sports medicine Volume 40 Issue 11 November 2010

Sports Med 2010; 40 (11): 899-906 0112-1642/10/0011-0899/$49.95/0

CURRENT OPINION

ª 2010 Adis Data Information BV. All rights reserved.

Behaviour, the Key Factor for Sports Injury Prevention Evert A.L.M. Verhagen, Maartje M. van Stralen and Willem van Mechelen Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands

Abstract

Safety in sports and physical activity is an important prerequisite for continuing participation in sports, as well as for maintenance of a healthy physically active lifestyle. For this reason, prevention, reduction and control of sports injuries are important goals for society as a whole. Recent advances in sports medicine discuss the need for research on real-life injury prevention. Such views call for a more behavioural approach when it comes to actual sports injury prevention. Nevertheless, the role of behaviour in sports injury prevention remains under-researched. In order to push the field of sports injury prevention forward, this article provides an overview of the relationship between behaviour and sports injury risk. Different types of behaviour relate to injury risk factors and injury mechanisms. Behaviour that influences risk factors and injury mechanisms is not confined only to the athlete. Various types of behaviour by, for example, the coach, referee, physical therapist or sports associations, also influence risk factors and injury mechanisms. In addition, multiple behaviours often act together. Some types of behaviour may directly affect injury risk and are by definition a risk factor. Other behaviours may only affect risk factors and injury mechanisms, and influence injury risk indirectly. Recent ideas on injury prevention that call for studies on real-life injury prevention still rely heavily on preventive measures that are established through efficacy research. A serious limitation in such an approach is that one expects that proven preventive measures will be adopted if the determinants and influences of sports safety behaviours are understood. Therefore, if one truly wants to prevent sports injuries in a real-life situation, a broader research focus is needed. In trying to do so, we need to look at lessons learned from other fields of injury prevention research.

1. Introduction Safety in sports and physical activity is an important prerequisite for continuing participation in sports, as well as for maintenance of a healthy physically active lifestyle. For this reason, prevention, reduction and control of sports in-

juries are important goals for clinicians and researchers, as well as for society as a whole. A crucial part of injury prevention in sports and physical activity is the understanding of injury risks and injury aetiology. Since the early 1990s, several theoretical models have been put forward that have aided clinicians and researchers towards

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a better understanding of injury aetiology and, ultimately, the development of preventive measures. Arguably, the most widely accepted and used models are the ones postulated by van Mechelen et al.[1] and Meeuwisse.[2] In 1992, van Mechelen et al.[1] postulated that measures to prevent sports injuries do not stand by themselves; they form part of what the authors called the ‘sequence of prevention’. In order to achieve the primary goal of sports injury prevention, the second step in this sequence of prevention (i.e. identifying risk factors and injury mechanisms) is critical. Recently, a comprehensive model for injury causation was proposed by Bahr and Krosshaug.[3] This model is a further expansion of the epidemiological model by Meeuwisse et al.[2,4] that describes the interplay between different factors along the path to injury. The latter model clearly postulates that an injury is the result of a complex interaction between internal and external risk factors, and is not exclusively caused by the inciting event (injury mechanism) that is generally associated with the onset of injury. One common factor of the models referred to here is that they are based upon a clinical, biomedical and biomechanical research focus. Over the past decade both the ‘sequence of prevention’ and ‘aetiological model’ have been widely adopted in sports injury research. There is no doubt that the approach they encapsulate has led to a wide array of preventive measures for a variety of injuries within different sports. However, recently, debate has arisen about the ‘true’ effect of attained preventive measures in a reallife sports setting.[5,6] As stated by Finch,[5] only research outcomes that are adopted by athletes, coaches, other intermediaries and sporting bodies will actually prevent injuries. For this reason, Finch introduced the Translating Research into Injury Prevention Practice (TRIPP) model[5] as an expansion of the original sequence of prevention.[1] The TRIPP approach aims at a better understanding of the implementation context for injury prevention, and stresses the importance of understanding both behavioural inputs and outputs in relation to sports injury prevention. Recent advances, such as the TRIPP model, are an important step forward for sports injury ª 2010 Adis Data Information BV. All rights reserved.

prevention as they underline the important role of behaviour in injury risk and, consequently, injury prevention. This behavioural role has also been acknowledged and commented on by others in more recent sports injury literature.[7,8] Nevertheless, a recent systematic review by McGlashan and Finch[9] revealed that out of 100 published injury prevention studies, only 11 explicitly used behavioural and/or social sciences theories.[10-20] This shows that although conceptual ideas incorporating a more behavioural approach of sports injury prevention have been postulated,[5,7,8] the role of behaviour within this specific field remains under-researched. In order to push the field of sports injury prevention forward, and to successfully translate current and future knowledge in sports medicine to real-life injury prevention, a better notion and understanding of the various behaviours that relate to sports injury risk is needed. 2. What is Behaviour? 2.1 Conscious Planned Behaviour

Some behaviour can be considered as a planned or controlled reaction that is driven by an intention to perform a specific behaviour. This intention is influenced by a set of behavioural determinants. Epidemiological studies examining the determinants of health behaviours distinguish these determinants into personal immutable determinants (e.g. age, sex, ethnicity), intrinsic cognitive determinants (e.g. attitude, social norm, self-efficacy, intention) and extrinsic determinants (e.g. physical and political environment). The most commonly used Social Cognitive Models are the Health Belief Model,[21] the Theory of Planned Behavior,[22] the Protection Motivation Theory[23] and the Health Locus of Control.[24] Social cognitive models could be applicable in injury prevention research, and have been proven to be useful in explaining injury protection behaviour[10,25] and sports injury rehabilitation behaviour.[26] 2.2 Unconscious Automatic Behaviour

Behaviour can also be an unconscious, automated behaviour. Habitual behaviours are, to a Sports Med 2010; 40 (11)

Behaviour and Sports Injury Prevention

certain extent, unconscious (i.e. without awareness), are difficult to control and are mentally efficient.[27-29] Performing a healthy habit is fine, for example, wearing shin guards every time one is playing football. However, despite high motivation, it is difficult to change unhealthy habits.[30] This is mainly caused by the enduring presence of the cues that have resulted in the unhealthy habitual responses. Unwanted habits can best be changed by breaking the association between the cue and the habitual response. This can be achieved by removing the existing cues that trigger a habit or by creating new cues that provoke a more wanted behaviour (e.g. placing your bicycle helmet in a new and visible place).[29,30] In the transition from unhealthy habitual behaviour to healthy habitual behaviour, it is important that individuals become aware of their personal behaviour and the cues that led to the unhealthy habitual responses in the first place. In other words, in order to translate an unhealthy behaviour into a healthy behaviour, the behaviour has to become conscious and, thus, a planned behaviour.[27-29] 3. Behaviour in Relation to Injury Risk 3.1 Multiple Behaviours

Different types of behaviour relate to injury risk factors and injury mechanisms (figure 1). For instance, an athlete’s preventive behaviour influences the use of prophylactic measures, an athlete’s sports behaviour has an effect on the actions on the playing field and an athlete’s rehabilitation behaviour influences the physical capabilities when returning to play after an injury. Behaviour that influences risk factors and injury mechanisms is, however, not confined only to the athlete. Various types of behaviour by, for example, the coach, referee, physical therapist or sports associations, also influence risk factors and injury mechanisms. In addition, multiple behaviours often also act together. This theory of multiple behavioural influences is not new, as various authors have previously argued the need for multilevel preventive interventions based on ecological models.[4,11,31-33] Head injuries in soccer provide a good example of multiple behaviours influencing injury ª 2010 Adis Data Information BV. All rights reserved.

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Behaviour Preventive behaviour

Sports behaviour

Coaching behaviour

Rehabilitation behaviour

Referee behaviour

Other related behaviours

Risk factors and injury mechanisms Sports injury Fig. 1. A conceptual model of the relationship between behaviour, injury risk factors and injury mechanisms, and sports injury. Behaviours can have both a positive as well as a negative influence on injury risk and injury risk factors. The model is a rather ‘simplistic’ view and does not depict all specific forms of behaviour that relate in specific ways to injury risk.

risk. As shown by Arnason et al.,[34] most head injuries in soccer are due to illegal use of the elbow while heading the ball (player behaviour). The same study also indicated that this illegal elbow use preceding a head injury is often not penalized by the referee (referee behaviour). Hence, it was postulated that stricter enforcement of the rules may prevent head injury in soccer. During the 2006 World Cup, the FIFA (Fe´de´ration Internationale de Football Association), in an attempt to reinforce athlete behaviours, instructed the referees to implement the ‘elbow rule’ more strictly (sports association behaviour). This resulted in a drastic decline of the number of head injuries from 25 in the 2002 World Cup to 13 in the 2006 event.[35] 3.2 Is Behaviour a Risk Factor or Injury Mechanism?

Within the most commonly used injury causation models, psychological and behavioural factors are generally considered risk factors or injury mechanisms directly leading to injury. For instance, competitiveness, motivation and perception of risk are regarded as psychological internal risk factors in the Meeuwisse model,[2-4] and thereby have a share in predisposing the athlete to injury. In a similar manner, external risk Sports Med 2010; 40 (11)

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factors and injury mechanisms also include behavioural components. This view seems satisfactory from an epidemiological point of view when injury aetiology is the focus of research. However, when the aim is to prevent sports injuries, behaviour cannot always be considered a risk factor or injury mechanism. Some types of behaviour may directly affect injury risk and are by definition a risk factor. Other behaviours may only affect risk factors and injury mechanisms, and influence injury risk indirectly. In the latter case, behaviour acts as a confounder or effect modifier in the causal relationship between a risk factor and the injury risk, and should be accounted for as such in any analysis. 3.3 Direct Pathway

A clear example of how behaviour directly influences injury risk is the non-use of effective preventive measures. For instance, it has been shown that in-line skating injuries can be prevented by protective equipment such as wrist guards, elbow pads, kneepads and helmets.[36] Thereby, non-use or absence of protective equipment can be regarded as an external risk factor for injury. Despite this demonstrated effectiveness of protective equipment, such devices are rarely used among young skaters.[37-43] In professional sports, the use of protective equipment can, to a certain extent, be enforced; however, recreational sports require a different approach since enforcement cannot always provide the positive feedback that is necessary to change behaviour. A recent study of in-line skating from the Netherlands showed that the use of prophylactic measures was influenced by social influences, self-efficacy expectations and intention, and concluded that young skaters should improve their safety behaviour in order to prevent skate injuries.[15] This study also showed that other forms of behaviour (e.g. parent behaviour and group behaviour) affected prophylactic measure use as well. The latter association was also found by Lajunen and Ra¨sa¨nen[25] in another study. 3.4 Indirect Pathway

Behaviour may also indirectly relate to injury by influencing the magnitude of internal or exª 2010 Adis Data Information BV. All rights reserved.

ternal risk factors. Behaviour that indirectly affects injury risk can be most clearly explained by taking a rehabilitation-related behaviour as an example. For many injuries, it is known that there is an increased recurrence risk after an index injury. Even so, it is known that an index ankle sprain results in a 2-fold increased recurrence risk of an ankle sprain,[43] and that a neuromotor deficit is an internal risk factor for injury.[44-47] It is known from the literature that neuromotor (e.g. balance) training of the ankle reduces the increased recurrence risk to a ‘normal’ risk level.[48-51] The advocacy and use of neuromotor training programmes by sports bodies, clubs, therapists and coaches indirectly has an effect on the neuromotor deficit. Nonetheless, compliance to any such programme by an athlete affects the athlete’s neuromotor deficit and, consequently, injury risk. Although this example is specifically on neuromotor training, the same example goes for any training or programme affecting internal injury risk factors. 4. Injury Risk in Relation to Behaviour 4.1 Risk Compensation

The potential for severe side effects, the change in risk factors and/or the nature of injury risk also have to be taken into account. The most well known example of this phenomenon is described in the literature as ‘risk homeostasis’ or ‘risk compensation’.[52,53] Although contentious, this theory states that persons maintain their ‘risk behaviour’ at a level they perceive as acceptable and safe, showing athletes in a variety of sports becoming more ‘reckless’ after the introduction of prophylactic measures. For instance, consider the widening of crowded skiing slopes in order to limit the number of collisions and reduce the number skiing injuries. Such a measure is likely to result in skiers going faster because they now perceive it as safer to go faster. Therefore, by eliminating one injury risk factor (i.e. crowdedness on a slope), another is created or exacerbated from a previous lower level (i.e. speed of skiing). Thus, skiers may modify their behaviour in response to an alteration in environmental risk.[54,55] Sports Med 2010; 40 (11)

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Most evidence on risk compensation is available for contact sports where debate has arisen about the introduction of prophylactic devices because changes in injury patterns and mechanisms have occurred hand-in-hand with the introduction of protective equipment.[56-60] An example of this phenomenon, which was noted by Torg et al.,[56] was the shift in head and neck injury patterns in American football between 1959 and 1977 after the introduction of ‘better’ helmets. The number of serious head injuries decreased due to enhanced protective capabilities of the helmet/ face/mask unit, while the number of serious spinal injuries increased due to increased use of the head as the primary point of contact in blocking, tackling and head butting, i.e. ‘spearing’.[56] 4.2 Behavioural Change After Injury

Just as a change in injury risk factors has an influence on behaviour, an injury by itself can influence subsequent behaviour. It has been shown that athletes experience injury-related distress despite having physically recovered from their injuries.[61-63] It was shown in a 3-month prospective study of 260 11- to 14-year-old soccer players that adolescent athletes with a low self-estimation of ability were 4.42 times more likely to be injured than adolescent athletes with a high self-estimation of ability.[64] Although it remains relatively unclear whether post-injury distress includes a low self-estimation of ability, it is likely that an athlete will be hesitant to give his full effort when returning to sports after injury. Through this mechanism, the self-estimation of ability could be lowered and, consequently, injury risk increased. However, injury can also have a positive impact on behaviour. After injury, players might change their preventive behaviour in such a way that they are less hesitant to use prophylactic measures, and their perceived level of risk might have increased. 5. A Different Approach to Sports Injury Prevention In contemporary sports medicine, preventive measures are based upon risk factors and injury mechanisms, which are predominantly establishª 2010 Adis Data Information BV. All rights reserved.

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ed through biomedical and/or biomechanical research. Bluntly put, an injury risk factor is established and one studies (preferably in a randomized controlled trial) what happens to the injury risk when the risk factor is modified, reduced or removed. Although efficacy research is a necessary first step before effectiveness and implementation questions can be answered,[65,66] the controlled nature of efficacy research hampers generalization of the attained results to an actual sports setting. Positive results are seldom fully adopted by a sports population, indicating that in order to truly impact the athlete’s health, more research effort should be placed on translating efficacious preventive methods to practice. The latter has been recognized by multiple authors, calling for a more behavioural approach towards sports injury prevention.[5-8] Despite this, the role of behaviour in sports injury prevention remains under-researched.[5,6,9] Combining the meagre literature on this topic with knowledge from injury prevention in general, health promotion and common sense, it is possible to get some notion of the types of relationships that can exist between behaviour and injury risk, and of the different pathways through which behaviour may affect injury risk. However, a better understanding of different acting behaviours and their relationship with injury risk is needed to truly be able to translate current knowledge to real-life injury prevention.[5,11,32] Although the behavioural role has only been recognized in the sports injury area fairly recently,[5-8] there has long been recognition for the importance of the need to address behavioural factors by general injury researchers.[66-68] In this regard, the different injury fields remain somewhat segregated, give or take a few exceptions. In our attempt to fill the gap between efficacious preventive measures and the uptake and dissemination of such measures by the athletic population, we should learn from the experiences and expertise that is available from other injury prevention settings. After all, the same theoretical concepts and principles apply. One should be aware that recent ideas on injury prevention that call for studies on real-life injury prevention, still rely heavily on preventive Sports Med 2010; 40 (11)

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measures that are established through biomedical and/or biomechanical research. The same applies, in part, to the field of injury prevention in general, where interventions depend greatly upon environmental risk factors and passive interventions.[69,70] The contemporary attention to behavioural change research in combination with theory and model development provide new injury prevention opportunities.[69-72] Although new insights and theories exist, these have not been readily translated into injury prevention programme development or research, and specific behavioural and social sciences theories and models as a primary basis for research or programme design remain under-researched within the general field of injury prevention.[68] The same goes for the specific field of sports injury prevention, where a recent systematic review[9] revealed that out of 100 published injury prevention studies, only 11 explicitly used behavioural and/or social sciences theories.[10-20] A serious limitation in the current preventive approach is that one expects that efficacious preventive measures will be adopted if the determinants and influences of sports safety behaviours are understood.[1-4] It is known from studies on lifestyle interventions that altering an individual’s unhealthy behaviour is very difficult, if possible at all. Therefore, if one truly wants to prevent sports injuries in a real-life situation, a broader research focus is needed from the isolated injury and its underlying factors to the athlete as a whole. 6. Conclusions Recent advances in sports medicine emphasize the need for research on the effectiveness of injury preventive measures in real-world sporting contexts. Implicitly, such views call for a more behavioural approach when it comes to actual sports injury prevention. This article provides an overview of the types of relationships that can exist between behaviour and injury risk, thereby providing a starting point for future research on behaviour and sports injury prevention. There is no doubt that sports injury prevention studies should look further than just biomedical and bioª 2010 Adis Data Information BV. All rights reserved.

mechanical factors associated with injury, and should consider the athlete, including safety and risk behaviours as the study focus instead of considering the nature of the injury alone. Acknowledgements All of the authors contributed equally to this article. Evert Verhagen was involved in the conceptualization and writing of the first draft of the article. Maartje van Stralen and Willem van Mechelen were involved in further developing the idea and finalization of the article. All authors contributed to the final article by reading and correcting the draft versions. All authors declare that they have no competing interests. No sources of funding were used to assist in the preparation of this article.

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Correspondence: Dr Evert A.L.M. Verhagen, Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, NL-1081BT, Amsterdam, the Netherlands. E-mail: [email protected]

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CURRENT OPINION

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Physical Fitness Profiles of Young Men Associations Between Physical Fitness, Obesity and Health Heikki Kyro¨la¨inen,1,2 Matti Santtila,3 Bradley C. Nindl4 and Tommi Vasankari5,6 1 2 3 4

Department of Biology of Physical Activity, University of Jyva¨skyla¨, Jyva¨skyla¨, Finland National Defence University, Helsinki, Finland Personnel Division of Defence Command, Finnish Defence Forces, Helsinki, Finland Military Performance Division, The United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, USA 5 UKK Institute for Health Promotion Research, Tampere, Finland 6 National Institute for Health and Welfare, Helsinki, Finland

Abstract

Obesity in youth has increased during the last 10 years in Western countries. Several studies have investigated physical activity and its effects on obesity and health, showing that regular physical activity combined with improved physical fitness reduces the risk of obesity and several metabolic problems (e.g. diabetes mellitus, metabolic syndrome, heart disease) and also improves overall health. However, there is only limited scientific information available concerning the changes in the physical fitness profiles of youth. It is obvious that only slight changes observed in endurance-type physical activity can also be observed in aerobic capacity. Today and in the future, a major public health concern for teenage and young adults is the combination of increasing body fatness together with decreasing physical fitness. In order to evaluate overall fitness level, it is particularly essential to examine both aerobic and neuromuscular fitness. Therefore, in clinical practice work and health behaviour education, a person’s physical fitness should be measured more frequently with various measures. Furthermore, population-based surveys should be combined with regular measurement of physical fitness to study sedentary lifestyles, particularly in young people. This article presents a review of current physical fitness profiles of male children, adolescents and young adults, which hopefully initiates further studies in this relevant scientific field. In addition, the importance of physical fitness level is evaluated in relation to obesity and health. Collectively, studies examining physical fitness profiles of young men suggest a disturbing worldwide trend of decreased aerobic fitness and increased obesity. Continued efforts to foster improved physical fitness and healthy lifestyles should be encouraged to combat these trends. Such efforts should include frequent and objective assessment of physical fitness rather than solely relying on subjective assessment of physical activity.

It is well documented[1,2] that physical activity and training induce acute and chronic physiological responses. These responses stimulate structu-

ral and functional adaptations that improve physical fitness, as well as physical performance in specific tasks. To achieve optimal training responses,

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training must occur regularly, be performed at least at a moderate intensity (about 50% of maximum capacity) and must be of sufficient duration.[3] In addition, training should follow overload principles. Consequently, regular physical activity combined with increased physical fitness reduces the risk of obesity and several metabolic problems, as well as improving health. Kesa¨niemi et al.[4] have suggested that it is important to consider the intensity of physical activity as part of the doseresponse relationship between physical activity and health and fitness outcomes. Longitudinal and time-related cross-sectional studies over time have reported that physical fitness is decreasing while body fat is simultaneously increasing, which is a major concern for public health. These developmental trends are particularly prominent among young people. Existing data from Australia show that physical activity levels decrease during the teenage years and young adulthood, while the prevalence of inactivity increases.[5] These tendencies have been observed in both sexes between the ages of 12 and 21.[6] Sallis[7] has reported, based on data from cross-sectional and prospective studies in the US, that the decline in physical activity mainly occurs between the ages of 13 and 18 years. This may, in part, be explained by the fact that fewer school-age students are physically active during their leisure time.[8] Changes in social environments are often cited as explanatory factors for decreased physical activity among young people. Thus, within the early years of adulthood, significant changes in life circumstances, such as those occurring in urbanized societies and less daily physical activities, may strongly affect physical activity patterns.[5] On the other hand, many current occupational requirements in urbanized societies no longer require high physical demands (e.g. walking, lifting, carrying loads), which also impact current trends in physical fitness. For those occupations that do impose high physical demands, a positive association has been found between heavy physical work and a high level of fitness in young workers. More specifically, better aerobic fitness, handgrip strength, and trunk muscle endurance have been observed among men doing heavy physical work (e.g. work with frequent walking, standing work ª 2010 Adis Data Information BV. All rights reserved.

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with light loads or lifting, and carrying of heavy loads) compared with those doing lighter work (e.g. sedentary work). These associations were independent of leisure-time physical activity, bodyweight and height.[9] A reduced amount of physical activity (occupational, household and leisure time activities) combined with a hypercaloric diet has resulted in increasing numbers of overweight and obese individuals worldwide.[10] The increasing number of overweight children and teenagers is of particular concern.[11,12] In the US, the prevalence of obesity nearly doubled in the 1990s,[13] while at the same time the prevalence of type 2 diabetes mellitus and other obesity-related diseases has dramatically increased.[14] While this is true, there is some evidence showing that secular increases in fatness have coincided with secular declines in several cardiovascular disease risk factors such as cholesterol, blood pressure and smoking.[15] Particularly among obese persons, these changes have also coincided with increases in lipid-lowering and anti-hypertensive medication use. It is also important to note recent contradictory reports that have shown a plateau in the rate of overweight children and childhood obesity over the past decade.[16-18] In the scientific literature as a whole, there are several papers where associations between physical activity, obesity and health outcomes have been studied. However, a very limited number of studies have examined physical fitness in relation to health factors. Therefore, this article presents a review of current physical fitness profiles of young men. In addition, the importance of fitness level is evaluated in relation to obesity and health. The articles have been selected from literature searches using the main keywords ‘physical fitness’ and ‘young men’ from MEDLINE and SportDiscus search engines. References from 1966 to 2009 were selected. Additional selected references were included that encompassed reports for physical activity in children, as well as health outcomes (lipid and glucose metabolism, metabolic syndrome and hypertension). Together we found more than 500 published articles, of which 85 were selected for this review according to inclusive criteria of the main keywords and articles concerning physical activity and health outcomes. Sports Med 2010; 40 (11)

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1. Determination of Physical Fitness Physical fitness has been defined as a measure of ‘how well one performs physical activity’, which is, in turn, defined as ‘body movement produced by muscle action that increases energy expenditure’.[1] Physical fitness thus consists of various components such as endurance, strength, flexibility, coordination and balance, which have been well described by Knapik et al.[19] Neuromuscular fitness (muscle strength and coordination) can be measured either in laboratory conditions (e.g. isometric force production and counter-movement jump) or by field tests (e.g. bench press and standing long jump). Endurance refers to the ability to resist fatigue, and depends on the energy supply of working muscles and the adequacy of this supply. Aerobic fitness can be determined.exactly by measuring maximal oxygen uptake (VO2max) in laboratory circumstances, but different field tests (e.g. 12-minute run test) are also used to estimate . . VO2max in epidemiological studies. In fact, VO2max can be improved by optimal physical activity[20] by 12%,[21] although approximately 40–60% of its variation is genetically determined.[22] Furthermore, the . magnitudes of training-induced changes in VO2max differ among children, adolescents and young adults. The term ‘cardiorespiratory fitness’ has generally been defined as the ability of the circulatory and respiratory systems to supply oxygen to skeletal muscles during sustained physical activity. Aerobic fitness encompasses the functions of the circulatory and respiratory systems and, as such, can be utilized to study functional capability of those systems. In the present article, the terms ‘cardiovascular . fitness’, ‘cardiorespiratory fitness’ and ‘VO2max’ have been referred to as ‘aerobic fitness’. While muscle strength and endurance are essential components of physical fitness, this article will mainly focus on aerobic fitness as the fitness parameter of interest. 2. Profiles of Physical Fitness in Young Men Table I presents a summary of reports in which physical fitness has been studied, predominantly in male populations. However, only a small ª 2010 Adis Data Information BV. All rights reserved.

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number of studies have measured physical fitness in a large population. Thus, we have also included some surveys and literature reviews. Collectively, these studies suggest a disturbing worldwide trend of decreased aerobic fitness and increased obesity in male children, adolescents and young adults. Recent studies clearly demonstrate that physical fitness, particularly aerobic fitness, has dramatically decreased during the last 2–3 decades in young male populations.[19,29,33] In the UK, aerobic fitness has decreased by 11% in 9- to 11-year-old boys between 1998–9 and 2003–4.[27] However, this study should be interpreted with caution, as a 20 m shuttle run test was used, and. this test only partly describes the variance for VO2max values. Interestingly, in their serial cross-sectional study, physical fitness also decreased among lean children within a 6-year period. Among Australian children and adolescents, a significant decline has been observed in aerobic fitness test performances in recent decades.[41] In this regard, particularly strong evidence is provided by population-based studies of young men (aged 19–20 years) entering the army. Tests performed at the. beginning of military service indicated that VO2max values have decreased by 8–12% during the last 2–3 decades,[29,33] which corresponds to an approximate 4% decrease in each decade. Interestingly, Knapik et al.[19] have reported secular declines in 3.2 km (2 mile) run .times, but stability in aerobic fitness assessed by VO2max. Similar trends have also been reported over shorter time periods among children. A cross-sectional survey in young people aged 12–19 years in the US revealed that approximately one-third of males did not meet the recommended standards for aerobic fitness.[32] In addition, a survey in Georgia, USA showed that 52% of 12- to 14-year-old students did not meet the standard for aerobic fitness.[23] Leyk et al.[30] studied more than 58 000 applicants for the German Bundeswehr (army). Only volunteers who completed their schooling and had a body mass index (BMI) below 30 kg/m2 were selected to perform the tests. The accepted subjects (aged 17–26 years) performed a physical fitness test (PFT) consisting of a shuttle run, sit-ups, push-ups, standing jump and the 12-minute run test. The authors reported Sports Med 2010; 40 (11)

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Table I. Studies investigating the associations between physical fitness (PF), physical activity and body composition in young men during the last few decades Study, year

Subjects

Study design

Main findings

Other findings

Peneau et al.,[18] 2009

26 600 French boys and girls aged 6–15 y between 1996 and 2000

Cross-sectional (time-related)

Overweight prevalence increased between 1996 and 1998, but has remained stable since 2001

Overweight prevalence has also remained stable in socioeconomically disadvantaged group

Powell et al.,[23] 2009

Survey in Georgia, USA; a state-wide sample of 5th and 7th grade students; n = 5248, aged 12–14 y

Cross-sectional (single timepoint)

52% of students did not meet the standard for healthy aerobic fitness, 23% muscular strength, endurance and flexibility

30% were outside the recommended BMI range

McGavock et al.,[24] 2009

Annual school-based survey, two cohorts (n = 902 and 222), aged 6–15 y

Cross-sectional (time-related)

Risk of becoming overweight was 3.5-fold higher in youths with low cardiorespiratory fitness than in their fit counterparts

Decreased cardiorespiratory fitness was significantly and independently associated with increases in BMI

Dencker et al.,[25] 2008

225 children aged 8–11 y

Cross-sectional (single timepoint)

Vigorous activity was independently associated with aerobic fitness

Vigorous activity was negatively correlated with fat % and abdominal fat mass

Leyk et al.,[26] 2008

12 835 German males and females

Cross-sectional (single timepoint)

Increased cardiovascular risk factors for ages 20–25 y

50% of men were overweight, 60% smoked

Ogden et al.,[16] 2008

8165 US children from NHANES; 2003–4 and 2005–6

Cross-sectional (single timepoint)

Prevalence for high BMI showed no changes between 2003 and 2006 and no trends between 1999 and 2006

58% of children were above 85% percentile for 2000 BMI for age growth charts

Sjo¨berg et al.,[17] 2008

13 002 Swedish 4th grade children

Cross-sectional (time-related)

Between 2000 and 2005, prevalence of overweight and obesity in girls decreased from 19.6% to 15.9%

Between 2000 and 2005, prevalence of overweight and obesity among boys was stable (17.1% vs 17.6%)

Stratton et al.,[27] 2007

15 621 children (50% boys) aged 9–11 y; school cohorts in Liverpool, UK

Serial, crosssectional

Cardiorespiratory fitness decreased by 10.6% in boys, and BMI increased from 16.6 to 17.4

Among lean children, PF also decreased

Hivert et al.,[28] 2007

2 y randomized controlled trial (n = 115), aged 20 y

Longitudinal

No differences in PF, physical activity or energy intake, but the control group gained more weight

Educational intervention prevents weight gain in normal weight young adults

Santtila et al.,[29] 2006

Conscripts for the Finnish Defence Forces (n = 387 088), aged 20 y

Cross-sectional (time-related)

Aerobic capacity decreased by 12% since 1979; muscle fitness decreased dramatically since 1992

Bodyweight increased by 5.9%

Leyk et al.,[30] 2006

Applicants for the German Bundeswehr (army) [n = 58 000], aged 17–26 y, BMI <30 kg/m2

Cross-sectional (single timepoint)

More than 37% of the subjects failed the PF tests; the failure rates have increased since 2001; only 5.3% ran more than 2851 m in the Cooper test

Fogelholm et al.,[31] 2006

Healthy Finnish men (n = 951), aged 29 – 4 y

Cross-sectional

Functional muscle fitness of the upper body, trunk and lower extremities was impaired in individuals with abdominal obesity

Bodyweight and BMI increased between the ages of 17 and 26 y. PF was positively correlated, and BMI negatively correlated with education level . VO2max 42.7 – 7.2 mL/kg/min. The deterioration of NMF deserves further attention

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Table I. Contd Study, year

Subjects

Study design

Main findings

Knapik et al.,[19] 2006

Literature review of US army recruits; 19 papers

Cross-sectional (time-related)

Muscle strength increased between 1978 and 1998; no change in muscular endurance between 1984 and 2003; aerobic performance decreased between 1987 and 2006

Pate et al.,[32] 2006

US youths aged 12–19 y, (n = 4732)

Cross-sectional (single timepoint)

About one-third of males did not meet recommended standards for cardiorespiratory fitness

Dyrstad et al.,[33] 2005

18- to 19-year-old Norwegian men, n = 183 610 in 1980 and 1985; n = 1383 in 2001–2

Cross-sectional (time-related)

