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Life sciences · Journal article
Frontiers in Medicine · November 4, 2026
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Background Metabolic dysfunction-associated fatty liver disease (MAFLD) is closely linked to obesity and abnormal body composition. However, conventional indices such as body mass index (BMI) are limited in reflecting fat distribution and muscle status. The skeletal muscle mass-to-visceral fat area ratio (SVR) may better capture metabolic health. Objective To investigate the association between skeletal muscle mass-to-visceral fat area ratio (SVR) and metabolic dysfunction-associated fatty liver disease (MAFLD), and to explore the potential role of SVR as an integrated body composition marker for metabolic risk assessment. Methods This single-center cross-sectional study included 11,977 adults undergoing routine health examinations. Body composition was measured using bioelectrical impedance analysis. SVR was calculated as appendicular skeletal muscle mass divided by visceral fat area and categorized into quartiles. MAFLD defined according to the 2020 international expert consensus criteria, based on ultrasound-detected hepatic steatosis combined with metabolic dysfunction criteria. Multivariable logistic regression, ROC analysis, and subgroup analyses were performed. Results A total of 4,791 participants (40.0%) were diagnosed with MAFLD. SVR was significantly lower in MAFLD subjects compared with non-MAFLD individuals ( P < 0.001). SVR showed a strong inverse association with MAFLD ( OR = 0.383, 95% CI: 0.368–0.399). After multivariable adjustment, participants in higher SVR quartiles had lower odds of prevalent MAFLD compared with those in the lowest quartile(Q3: OR = 0.667; Q4: OR = 0.430; both P < 0.001). ROC analysis showed an AUC of 0.773 with an optimal cutoff of 0.25. Subgroup analyses suggested that the association between SVR and prevalent MAFLD varied by BMI and sex, whereas no statistically significant interaction was observed for age. Conclusion Lower SVR was associated with a higher prevalence of MAFLD in adults undergoing routine health examinations, SVR may help identify individuals with unfavorable metabolic profiles in health examination populations.