Agreement between AVABIO380® and InBody270® Bioelectrical Impedance Analyzers for Estimating Body Fat Percentage in a Brazilian Population
DOI:
https://doi.org/10.62827/nb.v25i2.3084Keywords:
Electric Impedance; Body Composition; Validation Study; Diagnostic Equipment; Body Fat Distribution.Abstract
Introduction: Electrical bioimpedance is a non-invasive, practical, and widely used method for estimating body composition. Multifrequency and octopolar devices may improve the accuracy of estimates; however, new devices require agreement studies with previously validated equipment before use in clinical and population settings. Objective: This study analyzed the agreement between the AVABIO380â multifrequency bioimpedance analyzer and the validated reference device InBody270â in estimating body fat percentage (%BF) in a heterogeneous Brazilian population. Methods: A cross-sectional agreement study was conducted with 100 volunteers (70 men, 30 women; 13–66 years). Measurements were performed using both devices, following a standardized protocol. Statistical analysis included the Intraclass Correlation Coefficient (ICC), Lin’s Concordance Correlation Coefficient (CCC), and Bland-Altman analysis to assess bias and limits of agreement (LoA). Results: High agreement was observed between the devices (ICC = 0.954; CCC = 0.976). Bland-Altman analysis showed a mean difference of -0.363 p.p, which was not statistically different from zero (95% CI: -0.868 to 0.142), with limits of agreement ranging from -5.35% to 4.62 p.p. Sex-stratified analysis maintained strong agreement for women (CCC = 0.968) and men (CCC = 0.953). Conclusion: The AVABIO380â analyzer demonstrated strong statistical agreement with the InBody270â. However, limits of agreement of approximately ±5 percentage points should be considered when interpreting individual assessments, as they may represent clinically relevant variations. The device appears to be a viable alternative for body composition analysis, provided that interpretation of its results takes into account the observed limits of agreement.
References
Khalil SF, Mohktar MS, Ibrahim F. The theory and fundamentals of bioimpedance analysis in clinical status monitoring and diagnosis of diseases. Sensors (Basel). 2014;14(6):10895-928. doi:10.3390/s140610895.
Dupertuis YM, Jimaja W, Beardsley Levoy C, Genton L. Bioelectrical impedance analysis instruments: how do they differ, what do we need for clinical assessment? Curr Opin Clin Nutr Metab Care. 2025;28(5):379-87. doi:10.1097/MCO.0000000000001142.
Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis-part I: review of principles and methods. Clin Nutr. 2004;23(5):1226-43. doi:10.1016/j.clnu.2004.06.004.
Heymsfield SB, Lohman TG, Wang ZM, Going SB, editors. Human body composition. 2nd ed. Champaign (IL): Human Kinetics; 2005. 536 p.
Foster KR, Lukaski HC. Whole-body impedance–what does it measure? Am J Clin Nutr. 1996;64(3 Suppl):388S-96S. doi:10.1093/ajcn/64.3.388S.
El Dimassi S, Gautier J, Zalc V, Boudaoud S, Istrate D. Body water volume estimation using bioimpedance analysis: where are we? IRBM. 2024;45(3):100839. doi:10.1016/j.irbm.2024.100839.
Hamilton-James K, Collet TH, Pichard C, Genton L, Dupertuis YM. Precision and accuracy of bioelectrical impedance analysis devices in supine versus standing position with or without retractable handle in Caucasian subjects. Clin Nutr ESPEN. 2021;45:267-74. doi:10.1016/j.clnesp.2021.08.010.
Looney DP, Schafer EA, Chapman CL, Pryor RR, Potter AW, Roberts BM, et al. Reliability, biological variability, and accuracy of multi-frequency bioelectrical impedance analysis for measuring body composition components. Front Nutr. 2024;11:1491931. doi:10.3389/fnut.2024.1491931.
Lukaski HC, Vega Diaz N, Talluri A, Nescolarde L. Classification of hydration in clinical conditions: indirect and direct approaches using bioimpedance. Nutrients. 2019;11(4):809. doi:10.3390/nu11040809.
Matthie J. Bioimpedance measurements of human body composition: critical analysis and outlook. Expert Rev Med Devices. 2008;5(2):239-61. doi:10.1586/17434440.5.2.239.
Ling CH, de Craen AJ, Slagboom PE, Gunn DA, Stokkel MP, Westendorp RG, et al. Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population. Clin Nutr. 2011;30(5):610-5. doi:10.1016/j.clnu.2011.04.001.
Ward LC. Bioelectrical impedance analysis for body composition assessment: reflections on accuracy, clinical utility, and standardisation. Eur J Clin Nutr. 2019;73(1):1-6. doi:10.1038/s41430-018-0335-3.
