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Updated: Nov 2, 2025
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Anthropometry-based prediction of body composition in early infancy compared to air-displacement plethysmography
Laurentya Olga1, Inge A L P van Beijsterveldt2, Ieuan A Hughes1
1Department of Paediatrics, University of Cambridge, Cambridge, UK.
Insights
New anthropometry equations accurately estimate infant body composition, outperforming existing methods. These new infant body fat mass and fat-free mass prediction models offer improved validity for 3- and 6-month-old cohorts.
Area of Science:
- Pediatric Nutrition
- Body Composition Analysis
- Infant Growth Monitoring
Background:
- Existing anthropometry-based equations for infant body composition are often designed for newborns or adolescents.
- Accurate estimation of body composition in infancy is crucial for monitoring growth and health.
- There is a need for validated prediction equations specific to the infant period.
Purpose of the Study:
- To derive new prediction equations for infant body composition using air-displacement plethysmography (ADP-PEA Pod) as the criterion.
- To validate these newly developed equations in an independent infant cohort.
- To compare the performance of the new equations against previously published equations.
Main Methods:
- Anthropometric data, including skinfold thicknesses (SFT) at four sites, were collected from infants in the Cambridge Baby Growth Study (CBGS).
- Total body fat mass (FM) and fat-free mass (FFM) were derived using ADP-PEA Pod.
- Linear regression models were used to develop prediction equations in CBGS and subsequently validated in the Sophia Pluto cohort using Bland-Altman analyses.
Main Results:
- The newly developed CBGS equations, incorporating sex, age, weight, length, and SFT, explained 65% of the variance in FM and 79% in FFM.
- In the independent Sophia Pluto cohort, the CBGS equations demonstrated smaller mean bias for estimating FM and FFM at 3 and 6 months compared to published equations.
- Specific mean bias (95% limits of agreement) for FM at 3 months was 0.008 kg (-0.489, 0.505) and at 6 months was 0.084 kg (-0.545, 0.713).
Conclusions:
- The CBGS prediction equations for infant fat mass (FM) and fat-free mass (FFM) exhibit superior validity in an independent cohort at 3 and 6 months of age.
- These new equations provide a more accurate assessment of infant body composition compared to existing methods.
- The findings support the use of these refined equations for better infant growth monitoring and nutritional assessment.
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.
