1. Comparisons of Body-Composition Prediction Accuracy: A Study of 2 Bioelectric Impedance Consumer Devices in Healthy Chinese Persons Using DXA and MRI as Criteria Methods
- Author
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Qi-Yun Cao, Jiguang Wang, Tetsuya Sato, Maoying Wang, Xing-Shan Zhao, Xiaoguang Cheng, Li Xu, and Wei Liang
- Subjects
Adult ,Male ,China ,Endocrinology, Diabetes and Metabolism ,Population ,Young Adult ,Absorptiometry, Photon ,Asian People ,Electric Impedance ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Orthopedics and Sports Medicine ,education ,Bioelectric Impedance ,Dual-energy X-ray absorptiometry ,Aged ,education.field_of_study ,medicine.diagnostic_test ,business.industry ,Limits of agreement ,Reproducibility of Results ,Chinese adults ,Magnetic resonance imaging ,Middle Aged ,Magnetic Resonance Imaging ,Body Composition ,Lean body mass ,Female ,Nuclear medicine ,business ,Bioelectrical impedance analysis - Abstract
We compared the accuracy of body-composition estimation for 2 commercial single-frequency bioelectric impedance analysis (BIA) devices in 200 healthy Chinese adults using magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA) as criterion methods. We evaluated the fat mass percentage (%FM), skeletal muscle mass percentage (%SM), or total-body bone-free lean mass percentage (%TBBLM), and level of visceral fat mass (VF(level)) using the Omron HBF-359 (SF-BIA8) and Tanita BC-532 (SF-BIA4) BIA devices, MRI, and DXA. Both devices showed a similarly high correlation with DXA for %FM prediction (r=0.89 for SF-BIA8 and 0.90 for SF-BIA4) and with MRI and DXA for %SM and %TBBLM prediction (r=0.85 for SF-BIA8 and 0.89 for SF-BIA4). There were small but significant biases in all body-composition parameter evaluations except for %SM assessed by the SF-BIA8. Both the SF-BIA8 and SF-BIA4 provided small, insignificant mean biases but wide limits of agreement with MRI for VF(level) assessments. Both BIA devices can relatively accurately predict %FM and %SM in healthy Chinese adults. The SF-BIA8 is suitable for individual prediction of %SM, whereas the SF-BIA8 is required to eliminate systematic errors in this population by improving population-specific prediction equations from height, weight, and age to increase estimation accuracy.
- Published
- 2011