sports medicine Volume 40 Issue 8 August 2010

Sports Med 2010; 40 (8): 625-634 0112-1642/10/0008-0625/$49.95/0

LEADING ARTICLE

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Game, Set and Match? Substantive Issues and Future Directions in Performance Analysis Paul S. Glazier Centre for Sport and Exercise Science, Sheffield Hallam University, Collegiate Campus, Sheffield, UK

Abstract

This article discusses the main substantive issues surrounding performance analysis and considers future directions in this recently formed sub-discipline of sport science. It is argued that it is insufficient to bring together sport biomechanics and notational analysis on the basis that they share a number of commonalities, such as they both aim to enhance performance, they both make extensive use of information and communications technology, and both are concerned with producing valid and reliable data. Rather, it is suggested that the common factor linking sport biomechanics and notational analysis is that they can both be used to measure and describe the same phenomenon (i.e. emergent pattern formation) at different scales of analysis (e.g. intra-limb, inter-limb and torso, and inter-personal). Key concepts from dynamical system theory, such as self-organization and constraints, can then be used to explain stability, variability and transitions among coordinative states. By adopting a constraints-based approach, performance analysis could be effectively opened up to sport scientists from other sub-disciplines of sport science, such as sport physiology and psychology, rather than solely being the preserve of sport biomechanists and notational analysts. To conclude, consideration is given to how a more unified approach, based on the tenets of dynamical systems theory, could impact on the future of performance analysis.

The emergence of performance analysis as an independent sub-discipline of sport science in the last decade has provoked some debate among academics from the more established subdisciplines of sport physiology, sport psychology and sport biomechanics. The generally accepted conceptualization of performance analysis – that is, the bringing together of sport biomechanics and notational analysis[1-3] – has attracted frequent criticism from sceptics who have condemned it as a ‘marriage of convenience’ contrived to produce vocational pathways for applied sport biomechanists and notational analysts. Much of the

controversy appears to be centered on the rationale for combining sport biomechanics and notational analysis, the apparent ‘dumbing down’ of the theory and methods of biomechanics, and the fact that the current conceptualization of performance analysis offers limited scope and opportunity for other applied sport scientists, such as sport physiologists and psychologists, who would argue that they, too, are performance analysts. This article outlines the main substantive issues currently inhibiting progress in performance analysis. It should become clear that what is

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required is a unified multidisciplinary theoretical framework that not only brings together sport biomechanics and notational analysis more effectively, but one that also provides the scope and opportunity for the integration of ideas and theoretical concepts from other sub-disciplines of sport science, such as sport physiology and psychology. As it has already been proposed as a viable theoretical framework for both applied sport biomechanics[4,5] and notational analysis,[6,7] it can be argued that dynamical systems theory may offer even greater scope and potential for scientific endeavour in performance analysis. The common factor linking sport biomechanics and notational analysis is that they both can be used to measure and describe the same phenomenon (i.e. emergent pattern formation) at different scales of analysis (e.g. intra-limb, inter-limb and torso, and inter-personal) and that key concepts from dynamical system theory, such as selforganization and constraints, can be used to help explain stability, variability and transitions among coordinative states. To conclude, consideration is given to how a more unified approach, based on dynamical systems theory, could impact on the future of performance analysis. 1. Current Status and Substantive Issues in Performance Analysis Although a conclusive definition of performance analysis has yet to be formalized (see Hughes[8] for a commentary), it is generally regarded to be the symbiosis of sport biomechanics and notational analysis. Motor control has featured in more recent schematics of performance analysis (see figures 2 and 3 of Hughes[8]) but the rationale for doing so was not provided and the prevalence of its application in the extant literature since has been extremely limited. According to Bartlett[2,3] and Hughes and Bartlett,[1,9,10] the bringing together of sport biomechanics and notational analysis is predicated on a number of commonalities that the two sub-disciplines apparently share including (i) the aim of enhancing performance; (ii) the analysis of movements of sport performers; (iii) the extensive use of information technology and communications ª 2010 Adis Data Information BV. All rights reserved.

equipment; (iv) the provision of objective feedback to sport performers and their coaches; (v) the importance of producing valid and reliable data; (vi) the need to normalize, scale or nondimensionalize data; (vii) the use of ‘performance parameters’ or ‘performance indicators’ that are derived from theoretical models of performance; and (viii) the opportunity to exploit and apply more fully recent developments in artificial intelligence. Although Hughes and Bartlett should be applauded for attempting to conjoin notational analysis, which has traditionally been viewed as a methodology rather than a science, with the more traditional sub-discipline of sport biomechanics, it could be argued that the existence of these proposed commonalities, on their own, do not justify the formation of a new subdiscipline of sport science. There appears to be a number of problems related to the current conceptualization of performance analysis. First, the commonalities apparently shared by sport biomechanics and notational analysis are not unique to those subdisciplines. Academics from every sub-discipline of sport science are concerned with enhancing performance and producing valid and reliable data, and data normalization is commonplace, particularly in sport physiology (e.g. maximal . oxygen uptake [VO2max] per unit bodyweight, percentage of age-related maximum heart rate, percentage of one repetition maximum). The performance parameter or performance indicator concept also features strongly in both sport physiology and psychology research. For example, . VO2max and lactate threshold have both been shown to be key variables underpinning endurance performance[11,12] and a certain level of arousal has been shown to be necessary for optimal perceptuo-motor performance.[13,14] However, as discussed further and in more detail within this section, despite the widespread use of performance parameters or performance indicators in sport science, these variables do not significantly enhance our understanding and could be considered a concept of limited application. Second, although one can tentatively appreciate how sharing knowledge and experience may enrich the respective skills and enhance the career Sports Med 2010; 40 (8)

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prospects of applied sport biomechanists and notational analysts, it is less clear how doing so will actually help athletes and coaches to enhance performance. Bartlett[2] makes reference to a number of examples where sport biomechanics and notational analysis have been used successfully by various organizations and national governing bodies, as part of their sports science support programmes. Although it is not possible to comment on how effective this sport biomechanics and notational analysis support has been, it is debatable whether an increased knowledge and understanding of the theory and methods of notational analysis can actually help applied sport biomechanists, or vice versa, to provide more effective scientific support and, ultimately, to enhance performance. Of course, what this extra knowledge and experience does provide is the opportunity for sport biomechanists and notational analysts to service a much wider range of sports and clientele in a greater variety of contexts. The benefits to athletes and coaches, in contrast, are far less tangible. One practical outcome of performance analysis identified by Bartlett,[2,3] is that well chosen performance parameters can highlight good and bad sport techniques. However, as Lees[15] pointed out, performance parameters are derived from deterministic or hierarchical models of performance, not models of technique. The emphasis in these performance models is very much on the outcome rather than the causative mechanisms and processes underpinning the outcome. For example, in the hierarchical model of javelin throwing outlined by Morriss and Bartlett,[16] one of the most important performance parameters is release speed (see figure 1). Although some information regarding isolated aspects of technique believed to be mechanically related to this important performance parameter are provided, the model does not specify what movement patterns should be used to produce a high javelin speed at the moment of release. In addition, as elaborated further in this section, the efficacy of such models is challenged by evidence indicating that individual athletes scale and parameterize aspects of technique according to interacting constraints impinging on performance.[18] In ª 2010 Adis Data Information BV. All rights reserved.

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Range Release speed Speed generated in run-up and crossovers Force impulse applied to javelin Torque impulse applied by working muscles Effectiveness of block Sequence of muscle activation Body position at final foot strike Shoulder axis alignment Throwing arm elbow angle Javelin carry position Release angle Release angle of attack Release angle of yaw Release pitching moment Aerodynamic factors Fig. 1. A deterministic or hierarchical model of javelin throwing (reproduced from Morriss and Bartlett,[16] with permission from Adis, a Wolters Kluwer business ª Adis Data Information BV, 1996. All rights reserved). Although this model does not strictly conform to the criteria set out by Hay and Reid[17] for constructing these performance models, it does provide a useful indication of what mechanical factors might be most related to performance.

principle, many different movement patterns or more precisely coordination patterns, could be used to generate the same set of performance parameter values for any given motor skill (a phenomenon known as motor equivalence[19]). It could be suggested, therefore, that rather than adopting this type of reductionist, nomothetic (inter-individual) product-oriented approach, a more holistic, idiographic (intra-individual), process-oriented approach emphasizing the analysis of emergent patterns of coordination and control underpinning performance in specific individuals, might be more profitable (see McGarry[20] for a similar discussion of the need to link sports behaviours to outcomes). Indeed, Davids Sports Med 2010; 40 (8)

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et al.[21] argued that this type of analytical approach could form a significant component of scientific programmes for talent identification and skill development in soccer. However, as discussed further in this section, due to the limitations of the video analysis technology habitually used by performance analysts, this strategy may be difficult to implement. Another more general problem with the performance parameter or performance indicator concept is that it promotes only a very rudimentary understanding of human motor performance. For example, it is somewhat self-evident that a high release speed is a prerequisite for proficient javelin throwing performance. Like. wise, a large VO2max is a prerequisite for adept performance in endurance athletic events. However, reducing human motor performance to a small number of measurable outcome variables belies the enormous complexity of the biomechanical, physiological and psychological processes underlying performance. Accurate prediction of human motor performance for a given task at a given time is far from straightforward because of the existence of complex, non-linear interactions between the many independent component parts of the human movement system at different levels of the system. In principle, small-scale changes at a more microscopic level of the system (e.g. molecular, cellular, neuromuscular) can have a large-scale impact at a more macroscopic level (e.g. behavioural, biomechanical, psychological).[22-24] Furthermore, not only is the current state of the human movement system important, environmental conditions and the specific requirements of the task being undertaken are also influential in shaping and guiding the ensuing patterns of coordination and control.[18] Third, there appears to be increasing concern, particularly amongst more traditional sport biomechanists, regarding the apparent ‘dumbing down’ of the theory and methods of biomechanics. Perhaps the most contentious issue is that ‘coach-friendly’ video analysis packages habitually used by performance analysts, are being used in a capacity far beyond for which they were designed. Software applications, such as ª 2010 Adis Data Information BV. All rights reserved.

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Quintic (Quintic Consultancy Ltd, Coventry, UK; www.quintic.com) and siliconCOACH (siliconCOACH, Dunedin, New Zealand; www. siliconcoach.com) are useful for planar semiquantitative analyses and frame-by-frame or split-screen video playback, but they are no substitute for purpose-built, image-based or markerbased motion capture systems. As recommended above in this section, performance analysts need to dedicate much greater attention to measuring and analysing patterns of intra-limb and interlimb coordination and control rather than just focusing on the time-discrete performance parameters most related to the performance outcome. However, only the most sophisticated automated motion capture systems can produce sufficiently large and accurate time-continuous datasets to construct variable-variable plots (e.g. angle-angle plots, phase-plane portraits) and apply various coordination (e.g. continuous relative phase, cross-correlations, vector coding) and variability measures (e.g. standard deviation, coefficient of variation, normalized root-mean-square, transentropy).[25-30] Another concern that has been aired frequently by sceptics is that much of the work being conducted in performance analysis lacks sound theoretical rationale and, consequently, is descriptive rather than explanatory. Over the years a similar criticism has been directed, with some justification, at applied sport biomechanics research.[31-34] One of the main problems has been that empirical studies in sport biomechanics have seldom moved beyond the kinematic level of analysis. However, to fully understand the causative mechanisms underpinning performance, sport biomechanists need to focus much more on the kinetic level of analysis.[35] As it is virtually impossible to make inferences about the underlying kinetics from the kinematics, complex inverse dynamics analyses have been used to examine net joint torques and reaction forces, and mechanical work and power transfers among joints.[36] Although inverse dynamics analyses are still comparatively rare and somewhat hypothetical in nature,[37] they at least enable sport biomechanists to explore the causative mechanisms that underpin performance and explain them Sports Med 2010; 40 (8)

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using the fundamental theoretical laws and principles of Newtonian and Euler mechanics. Due to the complexity of inverse dynamics analyses, combined with the need to use sophisticated force measuring equipment (usually in a controlled environment) and the need to acquire athlete-specific anthropometric (geometric and inertia) data, it is unlikely that performance analysts will be able to implement this type of analysis. Furthermore, it is unlikely whether athletes and coaches will be able to relate well to concepts such as ‘net joint torques’ and ‘mechanical power transfers’. Perhaps a more effective approach would be to analyse and explain the underlying processes of coordination and control at the kinematic level of analysis using the analytical tools and theoretical concepts of dynamical systems theory, respectively, particularly given that athletes and coaches use relative motion information about the limbs and the torso when making judgements about sports techniques.[38] As discussed in more detail in section 2, one of the advantages of adopting a dynamical systems framework is that it can be used to explain stability, variability and transitions between coordinative states in any complex system irrespective of the material composition of that system – that is, the same theoretical concepts governing intra-limb and inter-limb coordination also govern inter-personal coordination.[39,40] For this reason, combined with the fact that it has been closely linked already with applied sport biomechanics[4,5] and notational analysis,[6,7] dynamical systems theory would appear to be an ideal theoretical framework for performance analysis. Fourth, performance analysis appears to be almost exclusively the preserve of sport biomechanists and notational analysts with very limited scope and opportunity for sport physiologists and psychologists. This state of affairs appears to have been perpetuated by remarks that sport physiologists and psychologists are only really concerned with the preparation of sport performers for competition.[1] However, given the fact that sport physiologists and psychologists must analyse and evaluate performance to establish the effectiveness of, and make subª 2010 Adis Data Information BV. All rights reserved.

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sequent modifications to, any strength and conditioning programmes, psychological interventions or coping strategies that they might have administered, it could be argued that they too must also be performance analysts. However, one of the problems preventing sport physiologists and psychologists from becoming more involved in performance analysis is that the affect of key physiological and psychological factors, such as fatigue and anxiety, on the processes underpinning performance, is not well understood.[41,42] Of course, anyone who has been involved in sport knows that fatigue and anxiety tend to cause decrements or errors in performance outcome (e.g. speed and accuracy), but how do these decrements come about? How does fatigue and anxiety impact on patterns of intra-limb and inter-limb coordination and control when executing kicking, throwing or striking actions? Furthermore, how does fatigue and anxiety affect patterns of inter-personal coordination in a game, match or contest? In summary, it can be argued that the current formulation of performance analysis is rather illconceived and that much stronger rationale for linking sport biomechanics and notational analysis is necessary if performance analysis is to survive and prosper as an independent academic sub-discipline of sport science. The real link between sport biomechanics and notational analysis is not, or should not be, the fact that they share a number of rather tenuous commonalities, but because they both can be used to measure and describe the same phenomenon (i.e. emergent pattern formation) at different scales of analysis (e.g. intra-limb, inter-limb and torso, and interpersonal). Performance analysts must focus much more on the processes of coordination and control underpinning the performance outcome and not just the performance outcome itself. However, merely describing patterns of coordination and control is unlikely to make a significant impact on performance analysis. What is required is a multidisciplinary theoretical framework that explains stability, variability and transitions among coordinative states, and one such candidate with an excellent pedigree in science is dynamical systems theory. Section 2 provides a brief Sports Med 2010; 40 (8)

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overview of the basic tenets of dynamical systems theory and outlines how key concepts, such as self-organization and constraints, can be applied to performance analysis. 2. Modelling Emergent Pattern Formation in Sport at the Individual and Team Level: Applications of Dynamical Systems Theory What do individual sports performers executing goal-directed movements and a team of sports performers participating in a game, match or contest have in common? The answer is that they both can be conceptualized as complex non-linear dynamical systems. In general, non-linear dynamical systems are those physical, chemical, biological or social systems that exhibit many independent component parts or degrees of freedom that are free to vary over space and time. These complex systems are typically open systems that operate under conditions that are said to be far from thermodynamic equilibrium; that is, they are capable of interacting with the environment and are in a constant state of flux due to changes in internal and external energy flows.[43-45] Despite the enormous potential for disorder, complex nonequilibrium dynamical systems are able to exploit these energy flows and the surrounding constraints to form orderly and stable relationships among the many degrees of freedom at different levels of the system.[46-48] However, rather than being pre-planned or prescribed by an intelligent executive or external regulating agent, these functional coordinative states, or attractor states in dynamical systems language, emerge spontaneously through ubiquitous processes of physical self-organization.[49-51] Once assembled into an attractor state, degrees of freedom operate autonomously and in self-regulatory fashion due to being functionally, rather than mechanically, coupled together. The ‘soft assembly’ of system degrees of freedom means that if any of the many individual degrees of freedom are perturbed by internal or external influences, the other degrees of freedom adjust their relative contribution, thus preserving system output.[52,53] ª 2010 Adis Data Information BV. All rights reserved.

A research strategy commonly adopted by human movement scientists studying pattern formation in complex neurobiological systems is the ‘synergetic strategy’.[49,54,55] This approach, based on the pioneering work of Haken[56] in the field of synergetics, involves the identification of collective variables or ‘order parameters’ that define stable and reproducible relationships among degrees of freedom and ‘control parameters’ that move the system through its many different coordinative states. As Kelso[51] noted, order parameters and control parameters are the ‘‘yin and yang’’ of the synergetic approach – they are ‘‘separate but intimately related’’ (page 45). In neurobiological systems, relative phase has been the primary, if not the only, order parameter identified to date[57,58] and oscillatory frequency has typically been considered to be an important control parameter.[51,59,60] When an attractor state is adopted, order parameter dynamics have been shown to be highly ordered and stable, reflecting the capacity of the system to produce consistent and reproducible patterns of coordination.[59,60] As control parameters increase towards a critical value, variability of order parameter dynamics typically increases until stability is lost, leading to a non-equilibrium phase transition and the adoption of a new attractor state. The main emphasis of the synergetic strategy has been to identify candidate control parameters and systematically manipulate or scale them through their full range and observe concomitant changes in order parameter dynamics and other related non-linear phenomena. The synergetic strategy has been successfully applied to empirical analyses of within-individual coordination[61,62] and between-individual coordination.[63,64] 2.1 The Role of a Constraints-Based Approach and the Future of Performance Analysis

As outlined in section 2, the synergetic strategy has been integral to many experimental investigations into pattern formation both within and between individuals.[61-64] However, just as coaches and athletes might struggle to comprehend complex biomechanical concepts like ‘net Sports Med 2010; 40 (8)

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joint torques’ and ‘mechanical power transfers’, specialist terminology from the field of synergetics such as ‘control parameters’, ‘order parameters’, ‘bifurcations’ and ‘non-equilibrium phase transitions’ could be equally baffling. Indeed, it would appear that even some academics have had difficulty understanding the technical jargon and are sceptical about whether this approach is ready to make a practical contribution to sport.[65] A possible alternative approach that has received some exposure in the sport and human movement science literature, which could be useful in performance analysis, is the ‘constraintsbased’ approach. This approach, based on the widely cited constraints framework introduced by Newell[18] and championed largely by Davids and colleagues,[66-69] was originally conceived to help explain emergent pattern formation in single-agent neurobiological systems (i.e. intrapersonal coordination) but could, in principle, be useful in helping to provide important insights into emergent pattern formation in multi-agent neurobiological systems (i.e. inter-personal coordination). This approach proposes that pattern formation in neurobiological systems emerges from the confluence of competing and cooperating physical and informational constraints impinging on the system. These constraints coalesce to shape coordinative states not by prescribing them but by channelling the search towards optimal movement solutions. According to Newell,[18] the constraints on performance originate from one of three sources: the organism, environment or task. Organismic constraints are those that are internal to the neurobiological system and can be classified as being either structural or functional. Structural organismic constraints tend to change very slowly over time and include factors such as age, height, body mass, muscle fibre composition and genetic make-up, among others. Functional organismic constraints, in contrast, have a more rapid rate of change and include factors such as the onset of fatigue, anxiety levels and emotional state. The intentions of individual athletes are also an important functional organismic constraint on performance.[51] Environmental constraints ª 2010 Adis Data Information BV. All rights reserved.

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are those that are external to the neurobiological system. Examples of important environmental constraints in sport are weather conditions, ambient light and temperature, altitude, crowd influence, the frictional and stiffness characteristics of playing surfaces and the dimensions of the playing area. The relative positioning of defenders to one another and their proximity to the target area (e.g. goal, try-line or basket) have been shown to be important environmental constraints in the symmetry-breaking behaviour of attackers in team sports.[70] Task constraints are more specific to the task at hand and are related to the goal of the task and the rules that govern the task.[22] The need to score goals or points or defend a lead are key task constraints in sport. Instructions and tactics issued by the coaching staff or team captain can also be considered as major task constraints. Recent advances in player tracking technology could help establish the affect of different constraints on pattern formation among individuals in a game, match or contest. Although player tracking systems such as Prozone (Prozone Sports Ltd, Leeds, UK; www.prozonesports. com) and TRAKUS (TKS Inc., MA, USA; www.trakus.com) are still relatively new and not without limitation (see Barris and Button[71] for a state of the art review), they do have enormous potential, especially if interfaced or synchronized with other performance-monitoring technologies (e.g. heart rate monitors), for mapping spatiotemporal relationships among individuals under different organismic, environmental and task constraints. For example, in rugby union, it would be informative for coaches to establish how attacking and defensive formations change during the course of a match as specific individuals get fatigued, if weather conditions deteriorate or if the specific requirements of the game change as the final whistle nears. The data produced by these player tracking systems could be used to inform tactical decision making, direct technical development strategies and prescribe modifications to strength and conditioning programmes. Although less formal and not as mathematically rigorous as the synergetic approach, the constraints-based approach is arguably more versatile and likely to Sports Med 2010; 40 (8)

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be more comprehensible to athletes and coaches seeking to understand pattern formation within and between individuals in a sporting contest. 3. Conclusion The common factor linking sport biomechanics and notational analysis is that they can both be used to measure and describe the same phenomenon (i.e. emergent pattern formation) at different scales of analysis (e.g. intra-limb, inter-limb and torso, and inter-personal) and that key concepts from dynamical system theory, such as selforganization and constraints, can be used to help explain stability, variability and transitions between coordinative states. The adoption of dynamical systems theory as the basis of performance analysis is a logical progression given that it has previously been suggested to be a viable theoretical framework for both applied sport biomechanics[4,5] and notational analysis.[6,7] However, rather than adopting a research approach based on the ‘synergetic strategy’[49,54,55] as has typically been the case in empirical analyses of pattern formation both within and between individuals, a constraints-based approach[18] might be more appropriate, particularly in an applied context, given that it is likely to be more comprehensible by athletes and coaches. The utility of this approach has already been demonstrated in applied sports biomechanics[72] and motor control and learning[73] research, but further research is necessary to establish its utility in notational analysis. Acknowledgements No sources of funding were used to assist in the preparation of this article. The author has no conflict of interest that is directly relevant to the content of this article.

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39. Haken H, Wunderlin A. Synergetics and its paradigm of selforganization in biological systems. In: Whiting HTA, Meijer OG, van Wieringen PCW, editors. The naturalphysical approach to movement control. Amsterdam: Free University Press, 1990: 1-36 40. McGarry T, Franks IM. System approach to games and competitive playing: reply to Lebed (2006). Eur J Sport Sci 2007; 7: 47-53 41. Weinburg RS. Anxiety and motor performance: where to from here? Anxiety Res 1990; 2: 227-42 42. Rodacki ALF, Fowler NE, Bennett SJ. Multi-segment coordination: fatigue effects. Med Sci Sports Exerc 2001; 33: 1157-67 43. Kugler PN, Turvey MT. Information, natural law, and the self-assembly of rhythmic movement. Hillsdale (NJ): Lawrence Erlbaum Associates, 1987 44. Thelen E, Smith LB. A dynamic systems approach to the development of cognition and action. Cambridge (MA): MIT Press, 1994 45. Wallace SA. Dynamic pattern perspective of rhythmic movement: an introduction. In: Zelaznik HN, editor. Advances in motor learning and control. Champaign (IL): Human Kinetics, 1996: 155-94 46. Kugler PN. A morphological perspective on the origin and evolution of movement patterns. In: Wade MG, Whiting HTA, editors. Motor development in children: aspects of coordination and control. Dordrecht: Martinus Nijhoff, 1986: 459-525 47. Kaufmann SA. The origins of order: self-organization and selection in evolution. New York: Oxford University Press, 1993 48. Clark JE. On becoming skillful: patterns and constraints. Res Q Exerc Sport 1995; 66: 173-83 49. Kelso JAS, Scho¨ner G. Self-organization of coordinative movement patterns. Hum Mov Sci 1988; 7: 27-46 50. Beek PJ, Peper CE, Stegeman DF. Dynamical models of movement coordination. Hum Mov Sci 1995; 14: 573-608 51. Kelso JAS. Dynamic patterns: the self-organization of brain and behavior. Cambridge (MA): MIT Press, 1995 52. Kay B. The dimensionality of movement trajectories and the degrees of freedom problem: a tutorial. Hum Mov Sci 1988; 7: 343-64 53. Latash ML, Scholz JP, Scho¨ner G. Motor control strategies revealed in the structure of motor variability. Exerc Sport Sci Rev 2002; 30: 26-31 54. Kelso JAS, Scho¨ner G, Scholz JP, et al. Nonequilibrium phase transitions in coordinated movements involving many degrees of freedom. Ann N Y Acad Sci 1987; 504: 293-96 55. Scho¨ner G, Kelso JAS. A synergetic theory of environmentally-specified and learned patterns of movement coordination: I. Relative phase dynamics. Biol Cyber 1988; 58: 71-80 56. Haken H. Synergetics: an introduction. Non-equilibrium phase transitions and self-organization in physics, chemistry and biology. 3rd ed. Berlin: Springer, 1983 57. Michaels C, Beek P. The state of ecological psychology. Ecol Psych 1995; 7: 259-78 58. Summers JJ. Has ecological psychology delivered what it promised? In: Summers JJ, editor. Motor behavior and

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human skill: a multidisciplinary approach. Champaign (IL): Human Kinetics, 1998: 385-402 Kelso JAS. Phase transitions and critical behaviour in human bimanual coordination. Am J Physiol Regul Integr Comp Physiol 1984; 246: R1000-4 Haken H, Kelso JAS, Bunz H. A theoretical model of phase transitions in human hand movements. Biol Cyber 1985; 51: 347-56 Kelso JAS, Buchanan JJ, Wallace SA. Order parameters for the neural organization of single, multijoint limb movement patterns. Exp Brain Res 1991; 85: 432-44 Kelso JAS, Jeka JJ. Symmetry breaking dynamics of human multilimb coordination. J Exp Psychol Hum Perc Perform 1992; 18: 645-68 Schmidt RC, Carello C, Turvey MT. Phase transitions and critical fluctuations in the visual coordination of rhythmic movements between people. J Exp Psychol Hum Perc Perform 1990; 16: 227-47 Schmidt RC, O’Brien B, Sysko R. Self-organization of between-persons cooperative tasks and possible applications to sport. Int J Sport Psychol 1999; 30: 558-79 Hopkins W. Sport performance at the Oslo Conference of the European College of Sport Science. Sportscience 2009; 13: 28-32 [online]. Available from URL: http://www. sportsci.org/2009/wghECSS.htm [Accessed 2009 Sep 1] Arau´jo D, Davids K, Bennett SJ, et al. Emergence of sport skills under constraints. In: Williams AM, Hodges NJ,

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editors. Skill acquisition in sport research, theory and practice. London: Routledge, 2004: 409-33 Davids K, Button C, Bennett S. Dynamics of skill acquisition: a constraints-led approach. Champaign (IL): Human Kinetics, 2008 Davids K, Arau´jo D, Shuttleworth R, et al. Acquiring skill in sport: a constraints-led perspective. Int J Comp Sci Sport 2003; 2: 31-9 Handford C, Davids K, Bennett S, et al. Skill acquisition in sport: some applications of an evolving practice ecology. J Sport Sci 1997; 15: 621-40 Passos P, Arau´jo D, Davids K, et al. Interpersonal dynamics in sport: the role of artificial neural networks and 3-D analysis. Behav Res Meth 2006; 38: 683-91 Barris S, Button C. A review of vision-based motion analysis in sport. Sports Med 2008; 38: 1025-43 Seifert L, Chollet D, Rouard A. Swimming constraints and arm coordination. Hum Mov Sci 2007; 26: 68-86 Davids K, Bennett S, Handford C, et al. Acquiring coordination in self-paced extrinsic timing tasks: a constraintsled perspective. Int J Sport Psychol 1999; 30:437-61

Correspondence: Paul S. Glazier, Centre for Sport and Exercise Science, Sheffield Hallam University, Collegiate Campus, Sheffield, S10 2BP, UK. E-mail: [email protected]

Sports Med 2010; 40 (8)

Sports Med 2010; 40 (8): 635-655 0112-1642/10/0008-0635/$49.95/0

REVIEW ARTICLE

ª 2010 Adis Data Information BV. All rights reserved.

