Exercise, Brain and Cognitive Functioning

#### **Chapter 1**

## The Performance during the Exercise: Legitimizing the Psychophysiological Approach

*Ricardo Ferraz, Pedro Forte, Luís Branquinho, José E. Teixeira, Henrique Neiva, Daniel A. Marinho and Mário C. Marques*

#### **Abstract**

Over the years, there has been a growing interest in the study of issues related to the psychophysiological processes underlying sports performance. A relatively recent perspective is supported by the concept that the brain acts as a central regulator of performance during exercise. This phenomenon is called pacing and is based on the premise that prior knowledge about the activity plays a fundamental role for individuals to self-regulate their efforts throughout the exercise. However, knowledge regarding this topic remains scarce, and further clarification is needed. This chapter reports new perspectives in relation to the existing evidence regarding the role of the brain as a central regulator of performance, questioning the complex interdependencies and interrelations between fatigue and physical exercise in the light of a psychophysiological perspective. A broader understanding of the cognitive basis of the psychophysiological phenomenon during the exercise is needed, bringing together concepts such as pacing behavior, decision-making, self-regulation of effort, prior knowledge of the duration of the task, and perception of effort.

**Keywords:** psychophysiological, brain, fatigue, pacing, performance

#### **1. Introduction**

Exercise is characterized as a complex activity, in which the phenomenon of fatigue is enigmatic and stimulating, therefore requiring further investigation [1–4]. Over time, efforts have been made to study this phenomenon in the field of sports sciences [5–7]. However, knowledge about fatigue remains ambiguous, unpredictable, and difficult to fully explain. There is a wide range of variables (training load, anxiety, etc.) that can affect the fatigue process during exercise and its synergies with the human body responses [8, 9]. For these reasons, there is no consensus in the scientific community regarding fatigue during exercise [4, 10–12], and therefore, there is no unique definition for the concept of exercise fatigue. Thus, reaching a single definition remains a scientific challenge.

Until today, classical fatigue theories continue to be the main focus of discussion on the subject. However, recent studies have emerged, identifying flaws and limitations in these theories, essentially because they do not consider significant factors in their analysis [1, 2, 4]. Following this line of investigation, the concept of fatigue has been evidenced in new investigations as a result of other aspects [13].

So far, the fatigue concept was specially based on physiological variables [14]. The new data do not fully support innovative approaches in relation to the phenomena considered until then. In fact, the studies suggested expanding the scope and focus of the fatigue research [2]. This is because the physiological perspective justifies part of the problem [15]. However, the remaining problem seems to be explained by multifactorial variables, raising the possibility of new perspectives and psychophysiological approaches [16–18].

Based on this perspective, effort regulation has emerged as a choice that athletes should take during exercise and that strongly influences performance [17]. This control of effort on the part of athletes has been called "pacing," and it is assumed as a valuable concept in sport, supporting the existence of a psychophysiological perspective [16]. Although coaches and athletes are aware of the importance of pacing, it has been the object of study by researchers only in recent years, and so, it continues to have little expression in literature [19]. However, investigations have shown the existence of a psychophysiological system capable of controlling physical capacities and with apparent applicability in all types of exercises, including team sports [16]. The pacing phenomenon is directly linked to exercise, and until now, there was a propensity to look at pacing as a purely psychological phenomenon. It was not considered an object of analysis in the field of sports sciences, which mainly explores physiological phenomena associated with exercise [20]. Recent findings in brain research have shown that pacing is a phenomenon with strong interconnection between the psychological and physiological dimensions [16]. In fact, stress resulting from high-intensity exercise (which leads to exhaustion) can cause an unconscious or conscious inhibition of the athlete's tolerance to pain [21]. This may cause the central nervous system (CNS) to regulate the exercise pace as much as necessary for the athlete's pain to become bearable, allowing the task to be completed [4, 10]. Generally, researchers agree that the perceived discomfort of fatigue occurs just before the occurrence of physiological limitations in the muscles. However, the precise role of the CNS in detecting, causing, or even canceling the perception of fatigue remains unclear, and there is a gap in the literature regarding this phenomenon [12, 18]. This perspective does not come from the physiological system, it only emphasizes that effort regulation is consciously or unconsciously commanded by the brain. Thus, greater knowledge regarding the exercise operating mechanisms may bring about new approaches to explore the phenomenon of pacing in exercise [4, 10, 12, 16, 18]. Furthermore, if the pacing phenomenon acts as a regulatory system that allows the effort to be completed in the context of training and competition, factors such as previous experience and perfect knowledge of the task appear to be fundamental to success [4, 10, 16]. In fact, prior knowledge about the activity to be performed (i.e., duration, importance, demands of the game) is assumed to be a fundamental point to support a psychophysiological approach to the phenomenon of pacing [9, 18, 22]. That is how athletes are able to self-regulate their own performance during exercise [19].

Athletes' previous knowledge about the duration of the task can induce changes in the performance, as demonstrated in ultra-marathon running [23]. In addition, the circumstance in which fatigue is expressed is another interesting factor for investigation, although little explored. The sports modalities' specificities are important and help to interpret the results and sensations of perceived fatigue [16, 18]. This is because the type of required effort differs between modalities (i.e., collective or individual) [19]. Upon that, different reflections about the mechanisms of fatigue are necessary. It is also important to note that there is a research gap considering this subject in team sports, since the existing studies on the phenomenon of pacing are mostly related to endurance sports [16, 18, 19]. This may be related to the intrinsic and specific characteristics of each team sport. It can create issues in the

analysis, possibly provoking a propensity for the study of specific variables, which could be considered as a reductionist approach to the problem. That said, based on the lack of identified research, it becomes important to enhance knowledge about the mechanisms of fatigue in sport.

### **2. The fatigue in sport and exercise**

As presented above, there are several concepts about fatigue; nevertheless, it can be defined as "extreme tiredness after effort; reduction in the efficiency of a muscle or organ after prolonged activity" [24]. Previous research has shown that the fatigue phenomenon is more complex and has a broader spectrum of parameters, and more comprehensive concepts are necessary. The wide range of investigations carried out had a beneficial impact in expanding the available definitions of fatigue. It is difficult to accurately determine the development of fatigue as a concept in the sports sciences [1]. At the beginning of the twentieth century, two phenomena were identified that helped to characterize fatigue; (i) the reduction of muscle strength; (ii) tiredness as a sensation [25]. In fact, over time, there have been variations in the definitions of fatigue in the field of sports sciences such as; (i) "the difficulty in maintaining the necessary or expected strength" [26]; (ii) "the decreased ability to generate maximum strength" [27]; (iii) "a reversible state of strength depression, including a lower rate of strength increase and slower relaxation" [28]. That said, it is difficult to gather consensus on a single definition of fatigue. This is problematic when trying to consistently compare and interpret the different concepts. However, these inconsistencies allow the debate on the topic to be constantly open, mainly on its usefulness and applicability in the different modalities. Moreover, reaching an early definition of fatigue, which is only accepted for lack of alternatives, may help to reiterate the complexity of the fatigue phenomenon [1, 2].

#### **2.1 Peripheral fatigue and central fatigue**

Fatigue in sport and exercise can theoretically be categorized into two types (i.e., peripheral fatigue and central fatigue) [29, 30]. Peripheral fatigue is related to decreased muscle strength production caused by processes distal to the myoneural junction [31]. The concept of peripheral fatigue originated from studies carried out in the 1920s [32–34]. These studies led to the conclusion that, just before the end of the exercise, the muscles' requirement for oxygen exceeded the heart's ability to supply that oxygen. This process develops an anaerobiosis in the muscles in activity, causing the accumulation of carboxylic acid. Due to this change in the intramuscular environment, the continuation of the contraction becomes impossible, and therefore, the muscles reach a state of failure. These pioneering studies claim that fatigue is the result of increased intramuscular carboxylic acid, which is produced within the body only under anaerobic conditions [1]. These conclusions were supported by the fact that exercise performance improves with oxygen inhalation [35]. Furthermore, the authors also concluded that the main limiting factor in exercise tolerance was the heart's ability to pump blood to active muscles. Thus, fatigue is possibly a consequence of the heart's inability to supply oxygen and the cardiovascular system not being ready to remove waste through the oxidation of active muscles [1]. Based on this perspective, the cardiovascular system appears to restrict performance due to the difficulties induced by the breakdown of the supply of blood, nutrients, and oxygen to the active muscles [36, 37]. Insufficiencies in the heart's pumping capacity, as well as the reduced density of capillaries, can limit the amount of ventilated blood that reaches the muscles, consequently limiting

performance. This theory, known as the anaerobic/cardiovascular/catastrophic model of human performance exercise, predicts the failure of cardiac homeostatic balance [32–34]. Although this model has been criticized, this theory has prevailed and is probably still the most cited theory of exercise-induced fatigue, but some limitations are known and have been the subject of previous analysis.

An investigation [38] concluded that the maximum cardiac output limit of the heart was reached via the evolution of myocardial ischemia, when the heart loses the ability to pump more blood because it has reached the rate of oxygen consumption limit. Additionally, this investigation showed that obtaining a higher flow rate limits the blood flow to the muscles in activity, inflicting the anaerobiosis and limiting the capacity to remove lactic acid. The increase in the concentration of lactic acid directly influences the contractile capacity of muscle fibers, presenting an association with mechanisms that induce muscle fatigue. In addition, the same authors also considered the prospect that myocardial ischemia, as a result of reaching maximum cardiac output, which is a limiting factor in exercise and a threat to the integrity of cardiac tissue, can be avoided due to the existence of a governor, located in the brain or the heart, which protects from possible damages.

Even so, there is still a lack of scientific evidence showing that muscles' energetic profile actually becomes anaerobic during exercise and close to fatigue; or even that oxygen consumption or cardiac output consistently reaches a peak. This peak would be a requirement for its implication in fatigue during maximal intensity exercises [1]. In addition, a healthy heart, even during maximal intensity exercises, does not assume the existence of myocardial ischemia. Upon that, the hypothesis about an existing regulator in the brain or in the heart lacks scientific support. The model also suggests that peripheral fatigue events would lead the brain to recruit additional muscle fibers in an effort to help these fatigued fibers. Thus, to maintain the intensity of the exercise, it will be necessary to engage more and more available muscle fibers at their maximum capacity. However, this prediction is contradictory to other aspects of the model, as the continuous muscular recruitment should aggravate the metabolic crisis that the model foresees to be the reason for the end of the exercise [29, 30]. The main issue of this theory is that fatigue is a catastrophic event, sustained by an assertive response, leading to the total failure of the active muscles to continue to produce strength. However, catastrophic muscle or organ failure clearly does not occur in exhaustion for healthy individuals during any type of exercise [1]. Additionally, for this model, fatigue is shown from the perspective of an exhaust failure system. However, skeletal muscle fibers are never fully recruited during exercise; muscle adenosine triphosphate (ATP) never falls below 60% of resting levels, and glycogen concentration decreases but is not depleted during exercise [39]. Even more, in many circumstances, fatigue occurs before high concentrations of metabolites, such as lactate, H<sup>+</sup> , extracellular K<sup>+</sup> , without disturbances in muscle Ca2+ kinetics and without high core temperatures or significant hypohydration [40].

All these observations contradict the prediction of the peripheral linear catastrophic model, which states that some type of homeostatic failure should occur to cause fatigue. However, the importance of the model peripheral component remained. In the Hill's model (presented in the beginning of the twentieth century) [32, 34], the physiological aspect is accepted; although it proves unable to respond to the complexity of the fatigue phenomenon in a broader scope. The model considers a refutable role of the brain to disrupt myocardial ischemia; however, it ignores the role of neural control over all physiological systems [1]. While peripheral fatigue occurs through processes outside the CNS, it is believed that the origin of central fatigue lies in the CNS, with the loss of muscle strength occurring through processes proximal to the myoneural junction. Specifically, this refers to sites within the brain, spinal nerves, and motor neurons, and

#### *The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

it is related to instances in which the CNS presents a decrease in neural impulse to the muscle [41]. Central fatigue is perceived as the failure of the central nervous system to drive the muscle to its maximum, resulting in some loss of strength [42]. The decrease in strength/performance production [43] is largely justified within the central nervous system (brain and spine—central) and anywhere outside the central nervous system (e.g., peripheral muscle). Comparatively, little research has been done on the role of the CNS in fatigue until the last decades [44], which is curious considering that it has long been suspected of being a central component of fatigue [1]. The impact of the research findings on peripheral fatigue and the limitations to measure central fatigue due to the lack of objective and direct tools explain the current research gap in this field. In fact, central fatigue is usually only accepted when experimental findings do not support any peripheral cause of fatigue [44].

The central nervous system plays an important role in maintaining homeostasis [45]. Therefore, the motor component of the brain is responsible for the production of motor drive and the recruitment of motor units during exercise [45]. Thus, the brain takes control of cognition and recognition of physical sensations that are perceived as fatigue. Perceived fatigue results from exercise, and it is felt as a "sensation" (common/frequent) during exercise. The workload can create a sensation so intense that it is perceived as a need to reduce the strength to successfully complete the activity (i.e., pacing). In some cases, it may be necessary to stop exercising altogether if the sensations felt are too intense [46]. For this reason, the various stages that athletes go through during exercise are indicative that physiological mechanisms are not the only ones responsible for regulating exercise intensity. Also, humans exhibit an anticipated aspect of exercise regulation, possibly with regard to factors such as perception of the effort required for the task, and motivation [1]. Physical and biochemical changes during exercise are physiological aspects that naturally must be considered. However, perceived fatigue should also be carefully considered due to the influence in behavior/performance. Therefore, it is important to study perceived fatigue with similar importance [1, 45, 46]. Considering that the catastrophic failure of the system does not occur, there is a possibility for the appearance of a psychophysiological model [16].

#### **2.2 Psychophysiological evidence**

The inability of the peripheral and central fatigue processes to convincingly explain sport and exercise fatigue allowed the researcher to predict explanations for the fatigue phenomenon [29, 30]. An interesting perspective that has recently emerged is the concept of the brain acting as a central regulator of the exercise performance [4].

As mentioned above, the peripheral catastrophic model remains the dominant model, and this is essentially due to the modifications made to the Hill's model [32–34] with the incorporation of factors such as energy supply and depletion [47]. In fact, the introduction of energy supply to the model suggested that high-intensity exercise was due to the inability to provide ATP at rates fast enough to maintain the exercise high intensities [47]. Based on this model, the training process and the diet generate an increase in the storage capacity (for example, glycogen), and the increased use of metabolic substrates during exercise may result in a higher production capacity of ATP. Controversially, in the variation of energy depletion of the model, it was suggested that the amount of carbohydrates was the limiting factor [47]. This is probably due to the finding that fatigue during prolonged exercise is strongly associated with significant reductions in the liver and muscle glycogen [37, 48]. In addition, improvements in tolerance to hypoglycemia as a result of exercise allow exercise to continue [48]. Nevertheless, none of the models are fully accepted.

The concept of the existence of a central regulator, responsible for regulating muscle metabolic activity and performance via peripheral afferent feedback, was reintroduced by Ulmer in 1994 [49]. The author suggested that this central regulator anticipates the end point of an exercise. Anticipation was based on previous experience of the same exercise or knowledge of the duration of the task, which regulates the metabolic demand from the beginning of the exercise. This allows the task to be completed without catastrophic physiological failure. The control of the metabolic demand regulated by the brain is called teleanticipation. This central governor evidenced by Ulmer [49] has been analyzed in several research studies [40, 41, 45, 50, 51]. These studies were the starting point for the appearance of the so-called anticipatory feedback model of exercise regulation [4], which constitutes a psychophysiological approach of the fatigue phenomenon. This model assumes that the exercise is self-regulated from the beginning by the athletes based on previous experiences, knowledge of the expected distance, duration of the current exercise, and afferent physiological feedback regarding some variables (i.e., muscle glycogen levels, skin and body temperature) [40, 41]. Processing this information allows the brain to predict and regulate the most appropriate exercise intensity allowing an optimal performance without serious homeostatic disruptions [51]. These predictions are similar to the model that classified the perceived effort (RPE). Moreover, the physical, mechanical, and biomechanical variables required during exercise are constantly monitored by the brain, and it is through this afferent feedback that the athlete's conscious RPE arises. During exercise, conscious RPE is continuously compared with standard RPE and will progressively increase and reach its desired maximum at the expected end of the exercise. The intensity of the exercise is modulated according to an acceptable level that the brain interprets as tolerated, taking into account the continuous comparison between the standard RPE and the real, conscious RPE [50, 52].

The anticipatory feedback model defends that fatigue, instead of a physical state, is a conscious sensation generated from the interpretation of subconscious regulatory processes [45, 51]. It is also suggested that RPE is not simply a direct manifestation of afferent physiological feedback, but that it also plays an important role in preventing excessive intensity of exercise duration. It acts as the motivating element behind the athlete's decision to completely stop the exercise or adjust the intensity to guarantee its completion without significant or harmful physical damage [4]. Despite the lack of experimental research on the subject, some phenomena support this fatigue model [53].

#### **2.3 The concept of pacing**

Recently, numerous studies investigated the interaction between cognition and sports performance [54, 55]. The pacing behavior has been widely identified as an essential component of success in many sports and is directly related to a high spectrum of cognitive skills [56–61]. Pacing has been described as a multifaceted process that requires a set of decision-making in which athletes need to decide when and how they will distribute their available energy throughout an exercise [60, 62, 63].

The ideal pacing behavior in time trial competitions is characterized by: the balance between the quick start to make optimal use of energy resources; preventing negative changes in performance resulting from early fatigue; and inefficient energy losses associated with speed fluctuations during the race [64]. To determine the most appropriate pacing behavior, a set of variables (i.e., biomechanical, physiological, psychological, and environmental) [46] are crucial to maintain internal homeostasis [65] and to avoid premature burnout [66, 67].

#### *The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

The concept of pacing supports the anticipatory feedback model and cannot be investigated from a purely physiological perspective [62]. The effort distribution is part of the exercise, which suggests that voluntary behavior (effort) may limit performance rather than the absolute capacity of a single physiological system [46]. The role of a central process and how it will be executed must be considered when developing a pacing behavior.

A heuristic model of decision-making was developed to integrate the theories of decision-making and pacing, in which heuristics were considered intuitions that require low cognitive demands [20]. However, the heuristic decision-making model did not consider the connection between perception and action that takes place in tactical pacing environments, in which some actions depend on the opponents' behavior [20, 63, 68]. Later, a detailed explanation of the pacing phenomenon emerged and was presented as a behavioral result of the decision-making process and included human-environment interactions. Pacing leads athletes to make decisions in complex and demanding environments, where they are successively encouraged to modify, choose, and evaluate their behavior [69]. The brain and cognitive processes interact and act as an information processing system [70].

The competitive environments such as the stage of competition [71], the importance of competition, and the probability of qualifying time [72] can modify the athlete's pacing behavior. During the competition, opponents are the most common affordances. However, there are other environmental factors that can influence the pacing behavior of athletes. Factors such as music [73], performance feedback [74], and weather conditions [75] can lead to voluntary reductions in exercise intensity. These reductions in intensity occur before any real physical need to do so and before the performance compromise occurs as a result of any failure of the physical system [76, 77].

The presence of pacing behavior in sports is important regarding the view of the anticipatory regulation proposed for the performance of the exercise. It seems that athletes perform the exercise less effectively when performing an exercise that is unfamiliar and whose demands are not entirely clear [78, 79].

Changes in exercise intensity during resistance exercises were reported in the initial phase of exercise before any peripheral physiological cause of fatigue [80]. These data suggest that the modification of exercise intensity (pacing) during exercise occurs in anticipation and not as a result of stress or failure of the physiological system [62]. Thus, the pacing strategies may be used to guarantee the completion of the exercise without any physical damage. The previous experience and knowledge of the demands of the exercise will play an important role [62].

The use of pacing strategies during exercise can provide support for components of the anticipatory feedback model [81, 82] as well as refute aspects of the peripheral linear catastrophic model. During the self-regulated exercise, it is observed that the pacing behavior depends on the environment, the demands, and objectives of the exercise and the afferent physiological feedback [83]. This is in agreement with the anticipatory feedback model. If an athlete's pacing behavior is determined by the accumulation of metabolic products or depletion of energy reserves, as predicted by the peripheral linear catastrophic model, athletes would always begin exercising at an unsustainable pace [49, 74, 84–86]. Gradually, they would slow down due to the negative effect of peripheral variables, which is not actually put into practice. The peripheral linear catastrophic model states that the only possible stimulation behavior in exercise is linear [27, 29, 30, 45, 67]. The model simply does not allow the existence of other strategies. However, the evidence for these other strategies is abundant [16, 19].

Previous exercise knowledge/experience can be important information that the brain uses to select a more appropriate exercise intensity. Research on the use of pacing strategies in exercises has confirmed that the precision ability of pacing is improved with training and experience [84, 87].

#### **2.4 The end spurt phenomenon**

The end spurt phenomenon supports the anticipatory feedback model [23] and is characterized by a substantial increase in the intensity of the exercise when it approaches the end. This model disregards the effort during the entire exercise. Throughout the exercise, there is often a level of uncertainty about the precise end point of the exercise period and the type of effort that will need to be spent until the end. These aspects are responsible for influencing the athlete's pace and can, at any time, force the athlete to make changes in the pace, which cannot be predicted before exercise. This type of uncertainty can result in the maintenance of a motor unit and metabolic reserve throughout the exercise [4, 82, 88]. The athlete cannot be sure of what can happen in the rest of the exercise period and (unconsciously) retains some type of reserve to remain prepared to respond to any potential physical challenges. This may allow the accomplishment of the exercise without significant interruption of homeostasis. When the end of the exercise approaches, the uncertainty decreases and the accumulated reserve is no longer accurate, so that the athlete can significantly increase the metabolic demand increasing speed/power. Actually, this is a possible evidence that fatigue is not caused by the inability of muscles to produce strength [23].

#### **2.5 The knowledge about the exercise duration**

Knowledge of exercise duration as a regulator of exercise performance plays an important role and is supported by investigations about the knowledge or no knowledge of the task duration [1, 79, 89–91]. This type of research is usually called "deception," in which participants believe that the exercise will last for a certain length of time; however, at the end of that period, they are asked to continue exercising. In one of the first researches on the topic [90], participants were asked to run on a treadmill at 75% of their maximum speed. However, in the first phase, they were asked to run for 20 min and were interrupted after 20 min. In a second phase, they were asked to run for 10 min, and at the end of this period, they were asked to run for 10 min more. In a third phase, they were asked to run, but were not told for how long (they were stopped after 20 min). All phases were performed at the same running speed and lasted 20 min. The results indicated that the participants' RPE had increased significantly between 10 and 11 min in the 10 min deception. The deception occurred immediately after revealing the information that the participants were required to continue the exercise for a longer time. These changes in the perception of effort and pleasure occurred despite the fact that there were no changes in running speed or in physiological responses to the exercise period. The significant increase in RPE after the participants were asked to prolong the exercise was also found in another research with similar protocols [91], reporting that the effect also increased in the last minutes of exercise, probably because the participants were aware that the exercise was close to ending. These findings are related to the end spurt phenomenon. An increase in feelings of pleasure at the end of the exercise may explain the end spurt happening. Furthermore, there was no increase in the effect on the trial when the participants did not know the duration of the exercise, and the effect continued to decrease throughout the trial [91].

A recent study [79] assessed how the manipulation of knowledge about the duration of a training task restricts the pace and tactical behavior of soccer players during the performance of small-sided games (SSG). Players were instructed to play the SSG for 10 min, but after completing the 10-min game, they were asked to play for another 10 min, and in another situation, they were previously informed that they would play for 20 min. The results indicate that the first 10 min of each

#### *The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

scenario had a greater physical impact regardless of the initial information that had been revealed. During that time, tactical behavior has also showed greater variability. In addition, there was an increase in distance from teammates during the second 10-min period in which the duration was fully known. That may be due to a smaller pacing behavior. This study showed that prior knowledge of the duration of the task led to different physical and tactical behaviors of the players, and these data have been corroborated by other investigations [92–94]. These findings confirm the possibility of changes in the pacing patterns of the players, as a consequence of the knowledge of the duration of the task that leads to consider the possibility of the nonlinearity of the fatigue effect previously reported in other studies [23, 95]. These data suggested that the knowledge of the exercise duration assumes a fundamental role for the adequate regulation of the exercise performance, as in the anticipatory feedback model. The increases seen in athletes' RPE when deception is revealed may reflect an interruption of the feed-forward/feedback mechanism, which is fundamental to RPE as suggested by other studies [4, 96]. Moreover, it is also verified that both the RPE and the physiological responses (oxygen consumption, heart rate) present lower values when the duration of the exercise is not known compared with the moments when the duration is known. However, no significant differences in exercise intensity were found [90, 91]. Thus, these responses may reflect a subconscious improvement in the effort economy in order to retain energy due to the unknown duration of the exercise period. That said, knowledge of the end point of the exercise plays a great role in the perceptual and physiological responses to that same period of exercise [97]. This fact is further evidenced by the observation that the responses of the RPE to the exercise are robust when the duration of the exercise is known, even when no information is provided to the athlete about the exercise [85].

Research results related to exercise duration prior knowledge provide additional evidence on some processes by which athletes can retain physiological reserves during exercises of uncertain duration [91]. These findings provide support for a central role of the CNS in regulating exercise performance [98], probably to ensure the maintenance of homeostasis and the guarantee of an emergency "reserve" of energy/physical capacity [12, 91].

