Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Nutrition and Health (including climate and ecological aspects)

The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

Abstract

Background

Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians’ offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the ‘BIA International Database’ project and encourage researchers to join the consortium.

Methods

The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants.

Conclusion

The BIA International Database represents a key resource for research on body composition.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2: Data analysis.
Fig. 3: Graphical representation of the relationship between impedance index (cm2/ Ω) and FFM (assessed by DXA), stratified by age and sex.

Similar content being viewed by others

Data availability

The data sets generated and/or analyzed during the current project are not publicly available due to the data confidentiality requirements of the ethics committee for each study but are available from the corresponding author on reasonable request and approval from the ethics committee.

References

  1. Aleman-Mateo H, Rush E, Esparza-Romero J, Ferriolli E, Ramirez-Zea M, Bour A. et al. Prediction of fat-free mass by bioelectrical impedance analysis in older adults from developing countries: a cross-validation study using the deuterium dilution method. J Nutr Health Aging. 2010;14:418–26. https://doi.org/10.1007/s12603-010-0031-z.

    Article  CAS  PubMed  Google Scholar 

  2. Buchholz AC, Bartok C, Schoeller DA. The validity of bioelectrical impedance models in clinical populations. Nutr Clin Pr. 2004;19:433–46. https://doi.org/10.1177/0115426504019005433.

    Article  Google Scholar 

  3. Earthman C, Traughber D, Dobratz J, Howell W. Bioimpedance spectroscopy for clinical assessment of fluid distribution and body cell mass. Nutr Clin Pr. 2007;22:389–405. https://doi.org/10.1177/0115426507022004389.

    Article  Google Scholar 

  4. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gomez JM. et al. Bioelectrical impedance analysis–part I: review of principles and methods. Clin Nutr. 2004;23:1226–43. https://doi.org/10.1016/j.clnu.2004.06.004.

    Article  PubMed  Google Scholar 

  5. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Manuel Gomez J. et al. Bioelectrical impedance analysis-part II: utilization in clinical practice. Clin Nutr. 2004;23:1430–53. https://doi.org/10.1016/j.clnu.2004.09.012.

    Article  PubMed  Google Scholar 

  6. Campa F, Gobbo LA, Stagi S, Cyrino LT, Toselli S, Marini E, et al. Bioelectrical impedance analysis versus reference methods in the assessment of body composition in athletes. Eur J Appl Physiol. 2022;122:561–89. https://doi.org/10.1007/s00421-021-04879-y.

    Article  PubMed  Google Scholar 

  7. Lukaski HC. Evolution of bioimpedance: a circuitous journey from estimation of physiological function to assessment of body composition and a return to clinical research. Eur J Clin Nutr. 2013;67:S2–9. https://doi.org/10.1038/ejcn.2012.149.

    Article  PubMed  Google Scholar 

  8. Lukaski HC, Kyle UG, Kondrup J. Assessment of adult malnutrition and prognosis with bioelectrical impedance analysis: phase angle and impedance ratio. Curr Opin Clin Nutr Metab Care. 2017;20:330–9. https://doi.org/10.1097/MCO.0000000000000387.

    Article  PubMed  Google Scholar 

  9. Heitmann BL. Prediction of body water and fat in adult Danes from measurement of electrical impedance. A validation study. Int J Obes. 1990;14:789–802.

    CAS  PubMed  Google Scholar 

  10. Bedogni G, Grugni G, Tringali G, Agosti F, Sartorio A. Assessment of fat-free mass from bioelectrical impedance analysis in obese women with Prader-Willi syndrome. Ann Hum Biol. 2015;42:538–42. https://doi.org/10.3109/03014460.2014.990922.

    Article  PubMed  Google Scholar 

  11. Cleary J, Daniells S, Okely AD, Batterham M, Nicholls J. Predictive validity of four bioelectrical impedance equations in determining percent fat mass in overweight and obese children. J Am Diet Assoc. 2008;108:136–9. https://doi.org/10.1016/j.jada.2007.10.004.

    Article  PubMed  Google Scholar 

  12. Costa RFD, Masset K, Silva AM, Cabral B, Dantas PMS Development and cross-validation of predictive equations for fat-free mass and lean soft tissue mass by bioelectrical impedance in Brazilian women. Eur J Clin Nutr. 2021. https://doi.org/10.1038/s41430-021-00946-x

  13. Deurenberg P, van der Kooy K, Leenen R, Weststrate JA, Seidell JC. Sex and age specific prediction formulas for estimating body composition from bioelectrical impedance: a cross-validation study. Int J Obes. 1991;15:17–25.

