Bioelectrical impedance analysis in the health field: a still scientifically fragile tool for body composition assessmentDear Editor,
The paper entitled "Bioelectrical impedance analysis and skinfold thickness for the estimation of body fat: A population-based study in southern Brazil," published in the Revista da Associacão Médica Brasileira (2025), compared bioelectrical impedance analysis (BIA) and skinfold measurements for estimating body fat in adults. Arlindo Sousa et al. concluded that the two methods (BIA and skinfold) showed good agreement between the mean values of body fat percentage1. This is a wonderful study1. I sincerely congratulate the authors on their excellent work1. My scientific critique focuses exclusively on highlighting the scientifically fragile nature of the BIA for body composition assessment. The use of BIA as a bedside method has increased because the equipment is portable and safe, the procedure is simple and "non-invasive," and the results are reproducible and rapid2. More recently, segmental BIA has been developed to overcome inconsistencies between trunk resistance and body mass3. However, it is still a scientifically fragile tool for body composition assessment4.
In addition, BIA measurements must be standardized to obtain reproducible body composition: reported mean coefficients of variation for within-day resistance measurements are ≈1–2%; daily or weekly intra-individual variability is slightly greater, ranging from ≈2 to 3.5%; daily coefficients of variation increase for frequencies below 50 kHz3,4. Overall reproducibility/precision is 2.7–4.0%. Prediction errors have been estimated to be 3–8% for total body water and 3.5–6% for fat-free mass (one of the body composition assessment components)4.
Body composition estimates are based on specific and general mathematical models5. Generalist models are more scientifically fragile because they are applicable to different populations and age groups (and therefore have more errors)6. Specific models have fewer errors because they have been validated for a specific population5–7. The article by Arlindo Sousa et al. provides an example1.
The authors1 adopted the body density formulas proposed by Petrosky to estimate body fat from skinfolds, as they have been validated in a sample of adults from southern Brazil (i.e., a specific mathematical model)8,9, namely: men (18–66 years old): 1.10726863—(0.00081201*X4)+(0.00000212*X42)—(0.00041761*age); women (18–51 years old): 1.02902361—(0.00067159*X4)+(0.00000242*X42)—(0.00026073*age)—(0.00056009*body mass)+(0.00054 649*stature). Finally, the Siri's equation was used to convert body density into body fat percentage10.
The above example demonstrates the need to use specific equations for each population and points to the scientific fragility of BIA for body composition assessment, suggesting the question: for which population has BIA been validated? What mathematical models are available in their software? BIAs used in assessment routines do not demonstrate the equations used to estimate body density and body composition, and this is a serious problem due to it being a doubly indirect method for this purpose. In other words, to determine the margin of error in the assessment, it is necessary to know which mathematical model was used, but manufacturers are not clear about this.
Some scientists may suggest reliability and agreement studies11–14, but this does not solve the problem of the scientifically fragile nature of BIA for body composition assessment, as positive results may be obtained purely by the role of chance in scientific discovery, since it is not known which population is being specifically studied by the BIA software. In contrast, if the BIA happens to use generalist methods, this increases the chance of obtaining positive results—but generalist methods have long been discouraged5.