#### **2.6 The relationship between RPE and performance**

The perceived effort during the exercise is reflected in changes in the sensation to regulate the athlete's physical integrity [99]. The output (perceived effort) is based on a combination of sensory inputs and cognitive processes [100]. One of the most accepted parameters during the exercise is the RPE response, which represents a sum of afferent feedback signals [100] and supra-spinal mechanisms [86]. Based on the principles of self-regulation, it is suggested that the use of RPE methods to monitor training presents itself as an effective tool for all types of exercise.

RPE has been recognized as a valid and reliable indicator of the level of physical effort by the American College of Sports Medicine. The RPE characterizes the conscious perception of the effort experienced during the exercise, which gives it a considerable practical value for the athlete. Thus, exercises that require higher levels of energy expenditure and physiological effort usually present higher RPE. Furthermore, previous studies [4, 20, 63] reported the existence of a relationship between variations in the RPE during the exercise and the duration of the exercise, which highlights the assumptions of the anticipatory feedback model. They also suggest that the RPE is effectively a crucial regulator of the exercise performance. Additionally, the suggestion that RPE may vary from the beginning of the exercise

through changes in the ambient temperature and intensity of the exercise [4, 101] before effective physiological changes supports the role of the RPE in anticipatory regulation of the exercise. This evidence suggests that RPE may not be a direct reflection of the athlete's physiological state during exercise, but rather an anticipatory sensory regulator of exercise performance. Upon that, the RPE may undergo variations during the exercise in anticipation of the occurrence of physiological changes and not because of these changes. This supports the fact that the nature of fatigue should be considered as previously reported [90].

#### **2.7 Other approaches**

An interesting alternative to the brain regulation model has been proposed [11]. In this approach, there is an acceptance that the brain regulates muscle recruitment and limits performance; however, there is also reticence about the need for a central regulatory governor. This perspective suggests that the search for a central governor in the brain's subconscious may be similar to current reductionist approaches that search for a single cause of fatigue. The anticipatory feedback model states that a central regulator in the brain maintains subconscious control over skeletal muscle fibers recruitment during exercise. However, the presence of a single region of the brain, exclusively dedicated to regulating exercise performance, is highly unlikely. It is antagonistic regarding everything known about the functioning of the brain as an integrated organ of maximum complexity where each region contributes to the general functioning of the brain [62]. This may also explain why the specific region of the brain considered the central governor was not found. This model also states that the perception of effort is fundamental to demote the individual to continue in dangerous levels of conscious exercise that can be theoretically redundant. This is because the subconscious regulator will prevent athletes from exercising at a dangerous level regardless of the motivation that may exist to continue. However, another author [4] states that the anticipatory feedback model could exist without the perception of effort being considered. An alternative suggestion was given with a simplified model that helps to explain some of the evidence attributed to the anticipatory feedback model. This model determines that the end of the exercise occurs when the effort required to continue exercising is similar to the maximum effort that the individual is willing to provide or when the individual believes that he/she has provided a true maximum. Therefore, the subject realizes that it is not viable to continue exercising [11].

The increase in the effort that the individual is willing to put into the exercise will improve his tolerance, as long as it does not exceed what the individual understands as his maximum effort [11]. The importance of the perception of effort remains clear, but the existence of a central regulator in the brain is not necessary. Additionally, it has been suggested that the gradual increase in RPE over time and at different rates in response to changes in exercise intensity and ambient temperature can be explained by other factors; a central regulator that uses perceived exertion as a mechanism of security would be an insufficient explanation. The RPE is generated through signals originating in the CNS, specifically referring to prolonged submaximal exercises with a constant workload [31]. These data are highlighted and refuted in other investigations [10, 11]. It was demonstrated that the RPE suffered changes almost since the beginning of the exercise as a result of the verified differences in the exercise intensity and in the ambient temperature. In addition, it is important to note that the increase in the CNS motor commands could not happen without afferent sensory feedback, which is similar to the anticipatory feedback model [10].

*The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

### **3. Conclusion**

This chapter provided a broader understanding of the cognitive basis of the psychophysiological phenomenon during the exercise, bringing together concepts such as pacing behavior, decision-making, self-regulation of effort, prior knowledge of the duration of the task, and perception of effort. This reinforced the role and contribution of the cognitive component in the pacing behavior. Furthermore, the development of fatigue during exercise seems to result from a complex interaction between the physical and psychophysiological components responsible for changes in the exercise intensity, and it can be pointed out that central and peripheral fatigue can help to exercise the intensity regulation at the beginning of a rhythmic self-paced. Also, the perceived responses may be of higher importance to control the intensity of the exercise, especially in the final phase, this results from the attempt to retain a reserve of energy that allows maximum effort in the end. About the prior knowledge about the task duration, it can create a greater capacity to regulate the effort, leading athlete to better manage energy reserves throughout the exercise. It would be also interesting to continue to analyze the impact of psychophysiological factors on the perception and regulation of fatigue by team sports players according to recent studies of psychophysiological fatigue.

#### **Acknowledgements**

This work is supported by national funding through the Portuguese Foundation for Science and Technology, I.P., under the project UID04045/2020.

### **Conflict of interest**

The authors declare no conflict of interest.

*Exercise Physiology*

#### **Author details**

Ricardo Ferraz1,2\*, Pedro Forte2,3,4, Luís Branquinho3 , José E. Teixeira2,5, Henrique Neiva1,2, Daniel A. Marinho1,2 and Mário C. Marques1,2

1 University of Beira Interior, Covilhã, Portugal

2 Research Center in Sports Sciences Health Sciences and Human Development, Covilhã, Portugal

3 Douro Higher Institute of Educational Sciences, Penafiel, Portugal

4 Instituto Politécnico de Bragança, Bragança, Portugal

5 University of Trás-os-Montes e Alto Douro, Vila Real, Portugal

\*Address all correspondence to: ricardompferraz@gmail.com

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

#### **References**

[1] Noakes TD. Fatigue is a brain-derived emotion that regulates the exercise behavior to ensure the protection of whole body homeostasis. Frontiers in Physiology. 2012;**3**:82. DOI: 10.3389/ fphys.2012.00082

[2] Marino FE, Gard M, Drinkwater EJ. The limits to exercise performance and the future of fatigue research. British Journal of Sports Medicine. 2011;**45**: 65-67. DOI: 10.1136/bjsm.2009.067611

[3] Smith MR, Marcora SM, Coutts AJ. Mental fatigue impairs intermittent running performance. Medicine and Science in Sports and Exercise. 2015;**47**:1682-1690. DOI: 10.1249/ MSS.0000000000000592

[4] Tucker R. The anticipatory regulation of performance: The physiological basis for pacing strategies and the development of a perceptionbased model for exercise performance. British Journal of Sports Medicine. 2009;**43**:392-400. DOI: 10.1136/ bjsm.2008.050799

[5] Halson SL. Monitoring training load to understand fatigue in athletes. Sports Medicine. 2014;**44**:139-147. DOI: 10.1007/s40279-014-0253-z

[6] Borresen J, Ian LM. The quantification of training load, the training response and the effect on performance. Sports Medicine. 2009;**39**:779-795. DOI: 10.2165/ 11317780-000000000-00000

[7] Russell S, Jenkins D, Smith M, Halson S, Kelly V. The application of mental fatigue research to elite team sport performance: New perspectives. Journal of Science and Medicine in Sport. 2019;**22**:723-728. DOI: 10.1016/j. jsams.2018.12.008

[8] Jones CM, Griffiths PC, Mellalieu SD. Training load and fatigue marker

associations with injury and illness: A systematic review of longitudinal studies. Sports Medicine. 2017;**47**:943-974

[9] Balagué N, Hristovski R, Almarcha MDC, Garcia-Retortillo S, Ivanov PC. Network physiology of exercise: Vision and perspectives. Frontiers in Physiology. 2020;**11**:1607

[10] David Noakes T, Tucker R. Do we really need a central governor to explain brain regulation of exercise performance? A response to the letter of Dr. Marcora. European Journal of Applied Physiology. 2008;**104**:933-935. DOI: 10.1007/s00421-008-0842-3

[11] Marcora SM. Do we really need a central governor to explain brain regulation of exercise performance? European Journal of Applied Physiology. 2008;**104**:925-929. DOI: 10.1007/s00421-008-0818-3

[12] Swart J, Lindsay TR, Lambert MI, Brown JC, Noakes TD, Robert Lindsay T, et al. Perceptual cues in the regulation of exercise performance—physical sensations of exercise and awareness of effort interact as separate cues. British Journal of Sports Medicine. 2012;**46**:42- 48. DOI: 10.1136/bjsports-2011-090337

[13] Kalkhoven JT, Watsford ML, Coutts AJ, Edwards WB, Impellizzeri FM. Training load and injury: Causal pathways and future directions. Sports Medicine. 2021;**51**:1137-1150

[14] Djaoui L, Haddad M, Chamari K, Dellal A. Monitoring training load and fatigue in soccer players with physiological markers. Physiology & Behavior. 2017;**181**:86-94

[15] Mujika I, Halson S, Burke LM, Balagué G, Farrow D. An integrated, multifactorial approach to periodization for optimal performance in individual and team sports. International Journal

of Sports Physiology and Performance. 2018;**13**:538-561

[16] Edwards A, Polman R. Pacing in Sport and Exercise: A Psychophysiological Perspective. New York: Nova Science Publishers; 2012. Available from: https:// researchonline.jcu.edu.au/22922/ [Accessed: January 10, 2021]

[17] Gabbett TJ, Walker B, Walker S. Influence of prior knowledge of exercise duration on pacing strategies during game-based activities. International Journal of Sports Physiology and Performance. 2015;**10**:298-304. DOI: 10.1123/ijspp.2013-0543

[18] Waldron M, Highton J. Fatigue and pacing in high-intensity intermittent team sport: An update. Sports Medicine. 2014;**44**:1645-1658. DOI: 10.1007/ s40279-014-0230-6

[19] Thompson K. Pacing: Individual Strategies for Optimal Performance. Champaign: Human Kinetics; 2014

[20] Renfree A, Martin L, Micklewright D, St Clair Gibson A. Application of decision-making theory to the regulation of muscular work rate during self-paced competitive endurance activity. Sports Medicine (Auckland, NZ). 2014;**44**:147-158. DOI: 10.1007/s40279-013-0107-0

[21] Marcora SM, Staiano W. The limit to exercise tolerance in humans: Mind over muscle? European Journal of Applied Physiology. 2010;**109**:763-770

[22] Ferraz R, Gonçalves B, Van Den Tillaar R, Jiménez Sáiz S, Sampaio J, Marques MC. Effects of knowing the task duration on players' pacing patterns during soccer small-sided games. Journal of Sports Sciences. 2018;**36**:116-122. DOI: 10.1080/24733938.2017.1283433

[23] Millet GY. Can neuromuscular fatigue explain running strategies and performance in ultra-marathons?: The flush model. Sports Medicine (Auckland, NZ). 2011;**41**:489-506. DOI: 10.2165/11588760-000000000- 00000

[24] Online OE. Help|Oxford English Dictionary 2010. Available from: https://public.oed.com/help/ [Accessed: January 10, 2021]

[25] Mosso A. Fatigue. 2nd ed. London/ New York: Swan Sonnenschein & Co. Ltd; 1906

[26] Edwards RH. Human muscle function and fatigue. Ciba Foundation Symposium. 1981;**82**:1-18. DOI: 10.1002/9780470715420.ch1

[27] Bigland-Ritchie B, Furbush F, Woods JJ. Fatigue of intermittent submaximal voluntary contractions: Central and peripheral factors. Journal of Applied Physiology. 1986;**61**:421-429. DOI: 10.1152/jappl.1986.61.2.421

[28] Fitts RH, Holloszy JO. Effects of fatigue and recovery on contractile properties of frog muscle. Journal of Applied Physiology Respiratory Environmental and Exercise Physiology. 1978;**45**:899-902. DOI: 10.1152/ jappl.1978.45.6.899

[29] Carroll TJ, Taylor JL, Gandevia SC. Recovery of central and peripheral neuromuscular fatigue after exercise. Journal of Applied Physiology. 2017;**122**:1068-1076

[30] Zając A, Chalimoniuk M, Maszczyk A, Gołaś A, Lngfort J. Central and peripheral fatigue during resistance exercise–A critical review. Journal of Human Kinetics. 2015;**49**:159

[31] Ament W, Verkerke G. Exercise and fatigue. Sports Medicine. 2009;**39**: 389-422. DOI: 10.2165/00007256- 200939050-00005

[32] Hill AV, Long CNH, Lupton H. Muscular exercise, lactic acid and the *The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

supply and utilisation of oxygen—Parts VII–VIII. Proceedings of the Royal Society of London Series B, Containing Papers of a Biological Character. 1924;**97**:155-176. DOI: 10.1098/ rspb.1924.0048

[33] Hill AV, Lupton H. Muscular exercise, lactic acid, and the supply and utilization of oxygen. QJM. 1923;**os-16**:135-171. DOI: 10.1093/qjmed/ os-16.62.135

[34] Hill AV, Long CNH, Lupton H. Muscular exercise, lactic acid, and the supply and utilisation of oxygen.—Parts IV-VI. Proceedings of the Royal Society of London Series B, Containing Papers of a Biological Character. 1924;**97**:84-138

[35] Hill L, Flack M. The influence of oxygen inhalations on muscular work. The Journal of Physiology. 1910;**40**:347- 372. DOI: 10.1113/jphysiol.1910. sp001374

[36] Bassett DR, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Medicine and Science in Sports and Exercise. 2000;**32**:70-84. DOI: 10.1097/00005768-200001000- 00012

[37] Fitts RH. Cellular mechanisms of muscle fatigue. Physiological Reviews. 1994;**74**:49-94. DOI: 10.1152/ physrev.1994.74.1.49

[38] Raskoff WJ, Goldman S, Cohn K. The "Athletic Heart": Prevalence and physiological significance of left ventricular enlargement in distance runners. JAMA: The Journal of the American Medical Association. 1976;**236**:158-162. DOI: 10.1001/ jama.236.2.158

[39] Rauch HGL, St. Clair Gibson A, Lambert EV, Noakes TD. A signalling role for muscle glycogen in the regulation of pace during prolonged exercise. British Journal of Sports

Medicine. 2005;**39**:34-38. DOI: 10.1136/ bjsm.2003.010645

[40] Noakes TD. Physiological models to understand exercise fatigue and the adaptations that predict or enhance athletic performance. Scandinavian Journal of Medicine and Science in Sports. 2000;**10**:123-145. DOI: 10.1034/j. 1600-0838.2000.010003123.x

[41] Noakes TD, St Clair Gibson A, Lambert EV. From catastrophe to complexity: A novel model of integrative central neural regulation of effort and fatigue during exercise in humans: Summary and conclusions. British Journal of Sports Medicine. 2005;**39**:120-124. DOI: 10.1136/ bjsm.2003.010330

[42] Taylor JL, Todd G, Gandevia SC. Evidence for a supraspinal contribution to human muscle fatigue. Clinical and Experimental Pharmacology & Physiology. 2006;**33**:400-405. DOI: 10.1111/j.1440-1681.2006.04363.x

[43] Merton PA. Voluntary strength and fatigue. The Journal of Physiology. 1954;**123**:553-564. DOI: 10.1113/ jphysiol.1954.sp005070

[44] Davis JM, Bailey SP. Possible mechanisms of central nervous system fatigue during exercise. Medicine and Science in Sports and Exercise. 1997;**29**:45-57. DOI: 10.1097/ 00005768-199701000-00008

[45] Lambert EV, St Clair Gibson A, Noakes TD. Complex systems model of fatigue: Integrative homoeostatic control of peripheral physiological systems during exercise in humans. British Journal of Sports Medicine. 2005;**39**:52-62. DOI: 10.1136/bjsm.2003. 011247

[46] Noakes TD. Time to move beyond a brainless exercise physiology: The evidence for complex regulation of human exercise performance. Applied

Physiology, Nutrition and Metabolism. 2011;**36**:23-35. DOI: 10.1139/H10-082

[47] Costill D, Thomason H, Roberts E. Fractional utilization of the aerobic capacity during distance running. Medicine and Science in Sports and Exercise. 1973;**5**:248-252. DOI: 10.1249/ 00005768-197300540-00007

[48] Coggan AR, Coyle EF. Reversal of fatigue during prolonged exercise by carbohydrate infusion or ingestion. Journal of Applied Physiology. 1987;**63**:2388-2395. DOI: 10.1152/ jappl.1987.63.6.2388

[49] Ulmer HV. Concept of an extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiological feedback. Experientia. 1996;**52**:416-420. DOI: 10.1007/BF01919309

[50] St Clair Gibson A, Noakes TD. Evidence for complex system integration and dynamic neural regulation of skeletal muscle recruitment during exercise in humans. British Journal of Sports Medicine. 2004;**38**:797-806. DOI: 10.1136/ bjsm.2003.009852

[51] Crewe H, Tucker R, Noakes TD. The rate of increase in rating of perceived exertion predicts the duration of exercise to fatigue at a fixed power output in different environmental conditions. European Journal of Applied Physiology. 2008;**103**:569-577. DOI: 10.1007/s00421-008-0741-7

[52] Noakes TD, Peltonen JE, Rusko HK. Evidence that a central governor regulates exercise performance during acute hypoxia and hyperoxia. The Journal of Experimental Biology. 2001;**204**:3225-3234

[53] Looft JM, Herkert N, Frey-Law L. Modification of a three-compartment muscle fatigue model to predict peak torque decline during intermittent tasks. Journal of Biomechanics. 2018;**77**:16-25

[54] Clemente FM, Pracą GM, Bredt SDGT, Der Linden CMIV, Serra-Olivares J. External load variations between medium- and large-sided soccer games: Ball possession games vs regular games with small goals. Journal of Human Kinetics. 2019;**70**:191-198. DOI: 10.2478/hukin-2019-0031

[55] Walton CC, Keegan RJ, Martin M, Hallock H. The potential role for cognitive training in sport: More research needed. Frontiers in Psychology. 2018;**9**:1121. DOI: 10.3389/ fpsyg.2018.01121

[56] Wiersma R, Stoter IK, Visscher C, Hettinga FJ, Elferink-Gemser MT. Development of 1500-m pacing behavior in junior speed skaters: A longitudinal study. International Journal of Sports Physiology and Performance. 2017;**12**:1224-1231. DOI: 10.1123/ ijspp.2016-0517

[57] Whitehead AE, Jones HS, Williams EL, Rowley C, Quayle L, Marchant D, et al. Investigating the relationship between cognitions, pacing strategies and performance in 16.1 km cycling time trials using a think aloud protocol. Psychology of Sport and Exercise. 2018;**34**:95-109. DOI: 10.1016/ j.psychsport.2017.10.001

[58] McGibbon KE, Pyne DB, Shephard ME, Thompson KG. Pacing in swimming: A systematic review. Sports Medicine. 2018;**48**:1621-1633. DOI: 10.1007/s40279-018-0901-9

[59] de Koning JJ, Foster C, Bakkum A, Kloppenburg S, Thiel C, Joseph T, et al. Regulation of pacing strategy during athletic competition. PLoS One. 2011;**6**:e15863. DOI: 10.1371/journal. pone.0015863

[60] Abbiss CR, Laursen PB. Describing and understanding pacing strategies during athletic competition. Sports Medicine. 2008;**38**:239-252. DOI: 10.2165/ 00007256-200838030-00004

*The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

[61] Ferraz R, Gonçalves B, Coutinho D, Marinho DA, Sampaio J, Marques MC. Pacing behaviour of players in team sports: Influence of match status manipulation and task duration knowledge. PLoS One. 2018;**13**: e0192399. DOI: 10.1371/journal. pone.0192399

[62] Edwards AM, Polman RCJ. Pacing and awareness: Brain regulation of physical activity. Sports Medicine. 2013;**43**:1057-1064. DOI: 10.1007/ s40279-013-0091-4

[63] Smits BLMM, Pepping GJ, Hettinga FJ. Pacing and decision making in sport and exercise: The roles of perception and action in the regulation of exercise intensity. Sports Medicine. 2014;**44**:763-775. DOI: 10.1007/ s40279-014-0163-0

[64] Stoter IK, Macintosh BR, Fletcher JR, Pootz S, Zijdewind I, Hettinga FJ. Pacing strategy, muscle fatigue, and technique in 1500-m speed-skating and cycling time trials. International Journal of Sports Physiology and Performance. 2016;**11**:337-343. DOI: 10.1123/ ijspp.2014-0603

[65] Esteve-Lanao J, Lucia A, de Koning JJ, Foster C. How do humans control physiological strain during strenuous endurance exercise? PLoS One. 2008;**3**:e2943. DOI: 10.1371/ journal.pone.0002943

[66] Baron B, Moullan F, Deruelle F, Noakes TD. The role of emotions on pacing strategies and performance in middle and long duration sport events. British Journal of Sports Medicine. 2011;**45**:511-517. DOI: 10.1136/ bjsm.2009.059964

[67] Gibson ASC, Lambert EV, Rauch LHG, Tucker R, Baden DA, Foster C, et al. The role of information processing between the brain and peripheral physiological systems in pacing and perception of effort. Sports Medicine. 2006;**36**:705-722. DOI: 10.2165/00007256-200636080- 00006

[68] Micklewright D, Kegerreis S, Raglin J, Hettinga F. Will the conscious– subconscious pacing quagmire help elucidate the mechanisms of self-paced exercise? New opportunities in dual process theory and process tracing methods. Sports Medicine. 2017;**47**: 1231-1239. DOI: 10.1007/s40279-016- 0642-6

[69] Corbett J. An analysis of the pacing strategies adopted by elite athletes during track cycling. International Journal of Sports Physiology and Performance. 2009;**4**:195-205. DOI: 10.1123/ijspp.4.2.195

[70] Song J-H. Abandoning and modifying one action plan for alternatives. Philosophical Transactions of the Royal Society B: Biological Sciences. 2017;**372**:20160195. DOI: 10.1098/rstb.2016.0195

[71] Noorbergen OS, Konings MJ, Micklewright D, Elferink-Gemser MT, Hettinga FJ. Pacing behavior and tactical positioning in 500-and 1000-m short-track speed skating. International Journal of Sports Physiology and Performance. 2016;**11**:742-748. DOI: 10.1123/ijspp.2015-0384

[72] Konings MJ, Noorbergen OS, Parry D, Hettinga FJ. Pacing behavior and tactical positioning in 1500-m short-track speed skating. International Journal of Sports Physiology and Performance. 2016;**11**:122-129. DOI: 10.1123/ijspp.2015-0137

[73] Karageorghis CI, Priest DL. Music in the exercise domain: A review and synthesis (Part I). International Review of Sport and Exercise Psychology. 2012;**5**:44-66. DOI: 10.1080/1750984X. 2011.631026

[74] Smits BLM, Polman RCJ, Otten B, Pepping G-J, Hettinga FJ. Cycling in the absence of task-related feedback: Effects on pacing and performance. Frontiers in Physiology. 2016;**7**:348. DOI: 10.3389/ fphys.2016.00348

[75] Teunissen LPJ, De Haan A, De Koning JJ, Daanen HAM. Effects of wind application on thermal perception and self-paced performance. European Journal of Applied Physiology. 2013;**113**:1705-1717. DOI: 10.1007/ s00421-013-2596-9

[76] Dugas JP, Oosthuizen U, Tucker R, Noakes TD. Rates of fluid ingestion alter pacing but not thermoregulatory responses during prolonged exercise in hot and humid conditions with appropriate convective cooling. European Journal of Applied Physiology. 2009;**105**:69-80. DOI: 10.1007/s00421-008-0876-6

[77] Marcora SM, Staiano W, Manning V. Mental fatigue impairs physical performance in humans. Journal of Applied Physiology. 2009;**106**:857-864. DOI: 10.1152/ japplphysiol.91324.2008

[78] Paterson S, Marino FE. Effect of deception of distance on prolonged cycling performance. Perceptual and Motor Skills. 2004;**98**:1017-1026. DOI: 10.2466/pms.98.3.1017-1026

[79] Ferraz R, Gonçalves B, Coutinho D, Oliveira R, Travassos B, Sampaio J, et al. Effects of knowing the task's duration on soccer players' positioning and pacing behaviour during small-sided games. International Journal of Environmental Research and Public Health. 2020;**17**:1-12. DOI: 10.3390/ijerph17113843

[80] RDA A, Silva-Cavalcante MD, Lima-Silva AE, Bertuzzi R. Fatigue development and perceived response during self-paced endurance exercise: State-of-the-art review. European Journal of Applied Physiology. 2021;**121**:687-696. DOI: 10.1007/ s00421-020-04549-5

[81] Sakalidis KE, Burns J, Van Biesen D, Dreegia W, Hettinga FJ. The impact of cognitive functions and intellectual impairment on pacing and performance in sports. Psychology of Sport and Exercise. 2021;**52**:101840. DOI: 10.1016/ j.psychsport.2020.101840

[82] Tee JC, Coopoo Y, Lambert M. Pacing characteristics of whole and part-game players in professional rugby union. European Journal of Sport Science. 2020;**20**:722-733. DOI: 10.1080/17461391.2019.1660410

