Estimating an Athlete’s Energy Requirements
Dexalytics recently announced a couple of new features to help you determine energy needs. Over the next couple of blogs, I will explain why two options are available and how to use the best option to increase the accuracy of estimating energy requirements.
What is the difference between resting metabolic rate (RMR) and basal metabolic rate (BMR)? Resting metabolic rate (RMR) can be defined simply as the amount of energy (i.e., calories) expended by a person at rest over a 24-hour period. For an athlete who engages in hours of exercise training, the RMR may account for up to half of their total energy needs (Brooks et al., 2004). For sedentary individuals, the RMR can account for almost 75% of their daily energy expenditure (Levine 2005).
An individual’s BMR is considered the RMR just after awakening in the morning. RMR and BMR typically differ by approximately 10% (DRI, 2005) so the two terms are often used interchangeably. The RMR is determined by indirect calorimetry, which involves the measurement of oxygen consumption and carbon dioxide production using an expensive metabolic gas analysis system. Typically, the RMR is measured for 30-60 minutes in the morning 10-12 hours after the last meal, while the individual is in the supine position.
What variables are used to estimate resting energy needs? A simpler way to determine one’s RMR is to calculate it from body composition variables. In 1918, two researchers named Harris and Benedict published a paper (Harris & Benedict, 1918) on the calculation of RMR from height and weight. The equation became known, as the Harris-Benedict equation and is still used today to estimate RMR. The Harris-Benedict equation uses age, gender, height and weight.
On the Dexalytics dashboard there is a calculation of RMR displayed that uses the Harris-Benedict equation. The problem with using this equation to estimate RMR is that the Harris-Benedict equation has often been found to overestimate RMR in obese populations due to their lower lean to fat mass ratio, while underestimating RMR in athletes due to their high lean to fat mass ratio.
You will also notice on the dashboard that RMR is calculated using an equation developed by J.J. Cunningham (Cunningham, 1991). The Cunningham equation uses fat-free mass instead of height and weight, which increases the accuracy of estimating RMR especially in athletic populations (Thompson & Manore, 1996).
Dexalytics gives the user the option to utilize the best equation for estimating RMR based on body composition. When you couple the RMR with an individual’s physical activity energy expenditure you can calculate ones daily energy expenditure. Read my next blog to learn how to use this feature to determine weight gain, weight loss and weight maintenance.
Brooks GA, Butte NF, Rand WM, Flatt JP, Caballero B. Chronicle of the Institute of Medicine physical activity recommendation: how a physical activity recommendation came to be among dietary recommendations. Am J Clin Nutr. 2004;79(5):921S-930S.
Cunningham JJ. Body composition as a determinant of energy expenditure: a synthetic review and a proposed general prediction equation. Am J Clin Nutr. 1991;54(6): 963-969.
Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients). Panel on Macronutrients, Panel on the Definition of Dietary Fiber, Subcommittee on Upper Reference Levels of Nutrients, Subcommittee on Interpretation and Uses of Dietary Reference Intakes, and the Standing Committee on the Scientific Evaluation of Dietary Reference Intakes, Food and Nutrition Board. The National Academies Press: Washington, D.C., 2005.
Harris JA, Benedict FG. A biometric study of human basal metabolism. Proc Natl Acad Sci U.S.A. 1918;4(12):370-373.
Levine JA. Measurement of energy expenditure. Public Health Nutr. 2005:8(7A):1123-1132.
Thompson J, Manore MM. Predicted and measured resting metabolic rate of male and female endurance athletes. J Am Diet Assoc. 1996;96(1):30-34.
About the Author: Donald Dengel, Ph.D., is a Professor in the School of Kinesiology at the University of Minnesota and is a co-founder of Dexalytics. He serves as the Director of the Laboratory of Integrative Human Physiology, which provides clinical vascular, metabolic, exercise and body composition testing for researchers across the University of Minnesota.