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Aim: To highlight energy availability status, resting metabolic rate measures, dietary protein intake, and testosterone concentration in 4 elite male track cycling athletes (mean [SD]: age: 20.8 [1.5] y, body mass: 76.3 [3.6] kg, height: 181.8 [2.9] cm)., Method: A cross-sectional observation included measures of energy availability (energy intake minus exercise energy expenditure, divided by fat-free mass), resting metabolic rate from indirect calorimetry, dietary protein intake from food records, blood analysis to assess sex hormone status, and performance markers., Results: Midrange testosterone (16.9-19.8 nmol/L), lowered resting metabolic rate ratio (0.76-0.98), varied luteinizing hormone (4-10 U/L), and suboptimal energy availability (26-41 kcal/kg fat-free mass/d, range) were observed in the male track cyclists. Protein intakes ranged from 2.0 g to 2.8 g protein/kg/d., Conclusion: The current cohort may have within-day energy deficiency, putting them in a catabolic state.

New Findings: What is the topic of this review? We review the issues with using predicted resting metabolic rate equations in athletic populations. What advances does it highlight? The use of dated predicted resting metabolic rate equations is not appropriate for athletic populations until more studies have been conducted among these unique populations., Abstract: Resting metabolic rate (RMR) is the amount of energy the body uses at rest. A suppressed RMR has been correlated with low energy availability and therefore used as an indicator of an individual's energy state. Furthermore, confounding identification of low energy availability within an athletic population are the physiological measures required, which can be time consuming and require professional expertise. To negate the demands of laboratory protocols in measuring RMR, predicted RMR ( p RMR) equations were developed. Caution should be exercised when applying the p RMR equations for determining low energy availability in athletes owing to the population used to develop the equations and the higher metabolic cost of fat-free mass, thus elevated RMR, associated with athletes. Moreover, a low ratio of measured RMR to p RMR is often used as an alternative marker for energy deficiency. Predictive equations should implement fat-free mass within the algorithm when estimating RMR in athletic populations. The purpose of this paper is to describe p RMR equation development and the issues associated with use of p RMR equations for athletic populations. As professional sport increases, validation of p RMR equations in the modern athlete population is needed to monitor energy availability for athletic health and performance., (© 2019 The Authors. Experimental Physiology © 2019 The Physiological Society.)