    CAS  PubMed  Google Scholar 

  14. Deurenberg P, van der Kooy K, Paling A, Withagen P. Assessment of body composition in 8-11 year old children by bioelectrical impedance. Eur J Clin Nutr. 1989;43:623–9.

    CAS  PubMed  Google Scholar 

  15. Dey DK, Bosaeus I, Lissner L, Steen B. Body composition estimated by bioelectrical impedance in the Swedish elderly. Development of population-based prediction equation and reference values of fat-free mass and body fat for 70- and 75-y olds. Eur J Clin Nutr. 2003;57:909–16. https://doi.org/10.1038/sj.ejcn.1601625.

    Article  CAS  PubMed  Google Scholar 

  16. Gonzalez MC, Orlandi SP, Santos LP, Barros AJD. Body composition using bioelectrical impedance: Development and validation of a predictive equation for fat-free mass in a middle-income country. Clin Nutr. 2019;38:2175–9. https://doi.org/10.1016/j.clnu.2018.09.012.

    Article  PubMed  Google Scholar 

  17. Goran MI, Kaskoun MC, Carpenter WH, Poehlman ET, Ravussin E, Fontvieille AM. Estimating body composition of young children by using bioelectrical resistance. J Appl Physiol. 1993;75:1776–80. https://doi.org/10.1152/jappl.1993.75.4.1776.

    Article  CAS  PubMed  Google Scholar 

  18. Kanellakis S, Skoufas E, Karaglani E, Ziogos G, Koutroulaki A, Loukianou F. et al. Development and validation of a bioelectrical impedance prediction equation estimating fat free mass in Greek - Caucasian adult population. Clin Nutr ESPEN. 2020;36:166–70. https://doi.org/10.1016/j.clnesp.2020.01.003.

    Article  PubMed  Google Scholar 

  19. Kotler DP, Burastero S, Wang J, Pierson RN,Jr. Prediction of body cell mass, fat-free mass, and total body water with bioelectrical impedance analysis: effects of race, sex, and disease. Am J Clin Nutr. 1996;64:489S–97S. https://doi.org/10.1093/ajcn/64.3.489S.

    Article  CAS  PubMed  Google Scholar 

  20. Kyle UG, Genton L, Karsegard L, Slosman DO, Pichard C. Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years. Nutrition. 2001;17:248–53. https://doi.org/10.1016/s0899-9007(00)00553-0.

    Article  CAS  PubMed  Google Scholar 

  21. Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Dugas LR. et al. Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin. Eur J Clin Nutr. 2013;67:956–60. https://doi.org/10.1038/ejcn.2013.123.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Matias CN, Campa F, Santos DA, Lukaski H, Sardinha LB, Silva AM. Fat-free Mass Bioelectrical Impedance Analysis Predictive Equation for Athletes using a 4-Compartment Model. Int J Sports Med. 2021;42:27–32. https://doi.org/10.1055/a-1179-6236.

    Article  CAS  PubMed  Google Scholar 

  23. Steinberg A, Manlhiot C, Li P, Metivier E, Pencharz PB, McCrindle BW. et al. Development and Validation of Bioelectrical Impedance Analysis Equations in Adolescents with Severe Obesity. J Nutr. 2019;149:1288–93. https://doi.org/10.1093/jn/nxz063.

    Article  PubMed  Google Scholar 

  24. Stolarczyk LM, Heyward VH, Goodman JA, Grant DJ, Kessler KL, Kocina PS, et al. Predictive accuracy of bioimpedance equations in estimating fat-free mass of Hispanic women. Med Sci Sports Exerc. 1995;27:1450–6.

    Article  CAS  PubMed  Google Scholar 

  25. Stolarczyk LM, Heyward VH, Hicks VL, Baumgartner RN. Predictive accuracy of bioelectrical impedance in estimating body composition of Native American women. Am J Clin Nutr. 1994;59:964–70. https://doi.org/10.1093/ajcn/59.5.964.

    Article  CAS  PubMed  Google Scholar 

  26. Sun SS, Chumlea WC, Heymsfield SB, Lukaski HC, Schoeller D, Friedl K, et al. Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys. Am J Clin Nutr. 2003;77:331–40. https://doi.org/10.1093/ajcn/77.2.331.