[83] Pusenjak N, Grad A, Tusak M, Leskovsek M, Schwarzlin R. Can biofeedback training of psychophysiological responses enhance athletes' sport performance? A practitioner's perspective. The Physician and Sportsmedicine. 2015;**43**:287-299. DOI: 10.1080/00913847.2015.1069169

[84] Mauger AR, Jones AM, Williams CA. Influence of feedback and prior experience on pacing during a 4-km cycle time trial. Medicine and Science in Sports and Exercise. 2009;**41**:451-458. DOI: 10.1249/ MSS.0b013e3181854957

[85] Faulkner J, Arnold T, Eston R. Effect of accurate and inaccurate distance feedback on performance markers and pacing strategies during running. Scandinavian Journal of Medicine & Science in Sports. 2011;**21**:e176-e183. DOI: 10.1111/j.1600-0838.2010.01233.x

[86] Marcora S. Perception of effort during exercise is independent of afferent feedback from skeletal muscles, heart, and lungs. Journal of Applied Physiology. 2009;**106**:2060-2062. DOI: 10.1152/japplphysiol.90378.2008

[87] Micklewright D, Papadopoulou E, Swart J, Noakes T. Previous experience influences pacing during 20 km time trial cycling. British Journal of Sports Medicine. 2010;**44**:952-960. DOI: 10.1136/bjsm.2009.057315

*The Performance during the Exercise: Legitimizing the Psychophysiological Approach DOI: http://dx.doi.org/10.5772/intechopen.102578*

[88] Júnior JFCR, Mckenna Z, Amorim FT, Sena AFDC, Mendes TT, Veneroso CE, et al. Thermoregulatory and metabolic responses to a half-marathon run in hot, humid conditions. Journal of Thermal Biology. 2020;**93**:102734

[89] Negra Y, Chaabene H, Hammami M, Khlifa R, Gabbet T, Hachana Y. Allometric scaling and age related differences in change of direction speed performances of young soccer players. Science & Sports. 2016;**31**:19-26. DOI: 10.1016/j.scispo.2015.10.003

[90] Baden DA, McLean TL, Tucker R, Noakes TD, St.Clair GA. Effect of anticipation during unknown or unexpected exercise duration on rating of perceived exertion, affect, and physiological function. British Journal of Sports Medicine. 2005;**39**:742-746. DOI: 10.1136/bjsm.2004.016980

[91] Eston R, Stansfield R, Westoby P, Parfitt G. Effect of deception and expected exercise duration on psychological and physiological variables during treadmill running and cycling. Psychophysiology. 2012;**49**:462- 469. DOI: 10.1111/j.1469-8986.2011. 01330.x

[92] Clemente FM, Rabbani A, Ferreira R, Araújo JP. Drops in physical performance during intermittent small-sided and conditioned games in professional soccer players. Human Movement. 2020;**21**:7-14

[93] Batista J, Goncalves B, Sampaio J, Castro J, Abade E, Travassos B. The influence of coaches' instruction on technical actions, tactical behaviour, and external workload in football small-sided games. Montenegrin Journal of Sports Science and Medicine. 2019;**8**:29-36. DOI: 10.26773/ mjssm.190305

[94] Branquinho L, Ferraz R, Marques MC. 5-a-side game as a tool for the coach in soccer training. Strength &

Conditioning Journal. 2021;**43**:96-108. DOI: 10.1519/ssc.0000000000000629

[95] Ferraz R, van den Tillaar R, Marques MC. The effect of fatigue on kicking velocity in soccer players. Journal of Human Kinetics. 2012;**35**:97- 107. DOI: 10.2478/v10078-012-0083-8

[96] Billaut F, Bishop DJ, Schaerz S, Noakes TD. Influence of knowledge of sprint number on pacing during repeated-sprint exercise. Medicine and Science in Sports and Exercise. 2011;**43**:665-672. DOI: 10.1249/ MSS.0b013e3181f6ee3b

[97] Morton RH. Deception by manipulating the clock calibration influences cycle ergometer endurance time in males. Journal of Science and Medicine in Sport. 2009;**12**:332-337. DOI: 10.1016/j.jsams.2007.11.006

[98] Meeusen R, Watson P, Hasegawa H, Roelands B, Piacentini MF. Central fatigue: The serotonin hypothesis and beyond. Sports Medicine (Auckland, NZ). 2006;**36**:881-909. DOI: 10.2165/ 00007256-200636100-00006

[99] Enoka RM, Duchateau J. Translating fatigue to human performance. Medicine and Science in Sports and Exercise. 2016;**48**:2228-2238. DOI: 10.1249/MSS.0000000000000929

[100] Hureau TJ, Romer LM, Amann M. The 'sensory tolerance limit': A hypothetical construct determining exercise performance? European Journal of Sport Science. 2018;**18**:13-24. DOI: 10.1080/17461391.2016.1252428

[101] Davis L, Appleby R, Davis P, Wetherell M, Gustafsson H. The role of coach-athlete relationship quality in team sport athletes' psychophysiological exhaustion: Implications for physical and cognitive performance. Journal of Sports Sciences. 2018;**36**:1985-1992. DOI: 10.1080/02640414.2018.1429176

**Chapter 2**

## The Importance of Sleep in Athletes

*Júlio Costa, Pedro Figueiredo, Fábio Y. Nakamura and João Brito*

#### **Abstract**

Sleep is an essential component for athletes' recovery from fatigue, due especially to its physiological and psychological restorative effects. Moreover, sleep is extremely important for numerous biological functions, and sleep deprivation can have significant effects on athletic performance in short-, medium-, and long term. For example, and considering the physiology of sleep for athletes, some hormonal responses that take place in the lead up to and during sleep (e.g., growth hormone—important role in muscle growth and repair) may be affected following exercise (i.e., training and competition), especially when compared with non-athlete's populations. Thus, monitoring sleep is also crucial to understand responses to training and readiness, enabling appropriate planning. Importantly, sleep monitoring also intends to reduce the risk of injury, illness, and nonfunctional overreaching. Moreover, an "individual approach" in athletes monitoring could help in better prescribe training contents and more adequately manage fatigue, as well as recommend pertinent post-match recovery strategies, such as sleep hygiene interventions. Overall, for understanding the athlete's sleep patterns/responses and to optimize the recovery strategies, it is crucial for comprehensive monitoring of his/her health, performance, fitness, and fatigue status.

**Keywords:** athletes, sleep interventions, sleep technology, performance, health

#### **1. Introduction**

Sleep is fundamental for sports performance, as well as for emotional regulation and development of the physical and mental health of athletes. In fact, inadequate sleep (e.g., reduced sleep duration and quality) may lead to an increased risk of injury and illness in athletes.

In recent years, growing interest in understanding the sleep of athletes has seen an increase in published studies [1]. In fact, athletes and coaches have ranked sleep as the most important recovery strategy [2]. Interestingly, the fundamental difference between recovery interventions with established protocols (e.g., cold water immersion, compression garments, electrical stimulation) [3] and sleeping lies in the fact that sleep initiation does not depend entirely on the willingness of the athlete [4].

During sleep, anabolic metabolism is upregulated [5], procedural memories are consolidated [6], and immune responses are augmented [7]. However, sleep loss or deprivation can have significant effects on performance, motivation, perception of effort, and cognition as well as numerous other biological functions [8]. Furthermore, sleep is associated with many physiological processes that may facilitate recovery from, and adaptation to, athletic training and competition [9]. Studies have analyzed the importance of sleep to regulate key molecular mechanisms (i.e., transcriptional regulatory proteins [10–12]), demonstrating that sleep has an integral role in metabolic homeostasis [13]. The capacity of humans to cope with physiological and psychological stressors is fundamental to athletic performance outcomes [14] and may be influenced by numerous factors, such as experience, fitness, motivation, and the normal fluctuation of physiological and behavioral procedures across a 24-h period (i.e., sleep–wake cycle, body temperature, hormone regulation) [15].

Importantly, the circadian rhythms are mainly controlled by the suprachiasmatic nucleus within the hypothalamus [16]. However, the suprachiasmatic nucleus is unable to continuously sustain control over these patterns (i.e., between the suprachiasmatic nucleus within the hypothalamus), as humans are extremely sensitive to changes in their normal environment [16, 17], most notably through the light–dark cycle [18]. When athletes face disturbances to their environments (e.g., training and/or competing close to bedtime sleep and travel), endogenous circadian rhythms and normal sleep-wake cycles can become desynchronized [16, 19]. These perturbations in sleeping patterns can cause an increase in homeostatic pressure and affect emotional regulation, core temperature, and circulating levels of melatonin, causing a delay in sleep onset [20].

Additionally, there is potential for sleep loss and neurocognitive and physiological performance to be compromised [9, 21–23]. Emerging research suggests that there are differences in sleep duration and quality between athletes and healthy controls. In contrast to non-athletes, athletes are often exposed to conditions that can interfere with sleep duration and quality, such as jet lag, unfamiliar sleeping environments, evening training, and/or competition and underlying fatigue [24].

In this sense, sleep monitoring has become a common practice in sport, and, in athletes, it may be useful to identify those who may need an intervention in terms of sleep disorders. Consequently, it is necessary to identify atypical patterns in the sleep and wakefulness of athletes and provide adequate sleep hygiene strategies to avoid disturbances in sleep duration and quality. Efficient and noninvasive methods and equipment, such as actigraphy and other alternatives to polysomnography, can provide detailed information about sleep and wakefulness during the sporting season.

Although there is high availability of information regarding the duration and quality of sleep in different age groups in the general population, information available in the scientific literature about sleep in athletes is still scarce. However, sleep is currently recognized as one of the essential components in the recovery from fatigue and, consequently, in the performance of athletes. Thus, it is essential that athletes, coaches, and clinicians understand the factors that can affect sleep, as well as realizing the usefulness of methods and equipment for assessing the duration and quality of sleep, as this process can result in better health and performance for the athlete.

#### **2. The importance of sleep**

Sleep is an essential component for athletes' recovery from fatigue, due especially to its physiological and psychological restorative effects [25]. In fact, it seems important that athletes learn to manage their sleeping and waking times, given the influence on circadian rhythm, since alterations in the biological clock may affect not only the duration and quality of sleep, but, mainly, sports performance [17].

#### *The Importance of Sleep in Athletes DOI: http://dx.doi.org/10.5772/intechopen.102535*

Athletes and coaches recognize the importance of sleep as one of the most important strategies for recovering from fatigue and improving an athlete's performance [2]. However, during the competitive period, it is common for athletes to follow strict training and competition schedules, which, associated with intense training loads and the physical and emotional demands of competitions, may interfere and reduce the duration and quality of their sleep [26] and, consequently, decrease the fatigue recovery process [27]. This potential imbalance can actually occur when training and competitions are held close to bedtime [28]. Furthermore, exercise, when performed close to bedtime, may alter circadian rhythms [29] and sleep patterns (e.g., reducing sleep duration) [28, 30]. In fact, it seems important that athletes learn to manage their sleeping and waking times, given the influence on circadian rhythm, since alterations in the biological clock may affect not only the duration and quality of sleep, but, mainly, sports performance [2].

In the general population, less than 8 h of sleep per night may be associated with alterations in cognitive performance, mood, and wakefulness, as well as with increases in daytime sleepiness episodes [31]. This theme extends to younger athletes, who are expected to have a greater physiological need for sleep (8–10 h per night) compared with adults (7–9 h per night) and who often experience delays in sleep onset and awakening [32, 33]. Similarly, compared with adult athletes, young athletes have different daily commitments, such as school and social activities (including time spent online during the night), which can further alter sleep habits and/or wakefulness [34]. As an example, in an epidemiological study [35], significant reductions in neurocognitive performance (assessed through visual tests of memory and speed of response to a given visual stimulus) were observed in 7150 young athletes from different sports, who had a sleep duration of less than 5 h per night.

However, despite the high availability of information regarding the duration and quality of sleep in different age groups in the general population, in the scientific literature, the information available regarding the duration and quality of sleep in athletes is still scarce [36]. In fact, this seems contradictory given that sleep is currently recognized as one of the essential components in athletes' recovery [25]. Thus, there is a need to investigate, through sensitive and noninvasive methods, the monitoring of sleep patterns and wakefulness in athletes, in order to promote better sleep hygiene and, consequently, better recovery and performance.

#### **3. Sleep, injuries, and performance**

The current training and competition demands are topics with the greatest interest and discussion in the fields of sports science and sports medicine. This theme is commonly associated with the problem of sports injuries that affect athletes. In this sense, it is essential that clubs create ideal conditions for the training and development of athletes, integrating strategies and best practices for the prevention, treatment, and rehabilitation of injuries in an integrated perspective for athletes' health and performance.

Sleep can influence the risk of injury and illness. In a study of 122 athletes, it was observed that the risk of injury increased by 65% when athletes slept less than 8 h per night [37]. In another more recent study, it was possible to observe that 23 athletes with reduced sleep durations (<8 h) demonstrated a high association with the increase in musculoskeletal injuries. However, evidence in the literature is still very limited about this association. It is also important to note that sports injury is an emergent complex phenomenon, and the risk factors of injury comprise nonlinear associations between various factors such as the biomechanics, training and competitions workloads, as well as psychological and physiological characteristics. For example, according to Laux et al. [38] results, the highest risk for injury appears to occur from a synchronized growth in training and competitions workloads and loss in total sleep time; nonetheless, prospective randomized trials determining that decreased sleep quality leads an injury could require a more decisive response. Research on this topic may provide important information for coaches and practitioners in identifying potential strategies to maintain and improve athlete well-being.

Effects of inadequate sleep duration and quality on performance are likely to be seen specifically in competitive athletes, because of their high-performance demands being more likely to show the harmful effects of suboptimal sleep. Research studies have found negative results of sleep deficiency on athletic performance and well-being, specifically relative to time to exhaustion, muscle strength, and mood state [39, 40]. In a study of a sleep banking (i.e., sleep extension) for college basketball players (*n* = 11, 18–22 age), sleep duration was augmented by 110.9 ± 79.7 min (*p* < 0.001), together with significant increases in daytime sleepiness, reaction time, sprinting time, accuracy, fatigue, tension, depression, irritation, confusion, and mood disturbance [41]. In other study of cyclist's athletes and triathletes [42], an improved endurance performance was shown after three nights of sleep banking (~8.4 h sleep each night) compared with usual sleep (~6.8 h sleep each night), suggesting that endurance athletes' sleep must be >8 h each night to improve performance.

Considering the importance of examining sleep habits and wakefulness in athletes, the impact of training and competition schedules and loads on sleep indices has recently been explored [43–45]. In these studies, it was observed that sleep habits (i.e., the duration and quality of sleep) can be affected by schedule variations and by training and competition loads, especially when sessions are held at night, close to bedtime.

It should also be noted that the sleep habits and wakefulness of athletes may depend on the type of sport practiced [26]. For instance, Lastella et al. [26] investigated sleep/wake behavior of elite athletes, including young female and male athletes, and compared differences between athletes from individual (cycling, mountain bike, racewalking, swimming, and triathlon) and team sports (Australian football, basketball, soccer, and rugby union). Sleep/wake behaviors of elite athletes (*n* = 124) were well below the recommended 8 h of sleep per night, with shorter sleep duration existing in individual sports. These outcomes suggest that the amount of sleep the athletes obtain depends also on their sport.

That said, and although the duration and quality of an athlete's sleep may be associated with the schedules and loads of training and competition, it is also important to consider other factors that can influence sleep indices and wakefulness, namely age, sex, and chronotype [46]. For example, sex was identified as a risk factor for lifetime sleep problems in elite French athletes, with a greater incidence of sleep problems in female athletes [47]. Age has been shown to relate to the prevalence of poor sleep quality, with athletes >25 years of age reporting greater Pittsburgh Sleep Quality Index (PSQI) scores compared with ages <20 [48]; early fatherhood and/or motherhood could be a causal factor [49]. The age of the athletes was also classified as a risk factor for sleep disturbance previous to a competition; however, habitual sleep quality was not [50]. These findings may indicate that athletes who normally report good sleep quality are not necessarily resilient against sleep disturbance during, for instance, a major competition.

#### **4. Measuring sleep**

To detect and control sleep disorders, it is important to monitor sleep habits and perceptions of sleep through subjective and objective measures [51].

#### *The Importance of Sleep in Athletes DOI: http://dx.doi.org/10.5772/intechopen.102535*

In general, the main recommendations on sleep monitoring point to polysomnography, which uses surface electrodes to monitor physiological parameters such as brain, muscle, cardiac, and respiratory activity [52]. Polysomnography is particularly useful for investigating sleep pathologies, including sleep-disordered breathing [53] and sleep disorders caused by concussion [54]. However, polysomnography is an expensive technique and requires specialized laboratory equipment, so its use in athletes in the real context is impractical [55].

On the other hand, actigraphy uses accelerometers placed in portable devices to record movements that, analyzed using algorithms, estimate the quality and duration of sleep [56]. Actigraphy is less expensive, noninvasive, and can be used in training and competition routines, ideally requiring two consecutive weeks of monitoring [57]. Thus, actigraphy emerges as the most accessible method to objectively monitor the sleep of athletes during the night [55]. Overall, wrist-worn accelerometers allow estimation of total sleep time (the total amount of sleep obtained during a sleep period), time in bed (the amount of time spent in bed attempting to sleep between bedtime and get-up time), wake up time (time at which a athlete got out of bed and stopped attempting to sleep), sleep onset time (transition from wakefulness into sleep), wake after sleep onset (number of min awake after sleep onset), latency (the period of time between bedtime and sleep onset time), and sleep efficiency (percentage of time in bed that was spent asleep) [55]. However, it is imperative to highlight that activity monitors tend to underestimate sleep in people who exhibit high levels of movement during light sleep [58]. In fact, some works showed that (elite) athletes obtain less sleep than the general population [59, 60] and present larger movement and fragmentation during sleep [61, 62]. Thus, and given the sleep characteristics of (elite) athletes, it is important to determine how well activity monitors are sensitive to recognize moments of sleep and vigilance in this type of population. This raises a potential issue with the use of activity monitors for measuring sleep in (elite) athletes.

Questionnaires and in particular "sleep diaries" are also used to record the start and end times for all sleep periods (i.e., night sleep and daily naps) [57]. Nevertheless, subjective reports (e.g., PSQI) might deviate from objective measures [63], especially with regard to mood and memory biases, while personality characteristics may also affect self-reported sleep ratings [64]. Indeed, some discrepancies have been detected when comparing subjective parameters with objective measures [65].

Additionally, and considering the ability of monitoring (objectively or subjectively) sleep duration and quality obtained by an (elite) athlete as a useful tool for evaluating recovery from training and competition [55], it is crucial to highlight the importance of individualized monitoring.

Although it is conventional to focus monitoring on group mean responses following a particular training intervention or competition, sport settings frequently produce diverse results with high and low responders being often lost in the averaged data reports [66, 67]. As a consequence, an increased attention for individualization of monitoring in sport settings has growth to a variety of athlete-monitoring approaches, allowing coaches to better manage fatigue and planning training prescription on an individual basis [68].

Nevertheless, research examining the sleep of athletes has typically averaged data across several nights, providing a mean estimate of usual sleep [26, 48, 61]. While such approaches are useful to allow basic insight into sleep (to better understand fatigue and recovery in athletes), they lack the sophistication to provide understanding of how sleep may vary across multiple nights at the individual level [69–71]. Moreover, individual variability can reflect differences within individuals over time [72], with high intra-individual variability in the athletes' sleep indicating the need for individualized sleep education strategies and interventions to promote appropriate sleep [69].

Although identifying the optimal amount of sleep on an individual basis may be difficult [73], young and adult athletes who exhibit average sleep of less than 8 or 7 h, respectively, likely warrant additional assessment to classify their sleep difficulties. Hence, those athletes that reveal deleterious effects of inadequate total sleep time should be stimulated to use sleep hygiene strategies to increase sleep during night and vigilance during the day [74]. Longitudinal monitoring of training and match load, sleep, fatigue (e.g., through heart rate variability), stress, and mood may not only help identify individuals at risk, but also monitor improvements in sleep, well-being, and performance after interventions [75].

Overall, it might be important to include sleep monitoring in (elite) athletes encompassing individual responses, in addition to group means [69]. Also, special attention should be given to the sleep behavior of (elite) athletes (e.g., total sleep time) during periods of congested fixtures, such as international competitions, since sleep deficits can impair performance [17], as already mention above (point 3).

#### **5. Sleep hygiene**

The implementation of strategies that promote sleep quality should be a priority for athletes. In fact, during sleep, fundamental physiological and psychological processes take place for the recovery from fatigue, so the optimization of sleep hygiene strategies increasingly assumes an important role in the routines and planning of those dedicated to improving sport performance.

A recent study [76] evaluated the effect of education on sleep hygiene in athletes. It was found that sleep hygiene education had a considerable positive impact on sleep indices. Educational programs on sleep hygiene in athletes provided a significant improvement in sleep duration and quality and reduced daytime sleepiness. Furthermore, research into the effects of sleep hygiene education on athletes, especially young people, is quite limited [31].

As mentioned before, there are several factors that can influence the duration and quality of sleep in athletes. Calendars congested with competitions and regular trips, competitions of great physical and emotional demand that take place at night, or constant changes in the morning time to wake up because of training and travel are examples of common factors that can negatively influence the duration and quality of sleep in athletes.

In this context, the management of light exposure emerges as fundamental, as this factor has a significant impact on sleep. Exposure to light influences the production of melatonin, so managing the times of exposure to artificial light throughout the day can be used as a sleep management and hygiene strategy. Additionally, in competitions that take place at night, athletes are exposed to immense artificial light: lighting in sports facilities, the projectors used by the media in interviews at the end of competitions, light from busses, airports, and planes.

On the other hand, social contexts may also be decisive. In recent studies carried out with female soccer players in Portugal, who usually start training very late, close to bedtime, due to their daily commitments (e.g., work, studies) that have to be reconciled with the training and match schedules, it was found that the athletes showed a reduction in total sleep time and length of time to fall asleep on training days performed at night, compared with training days performed during the day or on rest days (i.e., days without exercise) [28, 44]. It was pointed out that one of the additional explanations for the observed results could have been in the athletes'

#### *The Importance of Sleep in Athletes DOI: http://dx.doi.org/10.5772/intechopen.102535*

exposure to the light emitted in the stadium. In fact, these data are little studied in sport, but during the training days, the athletes were exposed to >1200 lux and 5600 K, with the bright polychromatic light ≥1000 lux, which could be enough to stimulate wakefulness effects during sleep [77]. However, it should be borne in mind that, currently, one of the main sources of exposure to light results from the use of electronic devices (especially smartphones and tablets) and that their use around bedtime is possibly the factor that most influences the sleep latency of athletes.

Thus, the term sleep hygiene, which refers to the recommendations, strategies, behaviors, and conditions developed to promote quality and duration of sleep, has been appearing more and more often in the list of sports planning tasks for athletes [25]. It is important to be aware that, unlike other possible recovery strategies used in sport (e.g., cryotherapy, massage, nutrition, nutritional supplementation), sleep has particularities that are not always controlled by the athlete themselves. Thus, bearing in mind the importance that sleep can have on sports performance, this is a subject that deserves the greatest attention of all those dedicated to promoting health and performance in athletes.

#### **6. Conclusions**

Athletes, coaches, and supporting staff should adopt a scientific approach to both designing and monitoring training programs. Appropriate health and load monitoring is crucial for determining whether a player is adapting to a training program and minimizing the risk of developing nonfunctional overreaching, illness, or injury. To gain understanding of the training and match demands and their effects on the player, several potential markers are available. However, very few of them have strong scientific evidence supporting their use. Moreover, it is important to note that athletes, from different types of sports, normally obtain inadequate sleep duration and quality. From an athletic point of view, reductions in performance, decision-making ability, learning, and cognition can occur alongside reductions in immune function and an increased susceptibility to injury gain.

In this respect, monitoring sleep in athletes can be useful for early detection and intervention before significant performance and health decrements are observed. Noninvasive and time-efficient methods/equipment such as wearable actigraphy monitors can provide detailed information about positive and negative adaptions over short and long periods throughout the competitive season. In addition, each athlete can perform the recordings at home and/or training facilities, adopting a "real world scenario" to grant high ecological validity to the research and/or practical interventions. The accumulated knowledge regarding the importance of sleep has sleep monitoring to become a popular strategy among (elite) athletes, coaches, and supporting staff. However, given the complexity of analyzing sleep patterns and the limited availability of athletes to participate in sleep studies, those indicators are yet poorly documented.

Overall, factors related to training and competition can alter sleep patterns in athletes. Therefore, topics such as: (1) sleep patterns and disorders among athletes; (2) sleep and optimal functioning among athletes; (3) screening, tracking, and assessment of athletes' sleep; and (4) interventions (i.e., sleep hygiene) to improve sleep must be further investigated.

#### **Conflict of interest**

The authors declare no conflict of interest.