Gregg et al.,[15] 2005

Analysis of 5 US crosssectional surveys (n > 45 000 subjects) over a 40-y period (1960–2000) involving men and women aged 20–74 y

Cross-sectional (time-related)

Prevalence of risk factors (cholesterol, blood pressure, smoking, etc.) decreased over time for overweight and obese individuals

Diabetes risk factors were similar over time

Ferreira et al.,[34] 2005

364 adolescent boys and girls (aged 13 y) at the beginning of the study through to young adulthood (aged 36 y); data were collected from the same subjects during a 24-y follow-up period

Longitudinal

The prevalence of metabolic syndrome at the age of 36 y was 10.4% due to increases in body fatness, decreases in cardiopulmonary fitness, and higher energy intake

Fatness, fitness and lifestyle are important independent determinants of metabolic syndrome in young adults

Dowda et al.,[35] 2003

The civilian noninstitutional population of the US (n = 4964), aged 18–20 y

Cross-sectional (single timepoint)

Education, social support index and trying to lose bodyweight were positively associated with vigorous physical activity

Demographic and social factors are important determinants of physical activity

Knapik et al.,[36] 2001

756 male and 474 female US soldiers

Cross-sectional (single timepoint)

Women have twice the injury rate than men; fewer pushups, slower 3.2 km run times, . lower VOpeak, and smoking were risk factors for timeloss injuries

Among men only, lower levels of physical activity before basic combat training and high and low flexibility were risk factors for time-loss injury

Leslie et al.,[5] 2001

Three Australian samples, aged 18–19, 20–24, and 25–29 y (n = 2729)

Cross-sectional (single timepoint)

There was at least a 15% difference in vigorousintensity leisure-time physical activity between the age groups of 18–19 and 25–29 y, and at least a 10% difference in moderateintensity leisure-time physical activity

Promoting walking and various forms of moderateintensity physical activities may help to ameliorate decreases in physical activity over the adult lifespan

. VO2max relative to bodyweight decreased by 8% over the last 20 y; at the same time, bodyweight increased by 7% (4.7 kg)

Other findings . VO2max did not change between 1975 and 1998; body mass (body fat and fat-free mass), and BMI increased between 1998 and 2003

Low levels of physical activity and high levels of sedentary behaviour were associated with lower cardiorespiratory fitness BMI has increased by 6%; the number of men in the group . with lowest relative VO2max had doubled

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Table I. Contd Study, year

Subjects

Study design

Main findings

Other findings

Kemper et al.,[37] 2000

Male and female participants, aged 13–27 y (n = 182)

Longitudinal

A significant relationship was found between daily physical . activity and VO2max; neuromuscular fitness was associated with bone mineral density

30% increase in physical activity increased aerobic fitness by 2–5%; daily physical activity decreased from 5000 MET/wk in boys (aged 13 y) to 3000 MET/wk in men (aged 21 y)

Rasmussen et al.,[38] 1999

All Swedish males born in 1953, 1958, 1963, 1968 and 1973–7; (n = 503 689); mean age 18 y

Cross-sectional (time-related)

Mean BMI increased by 6.6% from 1971 (21.2 kg/m2) to 1995 (22.4 kg/m2); the prevalence of overweight individuals increased 1.4 times and obesity 1.7 times between 1971 and 1993

There is increased risk of becoming overweight among young men in low educated families and in rural areas

Armstrong et al.,[33] 1991

British children aged 11–16 y (226 boys and 194 girls)

Cross-sectional (single timepoint)

Jones et al.,[39] 1993

124 male and 186 female US soldiers

Cross-sectional (single timepoint)

Women had higher incidence of time-loss injuries than men (45% vs 29%)

Low aerobic fitness is associated with injury risk

Jones et al.,[40] 1993

303 male soldiers

Cross-sectional (single timepoint)

Age, smoking, previous injury, low levels of prior activity, low frequency of running, flexibility were risk factors for injury

High unit running mileage was also associated with injury risk

. Boys VOpeak in relation to body mass was consistent over the age range studied and greater than girls

More mature boys and girls . had VOpeak

BMI = body NHANES = National . mass index; MET =. metabolic equivalent; . . . Health and Nutrition Examination Surveys; NMF = neuromuscular fitness; VO2 = oxygen uptake; VO2max = maximal VO2; VO2peak = peak VO2.

that the failure rates of male volunteers had significantly increased since 2001, and more than 37% of the participants failed to pass the PFT. The CARDIA (Coronary Artery Risk Development In Young Adults) study further revealed that fitness declined during young adulthood and that changes in fitness are related to changes in body mass and physical activity.[42] Very few studies have examined how neuromuscular fitness has changed during the last few decades and, due to this issue, it remains controversial. A review by Knapik et al.[19] shows that muscle strength has increased among US Army recruits between 1978 and 1998. In a populationbased study, muscle fitness has been shown to decrease, but this occurred later than the decrease in aerobic fitness (from 1992 onwards).[29] The functional significance of lowered physical fitness ª 2010 Adis Data Information BV. All rights reserved.

profiles has been demonstrated by showing an increased risk of musculoskeletal injuries among US soldiers.[36,39,40] 3. Associations between Physical Fitness, Body Composition and Obesity Body composition is strongly related to physical fitness. Increased fat mass is a strong predictor of poor physical fitness.[43] In 2266 boys and girls aged 15–16 years, being overweight was found to be negatively associated with both aerobic and muscle endurance, as well as explosive power.[44] These are examples of studies showing the interaction between body composition and physical fitness.[45] In addition to the recent decrease in physical fitness, it is well known that the prevalence of obesity has increased during recent decades in Sports Med 2010; 40 (11)

Physical Fitness Profiles of Young Men

Western countries.[46] In fact, this trend has been apparent across all age and social groups from 1960 to 1991.[47] Body mass and BMI have reportedly also increased among applicants for the German army from 2001 to 2006.[30] A survey among 12- to 14-year-old children, of whom 52% did meet the standard of aerobic fitness, revealed that 30% were outside of their recommended BMI range.[23] In a cross-sectional study of children aged 8–11 years, vigorous activity was found to be negatively correlated with body fat percentage and abdominal fat mass.[25] However, a prospective 4-year study among 18-year-old participants suggested that dietary intake was the major contributor to positive energy balance,[48] which is indicative of weight gain. In that study, physical activity and fat mass were significantly associated with each other. In addition, it was observed that fat distribution differed in lean, fit, young males; increasing adiposity was not found in the trunk region, but rather in the arms.[49] A review by Ekelund et al.[48] reported that the number of overweight and obese people is increasing exponentially in all age groups in the US, Australia, Latin America and many European countries. Gains in body mass, particularly fat mass, are the consequence of a positive energy balance. This may primarily be caused by dietary intake (energy-dense food)[48] and/or decreased physical activity. Furthermore, obese Japanese males have been shown to be characterized by lower physical fitness.[50] A national survey (a cohort study in 1985 of children aged 7–15 years [n = 8498] and 2005 [n = 4571]) has shown that childhood obesity has also increased in Australia. Among boys, the proportion of overweight individuals has increased from 9% to 15%, and obesity prevalence from 1% to 5%. The relative risk of becoming an obese adult was significantly greater (4.7-fold higher) for those who had been obese as children than for those who were normal weight. Therefore, obesity in childhood is strongly predictive of obesity in early adulthood. However, the most obese young adults were actually in a healthy weight range as children.[51] A 2004–6 Canadian longitudinal study using an annual school-based survey of children aged 6–15 years reported that the risk of becomª 2010 Adis Data Information BV. All rights reserved.

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ing overweight was 3.5-fold higher in youth with low aerobic fitness than in their fit counterparts.[24] Reductions in aerobic fitness have also been found to be significantly and independently associated with increases in BMI. Furthermore, table I shows that mean BMI increased by 7% from 1971–95 among 18-year-old Swedish men.[38] Several intervention strategies have been studied to combat obesity and poor physical fitness. A randomized controlled trial performed over 2 years with an educational healthy lifestyle intervention revealed that the control group gained more body mass compared with the non-educational group, and their plasma triglyceride levels increased compared with the non-intervention group.[28] In general, several studies[28,35] have suggested that educational factors are important determinants of physical activity and, thus, also of physical fitness. Physically inactive people are more often obese than those who are either active during their leisure time or those whose work is physically challenging.[52] Therefore, physical activity is a very powerful method of reducing bodyweight.[53] Although BMI may not change, exercise decreases fat mass, waist circumference[54] and visceral fat.[53] It should be emphasized that these are all positive health effects.[54] It has been shown that an increase of 30% in physical activity can increase aerobic fitness by 2–5%.[55] This positive development is naturally highest among people with poor physical fitness. Trunk et al.[56] reported that recruits who were in poor physical condition at the beginning of the training season improved their run times in a 2.4 km (1.5-mile) run test more than those who entered in better physical condition. Similar findings were also reported in a. study by Santtila et al.;[21] the lower the initial VO . 2max values, the greater the enhancement of VO2max. In addition, inactive subjects . showed the greatest improvements (19%) in VO2max values during the 8-week military basic training. 4. Health-Related Outcomes 4.1 Metabolism and Body Composition

Physical fitness is known to be associated with several components of metabolism. In the Sports Med 2010; 40 (11)

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Amsterdam Growth and Health Longitudinal Study,[34] when subjects with metabolic syndrome (mean age 36 years) were compared with those without the syndrome, the following characteristics were exhibited between adolescence and the age of 36 years: (i) a marked increase in total body fatness and subcutaneous trunk fat; (ii) a marked decrease in aerobic fitness level; (iii) a marked increase in physical activities of light to moderate intensity, but a greater decrease in vigorous physical activities; (iv) a trend towards a higher energy intake; and (v) an increased likelihood of drinking alcoholic beverages. Therefore, the authors concluded that physical fitness, as well as fatness and lifestyle, appear to be important determinants of metabolic syndrome in young adults.[34] Further supporting data have also been published from the CARDIA study in which subjects with low aerobic fitness (<20th percentile) were 3–6 times more likely to develop diabetes, hypertension and metabolic syndrome than subjects with high fitness (>60th percentile) after adjusting for age, race, sex and smoking status, family history of diabetes, hypertension, or premature myocardial infarction. After baseline adjustment for aerobic fitness, BMI diminished the strength of these associations to 2-fold, but this was still highly significant. Interestingly, the association between low aerobic fitness and hypercholesterolaemia was modest (hazard ratio [HR] 1.4; p = 0.04) and became nonsignificant after BMI adjustment.[57] In a cross-section of 12 835 German males aged 16–25 years, Leyk et al.[26] have reported that 50% were overweight and 60% smoked, resulting in elevated cardiovascular risk profiles. Furthermore, improved aerobic fitness over a 7-year period was associated with a reduced risk of developing diabetes (HR 0.4; p = 0.04) and metabolic syndrome (HR 0.5; p < 0.001).[57] Another group reported that muscular strength was inversely associated with metabolic syndrome incidence, independent of age and body size, in 3233 healthy men aged 20–80 years. In a regression analysis adjusted for age, the HRs of metabolic syndrome associated with incremental categories of muscular strength were 1.00 (reference), 0.88, 0.77 and 0.54, respectively (linear trend p < 0.0001). The inverse trend persisted ª 2010 Adis Data Information BV. All rights reserved.

after adjustment for smoking, alcohol intake, number of baseline metabolic syndrome risk factors, family history of diabetes, hypertension and premature coronary disease (p = 0.004), but was attenuated when further adjusted for aerobic fitness (p = 0.06).[58] Therefore, both aerobic and muscular fitness seem to offer protective effects against metabolic syndrome.[34,57,58] The relationship between glucose metabolism and physical fitness has also been investigated in studies using insulin-adjusted glucose disposal rate as a measure of glucose metabolism. In 20- to 24-year-old men with high and normal blood pressure (both n = 19), insulin-adjusted glucose disposal rate during a hyperinsulinaemic glucose clamp test was positively and independently associated with peak oxygen uptake.[59] The authors also reported in the same study that insulin sensitivity and autonomic cardiac control were independently related to physical fitness in young men.[60] These associations were further investigated in the CARDIA study, where autonomic dysfunction in combination with poor aerobic fitness was suggested to be a mechanism associated with early glucose dysmetabolism and the development of diabetes.[61] The relationship between insulin sensitivity and physical fitness was also evaluated in another study, where aerobic fitness and minimal forearm vascular resistance independently explained 60% of the variation in insulin sensitivity in 27 young men with blood pressure of 140/90 mmHg or higher.[62] 4.2 Cardiovascular Health

Aerobic fitness is associated with reduced cardiovascular morbidity, inflammation and mortality.[63-65] One possible mechanism by which physical fitness may reduce the risk of cardiovascular diseases is by influencing arterial stiffness. In a longitudinal study,[66] increased aerobic fitness from adolescence to the age of 36 years was associated with reduced arterial stiffness. However, improved fitness was not associated with carotid intima media thickness in that study. Aerobic fitness, physical activity and arterial stiffness were also measured in 405 young men and women in the Northern Ireland Young Heart Sports Med 2010; 40 (11)

Physical Fitness Profiles of Young Men

Study. Both aerobic fitness and sport-related physical activity, but not leisure nor work-related physical activity, were inversely associated with arterial stiffness. The associations between sportrelated physical activity and arterial stiffness were also strongly mediated by fitness, but physical activity levels did not affect the associations between aerobic fitness and arterial stiffness. Therefore, the authors suggested that arterial stiffnessrelated benefits are most likely to accrue if exercise targets improvements in aerobic fitness.[67] Another study investigated the effects of aerobic fitness on nitrite/nitrate concentrations and microcirculatory endothelial function in male adults. Nitrite/nitrate concentrations were positively correlated with aerobic fitness, and the authors concluded that chronic exercise may improve endothelial function, probably by increasing nitric oxide availability.[68] C-reactive protein (CRP) has also been used as a predictor of cardiovascular events. CRP has been demonstrated to be inversely associated with aerobic fitness in 26-year-old men (n = 400) and women (n = 315), independent of obesity, blood pressure or smoking. This may indicate that physical fitness could decrease the risk of cardiovascular events by reducing inflammation.[65] The relationship between physical fitness and CRP was also found in children and young adults in the Columbia University BioMarkers Study,[69] where fitness level was inversely correlated with CRP (r = -0.22). Previous studies have reported that white blood cell count is inversely associated with physical fitness.[70] Both aerobic fitness and physical activity are also known to influence several risk factors for cardiovascular diseases. In a large-scale, crosssectional study of 6748 healthy young men, independent relationships between physical fitness and several risk factors were evaluated. While physical activity itself showed no association with other variables, good physical fitness was related to improved blood pressure and blood lipids. These relationships were independent of participation in endurance or non-endurance sports, of physical activity per se, and did not depend on smoking and drinking habits.[71] In addition, results from one population-based longitudinal ª 2010 Adis Data Information BV. All rights reserved.

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cohort study (CARDIA)[72] revealed that decreased aerobic fitness was associated with decreased high-density lipoprotein cholesterol (HDL-C) and, conversely, increased fitness was associated with increased HDL-C during a 7-year follow-up. In addition, changes in fitness were minimally correlated with changes in low-density lipoprotein cholesterol (LDL-C), triglycerides and total cholesterol. However, the magnitudes of these correlations were further reduced with adjustment for weight change. Interestingly, correlations between changes in physical activity and changes in lipids were weak or nonexistent, which was at least partly explained by imprecision of activity measurement.[72] The association between total cholesterol and physical fitness has also been reported in 18-year-old Australians (n = 587). In that study, physical fitness was negatively correlated with systolic blood pressure.[73] Excellent aerobic fitness can cause cardiac changes, called ‘athlete’s heart’, which include greater left ventricular wall thickness, internal diameter and muscle mass, and lower heart rate. In a study of 346 athletes and controls, echocardiography analyses indicated that in athletes having higher aerobic fitness, oxygen consumption depends largely on cardiac condition, while in athletes with lower endurance capacity, the consumption might be limited by peripheral conditions.[74] Another recent study[75] demonstrated a nonlinear relationship between haemoglobin concentration and aerobic fitness. A haemoglobin level of 12–14 g/dL was significantly associated with a faster 2000 m running time (mean 530 seconds; n = 176) than both the lower haemoglobin group (570 seconds; n = 16) and the higher haemoglobin group (552 seconds; n = 166).[75] The relationship between some components of musculoskeletal fitness and all-cause mortality was studied in 8116 people aged 20–69 years (Canadian fitness survey).[76] In this study, a sit-up test was performed as a measure of abdominal muscular endurance, and the researchers observed an increased risk of mortality in those individuals in the lower quartile of sit-up performance in both men and women. Similarly, there was a 49% increased risk of all-cause death in individuals in the lower quartile of grip strength performance in men.[76] Sports Med 2010; 40 (11)

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4.3 Musculoskeletal Health

Physical activity has effects on bone health, but the association between physical fitness and bone health is more complex. In the Amsterdam Growth and Health Longitudinal Study,[37] the relationship between lumbar and femoral bone mineral density (BMD) and physical fitness/ physical activity was investigated in a sub-study of 182 participants. Physical fitness was measured based on neuromuscular fitness tests (six strength, flexibility and speed tests) and aerobic fitness . (VO2max). During young adulthood, neuromuscular fitness, but not aerobic fitness, was related to bone health measured as BMD in 28-year-old individuals.[37] Supporting data were reported in another study where BMD was associated with muscle strength in healthy young men.[77] Although aerobic training can also improve BMD, it appears that high-impact training has a greater relative relationship to bone health than aerobic fitness.[78] The relationship between physical fitness and injury risk is very complex. In a study of 135 987 Finnish army conscripts, over 7000 were hospitalized, of which 50% were due to lower limb injuries. The strongest risk factors for injury-related hospitalization were being female (odds ratio [OR] 2.3) and being overweight (OR 1.4). Surprisingly, excellent aerobic fitness was also a specific risk factor for lower limb injury (OR 1.3).[79] However, in another epidemiological prospective cohort study of 152 095 healthy Finnish conscripts, poor muscle strength and a poor 12-minute run time were significantly associated with MRIdetected bone stress injuries.[77] An association between poor physical fitness and injury risk has also been observed among Danish and Norwegian military conscripts.[80,81] To conclude, both poor muscle strength and poor aerobic fitness seem to be associated with the tendency to be injury prone, but interestingly, excellent aerobic fitness may also be a risk factor for lower limb injuries, possibly attributed to increased training volume. As previously mentioned in section 2, lowered physical fitness profile has been shown to be associated with increased risk of musculoskeletal injuries among US soldiers.[36,39,40] ª 2010 Adis Data Information BV. All rights reserved.

5. Conclusions Important factors determining health include hereditary characteristics and lifestyle, as well as social and physical environments. In young men, declines in physical fitness combined with increases in body mass and fat create a major public health threat. Lifestyle and health behaviour are closely connected. In other words, a person can change some health risk factors by modifying his or her lifestyle, which has been the goal of modern preventative medicine. Various behaviour modification techniques have been widely applied to motivate people to change their lifestyle in order to diminish health risk factors. Parental encouragement to be active has been shown to be associated with increased physical activity among men.[82] Thus, encouragement from parents might be an effective method of altering physical activity habits of children and adolescents. As well as parents, the role of kindergartens and schools are essential in the promotion of physical activity, and subsequent increases in physical fitness in young people. Countries that have a compulsory military service (e.g. Finland) may also have an influence on physical activity patterns. It is not surprising that military employment has an effect on physical activity patterns, given the requirements for soldiers to possess high levels of physical fitness. In addition, it has been shown that employees practicing sports take significantly fewer sick absences than their nonsporting counterparts.[83] Another study reported that workers who were active in their leisure time two or more times per week took fewer sickness absences than inactive workers.[84] Kyro¨la¨inen et al.[85] have concluded that poor muscle strength and endurance, as well as high BMI, are risk factors for productivity loss causing additional costs to employers. Therefore, workers at a greater risk should be offered multifaceted information about potential health risks, as well as motivational support to improve their lifestyle. Proper nutrition is yet another aspect of this complex problem. In addition to a reduced energy intake, dietary composition is also important. It has been shown that increased consumption of fruit and dairy products, and reduced energy intake Sports Med 2010; 40 (11)

Physical Fitness Profiles of Young Men

from fat are related to increased physical activity.[86] However, Leyk et al.[30] have cautioned against treating the terms ‘overweight’ and ‘physically unfit’ as being synonymous, despite the existence of correlations between BMI and physical fitness. According to the general recommendations[87] to improve physical fitness, and to promote and maintain health, all healthy adults aged 18–65 years require moderate-intensity, endurance-based aerobic exercise for a minimum of 30 minutes, 5 days a week, for example, by walking briskly, or performing other activities that noticeably increase heart rate. It is also possible to achieve sufficient physical activity levels by performing vigorousintensity aerobic exercise for at least 20 minutes, 3 days a week, such as jogging or performing other exercises that cause rapid breathing and a substantial increase in heart rate. These recommendations can also be achieved by combinations of moderate- and vigorous-intensity physical activity. In addition, healthy adults should perform physical exercises that maintain or increase muscular strength and endurance a minimum of twice per week. Individuals who wish to further improve their physical fitness, reduce their risk of chronic diseases and disabilities, or prevent unhealthy weight gain may benefit from exceeding the minimum recommended volume of physical activity due to the dose-response relationship between physical activity and health. Both high-volume physical activity and good physical fitness are associated with reduced mortality and enhanced health.[63,64] However, physical activity and physical fitness are not synonymous. In some respects, the scientific evidence concerning the benefits is stronger in the case of physical activity, and in other aspects, in the case of physical fitness. Different types of physical activity have various effects on health in the same way that different types of fitness are associated with different components of health. Aerobic fitness is more strongly associated with reduced cardiovascular and metabolic morbidity, while musculoskeletal fitness is mainly linked to bone, muscular and metabolic health. Therefore, in order to evaluate the overall fitness level, it is essential to examine all the elements of fitness including aerobic ª 2010 Adis Data Information BV. All rights reserved.

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and muscular fitness. Measurement of physical fitness is a more objective than subjective estimation of physical activity levels. Therefore, in clinical practice and health education, a person’s physical fitness should be frequently measured. Moreover, population-based surveys should be combined with regular measurement of physical fitness to study sedentary lifestyles, particularly in young people. Acknowledgements The opinions or assertions contained in this review are the private views of the authors and are not to be construed as official or reflecting the views of the US Army or the US Department of Defense. No sources or funding were used to assist in the preparation of this review. The authors have no conflicts of interest that are directly relevant to the content of this review.

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80. Rosendal L, Langberg H, Skov-Jensen A, et al. Incidence of injury and physical performance adaptations during military training. Clin J Sport Med 2003; 13: 157-63 81. Heir T, Eide G. Injury proneness in infantry conscripts undergoing a physical training programme: smokeless tobacco use, higher age, and low levels of physical fitness are risk factors. Scand J Med Sci Sports 1997; 7: 304-11 82. Bauer KW, Nelson MC, Boutelle KN, et al. Parental influences on adolescents’ physical activity and sedentary behavior: longitudinal findings from Project EAT-II. Int J Behav Nutr Phys Act 2008; 5: 1-7 83. van Heuvel SG, Boshuizen HC, Hildebrandt VH, et al. Effect of sporting activity on absenteeism in a working population. Br J Sports Med 2005; 39: 1-5 84. van Amelsvoort LGPM, Spigt MG, Swaen GMH, et al. Leisure time physical activity and sickness absenteeism; a prospective study. Occup Med 2006; 56: 210-12

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85. Kyro¨la¨inen H, Ha¨kkinen K, Kautiainen H, et al. Physical fitness, BMI and sickness absence in male military personnel. Occup Med 2008; 58: 251-6 86. Jago R, Nicklas T, Yang SJ, et al. Physical activity and health enhancing dietary behaviors in young adults: Bogalusa Heart Study. Prev Med 2005; 41 (1): 194-202 87. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007; 39 (8): 1423-34

Correspondence: Dr Heikki Kyro¨la¨inen, Department of Biology of Physical Activity, University of Jyva¨skyla¨, P.O. Box 35, 40014, Jyva¨skyla¨, Finland. E-mail: [email protected]

Sports Med 2010; 40 (11)

REVIEW ARTICLE

Sports Med 2010; 40 (11): 921-940 0112-1642/10/0011-0921/$49.95/0

ª 2010 Adis Data Information BV. All rights reserved.

The Impact of Training Modalities on the Clinical Benefits of Exercise Intervention in Patients with Cardiovascular Disease Risk or Type 2 Diabetes Mellitus Dominique Hansen,1,2,3 Paul Dendale,1,2 Luc J.C. van Loon4 and Romain Meeusen5 1 Jessa Hospital/Heart Centre Hasselt, Hasselt, Belgium 2 Faculty of Medicine, Hasselt University, Diepenbeek, Belgium 3 Rehabilitation & Healthcare Research Centre, Department of Healthcare, PHL-University College, Hasselt, Belgium 4 Department of Human Movement Sciences, Nutrition and Toxicology Research Institute (NUTRIM), Maastricht University Medical Centre, Maastricht, the Netherlands 5 Department of Human Physiology and Sports Medicine, Vrije Universiteit Brussel, Brussels, Belgium

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Literature Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. General Clinical Benefits of Endurance-Type Exercise Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Obesity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Metabolic Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Type 2 Diabetes Mellitus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Heart Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Impact of Training Modalities on Clinical Benefits of Exercise Intervention . . . . . . . . . . . . . . . . . . . . . . 4.1 Programme Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Additional Resistance-Type Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Continuous Exercise Training Intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 High-Intensity Interval Exercise Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Training Session Volume/Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Training Frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. General Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

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Exercise training intervention represents an effective means to reduce adipose tissue mass, improve glycaemic control and increase whole-body oxygen . uptake capacity (VO2peak) in obesity, metabolic syndrome, type 2 diabetes mellitus (T2DM) and heart disease patients. In this manuscript, we review the impact of different exercise training modalities on clinical benefits of prolonged exercise intervention in these patient (sub)populations. By changing training modalities, significantly greater clinical benefits can be obtained.

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Greater training frequency and longer programme duration is associated with greater reduction in adipose tissue mass in obesity patients. A greater training frequency (up to 2 days/week) and a longer programme duration (up . to 38 weeks) seems to be associated with greater improvements in VO2peak in heart disease patients. Longer programme duration and addition of resistancetype exercise further improve glycaemic control in T2DM patients. The first line of evidence seems to indicate that high-intensity interval exercise training . has a greater impact on VO2peak in heart disease patients and insulin sensitivity in subjects with metabolic syndrome, but not on adipose tissue mass in obese subjects. However, it remains unclear whether addition of resistancetype exercise and continuous higher-intensity endurance-type exercise train. ing are accompanied by greater improvements in VO2peak in heart disease patients. Furthermore, the impact of training session duration/volume on adipose tissue mass loss and glycaemic control in obesity and T2DM patients, respectively, is currently unknown. The impact of training frequency on glycaemic control remains to be investigated in T2DM patients.

1. Introduction Over the past 2 decades, the world has experienced an increased incidence of obesity, resulting in a global obesity epidemic.[1] A key reason behind this epidemic is the lack of habitual physical activity and food abundance. Our genome was probably selected in the late Palaeolithic period (50 000–10 000BC) from criteria that favoured survival in a physically demanding environment, such as our ancestors’ hunter and gatherer society.[2] Fluctuations between feast and famine were common, resulting in oscillations in endogenous fuel storage, plasma insulin and metabolic regulatory proteins, which in turn may have driven selection of a metabolic genotype optimal for such conditions. The ‘thrifty genes’ theory states that these feast-famine cycles are required for optimal metabolic function.[2,3] Those individuals in the late Palaeolithic period who were capable of converting joules into adipose tissue and could easily store lipids during feasting were more likely to have higher survival rates during famine and were capable of passing their genes onto the next generation. It is evident that most individuals within our modern society are carriers of this socalled thrifty genotype. Therefore, overfeeding in combination with a sedentary lifestyle, as seen in the modern era, is the main cause for the increased prevalence of obesity.[4] ª 2010 Adis Data Information BV. All rights reserved.

In addition to increased mortality risk, obesity is closely linked to development of insulin resistance, metabolic syndrome, type 2 diabetes mellitus (T2DM) and heart disease.[4] Recent estimations indicate that the incidence of T2DM will continue to increase, with an estimated rise in number of T2DM patients up to 366 million in the year 2030.[5] It is expected that economic costs related to treatment of these diseases will increase exponentially. Clinical guidelines have been published to optimize primary and secondary prevention of T2DM and heart disease in an attempt to suppress this epidemic.[6,7] Besides medication prescription and food intake modification, exercise training interventions are considered a cornerstone in prevention and care of individuals with obesity, metabolic syndrome, T2DM and/or heart disease. According to current clinical guidelines, significant health benefits can be obtained when performing a minimum of 150 minutes of moderateintensity exercise per week, with a progressive increase to 200–300 minutes per week.[6,7] These exercises should be executed on at least 3, and preferably 5, days per week, and be accompanied by resistance-type exercise. These guidelines provide an effective strategy for the care of these patient populations. Tjønna and colleagues[8] recently showed a 24% lower cardiovascular mortality risk in patients with cardiovascular disease risk factors who were more physically active than in their seSports Med 2010; 40 (11)

Exercise Training Modalities

dentary counterparts. Nonetheless, a more detailed prescription of training modalities is lacking in the current guidelines. More detailed information is necessary because a different selection of training modalities might be instrumental to further optimize clinical benefits of exercise intervention. In people with obesity, metabolic syndrome, T2DM and/or heart disease, healthcare professionals should aim to maximize clinical benefits of exercise intervention. It is important to reduce adipose tissue mass, improve glycaemic control and increase whole-body oxy. gen uptake capacity (VO2peak) as effectively as possible. For this purpose, the impact of different training modalities during long-term exercise intervention needs to be examined. Factors such as training intensity and frequency, session and programme duration, and the need to also implement resistance-type exercise are likely key factors that modulate clinical benefits of exercise intervention. Besides changes . in body composition, glycaemic control and VO2peak, exercise intervention has a profound impact on other parameters related to cardiovascular health. Exercise intervention improves blood rheology and endothelial function, lowers low-grade inflammation and oxidative stress, reduces coronary atherosclerosis and facilitates vascular remodelling, angiogenesis and arteriogenesis.[9-13] Though all of these changes are of great relevance for patients with obesity, metabolic syndrome, T2DM and/or heart disease, they will not be discussed in great detail in this review. Here, we present the current state of knowledge on the proposed effects of training modalities on changes in adipose tissue mass, metabolic syndrome, glycae. mic control and VO2peak in obese subjects, subjects with metabolic syndrome, patients with T2DM and/or heart disease. 2. Literature Search PubMed was used to search for manuscripts analysing the effects of exercise intervention in patients with obesity, metabolic syndrome, T2DM and/or heart disease (from 1970 to September 2010). Combinations of the following keywords were used: exercise intervention, exercise training, rehabilitation, obesity, fat mass, metabolic syndrome, ª 2010 Adis Data Information BV. All rights reserved.

