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PLoS One. 2013;8(3):e58533. doi: 10.1371/journal.pone.0058533. Epub 2013 Mar 6.

Accuracy of specific BIVA for the assessment of body composition in the United States population.

Author information

1
Department of Environmental and Life Sciences, University of Cagliari, Cagliari, Italy.

Abstract

BACKGROUND:

Bioelectrical impedance vector analysis (BIVA) is a technique for the assessment of hydration and nutritional status, used in the clinical practice. Specific BIVA is an analytical variant, recently proposed for the Italian elderly population, that adjusts bioelectrical values for body geometry.

OBJECTIVE:

Evaluating the accuracy of specific BIVA in the adult U.S. population, compared to the 'classic' BIVA procedure, using DXA as the reference technique, in order to obtain an interpretative model of body composition.

DESIGN:

A cross-sectional sample of 1590 adult individuals (836 men and 754 women, 21-49 years old) derived from the NHANES 2003-2004 was considered. Classic and specific BIVA were applied. The sensitivity and specificity in recognizing individuals below the 5(th) and above the 95(th) percentiles of percent fat (FMDXA%) and extracellular/intracellular water (ECW/ICW) ratio were evaluated by receiver operating characteristic (ROC) curves. Classic and specific BIVA results were compared by a probit multiple-regression.

RESULTS:

Specific BIVA was significantly more accurate than classic BIVA in evaluating FMDXA% (ROC areas: 0.84-0.92 and 0.49-0.61 respectively; p = 0.002). The evaluation of ECW/ICW was accurate (ROC areas between 0.83 and 0.96) and similarly performed by the two procedures (p = 0.829). The accuracy of specific BIVA was similar in the two sexes (p = 0.144) and in FMDXA% and ECW/ICW (p = 0.869).

CONCLUSIONS:

Specific BIVA showed to be an accurate technique. The tolerance ellipses of specific BIVA can be used for evaluating FM% and ECW/ICW in the U.S. adult population.

PMID:
23484033
PMCID:
PMC3590169
DOI:
10.1371/journal.pone.0058533
[Indexed for MEDLINE]
Free PMC Article

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