Body shape and size in 6-year old children: assessment by three-dimensional photonic scanning
- PMID: 26880232
- PMCID: PMC4899819
- DOI: 10.1038/ijo.2016.30
Body shape and size in 6-year old children: assessment by three-dimensional photonic scanning
Abstract
Background: Body shape and size are typically described using measures such as body mass index (BMI) and waist circumference, which predict disease risks in adults. However, this approach may underestimate the true variability in childhood body shape and size.
Objective: To use a comprehensive three-dimensional photonic scan approach to describe variation in childhood body shape and size.
Subjects/methods: At age 6 years, 3350 children from the population-based 2004 Pelotas birth cohort study were assessed by three-dimensional photonic scanner, traditional anthropometry and dual X-ray absorptiometry. Principal component analysis (PCA) was performed on height and 24 photonic scan variables (circumferences, lengths/widths, volumes and surface areas).
Results: PCA identified four independent components of children's body shape and size, which we termed: Corpulence, Central:peripheral ratio, Height and arm lengths, and Shoulder diameter. Corpulence showed strong correlations with traditional anthropometric and body composition measures (r>0.90 with weight, BMI, waist circumference and fat mass; r>0.70 with height, lean mass and bone mass); in contrast, the other three components showed weak or moderate correlations with those measures (all r<0.45). There was no sex difference in Corpulence, but boys had higher Central:peripheral ratio, Height and arm lengths and Shoulder diameter values than girls. Furthermore, children with low birth weight had lower Corpulence and Height and arm lengths but higher Central:peripheral ratio and Shoulder diameter than other children. Children from high socio-economic position (SEP) families had higher Corpulence and Height and arm lengths than other children. Finally, white children had higher Corpulence and Central:peripheral ratio than mixed or black children.
Conclusions: Comprehensive assessment by three-dimensional photonic scanning identified components of childhood body shape and size not captured by traditional anthropometry or body composition measures. Differences in these novel components by sex, birth weight, SEP and skin colour may indicate their potential relevance to disease risks.
Similar articles
-
Kinanthropometry and body composition: a natural home for three-dimensional photonic scanning.J Sports Sci. 2010 Mar;28(5):455-7. doi: 10.1080/02640411003661304. J Sports Sci. 2010. PMID: 20419588 No abstract available.
-
Relationship between BMI and adiposity among different ethnic groups in 2-year-old New Zealand children.Br J Nutr. 2019 Mar;121(6):670-677. doi: 10.1017/S000711451800380X. Br J Nutr. 2019. PMID: 30912736 Free PMC article.
-
[Simple obesity in children. A study on the role of nutritional factors].Med Wieku Rozwoj. 2006 Jan-Mar;10(1):3-191. Med Wieku Rozwoj. 2006. PMID: 16733288 Review. Polish.
-
Percentile reference values for anthropometric body composition indices in European children from the IDEFICS study.Int J Obes (Lond). 2014 Sep;38 Suppl 2:S15-25. doi: 10.1038/ijo.2014.131. Int J Obes (Lond). 2014. PMID: 25219408
-
Whole-body three-dimensional photonic scanning: a new technique for obesity research and clinical practice.Int J Obes (Lond). 2008 Feb;32(2):232-8. doi: 10.1038/sj.ijo.0803727. Epub 2007 Oct 9. Int J Obes (Lond). 2008. PMID: 17923860 Review.
Cited by
-
Effects of dietary intake patterns from 1 to 4 years on BMI z-score and body shape at age of 6 years: a prospective birth cohort study from Brazil.Eur J Nutr. 2019 Jun;58(4):1723-1734. doi: 10.1007/s00394-018-1720-3. Epub 2018 May 17. Eur J Nutr. 2019. PMID: 29774385 Free PMC article.
-
Automated body composition estimation from device-agnostic 3D optical scans in pediatric populations.Clin Nutr. 2023 Sep;42(9):1619-1630. doi: 10.1016/j.clnu.2023.07.012. Epub 2023 Jul 18. Clin Nutr. 2023. PMID: 37481870 Free PMC article.
-
Prediction of total and regional body composition from 3D body shape.NPJ Digit Med. 2024 Oct 23;7(1):298. doi: 10.1038/s41746-024-01289-0. NPJ Digit Med. 2024. PMID: 39443585 Free PMC article.
-
High-Resolution Three-Dimensional Photonic Scan-Derived Equations Improve Body Surface Area Prediction in Diverse Populations.Obesity (Silver Spring). 2020 Apr;28(4):706-717. doi: 10.1002/oby.22743. Epub 2020 Feb 26. Obesity (Silver Spring). 2020. PMID: 32100449 Free PMC article.
References
-
- Taylor RW, Grant AM, Williams SM, Goulding A. Sex differences in regional body fat distribution from pre- to postpuberty. Obesity 2010; 18: 1410–1416. - PubMed
-
- Wells JCK, Treleaven P, Cole TJ. BMI compared with 3-dimensional body shape: the UK National Sizing Survey. Am J Clin Nutr 2007; 85: 419–425. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Molecular Biology Databases