The Resting Metabolic Rate: Why It Is Relevant For Athletes And How You Can Know It

When it comes to optimizing performance, athletes pay close attention to every aspect of their training and nutrition. Resting Metabolic Rate (RMR) is a crucial piece of this puzzle, as it represents the amount of energy an athlete’s body uses to sustain basic functions at rest. In this blog, we’ll delve into what RMR means for athletes and how it can be estimated. We also explain the benefits of a physical RMR test.

What is RMR and why does it matter for athletes?

Resting Metabolic Rate (RMR) is the baseline number of calories your body burns while at rest, performing essential functions like breathing, circulating blood, and maintaining body temperature. For athletes, understanding their RMR is critical for several reasons. It helps to know your daily energy needs. This can aid in setting the daily calorie target to maintain, gain or loose weight. Hence it makes personalizing nutrition plans possible, considering one’s individual metabolic rate. Besides that, measuring the RMR on a more frequent basis could help to track changes in metabolic health over time.

The Cunningham equation: a valuable estimation

The RMR can be estimated using a number of formulas. One of them being the Cunningham equation (Cunningham, 1980). Research has shown that for active athletes it provides a fair estimate of ones true RMR (Freire et al., 2022; Jagim et al., 2018). It takes into account lean body mass, which is particularly relevant for athletes. Muscle mass, being metabolically active, requires more energy to maintain than fat. Therefore, athletes with higher muscle mass often have a higher RMR. This equation offers a more tailored estimate compared to older formulas like the Harris-Benedict and Mifflin-St Jeor Equation, especially for athletes.

However, it’s still an estimation

While the Cunningham equation is a valuable estimation, it’s essential to remember that it’s still an estimation. It doesn’t provide the precise, real-time measurement that a physical RMR test can offer. There are several reasons why estimations can fall short. The most important of which is simply individual variability. While estimations give a valid estimate on average, individual persons may just have non-average metabolic rates.

The Cunningham equation assumes an average relationship between lean body mass and RMR. This relates to the second limitation: the equation does not take into account all possible physiological factors that influence metabolism. It merely is a mechanism to describe the metabolism of a population based on a very limited amount of physiological characteristics.

Lastly, it shouldn’t be forgotten that estimations are static. The metabolism of an individual can change over time, and this is not directly taken into account by the estimation.

The superiority of a physical RMR test

For athletes seeking the most accurate and personalized measurement of RMR, a physical RMR test conducted in a sober state is the gold standard. This test involves indirect calorimetry, which measures oxygen consumption and carbon dioxide production to calculate energy expenditure. So, its precision is higher than any estimate. Also, when you repeat the test every now and then, you can get insight into the fluctuations over time. Hence it forms a good foundation for truly personalized nutrition plans.

Calculating daily energy needs

When you know your RMR, the energy needs for a whole day can be calculated. Basically, the day can be split into three parts.

1. Sleeping hours: during these hours your burn is approximately the same rate as your RMR.
2. Hours that you are awake but not exercising: during the day you perform all kinds of tasks requiring energy, from brushing teeth to working and doing groceries. To account for the extra energy you burn compared to your RMR, the RMR should be multiplied by a factor. This factor is the Physical Activity Level (PAL). The more active you are, the higher the PAL.
3. Exercise: during exercise you usually burn a lot more than resting hours. The energy burn can be calculated more precisely using e.g. the data from power meters.

The sum of these three parts is the total energy need for the whole day.

Differences with energy expenditure according to your smart watch

Nowadays smart watches also provide estimations of your energy burn during the day. You will notice that these estimations can be very different from the numbers in the EatMyRide app. Fuller et al. (2020) showed that wearable devices in general fail to estimate the energy expenditure accurately. So it is advised to not directly use those numbers in determining the required intake throughout the day.

In conclusion, understanding your RMR is essential for optimizing athletic performance and nutrition. The Cunningham equation is a valuable tool for estimating RMR, particularly for athletes. However, for the utmost precision and personalization, a physical RMR test conducted in a sober state remains superior. Athletes looking to fine-tune their nutrition and training regimens should consider investing in this gold standard assessment of their metabolic rate for the most accurate guidance on their journey toward peak performance.

References

• Cunningham, J. J. (1980). A reanalysis of the factors influencing basal metabolic rate in normal adults. The American journal of clinical nutrition, 33(11), 2372-2374.
• Freire, R., Pereira, G., Alcantara, J. M., Santos, R., Hausen, M., & Itaborahy, A. (2022). New Predictive Resting Metabolic Rate Equations for High-Level Athletes: A Cross-validation Study. Medicine and science in sports and exercise.
• Fuller, D., Colwell, E., Low, J., Orychock, K., Tobin, M. A., Simango, B., … & Taylor, N. G. (2020). Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and heart rate: systematic review. JMIR mHealth and uHealth, 8(9), e18694.
• Jagim, A. R., Camic, C. L., Kisiolek, J., Luedke, J., Erickson, J., Jones, M. T., & Oliver, J. M. (2018). Accuracy of resting metabolic rate prediction equations in athletes. The Journal of Strength & Conditioning Research, 32(7), 1875-1881.

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