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Research Article: Association between triglyceride glucose-body mass index and diabetic kidney disease in hospitalized patients with type 2 diabetes mellitus: a retrospective cross-sectional study

Date Published: 2026-09-24

Abstract:
To analyze the association between the triglyceride glucose-body mass index (TyG-BMI) and diabetic kidney disease (DKD) in patients with type 2 Diabetes Mellitus (T2DM). A single-center retrospective cross-sectional study was conducted enrolling 1,966 patients diagnosed with T2DM. General clinical data, as well as data on medication use, smoking history, alcohol consumption, and comorbidities, were collected. According to DKD diagnostic criteria, participants were divided into the non-DKD group ( n =?1,359) and the DKD group ( n =?607). Subgroup analyses were performed according to DKD clinical stages. Multivariate logistic regression analysis was employed to investigate the association between the TyG-BMI index and DKD in T2DM patients, and receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminatory ability of TyG-BMI for DKD. Compared to the Non-DKD group, patients in the DKD group exhibited significantly higher age, DM duration, SBP, DBP, WC, WHR, BMI, sCr, UACR, FPG, 2hPPG, HbA1c, FCP, TG, and the TyG-BMI index ( P <?0.05). Conversely, HDL-C, e-GFR, and ALT were significantly lower in the DKD group ( P <?0.05). Subgroup analysis revealed that TyG-BMI index showed a gradual increasing trend with increasing DKD severity, but the difference between the two subgroups was not statistically significant ( P >?0.05). Multivariate logistic regression analysis, after adjusting for confounders including age, sex, diabetes duration, SBP, comorbidities, and medication history, identified the TyG-BMI index as an independent factor associated with DKD, with each 10-unit increase in TyG-BMI associated with an 8.5% increase in DKD risk (OR?=?1.085, 95% CI: 1.059–1.112, P =?0.000). When TyG-BMI index was stratified by quartiles, logistic regression analysis demonstrated that the risk of DKD gradually increased with higher TyG-BMI levels, and the trend test indicated a significant dose–response relationship ( P for trend?<?0.001). ROC curve analysis showed that the combined model (including TyG-BMI, demographic and clinical variables) achieved an area under the curve (AUC) of 0.709 (95% CI: 0.683–0.734) for identifying DKD, with an optimal predicted probability cut-off of 0.330 (corresponding to a raw TyG-BMI index value of 315.962), a sensitivity of 58.4%, and a specificity of 73.4%. The AUC for TyG-BMI alone was 0.574 (95% CI: 0.547–0.601), and for BMI alone was 0.552 (95% CI: 0.524–0.580). The DeLong test demonstrated that the AUC of the combined model was significantly superior to that of TyG-BMI alone and BMI alone (both P <?0.001), indicating that the addition of other clinical variables significantly improved the discriminative ability of the model. This study identified a significant association between the TyG-BMI index and DKD in patients with T2DM, with a dose-response trend. As a simple composite index derived from TG, FBG, and BMI, TyG-BMI index may serve as an auxiliary reference indicator for DKD risk assessment in T2DM patients, facilitating the identification of high-risk individuals. However, due to the selection bias inherent in the hospitalized population and the cross-sectional design, these findings require further validation in community-based cohorts.

Introduction:
With the improvement of economic standards, changes in lifestyle, and the aging of the population, the global incidence of diabetes mellitus (DM) has been increasing. According to the International Diabetes Federation (IDF) diabetes Atlas ( 1 ), the global diabetes prevalence among individuals aged 20–79 years was estimated at 10.5% (536.6 million people) in 2021 and is projected to increase to 12.2% (783.2 million people) by 2045. China has the largest number of individuals with diabetes worldwide. According to…

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