*Exercise Physiology*

#### **Author details**

Júlio Costa1 \*, Pedro Figueiredo1,2, Fábio Y. Nakamura3 and João Brito1

1 Portugal Football School, Portuguese Football Federation (FPF), Oeiras, Portugal

2 CIDEFES, Universidade Lusófona, Lisboa, Portugal

3 Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), University of Maia (ISMAI), Maia, Portugal

\*Address all correspondence to: jahdc@hotmail.com

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Roberts SSH, Teo WP, Warmington SA. Effects of training and competition on the sleep of elite athletes: A systematic review and meta-analysis. British Journal of Sports Medicine. 2019;**53**(8):513-522. DOI: 10.1136/bjsports-2018-099322

[2] Fallon KE. Blood tests in tired elite athletes: Expectations of athletes, coaches and sport science/sports medicine staff. British Journal of Sports Medicine. 2007;**41**(1):41-44. DOI: 10.1136/bjsm.2006.030999

[3] Nedelec M, McCall A, Carling C, Legall F, Berthoin S, Dupont G. Recovery in soccer: Part ii: Recovery strategies. Sports Medicine. 2013;**43**(1): 9-22. DOI: 10.1007/s40279-012-0002-0

[4] Nedelec M, Halson S, Abaidia AE, Ahmaidi S, Dupont G. Stress, sleep and recovery in elite soccer: A critical review of the literature. Sports Medicine. 2015;**45**(10):1387-1400. DOI: 10.1007/ s40279-015-0358-z

[5] Chennaoui M, Arnal PJ, Drogou C, Sauvet F, Gomez-Merino D. Sleep extension increases IGF-I concentrations before and during sleep deprivation in healthy young men. Applied Physiology, Nutrition, and Metabolism. 2016;**41**(9):963-970. DOI: 10.1139/apnm-2016-0110

[6] Frank MG, Benington JH. The role of sleep in memory consolidation and brain plasticity: Dream or reality? The Neuroscientist. 2006;**12**(6):477-488. DOI: 10.1177/1073858406293552

[7] Besedovsky L, Lange T, Born J. Sleep and immune function. Pflügers Archiv: European Journal of Physiology. 2012;**463**(1):121-137. DOI: 10.1007/ s00424-011-1044-0

[8] Halson SL. Sleep in elite athletes and nutritional interventions to enhance

sleep. Sports Medicine. 2014;**44** (Suppl. 1):S13-S23

[9] Samuels C. Sleep, recovery, and performance: The new frontier in high-performance athletics. Neurologic Clinics. 2008;**26**(1):169-180. DOI: 10.1016/j.ncl.2007.11.012

[10] Allada R, Siegel JM. Unearthing the phylogenetic roots of sleep. Current Biology. 2008;**18**(15):R670-R6R9

[11] Crocker A, Sehgal A. Genetic analysis of sleep. Genes & Development. 2010;**24**(12):1220-1235

[12] Abel T, Havekes R, Saletin JM, Walker MP. Sleep, plasticity and memory from molecules to whole-brain networks. Current Biology. 2013; **23**(17):R774-R788

[13] Xie L, Kang H, Xu Q, Chen MJ, Liao Y, Thiyagarajan M, et al. Sleep drives metabolite clearance from the adult brain. Science. 2013;**342**(6156): 373-377

[14] Bishop D. An applied research model for the sport sciences. Sports Medicine. 2008;**38**(3):253-263

[15] Drust B, Waterhouse J, Atkinson G, Edwards B, Reilly T. Circadian rhythms in sports performance: An update. Chronobiology International. 2005;**22**(1):21-44

[16] Beersma DG, Gordijn MC. Circadian control of the sleep-wake cycle. Physiology & Behavior. 2007;**90**(2-3):190-195

[17] Fullagar H, Skorski S, Duffield R, Hammes D, Coutts AJ, Meyer T. Sleep and athletic performance: The effects of sleep loss on exercise performance, and physiological and cognitive responses to exercise. Sports Medicine. 2015;**45**(2):161- 186. DOI: 10.1007/s40279-014-0260-0

[18] Czeisler CA, Allan JS, Strogatz SH, Ronda JM, Sanchez R, Rios CD, et al. Bright light resets the human circadian pacemaker independent of the timing of the sleep-wake cycle. Science. 1986;**233**(4764):667-671

[19] Reilly T, Edwards B. Altered sleepwake cycles and physical performance in athletes. Physiological and Behavior. 2007;**90**(2-3):274-284. DOI: 10.1016/j. physbeh.2006.09.017

[20] Lack LC, Wright HR. Chronobiology of sleep in humans. Cellular and Molecular Life Sciences. 2007;**64**(10):1205-1215

[21] Halson SL. Nutrition, sleep and recovery. European Journal of Sport Science. 2008;**8**(2):119-126

[22] Goel N, Rao H, Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Seminars in Neurology. 2009;**29**(4):320-339

[23] Banks S, Dinges DF. Behavioral and physiological consequences of sleep restriction. Journal of Clinical of Sleep Medicine. 2007;**3**(5):519-528

[24] Robey E, Dawson B, Halson S, Gregson W, Goodman C, Eastwood P. Sleep quantity and quality in elite youth soccer players: A pilot study. European Journal of Sport Science. 2014;**14**(5): 410-417. DOI: 10.1080/17461391.2013. 843024

[25] Walsh NP, Halson SL, Sargent C, Roach GD, Nedelec M, Gupta L, et al. Sleep and the athlete: Narrative review and 2021 expert consensus recommendations. British Journal of Sports Medicine. 2020;**55**(7):356-368. DOI: 10.1136/bjsports-2020-102025

[26] Lastella M, Roach GD, Halson SL, Sargent C. Sleep/wake behaviours of elite athletes from individual and team sports. European Journal of Sport Science. 2015;**15**(2):94-100

[27] Vitale JA, Banfi G, Galbiati A, Ferini-Strambi L, Torre A. Effect of night-game on actigraphy-based sleep quality and perceived recovery in top-level volleyball athletes. International Journal of Sports Physiology and Performance. 2018;**14**: 1-14. DOI: 10.1123/ijspp.2018-0194

[28] Costa JA, Brito J, Nakamura FY, Oliveira EM, Costa OP, Rebelo AN. Does night-training load affect sleep patterns and nocturnal cardiac autonomic activity in high-level female soccer players? International Journal of Sports Physiology and Performance. 2018;**14**(6):779-787. DOI: 10.1123/ ijspp.2018-0652

[29] Buman MP, Phillips BA, Youngstedt SD, Kline CE, Hirshkowitz M. Does nighttime exercise really disturb sleep? Results from the 2013 National Sleep Foundation Sleep in America Poll. Sleep Medicine. 2014;**15**(7):755-761. DOI: 10.1016/j.sleep.2014.01.008

[30] Fowler P, Duffield R, Vaile J. Effects of simulated domestic and international air travel on sleep, performance, and recovery for team sports. Scandinavian Journal of Medicine & Science in Sports. 2015;**25**(3):441-451. DOI: 10.1111/ sms.12227

[31] Fox JL, Scanlan AT, Stanton R, Sargent C. Insufficient sleep in young athletes? Causes, consequences, and potential treatments. Sports Medicine. 2020;**50**(3):461-470

[32] Crowley S, Carskadon M. Modifications to weekend recovery sleep delay circadian phase in older adolescents. Chronobiology International. 2010;**27**(7):1469-1492. DOI: 10.3109/07420528.2010.503293

[33] Hirshkowitz M, Whiton K, Albert S, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation's sleep time duration recommendations: Methodology and *The Importance of Sleep in Athletes DOI: http://dx.doi.org/10.5772/intechopen.102535*

results summary. Sleep Health. 2015;**1**(1):40-43. DOI: 10.1016/j. sleh.2014.12.010

[34] Carskadon M. Sleep in adolescents: The perfect storm. Pediatric Clinics of North America. 2011;**58**(3):637-647. DOI: 10.1016/j.pcl.2011.03.003

[35] Sufrinko A, Johnson EW, Henry LC. The influence of sleep duration and sleep-related symptoms on baseline neurocognitive performance among male and female high school athletes. Neuropsychology. 2016;**30**(4):484-491

[36] Sargent C, Lastella M, Halson SL, Roach GD. How much sleep does an elite athlete need? International Journal of Sports Physiology and Performance. 2021;**16**:1-12

[37] Milewski MD, Skaggs DL, Bishop GA, Pace JL, Ibrahim DA, Wren TA, et al. Chronic lack of sleep is associated with increased sports injuries in adolescent athletes. Journal of Pediatric Orthopedics. 2014;**34**(2):129- 133. DOI: 10.1097/BPO.00000000000 00151

[38] Laux P, Krumm B, Diers M, Flor H. Recovery-stress balance and injury risk in professional football players: A prospective study. Journal of Sports Sciences. 2015;**33**(20):2140-2148. DOI: 10.1080/02640414.2015.1064538

[39] VanHelder T, Radomski MW. Sleep deprivation and the effect on exercise performance. Sports Medicine. 1989;**7**(4):235-247. DOI: 10.2165/00007256- 198907040-00002

[40] Van Ryswyk E, Weeks R, Bandick L, O'Keefe M, Vakulin A, Catcheside P, et al. A novel sleep optimisation programme to improve athletes' well-being and performance. European Journal of Sport Science. 2017;**17**(2):144-151. DOI: 10.1080/ 17461391.2016.1221470

[41] Mah CD, Mah KE, Kezirian EJ, Dement WC. The effects of sleep extension on the athletic performance of collegiate basketball players. Sleep. 2011;**34**(7):943-950. DOI: 10.5665/ SLEEP.1132

[42] Roberts SSH, Teo WP, Aisbett B, Warmington SA. Extended sleep maintains endurance performance better than normal or restricted sleep. Medicine and Science in Sports and Exercise. 2019;**51**(12):2516-2523. DOI: 10.1249/MSS.000000000000 2071

[43] Lastella M, Roach GD, Vincent GE, Scanlan AT, Halson SL, Sargent C. The impact of training load on sleep during a 14-day training camp in elite, adolescent, female basketball players. International Journal of Sports Physiology and Performance. 2020;**15**:1- 7. DOI: 10.1123/ijspp.2019-0157

[44] Costa JA, Brito J, Nakamura FY, Figueiredo P, Oliveira E, Rebelo A. Sleep patterns and nocturnal cardiac autonomic activity in female athletes are affected by the timing of exercise and match location. Chronobiology International. 2018;**36**(3):360-373. DOI: 10.1080/07420528.2018.1545782

[45] Figueiredo P, Costa J, Lastella M, Morais J, Brito J. Sleep indices and cardiac autonomic activity responses during an international tournament in a youth national soccer team. International Journal of Environmental Research and Public Health. 2021;**18**(4): 2076. DOI: 10.3390/ijerph18042076

[46] Lastella M, Roach GD, Halson SL, Sargent C. The chronotype of elite athletes. The Journal of Human Kinetics. 2016;**54**:219-225. Epub 2016/12/30. DOI: 10.1515/hukin-2016-0049

[47] Schaal K, Tafflet M, Nassif H, Thibault V, Pichard C, Alcotte M, et al. Psychological balance in high level athletes: Gender-based differences and sport-specific patterns. PLoS One.

2011;**6**(5):e19007. Epub 2011/05/17. DOI: 10.1371/journal.pone.0019007

[48] Swinbourne R, Gill N, Vaile J, Smart D. Prevalence of poor sleep quality, sleepiness and obstructive sleep apnoea risk factors in athletes. European Journal of Sport Science. 2016;**16**(7): 850-858. Epub 2015/12/25. DOI: 10.1080/17461391.2015.1120781

[49] Finan PH, Quartana PJ, Smith MT. The effects of sleep continuity disruption on positive mood and sleep architecture in healthy adults. Sleep. 2015;**38**(11):1735-1742. DOI: 10.5665/ sleep.5154

[50] Juliff LE, Halson SL, Peiffer JJ. Understanding sleep disturbance in athletes prior to important competitions. Journal of Science and Medicine in Sport. 2015;**18**(1):13-18. DOI: 10.1016/j.jsams.2014.02.007

[51] Myllymaki T, Kyrolainen H, Savolainen K, Hokka L, Jakonen R, Juuti T, et al. Effects of vigorous latenight exercise on sleep quality and cardiac autonomic activity. Journal of Sleep Research. 2011;**20**(1 Pt 2):146-153

[52] Kushida CA, Littner MR, Morgenthaler T, Alessi CA, Bailey D, Coleman J Jr, et al. Practice parameters for the indications for polysomnography and related procedures: An update for 2005. Sleep. 2005;**28**(4):499-521

[53] George CF, Kab V, Levy AM. Increased prevalence of sleepdisordered breathing among professional football players. The New England Journal of Medicine. 2003; **348**(4):367-368. DOI: 10.1056/ NEJM200301233480422

[54] Gosselin N, Lassonde M, Petit D, Leclerc S, Mongrain V, Collie A, et al. Sleep following sport-related concussions. Sleep Medicine. 2009;**10**(1):35-46. DOI: 10.1016/j.sleep.2007.11.023

[55] Sargent C, Lastella M, Halson SL, Roach GD. The validity of activity monitors for measuring sleep in elite athletes. Journal of Science and Medicine in Sport. 2016;**19**(10):848-853. DOI: 10.1016/j.jsams.2015.12.007

[56] Ancoli-Israel S, Cole R, Alessi C, Chambers M, Moorcroft W, Pollak CP. The role of actigraphy in the study of sleep and circadian rhythms. Sleep. 2003;**26**(3):342-392

[57] Halson SL. Sleep monitoring in athletes: Motivation, methods, miscalculations and why it matters. Sports Medicine. 2019;**49**:1487-1497. DOI: 10.1007/s40279-019-01119-4

[58] Tryon WW. Issues of validity in actigraphic sleep assessment. Sleep. 2004;**27**(1):158-165

[59] Roach GD, Schmidt WF, Aughey RJ, Bourdon PC, Soria R, Claros JC, et al. The sleep of elite athletes at sea level and high altitude: A comparison of sea-level natives and high-altitude natives (ISA3600). British Journal of Sports Medicine. 2013;**47**(Suppl. 1):i114-i120. DOI: 10.1136/bjsports-2013-092843

[60] Sargent C, Halson S, Roach GD. Sleep or swim? Early-morning training severely restricts the amount of sleep obtained by elite swimmers. European Journal of Sport Science. 2014;**14** (Suppl 1):S310-S315. DOI: 10.1080/ 17461391.2012.696711

[61] Leeder J, Glaister M, Pizzoferro K, Dawson J, Pedlar C. Sleep duration and quality in elite athletes measured using wristwatch actigraphy. Journal of Sports Science. 2012;**30**(6):541-545

[62] Taylor SR, Rogers GG, Driver HS. Effects of training volume on sleep, psychological, and selected physiological profiles of elite female swimmers. Medicine & Science in Sports & Exercise. 1997;**29**(5):688-693 *The Importance of Sleep in Athletes DOI: http://dx.doi.org/10.5772/intechopen.102535*

[63] Kawada T. Agreement rates for sleep/wake judgments obtained via accelerometer and sleep diary: A comparison. Behavior Research Methods. 2008;**40**(4):1026-1029

[64] Jackowska M, Dockray S, Hendrickx H, Steptoe A. Psychosocial factors and sleep efficiency: Discrepancies between subjective and objective evaluations of sleep. Psychosomatic Medicine. 2011; **73**(9):810-816

[65] Kolling S, Endler S, Ferrauti A, Meyer T, Kellmann M. Comparing subjective with objective sleep parameters via multisensory actigraphy in german physical education students. Behavioral Sleep Medicine. 2016;**14**(4): 389-405

[66] Mann TN, Lamberts RP, Lambert MI. High responders and low responders: Factors associated with individual variation in response to standardized training. Sports Medicine. 2014;**44**(8):1113-1124. DOI: 10.1007/ s40279-014-0197-3

[67] Chrzanowski-Smith OJ, Piatrikova E, Betts JA, Williams S, Gonzalez JT. Variability in exercise physiology: Can capturing intraindividual variation help better understand true inter-individual responses? European Journal of Applied Physiology. 2019;**20**:452-460. DOI: 10.1080/17461391.2019.1655100

[68] Halson SL. Monitoring training load to understand fatigue in athletes. Sports Medicine. 2014;**44**(Suppl 2):S139-S147. DOI: 10.1007/s40279-014-0253-z

[69] Nedelec M, Aloulou A, Duforez F, Meyer T, Dupont G. The variability of sleep among elite athletes. Sports Medicine—Open. 2018;**4**(1):34. DOI: 10.1186/s40798-018-0151-2

[70] Buchheit M. Monitoring training status with HR measures: Do all roads lead to Rome? Frontiers in Physiology. 2014;**5**:73. DOI: 10.3389/fphys.2014. 00073

[71] Bei B, Wiley JF, Trinder J, Manber R. Beyond the mean: A systematic review on the correlates of daily intraindividual variability of sleep/wake patterns. Sleep Medicine Reviews. 2016;**28**:108-124. DOI: 10.1016/j.smrv.2015.06.003

[72] Van Dongen HP. Analysis of interand intra-individual variability. Journal of Sleep Research. 2005;**14**(2):201-203. DOI: 10.1111/j.1365-2869.2005.00453.x

[73] Watson AM. Sleep and athletic performance. Current Sports Medicine Reports. 2017;**16**(6):413-418. DOI: 10.1249/JSR.0000000000000418

[74] Gupta L, Morgan K, Gilchrist S. Does elite sport degrade sleep quality? A systematic review. Sports Medicine. 2017;**47**(7):1317-1333. DOI: 10.1007/ s40279-016-0650-6

[75] Simpson NS, Gibbs EL, Matheson GO. Optimizing sleep to maximize performance: Implications and recommendations for elite athletes. Scandinavian Journal of Medicine & Science in Sports. 2017;**27**(3):266-274. DOI: 10.1111/sms.12703

[76] Driller MW, Lastella M, Sharp AP. Individualized sleep education improves subjective and objective sleep indices in elite cricket athletes: A pilot study. Journal of Sports Sciences. 2019;**37**(17): 2121-2125. DOI: 10.1080/02640414.2019. 1616900

[77] Cajochen C. Alerting effects of light. Sleep Medicine Reviews. 2007;**11**(6):453-464. DOI: 10.1016/j. smrv.2007.07.009

#### **Chapter 3**

## Physiological Adaptions to Acute Hypoxia

*Erich Hohenauer*

#### **Abstract**

When tissues are insufficiently supplied with oxygen, the environment is said to be hypoxic. Acute (exposures to) hypoxia can occur occupationally, within the scope of training and competitions or under pathological conditions. The increasing interest in acute exposure to altitude for training and research purposes makes it more important than ever to understand the physiological processes that occur under hypoxic conditions. Therefore, the scope of this chapter is to describe the main types of hypoxia on the oxygen cascade, to summarize the physiological consequences of acute hypoxia on the three main areas and to highlight the clinical consequences of acute hypoxia exposures for healthcare practitioners.

**Keywords:** hypoxia, altitude, oxygen, physiology, cardiorespiratory

#### **1. Introduction**

The human body cells need the energy to maintain their functions. This energy is mainly provided by sugar, carbohydrates and fat. To utilize these nutritive substances and to produce energy in return, inspired oxygen (O2) from the air is needed. In the mitochondrial electron transport chain, O2 is the final electron acceptor to generate ATP within the eukaryotic cells [1]. Whilst O2 is needed for most life on earth, most of the earth's atmosphere does not contain a lot of O2. From the surface of the planet, up to the border of space, the atmosphere contains a constant fraction of around 21% O2 (often expressed as the FiO2 of around 0.21), 78% of nitrogen, 0.9% argon and 0.1% of other gases like carbon dioxide, methane, water vapor, etc. At sea level, the partial pressure of the above-mentioned gases can be estimated to be 593 mmHg for nitrogen, 160 mmHg for oxygen and 7.6 mmHg for argon. Indeed, the weight of air is responsible for atmospheric pressure.

It's well known that increasing altitude leads to quasi-exponential reductions in barometric pressure (PB). At the summit of Mt. Everest (8848 m), the PB is about onethird of the sea-level values. The reduced atmospheric pressure has therefore a direct influence on the partial pressure of inspired oxygen, which can be seen in **Figure 1**.

The inspired partial pressure of oxygen (PiO2) is lower than atmospheric oxygen partial pressure because water vapor is in the airways. The pressure of water vapor (PH2O), which is not dependent on atmospheric pressure but temperature, should be taken into account when PiO2 is calculated [2]. The inhaled air gases will get humified and warmed by the airways and as a result, the PH2O will adjust the partial pressure of all inhaled gases, including O2.

#### **Figure 1.**

*Relationship between barometric pressure (PB), partial pressure of inspired oxygen (PiO2) and altitude. PB and PiO2 decrease exponentially with increasing altitude at a constant FiO2 of 21%. The solid line represents PB and the broken line represents PiO2.*

Accordingly, the product of PiO2 can be calculated using Eq. (1):

$$\rm{P}\_{\rm{l}}\rm{O}\_{\rm{z}} = \left(\rm{P}\_{\rm{B}} - \rm{PH}\_{\rm{z}}\rm{O}\right) \times \rm{F}\_{\rm{l}}\rm{O}\_{\rm{z}}.\tag{1}$$

Since PB is known to be approximately 760 mmHg at sea level, PH2O is normally about 47 mmHg and O2 makes up to 20.93% (FiO2 of 0.2093), PiO2 is equal to 0.20932 multiplied by 713 mmHg.

Consequently, hypoxia is defined as a combination of PB and the FiO2 that results in any PiO2 under a normoxic value of 150 mmHg [3]. However, the duration of hypoxic exposures as well as the magnitude of PB reductions has a significant impact on the (patho-)physiological response. Examples of fast-changing normoxic to hypoxic environments are fast ascended on the mountain summits during mountaineering, military and rescue services and travels with fast transportation to altitude. Acute mountain sickness is well-known to occur due to extensive and fast decreases in Pb, normally beginning at an altitude of above 2500 m. The Lake Louis Consensus Group defined acute mountain sickness as the presence of headache in an unacclimatised person (recently arriving at an altitude above 2500 m), plus the presence of one or more of the following symptoms: gastrointestinal symptoms, fatigue and/or weakness, dizziness or a positive clinical functional score, resulting in a total score of ≥3 [4]. If not treated correctly, people with acute mountain sickness can develop highaltitude pulmonary oedema or high-altitude cerebral oedema [5]. However, if the human body is gradually exposed to hypoxic conditions, it can acclimatize and adapt.

The following chapters will focus on the main types of hypoxia, the physiological consequences of acute hypoxia and the clinical consequences of the current chapter.

#### **2. Types of hypoxia**

Insufficient O2 supply to the human tissues can have various reasons and can lead to severely impaired body functions. There are four main types of hypoxia, which can be classified as hypoxaemic hypoxia, anemic hypoxia, stagnant hypoxia and histotoxic hypoxia.

#### **2.1 Hypoxaemic type**

One of the most common types of hypoxia is called generalized or hypoxic hypoxia, which is generated from the actual (natural/simulated) environment and inside the lungs. This type is caused by a reduction of the partial pressure of alveolar O2 (PAO2) [6]. This value is well known and a great help to calculate the partial pressure of oxygen inside the alveoli (as it is not possible to collect gases directly from the alveoli), which can be used for potential cell diffusion [7]. The alveolar gas equation uses three variables to calculate the alveolar concentration of oxygen, which can be seen in Eq. (2):

$$\mathbf{P\_AO\_z = F\_iO\_z \times (P\_B - PH\_zO) - P\_zCO\_z / RQ} \tag{2}$$

where PaCO2 is the partial pressure of carbon dioxide which is under normal physiological conditions approximately 40 mmHg. RQ is the respiratory quotient which is, the ratio of the volume of produced CO2 divided by the volume of consumed O2 during the same time [8]. Dependent on metabolic activity and diet, RQ is considered to be around 0.825 [9], within a physiological range between 0.70 and 1.00. Consequently, PAO2 at sea level is: 0.2093 × (760–47) – 40/0.825 = 100.7 mmHg. PAO2 is the main driving factor for alveolar diffusion and thus O2 supply on a cellular level.

Hypoxic hypoxia can be observed typically when FiO2 is low, during hypoventilation of the lungs or at the presence of pathological airway conditions. Low FiO2 levels can occur due to failure of gas delivery systems, inadequate supply from altitude simulating machines, or e.g., exorbitant inhalation of nitrous oxide during anesthesia [10]. Hypoventilation can occur due to insufficient respiratory rate, obstruction of airways, skeletal deformities, respiratory muscle paralysis, etc. Severe lung diseases (e.g., pulmonary fibrosis, pulmonary embolism) can also lead to alveolar-capillary diffusion blockade [11]. Hypoxic hypoxia affects the entire body. Typical symptoms are agitation and anxiety while low blood O2 goes along with increased heart rate, dyspnea and bluish color of the skin.

#### **2.2 Anemic type**

Anemic hypoxia is caused by reduced oxygen transport capacity in the blood [12]. The red blood cells (erythrocytes) are responsible for the transport of O2 through the body [13]. Around 90% of the erythrocyte is made up of haemoglobin, the iron-containing protein that binds O2 on its heme. Although, the arterial oxygen tension is normal at this type, reduced erythrocytes/haemoglobin or functional insufficiency of haemoglobin leads to impaired oxygen delivery to the tissues [14].

A deficiency in the number of erythrocytes can result, for example, from excessive blood loss after trauma. Other forms of the reduced number of erythrocytes can be present in case of abnormal red blood cell breakdown (haemolytic anemia) [15]. Increased haemolysis can be observed during hereditary spherocytosis, sickle cell disease or autoimmune diseases (e.g., aplastic anemia) [16].

