What this is
- This review updates previous findings on () in athletes, emphasizing its prevalence and risks.
- Low can lead to significant health issues, including menstrual dysfunction and impaired sports performance.
- The review also highlights the need for better screening tools and educational initiatives for athletes and coaches.
Essence
- () affects both male and female athletes, leading to health risks and impaired performance. Improved screening and education on are necessary for better athlete outcomes.
Key takeaways
- Low prevalence ranges from 22% to 58% across various sports, affecting both genders. Accurate estimation remains challenging due to variability in measurement methods.
- Screening tools like the in Females Questionnaire (LEAF-Q) help identify at-risk athletes, but similar tools for males are still in development.
- Educational initiatives are crucial, as knowledge of (RED-S) is low among coaches and athletes, impacting their ability to identify and manage low .
Caveats
- The review is based on cross-sectional studies, limiting the ability to draw causal conclusions about low and its effects on health and performance.
- Self-reported data in many studies may introduce bias, affecting the reliability of findings related to and associated health outcomes.
Definitions
- Low Energy Availability (EA): Inadequate energy intake relative to exercise energy expenditure, leading to negative health and performance consequences.
- Relative Energy Deficiency in Sport (RED-S): A syndrome resulting from low EA, affecting physical and psychological health in athletes.
Simplified
1. Introduction
Considerable research has been undertaken to understand the health and performance consequences of relative energy deficiency in sports (RED-S), a condition frequently observed among high performing male and female athletes [1,2]. It is widely acknowledged that low energy availability (EA), described as inadequate energy intake relative to exercise energy expenditure, is the main factor triggering the unfavourable health and performance consequences associated with RED-S [3]. Since the publication of the International Olympic Committee (IOC) consensus papers on RED-S in 2014 and 2018 [1,2], scientific evidence for the risk of and performance consequences of low EA has grown [4,5].
Although an understanding of the physiological effects of low EA in male athletes remains limited, a recent cross-sectional study conducted on males participating in endurance training reported that regular exposure to high levels of chronic intense and long duration training is associated with a decreased libido score. [6]. Therefore, the IOC and other researchers in the field [7] advise that research should now focus on the energy demands and performance criteria of males engaged in a range of sports as the majority of research in the past has focused on women [2].
Following publication of our 2018 review on the prevalence of low EA and associated health and performance consequences [7], the volume of research on RED-S has substantially increased (peer-reviewed articles in 2018 (n = 21), 2019 (n = 24) vs. 2016 (n = 6) and 2017 (n = 10)). The purpose of this investigation is to identify other potential methods for assessing low EA given that the current methods used remain challenging. Furthermore, the review highlights recent data on the prevalence and risk of low EA, within-day energy deficiency and the health and sporting performance consequences associated with low EA. Furthermore, the published literature on awareness and knowledge of RED-S among athletes and coaches has been evaluated to identify gaps in the practical application of low EA education in sports [8,9,10,11].
2. Methodology
This is an update of a narrative review [7] which was conducted using targeted database searches, for example, PubMed, Google Scholar and Web of Science. Combinations of the following key search terms were included: athlete, EA, low EA, low EA risk, within-day energy balance, low EA knowledge and awareness of low EA, nutrition education/diet intervention and RED-S. Articles published between 2017 and 2019 were considered if they were published in English, available in full text and were conducted among trained or exercising human subjects. The inclusion criteria was as follows: only studies that quantified EA by assessing energy intake, exercise energy expenditure (EEE) and body composition and that investigated symptoms associated with low EA within the text of the manuscript were included in this review. The reference lists of retrieved articles were also reviewed to identify any articles not identified by the database searches. Animal studies were excluded. The quality and strength of the supporting evidence were graded according to the criteria of the Scottish Intercollegiate Guidelines Network (SIGN) [12]. The SIGN grading criteria include the assessment of study design and its ability to minimise the possibility of bias as well as an evaluation of the methodological quality, quantity, consistency, and applicability of a study’s results to the evidence base.
