Cited by 575Body Composition Measurement TechniquesElectrical and Bioimpedance TomographyNutrition and Health in Aging

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Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years

Kyle, Ursula G, Genton, Laurence, Karsegard, Laurie, Slosman, Daniel O, Pichard, Claude·2001·Nutrition

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Abstract

Existing equations for bioelectrical impedance analysis (BIA) are of limited use when subjects age or become overweight because these equations were developed in young, normal-weight subjects and are not valid in elderly or overweight people. The purpose of this study was to validate a single BIA equation in healthy white subjects aged 22--94 y with a body mass index between 17.0 and 33.8 kg/m(2). Healthy subjects (202 men and 141 women) aged 20--94 y were measured by two methods: fat-free mass (FFM) was measured by dual-energy x-ray absorptiometry (Hologic QDR-4500) and by a bioelectrical impedance analyzer (Xitron 4000B). Validity of BIA was assessed by double cross validation. Because correlations were high (r = 0.986--0.987) and prediction errors low, a single equation was developed using all subjects, as follows: FFM = -4.104 + (0.518 x height(2)/resistance) + (0.231 x weight) + (0.130 x reactance) + (4.229 x sex: men = 1, women = 0). FFM predicted with dual-energy x-ray absorptiometry was 54.0 +/- 10.7 kg. BIA-predicted FFM was 54.0 +/- 10.5 kg (r = 0.986, standard error of the estimate = 1.72 kg, technical error = 1.74 kg). In conclusion, the new Geneva BIA equation was valid for prediction of FFM in healthy adults aged 22--94 y with body mass indexes between 17.0 and 33.8 kg/m(2). Inclusion of reactance in the single prediction equation appeared to be essential for use of BIA equations in populations with large variations in age or body mass.

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Smith, L. O., Olieman, J. F., Berk, K. A., Ligthart‐Melis, G. C., & Earthman, C. P. (2022) · Journal of Parenteral and Enteral Nutrition · doi:10.1002/jpen.2444 · Cited by 21
Fiber atrophy, oxidative stress, and oxidative fiber reduction are the attributes of different phenotypes in chronic obstructive pulmonary disease patients
Gouzi, F., Abdellaoui, A., Molinari, N., Pinot, E., Ayoub, B., Laoudj‐Chenivesse, D., Cristol, J., Mercier, J. G., Hayot, M., & PREFAUT, C. G. (2013) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00778.2013 · Cited by 23
Muscle performance, body fat, pain and function in the elderly with arthritis
dos Santos, W. T., Rodrigues, É. C., & Mainenti, M. R. M. (2014) · Acta Ortopédica Brasileira · doi:10.1590/s1413-78522014000100010 · Cited by 20
Hand-to-Hand Model for Bioelectrical Impedance Analysis to Estimate Fat Free Mass in a Healthy Population
Lu, H.-K., Chiang, L.-M., Chen, Y.-Y., Chuang, C.-L., Chen, K.-T., Dwyer, G. B., Hsu, Y., Chen, C., & Hsieh, K.-C. (2016) · Nutrients · doi:10.3390/nu8100654 · Cited by 19
“Upon direct observation of the LOA region, the region was wider and could be applied in epidemiological or clinical Geneva BIA equations [20].”
Method
Waist to height ratio is the anthropometric index that most appropriately mirrors the lifestyle and psychological risk factors of obesity
Tomas, Ž., Škarić‐Jurić, T., Petranović, M. Z., Jalšovec, M., Šikanjić, P. R., & Narančić, N. S. (2019) · Nutrition & Dietetics · doi:10.1111/1747-0080.12520 · Cited by 21
Sarcopenia and its relation to protein intake across older ethnic populations in the Netherlands: the HELIUS study
Dorhout, B. G., Overdevest, E., Tieland, M., Nicolaou, M., Weijs, P. J. M., Snijder, M. B., Peters, R. J. G., van Valkengoed, I. G. M., Haveman‐Nies, A., & de Groot, C. P. G. M. (2020) · Ethnicity and Health · doi:10.1080/13557858.2020.1814207 · Cited by 20
“The BIA equations of Janssen et al. and Kyle et al. resulted in comparable SMM (mean ± SD: 24.8 ± 6.5, 25.0 ± 4.7, respectively) and therefore the type of equation might result in only small differences in sarcopenia prevalence.”
