Validity of bioelectrical impedance to estimate fat-free mass in boys with Duchenne muscular dystrophy.
Open accessAbstract
The evaluation of fat-free mass (FFM) in patients with Duchenne muscular dystrophy (DMD) is useful to investigate disease progression and therapeutic efficacy. This study aimed to validate the Bioelectrical impedance (BIA) method compared with the dual-energy X-ray absorptiometry (DXA) for estimating the %FFM in boys with DMD. This is a cross-sectional study performed with children and adolescents diagnosed with DMD. Resistance and reactance were measured with a BIA analyzer, from which eight predictive equations estimated the %FFM. The %FFM was also determined by DXA and its used as a reference method. Pearson correlation test, coefficient of determination, the root-mean-square error, the interclass correlation coefficient, and linear regression analysis were performed between %FFM values obtained by BIA and DXA. The agreement between these values was verified with the Bland-Altman plot analysis. Forty-six boys aged from 5 to 20 years were enrolled in the study. All the equations showed a correlation between the %FFM estimated by BIA and determined by DXA (p < 0.05). The Bland-Altman method indicated that two equations have a significant bias (p < 0.05) and six equations showed no significant bias of %FFM (p > 0.05). However, one of them has high variation and wide limits of agreement. Five of eight %FFM predictive equations tested in DMD were accurate when compared with the DXA. It can be concluded that BIA is a validity method to evaluate patients with DMD.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
BIA is one of the most convenient techniques for assessing body composition in a clinical setting and in epidemiological approaches, mainly because it is easy to apply, fast, and non-invasive, in addition to having a relatively low cost.
“The BIA is one of the most convenient techniques for assessing body composition in a clinical setting and in epidemiological approaches, mainly, because it is easy to apply, fast, and non-invasive, in addition to having a relatively low cost (5, 45, 46).”
From Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance (2022) · cites this paper as [45]
The Introduction describes BIA as simple, practical, and low-cost for evaluating body composition in clinical practice; the Discussion calls it easy to apply and inexpensive compared with DXA. Our copy does not establish its use in epidemiological approaches or explicitly describe it as fast or non-invasive. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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 · see citing works
Development of a WHO growth reference for school-aged children and adolescents
de Onis, M. (2007) · Bulletin of the World Health Organization · doi:10.2471/blt.07.043497 · Cited by 8,826 · see citing works
Understanding bland altman analysis
Giavarina, D. (2015) · Biochemia Medica · doi:10.11613/bm.2015.015 · Cited by 4,022 · see citing works
Validation of tetrapolar bioelectrical impedance method to assess human body composition
Lukaski, H. C., Bolonchuk, W. W., Hall, C. B., & Siders, W. A. (1986) · Journal of Applied Physiology · doi:10.1152/jappl.1986.60.4.1327 · Cited by 1,376 · see citing works
Fat-free and fat mass percentiles in 5225 healthy subjects aged 15 to 98 years
Kyle, U. G., Genton, L., Slosman, D. O., & Pichard, C. (2001) · Nutrition · doi:10.1016/s0899-9007(01)00555-x · Cited by 440 · see citing works
