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dc.contributor.CRUESPUNIVERSIDADE DE ESTADUAL DE CAMPINASpt_BR
dc.typeArtigo de Periódicopt_BR
dc.titleValidity Of Bioelectrical Impedance Analysis To Estimation Fat-free Mass In The Army Cadetspt_BR
dc.contributor.authorLangerpt_BR
dc.contributor.authorRD; Borgespt_BR
dc.contributor.authorJH; Pascoapt_BR
dc.contributor.authorMA; Cirolinipt_BR
dc.contributor.authorVX; Guerrapt_BR
dc.contributor.authorG; Goncalvespt_BR
dc.contributor.authorEMpt_BR
unicamp.author.emailraqueldlanger@gmail.com; borgesedfisica@gmail.com; pascoawaf@bol.com.br; vxcirolini@hotmail.com; gilguer@fcm.unicamp.br; emaildozeique@gmail.compt_BR
dc.subjectBody Compositionpt_BR
dc.subjectDual-energy X-ray Absorptiometrypt_BR
dc.subjectPredictive Equationspt_BR
dc.description.abstractBioelectrical Impedance Analysis (BIA) is a fast, practical, non-invasive, and frequently used method for fat-free mass (FFM) estimation. The aims of this study were to validate predictive equations of BIA to FFM estimation in Army cadets and to develop and validate a specific BIA equation for this population. Methods: A total of 396 males, Brazilian Army cadets, aged 17-24 years were included. The study used eight published predictive BIA equations, a specific equation in FFM estimation, and dual-energy X-ray absorptiometry (DXA) as a reference method. Student's t-test (for paired sample), linear regression analysis, and Bland-Altman method were used to test the validity of the BIA equations. Results: Predictive BIA equations showed significant differences in FFM compared to DXA (p < 0.05) and large limits of agreement by Bland-Altman. Predictive BIA equations explained 68% to 88% of FFM variance. Specific BIA equations showed no significant differences in FFM, compared to DXA values. Conclusion: Published BIA predictive equations showed poor accuracy in this sample. The specific BIA equations, developed in this study, demonstrated validity for this sample, although should be used with caution in samples with a large range of FFM.en
dc.relation.ispartofNutrientspt_BR
dc.publisher.cityBASELpt_BR
dc.publisherMDPI AGpt_BR
dc.date.issued2016pt_BR
dc.identifier.citationNutrients. MDPI AG, n. 8, n. 3, p. .pt_BR
dc.language.isoEnglishpt_BR
dc.description.volume8pt_BR
dc.description.issuenumberpt_BR
dc.description.lastpagept_BR
dc.rightsabertopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn2072-6643pt_BR
dc.identifier.wosidWOS:000373528500033pt_BR
dc.identifier.doi10.3390/nu8030121pt_BR
dc.identifier.urlhttp://www.mdpi.com/2072-6643/8/3/121pt_BR
dc.description.sponsorshipCoordination for the Improvement of Higher Education Personnel-CAPES [23001.000422/98-30]pt_BR
dc.description.sponsorshipSao Paulo Research Foundation-FAPESP [2011/23460-1]pt_BR
dc.description.sponsorship1Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)pt_BR
dc.description.sponsorship1Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.date.available2016-12-06T18:32:29Z-
dc.date.accessioned2016-12-06T18:32:29Z-
dc.description.provenanceMade available in DSpace on 2016-12-06T18:32:29Z (GMT). No. of bitstreams: 1 000373528500033.pdf: 1600847 bytes, checksum: cdf761f7e301dd9be8fa3b8bef02beab (MD5) Previous issue date: 2016en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/320553-
dc.description.conferencelocationpt_BR
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