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. 2021 Apr;26(3):879-886.
doi: 10.1007/s40519-020-00918-3. Epub 2020 May 19.

Validity and accuracy of body fat prediction equations using anthropometrics measurements in adolescents

Wagner L Ripka #  1   2 , Camila E Orsso #  3 , Andrea M Haqq  3   4 , Carla M Prado  3 , Leandra Ulbricht  5 , Neiva Leite  6
Affiliations

Validity and accuracy of body fat prediction equations using anthropometrics measurements in adolescents

Wagner L Ripka et al. Eat Weight Disord. 2021 Apr.

Abstract

Background: The pediatric relative fat mass (RFM) has been recently presented and validated as an index for estimating percentage body fat (%BF) in North American children and adolescents. Similar to body mass index (BMI) and tri-ponderal mass index (TMI), RFM uses anthropometric measures (i.e., weight, height and waist circumference) to estimate body composition. The primary purpose of this study was to validate the newly developed RFM equation for %BF prediction in Southern Brazilian adolescents; as secondary objective, we compared %BF estimation from BMI- and TMI-derived equations.

Methods: A total of 631 individuals (434 boys) aged 11 to 18 were analyzed. Bland-Altman analyses were used to determine concordance between predicted equations and %BF measured by DXA; results are presented using mean difference (i.e., bias) and standard deviation. Sensitivity and specificity were calculated for %BF percentile classifications.

Results: RFM underestimated %BF in 65.2% of boys (- 4.3 ± 2.8%) and 84.8% of girls (- 5.3 ± 2.7%). In contrast, TMI overestimated %BF in 62.9% of boys (4.0 ± 2.9%) and 56.3% (3.5 ± 3.0%) of girls. The performance of BMI showed mixed results; %BF was overestimated in 68.4% of boys (5.0 ± 4.0%) and underestimated in 67.5% of girls (- 3.9 ± 2.6%), all p < 0.001. Although, RFM had the highest specificity for %BF percentile classifications, sensitivity was low and inferior to BMI and TMI.

Conclusion: TMI was superior to RFM and BMI in predicting %BF in Southern Brazilian adolescents. Using RFM, BMI or TMI equations for %BF prediction without a population-specific correction factor may lead to incorrect interpretations. We suggest that correction factors should be investigated to improve the accuracy of these surrogate indices for body composition assessment.

Level of evidence: Level V, cross sectional descriptive study.

Keywords: Adolescents; Body composition; Body fat; Obesity; Public health.

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