3. Results
3.1. Low Energy Availability
Recent studies have investigated the prevalence of low EA in various sports [8,13,14,15,16,17,18,19,20,21,22]. Prevalence ranges from 22% to 58% (Table 1). It is apparent that low EA exists in males as well as females as evidenced by studies conducted in male road cyclists [9] and elite distance athletes [23,24,25]. Nonetheless, accurate estimation of the prevalence of low EA remains problematic due to continuing variability in the methods used to estimate EA (Table 2). Furthermore, there are some limitations to the application of clinically low EA < 30 kcal/kg fat free mass (FFM)/kg/day [3] in cross-sectional studies. Self-reported nutritional data in free-living athletes have failed to find clear thresholds or associations between EA and objective measures of energy conservation or health impairment such as disruption to metabolic hormones [24,26] and menstrual disturbances [27,28,29]. Most recently (Table 3), athletes are being screened for symptoms of low EA using questionnaires that screen for physiological symptoms associated with the Female Athlete Triad (Triad) and RED-S, an example of which is the Low EA in Females Questionnaire (LEAF-Q) [30]. The current evidence implies that clinical, individual assessment of the diagnostic criteria of the Triad [31], the LEAF-Q [30] and the RED-S clinical assessment tool (RED-S CAT) [32] is necessary. This assessment should be conducted with an evaluation of disordered eating behaviours and reproductive biomarkers (blood biochemical assessment of sex-hormones and prospective collection of oestrogen and progesterone during one or more menstrual cycles). This may represent a more objective and accurate indicator of optimal EA for health in females than the estimation of EA using dietary and training logs [24]. Nevertheless, further research is warranted as there is limited research on the effect of hormonal contraception on physiological function and biochemical assessment of low EA/RED-S.
Furthermore, a low ratio between measured and predicted resting metabolic rate (RMR) is an acknowledged marker of low EA (RMR ratio < 0.90) [27]. Associations between suppressed RMR and elevated low EA risk scores in female ballet dancers and with higher training volume in male ballet dancers have recently been observed [38]. These results indicate low RMR ratio as a potential surrogate marker for low EA. However, the prevalence of suppressed RMR ratio using dual-energy X-ray (DXA) and different RMR predictive equations such as the Harris–Benedict and Cunningham equations showed large variability in both male and female professional ballet dancers, ranging from 25% to 80% and 35% to 100% in males and females, respectively [38]. Thus, the identification of athletes at risk of low EA varies greatly depending on the predictive equation used. A recent review of the validity of RMR predictive equations to assess low EA in athletes emphasized that predictive equations that do not have FFM incorporated within the algorithm are unsuitable for use in athletes and that accurate RMR laboratory protocols are essential when monitoring EA [42]. Thus, the development of a reliable RMR laboratory protocol in athletes is needed before measured RMR or the RMR ratio can reliably be used to diagnose low EA [27,38,43].
3.2. Low Energy Availability Risk
The risk of low EA has been investigated using surrogate markers or self-reported symptoms of low EA in various athlete populations including elite para-athletes [34], adolescent/young adult [35,36] and Olympic athletes [40], female sprinters [41], male jockeys [39] and recreationally active individuals [33,37], and ranges from 14% to 63% (Table 3). The largest cross-sectional study investigating self-reported health and performance outcomes linked to low EA and RED-S [5] placed emphasis on including body systems beyond reproductive function and bone health such as metabolic, haematological, psychological and cardiovascular health and gastrointestinal function. The authors acknowledged that associations identified in their study (Table 3) were based on self-reported data and highlight the need to investigate the health and performance components of RED-S in a controlled setting, whereby low EA is measured under strict conditions in a laboratory setting, to understand causative pathways [5]. Another cross-sectional study supports associations between low EA risk and self-reported medical illness [40]. Moreover, associations have been described between low EA risk and stress fractures, absence from training for >22 days due to illness and reported adherence to a gluten-free diet [37]. These findings suggest that those at risk of low EA can present with symptoms other than those traditionally expected e.g., menstrual irregularities, and highlight the complexity of identifying individuals at risk [40]. The LEAF-Q enables early recognition of active females at risk of low EA by evaluating the presence of symptoms associated with low EA, such as menstrual and gastrointestinal dysfunction, injury history, as well as oral contraceptive use [30]. The LEAF-Q is an easily administered questionnaire that has been validated for use in athletic endurance-trained females [30]. As such, it offers a validated method to investigate risk of low EA in large, exercising cohorts and alleviates some of the challenges associated with directly measuring EA [44]. In the measurement of the components of the EA equation, significant errors of reliability (e.g., variation in the time and techniques used to estimate EA) and validity (e.g., under/over estimation of EI and/or EEE) can occur [45]. Although low EA risk has been investigated in elite male cyclists [9] using non-validated tools such as a sport-specific questionnaire and clinical interview (SEAQ-I) [9], a screening questionnaire for male athletes similar to the LEAF-Q is required and is currently being developed (the Low Energy Availability in Male’s Questionnaire (LEAM-Q) [2]. Following its development and validation, it is anticipated that potential risk of low EA will be identified in a range of athletic male populations.
