RESUMEN
SUMMARY OBJECTIVE: The aim of this study was to explore the correlation between skeletal muscle content and the presence and severity of metabolic dysfunction-associated fatty liver disease in patients with metabolic dysregulation in China. METHODS: A cross-sectional study was conducted among patients from the endocrinology outpatient department at Ningbo First Hospital, in Ningbo, China, in April 2021. Adult patients with metabolic dysregulation who accepted FibroScan ultrasound were included in the study. However, those without clinical data on skeletal muscle mass were excluded. FibroScan ultrasound was used to noninvasively evaluate metabolic dysfunction-associated fatty liver disease. The controlled attenuation parameter was used as an evaluation index for the severity of liver steatosis. Bioelectrical impedance analysis was used to measure the skeletal muscle index. RESULTS: A total of 153 eligible patients with complete data were included in the final analysis. As the grading of liver steatosis intensifies, skeletal muscle index decreases (men: Ptrend<0.001, women: Ptrend=0.001), while body mass index, blood pressure, blood lipid, uric acid, aminotransferase, and homeostatic model assessment of insulin resistance increase (Ptrend<0.01). After adjusting for confounding factors, a negative association between skeletal muscle index and the presence of metabolic dysfunction-associated fatty liver disease was observed in men (OR=0.691, p=0.027) and women (OR=0.614, p=0.022). According to the receiver operating characteristic curve, the best cutoff values of skeletal muscle index for predicting the metabolic dysfunction-associated fatty liver disease presence were 40.37% for men (sensitivity, 87.5%; specificity, 61.5%) and 33.95% for women (sensitivity, 78.6%; specificity, 63.8%). CONCLUSION: Skeletal muscle mass loss among patients with metabolic dysregulation was positively associated with metabolic dysfunction-associated fatty liver disease severity in both sexes. The skeletal muscle index cutoff value could be used to predict metabolic dysfunction-associated fatty liver disease.