New research indicates that simple blood test-based insulin resistance measures, adapted for body mass, can more accurately detect fatty liver disease in individuals with type 2 diabetes, potentially guiding more effective screening practices.
A new analysis from researchers in China suggests that simple insulin resistance measures drawn from routine blood tests and body measurements can help spot metabolic dysfunction-associated fatty liver disease, or MAFLD, in people with type 2 diabetes, but that the best index depends on body mass. The study, published in Dove Medical Press and based on 5,000-plus patients across a training cohort and an external validation cohort, found that TyG-BMI performed best in overweight and obese patients, while TG/HDL-C offered the strongest performance in normal-weight individuals. The pattern points to a practical, BMI-aware approach to screening rather than a single universal cut-off.
The findings matter because MAFLD, previously known as non-alcoholic fatty liver disease, is now understood as a common liver disorder closely tied to metabolic dysfunction, insulin resistance and type 2 diabetes. The condition can progress from simple fat accumulation in the liver to inflammation, fibrosis and cirrhosis, yet many patients are never diagnosed early because biopsy is invasive and imaging has limits in routine care. In that context, the appeal of indices such as TyG, TyG-BMI, METS-IR and TG/HDL-C is obvious: they are inexpensive, repeatable and based on measurements clinicians already collect.
In the Chinese cohort, the researchers compared six surrogates of insulin resistance: HOMA-IR, TyG, TyG-BMI, METS-IR, TG/HDL-C and CVAI. Among overweight and obese participants, TyG-BMI gave the highest overall discrimination, with METS-IR close behind. In normal-weight patients, TG/HDL-C edged ahead, although TyG-BMI remained competitive. The study also reported that these indices tended to have stronger negative predictive value in people with normal weight, which may make them especially useful for ruling out disease in this group.
That distinction is important because MAFLD is not limited to people with higher body mass. The authors noted that a substantial share of fatty liver cases occur in non-obese or lean patients, a group that can still have significant visceral adiposity, dyslipidaemia and marked insulin resistance. Related work in other populations has pointed in the same direction. A 2023 Scientific Reports study found that markers such as TyG-BMI, TyG-waist circumference and TyG-waist-to-height ratio were strong predictors of fatty liver in non-diabetic adults, while a separate cross-sectional study published in 2024 reported that TyG-based indices ranked among the best non-invasive indicators for MAFLD and liver fibrosis.
The new paper also strengthens its case by using an independent validation cohort, where the main patterns largely held up. TyG-BMI again emerged as the top performer in overweight and obese patients, while TG/HDL-C remained the most balanced measure in normal-weight participants. That kind of replication is useful because it suggests the findings are not merely a quirk of one hospital sample. The study’s authors argue that routine screening at the point of diabetes diagnosis, and then annually, could help identify people who should go on to liver ultrasound or other confirmatory testing.
Taken together, the research adds to a growing body of evidence that insulin resistance indices can do more than describe metabolic risk: they may help triage fatty liver screening in everyday diabetes care. A 2026 review comparing CVAI with traditional insulin resistance measures reached a similar conclusion that several of these indices can identify MAFLD in Chinese adults with type 2 diabetes, while other studies in Bangladesh and the US have also linked insulin resistance metrics to fatty liver risk. The broader message is clear. In people with type 2 diabetes, the most useful screening tool may not be the same for everyone, and body size still matters when deciding which index to trust most.
Disclaimer: This content is for informational purposes only and is not intended to be a substitute for professional medical judgment, advice, diagnosis, or treatment.
