Agreement between anthropometric equations and multifrequency bioimpedance for estimating body fat percentage in young Chilean adults
DOI:
https://doi.org/10.12873/Keywords:
composición corporal, grasa subcutánea, impedancia bioeléctricaAbstract
Introduction: Determining body composition is essential
for maintaining good control of people’s health, but its estimation depends on the method applied, since there is the possibility of delivering data that does not coincide with each other.
Objectives: To evaluate the degree of agreement of the
most commonly used predictive equations in determining body fat percentage (%BF) and bioimpedance.
Materials and methods: Cross-sectional concordance
study. 100 healthy adults between 18-35 years old
(61% women) were studied. The equations of Palafolls
2019, Lean 1996, Brozek 1963 and Deurenberg 1991 were applied; in addition to a bioelectrical impedance (BIA) with Seca mBCA 525 equipment. The intraclass compensation coefficient (ICC) and Bland-Altman graphs were applied. The R-Studio package was applied.
Results: Compared with BIA, the Brozek 1963 and Deurenberg 1991 equations presented ICC=0.84 (95%CI: 0.76-0.89) and 0.84 (95%CI: 0.77-0.89); while Palafolls 2019 was 0.73 (95%CI: 0.42-0.86) and with Lean 1996 0.36 (95%CI: 0.180.52). The four equations present an inverse systematic cycle for the determination of fat mass.
Conclusions: Fat estimates with the Brozek, 1963 and
Deurenberg 1991 equations can be interchanged with BIA.
The observed inverse cycle creates a challenge for re
searchers to search for predictors in new equations that minimize such errors.
References
1. Sakers A, De Siqueira MK, Seale P, Villanueva CJ. Adipose-tissue plasticity in health and disease. Cell. 2022;185(3):419-46. DOI: https://doi.org/10.1016/j.cell.2021.12.016
2. Molina-Luque R, Romero-Saldaña M, Álvarez-Fernández C, Bennasar-Veny M, Álvarez-López Á, Molina-Recio G. Equation Córdoba: A Simplified Method for Estimation of Body Fat (ECORE-BF). Int J Environ Res Public Health. 2019;16(22):4529. DOI: https://doi.org/10.3390/ijerph16224529
3. Barrios V, Gómez-Huelgas R, Rodríguez R, de Pablos-Velasco P. Adiponectina, un factor de riesgo cardiovascular emergente. Estudio REFERENCE. Rev Esp Cardiol. 2008;61(11):1159-67. DOI: https://doi.org/10.1157/13127847
4. Mill-Ferreyra E, Cameno-Carrillo V, Saúl-Gordo H, Camí-Lavado MC. Estimación del porcentaje de grasa corporal en función del índice de masa corporal y perímetro abdominal: fórmula Palafolls. Semergen. 2019;45(2):101-8. DOI: https://doi.org/10.1016/j.semerg.2018.04.007
5. Holmes CJ, Racette SB. The Utility of Body Composition Assessment in Nutrition and Clinical Practice: An Overview of Current Methodology. Nutrients. 2021;13(8):2493. DOI: https://doi.org/10.3390/nu13082493
6. Liu M, Zhang Z, Zhou C, Ye Z, He P, Zhang Y, et al. Predicted fat mass and lean mass in relation to all-cause and cause-specific mortality. J Cachexia Sarcopenia Muscle. 2022;13(2):1064-75. DOI: https://doi.org/10.1002/jcsm.12921
7. Pineau JC, Ramírez Rozzi FV. Measuring body fat-How accurate is the extrapolation of predictive models in epidemiology? PLoS One. 2022;17(2):e0263590. DOI: https://doi.org/10.1371/journal.pone.0263590