    Article  CAS  PubMed  Google Scholar 

  27. Tint MT, Ward LC, Soh SE, Aris IM, Chinnadurai A, Saw SM, et al. Estimation of fat-free mass in Asian neonates using bioelectrical impedance analysis. Br J Nutr. 2016;115:1033–42. https://doi.org/10.1017/s0007114515005486.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. da Costa RF, Silva AM, Masset K, Cesário TM, Cabral B, Ferrari G, et al. Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance. Front Nutr. 2022;9:820736. https://doi.org/10.3389/fnut.2022.820736.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Wang L, Hui SS, Wong SH. Validity of bioelectrical impedance measurement in predicting fat-free mass of Chinese children and adolescents. Med Sci Monit. 2014;20:2298–310. https://doi.org/10.12659/msm.890696.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Nightingale CM, Rudnicka AR, Owen CG, Donin AS, Newton SL, Furness CA, et al. Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assessment of body composition in children study. PLoS One. 2013;8:e76426. https://doi.org/10.1371/journal.pone.0076426.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Essa’a VJ, Dimodi HT, Ntsama PM, Medoua GN. Validation of anthropometric and bioelectrical impedance analysis (BIA) equations to predict total body water in a group of Cameroonian preschool children using deuterium dilution method. Nutrire. 2017;42:20. https://doi.org/10.1186/s41110-017-0045-y.

    Article  CAS  Google Scholar 

  32. van Zyl A, White Z, Ferreira J, Wenhold FAM. Developing an Impedance Based Equation for Fat-Free Mass of Black Preadolescent South African Children. Nutrients 2019;11. https://doi.org/10.3390/nu11092021

  33. Nigam P, Misra A, Colles SL. Comparison of DEXA-derived body fat measurement to two race-specific bioelectrical impedance equations in healthy Indians. Diabetes Metab Syndr. 2013;7:72–7. https://doi.org/10.1016/j.dsx.2013.02.031.

    Article  PubMed  Google Scholar 

  34. Beaudart C, Bruyère O, Geerinck A, Hajaoui M, Scafoglieri A, Perkisas S, et al. Equation models developed with bioelectric impedance analysis tools to assess muscle mass: A systematic review. Clin Nutr ESPEN. 2020;35:47–62. https://doi.org/10.1016/j.clnesp.2019.09.012.

    Article  PubMed  Google Scholar 

  35. Matias CN, Santos DA, Judice PB, Magalhaes JP, Minderico CS, Fields DA. et al. Estimation of total body water and extracellular water with bioimpedance in athletes: A need for athlete-specific prediction models. Clin Nutr. 2016;35:468–74. https://doi.org/10.1016/j.clnu.2015.03.013.

    Article  PubMed  Google Scholar 

  36. Sergi G, Bussolotto M, Perini P, Calliari I, Giantin V, Ceccon A, et al. Accuracy of bioelectrical impedance analysis in estimation of extracellular space in healthy subjects and in fluid retention states. Ann Nutr Metab. 1994;38:158–65. https://doi.org/10.1159/000177806.

    Article  CAS  PubMed  Google Scholar 

  37. Dittmar M, Reber H. Validation of different bioimpedance analyzers for predicting cell mass against whole-body counting of potassium (40 K) as a reference method. Am J Hum Biol. 2004;16:697–703. https://doi.org/10.1002/ajhb.20078.

    Article  PubMed  Google Scholar 

  38. Flury S, Trachsler J, Schwarz A, Ambuhl PM. Quantification of excretory renal function and urinary protein excretion by determination of body cell mass using bioimpedance analysis. BMC Nephrol. 2015;16:174 https://doi.org/10.1186/s12882-015-0171-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Janssen I, Heymsfield SB, Baumgartner RN, Ross R. Estimation of skeletal muscle mass by bioelectrical impedance analysis. J Appl Physiol. 2000;89:465–71. https://doi.org/10.1152/jappl.2000.89.2.465

    Article  CAS  PubMed  Google Scholar 

  40. Silva AM, Fields DA, Heymsfield SB, Sardinha LB. Body composition and power changes in elite judo athletes. Int J Sports Med. 2010;31:737–41. https://doi.org/10.1055/s-0030-1255115.