923

diabetes, insulin sensitivity, heart disease, PCI, CABG, myocardial infarction, oxygen uptake, exercise capacity, fitness. From these abstracts, we included those studies that examined obese individuals (body mass index >30 kg/m2), metabolic syndrome and/or T2DM patients or patients with heart disease (coronary artery disease, myocardial infarction, coronary revascularisation) following long-term (>4 weeks) exercise intervention (endurance-type exercise intervention with or without additional resistance-type exercise). . Adipose tissue mass, glycaemic control and/or VO2peak had to be assessed directly at entry and completion of exercise intervention. In this review, we specifically focus on those studies examining the impact of different training modalities (exercise intensity, session duration and frequency, programme duration, addition of resistance-type exercise) on . adipose tissue mass, glycaemic control or VO2peak. Most patients with cardiometabolic disease do not achieve the criteria to determine maximum . exoxygen uptake (VO2max) during incremental . . On ercise testing, which limits the use of VO 2max . the other hand, VO2peak can always be properly determined in these patients. In order to avoid . . confusion by using VO2max and VO2peak interchangeably . in this manuscript, we have chosen to use only ‘VO2peak’. 3. General Clinical Benefits of Endurance-Type Exercise Training 3.1 Obesity

In obese individuals, adipose tissue mass loss can be effectively achieved by combining energy intake restriction with endurance-type exercise training. As a result of 16 weeks of combined endurance-type exercise training and energy intake restriction, an average weight loss of ~11 kg can be achieved in obese individuals.[14] Even without dietary restriction, endurance-type exercise effectively lowers bodyweight in obese subjects, although to a lesser extent (on average ~3 kg).[14] However, many studies report that inclusion of endurancetype exercise, in addition to energy intake restriction, does not further augment adipose tissue mass loss.[14] It seems that a compensatory reduction in Sports Med 2010; 40 (11)

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habitual physical activity due to energy intake restriction was not prevented by implementation of structured endurance-type exercise training.[15] This compensatory behaviour might have suppressed the clinical efficacy of exercise training, and should be monitored closely. Besides changes in habitual activity outside the exercise training facilities, certain baseline factors determine loss of adipose tissue mass as a result of endurancetype exercise intervention in obese subjects, and should be taken into account: lower baseline adipose tissue mass and female gender predict smaller effects.[16-18] When a reduction in adipose tissue mass is achieved as a result of endurancetype exercise training, this is accompanied by secondary positive effects. Combined endurance and resistance-type exercise interventions seem effective to reduce or even prevent the decline in skeletal muscle mass that is generally observed during energy intake restriction.[19] In addition, a relatively greater decline in visceral adipose tissue mass was observed in a combined energy intake restriction/endurance training programme.[20] These findings imply a preferential loss of central adiposity following a combined energy intake restriction and endurance-type exercise training intervention. This would represent a major health benefit, as there is a strong relationship between visceral obesity and cardiovascular disease risk or insulin resistance.[21,22] Most obesity patients have lowered insulin sensitivity or have already progressed to T2DM. In these patients, additional clinical benefits can be obtained by means of exercise training intervention. 3.2 Metabolic Syndrome

The metabolic syndrome is a cluster of cardiovascular disease risk factors, including dyslipidaemia, elevated blood pressure, impaired glycaemic control and/or abdominal obesity. The metabolic syndrome is often regarded as a precursor for T2DM. It might be questioned whether exercise intervention affects the components of metabolic syndrome: blood lipid profile, blood pressure, glycaemic control and bodyweight.[23-33] The effects of exercise intervention on blood lipid profile in metabolic syndrome patients reª 2010 Adis Data Information BV. All rights reserved.

main controversial. Yassine et al.[33] and Roussel et al.[32] report a significant reduction in plasma low-density lipoprotein and total cholesterol content, and an increase in plasma high-density lipoprotein content, as a result of exercise intervention. Conversely, many other studies have failed to reproduce significant changes in plasma lipid profile as a result of an exercise regimen in patients with metabolic syndrome.[24,25,27,28] Changes in the plasma lipid profile following exercise intervention could be camouflaged by prescribed medication[29] and/or different training modalities.[23] Establishing a reduction in blood pressure seems difficult by means of exercise intervention in patients with metabolic syndrome. Most, but not all,[23] studies report no change in this parameter as a result of exercise intervention.[25,27,29] On the other hand, glycaemic control seems to be positively affected by exercise intervention in these patients. Studies unequivocally indicate that exercise training improves insulin sensitivity[24,33] and/or reduces fasting plasma insulin levels.[25] In line with glycaemic control, bodyweight is also positively affected by exercise intervention. Many studies report a significant decrease in bodyweight, waist circumference and/or adipose tissue mass (assessed by an imaging technique or hydrostatic weighing) as a result of prolonged exercise intervention in patients with metabolic syndrome.[24-26,28,32,33] Moreover, a reduction in bodyweight correlates with improvements in insulin sensitivity[24] and postprandial insulin reswith metabolic syndrome. ponses[25] in patients . Even though VO2peak is not considered a component of the metabolic syndrome, . studies unequivocally report an increase in VO2peak following prolonged exercise training in patients with the metabolic syndrome.[23,25,27,29,31,33] In conclusion, exercise intervention represents an effective therapeutic strategy to improve glycaemic control, reduce bodyweight and increase physical fitness in subjects with the metabolic syndrome. 3.3 Type 2 Diabetes Mellitus

Exercise intervention is well capable of improving glycaemic control.[34-37] A recent meta-analysis Sports Med 2010; 40 (11)

Exercise Training Modalities

reported a decrease in blood glycosylated haemoglobin (HbA1c) content by 0.8% as a result of >12 weeks’ combined resistance and endurancetype exercise training in T2DM patients.[38] Considering the significant relationship between blood HbA1c content and risk of cardiovascular disease and premature death, such a decline in blood HbA1c content would translate into a substantial reduction in risk of micro- and macrovascular disease and premature death.[39,40] Besides lowering blood HbA1c content in T2DM patients, exercise training interventions improve exercise performance capacity.[41] Exercise training also decreases adipose tissue mass, improves blood plasma lipid profile and reduces mean arterial blood pressure.[42-44] Even enhanced pancreatic b-cell function has been observed as a result of exercise training in T2DM patients with moderate baseline insulin-secretory capacity.[45] Therefore, exercise training interventions should form a cornerstone in the care of T2DM patients. Various baseline parameters seem to affect the improvements in glycaemic control following exercise training. It seems that higher baseline blood HbA1c content and/or fasting glycaemia level, and female gender, are related to better outcome results.[42,46] Whether baseline adipose tissue mass affects the change in glycaemic control is currently under discussion.[46,47] When an improvement in glycaemic control is achieved as a result of exercise training in T2DM patients, it seems, for the greater part, attributable to a reduction in visceral adipose tissue mass.[48-52] Even though some studies show an improvement in skeletal muscle oxidative capacity and/or changes in muscle fibre type composition in T2DM patients, correlations between these changes and improvement in glycaemic control have not been established.[53-56] 3.4 Heart Disease

In many T2DM patients, evidence for coronary atherosclerosis and/or stenosis is present.[57] When such cardiovascular co-morbidity is present, implementation of exercise training intervention might be of even greater importance. In patients . with heart disease, it is important to increase VO2peak by exercise intervention, as this is significantly ª 2010 Adis Data Information BV. All rights reserved.

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related to a reduction in all-cause mortality risk.[58,59] A recent meta-analysis indicates significant survival benefits, and lowering of recurrent cardiovascular event incidence, when exercise training interventions are implemented in the care of . heart disease patients.[60] In addition, VO2peak reflects the clinical effectiveness of exercise intervention without influence of medication prescription (as opposed to glycaemic control, blood lipid profile and blood pressure). .In general, most studies report an increase in VO2peak ranging from 7% to 87% (mean 23 – 13%) following exercise training in heart disease patients.[61] However, some studies report no increase in exercise performance capacity as result of exercise training.[62] Certain factors, such as baseline exercise performance capacity and skeletal muscle metabolism, presence of hibernating myocardium and R-wave amplitude changes during incremental exercise, seem to affect training outcome.[63-66] Age, gender, ethnic origin and b-adrenoceptor antagonist (b-blocker) treatment do not seem to interfere with exercise training outcome.[67-69] When improvements in exercise performance capacity in heart disease patients are achieved, they are generally accompanied by increased mitochondrial volume density and oxidative capacity in leg muscle tissue, peripheral oxygen extraction, peripheral vasodilatory muscular capacity and cardiac output, and decreased restenosis incidence and left ventricular end-diastolic pressure.[64,70-75] Both cardiac as well as peripheral skeletal muscle adaptive responses seem associated with improvements in exercise performance capacity in heart disease patients following exercise intervention. 4. Impact of Training Modalities on Clinical Benefits of Exercise Intervention When implementing exercise training interventions in the care of patients with obesity, metabolic syndrome, T2DM and/or heart disease, the clinical effectiveness might be dependent on selection of training modalities (session and training programme duration, addition of resistance-type exercise, training intensity and session frequency). In sections 4.1–4.6, a detailed review of the impact Sports Med 2010; 40 (11)

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of different exercise training modalities on clinical benefits of exercise intervention is provided. 4.1 Programme Duration

According to current clinical guidelines, life-long participation in an exercise intervention programme is advised in patients with obesity, metabolic syndrome, T2DM and/or heart disease.[6,7] It is suggested to incorporate habitual physical activity/exercise training into the daily routine of patients once supervision from healthcare professionals is no longer present.[6,7] This suggestion is supported by many investigations (see table I). It seems that prolonged exercise training programmes result in a significantly greater reduction in adipose tissue mass in obesity patients, improvement in glycaemic . control in T2DM patients and increase in VO2peak in heart disease patients.[17,73,75-103] In the long term, these greater clinical benefits might result in lower risk for micro- and macrocardiovascular events, reduction in healthcare costs and greater life expectancy as well as improvements in quality of life.[33,58-60] It seems necessary to stimulate patients to continue to implement physical activity and/or exercise in their daily routine throughout their life. Exercise training programmes with limited duration, as is currently often the case because of financial/governmental restrictions, do not provide durable improvements in health or protection from development of chronic metabolic disease. Longer exercise programme duration is accompanied by greater clinical benefits, but when the intervention continues, further improvements in patients’ physical condition are generally not observed. For example, in heart disease patients, . VO2peak does not increase further after 38 weeks of exercise intervention.[103] It seems important to warn the patient that such stabilization (or even a small decline) of clinical benefits as a result of long-term exercise intervention is to be expected. At the same time, efforts should be made to encourage patients to adhere to the programme and to maintain motivation to continue exercising. In conclusion, prolongation of exercise interventions results in greater clinical benefits. Relaª 2010 Adis Data Information BV. All rights reserved.

tively smaller clinical benefits are expected after a certain timeframe. 4.2 Additional Resistance-Type Exercise

Clinical guidelines suggest adding resistancetype exercise to an endurance-type exercise regimen in patients with obesity, metabolic syndrome, T2DM and/or heart disease.[6,7] Whether addition of resistance-type exercise augments clinical benefits as a result of prolonged endurance-type exercise training depends on intervention targets (see table II). The effect of implementation of resistancetype exercise training within an endurance exercise training programme on adipose tissue mass loss has been intensively studied in the obese. Even though energy expenditure is increased as a consequence of additional use of resistancetype exercise training, this generally does not induce greater adipose tissue mass loss in obesity patients.[11,17,82,83,105,106] However, addition of resistance-type exercise to an endurance exercise training intervention programme does attenuate the loss of skeletal muscle tissue and, as such, prevents a decline in resting metabolic rate due to energy intake restriction.[83,116] This represents an important clinical benefit as it improves longterm weight maintenance. The implementation of additional resistancetype exercise within an endurance-type exercise training programme is accompanied by important clinical benefits for T2DM patients. Cuff et al.[50] compared the effects of 16 weeks of endurance versus combined endurance and resistancetype exercise training in T2DM patients. Insulin sensitivity improved with significantly greater magnitude in the combination-trained group, when compared with the endurance-trained group (as assessed by glucose infusion rate: 77% increase in combination-trained group, 20% increase in endurance-trained group). Sigal et al.[42] observed a 0.9% decline in blood HbA1c content following 22 weeks of combined endurance and resistancetype exercise training, when compared with a 0.4% decline following endurance-type exercise training. Some authors propose that an increase in skeletal muscle mass as a result of resistance-type Sports Med 2010; 40 (11)

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Table I. Impact of training programme duration on clinical benefits of exercise training Study

Age (years)

Wadden et al.[17]

43

Van Loan et al.[76]

No. of subjects

Subject characteristics

Effect parameter

Comparison

Effect

29

Obesity patients

Adipose tissue mass

8 vs 24 vs 48 weeks (repeated assessment)

Greater reduction with longer duration

25

5

Obesity patients

Bodyweight

5 vs 8 vs 11 vs 24 weeks (repeated assessment)

Greater reduction with longer duration

van Dale and Saris[77]

33

7

Obesity patients

Adipose tissue mass

5 vs 14 weeks (repeated assessment)

Greater reduction with longer duration

Kukkonen et al.[78]

41

95

Obesity patients

Bodyweight

8 vs 20 vs 44 vs 68 weeks (repeated assessment)

Greater reduction with longer duration

Jeffery et al.[79]

42

84

Obesity patients

Bodyweight

24 vs 52 vs 72 weeks (repeated assessment)

Greater reduction with longer duration

Hays et al.[80]

65

12

Obesity patients

Adipose tissue mass

7 vs 14 weeks (repeated assessment)

Greater reduction with longer duration

Fox et al.[81]

65

16

Obesity patients

Adipose tissue mass

12 vs 24 weeks (repeated assessment)

Greater reduction with longer duration

Donnelly et al.[82]

54

11

Obesity patients

Adipose tissue mass

36 vs 64 weeks (repeated assessment)

Greater reduction with longer duration

Sweeney et al.[83]

38

5

Obesity patients

Adipose tissue mass

12 vs 24 weeks (repeated assessment)

Greater reduction with longer duration

Perri et al.[84]

49

25

Obesity patients

Bodyweight

Frequently repeated assessment over 60 weeks

Greater reduction with longer duration

Pasman et al.[85]

36

12

Obesity patients

Adipose tissue mass

16 vs 40 vs 64 weeks (repeated assessment)

Greater reduction with longer duration

Hammer et al.[86]

32

14

Obesity patients

Adipose tissue mass

4 vs 8 vs 12 weeks (repeated assessment)

Greater reduction with longer duration

Ozcelik et al.[87]

39

12

Obesity patients

Adipose tissue mass

4 vs 8 weeks (repeated assessment)

Greater reduction with longer duration

Lehmann et al.[88]

54

16

T2DM patients

HbA1c

12 vs 24 weeks (repeated assessment)

No effect found

Saltin et al.[89]

48

25

T2DM patients

AUC during OGTT

12 vs 24 weeks (repeated assessment)

No further reduction after 12 weeks of intervention

Bourn et al.[90]

NA

20

T2DM patients

HbA1c

Repeated assessment during 104 weeks

Ceased to decrease after 84 weeks of intervention

Uusitupa[91]

NA

18

T2DM patients

HbA1c

12 vs 60 weeks (repeated assessment)

Reduced more with longer duration

Tokmakidis et al.[92]

55

9

T2DM patients

4 vs 16 weeks (repeated assessment)

Reduced more with longer duration

Brubaker et al.[93]

54 vs 62

Heterogeneous

AUC during OGTT . VO2peak

12 vs 52 weeks

Greater improvement with longer duration

Dubach et al.[94]

56

12

CHF

. VO2peak

4 vs 8 weeks (repeated assessment)

Greater improvement with longer duration

Demopoulos et al.[73]

61

16

CHF

. VO2peak

6 vs 12 weeks (repeated assessment)

Greater improvement with longer duration

25 vs 25

Continued next page

ª 2010 Adis Data Information BV. All rights reserved.

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Table I. Contd Study

Age (years)

Lan et al.[75]

52

DeBusk et al.[95]

NA

Belardinelli et al.[96]

56

Foster et al.[97]

No. of subjects

PCI

Effect parameter . VO2peak

AMI

METmax

50

CHF

. VO2peak

56

19

CABG

METmax

Kiilavuori et al.[98]

52

12

CHF

. VO2peak

Keteyian et al.[99]

52

15

CHF

. VO2peak

Ades et al.[100]

NA

11

Heterogeneous

. VO2peak

Dugmore et al.[101]

NA

62

AMI

. VO2peak

Kavanagh et al.[102]

62

21

CHF

. VO2peak

Hamm et al.[103]

60

623

Heterogeneous

. VO2peak

9

30 vs 31

Subject characteristics

Comparison

Effect

6 vs 12 weeks (repeated assessment)

Greater improvement with longer duration

8 vs 23 weeks

Greater improvement with longer duration

8 vs 56 weeks (repeated assessment)

Greater improvement with longer duration

2 vs 8 vs 24 weeks (repeated assessment)

Greater improvement with longer duration

12 vs 24 weeks (repeated assessment)

No further increase after 12 weeks of intervention

12 vs 24 weeks (repeated assessment)

Greater improvement with longer duration

12 vs 52 weeks (repeated assessment)

Greater improvement with longer duration

16 vs 32 vs 52 weeks (repeated assessment)

Greater improvement with longer duration

Frequently repeated assessment during 52 weeks

No further increase after 16 weeks of intervention

Repeated monthly assessment during 52 weeks

No further increase after 38 weeks of intervention

AMI = acute myocardial infarction; AUC = area under the concentration-time curve; CABG = coronary artery bypass graft surgery; NA = not available; OGTT = oral CHF = congestive heart failure; HbA1c = glycosylated haemoglobin; METmax = maximal metabolic equivalent; . glucose tolerance test; PCI = percutaneous coronary intervention; T2DM = type 2 diabetes mellitus; VO2peak = whole-body oxygen uptake capacity.

exercise, leading to an increase in blood glucose disposal capacity, might be responsible for greater improvements following combined resistanceand endurance-type exercise training in T2DM patients.[117,118] Furthermore, it should be noted that greater muscle strength and increased functional performance capacity increases the capacity to lead a more active, healthy lifestyle. In patients with heart disease, the effect of additional resistance-type exercise on an increase . in VO2peak within an endurance-type training programme is presently under intense debate. Studies . have reported a greater increase in VO2peak as a result of the addition of resistance-type exercise.[107-111] However, other studies indicate that ª 2010 Adis Data Information BV. All rights reserved.

the addition of resistance-type exercise . does not result in greater improvements in VO2peak in heart disease patients.[112-115] An explanation for the contradiction in results between studies remains to be provided. The effects of additional . resistance-type exercise on improvement in VO2peak in heart disease patients might be dependent on patient population (magnitude of skeletal muscle atrophy, baseline exercise performance capacity and/or hospitalization period), resistance-type exercise modalities and/or presence of cardiovascular co-morbidities. In conclusion, addition of resistance-type exercise to endurance-type exercise does not augment adipose tissue mass loss in obesity patients. Sports Med 2010; 40 (11)

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929

In T2DM patients, such addition results in a greater improvement in glycaemic control. The additional . benefit of resistance-type exercise training on VO2peak in heart disease patients remains unclear. 4.3 Continuous Exercise Training Intensity

Clinical guidelines suggest selecting continuous . exercise intensities between 40% and 85% VO2peak during training interventions in patients with obesity, metabolic syndrome, T2DM and/or heart

disease.[6,7] Because of the large range between lower and upper limits of intensity, it remains speculative at what intensity these patients should exercise (see table III). Historically, in obese individuals, low-intensity endurance-type exercise has been prescribed to maximize skeletal muscle fat oxidation[126] and, as such, to maximize adipose tissue mass loss. As a consequence, many studies have aimed to assess the impact of exercise training intensity on adipose tissue mass loss in obese patients. These studies

Table II. Impact of the addition of resistance-type exercises on clinical benefits of endurance-type exercise training Study

Age (years)

No. of subjects

Subject characteristics

Effect parameter

Comparison

Effect

Ashutosh et al.[104]

41 vs 45

8 vs 9

Obesity patients

Adipose tissue mass

Endurance vs endurance + strength

Equal reduction

Donnelly et al.[82]

NA

16 vs 9

Obesity patients

Adipose tissue mass

Endurance vs endurance + strength

Equal reduction

Donnelly et al.[105]

NA

18 vs 21

Obesity patients

Adipose tissue mass

Endurance vs endurance + strength

Equal reduction

Marks et al.[106]

39 vs 40

10 vs 10

Obesity patients

Adipose tissue mass

Endurance vs endurance + strength

Equal reduction

Sweeney et al.[83]

32 vs 29

5 vs 6

Obesity patients

Adipose tissue mass

Endurance vs endurance + strength

Equal reduction at 6 months of intervention

Wadden et al.[17]

41 vs 43

31 vs 29

Obesity patients

Adipose tissue mass

Endurance vs endurance + strength

Equal reduction

Cuff et al.[50]

63 vs 59

10 vs 9

T2DM patients

Glucose infusion rate

Endurance vs endurance + strength

Greater increase of glucose infusion rate

Sigal et al.[42]

53 vs 54

64 vs 60

T2DM patients

HbA1c

Endurance vs endurance + strength

Greater reduction of HbA1c

Stewart et al.[107]

52 vs 57

12 vs 11

AMI

. VO2peak

Endurance vs endurance + strength

Greater increase when resistance exercises added

Delagardelle et al.[108]

60 vs 54

10 vs 10

CHF

. VO2peak

Endurance vs endurance + strength

Greater increase when resistance exercises added

Gayda et al.[109]

NA

8 vs 8

Heterogeneous

. VO2peak

Endurance vs endurance + strength

Greater increase when resistance exercises added

Marzolini et al.[110]

58 vs 61 vs 63

16 vs 19 vs 18

Heterogeneous

. VO2peak

Endurance vs endurance + strength

Greater increase when resistance exercises added

Pierson et al.[111]

61 vs 59

10 vs 10

Heterogeneous

. VO2peak

Endurance vs endurance + strength

Greater increase when resistance exercises added

Daub et al.[112]

49 vs 47 vs 51

14 vs 13 vs 15

AMI

. VO2peak

Endurance vs endurance + strength

Equal increase

Santa-Clara et al.[113]

55 vs 57

13 vs 13

Heterogeneous

. VO2peak

Endurance vs endurance + strength

Equal increase

Arthur et al.[114]

NA

46 vs 46

Heterogeneous

. VO2peak

Endurance vs endurance + strength

Equal increase

Beckers et al.[115]

58 vs 59

28 vs 30

CHF

. VO2peak

Endurance vs endurance + strength

Equal increase

AMI = acute myocardial infarction; CHF = congestive heart failure; HbA1c = glycosylated haemoglobin; NA = not available; T2DM = type 2 . diabetes mellitus; VO2peak = whole-body oxygen uptake capacity.

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Table III. Impact of continuous exercise intensity on clinical benefits of exercise training Study

Age (years)

No. of subjects

Subject characteristics

Effect parameter

Comparison

Effect

Ballor et al.[119]

NA

14 vs 13

Obesity patients

Adipose tissue mass

40–50% vs . 80–90% VO2peak

Equal reduction

Leutholtz et al.[120]

43 vs 40

20 vs 20

Obesity patients

Adipose tissue mass

40% vs 60% HRR

Equal reduction

van Aggel-Leijssen et al.[121]

43 vs 40

12 vs 12

Obesity patients

Adipose tissue mass

40% vs 70% . VO2peak

Equal reduction

Irving et al.[31]

51

15 vs 12

Metabolic syndrome patients

Adipose tissue mass

LT

Greater reduction in HI

Hansen et al.[122]

58 vs 59

25 vs 25

T2DM patients

Blood HbA1c content

50% vs 75% . VO2peak

Equal reduction

Johnson et al.[26]

54 vs 53

41 vs 45

Metabolic syndrome patients

Insulin sensitivity

40–55% vs . 65–80% VO2peak

Improved in LI, but not in HI

Blumenthal et al.[123]

51 vs 52

23 vs 23

AMI

. VO2peak

Equal improvement

Jensen et al.[124]/ Oberman et al.[125]

55 vs 53

83 vs 103

Heterogeneous

. VO2peak

<45% vs 65–75% . VO2peak

Greater improvement in HI

Adachi et al.[62]

62 vs 51

11 vs 10

CABG

. VO2peak

50% vs 50–85% . VO2peak 80% vs 120% VT

Greater improvement in HI

AMI = acute myocardial infarction; CABG = coronary artery bypass graft surgery; HbA1c = glycosylated haemoglobin; HI = high-intensity intervention; . HRR = heart rate reserve; LI = low-intensity intervention; LT = lactate threshold; NA = not available; T2DM = type 2 diabetes mellitus; VO2peak = whole-body oxygen uptake capacity; VT = ventilatory threshold.

unequivocally report no difference in adipose tissue mass loss when comparing continuous lowversus high-intensity exercise training programmes (with matched energy expenditure between trials).[119-121] These data suggest that exercise volume as opposed to training intensity forms the main factor that determines adipose tissue mass loss during exercise intervention in obese subjects. However, compliance to an exercise intervention regimen has been reported to be associated with the impact of the training workload.[127] Because compliance to a continuous high-intensity exercise training programme is generally lower than lower-intensity exercise intervention regimens,[127] selecting higher intensities during early stages of such interventions is not advised. In patients with metabolic syndrome, on the other hand, a significantly different change in adipose tissue was found between exercise regimens applying different exercise intensities.[31] After 16 weeks of intervention, Irving et al.[31] reported a significant loss in adipose tissue mass, abdominal adipose tissue area, as well as subcutaneous adipose tissue area as a result of continuous high-intensity exª 2010 Adis Data Information BV. All rights reserved.

ercise training, but not as a result of continuous low-intensity exercise training. So far, there is no apparent explanation for the discrepancy between studies.[31,119-121] Exercise intensity has been suggested to represent one of the more important exercise modalities that determine the clinical outcome of an exercise intervention in T2DM patients.[27,122] This has been attributed to the inverse relationship between exercise intensity and muscle glycogen use.[128,129] The magnitude of increase in insulin sensitivity following an acute bout of endurance-type exercise has been associated with the extent of muscle glycogen depletion and subsequent glycogen repletion rate.[130] However, recent studies indicate that different continuous exercise intensities do not modulate improvements in glycaemic control during long-term exercise interventions in T2DM patients.[122] We have compared the clinical benefits . of 6 months of continuous low-intensity (50% VO 2peak) versus high. intensity (75% VO2peak) exercise training in T2DM patients.[122] Blood HbA1c content decreased to a similar extent as a result of exercise regimens with Sports Med 2010; 40 (11)

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931

. different intensities. Moreover, VO2peak, skeletal muscle oxidative capacity and fat-free mass increased in both low- and high-intensity exercise regimens, with no difference between programmes. As mentioned previously, higher exercise intensities are generally associated with a greater dropout rate during long-term training regimens in previously sedentary individuals.[127] It might therefore be suggested to encourage lower exercise intensities during the early stages of implementing an exercise training regimen in T2DM patients. The latter suggestion seems also applicable to patients with the metabolic syndrome. Johnson et al.[26] compared the effects of 6 months of . exercise training at 40–55% versus 65–80% of VO2peak on insulin sensitivity. Their results showed significant improvements in insulin sensitivity following low-intensity as opposed to high-intensity exercise training.[26] Therefore, when exercise bouts are prolonged, low-intensity exercise intervention is at least as effective as high-intensity exercise intervention to improve glycaemic control in subjects with the metabolic syndrome. In patients with heart disease, the proper selection of training intensity is currently a matter of intense debate. Several studies have investigated effects . of continuous training intensities on change in VO2peak during exercise intervention in heart disease patients. Data from these investigations were equivocal: continuous high-intensity

exercise training was found . to be of greater or equal impact on change in VO2peak compared with continuous low-intensity exercise training.[62,123-125] A systematic review indicated no threshold effect . of training intensity on change in VO2peak in a cohort of cardiac patients.[131] Large-cohort randomized trials are required to assess the impact of .continuous exercise intensities on increase in VO2peak in heart disease patients. In conclusion, exercise intensity does not modulate adipose tissue mass loss in obese patients, and/or effect a change in glycaemic control in T2DM patients during continuous endurancetype exercise training. In patients with metabolic syndrome, higher exercise intensities seem to be accompanied by greater reductions in adipose tissue mass but lower improvements in insulin sensitivity. Studies are required to assess the impact of continuous exercise intensity during longterm endurance-type exercise interventions on . change in VO2peak in heart disease patients. 4.4 High-Intensity Interval Exercise Training

In recent studies, effects of high-intensity interval training have been assessed in obesity, metabolic syndrome and heart disease patients (see table IV). This training methodology is different from more continuous exercise training.[137] Interval training is characterized by sessions consisting

Table IV. Impact of high-intensity interval exercise training on clinical benefitsa Study

Age (years)

No. of subjects

Subject characteristics

Effect parameter

Comparison

Effect

Schjerve et al.[132]

44 vs 47

13 vs 14

Obesity patients

Adipose tissue mass

60–70% HRmax vs interval

Equal reduction

Tjønna et al.[23]

52 vs 55

8 vs 11

Metabolic syndrome patients

70% HRmax vs interval

Greater improvement in interval training

Warburton et al.[133]

55 vs 57

7 vs 7

CABG and PCI

Insulin sensitivity . VO2peak

Equal improvement

Rognmo et al.[134] and Amundsen et al.[135]

63 vs 61

9 vs 8

Cardiac patients

. VO2peak

65% HRR vs interval . 50–60% VO2peak vs interval

Moholdt et al.[136]

60 vs 62

28 vs 31

CABG

. VO2peak

70% HRmax vs interval

Equal improvement at 4 weeks

Wisloff et al.[138]

74 vs 76

9 vs 9

CHF

. VO2peak

70–75% HRmax vs interval

Greater improvement in interval training

a

Greater improvement in interval training

No studies executed in T2DM patients.

CABG = coronary artery bypass graft surgery; CHF = congestive heart failure; HRmax = maximal heart rate; HRR = heart rate reserve; . PCI = percutaneous coronary intervention; T2DM = type 2 diabetes mellitus; VO2peak = whole-body oxygen uptake capacity.

ª 2010 Adis Data Information BV. All rights reserved.

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of successive bouts of short duration (1–4 minutes) at . a relatively high-intensity workload (80–100% VO2peak), alternated with small . periods of active rest (1–4 minutes at 50–60% VO2peak). Schjerve et al.[132] compared the effects of highintensity interval training versus a more moderateintensity exercise regimen (matched for energy expenditure) in a cohort of obese adults. After 12 weeks of intervention, total-body adipose tissue mass had declined to a similar extent (by 2.2% vs 2.5%, respectively). Therefore, it is not necessary to apply repeated bouts of greater exercise intensities to modify adipose tissue mass in obesity patients. This is important because this type of exercise regimen could be seen as more difficult by these patients, and could thus lower exercise motivation. Therefore, high-intensity exercise bouts (85–95% maximal heart rate) do not seem to be required to increase the loss in adipose tissue mass in obesity patients. The effect of high-intensity interval exercise training on glycaemic control in T2DM patients is unknown. Tjønna and colleagues[23] evaluated the effect of high-intensity interval versus continuous moderate-intensity endurance-type exercise training on insulin sensitivity in patients with metabolic syndrome. After 16 weeks of intervention, insulin sensitivity increased significantly as a result of high-intensity interval training, but not as a result of the continuous moderate-intensity endurance-type exercise training programme.[23] Consequently, this study indicates that intervaltype exercise training might be of greater benefit to improve glycaemic control than more routinely used endurance-type exercise training. The interval-type exercise training methodology is believed to induce more rapid physiological adaptations in skeletal muscle tissue than more continuous high-intensity endurance-type exercise training.[137] Most, but not all, data indeed seem to indicate that high-intensity interval exercise training is more effective in increas. ing VO2peak than continuous low-intensity exercise training in heart disease patients.[133-135,138] . Moholdt et al.[136] found similar increases in VO2peak when comparing four weeks of supervised highintensity interval vs continuous moderate-intensity exercise training in coronary artery bypass surª 2010 Adis Data Information BV. All rights reserved.

Hansen et al.

