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

Atherton, Rachel R.; Williams, Jane; Wells, Jonathan C. K.; Fewtrell, Mary

doi:10.1371/journal.pone.0062139

Cited by 15 publications

(29 citation statements)

References 20 publications

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“…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.…”

Section: Discussion With Conclusionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 97%

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

et al. 2016

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SUMMARYMany modern pesticides have endocrine disrupting abilities and early-life exposure may affect growth and disease risk later in life. Previously, we reported associations between prenatal pesticide exposure and higher childhood body fat content measured by anthropometry. The associations were affected by child PON1 Q192R genotype. We aimed to study whether prenatal pesticide exposure was still associated with body fat content and distribution in the children at puberty and the potential impact of both maternal and child PON1 Q192R genotype. In this prospective cohort study of 247 children born by occupationally exposed or unexposed women (greenhouse workers and controls) two follow-up examinations (age 10-15 and 11-16 years) including simple anthropometry, skinfold measurements, pubertal staging and blood sampling were performed. Total and regional fat% was determined by dual X-ray absorptiometry (DXA) at age 10-15. Prenatal pesticide exposure was associated with increased total, android, and gynoid fat percentage (DXA) at age 10-15 years after adjustment for sex, socioeconomic status, and puberty (all b = 0.5 standard deviation score (SDS) p < 0.05). Stratified by sex, the associations were significant in girls (total fat: b = 0.7 SDS, android-gynoid ratio: b = 0.1, both p < 0.05), but not in boys. Carrying the R-allele (child or mother, separately, or both) augmented the differences between exposed and unexposed children (total fat: b = 1.0 SDS, b = 0.8 SDS, p < 0.05, respectively, and b = 1.2 SDS, p < 0.01). No exposure-related differences were found if either the child or mother had the QQ wild-type. At age 11-16, exposed children tended to have a higher total fat% estimated by skinfolds than unexposed children (p = 0.06). No significant associations between prenatal exposure and body mass index or waist circumference were found. Prenatal pesticide exposure was associated with higher adolescent body fat content, including android fat deposition, independent of puberty. Girls appeared more susceptible than boys. Furthermore, the association depended on maternal and child PON1 Q192R genotype.

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Section: Discussion With Conclusionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

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

et al. 2016

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“…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.…”

Section: Discussionmentioning

confidence: 99%

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

Barse

Tiemeier

Leermakers

et al. 2015

Int J Behav Nutr Phys Act

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BackgroundChildren’s fussy eating behavior has been related to both underweight and overweight in cross-sectional studies, but the direction of these associations and the relation with more detailed measures of body composition remains unclear. We aimed to examine whether fussy eating at age 4 years is longitudinally related to body mass index (BMI), fat mass index (FMI) and fat-free mass index (FFMI) at 6 years of age.MethodsThis study was embedded in Generation R, a population-based, prospective cohort. Data were available for 4191 children. The Children’s Eating Behaviour Questionnaire (CEBQ), administered at age 4 years, was used to derive a fussy eating profile. This profile is characterized by high scores on food avoidant scales and low scores on food approach scales. At age 6 years, height and weight were measured at our research center. Body fat and fat-free mass were measured using Dual-energy-X-ray absorptiometry. We used age- and sex-specific standard deviation scores (SDS) for all outcomes.ResultsAfter adjustment for confounders, the fussy eating profile was related to lower BMI-SDS (B = −0.37, 95 % CI: −0.47;−0.26), lower FMI-SDS (B = −0.22, 95 % CI: −0.33;−0.12) and lower FFMI-SDS (B = −0.41, 95 % CI: −0.54;−0.29). When adjusting for baseline BMI at 4 years, the fussy eating profile predicted a 0.11 lower BMI-SDS at age 6 (95 % CI: −0.19;−0.04). This change in BMI was mainly due to a decrease in FFMI (B = −0.19, 95 % CI: −0.29;−0.09). Fussy eaters also had a higher risk of becoming underweight than non-fussy eaters (OR = 2.28, 95 % CI: 1.34;3.87).ConclusionsOur findings suggest that young fussy eaters are at risk of having a lower fat free mass and of becoming underweight over a 2-year period. This implies that fussy eaters may benefit from careful monitoring to prevent an adverse growth development.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-015-0313-2) contains supplementary material, which is available to authorized users.

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“…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.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2014

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BackgroundThere is a need for a practical, inexpensive method to assess body composition in obese adolescents. This study aimed to 1) compare body composition parameters estimated by a stand-on, multi-frequency bioelectrical impendence (BIA) device, using a) the manufacturers’ equations, and b) published and derived equations with body composition measured by dual-energy x-ray absorptiometry (DXA) and 2) assess percentage body fat (%BF) change after a weight loss intervention.MethodsParticipants were 66 obese adolescents, mean age (SD) 12.9 (2.0) years. Body composition was measured by Tanita BIA MC-180MA (Tanita BIA8) and DXA (GE-Lunar Prodigy). BIA resistance and reactance data at frequencies of 5, 50, 250 and 500 kHz, were used in published equations, and to generate a new prediction equation for fat-free mass (FFM) using a split-sample method. Approximately half (n = 34) of the adolescents had their body composition measured by DXA and BIA on two occasions, three to nine months apart.ResultsThe correlations between FFM (kg), fat mass (kg) and %BF measured by BIA and DXA were 0.92, 0.93 and 0.78, respectively. The Tanita BIA8 manufacturers equations significantly (P < 0.001) overestimated FFM (4.3 kg [-5.3 to 13.9]) and underestimated %BF (-5.0% [-15 to 5.0]) compared to DXA. The mean differences between BIA derived equations and DXA measured body composition parameters were small (0.4 to 2.1%), not significant, but had large limits of agreements (~ ±15% for FFM). After the intervention mean %BF loss was similar by both methods (~1.5%), but with wide limits of agreement.ConclusionThe Tanita BIA8 could be a valuable clinical tool to measure body composition at the group level, but is inaccurate for the individual obese adolescent.

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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

Cited by 15 publications

References 20 publications

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

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

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

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

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