Bioimpedance in 7-Year-Old Children: Validation by Dual X-Ray Absorptiometry - Part 1: Assessment of Whole Body Composition

Luque, Verónica; Closa‐Monasterolo, Ricardo; Rubio-Torrents, Carmen; Zaragoza‐Jordana, Marta; Ferré, Natàlia; Gispert-Llauradó, Mariona; Escribano, Joaquín

doi:10.1159/000356450

Cited by 30 publications

(30 citation statements)

References 20 publications

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“…Finally, using gold-standard measures of body composition such as dual-energy X-ray absorptiometry (DEXA) would have been preferable, but is too costly to be applied in such large samples as the present. Notably though, bioimpedance analyses of children’s body composition is found to be valid as tested against DEXA [44] and Tanita scales are considered accurate and efficient means of assessing body composition in epidemiological studies of elementary school children [44–46]. …”

Section: Discussionmentioning

confidence: 99%

Body composition impacts appetite regulation in middle childhood. A prospective study of Norwegian community children

Steinsbekk

Llewellyn

Fildes

et al. 2017

Int J Behav Nutr Phys Act

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BackgroundResearch suggests a role for both fat mass and muscle mass in appetite regulation, but the longitudinal relationships between them have not yet been examined in children. The present study therefore aimed to explore the prospective relationships between fat mass, muscle mass and the appetitive traits food responsiveness and satiety responsiveness in middle childhood.MethodsFood responsiveness and satiety responsiveness were measured using the parent-reported Children’s Eating Behavior Questionnaire in a representative sample of Norwegian 6 year olds, followed up at 8 and 10 years of age (n = 807). Body composition was measured by bioelectrical impedance.ResultsApplying a structural equation modeling framework we found that higher fat mass predicted greater increases in food responsiveness over time, whereas greater muscle mass predicted decreases in satiety responsiveness. This pattern was consistent both from ages 6 to 8 and from ages 8 to 10 years.ConclusionsOur study is the first to reveal that fat mass and muscle mass predict distinct changes in different appetitive traits over time. Replication of findings in non-European populations are needed, as are studies of children in other age groups. Future studies should also aim to reveal the underlying mechanisms.

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Section: Discussionmentioning

confidence: 99%

Body composition impacts appetite regulation in middle childhood. A prospective study of Norwegian community children

Steinsbekk

Llewellyn

Fildes

et al. 2017

Int J Behav Nutr Phys Act

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“…Body Fat Percentage: A bioelectric impedance scale (Tanita BC-568 Inner-Scan Segmental Body Composition Monitor, Tanita, Arligton, IL, USA) was used to estimate body fat percentage [20]. To complete this assessment, each child stood on the bioelectrical impendence platform with a grip in each hand.…”

Section: Methodsmentioning

confidence: 99%

“…To complete this assessment, each child stood on the bioelectrical impendence platform with a grip in each hand. From this position, a small electrical current was passed through the child’s body and resistance to this electrical current was measured, from which water percentage was estimated [20]. From this estimation, body fat percentage can be estimated.…”

Section: Methodsmentioning

confidence: 99%

Association between Functional Movements Skills and Health Indicators in Children Aged between 9 and 12 Years Old

Comeau

B̀ouchard

Levesque³

et al. 2017

IJERPH

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Background: Children’s health is a current concern and data suggests that poor fundamental movement skills (FMS) could be associated with poor health, which may or may not be mediated by low physical activity level. However, tools to assess FMS have not been standardized, and could consequently lead to different associations between FMS and health indicators. Objective: The primary objective of this study was to evaluate the associations between FMS and health indicators using two different FMS measurement tools often used in Canada. Methods: A total of 145 children between the ages of 9 to 12 were recruited from schools, after school programs, and summer camps in 2016. FMS were evaluated using the Passport for Life (bound, plank, run, kick, throw) and the PLAYbasic (run, hop, throw, kick, and balance). The association between each test and an average score for each tool were tests with health indicators including anthropometric measures, grip strength, cardiorespiratory fitness, and percent body fat. Results: Participants were composed of 54.2% boys aged 10.4 ± 1.2 years with an average body mass index of 18.8 ± 3.8 kg/m2. The association between the average score of both tools was 0.77 (p < 0.01), body mass index was significantly associated with 67% of FMS elements using the Passport for Life (r ranging from −0.18 to −0.32; p < 0.05), and 60% of FMS using the PLAYbasic (r ranging from −0.15 to −0.30; p < 0.05). There were no significant differences between the associations of the health indicators with FMS and either FMS assessment tool (Passport for Life and PLAYbasic) (p = 0.05). Average score of FMS was significantly associated with all health indicators using both PLAYbasic and Passport for Life (all p < 0.05). Conclusions: Health indicators in children are associated with FMS regardless of whether the Passport for Life or the PLAYbasic was used as the assessment tool. It is worth investigating if interventions that improve FMS lead to improvements in these health indicators.

