The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The Validity of Bioelectrical Impedance Models in Clinical Populations
Abstract
Bioelectrical impedance analysis (BIA) is the most commonly used body composition technique in published studies. Herein we review the theory and assumptions underlying the various BIA and bioelectrical impedance spectroscopy (BIS) models, because these assumptions may be invalidated in clinical populations. Single‐frequency serial BIA and discrete multifrequency BIA may be of limited validity in populations other than healthy, young, euvolemic adults. Both models inaccurately predict total body water (TBW) and extracellular water (ECW) in populations with changes in trunk geometry or fluid compartmentalization, especially at the level of the individual. Single‐frequency parallel BIA may predict body composition with greater accuracy than the serial model. Hand‐to‐hand and leg‐to‐leg BIA models do not accurately predict percent fat mass. BIS may predict ECW, but not TBW, more accurately than single‐frequency BIA. Segmental BIS appears to be sensitive to fluid accumulation in the trunk. In general, bioelectrical impedance technology may be acceptable for determining body composition of groups and for monitoring changes in body composition within individuals over time. Use of the technology to make single measurements in individual patients, however, is not recommended. This has implications in clinical settings, in which measurement of individual patients is important.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965
Nutritional assessment with bioelectrical impedance analysis in maintenance hemodialysis patients.
Chertow, G. M., Lowrie, E. G., Wilmore, D. W., Gonzalez, J., Lew, N. L., Ling, J., Leboff, M. S., Gottlieb, M. N., Huang, W., & Zebrowski, B. (1995) · Journal of the American Society of Nephrology · doi:10.1681/asn.v6175 · Cited by 257
Pirlich, M., Schütz, T., Spachos, T., Ertl, S., WeiΒ, M.-L., Lochs, H., & Plauth, M. (2000) · Hepatology · doi:10.1053/jhep.2000.20524 · Cited by 207
Estimation of body composition from bioelectric impedance of body segments
Baumgartner, R. N., Chumlea, W. C., & Roche, A. F. (1989) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/50.2.221 · Cited by 201
Eisenkölbl, J., Kartasurya, M., & Widhalm, K. (2001) · European Journal of Clinical Nutrition · doi:10.1038/sj.ejcn.1601184 · Cited by 115
Validity and accuracy of regional bioelectrical impedance devices to determine whole-body fatness
Lukaski, H. C., & Siders, W. A. (2003) · Nutrition · doi:10.1016/s0899-9007(03)00166-7 · Cited by 73
Cited by
Khalil, S., Mohktar, M., & Ibrahim, F. (2014) · Sensors · doi:10.3390/s140610895 · Cited by 712
Jaffrin, M. Y., & Morel, H. (2008) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2008.06.009 · Cited by 490
Dehydration: Physiology, Assessment, and Performance Effects
Cheuvront, S. N., & Kenefick, R. W. (2014) · Comprehensive Physiology · doi:10.1002/cphy.c130017 · Cited by 461
Bioimpedance at the Bedside: Current Applications, Limitations, and Opportunities
Mulasi, U., Kuchnia, A. J., Cole, A. J., & Earthman, C. P. (2015) · Nutrition in Clinical Practice · doi:10.1177/0884533614568155 · Cited by 337
International society of sports nutrition position stand: diets and body composition
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., et al. (2017) · Journal of the International Society of Sports Nutrition · doi:10.1186/s12970-017-0174-y · Cited by 301
Metadata
- Authors
- Buchholz, A. C., Bartok, C., & Schoeller, D. A.
- Venue
- Nutrition in Clinical Practice
- Publisher
- Wiley
- Published
- 2004-10
- Volume
- 19
- Issue
- 5
- Pages
- 433-446
- ISSN
- 0884-5336 (ISSN-L)
- 1941-2452
- OpenAlex
- W2114211170
- Cited by
- 229
- References
- 6
- FWCI
- 3.23
- Type
- journal article
- Language
- en
- Open access
- closed
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Validity of Bioelectrical Impedance Models in Clinical Populations. https://app.cochat.ai/papers/10.1177/0115426504019005433
- The paper
- Buchholz, A. C., Bartok, C., & Schoeller, D. A. (2004). The Validity of Bioelectrical Impedance Models in Clinical Populations. Nutrition in Clinical Practice. https://doi.org/10.1177/0115426504019005433
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.