ResultInfluential
Body Composition and Wages
Wada, R., & Tekin, E. (2007) · National Bureau of Economic Research · doi:10.3386/w13595 · Cited by 21
Lateral Asymmetry in Upper and Lower Limb Bioelectrical Impedance Analysis in Youth Tennis Players
Filipčić, A., Čuk, I., & Filipčić, T. (2016) · International Journal of Morphology · doi:10.4067/s0717-95022016000300012 · Cited by 19
“BIA is an affordable, non-invasive and fast method for assessing body composition (Baumgartner, 1996; De Lorenzo et al., 2000; Kyle et al., 2001; Yamada et al., 2013).”
Method
Body composition assessment in individuals with class II/III obesity: a narrative review
Silveira, É. A., Castro, M. C. R., Rezende, A. T. O., Rodrigues, A. P. D. S., Delpino, F. M., Oliveira, E. S., Corgosinho, F. C., & de Oliveira, C. M. (2024) · BMC Nutrition · doi:10.1186/s40795-024-00913-2 · Cited by 18
“In single-frequency ohmmeters, impedance may estimate fat-free mass but does not determine or differentiate extra and intracellular fractions of water [23].”
Background
Oral function in amyotrophic lateral sclerosis patients: A matched case–control study
Schimmel, M., Leuchter, I., Barras, A.-C. H., et al. (2021) · Clinical Nutrition · doi:10.1016/j.clnu.2021.06.022 · Cited by 18
Self-citation
The novel application of artificial neural network on bioelectrical impedance analysis to assess the body composition in elderly
Hsieh, K.-C., Chen, Y.-J., Lu, H.-K., Lee, L.-C., Huang, Y., & Chen, Y.-Y. (2013) · Nutrition Journal · doi:10.1186/1475-2891-12-21 · Cited by 16
“[37] show that the differences between the measured FFM and the DXA were 0.”
Background
Population Pharmacokinetic‐Pharmacodynamic Modeling for Propofol Anesthesia Guided by the Bispectral Index (BIS)
Araújo, A., Machado, H. S., de Pinho, P. G., Soares-da-Silva, P., & Falcão, A. C. (2019) · The Journal of Clinical Pharmacology · doi:10.1002/jcph.1560 · Cited by 18
Accuracy of surrogate methods to estimate skeletal muscle mass in non-dialysis dependent patients with chronic kidney disease and in kidney transplant recipients
Silva, M. I. B., Barreto, A. P. M. M., Pontes, K. S. D. S., da Costa, M. S., Rosina, K. T. D. C., Souza, E., Bregman, R., Prado, C. M. M., & Klein, M. R. S. T. (2020) · Clinical Nutrition · doi:10.1016/j.clnu.2020.05.021 · Cited by 20
Differences in Body Composition Convey a Similar Risk of Type 2 Diabetes Among Different Ethnic Groups With Disparate Cardiometabolic Risk—The HELIUS Study
Zethof, M., Mosterd, C. M., Collard, D., et al. (2021) · Diabetes Care · doi:10.2337/dc21-0230 · Cited by 18
Blood rheology and body composition as determinants of exercise performance in female rugby players
Brun, J. ‐., Varlet‐Marie, E., Cassan, D., & de Mauverger, É. R. (2011) · Clinical Hemorheology and Microcirculation · doi:10.3233/ch-2011-1470 · Cited by 19
“Subjects were assessed in our laboratory with bioimpedance analysis (Dietosystem) for measuring body composition with published equations [19, 21] and a maximal exercise test on cycloergometer in order to measure their maximal oxygen consumption VO2max according to the guidelines of the French Society of Sports Medici…”
Method
Complications of Oropharyngeal Dysphagia: Malnutrition and Aspiration Pneumonia
Carrión, S., Vérin, É., Clavé, P., & Laviano, A. (2011) · Medical radiology · doi:10.1007/174_2011_348 · Cited by 19
Body Composition and Aging
Visser, M., & Harris, T. B. (2012) · Springer eBooks · doi:10.1007/978-94-007-5061-6_16 · Cited by 20
Body Composition Comparison: Bioelectric Impedance Analysis with Dual-Energy X-Ray Absorptiometry in Adult Athletes
Joe Company, & Ball, S. (2010) · Measurement in Physical Education and Exercise Science · doi:10.1080/1091367x.2010.497449 · Cited by 17
“Numerous studies encourage body building to be taken into account when developing a BIA equation (Brodie et al., 1998; Houtkooper, Going, Westfall, & Lohman, 1989; Kyle et al., 2001; Sigurbjorn et al., 2000).”