8. Moonen HPFX, Van Zanten ARH. Bioelectric impedance analysis for body composition measurement and other potential clinical applications in critical illness. Curr Opin Crit Care. 2021;27(4):344-53. DOI: https://doi.org/10.1097/MCC.0000000000000840
9. Regli IB, Turner R, Woyke S, Rauch S, Brugger H, Gatterer H. Bioelectrical Impedance Vector Analysis: A Valuable Tool to Monitor Daily Body Hydration Dynamics at Altitude. Int J Environ Res Public Health. 2021;18(10):5455. DOI: https://doi.org/10.3390/ijerph18105455
10. Wells JC, Williams JE, Ward LC, Fewtrell MS. Utility of specific bioelectrical impedance vector analysis for the assessment of body composition in children. Clin Nutr. 2021;40(3):1147-54. DOI: https://doi.org/10.1016/j.clnu.2020.07.022
11. Penagini F, Leone A, Borsani B, Bosetti A, Dilillo D, Rendo G, et al. Predictive Fat Mass Equations for Children With Inflammatory Bowel Disease. J Pediatr Gastroenterol Nutr. 2021;73(4):e98-e104. DOI: https://doi.org/10.1097/MPG.0000000000003188
12. Kammerer M, Ceballos NC, Mayor MC, Hoyos HH, Gómez S. Evaluación de la exactitud de distintas fórmulas de predicción de la composición corporal, comparadas con la absorciometría de energía dual de rayos X, en futbolistas de equipos profesionales colombianos. Nutr Hosp 2021;38(2):290-7. DOI: https://doi.org/10.20960/nh.03206
13. Salazar G, Leyton B, Aguirre C, Anziani A, Weisstaub G, Corvalán C. Anthropometric and bioimpedance equations for fat and fat-free mass in Chilean children 7-9 years of age. Br J Nutr. 2021;126(1):37-42. DOI: https://doi.org/10.1017/S0007114520003906
14. Manzo-Sepúlveda F, Rodríguez-Sanhueza M, Cares-Muñoz A, López-Espinoza M. Degree of agreement of percentage fat mass in young adults estimated with skinfolds versus bioelectrical impedance. Salud, Ciencia y Tecnología. 2024; 3: 715. DOI: https://doi.org/10.56294/saludcyt2023715
15. Martín V, Gómez J, Antoranz MJ. Body Fat Estimated by Bioelectrical Impedance, Skinfold Thickness and Anthropometric Equations. A Comparative Analysis. Rev Esp Salud Pública 2001; 75: 221-36.
16. Ortega JA, Vázquez F, Vélez M, Cortés C, Barrios C, Cueto K, et al. Comparison of classical anthropometry methods and bioelectrical impedance through the determination of body composition in university students. Nutr Clín Diet Hosp. 2018;38(4):164-71. DOI: https://doi.org/10.12873/384ortega
17. Lean MEJ, Han TS, Deurenberg P. Predicting body composition by densitometry from simple anthropometric measurements. Am J Clin Nutr 1996; 63: 4-14
18. Brozek J, Grande F, Anderson JT, Keys A. Densitometric analysis of body composition: revision of some quantitative assumptions. Ann N Y Acad Sci. 1963;110:113-40. DOI: https://doi.org/10.1111/j.1749-6632.1963.tb17079.x
19. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr. 1974;32(1):77-97. DOI: https://doi.org/10.1079/bjn19740060
20. Deurenberg P, Weststrate JA, Seidell JC. Body mass index as a measure of body fatness: age- and sex-specific prediction formulas. Br J Nutr. 1991;65(2):105-14. DOI: https://doi.org/10.1079/bjn19910073
21. Lehnert B. BlandAltmanLeh Intro. R-project.org. Acceso el 23 de noviembre de 2023. Disponible en: https://cran.r-project.org/web/packages/BlandAltmanLeh/vignettes/Intro.html
22. Package “irr”. R-project.org. 2022. Acceso el 23 de noviembre de 2023. Disponible en: https://cran.r-project.org/web/packages/irr/irr.pdf
23. The R project for statistical computing. R-project.org. Acceso el 23 de noviembre de 2023. Disponible en: https://www.r-project.org/20
