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Higher TyG-BMI indicates higher risk of MAFLD in lean females
China: A recent study published in BMJ Open has suggested TyG-body mass (TyG-BMI) as a promising predictor for metabolic-associated fatty liver disease (MAFLD), particularly in lean and female individuals.
There has been a marked increase in the global prevalence of MAFLD, previously known as NAFLD (non-alcoholic fatty liver disease), by up to 25%. Furthermore, studies have linked MAFLD with adverse clinical sequelae that may eventually result in elevated mortality. Therefore, early MAFLD identification is critical. However, a practical, simple, non-invasive MAFLD screening tool is unavailable.
MAFLD developed through complex interactions between insulin resistance and obesity. Obesity indicators, such as waist circumference (WC) and body mass index (BMI), are strongly related to fatty liver and metabolic disorders. However, some studies have revealed that 5%–26% of MAFLD patients have normal BMI. Thus, these people and those exhibiting pre-MAFLD are often overlooked during MALFD screening. Sole reliance on BMI and WC as a total MAFLD reflection is unreliable due to their IR omission.
The TyG (triglyceride glucose) index is a newly proposed index that is more reliable and simpler for IR evaluation than the homeostasis model assessment of the IR index. Therefore, Mingxing Chang, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China, and colleagues aimed to evaluate the performance of the TyG index and its related markers in predicting MAFLD in healthy Chinese participants in a cross-sectional study.
The study was conducted at the Affiliated Hospital of Xuzhou Medical University. It included 20 922 asymptomatic Chinese participants (56% men).
MAFLD diagnosis was made by hepatic ultrasonography based on the latest diagnostic criteria. TyG-BMI, the TyG, and TyG-WC indices were calculated and analysed.
The study revealed the following findings:
- The adjusted ORs for MAFLD were 20.76, 92.33 and 380.87 in the second, third and fourth quartiles, respectively, compared with the lowest quartile of the TyG-BMI.
- In the subgroup analysis, the TyG-BMI in the lean and female groups (BMI<23 kg/m2) showed the most substantial predictive value, with optimal cut-off values for MAFLD of 162.05 and 156.31, respectively.
- The areas under the receiver operating characteristic curves in the female and lean groups were 0.933 and 0.928, respectively, with 81.2% specificity and 90.7% sensitivity in female participants with MAFLD and 87.1% specificity and 87.2% sensitivity in lean participants with MAFLD.
- The TyG-BMI index showed superior predictive ability for MAFLD compared with other markers.
"The TyG-BMI is a simple, effective and promising tool for MAFLD prediction, especially in lean and female participants," the researchers wrote. However, they warn about carefully interpreting the findings due to the study's observational design.
"Further research is warranted to validate the findings in more extensive and diverse populations," they conclude.
Reference:
Chang M, Shao Z, Shen GAssociation between triglyceride glucose-related markers and the risk of metabolic-associated fatty liver disease: a cross-sectional study in healthy Chinese participantsBMJ Open 2023;13:e070189. doi: 10.1136/bmjopen-2022-070189
MSc. Biotechnology
Medha Baranwal joined Medical Dialogues as an Editor in 2018 for Speciality Medical Dialogues. She covers several medical specialties including Cardiac Sciences, Dentistry, Diabetes and Endo, Diagnostics, ENT, Gastroenterology, Neurosciences, and Radiology. She has completed her Bachelors in Biomedical Sciences from DU and then pursued Masters in Biotechnology from Amity University. She has a working experience of 5 years in the field of medical research writing, scientific writing, content writing, and content management. She can be contacted at  editorial@medicaldialogues.in. Contact no. 011-43720751
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751