    Article  CAS  PubMed  Google Scholar 

  41. Knudsen NN, Kjærulff TM, Ward LC, S‘bye D, Holst C, Heitmann BL. Body water distribution and risk of cardiovascular morbidity and mortality in a healthy population: A prospective cohort study. PLoS One. 2014;9:e87466. https://doi.org/10.1371/journal.pone.0087466.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Silva AM, Fields DA, Heymsfield SB, Sardinha LB. Relationship between changes in total-body water and fluid distribution with maximal forearm strength in elite judo athletes. J Strength Cond Res. 2011;25:2488–95. https://doi.org/10.1519/JSC.0b013e3181fb3dfb

    Article  PubMed  Google Scholar 

  43. Silva AM, Matias CN, Santos DA, Rocha PM, Minderico CS, Sardinha LB. Increases in intracellular water explain strength and power improvements over a season. Int J Sports Med. 2014;35:1101–5. https://doi.org/10.1055/s-0034-1371839.

    Article  CAS  PubMed  Google Scholar 

  44. Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019;92:6–10. https://doi.org/10.1016/j.metabol.2018.09.005

    Article  CAS  PubMed  Google Scholar 

  45. Moisey LL, Mourtzakis M, Cotton BA, Premji T, Heyland DK, Wade CE, et al. Skeletal muscle predicts ventilator-free days, ICU-free days, and mortality in elderly ICU patients. Crit Care. 2013;17:R206. https://doi.org/10.1186/cc12901

    Article  PubMed  PubMed Central  Google Scholar 

  46. Soares MN, Eggelbusch M, Naddaf E, Gerrits KHL, van der Schaaf M, van den Borst B, et al. Skeletal muscle alterations in patients with acute Covid-19 and post-acute sequelae of Covid-19. J Cachexia Sarcopenia Muscle. 2022;3:11–22. https://doi.org/10.1002/jcsm.12896

  47. Weijs PJ, Looijaard WG, Dekker IM, Stapel SN, Girbes AR, Oudemans-van Straaten HM, et al. Low skeletal muscle area is a risk factor for mortality in mechanically ventilated critically ill patients. Crit Care. 2014;18:R12 https://doi.org/10.1186/cc13189

    Article  PubMed  PubMed Central  Google Scholar 

  48. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16–31. https://doi.org/10.1093/ageing/afy169

    Article  PubMed  Google Scholar 

  49. Buffa R, Floris G, Marini E. Assessment of nutritional status in free-living elderly individuals by bioelectrical impedance vector analysis. Nutrition. 2009;25:3–5. https://doi.org/10.1016/j.nut.2008.07.014

    Article  PubMed  Google Scholar 

  50. Langer RD, Larsen SC, Ward LC, Heitmann BL. Phase angle measured by bioelectrical impedance analysis and the risk of cardiovascular disease among adult Danes. Nutrition. 2021;89:111280 https://doi.org/10.1016/j.nut.2021.111280.

    Article  PubMed  Google Scholar 

  51. Campa F, Matias CN, Marini E, Heymsfield SB, Toselli S, Sardinha LB, et al. Identifying Athlete Body Fluid Changes During a Competitive Season With Bioelectrical Impedance Vector Analysis. Int J Sports Physiol Perform. 2019;1-7. https://doi.org/10.1123/ijspp.2019-0285

  52. Castizo-Olier J, Irurtia A, Jemni M, Carrasco-Marginet M, Fernandez-Garcia R, Rodriguez FA. Bioelectrical impedance vector analysis (BIVA) in sport and exercise: Systematic review and future perspectives. PLoS One. 2018;13:e0197957 https://doi.org/10.1371/journal.pone.0197957

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Girma T, Hother Nielsen AL, Kaestel P, Abdissa A, Michaelsen KF, Friis H, et al. Biochemical and anthropometric correlates of bio-electrical impedance parameters in severely malnourished children: A cross-sectional study. Clin Nutr. 2018;37:701–5. https://doi.org/10.1016/j.clnu.2017.02.017

    Article  CAS  PubMed  Google Scholar 

  54. Girma T, Kaestel P, Molgaard C, Ritz C, Andersen GS, Michaelsen KF, et al. Utility of bio-electrical impedance vector analysis for monitoring treatment of severe acute malnutrition in children. Clin Nutr. 2021;40:624–31. https://doi.org/10.1016/j.clnu.2020.06.012

    Article  PubMed  Google Scholar 

  55. Lee S, Bountziouka V, Lum S, Stocks J, Bonner R, Naik M, et al. Ethnic variability in body size, proportions and composition in children aged 5 to 11 years: is ethnic-specific calibration of bioelectrical impedance required? PLoS One. 2014;9:e113883 https://doi.org/10.1371/journal.pone.0113883

