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Vol. 5 No. 1 (2025): Volume 5, Issue 1, Year 2025

Articles

Agreement between Body Fat Estimation Methods: From Durnin and Womersley Equation to Bioimpedance

  • Luisina Andrea Capone,
  • María Victoria Muscia,
  • Diego Nicolás Messina
Luisina Andrea Capone
Universidad Juan Agustín Maza, Facultad de Ciencias de la Nutrición, Acceso Este Lateral Sur 2245, Guaymallén (5519), Mendoza, Argentina
María Victoria Muscia
Universidad Juan Agustín Maza, Facultad de Ciencias de la Nutrición, Acceso Este Lateral Sur 2245, Guaymallén (5519), Mendoza, Argentina
Diego Nicolás Messina
Universidad Juan Agustín Maza, Facultad de Ciencias de la Nutrición, Acceso Este Lateral Sur 2245, Guaymallén (5519), Mendoza, Argentina
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DOI: https://doi.org/10.34256/ijk25112

Published 18-04-2025

Keywords

  • Anthropometry,
  • Electric bioimpedance,
  • Body composition,
  • Waist circumference,
  • Hip circumference

How to Cite

Capone, L. A., Muscia, M. V., & Nicolás Messina, D. (2025). Agreement between Body Fat Estimation Methods: From Durnin and Womersley Equation to Bioimpedance. International Journal of Kinanthropometry, 5(1), 121–131. https://doi.org/10.34256/ijk25112

Copyright (c) 2025 Luisina Andrea Capone, María Victoria Muscia, Diego Nicolás Messina

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Abstract

Introduction: The Durnin-Womersley equation (DWe) for estimating body fat (%BF) and bioelectrical impedance analysis (BIA) generally give similar results, but in some cases the differences are striking, which could be related to the distribution of fat in some individuals. The objective of this study was to analyze the agreement between both methods and investigate their relationship with the distribution of fat mass. Methods: A sample of 326 individuals (201 women and 125 men), aged between 18 and 74 years, was analyzed. Their %BF was determined by DWe and BIA, using a Tanita RD545 scale. Height, waist, and hip circumferences were also analyzed. Absolute differences between methods (DWe-BIA) were analyzed using simple linear correlation, Bland-Altman analysis, and chi-square tests with GraphPad Prism 8 software. Results: There is high agreement between methods; Bland-Altman analysis showed a mean bias of -1.545 points (-10.58 to 7.49), with a higher proportion of cases in which DWe underestimates the %BF calculated by BIA (approximately 2/3 of cases). The higher the value obtained by BIA, the greater the underestimation of DWe. No association was found between height and DWe-BIA differences. An increment in age was associated with a greater probability of overestimation by DWe. Higher values ​​for waist, hip, and waist/height and hip/height ratios were related to a greater probability of underestimation of %BF by the DWe. Conclusions: The DWe tends to underestimate the %BF in relation to that estimated by BIA, as the latter increases. On the other hand, an increment in waist and hip circumferences also increases the probability that this equation underestimates %BF.