. gery patients. However, greater gains in VO2peak were observed as result of subsequent 6 months of home-based (unsupervised) high-intensity interval vs continuous moderate-intensity exercise training. Such an effect might be of important long-term clinical benefit. Nonetheless, these studies are generally limited by small sample sizes, and the effect of high-intensity interval exercise training on intervention adherence remains to be examined. In conclusion, the first line of evidence indicates that high-intensity interval exercise training . might be more effective in increasing VO2peak in heart disease patients than exercise regimens of continuous exercise intensities. Reduction in adipose tissue mass does not seem to be affected by the application of high-intensity interval exercise regimens in obesity patients. The effect of highintensity interval exercise training on glycaemic control in T2DM patients remains unknown, even though studies in patients with the metabolic syndrome seem to suggest that greater improvements in insulin sensitivity are to be expected as result of high-intensity interval training. 4.5 Training Session Volume/Duration

Clinical guidelines suggest that patients with T2DM, metabolic syndrome and/or heart disease should exercise for at least 40 minutes per session, and increase session time up to 60 minutes during the course of long-term training interventions.[6,7] In cases of obesity, even longer training sessions are advised.[6,7] Although clinical guidelines are often used as a reference to design exercise interventions, there seems to be great lack of data on impact of training session volume/duration (see table V). In obese individuals, effects of training session volume/duration on adipose tissue mass loss are rarely studied. Prolonged exercise is associated with an increase in adipose tissue lipolysis and availability of plasma free fatty acids for oxidation. However, it remains to be examined whether such exercise prolongation would result in greater adipose tissue mass loss in obesity patients. In a study by Bond Brill et al.,[139] the dose-dependent effect of walking (30- vs 60-minute sessions) on Sports Med 2010; 40 (11)

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Table V. Impact of training session volume/duration on clinical benefits of exercise traininga Study

Age (years)

No. of subjects

Subject characteristics

Effect parameter

Comparison

Effect

Bond Brill et al.[139]

39 vs 40

21 vs 19

Obesity patients

Adipose tissue mass

30 vs 60 minute/ session

Equal reduction

Johnson et al.[26]

53 vs 51

45 vs 44

Metabolic syndrome patients

114 vs 175 minute/ week

Equal improvement

Hansen et al.[140]

63 vs 63

67 vs 67

CAD patients

Insulin sensitivity . VO2peak

40 vs 60 minute/ session

Equal improvement

a

No studies executed in T2DM patients. . CAD = coronary artery disease; HRmax = maximal heart rate; T2DM = type 2 diabetes mellitus; VO2peak = whole-body oxygen uptake capacity.

body composition was analysed during energy intake restriction intervention. After 12 weeks of exercise training, no difference in adipose tissue mass loss was observed between groups. The authors speculated that energy intake restriction intervention is of much greater impact on adipose tissue mass loss than different exercise volume. Additional study seems required to assess the effect of training session volume/duration on decrease in adipose tissue mass in obesity patients. In T2DM patients, no single study has examined the effect of training session volume/duration on the change in glycaemic control during exercise intervention. From the few data that are currently available, it seems that when applying greater exercise bout volumes in T2DM patients, shortterm glycaemic control improves with greater magnitude. Sriwijitkamol et al.[141] found a greater decrease in plasma glucose levels in T2DM . patients when cycling for 40 minutes at 70% VO 2max . compared with 40 minutes at 50% VO2peak. These changes were accompanied by greater skeletal muscle glycogen depletion and peroxisome proliferatoractivated receptor g coactivator 1-a (PGC-1a) expression in cases of greater exercise bout volume. However, because a change in glycaemic control during the first 24 hours following exercise is of greater clinical relevance, the impact of training session volume with 24-hour continuous glucose monitoring needs to be assessed.[142] Whether a greater exercise bout volume will contribute to greater improvement in glycaemic control during long-term intervention remains presently unknown in T2DM patients. For example, during a 6-month exercise intervention in patients with metabolic syndrome, a greater exercise volª 2010 Adis Data Information BV. All rights reserved.

ume (175 minutes of exercise/week) did not seem to contribute to greater improvements in insulin sensitivity when compared with a lower exercise volume (114 minutes of exercise/week).[26] In heart disease patients, the impact of exercise session volume/duration has been investigated by our laboratory.[140] We compared effects of 40- vs 60-minute exercise bouts during a 7-week exercise intervention in coronary artery disease patients. Even though different exercise volumes were ap. plied, VO2peak increased with a similar magnitude. As a result, the time investment in exercise bouts can be reduced . significantly without affecting the change in VO2peak. This might contribute to greater working efficiency of cardiac rehabilitation centres. In conclusion, the effects of training session volume/duration on clinical benefits of long-term exercise intervention remain presently uncertain in patients with obesity or T2DM. In patients with heart disease, exercise session volume does . not affect change in VO2peak. 4.6 Training Frequency

Obesity, metabolic syndrome, T2DM and/or heart disease patients are advised to exercise at least 3, and preferably 5, days a week.[6,7] These exercise bouts should best be distributed equally over the week. Only a few studies assessed the influence of training frequency on clinical benefits as a result of long-term exercise intervention in obesity and heart disease patients (see table VI). Whatley et al.[143] compared the effects of two exercise frequencies (3 vs 5 days a week) during a Sports Med 2010; 40 (11)

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Table VI. Impact of training frequency on clinical benefits of exercise traininga Study

Age (years)

No. of subjects

Subject characteristics

Effect parameter

Comparison

Effect

Whatley et al.[143]

39 vs 36

8 vs 8

Obesity patients

Bodyweight

3 vs 5 sessions/week

Greater reduction with higher frequency

Dressendorfer et al.[144]

54 vs 55 vs 56

13 vs 13 vs 12

AMI

. VO2peak

1 vs 2 vs 3 sessions/week

Greater increase with higher frequency

Tygesen et al.[145]

56 vs 57

33 vs 29

AMI and CABG

Wmax

2 vs 6 sessions/week

Greater increase with higher frequency

Nieuwland et al.[146]

52 vs 53

63 vs 67

Heterogeneous

. VO2peak

2 vs 10 sessions/week

Equal increase

a

No studies executed in T2DM patients. . AMI = acute myocardial infarction; CABG = coronary artery bypass graft surgery; T2DM = type 2 diabetes mellitus; VO2peak = maximal wholebody oxygen uptake capacity; Wmax = maximal cycling power output.

12-week intervention programme in obese females, during which energy intake was restricted. In this study, the high-frequency training group lost considerably more adipose tissue mass than the low-frequency training group (16 – 4 vs 13 – 4 kg). A significant correlation between adipose tissue mass loss and total work duration was reported.[143] A greater exercise frequency seems associated with a greater adipose tissue mass loss in obese individuals. Nonetheless, further study is warranted to verify these findings. In heart disease .patients, similar effects were found for change in VO2peak. Dressendorfer et al.[144] reported a significantly greater improvement in . VO2peak when increasing training frequency (one vs two vs three sessions a week) in a cohort of acute myocardial infarction patients. A greater improvement in maximal cycling power output was reported by Tygesen et al.[145] when heart disease patients exercised for six sessions a week, compared with two sessions a week. No such effect was found in a study by Nieuwland et al.,[146] where effects. of two versus six sessions a week on increase in VO2peak . were compared. It might be speculated that VO2peak increases by a greater magnitude when increasing exercise frequency up to 2. days/week, while no further improvements in VO2peak are expected with exercise frequencies >2 days/week. Data seem to indicate that T2DM patients should exercise on a regular basis to improve glycaemic control. This suggestion results from the finding that increased insulin sensitivity as a result ª 2010 Adis Data Information BV. All rights reserved.

of an exercise bout disappears within approximately 48 hours in T2DM patients.[147] It seems essential for T2DM patients to exercise at least three times a week (with one recovery day in between) to maintain increased insulin sensitivity throughout the week. However, studies directly comparing effects of a low- or high-frequency exercise training intervention on glycaemic control in T2DM patients are not present. It remains to be investigated whether training frequency affects the change in glycaemic control in this subset of patients. In conclusion, greater exercise frequency during long-term exercise intervention seems associated with greater . adipose tissue mass loss and improvement in VO2peak in obesity and heart disease patients, respectively. The effect of this training modality on changes in glycaemic control remains to be examined in T2DM patients. 5. General Conclusions Exercise training interventions represent an effective means to reduce adipose tissue. mass, improve glycaemic control and increase VO2peak in obesity, T2DM and heart disease patients, respectively. By changing training modalities, significantly greater clinical benefits can be obtained. Greater training frequency and longer programme duration is associated with a greater reduction in adipose tissue mass in obesity patients. A greater training frequency (up to 2 days/week) and a longer programme duration (up to 38 weeks) seems to be Sports Med 2010; 40 (11)

Exercise Training Modalities

. associated with greater improvements in VO2peak in heart disease patients. Longer programme duration and the addition of resistance-type exercises further improves glycaemic control in T2DM patients. The first line of evidence suggests that high-intensity interval exercise training has a . greater impact on VO2peak in heart disease patients and insulin sensitivity in patients with metabolic syndrome. The latter does not seem to be the case when looking at changes in adipose tissue mass following exercise interventions in obese subjects. Healthcare professionals have the opportunity to improve the clinical efficacy of exercise training intervention by implementing such programme modifications. Intense debate continues as to whether changes in certain training modalities can alter the clinical outcome during long-term exercise intervention in these patients. It remains speculative whether the addition of resistance-type exercise and higher continuous endurance-type exercise training at certain workload intensities .are accompanied by greater improvements in VO2peak in heart disease patients. The effect of training session duration/volume on adipose tissue mass in obesity patients, and glycaemic control in T2DM patients, is currently unknown. The impact of training frequency remains to be investigated in T2DM patients. Acknowledgements This review was supported by an unrestricted grant from the clinical research foundation Hartcentrum Hasselt. There has been no previous presentation and the authors have no conflicts of interest that are directly relevant to the contents of this review.

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97. Foster C, Pollock ML, Anholm JD, et al. Work capacity and left ventricular function during rehabilitation after myocardial revascularization surgery. Circulation 1984 Apr; 69 (4): 748-55 98. Kiilavuori K, Sovijarvi A, Naveri H, et al. Effect of physical training on exercise capacity and gas exchange in patients with chronic heart failure. Chest 1996 Oct; 110 (4): 985-91 99. Keteyian SJ, Levine AB, Brawner CA, et al. Exercise training in patients with heart failure: a randomised controlled trial. Ann Intern Med 1996 Jun; 124 (12): 1051-7 100. Ades PA, Waldmann ML, Poehlman ET, et al. Exercise conditioning in older coronary patients: submaximal lactate response and endurance capacity. Circulation 1993 Aug; 88 (2): 572-7 101. Dugmore LD, Tipson RJ, Philips MH, et al. Changes in cardiorespiratory fitness, psychological wellbeing, quality of life, and vocational status following a 12 month cardiac exercise rehabilitation programme. Heart 1999 Apr; 81 (4): 359-66 102. Kavanagh T, Myers MG, Baigrie RS, et al. Quality of life and cardiorespiratory function in chronic heart failure: effects of 12 months’ aerobic training. Heart 1996 Jul; 76 (1): 42-9 103. Hamm LF, Kavanagh T, Campbell RB. Timeline for peak improvements during 52 weeks of outpatient cardiac rehabilitation. J Cardiopulm Rehabil 2004 Nov-Dec; 24 (4): 374-82 104. Ashutosh K, Methrotra K, Fragale-Jackson J. Effects of sustained weight loss and exercise on aerobic fitness in obese women. J Sports Med Phys Fitness 1997 Dec; 37 (4): 252-7 105. Donnelly JE, Jacobsen DJ, Jakicic JM, et al. Very low calorie diet with concurrent versus delayed and sequential exercise. Int J Obes 1994 Jul; 18 (7): 469-75 106. Marks BL, Ward A, Morris DH, et al. Fat-free mass is maintained in women following a moderate diet and exercise program. Med Sci Sports Exerc 1995 Sep; 27 (9): 1243-51 107. Stewart KJ, McFarland LD, Weinhofer JJ, et al. Safety and efficacy of weight training soon after acute myocardial infarction. J Cardiopulm Rehabil 1998 Jan-Feb; 18 (1): 37-44 108. Delagardelle C, Feiereisen P, Autier P, et al. Strength/ endurance training versus endurance training in congestive heart failure. Med Sci Sports Exerc 2002 Dec; 34 (12): 1868-72 109. Gayda M, Choquet D, Ahmaida S. Effects of exercise training modality on skeletal muscle fatigue in men with coronary heart disease. J Electromyogr Kinesiol 2009 Apr; 19 (2): e32-9 110. Marzolini S, Oh PI, Thomas SG, et al. Aerobic and resistance training in coronary disease: single versus multiple sets. Med Sci Sports Exerc 2008 Sep; 40 (9): 1557-64 111. Pierson LM, Herbert WG, Norton HJ, et al. Effects of combined aerobic and resistance training versus aerobic training alone in cardiac rehabilitation. J Cardiopulm Rehabil 2001 Mar-Apr; 21 (2): 101-10

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Exercise Training Modalities

112. Daub WD, Knapik GP, Black WR. Strength training early after myocardial infarction. J Cardiopulm Rehabil 1996 Mar-Apr; 16 (2): 100-8 113. Santa-Clara H, Fernhall B, Mendes M, et al. Effect of a 1 year combined aerobic- and weight-training exercise programme on aerobic capacity and ventilatory threshold in patients suffering from coronary artery disease. Eur J Appl Physiol 2002 Oct; 87 (6): 568-75 114. Arthur HM, Gunn E, Thorpe KE, et al. Effect of aerobic vs combined aerobic-strength training on 1-year, post-cardiac rehabilitation outcomes in women after a cardiac event. J Rehabil Med 2007 Nov; 39 (9): 730-5 115. Beckers PJ, Denollet J, Possemiers NM, et al. Combined endurance-resistance training vs. endurance training in patients with chronic heart failure: a prospective randomized study. Eur Heart J 2008 Aug; 29 (15): 1858-66 116. Bryner RW, Ullrich IH, Sauers J, et al. Effects of resistance vs. aerobic training combined with an 800 calorie liquid diet on lean body mass and resting metabolic rate. J Am Coll Clin Nutr 1999 Apr; 18 (2): 115-21 117. Dunstan DW, Daly RM, Owen N, et al. High-intensity resistance training improves glycemic control in older patients with type 2 diabetes. Diabetes Care 2002 Oct; 25 (10): 1729-36 118. Eriksson J, Taimela S, Eriksson K, et al. Resistance training in the treatment of non-insulin-dependent diabetes. Int J Sports Med 1997 May; 18 (4): 242-6 119. Ballor DL, McCarthy JP, Wilterdink EJ. Exercise intensity does not affect the composition of diet- and exercise-induced body mass loss. Am J Clin Nutr 1990 Feb; 51 (2): 142-6 120. Leutholtz BC, Keyser RE, Heusner WW, et al. Exercise training and severe caloric restriction: effect on lean body mass in the obese. Arch Phys Med Rehabil 1995 Jan; 76 (1): 65-70 121. van Aggel-Leijssen D, Saris WHM, Wagenmakers AJM, et al. Effect of exercise training at different intensities on fat metabolism of obese men. J Appl Physiol 2002 Mar; 92 (3): 1300-9 122. Hansen D, Dendale P, Jonkers RA, et al. Continuous low-tomoderate intensity exercise is equally effective as moderateto-high intensity exercise training at lowering blood HbA1c content in obese type 2 diabetes patients. Diabetologia 2009 Sep; 52 (9): 1789-97 123. Blumenthal JA, Rejeski WJ, Walsh-Riddle M, et al. Comparison of high- and low-intensity exercise training early after acute myocardial infarction. Am J Cardiol 1988 Jan; 61 (1): 26-30 124. Jensen BE, Fletcher BJ, Rupp JC, et al. Training level comparison study: effect of high and low intensity training on ventilatory threshold in men with coronary artery disease. J Cardiopulm Rehabil 1996 Jul-Aug; 16 (4): 227-32 125. Oberman A, Fletcher GF, Lee J, et al. Efficacy of highintensity exercise training on left ventricular ejection fraction in men with coronary artery disease (the training level comparison study). Am J Cardiol 1995 Oct; 76 (10): 643-7 126. Friedlander AL, Jacobs KA, Fattor JA, et al. Contributions of working muscle to whole body lipid metabolism are altered by exercise training and intensity. Am J Physiol 2007 Oct; 292 (4): E107-12 127. Perri MG, Anton SD, Durning PE, et al. Adherence to exercise prescriptions: effects of prescribing moderate

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143. Whatley JE, Gillespie WJ, Honig J, et al. Does the amount of endurance exercise in combination with weight training and a very-low-energy diet affect resting metabolic rate and body composition? Am J Clin Nutr 1994 May; 59 (5): 1088-92 144. Dressendorfer RH, Franklin BA, Cameron JL, et al. Exercise training frequency in early post-infarction cardiac rehabilitation: influence on aerobic conditioning. J Cardiopulm Rehabil 1995 Jul-Aug; 15 (4): 269-76 145. Tygesen H, Wettervik C, Wennerblom B. Intensive homebased exercise training in cardiac rehabilitation increases exercise capacity and heart rate variability. Int J Cardiol 2001 Jul; 79 (2-3): 175-82 146. Nieuwland W, Berkhuysen MA, van Veldhuizen DJ, et al. Differential effects of high-frequency versus low-frequency

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exercise training in rehabilitation of patients with coronary artery disease. J Am Coll Cardiol 2000 Jul; 36 (1): 202-7 147. Henriksen EJ. Exercise effects of muscle insulin signalling and action: effects of acute exercise and exercise training on insulin resistance. J Appl Physiol 2002 Aug; 93 (2): 788-96

Correspondence: Prof. Dr Romain Meeusen, Vrije Universiteit Brussel (VUB), Faculty LK, Department of Human Physiology and Sportsmedicine, Pleinlaan 2, 1050 Brussels, Belgium. E-mail: [email protected]

Sports Med 2010; 40 (11)

Sports Med 2010; 40 (11): 941-959 0112-1642/10/0011-0941/$49.95/0

REVIEW ARTICLE

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Short-Term Recovery from Prolonged Exercise Exploring the Potential for Protein Ingestion to Accentuate the Benefits of Carbohydrate Supplements James A. Betts1 and Clyde Williams2 1 Human Physiology Research Group, University of Bath, Bath, UK 2 School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, UK

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Ingestion of Carbohydrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Timing of Carbohydrate Ingested . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Type/Form of Carbohydrate Ingested . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Amount of Carbohydrate Ingested . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Ingestion of Carbohydrate with Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Glycaemic and Insulinaemic Responses to Protein/Amino Acid Ingestion. . . . . . . . . . . . . . . . . . . 3.2 Combined Carbohydrate-Protein Ingestion and Glycogen Resynthesis . . . . . . . . . . . . . . . . . . . . 3.3 Combined Carbohydrate-Protein Ingestion and Physical Performance . . . . . . . . . . . . . . . . . . . . 4. Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

941 942 945 945 945 946 947 948 949 951 955

This review considers aspects of the optimal nutritional strategy for recovery from prolonged moderate to high intensity exercise. Dietary carbohydrate represents a central component of post-exercise nutrition. Therefore, carbohydrate should be ingested as early as possible in the post-exercise period and at frequent (i.e. 15- to 30-minute) intervals throughout recovery to maximize the rate of muscle glycogen resynthesis. Solid and liquid carbohydrate supplements or whole foods can achieve this aim with equal effect but should be of high glycaemic index and ingested following the feeding schedule described above at a rate of at least 1 g/kg/h in order to rapidly and sufficiently increase both blood glucose and insulin concentrations throughout recovery. Adding ‡0.3 g/kg/h of protein to a carbohydrate supplement results in a synergistic increase in insulin secretion that can, in some circumstances, accelerate muscle glycogen resynthesis. Specifically, if carbohydrate has not been ingested in quantities sufficient to maximize the rate of muscle glycogen resynthesis, the inclusion of protein may at least partially compensate for the limited availability of ingested carbohydrate. Some studies have reported improved physical performance with ingestion of carbohydrate-protein mixtures, both during exercise and during recovery prior to a subsequent exercise test. While not all of the evidence supports these ergogenic benefits,

Betts & Williams

942

there is clearly the potential for improved performance under certain conditions, e.g. if the additional protein increases the energy content of a supplement and/or the carbohydrate fraction is ingested at below the recommended rate. The underlying mechanism for such effects may be partly due to increased muscle glycogen resynthesis during recovery, although there is varied support for other factors such as an increased central drive to exercise, a blunting of exercise-induced muscle damage, altered metabolism during exercise subsequent to recovery, or a combination of these mechanisms.

1. Introduction Many athletes are required to train or compete on more than one occasion within a single day and therefore strive to maximize their recovery in the often relatively short interval between exercise sessions. Exercise at the intensities commonly observed in competitive sport places a high demand on the body’s finite endogenous reserves of carbohydrate such that this substrate may become progressively depleted over time.[1,2] If such exercise is continued for a prolonged duration (i.e. ‡60–90 minutes), then fatigue often occurs once muscle glycogen concentrations reach critically low levels.[3] Therefore, a logical extension of these findings is that the capacity to perform physical exercise for extended periods will be determined to a large extent by the availability of glycogen at the onset of exercise.[4] In view of the relationships described above, it is reasonable to suggest that the rapid replenishment of depleted carbohydrate reserves will constitute an important component of effective recovery, along with rehydration and repair/ regeneration of damaged tissue. When recovery time is ‡24 hours, then simply ingesting carbohydrate in quantities sufficient to replace losses can completely restore the capacity for physical exertion.[5] Conversely, when the time available for recovery is limited to £8 hours, neither muscle glycogen concentrations nor exercise capacity are likely to be entirely restored following exerciseinduced glycogen depletion. Under these circumstances there is a greater need to identify optimal nutritional strategies to promote recovery before subsequent exercise. However, there is a related but separate question (though beyond the scope of this review), which is whether or not adaptations to ª 2010 Adis Data Information BV. All rights reserved.

chronic training may be greater when exercise is repeated while glycogen stores remain relatively low.[6] This review begins with a brief overview of current evidence-based recommendations for carbohydrate intake during short-term recovery from prolonged exercise. For this, a comprehensive literature search was conducted, primarily using PubMed (www.pubmed.gov), to identify studies that have reported muscle glycogen resynthesis and/or the recovery of physical performance in human participants ingesting carbohydrate alone over recovery periods of >2–6 hours in duration (table I). Only full articles published in scientific peer-reviewed journals met inclusion criteria, and data from non-human models are used only to support certain mechanistic discussion where no human data are available. In addition to the summary of this data, we provide specific consideration of the relative importance of and interactions between various nutritional and exercise factors in relation to carbohydrate intake and post-exercise recovery (e.g. timing/type/form/quantity of carbohydrate and the degree of muscle glycogen depletion induced prior to recovery). Thereafter, the focus is on those studies that have examined whether the ingestion of carbohydrate-protein mixtures can offer greater benefit during recovery from exercise than the ingestion of carbohydrate alone (with the same literature search strategy applied). Therefore, the main purpose of this review is to consider the direct effects of ingesting carbohydrateprotein mixtures on physical performance, whether or not related to muscle glycogen resynthesis. In this regard, additional novel elements of discussion include the metabolic responses (e.g. glucose and insulin) during both recovery and subsequent exercise, along with the precise dose/type of protein that most effectively elicits these responses. Sports Med 2010; 40 (11)

Mode of exercise prior to recovery

Battram et al. (2004)[7] Berardi et al. (2006)

[8]

Exhaustive cycling

Post-exercise muscle glycogen concentration (mmol glucosyl units/kg dm) 50 a

Duration of recovery (h)

Rate of carbohydrate ingestion during recovery (g/kg/h)

Frequency of carbohydrate ingestion during recovery

Type of carbohydrate ingested during recovery

Rate of muscle glycogen resynthesis during recovery (mmol glucosyl units/kg dm/h)

6

0.98

IMPE and 1 h intervals

Glucose polymer

49

6

0.80

IMPE, 1, 2 and 4 h

Glucose polymer/meal

22a

55

Betts et al. (2008)[9]

Non-exhaustive running

203

4

0.80

IMPE and 30 min intervals

Sucrose

12

Blom et al. (1987)[10]

Exhaustive cycling

34 64 98 98 137

5

0.35 0.35 0.35 0.70 0.18

IMPE and 2 h intervals

Sucrose Glucose Fructose Glucose Glucose

27 25 14 24 9

Blom (1989)[11]

Exhaustive cycling

94

3

0.93

IMPE and 2 h intervals

Glucose

40

Carrithers et al. (2000)[12]

Non-exhaustive cycling

107

4

1.00

IMPE and 30 min intervals

Glucose

31

Casey et al. (2000)[13]

Non-exhaustive cycling

55a 60a 70a

4

0.25 0.25 0.00

IMPE

Sucrose Glucose Placebo

24a 32a -3a

Casey et al. (1995)[14]

Exhaustive cycling

25

3

1.00

IMPE and 2 h intervals

Glucose

40

De Bock et al. (2005)[15]

Non-exhaustive cycling

110 190

4

1.50

IMPE and 1 h intervals

Glucose polymer

33 11

Doyle et al. (1993)[16]

Non-exhaustive cycling

144 147

4

1.60

IMPE and 15 min intervals

Glucose polymer

43 39

Howarth et al. (2009)[17]

Non-exhaustive cycling

100 100

4

1.20 1.60

IMPE and 15 min intervals

Glucose polymer

23 25

Ivy et al. (1988)[18]

Non-exhaustive cycling

132 153

4

1.00

2h IMPE

Glucose polymer

14 17

Ivy et al. (1988)[19]

Non-exhaustive cycling

137 153 156

4

1.50 0.75 0.00

IMPE and 2 h intervals

Glucose polymer

22 19 2

Continued next page

943

Sports Med 2010; 40 (11)

Non-exhaustive cycling

Nutrition for Post-Exercise Recovery

ª 2010 Adis Data Information BV. All rights reserved.

Table I. Summary of studies examining muscle glycogen resynthesis during short-term recovery (i.e. >2–6) from exercise at varied rates of ingesting carbohydrate alone Study (year)

944

ª 2010 Adis Data Information BV. All rights reserved.

Table I. Contd Study (year)

Mode of exercise prior to recovery

Post-exercise muscle glycogen concentration (mmol glucosyl units/kg dm)

Duration of recovery (h)

Rate of carbohydrate ingestion during recovery (g/kg/h)

Frequency of carbohydrate ingestion during recovery

Type of carbohydrate ingested during recovery

Rate of muscle glycogen resynthesis during recovery (mmol glucosyl units/kg dm/h)

Jentjens et al. (2001)[20]

Exhaustive cycling

106

3

1.20

IMPE and 30 min intervals

Glucose polymer

40

Maehlum et al. (1978)[21]

Exhaustive cycling

68

2.5

0.55

15 min

Glucose

28

McCoy et al. (1996)[22]

Non-exhaustive cycling

116

6

1.00

IMPE and 2 h intervals

Carbohydrate meal

37

Pedersen et al. (2008)[23]

Exhaustive cycling

75

4

1.00

IMPE and 1 h intervals

Glucose

38

Piehl Aulin et al. (2000)[24]

Exhaustive cycling and running

53

4

1.80

IMPE and 30 min intervals for 2 h

Low-osmolality glucose Hi-osmolality glucose

35

58

Price et al. (2000)[25]

Calf raises

Reed et al. (1989)[26]

27

5

0.00

N/A

Placebo

26 11

Non-exhaustive cycling

105 119

4

0.75

IMPE and 2 h intervals

Solid carbohydrate Liquid carbohydrate

24 22

Roy and Tarnopolsky (1998)[27]

Non-exhaustive resistance circuits

235 247

4

0.50 0.00

IMPE and 1 h

Glucose polymer Placebo

19 2

Ruby et al. (2005)[28]

Non-exhaustive cycling

57

4

0.90

IMPE and 2 h intervals

Glucose

28

Exhaustive cycling

59

5

1.03

IMPE and 1 h intervals

Glucose polymer

48

Non-exhaustive cycling

193

4

0.90

IMPE and 2 h intervals

Glucose polymer

34

Tarnopolsky et al. (1997)[31]

Non-exhaustive cycling

163 210

4

0.50 plus ~0.6 0.00 plus ~0.6

IMPE and 1 h plus lunch

Glucose polymer

40 3

Tsintzas et al. (2003)[32]

Non-exhaustive running

252 259

4

0.15 0.53

IMPE, 20 min, 1, 1.5, 2 and 3 h

Glucose polymer

8 19

van Hall et al. (2000)[33]

Exhaustive cycling

110

3

0.80

15 min, 1 and 2 h

Glucose

28

Shearer et al. (2005) Slivka et al. (2008)

[29]

[30]

Sports Med 2010; 40 (11)

Continued next page

Betts & Williams

16 51

Glucose polymer

Glucose polymer

IMPE and 20 min intervals

IMPE and 2 h intervals

26

Glucose polymer IMPE and 1 h intervals

38 13

Glucose/fructose Glucose IMPE and 30 min intervals

24

Glucose polymer IMPE and 30 min intervals

39 44

Placebo Sucrose IMPE and 15 min intervals

45 17

It has been consistently demonstrated that ingesting carbohydrate during short-term recovery from exercise can increase the rate of glycogen resynthesis[13,31,34] and also restore exercise capacity more rapidly[40] than when no carbohydrate is ingested. Over the last 50 years, a large number of well controlled investigations have sought to better understand the metabolic consequences of carbohydrate ingestion following exercise. These studies have not only led to a better understanding of carbohydrate metabolism after exercise but also to recommendations about the optimal timing, type/form and quantity of carbohydrate that should be ingested during recovery.

0.77 dm = dry mass; IMPE = immediately post-exercise; N/A = not applicable.

4 233 Non-exhaustive cycling

Glycogen concentrations in mmol/L and resynthesis rates in mmol/L/h.

Zawadzki et al. (1992)[39]

ª 2010 Adis Data Information BV. All rights reserved.

a

0.70 Non-exhaustive cycling Zachweija et al. (1991)[38]

6

1.00 143 Non-exhaustive cycling Yaspelkis and Ivy (1999)[37]

4

1.20 112 128 Exhaustive cycling Wallis et al. (2008)[36]

4

1.20 0.80 5 138 190 Exhaustive cycling van Loon et al. (2000)[35]

78 90 Exhaustive cycling van Hall et al. (2000)[34]

4

0.00 1.30

2.1 Timing of Carbohydrate Ingested

Mode of exercise prior to recovery

Post-exercise muscle glycogen concentration (mmol glucosyl units/kg dm)

Duration of recovery (h)

Rate of carbohydrate ingestion during recovery (g/kg/h)

Type of carbohydrate ingested during recovery

10 41

2. Ingestion of Carbohydrate

Study (year)

Table I. Contd

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Frequency of carbohydrate ingestion during recovery

Rate of muscle glycogen resynthesis during recovery (mmol glucosyl units/kg dm/h)

Nutrition for Post-Exercise Recovery

If carbohydrate is the only macronutrient ingested during recovery, then it is important to begin feeding immediately after exercise, thus taking full advantage of the transient period of exercise-induced insulin sensitivity that leads to the rapid conversion of ingested carbohydrate into glycogen.[41-43] Conversely, delaying carbohydrate ingestion by just ‡2 hours following exercise can result in a 50% reduction in the rate of muscle glycogen resynthesis.[18] Of course, it would be prudent to begin feeding as early as possible in recovery simply to maximize the time available to consume exogenous carbohydrates and incorporate them into endogenous glycogen stores. In addition, the consensus view is that carbohydrate supplementation should be continued throughout recovery, with more rapid rates of muscle glycogen resynthesis typically achieved when carbohydrate is provided at relatively frequent intervals (i.e. every 15–30 minutes).[16,20,24,35]

2.2 Type/Form of Carbohydrate Ingested

A number of studies have examined the types of carbohydrate that can most effectively stimulate muscle glycogen resynthesis during Sports Med 2010; 40 (11)

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recovery from exercise. Insulin plays a central role in facilitating endogenous carbohydrate storage, and the elevated insulin response to high glycaemic index (GI) carbohydrates as opposed to low GI carbohydrates can accelerate muscle glycogen resynthesis over the first 6 hours of recovery.[44,45] However, it remains debatable whether these differences persist over a more prolonged (i.e. ‡20 hours) recovery period.[44,45] Furthermore, while fructose has a lower GI than glucose and therefore results in a relatively slow rate of muscle glycogen storage,[10] ingesting a mixture of glucose and fructose may provide the optimal balance of dietary carbohydrates for the effective combined resynthesis of both muscle[36] and liver glycogen.[10,13] This is partly due to the preferential hepatic synthesis of glycogen from fructose[46] but also because intestinal fructose absorption occurs via a different transport system than glucose, thus optimizing overall carbohydrate delivery.[47] From a practical perspective, recent evidence also indicates that the ingestion of lower GI carbohydrates during recovery can improve the capacity for continuous exercise either later the same day[48] or on the following day.[49] Such effects may operate via an increased oxidation of lipid during exercise following feeding (thus reducing reliance on finite carbohydrate reserves and delaying glycogen depletion), which may explain why no such ergogenic benefit occurs during high-intensity intermittent exercise where sustained performance relies more heavily on carbohydrate metabolism.[50] Whether carbohydrate is ingested in solid or liquid form does not appear to influence the rate of muscle glycogen storage during recovery.[26,51] This is consistent with the view that the gastric emptying rate of ingested carbohydrate is unlikely to limit the rate of muscle glycogen resynthesis in most situations.[52,53] However, liquid supplements can provide an exogenous source of carbohydrate while simultaneously contributing to rehydration. Whether the osmolality of a carbohydrate solution can influence the rate of carbohydrate delivery and muscle glycogen resynthesis is a question that is currently the focus of research.[24,54] For example, a recent study reported ª 2010 Adis Data Information BV. All rights reserved.

