4.3 Article

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

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AMERICAN JOURNAL OF HUMAN BIOLOGY
卷 33, 期 3, 页码 -

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WILEY
DOI: 10.1002/ajhb.23503

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  1. Federal University of Rio Grande do Norte (UFRN)
  2. Physical Activity and Health (AFISA) research base
  3. Child and Adolescent Maturation Research Group (GEPMAC)
  4. National Council for Scientific Development (CNPQ)
  5. Higher Education Personnel Improvement Coordination (CAPES)

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This study confirmed the correlation between body adiposity index (BAI) and dual-energy X-ray absorptiometry (DXA) in analyzing body composition in children and adolescents. However, it was found that BAI has low reliability and a high proportion bias in estimating %F.
Background It is important to clarify the association of lean and fat mass between children and adolescents considering the rising prevalence of overweight and obesity in this age group. The aim of this study was to verify the association between the body adiposity index (BAI) and dual-energy X-ray absorptiometry (DXA) methods for analyzing body composition, as well as analyzing the validity of BAI to verify the percentage of fat in children and adolescents. Methods The sample was composed of 106 children and adolescents, 44 females (age: 11.5 +/- 1.8 years) and 62 evils (13.6 +/- 2.6 years). The body fat (%F) was measured using DXA and the doubly indirect BAI body fat estimation technique. Results The BAI and DXA estimates of %F were strongly correlated (boys:r= .71,P< .0001; girls:r= .72,P< .0001). The linear regression analyses showed that BAI is significant to estimate the %F in total sample (P< .0001). For boys, the %F analyzes performed by BAI and DXA did not show any differences when compared (P= .2). In addition, BAI pointed out a significant proportion bias for both sexes (P< .0001), which suggests its inefficiency in the analysis of %F. Conclusions BAI and DXA correlate; however, there is low reliability and a high proportion bias for the analysis of %F by BAI.

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