The association between insulin resistance and the occurrence of metabolic syndrome in Chinese patients with type 2 diabetes, and the application of China Age-Sex-Ethnicity-Specific of Metabolic Syndrome Severity scoring
Abstract Background Metabolic syndrome (MetS) is conventionally diagnosed using a binary classification framework—a method that fails to reflect the considerable heterogeneity in metabolic risk among individuals with type 2 diabetes mellitus (T2DM). Converting MetS into a continuous severity metric enables more precise, quantitative assessment of overall metabolic burden. This study aimed to examine the associations of three insulin resistance–related biomarkers—the metabolic score for insulin resistance (METS-IR), the homeostasis model assessment of insulin resistance (HOMA-IR), and the serum uric acid-to-high-density lipoprotein cholesterol ratio (UHR)—with both the presence and severity of MetS in patients with T2DM. Methods This retrospective case study enrolled 726 patients with confirmed type 2 diabetes mellitus (T2DM) who were hospitalized Longyan First Affiliated Hospital of Fujian Medical University, between June 2022 and May 2025. Correlation analysis, multivariable regression analysis, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA) were conducted to evaluate the associations between insulin resistance (IR) indices and MetS, as well as its severity. Results After multivariable adjustment, METS-IR, HOMA-IR, and UHR were each independently associated with MetS(all P < 0.001) and exhibited positive associations with MetS severity (METS-IR: β = 0.12, 95% CI 0.11–0.12; HOMA-IR: β = 0.14, 95% CI 0.12–0.17; UHR: β = 0.14, 95% CI 0.13–0.15; all P < 0.001). Among these indices, METS-IR demonstrated the strongest discriminative performance for MetS (AUC = 0.893). DCA revealed that METS-IR conferred the highest clinical net benefit across a broad range of risk thresholds, underscoring its superior practical utility as a screening tool relative to HOMA-IR and UHR. Conclusion METS-IR is strongly associated with both the development and severity of metabolic syndrome and plays a significant role in the risk assessment and clinical management of metabolic syndrome. Clinical trial number Not applicable.
Authors
- Tao Chen (ORCID: https://orcid.org/0000-0002-8371-779X)
- Jiying Zhu
Institutions
- Fujian Medical University (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
Publication Details
- Journal
- BMC Endocrine Disorders
- Published
- 2026-09-21
- DOI
- https://doi.org/10.1186/s12902-026-02580-9
- Primary Topic
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Type
- article
- Field-Weighted Citation Impact
- 0.00