The Science of Resting Energy Expenditure and Body Composition: Master Athletes

Nutritional assessment has the primary purpose of evaluating the patient to provide the best dietetic advice and lifestyle changes. However, a crucial part of this assessment is the determination of the patient’s energy requirements. In turn, resting energy expenditure associates directly with body composition, health status, age, gender, and physical activity. Consequently, the phase angle measurement, which tends to decline with age, can apply differently in those master athletes. On the other hand, the phase angle is a strong determinant of nutritional status and energy requirement in hospitalized patients.

A master athlete is a subject older than 35 years old who participates in athletic competitions and continues their high endurance physical training. As the number of these master athletes increases, new observations point out that REE equations can no longer apply to this population. The main reason is that these individuals have specific energy demands. Also, they have different physiological changes, mainly due to their high physical performance and high skeletal muscle mass.

What is Resting Energy Expenditure?

It is the amount of energy or calories that our body needs to maintain essential body functions. Resting energy expenditure contributes to 60-70% of the total energy expenditure (TEE), and fat-free mass (FFM) determines REE. However, other factors that influence REE, such as age, which associates with a loss of muscle mass.

How can we measure it?

Multiple equations can predict resting energy expenditure. Some of them are listed down:

Harris-Benedict: it defines an individual’s heat production after a 12-14h after the last meal at rest. 

• Men: REE(kcal/d)=66.47+13.75×Bodyweight(kg) + 5.0 × Height(cm) − 6.76 × Age(years). 
• Women: REE(kcal/d)=655.1+9.56×Bodyweight(kg) + 1.85 × Height(cm) − 4.68 × Age(years). 

World Health Organization: the WHO energy requirement equation is based on several studies that estimate the food requirements of specific populations. Its equations are categorized by age and gender:

• Men30−60years:REE(kcal/d)= 11.6×Bodyweight(kg) + 879. 
• Men>60years:REE(kcal/d)= 13.5×Bodyweight(kg) + 487. 
• Women30−60years:REE(kcal/d)= 8.7×Bodyweight(kg) + 829. 
• Women>60years:REE(kcal/d)= 10.5×Bodyweight(kg) + 596. 

Cunningham: This equation solidifies Harris-Benedict’s findings that FFM is the strongest predictor of REE. Therefore, the Cunningham equation uses this factor along with constant variables to determine REE.

• REE(kcal/d) = 500 + 22 × FFM(kg).

Indirect Calorimetry: the gold standard

Besides these equations, indirect calorimetry (IC) is a non-invasive method to measure REE. IC measures oxygen (O2) consumption and carbon dioxide (CO2) dispersal, these markers associate with the metabolism of energy-rich substrates such as carbohydrates and fats. The Weir equation predicts the REE once with the previous knowledge of urinary nitrogen, CO2, and O2 volume. 

• REE(kcal/day) = [(VO2 × 3.941) + (VCO2 × 1.11) + (uN2 × 2.17)] × 1, 440. 

The urinary nitrogen is hard to determine, and it makes the IC calculation difficult since its recollection is for 24 h. Up until now, IC devices were used for clinical applications; and an IC technician was needed to perform the analysis. These and other factors made the IC application difficult in other areas of application.

A study was performed on master athletes to observe how their body composition is associated with REE equations. This study determined that the most critical factor contributing to the REE was the fat-free mass and body weight. As the phase angle is a strong predictor of cell mass, cell membrane permeability, and these body composition markers associate with a high skeletal muscle mass. However, these authors state that the phase angle is not a potent modifier of REE in master athletes. Finally, this study shows that age and fat-free mass are essential factors to consider when calculating the REE of a master athlete.

The phase angle measurement has strong validation and can predict health status or deterioration when applied to clinical settings. However, when determining the REE of a specific population, such as master athletes, other factors like body weight and fat-free mass have a more substantial influence than PhA.- Ana Paola Rodríguez Arciniega, MS.

References:

Frings-Meuthen, Petra et al. “Resting Energy Expenditure of Master Athletes: Accuracy of Predictive Equations and Primary Determinants.” Frontiers in physiology vol. 12 641455. 22 Mar. 2021, doi:10.3389/fphys.2021.641455

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