Usefulness of health checkup for screening metabolic dysfunction-associated fatty liver disease and alcohol-related liver disease in Japanese male young adults.

We aimed to assess metabolic dysfunction-associated fatty liver disease (MAFLD) and alcohol-related liver disease (ALD) prevalence in young male adults and the role of health checkups in disease screening. We recruited 313 male graduate students at Gifu University in April 2022. With hepatic steatosis diagnosed by ultrasonography, MAFLD and nonalcoholic fatty liver disease (NAFLD) were diagnosed based on health checkup data, and ALD was diagnosed with alcohol consumption > 30 g/day. The ability of each variable to identify MAFLD, NAFLD, and ALD was assessed using logistic regression and receiver-operating characteristic curve analyses. Participants' mean age was 23 (± 4) years, and MAFLD, NAFLD, and ALD prevalence was 11%, 17%, and 1%, respectively. Among Japanese male young adults, alanine aminotransferase (ALT) (odds ratio [OR] 1.04; 95% confidence interval [CI] 1.01-1.07; P = 0.008) and body mass index (BMI) (OR 2.02; 95% CI 1.58-2.58; P < 0.001) were independently associated with MAFLD. Furthermore, only the alcohol use disorders identification test (AUDIT) was able to identify ALD (OR 1.49; 95% CI, 1.28-1.74; P = 0.001). Our study revealed that health checkups, including measurement of ALT, BMI, and AUDIT, are important for screening MAFLD and ALD in younger generations.

Impact of body fat accumulation on metabolic dysfunction-associated fatty liver disease and nonalcoholic fatty liver disease in Japanese male young adults.

AIM: Nonalcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) are global concerns. The aim of this study was to reveal the relationship between body composition and NAFLD and MAFLD in male young adults. METHODS: We recruited 335 male graduate students from Gifu University who underwent a health checkup in April 2022. The diagnosis of NAFLD and MAFLD was based on health checkup data and ultrasonography. Muscle and fat mass were measured using bioelectrical impedance analysis and demonstrated as skeletal muscle mass index and fat mass index (FMI), respectively. We assessed factors associated with NAFLD and MAFLD using the logistic regression, decision tree, and random forest analyses. RESULTS: The median age of the participants was 22 years, and 9% were overweight or obese (body mass index ≥25 kg/m2 ), 8% had MAFLD, and 16% had NAFLD. In the multivariate logistic regression analysis, FMI was independently associated with NAFLD (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.26-1.75; p < 0.001) and MAFLD (OR, 1.93; 95% CI, 1.51-2.46; p < 0.001). The decision tree and random forest analyses revealed that the strongest classifier for NAFLD and MAFLD was FMI. Additional analyses among nonobese individuals also showed the strong relationship between FMI, NAFLD, and MAFLD. CONCLUSION: Our study revealed that fat accumulation plays a key role in the development of NAFLD and MAFLD in male young adults, even in nonobese individuals. The results could shed new light on the pathophysiology of NAFLD and MAFLD in young adults.