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References

  1. Aragon, A. A., Schoenfeld, B. J., Wildman, R., Kleiner, S., VanDusseldorp, T., Taylor, L., Earnest, C.P., Arciero, P. J., Wilborn, C., Kalman, D.S., Stout, J. R., Willoughby, D. S., Campbell, B., Arent, S. M., Bannock, L., Smith-Ryan, A. E., & Antonio, J. (2017). International society of sports nutrition position stand: diets and body composition. Journal of the International Society of Sports Nutrition, 14: 16. https://doi.org/10.1186/s12970-017-0174-y
  2. Arroyo, M., Freire, M., Ansotegui, L., Rocandio, A.M. (2010). Intraobserver error associated with anthropometric measurements made by dietitians. Nutricion hospitalaria, 25(6): 1053–1056.
  3. Bennouar, S., Bachir Cherif, A., Hani, H.M., Kerrouche, A., Abdi, S. (2023). Prediction of body fat percentage: Development and validation of new anthropometric equations. Clinical nutrition ESPEN, 57: 510–518. https://doi.org/10.1016/j.clnesp.2023.08.002
  4. Bland, J.M., Altman, D.G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 1(8476): 307–310. https://doi.org/10.1016/S0140-6736(86)90837-8
  5. Blew, R.M., Sardinha, L.B., Milliken, L.A., Teixeira, P.J., Going, S.B., Ferreira, D.L., Harris, M.M., Houtkooper, L.B., Lohman, T.G. (2002). Assessing the validity of body mass index standards in early postmenopausal women. Obesity research, 10(8): 799–808. https://doi.org/10.1038/oby.2002.108
  6. Cedillo, Y.E., Knight, R.O., Darnell, B., Fernandez, J.R., Moellering, D.R. (2022). Body fat percentage assessment using skinfold thickness agrees with measures obtained by DXA scan in African American and Caucasian American women. Nutrition research, 105: 154–162. https://doi.org/10.1016/j.nutres.2022.07.005
  7. Davidson, L.E., Wang, J., Thornton, J.C., Kaleem, Z., Silva-Palacios, F., Pierson, R.N., Heymsfield, S.B., Gallagher, D. (2011). Predicting fat percent by skinfolds in racial groups: Durnin and Womersley revisited. Medicine and science in sports and exercise, 43(3): 542–549. https://doi.org/10.1249/MSS.0b013e3181ef3f07
  8. Durnin, J.V., Womersley, J. (1974). 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. The British journal of nutrition, 32(1): 77–97. https://doi.org/10.1079/bjn19740060
  9. Escamilla, R.F., Yamashiro, K., Asuncion, R., MacLean, D., Thompson, I.S., McKeough, M. (2024). Comparison of four quick and reliable methods of assessing body fat appropriate for clinical settings among young, middle-age, and older healthy male and female adults. Journal of physical therapy science, 36(9): 518–525. https://doi.org/10.1589/jpts.36.518
  10. Esparza-Ros F, Vaquero-Cristóbal R (2023). Antropometría: Fundamentos para la aplicación e interpretación, McGraw Hill. Spain
  11. Fogelholm, M., van Marken Lichtenbelt, W. (1997). Comparison of body composition methods: a literature analysis. European journal of clinical nutrition, 51(8): 495–503. https://doi.org/10.1038/sj.ejcn.1600448
  12. Garcia, A.L., Wagner, K., Hothorn, T., Koebnick, C., Zunft, H.J., Trippo, U. (2005). Improved prediction of body fat by measuring skinfold thickness, circumferences, and bone breadths. Obesity research, 13(3): 626–634. https://doi.org/10.1038/oby.2005.67
  13. Gordon, C.C., Bradtmiller, B. (1992). Interobserver error in a large scale anthropometric survey. American journal of human biology : the official journal of the Human Biology Council, 4(2): 253–263. https://doi.org/10.1002/ajhb.1310040210
  14. Heymsfield, S.B., Strauss, B.J.G. (2022). The making of a classic: the 1974 Durnin-Womersley body composition paper. The British journal of nutrition, 127(1): 87–91. https://doi.org/10.1017/S0007114521003950
