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Updated: Jan 21, 2026

Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
Published on: March 24, 2023
Associations Between Body Fat, Muscle Mass, and Nonalcoholic Fatty Liver Disease: A Population-Based Study
Julianna C Hsing1,2, Mindie H Nguyen3,4, Baiyu Yang4
1Center for Policy, Outcomes and Prevention Stanford University School of Medicine Stanford CA.
Abstract:
Nonalcoholic fatty liver disease (NAFLD) is one of the most common forms of liver disease worldwide and has emerged as a significant public health concern in China. A better understanding of the etiology of NAFLD can inform effective management strategies for this disease. We examined factors associated with NAFLD in two districts of Hangzhou, China, focusing on the relationship of regional body fat distribution, muscle mass, and NAFLD. We used baseline data to carry out a cross-sectional analysis among 3,589 participants from the Wellness Living Laboratory (WELL) China study, a longitudinal population-based study that aims to investigate and promote well-being among the Chinese population. NAFLD was defined using the widely validated fatty liver index (FLI). Multivariate logistic regressions were performed to assess independent associations between NAFLD and metabolic risk factors (e.g., insulin resistance) and dual x-ray absorptiometry (DXA)-derived measures (e.g., android fat ratio [AFR] and skeletal muscle index [SMI]). Of the 3,589 participants, 476 (13.3%) were classified as having FLI-defined NAFLD (FLI ≥60). Among those, 58.0% were men. According to our analysis, AFR (odds ratio [OR], 10.0; 95% confidence interval [CI], 5.8-18.5), insulin resistance (OR, 4.0; 95% CI, 3.0-5.3), high alanine aminotransferase levels (OR, 7.6; 95% CI, 5.8-10.0), smoking (OR, 2.0; 95% CI, 1.4-3.0), and male sex (OR, 2.9; 95% CI, 2.0-4.2) were positively associated with NAFLD risk, while SMI (OR, 0.1; 95% CI, 0.07-0.13) was inversely associated with NAFLD risk. Conclusion: In addition to known metabolic risk factors, DXA-derived AFR and SMI may provide additional insights to the understanding of NAFLD. Interventions that aim to decrease AFR and increase SMI may be important to reduce the burden of NAFLD in this population.
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