Anthropometry‐based prediction of body composition in early infancy compared to air‐displacement plethysmography
Published version
Peer-reviewed
Repository URI
Repository DOI
Change log
Authors
Abstract
Summary: Background: Anthropometry‐based equations are commonly used to estimate infant body composition. However, existing equations were designed for newborns or adolescents. We aimed to (a) derive new prediction equations in infancy against air‐displacement plethysmography (ADP‐PEA Pod) as the criterion, (b) validate the newly developed equations in an independent infant cohort and (c) compare them with published equations (Slaughter‐1988, Aris‐2013, Catalano‐1995). Methods: Cambridge Baby Growth Study (CBGS), UK, had anthropometry data at 6 weeks (N = 55) and 3 months (N = 64), including skinfold thicknesses (SFT) at four sites (triceps, subscapular, quadriceps and flank) and ADP‐derived total body fat mass (FM) and fat‐free mass (FFM). Prediction equations for FM and FFM were developed in CBGS using linear regression models and were validated in Sophia Pluto cohort, the Netherlands, (N = 571 and N = 447 aged 3 and 6 months, respectively) using Bland–Altman analyses to assess bias and 95% limits of agreement (LOA). Results: CBGS equations consisted of sex, age, weight, length and SFT from three sites and explained 65% of the variance in FM and 79% in FFM. In Sophia Pluto, these equations showed smaller mean bias than the three published equations in estimating FM: mean bias (LOA) 0.008 (−0.489, 0.505) kg at 3 months and 0.084 (−0.545, 0.713) kg at 6 months. Mean bias in estimating FFM was 0.099 (−0.394, 0.592) kg at 3 months and −0.021 (−0.663, 0.621) kg at 6 months. Conclusions: CBGS prediction equations for infant FM and FFM showed better validity in an independent cohort at ages 3 and 6 months than existing equations.
Description
Funder: Danone Nutricia Research
Funder: EU Commission for JPI HDHL program ‘Call III Biomarkers’ for project: BioFN ‐ Biomarkers for Infant Fat Mass Development and Nutrition; Grant(s): 696295
Keywords
Journal Title
Conference Name
Journal ISSN
2047-6310
Volume Title
Publisher
Publisher DOI
Sponsorship
Medical Research Council Epidemiology Unit (MC_UU_00006/2, MC_UU_12015/2)
NIHR Cambridge Biomedical Research (IS‐BRC‐1215‐20014)
ZonMw (529051013)