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Gabrielle Brewer – Graduate Student, University of North Carolina at Chapel Hill

Malia Blue, MA – Doctoral Candidate, University of North Carolina at Chapel Hill

Katie Hirsch, MA, EP-C, CISSN – Doctoral Candidate, University of North Carolina at Chapel Hill

Austin Peterjohn

Abbie Smith-Ryan


Multi-frequency bioelectrical impedance analysis (BIA) technology offers enhanced body composition outcomes including regional estimates (i.e. trunk, limbs) in a relatively short testing period. Research examining the accuracy of stand-up multi-frequency BIA devices compared against a four-compartment (4C) model criterion is limited. PURPOSE: The purpose of this study was to validate the use of stand-up BIA compared to a 4C model criterion for measurement of body composition including fat mass (FM), fat free mass (FFM), and body fat percentage (%fat) among the total sample and each sex. METHODS: Eighty-two healthy male (n=26) and female (n=56) normal weight young adults (Mean ± SD; Age: 19.6 ± 1.2 years; Height: 168.5 ± 9.3 cm; Weight: 63.0 ± 8.6 kg; BMI: 22.2 ± 1.8 kg/m2) participated in body composition testing. Body composition was determined using a traditional 4C reference assessment to estimate FM, FFM, and %fat. Body volume was determined from air displacement plethysmography, total body bone mineral content was determined from dual-energy absorptiometry, and total body water was estimated in the supine position from bioelectrical impedance spectroscopy (BIS). Body composition was also determined from stand-up BIA. The 4C body composition variables (FM, FFM, and %fat) were compared against estimates by the single BIA test; validity statistics included total error (TE) and standard error of the estimate (SEE) to examine prediction error between BIA measurement and a 4C model for the same variables. RESULTS: Significant differences were found for FM (p< 0.001), FFM (p< 0.001), and %fat (p< 0.001) values between BIA and 4C model estimates. For the total sample, prediction error was the highest for %fat (TE=4.2 %; SEE=3.9 %) compared to FM (TE=2.4 kg; SEE=2.2 kg) and FFM (TE=2.4 kg; SEE=2.2 kg). For the male sample, prediction error of %fat (TE=1.4 %; SEE=2.2 %) and FFM (TE=1.1 kg; SEE=1.6 kg) were ideal compared to the 4C criterion. Prediction error of FFM was the same as FM (TE=1.1 kg; SEE=1.6 kg). For the female sample, prediction error of %fat (TE= 3.9 %; SEE=4.4 %) ranged from good to fairly good; prediction errors were very good to excellent for FFM (TE=2.1 kg; SEE=2.3 kg). Prediction error for FFM were similar to FM (TE=2.1 kg; SEE=2.4 kg). CONCLUSIONS: Validation of stand-up BIA technology compared to a 4C model revealed differences for estimates of FM, FFM and %fat. Specifically, the highest error was seen in %fat for the total sample and each sex. All measurements of error were higher in females compared to males. PRACTICAL APPLICATIONS: These results suggest that utilization of stand-up BIA in men may result in a 1.4 % overestimation of %fat, 1.0 kg overestimation of FM, and 1.0 kg underestimation of FFM compared to estimation by a 4C model. For females, stand-up BIA may result in a 1.7 % overestimation of %fat, 1.0 kg overestimation of FM, and 1.0 kg underestimation of FFM compared to estimation by a 4C model. Estimation for FM and FFM values by stand-up BIA compared to a 4C model demonstrate good agreement, and may be a practical, feasible, and accurate measure of body composition.


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