Evidence map›Paper›PMID 23732547›Full record

ArticleThe journal of nutrition, health & aging2013

Efficacy of specific bioelectrical impedance vector analysis (BIVA) for assessing body composition in the elderly.

E Marini, G Sergi, V Succa, B Saragat, S Sarti, A Coin, E Manzato, R Buffa

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Article in The journal of nutrition, health & aging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Effect of Physical Training on Body Composition in Brazilian Military.International journal of environmental research and public health · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

E MariniDepartment of Environmental and Life Sciences, Anthropological Science Section, University of Cagliari, Cittadella Universitaria, 09042 Monserrato (Cagliari), Italy. emarini@unica.it
G Sergi
V Succa
B Saragat
S Sarti
A Coin
E Manzato
R Buffa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to ascertain the efficacy of bioelectrical impedance vector analysis (BIVA) in assessing body composition in the elderly by comparing findings with the results of dual-energy X-ray absorptiometry (DXA), and to test an analytical variant of the method (specific BIVA).

designCross-sectional study.

participantsThe sample comprised 207 free-living elderly individuals (75 men and 132 women) aged 65 to 93 years. MEASUREMENTS: Anthropometric and bioelectrical measurements were taken according to standard criteria. BIVA was applied using the 'classic' procedure and correcting bioelectrical values for body geometry to obtain an estimate of the whole-body impedivity. DXA was used as a reference body composition assessment method. BIVA (classic and specific values) and DXA findings were compared using Student's t and Hotelling's T2 tests, and Pearson's correlation coefficient.

resultsIn both sexes, BIVA distinguished between individuals with different amounts of fat and fat-free mass (lean mass including bone mineral content), according to DXA, but not between those with different proportions of fat mass (FM%). Specific bioelectrical values detected changes in body composition.

conclusionBIVA should be used with caution for evaluating body composition in the elderly. Specific bioelectrical values proved effective, showing promise as a methodological variant of BIVA, suitable for identifying age-related changes in body fatness.

Indexed as

Body CompositionElectric ImpedanceAbsorptiometry, PhotonAdipose TissueAgedAged, 80 and overAnthropometryBody Mass IndexBone DensityCross-Sectional StudiesFemaleHumansMaleNutritional Status

Identifiers

PMID23732547
PMCPMC12879001

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.