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“…The number of participants ranged from n ¼ 16 [34] to n ¼ 1125 [44], who were mainly Caucasian ( Table 2). Regarding the participants' age, 10 studies proposed an equation for subjects aged 65 years and older [35,41,45e48,51e53], 9 for adults (age range 24e53 years) [16,31,36e39,42,50,54], 4 for children [32,33,43,49] and 2 did not report the age of the study population [34,40]. Most studies included healthy participants, except for some specific populations such as obese children [32,33], adults with chronic kidney diseases [41,42], healthy adults but at risk of osteopenia [38], and older subjects presenting sarcopenia or frailty [51,53].…”

Section: Studies Characteristicsmentioning

confidence: 99%

“…Regarding BIA devices used, it is observed that: 1) Different brands of BIA have been used throughout the studies: among them, 5 studies reported using the Inbody device [16,39,42,44,46], 8 used the RJL systems [35,37,38,43,47,49,52,53], 4 studies reported using the Tanita system [32,33,45,50], 3 used the Xitron devices [40,41,51] and the 5 last ones used other devices [31,34,36,48,54]. However, among the same brand of BIA devices a large diversity is also observed regarding the version of the devices used.…”

Section: Muscle Mass Assessmentmentioning

confidence: 99%

Equation models developed with bioelectric impedance analysis tools to assess muscle mass: A systematic review

Beaudart

Bruyère

Geerinck

et al. 2020

Clinical Nutrition ESPEN

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Background & aims: This systematic review aims to systematically assess and summarize the equation models developed to estimate muscle mass with bioelectric impedance analysis (BIA) instruments against a reference instrument (DXA, MRI, CT-scan, Ultrasonography), in order to help researchers and clinicians choose the most adapted equation, depending on the device and the population in question. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement was followed. Medline (via Ovid) and Scopus were searched in January 2019 for observational (transversal, longitudinal, retrospective) studies developing an equation prediction model to validate BIA against another reference method for the assessment of muscle mass. Study selection and data extraction was performed independently by two researchers. Methodological quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Results: 25 studies matched the inclusion criteria and were included in the present systematic review. Among them, 10 studies proposed an equation for subjects aged 65 years and older, 9 for adults, 4 for infants and 2 did not report the age of the population. A large heterogeneity was observed regarding the brand and type of BIA as well as the administration protocol (mode, frequency, number of electrodes, administration position and empty bladder/stomach or not). Most of the studies used DXA as the reference instrument, except 4 that used MRI. In each of the included papers authors provided, through simple or multiple regression, a predictive equation for muscle mass. BIA resistance index, sex, weight, age, BIA reactance and height were most frequently included as predictive variables. The majority of the equations developed explained more than 80% of the variance between both instruments. Out of the 25 equations available, only 9 were also validated in another population within the same paper. Conclusion: This systematic review of the literature offers clinicians and researchers the opportunity to verify the existence of a prediction equation when using a BIA device for estimating muscle mass. This will help them to obtain a valid estimation of muscle mass in a specific population and with a specific instrument. If the equation exists and has been validated by a study free of high risk of bias, it's use is recommended because the development of a new equation in the same context seems redundant and undesirable. If a validation has not been carried out for a specific brand of BIA, reference method or population, we recommend the development and cross-validation of a new equation.

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Bioimpedance in 7-Year-Old Children: Validation by Dual X-Ray Absorptiometry - Part 1: Assessment of Whole Body Composition

Cited by 30 publications

References 20 publications

Body composition impacts appetite regulation in middle childhood. A prospective study of Norwegian community children

Body composition impacts appetite regulation in middle childhood. A prospective study of Norwegian community children

Association between Functional Movements Skills and Health Indicators in Children Aged between 9 and 12 Years Old

Equation models developed with bioelectric impedance analysis tools to assess muscle mass: A systematic review

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