  15. Kok, P., Seidell, J.C., Meinders, A.E. (2004). De waarde en de beperkingen van de 'body mass index' (BMI) voor het bepalen van het gezondheidsrisico van overgewicht en obesitas [The value and limitations of the body mass index (BMI) in the assessment of the health risks of overweight and obesity]. Nederlands tijdschrift voor geneeskunde, 148(48): 2379–2382.
  16. Kouchi, M., Mochimaru, M., Tsuzuki, K., Yokoi, T. (1999). Interobserver errors in anthropometry. Journal of human ergology, 28(1-2): 15–24.
  17. Lee, G., Chang, J., Hwang, S.S., Son, J.S., Park, S.M. (2021). Development and validation of prediction equations for the assessment of muscle or fat mass using anthropometric measurements, serum creatinine level, and lifestyle factors among Korean adults. Nutrition research and practice, 15(1): 95–105. https://doi.org/10.4162/nrp.2021.15.1.95
  18. Lukaski, H.C., Johnson, P.E., Bolonchuk, W.W., Lykken, G.I. (1985). Assessment of fat-free mass using bioelectrical impedance measurements of the human body. The American journal of clinical nutrition, 41(4): 810–817. https://doi.org/10.1093/ajcn/41.4.810
  19. Marin-Jimenez, N., Cruz-Leon, C., Sanchez-Oliva, D., Jimenez-Iglesias, J., Caraballo, I., Padilla-Moledo, C., Cadenas-Sanchez, C., Cuenca-Garcia, M., Castro-Piñero, J. (2022). Criterion-Related Validity of Field-Based Methods and Equations for Body Composition Estimation in Adults: A Systematic Review. Current obesity reports, 11(4): 336–349. https://doi.org/10.1007/s13679-022-00488-8
  20. Marra, M., Sammarco, R., De Lorenzo, A., Iellamo, F., Siervo, M., Pietrobelli, A., Donini, L. M., Santarpia, L., Cataldi, M., Pasanisi, F., Contaldo, F. (2019). 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 & molecular imaging, 2019: 3548284. https://doi.org/10.1155/2019/3548284
  21. Mecherques-Carini, M., Albaladejo-Saura, M., Esparza-Ros, F., Baglietto, N., & Vaquero-Cristóbal, R. (2025). Validity between dual-energy x-ray absorptiometry and bioelectrical impedance for segmental fat analysis and a novel low-cost model developed using anthropometry in young adults. Journal of translational medicine, 23(1): 40. https://doi.org/10.1186/s12967-024-06062-1
  22. Mecherques-Carini, M., Albaladejo-Saura, M., Vaquero-Cristóbal, R., Baglietto, N., & Esparza-Ros, F. (2024). Validity and agreement between dual-energy X-ray absorptiometry, anthropometry and bioelectrical impedance in the estimation of fat mass in young adults. Frontiers in nutrition, 11: 1421950. https://doi.org/10.3389/fnut.2024.1421950
  23. Mecherques-Carini, M., Esparza-Ros, F., Albaladejo-Saura, M., Vaquero-Cristóbal, R. (2022). Agreement and Differences between Fat Estimation Formulas Using Kinanthropometry in a Physically Active Population. Applied Sciences, 12(24): 13043. https://doi.org/10.3390/app122413043
  24. Mehra, A., Starkoff, B.E., Nickerson, B.S. (2025). The evolution of bioimpedance analysis: From traditional methods to wearable technology. Nutrition (Burbank, Los Angeles County, Calif.), 129: 112601. https://doi.org/10.1016/j.nut.2024.112601
  25. Messina, D.N. (2024). Estimation of Arm Fat Percentage: from Segmental Bioimpedance to Anthropometry. International Journal of Kinanthropometry, 4(1), 24–31. https://doi.org/10.34256/ijk2414
  26. Orsso, C.E., Gonzalez, M.C., Maisch, M.J., Haqq, A.M., Prado, C.M. (2022). Using bioelectrical impedance analysis in children and adolescents: Pressing issues. European journal of clinical nutrition, 76(5): 659–665. https://doi.org/10.1038/s41430-021-01018-w
  27. Reinert, B.L., Pohlman, R., Hartzler, L. (2012). Correlation of Air Displacement Plethysmography with Alternative Body Fat Measurement Techniques in Men and Women. International journal of exercise science, 5(4): 367–378. https://doi.org/10.70252/IKWZ5306
