Evaluation of the body adiposity index against dual‐energy X‐ray absorptiometry for assessing body composition in children and adolescents

Cesário, Tatianny de Macêdo; Almeida-Neto, Paulo Francisco de; Matos, Dihogo Gama de; Wells, Jonathan C. K.; Aidar, Felipe J.; Cabral, Breno Guilherme de Araújo Tinôco

doi:10.1002/ajhb.23503

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…This fact corroborates the findings of the present study in relation to lean mass. In addition, although maturation has been associated with higher concentrations of muscle strength [37,[40][41][42], we found that maturation was not associated with the peak power estimated by the mathematical model proposed by our study. Suggesting that there is no need to take maturation into account when estimating peak power.…”

Section: Plos Onecontrasting

confidence: 79%

Equation for analyzing the peak power in aquatic environment: An alternative for olympic rowing athletes

et al. 2020

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Purpose To develop an equation to provide the peak power (PP) through a specific stimulus performed in an aquatic environment, as well as to correlate morphological, anthropometric and strength variables with rowing performance. Methods The sample consisted of 16 elite young rowing athletes of both sexes (15.7 ± 1.21 years). The strength of upper limbs and lower limbs was verified. To analyze the PP, a 100-m Sprint test was performed on an indoor rowing type ergometer, and after a 72-hour wash-out, the test was repeated in an aquatic environment on a vessel equipped with a global position system. Body composition was analyzed by examining bone densitometry with an X-ray source and maturation was verified by anthropometry. Results The tests for water sprint and indoor rowing showed significant reliability (ICC = 0.695; p = 0.0007). The PP aquatic showed reliability with that acquired in indoor rowing (ICC = 0.897; p<0.0001) and was related to maturation (p<0.05). The morphology, anthropometry and strength of the upper limbs were related to the sprint and peak strength in both tests (p<0.05). Conclusion The equation for the PP in aquatic environment presented by the present study is highly reliable with an indoor ergometer digital ergometer.

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Section: Plos Onecontrasting

confidence: 79%

Equation for analyzing the peak power in aquatic environment: An alternative for olympic rowing athletes

et al. 2020

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“…However, this study used skinfold measurements as a reference method to validate the model, which is a limitation in studies of this nature. Other studies have observed a high proportion of bias and low agreement between the %BF predicted by DXA and the %BF predicted by BAI in Brazilian children and adolescents [15,16].…”

Section: Introductionmentioning

confidence: 82%

Prediction of body fat in adolescents: validity of the methods relative fat mass, body adiposity index and body fat index

et al. 2021

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Objective To verify the validity of anthropometric methods body adiposity index (BAI), relative fat mass (RFM) and body fat index (BFI) to estimate body fat percentage (%BF) in adolescents. Methods A cross-sectional study was carried out with 420 Brazilian adolescents aged 15-19 years, stratified by age (< 18 years, n = 356; ≥ 18 years, n = 64) and sex (boys, n = 216; girls, n = 204). The Anthropometric measurements height, body weight, hip circumference and waist circumference were collected to calculate the %BF by BAI, RFM, BFI methods. Subsequently, %BF was measured by dual emission X-ray absorptiometry (DXA), adopted as a reference method. In the statistical analysis of the data, the Pearson correlation test and the paired t test between %BF obtained by the equations and by the DXA were performed. The method validation criterion was that 68% of individuals should be within an acceptable error range of ± 3.5% of BF and Cohen's Kappa index ≥ 0.61. Additionally, the Bland-Altman graphical analysis was performed. Results All methods showed a high correlation with DXA. For the Kappa index, only the RFM reached the criterion in the total sample (0.67) and in the sample < 18 years (0.68). None of the methods reached the criterion of 68% of the sample within the error range of ± 3.5% of BF. ConclusionThe BAI, RFM and BFI equations were not valid for predicting BF in the studied sample according to the criteria adopted regardless of sex or age. Level of evidence Level V, cross-sectional descriptive study.

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“…Body composition was assessed with dual energy x-ray bone densitometry (DXA) (LUNAR® / GE PRODIGY—LNR 41,990, Software enCORE version 18; United States) using specific algorithms for the pediatric population [ 23 ]. This procedure is considered one of the most reliable standard for measuring body composition [ 24 ]. Evaluations lasted 10 minutes average.…”

Section: Methodsmentioning

confidence: 99%

Lean mass and biological maturation as predictors of muscle power and strength performance in young athletes

et al. 2021

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Background The biological maturation (BM) analyzed by peak height velocity (PHV) and bone age (BA), and lean body mass has been associated with the strength and muscle power of young athletes. However, the ability of BM (PHV and BA) and LM markers to predict muscle strength and power in young athletes remains uncertain. Objective The Aim was determine the predicting power of BM markers (PHV and BA) and LM in relation to muscle power of upper and lower limbs and muscle strength of upper limbs in adolescent athletes at puberty. Methods Ninety-two adolescent athletes (both sexes; age 12.4 ± 1.02 years) were assessed for body composition by dual-energy X-ray absorptiometry (DXA). Power of upper limbs (ULP), force handgrip (HG), vertical jump (VJ) and countermovement jump (CMJ) were recorded. BM was predicted by mathematical models to estimate PHV and BA. Multilayer artificial neural network analyses (MLP’s) were used to determine the power of prediction of LM, PHV and BA on muscle power and strength of upper- and lower-limbs of the athletes. Results LM, BA and PHV were associated with HG (r>0.74, p<0.05) and ULS (r>0.60, p<0.05) in both sexes. In both sexes BA was associated with VJ (r>0.55, p<0.05) and CMJ (r>0.53, p<0.05). LM indicated associations (r>0.60, p<0.05) with BA and with PHV (r<0.83, p<0.05) in both sexes. MLP’s analysis revealed that the LM provides > 72% of probability to predict the muscle power of upper- and lower-limbs, and the strength of the upper limbs; whereas PHV provides > 43% and bone age >64% in both female and male adolescent athletes. Conclusion We identified that, like PHV and BA, LM is a strong predictor of low cost of both upper limbs muscle strength and upper and lower limbs power in adolescent athletes.

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Evaluation of the body adiposity index against dual‐energy X‐ray absorptiometry for assessing body composition in children and adolescents

Cited by 11 publications

References 35 publications

Equation for analyzing the peak power in aquatic environment: An alternative for olympic rowing athletes

Equation for analyzing the peak power in aquatic environment: An alternative for olympic rowing athletes

Prediction of body fat in adolescents: validity of the methods relative fat mass, body adiposity index and body fat index

Lean mass and biological maturation as predictors of muscle power and strength performance in young athletes

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