Betts & Williams

improved cycling time-trial performance 2 hours following exhaustive exercise, with cyclists ingesting high, as opposed to low, molecular weight glucose polymer solutions during recovery.[55] Further research is therefore warranted to extend current understanding and nutritional recommendations in relation to carbohydrate solutions with specifically modified osmolalities. 2.3 Amount of Carbohydrate Ingested

While the considerations regarding the timing and type of carbohydrate ingested during recovery are undoubtedly important, it is perhaps of greater practical value to establish the optimal amount of carbohydrate to ingest following exercise. The finding that carbohydrate supplementation of any substantial magnitude during recovery can stimulate far greater rates of muscle glycogen resynthesis than when ingesting no carbohydrate at all has been well established.[13,19,31,34] What is less clear are the precise effects of increasing carbohydrate intake/dose on subsequent glycogen storage rates, particularly those factors that may limit the rate of muscle glycogen resynthesis when large quantities of carbohydrate are ingested. There are a number of factors that might explain the difficulty in ascertaining from the literature the smallest quantity of carbohydrate necessary to maximize muscle glycogen resynthesis. Not least are the confounding influences such as the timing[18,56] and type[10,24] of carbohydrate ingested (as discussed in sections 2.1 and 2.2) and, perhaps most importantly, the degree of prior exerciseinduced glycogen depletion[38] (table I). Many studies have attempted to determine the ‘optimal’ rate of carbohydrate ingestion for muscle glycogen resynthesis; as a result, our understanding of the mechanisms involved in this anabolic process has improved. To our knowledge, there are currently 33 published studies that have reported rates of muscle glycogen resynthesis in response to ingesting varying amounts of carbohydrate during a short-term (i.e. >2–6 hours) recovery in humans. When these studies are considered collectively (figure 1), a significant positive correlation appears between the two variables (i.e. amount ingested and rate of glycogen synthesis: Sports Med 2010; 40 (11)

Nutrition for Post-Exercise Recovery

Muscle glycogen synthetic rate (mmol glucosyl units/kg dm/h)

50 40 30 20 10 0 0

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Carbohydrate ingestion rate (g/kg/h)

Fig. 1. Reported rates of muscle glycogen resynthesis across the 33 published studies that have measured muscle glycogen concentrations during short-term recovery periods (i.e. >2–6 hours) with varied rates of ingesting carbohydrate alone. The solid trend line represents the correlation coefficient (r = 0.7; p < 0.01; n = 27) for the 50% of data points in which muscle glycogen was less depleted (i.e. ‡110 mmol glucosyl units per kg dry mass [dm]) at the onset of recovery,[9,10,12,15,16,18,19,22,26-28,30-33,35-37,39] while the broken trend line represents the correlation coefficient (r = 0.6; p < 0.01; n = 26) for the 50% of data points in which muscle glycogen was more depleted (i.e. <110 mmol glucosyl units per kg dm) at the onset of recovery.[7,8,10,11,13,14,17,20,21,23-26,29,34] The study by Zachwieja et al.[38] is represented as data points but does not contribute to either trend line since no absolute muscle glycogen concentrations were reported in this study.

r = 0.6; p < 0.01). The protocols adopted across this diverse number of studies have varied greatly with respect to several factors that are known to influence muscle glycogen resynthesis. For example, studies using non-exhaustive running[9,32] or resistance-type[25,27] exercise protocols prior to recovery are illustrated alongside the more commonly employed cycling protocols, which have been both exhaustive[7,10,11,14,20,21,23,24,29,33-36] and nonexhaustive[8,12,13,15-19,22,26,28,30,31,37-39] in nature. This would account for the broad range of muscle glycogen concentrations reported at the onset of recovery (i.e. ~16–260 mmol glucosyl units per kg dry mass).[25,32] Given both the effective autoregulation of muscle glycogen concentration[57] and associated metabolic consequences of reduced glycogen content (e.g. increased availability and oxidation of free fatty acids[58]), it is highly likely that the large variation in glycogen resynthesis at any given rate of carbohydrate ingestion is mainly the result of these differences in glycogen ª 2010 Adis Data Information BV. All rights reserved.

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concentrations at the beginning of the recovery process. Interestingly, when the studies shown in figure 1 are stratified according to the absolute degree of glycogen depletion prior to recovery (see trend lines), it is apparent that the capacity for glycogen availability to mediate glycogen storage may be less pronounced at higher rates of carbohydrate ingestion. Of primary importance, however, is that a general dose-response relationship appears to exist between the rate of carbohydrate ingestion and muscle glycogen resynthesis, as was evident in 2003 when information on this topic was last summarized (see figure 2 [page 130] in Jentjens and Jeukendrup[59]). Since then, it is notable that 11 further studies can now be added to this analysis,[7-9,15,17,23,28-30,32,36] and, even so, the highest reported rates of glycogen resynthesis over >2–6 hours of recovery remain in the region of 45–50 mmol glucosyl units per kg dry mass/h following the ingestion of ~1 g/kg/h of carbohydrate.[7,29,35,36] Therefore, based on current evidence, it seems that ingesting carbohydrate alone at a rate of ~1 g/kg/h may be sufficient to maximize the rate of muscle glycogen resynthesis such that additional carbohydrate intake will provide no further increase in this fuel store. 3. Ingestion of Carbohydrate with Protein Sections 2–2.3 have broadly outlined the results regarding ingestion of carbohydrate during short-term recovery from exercise. The remainder of this review considers the metabolic and/or ergogenic consequences of ingesting carbohydrate in combination with protein during post-exercise recovery. In addition, studies on the effects of ingesting these supplements during exercise are also discussed in order to explore whether any ergogenic benefits of ingesting added protein in recovery may be solely due to mechanisms that can occur before a repeated bout of exercise. For example, alternative mechanisms other than accelerated muscle glycogen resynthesis during recovery may carry over and operate during subsequent exercise. Indeed, there appears to be a range of potentially favourable metabolic consequences of including a small quantity of protein in a postSports Med 2010; 40 (11)

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exercise carbohydrate supplement, which may promote recovery more effectively than ingesting carbohydrate alone. 3.1 Glycaemic and Insulinaemic Responses to Protein/Amino Acid Ingestion

It was established over 4 decades ago that pancreatic insulin secretion can be induced either through intravenous infusion or oral ingestion of certain amino acids.[60,61] Of greater relevance to the present review are the studies showing a synergistic influence on insulin release when amino acids or proteins are ingested with carbohydrate.[61-63] A study by van Loon et al.[64] examined the specific magnitude of insulinaemic responses following ingestion of different amino acid/protein mixtures with carbohydrate. The results suggested that the insulinaemic response to a carbohydrate-protein mixture is strongly dependent on the amounts of leucine, phenylalanine and tyrosine in the mixture.[64] Interestingly, despite the fact that arginine is known to be highly insulinotropic when delivered intravenously,[60] the available evidence suggests that arginine is an ineffective means of elevating serum insulin when given orally,[65,66] which can cause gastrointestinal discomfort.[64] Finally, the study by van Loon et al.[64] also indicated that ingestion of protein hydrolysates may increase circulating amino acid concentrations more effectively than ingestion of intact casein. Indeed, subsequent research by these authors has now confirmed that co-ingestion of carbohydrate, protein hydrolysate, leucine and phenylalanine provides an effective means of increasing plasma insulin concentrations during a 3-hour post-exercise recovery.[67] Regarding the question of what might be the most effective dose of amino acids to ingest during recovery, the study by van Loon et al.[67] also found that a greater insulinaemic response can be achieved through increasing the amount of protein in a given carbohydrate-protein mixture from 0.2 to 0.4 g/kg/h. While an earlier study reported no significant dose-response relationship between protein intake and insulin release when assessing a range of protein intakes alongside carbohydrate, an inverse relationship between elevations in ª 2010 Adis Data Information BV. All rights reserved.

plasma glucose and protein intake was reported.[68] However, it cannot be established from these findings whether the lower blood glucose concentrations at higher rates of protein intake were the result of increased glucose uptake, reduced appearance of glucose due to a delayed rate of gastric emptying, or both.[69] Recent evidence indicates that the reduced glycaemic responses to the ingestion of a carbohydrate-protein mixture following exercise in healthy individuals are indeed more likely to reflect a reduced rate of glucose appearance from the gastrointestinal tract than an increased rate of glucose disposal.[70] Irrespective of whether glucose uptake is affected, it appears that carbohydrate-protein mixtures will be most effective in elevating circulating insulin concentrations when the protein component is ingested at rates in excess of ~0.3 g/kg/h. Compiling the results of studies on the insulinaemic responses to ingesting carbohydrateprotein mixtures shows that when the protein intake is of the order of 0.3–0.5 g/kg/h, there is a strong trend towards higher insulin concentrations.[8,9,17,20,33-35,39,67,70-74] Conversely, those studies that have not reported any increase in insulinaemic responses following ingestion of a carbohydrate-protein mixture rather than carbohydrate alone have typically provided protein in quantities closer to 0.1 g/kg/h.[12,31,75,76] Furthermore, in agreement with previous findings,[68] 13 of the 18 investigations cited above have reported significantly lower blood glucose concentrations following ingestion of a carbohydrate-protein mixture rather than carbohydrate alone.[9,12,33-35,39,70-76] It should also be noted that, of the five remaining studies, two did not report any blood glucose data[8,17] and two did in fact observe a reduced glycaemic response when protein was added, but this difference did not attain statistical significance.[31,67] Again, however, it is difficult to determine whether these attenuated elevations in blood glucose concentration are the consequence of decreased glucose appearance or increased glucose uptake, although the studies by van Hall et al.[34] and Kaastra et al.[70] certainly appear to support the former explanation. Notwithstanding this evidence, it cannot be entirely discounted that the synergistic influence of carbohydrate and protein on insulin secretion might Sports Med 2010; 40 (11)

Nutrition for Post-Exercise Recovery

increase glucose uptake and thus facilitate glycogen storage during recovery, a possibility that is addressed in section 3.2. 3.2 Combined Carbohydrate-Protein Ingestion and Glycogen Resynthesis

As discussed in section 3.1, it appears that the greatest insulinaemic response will be achieved when the protein fraction of a carbohydrate-protein mixture is composed of hydrolysed protein combined with certain essential amino acids,[64] and recent evidence from a study using laboratory rats shows that hydrolysed whey may more effectively accelerate muscle glycogen resynthesis than either intact protein or branched chain amino acids when ingested with glucose.[77] The addition of individual amino acids such as leucine, glutamine or arginine to a carbohydrate supplement has not been found to substantially increase circulating insulin concentrations, and while adding leucine to carbohydrate has been shown to enhance muscle glycogen storage in rats,[78] ingestion of either glutamine or arginine in isolation has failed to accelerate muscle glycogen accumulation during recovery in humans.[33,37,79] However, it cannot entirely be ruled out that glycogenic amino acids such as glutamine might be deaminated and converted into glycogen directly rather than promoting glycogenesis from exogenous glucose.[80] In support of this, the increased availability of free fatty acids associated with muscle glycogen depletion is known to stimulate hepatic glucose production,[81] and recent evidence from a study using canines shows that even large increases in systemic insulin concentrations may result in only a modest inhibition of gluconeogenesis.[82] In contrast, a number of studies support the view that the augmented insulin concentrations following combined carbohydrate-protein ingestion can increase the rate of muscle glycogen resynthesis following exercise.[8,33,35,39,75,83,84] In two of these studies, the carbohydrate-protein mixture was assessed in relation to a carbohydrate solution that was also lower in carbohydrate content.[83,84] This raises the question of whether the glycogenic effect of the carbohydrate-protein solution was due to the added proª 2010 Adis Data Information BV. All rights reserved.

949

tein or to the additional carbohydrate. Of the other studies cited above, the study by Zawadzki et al.[39] was the first to examine whether ingesting carbohydrate (~0.8 g/kg/h) plus protein (~0.3 g/kg/h) would increase the rate of muscle glycogen storage during recovery more than when ingesting the carbohydrate fraction alone. Although the absolute concentrations of muscle glycogen were not different between trials by the end of recovery, the rate of muscle glycogen storage was 38% greater when protein had been included in the recovery solution.[39] However, it cannot be established whether this increased rate of glycogenesis was purely a result of the increased insulin response or a consequence of the 43% increase in energy provision when protein was added to the carbohydrate solution. Indeed, both the carbohydrate content and the energy content of a supplement are known to influence the rate of muscle glycogen storage during recovery from exercise.[27] Another well controlled study examined rates of glycogen resynthesis in response to the co-ingestion of carbohydrate (0.8 g/kg/h) and protein (0.4 g/kg/h) during recovery from exhaustive cycling. Importantly, the carbohydrate-protein supplement was evaluated both in comparison with a solution matched for carbohydrate content and another solution matched for available energy content (i.e. 1.2 g/kg/h of carbohydrate). Application of this comprehensive research design established that the rate of muscle glycogen accumulation can be increased with equal effect whether protein or additional carbohydrate are added to an existing solution that provides carbohydrate in relatively moderate quantities (i.e. £0.8 g/kg/h).[35] Interestingly, more recent evidence suggests that including protein with similarly moderate amounts of carbohydrate can increase post-exercise glycogen resynthesis even if the protein replaces some of the carbohydrate in the solution (i.e. isoenergetic supplements).[8,75] In contrast to the above evidence, there are also a comparable number of investigations that have observed the increase in insulinaemic response when protein has been added to a standard carbohydrate solution but have reported no concomitant increase in the rate of muscle glycogen storage during recovery.[9,17,20,33,34,71,74] The studSports Med 2010; 40 (11)

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ies by Jentjens et al.,[20] van Hall et al.[34] and Howarth et al.[17] all assessed whether the proposed ‘maximal’ rate of muscle glycogen resynthesis in response to ingesting ~1.2 g/kg/h of carbohydrate could be exceeded when added protein, rather than additional carbohydrate, is ingested during a 3- to 4-hour recovery.[17,20,34] Notably, all of these studies concluded that the added protein did not further increase the rate of glycogen resynthesis during recovery, despite some reporting a significantly increased insulin release.[20,34] It therefore appears that the important distinction between these studies and those cited previously, in which muscle glycogen resynthesis was accelerated, is the precise quantity of carbohydrate to which the protein was added. When presented graphically (figure 2), it becomes apparent that those studies that have provided ‡1 g/kg/h of carbohydrate have not observed any increase in muscle glycogen resynthesis when protein is added.[17,20,34] This has prompted some authors to suggest that ingesting ‡1 g/kg/h of carbohydrate during recovery may maximally stimulate glucose uptake such that further elevations in systemic insulin concentrations via the ingestion of added protein are unnecessary.[12,20,35] Conversely, muscle glycogen resynthesis has more commonly been accelerated when protein has been included in solutions providing carbohydrate at a lower ingestion rate (i.e. £0.8 g/kg/h).[8,33,35,39,75]

The only studies that are inconsistent with this line of reasoning are those by Rotman et al.[71] and Betts et al.,[9] which found similar rates of glycogen storage with a suboptimal dose of carbohydrate (i.e. ~0.8 g/kg/h) compared with energymatched and carbohydrate-matched carbohydrateprotein mixtures, respectively. The precise reasons for these apparently discrepant findings are not clear but may be related either to the methods used to quantify muscle glycogen content or to the specific type of exercise that was performed prior to recovery (i.e. cycling vs running). For example, Rotman et al. employed 13C-magnetic resonance spectroscopy to quantify glycogen in their study[71] and, while this technique does correlate well with data acquired using the needle biopsy technique,[85] it is impossible to determine whether the rates of muscle glycogen resynthesis were indeed submaximal given that no absolute glycogen concentrations are available (therefore precluding the inclusion of these data in figure 2). Equally, the study we conducted involved recovery from treadmill running[9] rather than cycling, as was used by all other published studies in this area. Therefore, it is possible that, compared with cycling, insulin-mediated glucose transport and glycogen resynthesis may be relatively impaired after treadmill running due to the increased eccentric muscle action and resultant myofibrillar damage associated with this type of exercise.[16,86-89] A logical

Muscle glycogen synthetic rate (mmol glucosyl units/kg dm/h)

50

CHO

CHO/PRO Zawadzki et al., 1992 Jentjens et al., 2001 van Loon et al., 2000 Ivy et al., 2002 van Hall et al., 2000 van Hall et al., 2000 Berardi et al., 2006 Betts et al., 2008 Howarth et al., 2009

40 30 20 10 0 0.4

0.6

0.8

1.0

1.2

1.4

1.6

Carbohydrate ingestion rate (g/kg/h) Fig. 2. Reported rates of muscle glycogen resynthesis across nine studies that have measured muscle glycogen concentrations over >2–6 hours post-exercise with varied carbohydrate (CHO) ingestion rates either with or without protein (PRO).[8,9,17,20,33-35,39,75] Any published studies that have not matched for either carbohydrate or available energy or did not measure absolute glycogen concentrations have been excluded.[71,83,84] The apparent difference between treatments in the study by Jentjens et al.[20] is a product of large inter-individual variation during the exercise-induced component of glycogen resynthesis and is not statistically significant. dm = dry mass.

ª 2010 Adis Data Information BV. All rights reserved.

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Nutrition for Post-Exercise Recovery

extension of this reasoning is that exercise with a substantial eccentric (damaging) component might result in a lower ‘maximal’ rate of muscle glycogen storage that could be attained even when only £0.8 g/kg/h of carbohydrate is ingested during recovery. As discussed in section 3.1, it is likely that ingestion of ‡0.3 g/kg/h of protein is necessary to achieve a marked synergistic effect of combined carbohydrate-protein ingestion on insulin secretion.[67] This finding may explain why some investigators have failed to increase glycogen storage when adding less than this critical amount of protein to carbohydrate recovery solutions, since insulinstimulated glucose transport would not be expected to differ between treatments.[12,31] However, the study by Ivy et al.[75] demonstrated that ingestion of just ~0.2 g/kg/h of protein can accelerate muscle glycogen resynthesis beyond that achieved when ingesting the carbohydrate fraction alone (~0.5 g/kg/h) or even an isoenergetic supplement providing ~0.7 g/kg/h of carbohydrate. Of further interest is that this effect was not associated with any significant increase in circulating insulin concentrations, thus presenting the possibility that enhanced insulin-mediated glucose uptake may not be the only mechanism through which carbohydrate-protein ingestion can increase carbohydrate storage.[75] In summary, it appears that the rate of muscle glycogen resynthesis during short-term recovery can be maximized either through ingesting ‡1 g/kg/h of carbohydrate or through the ingestion of a smaller quantity of carbohydrate in combination with protein and/or mixed amino acids. The primary mechanism through which added protein increases muscle glycogen resynthesis is likely to be related to the synergistic influence of carbohydrate and protein on insulin secretion, especially when ‡0.3 g/kg/h of protein is ingested. Irrespective of the mechanism, the potential for protein to accelerate glycogen resynthesis when ingested alongside carbohydrate introduces the attractive possibility that subsequent physical performance might also be enhanced. Section 3.3 therefore reviews those studies that have examined the efficacy of carbohydrateprotein ingestion in terms of rapidly restoring the capacity for physical exercise within 8 hours of prior exertion. ª 2010 Adis Data Information BV. All rights reserved.

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3.3 Combined Carbohydrate-Protein Ingestion and Physical Performance

As discussed in the previous section, the addition of protein to a carbohydrate recovery solution has the potential to increase the rate of muscle glycogen resynthesis following an initial bout of prolonged exercise. This has prompted further research into whether subsequent exercise capacity might also be improved, given the established association between pre-exercise muscle glycogen availability and exercise time to fatigue[4] (although whether this association applies to short-term recovery of exercise capacity is discussed later in this section). Furthermore, the potential interaction of ingested protein with the liver might also be relevant in terms of recovery, since it has been suggested that resynthesis of hepatic glycogen might be another crucial factor that influences subsequent endurance capacity.[13,90] Some support for this suggestion is obtained from an examination of the correlation between recovery of exercise capacity and the resynthesis of endogenous carbohydrate reserves as a whole (i.e. muscle and liver glycogen: r = 0.5; p < 0.05) in relation to the resynthesis of liver glycogen per se (r = 0.6; p < 0.05).[13] An early example of evidence supporting the efficacy of ingesting added protein for enhanced performance is the study by Saunders et al.[91] This study involved the ingestion of carbohydrate either with or without added whey protein both during and after a prolonged bout of cycling to exhaustion at 75% maximum oxygen uptake . (VO2max) followed 12–15 hours . later by another cycling capacity test at 85% VO2max. Including protein in the solution was reported to increase exercise time to exhaustion by 29% during the first exercise test and by 40% during the second exercise test. However, while the two solutions provided in this study were matched for carbohydrate content, the inclusion of protein unavoidably resulted in a 20% increase in total energy provision.[91] Therefore, similar to much earlier research regarding muscle glycogen resynthesis, it remained to be established whether the ergogenic benefit of the carbohydrate-protein solution was due to the increase in available energy or, as suggested by the authors of the study, some Sports Med 2010; 40 (11)

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mechanism directly mediated by the inclusion of protein per se (e.g. stimulation of protein synthesis and/or repair of damaged tissue). Indeed, the potential for carbohydrate-protein mixtures to provide a protective effect against exercise-induced muscle damage has been the focus of numerous recent studies. Many of these studies have shown that adding protein to a carbohydrate solution reduces indirect evidence of muscle damage such as serum concentrations of myoglobin,[92-96] activities of both creatine kinase[91-95,97-102] and lactate dehydrogenase[98] or 3-methylhistidine excretion,[103] yet many equally well controlled studies do not support these findings.[104-110] Such discrepancies are most likely due, at least in part, to the inherent inter-individual variability that exists for indirect systemic indices of muscle damage, particularly creatine kinase.[111] This variability certainly questions the value of using only creatine kinase as a quantitative proxy measure for the degree of muscle damage sustained, particularly when using a between-groups experimental design. From this perspective, it is notable that only seven extant studies on this topic have examined muscle contractile function,[93,95,104,105,107,108,110] which is believed to represent the most reliable and practical indication of the magnitude of muscle damage sustained.[112] Of these, only two have provided any evidence of improved restoration of contractile function following ingestion of supplements containing carbohydrate and protein compared with carbohydrate alone.[93,95] Several studies have also provided evidence of an ergogenic effect of post-exercise carbohydrate-protein ingestion for prolonged whole-body exercise over repeated days of testing.[91,101,113] It therefore remains a slight possibility that protein may facilitate functional recovery from exercise via a reduction in muscle damage over more prolonged recovery periods (i.e. ‡15 hours). However, it is arguably less likely that any substantial repair of muscle tissue will occur during a more short-term recovery, at least not sufficiently to account for marked effects on physical performance within just 8 hours of recovery. For example, even though the inclusion of protein in a carbohydrate supplement can result in a transition from net ª 2010 Adis Data Information BV. All rights reserved.

Betts & Williams

negative to net positive protein balance over the first 3–4 hours of recovery,[17,114] this effect has been associated with little[114] or no[17] increase in whole-body protein synthesis. Furthermore, any net accrual of tissue mass can be estimated at only ~0.01% (i.e. 0.1 g/kg) over 4 hours relative to ingestion of carbohydrate alone.[114] Whilst the accumulation of small changes in muscle quality and/or quantity can produce worthwhile training adaptations if sustained over weeks or months, the acute change during a single short-term recovery would not be expected to have an effect on subsequent performance. It is possible to gain further insight into the underlying mechanisms responsible for improved performance following the ingestion of carbohydrate with added protein during recovery by considering those studies that have examined these supplements when ingested during exercise. In this way, it is interesting to view feeding during recovery as a pre-exercise nutritional intervention with mechanisms that can be contrasted against those suggested to take effect during exercise. For example, Ivy et al.[76] reported that time to fatigue following 3 hours of variable intensity cycling was improved by 36% when their cyclists ingested a mixture of carbohydrate and protein when compared with a matched quantity of carbohydrate. The fact that this effect occurred without any prior manipulation of muscle glycogen availability therefore leads to the possibility that combined carbohydrate-protein ingestion might also operate via mechanisms other than the avoidance of muscle glycogen depletion. Interestingly, there were no significant differences in plasma insulin concentrations during the exercise, despite the intermittent periods of low-intensity activity, which would tend also to argue against the possibility that muscle glycogen was spared in the carbohydrate-protein trial.[76] Alternative explanations for the differences in exercise capacity between trials may involve specific protein-mediated mechanisms such as an increased central drive for exercise[115] or anaplerotic replenishment of tricarboxylic acid cycle intermediates.[76,116] However, it remains debatable whether the co-ingestion of glucose along with protein can actually improve performance Sports Med 2010; 40 (11)

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through attenuated sensations of fatigue.[117,118] Likewise, other evidence has also challenged the hypothesis that protein ingestion can maintain tricarboxylic acid cycle flux during prolonged exercise.[119,120] Notwithstanding the absence of any clearly supported underlying mechanism, various recent studies have subsequently confirmed that including protein in a carbohydrate supplement can indeed postpone fatigue during exhaustive exercise[76,91,100,101,121] and possibly even improve ‘late-exercise time-trial performance’.[109] However, it is difficult to entirely dissociate the latter finding from the trial order effect reported in that study, particularly given the potential for interactive/synergistic effects between treatment and trial order (i.e. the efficacy of protein may be trial dependent).[109] All of the studies cited above should also be considered in relation to eight other studies that have reported no ergogenic effect of ingesting added protein in terms of either exercise capacity (i.e. time. to fatigue at 70–85% peak oxygen uptake [VO2peak][95,96,98,122]) or exercise performance (i.e. time to complete 7 kJ/kg;[123] 880 – 27 kJ;[110] 80 km time-trial;[124] 6 km timetrial[125]). Notably, while six of these studies examined supplements matched for either carbohydrate[110,124] or available energy,[95,98,122,125] another has identified no performance benefit of the added protein even though the carbohydrateprotein mixture also contained ~25% more carbohydrate and therefore ~51% more energy.[123] This pattern of findings becomes yet more complicated by a recent report that the inclusion of only a moderate protein in a carbohydrate supplement may at least maintain the capacity for exercise even relative to a supplement providing twice as much carbohydrate and over 40% more energy.[96] Resolution of these apparently inconsistent findings may therefore lie in the central role of carbohydrate during such exercise tests. Specifically, the benefits of added protein have been observed only either when that protein increases the energy content of the supplement and/or the carbohydrate fraction is below the amount recommended to satisfy oxidative requirements during exercise. This reasoning would certainly be consistent with our observation of ª 2010 Adis Data Information BV. All rights reserved.

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deteriorated exercise performance when protein replaced carbohydrate in an isocaloric carbohydrate supplement during a high-intensity exercise test.[125] Overall, the possibility remains that an enhanced rate of post-exercise muscle glycogen resynthesis might not be the only factor contributing to improved recovery of performance with combined carbohydrate-protein ingestion. In fact, there is very little evidence to support the hypothesis that an enhanced rate of muscle glycogen resynthesis during short-term recovery results in an improved recovery of exercise capacity. The rate of muscle glycogen resynthesis is very low when no carbohydrate is consumed during recovery,[19,31,34] yet increasing the rate of muscle glycogen storage through the provision of carbohydrate has not consistently been found to enhance subsequent exercise capacity.[13,40] However, one of these studies may not have provided sufficient carbohydrate throughout recovery to reveal an effect of carbohydrate ingestion on physical performance.[13] Furthermore, in contrast to the well documented relationship between carbohydrate ingestion rate and muscle glycogen resynthesis (figure 1), far fewer studies have examined the relationship between carbohydrate intake and exercise capacity.[73,126,127] Of these, only one study has shown increased carbohydrate intake during recovery to translate into an enhanced capacity for physical exercise following a short-term recovery.[73] To our knowledge, only one published investigation has demonstrated that an increased rate of muscle glycogen resynthesis during a short-term recovery can improve exercise capacity during subsequent exercise.[83] This investigation by Williams et al.[83] is also of particular relevance to this review given that it was the first study to have investigated the effect of combined carbohydrate-protein ingestion during short-term recovery on the capacity for subsequent exercise. In this study, . participants were required to cycle at 65–75% VO2max for >105 minutes in order to deplete muscle glycogen stores and reduce blood glucose concentrations below 4.0 mmol/L. Once glucose homeostasis had been sufficiently challenged, participants began a 4-hour recovery during which they consumed either carbohydrate alone (0.15 g/kg/h) or carbohydrate (0.40 g/kg/h) plus protein (0.10 g/kg/h). Notably, Sports Med 2010; 40 (11)

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the carbohydrate-protein mixture resulted in a 92% greater insulinaemic response and 128% greater rate of muscle glycogen resynthesis than the solution that provided less carbohydrate and no protein. Of greater practical importance was the finding that participants were able to exercise 55% longer (i.e. 20 vs 31 minutes) during a subsequent exer. cise capacity test at 85% VO2max when mixed carbohydrate-protein rather than carbohydrate alone had been ingested during recovery.[83] Interestingly, these same two supplements have also been examined in a more recent investigation in which cycling capacity was actually impaired following the ingestion of the additional carbohydrate and protein, although a separate comparison with a milk-based carbohydrate-protein mixture did not produce this negative effect.[128] Notwithstanding this inconsistency, the study by Williams et al.[83] remains as the first evidence that increased muscle glycogen resynthesis during recovery can potentially be translated into an enhanced capacity for subsequent exercise. More recent research on this topic has subsequently attempted to establish whether an enhanced recovery of exercise capacity would also occur if a carbohydrate-protein solution were evaluated in comparison with a solution that was matched for either carbohydrate or available energy content. Of course, such a comparison would not be expected to induce differences in muscle glycogen resynthesis of the magnitude reported by Williams et al.,[83] and part of the difficulty for researchers in this area is that the application of muscle biopsy procedures can potentially influence the validity of subsequent exercise testing. One solution has been to use 13C-MRS to quantify muscle glycogen concentrations, which was applied to good effect in the study by Berardi et al.[8] This comprehensive study compared energy-matched carbohydrate-protein and carbohydrate-only supplements ingested over a 6-hour recovery from a 60-minute cycling test and found that, while muscle glycogen resynthesis was significantly accelerated by the addition of protein, there was no difference between treatments in terms of a second exercise performance test following recovery.[8] This finding regarding restoration of exercise performance is consistent ª 2010 Adis Data Information BV. All rights reserved.

