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Triglyceride–glucose index: a potent predictor of metabolic risk factors and eating behavior patterns among obese individuals

Amr Ali Mohamed Abdelgawwad El‐SehrawyDepartment of Internal Medicine, Diabetes, Endocrinology and Metabolism, Mansoura University, Mansoura, EgyptLusine KhachatryanDepartment of Pediatric Diseases, N.F. Filatov Clinical Institute of Children's Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, RussiaAziz KubaevDepartment of Maxillofacial Surgery, Samarkand State Medical University, 18 Amir Temur Street, Samarkand, 140100, Uzbekistan. [email protected]M. M. RekhaDepartment of Chemistry and Biochemistry, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, IndiaSafia Obaidur RabCentral Labs, King Khalid University, AlQura'a, P.O. Box 960, AlQura'a, Abha, Saudi ArabiaMandeep KaurDepartment of Sciences, Vivekananda Global University, Jaipur, Rajasthan, 303012, IndiaManmeet SinghDepartment of Applied Sciences, Chandigarh Engineering College, Chandigarh Group of Colleges- Jhanjeri, Mohali, Punjab, 140307, IndiaManish SrivastavaDepartment of Endocrinology, National Institute of Medical Sciences, NIMS University Rajasthan, Jaipur, IndiaAbed J. KadhimDepartment of Medical Engineering, Al-Nisour University College, Baghdad, IraqAhmed Hussein ZwamelMedical Laboratory Technique College, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq
BMC Endocrine Disordersjournal2025en
ABI

Аннотация

BACKGROUND: The strong potential of triglyceride to glucose index (TyG) in prediction of metabolic abnormalities is well identified in numerous disease including diabetes, metabolic syndrome and kidney disorders. However, no study is available to assess its validity and association with metabolic phenotype among obese individuals. In the current study, we aimed to evaluate the TyG index, its validity and association with metabolic parameters among obese individuals. METHODS AND MATERIALS: In the current cross-sectional study, 300 obese individuals were enrolled. Their demographic, anthropometric measurements were done and laboratory parameters including serum lipids, glycemic markers and insulin resistance were evaluated. Blood pressure was also measured with standard methods. The TyG index was calculated as the ln (fasting triglyceride level [mg/dL] × fasting glucose level [mg/dL]/2). Eating pattern was measured with three factor eating behavior questionnaire (TFEQ). Receiver operator characteristic curve was used to assess the TyG validity. RESULTS: Subjects at the higher TyG tertile had higher waist o hip ratio (WHR) and eating disorder compared with lowest tertiles. Also, those at the highest tertiles had significantly higher total cholesterol (TC), triglyceride (TG), and fasting blood sugar (FBS), and lower high density lipoprotein cholesterol (HDL). According to the ROC curve analysis for various metabolic parameters, TyG demonstrated the highest area under curve (AUC) value of 0.838 compared with other metabolic parameters in identification of metabolic syndrome. CONCLUSION: The current study provides valuable insights into the relationship between TyG index, metabolic parameters, and eating behaviors among obese individuals.

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