset Diabetes in Middle-Aged and Elderly Adults with Cardiovascular-Kidney-Metabolic Syndrome.

Authors

Yan-Ting Liang, Yu-Jian He, Jing-Yuan Liu, Yu-Ting Liu, Nan Hu, Zhen Wang, Hua-Lin Ma, Xin-Zhou Zhang

Published in

Current medical science. Oct 20, 2026. Epub Oct 20, 2026.

Abstract

Insulin resistance (IR) is central to cardiovascular-kidney-metabolic (CKM) syndrome, but the best IR-related marker for identifying CKM patients at high risk of diabetes remains uncertain. This study examined associations between IR-related markers and new-onset diabetes and compared their predictive performance.
We analyzed 6,307 CKM participants from the China Health and Retirement Longitudinal Study (CHARLS) and 6,388 from the National Health and Nutrition Examination Survey (NHANES). Logistic regression and restricted cubic spline analyses were used to assess associations of triglyceride-glucose (TyG), TyG-body mass index (TyG-BMI), TyG-waist-to-height ratio (TyG-WHtR), metabolic score for IR (METS-IR), and estimated glucose disposal rate (eGDR) with diabetes. Subgroup analyses and receiver operating characteristic curves were employed to evaluate robustness and discrimination.
Over 7 years, diabetes developed in 736 CHARLS participants (11.67%) and 1,451 NHANES participants (22.71%). Five IR-related markers were significantly associated with the risk of diabetes and demonstrated good predictive performance. Elevated levels of TyG, TyG-BMI, TyG-WHtR, and METS-IR, as well as lower levels of eGDR, were associated with increased diabetes risk (all P < 0.001). Most associations remained robust across subgroup analyses. Among the five markers, eGDR demonstrated the highest predictive performance in the NHANES cohort (AUC: 0.789; 95% CI: 0.776-0.802) and showed favorable predictive ability in the CHARLS cohort.
IR-related markers are significantly associated with the risk of diabetes in individuals with CKM syndrome and serve as reliable predictors of new-onset diabetes. Among these indicators, eGDR and TyG-WHtR were relatively reliable predictors, highlighting their potential as valuable tools for early diabetes screening.

PMID:
42900339
Bibliographic data and abstract were imported from PubMed on 21 Oct 2026.

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