Frontiers in Nutrition · Oct 30, 2026

Sarcopenic Obesity Was Associated with MASLD in Elderly Chinese: A Multi-centre Community Study

By Xiaohui Liu, Xiaodie Wei, Jian Wu et al.

Background: Sarcopenia and obesity are major public health concerns in aging populations. Several classification frameworks for sarcopenic obesity (SO) have been proposed, but data on the associations of SO classified using different approaches with metabolic dysfunction-associated steatotic liver disease (MASLD) remain limited among elderly Chinese population. Methods: The study recruited 1,690 elderly residents from two Beijing communities. Bioelectrical impedance analysis (BIA) and hand grip evaluated body composition and muscle strength. Fatty liver was detected by ultrasound. Advanced liver fibrosis was defined as NAFLD fibrosis score (NFS) ≥0.676. SO was defined by the ESPEN/EASO criteria, a modified application of the diagnostic-stage components of the 2024 JWGSO framework, and a study-specific operationalization informed by the GLIS conceptual definition. Results: The study cohort had a median age of 69 years, with 36.63% being male and 58.6% having MASLD. SO prevalence varied across the three classification approaches (5.0% under the ESPEN/EASO criteria, 7.5% under the modified 2024 JWGSO-based approach, and 11.2% under the study-specific GLIS-based definition). SO was significantly associated with the presence of MASLD under three classification approaches, with odds ratios (95% CI) of 3.39 (2.03-5.66) with ESPEN/EASO, 5.41 (3.22-9.08) with JWGSO-based approach, and 3.77 (2.58-5.51) with the study-specific GLIS-based approach (all P<0.001). Among patients with MASLD, SO defined by the study-specific GLIS-based approach was associated with higher odds of advanced fibrosis (aOR 2.35, 95% CI 1.03-5.35; P=0.04). Conclusion: SO was associated with MASLD across the three classification approaches. The observed association between the study-specific GLIS-based defined SO with advanced fibrosis remains preliminary and requires further validation.

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