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      Bioelectrical impedance analysis to estimate body composition, and change in adiposity, in overweight and obese adolescents: comparison with dual-energy x-ray absorptiometry

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          Abstract

          Background

          There is a need for a practical, inexpensive method to assess body composition in obese adolescents. This study aimed to 1) compare body composition parameters estimated by a stand-on, multi-frequency bioelectrical impendence (BIA) device, using a) the manufacturers’ equations, and b) published and derived equations with body composition measured by dual-energy x-ray absorptiometry (DXA) and 2) assess percentage body fat (%BF) change after a weight loss intervention.

          Methods

          Participants were 66 obese adolescents, mean age (SD) 12.9 (2.0) years. Body composition was measured by Tanita BIA MC-180MA (Tanita BIA 8) and DXA (GE-Lunar Prodigy). BIA resistance and reactance data at frequencies of 5, 50, 250 and 500 kHz, were used in published equations, and to generate a new prediction equation for fat-free mass (FFM) using a split-sample method. Approximately half (n = 34) of the adolescents had their body composition measured by DXA and BIA on two occasions, three to nine months apart.

          Results

          The correlations between FFM (kg), fat mass (kg) and %BF measured by BIA and DXA were 0.92, 0.93 and 0.78, respectively. The Tanita BIA 8 manufacturers equations significantly (P < 0.001) overestimated FFM (4.3 kg [-5.3 to 13.9]) and underestimated %BF (-5.0% [-15 to 5.0]) compared to DXA. The mean differences between BIA derived equations and DXA measured body composition parameters were small (0.4 to 2.1%), not significant, but had large limits of agreements (~ ±15% for FFM). After the intervention mean %BF loss was similar by both methods (~1.5%), but with wide limits of agreement.

          Conclusion

          The Tanita BIA 8 could be a valuable clinical tool to measure body composition at the group level, but is inaccurate for the individual obese adolescent.

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          Most cited references25

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            New bioimpedance analysis system: improved phenotyping with whole-body analysis.

            Bioimpedance analysis (BIA) is a potential field and clinical method for evaluating skeletal muscle mass (SM) and %fat. A new BIA system has 8-(two on each hand and foot) rather than 4-contact electrodes allowing for rapid 'whole-body' and regional body composition evaluation. This study evaluated the 50 kHz BC-418 8-contact electrode and TBF-310 4-contact electrode foot-foot BIA systems (Tanita Corp., Tokyo, Japan). There were 40 subject evaluations in males (n=20) and females (n=20) ranging in age from 6 to 64 y. BIA was evaluated in each subject and compared to reference lean soft-tissue (LST) and %fat estimates in the appendages and remainder (trunk+head) provided by dual-energy X-ray absorptiometry (DXA). Appendicular LST (ALST) estimates from both BIA and DXA were used to derive total body SM mass. The highest correlation between total body LST by DXA and impedance index (Ht(2)/Z) by BC-418 was for the foot-hand segments (r=0.986; left side only) compared to the arm (r=0.970-0.979) and leg segments (r=0.942-0.957)(all P or =0.95, P<0.001) and group means did not differ across methods. Skeletal muscle mass calculated (Kim equation) from total ALST by DXA (X+/-s.d.)(23.7+/-9.7 kg) was not significantly different and highly correlated with BC-418 estimates (25.2+/-9.6 kg; r=0.96, P<0.001). There was a good correlation between total body %fat by 8-electrode BIA vs DXA (r=0.87, P<0.001) that exceeded the corresponding association with 4-electrode BIA (r=0.82, P<0.001). Group mean segmental %fat estimates from BC-418 did not differ significantly from corresponding DXA estimates. No between-method bias was detected in the whole body, ALST, and skeletal muscle analyses. The new 8-electrode BIA system offers an important new opportunity of evaluating SM in research and clinical settings. The additional electrodes of the new BIA system also improve the association with DXA %fat estimates over those provided by the conventional foot-foot BIA.
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              Predicting body cell mass with bioimpedance by using theoretical methods: a technological review.

              The body cell mass (BCM), defined as intracellular water (ICW), was estimated in 73 healthy men and women by total body potassium (TBK) and by bioimpedance spectroscopy (BIS). In 14 other subjects, extracellular water (ECW) and total body water (TBW) were measured by bromide dilution and deuterium oxide dilution, respectively. For all subjects, impedance spectral data were fit to the Cole model, and ECW and ICW volumes were predicted by using model electrical resistance terms RE and Rt in an equation derived from Hanai mixture theory, respectively. The BIS ECW prediction bromide dilution was r = 0.91, standard error of the estimate (SEE) 0.90 liter. The BIS TBW prediction of deuterium space was r = 0.95, SEE 1.33 liters. The BIS ICW prediction of the dilution-determined ICW was r = 0.87, SEE 1.69 liters. The BIS ICW prediction of the TBK-determined ICW for the 73 subjects was r = 0.85, SEE = 2.22 liters. These results add further support to the validity of the Hanai theory, the equation used, and the conclusion that ECW and ICW volume can be predicted by an approach based solely on fundamental principles.
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                Author and article information

                Contributors
                angelawan.c.s@gmail.com
                l.ward@uq.edu.au
                jocelyn.halim@gmail.com
                megan.gow@health.nsw.gov.au
                mandy.ho@health.nsw.gov.au
                julie.briody@health.nsw.gov.au
                kelvinleung616@gmail.com
                chris.cowell@health.nsw.gov.au
                sarah.garnett@health.nsw.gov.au
                Journal
                BMC Pediatr
                BMC Pediatr
                BMC Pediatrics
                BioMed Central (London )
                1471-2431
                3 October 2014
                2014
                : 14
                : 1
                : 249
                Affiliations
                [ ]School of Molecular Bioscience, University of Sydney, Sydney, Australia
                [ ]School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
                [ ]Institute of Endocrinology & Diabetes, The Children’s Hospital at Westmead, Locked Bag 4001, Westmead, NSW2145 Australia
                [ ]The Children’s Hospital at Westmead Clinical School, University of Sydney, Sydney, Australia
                [ ]Department of Nuclear Medicine, The Children’s Hospital at Westmead, Sydney, Australia
                [ ]Kids Research Institute, The Children’s Hospital at Westmead, Sydney, Australia
                Article
                1173
                10.1186/1471-2431-14-249
                4288657
                25280868
                a1059aa1-a223-4f34-90fc-4e30bc551dc6
                © Wan et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 24 July 2014
                : 30 September 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Pediatrics
                obese,bioelectrical impedance analysis,dual-energy x-ray absorptiometry,adolescents,cole-cole plot

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