Relationships Between Insulin Resistance Surrogate Indicators and Chronic Kidney Disease in Non-Diabetic Individuals: A Retrospective Cross-Sectional Study - Liu Q; An XF; Li L; Zhang H; Zuo YQ (Diabetes, Metabolic Syndrome and Obesity, 2025)
Qing Liu,1 Xiao-Fan An,2 Li Li,3 Han Zhang,4 Yu-Qiang Zuo4 1Department of Medical Equipment, the 2nd Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, People’s Republic of China; 2Department of Gynecology, Xinle Hospital, Shijiazhuang, Hebei Province, People’s Republic of China; 3Department of Pharmaceutical, Xinle Hospital, Shijiazhuang, Hebei Province, People’s Republic of China; 4Department of Physical Examination Center, The 2nd Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, People’s Republic of ChinaCorrespondence: Yu-Qiang Zuo, Email xiamu820101@sina.comPurpose: This study aimed to investigate the associations between insulin resistance (IR) surrogate indicators and chronic kidney disease (CKD) in non-diabetic individuals.Methods: A retrospective analysis was conducted on 29625 participants who underwent annual health examinations from January to December 2024. Based on estimated glomerular filtration rate, participants were divided into non-CKD and CKD groups. Univariate and multivariate logistic regression analyses were performed to evaluate the relationships between insulin resistance surrogate indicators, including metabolic score of insulin resistance (METS-IR), triglyceride glucose index (TyG), triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C), total cholesterol-high density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (Non-TG/HDL-C), and CKD, adjusting for potential confounders such as age, sex, blood pressure, and metabolic parameters. Receiver operating characteristic (ROC) curves and DeLong tests were used to compare the predictive performances of different indicators.Results: Among the recruited 29,625 participants, 8.01% (2372/29,625) participants were CKD patients. All insulin resistance surrogate indicators were found to be correlated with the prevalence of CKD. After adjusting for confounding variables, the METS-IR exhibited stronger association with CKD than other insulin resistance surrogate indicators; the odd ratio for CKD in the highest quartile of the METS-IR was 2.360 (95% CI:1.594− 3.493). The ROC results showed the area under curve (AUC) of METS-IR were the best, with AUC = 0.681 (0.671− 0.691), which was higher than TyG, TG/HDL-C, and NonTG/HDL-C. Results of the DeLong test showed that there was a statistically significant difference between METS-IR and other IR indicators.Conclusion: IR indicators (METS-IR, TyG, TG/HDL-C, and NonTG/HDL-C) were positively correlated with the prevalence of CKD in the non-diabetic population. The METS-IR had the best predictive ability for CKD in this population. Detection and early intervention of elevated IR indicators may help prevent CKD in non-diabetic individuals.Keywords: insulin resistance, metabolic score for insulin resistance, triglyceride glucose index, chronic kidney disease