Literature DB >> 18256451

VO(2max) prediction from multi-frequency bioelectrical impedance analysis.

Alexander Stahn1, Günther Strobel, Elmarie Terblanche.   

Abstract

Bioelectrical impedance analysis (BIA) has been shown to be highly related to skeletal muscle mass and blood volume, both of which are important determinants of maximal oxygen uptake (VO(2max)). The aim of the present study was therefore to investigate the ability of whole-body and segmental multi-frequency BIA to improve current nonexercise VO(2max) prediction models. Data for VO(2max) (mL min(-1)), anthropometry, self-reported physical activity (PA-R) and BIA were collected in 115 men and women. Multiple linear regression analysis (MLR) was used to develop the most parsimonious prediction model. Segmental BIA was not superior to whole-body measurements. Correlation coefficients between VO(2max) and resistance indices were significantly higher at 500 kHz compared to 50 kHz (p < 0.05). Intracellular resistance index, however, showed the highest correlation with VO(2max) (r = 0.89). After adjusting for age, gender and PA-R, MLR revealed that the inclusion of intracellular resistance index was slightly, but significantly (p < 0.001), superior to models based on anthropometry. Subgroup analyses indicated that the true benefit of BIA might be most prevalent in subjects with particularly low VO(2max) (<2500 mL min(-1)). In short, whole-body BIA marginally improves the accuracy of nonexercise VO(2max) prediction models and its advantage is most pronounced in individuals with particularly low VO(2max).

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Year:  2008        PMID: 18256451     DOI: 10.1088/0967-3334/29/2/003

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  6 in total

1.  The magnitude and duration of post-exercise hypotension after land and water exercises.

Authors:  Elmarie Terblanche; Aletta M E Millen
Journal:  Eur J Appl Physiol       Date:  2012-04-17       Impact factor: 3.078

2.  Prediction of maximal oxygen uptake by bioelectrical impedance analysis in overweight adolescents.

Authors:  M D Roberts; B Drinkard; L M Ranzenhofer; C G Salaita; N G Sebring; S M Brady; C Pinchbeck; J Hoehl; L B Yanoff; D M Savastano; J C Han; J A Yanovski
Journal:  J Sports Med Phys Fitness       Date:  2009-09       Impact factor: 1.637

3.  Multi-frequency bioimpedance in human muscle assessment.

Authors:  Else Marie Bartels; Emma Rudbæk Sørensen; Adrian Paul Harrison
Journal:  Physiol Rep       Date:  2015-04

4.  Muscle assessment using multi-frequency bioimpedance in a healthy Danish population aged 20-69 years: a powerful non-invasive tool in sports and in the clinic.

Authors:  Else Marie Bartels; Eva Littrup Andersen; Jack Kvistgaard Olsen; Lars Erik Kristensen; Henning Bliddal; Bente Danneskiold-Samsøe; Adrian Paul Harrison
Journal:  Physiol Rep       Date:  2019-06

5.  Probing cellular health at the muscle level-Multi-frequency bioimpedance in Parkinson's disease.

Authors:  Marko Celicanin; Adrian Paul Harrison; Jack Kvistgaard Olsen; Lise Korbo; Annemette Løkkegård; Charlotte Bjerg Petersen; Bente Danneskiold-Samsøe; Hartwig Roman Siebner; Tihomir Ilic; Else Marie Bartels
Journal:  Physiol Rep       Date:  2022-10

6.  Wearable Multi-Frequency and Multi-Segment Bioelectrical Impedance Spectroscopy for Unobtrusively Tracking Body Fluid Shifts during Physical Activity in Real-Field Applications: A Preliminary Study.

Authors:  Federica Villa; Alessandro Magnani; Martina A Maggioni; Alexander Stahn; Susanna Rampichini; Giampiero Merati; Paolo Castiglioni
Journal:  Sensors (Basel)       Date:  2016-05-11       Impact factor: 3.576

  6 in total

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