The Role of Physiology in the Development of Golf Performance Mark F. Smith Department of Sport, Coaching and Exercise Science, University of Lincoln, Lincoln, UK

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. The Paradox of Golf: Why does One Need to be Physically Fit to Play Golf? . . . . . . . . . . . . . . . . . . . 2. Macro Aspects of Golf Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Micro Aspects of Golf Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Role of Physiology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. A Multidimensional Approach to Golf Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. The Physical Requirements of Golf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 On-Course Physical Demands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.1 Cardiorespiratory Demands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Metabolic and Hormonal Response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.3 Musculoskeletal Demands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.4 Energy Expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.5 Nutritional Requirements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.6 Impact of Fatigue on Decision Making. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7. Physical Attributes of the Golfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Aerobic Fitness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Anaerobic Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Functional Strength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Flexibility and Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Podiatric Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Visual Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8. Player Profiling and Training Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Effective Physical Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Physical Training to Improve Golf Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9. Long-Term Monitoring for Performance Success . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10. Physical Development Model for Golf. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11. Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

635 637 637 637 637 639 640 641 641 642 643 643 643 644 644 645 645 645 646 647 647 648 648 648 650 651 652

The attainment of consistent high performance in golf requires effective physical conditioning that is carefully designed and monitored in accordance with the on-course demands the player will encounter. Appreciating the role that physiology plays in the attainment of consistent performance, and how a player’s physicality can inhibit performance progression, supports the notion that the application of physiology is fundamental for any player wishing to excel in golf. With cardiorespiratory, metabolic, hormonal, musculoskeletal and nutritional demands acting on the golfer within and between rounds, effective physical screening of a player will ensure physiological and anatomical

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deficiencies that may influence performance are highlighted. The application of appropriate golf-specific assessment methods will ensure that physical attributes that have a direct effect on golf performance can be measured reliably and accurately. With the physical development of golf performance being achieved through a process of conditioning with the purpose of inducing changes in structural and metabolic functions, training must focus on foundation whole-body fitness and golf-specific functional strength and flexibility activities. For long-term player improvement to be effective, comprehensive monitoring will ensure the player reaches an optimal physical state at predetermined times in the competitive season. Through continual assessment of a player’s physical attributes, training effectiveness and suitability, and the associated adaptive responses, key physical factors that may impact most on performance success can be determined.

Golf, as a sporting pursuit, requires the player to undertake a range of physically demanding movement patterns throughout the course of play.[1] The player must be able to cope with stressors that affect the physiological process of movement within various situational and environmental contexts during each competitive round. Depending on the specific requirements encountered on-course, the golfer must optimally organize and create complex swing movements repetitively in order to maximize scoring opportunities.[2] While the need for such invariance in technique across all swings for a number of key discrete golf swing positions has recently been demonstrated,[3,4] dynamical systems theory does suggest that high-level performance in sports like golf would benefit from some degree of functional variability in non-key swing positions.[5] Such findings reveal that the summation of movement requires a multifactorial approach to performance, which encompasses physical, mental, tactical and technical attributes.[3] Energetically, golf necessitates the interplay between biochemical, neurological, endocrinological and muscular functioning, allowing for the execution of each individual shot. The aim of this review is to elucidate the important role physiology plays in the development of the golf player. By describing the demands the golfer encounters throughout the course of play, the characteristics inherent in proficient players can be examined and compared with those of lower ability. By further examining factors that contribute to optimized physical status of the player, strategies can be developed to assist both ª 2010 Adis Data Information BV. All rights reserved.

player and coach in the enhancement of this fundamental aspect of golf success. Finally, to assist coaches, trainers, players and scientists in identifying and monitoring progress to maintain motivation and advance performance throughout training and competition, the evolvement of a physical-development framework for performance enhancement is presented. Where gaps in the golf-related literature exist, evidence from the wider sports science literature is included to advance applied knowledge and understanding. It is not the intention of this review to discuss or outline in detail the technical or biomechanical aspects of the swing characteristics; therefore, interested readers are directed to comprehensive reviews by Hume et al.,[1] Jorgensen,[6] and Peary and Richardson.[7] Nevertheless, an understanding of how the physical aspects affect overall player success is examined, allowing for the development of more multidisciplinary approaches to player movement optimization and competition performance maintenance. For the purposes of this review, original and review articles from 1988 to the present were considered by the author. Prior to this date, it was viewed that golf-related research lacked methodological suitability. A literature search of conference proceedings was performed (e.g. World Science Congress of Golf-Science and Golf: 1990–2008), SportDiscus, MEDLINE and ScienceDirect databases, and the internet (i.e. Google Scholar), using the keywords ‘golf’, ‘physical fitness’, ‘exercise’ and ‘physiology’ to identify Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

relevant articles. Manual searches were also performed by searching through article reference lists. 1. The Paradox of Golf: Why does One Need to be Physically Fit to Play Golf? Golf is perceived as a relatively gentle game in which the physiological demands are not particularly demanding. From a less-informed perspective, success in golf is seen to be more about the technical, tactical and mental aspects rather than the physical. By viewing the range of physiques and associated fitness levels golfers exhibit, one can begin to see why this view has developed. The physical fitness of the golfer, historically, has not appeared to be of that much importance. Consider, however, the repetitive acceleration and deceleration of the body during the golf swing. Combined with repeated compression and rotational torsion of the spine, and shearing around the joints, one can begin to identify that from a global position, the physiological demands of golf seem no different from that of walking. From a skeletal and muscle functioning perspective, however, substantial physical stress is applied. Taken that over 2000 swings are being performed by the tournament professional through practice and competition each week,[8] and up to 300 powerful movements per practice session,[9] plus competitions lasting up to 4 days in demanding environmental conditions, one can begin to appreciate the importance of physical fitness to golf performance. With the advent of golf science, technological changes and players looking for an edge over their competitors, the addition of physical conditioning training into a golfers practice schedule has revealed the importance of the physically fit golfer. With growing evidence suggesting that the physical fitness of the highly proficient player is somewhat different from that of a lower ability player,[10] attention has been given to the role physical fitness and physical conditioning can play in developing golf performance. 2. Macro Aspects of Golf Performance From a physical perspective, golf can be viewed from two levels. From a ‘macro’ aspect of ª 2010 Adis Data Information BV. All rights reserved.

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performance, operationally defined as all physical movements that occur outside the executed golf swing, the ability to walk the course with minimal impact on the mental and/or technical proficiency of the player promotes optimal execution of individual shots. The time taken to complete a round and the movement demands in between each shot can affect the physical stability of the player throughout the course of play.[11] In studies that have measured total walking distance over the course of 18 holes, the actual distance covered in relation to measured course length was on average 38% longer, equating to an extra 2.32 km travelled.[10-12] Taking this into account, the ‘macro’ aspects of golf performance, although not physiologically demanding, can have a meaningful impact on the physical condition whilst performing each swing. 3. Micro Aspects of Golf Performance Remaining in a stable state throughout these in-between periods ensures the performer is capable of attaining the desired outcome through the ‘micro’ physical aspect of performance. This is operationally defined as all physical movements that occur during the execution of the golf swing. Occurring in <1.3 seconds to impact,[13] the physiological chain of events that bring about the dynamism of the golf swing, irrespective of the shot type, characterizes the main acute physical demands acting on the golfer. Given that a highly proficient player will shoot around 70–76 shots per round, 91–99 seconds is all that is required to perform at this micro level of movement. Given that round times can extend up to 5–6 hours on the professional tours, around 0.5% of time during a tournament round will be spent executing golf shots. Despite such a small amount, the importance of this defines the success or failure of the player. 4. Role of Physiology To achieve consistent performance throughout a round of golf, one might consider the value of a stable physiological state. Accordingly, a player/coach would consider a training programme and nutritional strategy that promotes such a Sports Med 2010; 40 (8)

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stable physiological state within a round and across days. An understanding of such a state and how it affects movement potential will provide the coach with a valuable awareness as to the importance of correct preparation and maintenance throughout player development. Appreciating the role that physiology plays in the attainment of technical excellence and how a player’s physicality can inhibit performance progression supports the notion that physiology should be a fundamental area of focus for any player wishing to excel in golf. In viewing player optimization from a multidisciplinary perspective, the role of physiology should be seen as equally important as other contributing factors. Technical, tactical, mental and life skills will affect and be influenced by the physiological status of the player.[3] For the coach or player who does not acknowledge and integrate physiological aspects of performance into their development plan, the chances of reaching optimal movement capabilities will not be realized.

Segmental mobility

Although, in the broadest of sense, physiology of movement is concerned with the understanding of how physical activity alters biological systems during and immediately after movement, as well as in response to physical training,[14] wider aspects contribute to a more holistic appreciation of the impact this area has in understanding how golf performance can be optimized. Anatomical characteristics, body composition, movement measurement and evaluation, nutrition, ergogenic aids, mechanisms of fatigue and environmental stresses[15] are factors that to one extent or another affect technical aspects of movement, tactical and mental approaches within and between play, player development and training, and management of physical status. Viewed from a whole-body physiological perspective, performance in golf requires operation of all functional and system components of the golfer (figure 1). An appreciation of these will facilitate a more complete understanding of the true physiological parameters influencing performance achievement.

Proprioreceptive response

Segmental stability

Immune response

Body structure

Muscular strength

Neurological functioning

Peripheral fatigue processes

Muscular power Aerobic capacity/ endurance

Thermoregulatory control

Fig. 1. Physiological factors that can affect successful golf performance.

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Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

It is the application of such multidimensional approaches to player enhancement, combining technical, tactical and mental skills with physiological aspects that will bring about the desired change in the player and lead to an increased chance of repeatable success. 5. A Multidimensional Approach to Golf Improvement The synergistic relationship between equipment, technique and body enables the golfer to repetitively coordinate the body to produce the golf swing movement. The relative contribution of each of these components will impact on the attainment of an optimized golf swing and consequentially influence competitive success (i.e. lower scores). From the coach’s perspective, an understanding as to the relative importance of each component will allow for effective evaluative measures of the golf swing and the identification of movement limitations that may ensure corrective advice appropriately focuses on the necessary impingement to swing enhancement. From a sport scientist and researcher’s viewpoint, establishing causal links between each component and performance outcome can provide evidence as to how performance can be improved through effective intervention strategies. A framework in which golf performance can be divided into components provides the coach and player with an elementary entry point into the more detailed factors influencing both decision making and movement. Existing models examining the physical components of golf primarily focus on aspects relating to muscular strength, flexibility, cardiovascular and body conditioning.[16-19] Attention drawn to preparatory practices tends to neglect, however, the importance of maintaining a stable state whilst competing. It is the achievement of such state throughout the course of play and the ability to minimize deterioration through appropriate management techniques that may improve on overall scoring success. How a player’s physical state is managed during play could therefore have significant effect on optimal golf performance in the latter stages of the round or competition.[20] ª 2010 Adis Data Information BV. All rights reserved.

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As illustrated in figure 2, prior to play, the golfer’s objective is to ensure that aspects relating to aerobic capacity, strength and conditioning, flexibility, podiatric and optometric considerations, dietary habits and injury management are factored into the overall player plan. Once competition begins, the objective shifts to the maintenance of such state. Taking into consideration environmental conditions and the consequential impact these will have on physical performance, the player must select appropriate strategies in order to minimize performance disruption. The relative importance of each of these will obviously change within and between players, and – dependent on experiences, expectations and aspirations – development focus should follow an individualized approach to player improvement. Such a holistic approach to optimized performance development is widely accepted as a means of reaching performance potential,[15,21] and extensive holistic practice ensures that peak form can be attained in all aspects of performance. Aspects relating to physical, tactical, technical, life and mental skills have evolved our understanding of golf as a complex dynamic activity that encompasses a multidisciplinary approach to player development.[20] In determining the relative importance of such components within a multidisciplinary approach to player development, it must be established which elements underpin the development of successful golf performance. In achieving this, it must firstly be recognized that success in golf should be viewed with some subjectivity. Despite skill development and optimization of the player, the determination of scoring success will to some extent be influenced by equipment, weather and course conditions.[22] Nevertheless, the achievement of consistently successful scoring in golf should be built on the premise that objective aspects of performance must be the primary focus of any player or coach in attaining a consistent, efficient, repeatable golf swing that brings about the desired outcome. Ultimately, to execute such skill and achieve the required goal the player must exhibit exemplary performance in all aspects of their game. Deficiency in one or more components will be detrimental to overall scoring Sports Med 2010; 40 (8)

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‘Competition’ scoring success (i.e. lower score)

Optimal technical state during ‘competition’

Optimal tactical state during ‘competition’

Optimal physical state during ‘competition’

Optimal mental state during ‘competition’

Optimal life skill state

Optimal ‘preparatory’ physical state

Physical maintenance during ‘competition’

Diet and nutrition

External factors (e.g. environment)

Optometry

Strength and conditioning

Aerobic capacity

Mobility, stability and flexibility

Podiatry Physical screening Management of injuries Fig. 2. A multidisciplinary approach to golf performance enhancement.

success and consequently diminish optimal performance achievement and maintenance. 6. The Physical Requirements of Golf Dynamics of the golf swing are to a large extent dictated by the anatomical and physiological make-up of the body (figure 1). Swing types are usually governed by what the player can and cannot do with their bodies during static and dynamic positioning. The achievement of optimized golf performance could therefore be compromised by player physicality, affecting ª 2010 Adis Data Information BV. All rights reserved.

the attainment of required swing mechanics in bringing about successful ball displacement. Genotypic attributes – such as sex, maturational status, limb characteristics (e.g. limb length and limb symmetry) and stature – in combination with physiological indices – such as muscular activation patterns, muscle balance and symmetry, muscle fibre type, strength, flexibility, mobility, coordination, proprioception and somatotype – will dictate static postural characteristics and dynamic body movements. For example, rotational aspects of the hip, shoulder and spine through the swing have been shown Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

to affect club-head speed and consequently ball distance.[23-25] The inter-relationship between energy system utilization, thermoregulatory processes and fluid balance will further affect the player’s condition when performing movements throughout the course of play.[26] Performing in a varied range of conditions will also contribute to altered physical status and further compromise swing dynamics. Environmental factors will have considerable impact on the physiological status of the body.[26] Temperature,[12,26] altitude[27] and course topography[28,29] will alter internal conditions, and the player must have the appropriate strategies to ensure that any potential physical change is minimized and does not manifest in detrimental swing performance. 6.1 On-Course Physical Demands

It is not unusual for elite players to cover distances in excess of 10 km during the course of play[30] and, dependent on course topography and altitude changes, additional demands will be placed on the golfer.[29,31] Furthermore, influences such as unpredictable weather conditions, speed of play and length of match combined with temporary internal physiological alterations, caused by stress response[20,32,33] and player confidence,[34] will affect strategic approaches taken during competition. Throughout the course of the round and across days, the player must attempt to stabilize physiological status. Developed

641

during preparation, the player must ensure that for each shot played, their physiological state remains as close to their starting point as possible without any undue fatigue, for it is the player who can minimize such decrement that will remain in an optimized state for the longest. As illustrated in table I, the ‘macro’ energetic demands of golf highlight the relatively low cardiorespiratory requirements needed by the golfer during the course of play. Considering the multidisciplinary approach to golf performance (figure 2), this consequentially will have a significant impact on optimized scoring success. 6.1.1 Cardiorespiratory Demands

The cardiorespiratory challenges that arise from golf are not considered intense,[39] and reflect the low energetic nature of golf performance. Due to ease of measurement and cost associated with monitoring heart rate response throughout the course of play, findings of past research highlight the cardiovascular stress response (table II). On-course playing conditions over a variety of course terrains indicate relatively low cardiovascular stress response when compared with other activities.[15] Exercise intensity expressed as a percentage of predicted maximal heart rate ranges from 52.1% to 78.7%, with absolute values of 95[1] to 137 beats/min.[28] The higher relative and absolute values, however, relate to playing only three selected holes on a hilly course and therefore may not reflect

Table I. Reported ‘macro’ energy demands of playing 18 holes of golf on an undulating course. All data relate to walking the course whilst carrying a full set of clubs Performance variable . VO2 (mL/min/kg) . VO2max (%)

Value/range

Reference

22.4

35

35–46

36,37

Heart rate response (beats/min)

95–120

11,12,20,31

HRmax (%)

52.1–67.4

11,12,20,31

Ventilatory response (L/min)

50.8

35

Respiratory exchange ratio

0.87

35

Lactate response (mmol/L)

0.8–1.1

38

Total energy expenditure (kcal)

960–1954

35,36

Energy expenditure (kcal/min)

6.0–11.8

35,36

Distance covered in excess of course distance (%) . . . HRmax = maximal heart rate; VO2 = oxygen uptake; VO2max = maximal VO2.

27–72

11,12,30,35

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Sports Med 2010; 40 (8)

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Table II. Mean absolute and relative heart rate (HR) response measured during on-course golf performance Study (year) Hayes et al.[11] (2008) Peterson[12] (2008) McKay et al.[20] (1997)

No. of subjects 7

Handicap

Sex

Age (y)

No. of holes

Absolute HR (beats/min)

HRmax (%)a

12.5

M

50

18

95

54.8

£7

M

24.1

18

111

58.4

15

3.8 – 0.5

M

22.5

18 (practice)

100

52.1

15

3.8 – 0.5

M

22.5

18 (competition)

117

61.0

46.9

122

69.5

13

Magnusson[28] (1999)

9

?

F

Magnusson[28] (1999)

10

?

M

48.9

3

137

78.7

Stauch et al.[29] (2008)

30

?

M/F

53.5

18

113

66.1

Burkett et al.[31] (1999)

10

5–20

M

24

18

120

62.9

?

M

43

18

120

67.4

Sell et al.[35] (2008) a

1

3

Predicted HRmax = 206.9 - (0.67 * age).

F = female; HRmax = maximal HR; M = male; ? indicates not specified.

cardiovascular response throughout an entire 18-hole round.[28] McKay et al.[20] found a 17% increase in absolute heart rate response between a practice and competition round, possibly reflecting a psycho-physiological stress response during tournament play. In a study by Sell et al.,[35] the cardiorespiratory response to three playing conditions was determined over 18 holes. Average oxygen . uptake (VO2) and expiratory volume for walking whilst carrying clubs was higher (22.4 mL/min/kg; 50.8 L/min) than when walking with an electric trolley (18.3 mL/min/kg; 44.2 L/min) or riding on a cart (15.6 mL/min/kg; 33.1 L/min). The respiratory exchange ratio was highest in the walk-carry condition (0.87) compared with the others (0.63 and 0.71, respectively). Murase et al.[36] found that middle-aged men walking an 18-hole course functioned at a mean exercise intensity . corre. sponding to 35–41% maximal VO2 (VO2max). These findings seem comparable with others,[37] who have .reported maximal aerobic capacity of 46 – 2.6% VO2max in amateur golfers. From a non-locomotive movement perspective, increases in blood pressure (diastolic, systolic and mean arterial pressure) and cardiac output have been reported during fast isokinetic movement.[40] With movement characteristics similar to that encountered throughout the swing, findings suggest the presence of acute cardiovascular stress during the golf swing. Furthermore, findings from non-golf-related research that investigated cardiovascular stress response ª 2010 Adis Data Information BV. All rights reserved.

to force-velocity properties of dynamic movement found increases in mean arterial pressure, indicating that individuals with a greater muscular strength and speed of movement might respond with larger acute cardiovascular disruption.[41] Measuring inter-beat interval during three different shot types, Cotterill and Collins[42] found there to be an increase in the duration of inter-beat intervals prior to shot execution, indicating a decrease in heart rate response. Interestingly, all golfers showed a greater increase in inter-beat interval for shots using a putter compared with the driver. A more recent study[43] found elite golfers, when compared with experienced and novice players, showed a more pronounced deceleration in heart rate immediately prior to a putt and a greater tendency to show a respiratory pattern of exhaling immediately prior to movement. Findings indicate an inherent pre-shot execution pattern that has a cardiorespiratory impact and may be linked to conscious alterations in breathing frequency and cardiac response.[43] 6.1.2 Metabolic and Hormonal Response

Indicators of metabolic and hormonal response prior to, during and after golf competition are suggestive of enhanced physiological and psychological stress that may affect effective shot-making. Lactate response during the course of 18 holes of play has been recorded around 0.8–1.1 mmol/L – indicative of resting levels.[38] Following the completion of 18 holes of golf, Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

blood glucose levels have been shown to decrease with a concomitant increase in fatty free acids.[36] Broman et al.[44] noted that following the completion of an 18-hole course, mean blood glucose levels fell on average by 20%, 10% and 30% in young (27 – 5 years), middle-aged (50 – 7 years) and older men (75 – 4 years), respectively. Dobrosielski et al.[37] reported elevated levels of adrenaline (epinephrine) and noradrenaline (norepinephrine) throughout the course of play compared with baseline levels; however, there was no change in the ratio throughout the competition. Cortisol has been linked to the homeostatic regulation of various psychological and physiological processes, such as emotional control and metabolic support.[45] During performance, cortisol levels, which reflect physiological coping, have been shown to alter through a round of golf. McKay et al.[20] revealed that cortisol levels were significantly higher throughout an 18hole competition compared with a practice round (5.8 – 1.6 vs 2.4 – 1.1 nmol/L, respectively). Further findings revealed levels for both practice and competition reduced significantly throughout the 18 holes. Supported by more recent evidence,[46] it has also been noted that non-elite players (handicap >7) tend to have a higher, although nonsignificant, cortisol level prior to, during and after competition compared with elite players (handicap <3). This may indicate more developed psychological coping strategies and advanced training programmes to deal with competitive stress. Wang et al.[47] found that in elite golfers competing in a national tournament, recorded levels of cortisol and dehydroepiandrosterone sulphate, which has been associated with the magnitude of psychological stress,[47] both fell significantly and remained lower in those who failed to make the cut, when compared with those players who did. 6.1.3 Musculoskeletal Demands

Musculoskeletal functioning during the golf swing has been extensively studied and reviewed.[1,2] It must be observed that with in excess of 2000 swings being performed by the tournament professional during practice and competition each week[8] and with up to 300 powerful movements per practice session,[9] such musculoª 2010 Adis Data Information BV. All rights reserved.