Houtkooper, L. B., Going, S. B., Lohman, T. G., Roche, A. F., & Van Loan, M. (1992) · Journal of Applied Physiology · doi:10.1152/jappl.1992.72.1.366 · Cited by 348 · see citing works
Chumlea, W. M. C., Guo, S., & Steinbaugh, M. (1994) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(94)92540-2 · Cited by 312 · see citing works
Schaefer, F., Georgi, M., Zieger, A., & Schärer, K. (1994) · Pediatric Research · doi:10.1203/00006450-199405000-00016 · Cited by 260 · see citing works
Santis, S. D., Galleggiante, V., Scandiffio, L., Liso, M., Sommella, E., Sobolewski, A., Spilotro, V., Pinto, A., Campiglia, P., Serino, G., et al. (2017) · Nutrients · doi:10.3390/nu9070706 · Cited by 252 · see citing works
Designing Insurance to Promote Use of Childhood Obesity Prevention Services
Rask, K. J., Gazmararian, J. A., Kohler, S. S., Hawley, J. N., Bogard, J., & Brown, V. A. (2013) · Journal of Obesity · doi:10.1155/2013/379513 · Cited by 218 · see citing works
The Use of Skinfold to Estimate Body Fatness on Children and Youth
Lohman, T. G. (1987) · Journal of Physical Education Recreation & Dance · doi:10.1080/07303084.1987.10604383 · Cited by 199 · see citing works
Horlick, M., Arpadi, S. M., Bethel, J., Wang, J., Moye, J., Cuff, P. A., Pierson, R. N., & Kotler, D. P. (2002) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/76.5.991 · Cited by 137 · see citing works
Rush, E. C., Puniani, K., Valencia, M. E., Davies, P. S. W., & Plank, L. D. (2003) · European Journal of Clinical Nutrition · doi:10.1038/sj.ejcn.1601701 · Cited by 134 · see citing works
(1990) · PubMed · Cited by 128 · see citing works
Puberty timing associated with obesity and central obesity in Chinese Han girls
Lian, Q., Mao, Y., LUO, S. H., Zhang, S., Tu, X., Zuo, X., Lou, C., & Zhou, W. (2019) · BMC Pediatrics · doi:10.1186/s12887-018-1376-4 · Cited by 127 · see citing works
Joseph, S., Wang, C., Bushby, K. M. D., et al. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2019.0242 · Cited by 111 · see citing works
Update in Duchenne and Becker muscular dystrophy
Waldrop, M. A., & Flanigan, K. M. (2019) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000739 · Cited by 111 · see citing works
Nutritional Challenges in Duchenne Muscular Dystrophy
Salera, S., Menni, F., Moggio, M. G., et al. (2017) · Nutrients · doi:10.3390/nu9060594 · Cited by 75 · see citing works
Strijkers, G. J., Araújo, E. C. D. A., Azzabou, N., Bendahan, D., Blamire, A. M., Burakiewicz, J., Carlier, P. G., Damon, B. M., Deligianni, X., Froeling, M., et al. (2018) · Journal of Neuromuscular Diseases · doi:10.3233/jnd-180333 · Cited by 68 · see citing works
Nutrition Considerations in Duchenne Muscular Dystrophy
Davis, J., Samuels, E., & Mullins, L. (2015) · Nutrition in Clinical Practice · doi:10.1177/0884533615586202 · Cited by 65 · see citing works
Mok, É., Béghin, L., Gachon, P., Daubrosse, C., Fontan, J., Cuisset, J., Gottrand, F., & Hankard, R. (2006) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/83.1.65 · Cited by 60 · see citing works
Saunders, C. M., Rehbinder, E. M., Carlsen, K. C. L., Gudbrandsgard, M., Carlsen, K., Haugen, G. N., Hedlin, G., Jonassen, C. M., Sjøborg, K., Landrø, L., et al. (2019) · Food & Nutrition Research · doi:10.29219/fnr.v63.3676 · Cited by 60 · see citing works
Body Composition and Water Compartment Measurements in Boys with Duchenne Muscular Dystrophy
McDonald, C. M., Carter, G. T., Abresch, R. T., Widman, L. M., Styne, D. M., SCHONFELD-WARDEN, N. A., & Kilmer, D. D. (2005) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/01.phm.0000166880.91117.04 · Cited by 57 · see citing works
Fat-free mass by bioelectrical impedance Vs dual-energy X-ray absorptiometry (DXA)
