Prediction of Nonalcoholic Fatty Liver Disease by Anthropometric Indices and Bioelectrical Impedance Analysis in Children

Bioelectrical impedance parameters add incremental value to waist-to-hip ratio for prediction of metabolic dysfunction associated steatotic liver disease in youth with overweight and obesity

Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing health concern in pediatric populations due to its association with obesity and metabolic syndrome. Bioelectrical impedance analysis (BIA) offers a non-invasive and potentially effective alternative for identifying MASLD risk in youth with overweight or obesity. Therefore, this study aimed to assess the utility of BIA for screening for MASLD in the youth.

Method

This retrospective, cross-sectional study included 206 children and adolescents aged <20 years who were overweight and obese. The correlations between anthropometric measurements and BIA parameters and alanine aminotransferase (ALT) levels were assessed using Pearson's correlation analysis. Logistic regression analysis was performed to examine the associations between these parameters and ALT level elevation and MASLD score. Receiver operating characteristic (ROC) curves were generated to assess the predictive ability of the parameters for MASLD.

Results

Pearson's correlation analysis revealed that waist-to-hip ratio (WHR), percentage body fat (PBF), and BIA parameters combined with anthropometric measurements were correlated with ALT level. Logistic regression revealed that WHR, skeletal muscle mass/WHR, PBF-WHR, fat-free mass/WHR, and appendicular skeletal muscle mass/WHR were correlated with ALT level elevation after adjusting for age, sex, and puberty. WHR, PBF-WHR, and visceral fat area (VFA)-WHR were positively correlated with the MASLD score in the total population after adjusting for age, sex, and puberty. PBF-WHR and VFA-WHR were correlated with the MASLD score even in youth with a normal ALT level. The cutoff points and area under the ROC curves were 34.6 and 0.69 for PBF-WHR, respectively, and 86.6 and 0.79 for VFA-WHR, respectively.

Discussion

This study highlights the utility of combining BIA parameters and WHR in identifying the risk of MASLD in overweight and obese youth, even in those with a normal ALT level. BIA-based screening offers a less burdensome and more efficient alternative to conventional MASLD screening methods, facilitating early detection and intervention in youth at risk of MASLD.

Innovative Therapeutic Approaches in Non-Alcoholic Fatty Liver Disease: When Knowing Your Patient Is Key

Non-alcoholic fatty liver disease (NAFLD) encompasses a spectrum of disorders ranging from simple steatosis to non-alcoholic steatohepatitis (NASH). Hepatic steatosis may result from the dysfunction of multiple pathways and thus multiple molecular triggers involved in the disease have been described. The development of NASH entails the activation of inflammatory and fibrotic processes. Furthermore, NAFLD is also strongly associated with several extra-hepatic comorbidities, i.e., metabolic syndrome, type 2 diabetes mellitus, obesity, hypertension, cardiovascular disease and chronic kidney disease. Due to the heterogeneity of NAFLD presentations and the multifactorial etiology of the disease, clinical trials for NAFLD treatment are testing a wide range of interventions and drugs, with little success. Here, we propose a narrative review of the different phenotypic characteristics of NAFLD patients, whose disease may be triggered by different agents and driven along different pathophysiological pathways. Thus, correct phenotyping of NAFLD patients and personalized treatment is an innovative therapeutic approach that may lead to better therapeutic outcomes.

Relationship between metabolic associated fatty liver disease and body fat ratio, visceral fat area, and resting metabolic rate estimated by bioelectrical impedance analysis

BACKGROUND

It is very important to identify the risk of metabolic associated fatty liver disease (MAFLD) in early stage, and body components measured by bioelectrical impedance analysis (BIA) would be a new way to achieve the prediction safely and noninvasively.

AIM

To measure the body composition by BIA, and explore the association of body fat ratio (BFR), visceral fat area (VFA), and resting metabolic rate (RMR) with MAFLD.

METHODS

A total of 509 subjects were divided into either a MAFLD group or a non-MAFLD group. Indicators of anthropo-metric measurements, BIA, and laboratory tests were collected. Spearman correlation analysis, receiver operating characteristic (ROC) curve analysis, and binary logistic regression analysis were used to explore the relationship of BFR, VFA, and RMR with MAFLD.

RESULTS

The differences in BFR, VFA, and RMR between the MAFLD group and the non-MAFLD group were statisti-cally significant both in male and female subjects (P < 0.05), and BFR, VFA, and RMR were significantly correlated with alanine aminotransferase, total bilirubin, triglyceride (TG), total cholesterol, fasting blood-glucose (FBG), and postprandial blood glucose (P < 0.05). The area under the ROC curve (AUC) values of BFR, VFA, and RMR were 0.800 (95% confidence interval [CI]: 0.752-0.875), 0.894 (95%CI: 0.847-0.941), and 0.715 (95%CI: 0.639-0.790), respectively, and VFA was the best indicator with a cutoff value of 87.10 cm² (87.25 cm² in males and 117.05 cm² in females). The odds ratio values of BFR, VFA, and RMR were 1.357 (95%CI: 1.214-1.517), 1.079 (95%CI: 1.049-1.111), and 1.009 (95%CI: 1.005-1.014), respectively, after adjsuting for gender, age, FBG, and TG.

CONCLUSION

BFR, VFA, and RMR estimated by BIA method can be well applied in the risk prediction of MAFLD, with VFA being the best indicator.

Bioelectrical Impedance Analysis Can Be an Effective Tool for Screening Fatty Liver in Patients with Suspected Liver Disease

Background and study aims: Although abdominal ultrasound (USG) or controlled attenuation parameter (CAP) score of transient elastography (TE) is recommended for the diagnosis of fatty liver, issues regarding cost and accessibility still exist. The aim of this study was to evaluate if bioelectrical impedance analysis (BIA) can be used as a reliable screening tool for fatty liver. Patients and methods: A total of 249 patients who underwent all three tests including TE, BIA, and USG were enrolled. The correlation between fat mass measured by BIA, CAP score of TE, and fatty liver grade measured by USG was analyzed. In addition, the cut-off value of BIA which can predict the fatty liver grade was calculated. Results: Fat mass index (FMI) assessed by BIA increased significantly along with the rise in fatty liver grade measured by USG (normal: 6.2 ± 2.4, Gr I: 8.0 ± 3.7, Gr II: 10.6 ± 3.5, Gr III: 10.7 ± 3.7 kg/m2, p < 0.001). In addition, a positive correlation was found between the CAP score of TE and the FMI of BIA. Additionally, a total body fat mass increase by 24.3% or 29.8% in men and 34.8% or 35.1% in women increased the possibility of developing any grade of fatty liver or significant fatty liver (≥Gr II fatty liver), respectively. Conclusion: The total fat or fat mass index of BIA was related to fatty liver as assessed by ultrasound or CAP score, and area under the receiver operating characteristic (AUROC) was about 0.8. Thus, BIA can be used as a screening tool for fatty liver in patients with suspected liver disease.