Development and validation of bioimpedance prediction equations for fat-free mass in unilateral male amputees
Open accessAbstract
Background: Metabolic disease due to increased fat mass is observed in amputees (APTs), thereby restricting their activity. Systemic health management with periodic body composition (BC) testing is essential for healthy living. Bioelectrical impedance analysis (BIA) is a non-invasive and low-cost method to test BC; however, the APTs are classified as being exempted in the BIA. Objective: To develop segmental estimated regression equations (sEREs) for determining the fat-free mass (FFM, kg) suitable for APTs and improve the accuracy and validity of the sERE. Methods: Seventy-five male APTs participated in this cross-sectional study. Multiple regression analysis was performed to develop highly accurate sEREs of BIA based on independent variables derived from anthropometric measurements, dual-energy X-ray absorptiometry (DXA), and BIA parameters. The difference in validity between the predicted DXA and sum of the segmentally-predicted FFM values by sEREs (Sum_sEREs) values was evaluated using bivariate linear regression analysis and the Bland–Altman plot. Results: The coefficient of determination ( R 2 ) and total error ( TE ) between DXA and Sum_sEREs were 71% and 5.4 (kg) in the cross-validation analysis. Conclusions: We confirmed the possibility of evaluating the FFM of APTs through the sEREs developed in this study. We also identified several independent variables that should be considered while developing such sEREs. Further studies are required to determine the validity of our sEREs and the most appropriate BIA frequencies for measuring FFM in APTs.
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Nine equations for people with diseases were made with multifrequency devices involving measures obtained at 50 and 100 kHz.
“Seven equations were developed using single frequency devices at 50 kHz [35, 40, 98], while 9 equations were made with multifrequency devices involving measures obtained at 50 [41, 64, 65, 99] and 100 kHz [56].”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [41]
The Experimental device (BIA) section describes an InBody S10 capable of multifrequency measurement, and the Results describe equations for unilateral amputees. But the paper says it used only 50 kHz for these equations; it does not support attributing a 100-kHz measurement or the aggregate count of nine equations to this study. Page numbers are unavailable in our copy. (LLM, conf=0.87)
Experimental — accuracy not yet measuredRegarding foot-to-hand technology for people with diseases, four equations are for assessing FFM in amputee males.
“Regarding the foot to hand technology, there is one equation suitable for assessing FFM in overweight and obese postmenopausal females [98], four for appendicular FM and FFM in functionally limited male and female individuals [40], four for assessing FFM in amputee males [41], one for predicting TBW in anorexic females [56], and three for appendicular LSM in frail [64], chronic kidney [65], or hem”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [41]
The Results (Segmental Estimated Regression Equation; page unavailable) report FFM prediction equations for male amputees, and the Experimental device section describes electrodes placed at the hand and foot. But the Results specify equations for the left and right arms, left and right legs, and trunk—five segmental equations, not four. (LLM, conf=0.89)
Experimental — accuracy not yet measuredRisk of bias was unclear in six studies.
“Risk of bias was high in two [34, 35] and unclear in six [36–41] studies due to the low to moderate (R2 < 80%) coefficient of determination (R2) resulted from the multiple regression models.”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [41]
Concerns with applicability were unclear in 12 studies.
“Concerns with applicability were high in 19 studies [37, 42–59] and unclear [41, 50, 60–69] in 12 studies due to the restricted sample size.”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [41]
Out of the 16 available equations for people with diseases, eight were developed using segmental technology.
“Out of the 16 available equations, 14 were developed with foot to hand technology [40, 64, 98] and eight using segmental technology [40, 41, 56, 64, 65, 98, 99].”
From High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review (2024) · cites this paper as [41]
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Cited by
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Campa, F., Coratella, G., Cerullo, G., Noriega, Z., Francisco, R., Charrier, D., Irurtia, A., Lukaski, H., Silva, A. M., & Paoli, A. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-05272-x · Cited by 80 · see citing works
“Out of the 16 available equations, 14 were developed with foot to hand technology [40, 64, 98] and eight using segmental technology [40, 41, 56, 64, 65, 98, 99].”
BackgroundMethodInfluentialTuan, S., Chang, L., Sun, S., Lin, K., & Tsai, Y. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.1071409 · Cited by 16 · see citing works
Kampo, D., Závodná, E., & Vondra, V. (. (2025) · Physiological Research · doi:10.33549/physiolres.935758 · Cited by 5 · see citing works
Validation of body composition assessment for unilateral amputees via BIA by comparison with DXA
Choi, H., Ko, C., Chang, Y., Kim, G., & Kim, C. (2022) · Measurement · doi:10.1016/j.measurement.2022.111145 · Cited by 3 · see citing works
Self-citationSydorova, N. M., Kazmirchuk, K., Kolisnyk, O., Царалунга, В. М., Kobirnichenko, Y., & Sydorova, L. (2025) · Acta medica Lituanica · doi:10.15388/amed.2025.32.1.2 · Cited by 2 · see citing works
Peluso, I., Raguzzini, A., Toti, E., Boccia, G., Ferrara, R., Munzi, D., Brustio, P. R., Rainoldi, A., Cavedon, V., Milanese, C., et al. (2025) · Journal of Functional Morphology and Kinesiology · doi:10.3390/jfmk10030305 · Cited by 1 · see citing works
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Fiziksel Engellilik Vücut Bileşimini Saptamada Engel mi?
Sukan-Karaçağıl, B., & Köksal, E. (2023) · İstanbul Gelişim Üniversitesi Sağlık Bilimleri Dergisi · doi:10.38079/igusabder.1180134
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Campa, F., Coratella, G., Cerullo, G., Noriega, Z., Francisco, R., Charrier, D., Irurtia, A., Lukaski, H. C., Silva, A. M., & Paoli, A. (2024) · Figshare · doi:10.6084/m9.figshare.26727262
- Authors
- Choi, H.-J., Ko, C.-Y., Chang, Y., Kim, G.-S., Choi, K., & Kim, C.-H.
- Affiliations
- Rehabilitation Engineering Research Institute (KR)
- Department of Research & Development, Refind Inc, Wonju, Gangwon-do, Republic of Korea
- Department of Medical Convergence Research & Development, Rehabilitation Engineering Research Institute, Incheon, Republic of Korea
- Department of Healthcare Business Division, Healthmax company, Seoul, Gangnam-gu, Republic of Korea
- Soonchunhyang University (KR)
- Corresponding author
- Kim, Chul-Hyun
- Venue
- PeerJ
- Publisher
- PeerJ
- Published
- 2021-03-08
- Volume
- 9
- Pages
- e10970
- ISSN
- 2167-8359 (ISSN-L)
- PMC
- PMC7950192
- OpenAlex
- W3133851255
- Cited by
- 10
- References
- 86
- Citations by year
- 2025: 4 · 2024: 3 · 2023: 1 · 2022: 2
- FWCI
- 0.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PeerJ (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Ministry of Science and ICT in 2020 (2019-0-01758)
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrical and Bioimpedance Tomography
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Keywords
- bioelectrical impedance analysis, fat-free mass, amputees, body composition, prediction equation validation, dual-energy X-ray absorptiometry, anthropometry, unilateral amputation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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