643

skeletal involvement requires muscular stability and strength to withstand complex loading patterns. These include shear,[48] compression[48] and axial torsional loads.[49] Such rapid directional changes that require alternating force production necessitates the activation of trunk and axial muscle groups at specific periods throughout the movement. With the most active muscles during the swing being located in the torso, shoulder and hip,[2] the musculoskeletal demands acting on the body require structural and physiological stability and strength.[10] 6.1.4 Energy Expenditure

Total calorific expenditure for a round of golf has been determined for a range of conditions.[35] It has been estimated by way of portable cardiorespiratory measures during play on a hilly course that walking whilst carrying a bag expended 1954 kcal (11.8 kcal/min) covering a distance of 8.69 km in a time of 2 hours 46 minutes. This was reduced to 1527 kcal (9.2 kcal/min) for walking with a trolley (total distance was 7.89 km in a time of 2 hours 46 minutes. However, Murase et al.[36] found average calorific values of 960 kcal following 18 holes of golf, which equated to 6.0 kcal/min. Estimating oxygen demands and extrapolating energy expenditure, however, may have underestimated actual energy requirements. 6.1.5 Nutritional Requirements

With a single round of golf taking between 2.5 and 6 hours – depending on course terrain and distance, playing partner(s) and the nature of competition – effective nutrition ensures energetic requirements of play are met and hydration status maintained.[50] This is further affected when issues relating to ambient conditions,[12] optimal dietary provision surrounding travel to and from training and competition,[51] specific physique requirements[1] and the impact that excess weight may have on movement skills[52] are taken into account. The onset of mental and physical fatigue through inadequate and/or inappropriate dietary practices will have a significant impact on the player’s ability during performance. Research conducted by Derave et al.[53] illustrates that suboptimal hydration strategies will compromise Sports Med 2010; 40 (8)

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functional ability, in particular dynamic postural stability. This will inevitably jeopardise dynamic movement capabilities and lead to diminished optimal performance success. It has been identified that golfers in a dehydrated state significantly underestimated distances to the pin, when compared with a euhydrated state (Newell et al., unpublished observations). Correct nutritional choices can mean the difference between causing and preventing low energy, hunger and muscle fatigue during performance. Low blood sugar, as found following 18 holes of golf,[44] can easily contribute to or cause a lack of focus, irritation, impatience and poor decision making.[15] 6.1.6 Impact of Fatigue on Decision Making

In planning an approach to stabilize physical performance during competition, the coach and player must recognize that a key strategy is to minimize both local muscular and central fatigue development. Such onset of fatigue will impact, first, on the ability to select the right shot type and, second, the execution of the swing. Low level fatigue similar to that which might be encountered during a round of golf has been shown to impact negatively on decision-making accuracy.[54] During a decision-making test, which involved selecting the correct performance outcome from a range of scenarios, accuracy scores following sustained light exertion were significantly lower compared with pre-test and high-exertion performance. In light of these observations, small decrements in decision-making accuracy for the golfer may occur during extended matches in unfavourable conditions or across days within a tournament. As outlined by Tripp et al.,[55] in complex kinetic chain movements, such as the golf swing, localized muscle fatigue caused by both acute and prolonged muscular activation can have a negative effect on how the body moves. Upper extremity muscle groups have been shown to reorganize muscle activity patterns during the onset of fatigue, thereby combating overload of specific muscles and minimizing fatigue.[55] Such reorganization of multiple joint angles or muscle firing patterns may therefore compensate for fatigue of one muscle or synergistic muscles throughout the movement. Despite this, such ª 2010 Adis Data Information BV. All rights reserved.

mechanisms, in preventing the onset of fatigue, may actually alter the complex coordinative segmental patterns of movement necessary to bring about required golf swing. The involvement of additional muscle(s) to offset fatigue may play a detrimental role in swing mechanics and therefore, considering the small margins of error involved in precise impact achievement, even slight fatigue may compromise outcome success. Such a notion is supported by evidence that has highlighted the effect fatigue – induced by maximal dynamic movements, similar to that encountered during golf – has had on skilled movement performance.[56] Davey et al.[56] noted that following sustained movement, which resulted in peripheral fatigue, the ability to perform a dynamic tennis shot was diminished. The authors postulated that with the onset of fatigue comes an accompanying decline in skill, manifesting through poor timing, body alignment and segment coordination. 7. Physical Attributes of the Golfer With a growing empirical research base characterizing the physical attributes of the highperformance golfer and the application of such data to player enhancement strategies, a greater acceptance and value of applied physiological research into golf is emerging (table III). As a consequence, an understanding of the physiological nature of golf and the profiling of the player from a functional movement point of view has grown in popularity. As a consequence, this has provided the technical coach with a much clearer evaluation of movement limitations and areas of development, with evidence revealing the significance of such data collected from these assessments for overall performance achievement. With the focus on the physical aspects of mobility, stability and strength at movement points activated during the golf swing,[63] the elucidation of the physiological differences between highly proficient and less able golfers provides a starting point from which physical scientific support can commence. By understanding the qualities exhibited by the player and determining the areas of weakness, effective implementation can be integrated into the routine development plan. Sports Med 2010; 40 (8)

17.3% . BIA = bioelectrical impedance analysis; F = female; HRmax = maximal heart rate; M = male; VO2max = maximal oxygen uptake; ? indicates not specified.

Predicted HRmax = 206.9 – (0.67 * Age).

48.7 (predicted) 180 75.6 18 M/F Elite (i.e. £3) 148 Duncan et al.[62] (2006)

a

121 mm (7-site) ?

195a

95.1 mm (7-site) ?

? ?

?

?

? ?

F ? Russell and Owies[61] (2000)

Low (i.e. £8)

? Russell and Owies[61] (2000)

Low (i.e. £5)

M

?

?

12.5% (4-site)

10.2%(3.2–23.2%: 3-site) ? ? ? 17 56 Kras and Abendrroth-Smith[60] (2001)

Amateur

M

?

10.0% (4-site)

?

? ?

? 177

180

27.8

76.8 22.9

M 10 Keogh et al.[59] (2009)

High (i.e. 20.3)

10 Keogh et al.[59] (2009)

Low (i.e. 0.3)

M

73.5

23.9%

20.8% (18–27%: BIA)

45.7

?

198

? 179.5

162 65.7

74.9

?

16

F

ª 2010 Adis Data Information BV. All rights reserved.

645

7.1 Aerobic Fitness

M £8 (mean, 5.8)

Elite 1

8

(2008) Pheasey

Kosendiak et al.[58] (2007)

? ? 73.6 22.4 5

[57]

Burkett and von Heijne-Fisher[31] (1998)

8–13

M

176.0

?

?

? ? ? 5 Burkett and von Heijne-Fisher[31] (1998)

£8

73.4 25.6 M

178.0

? 33.2

38.5 182

176 ?

? 82.4 46.9

66.9 48.9

F 9 Magnusson[28] (1999)

?

10 Magnusson[28] (1999)

?

M

Mass (kg) Age (y) Sex Handicap No. of subjects Study (year)

Table III. Anthropometric and physiological characteristics measured during golf-related research

Height (cm)

HRmax (beats/min)

. VO2max (mL/min/kg)

Body composition

Physiology in the Development of Golf Performance

With golf imposing a relatively low cardio[35,36] it is of no surprise that respiratory . demand, reported VO2max values for golfers are lower than other more demanding endurance-based sports,[14] and similar to that of healthy active adults.[15] Values of 45.7 mL/min/kg have previously been reported in elite female golfers when assessed on a bicycle ergometer,[57] whilst others reported values as low as 33.8 mL/min/kg in middle-aged amateur golfers[28] during treadmill assessment. 7.2 Anaerobic Capacity

With the complete golf swing lasting less than 2 seconds,[13] the measurement of anaerobic capacity has been made in an attempt to reflect energy demands of the movement. Conducting a Wingate sprint assessment on a group of elite junior golfers, Kosendiak et al.[58] reported peak power values of 722.3 W (9.64 W/kg), similar to those recorded by athletes from wrestling, athletics and football.[58] Although such assessment has little direct transfer to the golf swing movement, the measurement of anaerobic fitness as part of a wider physical screening programme can offer indices for global physical fitness and response to training. 7.3 Functional Strength

Strength, especially around the hips, pelvis and lower back, is essential for optimal performance in golf.[10,59] Every effective swing has a starting point or setup, which places the golfer in an optimal position to execute the repeatable, efficient movement through impact. Such interface between the ground and the body allows for stabilization in which kinetic energy can be created and utilized. Throughout the initiation of the movement, such forces are built from the ground upwards with the kinetic linkage between upper and lower body segments triggering movement, bringing about hip to shoulder rotational difference.[58] With higher velocity of movement within these areas, comes a greater need for strength of the activated musculature. Assessing the torso, shoulder and hip strength of golfers across three proficiency levels (low, Sports Med 2010; 40 (8)

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handicap <0; mid, handicap 1–9; high, handicap 10–20), Sell et al.[10] found that low handicap players recorded significantly greater (p < 0.05) right hip abduction, right hip adduction, left hip abduction, right torso rotation and left torso rotation strength than both mid- and high-handicap groups. Furthermore, strength recorded for right shoulder internal rotation, right shoulder external rotation and left shoulder external rotation was significantly higher (p < 0.05) than the high-handicap group. Findings reveal that highly proficient golfers, who are able to generate higher club head speed and create a greater ‘X’ factor stretch,[64] have greater spinal and shoulder strength, especially of the rotor cuff. This has particular importance with regard to injury prevention and joint stabilization considering the high prevalence of shoulder- and cervical-related injuries recorded in professional players.[65] Through the measurement of golf-specific functional rotational strength (i.e. golf swing-specific cable wood chop), Keogh and colleagues[59] found that low-handicap golfers (0.3 – 0.5) had significantly greater (p = 0.001) strength than high-handicap players (20.3 – 2.4). Findings also revealed significantly greater (p < 0.05) strength measured by way of a non-golf-specific 1 repetition maximum bench press. When functional rotational strength and bench press strength were correlated with maximum club head speed, findings revealed a significant positive relationship (r = 0.706, p < 0.01; r = 0.500, p < 0.05; respectively). With evidence being collected from mainly male populations, further research is warranted across age groups and between sexes in order to develop more individualized training programmes based on differing physiological characteristics. 7.4 Flexibility and Balance

Throughout the golf swing, individuals are required to attain positions that require good flexibility and balance. The inability to attain and maintain movement positions within and between swings through poor range of motion can lead to ineffective movement patterns and unwanted shot outcomes. Assessment of global lower back and hamstring flexibility (i.e. sit-andª 2010 Adis Data Information BV. All rights reserved.

reach) in a range of golfing abilities[21,60] has revealed greater range of motion in more able players. Furthermore, measures of shoulder abduction and shoulder external rotation have shown greater flexibility in players with a lower handicap.[59,66,67] Confirming previous observations, Sell et al.[10] recorded significantly greater range of motion for right shoulder extension, right shoulder external rotation and left shoulder extension in highly proficient players compared with lower ability levels. Moreover, when evaluating lower limb and torso flexibility for the first time, findings revealed that the lower handicap players (handicap <0) had significantly greater right hip extension, left hip flexion and right torso rotation than the less proficient players (handicap 10–20).[10] These findings have been further reinforced by Keogh et al.,[59] who observed measurable differences in follow-through trunk rotation (degree of rotation) and backswing trunk rotation (degree of rotation). Little evidence is currently available that has investigated flexibility across sex or age groups. What primitive empirical data that have been presented, suggest that for similar playing standards, torso rotational flexibility appears to be comparable in males and females.[68] However, considering anatomical and physiological differences between sexes and the impact age has on physical status,[39,69] such findings are far from conclusive and further methodologically rigorous investigations utilizing larger samples are necessary. For optimal execution of each shot, balance in the form of good tempo and rhythm, free from jerky unnecessary movements, allows for controlled, posturally stable maintenance of the centre of mass around the base of support.[1] Studies examining balance characteristics have utilized fairly basic assessment methods to establish differences between playing ability. Evaluating a number of high-school junior golfers, Kras and Abendrroth-Smith[60] measured the duration of a one-legged stance with the player’s eyes closed (stork test). Findings revealed a wide dispersion of times ranging from 4 to 60 seconds (mean 28.4 seconds). Sell et al.[10] applied the same assessment, advancing further by measuring anterior/posterior and medial/lateral ground Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

reaction forces for both legs with eyes open and closed. It was noted that low-handicap players (<0) had a significantly greater balance on the right leg under the eyes-open condition for the medial/lateral and anterior/posterior force compared with higher-handicap players. 7.5 Podiatric Factors

In storing kinetic energy during the swing, a firm foot-to-ground interface must occur, as different foot pressure patterns will affect swing success.[69,70] Equally, once the kinetic energy is released and unwinding begins, an effective footto-ground relationship will promote a stable base for rotational movement back to ball impact and beyond. Forces building up through the foot therefore have an all-important part in the ability to bring about the desired movement in other body segments.[69] With such shear forces permeating through the feet during all aspects of the movement, an appreciation of the podiatric attributes of the golfer may have a positive impact on performance. From an anatomical perspective, lower extremity length discrepancies have been reported to influence the biomechanical aspects of dynamic movements.[71] As Perrin[71] notes, the spine, pelvis and lower extremities are all involved in compensating for leg length differences. Key compensatory mechanisms that would impact on the golf swing include pelvic tilt, lumbar scoliosis, knee flexion, plantar flexion and supination. Structural aspects relating to physical shortening of unilateral lower limbs, which may be congenital or caused through trauma, and functional unilateral discrepancies, potentially caused as a result of shortening of soft tissues, ligament laxity, hyperpronation or lumbar scoliosis.[71] Such physical deformities may manifest through habitual golf posture,[72] which will mechanistically alter swing dynamics. The prescription of appropriately fitted orthotic insoles, for example, may provide a corrective measure that in part improves balance, proprioceptive symmetry[73] and dynamic mechanical efficiency,[74] off-setting leg length inequalities. There are currently no empirical data in the golfrelated literature that document the prevalence of ª 2010 Adis Data Information BV. All rights reserved.

647

leg length discrepancy or foot pathology in golfers. What is known is that leg length inequality is common, with 23% of the general population having a discrepancy ‡1 cm.[75] This means that nearly one in four golfers will have leg length differences that may be impacting on swing performance. The prevalence of leg length inequality requiring a corrective device, such as that of an orthotic device, has been reported as one in 1000;[75] however, many may be unaware and therefore are not reported. McRitchie and Curran[76] found that the use of orthotic inserts by golfers who had previously been diagnosed with underlying foot pathology reported less pain and significantly enhanced foot posture throughout the golf swing. Stude and Gullickson[77] noted that with the addition of orthotic shoe inserts over a 6-week period to correct for structural abnormalities, measures of club head velocity increased by up to 7%, equating to an extra 15 yards (~14 m). Furthermore, a reduced level of fatigue was reported that led to a more consistent golf swing. Further research is warranted to evaluate the prevalence of leg length inequality within the golfing community, so more specific corrective programmes and associated treatments can be delivered specifically to this population. 7.6 Visual Function

The decision of shot type and the following execution of the swing are primarily dependent on inflowing visual information about the target and surrounding areas. Interpretation of environmental cues will inform internal decision-making processes, thereby bringing about movement pattern requirements.[78] Considering this, visual acuity and ability to perceive contextual differences (i.e. shades of green, gradient changes, flag distances) should be viewed as important physical attributes of the golfer. Compromised visual function may influence the processing of external information and result in performance inconsistency. Anecdotal evidence by leading PGA (Professional Golfer’s Assocation) tour players,[79] supported by scientific research,[80] underlines the need for regular evaluative visual examinations throughout any player’s physical development plan. Optometric assessments to Sports Med 2010; 40 (8)

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establish functioning – such as visual acuity (ability to resolve detail in a high contrast area), depth perception (simultaneous two-eye processing of subtle visual information over distances) and contrast sensitivity (ability to resolve detail under reduced contrast conditions)[80] – will provide informative descriptive data as to areas of player weakness. As outlined by Coffey et al.,[80] all these measures are trainable and have been shown to differ across performance abilities. Professional tour players, for example, have been shown to have significantly better visual functioning in all three areas compared with amateur and senior players. Findings reveal, therefore, that superior visual functioning may be due to years spent practicing through an optimized physical, technical and tactical training approach.[80] 8. Player Profiling and Training Implementation 8.1 Effective Physical Screening

In establishing the physical attributes of the golfer and their associated on-course physiological status, a periodized approach to physical assessment is required.[9] The process of physical screening should be the first strategy of players and coaches in developing an effective conditioning programme. Assembling a team to support the player will only be effective if a starting point for player development is established. As outlined by McMaster et al.[22] and Russell and Owies,[61] a range of assessment approaches should be applied to effectively evaluate the player’s strengths and weaknesses, establish baseline measures and provide the educational impetus for player development autonomy. As indicated in table IV, a wide range of assessment methods have been used within the research to assess the physical attributes of golfers. The application of self-assessment provides a starting point for the player, in which basic screening procedures and techniques can be integrated into the development plan. Allowing for regular self-monitoring ensures continuous reflection and refinements to the plan. With quesª 2010 Adis Data Information BV. All rights reserved.

tionnaire-based resources[84] and comprehensive online facilities available to both player and coach (e.g. Titleist Performance Institute, http://www. mytpi.com), self-evaluation packages provide the tools that allow the player to feel in control of their own development. However, the need for more scientifically rigorous and reliable screening practices across a wider range of physiological indices will provide both player and coach with more specific diagnoses. These may include measures of anatomical characteristics and physical anomalies, dynamic strength and functional capabilities, movement ranges and possible impingements, cardiovascular capacity and readiness for exercise, specific nutritional practices and general dietary habits, podiatric and optometric functioning, and injury screening. With a full musculoskeletal examination,[72] aerobic fitness evaluation,[62] functional strength measurement,[85] nutritional and dietary record-taking[21] and medical assessment,[9] the physical screening process should be viewed by all coaches and players as a fundamental stage in optimizing their physical state. Further, considering the biomechanics of the golf swing,[1] a player’s physicality will have significant impact on their ability to physically function. Effective evaluation by a clinician to determine any anatomical or functional complications will also allow for correct interventions, such as custom-fitted orthotics, appropriate shoe type and regular shoe replacement, thereby reducing any compensatory mechanisms that could limit the achievement of movement potential. 8.2 Physical Training to Improve Golf Performance

Through functional training of joint range of motion, flexibility, functional strength and dynamic postural balance, and segmental stabilization, meaningful improvements in club swing range, speed and power have been observed. As is highlighted in table V, it is now clear that physical conditioning in the areas of golf-specific flexibility, strength and core stability at least 3 to 4 times per week over a period of 8 weeks will significantly improve club head velocity by an average of 4.2% Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

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Table IV. Physical screening assessments used to identify physical attributes of the golfer Physical attribute

Assessment method

References

Cardiorespiratory fitness . VO2max

Incremental exercise assessment (bicycle/treadmill)

57,61,62

2-Minute step test

81

One-mile walking test

10,60

Lung function (FVC, FEV, PEF)

Spirometry

57

Resting heart rate

Seated rest

62

HRmax

Incremental exercise assessment (bicycle/treadmill)

57,62

Wingate 30-second sprint test

58

Anaerobic functioning Peak power output Functional strength Isolated single/multi-joint strength Grip strength

Isokinetic dynamometer

10,61

Maximal repetition on static machines/free-weights

59,68

Handgrip dynamometer

57,60,62

Functional power Upper limb dynamic power

Medicine ball throw

68

Lower limb dynamic power

Vertical jump/standing board jump

60,62

Functional range of motion

Flexibility machine (i.e. torso rotator) Goniometry assessment

10,59-61,82

Global flexibility (lower back/hamstrings)

Sit-and-reach test

19,23,62

Stork test (bilateral balance with open/closed eye)

10,60

Flexibility/range of motion

Balance Postural stability Anthropometry Physical dimensions

Length, breadth and girth measures

59

Body fat

Skinfolds assessment (3/4/7-site)

57,59-61

Somatotype

Heath-Carter assessment instrument 83 . FEV = forced expiratory volume; FVC = forced vital capacity; HRmax = maximal heart rate; PEF = peak expiratory flow; VO2max = maximal oxygen uptake.

and add up to 5.6% extra distance on a drive (14 yards extra of a 250 yard drive [13 m extra of 231 m drive]). With research focusing on functional development of the shoulder, torso and hip following foundation developments of wholebody strength, flexibility and postural stability,[68,87] recommendations focus on the need for golf-specific movement drills to replicate the swing as closely as possible.[67,68] With a well rounded, periodized resistance training programme that develops functional strength at speed (i.e. power), the golfer needs to develop golf-specific power during the dynamic movement of a swing.[85] This can be achieved by ensuring that any resistance and flexibility training targets the active muscle groups in a movement-specific way necessary to bring power transfer to the golf swing. ª 2010 Adis Data Information BV. All rights reserved.

Despite the relatively low cardiorespiratory requirements of golf, any physical conditioning programme should contain aerobic-based activity to support the training and competition demands. Regular endurance-based exercise (i.e. 3 to 5 times per week for 20–60 minutes), functioning at an intensity equivalent to 60–80% of maximal heart rate, will provide the golfer with sufficient effective and safe cardiovascular conditioning.[90] For the aerobically unconditioned golfer, maintaining workloads over an undulating course for up to 6 hours in unfavourable conditions will induce cardiorespiratory, metabolic and hormonal stress leading to sensations of fatigue. By developing an effective training programme, foundation physical conditioning will support increases in resistance training, practice and competition. Sports Med 2010; 40 (8)

Smith

>6% club-head velocity Functional training = flexibility, core stability, balance and resistance exercises. b

F = female; M = male; NS = nonsignificant (p > 0.05); PNF = proprioceptive neuromuscular facilitation; ? indicates not specified.

4 8 Strength/flexibility 17

M

57

? All changes in performance are significant (p < 0.05) unless stated. a

Larkin et al.

(1990)

4

ª 2010 Adis Data Information BV. All rights reserved.

9. Long-Term Monitoring for Performance Success

Wescott et al.[89] (1996)

>4.9% club-head velocity

>45% trunk rotational power ?

3 8

3 Strength/flexibility ? ?

Functional trainingb Mixed 70.7

[88]

M 11 Thompson et al.[81] (2007)

?

>5.2% club-head velocity >6.8% driving distance 3–4 8 Strength/flexibility 12.1 – 6.4 47.2 15 Lephart et al.[87] (2007)

M

>1.5% club-head velocity >4.3% driving distance

>3.4% club-head velocity (NS) 3

2 8

11 Strength/flexibility

Strength/plyometric 5.5 – 3.3

5–10 18.5

29 M

F 6

11

M 10

Fletcher and Hartwell[86] (2004)

>7.2% club-head velocity

>0.6% club-head velocity (NS) 3 11 Strength/flexibility 0

>2.7% club-head velocity

Doran et al.[68] (2006)

19.8

3

3 8

8 PNF stretching

Strength/flexibility Mixed

? 51.9

64.3

16 Jones[66] (1999)

M

19 Thompson and Osness[25] (2004)

M

>6.2% club-head velocity

>5 iron hitting distance 4

2 8

8 Strength/flexibility

Strength/flexibility ?

? 16

52.4 M/F

M 7

17 Hetu et al.[23] (1998)

Lennon[19] (1999)

Duration (wk) Training type Handicap Age (y) Sex No. of subjects Study (year)

Table V. Golf performance changes as an effect of physical conditioning training. All results are mean – SD (where reported)

Frequency (d/wk)

Change in performancea

650

A player development strategy necessary to achieve long-term performance success should include regular monitoring of physical development to determine adaptive response to training.[91] The implementation of player monitoring to track physical development,[57] evaluate the adaptive impact of physical training on performance,[68] and even predict golfing success,[92] can facilitate greater specificity of training approaches and effective long-term planning of physical conditioning programmes. Limited available evidence exist that documents the impact long-term monitoring has on developing golf performance success. Pheasey[57] is the only one to report provision of ongoing physiological support over an extended period (5 years). Assessing elite female golfers twice a year, once before the competitive season (March–April) and once after (October–November), findings reveal marked improvements across a range of physical attributes. For one player over a 3-year period, reductions in body mass (73.8–65.8 kg), reductions . in body fat (30.1–23.9%), increases in VO2max (29.2–45.7 mL/min/kg) and increases in maximal heart rate (183–198 beats/min) were recorded. By utilizing the bi-yearly assessment findings to implement individual training programmes to each player, the author noted that specificity ensured effectiveness (increased adherence) and compatibility with other support providers (i.e. physiotherapists). Although the impact such physiological adaptations had on golf success were not documented directly, accounts of competitive achievements throughout the 5-year monitoring period do underpin the importance of long-term physiological support to player development. Further research is warranted to elucidate the association between long-term monitoring, training implementation and golf performance success. By establishing the relationship between physical attributes and golf performance, practitioners can implement more focused and effective development strategies that will have a direct impact on success. Attempting to identify physiological Sports Med 2010; 40 (8)

Physiology in the Development of Golf Performance

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correlates of golf performance, Wells et al.[92] found the best predictors of success were core strength, stability, flexibility, balance and peripheral muscle strength. However, considering that golf success was broken down into average score, greens in regulation, short game measures and putting accuracy, such findings provide only tentative conclusions when attempting to establish which physical attributes best relate to golf achievement.

plan effective long-term player optimization, such intervention strategies should positively assist the player to enhance their physiology. As represented in figure 3, a physical development framework for optimization in golf provides a systematic manner in which physical aspects of the player can be enhanced. In order to establish a physiological support system that truly pushes the limits of performance, a formal systematic process of data gathering, player screening, player profiling, training implementation and long-term development planning must occur. Through a process of implementation, evaluation and development, the following questions can assist when applying the model:  Can our current level of understanding about physiological demands/requirements of golf at a micro/macro level be extended further?  Are all the physical attributes that may contribute to golf performance success known?  Are the current assessment methods being deployed suitable for golf?

10. Physical Development Model for Golf It is now well established that the optimization of golf performance is a multifactorial process[16,21] and that the available scientific literature supports the notion that physical training can increase aspects of golf performance.[10,25] For effective player development to occur, a strategy must be in place to ensure that evidence is constructively applied to develop corrective intervention measures. For the practitioner to

Physical requirements of golf: Appreciation of the inherent movement patterns of golf and the related ‘macro’ and ‘micro’ physical demands acting on the performer

1

Long-term monitoring: The long-term monitoring of training adaptations, impact of training intervention and the prediction of performance success

4

2

Golfer’s physical attributes: Identification of the physical qualities that characterize high-performance players and how these may differ from sub-elite performers

3

Player profiling and training: Player profiling to allow for effective implementation of physical training for on- and offcourse optimization Fig. 3. A physical development framework for optimization in golf.

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 Can specific training approaches be refined further to optimize adaptive responses specific to golf?  What contribution does physical conditioning have on overall golf success, and can a predictive model be developed? Without a systematic approach, the long-term physical development of the player will not lead to optimal performance on course, and will obstruct the ability to achieve peak physical state. It is through a continual cyclic process where each stage of the model informs the next that the attainment of consistent high performance can be realized. 11. Conclusions and Recommendations A growing body of research evidence supports the role physiology plays in the achievement of overall golf performance success. An understanding of the dynamic muscle activation patterns during the swing, the physiological demands of on-course performance, the impact physical and anatomical characteristics have on movement, physical conditioning approaches and measurement and evaluation techniques for golf has moved the importance of physiology and physical conditioning programmes higher up the coach, player and sport scientist’s agenda. For effective long-term player development, implementation of an effective strategy will increase the potential for performance success. By appreciating the requirements of competitive golf performance, specific player attributes can be determined using appropriate and golf-specific assessment methods. Providing a player profile through comprehensive physical screening allows for specific conditioning programmes to be developed. Monitoring player development through continual assessment of training and associated adaptive responses provides an indication as to the key physical factors that may impact most on performance success. Through a cyclic process, the physical development model (figure 3) offers a framework by which a continual understanding of the physiology of golf can evolve. The attainment of consistent high performance requires effective physical conditioning that is carefully ª 2010 Adis Data Information BV. All rights reserved.

designed and monitored in accordance with the requirements of golf and the attributes of the player. Further research needs to focus more specifically on physiological aspects relating to women, junior and disability groups. It should not be assumed that research findings, associated performance models and practical applications apply to all, and therefore caution must be taken when translating and applying research to specific performance groups. Acknowledgements No sources of funding were used to assist in the preparation of this review. The author has no conflict of interest that is directly relevant to the content of this review.

