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dc.contributor.authorRamel, A
dc.contributor.authorGeirsdottir, O G
dc.contributor.authorArnarson, A
dc.contributor.authorThorsdottir, I
dc.date.accessioned2012-06-07T14:07:41Z
dc.date.available2012-06-07T14:07:41Z
dc.date.issued2011-08
dc.date.submitted2012-06-07
dc.identifier.citationEur. J. Clin. Nutr. 2011, 65(8):978-83en_GB
dc.identifier.issn1476-5640
dc.identifier.pmid21559037
dc.identifier.doi10.1038/ejcn.2011.65
dc.identifier.urihttp://hdl.handle.net/2336/227851
dc.descriptionTo access publisher full text version of this article. Please click on the hyperlink in Additional Links field.en_GB
dc.description.abstractBACKGROUND/OBJECTIVES: The aims were (1) to compare fat free mass (FFM) estimates from regional hand-held bioelectrical impedance analysis (HHBIA) with conventional BIA (CBIA) and dual energy X-ray absorptiometry (DXA) and (2) to develop a population specific equation for FFM prediction in Icelandic elderly. SUBJECTS/METHODS: DXA, CBIA and HHBIA data were available for 98 free-living Icelandic elderly (age=73.0 ± 5.6 years, body mass index=28.8 ± 5.2 kg/m(2)). Participants were randomized into a development block (n=50) and validation block (n=48). A population specific equation for FFM prediction was calculated using CBIA-derived resistance and anthropometric data from the development block and then compared with other BIA equations (Deurenberg, Segal, company-specific equations) and DXA estimates using the validation block. RESULTS: The correlations between BIA methods and DXA were very high, that is, >0.9; however, mean differences compared with DXA were quite variable, ranging from -5.0 (Deurenberg) to +2.5 (Segal, HHBIA) and +3.3 kg (CBIA). Mean difference of the population-specific equation was below 0.1 kg. The standard deviations of the differences ranged from 2.6 to 3.3 kg. The limits of agreement of the BIA methods were similar and between 9.9 and 12.9 kg. CONCLUSIONS: In Icelandic elderly, HHBIA and CBIA produce similar FFM estimates when using company-specific prediction equations. CBIA provides the additional possibility to use a population-specific prediction equation, which yields best results. However, limits of agreement were wide and similar of all employed BIA methods, which indicates principal limitations of BIA analysis in the determination of FFM.
dc.description.sponsorshipIcelandic Technology Development Fund 071323008 The University of Iceland Helga Jonsdottir and Sigurlidi Kristjansson Geriatric Research Funden_GB
dc.language.isoenen
dc.publisherNature Publishing Groupen_GB
dc.relation.urlhttp://dx.doi.org/10.1038/ejcn.2011.65en_GB
dc.rightsArchived with thanks to European journal of clinical nutritionen_GB
dc.subject.meshAbsorptiometry, Photonen_GB
dc.subject.meshAdipose Tissueen_GB
dc.subject.meshAgeden_GB
dc.subject.meshBody Compositionen_GB
dc.subject.meshBody Mass Indexen_GB
dc.subject.meshElectric Impedanceen_GB
dc.subject.meshFemaleen_GB
dc.subject.meshHumansen_GB
dc.subject.meshIcelanden_GB
dc.subject.meshMaleen_GB
dc.subject.meshRegression Analysisen_GB
dc.subject.meshReproducibility of Resultsen_GB
dc.titleRegional and total body bioelectrical impedance analysis compared with DXA in Icelandic elderly.en
dc.typeArticleen
dc.contributor.departmentUnit for Nutrition Research, Landspitali-University Hospital & Faculty of Food Science and Nutrition, University of Iceland, Reykjavik, Iceland. alfons@landspitali.isen_GB
dc.identifier.journalEuropean journal of clinical nutritionen_GB
html.description.abstractBACKGROUND/OBJECTIVES: The aims were (1) to compare fat free mass (FFM) estimates from regional hand-held bioelectrical impedance analysis (HHBIA) with conventional BIA (CBIA) and dual energy X-ray absorptiometry (DXA) and (2) to develop a population specific equation for FFM prediction in Icelandic elderly. SUBJECTS/METHODS: DXA, CBIA and HHBIA data were available for 98 free-living Icelandic elderly (age=73.0 ± 5.6 years, body mass index=28.8 ± 5.2 kg/m(2)). Participants were randomized into a development block (n=50) and validation block (n=48). A population specific equation for FFM prediction was calculated using CBIA-derived resistance and anthropometric data from the development block and then compared with other BIA equations (Deurenberg, Segal, company-specific equations) and DXA estimates using the validation block. RESULTS: The correlations between BIA methods and DXA were very high, that is, >0.9; however, mean differences compared with DXA were quite variable, ranging from -5.0 (Deurenberg) to +2.5 (Segal, HHBIA) and +3.3 kg (CBIA). Mean difference of the population-specific equation was below 0.1 kg. The standard deviations of the differences ranged from 2.6 to 3.3 kg. The limits of agreement of the BIA methods were similar and between 9.9 and 12.9 kg. CONCLUSIONS: In Icelandic elderly, HHBIA and CBIA produce similar FFM estimates when using company-specific prediction equations. CBIA provides the additional possibility to use a population-specific prediction equation, which yields best results. However, limits of agreement were wide and similar of all employed BIA methods, which indicates principal limitations of BIA analysis in the determination of FFM.


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