DATA AVAILABILITY STATEMENT
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
REFERENCES
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1 Arlindo Sousa C, Macedo B, Coutinho Azevedo L, Damasceno NRT, Ittermann T, Völzke H, et al. Bioelectrical impedance analysis and skinfold thickness for the estimation of body fat: a population-based study in southern Brazil. Rev Assoc Med Bras (1992). 2025;71(1):e20240406. https://doi.org/10.1590/1806-9282.20240406
» https://doi.org/10.1590/1806-9282.20240406 -
2 Branco MG, Mateus C, Capelas ML, Pimenta N, Santos T, Mäkitie A, et al. Bioelectrical impedance analysis (BIA) for the assessment of body composition in oncology: a scoping review. Nutrients. 2023;15(22):4792. https://doi.org/10.3390/nu15224792
» https://doi.org/10.3390/nu15224792 -
3 Gonzalez CH, Evans JA, Smye SW, Holland P. Total body water measurement using bioelectrical impedance analysis, isotope dilution and total body potassium: a scoring system to facilitate intercomparison. Eur J Clin Nutr. 2002;56(4):326-37. https://doi.org/10.1038/sj.ejcn.1601316
» https://doi.org/10.1038/sj.ejcn.1601316 -
4 Kyle UG, Bosaeus I, 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. https://doi.org/10.1016/j.clnu.2004.06.004
» https://doi.org/10.1016/j.clnu.2004.06.004 -
5 Pontes-Silva A, Lopes AL, Maciel EDS, Quaresma FRP, Dibai-Filho AV. Human metabolism and body composition: prospects for novel studies. Nutr Rev. 2023;82(1):5-8. https://doi.org/10.1093/nutrit/nuad040
» https://doi.org/10.1093/nutrit/nuad040 -
6 Pontes-Silva A, Kovaleva O, Gadzhiakhmedova A, Luchina A, Sinelnikov M, Maslennikov R, et al. Comments on ‘Relationship between body composition and PBRM1 mutations in clear cell renal cell carcinoma: a propensity score matching analysis’. Rev Assoc Med Bras (1992). 2023;69(9):e20230721. https://doi.org/10.1590/1806-9282.20230721
» https://doi.org/10.1590/1806-9282.20230721 -
7 Pontes-Silva A. Comment on "Relationship between different body composition and bone mineral density in Qinhuangdao city". Rev Assoc Med Bras (1992). 2022;68(10):1360. https://doi.org/10.1590/1806-9282.20220556
» https://doi.org/10.1590/1806-9282.20220556 -
8 Petroski EL, Neto CSP. Validação de equações antropométricas para a estimativa da densidade corporal em homens. Rev Bras Atividade Física Saúde. 1996;1:5-14. https://doi.org/10.12820/rbafs.v.1n3p5-14
» https://doi.org/10.12820/rbafs.v.1n3p5-14 - 9 Petroski EL, Neto CSP. Validação de equações antropométricas para a estimativa da densidade corporal em mulheres. Rev Bras Atividade Física Saúde. 1995;1:65-73.
- 10 Siri WE. Body composition from fluid space and density. In: Brozek J, Hanschel A, editors. Tech Meas body Compos. Washingt DC: National Academy of Sciences; 1961. p. 223-4.
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11 Schoeller DA. Bioelectrical impedance analysis. What does it measure? Ann N Y Acad Sci. 2000;904:159-62. https://doi.org/10.1111/j.1749-6632.2000.tb06441.x
» https://doi.org/10.1111/j.1749-6632.2000.tb06441.x -
12 Marra M, Sammarco R, Lorenzo A, Iellamo F, Siervo M, Pietrobelli A, et al. Assessment of body composition in health and disease using bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA): a critical overview. Contrast Media Mol Imaging. 2019;2019:3548284. https://doi.org/10.1155/2019/3548284
» https://doi.org/10.1155/2019/3548284 -
13 Gheri CF, Scalfi L, Luisi MLE, Vincenzo O. Bioelectrical impedance analysis (BIA) phase angle in stroke patients: a systematic review. Clin Nutr. 2024;43(12):63-72. https://doi.org/10.1016/j.clnu.2024.10.001
» https://doi.org/10.1016/j.clnu.2024.10.001 -
14 Aleixo GFP, Shachar SS, Nyrop KA, Muss HB, Battaglini CL, Williams GR. Bioelectrical impedance analysis for the assessment of sarcopenia in patients with cancer: a systematic review. Oncologist. 2020;25(2):170-82. https://doi.org/10.1634/theoncologist.2019-0600
» https://doi.org/10.1634/theoncologist.2019-0600
Edited by
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Scientifıc Editor:
Roseli Nomura http://orcid.org/0000-0002-6471-2125
