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Body composition measurement in young children using quantitative magnetic resonance: a comparison with air displacement plethysmography.

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/m2 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.

SUBMITTER: Chen LW

PROVIDER: S-EPMC5805128 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Body composition measurement in young children using quantitative magnetic resonance: a comparison with air displacement plethysmography.

Chen L-W LW Tint M-T MT Fortier M V MV Aris I M IM Shek L P-C LP Tan K H KH Rajadurai V S VS Gluckman P D PD Chong Y-S YS Godfrey K M KM Kramer M S MS Henry C J CJ Yap F F Lee Y S YS

Pediatric obesity 20171012 6

<h4>Background</h4>Quantitative magnetic resonance (QMR) has been increasingly used to measure human body composition, but its use and validation in children is limited.<h4>Objective</h4>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).<h4>Methods</h4>Agreements between QMR-based and ADP-based fat mass and fat mass index (FMI) were assessed usin ...[more]

PMID: 29024557

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Project description:With the greatest burden of infant undernutrition and morbidity in low and middle income countries (LMICs), there is a need for suitable approaches to monitor infants in a simple, low-cost and effective manner. Anthropometry continues to play a major role in characterising growth and nutritional status.We developed a range of models to aid in identifying neonates at risk of malnutrition. We first adopted a logistic regression approach to screen for a composite neonatal morbidity, low and high body fat (BF%) infants. We then developed linear regression models for the estimation of neonatal fat mass as an assessment of body composition and nutritional status.We fitted logistic regression models combining up to four anthropometric variables to predict composite morbidity and low and high BF% neonates. The greatest area under receiver-operator characteristic curves (AUC with 95% confidence intervals (CI)) for identifying composite morbidity was 0.740 (0.63, 0.85), resulting from the combination of birthweight, length, chest and mid-thigh circumferences. The AUCs (95% CI) for identifying low and high BF% were 0.827 (0.78, 0.88) and 0.834 (0.79, 0.88), respectively. For identifying composite morbidity, BF% as measured via air displacement plethysmography showed strong predictive ability (AUC 0.786 (0.70, 0.88)), while birthweight percentiles had a lower AUC (0.695 (0.57, 0.82)). Birthweight percentiles could also identify low and high BF% neonates with AUCs of 0.792 (0.74, 0.85) and 0.834 (0.79, 0.88). We applied a sex-specific approach to anthropometric estimation of neonatal fat mass, demonstrating the influence of the testing sample size on the final model performance.These models display potential for further development and evaluation in LMICs to detect infants in need of further nutritional management, especially where traditional methods of risk management such as birthweight for gestational age percentiles may be variable or non-existent, or unable to detect appropriately grown, low fat newborns.

Dataset Information

Body composition measurement in young children using quantitative magnetic resonance: a comparison with air displacement plethysmography.

Publications

Body composition measurement in young children using quantitative magnetic resonance: a comparison with air displacement plethysmography.

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