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Driving innovations in manufacturing: Open Access research from DMEM

Strathprints makes available Open Access scholarly outputs by Strathclyde's Department of Design, Manufacture & Engineering Management (DMEM).

Centred on the vision of 'Delivering Total Engineering', DMEM is a centre for excellence in the processes, systems and technologies needed to support and enable engineering from concept to remanufacture. From user-centred design to sustainable design, from manufacturing operations to remanufacturing, from advanced materials research to systems engineering.

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Skinfold prediction equation for collegiate athletes developed using a four-component model

Evans, E. and Rowe, D.A. and Misic, M. and Prior, B. and Arngrimsson, S. (2005) Skinfold prediction equation for collegiate athletes developed using a four-component model. Medicine and Science in Sports and Exercise, 37 (11). pp. 2006-2011. ISSN 0195-9131

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Introduction: Skinfold (SKF) equations exist to predict percent body fat (%BF) in athletes; however, none have been derived from multicomponent model reference measures. Purpose: To develop and cross-validate a %BF prediction equation based on SKF in athletes using a fourcomponent model as the reference measure. Methods: Subjects were 132 collegiate athletes (20.7 2.0 yr; 78 males: 28 black, 50 white; 54 females: 10 black, 44 white). Four-component model estimates of %BF (%BF4C) included measures of total body water from deuterium dilution, bone mineral by dual- energy x-ray absorptiometry (DXA), and body density by densitometry using underwater weighing. SKF measures included subscapular, triceps, chest, midaxillary, suprailiac, abdominal, and thigh sites (7SKF). A prediction equation was developed on 102 athletes using 7SKF, race, and gender as predictor variables. Cross-validation was performed on a representative holdout sample of 30 athletes. Results: The equation cross-validated well (slope and intercept both not different (P 0.05) from the line of identity (LOI); rYY= 0.85, total error (TE) 3.76%BF) and was better than the existing athlete SKF equations (intercept and slope both different from LOI (P 0.01); rYY= 0.76, TE 4.51%BF). Notably, a prediction equation developed using 3SKF sites (abdomen, thigh, and triceps) produced a similar accuracy (intercept and slope both not different from LOI (P 0.05); rYY= 0.85, TE 3.66%BF). Conclusions: The new 7SKF equation improved on SKF equations developed using densitometry. The final equation based on the whole sample was %BF= 10.566 0.12077*(7SKF) – 8.057*(gender) – 2.545*(race). Moreover, a 3SKF equation was comparable in accuracy to the 7SKF equation: %BF= 8.997 0.24658*(3SKF) – 6.343*(gender) – 1.998*(race).