OBJECTIVE: To evaluate the relationship between body mass index (BMI) and %body fat (%Fat) in collegiate football athletes (FBA) compared with age-matched/gender-matched general population volunteers (comparison group, CG) and compare body composition and overweight/obese frequencies by BMI between FBA and CG. DESIGN: Cross-sectional. SETTING: Two Division I-A (D-IA) universities in Texas. Integrative Health Technologies (San Antonio, Texas) laboratory. PARTICIPANTS: Football athletes (n = 156, 20.0 ± 1.3 years, 185.6 ± 6.5cm, 103.3 ± 20.4 kg). Comparison group (n = 260, 21.5 ± 2.7 years, 179.0 ± 7.6 cm, 86.3 ± 20.9 kg). STATISTICAL ANALYSIS: Body mass index and bone densitrometry (DEXA) body composition were assessed. Regression was used to predict %Fat from BMI in CG and FBA. To compare %Fat, fat mass (FM), fat-free mass (FFM), and weight (WT) between CG, FBA, linemen, and non-linemen, 1 × 4 analysis of variance was used. Chi-square analysis was used to compare the frequency of BMI ≥25 between groups. RESULTS: Body mass index differently predicted %Fat for CG (r = 0.643, SE = 6.258) and FBA (r =0.769, SE = 4.416). Body mass index cutoffs for overweight/obese corresponded to the following %Fat in each group [BMI ≥25 = 19.9% (CG) and 11.1% (FBA); BMI ≥30 = 27.3% (CG) and 20.2% (FBA)]. Football athletes had significantly higher WT, BMI, FFM, and frequency of BMI ≥25 with lower %Fat and FM than CG (α < 0.05). Linemen had the highest WT, BMI, FFM, %Fat, and frequency of BMI ≥25. CONCLUSIONS: The relationship between BMI and %Fat differed between CG and FBA. Using current BMI thresholds for obesity in FBA may result in misleading inferences about health risk.
OBJECTIVE: To evaluate the relationship between body mass index (BMI) and %body fat (%Fat) in collegiate football athletes (FBA) compared with age-matched/gender-matched general population volunteers (comparison group, CG) and compare body composition and overweight/obese frequencies by BMI between FBA and CG. DESIGN: Cross-sectional. SETTING: Two Division I-A (D-IA) universities in Texas. Integrative Health Technologies (San Antonio, Texas) laboratory. PARTICIPANTS: Football athletes (n = 156, 20.0 ± 1.3 years, 185.6 ± 6.5cm, 103.3 ± 20.4 kg). Comparison group (n = 260, 21.5 ± 2.7 years, 179.0 ± 7.6 cm, 86.3 ± 20.9 kg). STATISTICAL ANALYSIS: Body mass index and bone densitrometry (DEXA) body composition were assessed. Regression was used to predict %Fat from BMI in CG and FBA. To compare %Fat, fat mass (FM), fat-free mass (FFM), and weight (WT) between CG, FBA, linemen, and non-linemen, 1 × 4 analysis of variance was used. Chi-square analysis was used to compare the frequency of BMI ≥25 between groups. RESULTS: Body mass index differently predicted %Fat for CG (r = 0.643, SE = 6.258) and FBA (r =0.769, SE = 4.416). Body mass index cutoffs for overweight/obese corresponded to the following %Fat in each group [BMI ≥25 = 19.9% (CG) and 11.1% (FBA); BMI ≥30 = 27.3% (CG) and 20.2% (FBA)]. Football athletes had significantly higher WT, BMI, FFM, and frequency of BMI ≥25 with lower %Fat and FM than CG (α < 0.05). Linemen had the highest WT, BMI, FFM, %Fat, and frequency of BMI ≥25. CONCLUSIONS: The relationship between BMI and %Fat differed between CG and FBA. Using current BMI thresholds for obesity in FBA may result in misleading inferences about health risk.
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