Deficiencies of different factors can also lead to severe anemia. Iron is the main component of haemoglobin, giving the blood the red color and is the prime carrier of oxygen. During the physiological haemolysis, iron will be bound to the glycoprotein transferrin for transportation to the bone marrow, where it will be reused for haemoglobin synthesis. This process helps to limit an extensive loss of iron from the body. However, iron deficiency is one of the main causes of anemia, called microcytic hypochromic anemia [6]. This type of anemia can be caused by any factor which reduces the body's iron storage, leading to small erythrocytes with reduced haemoglobin mass [17]. In contrast, deficiencies in vitamin B12 or folic acid can cause anemia due to abnormally enlarged erythrocytes and their immature precursors, called macrocytic hyperchromic anemia [18].

Functional insufficiency of haemoglobin is associated with reduced oxygen binding capacity. An example is an intoxication through excessive carbon monoxide inhalation. Compared to oxygen, carbon monoxide has a 200–300 times higher affinity to haemoglobin. After inhalation, carbon monoxide reaches the respiratory gas exchange zone and binds on haemoglobin [10]. This chemical binding process leads to the formation of carboxyhaemoglobin. Consequently, oxygen-carrying capacity is decreased which will lead to reduced oxygen transportation to the tissues and as a consequence tissue hypoxia [19]. Another possibility of functional insufficiency for the transportation of oxygen is methaemoglobinemia. Haemoglobin changes to methaemoglobin, when bivalent iron (Fe2+) is oxidized to Fe3+, which is worthless for oxygen transport [20]. Under normal circumstances, methaemoglobin reductase limits the build-up of methaemoglobin through the reduction of haemoglobin oxidation [21]. Patients with a deficiency of methaemoglobin reductase, strong oxidative stress (e.g., smoking) and medication can therefor experience very low concentrations of tissue oxygenation, demonstrating comparable symptoms as seen in hypoxic hypoxia. However, it must be mentioned, that the unfavorable conditions of low tissue O2 can be compensated better during hypoxic hypoxia than during anemic hypoxia.

#### **2.3 Stagnant type**

Stagnant, also called ischemic or circulatory hypoxia takes place as a cause of insufficient blood supply to the tissues while the blood is normally oxygenated. Ischemic hypoxia can be observed on a central and local level [6].

Central circulatory hypoxia can often be observed in patients with cardiac manifestations. If the left ventricular output is for example decreased, blood flow to the organs is impaired [12]. This can also happen during shock or, at a local level after strong vasoconstriction (e.g., cold exposures) or venous stagnation of blood [22]. Oxygen can only be stored to the very limited amount within the human cells. Even myoglobin, binding O2 on its heme protein, has a very limited oxygen storage capacity [23]. Consequently, myoglobin is more involved in transportation than the storage of oxygen. Oxygen saturated myoglobin enables facilitated intercellular O2 transportation, because the oxygen-enriched myoglobin molecules can "move" within the cells (facilitated diffusion) which is extremely important at a low partial pressure of O2 (PO2) [24]. Although, the gas exchange rate on the alveolar level, the concentration of haemoglobin, oxygen content and tension are on a normal level, O2 extraction at the level of the capillaries will be increased [6]. This process will directly elevate the arteriovenous difference of blood O2 content leading to venous hypoxia. However, as the increased oxygen extraction is normally insufficient to supply the tissue with an adequate amount of O2, this process will lead to impaired cellular oxygen coverage and impaired functioning.

#### **2.4 Histotoxic type**

Histotoxic hypoxia or dysoxia is a state, where cells are unable to utilize oxygen effectively [12]. This is the case, when the mitochondrial terminal oxidation is disturbed while there is sufficient oxygen available in the blood. Dysoxia will therefore lead to a pathological reduction in ATP production by the mitochondria and is not preceded by hypoxaemia [6].

*Physiological Adaptions to Acute Hypoxia DOI: http://dx.doi.org/10.5772/intechopen.102532*

An example of histotoxic hypoxia is the intoxication with cyanides, which can occur from fire sources. Intravenous and inhalation of cyanide produce a more rapid onset of hypoxia than the oral or transdermal route due to the fast diffusion into the bloodstream [25]. The main effect of cyanide intoxication is related to the inhibition of oxidative phosphorylation, where oxygen is utilized for ATP production. Cyanide can reversibly bind to the enzyme cytochrome C oxidase, blocking the mitochondrial transport chain. This will cause cellular hypoxia and, as mentioned above, pathological low levels of ATP, causing metabolic acidosis and impairment of vital functions [26, 27].

#### **3. Physiological consequences of acute hypoxia**

Rapid ascends from sea level to altitude and sudden exposure to a hypoxic environment will immediately lead to acute physiological responses to adapt to the acute hypoxaemic situation [28]. The degree of acute hypoxic stress about time can lead to symptoms ranging from dizziness, feeling of unreality and dim visions to rapid unconsciousness [29]. Sudden exposure to the summit of Mt. Everest will for example lead to unconsciousness within 2 min. However, when the same amount of hypoxaemia is experienced over several days to weeks, one could function relatively well under these conditions. This adjustment is called acclimatization which is a complex process over time and shows great variability within individuals [29]. In the following chapters, the acute response to sudden exposure to a hypoxic environment is discussed.

#### **3.1 Respiratory system**

The respiratory system will directly respond to the low oxygen availability in the air and is often seen as the primary defense against the hypoxic environment. Chemosensory systems will rapidly lead to increased pulmonary ventilation because of compromised O2 availability [30]. These regulatory responses can be attributed due to specialized chemoreceptors such as the carotid bodies in the arterial circulation and neuroepithelial bodies in the respiratory tract as well as the direct response of vascular smooth muscles to hypoxia [31].

Whilst hypoxia acts as a vasodilator in the systemic circulation, it has been observed, that the vessels of the pulmonary vasculature constrict under hypoxia, leading to pulmonary hypertension [32, 33]. Hypoxic vasoconstriction is intrinsic to the pulmonary vasculature smooth muscle cells and is initiated by the inhibition of K<sup>+</sup> channels which set the membrane potential [34]. This process will lead to depolarization, activation of Ca2+ channels as a result of the electrical impulse and, as a consequence, an increase in cytosolic calcium levels and therefore constriction of the myocytes [31]. Pulmonary hypertension might help to match ventilation and perfusion within the lungs. However, pulmonary hypertension can also lead to severe pathological situations (e.g., altitude-related right heart failure).

Carotid bodies, sensitive to monitoring a drop in arterial O2 levels, and neuroepithelial bodies, detecting changes in inspired O2, respond immediately to decreased O2 supply [35]. Both respond by activating efferent chemosensory fibers to produce cardiorespiratory adjustments during hypoxic exposures [36, 37]. When low arterial PO2 is detected, the carotid body signals the central respiratory center to increase the (minute) ventilation. The increased ventilation of the respiratory tract can be primarily associated with an elevated tidal volume and an even greater elevation in respiratory rate [38]. This hypoxic ventilatory response counteracts the hypoxic environment by decreasing PACO2, increasing PAO2 and therefore improving oxygen delivery. Genetical determinants, as well as various external factors

(metabolic and respiratory stimulants), lead to wide inter-individual variety of ventilatory response intensity [39]. The increased ventilatory response demonstrates that adaptive processes are taking place and a "good" ventilatory response is known to enhance acclimatization and performance and that a very low response may contribute to the formation of illness [39, 40]. However, hyperventilation will subsequently lead to hypocapnia (increased pH) known as respiratory alkalosis by reducing the amount of carbon dioxide in the alveoli [41]. This condition will cause the oxygen dissociation curve to shift to the left and to further keep respiratory ventilation high. However, hypocapnia will also counteract the central respiratory center activation and thus limit further ventilatory increases [40, 42]. On the other hand, to reduce respiratory alkalosis, more bicarbonate will be produced from the kidneys to decrease the pH toward normal levels. This means that pulmonary ventilation is driven by low arterial PO2 and limited due to hypocapnia-induced alkalosis at the same time. This becomes clear when looking into Eq. (3), defining the alveolar ventilation as follows:

$$\mathbf{V\_{A}} = \mathbf{o}.86\mathbf{\hat{g}} \ge \mathbf{V}\mathbf{CO\_{z}} / \mathbf{P\_{A}}\mathbf{CO\_{z}}\tag{3}$$

VA is the alveolar ventilation, 0.863 is a constant, VCO2 is the CO2 output and PACO2 is the alveolar CO2. The ability to maintain oxygen homeostasis is essential and the physiological systems compete against each other to provide enough tissue O2 but also to maintain pH-homeostasis.

#### **3.2 Cardiovascular system**

To compensate for tissue hypoxaemia, the cardiovascular system must respond to maintain body functions. This is accomplished by increasing cardiac output, which is the product of stroke volume and heart rate [43]. Consequently, an increase in one of these variables will also lead to an increased volumetric flow rate. Upon ascent to hypoxic environments, the sympathetic nervous system activation leads to an initial increase in heart rate, cardiac output and blood pressure via the release of stress hormones [40, 44]. Stroke volume remains low in the first hours which is a consequence of reduced blood plasma volume because of bicarbonate diuresis. This occurs as a result of the fluid shift from the intravascular space and the suppression of aldosterone [40]. Interestingly, the sympathetic nervous system activation remains increased even if one is well acclimatized to altitude [45]. In contrast to sympathetic activation, cardiac output decrease once a certain level of hypoxia is reached after several days [46]. After a few days, e.g., muscle tissue adapts and extracts more O2 from the circulating blood by increasing the arterial–venous oxygen difference. This reduces the demand for higher cardiac output. Reductions in stroke volume can be attributed due to decreased plasma volume as well as the above-mentioned increased pulmonary vascular resistance. From the systemic circulation perspective, the endothelial autocoids nitric oxide and prostaglandins have received more attention as they are potentially mediating hypoxic vasodilation in the vessels [47]. Hypoxic-induced vasodilation will therefor quickly increase the blood flow to O2-deprived tissues. Low PaO2 levels will increase Ca2+ concentration inside the endothelial wall which might lead to increased synthetization of vasodilating endothelial factors [48]. The smooth muscle cells of the blood vessels also have K<sup>+</sup> ATP-channels, that are activated once the ATP/ADP quotient drops due to hypoxia. As a result of the increased conductivity of K+ , the cell membrane is hyperpolarized, followed by relaxation of the vascular muscle cells and vasodilation. This is especially well evoked in coronary and vertebral vessels [49].

*Physiological Adaptions to Acute Hypoxia DOI: http://dx.doi.org/10.5772/intechopen.102532*

PAO2 is, as mentioned earlier, at sea level around 100 mmHg and will decrease at altitude. At sea level, around 96% of haemoglobin is bound to O2 which can be seen in **Figure 2**. The oxyhaemoglobin dissociation curve plays a crucial role in O2 transport and demonstrates the interaction between the oxygen carrying capacity of haemoglobin and changes in partial pressure of oxygen [50]. When PAO2 drops to 50 mmHg at altitude, only about 80% of haemoglobin sites are bound to O2. The sigmoidal shape of the curve minimizes an abrupt decline in oxygen-carrying capacity of the blood. Another crucial adaptive process is, that the dissociation curve will shift to the left [51]. This is mediated by respiratory alkalosis and therefore rise in blood pH. This left shift causes that at a PAO2 of 50 mmHg, instead of 80%, around 90% of haemoglobin is bound to O2. As a result, more oxygen is bound on haemoglobin and more oxygen can be unloaded to the tissues [52].

#### **3.3 Cerebral system**

The brain consumes around 20% of the available oxygen at rest and is very sensitive to insufficient O2 supply [53]. The ability to process large amounts of oxygen (over a relatively small tissue mass) is necessary to support the high rate of ATP production to maintain an electrically active for the continual transmission of neuronal signals [54]. From this perspective, it is clear that hypoxia can have negative effects on cognitive function [55]. From the literature, it is well known that various factors have an important influence on cognitive impairment during hypoxia, in case they occur. These include the grade of hypoxia (e.g. altitude height), ambient temperatures, performing exercise tasks, individual physiological responses and the influence of PB [56].

One of the most sensitive regions of the central nervous system is the cerebral cortex. However, acute exposure to extreme hypoxia can also cause changes within wide regions of the brain. Subtle changes in the white and gray matter were already observed during ascending Mt. Everest and K2, reducing movement control and planning [57]. Motor speed and precision are also negatively affected in altitude compared to sea level performance [58, 59]. The complexity of central execution

#### **Figure 2.**

*S-shaped oxyhaemoglobin dissociation curve at sea level (solid black line). The curve is shifted left due to respiratory alkalosis under acute hypoxic exposure (broken gray line).*

tasks seems to play an important role when cognitive impairment is evaluated. Cognitive impairment seems to be more prominent when complex tasks must be solved rather than simple tasks [60, 61]. Indeed, altitude accidents that occur under hypoxia might be more related to poor judgment of complex situations as a consequence of hypoxic depression of cerebral function. However, also small mistakes or even small increases in reaction time [62] can also have fatal consequences.

However, the underlying mechanisms, why cognitive performance can be impaired during hypoxia are not fully understood [61]. Cerebral circulation, which is the product of arterial oxygen content and cerebral blood flow, is dependent on the net balance between hypoxic vasodilation and hypocapnia-induced vasoconstriction. It is well documented, that cerebral blood flow is increased under acute hypoxia to maintain cerebral O2-supply [54]. Cerebral blood flow increases, despite the hypocapnia, when arterial PO2 is less than 60 mmHg (altitude greater than 2800 m). Although, interindividual varieties in cerebral blood are linked to individual variations in the ventilatory response to hypoxia [63], cerebral oxygen delivery and global cerebral metabolism are well maintained under moderate hypoxia. If cerebral oxygen consumption is constant, the question arises of what causes the cognitive impairment at altitude. Cognitive changes might be related to specific neurotransmitters that are affected by mild hypoxia (e.g., serotonin, dopamine). Furthermore, alterations in blood flow and sensory displeasure, hyperhomocysteinemia and potential neuronal damage, and a decrease in catecholamine availability combined with psychological factors appear to play a key role for reduction in cognitive function during hypoxia [61]. In case cerebral tissue oxygenation is not maintained, brain injury will occur with fatal consequences [35]. Compensatory hyperventilation, tachycardia and increased cerebral blood flow can partially maintain cerebral oxygen delivery, however, if these mechanisms work inadequately, the brain will be the first organ to be compromised.

#### **4. Clinical consequences**

This chapter aimed to give an overview of the main hypoxia types and the main physiological consequences. Hypoxia can occur due to occupational responsibilities, recreationally but also under pathological conditions. Ascend to altitude or exposure to environments that lower the PiO2 will have direct consequences to the entire body systems, however various modulators such as PB, the severity of hypoxia, interindividual variability, health condition and others determine the physiological consequences and adaption processes. Exposing the body specifically to hypoxic environments can be used as a therapeutic tool, to increase sports performance or to achieve other goals [64]. However, it is important to precisely understand the different types of hypoxia and what consequences they have on the human body. Clinical manifestations of hypoxia underly inter-individual variations of cardiorespiratory and other physiological responses as well as the origin of hypoxia. In general, there are two major causes of hypoxia at the tissue level which are reduced blood flow to the tissues or reduced O2 content in the blood itself [65, 66]. As a result, four main types of hypoxia arise. First, hypoxaemic hypoxia, where the O2 transport to or through the alveoli is impaired [6]. Second, anemic hypoxia where the oxygen-carrying capacity is reduced due to e.g., severe blood loss, iron and folate deficiency, haemoglobin pathologies or functional insufficiency to carry O2 [10, 12, 14]. Third, stagnant hypoxia where the transport of O2 to the tissue is impaired while the blood may be sufficiently oxygenated [6]. Finally, histotoxic hypoxia exists, where the O2 is delivered to the tissues but they are unable to utilize oxygen effectively [12].

#### *Physiological Adaptions to Acute Hypoxia DOI: http://dx.doi.org/10.5772/intechopen.102532*

It is important to understand, how these types influence oxygen delivery to the tissues. The product of O2 content and blood flow is considered to reflect the oxygen delivery for the whole body (or to the individual organ system). As oxygen content is the sum of dissolved oxygen and that bound to haemoglobin, total oxygen delivery can be calculated according to Eq. (4):

$$\mathrm{DO}\_{\mathrm{z}} = \left(\mathrm{SaO}\_{\mathrm{z}} / \texttt{zoo} \times \left[\mathrm{Hb}\right] \times \texttt{z.g4} + \mathrm{P}\_{\mathrm{z}}\mathrm{O}\_{\mathrm{z}} \times \texttt{o.o2g}\right) \times \texttt{blood flow} \tag{4}$$

DO2 is the O2 delivery (ml min−1); PaO2 is the partial pressure of oxygen (kPa); SaO2 is the arterial oxygen saturation in percentage; Hb is the haemoglobin content (g dl−1); 0.023 is the solubility of oxygen (in ml dl−1 kPa−1); 1.34 is Hüfner's constant, the oxygen-carrying capacity of saturated haemoglobin (ml g−1); and blood flow (i.e., cardiac output) in dl min−1 [67]. From this equation, it can be seen that hypoxaemic hypoxia (via reduced PaO2 and SaO2), stagnant hypoxia (via reduced blood flow) and anemic hypoxia (via reduced haemoglobin content) may cause tissue hypoxia, as these three types reduce oxygen delivery. In contrast, there is no oxygen delivery deficiency in histotoxic hypoxia but rather an impairment of the tissue to use O2 [35]. Reduced oxygen tension, hypoventilation, ventilation-perfusion mismatch, right to left shunt and impaired diffusion of oxygen can all lead to hypoxia in the body [12].

The primary measurement to evaluate the hypoxic disease state is the analysis of arterial blood gas. Using this measurement, important parameters such as partial pressure of oxygen, partial pressure of carbon dioxide, acidity (pH), oxyhaemoglobin saturation and bicarbonate concentration in arterial blood can be assessed [68]. Management and treatment of persons under hypoxia should be started as soon as the evaluation has been successfully finished, and follows three categories: maintaining patent airways, increasing the oxygen content of the inspired air and improving the diffusion capacity [69–71]. Without adequate adaption processes and management, an imbalance between oxygen demand and oxygen delivery will occur leading to impaired homeostasis within the body. Therefore, healthcare practitioners (e.g., physiotherapists, sports scientists, exercise physiologists and others) should be able to understand the causes, types and consequences of hypoxia.

#### **5. Conclusion**

In this chapter, an overview is presented on the main types of hypoxia and the physiological consequences of the main systems. Hypoxaemic, anemic, stagnant and histotoxic hypoxia originate from different etiologies. Hypoxia to the tissues can be caused by any obstacle in the oxygen cascade, beginning from the O2 molecule in the atmosphere, until being the final electron acceptor within the mitochondria to generate ATP. However, the adult compensatory mechanisms to counteract the acute hypoxic state are mainly based on our ability to hyperventilate, adequately adapt the cardiovascular response and to increase oxygen uptake to provide enough tissue O2. This chapter might contribute to improving the understanding of the different types of hypoxia and to understand the physiological responses.

#### **Conflict of interest**

The author declares no conflict of interest.

*Exercise Physiology*

#### **Author details**

Erich Hohenauer1,2,3,4

1 University of Applied Sciences and Arts of Southern Switzerland, Landquart, Switzerland

2 International University of Applied Sciences THIM, Landquart, Switzerland


\*Address all correspondence to: erich.hohenauer@supsi.ch

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Physiological Adaptions to Acute Hypoxia DOI: http://dx.doi.org/10.5772/intechopen.102532*

### **References**

[1] Taylor CT. Mitochondria and cellular oxygen sensing in the HIF pathway. The Biochemical Journal. 2008;**409**(1):19-26

[2] Richalet J-P. CrossTalk opposing view: Barometric pressure, independent of , is not the forgotten parameter in altitude physiology and mountain medicine. The Journal of Physiology. 2020;**598**(5): 897-899

[3] Conkin J, Wessel JH 3rd. Critique of the equivalent air altitude model. Aviation, Space, and Environmental Medicine. 2008;**79**(10):975-982

[4] Roach RC, Hackett PH, Oelz O, Bartsch P, Luks AM, MacInnis MJ, et al. The 2018 Lake Louise Acute Mountain sickness score. High Altitude Medicine & Biology. 2018;**19**(1):4-6

[5] Wilson MH, Newman S, Imray CH. The cerebral effects of ascent to high altitudes. Lancet Neurology. 2009;**8**(2):175-191

[6] Pittman RN. Regulation of Tissue Oxygenation. Integrated Systems Physiology: From Molecule to Function to Disease. San Rafael (CA): Morgan & Claypool Life Sciences; 2011

[7] Hantzidiamantis PJ, Amaro E. Physiology, Alveolar to Arterial Oxygen Gradient. Treasure Island (FL): StatPearls; 2021

[8] Patel H, Kerndt CC, Bhardwaj A. Physiology, Respiratory Quotient. Treasure Island (FL): StatPearls; 2021

[9] Coleman MD. Chapter 2 - respiratory and pulmonary physiology. In: Duke J, editor. Anesthesia Secrets. Fourth ed. Philadelphia: Mosby; 2011. pp. 17-23

[10] Manninen PH, Unger ZM. Chapter 21 - hypoxia. In: Prabhakar H, editor. Complications in Neuroanesthesia. San Diego: Academic Press; 2016. pp. 169-180 [11] Brown LK. Hypoventilation syndromes. Clinics in Chest Medicine. 2010;**31**(2):249-270

[12] Bhutta BS, Alghoula F, Berim I. Hypoxia. Treasure Island (FL): StatPearls; 2021

[13] Rhodes CE, Varacallo M. Physiology, Oxygen Transport. Treasure Island (FL): StatPearls; 2021

[14] Lee EJ, Hung YC, Lee MY. Anemic hypoxia in moderate intracerebral hemorrhage: The alterations of cerebral hemodynamics and brain metabolism. Journal of the Neurological Sciences. 1999;**164**(2):117-123

[15] Phillips J, Henderson AC. Hemolytic Anemia: Evaluation and differential diagnosis. American Family Physician. 2018;**98**(6):354-361

[16] Sleijfer S, Lugtenburg PJ. Aplastic anaemia: A review. The Netherlands Journal of Medicine. 2003;**61**(5):157-163

[17] Chaudhry HS, Kasarla MR. Microcytic Hypochromic Anemia. Treasure Island (FL): StatPearls; 2021

[18] Nagao T, Hirokawa M. Diagnosis and treatment of macrocytic anemias in adults. Journal of General and Family Medicine. 2017;**18**(5):200-204

[19] Bleecker ML. Carbon monoxide intoxication. In: Handbook of Clinical Neurology. Vol. 131. 2015. pp. 191-203

[20] Ludlow JT, Wilkerson RG, Nappe TM. Methaemoglobinemia. Treasure Island (FL): StatPearls; 2021

[21] Benz EJ, Ebert BL. Chapter 43 - Hemoglobin variants associated with Hemolytic Anemia, altered oxygen affinity, and Methaemoglobinemias. In: Hoffman R, Benz EJ, Silberstein LE, Heslop HE, Weitz JI, Anastasi J, et al.,

editors. Hematology. Seventh ed. Philadelphia, PA, United States of America: Elsevier; 2018. pp. 608-615

[22] Cheung SS. Responses of the hands and feet to cold exposure. Temperature (Austin). 2015;**2**(1):105-120

[23] Feher J. 6.4 - oxygen and carbon dioxide transport. In: Feher J, editor. Quantitative Human Physiology. Second ed. Boston: Academic Press; 2017. pp. 656-664

[24] Wyman J. Facilitated diffusion and the possible role of myoglobin as a transport mechanism. The Journal of Biological Chemistry. 1966;**241**(1):115-121

[25] Graham J, Traylor J. Cyanide Toxicity. Treasure Island (FL): StatPearls; 2021

[26] Pauluhn J. Risk assessment in combustion toxicology: Should carbon dioxide be recognized as a modifier of toxicity or separate toxicological entity? Toxicology Letters. 2016;**262**:142-152

[27] Huzar TF, George T, Cross JM. Carbon monoxide and cyanide toxicity: Etiology, pathophysiology and treatment in inhalation injury. Expert Review of Respiratory Medicine. 2013;**7**(2):159-170

[28] Goldfarb-Rumyantzev AS, Alper SL. Short-term responses of the kidney to high altitude in mountain climbers. Nephrology Dialysis Transplantation. 2013;**29**(3):497-506

[29] Dietz TE, Hackett PH. 42 - highaltitude medicine. In: Keystone JS, Kozarsky PE, Connor BA, Nothdurft HD, Mendelson M, Leder K, editors. Travel Medicine. Fourth ed. London: Elsevier; 2019. pp. 387-400

[30] MacIntyre NR. Tissue hypoxia: Implications for the respiratory clinician. Respiratory Care. 2014;**59**(10):1590-1596

[31] Michiels C. Physiological and pathological responses to hypoxia. The American Journal of Pathology. 2004;**164**(6):1875-1882

[32] Duke HN, Killick EM. Pulmonary vasomotor responses of isolated perfused cat lungs to anoxia. The Journal of Physiology. 1952;**117**(3):303-316

[33] McMurtry IF, Davidson AB, Reeves JT, Grover RF. Inhibition of hypoxic pulmonary vasoconstriction by calcium antagonists in isolated rat lungs. Circulation Research. 1976;**38**(2):99-104

[34] Post JM, Hume JR, Archer SL, Weir EK. Direct role for potassium channel inhibition in hypoxic pulmonary vasoconstriction. The American Journal of Physiology. 1992;**262**(4 Pt 1):C882- C890

