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Updated: May 17, 2025

Author Spotlight: Establishing MASLD Cell Models for Investigating Disease Mechanisms and the Lipid-Lowering Effects of Koumiss
Published on: July 19, 2024
Clinical characteristics of MASLD/MetALD/MAFLD/NAFLD and the relative risk analysis on metabolic disorders
Hong-Ye Peng1,2, Chun-Li Lu3, Mo Zhao2
1Department of Infection, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Objectives:
Our objective was to compare the clinical features of Metabolic dysfunction-associated steatotic liver disease (MASLD) /metabolic alcohol-related liver disease (MetALD)/metabolic associated fatty liver disease (MAFLD)/nonalcoholic fatty liver disease (NAFLD) and the relative risk analysis of metabolic disorders.
Methods:
The National Health and Nutrition Examination Survey for the 2017-2018 cycle was used to screen the participants. Multivariate-adjusted logistic regression models were applied to explore the difference in relative risk analysis between NAFLD/MAFLD/MASLD/MetALD and metabolic disorders.
Results:
Among the 1,862 eligible individuals, 358(44.84%) had MASLD, 213(11.44%) had MetALD, 841(45.17%) had MAFLD, and 1,125(60.42%) had NAFLD. Positive associations with the risk of hypertension were discovered for MASLD (OR = 2.892, 95%CI = 2.226-3.756), MetALD (OR = 1.802, 95% CI = 1.355-2.398), MAFLD (OR = 3.455, 95%CI = 2.741-4.354) and NAFLD (OR = 1.983, 95%CI = 1.584-2.484). Positive associations with the risk of T2DM were discovered for MASLD (OR = 6.360, 95%CI = 4.440-9.109), MAFLD (OR = 7.026, 95%CI = 4.893-10.090) and NAFLD (OR = 3.372, 95%CI = 2.511-4.528). We discovered similar results for hyperlipidemia. Compared to mild steatosis, moderate to severe steatosis in patients with MASLD (OR = 3.924, 95%CI = 2.399-6.419), MAFLD (OR = 3.814, 95%CI = 2.367-6.144), NAFLD (OR = 4.910, 95%CI = 2.983-8.080) has a higher risk for T2DM.
Conclusion:
The proposed definitions of MASLD and MetALD are valuable and deserve further exploration. Our findings suggest that MAFLD is a more effective indicator for identifying patients at increased risk for metabolic disorders.
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