Publication detail
Assessing Diversity in Predictive Equations for Body Compartment Estimation
KAMPO, D.
Original Title
Assessing Diversity in Predictive Equations for Body Compartment Estimation
Type
conference paper
Language
English
Original Abstract
The paper evaluates the validity of prediction equations for estimating total body water (TBW), extracellular water (ECW), fat-free mass (FFM), and body cell mass (BCM) using bioelectrical impedance analysis (BIA). The study focuses on a sample of 10 Czech individuals of European ethnicity. Prediction equations were selected based on similarity to the study population and were compared to reference ranges for accuracy. Findings show promising outcomes for TBW estimation, with low relative errors (RE) of 0.11% and-3.26% for equations by Deurenberg et al. and Kotler et al. respectively. Matias et al.’s equation for ECW estimation demonstrated the most accurate results with an RE of 2.13%. For FFM estimation, equations by Lukaski et al. and Deurenberg et al. showed favorable outcomes with RE values of 4.4% and-1.27% respectively. However, none of the BCM prediction equations provided satisfactory accuracy. Further research with larger sample sizes is needed for more accurate validation. Nonetheless, this study offers valuable insights into selecting appropriate prediction equations for BIAbased body composition analysis.
Keywords
body composition, bioelectrical impedance analysis, multi-frequency BIA, total body water, extracellular water, fat free mass, body cell mass, prediction equations
Authors
KAMPO, D.
Released
23. 4. 2024
Publisher
Brno University of Technology, Faculty of Electronic Engineering and Communication
Location
Brno
ISBN
978-80-214-6230-4
Book
Proceedings II of the 30th Conference STUDENT EEICT 2024 Selected papers
Edition
1
Pages from
134
Pages to
141
Pages count
8
URL
BibTex
@inproceedings{BUT188933,
author="Dávid {Kampo}",
title="Assessing Diversity in Predictive Equations for Body Compartment Estimation",
booktitle="Proceedings II of the 30th Conference STUDENT EEICT 2024 Selected papers",
year="2024",
series="1",
pages="134--141",
publisher="Brno University of Technology, Faculty of Electronic Engineering and Communication",
address="Brno",
doi="10.13164/eeict.2024.134",
isbn="978-80-214-6230-4",
url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_2.pdf"
}