{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T01:09:32Z","timestamp":1779325772746,"version":"3.51.4"},"reference-count":29,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014361","name":"Hubei University of Medicine","doi-asserted-by":"publisher","award":["\u4e0d\u3002YC2023061, (\u7f16\u53f7 2020QDJRW003), AF2022003"],"award-info":[{"award-number":["\u4e0d\u3002YC2023061, (\u7f16\u53f7 2020QDJRW003), AF2022003"]}],"id":[{"id":"10.13039\/501100014361","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>There is limited data on the association between TyG-BMI and NAFLD in patients with Type 2 Diabetes Mellitus (T2DM). The magnitude of risk prediction and predictive efficacy of TyG-BMI for T2DM with NAFLD remains unclear.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>To examine the association of TyG-BMI with NAFLD in T2DM patients and assess the effectiveness of screening using the TyG-BMI index.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We conducted a retrospective analysis of clinical data from 602 T2DM patients at an enterprise health lodge from September 2021 to November 2022. Patients were categorized into two groups: T2DM alone (n=250) and T2DM with NAFLD (n=352). The Mann-Whitney U test was used for comparing non-normally distributed continuous data between groups, while the Chi-square test was used for categorical data. Logistic regression analysis was performed to evaluate the effect of BMI, TyG index, and TyG-BMI index on NAFLD. The ROC curve was used to assess the predictive efficacy of the TyG-BMI index for NAFLD in T2DM patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>BMI predicted the development of NAFLD in T2DM patients with an area under the receiver operating characteristic (ROC) curve of 0.792 (95% CI 0.757-0.828), and the optimal cutoff value was 25.22, with 72.2% sensitivity and 71.6% specificity; The area under the receiver operating characteristic (ROC) curve of the TyG index to predict the development of NAFLD in patients with T2DM was 0.755 (95% CI 0.716-0.794), and the optimal cutoff value was 8. 945, with a sensitivity of 80.1% and a specificity of 59.2%; The area under the receiver operating characteristic (ROC) curve of TyG-BMI index to predict the development of NAFLD in T2DM patients was 0.852, (95% CI 0.822-0.882), and the optimal cutoff value was 227.385, with a sensitivity and specificity of 80.1% and 59.2%, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The TyG-BMI index is a significant predictor of comorbid NAFLD in T2DM patients and provides better screening performance than BMI alone. The TyG-BMI index shows promise as an early screening tool for NAFLD in T2DM patients.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2024.1425024","type":"journal-article","created":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T05:24:39Z","timestamp":1737350679000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Value of triglyceride glucose-body mass index in predicting nonalcoholic fatty liver disease in individuals with type 2 diabetes 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