Betts & Williams

with two other studies, which examined recovery supplements matched for either carbohydrate or available energy content. Both studies failed to find performance benefits following the ingestion of the added protein in terms of running ca. pacity (i.e. time to exhaustion at ‡85% VO2max) within 2–4 hours of an initial prolonged bout of exercise.[72,106] In contrast, Berardi et al.[129] have subsequently repeated their study with the same research design but with a more sensitive and externally valid exercise test and, consistent with another recent report,[130] did observe a longer time to exhaustion with the carbohydrate-protein mixture (at least in terms of maintaining performance relative to the first bout). Notably, both of the studies by Berardi et al.[8,129] incorporated a standardized lunch into the post-exercise feeding regimen, which better reflects the real-life behaviour of athletes but has rarely been a feature of studies in this area.[8,31,129] Our own work on this topic revealed no difference between isocaloric carbohydrate and carbohydrate-protein supplements. However, every participant was able to exercise for longer during the post-recovery exercise test after ingesting the carbohydrateprotein mixture when compared with a control solution of matched carbohydrate content.[73] In addition, we also observed no acceleration of muscle glycogen synthesis during recovery,[9] thus lending further support to the hypothesis that part of the benefit of ingesting a mixed carbohydrate-protein solution may be unrelated to increased muscle glycogen availability. In this regard, it is noteworthy that our studies on this topic have consistently found an increased rate of whole-body carbohydrate oxidation during exercise following the ingestion of a protein-containing carbohydrate recovery supplement,[9,72,73] but with no alteration in the rate of muscle glycogen degradation.[9] Taken together, these findings suggest that the mechanism by which the ingestion of a carbohydrate-protein solution during recovery can postpone fatigue during subsequent exercise may be related at least partially to improved maintenance of euglycaemia and/or increased oxidation of extramuscular carbohydrate sources during exercise (i.e. both exogenous and hepatically derived). Sports Med 2010; 40 (11)

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From this perspective, it might be speculated that even very subtle differences in blood glucose availability late in exercise could potentially account for the observed ergogenic effects of ingesting carbohydrate with added protein. This proposed mechanism would explain why the ingestion of a carbohydrate-protein solution has been shown to be most effective during the latter stages of prolonged exercise or when protein is added to moderate quantities of carbohydrate (i.e. situations when carbohydrate availability may be compromised).[76,91,100,109] The precise physiological mechanism through which adding protein to carbohydrate operates may therefore involve an interaction of the established fatigue mechanisms. In this way, relative muscle glycogen depletion may sensitize the CNS to fluctuating blood glucose availability late in exercise before a central component of fatigue ultimately determines the capacity for continued exercise. An interaction of fatigue mechanisms as described above would therefore explain how an increased rate of blood glucose oxidation can delay fatigue independent of changes in total carbohydrate oxidation,[131] and is also intuitive as it relates to the preservation of homeostasis in advance of frank hypoglycaemia. However, further examination of such possibilities will require innovative research designs to isolate the relative and combined effects of each mechanism of action. 4. Conclusions and Future Directions The weight of available evidence supports the view that muscle glycogen resynthesis over the first 8 hours after prior exercise-induced glycogen depletion will be heavily dependent upon the ingestion of carbohydrate. However, the precise effects of either carbohydrate ingestion or muscle glycogen resynthesis on subsequent physical performance remain to be fully established. The most effective nutritional strategy to rapidly replenish depleted glycogen reserves is likely to involve ingesting a high GI carbohydrate source at a rate of at least 1 g/kg/h, beginning immediately after exercise and then at frequent (i.e. 15- to 30-minute) intervals thereafter. However, if a more moderate quantity of carbohydrate is inª 2010 Adis Data Information BV. All rights reserved.

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gested, the inclusion of a small amount of protein can accelerate muscle glycogen resynthesis and/or promote a more rapid restoration of exercise capacity (with these two outcomes not necessarily causally related). Future research is warranted to examine whether added protein can increase the rate of muscle glycogen resynthesis beyond the maximal levels that have been observed with carbohydrate alone. In addition, and perhaps more importantly, future investigations should aim to determine the precise causal relationships between post-exercise carbohydrate intake, muscle glycogen resynthesis and restoration of physical performance. The latter can be achieved by conducting more studies that include exercise as a measure of functional recovery within their research designs, with a more comprehensive and innovative range of assessments applied late in exercise to explore the primary mechanisms of fatigue under these conditions. Acknowledgements The authors’ studies which inform this review were funded by GlaxoSmithKline, who approved submission of this manuscript. The authors have no conflicts of interest that are directly relevant to the content of this review.

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cling exercise and subsequent high-intensity endurance capacity. Int J Sport Nutr Exerc Metab 2010; 20 (3): 216-23 Martinez-Lagunas V, Ding Z, Bernard JR, et al. Added protein maintains efficacy of a low-carbohydrate sports drink. J Strength Cond Res 2010; 24 (1): 48-59 Osterberg KL, Zachwieja JJ, Smith JW. Carbohydrate and carbohydrate + protein for cycling time-trial performance. J Sports Sci 2008; 26 (3): 227-33 van Essen M, Gibala MJ. Failure of protein to improve time trial performance when added to a sports drink. Med Sci Sports Exerc 2006; 38 (8): 1476-83 Toone RJ, Betts JA. Isocaloric carbohydrate versus carbohydrate-protein ingestion and cycling time-trial performance. Int J Sport Nutr Ex Met 2010; 20 (1): 34-43 Fallowfield JL, Williams C. The influence of a high carbohydrate intake during recovery from prolonged, constant pace running. Int J Sport Nutr 1997; 7: 10-25 Wong SH, Williams C. Influence of different amounts of carbohydrate on endurance running capacity following short term recovery. Int J Sports Med 2000; 21: 444-52 Karp JR, Johnston JD, Tecklenburg S, et al. Chocolate milk as a post-exercise recovery aid. Int J Sport Nutr Ex Met 2006; 16: 78-91 Berardi JM, Noreen EE, Lemon PW. Recovery from a cycling time trial is enhanced with carbohydrate-protein supplementation vs isoenergetic carbohydrate supplementation. J Int Soc Sports Nutr 2008; 5: 24 Thomas K, Morris P, Stevenson E. Improved endurance capacity following chocolate milk consumption compared with 2 commercially available sport drinks. Appl Physiol Nutr Metab 2009; 34 (1): 78-82 Claassen A, Lambert EV, Bosch AN, et al. Variability in exercise capacity and metabolic response during endurance exercise after a low carbohydrate diet. Int J Sport Nutr Ex Met 2005; 15: 97-116

Correspondence: Dr James A. Betts, Human Physiology Research Group, University of Bath, Bath, BA2 7AY, UK. E-mail: [email protected]

Sports Med 2010; 40 (11)

Sports Med 2010; 40 (11): 961-980 0112-1642/10/0011-0961/$49.95/0

REVIEW ARTICLE

ª 2010 Adis Data Information BV. All rights reserved.

Sport Psychiatry A Systematic Review of Diagnosis and Medical Treatment of Mental Illness in Athletes Claudia L. Reardon and Robert M. Factor University of Wisconsin Hospital and Clinics, Department of Psychiatry, Madison, Wisconsin, USA

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Search Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Psychiatric Diagnoses in Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 Mood Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 Anxiety Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3 Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.4 Attention-Deficit Hyperactivity Disorder (ADHD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.5 Addictive Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.6 Other Disorders. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Use of Psychopharmacological Agents by Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 General Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Antidepressants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Mood Stabilizers/Anticonvulsants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Anxiolytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Stimulants/ADHD Medications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Sedative Hypnotics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 Antipsychotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Psychiatric Diagnoses in Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Mood Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Anxiety Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Eating Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4 ADHD. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.5 Addictive Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Use of Psychopharmacological Agents by Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

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Sport psychiatry focuses on diagnosis and treatment of psychiatric illness in athletes in addition to utilization of psychological approaches to enhance performance. As this field and its research base are relatively new, clinicians often deliver psychiatric care to athletes without a full understanding of the diagnostic and therapeutic issues unique to this population. In this systematic review, we discuss published findings relating to psychiatric diagnosis and medical treatment of mental illness in athletes.

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There have been several studies looking at the prevalence of some psychiatric disorders in various athlete populations. Eating disorders and substance abuse are the most studied of these disorders and appear to be common problems in athletes. However, to provide informed understanding and treatment, we especially need more research on overtraining syndrome, bipolar disorder, suicidality, anxiety disorders, attention-deficit hyperactivity disorder (ADHD) and psychosis in athletes. Research is needed in the areas of prevalence, risk factors, prognosis and the unique experiences facing athletes with any of these disorders. Additionally, there have not been any large, systematic studies on the use of psychotropic medications in athletes. Small studies suggest that some medications may either be performance enhancing or detrimental to performance, but we need larger studies with rigorous methodology. Higher level athletes suffering from psychiatric symptoms often have reservations about taking medications with unknown performance and safety effects, and methodological issues with the current literature database preclude any definitive conclusions on performance effects of psychiatric medications. We need many more, higher quality studies on the use by athletes of antidepressants, mood stabilizers, anxiolytics, stimulants and other ADHD medications, sedative-hypnotics and antipsychotics. Such studies should utilize sensitive performance measures and involve longer term use of psychotropic medications. Furthermore, study subjects should include athletes who actually have the psychiatric disorder for which the medication is proposed, and should include more women.

1. Introduction Mental health professionals provide care for athletes of all abilities, from school team to elite competitor. Sport psychology, which focuses largely on performance enhancement, is an energetic and fairly well-developed specialty. On the other hand, sport psychiatry, with a focus on diagnosis and treatment of psychiatric illness in athletes in addition to performance enhancement, is still developing and evolving. Sport psychologists’ and sport psychiatrists’ approaches to athlete patients can be very complementary. However, general clinicians are the ones most often treating athletes and because of the still-developing state of knowledge of sport psychiatry, psychiatric care of athletes is often delivered without a full understanding of the diagnostic and therapeutic issues unique to this population. Appropriate diagnosis and treatment of mental illness is critical for the careers of upper level athletes. For recreational participants, it has the ability to impact overall satisfaction with sport and future involvement in physical activity. ª 2010 Adis Data Information BV. All rights reserved.

The assumption that there is a low prevalence of mental illness in athletes is one reason for the paucity of research in this area. A tendency to idealize athletes leads health care providers to deny the existence or significance of psychiatric symptoms. Athletes themselves have a tendency to minimize apparent signs of weakness. Moreover, athletic behaviours sometimes resemble symptoms of mental disorders (e.g. meticulous attention to diet, relative hyperactivity), thereby confounding recognition of illness. The International Society for Sport Psychiatry, with its core purpose ‘to facilitate scientific communication about, and understanding of, disorders of the brain and behaviour associated with sport, and to advance their prevention and treatment’, is an organization that has made significant strides in destigmatizing mental illness in athletes and informing healthcare professionals and the public that in fact mental illness does occur in athletes. Nonetheless, stigma and an underdeveloped research base in this field remain problematic because of all the aforementioned issues. Sports Med 2010; 40 (11)

Sport Psychiatry

While sport psychiatry is relatively new in the literature, our thorough review reveals important findings. In this paper, we discuss the current state of knowledge of (i) psychiatric diagnoses in athletes; and (ii) the use of psychiatric medications in athletes. Besides medications, sport psychiatrists also use psychotherapy and other treatment modalities, including family assessments and diagnosis[1-3] and participation in team assistance programmes.[4] However, non-medicationbased treatments are beyond the scope of this review. 2. Search Methods We identified studies through a MEDLINE search. Search terms included the following, individually and in combination: ‘psychiatry’, ‘athletes’, ‘sports’, ‘sport psychiatry’, ‘mental illness’, ‘major depressive disorder’, ‘depression’, ‘bipolar disorder’, ‘suicide’, ‘anxiety’, ‘generalized anxiety disorder’, ‘obsessive compulsive disorder’, ‘social phobia’, ‘social anxiety disorder’, ‘panic disorder’, ‘post-traumatic stress disorder’, ‘specific phobia’, ‘psychosis’, ‘eating disorders’, ‘anorexia nervosa’, ‘bulimia nervosa’, ‘attention-deficit hyperactivity disorder’, ‘substance abuse’, ‘substance dependence’, ‘addiction’, ‘alcohol’, ‘anabolic steroids’, ‘stimulants’, ‘tobacco’, ‘antidepressants’, ‘mood stabilizers’, ‘anxiolytics’, ‘antipsychotics’, ‘sedative hypnotics’, ‘psychotropics’, ‘medications’ and ‘psychiatric medications’. We restricted results to the English language and used no date restrictions. We retrieved all papers discussing psychiatric diagnosis or psychiatric medication treatment of athletes, including even brief case reports or letters to the editor. We reviewed the findings of each article, and reviewed the references of each paper for additional papers that had been missed in the initial search and that might include findings relevant to the scope of our review. In total, we retrieved and reviewed 172 papers, the majority of which arose from the primary database search. These papers are not all represented in this article’s citations, as we determined that some were beyond our scope after carefully reviewing each one. As a result, we included and cited 103 papers in this review. ª 2010 Adis Data Information BV. All rights reserved.

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3. Results 3.1 Psychiatric Diagnoses in Athletes

In many ways, the sport psychiatry diagnostic interview is similar to the general psychiatry interview. However, the healthcare provider must keep in mind the unique needs of the athlete, demands of the specific sport setting and stresses of athletic competition.[5] Moreover, it is important that the clinician attempt to differentiate the ‘person’ from the athletic ‘persona’.[6] The following various possible relationships between athletics and psychiatric disorders have been described:[7,8] (i) athletes may obtain high levels of success in spite of a coexistent primary psychiatric disorder; (ii) athletes may have chosen the athletic arena as a means of coping with a disorder; or (iii) athletes may have psychiatric illness precipitated or worsened by sport itself. 3.1.1 Mood Disorders Major Depressive Disorder

The main mood disorders are major depressive disorder (MDD) and bipolar disorder. MDD is a period of at least 2 weeks during which there is either depressed mood or the loss of interest or pleasure in nearly all activities, accompanied by other symptoms such as insomnia and changes in appetite, energy and concentration. Any of three possible relationships between athletics and, in this case, the psychiatric disorder of depression could exist in depressed athletes. That is, athletes’ depression might have nothing to do with their athletic pursuits or the athletic pursuits could be their way of coping with depression, or it even could be caused by athletic participation. These possibilities have not been studied per se. However, in the only textbook on sport psychiatry, Burton[9] concluded from the few epidemiological studies published that athletes experience psychiatric disorders, including mood disorders, at the same rate as the general population. The specific frequency of depression in athletic populations has been studied at a number of levels. At the high school level, Oler et al.[10] reported that athletic participation was a marker for decreased likelihood of depression and suicidal ideation. At Sports Med 2010; 40 (11)

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the college level, Yang et al.[11] studied 257 division 1 college athletes and found that athletes showed the same frequency of depressive symptoms as did a comparison group. However, athletes who were female, freshmen or who had pain were more likely to endorse depression. Puffer and McShane[12] asserted that college athletes were generally well adjusted, and that overtraining (OT) seemed to be the most common cause of depression in this population. Donohue et al.[13] compared 72 National Collegiate Athletic Association (NCAA) athletes and 64 recreational athletes at one university with data previously collected on 435 control students at another university. They found no difference in psychiatric symptoms, including those of depression, between the recreational and NCAA athletes, and between all athletes and the controls. We did not find any data in the literature on the prevalence of mood disorders in elite athletes. Subtypes of depression (e.g. with seasonal onset, with melancholic or atypical features) in athletes have been little studied. Rosen et al.[14] offered the only such study in their report of 68 division 1 college hockey players from the northern US. Eleven percent met criteria for seasonal affective disorder (SAD) and 39% exhibited ‘subsyndromal seasonal affective disorder’ as defined by Kasper et al.[15] While the 11% with SAD approximated the national average in northern latitudes, 39% exceeded the 13% average for the general population in northern latitudes.[16] While depression overall may be no more likely in athletes than non-athletes, when it does occur, precipitants may include OT, injury, competitive failure, aging, retirement from sport and the same psychosocial stressors that can precipitate depression within the general population. OT in particular may either induce or be symptomatic of depression.[17] Indeed, it can be difficult to distinguish OT from primary MDD. Similarities between the two include fatigue, insomnia, appetite change, weight loss, amotivation and diminished concentration.[17] Armstrong and VanHeest’s[17] review showed that symptoms of OT appeared in >60% of distance runners during their athletic careers, >50% of professional soccer players during a 5-month competiª 2010 Adis Data Information BV. All rights reserved.

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tive season and 33% of basketball players during a 6-week training camp. Morgan et al.[18] studied 400 competitive collegiate swimmers over 11 years and found that mood-state disturbance increased in a dose-response manner as the training stimulus increased during the season, and then fell to baseline with reduction of training load. Schwenk[19] argued that there is a tendency for the same symptoms diagnosed as MDD in the average primary care patient to be diagnosed as OT in athletes, and that this was related to stigmatization of mental illness in athletes. He asserted that the two should not be distinguished, as there are numerous physiological similarities. Ultimately, he suggested that the primary difference between MDD and OT is the nature of the role dysfunction: athletic performance versus social, cognitive and work performance. On the other hand, evidence for the two being distinct conditions includes that some physiological symptoms of OT are not present in MDD. For example, athletes with OT often exhibit elevated heart rate and blood pressure, muscle soreness and changes in serum hormone levels.[20-23] Moreover, in OT, a cessation of training often yields an improvement in mood, whereas depressed athletes who do not train or exercise often seem to experience worsened depressive symptoms. Anecdotally, the transition to retirement seems to be a high-risk time for emotional distress in athletes. Parham[24] offered data on this in his study of college athletes and concluded that three factors predicted the degree of emotional distress experienced by athletes upon retirement from sport: (i) extent of psychological attachment to sport; (ii) degree of devotion to sport to the exclusion of other activities; and (iii) level of success in sport. There have been at least two reports on depression in former elite athletes during the years after retirement. Backmand et al.[25] studied 664 former elite athletes and 500 controls and found that the best predictor of post-retirement depression was a low level of current physical activity. Schwenk et al.[26] sent a survey to 3377 retired National Football League (NFL) players, with 14.7% of the 1617 respondents reporting moderate to severe depression and 47.6% reporting ‘quite’ or Sports Med 2010; 40 (11)

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‘very common’ difficulty with physical pain. The authors concluded that the level of depressive symptoms was similar to the general population but the impact of the symptoms was exacerbated by high levels of pain. They hypothesized that high levels of chronic pain with which many players leave the NFL (or other sports) contributed to a predisposition to depression. Bipolar Disorder

Bipolar disorder is a mood disorder characterized by manic episodes consisting of an abnormally and persistently elevated, expansive or irritable mood, usually occurring separate from and in addition to episodes of major depression. In contrast to unipolar depression, very little has been written about bipolar disorder in athletes, with no known prevalence data. Suicide

Suicide is a concern when considering mood disorders in any population. Baum[27] reviewed the medical literature from 1960 to 2000 and the periodical literature from 1980 to 2000. She identified 71 cases of athletes who contemplated, attempted or completed suicide, including 66 completed suicides. This study had an obvious bias of anecdotal reporting but may be informative nonetheless. The average age of the 71 cases was 22, including 61 men and 10 women. The rank order of sports from most to least suicides reported included football, basketball, swimming, track and field, and baseball. Risk factors included substance abuse, post-retirement, eating disorders, anabolic steroid use, family history of suicide, homosexuality and sexual abuse (including sexual abuse by coaches). Smith and Milliner[28] reported that, based on five cases of injured athletes who attempted suicide, risk factors in injured athletes may include success in sport pre-injury, injury requiring surgery, a lengthy rehabilitation process restricting athletic participation from 6 weeks to 1 year, inability to recapture pre-injury success, post-concussive syndrome and replacement by team mates. They note that the Emotional Responses of Athletes to Injury Questionnaire[29] can be administered to injured athletes to identify those who might be at risk for suicidal behaviour. Begel[30] hypothesized that the catecholamine and endogenous opioid ª 2010 Adis Data Information BV. All rights reserved.

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systems may be downregulated after athletic injury, thereby contributing to the dysphoria that commonly occurs following injury. 3.1.2 Anxiety Disorders

Apart from the single study on social anxiety disorder, which is described in the following section, anxiety disorders, including social anxiety disorder, generalized anxiety disorder, obsessivecompulsive disorder (OCD), panic disorder, posttraumatic stress disorder and specific phobias, have been minimally studied in athletes. Many athletes have normal ‘state anxiety’, meaning they become appropriately anxious before competition but it does not permeate their entire life.[31] Social Anxiety Disorder

Social anxiety disorder is characterized by clinically significant anxiety provoked by exposure to certain types of social or performance situations, often leading to avoidance behaviour. Northon et al.[32] hypothesized that undergraduates with social anxiety would experience related anxiety symptoms in sports, as sports often involve performance demands and social evaluation. Thus, their hypothesis was that social anxiety might be an example of a psychiatric condition in which the symptoms are exacerbated by sport itself. Their study of 180 students showed that, especially in women, general levels of social anxiety were related to social-evaluative fears in sport, but they did not measure the effects of anxiety on performance. Additionally, social anxiety was positively correlated with avoidance of individual sports but not team sports. Social anxiety did not correlate with level of competition (e.g. no involvement vs intramural vs intercollegiate). Compulsive Disorders

Many mental health professionals consider OCD and addictive disorders to be related in sharing ritualistic behaviours that serve to assuage anxiety. There have been several studies that addressed exercise as a compulsive behaviour (variably referred to as ‘positive addiction’[33] ‘exercise addiction’[34] and ‘obligatory running’[35]). These studies have described a process in which individuals experience withdrawal symptoms such as depression, Sports Med 2010; 40 (11)

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anxiety and irritability when they are unable to exercise, and how exercise ‘addicts’ continue to exercise despite medical contraindications, with potential adverse impact on work, home and social life. No systematic studies of the prevalence of ‘exercise addiction’ have been published. ‘Muscle dysmorphia’ is probably a subtype of body dysmorphic disorder, which is often felt to lie on the OCD spectrum. It is a disorder of distorted body image in which patients who are quite muscular nonetheless feel that they are too small.[31] Muscle dysmorphia could well be an example of a psychiatric condition that is perpetuated by sport itself. No large, systematic studies of the prevalence of muscle dysmorphia have been published, but Pope et al.[36] have reported that bodybuilders seem to be at higher risk than other athletes and that women bodybuilders have a higher incidence than their men counterparts. It is also important for healthcare providers to distinguish superstitious rituals that are common in athletics from full-blown OCD.[31] OCD is characterized by at least an hour per day of obsessions or compulsive behaviour, in a manner that significantly interferes with daily functioning. Superstitions, on the other hand, are circumscribed to the athletic arena and do not interfere with functioning. Other Anxiety Disorders

We found no studies in athletes on generalized anxiety disorder, OCD, panic disorder, posttraumatic stress disorder or specific phobias. 3.1.3 Eating Disorders

Eating disorders include anorexia nervosa and bulimia nervosa. The former is characterized by a refusal to maintain a minimally normal bodyweight, while the latter involves repeated episodes of binge eating followed by inappropriate compensatory behaviours, such as food restriction, selfinduced vomiting or excessive exercise. Eating disorders among athletes have been relatively well studied, and these conditions might well represent psychiatric disorders that are perpetuated by participation in sport itself. Calhoun et al.[37] published a 1998 review on eating disorders in sport. They found that the ª 2010 Adis Data Information BV. All rights reserved.

incidence of eating disorders in women athletes has been reported to be as high as 60% and is mostly associated with long distance running, gymnastics and figure skating (so-called ‘leanness sports’). Rosen et al.[38] found that at the college level, 32% of women varsity respondents to an anonymous survey had engaged in at least one weight-control behaviour (self-induced emesis or use of laxatives, diuretics or diet pills) on a daily basis for at least 1 month. Also, at the college level, Burckes-Miller and Black[39] found that greater than one-third of 695 men and women athletes from intercollegiate teams reported significant weight fluctuation associated with binging and fasting. At the elite level, Byrne and McLean[40] showed that, of Australian women elite athletes representing many different’ sports, anorexia nervosa or bulimia nervosa was present in 15% of those in leanness sports and 2% in non-leanness sports, compared with 1% of non-athlete controls. Among Australian men elite athletes, anorexia nervosa or bulimia nervosa was present in 5% of those in leanness sports; no eating disorders were identified in men in non-leanness sports or in male controls. More recently, Torstveit et al.[41] and Sundgot-Borgen and Torstveit[42] confirmed a higher percentage of eating disorders in elite athletes in leanness sports than in both athletes competing in non-leanness sports and in controls. Research performed exclusively on men rowers and wrestlers suggested that the prevalence of eating disorders in some populations of men athletes is as high as in high-risk groups of women athletes.[43] Moreover, men athletes are more at risk of developing eating disorders compared with the general population of men than women athletes are when compared with the general population of women.[31] However, Glazer[44] reported that men may return more rapidly to their normal weights and eating behaviours than do women after ending their competitive athletic careers, although this is variable, with some retired athletes continuing to rely on eating disordered behaviours for stress reduction. Healthcare providers must consider the diagnosis of ‘anorexia athletica’ even if an athlete’s weight is not <85% of ideal bodyweight, since intense training can result in increased muscle Sports Med 2010; 40 (11)

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mass.[45] Despite ‘normal’ weight in these athletes, they may exhibit many of the other signs and symptoms of anorexia nervosa, such that this would be considered ‘Eating Disorder Not Otherwise Specified’ in Diagnostic and Statistical Manual of Mental Disorders (4th Edition) Text Revision nomenclature.[31] 3.1.4 Attention-Deficit Hyperactivity Disorder (ADHD)

Attention-deficit hyperactivity disorder (ADHD) is a persistent pattern of inattention and/or hyperactivity-impulsivity that is more frequently displayed and more severe than is typically observed in individuals at a comparable level of development. Based on anecdotal reports, ADHD appears to be more prevalent in athletes than non-athletes, possibly because those with ADHD are drawn to physical activity, this, thereby, being an example of athletes choosing the athletic arena as a means of coping with a disorder.[9] However, no systematic studies of the prevalence of this disorder among athletes have been published. 3.1.5 Addictive Disorders

Addictive disorders include substance abuse, characterized by a maladaptive pattern of substance use manifested by recurrent and significant adverse consequences related to the repeated use of a substance, and the more severe substance dependence, which is a cluster of cognitive, behavioural and physiological symptoms (often including tolerance and withdrawal symptoms) indicating the an individual continues use of a substance despite significant substance-related problems. In many cases, addictive disorders might represent conditions that are perpetuated by sports participation itself (e.g. stimulant and anabolic steroid abuse). As in the general population, alcohol is the most frequently abused substance among athletes.[46] Several studies have been published on the rates of substance use in different sports and levels of competition. Alcohol use among college athletes has been reported to be higher than in the general public (75–93% for men athletes and 71–93% for women athletes), with rates of alcohol use higher in swimming/diving, soccer and baseball/ softball than basketball, volleyball and track and ª 2010 Adis Data Information BV. All rights reserved.

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field.[46] In a very large retrospective NCAA study of 13 914 student athletes,[47] alcohol was the most widely used substance in the past year (used by 85% of athletes), followed by cannabis (28.4%) and smokeless tobacco (22.5%). Furthermore, the prevalence of alcohol, amphetamine, cannabis, psychedelic substance and cocaine use was highest in division 2 or 3 level athletes. The authors noted that a significantly higher percentage of division 1 programmes than lower division programmes conducted their own drug testing, which served as a deterrent to substance use. Additionally, men tended to use more substances than women, and White student athletes more than non-White student athletes in this study. Alcohol

Overall, college athletes cited alcohol as the substance with the most apparent negative effects on performance and health, despite it being the substance most used. Consistent with students’ perceptions of alcohol use as detrimental to performance, O’Brien[48] reported that alcohol consumption in the 24 hours before athletic activity caused reduction in aerobic performance by 11.4%. Miller et al.[49] addressed the possible link between psychopathology and alcohol abuse in athletes. They surveyed 262 college athletes about alcohol abuse and psychiatric symptoms. Twentyone percent reported heavy alcohol use, with significant dose-dependent correlations between alcohol abuse and depressive symptoms, as well as general psychiatric symptoms. They could not determine causality. Stimulants

Stimulant use is of particular importance in sport psychiatry. Athletes sometimes use stimulants for performance enhancement, but there can also be adverse effects of stimulant use on performance including anxiety, insomnia, tremulousness, irritability and weight loss. Athletes may use alcohol and sedatives to counteract the side effects of stimulant stacking.[50] Tobacco

Athletes use chewing tobacco for a variety of reasons. Among professional athletes, the most common reasons given for use are pre-game and Sports Med 2010; 40 (11)

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post-game relaxation, improved concentration, boredom, increased energy, the need to have something in the mouth and performance improvement.[47] College baseball players gave a different set of reasons including recreational or social reasons (48%), pleasure and stress relief; only 1.4% indicated performance enhancement.[47] Anabolic Steroids

Anabolic steroids are another important substance of abuse among athletes. In the US, the first Anabolic Steroid Control Act took effect in 1990 and promoted a shift from the use of illegal anabolic steroids to legal nutritional supplements (e.g. supplements containing testosterone precursors, such as androstenedione or dehydroepiandrosterone).[50] In the past few years, the Bay Area Laboratory Co-Operative steroid scandal in track and field and baseball has highlighted the strategies, such as so-called ‘designer steroids’, which some athletes may employ in order to test negative for steroids while using them. Steroidabusing athletes report dramatic increases in training and faster recovery times.[50] In addition to their strength effects, anabolic steroids have psychiatric side effects, including hostility, aggression, irritability and mood lability.[51,52] In 1993, Su et al.[51] were the first to conduct a prospective, placebo-controlled, double-blind study that examined the psychiatric effects of anabolic steroids. They found that methyltestosterone was significantly associated with increased positive mood symptoms (euphoria, energy, sexual arousal), negative mood symptoms (irritability, mood swings, violent feelings and hostility) and cognitive impairment (distractibility, forgetfulness and confusion). Pope and Katz[53] compared 88 athletes who used anabolic steroids to 68 non-users. They found that 23% of users reported major mood syndromes (mania, hypomania or major depression), including 12% with psychotic symptoms and 8% with other drug dependence. The large 2001 NCAA study also analysed steroid use.[47] Self-report rates by men varied greatly by sport, ranging from 0.2% (swimming) to 5% (water polo). Use by women NCAA athletes was much lower, ranging from 0.0% (in several sports) to 1.6% (lacrosse). ª 2010 Adis Data Information BV. All rights reserved.

