Variations in bioelectrical impedance devices impact raw measures comparisons and subsequent prediction of body composition using recommended estimation equations

被引:3
作者
Bennett, Jonathan P. [1 ]
Cataldi, Devon [1 ]
Liu, Yong En [1 ]
Kelly, Nisa N. [1 ]
Quon, Brandon K. [1 ]
Gonzalez, Maria Cristina [3 ]
Heymsfield, Steven B. [2 ]
Shepherd, John A. [1 ]
机构
[1] Univ Hawaii Canc Ctr, Dept Epidemiol, 701 Ilalo St, Honolulu, HI 96813 USA
[2] Louisiana State Univ, Pennington Biomed Res Ctr, 6400 Perkins Rd, Baton Rouge, LA 70808 USA
[3] Univ Fed Pelotas, Grad Program Nutr & Foods, Rua Gomes Carneiro,01 Ctr, BR-96010610 Pelotas, Brazil
关键词
Bioelectrical impedance analysis; Phase angle; Bioelectrical impedance vector analysis; BIVA; Empirical estimation; Body composition; Validation; Athletes; PHASE-ANGLE; BIOIMPEDANCE; PERFORMANCE; VECTOR;
D O I
10.1016/j.clnesp.2024.07.009
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Background & aims: Bioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA devices and the proprietary prediction equations used, studies have recommended the use of raw measures of resistance (R) and reactance (Xc) within population-specific equations to predict body composition. Objective: We compared raw measures from three BIA devices to assess inter-device variation and the impact of differences on body composition estimations. Methods: Raw R, Xc, impedance (Z) parameters were measured on a calibrated phantom and athletes using tetrapolar supine (BIASUP4), octapolar supine (BIASUP8), and octapolar standing (BIASTA8) devices. Measures of R and Xc were compared across devices and graphed using BIA vector analysis (BIVA) and raw parameters were entered into recommended athlete-specific equations for predicting fat-free mass (FFM) and appendicular lean soft tissue (ALST). Whole-body FFM and regional ALST were compared across devices and to a criterion five-compartment (5C) model and dual energy X-ray absorptiometry for ALST. Results: Data from 73 (23.2 +/- 4.8 y) athletes were included in the analyses. Technical differences were observed between Z (range 12.2-50.1U) measures on the calibrated phantom. Differences in whole-body impedance were apparent due to posture (technological) and electrode placement (biological) factors. This resulted in raw measures for all three devices showing greater dehydration on BIVA compared to published norms for athletes using a separate BIA device. Compared to the 5C FFM, significant differences (p < 0.05) were observed on all three equations for BIASUP8 and BIASTA8, with constant error (CE) from -2.7 to -4.6 kg; no difference was observed for BIASUP4 or when device-specific algorithms were used. Published equations resulted in differences as large as 8.8 kg FFM among BIA devices. For ALST, even after a correction in the error of the published empirical equation, all three devices showed significant (p < 0.01) CE from -1.6 to -2.9 kg. Conclusions: Raw bioimpedance measurements differ among devices due to technical, technological, and biological factors, limiting interchangeability of data across BIA systems. Professionals should be aware of these factors when purchasing systems, comparing data to published reference ranges, or when applying published empirical body composition prediction equations. Published by Elsevier Ltd on behalf of European Society for Clinical Nutrition and Metabolism.
引用
收藏
页码:540 / 550
页数:11
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