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Marini E, Campa F, Buffa R, Stagi S, Matias CN, Toselli S, et al. Phase angle and bioelectrical impedance vector analysis in the evaluation of body composition in athletes. Clin Nutr. 2020;39:447–54. https://doi.org/10.1016/j.clnu.2019.02.016

    Article  PubMed  Google Scholar 

  57. Moroni A, Varde C, Giustetto A, Stagi S, Marini E, Micheletti Cremasco M. Bioelectrical Impedance Vector Analysis (BIVA) for the monitoring of body composition in pregnancy. Eur J Clin Nutr. 2022;76:604–9. https://doi.org/10.1038/s41430-021-00990-7.

    Article  CAS  PubMed  Google Scholar 

  58. Norman K, Stobäus N, Pirlich M, Bosy-Westphal A. Bioelectrical phase angle and impedance vector analysis–clinical relevance and applicability of impedance parameters. Clin Nutr. 2012;31:854–61. https://doi.org/10.1016/j.clnu.2012.05.008.

    Article  PubMed  Google Scholar 

  59. Gupta D, Lammersfeld CA, Vashi PG, King J, Dahlk SL, Grutsch JF, et al. Bioelectrical impedance phase angle as a prognostic indicator in breast cancer. BMC Cancer. 2008;8:249 https://doi.org/10.1186/1471-2407-8-249

    Article  PubMed  PubMed Central  Google Scholar 

  60. Langer RD, Ward LC, Larsen SC, Heitmann BL. Can change in phase angle predict the risk of morbidity and mortality during an 18-year follow-up period? A cohort study among adults. Front Nutr. 2023;10:1157531 https://doi.org/10.3389/fnut.2023.1157531.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Sardinha LB. Physiology of exercise and phase angle: another look at BIA. Eur J Clin Nutr. 2018;72:1323–7. https://doi.org/10.1038/s41430-018-0215-x.

    Article  PubMed  Google Scholar 

  62. Gupta D, Lis CG, Dahlk SL, Vashi PG, Grutsch JF, Lammersfeld CA. Bioelectrical impedance phase angle as a prognostic indicator in advanced pancreatic cancer. Br J Nutr. 2004;92:957–62. https://doi.org/10.1079/bjn20041292

    Article  CAS  PubMed  Google Scholar 

  63. Kyle UG, Genton L, Pichard C. Low phase angle determined by bioelectrical impedance analysis is associated with malnutrition and nutritional risk at hospital admission. Clin Nutr. 2013;32:294–9. https://doi.org/10.1016/j.clnu.2012.08.001

    Article  PubMed  Google Scholar 

  64. Kyle UG, Soundar EP, Genton L, Pichard C. Can phase angle determined by bioelectrical impedance analysis assess nutritional risk? A comparison between healthy and hospitalized subjects. Clin Nutr. 2012;31:875–81. https://doi.org/10.1016/j.clnu.2012.04.002.

    Article  PubMed  Google Scholar 

  65. Schwenk A, Beisenherz A, Romer K, Kremer G, Salzberger B, Elia M. Phase angle from bioelectrical impedance analysis remains an independent predictive marker in HIV-infected patients in the era of highly active antiretroviral treatment. Am J Clin Nutr. 2000;72:496–501. https://doi.org/10.1093/ajcn/72.2.496

    Article  CAS  PubMed  Google Scholar 

  66. Valdespino-Trejo A, Orea-Tejeda A, Castillo-Martinez L, Keirns-Davis C, Montanez-Orozco A, Ortiz-Suarez G, et al. Low albumin levels and high impedance ratio as risk factors for worsening kidney function during hospitalization of decompensated heart failure patients. Exp Clin Cardiol. 2013;18:113–7.