[35] Kane AD, Kothmann E, Giussani DA. Detection and response to acute systemic hypoxia. BJA Education. 2020;**20**(2):58-64

[36] Peers C, Kemp PJ. Acute oxygen sensing: Diverse but convergent mechanisms in airway and arterial chemoreceptors. Respiratory Research. 2001;**2**(3):145-149

[37] Lopez-Barneo J, Pardal R, Ortega-Saenz P. Cellular mechanism of oxygen sensing. Annual Review of Physiology. 2001;**63**:259-287

[38] Hallett S, Toro F, Ashurst JV. Physiology, Tidal Volume. Treasure Island (FL): StatPearls; 2021

[39] Paralikar SJ, Paralikar JH. Highaltitude medicine. Indian Journal of Occupational and Environmental Medicin. 2010;**14**(1):6-12

[40] Hackett P, Roach R. High Altitude Medicine. Maryland Heights, MO, United States of America: Mosby; 2001. pp. 1-37

[41] Brinkman JE, Sharma S. Respiratory Alkalosis. Treasure Island (FL): StatPearls; 2021

*Physiological Adaptions to Acute Hypoxia DOI: http://dx.doi.org/10.5772/intechopen.102532*

[42] Lipsitz LA, Hashimoto F, Lubowsky LP, Mietus J, Moody GB, Appenzeller O, et al. Heart rate and respiratory rhythm dynamics on ascent to high altitude. British Heart Journal. 1995;**74**(4):390-396

[43] Talbot NP, Balanos GM, Dorrington KL, Robbins PA. Two temporal components within the human pulmonary vascular response to approximately 2 h of isocapnic hypoxia. Journal of Applied Physiology. 2005;**98**(3):1125-1139

[44] Mazzeo RS, Wolfel EE, Butterfield GE, Reeves JT. Sympathetic response during 21 days at high altitude (4,300 m) as determined by urinary and arterial catecholamines. Metabolism. 1994;**43**(10):1226-1232

[45] Domej W, Schwaberger G. Physiologie der mittleren, großen und extremen Höhen. In: Berghold F, Brugger H, Burtscher M, Domej W, Durrer B, Fischer R, et al., editors. Alpin- und Höhenmedizin. Berlin, Heidelberg: Springer Berlin Heidelberg; 2019. pp. 337-354

[46] Wagner PD. Reduced maximal cardiac output at altitude--mechanisms and significance. Respiration Physiology. 2000;**120**(1):1-11

[47] Busse R, Pohl U, Kellner C, Klemm U. Endothelial cells are involved in the vasodilatory response to hypoxia. Pflügers Archiv. 1983;**397**(1):78-80

[48] Franco-Obregon A, Lopez-Barneo J. Low PO2 inhibits calcium channel activity in arterial smooth muscle cells. The American Journal of Physiology. 1996;**271**(6 Pt 2):H2290-H2299

[49] Pohl U, de Wit C. Der Sauerstoff im Gewebe. In: Brandes R, Lang F, Schmidt RF, editors. Physiologie des Menschen: mit Pathophysiologie. Berlin, Heidelberg: Springer Berlin Heidelberg; 2019. pp. 365-375

[50] Brown JP, Grocott MP. Humans at altitude: Physiology and pathophysiology. Continuing Education in Anaesthesia, Critical Care and Pain. 2012;**13**(1):17-22

[51] Thorborg PAJ. CHAPTER 40 - blood gas analysis. In: Papadakos PJ, Lachmann B, Visser-Isles L, editors. Mechanical Ventilation. Philadelphia: W.B. Saunders; 2008. pp. 457-470

[52] Kenney WL, Wilmore JH, Costill DL. Physiology of Sport and Exercise. 6th ed. Champaign, IL, United States of America: Human Kinetics; 2015

[53] Attwell D, Laughlin SB. An energy budget for signaling in the grey matter of the brain. Journal of Cerebral Blood Flow and Metabolism. 2001;**21**(10):1133-1145

[54] Hoiland RL, Bain AR, Rieger MG, Bailey DM, Ainslie PN. Hypoxemia, oxygen content, and the regulation of cerebral blood flow. American Journal of Physiology Regulatory, Integrative and Comparative Physiology. 2016;**310**(5): R398-R413

[55] Nakata H, Miyamoto T, Ogoh S, Kakigi R, Shibasaki M. Effects of acute hypoxia on human cognitive processing: A study using ERPs and SEPs. Journal of Applied Physiology. 2017;**123**(5): 1246-1255

[56] Virués-Ortega J, Buela-Casal G, Garrido E, Alcázar B. Neuropsychological functioning associated with high-altitude exposure. Neuropsychology Review. 2004;**14**(4):197-224

[57] Di Paola M, Bozzali M, Fadda L, Musicco M, Sabatini U, Caltagirone C. Reduced oxygen due to high-altitude exposure relates to atrophy in motorfunction brain areas. European Journal of Neurology. 2008;**15**(10):1050-1057

[58] Berry DT, McConnell JW, Phillips BA, Carswell CM, Lamb DG, Prine BC. Isocapnic hypoxemia and neuropsychological functioning. Journal of Clinical and Experimental Neuropsychology. 1989;**11**(2):241-251

[59] Hornbein TF, Townes BD, Schoene RB, Sutton JR, Houston CS. The cost to the central nervous system of climbing to extremely high altitude. The New England Journal of Medicine. 1989;**321**(25):1714-1719

[60] Petrassi FA, Hodkinson PD, Walters PL, Gaydos SJ. Hypoxic hypoxia at moderate altitudes: Review of the state of the science. Aviation, Space, and Environmental Medicine. 2012;**83**(10): 975-984

[61] Taylor L, Watkins SL, Marshall H, Dascombe BJ, Foster J. The impact of different environmental conditions on cognitive function: A focused review. Frontiers in Physiology. 2015;**6**:372

[62] Cavaletti G, Tredici G. Long-lasting neuropsychological changes after a single high altitude climb. Acta Neurologica Scandinavica. 1993;**87**(2):103-105

[63] Ainslie PN, Poulin MJ. Ventilatory, cerebrovascular, and cardiovascular interactions in acute hypoxia: Regulation by carbon dioxide. Journal of Applied Physiology. 2004;**97**(1):149-159

[64] Heinonen IH, Boushel R, Kalliokoski KK. The circulatory and metabolic responses to hypoxia in humans - with special reference to adipose tissue physiology and obesity. Front Endocrinol (Lausanne). 2016;**7**:116

[65] Gaspar JM, Velloso LA. Hypoxia inducible factor as a central regulator of metabolism - implications for the development of obesity. Frontiers in Neuroscience. 2018;**12**:813

[66] Mesarwi OA, Loomba R, Malhotra A. Obstructive sleep Apnea, hypoxia, and nonalcoholic fatty liver disease. American Journal of Respiratory and Critical Care Medicine. 2019;**199**(7):830-841

[67] McLellan SA, Walsh TS. Oxygen delivery and haemoglobin. Continuing Education in Anaesthesia, Critical Care and Pain. 2004;**4**(4):123-126

[68] Sharma S, Hashmi MF. Partial Pressure of Oxygen. Treasure Island (FL): StatPearls; 2021

[69] Chen DW, Park R, Young S, Chalikonda D, Laothamatas K, Diemer G. Utilization of continuous cardiac monitoring on hospitalist-led teaching teams. Cureus. 2018;**10**(9):e3300

[70] Vali P, Underwood M, Lakshminrusimha S. Hemoglobin oxygen saturation targets in the neonatal intensive care unit: Is there a light at the end of the tunnel? (1). Canadian Journal of Physiology and Pharmacology. 2019;**97**(3):174-182

[71] Saito-Benz M, Sandle ME, Jackson PB, Berry MJ. Blood transfusion for anaemia of prematurity: Current practice in Australia and New Zealand. Journal of Paediatrics and Child Health. 2019;**55**(4):433-440

#### **Chapter 4**

## Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism Spectrum Disorder

*Thai Duy Nguyen*

### **Abstract**

Sleep problems are widespread, and sleep disorders are frequent in children with autism spectrum disorders (ASD). Physical activities (PA) are considered a practical, non-pharmacological approach for improving sleep. This study aims to explore the impact of PA on sleep in children with or without ASD. Seventy-five children were recruited, including 57 children with ASD and 18 typically developing (TD) children as control. Participants wore an accelerometer monitor (Sense Wear® Pro Armband 3, Body media) for 6 consecutive days and nights to assess sleep and PA. The results indicated ASD children had limited participation in PA compared with TD children (Total time for PA: 156 ± 79 vs. 216 ± 59 minutes on weekdays; 145 ± 93 vs. 178 ± 108 minutes on weekend). The children usually had more opportunities to participate in PA on weekdays and they tended to resist recommended bedtime (Sleep duration: 7.0 ± 0.8 vs. 9.6 ± 1.2 hours with ASD children; 7.1 ± 0.7 vs. 9.5 ± 1 hours with TD children). It also reported PA with moderate to vigorous intensity was better to improve sleep in children both with and without ASD. Finally, this study recommended promoting PA will help to improve sleep quality and reduce sedentary behaviors for children with ASD in particular and children in general.

**Keywords:** autism spectrum disorders, sleep disorder, physical activity, sleep quality

#### **1. Introduction**

Autism spectrum disorder (ASD) is known as a developmental disorder characterized by social communication difficulties and repetitive behavior. This is a complex syndrome related to genetic and environmental factors [1]. Great concerns about the high prevalence of poor sleep and the impact of sleep disturbance on ASD children are widely reported worldwide [2]. It is estimated that sleep disorders affect up to 80% of children with ASD compared with 10–25% of typically developing (TD) children [3, 4]. Children with ASD often face difficulties with sleep, and this has a strong relationship with daytime behavior problems; the most frequently reported issues include difficulty falling asleep, restless sleep, and frequent waking [5, 6]. Disturbed sleep could also exacerbate the core symptoms

of ASD. Sleep education, environmental changes, behavioral interventions, and exogenous melatonin medication are frequently used for promoting and improving sleep quality [7, 8]. Improving the quality of sleep plays a critical role for children because sleep helps to optimize cognition, memory, behavioral adjustment, and learning [9].

Compared with TD children, the rate of sleep problems is higher in children with ASD. Significant impairments in social interaction and restricted behavior, combined with increased rates of motor problems, are frequently observed in individuals with ASD [10]. It may make these children less motivated and less likely to participate in physical activities (PA), leading to the risk of increased sedentary behavior (SB). It also may contribute to harmful health outcomes like overweight or obesity [11]. Recent reports showed difficulties in motor skills and motor capacities for ASD children compared with TD children, and limitations in PA may reduce opportunities for social interaction and learning in children with ASD [12, 13].

Physical activity is defined as any form of movement that leads to energy expenditure and is not performed in competition, including all daily activities, leisure activities, and exercises [14]. PA is indispensable for children's health. However, most children in the world do not participate in at least 60 minutes per day of moderate to vigorous physical activity (MVPA) as was recommended [15, 16]. Studies showed children diagnosed with ASD had PA levels lower than typically developed peers [17]. There are many individuals, social, and community barriers that make PA participation more difficult and may contribute to increased screen time by children with ASD [18]. Evidence has also been presented of PA decreasing negative behaviors and promoting positive behaviors. It improved social contacts and friendships and increased motor skills [11]. Thus, participation in PA is particularly essential for children with developmental disabilities, who could potentially benefit from increased PA and reduced SB; it has a positive impact on their development, quality of life, health, and future [9].

A reciprocal relationship between sleep and PA has been documented in children with and without ASD. Increasing exercise has been reported as helping produce better sleep quality, reduced weight, pain prevention, and improved mood in insomnia patients [19]. Adjusting factors of PA such as level, intensity, and duration of exercise has a positive effect on sleep quality [20]. Association between sleep patterns and PA levels suggests that being more physically active tends to support healthier sleep in children without disabilities [21]. Other studies also revealed a significant improvement in sleep efficiency, sleep onset latency, sleep duration, and wake after sleep onset with increased PA. It highlighted the role of PA in improving sleep quality among children with ASD [22]. Accordingly, regular moderate-intensity PA is recommended to treat and prevent sleep disorders without using medications [23]. In contrast, sleep disorders can lead to reduced cognitive performance and PA, while increasing the risk of injury during exercises. Getting insufficient sleep has been identified as a risk factor associated with public health problems such as obesity, depression, and limited PA [19]. Also, poor sleep was associated with higher rates of repetitive behavior and had a negative effect on challenging behaviors [24].

The mechanism of how PA affects sleep is not yet fully understood. Therefore, new studies must be carried out to understand the benefit of PA in the promotion of sleep and understand better the physiological responses to sleep loss. Within the scope of this study, we wanted to explore the relationship between PA intensity and sleep quality, its specific impact on improving sleep parameters. Thereby, it is possible to establish an optimal PA plan as a non-drug intervention to improve sleep quality as well as the quality of life in children with ASD.

*Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*

#### **2. Method**

This study was approved by the local Ethics Committee of the Hospital (N°A00-865 40). It was conducted according to the Declaration of Helsinki and registered on the Clinicaltrials.gov registry (N°CT: 02830022).

#### **2.1 Subjects**

Each subject and their parents received both written and oral information, and those that agreed to participate signed a consent form. Seventy-five children were recruited to participate in the study, including 57 children with ASD and 18 typically developing children as a control group. All of them attended regular schools. Diagnosis of ASD was performed by experienced physicians and psychologists, according to the Diagnostic and Statistical Manual of Mental Disorders 5th edition criteria [25]. The subjects were also assessed with the Autism Diagnostic Observation Schedule (ADOS) [26]. Intelligence Quotient (IQ ) was estimated using the Wechsler Intelligence Scale for Children, 4th edition [27]. IQ criterion for children is IQ > 70, excluding children with intellectual disabilities (IQ < 70). Following the ethical guidelines, IQ scores and ADOS results were not provided to researchers. However, score certification of IQ > 70 for all ASD children in this study was confirmed by a clinical psychologist experienced in diagnosing children with ASD and autism. Children with psychiatric disorders, comorbid medical conditions, contraindications for exercise, and those taking medication were excluded from the study [9].

#### **2.2 Actigraphy**

Participants wore the accelerometer monitor (Sensewear® Pro Armband 3, Body media) for 6 days and nights (5 weekdays and 1 weekend day). Participants and their parents completed daily diaries to distinguish periods in which participants did not wear the accelerometer (shower or bath, swimming, or other water activities). Time not wearing the device was excluded from the analysis. The monitoring device used in this study is a bi-axial accelerometer, worn on the right arm triceps. It can estimate energy expenditure based on algorithms from measured parameters such as acceleration, heat flux, galvanic skin response, skin temperature, near-body temperature, and demographic characteristics like sex, age, height, and weight [9].

This device can measure sleep parameters such as sleep time, sleep latency, wake up time, wake after sleep onset (WASO), and sleep efficiency. It was also used to calculate the parameters related to PA, such as the time spent for PA with different intensities and energy expenditure for PA. In the experiment period, children slept in their own bedroom, and their parents often described a consistent bedtime routine.

#### **2.3 Child sleep diary**

Children and their parents recorded information related to sleep each night for 6 consecutive days. It included bedtime (the time when the children went to bed each evening), wake up time (the time when the children woke up each morning), and sleep time (parents' estimation of duration of the children's sleep time each night).

Parents of the children also completed other questionnaires on sleep, physical activity, and parental assessments.

• The children's sleep habits questionnaire (CSHQ ): This is the most used questionnaire to evaluate the sleep of ASD children, translated into French. CSHQ included 45 items with scores rated from 1 to 3, and was divided into eight subscales (bedtime resistance, sleep onset delay, sleep duration, sleep anxiety, night wakings, parasomnias, sleep-disordered breathing, and daytime sleepiness). CSHQ's total score was calculated and compared with the threshold value of 41. CSHQ's total score higher than 41 indicated sleep disorders or low sleep quality [28].


#### **2.4 Statistics**

The data collected by actigraphy, sleep diary, and questionnaires were processed by specialized software (Sensewear Software) and Excel software in different ways. We calculated the average values of weekdays (WD), weekends (WE), and all days (AD) during the experiment for each child. Data used for statistical analysis were the mean values ± standard deviation. The differences of data between questionnaires and actigraphy method; WD and WE measured by actimetry in children with and without ASD were compared by R software (*t*-test, Pearson's chi-squared, one-way test with significance considered as *p* < 0.05). The relationship between factors related to sleep and PA was assessed by correlation and linear regression with significance considered as *p* < 0.05 (R software). Finally, principal component analysis (PCA) and agglomerative hierarchical cluster analysis (AHCA) were applied to classify individuals according to the component group (R software). In this study, we had *n* = 75 observations (57 children with ASD, 18 control children) and *p* = 24 predictors (anthropometric characteristics and data from monitoring devices). We used the elastic net method and appropriate criteria to select variables [12]. Finally, only 17 pertinent variables were used for PCA and AHCA.

The factors related to sleep used for analysis were total time on the bed (h), sleep duration (h), sleep quality index (%), bedtime resistance (min), sleep latency (min), wake-up time resistance (min), awakening latency (min), and wake after sleep onset (min). The factors related to PA used for analysis were sleep energy expenditure (kcal), total PA energy expenditure in 24 h (kcal), MVPA energy expenditure in 24 h (kcal), sedentary PA energy expenditure in 24 h (kcal), total time for PA (min), time for sedentary PA (min), time for moderate PA (min), time for MVPA (min), time for vigorous PA (min), time for strong vigorous PA (min), and daily step number.

#### **3. Results**

No difference between children with or without ASD was found with regard to demographic characteristics. However, we observed ASD children had a low PAQ-C score and a higher CSHQ score than control children as reported by their parents. Also, sleep duration as collected by questionnaires was more than by monitoring device by around 2.6 hours (*p* < 0.001) in ASD children and 2.4 hours (*p* < 0.001) in control children (**Table 1**).


#### *Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*


*\$\$p < 0.05 significantly different between ASD group and control group on weekdays.*

*≠p < 0.05 significantly different between ASD group and control group on weekend.*

**Table 1.**

*Demographic data, and characteristics of sleep and PA.*

*Exercise Physiology*

*Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*

No difference was found on PA factors between weekdays and weekends in ASD children, but there were differences in control children. They were more active in PA participation on weekdays than weekends (**Table 1**). On weekdays, ASD children had less energy expenditure for MVPA and time for PA (moderate, moderate to vigorous, vigorous, and strong vigorous) than control children. Meanwhile, they had more time for sedentary PA than control children on both weekdays and weekends. No difference in sleep factors was found between the two groups (**Table 1**).

Principal component analysis (PCA) and agglomerative hierarchical cluster analysis (AHCA) were performed with 17 pertinent variables. PCA results indicated five main component groups which helped explain 86.1% of the variance, with an eigenvalue ≥1. Two clusters were determined with blue space representing ASD children and yellow space representing control children (**Figure 1**). Two children with ASD (17, 23) and one control child (70) were classified outside of these clusters. In this graphic representation, a child on the same side as a given variable obtained a high score for this variable. A low value for this variable was attributed to a child on the opposite side. The distribution of children in both groups was not focused on their specific clusters. ASD children had discrete distribution (blue cluster), while control children were more concentrated (yellow cluster).

Child #17 was characterized by a total of daily steps twice the group average (25,620 vs. 12,354 steps/24 h) and had the highest time for vigorous PA (117.87 vs. 17.87 min/24 h), strong vigorous PA (16.17 vs. 2.07 min/24 h) compared with the group average. Child #23 was characterized by a total PA energy expenditure two times higher than the group average (3826 vs. 1581 kcal/24 h) and a sleep latency multiplied by 2.5 compared to the other children (35.4 vs. 13.6 min/24 h). Child #70 was characterized by a total PA energy expenditure twice the group average (3470 vs. 1642 kcal/24 h) and the highest sleep energy expenditure of all children in the group (500 vs. 280 kcal/24 h).

#### **Figure 1.**

*Principal component analysis biplot of PA and sleep. ASD children are represented from 1 to 57, control children are represented from 58 to 75. (a1) Total time on bed (h); (a2) sleep duration; (a3) sleep quality index (%); (a4) bedtime resistance (min); (a5) sleep latency (min); (a7) awakening latency (min); (a8) wake after sleep onset (min); (a9) sleep energy expenditure (kcal); (a10) total PA energy expenditure (kcal); (a11) MVPA energy expenditure (kcal); (a12) sedentary PA energy expenditure (kcal); (a13) total time for physical activity; (a14) time for sedentary PA (min); (a15) time for moderate PA (min); (a16) time for MVPA (min); (a17) time for vigorous PA (min); and (a19) daily steps number.*

**Figure 2.** *(a) Dendrogram of individual's classification by AHCA. (b) Factor map of individual's classification by AHCA. \* Cluster 1 (saffron), cluster 2 (pink), cluster 3 (gray), and cluster 4 (green).*

The results of an individual's classification by AHCA in **Figure 2** showed the ranking of each child and clusters in which they were classified. Based on the dendrogram graph, all children with similar characteristics in both the ASD group (green color) and the control group (red color) were classified into four different clusters. The characteristics of children in clusters were shown by comparing the result of the mean values of variables (**Table 2**).

• Cluster 1 (saffron): A total of 22 ASD children. This cluster is characterized by children with limited participation in PA and bad sleep. They had the lowest


*Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*

#### **Table 2.**

*Characteristics of ASD children in classification clusters.*

PA (a11, a13, a15, a16, a17, and a19) except for sedentary PA (a12 and a14) and low sleep quality (a3) compared with other clusters.

• Cluster 2 (pink): A total of 24 members, including 18 ASD children and six control children. This cluster was characterized by children with moderate participation in PA and good sleep. They had high sleep quality (a3), high sleep duration (a2), and were moderate for PA compared with other clusters.


#### **4. Discussion**

Most current studies still have not explained how PA affects sleep exactly and vice versa. PA and sleep influence each other through multiple complex interactions, both physiological and psychological [19]. PA is considered beneficial for improving sleep quality, but the effectiveness of PA-based interventions remains a question [30]. Conversely, sleep problems could increase symptoms of anxiety and depression, and thereby indirectly affect PA performance.

According to the survey results, we found a difference between children in the two groups. PAQ-C score indicated ASD children had PA levels lower than control children. CSHQ score presented higher sleep problems in ASD children than control children. Besides these, parent-reported estimated sleep time was higher than actigraphymeasured sleep time by 37.1% in ASD children and 33.8% in control children (**Table 1**). This demonstrated the children did not go to bed according to the schedule that their parents set. It was consistent with data collected from the monitoring device about total time in bed being more than sleep duration. Moreover, studies have reported on factors affecting sleep in a modern society like sleep environment, lifestyle habits, high-tech devices, physical activities, and learning activities [18, 31, 32]. Also, the downside of social development, children were free in their own rooms with little control from their parents. Therefore, they tended to resist recommended bedtime and fell asleep later. A typical example was when children went to bed, and even were lying in bed, but did not sleep, and instead, read stories or used smart entertainment devices.

Comparing results between children in the two groups, we observed ASD children had less participation in PA than control children. They had a low energy consumption for MVPA, daily step number, and total time for PA compared with control children on weekdays (**Table 1**). Also, time for MVPA, vigorous PA, and strong vigorous PA was equal to 74.7, 42.8, and 28.6% of control children on weekdays. Meanwhile, the time for sedentary PA was higher than in the control group both weekdays and weekends (**Table 1**). It proved ASD children often faced difficulties related to PA, especially MVPA, and tended to increase sedentary behaviors. Recent studies on the relevance of obesity and sedentary PA to sleep in adolescents and children with ASD showed similar results [33, 34]. No any significant differences in sleep between ASD children and control children, the reason was PA does not always affect sleep directly, as sleep also depends on control factors (such as age, health status, and mode and intensity of exercise intervention) or psychological factors [35, 36]. Our results also indicated control children had more active participation in PA (MVPA, vigorous PA, and daily steps) on weekdays compared to the weekend (**Table 1**). These differences may come from children usually going to school and participating in school activities on weekdays, while ASD children tended to be less sedentary and have less PA participation than TD children [37]. On the weekend, children were free to stay at home with their families, so they tended to have less PA participation.

*Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*

PCA and AHCA analysis showed characteristics of PA and sleep in all children. We identified two relatively distinct clusters on the factors related to PA and sleep by PCA. One cluster included ASD children who had a positive correlation with sedentary PA, and the cluster with control children had a positive correlation with PA from moderate to vigorous, except for sedentary PA (**Figure 1**). Then, we presented the classification of individuals more clearly by AHCA, with four clusters determined to have a higher rate of ASD children than control children (**Figure 2**, **Table 2**). All of cluster 1 was ASD children; its characteristics were the lowest level of PA participation, highest sedentary behaviors, and bad sleep quality. This was consistent with the characteristics of children with ASD [6, 38]. Cluster 2 had 75% ASD children; its characteristics were a moderate level of PA participation, but they had better sleep in both duration and quality. Cluster 3 contained 57.7% ASD children; its characteristics were the highest level of PA participation, lowest sedentary behaviors, and worst sleep. Meanwhile, cluster 4 had 66.67% ASD children; its characteristics were a moderate level of PA participation and the best sleep quality. These classification results showed a difference between sedentary PA in ASD children and active PA participation in control children. Also, they indicated that PA with moderate to vigorous intensity was related to good sleep while limited participation in PA or strong vigorous PA was related to poor sleep. The positive effect of physical activity on sleep quality has also been discussed in studies of children with ASD [7, 39].