Background
Development and cross-validation of predictive equations for fat-free mass and lean soft tissue mass by bioelectrical impedance in Brazilian women.
Costa, R. F. D., Masset, K. V. D. S. B., Silva, A. M., Cabral, B. G. D. A. T., & Dantas, P. M. S. (2022) · European Journal of Clinical Nutrition · doi:10.1038/s41430-021-00946-x · Cited by 16
Physical exercise is associated with a reduction in plasma levels of fractalkine, TGF-β1, eotaxin-1 and IL-6 in younger adults with mobility disability
Kumar, P., Stiernborg, M., Fogdell‐Hahn, A., Månsson, K. N. T., Furmark, T., Berglind, D., Melas, P. A., Forsell, Y., & Lavebratt, C. (2022) · PLoS ONE · doi:10.1371/journal.pone.0263173 · Cited by 16
Minimal model-derived insulin sensitivity, insulin secretion and glucose tolerance: relationships with blood rheology
Brun, J. ‐., Varlet‐Marie, E., de Mauverger, É. R., & Mercier, J. G. (2012) · Clinical Hemorheology and Microcirculation · doi:10.3233/ch-2011-1425 · Cited by 15
Body composition changes in breast cancer patients during curative radiation therapy
Genton, L., Kyle, U. G., Majno, S. B., & Pichard, C. (2006) · e-SPEN the European e-Journal of Clinical Nutrition and Metabolism · doi:10.1016/j.eclnm.2006.07.005 · Cited by 16
Self-citation
Pain, Work-related Characteristics, and Psychosocial Factors among Computer Workers at a University Center
Mainenti, M. R. M., Felício, L. R., Rodrigues, É. C., et al. (2014) · Journal of Physical Therapy Science · doi:10.1589/jpts.26.567 · Cited by 16
Cross-mode bioelectrical impedance analysis in a standing position for estimating fat-free mass validated against dual-energy x-ray absorptiometry
Huang, A.-C., Chen, Y.-Y., Chuang, C.-L., Chiang, L.-M., Lu, H.-K., Lin, H.-C., Chen, K.-T., Hsiao, A.-C., & Hsieh, K.-C. (2015) · Nutrition Research · doi:10.1016/j.nutres.2015.08.005 · Cited by 15
Running performance in a timed city run and body composition: A cross-sectional study in more than 3000 runners
Herrmann, F. R., Graf, C. E., Karsegard, V. L., Mareschal, J., Achamrah, N., Delsoglio, M., Schindler, M., Pichard, C., & Genton, L. (2018) · Nutrition · doi:10.1016/j.nut.2018.10.022 · Cited by 16
Self-citation
Association between the handgrip strength and the isokinetic muscle function of the elbow and the knee in asymptomatic adults
Ostolin, T. L. V. D. P., Gonze, B. D. B., Vieira, W. D. O., et al. (2021) · SAGE Open Medicine · doi:10.1177/2050312121993294 · Cited by 16
Height differences and the associations between food insecurity, percentage body fat and BMI among men and women
Tayie, F., & Zizza, C. A. (2009) · Public Health Nutrition · doi:10.1017/s1368980009004777 · Cited by 17
Taking care of inpatients with fragility hip fractures: the hip-padua osteosarcopenia (Hip-POS) fracture liaison service model
Arcidiacono, G. P., Ceolin, C., Sella, S., Camozzi, V., Bertocco, A., Torres, M. O., Rodà, M. G., Cannito, M., Berizzi, A., Romanato, G., et al. (2024) · Journal of Endocrinological Investigation · doi:10.1007/s40618-024-02425-z · Cited by 15
“Estimates of fat-free mass (FFM) and appendicular skeletal muscle mass (ASMM) are calculated using the equations developed by Kyle et al. [28].”
