Abstract
High carbohydrate (CHO) intake as a proportion of total energy intake is a prominent feature of sports nutrition guidelines to optimize exercise performance and support athletes' health and well-being(Thomas et al., 2016). The evolution of these guidelines also includes the concept of specificity to the athlete and the exercise scenario (personalization) and differences in intake between and within days according to the fuel requirements and goals of each exercise session (periodization; Burke et al., 2018; Impey et al., 2018). More recently, sports nutrition guidelines have incorporated recommendations relating to energy availability (EA) that promote matching energy intake (EI)according to the energy demands of daily exercise to ensure that body metabolism and function are optimized (Mountjoy et al., 2018).EA refers to the amount of dietary energy available to support essential physiological functioning after accounting for exercise energy expenditure (EEE; Loucks et al., 2011). When dietary intake is not aligned to fluctuations in daily exercise patterns low energy availability (LEA) may occur, whereby the energy remaining to support physiological processes is inadequate. LEA can result in reduced quality of training or performance, but may also present as feelings of fatigue, poor mood, decreased attentiveness, impaired judgment, menstrual cycle disruptions (females), lowered libido(males), gastrointestinal upset, and increased prevalence of injury and/or illness (Ackerman et al.,2019). Reductions in EI and/or increases in EEE may be undertaken deliberately or occur inadvertently and may be advantageous or deleterious, depending on the scenario and the athlete’s goals (Wasserfurth et al., 2020). Within the daily training environment, sports nutrition professionals are reliant on feedback from individual athletes, coaches, and members of the multi-disciplinary team to determine daily energy requirements and interpret CHO intake guidelines to optimize daily training performance, health, and well-being.
Given the substantial impact of LEA on athlete health, well-being, and performance, several screening tools have been validated to detect problematic LEA. Tools available include the LEA in females questionnaire (LEAF-Q), resting metabolic rate (RMR) assessments, pathological testing(sex and other hormones), and dual x-ray absorptiometry (DXA) to assess bone health (Logue et al.,2020). Alongside these measures, calculations of EA can be performed by gathering information on an athlete’s EI, EEE, and fat free mass (FFM; (Burke, Lundy, et al., 2018). However, considerable time, effort, and financial investment is required from athletes and practitioners to undertake these assessments, with most providing a “snapshot” assessment that fails to capture the extended time course of the development of health and performance detriments caused by LEA (Heikura et al.,2021). Further, several of these tools assess outcome measures (i.e., change in bone health) which take several weeks, months, and even years to manifest and thus, have poor temporal resolution for assessing EA status amongst athletes. Thus, tools and biomarkers that monitor energy and CHO status in real-time may provide added benefit to athletes, coaches, and sports nutrition professionals as adjustments in daily fueling strategies can be made to align with daily exercise patterns. Continuous glucose monitors (CGMs), which monitor interstitial glucose concentrations in real-time, are a recent addition to the athlete monitoring toolbox. Although CGMs were initially designed to assist in the clinical management of diabetes, there is now interest in the application of real-time glucose monitoring to athletic populations. Several case studies have incorporated the use of CGMs to report interstitial glucose responses to exercise in an effort to characterize CHO availability of athletes when participating in endurance and ultra-endurance events (Francois et al., 2018; Ishihara et al., 2020; Sengoku et al., 2015). Manufacturers of CGM devices have leveraged athlete’s interest in monitoring their response to exercise and as such have created a wide interest among athletes to maintain optimal glucose levels during training (Abbott Laboratories, 2020). Several companies market CGMs as a tool to enable athletes to “push their limits longer and get bigger gains” (Supersapiens INC, 2021). Whether this is a justified need, creating value for the athlete, or simply represents clever marketing of existing technology to an audience that is receptive to real-time data remains unclear. This thesis aims to investigate the potential value of tracking interstitial glucose with continuous glucose monitors (CGMs) in athletes, highlighting possible applications and important considerations in the collection and interpretation of interstitial glucose data.
Chapter One introduces the concept of EA and its link to relative energy deficiency in sport(REDs). This chapter explains the nuances associated with current tools and methodology used to assess EA status and introduces CGMs as a novel tool to assess fueling status in athlete populations. This chapter also outlines the thesis concepts and aims.
Chapter Two presents results from a qualitative study that aimed to characterize the assessment and management practices employed by Sports Dietitians when assessing and managing athletes at risk of low energy availability (LEA). Sport Dietitians appeared to recognize and prioritize LEA management in athletes, but assessments were limited to dietary intake and training load (km/week); with collaborative approaches to LEA management lacking. The key outcomes from this study show that the development of novel, reliable assessment methods, and collaborative management approaches are needed to improve athlete care when suspected of LEA.
Chapter Three characterizes the day-to-day variation of CGM-measured glycemia and provides reference indices for glycemic variability amongst endurance athletes. The study found that 24 h mean amplitude of glycemic excursion (MAGE), mean of daily differences (MODD) and standard deviation (SD) for interstitial glucose were 1.99 ± 0.30 mmol·L-1, 0.71 ± 0.10 mmol·L-1, 0.89 ±0.10 mmol·L-1, respectively, and that mean 24 h glucose (5.65 ± 0.25 mmol·L-1) was higher than overnight (5.13 ± 0.29 mmol·L-1; P < 0.0001). This study provides reference indices for glycemic variability for endurance athletes under standardized conditions which appear lower than healthy individuals.
Chapter Four presents the findings from a pilot study that aimed to characterize interstitial glucose responses in elite endurance athletes using CGMs during acute exposure to LEA. The study found that overnight interstitial glucose variability while lower, was not significantly different across the 9-d intervention period in the LEA group (1.2 ± 0.9 mmol·L-1), compared with the high energy availability (HEA) group (1.9 ± 0.5 mmol·L-1). Participants in the LEA intervention experienced a trend of increased hypoglycemic episodes, suggesting a shift in interstitial glucose control during an acute period of LEA. Findings from this study suggest further research should be undertaken to determine the influence of altered EA on glucose responses in athletic populations.
Chapter Five aimed to determine the practical utility and sensitivity of glucose monitoring to mirror the magnitude of variation in energy availability across a typical training day in endurance-trained athletes using CGM technology. The case series presented in this chapter demonstrated a reduction in CGM-measured glucose variability markers in response to acute 21-hHEA and LEA interventions among endurance athletes, following 3-d of DH (equivalent to HEA). It is unclear whether perturbations to glucose control among the athletes in this case series occurred in response to an acute change (increase or decrease) in EA status or completion of two unfamiliar, strenuous exercise bouts (AM-HIT and PM-SS) during the 21-h intervention period. Further research in larger cohorts of well-trained athletes under varying EA conditions is required to establish athlete-specific reference ranges to enable more accurate analyses and to determine whether the accuracy of CGM devices is adequate for detecting acute exposure to EA status in (near) real-time.
This thesis concludes with Chapter Six which provides a summary of the important findings of this scholarly work and important considerations for future research.
| Date of Award | 28 Nov 2024 |
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| Original language | English |
| Supervisor | Gregory Cox (Supervisor), Vernon Coffey (Supervisor) & Louise M. Burke (Supervisor) |