Use of Fat Mass and Fat Free Mass Standard Deviation Scores Obtained Using Simple Measurement Methods in Healthy Children and Patients: Comparison with the Reference 4-Component Model

Abstract

BackgroundClinical application of body composition (BC) measurements for individual children has been limited by lack of appropriate reference data.Objectives(1) To compare fat mass (FM) and fat free mass (FFM) standard deviation scores (SDS) generated using new body composition reference data and obtained using simple measurement methods in healthy children and patients with those obtained using the reference 4-component (4-C) model; (2) To determine the extent to which scores from simple methods agree with those from the 4-C model in identification of abnormal body composition.DesignFM SDS were calculated for 4-C model, dual-energy X-ray absorptiometry (DXA; GE Lunar Prodigy), BMI and skinfold thicknesses (SFT); and FFM SDS for 4CM, DXA and bioelectrical impedance analysis (BIA; height2/Z)) in 927 subjects aged 3.8–22.0 y (211 healthy, 716 patients).ResultsDXA was the most accurate method for both FM and FFM SDS in healthy subjects and patients (mean bias (limits of agreement) FM SDS 0.03 (±0.62); FFM SDS −0.04 (±0.72)), and provided best agreement with the 4-C model in identifying abnormal BC (SDS ≤−2 or ≥2). BMI and SFTs were reasonable predictors of abnormal FM SDS, but poor in providing an absolute value. BIA was comparable to DXA for FFM SDS and in identifying abnormal subjects.ConclusionsDXA may be used both for research and clinically to determine FM and FFM SDS. BIA may be used to assess FFM SDS in place of DXA. BMI and SFTs can be used to measure adiposity for groups but not individuals. The performance of simpler techniques in monitoring longitudinal BC changes requires investigation. Ultimately, the most appropriate method should be determined by its predictive value for clinical outcome.

Prenatal pesticide exposure and PON1 genotype associated with adolescent body fat distribution evaluated by dual X‐ray absorptiometry (DXA)

“…To the best of our knowledge, this is the first study to describe total and regional fat percentage measured by DXA in pubertal children prenatally exposed to pesticides. Fat estimates based on DXA are more accurate than standard anthropometry (Atherton et al ., ) which may explain why associations were more pronounced in DXA outcomes compared with simple anthropometry such as waist circumference.…”

“…In this study, we have followed the children during puberty to investigate whether the association between prenatal pesticide exposure and body fat content persists into adolescent age. To improve the validity of our data on body fat content, we supplemented anthropometry with dual X‐ray absorptiometry (DXA), a highly accurate measure of total and regional fat percentage (%) (Atherton et al ., ). Furthermore, we aim to investigate the impact of both maternal and child PON1 Q192R polymorphism on this association.…”

Longitudinal association between preschool fussy eating and body composition at 6 years of age: The Generation R Study

“…While most previous studies focused on body mass only, we distinguished fat mass from fat-free mass. One of the studies that also included fat and fat-free mass used skinfold thickness [ 23 ] which is a less reliable method than the DXA measurements that we used [ 48 ]. Ideally, multiple DXA measurements would have been able to account for baseline fat and fat-free mass.…”

Bioelectrical impedance analysis to estimate body composition, and change in adiposity, in overweight and obese adolescents: comparison with dual-energy x-ray absorptiometry

“…The results are also broadly consistent with other paediatric studies which have compared estimates of body composition measures by BIA 8 (differing in manufactures/models) with reference body composition methods in healthy children, of various ages, nutritional status and ethnicity including Korean [ 18 ] rural Gambian [ 19 ], New Zealand European, Pacific islander, Asian and Maori [ 20 ]. However, recent evidence indicates that standardising BIA measurements, using new paediatric body composition reference data, [ 1 ] could be a reasonable measure of four compartment FFM if DXA was not available [ 21 ] and is worthy of further research. In the absence of an independent cohort our derived models were based on DXA body composition parameters and cross validated [ 2 ]; this may explain the improved agreement from the derived models with DXA, compared with the BIA 8 manufacturers’ estimates.…”