Anthropometry-based prediction of body composition in early infancy compared to air-displacement plethysmography.

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.