Close this panel
Browse By Date
Browse By Track
Browse By Poster Author
Browse By Title
Browse By Poster Number
Close this panel

(26) VALIDATION OF BIOELECTRICAL IMPEDANCE ANALYSIS COMPARED TO A FOUR-COMPARTMENT MODEL CRITERION


Authors:

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

Abstract:

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.

 

Rate This Poster

Stuff for notes
Stuff for Message board

Share Poster

Help

Technical Support

(877) 426-6323

support@meetingproceedings.com

Feedback

SUBMIT FEEDBACKfeedback icon

We really appreciate your feedback on the eventScribe website. We use the data to improve the experience and simplify the process for users like you.

Comments


Log In / Sign Up


Already have an Event Scheduler or mobile app login? Login with those details. If not, create a login.


Log In   Sign Up
Access your bookmarked poster and notes by logging in ...   Sign up to take notes on poster, bookmark poster, and submit feedback.
 
 
  Lost your access key?      
   
You need to be logged in to bookmark posters, save notes, or rate posters.