The findings in our study suggested the role of PA in improving sleep quality. Better sleep was the result of increased sleep duration and decreased sleep latency and wake after sleep onset. We should spend more daily energy consumption on MVPA, vigorous PA. It helps to increase PA and reduce SB. MVPA also was reported to enhance sleep quality by decreasing sleep latency and wake after sleep onset [40, 41]. Thus, we recommended increasing PA with moderate to vigorous intensity and sleep duration for improved sleep quality, especially with ASD children. This suggestion is in line with results reported in a comprehensive review of studies about the effects of PA on sleep quality with different PA intensities [23].

#### **5. Conclusion**

This study indicated ASD children tend to have low participation in PA and increased sedentary behaviors compared to control children. These children had more active PA participation on weekdays than the weekend, and they tended to resist bedtime by parents' request. Also, we provided evidence that PA with moderate to vigorous intensity can improve sleep quality, especially for children with ASD. It could be used as a non-pharmacological method to treat sleep disorders for ASD children. However, the nature and the magnitude of this impact are still controversial. Future studies need to clarify the mechanism of PA intensity effects on sleep quality. This way, they can give PA protocols based on reliable evidence to promote PA and prevent sedentary behaviors in children with ASD. This study also contributed to palliative treatment for children with ASD.

#### **6. Limitations**

The main limitation of our study was a disparity in the number of children between the ASD group and the control group. The sample sizes of the two groups were inconsistent. This affected the criteria on sleep quality used to distinguish children with and without ASD. These limitations need to be addressed in future studies.

*Exercise Physiology*

### **Author details**

Thai Duy Nguyen NICVB, Ministry of Health of Vietnam, Hanoi, Vietnam

\*Address all correspondence to: thainguyenduy@hotmail.com

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*

#### **References**

[1] Emberti Gialloreti L, Mazzone L, Benvenuto A, Fasano A, Garcia Alcon A, Kraneveld A, et al. Risk and protective environmental factors associated with autism spectrum disorder: Evidencebased principles and recommendations. Journal of Clinical Medicine. 2019;**8**:217

[2] Lord C. Taking sleep difficulties seriously in children with neurodevelopmental disorders and ASD. Pediatrics. 2019;**143**:e20182629

[3] Bangerter A, Chatterjee M, Manyakov NV, Ness S, Lewin D, Skalkin A, et al. Relationship between sleep and behavior in autism spectrum disorder: Exploring the impact of sleep variability. Frontiers in Neuroscience. 2020;**14**(211):1-13

[4] Moore M, Evans V, Hanvey G, Johnson C. Assessment of sleep in children with autism spectrum disorder. Children (Basel). 2017;**4**(72):1-17

[5] Deliens G, Peigneux P. Sleep– behaviour relationship in children with autism spectrum disorder: Methodological pitfalls and insights from cognition and sensory processing. Developmental Medicine and Child Neurology. 2019;**61**:1368-1376

[6] Souders MC, Zavodny S, Eriksen W, Sinko R, Connell J, Kerns C, et al. Sleep in children with autism spectrum disorder. Current Psychiatry Reports. 2017;**19**:34

[7] Andy C, Lee PH, Zhang J, Lai EW. Study protocol for a randomised controlled trial examining the association between physical activity and sleep quality in children with autism spectrum disorder based on the melatonin-mediated mechanism model. BMJ Open. 2018;**8**(e020944):1-7

[8] Richdale AL, Schreck KA. Examining sleep hygiene factors and sleep in young

children with and without autism spectrum disorder. Research in Autism Spectrum Disorders. 2019;**57**:154-162

[9] Bricout VA, Pace M, Guinot M. Sleep and physical activity in children with autism spectrum: About 3 clinical cases. Austin Journal of Autism & Related Disabilities. 2018;**4**:1049

[10] Ohara R, Kanejima Y, Kitamura M, Izawa K. Association between social skills and motor skills in individuals with autism spectrum disorder: A systematic review. European Journal of Investigation in Health, Psychology and Education. 2020;**10**:276-296

[11] Jones RA, Downing K, Rinehart NJ, Barnett LM, May T, McGillivray JA, et al. Physical activity, sedentary behavior and their correlates in children with autism spectrum disorder: A systematic review. PLoS One. 2017;**12**:e0172482

[12] Bricout VA, Pace M, Dumortier L, Miganeh S, Mahistre Y, Guinot M. Motor capacities in boys with high functioning autism: Which evaluations to choose? Journal of Clinical Medicine. 2019;**8**(1521):1-15

[13] Odeh CE, Gladfelter AL, Stoesser C, Roth S. Comprehensive motor skills assessment in children with autism spectrum disorder yields global deficits. International Journal of Developmental Disabilities. 2020;**89**:1-11

[14] Thivel D, Tremblay A, Genin PM, Panahi S, Rivière D, Duclos M. Physical activity, inactivity, and sedentary behaviors: Definitions and implications in occupational health. Frontiers in Public Health. 2018;**6**(288):1-5

[15] Colley RC, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay MS. Physical activity of Canadian children and youth: Accelerometer results from the 2007 to 2009 Canadian Health Measures Survey. Health Reports. 2011;**22**:15-23

[16] Parrish A-M, Tremblay MS, Carson S, Veldman SLC, Cliff D, Vella S, et al. Comparing and assessing physical activity guidelines for children and adolescents: A systematic literature review and analysis. International Journal of Behavioral Nutrition and Physical Activity. 2020;**17**:16-16

[17] Scharoun SM, Wright KT, Robertson-Wilson JE, Fletcher PC, Bryden PJ. Physical activity in individuals with autism spectrum disorders (ASD): A review. In: Fitzgerald M, Yip J, editors. Autism— Paradigms, Recent Research and Clinical Applications. London: IntechOpen; 2017. DOI: 10.5772/66680

[18] Must A, Phillips S, Curtin C, Bandini LG. Barriers to physical activity in children with autism spectrum disorders: Relationship to physical activity and screen time. Journal of Physical Activity and Health. 2015;**12**:529-534

[19] Chennaoui M, Arnal PJ, Sauvet F, Leger D. Sleep and exercise: A reciprocal issue? Sleep Medicine Reviews. 2015;**20**:59-72

[20] Healy S, Haegele JA, Grenier M, Garcia JM. Physical activity, screen-time behavior, and obesity among 13-year olds in Ireland with and without autism spectrum disorder. Journal of Autism and Developmental Disorders. 2017;**47**:49-57

[21] Benson S, Bender AM, Wickenheiser H, Naylor A, Clarke M, Samuels CH, et al. Differences in sleep patterns, sleepiness, and physical activity levels between young adults with autism spectrum disorder and typically developing controls. Developmental Neurorehabilitation. 2019;**22**:164-173

[22] Tse CYA, Lee HP, Chan KSK, Edgar VB, Wilkinson-Smith A, Lai WHE. Examining the impact of physical activity on sleep quality and executive functions in children with autism spectrum disorder: A randomized controlled trial. Autism. 2019;**23**:1699-1710

[23] Wang F, Boros S. The effect of physical activity on sleep quality: A systematic review. European Journal of Physiotherapy. 2019;**23**(1):1-8

[24] Abel EA, Schwichtenberg AJ, Brodhead MT, Christ SL. Sleep and challenging behaviors in the context of intensive behavioral intervention for children with autism. Journal of Autism and Developmental Disorders. 2018;**48**:3871-3884

[25] American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders-V. Arlington, VA: American Psychiatric Publishing; 2013

[26] Lord C, Risi S, Lambrecht L, Cook EH Jr, Leventhal BL, Dilavore PC, et al. The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders. 2000;**30**:205-223

[27] Wechsler D. Wechsler Intelligence Scale for Children. 4th Edition (WISC-IV). San Antonio, Tex: Harcourt Assessment; 2003

[28] Owens JA, Spirito A, McGuinn M. The children's sleep habits questionnaire (CSHQ ): Psychometric properties of a survey instrument for school-aged children. Sleep (New York). 2000;**23**:1043-1052

[29] Kowalski KC, Crocker PR, Faulkner RA. Validation of the physical activity questionnaire for older children. Pediatric Exercise Science. 1997; **9**:174-186

*Potential of Physical Activity-Based Intervention on Sleep in Children with and without Autism... DOI: http://dx.doi.org/10.5772/intechopen.102534*

[30] Rosenberger ME, Fulton JE, Buman MP, Troiano RP, Grandner MA, Buchner DM, et al. The 24-hour activity cycle: A new paradigm for physical activity. Medicine and Science in Sports and Exercise. 2019;**51**:454-464

[31] Reid Chassiakos Y, Radesky J, Christakis D, Moreno MA, Cross C. Children and adolescents and digital media. Pediatrics. 2016;**138**:e20162593

[32] Shochat T. Impact of lifestyle and technology developments on sleep. Nature and Science of Sleep. 2012;**4**:19-31

[33] Barnes DB. Short term examination of physical activity and sleep quality with children with autism spectrum disorder [Bachelor of Science (B.S.) Honors Undergraduate Theses]. University of Central Florida; 2019

[34] Mccoy SM, Morgan K. Obesity, physical activity, and sedentary behaviors in adolescents with autism spectrum disorder compared with typically developing peers. Autism. 2020;**24**:387-399

[35] Dolezal BA, Neufeld EV, Boland DM, Martin JL, Cooper CB. Interrelationship between sleep and exercise: A systematic review. Advances in Preventive Medicine. 2017;**2017**: 1364387

[36] Jung AR, Park JI, Kim H-S. Physical activity for prevention and management of sleep disturbances. Sleep Medicine Research. 2020;**11**:15-18

[37] Liang X, Li R, Wong SHS, Sum RKW, Sit CHP. Accelerometermeasured physical activity levels in children and adolescents with autism spectrum disorder: A systematic review. Preventive Medicine Reports. 2020; **19**:101147

[38] Bandini LG, Gleason J, Curtin C, Lividini K, Anderson SE, Cermak SA, et al. Comparison of physical activity between children with autism spectrum disorders and typically developing children. Autism. 2013;**17**:44-54

[39] Wachob D, Lorenzi DG. Brief report: Influence of physical activity on sleep quality in children with autism. Journal of Autism and Developmental Disorders. 2015;**45**:2641-2646

[40] Master L, Nye RT, Lee S, Nahmod NG, Mariani S, Hale L, et al. Bidirectional, daily temporal associations between sleep and physical activity in adolescents. Scientific Reports. 2019;**9**:7732

[41] Vanderlinden J, Boen F, Van Uffelen JGZ. Effects of physical activity programs on sleep outcomes in older adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity. 2020;**17**:11

#### **Chapter 5**

## Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology

*Mohamed Magdy Aly Hassan ElMeligie*

#### **Abstract**

Over the previous decade, there has been growing and fervent interest in scientific and commercial circles regarding the potential of bioactive compounds that mimic, or augment, the effects of exercise. These developments have given rise to the moniker 'exercise pills' or 'exercise mimetics'. The emergence of such orally-delivered bioactive compounds could hold substantial therapeutic value for combating metabolic disease. Such treatments might also present therapeutic value for morbidly obese individuals or those recovering from severe injury. This topic is not without controversy, however, as the search for a 'one size fits all' solution is not likely to bear fruit, given the complexity of the molecular and physiological mechanisms involved. The primary goal of this chapter is to explore the challenges of designing a pill that might reliably deliver the myriad and complex adaptations afforded by exercise training, with a focus on skeletal muscle. Furthermore, it will consider the issues, rationale, and practicality of implementing such therapeutics as a credible substitute to engaging in regular exercise training.

**Keywords:** exercise pill, bioactive, pharmaceuticals, human adaptation, skeletal muscle, homeostasis

#### **1. Introduction**

Physical exercise is recognized as a highly effective non-pharmaceutical intervention for a range of health conditions in humans. In the first instance, systematic review evidence (comprising millions of participants) has indicated that engagement in regular physical exercise is associated with a reduced risk for all-cause mortality, and in a dose-response manner [1]. Furthermore, it also has important benefits in the prevention and treatment of a range of chronic metabolic conditions [1], such as cardiovascular disease [2], diabetes [3], and cancer [4]. The benefits of regular physical exercise are not restricted solely to metabolic diseases, however. The whole-body homeostatic perturbations brought about by exercise-induced stress also encompass the central nervous system, skeletal muscle, skin, oxygen transport processes, and hepatic function [5]. An important observation is that the relationships between physical activity and health outcomes tend to be curvilinear, in that clinically relevant health benefits can be obtained from relatively little amounts of physical activity [1].

Despite its wide-ranging, multifaceted, and complex health benefits, almost one third of the global population over 15 years of age fails to meet the minimum prescription of physical exercise to obtain worthwhile health benefits [6]. In the United States, 8.3% (95% confidence interval: 6.4–10.2) of deaths have been attributed to inadequate levels of physical activity [7], a sobering statistic when considering the modifiable nature of this risk factor [8]. Yet more worrisome is the growing trend towards increasing sedentary behaviors (i.e., sitting time, computer use) over the previous decade [9, 10]; a fact made all the more severe by the ongoing COVID-19 pandemic and its associated government-mandated lockdown measures to protect public health [11]. Despite the seemingly global trend towards increased sedentariness and inadequate physical activity, impracticalities exist with regards to mandating an entire community, country, and/or global population to optimize their exercise habits [12]. It must also be noted that certain populations may not be able to engage in physical exercise due to injury, disease, or age-associated frailty, and thus would benefit from alternative solutions [13].

The potent effects of regular physical exercise on numerous important domains of human health have given rise to the notion of pharmacological compounds that mimic, or enhance, these effects. Such 'exercise mimetics' or 'exercise pills' have been touted as a potential, but not entirely probable, therapeutic solution [12, 14] for an otherwise challenging and ongoing public health problem. Although exercise brings about a range of physiological benefits to human health, compliance is often low and in certain groups may not be possible [15]. In recent decades, our understanding of the molecular determinants and physiological processes involved in exercise has improved at an alarming rate. This work has led to the emergence of chemical interventions that can induce the beneficial aspects of exercise, without necessitating actual skeletal muscle activity [15]. Such pharmacologic interventions may represent a viable strategy for addressing metabolic diseases associated with physical inactivity [16] or serve as an intermediary treatment for the morbidly obese or people recovering from serious injury [17]. The mechanistic basis for this supposition, and the opportunities and difficulties associated with such a strategy are the focal considerations of this chapter.

#### **2. The identification of cellular and molecular targets in skeletal muscle**

Skeletal muscle is the most abundant tissue in the human body, accounting for around 40% of total body weight, and is the most robustly activated organ in response to physical exercise [13]. In recent years, the effects of physical exercise on several molecular pathways and cellular targets in skeletal muscle have received significant attention. This investigative work has yielded numerous potential factors with relevance for 'exercise mimetic' applications in human health.

#### **2.1 The AMPK-SIRT1-PGC1α pathway**

The repeated muscular contractions brought about during physical exercise activate numerous signaling pathways in skeletal muscle, one of which is the AMPK-SIRT1-PGC1α axis that plays a key role in skeletal muscle energy metabolism and mitochondrial biogenesis [13].

#### *2.1.1 AMPK*

AMPK, or AMP-activated protein kinase, is a master regulator of energy homeostasis and metabolism within the cell. It is a heterotrimeric protein complex

#### *Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology DOI: http://dx.doi.org/10.5772/intechopen.102533*

that comprises a catalytic subunit (α) and two regulatory subunits (β and γ) of which numerous isoforms exist [18]. AMPK integrates important signals from metabolic pathways and balances nutrient availability with energy demand. During exercise, muscle contractions deplete adenosine triphosphate (ATP), which reduces the ATP:AMP and ATP:ADP ratios within the cell, subsequently activating AMPK [19]. In skeletal muscle, the activation of AMPK induces a switch from anabolic cellular metabolism to a catabolic state of metabolism, blocking energyconsuming activities and promoting the synthesis of ATP from fatty acid oxidation, glycosylation, and glucose uptake [13]. These effects are mediated acutely by direct phosphorylation of metabolic targets, whereas a more chronic effect is brought about by gene transcription [13]. Inactivation of AMPK in skeletal muscle leads to the loss of oxidative fibers, suppressed fat metabolism, and impaired mitochondrial biogenesis [20].

Exercise is perhaps the most prominent physiological activator of AMPK in skeletal muscle. Acutely, exercise intensities above 60% of maximal aerobic capacity can induce AMPK activation, as can lower intensities of a prolonged duration [21]. Given its 'global' role as a regulator of cellular energy stress in response to environmental factors such as caloric restriction, physical exercise, and metabolic disease [22], AMPK has garnered substantial attention. It continues to represent a promising potential target for pharmaceutical intervention, particularly when considering its interactions with other effectors.

#### *2.1.2 SIRT1*

Sirtuin 1 (SIRT1) is a central regulator of metabolic processes in response to energy availability, and is primarily localized in the nucleus [23]. It is responsive to NAD<sup>+</sup> to NADH concentrations, and thus cellular energy availability, through its activation by AMPK [20], and it also senses changes in intracellular redox state [13, 23]. The activation of SIRT1 deacetylates and activates peroxisome proliferator-activated gamma coactivator 1-alpha (PGC1-α), upregulating its specific activity as a transcription factor on genes related to mitochondrial respiration and fatty acid metabolism [13, 24]. In conditions of overexpression or knock-out however, there is evidence to suggest that SIRT1 can also serve as a PGC1-α inhibitor, thus reducing mitochondrial activity [13]. In addition, during low nutrient availability, SIRT1 induces a shift in cellular metabolism towards fatty acid oxidation due to the scarcity of glucose [23]. SIRT1 helps to support cellular energy balance by inducing catabolic processes while inhibiting anabolic processes, thus maintaining energy homeostasis [23].

Physical exercise, specifically high-intensity interval training, has been shown to elevate SIRT1 activity in human skeletal muscle, and this was also associated with mitochondrial biogenesis [25]. Moreover, chronic exercise results in systemic adaptations that increase the levels of SIRT1 expression in the kidney, liver and brain in patients with neurodegenerative diseases, normalizing cellular processes and decreasing disease severity [26]. Defects in the pathways mediated in part by SIRT1 are known to lead to numerous metabolic disorders. Therefore, given the potential benefits of exercise-associated activation of SIRT1 for health and disease, the pharmacological manipulation of this target might elicit multiple benefits, and as such remains an area of focused attention.

#### *2.1.3 PGC1-*α

PGC1-α plays an integral role in cellular metabolism, serving as a co-activator of a vast range of downstream transcriptional factors and effectors involved in

fatty acid oxidation and mitochondrial biogenesis [13]. In skeletal muscle, PGC1-α is activated by endurance exercise-mediated stimulation of p38 mitogen-activated protein kinase (MAPK) [13], subsequently enhancing mitochondrial biogenesis. Importantly, both acute and chronic physical exercise robustly increase the mRNA expression of PGC1-α in rodent muscle, therefore underscoring its importance in exercise training adaptations [20]. PGC1-α mediates the remodeling of skeletal muscle towards a more metabolically oxidative and less glycolytic fiber-type composition [27]. In muscle-specific PGC1-α knock-out models, impaired endurance, abnormal fiber composition, and inconsistent mitochondrial gene regulation have been documented [13], thus reinforcing the indispensable role of PGC1-α in exercise-mediated adaptations. It has also been posited that PGC1-α is a key factor in metabolic disorders, such as diabetes, obesity, and cardiomyopathy. These notions, allied to its regulatory action in lipid metabolism, make PGC1-α a potentially attractive target for pharmacological intervention [27].

### **2.2 PPARδ**

Peroxisome proliferator-activated receptor delta (PPARδ) is a nuclear hormone receptor that transcriptionally regulates over 100 genes, playing a vital role in many biological processes [13], particularly those relating to energy balance [28] and fatty acid oxidation [29]. Although expressed abundantly in a range of metabolically active tissues, in skeletal muscle PPARδ is predominantly expressed in oxidative slow-twitch as opposed to glycolytic fast-twitch fibers. This expression is further induced by endurance-type exercise activity known to trigger an oxidative and/ or slow-twitch phenotype [20]. Its role in skeletal muscle includes the regulation of slow/fast-twitch fibers, lipid metabolism, oxidative processes, mitochondrial biogenesis, weight reduction, impairment of liver gluconeogenesis, and management of inflammatory processes [13, 20]. In rodent models, muscle-specific activation of PPARδ has demonstrated 'exercise-like' effects, such as increasing running endurance and guarding against diet-induced obesity and type II diabetes [30]. Furthermore, ablation of PPARδ in skeletal muscle induces an age-dependent loss of oxidative muscle fibers, running endurance, and insulin sensitivity [31], thus further reinforcing the role of PPARδ in fiber type remodeling. The weight of this evidence has led to the assumption that PPARδ is a central transcriptional regulator of oxidative metabolism the slow-twitch phenotype [20] thus representing a major 'exercise mimetic' target of interest.

#### **2.3 ERRα/γ**

Estrogen-related receptors (ERRs) are key nuclear regulators in mitochondrial energy metabolism [29], with their transcriptional activity determined by cofactors such as PGC-1α. ERRα is expressed in a range of tissues with high energy turnover, including skeletal muscle. ERRγ has a similar expression pattern but is selectively expressed in tissues with high rates of oxidation such as brain, heart, and muscle [29]. When PGC-1α is induced, ERRα plays a major role in controlling the mitochondrial biogenic gene network; in its absence, the ability of PGC-1α to enhance the expression of mitochondrial genes is drastically reduced [29].

In skeletal muscle, ERRα is expressed in oxidative and glycolytic fibers, whereas ERRγ is expressed in oxidative fibers only [29, 32]. Notably, ERRγ regulates oxidative metabolism not just in skeletal muscle, but in other tissues as well [33], and is a key determinant of the oxidative muscle fiber phenotype [15]. As such, it is highly expressed in type I skeletal muscle fibers. In rodent models, when ERRγ is transgenically expressed in type II fibers, it induces metabolic and vascular adaptations,

*Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology DOI: http://dx.doi.org/10.5772/intechopen.102533*

in the absence of exercise [32]. These adaptations include prominent vascularization, the secretion of proangiogenic factors, and an alarming increase in endurance performance of 100% [32]. Given these characteristics, ERRγ is a prominent target for exercise mimetics because of its direct regulation of genes associated with mitochondrial oxidation, however there is a paucity of research on the topic [12]. When applied ectopically in glycolytic fibers, ERRγ instigates a shift in fiber type from glycolytic to oxidative, inducing mitochondrial biogenesis and bring about increased vascularization [29].

#### **2.4 REV-ERBα**

The nuclear receptor REV-ERBα (also known as nuclear receptor subfamily 1 group D member 1 (NR1D1), is highly conserved across species and plays important roles in circadian rhythm and metabolism [33]. In skeletal muscle, REV-ERBα are prominently involved in the regulation of mitochondrial biogenesis, mitophagy, the promotion of an oxidative fiber type, and the processes underpinning a higher endurance capacity [34]. In rodents, muscle-specific ablation of REV-ERBα was shown to blunt the AMPK-SIRT1-PGC-1α signaling pathway, decrease mitochondrial density, reduce oxidative phosphorylation activity, and downregulate genes associated with fatty acid metabolism [34]. Conversely, overexpression of REV-ERBα in C2C12 cells activated these regulators of training adaptations, increased mitochondrial biogenesis and induced fatty acid metabolism genes [35]. REV-ERBα also appears to play a role in modulating muscle mass, with its deficiency leading to increased expression of atrophy genes, and overexpression leading to diminished atrophy genes and increased fiber size [36]. Therefore, REV-ERBα has been identified as a promising pharmacological target for exercise mimetic applications.

#### **3. 'Exercise mimetic' pharmacologic compounds as putative therapeutics for human health**

The attractive properties of physical exercise for human health have garnered fervent interest from the pharmaceutical industry in recent years, likely due to the large and untapped market of sedentary individuals that, for varying reasons, do not engage in sufficient physical exercise [37]. Chiefly, the development of novel therapeutic approaches to replicate an exercise-training phenotype [38] by activating selected molecular targets—so-called 'exercise pills' [15] or 'exercise mimetics'—remains an area of substantial investment and effort. In using natural or synthetic compounds, it is possible to induce exercise-mimicking effects even in sedentary test animals [12], by activating molecular targets and genomic regulators such as those previously described. The foremost of these therapeutic approaches will now be discussed.

#### **3.1 AMPK activators**

AICAR, or 5-aminoimidazole-4-carboxamide-1-β-D-ribofuranoside, is at the forefront of several 'exercise-mimetic' compounds developed to target AMPK, a master regulator of cellular and organismal metabolism [39]. It is a well-known adenosine analog that is intracellularly converted into ZMP, which directly associates with and allosterically stimulates AMPK [12, 22] in a time- and dose-dependent manner [40]. Acutely, AICAR activates AMPK to bring about an increase in fatty acid oxidation, whereas chronic AICAR treatment promotes skeletal muscle fiber type transition from fast- to slow-twitch, and increases the expression of enzymes

associated with aerobic respiration [20]. This fiber type reorganization, in concert with mitochondrial biogenesis, has been shown to significantly increase exercise performance (by an unexpected 44%) in sedentary mice following AICAR administration alone [39]. AICAR also induces skeletal muscle glucose uptake by effecting the translocation of the GLUT4 receptor to the sarcolemma [22]. These findings highlight the potential of AICAR as a potential agent to address the insulin resistance seen in type II diabetes.