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Correspondence: Dr Mark F. Smith, Department of Sport, Coaching and Exercise Science, University of Lincoln, Lincoln LN7 6TS, UK. E-mail: [email protected]

Sports Med 2010; 40 (8)

REVIEW ARTICLE

Sports Med 2010; 40 (8): 657-679 0112-1642/10/0008-0657/$49.95/0

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Evaluation of Injury and Fatality Risk in Rock and Ice Climbing Volker Scho¨ffl,1,2,3 Audry Morrison,3 Ulrich Schwarz,4 Isabelle Scho¨ffl5 and Thomas Ku¨pper3,6 1 Department of Sportorthopedics, Orthopedics and Trauma Surgery, Klinikum Bamberg, Bamberg, Germany 2 Department of Trauma Surgery, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany 3 Medical Commission of Union Internationale des Associations d’Alpinisme, Bern, Switzerland 4 Private Practise, Oberstdorf, Germany 5 Department of Anatomy 1, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany 6 Institute of Occupational and Social Medicine, RWTH Aachen Technical University, Aachen, Germany

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Retrospective Data Collection and Climbing Participation Time Calculation . . . . . . . . . . . . . . . . . . . 2. Description of Rock Climbing Sub-Disciplines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Sport Climbing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Bouldering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Traditional (Alpine) Climbing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Indoor Climbing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Ice Climbing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Injury and Fatality Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Traditional, Sport Climbing and Bouldering. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Indoor Rock Climbing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Ice Climbing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Comparison of Climbing to Mountaineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Injury Risk Compared with Other Sports. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Is Climbing a High-Risk Sport? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7. Limitations of the Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

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Rock and ice climbing are widely considered to be ‘high-risk’ sporting activities that are associated with a high incidence of severe injury and even death, compared with more mainstream sports. However, objective scientific data to support this perception are questionable. Accordingly, >400 sportspecific injury studies were analysed and compared by quantifying the injury incidence and objectively grading the injury severity (using the National Advisory Committee for Aeronautics score) per 1000 hours of sporting participation. Fatalities were also analysed. The analysis revealed that fatalities occurred in all sports, but it was not always clear whether the sport itself or pre-existing health conditions contributed or caused the deaths. Bouldering

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(ropeless climbing to low heights), sport climbing (mostly bolt protected lead climbing with little objective danger) and indoor climbing (climbing indoors on artificial rock structures), showed a small injury rate, minor injury severity and few fatalities. As more objective/external dangers exist for alpine and ice climbing, the injury rate, injury severity and fatality were all higher. Overall, climbing sports had a lower injury incidence and severity score than many popular sports, including basketball, sailing or soccer; indoor climbing ranked the lowest in terms of injuries of all sports assessed. Nevertheless, a fatality risk remains, especially in alpine and ice climbing. In the absence of a standard definition for a ‘high-risk’ sport, categorizing climbing as a high-risk sport was found to be either subjective or dependent on the definition used. In conclusion, this analysis showed that retrospective data on sport-specific injuries and fatalities are not reported in a standardized manner. To improve preventative injury measures for climbing sports, it is recommended that a standardized, robust and comprehensive sport-specific scoring model should be developed to report and fully evaluate the injury risk, severity of injuries and fatality risk in climbing sports.

Rock climbing originated as a skill practice for difficult sections of a mountaineering ascent in the 1960s and was practiced by a small group of dedicated climbers. By the mid-1980s its popularity spread globally and diversified to include new categories such as ice climbing (climbing iced rock faces and frozen waterfalls),[1] bouldering (ropeless climbing to low heights), speed (competition climbing where two climbers climb simultaneously on identical routes against each other) and aid climbing (climbing with artificial aid and gear).[2,3] In 1991, only a few countries participated in the first World Championships but by 2005, some 500 athletes from 55 countries competed.[2-4] The International Federation of Sport Climbing is currently seeking recognition as an Olympic sport.[3,5,6] All of these climbing activities are regulated by national and international climbing organizations to promote safe participation, competitions[2,3,7] and to meet the needs of the rapidly rising club memberships. Learning to climb has never been easier with the advent of indoor artificial climbing walls found in many cities.[8] In some schools it forms part of the sport curriculum.[4,5] Rock climbing participation is accessible to all ages, toddler to pensioner,[4-7] and is enjoyed by many over a lifetime. There is little doubt that climbing as a sport has both diversified and grown in popuª 2010 Adis Data Information BV. All rights reserved.

larity, and has even become a spectator sport. However, with any sporting participation, there will be some risk of injury that must be weighed against the benefits of this exercise. To date, no known study has demonstrated that rock or ice climbing are high-risk sports, a commonly held perception. Epidemiological analysis of sport-specific injuries helps to provide preventive measures that can target the incidence and reduce their severity. Extensive studies on injuries in general rock climbing,[4,9-22] indoor climbing[8,10,23] and competition climbing[5] exist, including analysis of the injury risk per 1000 hours. Severe injuries during indoor or competition climbing are rare, but do happen.[5,8,10,12,16,17,19,21-33] Most injuries in rock climbing occur on the upper limbs, notably the fingers, and generally result from overstraining rather than acute injuries.[28,31,34-39] To date, no known study has objectively demonstrated that ice or rock climbing are high-risk sports, or that those climbing higher grades are more prone to experience severe injuries compared with those climbing lower grades. Nevertheless, the media’s lurid depiction of elite rock and ice climbers has helped to create a perception of climbing as being a hazardous and high-risk sport.[1,40] For example, a 1999 Time Magazine cover featured a sport climber with the headline ‘‘Why we take Sports Med 2010; 40 (8)

Rock and Ice Climbing

risks’’ with a subtitle stating ‘‘From extreme sports to day trading thrill seeking is becoming more popular.’’[40] Other ‘thrill seeking’ activities cited in this magazine’s feature article included having unprotected sex when AIDS was prevalent.[41] UK government statistics from around this time counter such titillating journalism by calculating the annual risk of death as a consequence of climbing to be 1 in 320 000 climbs, 1 in 200 000 dives if scuba diving, and 1 in 116 000 flights for hang gliding.[42] Many European accident and disability insurance policies either limit or exclude rock and ice climbing participation. In contrast, an established British policy[7] offers global coverage for different forms of climbing. This suggests that both the popular public and professional assessment of the actual risks associated with climbing may not be fully informed. To objectively analyse and compare injuries from different sports, a common scoring system for the grading of injuries is essential. In general, when assessing whether a sport presents a high risk of injury or death, a distinction between overstrain (overuse) injuries and acute injuries or accidents should be made. The reasons being, overstrain injuries are generally less severe and can generally be avoided with informed training, whereas an examination of the injury rate for acute sport-specific injuries, especially their severity, is crucial. In any case, an analysis of both overuse and acute injuries in climbing has been presented in this review. Although many studies and alpine clubs have recorded climbing accidents and injuries for over 100 years, two studies around 1990[20,21] pioneered the use of a scoring system (Injury Severity Score [ISS]) to grade registered climbing injuries and calculated the injury risk in correlation to climbing days[21] or climbing time.[20] However, this ISS score showed a weak validity for injury self recall,[43] and so future studies used the National Advisory Committee for Aeronautics (NACA) score[44] (see table I) for grading.[1,45] The NACA score is the most commonly used emergency score in Germany and is also part of the nationwide standard pre-hospital emergency physicians report form.[46] It is also recomª 2010 Adis Data Information BV. All rights reserved.

659

Table I. The National Advisory Committee for Aeronautics (NACA) scoring system[44] Patient status

Score level

Not an acute life-threatening disease or injury

1

Acute intervention not necessary; further diagnostic examination needed

2

Severe but not life-threatening disease or injury; acute intervention necessary

3

Development of vital (life threatening) danger possible

4

Acute vital (life threatening) danger

5

Acute cardiac or respiratory arrest

6

Dead

7

mended and used internationally for alpine trauma evaluation.[47] Therefore, this review sought to objectively compare different sports for their sport-specific injury risk by quantifying and grading the injury severity, and fatality rates per 1000 hours of sporting participation. The question as to whether any, or all, climbing activities should be considered high-risk sports was also examined. 1. Retrospective Data Collection and Climbing Participation Time Calculation An electronic PubMed search was conducted using the following search terms: ‘rock climbing’ (138 hits), ‘ice climbing’ (10 hits), ‘mountaineering’ (1821 hits), ‘sport injuries risk’ (5021 hits), ‘sport fatalities’ (243 hits), ‘epidemiology sport injuries’ (5102 hits) and ‘NACA score’ (13 hits). All studies on rock climbing and ice climbing were gathered and completely analysed. For mountaineering, all the abstracts were read and, if relevant, the full paper was accessed. A similar method was used for the other search terms once the relevant abstracts were identified. Additional information was sought by personal communication (with the German Alpine Club Safety Commission) and by an Internet search to obtain alpine club publications from Germany, Canada and America. From 400+ studies on climbing, mountaineering and other sports that supplied detailed information on sport-specific injuries, the injury risk per 1000 hours was either extracted directly Sports Med 2010; 40 (8)

Scho¨ffl et al.

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or calculated from the data of the selected study. If climbing days were reported and not the injury risk per 1000 hours of sports performance, a single rock climbing day was calculated using 4 hours for sport climbing, 8 hours for alpine climbing, 2 hours for indoor climbing,[5,8] 6 hours for ice climbing[1,5,8] and 16 hours for an expedition day. The rock climbing ability grade was transferred into the Union Internationale des Associations d’Alpinisme (UIAA) scale and then into the metric scale.[48] The injury definition and grading from the selected studies were initially evaluated by the independent analysis of the injuries using the NACA injury scoring system followed by a complete re-evaluation of these injuries in an identical manner by the consensus of three experienced trauma surgeons or sport physicians who were also experienced climbers. The fatality rate and case fatality were also analysed. In order to compare climbing with other sports, the injury risk per 1000 hours of sport participation was either given or calculated. 2. Description of Rock Climbing Sub-Disciplines Rock climbing is a multi-disciplined sport. Depending on the sub-discipline examined, the climber’s experience and skills, grade of route difficulty, equipment, climbing surface (type of rock or ice, artificial indoor wall, scree), remoteness of location, altitude and weather will implicate different levels of risk. In addition to these variables, many climbers regularly participate in more than one climbing sub-discipline. Designing scientific studies that can accurately reflect all these injury variables exclusively for outdoor climbing is difficult,[49] as many of these variables are common to anyone who engages in outdoor activity. Injuries at indoor climbing walls have more controlled sport-specific variables and are better documented.[5,8,23] Another variable considered when analysing climbing literature was careful interpretation of the origin of the study and geographical climbing area, as climbing terms and conditions differ among the continents (i.e. rock type, climbing grades, likely equipment used – especially in older studies, likely climbing ª 2010 Adis Data Information BV. All rights reserved.

sub-disciplines practiced), and this was reflected in tables II–V. Therefore, some climbing subdisciplines will be briefly described, followed by an analysis of injury data for climbing and other sports. 2.1 Sport Climbing

Sport climbing (figure 1) or free climbing requires gymnastic-like strength, flexibility, finger strength and strength endurance when climbing each unique and graded route. The climbing is slightly prescriptive as the climber ascends towards mostly permanently fixed anchors, such as bolts to clip their rope into for protection. The route length can range from 10 to 100+ m with fixed anchors generally around 2–5 m apart. Falls are frequent, trained for and are mostly harmless.[11] Physical hazards (rock fall, weather changes etc.) are small and the neglect of wearing a climbing helmet is widely accepted.[4,64] In contrast, fixed anchors will be very minimal when ‘free climbing’ and a helmet is recommended. 2.2 Bouldering

Ropeless climbing involves a short sequence of powerful and technical moves to complete the graded route on large rocks, occasionally up to 10+ m high. Bouldering (figure 2) can be done without a partner and with minimal equipment (climbing shoes and crash pad). Falling onto one’s feet or body is a normal part of bouldering, whether a route is completed or not. 2.3 Traditional (Alpine) Climbing

Traditional (alpine) climbing (or trad climbing) emphasizes the skills necessary for establishing routes in an exploratory fashion outdoors. The lead climber typically ascends a section of rock while placing removable protective devices where possible along the climb. Falls can therefore be longer than those experienced when sport climbing. Unreliable fixed pitons may occasionally be found on older established routes. As physical hazards are likely, the use of a helmet is considered mandatory.[65] Above approximately Sports Med 2010; 40 (8)

Type of climbing (geographical location)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Bowie et al.[21] (1988)

Traditional climbing, bouldering some rock walls 1000 m high (Yosemite Valley, CA, USA)

Data collection in the ER of the central hospital within the area

Mainly lead climbing falls; mostly lower extremity

37.5a

Majority of minor severity using ISS score; 95% ISS <13; 5% ISS 13–75

13 of 220 subjects had severe injuries, of which 11 were fatal (5.9%); case fatality rate 6%

Bias of injuries presented may reflect more serious injuries requiring ER treatment

Addiss and Baker[22] (1989)

Mountaineering and traditional climbing, includes snow and ice (US National Parks; includes snow and ice terrain)

127 rock climbing injuries that were reported to US National Park services (1981–2)

75% falls

NS

28% NACA seven (fatal)b

36 (28%); injuries on snow and ice were more likely to be fatal

Potentially high-risk activity

Schussmann et al.[20] (1990)

Mountaineering and traditional climbing (Grand Tetons, WY, USA)

Data collection through National Park registration from 1981 to 1986, representing 43 631 climbers, 108 accidents for all mountaineering activities

More mountaineering accidents than rock climbing

0.56 for injuries; 0.13 for fatalities; incidence 2.5 accidents/1000 mountaineers/y or 5.6 injuries/10 000 h of mountaineering

23% of the injuries were fatal (NACA 7)b

25 fatal, 23% case fatality rate; fatality rate 0.13/1000 h

Author concluded mountaineering was of a higher risk than pure rock climbing; climbing education and experience were considered preventative factors in accidents and injuries

Rooks et al.[18] (1995)

Recreational rock climbers, (GA, USA)

39 recreational climbers

Six climbers climbing beyond the sport level sustained a major injury from a fall, 35 sustained at least one significant injury; mostly to upper extremity

NS

NS

Six (15%) had a major injury from a fall

NS

Paige et al.[19] (1998)

Traditional climbing, sport climbing (NS)

94 rock climbers completed a retrospective questionnaire on overstrain injuries by mail, in person and via the Internet

Mainly lead climbing, falling when alpine climbing, injuries from hard moves in sport climbing; upper extremity, fingers especially affected

NS

NS

None as retrospective questionnaire

No major difference between alpine and sport climbing

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Study (year)

Rock and Ice Climbing

ª 2010 Adis Data Information BV. All rights reserved.

Table II. Injuries and fatalities in traditional and sport climbing

662

ª 2010 Adis Data Information BV. All rights reserved.

Table II. Contd Type of climbing (geographical location)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Rohrbourgh et al.[31] (2000)

Competition rock climbers at US National Championships (NS)

42 elite rock climbers; only overuse syndromes were studied

Mostly in upper limbs

NS

NS

None

No significant relationship between overuse injuries and years of climbing or difficulty level

Scho¨ffl et al.[15] (2003)

European climbers (NS)

604 injured climbers were seen prospectively over 4 y

Upper extremity 67%

NS

Mostly NACA 1–2, only 0.8% severe injuries (NACA 4 or 5)

None

Severe injuries were rare

Logan et al.[29] (2004)

Rock climbers, (UK)

545 members of the Climbers Club of Great Britain completed a questionnaire, which examined the prevalence of hand injuries

NS

Mostly NACA 1 and 2b

None reported as it was a retrospective survey on hand injuries

Climbing intensity score higher in injury group (including overstrains) (p < 0.05) although paper said intensity, grade is what is meant and clearer

Gerdes et al.[16] (2006)

Rock climbing (NS)

1887 subjects completed an anonymous Internet survey. There was a total of 2472 injuries, which included overuse syndrome injuries

Upper extremity 57.6%

NS

20% no injury; 60% NACA 1; 20% >NACA 1b

None reported as it was a retrospective survey

Traditional (p < 0.01) and solo climbing (p < 0.01) had more injuries (acute and overuse injuries). Injuries were fairly evenly distributed between indoor and outdoor climbing

Smith[12] (2006)

Review on alpine climbing injuries, (NS)

Review

Falls are the most frequent injury cause

NS

NS

NS

Falling injuries are more severe in alpine climbing

German Alpine Club[50] (2006)

All climbing disciplines (NS)

Reports on all climbing accidents were reported to the DAV insurance cover provider (2004–5)

NS

NS

NS

12% of all accidents in mountain sports are from rock and ice climbing: 48% of these from alpine climbing, 29% sport climbing, 9% indoor climbing, 6% ice climbing, 1% bouldering

Josephsen et al.[51] (2007)

Bouldering, indoor and outdoor (CA, USA)

Prospective, crosssectional cohort study (n = 54) of 152 subjects who completed the year-long study

NS

NS

None

Few differences between injuries experienced between indoor and outdoor bouldering

Continued next page

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Study (year)

None reported as it was a retrospective study Mostly NACA 1–2b, 11.3% hospitalization

Injuries/fatalities per 1000 h calculated by the authors according to the information given in the study.

NACA score graded by the authors according to the information given in the study.

a

Rock climbing injuries, indoor and outdoor (NS) Nelson and McKenzie[53] (2009)

b

Measures of participation and frequency of exposure to rock climbing are not specified Lower extremity mostly affected

Rock climbers, indoor and outdoor (NS) Jones et al.[52] (2007)

846 cases treated at US NEISS hospitals were collected and 40 282 injuries for the US were estimated from 1990 to 2007

NS 10% acute through falls, 33% overuse injuries, 28% acute through strenuous move Retrospective crosssectional study of 201 rock climbers

Type of climbing (geographical location)

ª 2010 Adis Data Information BV. All rights reserved.

DAV = German Alpine Club; ER = emergency room; ISS = Injury Severity Score; NACA = National Advisory Committee for Aeronautics; NEISS = National Electronic Injury Surveillance System; NS = not specified.

Climbing frequency and difficulty are associated with incidence of overuse injuries None reported as it was a retrospective study NS

Injury severity Injuries per 1000 h sport performance Cause of injury; body location Study profile

Over-exertion injuries more likely on the upper body

Risk evaluation Fatality

663

Study (year)

Table II. Contd

Rock and Ice Climbing

2500 m, physiological altitude-induced adaptations must also be factored into the climbs. 2.4 Indoor Climbing

Indoor climbing (figure 3) is performed on artificial structures that try to mimic climbing outdoors but in a more controlled environment. As physical hazards are almost totally eliminated, such climbing became an extra-curricular sport in many countries.[6] National and international competitions are held on such walls and involve three major disciplines: lead climbing (i.e. sport climbing), speed and bouldering. Bouldering is performed above thick foam mat flooring. 2.5 Ice Climbing

Ice climbing (figure 4) normally refers to roped and protected climbing of features such as icefalls, frozen waterfalls, and cliffs and rock slabs covered with ice refrozen from flows of water. Equipment includes ice axes for hands and crampons for feet. Physical hazards such as avalanches, rock and icefalls are present. 3. Injury and Fatality Risk 3.1 Traditional, Sport Climbing and Bouldering

Very few climbing injury studies differentiate between the sub-disciplines[51] of outdoor rock climbing, and many climbers participate in a few sub-disciplines, so traditional, sport climbing and bouldering will be examined together. Unfortunately, a high number of scientific climbing articles present case studies of common hand injuries[11,13-15,28,38,66-72] and are therefore not suitable for injury risk analysis, but they help to inform of overuse injury trends and preventative training. Nevertheless, most studies agree that the most (58–67%)[15,16] injured body region is the upper extremities.[15-19] In contrast, in their hospital and emergency room study based in the Yosemite Valley, USA, Bowie et al.[21] found that the lower extremity was most affected. The Yosemite area is famous for its 1000 m high walls, few bolts and mostly traditional climbing. Falls here can be quite long and may result in rock-hit trauma[4,27,73] as the Sports Med 2010; 40 (8)

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ª 2010 Adis Data Information BV. All rights reserved.

Table III. Injuries and fatalities in indoor and competition climbing Type of climbing (geographical location)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Limb[23] (1995)

90 indoor climbing walls (England, Wales and Scotland)

Postal survey of climbing walls; 55 accidents reported with 1.021 million visits

Mostly upper limb

0.027a

All >NACA 1a; none NACA 7

None

Climbing walls seem to be associated with a very low injury rate; injury rate not related to any identified wall design or safety feature

Scho¨ffl and Winkelmann[8] (1999)

Indoor climbing walls (Germany)

Prospective study of 25 163 registrants to indoor climbing walls

0.079

3 NACA 2; 1 NACA 3

None

Indoor climbing is a very low risk sport for acute injuries

Wright et al.[10] (2001)

Overuse injuries in indoor climbing at World Championship (Munich, Germany, 1999)

Semi-supervised questionnaire for 295 spectators and competitors

44% had overuse injuries; mostly fingers

NS

NACA 1–2b

None

Climbing harder routes was correlated to overuse injuries (p < 0.01)

Scho¨ffl and Ku¨pper[5] (2006)

Indoor competition climbing, World Championships (Munich, Germany)

443 climbers (273 M; 170 F) from 55 countries

18 acute injuries of which four were significant

3.1

16 NACA 1; 1 NACA 2; 1 NACA 3

None

Indoor rock climbing has a low injury risk and a good safety profile

Josephsen et al.[51] (2007)

Bouldering, indoor and outdoor (CA, USA)

Prospective cross-sectional cohort study n = 54 of 152 subjects who completed the year-long study

Overuse injuries

NS

NS

None

Few differences between indoor and outdoor climbing

German Alpine Club[50] (2006)

All climbing disciplines (NS)

Reports on all climbing accidents reported to the DAV insurance cover provider (2004–5)

NS

NS

NS

12% of all accidents in mountain sports are from rock and ice climbing: 48% of these are from alpine climbing, 29% sport climbing, 9% indoor climbing, 6% ice climbing and 1% bouldering

Jones et al.[52] (2007)

Rock climbers, indoor and outdoors (NS)

Retrospective crosssectional study of 201 rock climbers

NS

NS

None

Climbing frequency and difficulty are associated with incidence of overuse injuries

10% acute through falls; 33% overuse injuries; 28% acute through strenuous moves

a

Injuries/fatalities per 1000 h calculated by the authors according to the information given in the study.

b

NACA score graded by the authors according to the information given in the study.

DAV = German Alpine Club; F = females; M = males; NACA = National Advisory Committee for Aeronautics; NS = not specified.

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Sports Med 2010; 40 (8)

Study (year)

Type of climbing; (geographical location)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Mosimann[45] (2006)

Ice climbing (Switzerland)

Outcome of 46 ice climbers rescued by Swiss mountain rescue service over 6 y

Most frequent injury causes were falls (55%), but no fatal injuries were sustained through falls

NS

31% NACA 0; 42% NACA 2–3; 8% NACA 4; 6% NACA 5; 13% NACA 7

Case fatality rate 13%

Fatality rate in ice climbing is higher than in mountaineering and rock climbing

Scho¨ffl et al.[1] (2008)

Ice climbing (international)

Retrospective questionnaire of 88 experienced ice climbers who evaluated their injuries over previous 3 y

95 injuries, overuse syndrome

4.07 for NACA 1–3

2.87/1000 h NACA 1; 1.2/1000 h NACA 2/3; none >NACA 3

None reported as this is a retrospective study

Ice climbing is not a sport with a high risk of injury; 61% of injuries occurred while leading, 24% while following

American Alpine Club[54] (2006)

All climbing accidents (US)

Alpine club records from 1951 to 2003 reported 6111 accidents (5931 unharmed) from 11 089 mountaineers

NS

53% NACA 0a; 12% NACA 7a; 4% NACAa accidents on ice

1373 fatal accidents

NS

German Alpine Club[50] (2006)

All climbing disciplines (NS)

Reports on all climbing accidents reported to the DAV insurance cover provider (2004–5)

NS

NS

NS

12% of all accidents in mountain sports are from rock and ice climbing: 48% of these are from alpine climbing, 29% sport climbing, 9% indoor climbing, 6% ice climbing and 1% bouldering

Canadian Alpine Club[55] (2005)

All climbing accidents (Canada)

Alpine club records from 1951 to 2003 reported 958 accidents involving 2003 mountaineers; 715 injured, 163 occurred on ice

NS

NS

Of 292 fatal injuries, 30 were fatal ice climbing injuries, which occurred over a 30 y period

NS

a

NACA score graded by the authors according to the information given in the study.

DAV = German Alpine Club; NACA = National Advisory Committee for Aeronautics; NS = not specified.

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Study (year)

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Table IV. Injuries and fatalities in ice climbing

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ª 2010 Adis Data Information BV. All rights reserved.

Table V. Injuries and fatalities in mountaineering Type of climbing; (geographical location; includes snow and ice terrain)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Addiss and Baker[22] (1989)

Mountaineering and traditional climbing (US National Parks)

127 rock climbing injuries that were reported to US National Park services (1981–2)

75% falls

NS

28% NACA 7 (fatal)a

36 (28%) injuries on snow and ice were more likely to be fatal

Mountaineering was potentially a high-risk activity compared with rock climbing

Schussmann et al.[20] (1990)

Mountaineering and traditional climbing (Grand Tetons, WY, USA)

Data collection through National Park registration, 108 accidents

More mountaineering accidents than rock climbing

0.56 for injuries; 0.13 for fatalities

23% of the injuries were fatal (NACA 7)b

25 fatal cases; fatality rate 23%

Author concluded mountaineering was of a higher risk than pure rock climbing; climbing education and experience were considered preventative factors in accidents and injuries

Malcom[56] (2001)

Mountaineering (Mt Cook, New Zealand)

Fatality analysis of deaths on Mt Cook

NS

NS

0.12 for fatalitiesa or 1.87/1000 mountaineering days

Mountaineering was associated with a high risk compared with other leisure activities

Stephens et al.[57] (2005)

Unknown (Washington State Park, USA)

Retrospective, recreational injuries

NS

NS

Hiking was the most common activity during time of death with 58% fatalities. Mountaineering was 26%

NS

Monasterio[58] (2005)

Mountaineering and alpine rock climbing, maximum altitude 4000 m (New Zealand)

Prospective questionnaire regarding injuries over 4 y among 44 mountaineers (40 M; 4 F)

NS

NS

5 NACA 7 (fatal) [8.7%]; one death was unrelated to climbing, two fell into crevasses, two died by climbing misadventure (one climber was climbing alone)

Mountain climbing was associated with a high risk of serious injury and mortality; baseline climbing experience was 5–7 y

Continued next page

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Study (year)

Type of climbing; (geographical location; includes snow and ice terrain)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Firth et al.[59] (2008)

Mountaineering (mountaineers, Sherpas and climbers attempting to climb Mt Everest, 8850 m, highest point in the world)

Search of Himalayan database and other records from 1921 to 2006; analysis of mortality among n = 28 276 where 192 deaths occurred

113 died from objective falls or hazards; 52 nontraumatic (sudden death, altitude illness, hypothermia); 27 body never found

NS

NS

Mountaineers had a mortality rate of 1.3%

Debilitating symptoms of high altitude pulmonary oedema associated with descent from the summit; subsequent deaths were commonly associated with late arrival times to summit and profound fatigue

German Alpine Club[50] (2006)

All climbing disciplines that were covered by the insurance provider for the German Alpine Club

Reports on all climbing accidents reported to the DAV insurance cover provider (2004–5)

NS

NS

NS

12% of all accidents that occur in mountain sports are from rock climbing: 48% of these are from alpine climbing, 29% sport climbing, 9% indoor climbing and 1% bouldering

American Alpine Club[54] (2005)

All climbing accidents (US)

Alpine club records from 1951 to 2003 reported 6111 accidents (5931 unharmed) from 11 089 mountaineers

NS

53% NACA 0b; 12% NACA 7b; 4% NACAb accidents on ice

1373 fatal accidents

NS

Canadian Alpine Club[55] (2006)

All climbing accidents (Canada)

Alpine club records from 1951 to 2003 reported 958 accidents involving 2003 mountaineers; 715 injured, 163 occurred on ice

NS

NS

292 fatal injuries; 30 fatal ice climbing injuries occurred over a 30 y period

NS

Continued next page

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Table V. Contd

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ª 2010 Adis Data Information BV. All rights reserved.

