Comparison of Laboratory-Grade and Consumer-Grade Hand-to-Foot Bioelectrical Impedance Analyzers for Body Composition Estimation

Bioelectrical impedance analysis (BIA) is a simple and effective technique to estimate body composition, including body fat percentage (BFP). While these analyzers are a popular method of describing a person’s body composition, laboratory-grade devices are expensive and inaccessible to most people. As a result, they may be an unrealistic method for consumers to use. However, consumer-grade devices are increasingly available. PURPOSE: The purpose of this study was to compare laboratory-grade and consumer-grade bioelectrical impedance analyzers. METHODS: Seventy-five adults (40 F, 35 M) were evaluated using a laboratory-grade, hand-to-foot, multifrequency bioelectrical impedance analyzer (BIALAB; Seca mBCA 515) and a consumer-grade, hand-to-foot, single frequency bioelectrical impedance analyzer (BIACON; Omron HBF-516). Both devices administer undetectable electrical pulses through one extremity that are measured at another extremity, where the voltage drop (impedance) is determined. This information is used to estimate body fluids and composition. RESULTS: A strong, statistically significant correlation between devices was observed for BFP (r: 0.93, R2: 0.87, pCON overestimated BFP by 3.5 ± 3.4% (mean ± SD) relative to BIALAB (BIACON: 28.3 ± 9.6%; BIALAB: 24.8 ± 9.3%; pCONCLUSION: These results collectively suggest that while the laboratory-grade and consumer-grade analyzers in our study exhibit strong correlations when assessing a group of individuals, the consumer-grade device overestimates BFP. Additionally, the SEE indicates that 3.4% error can be expected with the consumer-grade device. Overall, the Omron HBF-516 consumer-grade device may be an adequate and affordable option to estimate body composition in some contexts, but results should be interpreted cautiously when used in individuals

Analyzing the Between-Day Reliability of Three-Dimensional Body Scanners for Body Composition Assessment

In the growing world of health and well-being, three-dimensional (3D) scanning is emerging as a popular tool to assess body composition. While body composition cannot be truly “measured” in living humans, it can be approximated. This, however, leads to two types of errors (i.e., technical and biological) in the body composition assessment. PURPOSE: This study was used to determine what percent or range of percentages in body fat one must exceed before concluding a real change has occurred. By conducting assessments on separate days, with only a short period of time between them, true changes in body composition are unlikely to occur. Therefore, this design can help determine the inherent, between-day error in a body fat assessment to provide context for longer-term changes. METHODS: In the present investigation, thirteen participants were scanned using three distinct 3D body scanners (Fit3D Proscanner, Sizestream SS20, and Styku S100) on two separate mornings, separated by 24 to 48 hours. Each subject had to follow the pre-assessment restrictions and ensure they fit all the eligibility requirements for this study. Then, all body fat percentage (BF%) values from the 3D scanners were recorded and analyzed to determine the between-day reliability. RESULTS: Intraclass correlation coefficients ranged from 0.971 to 0.997 for the three scanners. The least significant change (LSC) values were 1.2%, 2.6%, and 3.0% for the Styku S100, Fit3D Proscanner, and Sizestream SS20, respectively. When examining differences in BF% for individual participants, the between-day differences ranged from -1.1% to 1.0% for Styku S100, -1.9% to 3.2% for Fit3D Proscanner, and -4.0% to 3.0% for SizeStream SS20. CONCLUSION: These results collectively suggest that the Styku S100 has the highest between-day reliability and lowest technical error of the three scanning systems. Overall, however, it is important for consumers to understand that each 3D scanner contains some level of error that should be considered when interpreting the results of an assessment. This study can not only be applied to future research determining the most reliable body composition assessments, but it can also aid individuals in understanding how large of a change in body fat is needed to exceed the error of a 3D scanner and therefore be considered a “real” change