Dual-energy X-ray absorptiometry (DXA) and adipose tissue percentage estimates (AT%) derived from regression based skinfold equations were compared. 35 Gaelic games players [20.9 ± 1.7 years; 78.1 ± 8.6 kg; 179.5 ± 5.7 cm] underwent whole body fan beam DXA scans following a standardised protocol and assessment of skinfold thickness at 8 sites. Adipose tissue% from the sum of skinfolds and/or via body density were calculated for general and athlete specific equations (SKf-AT %). The relationship, i. e., proportional bias, fixed bias and random error (SEE) between DXA-AT % and AT % derived from the 6 skinfold equations were determined using least squares regression analysis. Skinfold AT% estimates were underestimated relative to DXA-AT % across all skinfold equations except that of Durnin and Wormersley [9] (D&W-∑(4AT %)) (16.7 ± 3.4 vs. 16.6 ± 4.0 %). All equations demonstrated 95 % prediction intervals ranges exceeding ~10 %. Each equation failed to predict AT% relative to DXA within an accepted ± 3.5 % anthropometric error rate. It is recommended that the conversion of absolute skinfold thickness to an AT % is avoided and that the skinfold equations assessed herein are not utilised in Gaelic games players. Alternate 'sum of skinfold' approaches should be considered.
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http://dx.doi.org/10.1055/s-0033-1333693 | DOI Listing |
J Sci Sport Exerc
November 2024
Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN 47403, USA.
Purpose: Researchers have predicted body fat percentage (BF%), as indicated by dual energy X-ray absorptiometry (DXA), from skinfold thicknesses in North American and European athletes, but not athletes from other regions. We sought to estimate an equation to predict BF% in elite Asian athletes from their skinfold thickness and girth measurements, with DXA as a reference method.
Methods: We collected data from two samples of athletes on Singaporean national teams.
Curr Nutr Rep
January 2025
Department of Nutrition and Dietetics, Gazi University, Ankara, Türkiye.
PeerJ
December 2024
Department of Anthropology and Human Genetics, Charles University, Prague, Czech Republic.
Background: The long-standing widespread prevalence of obesity includes issues of its evaluation. Nutritional status may be assessed using various tools and methods; among others simple anthropometric measurements are well established. Widely used body mass index (BMI), presents an obstacle of needing to calculate a standard deviation score (SD) for correct use in the child population.
View Article and Find Full Text PDFCureus
November 2024
Department of Pediatrics, Mahatma Gandhi Mission (MGM) Medical College and Hospital, MGM Institute of Health Sciences, Aurangabad, IND.
Background: Childhood obesity is a growing public health issue globally, including in India. Anthropometric measures such as body mass index (BMI), waist circumference, and skinfold thickness are commonly used to estimate body fat percentage (BF%), but their correlations with fat mass (FM) and fat mass index (FMI) are less emphasized. This study aimed to explore the relationships between anthropometric measurements and body fat indicators (BF%, FM, and FMI) in school-age children and obtain prediction equations for FM and FMI.
View Article and Find Full Text PDFEur J Appl Physiol
December 2024
Department of Biomedical Sciences, University of Padua, Via Marzolo, 3, 35131, Padua, Italy.
Purpose: Body composition can be estimated using anthropometric-based regression models, which are population-specific and should not be used interchangeably. However, the widespread availability of predictive equations in the literature makes selecting the most valid equations challenging. This systematic review compiles anthropometric-based predictive equations for estimating body mass components, focusing on those developed specifically for athletes using multicomponent models (i.
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