Table V. Contd Type of climbing; (geographical location; includes snow and ice terrain)

Study profile

Cause of injury; body location

Injuries per 1000 h sport performance

Injury severity

Fatality

Risk evaluation

Hearns et al.[60] (2006)

Mountaineers who were patients at a specialist spinal hospital (Scotland)

Retrospective study; 21 of 1400 patients identified with spinal injuries from mountaineering over 10 y; the 21 patients were followed up with questionnaires

Four rock climbing, six winter climbing, one other

NS

NS

No fatalities reported. Study was of survivors with spinal injuries from mountaineering

Incidence of spinal cord injury was less than in the overall group of spinal injury patients. Most of the 21 patients studied had other significant and potentially distracting injuries

McIntosh et al.[61] (2007)

School teaching outdoor training and wilderness skills taught at the National Outdoor Leadership School (Lander, WY, USA)

Retrospectively evaluated medical incidents and evacuations from National Outdoor Leadership School from 2002 to 2005; mean age of participants was 22 y

0.071 NACA 1a; 0.074 NACA 1–3a; 0.0056% NACA 2–3a

92% NACA 1b; 7.6% NACA 2–3b; none >NACA 3b

None

NS

McIntosh et al.[62] (2008)

Mountaineering (Mt McKinley [or Mt Denali] in Alaska, 6194 m)

Retrospectively reviewed fatalities from 1903 to 2006

0.063 for fatalitiesa

NS

3.08/1000 summit attempts, or 100/ 1 million exposure days on Mt Denali

Fatality rate is declining

McLennan and Ungersma[63] (1982)

Mountaineering (Sierra Nevada, Columbia; peaks up to 5700 m)

Retrospectively reviewed 5 y of accidents and their possible causes when climbing Class V routes

NS

NS

17 deaths, mostly from head injuries

Poor acclimatization with acute mountain sickness and hypothermia found in 104 patients, resulting in poor judgemental errors

215 mountaineering accidents; 94 involved ankle and lower tibia, 17 deaths mostly involved head injuries

a

Injuries/fatalities per 1000 h calculated by the authors according to the information given in the study.

b

NACA score graded by the authors according to the information given in the study.

DAV = German Alpine Club; F = females; M = males; NACA = National Advisory Committee for Aeronautics; NS = not specified.

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Study (year)

Rock and Ice Climbing

Fig. 1. Modern sport climbing, protected with bolts.

body swings into the wall with outstretched legs typically absorbing the impact.[4] More recently, Nelson and McKenzie[53] analysed American hospital emergency room records from 1990 to 2007 using data from the National Electronic Injury Surveillance System (NEISS) of the US Consumer Product Safety Commission. These reviewers also found that most of the climbing injuries were located on the lower extremities. However, this study was unable to determine what style of climbing, time of year (i.e. winter vs summer) or where exactly the accident took place (i.e. big walls). The falls were coded by mechanism (i.e. felt a ‘pop’, overexertion, sprain), by any descriptive narrative of the accident if available, and by whether the fall was £6 m or ‡6 m. Therefore, the bias of this study may report more falls ‡6 m where lower extremity injuries are more likely to result from big swings into the wall or big ª 2010 Adis Data Information BV. All rights reserved.

669

falls. The authors claim that the discrepancy between their finding of mostly lower extremity injuries and most other studies finding mostly upper extremity injuries may be partially explained by the minor nature of many rock climbing related injuries recalled by participants in the other surveys. Another study using a similar NEISS analysis[74] on American golf cart injuries from 1990 to 2007 found significantly more golf cart injuries resulted in emergency room admissions than from climbing – an estimated 147 696 injuries versus 40 282, respectively. The NEISS data do not permit access to information regarding patient outcomes over time, or more personal data. Addiss and Baker[22] and Schussmann et al.[20] combined data from rock climbing and mountaineering when analysing injuries in US National Parks. Both studies found mountaineering to be of a higher risk than pure rock climbing. Addiss and Baker[22] also found that falls on snow or ice were longer than falls on rock, and injuries on snow or ice were more likely to be fatal. The injury rate per 1000 hours can only be found in two studies and varied markedly from 37.5[21] to 0.56.[20] For alpine climbing (traditional climbing), a death rate (fatality rate) was documented by Bowie et al.[21] – 13 from 220 injured climbers died – a case fatality rate of 6%. This case fatality rate was much smaller than older US records

Fig. 2. Boulderer and protection (for protection a spotter [who works to direct the climber’s body toward the crash pad during a fall, while protecting the climber’s head from hazards] and a bouldering mat [crash pad] is used).

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Performing hard moves was the most common cause for overuse injuries.[52] In traditional climbing, falls lead to the most injuries, while in sport climbing performing strenuous moves tended to be the cause.[16,19] Overall, the majority of all injuries in these climbing studies was of minor severity (NACA 1 and 2),[15,16,18,20-22,29,53] with a fatality rate ranging from 0% to 28%.[22,51] The vast span in between these numbers must be further evaluated through ongoing studies, and may reflect the bias of injuries recorded in the study. Fig. 3. Indoor bouldering.

3.2 Indoor Rock Climbing

from 1951 to 1960 that recorded 41%,[75] 19% for the Grand Tetons[20] in 1982 and 8% for Sierra Nevada.[63] Schussmann et al.[20] calculated an incidence of 2.5 accidents/1000 mountaineers/ year or 5.6 injuries/10 000 hours of mountaineering. The 25 fatalities calculated to a fatality rate of 0.13/1000 hours or a case fatality rate of 23%. The Yosemite results from Bowie et al.[21] are in accordance with the results of Hubicka[76] for European climbing areas. As most of the analyses performed in these climbing injury studies were conducted retrospectively through questionnaires, the fatality rate is frequently biased. The ‘older’ studies (20 years ago)[20-22] reported the most severe injuries and the highest fatality rates, while recently, a prospectively conducted study on bouldering[51] reported no fatalities. The few bouldering injuries recorded in this latter study,[51] also found few injury differences between indoor and outdoor bouldering, which is in accordance with the data by Gerdes et al.[16] In summary, Schussmann et al.[20] already concluded in 1990 that rock climbing has a lower injury risk than football and horse riding, but with the obvious difference that latter sports rarely result in fatalities – although this is a negotiable argument concerning horse riding.[77] Climbing frequency and difficulty were associated with the incidence of overuse injuries[29,52] in some studies, while others could not find an association.[31] Most injuries occur when lead climbing,[12,19,21,22] with falls being the most common source of acute injuries.[12,19,21,22,53] ª 2010 Adis Data Information BV. All rights reserved.

Several studies explored injuries and injury rates in indoor and indoor competition climbing. Wright et al.[10] evaluated the frequency of overuse injury during the indoor 1999 World Cup Championship (n = 295) where 44% of the respondents had sustained an overuse injury, 19% at more than one site. Wright et al.[10] found

Fig. 4. Ice climbing.

Sports Med 2010; 40 (8)

Rock and Ice Climbing

an independent correlation to increased injuries (p < 0.01) when (i) climbing harder routes; (ii) bouldering or leading versus top rope climbing; and (iii) climbing for more than 10 years. Multivariate analysis removed the effect of sex as an independent predictor. Jones et al.[52] similarly found increased numbers of overuse injuries or injuries caused by strenuous moves and less from fall-related injuries than in traditional and outdoor sport climbing.[12,19,21,22] Two large-scale studies[8,23] analysed indoor climbing injuries. Limb[23] reported 55 accidents from 1.021 million climbing wall visits and no fatalities. Scho¨ffl and Winkelmann[8] prospectively surveyed 25 163 registrants at ten climbing walls. Only four significant injuries (NACA 3) were found and no fatalities; the injury risk per visit was 0.016% or 0.079 injuries/1000 hours of performance.[8] A higher injury risk rate of 3.1/1000 hours was found at the 2005 World Championships,[5] where 18 acute medical problems were treated (including 13 cases of skin bruising (see table VI). In summary, these indoor climbing studies demonstrated a very minor injury risk and severity compared with traditional climbing and various other sports.[5,8,23] Overuse injuries were commonly reported in upper limbs, with the finger most affected. No study reported a fatality rate, even though fatalities do occur when climbing indoors. Causation of these rare fatalities need to be addressed in future studies to distinguish whether climbing misadventure or pre-existing co-morbidities contributed most to any death.[50] 3.3 Ice Climbing

Although ice climbing is a popular sport, very little data on injuries and accidents exist. Schindera[99] reported on general 12 general glacier injuries where six patients fell into glacial crevasses and the other six slid down a glacier ice field. Patterson[100] reports about ice climbing in prose style. Mosimann[45] evaluated 46 rescued ice climbers for a non-peer-reviewed journal Bergundsteigen, a risk-management magazine for the German, Swiss and Austrian Alpine Clubs. ª 2010 Adis Data Information BV. All rights reserved.

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Scho¨ffl et al.[1] evaluated 88 ice climbers using a retrospective questionnaire where both iceclimbing frequency and risk behaviour were evaluated, and injuries and accidents were rated using the NACA score. In these latter two studies, most of the injuries were of minor severity. Scho¨ffl et al.[1] found mainly open wounds (55.2%) and haematomas (21.9%), 71% were NACA 1, and no injury scored above NACA 3. The injury incidence was 4.07/1000 hours for NACA 1–3 with 2.87/1000 hours in NACA 1, and none in NACA 4–7. Of 46 ice climbers rescued over 6 years, Mosimann[45] found 31% had no injury (NACA 0), 42% had NACA 2–3 injuries, 8% had NACA 4, 6% NACA 5, and 13% (6 climbers) had a fatal injury (NACA 7). The most frequent cause of injury was falls (55%), although no fatal injury was caused by a fall. The percentile death risk (fatality rate), which the author defined as the percentile portion of deaths in reference to the sum of all known emergencies, was reported as 13% for ice climbing. The author claimed the fatality risk was higher for ice climbing than in mountaineering (8%), ski mountaineering (7.5%) and rock climbing (4%), but gave no reference for these data. Since 1951, the American[54] and Canadian Alpine Clubs[55] recorded details of all mountain accidents in their respective climbing areas up to 2005. The American Alpine Club report[54] recorded 6111 mountaineering accidents. The Canadian Alpine Club[55] recorded 958 accidents and then separately analysed ice-climbing accidents over a 30-year period to reveal 92 mountaineers were injured while ice climbing, 30 were fatal. The German Alpine Club recorded iceclimbing accidents that were reported to their insurance cover provider. From 2004 to 2005, 150 climbing accidents were recorded, with 12% of all accidents occurring in mountain sports.[50] Alpine mixed climbing was recorded in 8% of all accidents, water ice-climbing was 6%. In summary, these studies demonstrated a small percentage of accidents had occurred on ice terrain. The limited data specifically on iceclimbing injuries showed a minor injury risk and some fatalities. Sports Med 2010; 40 (8)

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Table VI. Injury risk per 1000 hours of sport performance of various sports Sport

Type of athlete studied

Injuries per 1000 hours

Rugby

Amateurs, competition

283

References 78

Rugby

Professionals, competition; summer/winter

150/52

79

Ice hockey

Professionals

83

80

Rugby

Youth

57

81

Handball

F, competition

50

82

Soccer

M, competition/training UEFA Champions League

31.6/3–5

83

Traditional climbing 20 y ago

NS

37.5

21

Motorbike

Competition, professionals – race course, cross, trial

22.4

84

American football

German first league

15.7

85

Handball

M, competition/training

14.3/0.6

86

Basketball

Professionals and amateurs, M and F

9.8

87

Soccer

M, professionals overall injury risk

9.4

83

Sailing

Yacht sailing, professionals, competition and training

8.8

88

Polo

Competition

7.8

89

Kite surfing

NS

7

90

Volleyball

School children, training

6.7

91

Ice climbing

NS

4.07

Soccer

F, German first league

3.1/1.4

1 92

Competition climbing

NS

3.1

5

Triathlon

NS

2.5

93

Boxing

Amateur and professionals

2

94

Mountain biking

NS

1

95

Ski/snowboard

NS

1

96

Nordic walking

NS

0.9

97

Mountaineering and traditional climbing

NS

0.56

20

Surfing

NS

0.41

98

Indoor climbing

NS

0.079 0.027

8 23

F = female; M = male; NS = not specified; UEFA = Union of European Football Associations.

4. Comparison of Climbing to Mountaineering As the collective skills of all forms of rock and ice climbing are required when mountaineering a comparison with mountaineering activities is important. Mountaineering may include hiking, expeditions and mixed and Alpine climbing, to climbing the highest point in the world – Mount Everest (8850 m). All these activities present different physiological demands and involve different risks – from altitude-induced illnesses (beginning from around 2500 m) to diagnosing and managing all medical problems in the wilderness.[12,19-22,28,54,60,62,99,101-113] Most studies on mountaineering fatalities and accidents present ª 2010 Adis Data Information BV. All rights reserved.

the fatality/accident number per 1000 climbers or per 1000 summits, making direct comparison with sporting studies reporting injuries 1000 hours of sports performance difficult. McIntosh et al.[61] evaluated medical incidents at a US outdoor/wilderness school. Injuries occurred at a rate of 1.18 per 1000 programme days. Only 5% of the injuries resulted from the programme’s supervised rock climbing; 44% resulted from hiking with a backpack. Stephens et al.[57] similarly found hiking (58%) was the most common activity at the time of death in a fatality and 26% in mountaineering. McIntosh et al.[62] also reviewed mountaineering fatalities on Mount McKinley, Alaska (6194 m). More recently, fatality rates have declined to 3.08 of Sports Med 2010; 40 (8)

Rock and Ice Climbing

1000 summit attempts. McIntosh et al.[62] found this fatality rate to be 20 times higher than those given for trekkers hiking in Nepal by Shlim and Houston[113] and even higher than those for English and Welsh mountaineers.[114] McIntosh et al.[62] adjusted denominators to allow comparison and reported a fatality rate of 100/1 million exposure days on Mount McKinley, or a calculated fatality rate of 0.063/1000 hours. Malcom,[56] reported mountaineering fatalities on Mount Cook in New Zealand and found it to be 1.87/1000 exposure days, or a calculated 0.12 fatalities per 1000 hours of mountaineering. This figure seems extremely high and may have been the product of estimated exposure days based on hut night stays, rather than actual climbing days.[62] Firth et al.[59] calculated a mortality rate of 1.3% when examining causes of mortality among those who climbed Mount Everest from 1921 to 2006 (n = 192 fatalities from 28 276). Altitude-induced illnesses with neurological dysfunction or co-morbidities may have contributed to fatal falls (n = 113) or body disappearances (n = 27), but could not be confirmed. Pollard and Clarke,[115] similarly found that at extreme altitude, 70–80% of mountaineering deaths were related to environmental factors. Monasterio[58] prospectively surveyed 46 rock climbers/mountaineers over 4 years to determine the type and frequency of accidents. Monasterio[58] reported five deaths – one unrelated to climbing, two in avalanche and two from climbing misadventure. Unfortunately, neither Monasterio nor Pollard and Clarke reported climbing frequency during the study period. When summarizing the comparison of rock and ice climbing to mountaineering, the latter showed a higher injury and fatality rate. On 8000 m peaks, ascent success rates declined with summit height, but overall death rates, and death rates during descent from the summit, increased with summit height.[59,105] 5. Injury Risk Compared with Other Sports When comparing injury risk among different sports, the relative injury risk per 1000 hours of sport exposition is a useful and established paraª 2010 Adis Data Information BV. All rights reserved.

673

meter. Further subdivision within a specific sport can also reflect important injury risk factors. For example, the injury risk in soccer when competing was much higher than for training[83] (table VI). Similar results were reported for female soccer,[92] snowboarding,[116] handball (male and female)[82,86,117] and indoor climbing.[5,8,23] Sex differences also influence injury risk.[118] For example, the injury risk for soccer played by females was lower than for males when training versus competing.[83,92,118] In rugby, important differences exist between amateurs and professionals,[78,79] and between juniors and adults.[78,81] A comparison of the same disciplines performed either by school children or adults also shows significant differences.[119] Comparing not only the injury risk but also the seriousness of the injuries between different sports is difficult, as no standard score is present. Becker[92] evaluated all female soccer injuries or accidents, which resulted in a drop out of one playing or training unit and further assessed this injury time out according to <1, <3 or >6 weeks. An analysis of American Football injuries in the German First League graded an injury as minor if there was a competition or training dropout of up to 1 week; longer breaks or a hospital stay were graded as severe, and intensive care unit therapy or persistent neurological or orthopaedic damage was graded as fatal.[85,120] Other studies,[95,96,98] including the study by Neville et al.,[88] that evaluate injury risks in sport disciplines do not grade the injuries at all, even for combined injuries and diseases together. Spinks and McClure,[121] reviewed 48 studies that quantified the risk of injury from physical activity in children aged 5–15 years. There was no consistency in the injury definition among studies and the wide variation in reported injury rates did not necessarily represent actual differences in injury risk between activities. It is difficult to compare studies directly where a standardized injury severity and rate per 1000 hours of sports performance or equivalent is lacking, although some insight into sport-specific injuries may be possible. Fatality rates among sporting studies are even more difficult to compare as natural deaths and the influence of co-morbidities[122] on sporting fatalities are up to 30% and are not often explored.[122] Sports Med 2010; 40 (8)

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In soccer, a consensus statement on injury definition and data collection procedures was a greed under the auspices of FIFA (Fe´de´ration Internationale de Football Association) Medical Assessment and Research Centre.[123] A similar statement is desirable in other sports. In summary, Schussmann et al.[20] already concluded in 1990 that rock climbing has a lower injury risk than football and horse riding, but with the obvious difference that latter sports rarely result in fatalities which is a negotiable point when considering equine-related fatalities.[77] 6. Is Climbing a High-Risk Sport? Another aim of this study was to objectively evaluate whether climbing was a high-risk sport. Meyers encyclopaedia[124] defines extreme sports as the performance of exceptional sport disciplines where the athlete deals with high mental and physical stress. If the sport contains an objective or subjective sensed risk of damage to health or life it is considered a high-risk sport. Meyer’s definition is accurate but it does not define any real risk from the athlete’s perspective, that is, an experienced and highly skilled athlete is more likely to take and successfully manage higher perceived sporting risks compared with a novice. Kajtna and Tusak[125] define high-risk sports as any sport where one has to accept the possibility of severe injury or death as an inherent part of the activity. In contrast, Backx et al.[91] characterized high-risk sports as those performed mostly indoors with a high jump or contact rate, as in volleyball or basketball. Some authors substitute the terms ‘high-risk sport’ and ‘extreme sports’ or these terms interchangeably. Young[126] included climbing under the term ‘extreme sports’, together with inline skating, snowboarding, mountain biking etc. Young[126] stated that the category of extreme sports was fluid and the definition was inexact. In support of Young’s view, it is not known what selection criteria were for an ‘extreme sport’ to be included in the popular media event called the X-Games, a commercial annual sports event in the US. Climbing was occasionally represented in this annual event. ª 2010 Adis Data Information BV. All rights reserved.

Sport disciplines that are performed by a large population are subjectively considered harmless.[127] Therefore, more mainstream sports such as soccer, handball or rugby are not perceived or characterized as high-risk sports, even though they have a high risk of injury. A sport such as kite surfing reported a modest injury rate (7/1000 hours)[90] in a 6-month prospective study (n = 235). However, the injury incidence and severity rate was high and even recorded a fatality (124 injuries, 11 severe injuries and 1 fatal).[90] When assessing whether climbing should be considered a high-risk sport it is obvious that each climbing sub-discipline implicates different levels and types of risk of injury and fatality. When climbing outdoors, there are objective dangers and physical hazards such as variable rock and ice quality, extreme weather conditions, weapon-like equipment (ice climbing), difficult approaches and high mental and physical stress. In mountaineering, additional environmental factors can sometimes directly influence injuries and fatalities (e.g. avalanches, crevasses, altitudeinduced illnesses with neurological dysfunction) but these situations can still be avoided or sometimes successfully managed (e.g. using weather forecasts, training in alpine climbing/rescue skills, obtaining knowledge of local terrain, climbing permits, acclimatization and awareness of altitude-induced illnesses, access to helicopter mountain rescue). In contrast, with indoor and sport climbing, these objective and external dangers are greatly reduced but, nevertheless, a risk of a fatal injury is still given. The vast majority of climbers manage the above inherent risks with their climbing experience and skills, thereby avoiding serious injuries and even fatality. Sport and indoor-climbing, including competitions, cannot be considered as high-risk sporting activities. 7. Limitations of the Analysis The heterogeneity of the data collected in the various individual studies may limit the conclusions. In some studies, the narrative or data presented on injuries did not always distinguish whether the ‘climbing accident’ occurred while Sports Med 2010; 40 (8)

Rock and Ice Climbing

actively climbing or perhaps when walking or hiking towards the route. Was the accident a result of equipment failure or climbing misadventure? It is mostly unknown whether any coexisting health morbidities contributed or caused many sporting accidents or deaths. There may also be an underreporting of climbing injuries, especially the deaths associated with the sport as no mandatory reporting is required and the studies are often based upon retrospective survey data. The survey-based studies may suffer from recall bias of the participants, as well as misclassification bias by the investigators. Other limitations include possible sampling bias of these investigators (possibly not incorporating all of the studies), and difficulties in abstracting and manipulating data reported in previous publications. The calculation of climbing days into hours may also contain miscalculations. Internationally, there is no standardized method of recording climbing accidents by representative climbing bodies or otherwise. Such limitations may have resulted in a more descriptive study being realized. In addition, all the authors are experienced rock climbers. This may have resulted in a bias, but it was also important when interpreting data (i.e. the specific geographical location of the study will suggest climbing styles, the nationality of climbers may also suggest climbing styles and techniques). Many non-climbing people, including researchers, do not differentiate among the different climbing styles because they are unaware of such differences. Rock climbing is a multi-disciplined sport. Depending on the subdiscipline examined, the climber’s experience and skills, grade of route difficulty, equipment, climbing surface (e.g. type of rock or ice, artificial indoor wall, scree), the remoteness of location, altitude and weather will implicate different levels of risk. In addition to these variables, many climbers regularly participate in more than one climbing sub-discipline. Such data need to be understood in climbing injury studies. The present authors have all experienced injuries when rock climbing and have had friends die when climbing. We are also members of the International Medical Commissions for the UIAA providing advice to more than 7 million ª 2010 Adis Data Information BV. All rights reserved.

675

climbers in 76 countries (V.S., T.K., A.M.) and for the International Federation of Sport Climbing (IFSC) [V.S.], and the Safety Commission of the German Alpine Club (V.S.). We deal with climbing injuries and injury analysis on a regular basis both in document form, and even when medically treating patients (V.S., T.K.). We are obviously aware of the risks involved when climbing and wish to initiate a more comprehensive sport-specific reporting of such injuries and fatalities to objectively educate everyone about the real risks associated with climbing sports, and to promote evidence-based best practice with the sport itself. 8. Conclusions Scientific epidemiological analysis of sportspecific injuries helps to inform preventative measures that can target the injury incidence and reduce their severity, even potential fatality. It may even provide the robust criteria desirable in an objective and standardized definition of a ‘high-risk’ sport, which is currently lacking. According to the above definitions, few sports would qualify as not being a high-risk sport, including basketball, mountain biking, handball, soccer (contact sports) and horse riding (danger of potential fatality). Sporting fatalities should also ideally be assessed to determine whether coexisting morbidities contributed or caused the death, as opposed to sporting participation. Of all the sports objectively analysed, indoor climbing reported the fewest injuries per 1000 hours of participation, and no fatalities. Other climbing sub-disciplines similarly reported a low injury incidence relative to mainstream sports assessed, along with a low injury severity grade. However, overuse injuries of minor severity involving the upper limbs, notably the finger, are commonly reported in rock climbing studies. Nevertheless, a small number of fatalities do occur in all climbing disciplines, mainly in alpine and ice climbing. This must be further explored in future studies, both in terms of organized and individual sporting participation. When determining the relative injury risk in any sport, we suggest using the NACA injury Sports Med 2010; 40 (8)

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severity scoring system, for accuracy and simplicity, to evaluate 1000 hours of sport exposition. However, it is a pre-hospital score and lacks information about patient outcome – specifically, did a fatality ultimately result from a patient with a NACA score of 4 to 6 during the hospital stay? Therefore, additional information on how an injury was sustained and the final outcome would add completeness to sporting risk assessment. An international consensus statement for climbing and mountaineering is currently being drafted by the Medical Commissions of the UIAA and IFSC.[2,3]

14.

15.

16.

17. 18.

19.

