Possible prediction of obesity-related liver disease in children and adolescents using indices of body composition

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Background: Diagnosis of nonalcoholic fatty liver disease in children and adolescents currently requires advanced or invasive technologies. Objectives: We aimed to develop a method to improve diagnosis, using body composition indices and liver biochemical markers. Methods: To diagnose non-alcoholic fatty liver disease, 767 Danish children and adolescents underwent clinical examination, blood sampling, whole-body dual-energy X-ray absorptiometry scanning and proton magnetic resonance spectroscopy for liver fat quantification. Fourteen variables were selected as a starting point to construct models, narrowed by stepwise selection. Individuals were split into a training set for model construction and a validation test set. The final models were applied to 2120 Danish children and adolescents to estimate the prevalence. Results: The final models included five variables in different combinations: body mass index–standard deviation score, android-to-gynoid-fat ratio, android-regional fat percent, trunk-regional fat percent and alanine transaminase. When validated, the sensitivity and specificity ranged from 38.6% to 51.7% and 87.6% to 91.9%, respectively. The estimated prevalence was 24.2%–35.3%. Models including alanine transaminase alongside body composition measurements displayed higher sensitivity. Conclusions: Body composition indices and alanine transaminase can be used to estimate non-alcoholic fatty liver disease, with 38.6%–51.7% sensitivity and 87.6%–91.9%, specificity, in children and adolescents with overweight (including obesity). These estimated a 24.2%–35.3% prevalence in 2120 patients.

Original languageEnglish
JournalPediatric Obesity
Issue number10
Number of pages11
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 The Authors. Pediatric Obesity published by John Wiley & Sons Ltd on behalf of World Obesity Federation.

    Research areas

  • adolescents, body composition, children, DXA-scan, MAFLD, NAFLD

ID: 313648928