New Perspectives in the Association between Anthropometry and Mortality: The Role of Calf Circumference
Ceolin, C., Acunto, V., Simonato, C., Cazzavillan, S., Vergadoro, M., Papa, M. V., Trapella, G. S., Sermasi, R., Noale, M., RUI, M. D., et al. (2024) · The Journal of Frailty & Aging · doi:10.14283/jfa.2024.4 · Cited by 16
“…and accuracy of the resistance and reactance measurements allowed the smallest changes to be recorded at a resolution of 0.1 Ω. Fat-free mass (FFM) and appendicular skeletal muscle mass (ASMM) estimates for our sample were calculated using the equations developed by Kyle et al. (27,28)”
Influential
Feasibility of bioelectrical impedance analysis in persons with severe intellectual and visual disabilities
Havinga-Top, A. M., Waninge, A., van der Schans, C. P., & Jager‐Wittenaar, H. (2015) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2015.09.003 · Cited by 16
Die Bioelektrische Impedanzanalyse in der Diagnostik der Malnutrition
Wirth, R., & Miklis, P. (2005) · Zeitschrift für Gerontologie und Geriatrie · doi:10.1007/s00391-005-0330-x · Cited by 15
Development and validation of a bioelectrical impedance prediction equation estimating fat free mass in Greek - Caucasian adult population
Kanellakis, S., Skoufas, E., Karaglani, E., Ziogos, G., Koutroulaki, A., Loukianou, F., Michalopoulou, M., Gkeka, A., Marikou, F., & Manios, Y. (2020) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2020.01.003 · Cited by 14
Decreased IGF-1 levels potentiate association of inflammation with all-cause and cardiovascular mortality in prevalent hemodialysis patients
Beberashvili, I., Sinuani, I., Azar, A., Kadoshi, H., Shapiro, G., Feldman, L., Sandbank, J., & Averbukh, Z. (2013) · Growth Hormone & IGF Research · doi:10.1016/j.ghir.2013.07.005 · Cited by 14
“[27].”
Influence of the level of physical activity on physical fitness, lipid profile and health outcomes in overweight/obese adults with similar nutritional status
Muñoz-Vera, T., Sañudo, B., Cruz, B. D. P., del Pozo-Cruz, J., López‐Lluch, G., & Sánchez-Oliver, A. J. (2017) · Science & Sports · doi:10.1016/j.scispo.2016.05.006 · Cited by 16
Applications of Bioimpedance to End Stage Renal Disease (ESRD)
Roa, L. M., Naranjo, D., Reina‐Tosina, J., Lara, A., Milán, J. A., Estudillo‐Valderrama, M. Á., & Oliva, J. S. (2012) · Studies in computational intelligence · doi:10.1007/978-3-642-27458-9_14 · Cited by 15
“229 For Healthy adults (18-94 years) (Kyle et al. 2001) Women: -12.”