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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55. Canadian Alpine Club. Accidents in North American mountaineering: Canadian Alpine Club, 2005. Available from URL: http://www.alpineclub-edm.org/accidents/ type.asp?type=Ice+Climbing [Accessed 2007 Dec 30] 56. Malcom M. Mountaineering fatalities in Mt Cook National Park. N Z Med J 2001; 114 (1127): 78-80 57. Stephens BD, Diekema DS, Klein EJ. Recreational injuries in Washington State National Parks. Wilderness Environ Med 2005; 16 (4): 192-7 58. Monasterio ME. Accident and fatality characteristics in a population of mountain climbers in New Zealand [abstract]. N Z Med J 2005 Jan 28; 118 (1208): U1249 59. Firth PG, Zheng H, Windsor JS, et al. Mortality on Mount Everest, 1921-2006: descriptive study [abstract]. BMJ 2008; 337: a2654 60. Hearns ST, Fraser MH, Allan DB, et al. Spinal injuries in Scottish mountaineers. Wilderness Environ Med 2006 Fall; 17 (3): 191-4 61. McIntosh SE, Leemon D, Visitacion J, et al. Medical incidents and evacuations on wilderness expeditions. Wilderness Environ Med 2007; 18: 298-304 62. McIntosh SE, Campbell AD, Dow J, et al. Mountaineering fatalities on Denali. High Alt Med Biol 2008 Spring; 9 (1): 89-95 63. McLennan JG, Ungersma J. Mountaineering accidents in the Sierra Nevada. Am J Sports Med 1982; 11: 160-3 64. Scho¨ffl V. Sportklettern. In: Engelhardt M, editor. Sportverletzungen: Elsevier, Urban & Fischer, 2006: 455-60 65. Hochholzer T, Scho¨ffl V. One move too many. Ebenhausen: Lochner Verlag, 2003 66. Carmeli E, Wertheim M. Handverletzungen bei jugendlichen und erwachsenen sportkletterern: hand injuries in young and old wall climbers. Dtsch Z Sportmed 2001; 52 (10): 285-8 67. Bollen SR. Upper limb injuries in elite rock climbers. J R Coll Surg Edinb 1990 Dec; 35 (6 Suppl.): S18-20 68. Bollen SR. Injury to the A2 pulley in rock climbers. J Hand Surg [Br] 1990 May; 15 (2): 268-70 69. Bollen SR, Gunson CK. Hand injuries in competition climbers. Br J Sports Med 1990 Mar; 24 (1): 16-8 70. Kubiak EN, Klugman JA, Bosco JA. Hand injuries in rock climbers. Bull NYU Hosp Joint Dis 2006; 64 (3-4): 172-7 71. Scho¨ffl V. Handverletzungen beim klettern: hand injuries in rock climbing. Dtsch Z Sportmed 2008; 59 (4): 85-90 72. Scho¨ffl V, Scho¨ffl I. Finger pain in rock climbers-reaching the right differential diagnosis. J Sports Med Phys Fitness 2007; 47 (1): 70-8 73. Scho¨ffl V, Winkelmann HP. FuXdeformita¨ten bei sportkletterern: footdeformations in sportclimbers. Dtsch Z Sportmed 1999; 50: 73-6 74. Watson DS, Mehan TJ, Smith GA, et al. Golf cart-related injuries in the US. Am J Prev Med 2008 Jul; 35 (1): 55-9 75. Ferris BG. Mountain-climbing accidents in the United States. N Engl J Med 1963; 268: 430-1 76. Hubicka E. Rock climbing injuries sustained at the training centre in Cesky Raj (author’s transl) [article in Czech]. Acta Chir Orthop Traumatol Cech 1977 Feb; 44 (1): 77-82

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77. Chitnavis JP, Gibbons CL, Hirigoyen M, et al. Accidents with horses: what has changed in 20 years? Injury 1996 Mar; 27 (2): 103-5 78. Gabbett TJ. Incidence of injury in amateur rugby league sevens. Br J Sports Med 2002 Feb; 36 (1): 23-6 79. Gissane C, Jennings D, Kerr K, et al. Injury rates in rugby league football: impact of change in playing season. Am J Sports Med 2003 Nov-Dec; 31 (6): 954-8 80. Molsa J, Kujala U, Nasman O, et al. Injury profile in ice hockey from the 1970s through the 1990s in Finland. Am J Sports Med 2000 May-Jun; 28 (3): 322-7 81. Gabbett TJ. Incidence of injury in junior rugby league players over four competitive seasons. J Sci Med Sport 2008; 11 (3): 323-8 82. Wedderkopp N, Kaltoft M, Lundgaard B, et al. Prevention of injuries in young female players in European team handball: a prospective intervention study. Scand J Med Sci Sports 1999 Feb; 9 (1): 41-7 83. Ekstrand J, Walden M, Hagglund M. Risk for injury when playing in a national football team. Scand J Med Sci Sports 2004 Feb; 14 (1): 34-8 84. Tomida Y, Hirata H, Fukuda A, et al. Injuries in elite motorcycle racing in Japan. Br J Sports Med 2005 Aug; 39 (8): 508-11 85. Baltzer AW, Ghadamgahi PD. American football injuries in the German Federal League: risk of injuries and pattern of injuries. Unfallchirurgie 1998 Apr; 24 (2): 60-5 86. Seil R, Rupp S, Tempelhof S, et al. Sports injuries in team handball: a one-year prospective study of sixteen men’s senior teams of a superior nonprofessional level. Am J Sports Med 1998 Sep-Oct; 26 (5): 681-7 87. Cumps ED, Verhagen E, Annemans L. Injury risk and socio-economic costs resulting from sports injuries in Flanders. Data derived from Sports Insurance Statistics 2003. Br J Sports Med 2007; 42 (9): 767-2 88. Neville VJ, Molloy J, Brooks JH, et al. Epidemiology of injuries and illnesses in America’s Cup yacht racing. Br J Sports Med 2006 Apr; 40 (4): 304-11; discussion 11-2 89. Costa-Paz M, Aponte-Tinao L, Muscolo DL. Injuries to polo riders: a prospective evaluation. Br J Sports Med 1999 Oct; 33 (5): 329-31; discussion 31-2 90. Nickel C, Zernial O, Musahl V, et al. A prospective study of kitesurfing injuries. Am J Sports Med 2004; 32 (4): 921-7 91. Backx FJG, Beijer HJM, Bol E, et al. Injuries in high-risk persons and high-risk sports. Am J Sports Med 1991; 19: 124-30 92. Becker A. Verletzungen im FrauenfuXball. Homburg/Saar: Homburg, 2006 93. Burns J, Keenan A, Redmond A. Factors associated with traithlon-related overuse injuries. J Orthop Sports Phys Ther 2003; 33: 177-84 94. Zazryn T, Cameron P, McCrory P. A prospective cohort study of injury in amateur and professional boxing. Br J Sports Med 2006 Aug; 40 (8): 670-4 95. Gaulrapp H, Weber A, Rosemeyer B. Injuries in mountain biking. Knee Surg Sports Traumatol Arthrosc 2001; 9 (1): 48-53 96. Aschauer E, Ritter E, Resch H, et al. Injuries and injury risk in skiing and snowboarding. Unfallchirurg 2007 Apr; 110 (4): 301-6

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97. Knobloch K, Vogt PM. Nordic pole walking injuries: nordic walking thumb as novel injury entity. Sportverletz Sportschaden 2006 Sep; 20 (3): 137-42 98. Dau I, Dingerkurs ML, Lorenz S. Verletzungsmuster beim wellenreiten: injury patterns in surfing. Dtsch Z Sportmed 2005; 56 (12): 410-4 99. Schindera ST, Triller J, Steinbach LS, et al. Spectrum of injuries from glacial sports. Wilderness Environ Med 2005 Spring; 16 (1): 33-7 100. Patterson R. On thin ice: a rather personal look at the hazards of winter climbing. CMAJ 1992 Mar 15; 146 (6): 1041-7 101. Berghold F. Sportmedizinische Aspekte des Wanderns und Bergsteigens im Hochgebirge. Schweiz Z Sportmed 1982; 30: 5-12 102. Bunting CJ, Little MJ, Tolson H, et al. Physical fitness and eustress in the adventure activities of rock climbing and rappelling. J Sports Med Phys Fitness 1986 Mar; 26 (1): 11-20 103. Burdick TE, Brozen R. Wilderness event medicine. Wilderness Environ Med 2003 Winter; 14 (4): 236-9 104. Hartsock LA, Feagin Jr JA, Ogilvie BC. Climbing and the older athlete. Clin Sports Med 1991 Apr; 10 (2): 257-67 105. Huey RB, Eguskitza X. Limits to human performance: elevated risks on high mountains. J Exper Biol 2001 Sep; 204 (Pt 18): 3115-9 106. Madorsky JG, Kiley DP. Wheelchair mountaineering. Arch Phys Med Rehabil 1984 Aug; 65 (8): 490-2 107. Malcolm M. Mountaineering fatalities in Mt Cook National Park. N Z Med J 2001 Mar 9; 114 (1127): 78-80 108. Patscheider H. Morphologic findings in fatal mountainclimbing accidents. Schweiz Z Sportmed 1971; 19 (4): 7-27 109. Rettig A. Mountain climbing accidents: measures and problems in first aid. Osterr Schwesternztg 1973 Jul-Aug; 26 (8): 174-7 110. Townes DA. Wilderness medicine. Prim Care 2002 Dec; 29 (4): 1027-48 111. Wilson R, Mills Jr WJ, Rodgers DR, et al. Death on Denali. West J Med 1978 Jun; 128 (6): 471-6 112. Zafren K, Durrer B, Herry JP, et al. Lightning injuries: prevention and on-site treatment in mountains and remote areas: official guidelines of the International Commission for Mountain Emergency Medicine and the Medical Commission of the International Mountaineering and Climbing Federation (ICAR and UIAA MEDCOM). Resuscitation 2005 Jun; 65 (3): 369-72 113. Shlim DR, Houston R. Helicopter rescues and deaths among trekkers in Nepal. JAMA 1989; 261: 1017-9 114. Avery JG, Harper P, Ackroyd S. Do we pay too dearly for our sport and leisure activities? An investigation into fatalities as a result of sporting ane leisure activities in England and Wales. Public Health 1990; 104: 417-23 115. Pollard A, Clarke C. Deaths during mountaineering at extreme altitude [abstract]. Lancet 1988; I: 1277 116. Ku¨pper T, Huber N, Netzer N, et al. Rehabilitation and recovery training after snowboard accidents. Med Sport 2009; 13 (1): 1-4 117. Wedderkopp N, Kaltoft M, Lundgaard B, et al. Injuries in young female players in European team handball. Scand J Med Sci Sports 1997 Dec; 7 (6): 342-7

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118. Renstrom P, Ljungqvist A, Arendt E, et al. Non-contact ACL injuries in female athletes: an International Olympic Committee current concepts statement. Br J Sports Med 2008 Jun; 42 (6): 394-412 119. Ku¨pper T, Patig G, Hotz S, et al. Secondary prevention of accidents in school sports: does the teacher’s education fit with the demands at school? Med Sport 2008; 12 (4): 155-9 120. Baltzer AW, Ghadamgahi PD, Granrath M, et al. American football injuries in Germany: first results from Bundesliga football. Knee Surg Sports Traumatol Arthrosc 1997; 5 (1): 46-9 121. Spinks AB, McClure RJ. Quantifying the risk of sports injury: a systematic review of activity-specific rates for children under 16 years of age. Br J Sports Med 2007; 41: 548-57 122. Turk EE. Natural and traumatic sports-related fatalities. Br J Sports Med 2008; 42 (7): 604-8 123. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement of injury definitions and data collection procedures in studies of football (soccer) injuries. Scand J Med Sci Sports 2006; 16: 83-92

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124. Meyers. Meyers LexikonOnline 2.0. 2008 [online]. Available from URL: http://www.lexikon.meyers.de/meyers/ extremsport [Accessed 2008 Jan 16] 125. Kajtna T, Tusak M. Some psychological studies of high risk sports. Kinesiol Slovenica 2004; 10 (1): 96-105 126. Young CC. Extreme sports: injuries and medical coverage. Curr Sports Med Rep 2002 Oct; 1 (5): 306-11 127. Henke T, Glaser H. Die Risikobewertung der verschiedenen Sportarten-Epidemiologie von Sportverletzungen. In: Bergler R, editor. Irrationalita¨t und Risiko Gesundheitliche Risikofaktoren und deren naturwissenschaftliche und psychologische Bewertung. Ko¨ln: Ko¨lner Universita¨tsverlag, 2000: 300-18

Correspondence: Priv.-Doz. Dr.med. Volker Scho¨ffl MHBA, Department of Sportorthopedics, Orthopedic and Trauma Surgery, Klinikum Bamberg, Bugerstr. 80, 96049 Bamberg, Germany. E-mail: [email protected]

Sports Med 2010; 40 (8)

REVIEW ARTICLE

Sports Med 2010; 40 (8): 681-696 0112-1642/10/0008-0681/$49.95/0

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Energy Expenditure and Metabolism during Exercise in Persons with a Spinal Cord Injury Michael Price Department of Biomolecular and Sports Sciences, Faculty of Health and Life Sciences, Coventry University, Coventry, UK

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Muscle Mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Sympathetic Nervous System Innervation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Energy Expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Resting Energy Expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Active versus Inactive Persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Predicted Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Energy Expenditure During Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Endurance Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Handbiking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Team Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Other (Individual) Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.5 Comparison to Able-Bodied Equivalent Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.6 Training versus Competition Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Metabolic Responses to Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Incremental Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Prolonged Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Glucose Feeding Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

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Resting energy expenditure of persons with a spinal cord injury (SCI) is generally lower than that seen in able-bodied (AB) individuals due to the reduced amounts of muscle mass and sympathetic nervous system available. However, outside of clinical studies, much less data is available regarding athletes with an SCI. In order to predict the energy expenditure of persons with SCI, the generation and validation of prediction equations in relation to specific levels of SCI and training status are required. Specific prediction equations for the SCI would enable a quick and accurate estimate of energy requirements. When compared with the equivalent AB individuals, sports energy expenditure is generally reduced in SCI with values representing 30–75% of AB values. The lowest energy expenditure values are observed for

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sports involving athletes with tetraplegia and where the sport is a static version of that undertaken by the AB, such as fencing. As with AB sports there is a lack of SCI data for true competition situations due to methodological constraints. However, where energy expenditure during field tests are predicted from laboratory-based protocols, wheelchair ergometry is likely to be the most appropriate exercise mode. The physiological and metabolic responses of persons with SCI are similar to those for AB athletes, but at lower absolute levels. However, the underlying mechanisms pertaining to substrate utilization appear to differ between the AB and SCI. Carbohydrate feeding has been shown to improve endurance performance in athletes with generally low levels of SCI, but no data have been reported for mid to high levels of SCI or for sport-specific tests of an intermittent nature. Further research within the areas reviewed may help to bridge the gap between what is known regarding AB athletes and athletes with SCI (and other disabilities) during exercise and also the gap between clinical practice and performance.

Although there are a range of studies examining resting energy expenditure in clinical situations, limited evidence exists regarding the energy expenditure of specific wheelchair sports and activities. Persons who have a spinal cord injury (SCI) demonstrate a reduced muscle mass and sympathetic nervous system (SNS) available for exercise,[1,2] and subsequently reduced peak physiological responses when compared with ablebodied (AB) individuals.[3,4] As a consequence, the absolute power output representing, for ex. ample, 60% peak oxygen uptake (VO2peak) is lower for those with an SCI than for the AB. Therefore, energy expenditure values during exercise at a given relative workload are generally lower for those with SCI when compared with the AB.[5] As current guidelines for carbohydrate and fluid provision relate to and are based on data from AB athletes, there is a limited evidence base for nutritional recommendations specific to SCI individuals. This review will consider what is currently known regarding energy expenditure in persons with an SCI, referring to specific athlete groups where possible, and will attempt to answer the following key questions: how may SCI affect energy expenditure?; how may exercise metabolism be affected by SCI?; and how much energy should be replaced during exercise in athletes with SCI? Literature searching was undertaken via MEDLINE using the following general search ª 2010 Adis Data Information BV. All rights reserved.

headings: ‘energy expenditure’, ‘spinal cord injury’ and variants of ‘paraplegia’, tetraplegia’ and ‘wheelchair athlete’. Where specific physiological variables or sports were of interest, these terms were integrated into the search item. Peerreviewed journal articles up to June 2009 have been included.

1. Spinal Cord Injury SCI results in complete or incomplete transection of the spinal cord. In general, the higher the level of spinal cord lesion, the greater the loss of function. For example, where the level of injury occurs in the cervical region (tetraplegia or quadriplegia), the function of the upper limb and peak heart rate, amongst other systems, are affected due to the injury being located in the spinal region associated with the brachial plexus and motor control of the upper limb[6] and above that of the SNS.[1,2] Where the level of injury occurs in the thoracic area, lumbar area or below (paraplegia), upper limb function generally remains intact but with varying degrees of back, abdominal or lower limb function. Consequently, the level of spinal lesion determines the level of physiological system impairment. Although many physiological systems are affected by SCI, the key physiological systems to be addressed in this review relate to energy expenditure and substrate Sports Med 2010; 40 (8)

Energy Expenditure and Metabolism during Exercise in SCI

metabolism (i.e. recruitable muscle mass for exercise and the amount of SNS innervation). 1.1 Muscle Mass

With complete spinal cord transection, SCI results in paralysis of the voluntary muscles below the level of lesion. Consequently, a reduced muscle mass is available for exercise. In conjunction with factors such as reduced SNS innervation and cardiovascular function,[7] maximal exercise capacity is reduced when compared during inwith AB individuals.[3] For example, . cremental arm crank ergometry, VO2peak (2.04 vs 3.45 L/min) and peak power output (134 vs 213 W) are reduced in athletes with paraplegia when compared with AB athletes matched for training status.[3] Furthermore, athletes . with tetraplegia demonstrate a reduced VO2peak (1.26 L/min) when compared with athletes with high level paraplegia (1.70 L/min) and low level paraplegia (2.15 L/min).[4] As a consequence, the level of energy expenditure representing a given relative exercise intensity is lower in SCI than for AB individuals. 1.2 Sympathetic Nervous System Innervation

The SNS is innervated from the thoracic and lumbar regions of the spinal cord (T1–L2).[8,9] The adrenal glands, responsible for catecholamine production and release, are innervated between the fifth and ninth thoracic segments.[8] As a consequence, different levels of SCI demonstrate different amounts of SNS availability. When stimulated, this system is involved in hepatic glycogenolysis and gluconeogenesis and may have important consequences for metabolism in athletes with an SCI, especially those with higher level injuries. Schmid et al.[1,2] examined epinephrine and norepinephrine concentrations of persons with a range of SCI at rest, during graded wheelchair exercise[1] and during exercise intensities . of 60% and 100% maximal oxygen uptake (VO2max).[2] Those persons with tetraplegia demonstrated lower epinephrine and norepinephrine concentrations at rest when compared with those with paraplegia and non-disabled controls. Only ª 2010 Adis Data Information BV. All rights reserved.

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slight increases in epinephrine and norepinephrine were observed during exercise for the tetraplegia group. The attenuated epinephrine and norepinephrine responses were noted to be due to the interruption of nervous impulses from central centres and no considerable SNS stimulation.[1,2] Participants with high level paraplegia (T1–T4) demonstrated comparable norepinephrine with non-SCI participants but had lower epinephrine concentrations suggesting partial impairment to the SNS.[1] However, Stalknechte et al.[10] observed lower circulating concentrations for both epinephrine and norepinephrine for persons with high level SCI (T3–T5) when compared with. AB controls during prolonged exercise (60%VO2peak, 60 minutes). Both Steinberg et al.[11] and Frey et al.[12] observed similar norepinephrine but lower epinephrine in participants with high level SCI (T1–T6) when compared with those with low level SCI (T7–T12). Therefore, persons with tetraplegia have the greatest reduction in SNS (both norepinephrine and epinephrine) as a result of the high level of spinal lesion. Paraplegics with high level lesions and reduced SNS and adrenal gland stimulation may demonstrate norepinephrine values similar to those of the AB but a likely reduction in epinephrine concentrations. Those persons with low level SCI demonstrate a similar or augmented response to those of non-disabled groups. 2. Energy Expenditure The energy expenditure of many sports and activities in which AB individuals participate has been determined. Energy expenditure for AB activities can subsequently be estimated from tables of norm values.[13-15] Although resting energy expenditure has been examined in the SCI population, predominantly in a clinical setting, little data are available regarding the energy expenditure of wheelchair-based sports. Section 2.1 will present the key findings for resting energy expenditure (for a review, see Buchholz and Pencharz[16]) and some practical considerations before focusing upon the energy expenditure of athletes with SCI during sport and exercise. Sports Med 2010; 40 (8)

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2.1 Resting Energy Expenditure

Resting and daily energy expenditure is generally observed to be lower in persons with SCI than those without;[5,17-20] lower than predicted;[21-27] and related to lesion level.[23] For example, 24-hour resting energy expenditure values for persons with spinal injuries (C6–L3) have been reported as ~1870 kcal/day (7824 kJ/day) compared with ~2365 kcal/day (9941 kJ/day) for age-matched controls[20] (approximately 75% of control values). Lower energy expenditure values in those with SCI are generally due to the reduced muscle mass and available SNS.[16] For example, a number of studies have observed correlations between resting energy expenditure and fat-free mass.[19,20,22,27] Liusuwan et al.[20] noted that adjusting resting metabolic rate values for lean tissue mass resulted in there being no differences in energy expenditure between children (16–21 years) either with or without SCI. Furthermore, lower absolute resting metabolic rates were associated with reduced lean tissue mass.[18] Studies of resting energy expenditure have either used 24-hour data collection periods, particularly those in clinical settings,[21] or have used shorter collection periods and have extrapolated the data to 24-hour values.[22] For instance, Spungen et al.[22] measured resting energy expenditure values in persons with SCI over a 30-minute period which extrapolated to 1855 kcal/day. This value is similar to the measured 24-hour values of Monroe et al.[18] and suggests that daily energy expenditure values could be determined from shorter data collection periods. Barco et al.[21] examined this specific question in a group of 11 patients with tetraplegia (acute, isolated SCI on mechanical ventilation) during a 4-week period of the acute phase of SCI. The authors observed that 30-minute energy expenditure measurements could indeed accurately determine 24-hour energy requirements. However, it should be noted that these patients would not represent persons with SCI who are habitually active, athlete groups, values after the acute phase of rehabilitation or those of persons with paraplegia. Therefore, future research should examine resting energy expenditure in ª 2010 Adis Data Information BV. All rights reserved.

active or athlete populations with a range of SCI levels and attempt to validate shorter data collection periods. 2.1.1 Active versus Inactive Persons

Schneider et al.[28] examined resting and exercise energy expenditure values for physically active paraplegic (T10–T12) and AB persons. Resting energy expenditure values were found to be no different between the paraplegic (5.1 kJ/min; ~1.22 kcal/min) and AB groups (5.8 kJ/min; ~1.39 kcal/min). There were no dif. ferences between groups for VO2peak (29.6 and 29.3 mL/kg/min, respectively) or oxygen con. sumption (VO2) at two gas exchange thresholds. However, the SCI participants, who were all recreationally active (basketball and swimming), demonstrated anaerobic threshold values at a . greater percentage of their VO2peak, indicating a greater specific fitness. The AB group participated predominantly in team sports (basketball, rugby), with only one participating in activity involving the upper body (swimming). Consequently, this group was not specifically upperbody trained and was only recreationally active. Young trained, but not specifically upper-body trained, males have been shown to demonstrate . VO2peak values of between 38 and 42 mL/kg/min during arm crank exercise.[29,30] Furthermore, upper-body . trained athletes usually demonstrate greater VO2peak than athletes with paraplegia matched for training status.[3] The relatively greater and more specific training status of these paraplegic athletes in relation to controls may have increased their recruitable muscle mass and subsequently increased their metabolic rate. Price[5] noted lower resting energy expenditure values in well trained wheelchair athletes with an SCI (T3/4–L1; ~4.2 kJ/min; 1.07 kcal/min) than in upper-body trained AB athletes (~6.4 kJ/min; 1.53 kcal/min) matched for training status. It is important to note that this study was not specifically examining resting energy expenditure and utilized shorter (5 minutes) resting expired gas samples than may be expected for specific studies. However, these values are similar to those for athletes with SCI determined by Abel et al.[31,32] who reported resting energy expenditure values Sports Med 2010; 40 (8)

Energy Expenditure and Metabolism during Exercise in SCI

equivalent to 1.01 and 1.11 kcal/min, respectively, during 30 minutes of supine rest after an overnight fast. Interestingly, Abel et al.[32] noted that there were no differences in resting energy expenditure between athletes with tetraplegia and athletes with paraplegia, which may have been expected due to potential differences in the amount of recruitable muscle mass available between athletes with high and low level SCI. However, it was suggested that the athletes with tetraplegia may have elicited a greater development of their remaining musculature resulting in values similar to the athletes with paraplegia. Training status or activity level may therefore have significant effects on muscle mass and subsequently resting energy expenditure. Differences in daily energy expenditure between active and inactive persons with SCI (C6–L1/L2 and C6–L1) in relation to AB controls was examined by Yamasaki et al.[33] On active days, the daily energy expenditure for persons with SCI and controls did not differ, although those with lower level spinal cord lesions demonstrated greater values than those with higher lesions. The persons with SCI also showed greater heart rates than the AB over the active period. On inactive days, daily energy expenditure of the SCI group was lower than for the controls and was independent of the level of SCI, which is in contrast to previous studies in a clinical setting.[23] Importantly, on active days, those persons with high level SCI still demonstrated relatively low daily energy expenditure because of the small functional muscle mass limiting physical activity. Therefore, the level of SCI appears to be important in determining the level of habitual activity and potential energy expenditure. 2.1.2 Predicted Values

A recent review[16] reported that predicted values for resting energy expenditure overestimate actual values by between 5% and 32%. In a study of tetraplegics in the acute phase of SCI by Barco et al.,[21] the Harris Benedict equation was used to predict energy expenditure. Predicted values were modified to include an increment of 10% for bed rest activity and a 20% injury factor. Predicted values for energy expenditure (2564 kcal/day; ª 2010 Adis Data Information BV. All rights reserved.

