In patients with MASLD and T2D, DXA-derived body composition measures may complement conventional anthropometric assessment and help identify individuals with severe hepatic steatosis.
Key Findings
Results
DXA identified pathological fat mass percentage in nearly all patients, while BMI-based obesity criteria identified less than half.
97.9% of patients had pathological fat mass percentage by DXA criteria (>25% in men, >35% in women)
Only 46.4% of patients met BMI-based criteria for obesity
This discrepancy highlights BMI's inadequacy in reflecting individual differences in body composition and fat distribution
Study enrolled 97 consecutive patients with MASLD and T2D at a tertiary hepatology centre, with median age of 61 years
Results
Fat mass percentage was independently associated with severe hepatic steatosis at multivariate analysis.
Severe hepatic steatosis was defined as controlled attenuation parameter (CAP) ≥280 dB/m
Fat mass percentage was independently associated with severe hepatic steatosis (OR 1.100, p = 0.011)
Statistical analyses included Spearman's rank correlation, Chi Square test, logistic regression, and ROC curve analyses
Results
Pathological appendicular lean mass/height² (ALM/height²) index was independently and inversely associated with severe hepatic steatosis.
Pathological ALM/height² was independently related with severe hepatic steatosis (OR 0.292, p = 0.013)
The inverse association (OR < 1) indicates that reduced muscle mass was associated with greater likelihood of severe steatosis
Pathological ALM/height² was defined as <7.0 kg/m² in men and <5.5 kg/m² in women
Results
ROC curve analysis identified specific DXA-derived cut-offs for fat mass percentage and ALM/height² index for detecting severe liver steatosis.
Fat mass percentage cut-off of 38.65% yielded an AUC of 0.636 for detecting severe hepatic steatosis
ALM/height² index cut-off of 6.7 kg/m² yielded an AUC of 0.611 for detecting severe hepatic steatosis
Both individual cut-offs showed modest discriminative ability on their own
Results
A model combining both fat mass percentage and ALM/height² cut-offs demonstrated improved discriminative ability for severe hepatic steatosis.
The combined model yielded an AUC of 0.715 (95% CI 0.610–0.820, p = 0.001)
This represents an improvement over either measure used alone (AUC 0.636 and 0.611, respectively)
Hepatic steatosis and fibrosis were evaluated by controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), respectively
What This Means
This research suggests that standard body weight measurements like BMI are not adequate for identifying liver fat severity in people who have both type 2 diabetes and metabolic liver disease (MASLD). When researchers used a more detailed body scanning technology called DXA (dual-energy X-ray absorptiometry) — commonly used to assess bone density — they found that nearly all 97 patients (97.9%) had abnormally high body fat, while only about half (46.4%) would have been classified as obese using BMI alone. This means BMI substantially underestimates the burden of excess fat in this population.
The study found that two specific measurements from DXA scans were independently linked to severe liver fat accumulation: a higher percentage of body fat and lower muscle mass in the arms and legs (called appendicular lean mass). When both measurements were combined into a single predictive model, the ability to identify patients with severe liver steatosis improved meaningfully, achieving an area under the curve (AUC) of 0.715, compared to 0.636 and 0.611 for each measure alone. The specific thresholds identified were a fat mass percentage above 38.65% and an appendicular lean mass index below 6.7 kg/m².
This research suggests that body composition analysis using DXA — a tool already used in osteoporosis screening — could provide additional clinically useful information about liver disease severity in people with type 2 diabetes. Since these patients often undergo DXA scans for bone health assessment, the same scan data could potentially be used to help stratify their risk for serious liver disease, without requiring additional testing. This could be particularly valuable given that MASLD is the most common chronic liver disease worldwide and often goes undetected until it has progressed significantly.
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Asero C, Oliveri C, Franzè M, Basile G, Catalano A, Cacciola I. (2026). Body composition assessment for risk stratification of hepatic steatosis in patients with type 2 diabetes and MASLD undergoing osteoporosis screening.. Frontiers in endocrinology. https://doi.org/10.3389/fendo.2026.1901793