LORENZO, A. D., Sorge, S. P., Iacopino, L., Andréoli, A., Luca, P. P.-D., & Sasso, G. F. (1998) · Applied Radiation and Isotopes · doi:10.1016/s0969-8043(97)00099-7 · Cited by 56 · see citing works
Mok, É., Letellier, G., Cuisset, J., Denjean, A., Gottrand, F., & Hankard, R. (2010) · Clinical Nutrition · doi:10.1016/j.clnu.2010.03.011 · Cited by 56 · see citing works
Silva, A. M., Fields, D. A., & Sardinha, L. B. (2013) · Journal of Obesity · doi:10.1155/2013/148696 · Cited by 52 · see citing works
Growth, pubertal development, and skeletal health in boys with Duchenne Muscular Dystrophy
Ward, L. M., & Weber, D. R. (2018) · Current Opinion in Endocrinology Diabetes and Obesity · doi:10.1097/med.0000000000000456 · Cited by 50 · see citing works
Validity of Bioelectrical Impedance Analysis to Estimation Fat-Free Mass in the Army Cadets
Langer, R., Borges, J., Pascoa, M., Cirolini, V., Guerra-Júnior, G., & Gonçalves, E. (2016) · Nutrients · doi:10.3390/nu8030121 · Cited by 44 · see citing works
Sleep Disordered Breathing in Duchenne Muscular Dystrophy
LoMauro, A., D’Angelo, M. G., & Aliverti, A. (2017) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-017-0750-1 · Cited by 43 · see citing works
Ooi, C. Y., Sutherland, R., Castellani, C., et al. (2019) · BMC Pediatrics · doi:10.1186/s12887-019-1756-4 · Cited by 31 · see citing works
Body composition and body mass index in Duchenne muscular dystrophy: Role of dietary intake
Bernabé-García, M., Rodríguez‐Cruz, M., Atilano-Miguel, S., Cruz‐Guzmán, O. D. R., Almeida‐Becerril, T., Calder, P. C., & González, J. (2018) · Muscle & Nerve · doi:10.1002/mus.26340 · Cited by 29 · see citing works
Wong, S. H. (2014) · Medical Science Monitor · doi:10.12659/msm.890696 · Cited by 24 · see citing works
Mukhtar, F., Boffetta, P., Dabo, B., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0199745 · Cited by 21 · see citing works
Devakumar, D., Grijalva-Eternod, C. S., Roberts, S., Chaube, S. S., Saville, N. M., Manandhar, D. S., Costello, A. M. D. L., Osrin, D., & Wells, J. C. K. (2015) · PeerJ · doi:10.7717/peerj.785 · Cited by 18 · see citing works
Truncal fat distribution correlates with decreased vital capacity in Duchenne muscular dystrophy
Canapari, C. A., Barrowman, N., Hoey, L., Walker, S., Townsend, E. L., Tseng, B. S., & Katz, S. L. (2014) · Pediatric Pulmonology · doi:10.1002/ppul.23004 · Cited by 17 · see citing works
A Bedside Measure of Body Composition in Duchenne Muscular Dystrophy
Elliott, S. A., Davidson, Z. E., Davies, P. S. W., & Truby, H. (2014) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2014.08.008 · Cited by 16 · see citing works
Rutkove, S. B., Wu, J. S., Zaidman, C. M., Kapur, K., Yim, S., Pasternak, A. E., Madabusi, L., Szelag, H., Harrington, T., Li, J., et al. (2016) · Clinical Neurophysiology · doi:10.1016/j.clinph.2016.09.017 · Cited by 16 · see citing works
Annexstad, E. J., Fagerheim, T., Holm, I., & Rasmussen, M. (2019) · Journal of Neuromuscular Diseases · doi:10.3233/jnd-190402 · Cited by 15 · see citing works
Bioelectrical impedance vector analysis and phase angle in boys with Duchenne muscular dystrophy
Vermeulen, K. M., Lopes, M. M. G. D., Grilo, E. C., et al. (2019) · Food & Nutrition Research · doi:10.29219/fnr.v63.1615 · Cited by 14 · see citing works
Self-citationBody composition of patients with Duchenne muscular dystrophy: the Greek experience
Doulgeraki, A. E., Athanasopoulou, H., Katsalouli, M., et al. (2015) · Acta Neurologica Belgica · doi:10.1007/s13760-015-0582-1 · Cited by 12 · see citing works