    PubMed  PubMed Central  Google Scholar 

  67. Brantlov S, Jødal L, Andersen RF, Lange A, Rittig S, Ward LC. An evaluation of phase angle, bioelectrical impedance vector analysis and impedance ratio for the assessment of disease status in children with nephrotic syndrome. BMC Nephrol. 2019;20:331 https://doi.org/10.1186/s12882-019-1511-y.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Oh JH, Song S, Rhee H, Lee SH, Kim DY, Choe JC, et al. Normal Reference Plots for the Bioelectrical Impedance Vector in Healthy Korean Adults. J Korean Med Sci. 2019;34:e198 https://doi.org/10.3346/jkms.2019.34.e198.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Barbosa-Silva MC, Barros AJ, Wang J, Heymsfield SB, Pierson RN Jr. Bioelectrical impedance analysis: population reference values for phase angle by age and sex. Am J Clin Nutr. 2005;82:49–52. https://doi.org/10.1093/ajcn.82.1.49

    Article  CAS  PubMed  Google Scholar 

  70. Kuchnia AJ, Teigen LM, Cole AJ, Mulasi U, Gonzalez MC, Heymsfield SB, et al. Phase Angle and Impedance Ratio: Reference Cut-Points From the United States National Health and Nutrition Examination Survey 1999-2004 From Bioimpedance Spectroscopy Data. JPEN J Parenter Enter Nutr. 2017;41:1310–5. https://doi.org/10.1177/0148607116670378

    Article  Google Scholar 

  71. Bosy-Westphal A, Danielzik S, Dorhofer RP, Later W, Wiese S, Muller MJ. Phase angle from bioelectrical impedance analysis: population reference values by age, sex, and body mass index. JPEN J Parenter Enter Nutr. 2006;30:309–16. https://doi.org/10.1177/0148607106030004309

    Article  Google Scholar 

  72. Kyle UG, Genton L, Slosman DO, Pichard C. Fat-free and fat mass percentiles in 5225 healthy subjects aged 15 to 98 years. Nutrition. 2001;17:534–41. https://doi.org/10.1016/s0899-9007(01)00555-x

    Article  CAS  PubMed  Google Scholar 

  73. Campa F, Thomas DM, Watts K, Clark N, Baller D, Morin T, et al. Reference Percentiles for Bioelectrical Phase Angle in Athletes. Biology. 2022;11:264. https://doi.org/10.3390/biology11020264

    Article  PubMed  PubMed Central  Google Scholar 

  74. Wells JCK, Williams JE, Quek RY, Fewtrell MS. Bio-electrical impedance vector analysis: testing Piccoli’s model against objective body composition data in children and adolescents. Eur J Clin Nutr. 2019;73:887–95. https://doi.org/10.1038/s41430-018-0292-x

    Article  PubMed  Google Scholar 

  75. Piccoli A, Rossi B, Pillon L, Bucciante G. A new method for monitoring body fluid variation by bioimpedance analysis: the RXc graph. Kidney Int. 1994;46:534–9. https://doi.org/10.1038/ki.1994.305.

    Article  CAS  PubMed  Google Scholar 

  76. Marini E, Sergi G, Succa V, Saragat B, Sarti S, Coin A, et al. Efficacy of specific bioelectrical impedance vector analysis (BIVA) for assessing body composition in the elderly. J Nutr Health Aging. 2013;17:515–21. https://doi.org/10.1007/s12603-012-0411-7

    Article  CAS  PubMed  Google Scholar 

  77. Buffa R, Saragat B, Cabras S, Rinaldi AC, Marini E. Accuracy of specific BIVA for the assessment of body composition in the United States population. PLoS One. 2013;8:e58533. https://doi.org/10.1371/journal.pone.0058533

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Stagi S, Silva AM, Jesus F, Campa F, Cabras S, Earthman CP, et al. Usability of classic and specific bioelectrical impedance vector analysis in measuring body composition of children. Clin Nutr. 2022;41:673–9. https://doi.org/10.1016/j.clnu.2022.01.021.

    Article  PubMed  Google Scholar 

  79. 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;40:1147–54. https://doi.org/10.1016/j.clnu.2020.07.022.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. De Palo T, Messina G, Edefonti A, Perfumo F, Pisanello L, Peruzzi L, et al. Normal values of the bioelectrical impedance vector in childhood and puberty. Nutrition. 2000;16:417–24. https://doi.org/10.1016/s0899-9007(00)00269-0

    Article  PubMed  Google Scholar 

  81. Ibanez ME, Mereu E, Buffa R, Gualdi-Russo E, Zaccagni L, Cossu S, et al. New specific bioelectrical impedance vector reference values for assessing body composition in the Italian-Spanish young adult population. Am J Hum Biol. 2015;27:871–6. https://doi.org/10.1002/ajhb.22728

    Article  PubMed  Google Scholar 

  82. Piccoli A, Nigrelli S, Caberlotto A, Bottazzo S, Rossi B, Pillon L, et al. Bivariate normal values of the bioelectrical impedance vector in adult and elderly populations. Am J Clin Nutr. 1995;61:269–70. https://doi.org/10.1093/ajcn/61.2.269