Metformin is a drug of the biguanide class known to function in an AMPKdependent manner, and is one of the most broadly available antidiabetic agents presently available [22]. It represents a first line medication used to treat type II diabetes, and activates AMPK in the liver through inhibition of mitochondrial complex I, which concomitantly reduces cellular ATP generation [12]. The glucoselowering action of metformin is at least partly mediated by the activation of AMPK [38]. Although the mode of activation is different, metformin activates AMPK in a similar manner to AICAR, and they both have similar roles in hepatic glucose production [13]. In diabetic patients, metformin can reduce blood pressure and also improve multiple cardiovascular risk factors in obese individuals [13]. It may also possess anti-inflammatory properties, the specifics of which are still being explored.

#### **3.2 Resveratrol**

Resveratrol, a naturally occurring plant-derived polyphenol, is recognized as an activator of SIRT1 and AMPK [13, 22], but has multiple biological targets [20]. In yeast it has been shown to promote longevity, whereas in rodents this capacity is uncertain [33]. Although abundant in the human diet, resveratrol is perhaps most notably consumed in the seeds and skin of grapes [13]. It is highly lipophilic but has scarce bioavailability; nevertheless it is capable of extracellular, intracellular, and nuclear interactions [13]. Its role on the SIRT1-AMPK axis, as well as PGC1-α [38, 41], has received interest as a potential metabolism-regulating, 'exercise mimetic' compound. However, evidence in rodents is conflicting and it has been postulated that resveratrol might actually improve performance when used in synergy with exercise, rather than as a substitute [13]. In human clinical trials, resveratrol was shown to induce the expression of SIRT1 and AMPK in skeletal muscle, albeit in obese type II diabetic males [42]. From the perspective of exercise performance, resveratrol administration suppressed exercise-dependent improvements in aerobic respiration in aged inactive males, thus blunting the beneficial effects of training [43]. Therefore, further research is needed to cogently understand the mechanisms of action and optimal dose before it can be recommended in 'exercise mimetic' applications. It should also be noted that novel, more potent synthetic activators of SIRT1, such as SRT1720, have been developed that might represent promising candidates for application in a clinical setting [33], although research on these compounds is still in its infancy.

#### **3.3 GW501516**

The compound GW501516 is a selective agonist of PPARδ, and was initially developed for possible beneficial applications in metabolic and cardiovascular diseases [13]. However, pre-clinical work in animals highlighted its carcinogenic effects in multiple organs and the compound was subsequently abandoned [44]. Nevertheless, numerous studies from the past decade have linked this drug with potential 'exercise mimetic' effects [39]. For instance, a metabolomic study in mice showed that GW501516 treatment enhanced exhaustive running endurance *Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology DOI: http://dx.doi.org/10.5772/intechopen.102533*

in both trained and untrained animals, by increasing the specific consumption of fatty acids and sparing blood glucose [45]. The expression of genes regulated by PPARδ, including PGC1-α and pyruvate dehydrogenase kinase 4 (PDK4) were also significantly increased following treatment, as were other markers of fatty acid metabolism in skeletal muscle. Importantly, in untrained mice the administration of GW501516 alone was sufficient to increase running endurance, even following just 1 week of provision. Similar findings have been previously reported, albeit without any benefits to endurance capacity, demonstrating that GW501516 establishes an endurance gene signature, sharing 50% of the gene expression pattern with exercise [39]. Elsewhere, GW501516 administration improved endurance function in a mouse model of myocardial infarction when compared to placebo, and preserved oxidative capacity and fatty acid metabolism [46]. Collectively, these findings suggest that the activation of PPARδ at least partially mimics the effects of exercise.

#### **3.4 GSK4716**

GSK4716 is a synthetic ERRγ agonist that can activate the receptor with a similar potency to that of its ligand PGC-1α [15, 47]. It robustly activates genes involved in mitochondrial biogenesis, fatty acid oxidation, and the tricarboxylic acid cycle (TCA) when used to treat primary muscle cells [12], and promotes an endurancetrained phenotype in mice [32]. However, there is a discrepancy between acute and chronic activation of ERRγ in ligand-treated primary muscle cells and transgenic animals, respectively [33]. Although GSK4716 has been heralded as a candidate 'exercise pill' [15], the aforementioned 'exercise-mimicking' effects have not been established *in vivo* [12], and the compound is not yet approved for human use.

#### **3.5 SR9009**

The synthetic REV-ERBα agonist SR9009 was developed at the Scripps Research Institute in 2012 and has been identified as an 'exercise pill' of promise [15]. A single injection of SR9009 brought about 'exercise-like' effects in rodents, such as enhanced mitochondrial activity and the induction of genes associated with fatty acid metabolism [34]. After 12 days, energy consumption was enhanced without changing the respiratory exchange ratio, and after 30 days mouse running performance was significantly prolonged. Despite these positive findings, REV-ERB independent effects on cell proliferation, metabolism and gene expression have been found in a double-ablation model [48]. Therefore, positive outcomes with respect to the physiological and molecular effects of exercise should be interpreted with a degree of caution. More importantly, SR9009 has not been approved for human use at the time of writing, however tests have been devised against its surreptitious use [49].

#### **4. The challenges and controversies of developing an 'exercise pill'**

A pharmacological method of replicating the multifaceted and complex effects of physical exercise would no doubt be of value to populations that for whatever reason cannot engage in physical activity, such as people with disabilities, disease, frailty, or injury. For example, it might serve as an avenue towards reengaging with physical exercise after a severe injury, or a 'stepping stone' for individuals that are morbidly obese. However, there are several important considerations that need to be addressed.

#### **4.1 Can physical exercise be realistically replaced?**

There are inherent dangers in a 'reductionist' approach to exercise mimetics, as rodent knockout models have shown that no single 'exercise gene' or signaling pathway exists [37]. Even though PGC-1α has, for example, been described as the 'master regulator' of endurance exercise adaptations, evidence suggests that it may not be a prerequisite for exercise training-induced mitochondrial adaptations [37]. The biological responses to acute and chronic physical exercise in humans are characterized by a high degree of physiological redundancy at the molecular, cellular, organ-system, and whole-body levels [50]. Furthermore, the exercise-induced skeletal muscle phenotype is independent of a chosen few genes, proteins, and signaling pathways [51, 52]. Therefore, irrespective of the promising research findings discussed above, it is extremely unlikely that the emergence of a single pharmaceutical compound will be able to deliver the myriad and complex physiological, metabolic, and homeostatic disruptions brought about by exercise [5]. The multiplicity of responses, at a macro, 'systemwide' level [37], have been described as too diverse for a single pharmaceutical approach to address, and therefore a 'one size fits all' panacea is unlikely to come forward. It appears then that there is no true replacement for actual exercise, at least at present, due to the distinct and multifaceted metabolic responses that take place, especially in skeletal muscle. Despite these reservations, 'exercise mimetics' might represent an avenue to obtain at least some of the important benefits in those unable to achieve adequate amounts of physical exercise [12]. However, it could be argued that improving adherence to existing evidence-based exercise guidelines and pharmaceutical strategies (e.g., statins for cardiovascular disease) would be a more fruitful and productive objective for the promotion of human health.

#### **4.2 Doping implications for elite athletes**

From the perspective of performance sport, 'exercise mimetics' raise important and challenging questions. PPARδ agonists were added to the WADA Prohibited List that became effective in 2009, with AICAR also banned in the same year. In 2012, both GW501516 and AICAR were moved to class S4 (hormone and metabolic modulators) [53], and at the time of writing, this is still the case. Both of these compounds have received significant media attention over the last decade. For example, in 2012 members of the Spanish cycling team, including the team doctor, were arrested in connection with an international network supplying AICAR, due to its effectiveness on performance [12]. Despite this, it must be emphasized that AICAR is not approved for therapeutic use anywhere in the world, given its status as an experimental compound. In a separate instance, Russian race walker Elena Lashmanova tested positive for GW501516 in 2014 and was subsequently sanctioned. A very stable drug, GW501516 possesses a long half-life and is therefore easily detected in blood and urine samples [12], which poses major consequences for athletes seeking to obtain this compound for performance enhancement. By way of comparison, resveratrol is a natural, albeit weak, compound that has been shown to improve endurance performance in animals, yet it is not a prohibited substance. This is likely due to its low bioavailability and lack of consistently beneficial effects in humans [12]. Therefore, due care and attention must be observed when selecting compounds in pursuit of performance enhancement to ensure compliance with the WADA Prohibited List and mitigate the risk of compromising one's career.

*Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology DOI: http://dx.doi.org/10.5772/intechopen.102533*

#### **4.3 Side effects of human metabolic modulators**

The constant activation of metabolic pathways by pharmaceutical means, so-called 'metabolic overdrive', could have undesirable health effects [37, 54]. For example, the chronic activation of AMPK (i.e., via AICAR) and concomitant inhibition of the mechanistic target of rapamycin (mTOR; a central regulator of protein synthesis and anabolism) could bring about a state of chronic catabolism, or breakdown [37]. This problem would be exacerbated if multiple exercise mimetics or pills, targeting diverse pathways, were consumed. More specifically, and with relevance to the exercise mimetics discussed above, GW501516 demonstrated serious toxicity and multi-organ carcinogenicity in rodent studies, whereas human clinical trials reported no adverse effects, likely due to the short duration and low dose administered [53]. Even the naturally occurring compound resveratrol has been associated with side effects in humans, albeit to a lesser extent than the synthetic compounds previously discussed. In *in vitro* studies, the concentration-dependent cytotoxicity of resveratrol has been demonstrated, with high doses associated with deleterious effects [55]. Although safe and welltolerated at doses of up to 5 g per day in humans, diarrhea has been documented as a frequent side effect at doses of 2000 mg [56], and there may be implications of high dose resveratrol supplementation for people with underlying health conditions [55].

#### **5. Non-pharmacological 'exercise mimetic' alternatives**

There do exist non-pharmacological alternatives to 'exercise pills' that can potentially be applied to mimic the characteristics of exercise training. For example, neuromuscular electrical stimulation (NMES) has been used to induce involuntary muscle contractions and support the maintenance of muscle mass in injured athletes [57]. This can potentially serve as a surrogate for physical activity, as it has been shown to stimulate muscle protein synthesis rates in older men, and can ameliorate the muscle atrophy associated with limb immobilization to a certain extent [57]. In contrast to the pharmacological methods described above, NMES can maintain muscle mass without safety concerns or appreciable side effects [58], thus representing a potential strategy for mimicking, at least in part, the metabolic effects of physical exercise. These findings may have the most utility in clinical populations observing periods of bed rest or immobilization, by reintroducing a degree of muscle contraction. This activity can enhance muscle protein synthesis in the fasted and fed states, which might support muscle health during short-term periods of disuse in a clinical setting [59].

Acute passive heating has demonstrated some exercise mimetic properties in humans, namely type II diabetics, when implemented in proximity to an oral glucose tolerance test (OGTT) [60]. One-hour of passive heating in water at 40°C either 30 min before or 30 min after commencing an OGTT increased extracellular heat shock protein 70 in the blood and increased heart rate and total energy expenditure (via increased fat oxidation) [60]. However, passive heating did not affect blood glucose concentrations or insulin sensitivity compared with a control group. In skeletal muscle, there is preliminary evidence that chronic passive heating can promote hypertrophy in animal and human models, alongside augmented voluntary and involuntary strength [61]. With further study, passive heating might be a worthwhile non-pharmacologic and exercise mimetic strategy for people that are unable to complete sufficient exercise.

## **6. Conclusions**

Exercise mimetics remains an area of considerable effort and inquiry but is not without its challenges and controversies. Although early clinical research has identified numerous promising molecular targets for pharmaceutical intervention, there is a lack of human clinical data to support their implementation. This, allied to the multifaceted nature of the human physiological response to exercise, and the redundancy inherent in such a response, suggests that a 'one size fits all' approach will be unlikely to manifest. As such, efforts should be focused on increasing adherence to existing evidence-based exercise guidelines and pharmaceutical interventions for the promotion of human health. Notwithstanding, it is possible that multiple pharmaceutical approaches could emerge in the future that target specific molecular pathways for cumulative benefit. These strategies may offer substantial value for populations unable, or unwilling, to engage in actual physical exercise. Nonetheless, the implications of exercise pills for doping in elite sport, and the potential side effects associated with the administration of these compounds for human health, are areas of cautious consideration for the next decade and beyond.

### **Acknowledgements**

The authorship criteria are listed in our Authorship Policy: https://www.intechopen.com/page/authorship-policy.

#### **Conflict of interest**

The author declares no conflict of interest.

### **Author details**

Mohamed Magdy Aly Hassan ElMeligie Faculty of Physical Therapy, Department of Basic Sciences, October 6 University, 6th of October City, Egypt

\*Address all correspondence to: mohamed.magdy.pt@o6u.edu.eg

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology DOI: http://dx.doi.org/10.5772/intechopen.102533*

#### **References**

[1] Warburton DER, Bredin SSD. Health benefits of physical activity: A systematic review of current systematic reviews. Current Opinion in Cardiology. 2017;**32**:541-556

[2] Tian D, Meng J. Exercise for prevention and relief of cardiovascular disease: Prognoses, mechanisms, and approaches. Oxidative Medicine and Cellular Longevity. 2019;**2019**:3756750. DOI: 10.1155/2019/3756750

[3] Colberg SR, Sigal RJ, Yardley JE, et al. Physical activity/exercise and diabetes: A position statement of the American Diabetes Association. Diabetes Care. 2016;**39**:2065-2079

[4] Fong DYT, Ho JWC, Hui BPH, et al. Physical activity for cancer survivors: Meta-analysis of randomised controlled trials. BMJ. 2012;**344**:17

[5] Hawley JA, Hargreaves M, Joyner MJ, et al. Integrative biology of exercise. Cell. 2014;**159**:738-749

[6] Hallal PC, Andersen LB, Bull FC, et al. Global physical activity levels: Surveillance progress, pitfalls, and prospects. Lancet. 2012;**380**:247-257

[7] Carlson SA, Adams EK, Yang Z, et al. Percentage of deaths associated with inadequate physical activity in the United States. Preventing Chronic Disease. 2018;**15**:E38

[8] Thornton JS, Frémont P, Khan K, et al. Physical activity prescription: A critical opportunity to address a modifiable risk factor for the prevention and management of chronic disease: A position statement by the Canadian Academy of Sport and Exercise Medicine. British Journal of Sports Medicine. 2016;**50**:1109-1114

[9] Yang L, Cao C, Kantor ED, et al. Trends in sedentary behavior among the US population, 2001-2016. JAMA. 2019;**321**:1587-1597

[10] Guthold R, Stevens GA, Riley LM, et al. Worldwide trends in insufficient physical activity from 2001 to 2016: A pooled analysis of 358 population-based surveys with 1·9 million participants. The Lancet Global Health. 2018; **6**:e1077-e1086

[11] Stockwell S, Trott M, Tully M, et al. Changes in physical activity and sedentary behaviours from before to during the COVID-19 pandemic lockdown: A systematic review. BMJ Open Sport & Exercise Medicine. 2021;**7**:e000960

[12] Fan W, Evans RM. Exercise mimetics: Impact on health and performance. Cell Metabolism. 2017;**25**:242-247

[13] Guerrieri D, Moon HY, van Praag H. Exercise in a pill: The latest on exercisemimetics. Brain Plasticity. 2017;**2**:153

[14] Gubert C, Hannan AJ. Exercise mimetics: Harnessing the therapeutic effects of physical activity. Nature Reviews. Drug Discovery. 2021; **2021**:1-18

[15] Li S, Laher I. Exercise pills: At the starting line. Trends in Pharmacological Sciences. 2015;**36**:906-917

[16] Warden SJ, Fuchs RK. Are "exercise pills" the answer to the growing problem of physical inactivity? British Journal of Sports Medicine. 2008; **42**:862-863

[17] Hunter P. Exercise in a bottle: Elucidating how exercise conveys health benefits might lead to new therapeutic options for a range of diseases from cancer to metabolic syndrome. EMBO Reports. 2016;**17**:136

[18] Kjøbsted R, Hingst JR, Fentz J, et al. AMPK in skeletal muscle function and metabolism. The FASEB Journal. 2018;**32**:1741

[19] Gowans GJ, Hawley SA, Ross FA, et al. AMP is a true physiological regulator of AMP-activated protein kinase by both allosteric activation and enhancing net phosphorylation. Cell Metabolism. 2013;**18**:556-566

[20] Matsakas A, Narkar VA. Endurance exercise mimetics in skeletal muscle. Current Sports Medicine Reports. 2010;**9**:227-232

[21] Richter EA, Ruderman NB. AMPK and the biochemistry of exercise: Implications for human health and disease. The Biochemical Journal. 2009;**418**:261

[22] Wall CE, Yu RT, Atkins AR, et al. Nuclear receptors and AMPK: Can exercise mimetics cure diabetes? Journal of Molecular Endocrinology. 2016;**57**:R49-R58

[23] Nogueiras R, Habegger KM, Chaudhary N, et al. Sirtuin 1 and sirtuin 3: Physiological modulators of metabolism. Physiological Reviews. 2012;**92**:1479-1514

[24] Pardo PS, Boriek AM. The physiological roles of Sirt1 in skeletal muscle. Aging (Albany NY). 2011;**3**:430

[25] Gurd BJ, Perry CGR, Heigenhauser GJF, et al. High-intensity interval training increases SIRT1 activity in human skeletal muscle. Applied Physiology, Nutrition, and Metabolism. 2010;**35**:350-357

[26] Radak Z, Suzuki K, Posa A, et al. The systemic role of SIRT1 in exercise mediated adaptation. Redox Biology. 2020;**35**:101467

[27] Liang H, Ward WF. PGC-1α: A key regulator of energy metabolism.

American Journal of Physiology. Advances in Physiology Education. 2006;**30**:145-151

[28] Liu Y, Colby JK, Zuo X, et al. The role of PPAR-δ in metabolism, inflammation, and cancer: Many characters of a critical transcription factor. International Journal of Molecular Sciences. 2018;**19**:3339. DOI: 10.3390/IJMS19113339

[29] Fan W, Evans R. PPARs and ERRs: Molecular mediators of mitochondrial metabolism. Current Opinion in Cell Biology. 2015;**33**:49-54

[30] Luquet S, Lopez-Soriano J, Holst D, et al. Peroxisome proliferator-activated receptor δ controls muscle development and oxydative capability. The FASEB Journal. 2003;**17**:2299-2301

[31] Schuler M, Ali F, Chambon C, et al. PGC1α expression is controlled in skeletal muscles by PPARβ, whose ablation results in fiber-type switching, obesity, and type 2 diabetes. Cell Metabolism. 2006;**4**:407-414

[32] Narkar VA, Fan W, Downes M, et al. Exercise and PGC-1α-independent synchronization of type i muscle metabolism and vasculature by ERRγ. Cell Metabolism. 2011;**13**:283-293

[33] Handschin C. Caloric restriction and exercise "mimetics": Ready for prime time? Pharmacological Research. 2016;**103**:158

[34] Woldt E, Sebti Y, Solt LA, et al. Rev-erb-α modulates skeletal muscle oxidative capacity by regulating mitochondrial biogenesis and autophagy. Nature Medicine. 2013; **19**:1039-1046

[35] Fan W, Atkins AR, Yu RT, et al. Road to exercise mimetics: Targeting nuclear receptors in skeletal muscle. Journal of Molecular Endocrinology. 2013; **51**:T87-T100

*Exercise Mimetics: An Emerging and Controversial Topic in Sport and Exercise Physiology DOI: http://dx.doi.org/10.5772/intechopen.102533*

[36] Mayeuf-Louchart A, Thorel Q, Delhaye S, et al. Rev-erb-α regulates atrophy-related genes to control skeletal muscle mass. Scientific Reports. 2017;**7**:1-11

[37] Hawley JA, Joyner MJ, Green DJ. Mimicking exercise: What matters most and where to next? The Journal of Physiology. 2021;**599**:791-802

[38] Carey AL, Kingwell BA. Novel pharmacological approaches to combat obesity and insulin resistance: Targeting skeletal muscle with 'exercise mimetics'. Diabetologia. 2009;**52**:2015-2026

[39] Narkar VA, Downes M, Yu RT, et al. AMPK and PPARδ agonists are exercise mimetics. Cell. 2008;**134**:405-415

[40] Sullivan JE, Brocklehurst KJ, Marley AE, et al. Inhibition of lipolysis and lipogenesis in isolated rat adipocytes with AICAR, a cellpermeable activator of AMP-activated protein kinase. FEBS Letters. 1994;**353**:33-36

[41] Lagouge M, Argmann C, Gerhart-Hines Z, et al. Resveratrol improves mitochondrial function and protects against metabolic disease by activating SIRT1 and PGC-1α. Cell. 2006;**127**:1109-1122

[42] Goh KP, Lee HY, Lau DP, et al. Effects of resveratrol in patients with type 2 diabetes mellitus on skeletal muscle SIRT1 expression and energy expenditure. International Journal of Sport Nutrition and Exercise Metabolism. 2014;**24**:2-13

[43] Gliemann L, Schmidt JF, Olesen J, et al. Resveratrol blunts the positive effects of exercise training on cardiovascular health in aged men. The Journal of Physiology. 2013;**591**:5047-5059

[44] Sahebkar A, Chew GT, Watts GF. New peroxisome proliferator-activated receptor agonists: Potential treatments

for atherogenic dyslipidemia and non-alcoholic fatty liver disease. Expert Opinion on Pharmacotherapy. 2014;**15**:493-503

[45] Chen W, Gao R, Xie X, et al. A metabolomic study of the PPARδ agonist GW501516 for enhancing running endurance in Kunming mice. Scientific Reports. 2015;**5**:1-13

[46] Zizola C, Kennel PJ, Akashi H, et al. Activation of PPARδ signaling improves skeletal muscle oxidative metabolism and endurance function in an animal model of ischemic left ventricular dysfunction. American Journal of Physiology. Heart and Circulatory Physiology. 2015;**308**:H1078

[47] Wang L, Zuercher WJ, Consler TG, et al. X-ray crystal structures of the estrogen-related receptor-γ ligand binding domain in three functional states reveal the molecular basis of small molecule regulation. The Journal of Biological Chemistry. 2006;**281**: 37773-37781

[48] Dierickx P, Emmett MJ, Jiang C, et al. SR9009 has REV-ERBindependent effects on cell proliferation and metabolism. Proceedings of the National Academy of Sciences. 2019; **116**:12147-12152

[49] Geldof L, Deventer K, Roels K, et al. In vitro metabolic studies of REV-ERB agonists SR9009 and SR9011. International Journal of Molecular Sciences. 2016;**17**:1676

[50] Joyner MJ, Dempsey JA. Physiological redundancy and the integrative responses to exercise. Cold Spring Harbor Perspectives in Medicine. 2018;**8**:a029660. DOI: 10.1101/ CSHPERSPECT.A029660

[51] Qi Z, Zhai X, Ding S. How to explain exercise-induced phenotype from molecular data: Rethink and reconstruction based on AMPK and

mTOR signaling. Springerplus. 2013;**2**:1-10

[52] Kupr B, Schnyder S, Handschin C. Role of nuclear receptors in exerciseinduced muscle adaptations. Cold Spring Harbor Perspectives in Medicine. 2017;**7**:029835. DOI: 10.1101/ CSHPERSPECT.A029835

[53] Pokrywka A, Cholbinsk P, Kaliszewsk P, et al. Metabolic modulators of PPAR-delta. Journal of Physiology and Pharmacology. 2014;**65**:469-476

[54] Weihrauch M, Handschin C. Pharmacological targeting of exercise adaptations in skeletal muscle: Benefits and pitfalls. Biochemical Pharmacology. 2018;**147**:211-220

[55] Shaito A, Posadino AM, Younes N, et al. Potential adverse effects of resveratrol: A literature review. International Journal of Molecular Sciences. 2020;**21**:2084. DOI: 10.3390/ ijms21062084

[56] Salehi B, Mishra AP, Nigam M, et al. Resveratrol: A double-edged sword in health benefits. Biomedicine. 2018;**6**:91. DOI: 10.3390/BIOMEDICINES6030091

[57] Wall BT, Morton JP, van Loon LJC. Strategies to maintain skeletal muscle mass in the injured athlete: Nutritional considerations and exercise mimetics. European Journal of Sport Science. 2015;**15**:53-62

[58] Dirks ML, Wall BT, Snijders T, et al. Neuromuscular electrical stimulation prevents muscle disuse atrophy during leg immobilization in humans. Acta Physiologica. 2014;**210**:628-641

[59] Dirks ML, Wall BT, Van Loon LJC. Interventional strategies to combat muscle disuse atrophy in humans: Focus on neuromuscular electrical stimulation and dietary protein. Journal of Applied Physiology. 2018;**125**:850-861

[60] James T, Corbett J, Cummings M, et al. Timing of acute passive heating on glucose tolerance and blood pressure in people with type 2 diabetes: A randomized, balanced crossover, control trial. Journal of Applied Physiology. 2021;**130**:1093-1105

[61] Rodrigues P, Trajano GS, Wharton L, et al. Effects of passive heating intervention on muscle hypertrophy and neuromuscular function: A preliminary systematic review with meta-analysis. Journal of Thermal Biology. 2020;**93**:102684

## Section 2
