DXA-measured visceral fat mass and lean body mass reflect abnormal metabolic phenotypes among some obese and nonobese Chinese children and adolescents

作者:Ding, W. Q.*; Liu, J. T.; Shang, Y. X.; Gao, B.; Zhao, X. Y.; Zhao, H. P.; Wu, W. J.
来源:Nutrition Metabolism and Cardiovascular Diseases, 2018, 28(6): 618-628.
DOI:10.1016/j.numecd.2018.03.002

摘要

Background and aim: The exact constellation of body composition characteristics among metabolically unhealthy obese (MUO) and nonobese (MUNO) children and adolescents remains unclear. The purpose of this study was to identify the major body composition determinants of metabolically unhealthy phenotypes among Chinese children and adolescents. @@@ Methods and results: We used data from a cross-sectional survey in 2015 that included 1983 children and adolescents aged 6-18 years. Subjects were classified into two phenotypes based on a combination of body mass index (BMI) and metabolic syndrome components. Body composition was measured by dual-energy X-ray absorptiometry (DXA). Among all boys and among adolescent boys, those with MUNO phenotypes displayed significantly higher indices of body composition except for fat mass (FM) percentage and trunk-to-legs FM ratio compared with the metabolically healthy nonobese phenotype (all P < 0.05). MUO individuals had higher arm FM, lean body mass (LBM), and trunk lean mass compared to metabolically healthy obese individuals (all P < 0.05). Visceral fat mass (VFM) and BMI were the major independent determinants of MUNO (VFM, 6- to 9-year-old boys, OR = 1.02, 95% CI = 1.00-1.03, P = 0.021; BMI, 6- to 9-year-old girls, OR = 1.90, 95% CI = 1.31-2.84, P = 0.001; and adolescent boys, OR = 1.34, 95% CI = 1.23-1.44, P < 0.001). LBM was the major independent predictor of MUO among adolescent boys (OR = 1.90, 95% CI = 1.03-1.17, P = 0.003). @@@ Conclusions: Among children and adolescents, the metabolically unhealthy phenotype was associated with excess of body composition, but with significant differences observed based on age and sex. VFM and LBM derived by DXA can predict the metabolically unhealthy phenotype effectively in specific sex and age groups. (C) 2018 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V.