  28. Silva, A.M., Campa, F., Stagi, S., Gobbo, L.A., Buffa, R., Toselli, S., Silva, D.A.S., Gonçalves, E.M., Langer, R.D., Guerra-Júnior, G., Machado, D.R.L., Kondo, E., Sagayama, H., Omi, N., Yamada, Y., Yoshida, T., Fukuda, W., Gonzalez, M.C., Orlandi, S. P., Koury, J.C., Moro, T., Paoli, A., Kruger, S., Schutte, A.E., Andreolli, A., Earthman, C.P., Fuchs-Tarlovsky, V., Irurtia, A., Castizo-Olier, J., Mascherini, G., Petri, C., Busert, L.K., Cortina-Borja, M., Bailey, J., Tausanovitch, Z., Lelijveld, N., Ali Ghazzawi, H., Amawi, A.T., Tinsley, G.,. Kangas, S.T., Salpéteur, C., Vázquez-Vázquez, A., Fewtrell, M., Ceolin, C., Sergi, G., Ward, L.C., Heitmann, B.L., Fernandes da Costa, R., Vicente-Rodriguez, G., Micheletti Cremasco, M., Moroni, A., Shepherd, J., Moon, J., Knaan, T., Müller, M.J., Braun, W., García‐Almeida, J.M., Palmeira, A.L., Santos, I., Larsen, S.C., Zhang, X., Speakman, J.R., Plank, Boyd, L.D., Swinburn, A., Thaddeus Ssensamba, J., Shiose, K., Cyrino, E.S., Bosy-Westphal, A., Heymsfield, S.B., Lukaski, H., Sardinha, L.B., Wells J.C. Marini, E. (2023). The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data. European journal of clinical nutrition, 77(12): 1143–1150. https://doi.org/10.1038/s41430-023-01310-x
  29. Silva, A.M., Silva, T.R., Júdice, P.B., Rosa, G.B., Bernardino, A.V., Magalhães, J.P., Correia, I.R., Hetherington-Rauth, M., Sardinha, L.B. (2025). Regional fat mass estimation using bioelectrical impedance analysis in healthy adults. The British journal of nutrition, 1: 22. Advance online publication. https://doi.org/10.1017/S0007114525000510
  30. Singhal, N., Siddhu, A. (2011). Durnin and Womersley revisited: need for Bland-Altman plots. Medicine and science in sports and exercise, 43(8): 1598–1599. https://doi.org/10.1249/MSS.0b013e318220a122
  31. Sleiman, R., Abdelkader, W., AlTannir, D. (2024). Assessing the Body Composition of "Picky Eaters" Using Body Impedance Analysis: An Experience From a Tertiary Care Center. Cureus, 16(5): e60538. https://doi.org/10.7759/cureus.60538
  32. Smolik, R., Gaweł, M., Kliszczyk, D., Sasin, N., Szewczyk, K., Górnicka, M. (2025). Comparative Analysis of Body Composition Results Obtained by Air Displacement Plethysmography (ADP) and Bioelectrical Impedance Analysis (BIA) in Adults. Applied Sciences, 15(7): 3480. https://doi.org/10.3390/app15073480
  33. Swan, P.D., McConnell, K.E. (1999). Anthropometry and bioelectrical impedance inconsistently predicts fatness in women with regional adiposity. Medicine and science in sports and exercise, 31(7): 1068–1075. https://doi.org/10.1097/00005768-199907000-00023
  34. Sweatt, K., Garvey, W.T., Martins, C. (2024). Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?. Current obesity reports, 13(3): 584–595. https://doi.org/10.1007/s13679-024-00580-1
  35. Vaquero-Cristóbal, R. (2023). Assessing fat mass from a body composition perspective: a critical review. Cultura, Ciencia Y Deporte, 18(56): https://doi.org/10.12800/ccd.v18i56.2033
  36. Vaquero-Cristóbal, R., Albaladejo-Saura, M., Luna-Badachi, A.E., Esparza-Ros, F. (2020). Differences in Fat Mass Estimation Formulas in Physically Active Adult Population and Relationship with Sums of Skinfolds. International journal of environmental research and public health, 17(21): 7777. https://doi.org/10.3390/ijerph17217777
  37. Wu, Y., Li, D., Vermund, S.H. (2024). Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity. International journal of environmental research and public health, 21(6): 757. https://doi.org/10.3390/ijerph21060757