{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T22:21:19Z","timestamp":1792621279939,"version":"4.5.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T00:00:00Z","timestamp":1758758400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>This study aims to evaluate the triglyceride\u2013glucose (TyG) index as a biomarker for identifying prediabetes mellitus (PDM) in children and adolescents with obesity and to compare its predictive ability with traditional indicators.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A cross-sectional study was conducted with 213 children and adolescents with obesity, aged 8 to 18 years. Key inclusion criteria included obesity, defined as a BMI above the 95th percentile. Diagnostic criteria were based on fasting plasma glucose (FPG) and the oral glucose tolerance test (OGTT). Correlation analysis, least absolute shrinkage and selection operator (LASSO) logistic regression, logistic regression, and ROC curve analysis were performed to assess predictive performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The TyG index showed significant positive correlations with triglyceride (TG; <jats:italic>r<\/jats:italic> = 0.751), hemoglobin A1c (HbA1c; <jats:italic>r<\/jats:italic> = 0.422), 2hPG (<jats:italic>r<\/jats:italic> = 0.387), and FPG (<jats:italic>r<\/jats:italic> = 0.385) (all <jats:italic>p<\/jats:italic> &amp;lt; 0.001). LASSO regression identified TyG, HbA1c, and homeostasis model assessment of insulin resistance (HOMA-IR) as key predictors. Multivariate logistic regression demonstrated that the TyG index was an independent risk factor for PDM (OR = 13.287; 95% confidence interval [CI]: 5.357\u201332.956; <jats:italic>p<\/jats:italic> &amp;lt; 0.001). ROC analysis revealed an AUC of 0.776 (95% CI: 0.715\u20130.837) for the TyG index, with an optimal cutoff of 8.895, yielding a sensitivity of 55.1% and specificity of 85.2%, outperforming TG, FPG, and HOMA-IR.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The TyG index is a reliable and practical marker for identifying prediabetes in children and adolescents with obesity. Its predictive performance exceeds that of several conventional indicators, providing clinical value for early screening and intervention.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2025.1657912","type":"journal-article","created":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T04:18:05Z","timestamp":1758773885000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Can the triglyceride\u2013glucose index identify prediabetes in children and adolescents with obesity? a cross-sectional study"],"prefix":"10.3389","volume":"16","author":[{"given":"Hongxia","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luxin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caixia","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinming","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,25]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.47391\/jpma.22-63","article-title":"Triglyceride Glucose (TyG) Index: A surrogate biomarker of insulin resistance","volume":"72","author":"Ramdas Nayak","year":"2022","journal-title":"J Pak Med Assoc"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.2147\/dmso.S478287","article-title":"Role of triglyceride-glucose index in type 2 diabetes mellitus and its complications","volume":"17","author":"Pan","year":"2024","journal-title":"Diabetes Metab Syndr Obes"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.2337\/dc18-1920","article-title":"Elevated tyG index predicts progression of coronary artery calcification","volume":"42","author":"Park","year":"2019","journal-title":"Diabetes Care"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.973655","article-title":"Elevated triglyceride-glucose (TyG) index predicts impaired islet \u03b2-cell function: A hospital-based cross-sectional study. 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