CONTEXT: The recent increase in athlete size, particularly in football athletes of all levels, coupled with the increased health risk associated with obesity warrants continued monitoring of body composition from a health perspective in this population. Equations developed to predict percentage of body fat (%Fat) have been shown to be population specific and might not be accurate for football athletes. OBJECTIVE: To develop multiple regression equations using standard anthropometric measurements to estimate dual-energy x-ray absorptiometry %Fat (DEXA%Fat) in collegiate football players. DESIGN: Controlled laboratory study. PATIENTS AND OTHER PARTICIPANTS: One hundred fifty-seven National Collegiate Athletic Association Division IA football athletes (age = 20 ± 1 years, height = 185.6 ± 6.5 cm, mass = 103.1 ± 20.4 kg, DEXA%Fat = 19.5 ± 9.1%) participated. MAIN OUTCOME MEASURE(S): Participants had the following measures: (1) body composition testing with dual-energy x-ray absorptiometry; (2) skinfold measurements in millimeters, including chest, triceps, subscapular, midaxillary, suprailiac, abdominal (SFAB), and thigh; and (3) standard circumference measurements in centimeters, including ankle, calf, thigh, hip (AHIP), waist, umbilical (AUMB), chest, wrist, forearm, arm, and neck. Regression analysis and fit statistics were used to determine the relationship between DEXA%Fat and each skinfold thickness, sum of all skinfold measures (SFSUM), and individual circumference measures. RESULTS: Statistical analysis resulted in the development of 3 equations to predict DEXA%Fat: model 1, (0.178 · AHIP) + (0.097 · AUMB) + (0.089 · SFSUM) - 19.641; model 2, (0.193 · AHIP) + (0.133 · AUMB) + (0.371 · SFAB) - 23.0523; and model 3, (0.132 · SFSUM) + 3.530. The R(2) values were 0.94 for model 1, 0.93 for model 2, and 0.91 for model 3 (for all, P < .001). CONCLUSIONS: The equations developed provide an accurate way to assess DEXA%Fat in collegiate football players using standard anthropometric measures so athletic trainers and coaches can monitor these athletes at increased health risk due to increased size.
CONTEXT: The recent increase in athlete size, particularly in football athletes of all levels, coupled with the increased health risk associated with obesity warrants continued monitoring of body composition from a health perspective in this population. Equations developed to predict percentage of body fat (%Fat) have been shown to be population specific and might not be accurate for football athletes. OBJECTIVE: To develop multiple regression equations using standard anthropometric measurements to estimate dual-energy x-ray absorptiometry %Fat (DEXA%Fat) in collegiate football players. DESIGN: Controlled laboratory study. PATIENTS AND OTHER PARTICIPANTS: One hundred fifty-seven National Collegiate Athletic Association Division IA football athletes (age = 20 ± 1 years, height = 185.6 ± 6.5 cm, mass = 103.1 ± 20.4 kg, DEXA%Fat = 19.5 ± 9.1%) participated. MAIN OUTCOME MEASURE(S): Participants had the following measures: (1) body composition testing with dual-energy x-ray absorptiometry; (2) skinfold measurements in millimeters, including chest, triceps, subscapular, midaxillary, suprailiac, abdominal (SFAB), and thigh; and (3) standard circumference measurements in centimeters, including ankle, calf, thigh, hip (AHIP), waist, umbilical (AUMB), chest, wrist, forearm, arm, and neck. Regression analysis and fit statistics were used to determine the relationship between DEXA%Fat and each skinfold thickness, sum of all skinfold measures (SFSUM), and individual circumference measures. RESULTS: Statistical analysis resulted in the development of 3 equations to predict DEXA%Fat: model 1, (0.178 · AHIP) + (0.097 · AUMB) + (0.089 · SFSUM) - 19.641; model 2, (0.193 · AHIP) + (0.133 · AUMB) + (0.371 · SFAB) - 23.0523; and model 3, (0.132 · SFSUM) + 3.530. The R(2) values were 0.94 for model 1, 0.93 for model 2, and 0.91 for model 3 (for all, P < .001). CONCLUSIONS: The equations developed provide an accurate way to assess DEXA%Fat in collegiate football players using standard anthropometric measures so athletic trainers and coaches can monitor these athletes at increased health risk due to increased size.
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