کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
3271271 | 1208265 | 2011 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
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
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
غدد درون ریز، دیابت و متابولیسم
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: 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 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](/preview/png/3271271.png)
چکیده انگلیسی
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 (VFlevel) 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 VFlevel 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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Clinical Densitometry - Volume 14, Issue 4, OctoberâDecember 2011, Pages 458-464
Journal: Journal of Clinical Densitometry - Volume 14, Issue 4, OctoberâDecember 2011, Pages 458-464
نویسندگان
Li Xu, Xiaoguang Cheng, Jiguang Wang, Qiyun Cao, Tetsuya Sato, Maoying Wang, Xingshan Zhao, Wei Liang,