24. Eraso-Checa F, Rosero R, González C, Cortés D, Hernández E, Polanco J, et al. Modelos de composición corporal basados en antropometría: revisión sistemática de literatura. Nutr Hosp. 2023;40(5): 1068-79. DOI: https://dx.doi.org/10.20960/nh.04377
25. López-González AA, Martínez A, Silveira C, Martínez A, Arroyo S, Altisench B, et al. The CUN-BAE, Deurenberg Fat Mass, and visceral adiposity index as confident anthropometric indices for early detection of metabolic syndrome components in adults. Sci Rep. 2022: 12: 15486. DOI: https://doi.org/10.1038/s41598-022-19343-w
26. Bunt JC, Lohman TG, Boileau RA. Impact of total body water fluctuations on estimation of body fat from body density. Med Sci Sports Exerc. 1989;21(1):96-100. DOI: https://doi.org/10.1249/00005768-198902000-00017
27. Bautista M, Guadarrama R, Veytia M. Prevalencia de obesidad según los indicadores: porcentaje de grasa corporal, índice de masa corporal y circunferencia de cintura. Nutr Clín Diet Hosp. 2020; 40(3):18-25. DOI: https://doi.org/10.12873/403bautista
28. Mill-Ferreyra E, Cameno-Carrillo V, Saúl-Gordo H, Camí-Lavado MC. Estimación del porcentaje de grasa corporal en función del índice de masa corporal y perímetro abdominal: fórmula Palafolls, Medicina de Familia. SEMERGEN. 2019; 45 (2): 101-8. DOI: https://doi.org/10.1016/j.semerg.2018.04.007
29. McLester C, Nickerson B, Kliszczewicz B, McLester J. 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: https://doi.org/10.1016/j.jocd.2018.10.008
30. Feng Q, Besevic J, Conroy M, Omiyale W, Lacey B, Allen N. Comparison of body composition measures assessed by bioelectrical impedance analysis versus dual-energy X-ray absorptiometry in the United Kingdom Biobank. Clin Nutr ESPEN. 2024; 63:214-25. DOI: https://doi.org/10.1016/j.clnesp.2024.06.040
31. Olinto M, Lins VC, Rocha G, Dourado MA, Dutra M. Practical but Inaccurate? A-Mode Ultrasound and Bioelectrical Impedance Underestimate Body Fat Percentage Compared to Dual-Energy X-ray Absorptiometry in Male College Students. J Funct Morphol Kinesiol. 2024;9(3):113. DOI: https://doi.org/10.3390/jfmk9030113
32. Lopez-Gonzalez D, Wells JCK, Clark P. Body Composition Assessment in Mexican Children and Adolescents. Part 2: Cross-Validation of Three Bio-Electrical Impedance Methods against Dual X-ray Absorptiometry for Total-Body and Regional Body Composition. Nutrients. 2022;14(5):965. DOI: https://doi.org/10.3390/nu14050965
33. Deurenberg P. Limitations of the bioelectrical impedance method for the assessment of body fat in severe obesity. Am J Clin Nutr. 1996; 64 (3 Suppl): 449S-52S
34. Palacio AC, Vargas P, Ghiardo D, Ríos MJ, Vera G, Vergara C, et al . First consensus of Chilean nutritionists on bariatric surgery. Rev Chil Nutr. 2019; 46 (1): 61-72. DOI: http://dx.doi.org/10.4067/s0717-75182019000100061
35. Rubinoa F, Cummingsd D, Eckelf R, Coheng R, Wildingh J, Browni W, et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol. 2025; 13 (3): 221-62. DOI: https://doi.org/10.1016/S2213-8587(24)00316-4
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2025 Nutrición Clínica y Dietética Hospitalaria
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Los lectores pueden utilizar los textos publicados de acuerdo con la definición BOAI (Budapest Open Access Initiative)
