» Articles » PMID: 29024557

Body Composition Measurement in Young Children Using Quantitative Magnetic Resonance: a Comparison with Air Displacement Plethysmography

Overview
Journal Pediatr Obes
Date 2017 Oct 13
PMID 29024557
Citations 12
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Quantitative magnetic resonance (QMR) has been increasingly used to measure human body composition, but its use and validation in children is limited.

Objective: We compared body composition measurement by QMR and air displacement plethysmography (ADP) in preschool children from Singapore's multi-ethnic Asian population (n = 152; mean ± SD age: 5.0 ± 0.1 years).

Methods: Agreements between QMR-based and ADP-based fat mass and fat mass index (FMI) were assessed using intraclass correlation coefficient (ICC), reduced major axis regression and Bland-Altman plot analyses. Analyses were stratified for the child's sex.

Results: Substantial agreement was observed between QMR-based and ADP-based fat mass (ICC: 0.85) and FMI (ICC: 0.82). Reduced major axis regression analysis suggested that QMR measurements were generally lower than ADP measurements. Bland-Altman analysis similarly revealed that QMR-based fat mass were (mean difference [95% limits of agreement]) -0.5 (-2.1 to +1.1) kg lower than ADP-based fat mass and QMR-based FMI were -0.4 (-1.8 to +0.9) kg/m lower than ADP-based FMI. Stratification by offspring sex revealed better agreement of QMR and ADP measurements in girls than in boys.

Conclusions: QMR-based fat mass and FMI showed substantial agreement with, but was generally lower than, ADP-based measures in young Asian children.

Citing Articles

Prediction of fat-free mass in young children using bioelectrical impedance spectroscopy.

Lyons-Reid J, Ward L, Derraik J, Thway-Tint M, Monnard C, Ramos Nieves J Eur J Clin Nutr. 2023; 78(10):872-879.

PMID: 37524804 PMC: 7616480. DOI: 10.1038/s41430-023-01317-4.


Characteristics of Body Composition Estimated by Air-Displacement Plethysmography in Chinese Preschool Children.

Chen F, Wang J, Liu J, Huang G, Hou D, Liao Z Front Public Health. 2022; 10:926819.

PMID: 35719642 PMC: 9204163. DOI: 10.3389/fpubh.2022.926819.


Association of plasma kynurenine pathway metabolite concentrations with metabolic health risk in prepubertal Asian children.

Mei-Ling Tan K, Tint M, Kothandaraman N, Yap F, Godfrey K, Lee Y Int J Obes (Lond). 2022; 46(6):1128-1137.

PMID: 35173282 PMC: 7612806. DOI: 10.1038/s41366-022-01085-4.


The Kynurenine Pathway Metabolites in Cord Blood Positively Correlate With Early Childhood Adiposity.

Mei-Ling Tan K, Tint M, Kothandaraman N, Michael N, Sadananthan S, Velan S J Clin Endocrinol Metab. 2022; 107(6):e2464-e2473.

PMID: 35150259 PMC: 9113811. DOI: 10.1210/clinem/dgac078.


Breastfeeding may benefit cardiometabolic health of children exposed to increased gestational glycemia in utero.

Ong Y, Pang W, Huang J, Aris I, Sadananthan S, Tint M Eur J Nutr. 2022; 61(5):2383-2395.

PMID: 35124728 PMC: 7613060. DOI: 10.1007/s00394-022-02800-7.


References
1.
Lakshmi S, Metcalf B, Joglekar C, Yajnik C, Fall C, Wilkin T . Differences in body composition and metabolic status between white U.K. and Asian Indian children (EarlyBird 24 and the Pune Maternal Nutrition Study). Pediatr Obes. 2012; 7(5):347-54. PMC: 3541477. DOI: 10.1111/j.2047-6310.2012.00063.x. View

2.
Javed A, Jumean M, Murad M, Okorodudu D, Kumar S, Somers V . Diagnostic performance of body mass index to identify obesity as defined by body adiposity in children and adolescents: a systematic review and meta-analysis. Pediatr Obes. 2014; 10(3):234-44. DOI: 10.1111/ijpo.242. View

3.
Fields D, Allison D . Air-displacement plethysmography pediatric option in 2-6 years old using the four-compartment model as a criterion method. Obesity (Silver Spring). 2012; 20(8):1732-7. PMC: 3628559. DOI: 10.1038/oby.2012.28. View

4.
Wang Z, Heshka S, Wang J, Wielopolski L, Heymsfield S . Magnitude and variation of fat-free mass density: a cellular-level body composition modeling study. Am J Physiol Endocrinol Metab. 2003; 284(2):E267-73. DOI: 10.1152/ajpendo.00151.2002. View

5.
Yassi N, Campbell B, Moffat B, Steward C, Churilov L, Parsons M . Know your tools--concordance of different methods for measuring brain volume change after ischemic stroke. Neuroradiology. 2015; 57(7):685-95. DOI: 10.1007/s00234-015-1522-8. View