3.2.1. Eating Disorders and Exercise Addiction
Disordered eating behaviours and eating disorders are known to occur frequently in elite female athletes, particularly among those competing in weight class or leanness-demanding sports [46]. These conditions are associated with perfectionism as well as compulsive exercise behaviour, coupled with the inability to reduce training load [47] and can lead to unfavourable outcomes such as injury and emotional distress [47]. Recent research describes how compulsive exercise behaviour is associated with symptoms of disordered eating behaviour, perfectionism and obsessive-compulsive characteristics in long-distance runners of both sexes [48]. We encourage further exploration of the relationship between compulsive exercise behaviour and RED-S, since individuals demonstrating compulsive exercise behaviour may be at greater risk of the negative health outcomes associated with low EA [48].
Although most research into RED-S has been conducted in females, a recent study investigated associations between compulsive exercise behaviour, disordered eating symptoms and biomarkers of RED-S in trained male cyclists, triathletes and long-distance runners [49]. Using the Eating Disorder Examination Questionnaire (EDE-Q), higher total exercise dependence scores were associated with disordered eating symptoms. Participants with higher exercise dependence scores trained more frequently (~11 h/week) compared to those with lower scores (~8 h/week). Furthermore, participants with higher scores did not adjust their energy intake to meet increased energy needs, resulting in more pronounced low EA. This was associated with higher cortisol levels compared to those with lower exercise dependence scores [49]. Higher subscale exercise dependence scores were also associated with lower blood glucose, lower testosterone: cortisol ratio and higher cortisol: insulin ratio [49]. This suggests an association between biomarkers of RED-S and compulsive exercise behaviour. Although these findings currently relate only to endurance athletes, determining whether these associations exist in highly-trained athletes competing, in particular, in weight sensitive and team sports, represents an interesting area for future investigation.
Psychological factors such as stress, anxiety and depression can result in or contribute to disordered eating behaviour and low EA in athletes [1]. Moreover, it has been suggested that compulsive exercise behaviour could increase vulnerability to negative health and performance outcomes [48]. Despite the lack of conclusive evidence, mainly due to the absence of studies investigating associations between compulsive exercise, disordered eating behaviour symptoms and biomarkers of RED-S, there appears to be an opportunity to improve athlete health and performance. This may be possible through screening for potential underlying causes of low EA such as compulsive exercise, in conjunction with validated disordered eating behaviour and low EA risk questionnaires. Screening for compulsive exercise should increase awareness of the psychological factors underpinning and contributing to low EA and its associated consequences such as poor mental health. More precisely, identifying the relationship between compulsive exercise, disordered eating behaviour and RED-S in various sports and groups of athletes (e.g., gender, performance level and age) is recommended. Nevertheless, self-reported data need to be interpreted with caution as they may be heavily influenced by athletes’ perceptions, experiences and recollections, thus, further emphasising the need to use well-validated questionnaires to investigate outcomes associated with LEA in the athletic population.
3.2.2. Exercise Hypogonadal Male Condition
The Triad continuum, whereby a female can advance from optimal health status [optimal EA, normal menstrual function and good bone health] to a diseased state [low EA (with and without an eating disorder), menstrual dysfunction and low bone mineral density] at any point throughout her life course, has been extensively investigated over the last 30 years [50,51,52]. Rigorously executed studies have identified low EA, not the stress of exercise, as the underlying mechanism causing disruption to the female hypothalamic-pituitary-gonadal axis [51,53]. Further evidence suggests that endurance exercising males can develop a similar suppression of the reproductive function known as exercise hypogonadal male condition (EHMC) [54] (Figure 1). In EHMC, disruption to the male hypothalamic-pituitary-gonadal axis has been hypothesised, given that luteinising hormone and testosterone levels are suppressed (Figure 2 Left), just as in females with functional hypothalamic oligomenorrhea or amenorrhea (Figure 2 Right). In male athletes, associations between higher levels of intensive endurance training and reductions in testosterone and libido [6,54] have been observed without assessment of EA, and the underlying mechanisms remain unclear. Further research in a controlled setting (i.e., low EA is measured under strict conditions in a laboratory setting) is warranted to understand the causative pathways behind disruption to the male hypothalamic-pituitary-gonadal axis. Furthermore, accurately determining the reliability of testosterone levels as a potential indicator of low EA or RED-S and the impact of low testosterone levels on other testosterone-dependent physiological processes warrants thorough investigation.
