The Accuracy of a BMI-Based Equation in Predicting Percent Body Fat in College-Age Female Athletes

Body mass index (BMI), the ratio of one's height to one's weight, is a commonly used method for determining an individual's risk of developing health problems associated with being obese or underweight. However, BMI does not distinguish between lean and fat tissue, potentially misclassifying lean individuals, such as athletes, who have a high body weight but a low body fat percentage (BF%), as obese when their BF% is in a healthy range. More accurate means of assessing body composition, such as Dual energy X-ray absorptiometry (DEXA), are not generally available outside of clinical settings, leading coaches and strength and conditioning professionals to rely on quick, inexpensive field techniques. Body mass index-based BF% prediction equations have been validated for use in the general population. However, data on their accuracy for female athletes is limited. PURPOSE: The purpose of this study was to determine if three BMI-based equations for predicting BF% were accurate in college-age female athletes. METHODS: Fifty-seven female athletes from the National Association for Intercollegiate Athletics participated in the study. Each subject's height and weight taken to determine BMI. Three regression equations for estimating BF% based on BMI previously developed by Deurenberg et al. (DBMI-BF), Gallagher et al. (GBMI-BF), and Jackson et al. (JBMI-BF) were used in the study. Dual energy X-ray absorptiometry was used to obtain the criterion BF% values. RESULTS: The results showed no significant difference (p > 0.05) in mean BF% values between 2 of the BMI-based BF% (DBMI-BF = 27.8 ± 3.0%, JBMI-BF = 26.9 ± 4.8%) equations versus DEXA (28.1 ± 6.1%), while GBMI-BF (30.3 ± 4.9%) was slightly significantly (p < 0.05) higher compared to the criterion. Furthermore, each BMI-equation held significant relationships with the criterion variable (R^sup 2^ ranged from 0.39 to 0.45, p < 0.01). The standard error of estimate for the equations ranged from ± 4.4 to 4.8%. CONCLUSION: Due to the findings of this investigation, BMI-based BF% equations could potentially be utilized within a field setting to predict BF% in female athletes. However, due to the SEE of each equation, caution must be taken when using the BMI-based BF% equations to estimate BF% for this population. PRACTICAL APPLICATIONS: The ability to assess BF% quickly and easily in an athletic population is very important. Field estimates of BF% are commonly utilized in athletes because they rarely have time for BF% a