Endocrine · 2025
Dual-energy X-ray absorptiometry and bioelectrical impedance analysis are useful for predicting metabolic syndrome and nonalcoholic fatty liver disease in children and adolescents.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Song Kyungchul, Lee Eunju, Lee Hye Sun, Lee Hana, Kim Joon Young, Choi Youngha, Chae Hyun Wook
Аннотация
PURPOSE: Assessing body composition is essential for evaluating metabolic syndrome (MS) and nonalcoholic fatty liver disease (NAFLD). However, studies on the relationship between these conditions and dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) in children and adolescents remain limited. This study aimed to investigate the associations between DXA and BIA parameters, and their utility in predicting MS and NAFLD in the youth.
METHODS: Data from the Korea National Health and Nutrition Examination Survey 2009-2011 and 2022 were analyzed, including 1661 children and adolescents who underwent DXA, and 359 who underwent BIA; 712 were matched through propensity score matching. Pearson correlation and logistic regression analyses (with MS and NAFLD as dependent variables) were used to assess associations between DXA and BIA parameters. Predictive performance was evaluated using area under the receiver operating characteristic (ROC) curve comparisons.
RESULTS: Pearson correlation analyses revealed significant positive correlations between DXA and BIA parameters. In the logistic regression analyses, fat-related parameters were positively associated with MS and NAFLD, whereas muscle-related parameters showed negative associations, even after adjusting for age and sex. In the ROC analyses, BIA body fat mass had the highest predictive performance for both MS and NAFLD, followed by DXA body fat mass and percentage of body fat. Fat-related parameters were superior to muscle-related parameters for predicting MS and NAFLD.
CONCLUSION: BIA and DXA are useful tools for assessing MS and NAFLD in children and adolescents, and their complementary use enhances predictive accuracy, particularly through fat-related parameters.
METHODS: Data from the Korea National Health and Nutrition Examination Survey 2009-2011 and 2022 were analyzed, including 1661 children and adolescents who underwent DXA, and 359 who underwent BIA; 712 were matched through propensity score matching. Pearson correlation and logistic regression analyses (with MS and NAFLD as dependent variables) were used to assess associations between DXA and BIA parameters. Predictive performance was evaluated using area under the receiver operating characteristic (ROC) curve comparisons.
RESULTS: Pearson correlation analyses revealed significant positive correlations between DXA and BIA parameters. In the logistic regression analyses, fat-related parameters were positively associated with MS and NAFLD, whereas muscle-related parameters showed negative associations, even after adjusting for age and sex. In the ROC analyses, BIA body fat mass had the highest predictive performance for both MS and NAFLD, followed by DXA body fat mass and percentage of body fat. Fat-related parameters were superior to muscle-related parameters for predicting MS and NAFLD.
CONCLUSION: BIA and DXA are useful tools for assessing MS and NAFLD in children and adolescents, and their complementary use enhances predictive accuracy, particularly through fat-related parameters.