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*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Background/objectives
Prediction 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/methods
Data 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.

Results
Overall, 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.

Conclusions
The 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.
Original languageEnglish
Pages (from-to)715–723
Number of pages9
JournalEuropean Journal of Clinical Nutrition
Volume75
Early online date14 Oct 2020
DOIs
Publication statusPublished - 1 Apr 2021
Externally publishedYes

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