{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T15:55:25Z","timestamp":1759334125476,"version":"build-2065373602"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Endocr Disord"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Recent studies reveal that obesity and reduced muscle mass are key factors implicated in insulin resistance (IR) and abnormal glycemic metabolism. Nonetheless, it remains ambiguous which demographic, particularly those with obesity or diminished muscle mass, exhibits a greater vulnerability to insulin resistance.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Objective<\/jats:title>\n            <jats:p>The aim of this study is to investigate the relationship between insulin resistance assessed by the triglyceride and glucose index (TyG index) and abnormal blood glucose metabolism in individuals with both reduced muscle mass and obesity. Furthermore, we assess the efficacy of the TyG index in forecasting occurrences of atypical blood glucose metabolism within this particular demographic.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>This cross-sectional study utilized data collected from adults who underwent a health assessment at our institution between December 2022 and September 2024. The evaluation of insulin sensitivity was conducted utilizing the TyG index, whereas muscle mass was quantified through bioelectrical impedance analysis (BIA). Logistic regression, Receiver Operating Characteristic (ROC) curve analysis, subgroup analysis, and interaction effect analysis were employed to evaluate the association between triglyceride-glucose index levels with subgroups based on different body masses.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>This study comprised 1278 people with diminished muscle mass. We found a positive association between TyG index (OR\u2009=\u20097.73; 95% CI: 4.62\u201313.51; <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001) and the risk of abnormal glucose metabolism among those who were overweight\/obese. The analysis of the ROC curve revealed that the TyG index possesses a significant predictive capability for identifying abnormal glucose metabolism in individuals exhibiting diminished muscle mass (AUC\u2009=\u20090.906). This predictive value is particularly pronounced in those who do not present with overweight or obesity (AUC\u2009=\u20090.915), in contrast to its effectiveness in individuals who have both reduced muscle mass and overweight or obesity. Subgroup analyses confirmed the positive association of TyG index with abnormal blood glucose incidence.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>This study assessed the link between TyG and abnormal blood glucose metabolism events risk in people with sarcopenia and compared its predictive power for abnormal blood glucose metabolism events onset in those with low muscle mass but not overweight or obese. We recommend using the TyG index as the best predictive marker for assessing abnormal blood glucose metabolism events risk in individuals without concurrent overweight or obesity, regardless of their body mass index.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/s12902-025-02026-8","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T10:56:19Z","timestamp":1759229779000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predictive effect of the triglyceride glucose index on abnormal blood glucose metabolism events in populations with sarcopenia: a cross-sectional study"],"prefix":"10.1186","volume":"25","author":[{"given":"Yingying","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiabei","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunping","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingshuang","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"issue":"1","key":"2026_CR1","doi-asserted-by":"publisher","first-page":"15","DOI":"10.4093\/dmj.2021.0280","volume":"46","author":"SH Lee","year":"2022","unstructured":"Lee SH, Park SY, Choi CS. 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