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Does the Body Mass Index Accurately Reflect Percent Body Fat in Athletes?

Riewald, Scott PhD, CSCS, NSCA-CPT

Strength and Conditioning Journal: February 2008 - Volume 30 - Issue 1 - p 80-81
doi: 10.1519/SSC.0b013e318163bc23
OTHER FEATURES: Research Digest
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United States Olympic Committee, Colorado, Springs, Colorado

Scott Riewaldis Biomechanist and Performance Technologist at the US Olympic Committee.

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The body mass index (BMI) is a measure that was developed as a simple and noninvasive way to estimate body composition and categorize individuals based on body size and weight. The BMI is computed by dividing an individual's weight, (in kilograms), by his or her height, (in meters), squared. Based on the computed ratio, individuals are classified as being underweight (<18.5-kg·m−2), of normal weight (18.5–24.9-kg·m−2), overweight (25–29.9-kg·m−2), or obese (>30-kg·m−2). Individuals with a BMI greater than 25 kg·m−2 are thought to be at greater risk of heart disease, hypertension, and diabetes because they carry around excess body fat. Consequently, individuals with high BMIs may pay more for health insurance or life insurance because of the perceived health risk.

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ASSUMPTION: ATHLETES ARE LIKE EVERYONE ELSE

The underlying assumption with the BMI is that this measure accurately reflects body composition and percent body fat. For the average young adult it does; a BMI of 25-kg·m−2 roughly corresponds to the upper limit of what is considered a healthy percentage of body fat: 20% for males and 33% for females. Although the BMI may accurately reflect body composition in the general population, anecdotal observations and recent research suggest that the BMI does categorize athletes correctly. Athletes with healthy body fat percentages tend to register as being overweight or obese. This makes sense because athletes tend to be more muscular than the average individual and muscle is more dense than fat. It is entirely possible that the BMI overestimates the percent body fat in athletes and that a new evaluative standard should be used to classify athletes.

A recent study by Ode et al. (1) took a closer look at the BMI and how accurately it reflects body composition in collegiate athletes and nonathletes. They looked at a total of 226 collegiate varsity athletes (149 men and 77 women) and 213 nonathletes (78 men and 135 women). The athletes came from a variety of sports and were further categorized by gender and into a generic athlete group and football lineman group based on initial BMI assessments. The BMI was computed for each study participant, and body composition measurements were taken by using the BOD POD. When the data were analyzed, the results were interesting.

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IS THERE A MISCATEGORIZATION OF ATHLETES?

The study participants were classified two ways: according to their BMI and according to the measured percent body fat. Individuals with a BMI greater than 25-kg·m−2 were designated as being overweight. Men and women with a body fat percentage greater than 20% and 33%, respectively, were categorized as being “overfat.” From these classifications, the authors established four possible outcomes of using the BMI to categorize athletes:

  1. A true positive in which an athlete is overweight and overfat.
  2. A false positive in which an athlete is overweight but has a healthy percent body fat.
  3. A true negative in which an athlete is of normal weight and also has a healthy percent body fat.
  4. A false negative in which an athlete is of normal weight but has a higher than desired percent body fat.

The analysis of the data showed that the BMI is not an accurate measure of body fat in athletes. Specifically, the authors found that 67% of the male athletes who participated in the study were categorized as false positives, meaning that although they had a healthy percent body fat, the BMI classified them as being overweight. Comparatively, only 25% of the male nonathletes registered as false positives. In the female athlete group, 31% registered as false positives, compared to 7% of the participants in the female nonathlete group. There were no false negatives in the male or female athlete groups.

From these data, new BMI cutoffs were suggested to better reflect the body composition of athletic young adults. A BMI greater than 27.9 kg·m−2 was suggested as a new cutoff to classify male athletes as being overweight. This level more accurately reflects 20% body fat in this population. A BMI greater than 27.7 kg·m−2 was suggested as a new cutoff to classify female athletes as being overweight. This level more accurately reflects 33% body fat in this group. The results of the study suggested that BMI classifications could be adjusted to better reflect body fat percentages in nonathletes also. A BMI of 26.5 kg·m−2 for males and 24.0 kg m−2 for females more accurately reflects body fat percentages of 20% and 33%, respectively. The football linemen group, because of their vast difference in size and body composition compared to the generic athlete group, was treated differently. For this group, an acceptable body fat percentage was set at 25%, and when this criterion was taken into account, an acceptable football lineman BMI was 35.2 kg·m−2.

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TAKE-HOME MESSAGE

So how does this pertain to the reader? The take-home message from this study is that athletes are not like everyone else. Therefore, using the same BMI classification system that is used with the general population may paint an incorrect picture for an athlete, specifically as it relates to body composition and the health risks associated with being “overly fat.” When working with athletes, realize that because of their increased muscles mass, acceptable BMI values likely should be slightly higher than those used for the general population. Do not feel that athletes should have to fit into the classifications established for nonathletes. The BMI guidelines in this column can serve as better, athlete-specific descriptors for body composition in athletes.▪

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REFERENCE

1. Ode JJ, Pivarnik JM, Reeves MJ, and Knous JL. Body mass index as a predictor of percent fat in college athletes and non-athletes. Med Sci Sports Exerc 39: 403–409, 2007.
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