Determining a Resting Metabolic Rate Prediction Equation for Collegiate Female Athletes
| Autor: | Chad M. Kerksick, Kyle E. Witherbee, Andrea Sulavik, Hannah A. Zabriskie, Bradley T. Gieske, Alicia D. Watson |
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| Rok vydání: | 2019 |
| Předmět: |
Calorie
Adolescent Universities Population Physical Therapy Sports Therapy and Rehabilitation 030204 cardiovascular system & hematology Body weight Body fat percentage Cohort Studies 03 medical and health sciences Young Adult 0302 clinical medicine Statistics Humans Orthopedics and Sports Medicine education Mathematics Adiposity education.field_of_study biology Athletes Body Weight Calorimetry Indirect 030229 sport sciences General Medicine Mathematical Concepts biology.organism_classification Body Height Large cohort Skinfold Thickness Skinfold thickness Basal metabolic rate Body Constitution Female Basal Metabolism Sports |
| Zdroj: | Journal of strength and conditioning research. 33(9) |
| ISSN: | 1533-4287 |
| Popis: | Watson, AD, Zabriskie, HA, Witherbee, KE, Sulavik, A, Gieske, BT, and Kerksick, CM. Determining a resting metabolic rate prediction equation for collegiate female athletes. J Strength Cond Res 33(9): 2426-2432, 2019-A lack of evidence exists regarding the accuracy of common resting metabolic rate (RMR) prediction equations in athletic female populations. The purpose of this research was to measure RMR in a large cohort of NCAA Division II female athletes and use regression techniques to develop new prediction equations. Sixty-six female athletes from 11 different sports completed this protocol, which included skinfold measurements followed by an RMR assessment using indirect calorimetry. The average RMR was 1,466 ± 150 kcal·d. Many between-sport differences in body composition were identified, with gymnastics athletes having the lowest body fat percentage (p < 0.05) and basketball athletes having the greatest absolute fat-free mass (p < 0.05). Resting metabolic rate was moderately correlated (p < 0.05) with height (r = 0.52), total mass (r = 0.59), and fat-free mass (r = 0.54). Two equations were developed, both of which were more accurate for this population than other RMR prediction equations. One of the new equations, which used height and body mass as covariates (equation 1), was slightly more accurate than the equation using body composition parameters (equation 2). The new equations were cross-validated using a randomly selected subset (n = 22) of the original sample. The subset did not show statistically different results from the remainder of the sample (n = 44) between equation 1 (p = 0.083) and equation 2 (p = 0.22). Equation 1, which had more easily measurable parameters, exhibited heightened accuracy, which has important implications for implementation among athletes, coaches, and athletic support staff. |
| Databáze: | OpenAIRE |
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