    Article  CAS  PubMed  Google Scholar 

  83. Piccoli A, Pillon L, Dumler F. Impedance vector distribution by sex, race, body mass index, and age in the United States: standard reference intervals as bivariate Z scores. Nutrition. 2002;18:153–67. https://doi.org/10.1016/s0899-9007(01)00665-7

    Article  PubMed  Google Scholar 

  84. Ward LC, Heitmann BL, Craig P, Stroud D, Azinge EC, Jebb S, et al. Association between ethnicity, body mass index, and bioelectrical impedance. Implications for the population specificity of prediction equations. Ann N. Y Acad Sci. 2000;904:199–202. https://doi.org/10.1111/j.1749-6632.2000.tb06449.x.

    Article  CAS  PubMed  Google Scholar 

  85. Heitmann BL, Swinburn BA, Carmichael H, Rowley K, Plank L, McDermott R, et al. Are there ethnic differences in the association between body weight and resistance, measured by bioelectrical impedance? Int J Obes Relat Metab Disord. 1997;21:1085–92. https://doi.org/10.1038/sj.ijo.0800477.

    Article  CAS  PubMed  Google Scholar 

  86. Baumgartner RN, Heymsfield SB, Roche AF. Human body composition and the epidemiology of chronic disease. Obes Res. 1995;3:73–95. https://doi.org/10.1002/j.1550-8528.1995.tb00124.x

    Article  CAS  PubMed  Google Scholar 

  87. Shen W, Punyanitya M, Silva AM, Chen J, Gallagher D, Sardinha LB, et al. Sexual dimorphism of adipose tissue distribution across the lifespan: a cross-sectional whole-body magnetic resonance imaging study. Nutr Metab (Lond). 2009;6:17 https://doi.org/10.1186/1743-7075-6-17.

    Article  PubMed  Google Scholar 

  88. Silva AM, Shen W, Heo M, Gallagher D, Wang Z, Sardinha LB, et al. Ethnicity-related skeletal muscle differences across the lifespan. Am J Hum Biol. 2010;22:76–82. https://doi.org/10.1002/ajhb.20956.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Ward LC. Electrical Bioimpedance: From the Past to the Future. J Electr Bioimpedance. 2021;12:1–2. https://doi.org/10.2478/joeb-2021-0001.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Marini E, Buffa R, Saragat B, Coin A, Toffanello ED, Berton L. et al. The potential of classic and specific bioelectrical impedance vector analysis for the assessment of sarcopenia and sarcopenic obesity. Clin Inter Aging. 2012;7:585–91. https://doi.org/10.2147/CIA.S38488.

    Article  Google Scholar 

  91. Toselli S, Marini E, Maietta Latessa P, Benedetti L, Campa F. Maturity related differences in body composition assessed by classic and specific bioimpedance vector analysis among male elite youth soccer players. Int J Environ Res Public Health. 2020;17:729. https://doi.org/10.3390/ijerph17030729.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Fearon K, Arends J, Baracos V. Understanding the mechanisms and treatment options in cancer cachexia. Nat Rev Clin Oncol. 2013;10:90–99. https://doi.org/10.1038/nrclinonc.2012.209.

    Article  CAS  PubMed  Google Scholar 

  93. World Health Organization. Social determinants of health. Geneva, Switzerland: World Health Organization; 2009.

    Google Scholar 

  94. Wells JC, Sawaya AL, Wibaek R, Mwangome M, Poullas MS, Yajnik CS, et al. The double burden of malnutrition: aetiological pathways and consequences for health. Lancet. 2020;395:75–88. https://doi.org/10.1016/s0140-6736(19)32472-9.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Faculdade Motricidade Humana-Universidade de Lisboa kindly hosted the BIA database in the website for which we are thankful. Management group of the BIA International Database: AMS, LCW, ESC, AB-W, SBH, HL, LBS, JCW, EM.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the drafting and editing of the manuscript and to construction of the BIA International database.

Corresponding author

Correspondence to Analiza M. Silva.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Silva, A.M., Campa, F., Stagi, S. et al. The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data. Eur J Clin Nutr 77, 1143–1150 (2023). https://doi.org/10.1038/s41430-023-01310-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41430-023-01310-x

This article is cited by

Search

Quick links