3.1.6 Other Disorders Pathological Gambling

The essential feature of pathological gambling is persistent and recurrent maladaptive gambling behaviour that disrupts personal, family or vocational pursuits. In a survey of 636 college athletes at three universities, Kerber[54] found that almost 15% had problem or pathological gambling. They reported no control group. An American Psychiatric Association Task Force on Disorders of Impulse Control not Elsewhere Classified[55] reported that slot and poker machines were the favourite gambling activities of athletes. In a literature review, Miller et al.[56] reported that the largest sex difference among addictive behaviours by athletes involved gambling, with many more men than women athletes engaging in gambling. Concussion

Concussion is defined as a head injury with a transient loss of brain function, and it is the most frequent type of head injury that occurs in athletes.[57] Complicated concussions can result in numerous psychological symptoms, including irritability, depression, anxiety and impulsivity.[58,59] Broshek et al.[60] had 2340 men and women high school and collegiate athletes complete pre-season neurocognitive testing. They retested the 155 athletes who sustained sports-related concussions during their seasons. Women athletes showed greater declines in simple and complex reaction times and more post-concussion symptoms than men. Delirium

Delirium is a fairly rapidly developing disturbance of consciousness that is accompanied by a change in cognition and is due to medical/physical stressors on the body. Acute delirium can occur in endurance athletes, including cyclists, triathletes and mountaineers.[16] Causes include hyponatraemia, hyperthermia and heat stroke. 3.2 Use of Psychopharmacological Agents by Athletes 3.2.1 General Principles

There are a number of important issues to consider concerning the use of psychotropic Sports Med 2010; 40 (11)

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medications by athletes. These include their effects on athletic performance, their safety and considerations in relation to antidoping guidelines. Sport psychiatrists have shown concern about minimizing the negative effects of psychotropic drugs on performance. A 1999 survey of the prescribing practices of members of the International Society for Sport Psychiatry (ISSP) showed that 84% tried to avoid sedation, 68% tried to avoid extrapyramidal symptoms and 58% tried to avoid tremors.[8] Prescribers should know the guidelines of the relevant sport federation prior to prescribing any medication for a high-level athlete. The World Anti-Doping Agency (WADA) includes in its World Anti-Doping Code a list of prohibited substances. Importantly, this code is not ‘complete’ in that several categories of banned substances include a general ban on ‘other substances with a similar chemical structure or similar biological effect(s)’ to substances explicitly banned.[61] Additionally, even if a given medication is not included in the prohibited list of WADA, a specific sport federation might have a more stringent code that would supercede WADA guidelines. For example, the International Archery Federation currently bans all anxiolytics, antidepressants, antipsychotics and the three primary mood stabilizers (lithium, valproic acid and derivatives, and carbamazepine) because the federation feels that psychotropics unfairly diminish anxiety. However, even when a substance is banned in a particular sport, athletes may be granted a therapeutic use exemption, which allows athletes with clinical indications for banned substances to take them. While there are prohibitions against the use of certain medications for athletes at the college and elite levels, such prohibitions typically do not exist at lower levels of competition. Nonetheless, prescribers should know the performance effects, harmful or beneficial, of the medications they prescribe to athletes at any level. Psychotropic medications affect the levels of neurotransmitters and may cause up- or downregulation of neural circuits. This could be important for performance. There are several studies that support a CNS build up of serotonin as a possible factor leading to fatigue,[62-64] while a build up of dopamine ª 2010 Adis Data Information BV. All rights reserved.

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might allow continued exercise despite physiological indicators of fatigue.[65] 3.3 Antidepressants

Antidepressants are used most commonly to treat mood disorders, especially MDD, but are also sometimes used to treat other psychiatric disorders, including anxiety disorders, eating disorders and even ADHD. There have been few large randomized controlled trials of antidepressants in athletes. However, there have been studies of the effects of selective serotonin reuptake inhibitors (SSRIs), bupropion and a norepinephrine reuptake inhibitor in which participants served as their own controls. When 11 college athletes were given a single dose of fluoxetine 40 mg, a daily dose of fluoxetine 40 mg for 2 weeks or placebo, neither fluoxetine treatment affected muscle strength, anaerobic capacity, power or fatigue.[66] However, as none of the experimental arms of this study was equivalent in duration to the typical therapeutic use of fluoxetine, and as duration of therapy is critical for antidepressants, the significance of this negative result is unclear. Meeusen et al.[67] had eight male cyclists perform three 90-minute time trials after ingesting placebo or fluoxetine 20 mg the evening before and the morning of cycling time trials in a double-blind, randomized, crossover design. Performance was not affected by fluoxetine, though endorphins increased significantly less with the SSRI versus placebo. However, the same criticism concerning the experimental design of single-dose administration of antidepressants applies here and to many of the studies referenced in the following paragraphs. Paroxetine has also been studied in randomized controlled trials. Wilson and Maughan[68] studied seven men exercising to exhaustion on a bicycle ergometer at 70% of maximum oxygen . uptake (VO2max) after administration of paroxetine 20 mg or placebo. Exercise time after paroxetine was significantly less than after placebo (median 94 vs 116 minutes). However, the peripheral metabolic and cardiorespiratory responses to exercise (carbohydrate oxidized, blood glucose at exhaustion, blood lactate peak, plasma ammonia Sports Med 2010; 40 (11)

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and water consumption) were the same. The authors asserted that this supported a central component to fatigue that was mediated by the activity of serotonergic neurons. Strachan et al.[69] had eight men perform two cycle rides to exhaustion in a warm environment (temperature being the only major . difference from the prior study) at 60% of VO2max 5 hours after receiving paroxetine 20 mg or placebo in a randomized double-blind fashion. Time to exhaustion and perceived effort were not influenced by paroxetine, but rectal temperature was higher throughout exercise in the paroxetine subjects. In contrast to the previous study, the authors were surprised that paroxetine did not limit exercise capacity, especially in the heat, given that it caused increased body temperature and seemed to limit exercise in regular temperatures in the previous study. The inconsistency of these findings warrants further study. Bupropion has also been studied in small trials. This medication is of particular interest as it is on WADA’s 2009 Monitoring List, meaning WADA is monitoring for any concerning trends of inappropriate use.[61] Piacentini et al.[70] had eight men complete a maximal exercise test to determine maximal power output and two endurance performance tests, both in a double-blind, randomized, crossover design. Subjects received either one dose of bupropion 600 mg or placebo. Performance after a single dose was not affected by bupropion. The next year, several of the same investigators[71] conducted a similar study of bupropion but added environmental temperature as a variable. In this study, nine men took either bupropion 600 mg or placebo prior to 60 minutes of cycling in temperate or warm climates, immediately followed by a time trial. Time trial performance was significantly improved by bupropion in the heat but not in the temperate conditions. In the heat, both core temperature and heart rate were higher in the bupropion group, though this group did not perceive greater effort or thermal stress. Thus, bupropion seemed to allow greater performance in the heat, with athletes able to push themselves to higher temperatures and heart rates without perceiving greater effort. The authors speculated that either the ª 2010 Adis Data Information BV. All rights reserved.

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dopaminergic or noradrenergic properties of bupropion contributed to increased exercise abilities in the heat but could not determine which was responsible. Recently, members of this same research group[72] tried to determine if similar performance and thermoregulatory effects occurred following administration of bupropion over several days, as opposed to just a single dose. They administered bupropion 150 mg to eight men cyclists for 3 days followed by 300 mg for 7 days or placebo. The cyclists then completed two trials of 60 minutes of fixed intensity exercise followed by a time trial in hot temperatures. ‘Chronic’ bupropion administration significantly increased core temperature but not to the same extent as had been seen in this group’s study of acute bupropion administration, and it did not result in improved performance. The authors speculated that chronic administration might result in an adaptation of central neurotransmitter homeostasis. However, 10 days of bupropion treatment may still not be equivalent to the effects of longterm therapy. To address the question of whether the ergogenic properties of acute bupropion use are more likely due to its dopaminergic or noradrenergic properties, Piacentini et al.[73] conducted a doubleblind, randomized, crossover study in which seven men received either the norepinephrine reuptake inhibitor reboxetine 8 mg or placebo the night before and morning of 90-minute cycling time trails. Performance after two doses was not influenced by reboxetine. The authors concluded that it was therefore likely that the dopaminergic properties of bupropion, rather than the noradrenergic properties, enhanced performance in prior studies of this medication. This is consistent with studies showing other dopaminergic medications (stimulants) to be performance enhancing. Many of the same researchers[74] recently studied nine men cyclists, administering either reboxetine 16 mg or placebo followed by cycling for 60 minutes in temperate or warm conditions and then a time trial. A single dose of reboxetine decreased power output and, consequently, exercise performance in temperate and warm conditions, thereby offering further evidence that noradrenergic Sports Med 2010; 40 (11)

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medications may not enhance performance and may even limit it in hot conditions. Tricyclic antidepressants have been studied minimally in athletes and not in any randomized controlled trials. Fowler et al.[75] described supraventricular and ventricular arrhythmias in young and otherwise healthy people taking tricyclics. However, the effects of tricyclic-induced cardiac effects on athletic performance, while potentially important, have not been studied. Waslick et al.[76] measured the effect of tricyclics on non-competitive exercise. Twenty-two children and adults completed a graded treadmill exercise test before and after receiving desipramine at an average single dose of 3 mg/kg. Drug treatment did not affect exercise tolerance, but the effects on actual maximal performance were not measured. de Zwaan[77] reported the effects of exercise on desipramine and amitriptyline blood levels in two psychiatric outpatients who were taking stable, chronic doses of the drugs, showing that exercise caused desipramine and amitriptyline blood levels to rise 10% and 14.9%, respectively, though the author felt this was unlikely to be clinically significant. Moreover, levels returned to baseline within 1 hour after exercise. We found no studies of venlafaxine, duloxetine, mirtazapine, nefazodone, trazodone, electroconvulsive therapy or phototherapy in athletes. Despite the lack of large, systematic studies of antidepressants in athletes, sport psychiatrists have reported medication preferences in treating depressed athletes.[8] The majority (63%) prescribed fluoxetine for treatment of depression in athletes, followed by venlafaxine (21%), SSRIs in general (16%), bupropion (11%) and fewer than 5% each for clomipramine, fluvoxamine, nefazodone or paroxetine. Reasons cited for preference of fluoxetine included its activating properties and lack of weight gain. With altered serotonin activity implicated in both MDD and OT, Armstrong and VanHeest[17] have recommended pharmacological treatment of OT syndrome with antidepressants, though this has not been studied in any rigorous manner. Additionally, there are no data on whether antidepressants restore physical performance in athletes with depressive symptoms more or less effectively if symptoms are due to OT or a MDD not associated with OT. ª 2010 Adis Data Information BV. All rights reserved.

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3.4 Mood Stabilizers/Anticonvulsants

Mood stabilizers are most commonly used by mental health professionals to treat bipolar disorder, though they also can be used for treatmentresistant depression and, less commonly, for anxiety. Mood stabilizers have been studied much less than antidepressants. Safety and performance effects are important concerns in prescribing lithium to athletes. In one of the first studies of lithium and exercise, Smith[78] studied rats that underwent 3 hours of strenuous exercise. Their renal lithium clearance decreased significantly. Smith suggested that strenuous exercise in humans might cause a similar effect, meaning that lithium dose reduction might be necessary before heavy exercise to avoid toxicity. A few years later, Miller and colleagues[79] showed that the lithium content of pilocarpine-stimulated forearm sweat ranged from 1.2- to 4.6-fold higher than serum lithium concentration, suggesting that heat-induced sweating might actually lower serum lithium levels. In 1982, Jefferson and colleagues[80] studied four athletes taking lithium who ran a 20 km race in hot conditions. All four athletes became dehydrated during the race but had a decrease in serum lithium levels. They surmised that contrary to widely held belief, heavy sweating may not increase the risk of lithium intoxication, and it might be ill-advised to reduce lithium dosing before a strenuous exercise event, consistent with the findings from the Miller et al.[79] study. In considering performance effects of lithium, Macleod[16] reasoned that lithium-induced tremor might adversely affect fine motor coordination, which is important in some sports. However, we did not find any studies quantifying this hypothesis. Tilkian et al.[81] studied cardiovascular performance of 12 subjects during treadmill exercise and found no effect of long-term lithium therapy. As with antidepressants, Baum[8] surveyed the mood stabilizer prescribing preferences of sport psychiatrists. Fifty-eight percent of responding sport psychiatrists chose valproic acid as their most commonly prescribed mood stabilizer, stating that it caused less weight gain, tremor and sedation, and that there was less concern about Sports Med 2010; 40 (11)

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drug levels being altered by dehydration than with lithium. However, we found no actual studies in athletes on the use of valproic acid or mood stabilizers other than lithium. 3.5 Anxiolytics

Anxiolytics are used to treat a variety of anxiety disorders including social anxiety disorder, generalized anxiety disorder, OCD, panic disorder, post-traumatic stress disorder, and specific phobias. Beta-blockers have been banned since 1985 for the Olympic sports of shooting, archery, diving and ski jumping because of their ability to improve fine motor control and produce bradycardia, which allows for longer time to take aim. Thus, this class of medications would be disqualifying if prescribed for performance anxiety in these sports. The same is true for the use of pindolol for antidepressant augmentation. On the other hand, beta-blockers may diminish performance . in endurance sports as they negatively affect VO2max, endurance and time for a 20 km run.[82] Another study[83] showed that muscle strength was decreased by beta-blockers. Betablockers may reduce available energy by decreasing insulin release, glycogenolysis and lipolysis.[84] Marvin et al.[85] conducted a randomized controlled trial of buspirone in athletes in which 13 men exercised at 80% maximal rate of oxygen uptake following administration of a single dose of buspirone 45 mg or placebo. Perceived exertion was higher following buspirone and time to volitional fatigue fell significantly by approximately one-third from 26 minutes on placebo to 16 minutes following buspirone. Kennedy[86] suggested that clonidine, sometimes used for anxiety, may stimulate endogenous growth hormone release, which could be performance enhancing. However, this medication is not on the WADA code of banned substances and has not been studied in athletes. Physicians commonly use benzodiazepines to treat anxiety, and this class of medications is discussed in detail in section 3.7. In the ISSP membership survey,[8] the most commonly prescribed anxiolytic by sport psychiatrists was buspirone (37% of respondents). Memª 2010 Adis Data Information BV. All rights reserved.

bers reported that they avoided benzodiazepines because of sedation, dependence, impaired reflexes and balance, and cognitive impairment. Of those prescribing benzodiazepines, 32% used alprazolam and 26% lorazepam, reportedly because of their short half-lives. 3.6 Stimulants/ADHD Medications

Stimulants are most commonly used to treat ADHD, though less commonly they can be used to treat the rare sleep disorder narcolepsy and shift work-related sleep cycle problems. In 1957, two Olympic athletes admitted to using amphetamine (amfetamine) to enhance performance, thereby leading the American Medical Association to create an ad hoc committee to study the use of amphetamine in sport. This led to the first report of stimulants as potentially performance enhancing in 1959.[87] They reported enhanced performance in swimmers, runners and weight throwers after ingestion of a single dose of amphetamine 14 mg. Since 1959, there have been many studies of stimulant use by athletes that have tried to examine its effects more precisely. Chandler and Blair[88] improved upon studies prior to that date by using more adequate controls in their study of six men college athletes who received either dextroamphetamine (dexamfetamine) 15 mg/70 kg bodyweight or placebo 2 hours before being tested on several performance measures. The stimulant group exhibited increases in strength, acceleration, anaerobic capacity, time to exhaustion and maximum heart rates. The authors proposed that dextroamphetamine might mask the effects of fatigue but not prevent it from occurring as there . was no change in VO2max. They hypothesized that the ~9% increase in lactic acid concentration after maximum exercise with the stimulant was a result of the ability to maintain exercise . for longer despite no concomitant increase in VO2max. Roelands et al.[65] had eight men ingest methylphenidate 20 mg or placebo 1 hour prior to 60 minutes of cycling in temperate or warm climates immediately followed by a time trial. Methylphenidate improved performance in heat but there was no difference between treatments in temperate conSports Med 2010; 40 (11)

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ditions. In the heat, core temperature and heart rate were higher in the drug group, though this group did not perceive greater effort or thermal stress. The authors concluded that dopaminergic agents might not only be ergogenic but also might be harmful in the heat as athletes might be unaware of increasing heat stress on their bodies. Given the reported ergogenic effects of stimulants, prescribing these medications to athletes has been controversial, and this issue has been considered in the literature. In his review article of psychoactive drugs and athletic performance, Schwenk[84] noted that the NCAA permitted the use of methylphenidate for ADHD if the need were documented but ‘‘the practical implementation of this exception has yet to be fully assessed because of the imprecision of ADHD diagnosis and the theoretical possibility that methylphenidate prescribed for legitimate purposes may be used inappropriately.’’ We note that Schwenk’s article was published in 1997 and while the imprecision of ADHD remains an issue throughout psychiatry, it is possible that diagnostic rigour in diagnosing this condition has improved over the last 12 years. Very recently, there has been concern about inappropriate use of stimulants in major league baseball (MLB) in the US. According to a report released in January 2009, 106 players, representing 8% of MLB players, obtained therapeutic use exceptions for ADHD drugs in 2008.[89] This is a small increase from 103 players in 2007, though a large increase from 28 in 2006. Hickey and Fricker[90] noted that though CNS stimulants are not permitted for use in competition (without a therapeutic use exemption) by the International Olympic Committee or the US Olympic Committee, treatment with methylphenidate may be suitable for athletes with ADHD as cessation of therapy 24 hours before competition is usually adequate to allow drug clearance, thereby avoiding a positive result on drug testing. However, this does not take into account the issue of stimulant use outside of competition potentially conferring an unfair practice advantage, i.e. athletes potentially can practice longer and harder leading up to the competition if taking stimulants. Finally, they noted that other medications used to treat ADHD, such as modafinil, were not banned ª 2010 Adis Data Information BV. All rights reserved.

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in competition. However, modafinil was added to the WADA banned list in 2004, so it is no longer a therapeutic option for high-level athletes.[61] Despite the known ergogenic properties of stimulants, Conant-Norville and Tofler[91] discussed the psychopharmacological treatment of ADHD in athletes and explained that athletes may experience diminished performance in some sports with treatment of their ADHD symptoms. For example, basketball point guards or wrestlers may have an advantage if their untreated symptoms allow them to be spontaneous or unpredictable to their opponent. There has been no systematic study of this hypothesis. These authors proposed the therapeutic strategy of using a short-acting stimulant for student athletes while they attend classes, timing the medication so that it wears off for practice and competition. 3.7 Sedative Hypnotics

Sedative hypnotics are most often used to treat insomnia and other sleep disturbances and can also be used to treat daytime anxiety. Sleep is an important issue for athletes. Travel and anxiety about competition can contribute to insomnia but athletes may hesitate to take sedative hypnotics for fear of sedation or other side effects at the time of competition. Melatonin is one of the most studied sleep aids among athletes. Atkinson et al.[92] reviewed the relevance of melatonin to sports medicine. They noted that the two most important performancerelated effects of melatonin were its hypnotic and hypothermic properties. Indeed, these two properties have been studied in much research on melatonin use by athletes. Studies have shown that exercise may be limited by high core temperature.[93,94] Thus, strategies that use medications, including melatonin, to attempt to reduce body temperature prior to exercise theoretically could provide a greater margin before performancelimiting core temperatures are reached. Nonetheless, Atkinson and colleagues’ review concluded that, overall, there was little support for ergogenic effects of melatonin. However, most studies looking for such an effect involved low intensity exercise (e.g. walking).[92] Moreover, though melatonin Sports Med 2010; 40 (11)

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can reduce some physical performance measures immediately after it is taken, taking it as a hypnotic before night-time sleep does not appear to cause any significant hangover effects on performance the following morning.[92] Benzodiazepines have been studied in athletes using a variety of athlete populations and performance measures. Reilly et al.[95] assigned eight members of the British men’s gymnastics squad and nine support staff to receive temazepam 10 mg or placebo in a double-blind fashion before going to bed on days 1, 2 and 3 after travelling from the UK to Florida, USA. A test battery was given to the subjects at 07:00, 12:00, 17:00 and 21:00 on the first full day after arrival and on days 3, 5 and 7. Temazepam had little influence on subjective (sleep quality and length, subjective jet lag), physiological (tympanic temperature) and performance (choice reaction time, grip strength, leg strength and back strength) measures. The authors concluded that temazepam may be less associated with residual effects on performance than other benzodiazepines since its half-life is shorter and it has a lower receptor affinity than other benzodiazepines. However, they also noted that the low dose of temazepam used had no beneficial effect on subjective sleep quality, and they did not want to risk using a higher dose because these were elite athletes preparing for the 1996 Olympics. Moreover, these findings could not be extrapolated to eastward travel, which for most people requires a more difficult and prolonged adjustment. There are two published studies of zolpidem use in athletes. Ito et al.[96] conducted a double-blind, crossover study in which seven athletes received zolpidem 10 mg or placebo in two sessions over 2 nights. Zolpidem seemed to help sleep and did not affect athletic performance as measured by a combined test of finger dexterity, a simple discriminatory reaction test, critical flicker fusion (CFF) test, vertical jump and a 50 metre sprint. In looking at individual performance measures, there was a significant improvement in CFF, a sensitive measure of arousal levels, after use of zolpidem the previous evening. This was reported as a notable finding, as prior studies of benzodiazepines showed that CFF in medicated groups was lower than or equal to control groups.[97,98] Ito et al.[96] ª 2010 Adis Data Information BV. All rights reserved.

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concluded that short-acting non-benzodiazepine hypnotics such as zolpidem possibly have fewer subtle hangover effects and muscle relaxant effects than benzodiazepines. To determine if zolpidem would increase physical stress imposed by exercise, Mougin et al.[99] had eight men athletes perform 30 minutes of steady state cycling followed by a progressively increased workload until exhaustion. This testing occurred after an experimental night in which athletes were assigned to one of three groups: partially sleep deprived; single dose of zolpidem 10 mg; or placebo. The latter two groups were not sleep deprived. Zolpideminduced sleep did not affect hormonal and metabolic responses (assessed via levels of growth hormone, prolactin, cortisol and lactate) to subsequent exercise as compared with sleep deprivation or placebo. Tafti et al.[100] conducted a double-blind, crossover study in which eight male volleyball athletes received another non-benzodiazepine agent, zopiclone 7.5 mg, or placebo on two subsequent nights. Athlete performance batteries consisting of a choice reaction time test, eye-hand coordination test, CFF test, standing jump test and running time test did not show any significant difference between zopiclone and placebo, and zopiclone had favourable effects on self-estimated sleep quality and daytime alertness. This outcome was consistent with Tafti et al.’s a priori hypothesis, given the short half-life of zopiclone. Grobler et al.[101] compared performance effects of different sedative-hypnotic drugs. They gave 12 subjects a single dose of zopiclone 7.5 mg, loprazolam 2 mg or placebo on three different occasions separated by a 1-week washout period. Subjects completed a performance battery (eyehand coordination tests, a 30 metre sprint test, an agility test and a graded treadmill run to exhaustion) after drug administration and reported greater hangover effects following loprazolam compared with zopiclone or placebo administration. With loprazolam, subjects had decreased reaction time in the eye/hand coordination tests, but other performance measures were not affected. Paul et al.[102] also conducted a comparison study. They assessed 23 subjects using psychomotor testing prior to, and 7 hours after, ingestion of a single dose of zaleplon 10 mg, zopiclone Sports Med 2010; 40 (11)

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7.5 mg, temazepam 15 mg, melatonin time-released 6 mg or placebo in a double-blind crossover study. Zaleplon, zopiclone and temazepam impaired performance compared with placebo on all four studied tasks: serial reaction time, logical reasoning, serial subtraction and multitask. Melatonin did not impair performance on any task. The authors concluded that melatonin was superior to zaleplon in causing no impact on performance. The remaining drugs in increasing order of performance impact were zaleplon, temazepam and zopiclone. A third comparison study was conducted by Charles et al.[103] in which 27 physical education students were given nitrazepam 10 mg, temazepam 30 mg or placebo at night using a double-blind protocol for 9 nights. Morning observations were made after nights 2 and 9. Both drugs were equally effective in promoting and maintaining sleep, but nitrazepam, which has a markedly longer half-life than temazepam, had a subjective hangover effect. Maximum exercise levels on a bicycle ergometer attained using either drug were comparable to placebo on day 2, while maximum levels attained on temazepam and placebo were significantly higher than nitrazepam by day 9. 3.8 Antipsychotics

Antipsychotics are used to treat schizophrenia and bipolar disorder. Though these conditions might not be common in upper level athletes, antipsychotics can also be used off-label for more common conditions, including insomnia and anxiety. We found no articles on the use of antipsychotic medications in athletes. 4. Discussion 4.1 Psychiatric Diagnoses in Athletes 4.1.1 Mood Disorders

Psychiatric illnesses, including mood disorders, in athletes have been relatively understudied. Most existing data suggest that depression is equally common in athletes and non-athletes. However, depression in athletes needs significantly further study. One important question is the relationship between MDD and OT, given the prevalence of OT in athletes and its potential implications for ª 2010 Adis Data Information BV. All rights reserved.

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performance and quality of life. Prevention of OT should also be more rigorously studied. Morgan et al.[18] suggested that monitoring of mood states throughout the season could provide a potential method of preventing OT, but acceptability and feasibility of this for athletes needs further attention. Mood monitoring and appropriate adjustment of training might indeed prove more acceptable to athletes than taking psychotropic medication would be. Times of transition (e.g. post-injury and retirement) present increased risk for psychological distress, particularly symptoms of depression, in athletes. Accordingly, diagnosis of psychiatric symptoms during these times should be studied in a rigorous fashion. Suicide and bipolar disorder in athletes should be more rigorously studied as well as the former has not been systematically researched and the latter has not been studied at all. 4.1.2 Anxiety Disorders

Apart from one small study on social anxiety disorder in athletes, this group of disorders has not been scientifically studied in athletes and warrants further research attention. Anxiety could be a substantial deterrent to athletic participation. On the other hand, it well could be a reason to avidly encourage athletic participation as sport might prove a helpful treatment for anxiety disorders. This is an example in which knowledge about the prevalence of, and effects of, psychiatric diagnoses in athletes is an important issue for individual athletes but is a public health issue as well, further justifying the need for more and higher quality research in this area. For example, if people with anxiety disorders such as social phobia tend to avoid athletic involvement because of fear of negative evaluation, their physical and mental health could suffer, thereby contributing to a greater healthcare burden. Longitudinal studies of different mental illnesses, including anxiety and how they affect choices about whether to become involved in sport and exercise, could further the understanding of these issues. Ultimately, addressing psychological issues such as these, as well as diagnosing and treating mental disorders, might allow more people to become athletically active. Sports Med 2010; 40 (11)

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4.1.3 Eating Disorders

Eating disorders are especially prevalent in ‘leanness sports’ and are surprisingly common in men athletes in addition to being very common in women athletes. While all psychiatric conditions in athletes need more rigorous study, this is an area in which further research could be particularly high-yield for many athletes given that this might be one of the few areas in which the disorders are actually perpetuated by sports participation itself. 4.1.4 ADHD

In contrast to athletes with eating disorders, athletes with ADHD might choose to participate in sports as a coping strategy. However, this relationship between sports participation and coping with psychopathology is merely an anecdotal assertion and further research on ADHD in athletes is needed, especially given the implications that treatment involves using potentially performance-enhancing stimulants. 4.1.5 Addictive Disorders

Overall, athletes appear to use substances of abuse more than the general population, but it is not clear if the reason for this has more to do with issues of abuse/dependence or performance enhancement. Historically, it had been thought that stimulants and anabolic steroids had low physical dependence potential, suggesting that these substances might be predominantly used for performance enhancement, but there is now evidence that people can become physically dependent on these substances as well. The potential role of preexisting or emergent psychiatric symptoms in the development of drug and alcohol abuse in athletes merits further study. In considering prevention strategies, at least at the college level, more stringent drug testing has been associated with lower rates of substance use, and thus more rigorous urine and blood testing at all levels of athletics might prove helpful not only in diagnosis but also in leading to appropriate treatment. If coaches or healthcare providers have concerns about heavy alcohol use they also might consider testing alcohol levels in athletes in the early afternoon following suspected drinking, ª 2010 Adis Data Information BV. All rights reserved.

as the presence of alcohol at that late point in the day suggests heavy drinking the night before. Additionally, healthcare providers could ask all their athletes, including recreational ones and including both boys and girls starting at a young age, about their use of anabolic steroids. 4.2 Use of Psychopharmacological Agents by Athletes

There have not been any large, systematic studies on the use of psychotropic medications in athletes. Higher level athletes suffering from depressive or other psychiatric symptoms often have reservations about taking medications with unknown performance and safety effects. Even the slightest effect on performance, e.g. a few hundredths of a second in a 100 metre dash, can mean the difference between success and failure. The effect of medications on performance is critical in determining whether or not athletes should use psychotropic medications, but there are several problems with relying on the existing literature to determine what these effects might be. An important methodological issue is what performance measures were used to determine if a medication caused detrimental performance effects. A very sensitive measure of performance is needed to detect small but important decrements in performance. The most valuable performance measure would be to have athletes compete in their real-life athletic events after administration of the medication in question. However, the participation of athletes in such a study could threaten their competitiveness and livelihood if detrimental effects were to occur. Thus, optimal research on performance effects of medications will prove difficult to conduct. Even so, more rigorous research than that available now is mandatory so that athletes may make well-informed treatment decisions. An additional methodological issue in assessing the performance effects of medication is that many studies measure athletic performance after only one dose of medication. However, it is well established that many psychotropic medications produce their therapeutic effects only after several weeks of continuous use. Longer term use of Sports Med 2010; 40 (11)

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a psychotropic medication might have different performance effects than just a one-time dose. Indeed, the 1987 study by Charles et al.[103] comparing temazepam, nitrazepam and placebo found that on day 2 of using the medications, there were no performance effects but after 9 days performance effects were present. Likewise, studies of bupropion showed that acute administration in hot temperatures enhanced performance,[71] but by the tenth day of administration there was no effect on performance.[72] Another methodological issue is whether study subjects actually have the psychiatric disorder that the medication studied is intended to treat. For example, many studies of sedative hypnotics in athletes used subjects who did not suffer from insomnia. For such a subject athlete, a night-time benzodiazepine dose might be associated with next-day sedation compared with the same subject’s baseline. However, in a subject athlete who suffered from severe insomnia, there might be no next-day sedation (or even improved alertness) compared with the baseline of that athlete who has chronic sleep deprivation. Finally, almost all of the studies cited included only men subjects. Thus, extrapolation to women athletes may be very problematic. In addition to considering the possibility that medication could enhance or impair performance, the safety of psychiatric medications used by athletes is a critical issue. Some concerns are more intuitively apparent, e.g. the risks of lithium toxicity in heavily exercising athletes (though even this has been called into question by the research evidence). However, there might be less readily apparent safety concerns of which most practitioners are not aware. For example, exercising to the point of heat exhaustion is a real concern for athletes who are prescribed stimulants or other dopamine-enhancing medications such as bupropion. 5. Conclusions In summary, we need more research on all psychiatric disorders in athletes. However, based on the importance for this population and the extreme paucity of existing research we especially ª 2010 Adis Data Information BV. All rights reserved.

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need more research on OT syndrome, bipolar disorder, suicidality, anxiety disorders, ADHD and psychosis. We need to know more about the prevalence, risk factors, prognosis and the unique experiences facing athletes with these disorders. While physicians as a general rule should not purposefully provide their athlete patients with unfair performance advantages by prescribing ergogenic medications, they also do not want them to suffer unfair discrimination. Likewise, physicians want to be certain that the medications they are prescribing for their athlete patients are not only allowable by WADA standards but that they also are safe for use in athletic activity. We hope that more high quality, large studies of the use of psychotropic medications in athletes will be performed so that we can begin to answer these difficult questions more definitively. It would be particularly helpful to have studies that include sensitive performance measures, longer term use of psychotropics, athletes who actually have the psychiatric disorder for which the medication is designed and more women subjects. Acknowledgements The authors report no funding for the preparation of this review and no relevant conflicts of interest. Both authors made substantial contributions to this work and meet criteria for authorship. We thank the anonymous reviewers of this manuscript for their very helpful suggestions.