McLester CN, Nickerson BS, Kliszczewicz BM, McLester JR. Reliability and agreement of various InBody body composition analyzers as compared to dual-energy X-ray absorptiometry in healthy men and women. J Clin Densitom. 2020;23(3):443-50. doi:10.1016/j.jocd.2018.10.008.
Anderson LJ, Erceg DN, Schroeder ET. Utility of multifrequency bioelectrical impedance compared with dual-energy X-ray absorptiometry for assessment of total and regional body composition varies between men and women. Nutr Res. 2012;32(7):479-85. doi:10.1016/j.nutres.2012.05.009.
Larsen MN, Krustrup P, Araújo Póvoas SC, Castagna C. Accuracy and reliability of the InBody 270 multi-frequency body composition analyser in 10-12-year-old children. PLoS One. 2021;16(3):e0247362. doi:10.1371/journal.pone.0247362.
Brasil. Agência Nacional de Vigilância Sanitária. Resolução RDC nº 751, de 15 de setembro de 2022. Dispõe sobre a classificação de risco, os regimes de notificação e de registro, e os requisitos de rotulagem e instruções de uso de dispositivos médicos. Brasília (DF): ANVISA; 2022.
Mokkink LB, Prinsen CA, Bouter LM, de Vet HC, Terwee CB. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and how to select an outcome measurement instrument. Braz J Phys Ther. 2016;20(2):105-13. doi:10.1590/bjpt-rbf.2014.0143.
Brasil. Conselho Nacional de Saúde. Resolução nº 466, de 12 de dezembro de 2012. Aprova diretrizes e normas regulamentadoras de pesquisas envolvendo seres humanos. Brasília: Conselho Nacional de Saúde; 2012. Disponível em https://conselho.saude.gov.br
Bredella MA. Sex differences in body composition. Adv Exp Med Biol. 2017; 1043:9-27. doi:10.1007/978-3-319-70178-3_2.
Díaz-González CM, Mateos-López N, De la Rosa-Hormiga M, Carballo-Hernández G. Influence of hospital environmental variables on thermometric measurements and level of concordance: a cross-sectional descriptive study. Int J Environ Res Public Health. 2023;20(5):4665. doi:10.3390/ijerph20054665.
InBody Co., Ltd. InBody270 user manual. Seoul: InBody; 2020.
Malavolti M, Mussi C, Poli M, Fantuzzi AL, Salvioli G, Battistini N, et al. Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21-82 years. Ann Hum Biol. 2003;30(4):380-91.
Avanutri Equipamentos de Saúde. Manual do usuário AVABIO380. Três Rios (RJ): Avanutri; 2025.
Miot HA. Avaliação da normalidade dos dados em estudos clínicos e experimentais. J Vasc Bras. 2017;16(2):88-91. doi:10.1590/1677-5449.041117.
Bonett DG, Wright TA. Sample size requirements for estimating Pearson, Kendall and Spearman correlations. Psychometrika. 2000;65(1):23-28. doi:10.1007/BF02294183.
Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45(1):255-68. doi:10.2307/2532051.
Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307-10. doi:10.1016/S0140-6736(86)90837-8.
Spearman rank correlation coefficient. In: Lovric M, editor. International encyclopedia of statistical science. Berlin: Springer; 2011. p. 1349-50. doi:10.1007/978-3-642-04898-2_639.
Python Software Foundation. Python 3.11 documentation [Internet]. Wilmington (DE): Python Software Foundation; 2026 [cited 2026 May 19]. Available from: https://docs.python.org/3.11/
Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods. 2020;17(3):261-72. doi:10.1038/s41592-019-0686-2.
Yang SW, Kim TH, Choi HM. The reproducibility and validity verification for body composition measuring devices using bioelectrical impedance analysis in Korean adults. J Exerc Rehabil. 2018;14(4):621-7. doi:10.12965/jer.1836284.142.
Siedler MR, Rodriguez C, Stratton MT, Harty PS, Keith DS, Green JJ, et al. Assessing the reliability and cross-sectional and longitudinal validity of fifteen bioelectrical impedance analysis devices. Br J Nutr. 2023;130(5):827-40. doi:10.1017/S0007114522003749.
Doğan NÖ. Bland-Altman analysis: a paradigm to understand correlation and agreement. Turk J Emerg Med. 2018;18(4):139-41. doi:10.1016/j.tjem.2018.09.001.
Dehghan M, Merchant AT. Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J. 2008;7:26. doi:10.1186/1475-2891-7-26.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Manoel Henrique Pereira Coutinho, Leticia Azen Alves Coutinho, Danielli Braga de Mello (Autor)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Autores que publicam nesta revista concordam com os seguintes termos:
Autores mantém os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho simultaneamente licenciado sob a Licença Creative Commons Attribution 4.0 que permite o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
Autores têm autorização para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