Bioelectrical Impedance Analysis in a Mathematical Model for Estimating Fat-free Mass in Multiple Segments in Elderly Taiwanese Males
Yeh, C., Chen, Y.-J., Lai, L.-Y., Jang, T.-R., Chiang, J., Chen, Y.-Y., & Hsieh, K.-C. (2012) · International journal of gerontology · doi:10.1016/j.ijge.2012.01.031 · Cited by 12
Body composition in sarcopenic obesity: systematic review of the literature
Donini, L. M., Poggiogalle, E., Migliaccio, S., Aversa, A., & Pinto, A. (2013) · Mediterranean Journal of Nutrition and Metabolism · doi:10.1007/s12349-013-0135-1 · Cited by 24
Women undergoing Roux-en-Y Gastric Bypass surgery: Family resemblance in pre- to postsurgery physical activity and sedentary behavior in children and spouses
Berglind, D., Willmer, M., Tynelius, P., Ghaderi, A., Näslund, E. B., & Rasmussen, F. E. (2014) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2014.10.018 · Cited by 14
The ADAPP trial: a two-year longitudinal multidisciplinary intervention study for prostate cancer frail patients on androgen deprivation associated to curative radiotherapy
Mareschal, J., Weber, K., Rigoli, P., Biason, E., Frambati, L., Gotteland, C., Zilli, T., Pichard, C., & Miralbell, R. (2017) · Acta Oncologica · doi:10.1080/0284186x.2016.1273545 · Cited by 15
Self-citation
Are patients affected by mitochondrial disorders at nutritional risk?
Aubry, E., Aeberhard, C., Bally, L., Nuoffer, J., Risch, L., Mühlebach, S., Burgunder, J., & Stanga, Z. (2018) · Nutrition (Burbank, Los Angeles County, Calif.) · doi:10.1016/j.nut.2017.09.011 · Cited by 10
Glycine increases fat‐free mass in malnourished haemodialysis patients: a randomized double‐blind crossover trial
Genton, L., Teta, D., Pruijm, M. T., Stoermann, C., Marangon, N., Mareschal, J., Bassi, I., Wurzner‐Ghajarzadeh, A., Lazarević, V., Cynober, L., et al. (2021) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.12780 · Cited by 14
Self-citation
Fuzzy linguistic model for bioelectrical impedance vector analysis
Bronhara, B., Piccoli, A., & Pereira, J. C. R. (2012) · Clinical Nutrition · doi:10.1016/j.clnu.2012.02.014 · Cited by 14

Authors: Kyle, U. G., Genton, L., Karsegard, L., Slosman, D. O., & Pichard, C.
Affiliations: University Hospital of Geneva (CH)
ORCID: Genton, Laurence
Pichard, Claude
Venue: Nutrition
Publisher: Elsevier BV
Published: 2001-03
Volume: 17
Issue: 3
Pages: 248-253
ISSN: 0899-9007 (ISSN-L)
DOI: 10.1016/s0899-9007(00)00553-0
OpenAlex: W2041793073
Cited by: 575
References: 42
Citations by year: 2026: 13 · 2025: 19 · 2024: 26 · 2023: 24 · 2022: 28 · 2021: 39 · 2020: 27 · 2019: 31 · 2018: 34 · 2017: 35 · 2016: 32 · 2015: 35 · 2014: 35 · 2013: 26 · 2012: 33
FWCI: 7.95
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Nutrition (publishedVersion)
PubMed (publishedVersion)
Archive ouverte UNIGE (University of Geneva) (publishedVersion)
Archive ouverte UNIGE (University of Geneva) (submittedVersion)
Funders: Hôpitaux Universitaires de Genève
Topics: Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrical and Bioimpedance Tomography
Health Sciences › Medicine › Physiology (medical) › Nutrition and Health in Aging
Keywords: bioelectrical impedance analysis, fat-free mass, prediction equations, dual-energy X-ray absorptiometry, reactance, resistance, body mass index, older adults, overweight, validation, healthy adults
MeSH terms: Adult, Aged, Aged, 80 and over, Aging, Body Composition, Female, Humans, Male, Middle Aged, Reference Values, Regression Analysis, Reproducibility of Results, Absorptiometry, Photon, Body Mass Index, Electric Impedance

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Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years

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