Wood, C. L., Cheetham, T. D., Hollingsworth, K. G., Guglieri, M., Sahun, Y. A., Punniyakodi, S., Mayhew, A. G., & Straub, V. W. (2019) · BMC Pediatrics · doi:10.1186/s12887-019-1503-x · Cited by 12 · see citing works
Cross-validation of prediction equations for estimating body composition in ballet dancers
Leal, L. L. A., Barbosa, G. S. L., Ferreira, R. L. U., Avelino, E. B., Bezerra, A. N., Vale, S. H. D. L., & Maciel, B. L. L. (2019) · PLoS ONE · doi:10.1371/journal.pone.0219045 · Cited by 12 · see citing works
Self-citationPascual‐Morena, C., Martínez‐Vizcaíno, V., Álvarez-Bueno, C., et al. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-029341 · Cited by 12 · see citing works
Bayram, E., Topçu, Y., Karakaya, P., et al. (2012) · Acta Neurologica Belgica · doi:10.1007/s13760-012-0125-y · Cited by 8 · see citing works
O’Connor, M., & van der Kamp, S. (2007) · Lenus, The Irish Health Repository (Dr Steevens Hospital Library) · Cited by 4 · see citing works
Editorial: The changing profile of cerebrovascular diseases
Leys, D. (2018) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000648 · Cited by 4 · see citing works
Estimating the height of elderly nursing home residents: Which equation to use?
de Lima, M. F. S., de Oliveira, L. P., Cabral, N. L. D. A., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205642 · Cited by 3 · see citing works
CROSS-VALIDATION OF BODY COMPOSITION EQUATIONS FOR CHILDREN USING DUAL-ENERGY X-RAY ABSORPTIOMETRY
Jenkins, K. A., & Heyward, V. H. (1999) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-199905001-00924 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Costa, R. F. D., Silva, A. M., Masset, K. V. D. S. B., Cesário, T. D. M., Cabral, B. G. D. A. T., Ferrari, G., & Dantas, P. M. S. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.820736 · Cited by 18 · see citing works
“The BIA is one of the most convenient techniques for assessing body composition in a clinical setting and in epidemiological approaches, mainly, because it is easy to apply, fast, and noninvasive, in addition to having a relatively low cost (5, 45, 46).”
Method
- Authors
- Grilo, E. C., Cunha, T. A., Costa, Á. D. S., Araújo, B. G. M., Lopes, M. M. G. D., Maciel, B. L. L., Alves, C. X., Vermeulen-Serpa, K. M., Dourado-Júnior, M. E. T., Leite-Lais, L., Brandão-Neto, J., & Vale, S. H. L.
- Affiliations
- Universidade Federal do Rio Grande do Norte (BR)
- Corresponding author
- Grilo, Evellyn C.
- Cunha, Thais A.
- Costa, Ádila Danielly S.
- Araújo, Bárbara G. M.
- Lopes, Márcia Marília G. D.
- Maciel, Bruna L. L.
- Alves, Camila X.
- Vermeulen-Serpa, Karina M.
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-11-20
- Volume
- 15
- Issue
- 11
- Pages
- e0241722
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7679022
- OpenAlex
- W3103884425
- Cited by
- 13
- References
- 48
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 3
- FWCI
- 1.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (302298/2017-7, 422667/2016-1, 2017-7)
- Institute on the Environment, University of Minnesota
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
- Keywords
- Duchenne muscular dystrophy, bioelectrical impedance analysis, fat-free mass, dual-energy X-ray absorptiometry, prediction equations, method validation, children and adolescents, muscle mass assessment
- MeSH terms
- Adolescent, Algorithms, Body Composition, Body Weight, Child, Cross-Sectional Studies, Humans, Male, Absorptiometry, Photon, Body Mass Index, Linear Models, Electric Impedance, Muscular Dystrophy, Duchenne, Young Adult
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