Body Mass Index as a Predictor of Percent Fat in College Athletes and Nonathletes

May 3, 2007Medicine and science in sports and exercise

Body mass index linked to body fat percentage in college athletes and non-athletes

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Abstract

Sensitivity of BMI as a measure of percent fat ranged from 0.56 to 1.0 across different groups.

High sensitivity (0.83-1.0) was observed in male athletes, male nonathletes, and female athletes, indicating BMI's potential to correctly identify those with higher fat percentages.
Sensitivity was perfectly high (1.0) for male football linemen, suggesting BMI may effectively classify fatness in this specific group.
In contrast, female nonathletes exhibited low sensitivity (0.56) but high specificity (0.90), indicating BMI may not reliably identify higher fat percentages in this population.
The optimal BMI cut points for classifying overfatness varied significantly among groups, indicating a need for adjusted thresholds: 27.9 for male athletes, 34.1 for linemen, 26.5 for male nonathletes, 27.7 for female athletes, and 24.0 for female nonathletes.
Findings suggest that BMI should be applied cautiously for assessing fatness in college athletes and nonathletes, highlighting the necessity for tailored BMI classifications.

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INTRODUCTION: Body mass index (BMI) is used as a surrogate for percent fat (% fat) in classifying obesity. However, there is no established criterion for % fat and health risk, and few studies have examined the accuracy/validity of BMI as a measure of % fat. By default, BMI is used to classify athletes and young adults as obese. Consequently, it is critical to understand the accuracy of BMI in these populations. The purposes of this study were 1) to describe the relationship between BMI and % fat, and 2) to determine the accuracy of BMI as a measure of % fat in college athletes and nonathletes.

METHODS: A total of 226 college-aged athletes and 213 college-aged nonathletes participated. Three male groups (athletes, football linemen, and nonathletes) and two female groups (athletes and nonathletes) were created. BMI was calculated. Percent fat was determined via BOD POD. BMI >or= 25 kg.m(-2) was used to define overweight. Twenty percent fat for males and 33% fat for females were used to define overfatness. Using % fat as the criterion, sensitivity and specificity of BMI were calculated. Receiver operator characteristic curves determined optimal BMI cut points for % fat.

RESULTS: Sensitivity was high (0.83-1.0) and specificity was low (0.27-0.66) in male athletes, male nonathletes, and female athletes. Sensitivity was high in linemen (1.0). Sensitivity was low (0.56) and specificity was high (0.90) in female nonathletes. Optimal BMI cut points for male athletes, linemen, male nonathletes, female athletes, and female nonathletes were 27.9, 34.1, 26.5, 27.7, and 24.0 kg.m(-2), respectively.

CONCLUSIONS: BMI should be used cautiously when classifying fatness in college athletes and nonathletes. Our results support the need for different BMI classifications of overweight in these populations.

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Body Mass Index as a Predictor of Percent Fat in College Athletes and Nonathletes

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