4. Within-Day Energy Deficiency in Athletes
Recent research into within-day energy balance and within-day energy deficiency, whereby energy intake and exercise energy expenditure are assessed in 1-h intervals, may provide greater insight into real-time changes that are indicative of the endocrine responses associated with variations in EA and may help to identify markers of energy deficiency [55,56]. To date, two studies have examined within-day energy deficiency, one in male [56] and the other in female [55] endurance athletes. In the male study, the relationship between within-day energy deficiency and RMR was explored [56]. Despite similar EA, athletes identified with suppressed RMR spent more time (21 vs. 11 h) with an energy deficit exceeding 400 kcal across a 24-h period. Within-day energy deficiency was associated with higher blood cortisol level and lower testosterone: cortisol ratio [56]. In the female study, within-day energy deficiency was also associated with higher cortisol levels as well as with menstrual dysfunction, lower oestradiol and RMR ratio [55]. Furthermore, despite similar EA, female endurance athletes with menstrual dysfunction spent more time (22 vs. 18 h) in an energy deficient state exceeding 300 kcal compared to eumenorrheic athletes [55]. A positive association between within-day energy deficiency and more frequent meals was also observed. These findings contradict the commonly held belief that higher meal frequency may be necessary for some athletes to attain energy balance and prevent within-day energy deficiency [57]. Consumption of high fibre and low energy-dense foods were previously reported in endurance females with menstrual dysfunction [58]; thus, the energy density of food consumed at mealtimes needs careful consideration to improve within-day energy balance in females with menstrual dysfunction. Other dietary factors such as diet quality and differing attitudes towards food groups need to be investigated when assessing for risk of low EA.
In summary, the viability of measuring within-day energy deficiency and its ability to detect athletes at risk of negative health outcomes associated with low EA is unclear. Questions around appropriate assessment of within-day energy deficiency and the time periods over which it should be assessed impede the quality of research in this area. Further research, especially in female athletes, represents an interesting area for future investigation.
5. Low Energy Availability and Sports Performance
While low EA influences many body systems, for example, reproductive system suppression and menstrual cycle disruption as a mechanism to conserve energy, it is important to note other hormonal pathways are altered, resulting in numerous interrelated endocrine-derived physiological consequences [50,59]. These include increased cortisol levels and reduced triiodothyronine (T3), luteinizing hormone (LH) pulsatility and hypoestrogenism [50,59]. Low EA-related menstrual dysfunction is associated with increased bone stress injury risk which can impair training and competition availability [60]. Thus, low EA may be a contributor to poor sports performance due to associated detrimental endocrine effects [61]. A decrease in neuromuscular performance, assessed using isokinetic dynamometry, was observed in elite endurance athletes with menstrual dysfunction in contrast to eumenorrheic endurance athletes [62]. Furthermore, the decreased neuromuscular performance was associated with lower FFM in the leg, glucose, oestrogen, T3, and elevated cortisol [62]. While these findings are unable to provide sufficient evidence of a causal link between these biomarkers and performance, the interrelationship is biologically possible. The study authors hypothesized that a consistently low blood glucose may lead to increased cortisol and reduced T3, in addition to lower muscle mass in the long term, all of which have been associated with reduced neuromuscular performance [62]. Furthermore, these results support previous literature that indicates that physiological manifestations of low EA, such as menstrual dysfunction in female athletes, negatively impact on sporting performance [63,64].
One study, which did not assess EA but instead investigated associations between aspects of endurance exercise training and sexual libido in endurance training males, concluded that libido scores are associated with the duration and intensity of training [6]. These findings indicate that physiological adaptations may occur within males but reliance on self-reported measures limits the interpretation and generalisability of study results [6]. Nonetheless, these preliminary findings indicate that the amount and intensity of endurance training as potential contributing factors to low libido in males needs consideration. Further research is necessary to better understand the impact of low libido on sports performance.
