Evidence map›Paper›PMID 33057177›Full record

ArticleEuropean journal of clinical nutrition2021

Anthropometry-based prediction of body fat in infants from birth to 6 months: the Baby-bod study.

Sisitha Jayasinghe, Manoja P Herath, Jeffrey M Beckett, Kiran D K Ahuja, Nuala M Byrne, Andrew P Hills

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Article in European journal of clinical nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Sisitha JayasingheSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia.ORCID http://orcid.org/0000-0001-8805-385X
Manoja P HerathSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia.ORCID http://orcid.org/0000-0002-6581-5804
Jeffrey M BeckettSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia.ORCID http://orcid.org/0000-0002-2911-0313
Kiran D K AhujaSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia.
Nuala M ByrneSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia.
Andrew P HillsSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, TAS, 7250, Australia. andrew.hills@utas.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesPrediction equations generated from anthropometric measures are frequently used to quantify paediatric body composition. We tested the agreeability and predictive power of select (Lingwood and Aris) fat mass prediction equations against body fat measured via ADP; and generated and evaluated new anthropometry-based models for use in the first 6 months of life. SUBJECTS/

methodsData were obtained from 278 white European Australian infants at birth, 3 and 6 months. Prediction models (i.e. Baby-bod models) were generated for each time point via stepwise linear regression and compared for agreeability with ADP via limits of agreement, mean difference and total bias in Bland-Altman analyses. Predictive power of all equations in comparison to ADP were assessed using linear regression analysis.

resultsOverall, there was poor agreeability between percent body fat predicted via published equations and ADP. Proportional bias was detected for both methods (i.e. published equations and Baby-bod models) of body fat prediction. At birth, both Lingwood and BB0 equations overestimated percent body fat at the lower end of the FM spectrum. This trend was repeated at 3 months with all equations displaying a propensity to overestimate body fat at lower FM levels and underestimate at higher FM levels.

conclusionsThe results indicate that anthropometry, although less costly and relatively easier to implement, does not always produce comparable results with objective measures such as ADP. Given the importance of the accurate assessment of physical growth, including body composition in early life, it is timely to recommend the increased utilisation of techniques such as ADP.

Indexed as

Adipose TissueBody CompositionAnthropometryAustraliaChildHumansInfantInfant, NewbornLinear Models

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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.