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1.8 kcal/min) were similar to measured values (2468–2629 kcal/day) producing strong correlations between values over the 4-week period. As the authors were unable to determine compositional changes in body compartments, the prediction equation was not modified for decreases in body mass (9%) over the data collection period. If energy expenditure values could be determined from existing prediction equations and subsequently modified to provide accurate and valid estimates of energy requirements of the SCI populations, this would be of great benefit. The greater levels of resting energy expenditure observed from the use of predicted techniques for persons with SCI may be due to the use of clinical and relatively immobile populations or the wide range of SCI levels within the various groups examined. Consequently, more individualized approaches have been considered. Hayes et al.[34] examined whether heart rate values from an incremental arm crank ergometry test could be used to predict energy expenditure for activities of daily living. Using this method, actual energy expenditure values for activities of daily living were overestimated by approximately 25% when compared with values specifically measured during each activity. Whether heart rate values from a laboratory-based incremental wheelchair exercise test or field/specific activity-based protocols would produce more accurate estimations of energy expenditure should therefore be examined. Specific exercise protocols are likely to simulate activities of daily living more closely. 2.2 Energy Expenditure During Exercise

This section will examine the energy expenditure of a range of wheelchair sporting activities and will compare these values, where possible, to the equivalent AB sport. Some energy expenditure values presented, particularly those for the. AB sports, have been calculated from the mean VO2 and respiratory exchange ratio (RER) data presented in each article. 2.2.1 Endurance Events

Lakomy et al.[35] determined the physiological responses to a 5 km time trial on a treadmill in Sports Med 2010; 40 (8)

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wheelchair athletes. Performance times of approximately 20.3 minutes were achieved for ten athletes with paraplegia (T4–L1/2), and 20.6 minutes and 24.0 minutes for two athletes with . tetraplegia (both C7). VO2 for the time trial was predicted from a preliminary laboratory-based incremental treadmill test. Values of 1.50 L/min for athletes with paraplegia and 1.03 L/min for both tetraplegic athletes were predicted, approximating to 7.5 and 5.2 kcal/min, respectively. In comparison, Ramsbottom et al.[36] estimated the . VO2 of recreational AB runners during a 5 km time trial on an outdoor track. Performance times of 19.7 minutes were. achieved for this group, with an estimated VO2 of ~2.55 L/min representing 12 kcal/min. Energy expenditure for the wheelchair athletes with paraplegia would consequently be 62.5% of that achieved by the AB athletes, whereas for the tetraplegic wheelchair athletes it would be 43% of the AB value. wheelchair Knechtle et al.[37] noted that during . ergometry at 55%, 65% and 75% VO2peak, energy expenditure for athletes with paraplegia was 50–54% of that of well trained AB cyclists. 2.2.2 Handbiking

Abel et al.[31] compared the energy expenditure of handbiking and wheelchair exercise during incremental exercise tests in 25 athletes with SCI and two amputees. The handbikers were mostly active in endurance-based events and the wheelchair racers were mostly active in sprint events. Approximately half the group were members of their respective national team, whereas the others were recreationally active. At exercise intensities representing a blood lactate concentration of 2 mmol/L, energy expenditure for handbiking and wheelchair exercise were similar at 6.5 and 5.7 kcal/min (heart rates of 117 and 142 beats/min, respectively), increasing to 8.8 and 7.4 kcal/min, respectively, at 4 mmol/L blood lactate (heart rate of 146 and 165 beats/min). Heart rate was greater for the wheelchair exercise group, which was suggested to be due to these athletes being sprint rather than endurance trained, and possible differences in athlete position during propulsion between the handcycles and wheelchairs. Equivalent AB recreational runners exercising at lacª 2010 Adis Data Information BV. All rights reserved.

tate threshold pace (blood lactate of 1.9 mmol/L) for 30 minutes have produced energy expenditure values of ~18 kcal/min.[38] Energy expenditure values for the handbiking and wheelchair groups would subsequently represent 36% and 32% of the AB values, respectively. When compared with other wheelchair sports eliciting blood lactate concentrations of around 2 mmol/L, energy expenditures of 5.4 and 6.3 kcal/min for athletes with paraplegia and 4.1 kcal/min for athletes with tetraplegia have been reported.[32] Abel et al.[39] recorded the physiological responses to handbiking during a marathon competition in an athlete with a spinal cord lesion at T4. The mean energy expenditure over the event was 463 kcal/h (7.7 kcal/min) with lactate values of 4.4 mmol/L at 10 km, and 2.9 mmol/L at both 20 and 30 km. In comparison, energy expenditure values of ~13 kcal/min have been observed for AB runners during 60 minutes of treadmill running at marathon pace.[40] Interestingly, although the mean energy expenditure values over the event reported by Abel et al. are comparable to the incremental exercise test data in their previous study,[31] a maximal energy expenditure value of 758 kcal/h (12.6 kcal/min) was observed during the event. This illustrates the range of energy expenditures that may be experienced during actual competition and that these are not solely steady state values. 2.2.3 Team Sports Basketball

Although physiological responses have been examined for endurance events and during a range of prolonged and incremental laboratorybased exercise tests,[41-43] relatively little data are available regarding the energy expenditure of wheelchair-based team sports. Burke et al.[44] examined the energy expenditure of four wheelchair basketball players via the Douglas bag technique during a 30-minute practice session. Three of the athletes had SCI (T8–T10) and one was a double amputee. The mean energy expenditure for the group was 8.6 kcal/min. Interestingly, the amputee player and two players with SCI at T9 and T10 demonstrated similar values of 9.1–10.2 kcal/min, whereas the T8 player Sports Med 2010; 40 (8)

Energy Expenditure and Metabolism during Exercise in SCI

demonstrated a considerably lower value of 4.9 kcal/min. No specific reasons were given as to why these differences in energy expenditure occurred. In a later study, Bernardi et al.[45] examined the physiological responses of 14 wheelchair athletes with SCI in a range of sports via a portable metabolic analyser. All athletes had SCI with the majority being described as top level or well trained. Four basketball players (T4/L1–L2) were tested during competition with three de. monstrating similar VO2 values (1.4–1.6 L/min). One athlete who was relatively new to the sport (T10) demonstrated lower values of 0.94 L/min. . For the whole group, these VO2 values would translate to approximately 6.8 kcal/min and for the three athletes with similar responses approximately 7.4 kcal/min. Lower values than those reported by Burke et al.[44] were observed in a recent study of ten basketball players with paraplegia during basketball practice sessions (6.25 kcal/min).[32] However, the authors noted that this may have been due to either methodological differences (Douglas bags vs portable online analysis) or to the lower exercise intensities undertaken during the practice sessions examined, which were for basic endurance (aerobic) training with blood lactate values of just over 2 mmol/L. Tennis

Roy et al.[46] examined the energy expenditure responses of six wheelchair tennis players during competitive match play (n = 5 athletes with SCI [T5–T10]; n = 1 amputee, 42 years old). Athletes played each other twice and were matched according to ability. The energy expenditure of each match was predicted from heart rates obtained during each match and energy expenditure subsequently calculated from the heart rate versus . VO2 relationship obtained during an incremental arm crank ergometry test. A standard 5 kcal/L of oxygen consumed was. used in the calculations. Play represented 50% VO2peak and 69% peak heart rate, with an energy expenditure of 5.02 kcal/min, which is similar to the 5.4 kcal/min observed by Abel et al. for wheelchair tennis training sessions.[32] Roy et al.[46] also noted the total playing ª 2010 Adis Data Information BV. All rights reserved.

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time (70.4 minutes) and actual playing time (10.5 minutes, ~14.9%) for the games monitored. Although the range of heart rates and blood lactate responses reported during the wheelchair and AB games are comparable, effective playing times are shorter for the wheelchair players than for the AB (e.g. 29.3%[47] and 21.9%[48]). Differences in effective playing time may be due to a longer duration in between points and changing ends during the wheelchair game. Rugby

As well as determining the energy expenditure of wheelchair basketball and wheelchair tennis, Abel et al.[32] also determined energy expenditure values during training sessions for wheelchair rugby. Energy expenditure for wheelchair rugby (249 kcal/h; 4.2 kcal/min) was lower than for both basketball (375 kcal/h; 6.3 kcal/min) and tennis (325 kcal/h; 5.4 kcal/min). This is most likely due to the fact that wheelchair rugby is played predominantly by athletes with tetraplegia, whereas the basketball and tennis groups tested were comprised of athletes with paraplegia. Consequently, the lower functional capacity as a result of the high level SCI in tetraplegia resulted in lower energy expenditure values. 2.2.4 Other (Individual) Sports

. VO2 values have also been measured during fencing training and table tennis competition.[45] Values were found to be lower than basketball (~0.7 and ~0.5 L/min, respectively) with equivalent energy expenditure values of 3.5 and 2.6 kcal/min. When compared with predictions for AB individuals of equivalent body mass,[13] table tennis elicits 3.8 kcal/min, competitive fencing 11.2 kcal/min and recreational fencing 8.4 kcal/min. 2.2.5 Comparison to Able-Bodied Equivalent Sports

Table I shows energy expenditure values for the wheelchair sports described in sections 2.2.1–2.2.4 and values for equivalent AB sports. Energy expenditure for wheelchair sports can be seen to range between 25% and 75% of those observed for the equivalent AB activities. For . example, Smekal et al.[47] predicted VO2 for 20 AB male tennis players over 270 games. Assuming Sports Med 2010; 40 (8)

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Table I. Reported energy expenditure values for a range of wheelchair-based sports and for the equivalent able-bodied (AB) sport Wheelchair athletes activity

AB athletes activity

study

energy expenditure (kcal/min)

SCI value as % of AB

Recreational runners

Ramsbottom et al.[36]

12.0

43.0

Recreational runners (BLa 2 mmol  L-1)

Martin et al.[38]

18.0

36

7.7

Marathon pace

Loftin et al.[40]

13.0

59.2

PA

8.6

Structured basketball

McArdle et al.[13]

10.1

85.1

Bernardi et al.[45]

PA

6.5

67.3

Abel et al.[32]

PA

6.3

61.9

competitive match

Roy et al.[46]

PA

5.0

Competitive match play

Smekal et al.[47]

10.6

48.7

practice session

Abel et al.[32]

PA

5.4

Senior players

Ferrauti et al.[49]

10.0

52.4

Rugby

Abel et al.[32]

TP

4.2

Semi-professional game

Coutts et al.[50]

16.0

26.3

Fencing

Bernardi et al.[45]

PA

3.5

Competitive fencing

McArdle et al.[13]

11.2

31.3

Table tennis

Bernardi et al.[45]

PA

2.6

Table tennis

McArdle et al.[13]

3.8

68.4

study

group

energy expenditure (kcal/min)

5 km time trial

Lakomy et al.[35]

TP

5.2

PA

7.5

handbiking (BLa 2 mmol  L-1)

Abel et al.[31]

PA(Hb)

6.5

PA(Sp)

5.7

marathon

Abel et al.[31]

PA

practice session

Burke et al.[44]

competition training (endurance)

Endurance sports

62.5

32

Basketball

Tennis

BLa = blood lactate concentration; PA = athletes with paraplegia; PA(Hb) = handbiking athletes with paraplegia; PA(Sp) = sprint trained wheelchair athletes with paraplegia; SCI = spinal cord injury; TP = athletes with tetraplegia.

. a generic 5 kcal/L of VO2, this equates to approximately 637 kcal/h or 10.6 kcal/min. Similarly, Ferrauti et al.[49] observed an energy expenditure of 10.0 kcal/min for senior tennis players (47 years old and of similar age to the tennis players in the study by Roy et al.[46] . ) during treadmill running at an equivalent VO2 to that observed during tennis match play. Novas et al.[51] observed lower values of 7.4 kcal/min (1853 kJ/h) for direct measurement of 60 minutes of match play. However, this was for younger female players (18 years old) with an average rating of perceived exertion of ‘somewhat hard’ and heart rate of 146 beats/min over the session. Consequently, the exercise intensity may have been lower than for other stuª 2010 Adis Data Information BV. All rights reserved.

dies. Taking values for adult male tennis players, results in the energy expenditure for wheelchair tennis being approximately 50% of the AB game. Similarly to tennis, the energy expenditure for a structured AB basketball game can be estimated at 10.1 kcal/min.[13] A considerably lower energy expenditure of 196 kcal was measured for a ~37-minute high school basketball class (318 kcal/h; 5.3 kcal/min),[52] which would most likely be much less intense than a competitive oncourt game. When compared to the range of values for the wheelchair basketball studies cited, the wheelchair game can be estimated to be ~75% (48.5–100%) of the AB game. Sports Med 2010; 40 (8)

Energy Expenditure and Metabolism during Exercise in SCI

The greatest differences between wheelchair and AB sports appear to be observed for wheelchair rugby, fencing and endurance exercise at 2 mmol/L blood lactate. For example, one estimate of 7.9 megajoules) for energy expenditure during an AB semi-professional rugby league match (~1415 kcal/h; 16 kcal/min)[50] results in wheelchair rugby being only 26% of the AB value. The lower energy expenditure for the wheelchair players is most likely due to the lower recruitable muscle mass of tetraplegic rugby players in comparison to the larger body masses (~90 kg[50]) and consequently larger muscle mass available for exercise of AB players. Such large differences in the available muscle mass may also contribute to the sizeable differences in energy expenditures between AB running and wheelchair/handbiking exercise at lactate threshold (2 mmol/L blood lactate). Similarly, the large differences in energy expenditure for events such as fencing may be explained partly by the greater muscle mass of AB participants but also the activity pattern of the event. As wheelchair fencing is a static version of the AB sport, the activity pattern does not involve whole body movement patterns and subsequently elicits smaller energy expenditure values. Although the absolute exercise intensities and energy expenditures are much lower for wheelchair sports than those for the AB, it should be noted that the relative exercise intensities observed may be comparable in that they are within moderate to high exercise intensity zones. For example, 5 km running performance elicited 76% . for paraplegic athletes, and 85% and VO2peak . athletes[35] when 95% VO2peak for two tetraplegic . compared with 87% VO2peak for AB runners.[36] Exercise intensities during a 20-minute arm ergometry time trial for upper-body trained AB [54] have athletes[53] and athletes with paraplegia . been reported as 91% and 87% VO2peak, respectively. Similarly, wheelchair basketball can elicit 78% peak heart rate compared with 89% for the AB game,[55] and wheelchair tennis and AB tennis elicit 69% and 83% maximal heart rate, respectively.[46,56] From these studies, it would seem that paraplegic wheelchair athletes elicit physiological responses representative of high levels of exercise ª 2010 Adis Data Information BV. All rights reserved.

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intensity but, in general, the intensity of these is lower than their AB counterparts. It should be noted that it is difficult to directly compare athletes with and without SCI as methodological differences between studies (e.g. monitoring training vs competition, different competitive levels, range of exercise intensities) and other important factors such as propulsion technique compared with whole body movement are inevitable. Furthermore, the range of values recorded during each competition or testing session[39,45] have revealed that some values observed during competition or training reach values predicted as maximal[45] and, as may be expected, no one constant exercise intensity is undertaken. However, what is clear is that wheelchair sports induce lower absolute energy expenditures than their AB equivalents. Some activities elicit lower energy expenditures than others; however, these differences are most likely sport dependent. The specific responses of each sport remain to be elucidated. 2.2.6 Training versus Competition Data

An important consideration for energy expenditure assessment is whether competition or training activities are monitored. In assessing wheelchair tennis, Roy et al.[46] noted the comments of Coutts[57] in that heart rate is greater in competition conditions than for practice sessions because the opponents are hitting the ball away from each other rather than to each other as they may do in rally practice. Hoch et al.[58] observed greater catecholamine concentrations during competitive fencing when compared with non competitive situations which may contribute to differences in energy expenditure values. However, considering that athletes with tetraplegia demonstrate a much reduced catecholamine response at rest and during exercise,[1,2] it is conceivable that competitive and training responses may not affect energy expenditure as much as they do for either athletes with lower level SCI or AB athletes. However, due to the reduced functional capacity in athletes . with tetraplegia, accurate determination of VO2 and energy expenditure is essential if relative exercise intensities are to be compared. Sports Med 2010; 40 (8)

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Calorific expenditures have been predicted due to the impracticalities and invasiveness of obtaining direct measurements from actual competition and training situations. In order to overcome this, studies have examined match play where study participants play each other in a competitive manner, which may reflect more accurately the physiological demands of the game. For example, Ferrauti et al.[49] examined the physiological responses of AB tennis players . whilst running on a treadmill at the . same VO2 observed in tennis play. Although VO2 was matched, the respiratory exchange value was much greater for tennis match play, which most likely reflects the intermittent high intensity nature of the sport. Furthermore, when compared with continuous exercise at the same total energy expenditure, intermittent exercise in the AB elicits greater carbohydrate metabolism and lower fat metabolism,[59] which may have important implications for the type of fuel replaced during and after exercise. The effects of exercise protocol will most likely have the same implications for fuel use within wheelchair sports. Future research involving athletes with SCI should consider determining energy expenditure at specific race paces for endurance events and during specific intermittent team sports. However, practicalities and safety when using gas collection techniques and the logistics when assessing competitive situations may determine which sports can be easily and safely analysed. Prediction of energy expenditure for wheelchair team sports has involved incremental arm crank ergometry tests rather than wheelchair ergometry.[46] For well trained but not elite athletes who may perform equally well during arm crank and wheelchair ergometry tests,[60-63] . predictions may be relatively accurate as VO2peak and heart rate values are similar between modes. However, Yamasaki et al.[33] observed that energy expenditure predictions from arm crank ergometry tests overestimated the energy expenditure of activities of daily living in active and inactive wheelchair users. Where possible, if prediction has to be undertaken it may be more applicable for incremental wheelchair ergometry to be used. ª 2010 Adis Data Information BV. All rights reserved.

3. Metabolic Responses to Exercise Section 2.2 reviewed the gross energy expenditure of a range of wheelchair-based sport scenarios. A logical extension from this work is to consider the specific metabolic responses underlying and eliciting these energy expenditure values. Such data are of importance when considering fuel replacement during and after training and competition. Sections 3.1 and 3.2 consider metabolic responses to incremental and prolonged exercise as well as those studies examining carbohydrate feeding in wheelchair athletes. 3.1 Incremental Exercise

During incremental exercise, the RER, an indicator of metabolic substrate utilization, usually increases from resting values and reflects an increased carbohydrate metabolism. Knechtle et al.[37] compared RER responses and fat oxidation in trained wheelchair athletes and trained AB cyclists at different exercise intensities. Athletes exercised for 20 minutes at . 55%, 65% and 75% of their ergometer-specific VO2peak (arm crank ergometry or cycle ergometry for the SCI and AB, respectively). For both groups, the highest absolute fat oxidation rate (0.24 vs 0.70 g/min) and energy expenditure (9.5 vs 17.5 kcal/min. for the SCI and AB, respectively) was at 75% VO2peak, whereas the greatest . relative fat oxidation rate occurred at 55% VO2peak (31% vs 40%, respectively). In a later study, Knechtle et al.[64] observed similar results for endurance-trained male and female athletes with SCI (C5–T4, spina bifida and poliomyelitis) during wheelchair ergometry. Fat . oxidation decreased from 31% at 55% VO 2peak to . 21% at 75% VO2peak. Conversely, carbohydrate metabolism increased from 69% to 79%, respectively, as exercise intensity increased and was considered similar to that of AB athletes during comparable incremental exercise. 3.2 Prolonged Exercise

A number of laboratory-based studies have examined the physiological responses of athletes with SCI during prolonged steady-state exercise conditions. These studies have been primarily Sports Med 2010; 40 (8)

Energy Expenditure and Metabolism during Exercise in SCI

concerned with physiological responses,[10,35,41] thermoregulation[60,65,66] or pre-exercise carbohydrate ingestion during wheelchair[67] or arm crank ergometry.[54,68] Each of these studies has presented data that allows the calculation. of energy expenditure between 60% and 70% VO2peak along with the provision of data representative of AB controls[53,69] (table II). The studies shown in table II demonstrate energy expenditure values of 6–8 kcal/min during prolonged steady-state exercise. These values appear consistent between studies but represent lower exercise intensities than may be expected during endurance competition.[71,72] Wheelchair athletes with paraplegia are. able to maintain exercise intensities of 70–75% VO2peak (representing 80% top speed, an intensity often used by wheelchair athletes) for 60 minutes, which is similar to . the 76% VO2peak observed for a 5 km treadmill performance trial in wheelchair athletes.[35,70] Other performance trials over 20 minutes duration involving arm crank ergometry have refor presented 91% for AB athletes[53] and 87% . athletes with paraplegia,[54] and 80–83% VO2peak for 20 minutes of wheelchair ergometry.[67] These performance tests were undertaken following . 60 minutes of exercise at 65% VO2peak, so would most likely be of a greater intensity if performed in a non-fatigued state. Based on table II, the exercise intensities examined so far in the literature may be more representative for athletes with paraplegia, as wheelchair athletes with tetraplegia have been shown to compete at between 85% and 95% . VO2peak in events of 3.2, 5 and 7.5 km.[35,70,72,73] Specific data regarding exercise intensities undertaken during competition is required. Stalknechte et al.[10] examined the role of the sympathoadrenergic system on lipolysis in paraplegic men (T3–T5) during 60 minutes of arm . crank exercise at 60% VO2peak. The hypotheses that persons with high level SCI would have a smaller overall sympathoadrenergic activity and that regions distal to the injury level would be more affected were tested. The results demonstrated that subcutaneous adipose tissue lipolysis of the SCI group was stimulated less during exercise than for the AB controls. However, data suggested that this was not due to impaired local ª 2010 Adis Data Information BV. All rights reserved.

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sympathetic nerve activity but most likely due to lower circulating plasma catecholamines. The metabolism of specific substrates during incremental exercise in athletes with SCI therefore appears to adapt as expected for AB athletes; however, the mechanisms by which this happens may differ. Blood glucose has been shown to decrease by ~0.5 mmol/L during 1 hour of moderate exercise in persons with high[10] and low[68] levels of SCI, although the latter was not significant. Such a decrease is similar to studies of AB athletes[74,75] and is usually commensurate with an increase in fat metabolism.[76] Concentrations of free fatty acids have been shown to increase after 1 hour of exercise for athletes with low level SCI[69] or mixed groups of high and low level SCI.[68] Where persons with high level SCI (above T4) have been studied,[10] free fatty acids actually decreased during exercise, possibly due to the reduced amount of intact SNS available and a reduced ability to mobilize fatty acids. Where free fatty acids have not specifically been measured, an increase in fat metabolism has been intimated from a reduction in RER.[54] Skrinar et al.[68] examined the glycogen utilization of seven wheelchair athletes with SCI (C6–T12/L1) during 60. minutes of wheelchair ergometry at 60–70% VO2max. Muscle biopsies were taken from the anterior deltoid before and after exercise. A characteristic glycogen depletion of type I fibres was observed post-exercise along with an increase in free fatty acids and glycerol and a tendency for RER to decrease from 0.87 to 0.84. Although the metabolic responses were considered to be similar to those of AB athletes, a number of factors were considered to have potentially affected the results. Firstly, the resting muscle glycogen values of the athletes with SCI (~92 mmol/kg) were considered to be lower than leg muscles of AB athletes and may have reflected the habitual use of the arms for locomotion. The lower resting glycogen values were also considered to have contributed to a lower rate of glycogen usage than expected. The authors further noted the site of muscle biopsy may have affected the results as the anterior deltoid may not play a predominant role in power production during wheelchair ergometry. Sports Med 2010; 40 (8)

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ª 2010 Adis Data Information BV. All rights reserved.

Table II. Energy expenditure of laboratory-based studies of prolonged wheelchair and arm crank ergometry . Study Total exercise Time of data Intensity (%) RER Kcal per litre Total expenditure VO2 . duration (min) point (min) (kcal/min) (L/min) VO2 per min

CHO (%)

Fat (%)

CHO (g per hour)

Fat (g per hour)

Wheelchair exercise Skrinar et al.[68]

60

60

Gass and Camp[41]

80

57–60

Campbell et al.[70]

60

60

Price and Campbell[60]

60

Spendiff and Campbell[54]

60

. 67 VO2peak

1.34

0.84

4.850

6.5

47.2

52.8

43.2

22.5

1.79

0.82

4.825

8.6

40.3

59.7

48.8

33.6

. 70 VO2peak

1.09

0.81

4.813

5.2

36.9

63.1

27.0

21.6

60

. 60 VO2max

1.32

0.85

4.862

6.4

50.7

49.3

45.9

20.8

41–60

. 65 VO2peak

1.53

0.83

4.838

7.4

43.8

56.2

45.5

27.3

60–65 . VO2max

Arm crank ergometry (wheelchair athletes) Price and Campbell[65]

90

60

80 HRpeak

1.31

0.92

4.948

6.5

74.1

25.9

68.9

11.2

Price[69]

60

60

. 68 VO2max

1.37

0.91

4.936

6.8

70.8

29.2

68.6

13.2

Price and Campbell[66]

60

60

. 60 VO2max

1.34

0.88

4.899

6.6

60.8

39.2

56.7

17.1

Arm crank ergometry (able-bodied) 90

60

80 HRpeak

1.82

0.96

4.998

9.1

87.2

12.8

114.9

7.9

Price[69]

60

60

67.5 . VO2peak

2.33

0.96

4.998

11.6

87.2

12.8

147.1

10.1

Spendiff and Campbell[53]

60

41–60

2.09

0.74

4.727

9.9

12.0

88.0

16.3

55.7

. 65 VO2peak

. . . CHO = carbohydrate metabolism; Fat = fat metabolism; HRpeak = peak heart rate; RER = respiratory exchange ratio; VO2 = oxygen consumption; VO2max = maximal VO2; . . VO2peak = peak VO2.

Price

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Price and Campbell[65]

Energy Expenditure and Metabolism during Exercise in SCI

65

Substrate utilization (%)

60 55 50 45 40 35 30 0

10

20

30

40 50 Time (min)

60

70

80

90

Fig. 1. Proportional fat and carbohydrate metabolism usage during prolonged, steady-state wheelchair exercise in well trained athletes with a spinal cord injury. The data points presented as circles represent carbohydrate metabolism and those presented as squares represent fat metabolism. Dark squares and dark circles are mean values from Campbell et al. (1997).[70] The light circles and light squares are mean values taken from Gass and Camp (1987).[41]

Although a range of RER values during prolonged exercise have been reported for athletes with SCI, a general decrease with exercise duration is observed. This is similar to observations for AB athletes during prolonged exercise[75,77,78] and represents an increase in fat metabolism.[76,79] Greater RER values during 90 minutes of exercise have been observed for prolonged arm crank ergometry when compared with wheelchair ergometry[60] potentially due to the exercise mode and differences in force application to the ergometer flywheel when compared with wheelchair ergometry.[60] However, RER values still decreased over time as may be expected. Data for carbohydrate and fat metabolism from two studies[41,70] is shown in figure 1. Both studies involved wheelchair exercise with comparably well trained athletes exercising on a treadmill at similar exercise intensities Responses were similar between studies showing a predominance of carbohydrate metabolism up until 60 minutes and fat metabolism predominant thereafter. 4. Glucose Feeding Studies Few studies have examined the effects of carbohydrate ingestion prior to exercise in athletes with SCI. Furthermore, few have examined carª 2010 Adis Data Information BV. All rights reserved.

