Body composition estimation using skinfolds in children with and without health conditions affecting growth and body composition. (17th February 2017)

• Record Type: Journal Article
• Authors: Wendel, Danielle; Weber, David; Leonard, Mary B.; Magge, Sheela N.; Kelly, Andrea; Stallings, Virginia A.; Pipan, Mary; Stettler, Nicolas; Zemel, Babette S.
• Is Part Of: Annals of human biology. Volume 44:Number 2(2017)
• Page Start: 108
• Page End: 120
• Publication Date: 2017-02-17
• Subjects: Crohn's disease -- Down syndrome -- Fat mass -- fat-free mass -- percentage body fat; Human biology -- Periodicals; 612
• DOI: 10.3109/03014460.2016.1168867
• Languages: English
• ISSNs: 0301-4460

Abstract

Abstract: Background: Body composition prediction equations using skinfolds are useful alternatives to advanced techniques, but their utility across diverse paediatric populations is unknown. Aim: To evaluate published and new prediction equations across diverse samples of children with health conditions affecting growth and body composition. Subjects and methods: Anthropometric and dual-energy X-ray absorptiometry (DXA) body composition measures were obtained in children with Down syndrome ( n = 59), Crohn disease ( n = 128), steroid-sensitive nephrotic syndrome ( n = 67) and a healthy reference group ( n = 835). Published body composition equations were evaluated. New equations were developed for ages 3–21 years using the healthy reference sample and validated in other groups and national survey data. Results: Fat mass (FM), fat-free mass (FFM) and percentage body fat (%BF) from published equations were highly correlated with DXA-derived measures ( r = 0.71–0.98), but with poor agreement (mean difference = 2.4 kg, −1.9 kg and 6.3% for FM, FFM and %BF). New equations produced similar correlations ( r = 0.85–1.0) with improved agreement for the reference group (0.2 kg, 0.4 kg and 0.0% for FM, FFM and %BF, respectively) and in sub-groups. Conclusions: New body composition prediction equations show excellent agreement with DXA and improve body composition estimation in healthy children and those with selected conditions affecting growth.