Literature DB >> 8065848

Usefulness of bioelectric impedance and skinfold measurements in predicting fat-free mass derived from total body potassium in children.

F Schaefer1, M Georgi, A Zieger, K Schärer.   

Abstract

Despite the increasing use of tetrapolar whole-body bioelectric impedance (BI) analysis in the assessment of body composition, its usefulness in estimating fat-free mass (FFM) has not been evaluated in comparison with conventional skinfold anthropometry in children. We therefore compared 1) the intraobserver and interobserver reproducibility of BI and skinfold measurements and the derived FFM estimates, and 2) the predictability of FFM as calculated from measurements of total body potassium (TBK) using 40K spectrometry by equations based on either BI or skinfold measurements in 112 healthy children, adolescents, and young adults aged 3.9 to 19.3 y. A best-fitting equation to predict TBK-derived FFM from BI and other potential independent predictors was developed and cross validated in two randomly selected subgroups of the study population by stepwise multiple regression analysis. Although the technical error associated with BI measurements was much smaller than that of skinfold measurements, the reproducibility of BI-derived FFM estimates (intraobserver coefficient of variation [CV], 0.39%; interobserver CV, 1.23%) was only slightly better than that of FFM estimates obtained by use of weight and two skinfold measurements (0.62% and 1.39%, respectively). The cross validation procedure yielded the following best-fitting prediction equation: FFM = 0.65 x (height2/impedance) + 0.68 x age + 0.15 (R2 = 0.975, root mean square error = 1.98 kg, CV = 5.8%, 95% limits of agreement = -11.1% to +12.4%). Conventional anthropometry, using published equations to estimate FFM from skinfolds, slightly over-estimated TBK-derived FFM, but predicted FFM with precision similar to the best-fitting equation involving BI. Previously published FFM equations incorporating BI predicted TBK-drived FFM with variable predictive precision and accuracy.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1994        PMID: 8065848

Source DB:  PubMed          Journal:  Pediatr Res        ISSN: 0031-3998            Impact factor:   3.756


  62 in total

1.  Effect of an individualised training programme during weight reduction on body composition: a randomised trial.

Authors:  J Schwingshandl; K Sudi; B Eibl; S Wallner; M Borkenstein
Journal:  Arch Dis Child       Date:  1999-11       Impact factor: 3.791

2.  Pitfalls in the assessment of body composition in survivors of acute lymphoblastic leukaemia.

Authors:  J T Warner; W D Evans; D K H Webb; J W Gregory
Journal:  Arch Dis Child       Date:  2004-01       Impact factor: 3.791

3.  Effects of weight loss on leptin, sex hormones, and measures of adiposity in obese children.

Authors:  K M Sudi; S Gallistl; M H Borkenstein; D Payerl; R Aigner; R Möller; E Tafeit
Journal:  Endocrine       Date:  2001-04       Impact factor: 3.633

4.  Effect of birth weight and weight change during the first 96 h of life on childhood body composition--path analysis.

Authors:  M J Fonseca; M Severo; S Correia; A C Santos
Journal:  Int J Obes (Lond)       Date:  2015-02-03       Impact factor: 5.095

5.  Assessing Body Fatness in Obese Adolescents: Alternative Methods to Dual-Energy X-Ray Absorptiometry.

Authors:  Danielle Colley; Brittany Cines; Nina Current; Chelsea Schulman; Shanna Bernstein; Amber B Courville; Kirsten Zambell; James C Reynolds; Jack Yanovski
Journal:  Digest (Wash D C)       Date:  2015

6.  Relationships of maternal body mass index and plasma biomarkers with childhood body mass index and adiposity at 6 years: The Children of SCOPE study.

Authors:  Kathryn V Dalrymple; John M D Thompson; Shahina Begum; Keith M Godfrey; Lucilla Poston; Paul T Seed; Lesley M E McCowan; Clare Wall; Andrew Shelling; Robyn North; Wayne S Cutfield; Edwin A Mitchell
Journal:  Pediatr Obes       Date:  2019-06-24       Impact factor: 4.000

7.  Comparison of the validity of anthropometric and bioelectric impedance equations to assess body composition in adolescent girls.

Authors:  M Loftin; J Nichols; S Going; M Sothern; K H Schmitz; K Ring; G Tuuri; J Stevens
Journal:  Int J Body Compos Res       Date:  2007

8.  Comparison of different techniques to measure body composition in moderately active adolescents.

Authors:  A De Lorenzo; I Bertini; N Candeloro; L Iacopino; A Andreoli; M D Van Loan
Journal:  Br J Sports Med       Date:  1998-09       Impact factor: 13.800

Review 9.  Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine.

Authors:  G Atkinson; A M Nevill
Journal:  Sports Med       Date:  1998-10       Impact factor: 11.136

10.  Childhood dietary patterns and body composition at age 6 years: the Children of SCOPE study.

Authors:  Angela C Flynn; John M D Thompson; Kathryn V Dalrymple; Clare Wall; Shahina Begum; Jaijus Pallippadan Johny; Wayne S Cutfield; Robyn North; Lesley M E McCowan; Keith M Godfrey; Edwin A Mitchell; Lucilla Poston
Journal:  Br J Nutr       Date:  2020-02-26       Impact factor: 3.718

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