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Correspondence: Dr Claudia L. Reardon, University of Wisconsin Hospital and Clinics, Department of Psychiatry, 6001 Research Park Boulevard, Madison, WI 53719, USA. E-mail: [email protected]

Sports Med 2010; 40 (11)

Sports Med 2010; 40 (11): 981-990 0112-1642/10/0011-0981/$49.95/0

REVIEW ARTICLE

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The Effect of Playing Surface on Injury Rate A Review of the Current Literature Jason L. Dragoo and Hillary J. Braun Department of Orthopaedic Surgery, Stanford University, Palo Alto, California, USA

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Part 1: Grass and Artificial Field Surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Natural Grass. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 First-Generation Artificial Turf. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Second-Generation Artificial Turf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Third-Generation Artificial Turf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Part 2: Court Surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Grass. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Clay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Acrylic/Polyurethane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Wood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Part 3: Sport-Specific Surface Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 American Football . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Soccer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Tennis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Basketball . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

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Synthetic playing surfaces are widely used for field and court sports. Artificial turf surfaces are commonly used as an alternative to natural grass, while outdoor surfaces like clay and acrylic are also prevalent. The effect of these synthetic surfaces on injury rates has not been clearly established. The available literature is largely limited to football and soccer data and the majority of studies are short-term. Confounding variables such as climate, player position and footwear, as well as varying definitions of injury, also make it difficult to draw firm conclusions about the general effect of artificial playing surfaces on injury rates. Many peer-reviewed studies cite a higher overall rate of injury on first- and second-generation artificial turf surfaces compared with natural grass. Despite differences in injury type, the rate of injury on third-generation and natural grass surfaces appears to be comparable. It also appears that clay is significantly safer than either grass or hard court tennis

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surfaces, but this is a conclusion drawn with limited data. Further research investigating overall injury trends as well as sport-specific data is needed to draw more definitive conclusions regarding the effect of artificial playing surfaces on injury rates.

1. Introduction Artificial playing surfaces provide a costeffective, all-weather alternative to natural grass surfaces and are used today for a wide range of sports and activities. The varying physical characteristics of these surfaces have been thought to impact not only the pace and style of sports, but the observed injury patterns as well. Acrylic and clay courts were first used for tennis in the 1940s and 1950s, respectively, and are still used today as an alternative to grass courts. Artificial flooring has become a substitute for the traditional wooden floors of basketball and volleyball courts. Perhaps the most significant development occurred in the 1960s, when artificial turf surfaces first appeared as an alternative to natural grass fields. Artificial turf surfaces have continued to evolve over the past 50 years in an attempt to mimic the playing characteristics of natural grass. There are currently three generations of artificial turf, which are broadly defined by their physical characteristics. The first generation of artificial turf appeared in the late 1960s and was characterized by short pile length, minimal padding and high frictional coefficients. These surfaces were largely used for football, and they remained the primary artificial field surface until the 1980s when second-generation surfaces appeared, providing more cushion with longer pile length, rubber or sand infill and increased padding. Third-generation surfaces appeared in the late 1990s and further improved the padding, pile length and infill characteristics to provide increased cushion and minimize friction. The evolution of an alternative playing surface for field sports traditionally played on natural grass has raised many safety questions. This article reviews both epidemiological studies and injury data focused on addressing the difference in injury rates on artificial and natural playing ª 2010 Adis Data Information BV. All rights reserved.

surfaces. The peer-reviewed data is first presented by surface type to allow comparison of the effects of various playing surfaces, and secondly by sport to allow a sport-specific comparison. 2. Methods The PubMed database and Cochrane Library were searched between August 2008 and May 2009 using the following terms: ‘artificial playing surface’, ‘artificial turf + injury’, ‘artificial turf’, ‘football playing surface’, ‘soccer playing surface’, ‘tennis playing surface’ and ‘basketball playing surface’. Articles were initially excluded only if they did not relate to athletic injuries. The preliminary search yielded 106 relevant articles in the PubMed database and one relevant article in the Cochrane Library. With the exception of articles used for background and historical information, references were then deemed relevant if they met the following criteria: published in English, presented or referenced an epidemiological study or provided injury data and directly assessed and/or referenced the effect of playing surface on injury rate. The sources cited by these papers were then reviewed using the aforementioned criteria and the process was repeated. In total, 43 papers were referenced. Sports were selected based on the quantity of available literature; the bulk of published studies focus on soccer and American football. Articles examining injury rates in rugby, tennis and basketball are also present in the literature, but in significantly smaller numbers. Similarly, surfaces were also chosen according to literature prevalence. The most common artificial surfaces are those used as a substitute for natural grass fields, but studies on surfaces such as clay, acrylic/ polyurethane and wood that serve as artificial substitutes to court surfaces are present in limited quantities. Sports Med 2010; 40 (11)

Effect of Playing Surface on Injury Rate

Artificial turf surfaces are broadly categorized into three generations. Few papers explicitly state the generation of turf used, but manufacturing brand, date of study publication and explanation of physical characteristics were used to help classify the surfaces. Finally, review of the current literature reveals various definitions of injury. For the purpose of this paper, an injury is defined as an incident that occurs during training or competition that results in any amount of time loss from play. Using time loss as criteria ensures, at the very least, a baseline of perceived severity. Applying more stringent injury definitions to the available literature is not possible. Many papers independently define injury or include nuanced clauses with limited applicability. Articles with different injury definitions will be indicated within the manuscript. 3. Part 1: Grass and Artificial Field Surfaces Since the late 1960s, three generations of artificial turf have been developed in attempt to mimic the properties of natural grass and minimize the maintenance cost of playing surfaces. These surfaces have provided more cost-effective, allweather playing fields for sports such as soccer, football and rugby. 3.1 Natural Grass

Since the beginning of organized sporting competitions, natural grass has been viewed as the standard field surface. However, standardization of studies monitoring injury rates on natural grass surfaces is difficult due to the fact that natural surfaces are rarely uniform and are highly variable depending on environmental and temporal factors. Several studies have evaluated the effect of environmental variables on natural grass surfaces. Significantly lower rates of injury on grass during ‘wet/slippery’ conditions (1.7 injuries/game) were observed in high school football players when compared with ‘good’ field conditions (3.3 injuries/game).[1] Significantly higher rates of anterior cruciate ligament (ACL) injuries in the ª 2010 Adis Data Information BV. All rights reserved.

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Australian Football League (AFL) were reported at venues with drier grass.[2] Matches at sites with high evaporation rates due to increased temperatures and decreased humidity had a 2.8-fold greater risk of ACL injury, while matches at sites with low rainfall in the previous year had a 1.93fold greater risk of injury.[2] In contrast, another AFL study failed to find any significant correlation between ACL injury rates and ground hardness.[3] Primary grass type was also found to correlate significantly with injury rates.[4,5] Bermuda grass, characterized by a thick thatch layer, is predominantly found in areas with consistent temperatures >10C.[5] This is in contrast to rye grass, which has minimal thatch and is most prevalent in temperatures <10C.[5] ACL injuries in AFL players occurred up to 2.13 times more on Bermuda grass than on rye grass, which is thought to be due to the increased traction of football cleats on Bermuda grass caused by the thicker thatch layer.[5] Though grass fields vary widely, they are the standard with which artificial field surfaces are compared throughout this review. 3.2 First-Generation Artificial Turf

The first generation of artificial turf surfaces appeared in the late 1960s. The surface consisted of very short nylon fibres and was characterized by higher friction, stiffness and heat retention levels than natural surfaces. The emergence of ‘turf toe’ correlated with the more widespread use of artificial turf surfaces.[6-9] Higher incidences of prepatellar and olecranon bursitis were also reported to be associated with artificial surfaces in a 1973 survey of collegiate football players.[10] Early studies revealed higher overall rates of injury on these first generation surfaces.[11-16] In 1969, Bowers and Martin first found that the rates of football and ankle injuries were not lower after the installation of artificial turf compared with the rates prior to artificial surface installation, as insinuated by artificial turf manufacturers.[13] A similar study revealed significantly more abrasions and sprains on artificial surfaces.[15] Sports Med 2010; 40 (11)

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A study comparing injury rates on firstgeneration artificial turf and natural grass showed injury rates per game on artificial turf were significantly higher than those on natural grass (0.76 per game vs 0.52 per game).[14] This study also found the injury rate per game on dry artificial turf to be 0.93 per game, which was a significantly higher rate than on any other surface in wet or dry conditions.[14] A 1975–7 review of college football injury data from the National Athletic Injury/Illness Reporting System showed a significant correlation between play on firstgeneration artificial surfaces and increased rate of injury to both the knee and ankle compared with natural grass.[12] An additional study comparing injury rates on natural grass and Tartan Turf in intramural collegiate touch football found overall rates of injury to be significantly greater on Tartan Turf.[16] This study also confirmed that rates of minor injury on Tartan Turf were highest during wet conditions.[16] In a 1970 and 1971 high school football study comparing the injury rates on AstroTurf, designed using flat grass blades, and Tartan Turf, designed using round grass blades, both using different padding systems and pile composition, injury rates were significantly higher on AstroTurf (0.63 injuries/game) and significantly lower on Tartan Turf (0.28 injuries/game) when compared with grass (0.51 injuries/game).[11] All AstroTurf surfaces had significantly higher injury rates during dry games, and the Tartan Turf had significantly higher injury rates during wet games.[11] In summary, the overall injury rate appears to be higher on first-generation artificial turf compared with grass, which was mostly due to an increase in abrasions and lower extremity sprains.

3.3 Second-Generation Artificial Turf

Second-generation artificial turf first appeared in the early 1980s. These surfaces were typically filled with sand or another synthetic material and tended to have longer fibre lengths and thicker cushioning layers. Now used for field hockey and community centres, this generation of surfaces ultimately failed to meet international soccer ª 2010 Adis Data Information BV. All rights reserved.

surface standards set forth by the Federation Internationale de Football Association (FIFA). Several reports were published using surveillance data from National Football League (NFL) trainers and the NFL Injury Surveillance System (NFL ISS). Data from 1980 to 1985 showed significantly higher rates of injury on artificial turf when compared with natural grass surfaces.[17] Subsequent data from the 1980 to 1989 NFL ISS revealed significantly higher rates of knee sprains including medial collateral ligament (MCL) injuries in lineman, and ACL and knee sprains in the special teams units on artificial surfaces when compared with natural grass.[18] This data also showed rates of knee sprains per game to be significantly higher on artificial turf (0.22 injuries per game) when compared with natural grass (0.20 injuries per game)[18] and showed the overall injury rate for ankle sprains to be significantly higher on AstroTurf (0.18 injuries per games) when compared with natural grass (0.14 injuries per game).[19] A prospective cohort study of Canadian collegiate football players from 1993 to 1997 which was restricted to game injuries, found rates of lower extremity injuries to be twice as high on second-generation artificial surfaces compared with grass.[20] For teams that practised on natural grass, higher rates of head, neck and lower extremity injuries were present on secondgeneration surfaces.[20] A study of the pre-season conditioning programmes used by a collegiate football team from 1991 to 1995 showed that 35% of the athletes conditioning on only artificial turf developed a conditioning injury, compared with 13% of the athletes participating in both turf and swim conditioning.[21] The turf group experienced significantly more hamstring and quadriceps injuries than the turf and swim group.[21] More recently, a 1995–7 study of high school and collegiate football players reported that head contact with second-generation artificial turf was more likely to result in a Grade II concussion than contact with natural grass surfaces.[22] In contrast to the above data, there is one study which confirms an increased injury rate on grass. An analysis of injuries in the NFL from 1989 to 1993 showed non-contact ACL injuries Sports Med 2010; 40 (11)

Effect of Playing Surface on Injury Rate

during games were five times more likely on grass than second-generation artificial turf.[23] However, practice injuries revealed exactly the opposite pattern.[23] Another study using NFL data from 1989 to 1998 investigated the influence of both weather and surface variables on injury rates using indoor and outdoor stadium data. Knee and ankle sprains were less likely in outdoor venues at lower temperatures when compared with all domed venues as well as on grass compared with all artificial turf playing fields.[24] Overall injury rates for open artificial turf stadiums were lower than domed artificial stadiums.[24] The reduction in risk of ACL injury was also statistically significant for colder open second-generation artificial turf stadiums (<70F) compared with the same stadiums in warmer weather conditions (>70F).[24] Overall, the majority of second-generation artificial turf studies suggest higher rates of lower extremity injuries on artificial playing surfaces.[18,20-22] However, there is one study which shows higher injury rates on grass.[23] It is not clear whether the increased injury rate is due to footwear, environmental factors or the actual playing surface. 3.4 Third-Generation Artificial Turf

Third-generation surfaces began to appear in the late 1990s and early 2000s. These surfaces are characterized by longer fibre length, rubber synthetic infill and increased shock absorbency. A two-part study comparing injuries on natural grass and third-generation artificial turf surfaces using data from the National Collegiate Athletic Association Injury Surveillance System (NCAA ISS) was conducted during the 2005 and 2006 American soccer seasons. No significant differences were found for male or female players between the overall incidence of match injury on grass or artificial turf.[25] A significantly higher incidence of head/neck injuries was observed for men on artificial turf, though none of these were caused by player-surface contact.[25] The incidence of laceration/skin lesions was also significantly higher for men on artificial turf.[25] The ª 2010 Adis Data Information BV. All rights reserved.

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incidence of ankle sprains in women was significantly lower on artificial turf than on grass.[25] In part two of this study, the overall incidence of injury on artificial turf and natural grass did not differ significantly during practice and training.[26] Men incurred significantly more ankle, foot and joint injuries on artificial turf than on grass.[26] Conversely, joint injuries including ligament and cartilage lesions were significantly lower on artificial turf for women.[26] A 5-year prospective study between 1998 and 2002 comparing high school football injury rates on third-generation artificial turf and natural grass found a significantly higher incidence of muscle-tendon overload injuries and significantly greater amounts of abrasions, non-contact injuries, and running and sprinting injuries during temperatures of >70F on artificial turf.[27] Trends, though not statistically significant, included an increase of cervical strains on the third-generation artificial surface and an increase in concussions and ACL injuries on grass.[27] A prospective two-cohort study of Swedish soccer teams in the early 2000s found no statistically significant difference between overall rates of injury incidence on third-generation artificial turf when compared with natural grass.[28] The study did report a significantly higher risk of ankle sprains and a significantly lower risk of lower extremity muscle injuries on turf; however, these conclusions should be interpreted with caution due to a small sample size within injury subgroups.[28] Another prospective cohort study conducted in Norway with 2020 16-and-under female soccer players found that acute injury rates on second- and third-generation artificial turf surfaces and natural grass did not differ significantly in games or training sessions.[29] Though injury patterns may differ, it appears that there is not a significant difference between the overall injury rates on third-generation artificial surfaces and natural grass.

4. Part 2: Court Surfaces Sports involving competition on playing courts are also subject to variable surfaces. The Sports Med 2010; 40 (11)

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effect of artificial courts on injury rates has not been widely studied. 4.1 Grass

Tennis was invented in the late 19th century and initially played on natural grass. Typical courts are composed of seeded turf on a soil base. A 2007 study of incomplete matches in Grand Slam professional tennis tournaments from 1978 to 2005 did not present statistically significant results, but incomplete match numbers yield three trends pertaining to player-surface interaction as follows: fewer incomplete matches on grass courts; higher rates of incomplete matches on Australian hard courts than other surfaces for women; and a higher rate of incomplete matches on US hard courts for men.[30] 4.2 Clay

Clay courts became popular for use in tennis in the 1950s. This surface consists of layers of crushed stone topped with fine, gritty clay.[31] The gritty nature of clay courts creates a high frictional coefficient with the ball and the lowest frictional resistance with the player. Lower rates of knee problems have been observed in senior players who spent their careers on clay courts.[32] A study examining injury rates in professional male tennis players for 3 years on clay court, hard court, grass and carpet revealed injury treatment during match play was required most often on grass surfaces, and significantly more often on hard court than on clay, concluding that the risk of injury is higher on grass and hard court than clay.[33] 4.3 Acrylic/Polyurethane

Acrylic courts were introduced in the 1940s and have since become a popular tennis surface. These courts consist of an underlying asphalt or concrete base usually coated with rubber to offer increased shock absorption.[31] Acrylic courts are both the stiffest surface and the surface with the highest player-surface friction coefficient. A recent study of male tennis players revealed injury treatment to be significantly more likely on hard ª 2010 Adis Data Information BV. All rights reserved.

court than on clay, concluding the risk of injury to be significantly higher on hard court than on clay.[33] There is a higher rate of incomplete matches on Australian and US hard courts than on other surfaces for women and men, respectively.[30] 4.4 Wood

Wooden floors are common playing surfaces for indoor sports such as basketball, handball and floorball and are generally believed to have lower friction coefficients than their artificial counterparts. A 2003 study compared the ACL injury rate between wooden floors and floors with a rubber coating in team handball and found the rate of ACL injury in women to be significantly higher on artificial floors.[34] A 2008 study compared the injury rates in Finnish female floorball players on wooden floors and similarly coated rubber artificial floors. The overall risk of injury was found to be approximately twice as high on the artificial floors.[35] 5. Part 3: Sport-Specific Surface Comparisons In addition to surface-specific comparisons, sport-specific injury rates comparing relevant surface types have also been published. 5.1 American Football

Many of the studies evaluating artificial field surfaces use football data, with the bulk of these studies examining first- and second-generation artificial surfaces. Significantly higher rates of injury in football have been reported when comparing artificial and natural playing surfaces.[17-22,36] A study of high school football players found overall injury rates to be 1.6-fold higher on an unspecified artificial turf surface when compared with natural grass.[36] Lower extremity injuries in football games have been observed to be twice as high on artificial surfaces,[20] including higher rates of knee sprains in lineman and the special teams units as well as a higher rate of ankle sprains when competing on artificial turf.[18,19] Scranton et al. also reported the overall ACL injury Sports Med 2010; 40 (11)

Effect of Playing Surface on Injury Rate

rate (practice and game exposures combined) per team on artificial surfaces to be nearly twice that of natural grass.[23] These findings are in contrast to a subset of results presented by Scranton et al.,[23] which showed non-contact ACL injuries during games were five times more likely on grass. A separate study evaluating domed and open stadiums found the overall injury rates for open artificial turf stadiums were lower than domed artificial stadiums, with a statistically significant reduction in risk of ACL injury in open artificial turf stadiums.[24] Another study reviewed the injury rates of one professional football team from 1968 to 1985 and looked at differences in rates based on severity of injury. No statistically significant differences were found between artificial and natural grass surfaces for injuries.[37] Two remaining football studies revealed higher injury rates on artificial surfaces when compared with natural grass surfaces. Turf-only conditioning was reported to yield a 35% pre-season injury rate, compared with a 13% pre-season injury rate in the turf and swim conditioning group.[21] It has also been reported that out of the 10% of concussions that result from contact with a playing surface, contacts with artificial surfaces were more likely to result in a higher-grade concussion than contact with natural grass surfaces.[22] Collectively, these studies fail to provide a consensus about the effect of artificial playing surfaces on football injury rates. However, the majority of the studies demonstrate higher injury rates on artificial turf surfaces when compared with natural grass. Injury rates are not solely dependent on playing surface and can be influenced by shoe type, artificial surface brand, temporal and environmental factors. The conflicting results presented here highlight the variable nature of surface-related injuries and reinforce the need for more comprehensive studies on the effect of artificial playing surfaces on football injury rates.

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and natural grass. In a comprehensive report of collegiate soccer injury epidemiology, NCAA ISS data on men’s soccer showed 8% of game concussions resulted from player-surface contact.[38] Overall, 12.5% of ACL injuries resulted from contact with the playing surface.[39] Several studies found no overall difference in injury rates between turf and grass surfaces but noted significant differences in rates of injury sub-groups.[25,26,29] The incidence of lacerations was significantly higher for men on artificial turf,[25] while the incidence of ankle sprains in women was significantly lower on artificial turf than on grass.[25] Male players incurred significantly more foot and ankle injuries as well as ligament and cartilage injuries on third-generation artificial turf than on grass,[26] which is consistent with a Swedish soccer study which also noted a higher risk of ankle sprains observed during matches on artificial turf.[28] Conversely, ligament and cartilage injuries were significantly lower on artificial turf for female players.[26] This result is also supported by a Swedish soccer study, which noted a lower risk of lower extremity muscle injuries while competing on artificial turf.[28] A study of 16 and under Norwegian soccer players also found that acute injury rates on artificial turf and grass did not differ significantly in games or training sessions.[29] These studies are in contrast to a study of injury rates from five Icelandic elite soccer teams, which observed a significantly greater risk of overall injury on unspecified artificial surfaces when compared with natural grass.[40] The majority of studies evaluating the effect of artificial turf surfaces on soccer injury reveal no significant differences in overall injury rates when compared with natural grass. However, there is one study demonstrating contradictory results. It does appear that sex-specific injury patterns differ between the two playing surfaces.

5.3 Tennis 5.2 Soccer

The majority of soccer-specific data compares injury rates on third-generation artificial surfaces ª 2010 Adis Data Information BV. All rights reserved.

Overuse injuries are common in young tennis players[41] and have been linked with playing surface characteristics. Several studies have examSports Med 2010; 40 (11)

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ined the influence of playing surface on tennis injury including data which was compiled from 1978 to 2005 on incomplete matches in Grand Slam professional tournaments. While statistically significant results were not presented, three trends pertaining to player-surface interaction emerged as follows: (i) fewer incomplete matches occurred on grass courts; (ii) a higher rate of incomplete matches occurred on Australian hard courts than other surfaces for women; and (iii) a higher rate of incomplete matches occurred on US hard courts for men.[30] A separate study examining injury rates in professional male tennis players for 3 years on clay, asphalt, grass and carpet courts found that injury treatment was required most often on grass surfaces, and significantly more often on hard court than on clay.[33] Lower rates of knee problems have also been observed in senior players participating on clay surfaces.[32]

5.4 Basketball

NCAA ISS data on men’s basketball showed lower extremity injuries were the most common game injuries, with 20.9% of all game injuries resulting from contact with the surface.[42] In women’s basketball, 19.2% of all game injuries, including ankle ligament sprains, knee internal derangements, concussions and patellar problems, resulted from contact with the playing surface.[43] Currently, there is no available data comparing basketball injury rates on wooden floors and artificial floors.

6. Discussion Even though the purpose of this review was to examine the effect of playing surface on injury rate by presenting data from applicable peerreviewed studies, isolating and declaring ‘playing surface’ as the sole determinant of injury risk would be naive for several reasons. First, many factors ranging from environmental conditions to player position influence injury rates. Second, well constructed long-term studies that examine the relaª 2010 Adis Data Information BV. All rights reserved.

tionship between similar populations and playing surface are scarce. It is therefore difficult to determine the overall impact these surfaces have had on athletic injuries over the past 50 years. Third, available literature is heavily weighted towards studies observing injury rates in soccer and football players. These sports are both widespread and provide a large sample size, but the effect of artificial turf on injury rates in other sports such as rugby, lacrosse or field hockey is largely unknown. Similarly, the amount of injury data available for sports that are played on synthetic courts or indoor surfaces is minimal. Without this information, it is difficult to thoroughly assess the overall effect of these surfaces. Finally, there are significant study limitations and a general lack of uniformity among the papers referenced here. While this is inherent in any review, the subjectivity of injury definition as well as the potential for injuries to go unreported should not be overlooked. Athletic injury rates are a composite of many variables, ranging from environmental factors such as field conditions, shoe-surface interface and climate to sport-specific factors such as footwear, player position and skill level as well as musculoskeletal and biomechanical differences. Individually isolating these variables is difficult because of both the high variability and integrated nature. This review notes that in addition to surface type, surface dryness, environmental temperature and surface hardness play a significant role in the assessment of injury rates on both artificial and natural playing surfaces. On natural grass, lower rates of injury were observed under wet surface conditions when compared with dry conditions.[1,2] This trend was also observed on first-generation artificial turf surfaces.[11,14] Conversely, higher rates of injury were observed under increased environmental temperatures on natural grass[5] and second-[24] and third-generation artificial turf.[27] The effect of surface hardness is less clear, but given its dependence on environmental factors, it is thought to vary with the aforementioned variables. These observations suggest that the physical and environmental characteristics of both natural and artificial playing surfaces may influence injury rates as significantly as the Sports Med 2010; 40 (11)

Effect of Playing Surface on Injury Rate

type of surface itself. If similar trends are observed on both natural grass and artificial playing surfaces, then perhaps environmental factors play a more significant factor than initially anticipated. The current knowledge base could be significantly improved by further investigating the effect of these specific variables. Additionally, the current scope of artificial playing surface injury data is limited and would benefit from long-term studies evaluating injury rates on all three generations of artificial turf, greater numbers of studies on sports other than football and soccer and a more complete evaluation of indoor and court surfaces.

7. Conclusions Playing surface, sport and environmental conditions affect injury rates. The large numbers of contributing factors, as well as the varying definitions of injury, make it difficult to draw firm conclusions about the overall impact of artificial playing surfaces on injury rates. Additionally, the current knowledge base is limited in scope and focuses primarily on football and soccer injuries, yielding data that is not fully representative of all sports that utilize artificial surfaces. The studies reviewed here show that first- and secondgeneration turf surfaces are generally associated with significantly higher injury rates. They also suggest that the overall rate of injury on thirdgeneration artificial turf surfaces is similar to that of natural grass, despite differences in injury types. There also appears to be fewer injuries on wood and clay compared with artificial court surfaces but, again, this conclusion is drawn with limited data. Continued research into the effect of artificial playing surfaces on injury rates is imperative, especially as the surfaces continue to evolve to accommodate community and athletic needs. While some conclusions can be drawn from current studies examining surface-related injury, more studies are needed to help develop the next generation of artificial surfaces, which will hopefully lead to decreased injury rates compared with natural surfaces. ª 2010 Adis Data Information BV. All rights reserved.

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Acknowledgements No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interest that are directly relevant to the content of this review.

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17. Powell JW. Incidence of injury associated with playing surfaces in the National Football League 1980-1985. Athl Train 1987; 22 (3): 202-6 18. Powell JW, Schootman M. A multivariate risk analysis of selected playing surfaces in the National Football League, 1980 to 1989: an epidemiologic study of knee injuries. Am J Sports Med 1992 Nov-Dec; 20 (6): 686-94 19. Powell JW, Schootman M. A multivariate risk analysis of natural grass and Astroturf playing surfaces in the National Football League 1980-1989. Int Turfgrass Soc Res J 1993; 7 (23): 201-11 20. Hagel BE, Fick GH, Meeuwisse WH. Injury risk in men’s Canada West University football. Am J Epidemiol 2003 May 1; 157 (9): 825-33 21. Gorse K, Mickey CA, Bierhals A. Conditioning injuries associated with artificial turf in two preseason football training programs. J Athl Train 1997 Oct; 32 (4): 304-8 22. Guskiewicz KM, Weaver NL, Padua DA, et al. Epidemiology of concussion in collegiate and high school football players. Am J Sports Med 2000 Sep-Oct; 28 (5): 643-50 23. Scranton Jr PE, Whitesel JP, Powell JW, et al. A review of selected noncontact anterior cruciate ligament injuries in the National Football League. Foot Ankle Int 1997 Dec; 18 (12): 772-6 24. Orchard JW, Powell JW. Risk of knee and ankle sprains under various weather conditions in American football. Med Sci Sports Exerc 2003 Jul; 35 (7): 1118-23 25. Fuller CW, Dick RW, Corlette J, et al. Comparison of the incidence, nature and cause of injuries sustained on grass and new generation artificial turf by male and female football players. Part 1: match injuries. Br J Sports Med 2007 Aug; 41 Suppl. 1: i20-6 26. Fuller CW, Dick RW, Corlette J, et al. Comparison of the incidence, nature and cause of injuries sustained on grass and new generation artificial turf by male and female football players. Part 2: training injuries. Br J Sports Med 2007 Aug; 41 Suppl. 1: i27-32 27. Meyers MC, Barnhill BS. Incidence, causes, and severity of high school football injuries on FieldTurf versus natural grass: a 5-year prospective study. Am J Sports Med 2004 Oct-Nov; 32 (7): 1626-38 28. Ekstrand J, Timpka T, Hagglund M. Risk of injury in elite football played on artificial turf versus natural grass: a prospective two-cohort study. Br J Sports Med 2006 Dec; 40 (12): 975-80 29. Steffen K, Andersen TE, Bahr R. Risk of injury on artificial turf and natural grass in young female football players. Br J Sports Med 2007 Aug; 41 Suppl. 1: i33-7 30. Cross R. Grand Slam injuries 1978-2005. Med Sci Tennis 2006; 11 (1) [online]. Available from URL: http://www. stms.nl/index.php?option=com_content&task=view&id=521 &Itemid=350 [Accessed 2010 Aug 11]

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31. Miller S. Modern tennis rackets, balls, and surfaces. Br J Sports Med 2006 May; 40 (5): 401-5 32. Kulund DN, McCue III FC, Rockwell DA, et al. Tennis injuries: prevention and treatment. Am J Sports Med 1979; 7 (4): 249-53 33. Bastholt P. Professional tennis (ATP tour) and number of medical treatments in relation to type of surface. Med Sci Tennis 2000; 5 (2) [online]. Available from URL: http://www. stms.nl/index.php?option=com_content&task=view&id=881 &Itemid=263 [Accessed 2009 Apr 19] 34. Olsen OE, Myklebust G, Engebretsen L, et al. Relationship between floor type and risk of ACL injury in team handball. Scand J Med Sci Sports 2003 Oct; 13 (5): 299-304 35. Pasanen K, Parkkari J, Rossi L, et al. Artificial playing surface increases the injury risk in pivoting indoor sports: a prospective one-season follow-up study in Finnish female floorball. Br J Sports Med 2008 Mar; 42 (3): 194-7 36. Ramirez M, Schaffer KB, Shen H, et al. Injuries to high school football athletes in California. Am J Sports Med 2006 Jul; 34 (7): 1147-58 37. Nicholas JA, Rosenthal PP, Gleim GW. A historical perspective of injuries in professional football: twenty-six years of game-related events. JAMA 1988 Aug 19; 260 (7): 939-44 38. Dick R, Putukian M, Agel J, et al. Descriptive epidemiology of collegiate women’s soccer injuries: National Collegiate Athletic Association Injury Surveillance System, 1988-1989 through 2002-2003. J Athl Train 2007 Apr-Jun; 42 (2): 278-85 39. Agel J, Evans TA, Dick R, et al. Descriptive epidemiology of collegiate men’s soccer injuries: National Collegiate Athletic Association Injury Surveillance System, 1988-1989 through 2002-2003. J Athl Train 2007 Apr-Jun; 42 (2): 270-7 40. Arnason A, Gudmundsson A, Dahl HA, et al. Soccer injuries in Iceland. Scand J Med Sci Sports 1996 Feb; 6 (1): 40-5 41. Bylak J, Hutchinson MR. Common sports injuries in young tennis players. Sports Med 1998 Aug; 26 (2): 119-32 42. Dick R, Hertel J, Agel J, et al. Descriptive epidemiology of collegiate men’s basketball injuries: National Collegiate Athletic Association Injury Surveillance System, 1988-1989 through 2003-2004. J Athl Train 2007 Apr-Jun; 42 (2): 194-201 43. Agel J, Olson DE, Dick R, et al. Descriptive epidemiology of collegiate women’s basketball injuries: National Collegiate Athletic Association Injury Surveillance System, 1988-1989 through 2003-2004. J Athl Train 2007 Apr-Jun; 42 (2): 202-10

Correspondence: Jason L. Dragoo, Assistant Professor, Department of Orthopaedic Surgery, Stanford University, 450 Broadway, MC 6342, Redwood City, CA 94063, USA.

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