6. Knowledge of Low Energy Availability and Relative Energy Deficiency in Sport
Screening and interventions for low EA risk are needed to protect athlete health and performance. Coaches can play a pivotal role in the early identification of athletes at risk of low EA. However, there is little research exploring the knowledge coaches have on this topic. A recent cross-sectional survey that investigated knowledge of the Triad and RED-S among head athletic trainers at National Collegiate Athletic Association (NCAA) member institutions reported that almost all principal athletic trainers (98.6%) were aware of the Triad [10]. Only one-third (33%) were aware of RED-S [10]. Furthermore, 60% and 71% of principal athletic trainers reported that athletes were screened for eating disorders and menstrual irregularities respectively. Those athletes in need of multidisciplinary team support (e.g., athletes identified with menstrual dysfunction or bone stress injury) occurred at division I institutions compared to those in division II or III. A major limitation of this study is that only one third of the principal athletic trainers at NCAA member institutions responded to the survey. It may be that interest and knowledge of the Triad and RED-S was greater in study participants than in those who failed to respond.
Another study investigating risk of low EA and sports nutrition knowledge among female Australian Rules football players reported that 30% of participants were at risk of low EA [8]. Nutrition knowledge of participants was measured using the Sports Nutrition Knowledge Questionnaire [65]. Players answered ~55% of the questions correctly, with the lowest scores observed for responses in the supplement section [8]. Furthermore, an intervention study investigating the effect of a 6-month nutrition education program for male athletes who were at risk of RED-S, reported positive results on bone health and race performance [9]. These findings suggest that nutritional education programs, including specific information on low EA, its associated short and long-term health implications and dietary supplement use, may improve athlete health and performance outcomes. Education on RED-S for athletes and coaches is necessary to encourage screening for and early identification of athletes at risk of low EA. Multidisciplinary healthcare professional input to ensure appropriate interpretation of the results of screening questionnaires and implementation of interventions is required.
A recent intervention investigated changes in Triad knowledge among female high school athletes (n = 89) after participation in a number of brief (10-min) Triad educational videos [11]. The educational videos featured (1) a registered dietitian who defined the aetiology and progression of the Triad, and who provided nutritional strategies that may decrease its risk, (2) a former collegiate athlete who shared personal experiences of overcoming Triad-associated problems and, (3) a collegiate coach who shared insights into negative body image and pressure to achieve a specific bodyweight or appearance [11]. Knowledge about consequences of the Triad (for example, menstrual irregularity increases stress fracture risk; low energy intake is negatively associated with menstrual function and bone health) was identified in most participating athletes (≥ 89%) [11]. These findings suggest that educational videos may be an effective method of improving athlete knowledge of the Triad. Whether improved knowledge is associated with behavioural change in athletes with low EA (for example, athletes increasing their energy intake) represents an important area for investigation.
7. Conclusions
This article provides a synthesis of the research conducted on RED-S since our previously published review [7]. This is important given the number of studies conducted over the period. Detection of low EA by identifying physiological symptoms and measuring biomarkers associated with the condition has replaced the use of weighed dietary and exercise logs and heart rate monitors or accelerometers. This may facilitate better exploration of the health and performance outcomes associated with low EA. As the majority of studies are cross-sectional in design and cannot show causality, future longitudinal studies with sufficient numbers of those at risk are required to properly understand the consequences of low EA. The poor understanding by athletes and coaches of low EA and its potential health and performance consequences emphasizes the need for further research in this area. Education to increase awareness and to implement dietary and training interventions, in particular, for athletes engaged in intensive training is also vital.
Key points: Until 2015, low energy availability (EA) was predominantly identified using weighed dietary and exercise logs in combination with heart rate monitors or accelerometers [7]. Research published in the past four years has established that low EA is more easily and accurately identified by the use of surrogate markers including suppressed resting RMR [27,38,43] and validated questionnaires that screen for a drive for thinness and physiological symptoms associated with low EA [30]. Understanding athletes’ and coaches’ knowledge and perspectives on low EA and its health and performance consequences is required [10]. Few education initiatives exist to improve athlete understanding of low EA and its associated health and performance consequences [11]. The development and implementation of sports nutrition programmes to increase awareness and improve knowledge of EA and within-day energy balance, as well as sports nutrition treatment strategies for athletes at risk of low EA, are warranted.