693

bohydrate ingestion prior to prolonged upperbody exercise. A series of studies by Spendiff and Campbell[53,54,67] examined the physiological responses and performance of wheelchair athletes and those of AB upper-body trained athletes after a pre-exercise carbohydrate feeding. In their first two studies, athletes exercised for 60 minutes . at 62–70% VO2peak on an arm crank ergometer followed by a 20-minute performance trial to cover as much distance as possible. Trials involved ingestion of either an 8% carbohydrate solution or a flavoured placebo 20 minutes prior to exercise. Although there were no differences . between trials for VO2, heart rate or RER for the AB athletes, RER for the wheelchair athletes was greater between 41 and 60 minutes during the carbohydrate trial (0.86 vs 0.83). Ingestion of the carbohydrate solution resulted in a greater distance achieved in the performance trial when compared with the placebo for both the AB athletes (12.55 vs 11.50 km)[53] and the wheelchair athletes (10.83 vs 10.20 km, respectively).[54] The improved performance for both groups was considered to be due to increased carbohydrate availability and increased carbohydrate oxidation. In a third study,[67] the effectiveness of two different carbohydrate solutions (4% vs 11% carbohydrate) was examined during wheelchair ergometry. The protocol involved exercise at . ~65% VO2peak for 60 minutes followed by a 20-minute performance trial. No differences were observed between trials for heart rate, blood glucose, RER or between distance covered in the performance trial for the 11% carbohydrate trial (5.15 km) or 4% carbohydrate trial (5.01 km). However, there was a tendency for greater mean power output during the 11% carbohydrate trial (p = 0.08). Furthermore, plasma free fatty acids increased more after exercise for the 4% than for the 11% carbohydrate trial. The authors presented ‘persuadable evidence’ that the high carbohydrate solution provided an increase in RER during performance being reflective of an increase in carbohydrate oxidation. The authors also noted that neither drink caused hypoglycaemia or was detrimental to exercise performance. The tendencies for higher blood glucose, RER, power outputs and lower free fatty acids Sports Med 2010; 40 (8)

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suggested that the higher concentration solution may be a better choice for these athletes. Table II shows the carbohydrate utilization per hour. during steady state wheelchair exercise at 60% VO2peak at approximately 45–48 g/h, with greater values during arm crank ergometry. The use of 6–8% solutions (w/v; 60–80 g of carbohydrate per litre of fluid) may therefore provide an excess of calories which may, overtime, result in over feeding, especially for athletes with tetraplegia. This may be of particular importance as abnormalities of carbohydrate metabolism are often observed in persons with long term SCI.[80] Although an 11% solution has been recommended,[67] similar peak blood glucose values after ingestion were observed when compared with 4% and 8% solutions.[54,67] This may suggest that glucose absorption into the blood is limited. Future work should be undertaken to further our understanding of carbohydrate feeding in athletes with SCI. 5. Conclusions It is evident that the absolute energy expenditure values for persons with SCI are lower than for AB persons participating in the equivalent sport as a result of reduced functional capacity. Energy expenditure values are also dependent upon the mode of exercise and the specific sporting activity undertaken. Although the relative exercise intensities elicited by persons with SCI during a range of activities are lower, they are comparable with those of AB persons. The physiological and metabolic responses of athletes with SCI are also similar to those of AB athletes, but at lower absolute levels. 6. Future Research There is tremendous scope for future work in this area of exercise physiology with large gaps in the literature. In order to enhance performance of athletes with SCI, many aspects of energy expenditure and energy provision should be examined. Generation of prediction equations for energy expenditure for a range of athletes (and non-athletes) with different levels of SCI ª 2010 Adis Data Information BV. All rights reserved.

(and other disabilities) would be of tremendous value. Validation of measurement techniques, such as short duration resting expired gas sam. ples, heart rate and/or VO2 relationships from wheelchair ergometry and energy expenditure are needed in order to accurately predict energy expenditure of intermittent type exercise and to facilitate accurate data collection from training sessions and competitive events. More specific physiological data from training and competitive situations will consequently aid our understanding of the demands of specific sports activities. Understanding the underlying physiological responses of carbohydrate feeding and fluid replacement in athletes with SCI will enable improvements in substrate provision to be realized. Studies within the area may help to bridge not only the gap between what is known regarding AB athletes and athletes with SCI (and other disabilities) during exercise but also the gap between clinical practice and performance. Acknowledgements The author would like to acknowledge the help of Dr Rob James in proofreading the manuscript. No sources of funding were used to assist in the preparation of this review. The author has no conflicts of interest that are directly relevant to the content of this review

References 1. Schmid A, Huonker M, Barturen JM, et al. Catecholamines, heart rate, and oxygen uptake during exercise in persons with spinal cord injury. J Appl Physiol 1998; 85 (2): 635-41 2. Schmid A, Huonker M, Stahl F, et al. Free plasma catecholamines in spinal cord injured persons with different injury levels at rest and during exercise. J Auton Nerv Syst 1998; 19: 68 (1-2): 96-100 3. Price MJ, Campbell IG. Thermoregulatory responses of able-bodied and paraplegic athletes to prolonged upper body exercise. Eur J Appl Physiol 1997; 76: 552-60 4. Price MJ, Campbell IG. Effects of spinal cord lesion level upon thermoregulation during exercise in the heat. Med Sci Sports Exerc 2003; 35 (7): 1100-7 5. Price MJ. The effects of absolute exercise intensity on core temperature responses of athletes with a spinal cord injury. In: Cisneros AB, Goins BL, editors. Body temperature regulation. New York: Nova Biomedical Books Inc., 2009: 227-41 6. Hollinshead WH, Jenkins DB. Functional anatomy of the limb and back. 5th rev. ed. Philadelphia (PA): WB Saunders, 1981

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7. Hopman MT. Circulatory responses during arm exercise in individuals with paraplegia. Int J Sports Med 1994; 15 (3): 126-31 8. Tortora GJ. Principles of human anatomy. 8th rev ed. San Francisco (CA): Benjamin/Cummings Scientific Publishers, 1998 9. Guyton AC, Hall JE. Textbook of medical physiology. 9th rev. ed. Philadelphia (PA): WB Saunders, 1996: 770 10. Stallknecht B, Lorentsen J, Enevoldsen LH, et al. Role of the sympathoadrenergic system in adipose tissue metabolism during exercise in humans. J Physiol 2001; 536 (Pt 1): 283-94 11. Steinberg LL, Lauro FA, Sposito MM, et al. Catecholamine response to exercise in individuals with different levels of paraplegia. Braz J Med Biol Res 2000; 33 (8): 913-8 12. Frey GC, McCubbin JA, Dunn JM, et al. Plasma catecholamine and lactate relationship during graded exercise in men with spinal cord injury. Med Sci Sports Exerc 1997; 29 (4): 451-6 13. McArdle WD, Katch FI, Katch VL, et al. Exercise physiology: energy, nutition and human performance. 2nd ed. Philadelphia (PA): Lea and Febiger, 1986: 642-9 14. Ainsworth BE, Haskell WL, Whitt MC, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000; 32 (9 Suppl.): S498-504 15. Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc 1993; 25 (1): 71-80 16. Buchholz AC, Pencharz PB. Energy expenditure in chronic spinal cord injury. Curr Opin Clin Nutr Metab Care 2004; 7 (6): 635-9 17. Alexander LR, Spungen AM, Liu MH, et al. Resting metabolic rate in subjects with paraplegia: the effect of pressure sores. Arch Phys Med Rehabil 1995; 76 (9): 819-22 18. Monroe MB, Tataranni PA, Pratley R, et al. Lower daily energy expenditure as measured by a respiratory chamber in subjects with spinal cord injury compared with control subjects. Am J Clin Nutr 1998; 68 (6): 1223-7 19. Liusuwan RA, Widman LM, Abresch RT, et al. Body composition and resting energy expenditure in patients aged 11 to 21 years with spinal cord dysfunction compared to controls: comparisons and relationships among the groups. J Spinal Cord Med 2007; 30 Suppl. 1: S105-11 20. Liusuwan A, Widman L, Abresch RT, et al. Altered body composition affects resting energy expenditure and interpretation of body mass index in children with spinal cord injury. J Spinal Cord Med 2004; 27 Suppl. 1: S24-8 21. Barco KT, Smith RA, Peerless JR, et al. Energy expenditure assessment and validation after acute spinal cord injury. Nutr Clin Pract 2002; 17 (5): 309-13 22. Spungen AM, Bauman WA, Wang J, et al. The relationship between total body potassium and resting energy expenditure in individuals with paraplegia. Arch Phys Med Rehabil 1993; 74 (9): 965-8 23. Mollinger LA, Spurr GB, el Ghatit AZ, et al. Daily energy expenditure and basal metabolic rates of patients with spinal cord injury. Arch Phys Med Rehabil 1985; 66 (7): 420-6 24. Kearns PJ, Thompson JD, Werner PC, et al. Nutritional and metabolic response to acute spinal-cord injury. J Parenter Enteral Nutr 1992; 16 (1): 11-5 25. Patt PL, Agena SM, Vogel LC, et al. Estimation of resting energy expenditure in children with spinal cord injuries. J Spinal Cord Med 2007; 30 Suppl. 1: S83-7

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26. Chermesino C, Edelstein S. Energy expenditure after spinal cord injury: a case study. SCI Nurs 2003; 20 (4): 258-60 27. Sedlock DA, Laventure SJ. Body composition and resting energy expenditure in long term spinal cord injury. Paraplegia 1990; 28 (7): 448-54 28. Schneider DA, Sedlock DA, Gass E, et al. VO2peak and the gas-exchange anaerobic threshold during incremental arm cranking in able-bodied and paraplegic men. Eur J Appl Physiol Occup Physiol 1999; 80 (4): 292-7 29. Price MJ, Campbell IG. Determination of peak oxygen uptake during upper body exercise. Ergonomics 1997; 40 (4): 491-9 30. Smith PM, Price MJ, Doherty M. The influence of crank rate on peak oxygen uptake during arm crank ergometry. J Sports Sci 2001; 19: 955-60 31. Abel T, Kro¨ner M, Rojas Vega S, et al. Energy expenditure in wheelchair racing and handbiking: a basis for prevention of cardiovascular diseases in those with disabilities. Eur J Cardiovasc Prev Rehabil 2003; 10 (5): 371-6 32. Abel T, Platen P, Rojas Vega S, et al. Energy expenditure in ball games for wheelchair users. Spinal Cord 2008; 46 (12): 785-90 33. Yamasaki M, Irizawa M, Komura T, et al. Daily energy expenditure in active and inactive persons with spinal cord injury. J Hum Ergol (Tokyo) 1992; 21 (2): 125-33 34. Hayes AM, Myers JN, Ho M, et al. Heart rate as a predictor of energy expenditure in people with spinal cord injury. J Rehabil Res Dev 2005; 42 (5): 617-24 35. Lakomy HK, Campbell I, Williams C. Treadmill performance and selected physiological characteristics of wheelchair athletes. Br J Sports Med 1987; 21 (3): 130-3 36. Ramsbottom R, Nute MG, Williams C. Determinants of five kilometre running performance in active men and women. Br J Sports Med 1987; 21 (2): 9-13 37. Knechtle B, Mu¨ller G, Willmann F, et al. Comparison of fat oxidation in arm cranking in spinal cord-injured people versus ergometry in cyclists. Eur J Appl Physiol 2003; 90 (5-6): 614-9 38. Martin L, Doggart AL, Whyte GP. Comparison of physiological responses to morning and evening submaximal running. J Sports Sci 2001; 19 (12): 969-76 39. Abel T, Schneider S, Platen P, et al. Performance diagnostics in handbiking during competition. Spinal Cord 2006; 44 (4): 211-6 40. Loftin M, Sothern M, Koss C, et al. Energy expenditure and influence of physiologic factors during marathon running. J Strength Cond Res 2007; 21 (4): 1188-91 41. Gass GC, Camp EM. Effects of prolonged exercise in highly trained traumatic paraplegic men. J Appl Physiol 1987; 63 (5): 1846-52 42. Gass GC, Camp EM, Davis HA, et al. The effects of prolonged exercise on spinally injured subjects. Med Sci Sports Exerc 1981; 13 (5): 277-83 43. Gass GC, Camp EM. Physiological characteristics of trained Australian paraplegic and tetraplegic subjects. Med Sci Sports 1979; 11 (3): 256-9 44. Burke EJ, Auchinachie JA, Hayden R, et al. Energy cost of wheelchair basketball. Phys Sports Med 1985; 13 (3): 99-102 45. Bernardi M, Canale I, Felici F, et al. Field evaluation of the energy cost of different wheelchair sports. Int J Sports Cardiol 1988; 5: 58-61

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46. Roy JL, Menear KS, Schmid MM, et al. Physiological responses of skilled players during a competitive wheelchair tennis match. J Strength Cond Res 2006; 20 (3): 665-71 47. Smekal G, von Duvillard SP, Rihacek C, et al. A physiological profile of tennis match play. Med Sci Sports Exerc 2001; 33 (6): 999-1005 48. Fernandez-Fernandez J, Mendez-Villanueva A, FernandezGarcia B, et al. Match activity and physiological responses during a junior female singles tennis tournament. Br J Sports Med 2007; 41 (11): 711-6 49. Ferrauti A, Bergeron MF, Pluim BM, et al. Physiological responses in tennis and running with similar oxygen uptake. Eur J Appl Physiol 2001; 85 (1-2): 27-33 50. Coutts A, Reaburn P, Abt G. Heart rate, blood lactate concentration and estimated energy expenditure in a semiprofessional rugby league team during a match: a case study. J Sports Sci 2003; 21 (2): 97-103 51. Novas AM, Rowbottom DG, Jenkins DG. A practical method of estimating energy expenditure during tennis play. J Sci Med Sport 2003; 6 (1): 40-50 52. Ballor DL, Burke LM, Knudson DV, et al. Comparison of three methods of estimating energy expenditure: caltrac, heart rate, and video analysis. Res Q Exerc Sport 1989; 60 (4): 362-8 53. Spendiff O, Campbell IG. The effect of glucose ingestion on endurance upper-body exercise and performance. Int J Sports Med 2002; 23 (2): 142-7 54. Spendiff O, Campbell IG. Influence of glucose ingestion prior to prolonged exercise on selected responses of wheelchair athletes. Adapt Phys Act Q 2003; 20: 80-90 55. McInnes SE, Carlson JS, Jones CJ, et al. The physiological load imposed on basketball players during competition. J Sports Sci 1995; 13 (5): 387-97 56. Christmass MA, Richmond SE, Cable NT, et al. Exercise intensity and metabolic response in singles tennis. J Sports Sci 1998; 16 (8): 739-47 57. Coutts KD. Heart rates of participants in wheelchair sports. Paraplegia 1988; 26: 43-9 58. Hoch F, Werle E, Weicker H. Sympathoadrenergic regulation in elite fencers in training and competition. Int J Sports Med 1988; 9 Suppl. 2: S141-5 59. Christmass MA, Dawson B, Passeretto P, et al. A comparison of skeletal muscle oxygenation and fuel use in sustained continuous and intermittent exercise. Eur J Appl Physiol Occup Physiol 1999; 80 (5): 423-35 60. Price MJ, Campbell IG. Thermoregulatory and physiological responses of wheelchair athletes to prolonged arm crank and wheelchair exercise. Int J Sports Med 1999; 20 (7): 457-63 61. McConnell TJ, Horvat MA, Beutel-Horvat TA, et al. Arm crank versus wheelchair treadmill ergometry to evaluate the performance of paraplegics. Paraplegia 1989; 27 (4): 307-13 62. Pitetti KH, Snell PG, Stray-Gundersen J. Maximal response of wheelchair-confined subjects to four types of arm exercise. Arch Phys Med Rehabil 1987; 68 (1): 10-3 63. Glaser RM, Sawka MN, Brune MF, et al. Physiological responses to maximal effort wheelchair and arm crank ergometry. J Appl Physiol 1980; 48 (6): 1060-4 64. Knechtle B, Mu¨ller G, Willmann F, et al. Fat oxidation at different intensities in wheelchair racing. Spinal Cord 2004; 42 (1): 24-8

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Price

65. Price MJ, Campbell IG. Thermoregulatory responses of paraplegic and able-bodied athletes at rest and during prolonged upper body exercise and passive recovery. Eur J Appl Physiol Occup Physiol 1997; 76 (6): 552-60 66. Price MJ, Campbell IG. Thermoregulatory responses of spinal cord injured and able-bodied athletes to prolonged upper body exercise and recovery. Spinal Cord 1999; 37 (11): 772-9 67. Spendiff O, Campbell IG. Influence of pre-exercise glucose ingestion of two concentrations on paraplegic athletes. J Sports Sci 2005; 23 (1): 21-30 68. Skrinar GS, Evans WJ, Ornstein LJ, et al. Glycogen utilization in wheelchair-dependent athletes. Int J Sports Med 1982; 3 (4): 215-9 69. Price MJ. Thermoregulatory responses of spinal cord injured and able-bodied athletes to prolonged exercise and thermal stress [PhD Thesis]. Manchester: Manchester Metropolitan University, 1997 70. Campbell IG, Williams C, Lakomy HK. Physiological responses of wheelchair athletes at percentages of top speed. Br J Sports Med 1997; 31 (1): 36-40 71. Bhambhani YN, Holland LJ, Eriksson P, et al. Physiological responses during wheelchair racing in quadriplegics and paraplegics. Paraplegia 1994; 32 (4): 253-60 72. Bhambhani YN, Burnham RS, Wheeler GD, et al. Physiological correlates of simulated wheelchair racing in trained quadriplegics. Can J Appl Physiol 1995; 20 (1): 65-77 73. Asayama K, Nakamura Y, Ogata H, et al. Physical fitness of paraplegics in full wheelchair marathon racing. Paraplegia 1985; 23 (5): 277-87 74. Knoepfli B, Riddell MC, Ganzoni E, et al. Off seasonal and pre-seasonal assessment of circulating energy sources during prolonged running at the anaerobic threshold in competitive triathletes. Br J Sports Med 2004; 38 (4): 402-7 75. Howlett KF, Spriet LL, Hargreaves M. Carbohydrate metabolism during exercise in females: effect of reduced fat availability. Metabolism 2001; 50 (4): 481-7 76. Thomas TR, Feiock CW, Araujo J. Metabolic responses associated with four modes of prolonged exercise. J Sports Med Phys Fitness 1989; 29 (1): 77-82 77. Carey AL, Staudacher HM, Cummings NK, et al. Effects of fat adaptation and carbohydrate restoration on prolonged endurance exercise. J Appl Physiol 2001; 91 (1): 115-22 78. Bangsbo J, Jacobsen K, Nordberg N, et al. Acute and habitual caffeine ingestion and metabolic responses to steady-state exercise. J Appl Physiol 1992; 72 (4): 1297-303 79. Pillard F, Moro C, Harant I, et al. Lipid oxidation according to intensity and exercise duration in overweight men and women. Obesity 2007; 15 (9): 2256-62 80. Bauman WA, Spungen AM. Carbohydrate and lipid metabolism in chronic spinal cord injury. J Spinal Cord Med 2001; 24 (4): 266-77

Correspondence: Dr Michael Price, Department of Biomolecular and Sports Sciences, Faculty of Health and Life Sciences, Coventry University, Priory Street, Coventry, CV1 5FB, UK. E-mail: [email protected]

Sports Med 2010; 40 (8)

Sports Med 2010; 40 (8): 697-714 0112-1642/10/0008-0697/$49.95/0

REVIEW ARTICLE

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Bone Metabolism Markers in Sports Medicine Giuseppe Banfi,1 Giovanni Lombardi,1 Alessandra Colombini1 and Giuseppe Lippi2 1 IRCCS Galeazzi, Milan, Italy 2 Laboratorio Analisi, Azienda Ospedaliera Universitaria di Parma, Parma, Italy

Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Bone Metabolism Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Bone Formation Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Bone Alkaline Phosphatase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Osteocalcin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.3 N-Terminal and C-Terminal Propeptides of Type I Procollagen . . . . . . . . . . . . . . . . . . . . . . . 1.2 Bone Resorption Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Collagen Cross-Links – Pyridinoline and Deoxypiridinoline . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Cross-Linked Telopeptides of Type I Collagen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Tartrate-Resistant Acid Phosphatase-5b. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Bone Metabolism and Energy Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Effects of Single-Bout Training and Physical Exercise on Bone Metabolism Serum Markers . . . . . . . . . 3. Effects of Training on Bone Metabolism Serum Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Effects of Long-Term Training and Competition on Bone Metabolism Serum Markers and Sex-Related Effects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Bone Metabolism Markers and Different Types of Sport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abstract

697 698 700 700 700 700 701 701 701 701 702 702 703 707 708 710 711

Bone mass can be viewed as the net product of two counteracting metabolic processes, bone formation and bone resorption, which allow the skeleton to carry out its principal functions: mechanical support of the body, calcium dynamic deposition and haemopoiesis. Besides radiological methods, several blood and urinary molecules have been identified as markers of bone metabolic activity for estimating the rates and direction of the biological activities governing bone turnover. The advantages for the use of bone metabolism markers are that they are potentially less dangerous than radiological determinations, are more sensitive to changes in bone metabolism than radiological methods and are easily collected and analysed. The disadvantages are that they have high biological variability. Physical exercise is a known source of bone turnover and is recommended for preventing osteoporosis and bone metabolism problems. There are numerous experiments on bone metabolism markers after acute exercise, but not after long-term training and during or after a whole competition season. Moreover, few studies on bone metabolism markers have evaluated their

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performance in elite and top-level athletes, who have a higher bone turnover than sedentary individuals. Despite discrepant results among studies, most have shown that short exercise is insufficient for modifying serum concentrations of bone metabolism markers. Marker variations are more evident after several hours or days after exercise, bone formation markers are more sensitive than bone resorption markers, and stimulation of osteoblast and/or osteoclast functions is exercise dependent but the response is not immediate. The response depends on the type of exercise; the markers seem to be less sensitive to resistance exercise and the intensity of exercise is not discriminate. Comparisons between trained subjects and untrained controls have demonstrated the influence of exercise on bone turnover. During training, carboxy-terminal collagen cross-links (CTx), a bone resorption marker, was shown to be less sensitive than amino-terminal cross-linking telopeptide of type I collagen (NTx) and urinary pyridinolines, which were sensitive to anaerobic exercise. Whereas, the bone formation markers, bone alkaline phosphatase (BAP) and osteocalcin (OC) changed after 1 month and 2 months of an exercise programme, respectively. After 2 months, while BAP normalized, it was found to be sensitive to aerobic exercise and OC was found to be sensitive to anaerobic exercise. After prolonged training and competition, bone formation markers are found to change in sedentary subjects enrolled in a physical activity programme. Professional athletes show changes in bone formation markers depending on programme intensity, whereas bone resorption appears to stabilize. Crucial for long-term training, are the characteristics of exercise (e.g. weight-bearing, impact).

To accurately define bone metabolism, the type of sport practiced needs to be taken into account; especially, because of the different weight-bearing characteristics specific to a given activity. The practical implication is that even with the use of serum and urine markers to interpret bone metabolism rates, athletes cannot be indiscriminately considered as a homogeneous group. 1. Bone Metabolism Markers Bone mass can be considered as the net product of two counteracting metabolic processes: bone formation and bone resorption,[1] which enable the skeleton to carry out its principal functions of mechanical support to the body, calcium dynamic deposition and haemopoiesis. The two processes are closely regulated by the relative equilibrium between endogenous (hormones, growth factors and cytokines) and exoª 2010 Adis Data Information BV. All rights reserved.

genous factors (mainly mechanical loading).[2] Under normal conditions, the resorptive activity of multi-nucleated resorptive macrophagederived osteoclasts is tightly coupled and is regulated by the anabolic action of osteoblasts and osteocytes.[3] Perturbations in this controlled system, primarily consequent to derangements in the production of modulating factors, are responsible for the onset of metabolic bone diseases such as osteoporosis. The long-term result of imbalanced bone turnover is altered bone mass and structure, which can be assessed by radiological and densitometric techniques. Unlike these static measures, bone metabolism biomarkers are ideal tools to detect the dynamics of the metabolic imbalance itself, since they provide a picture of the actual metabolic status of the bone, other than a well established result of abnormal metabolism. Radiological and biochemical determinations can be employed to complement one Sports Med 2010; 40 (8)

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another in the assessment of skeletal homeostasis and the diagnosis of bone disease.[4] Several blood and urinary molecules have been identified as markers of bone metabolic activity, providing estimations of the rates and direction of the biological activities governing bone turnover. However, caution is warranted in the routine use of bone turnover markers. First, some may reflect, to a certain degree, both bone deposition and resorption. Second, the majority of these molecules are present in other tissues besides the bone and their measured levels may be influenced by nonskeletal processes. Generally, bone turnover markers are classified according to the metabolic process they are considered to reflect or the biological compartment they belong to.[1] Bone turnover markers are listed in table I.

We performed a review of numerous studies on the behaviour of bone metabolism markers in sports medicine. There is growing interest in bone metabolism and bone remodelling in athletes. Because the effect of exercise-induced modifications on bone density may be beneficial or harmful, monitoring of bone metabolism by means of biochemical markers, which are widely used in pathology, could also be particularly useful in athletes. However, a review of the literature on acute exercise, training, competitions, effects of sex and effects of each sport discipline is lacking. We conducted a search of the medical literature in the PubMed database, a service of the US National Library of Medicine, using ‘bone turnover markers’ or ‘bone metabolism markers’ matched with ‘athletes’ and ‘sport’ as keywords.

Table I. Bone turnover markers Markera

Biological material

Biological variability CVI (%)

CVG (%)

Serum

6.6[5,6]

35.6[5,6]

[5,6]

30.9[5,6]

Bone formation markers BAPb OC

c

Serum

9.1

PICP

Serum

8.6[6]

PINP

Serum

17.6[6]

Bone resorption markers Pyrd d,e

Urine or serum

18.6 (free u-Pyr)[6] f[6]

24.8 (free u-Pyr)[6]

Dpd

Urine or serum

23.5 (total u-Dpd) 13.1 (free u-Dpd)f[6]

26.0 (total u-Dpd)[6] 26.0 (free u-Dpd)[6]

ICTP

Serum

6.9[6]

28.8[6]

CTx

Urine

NTx

Urine

14.7 (u-NTx)[6]

26.9 (u-NTx)[6]

TRAP5b

Serum

10.8[5,6]

13.3[5,6]

a

The marker acronyms are nonstandard; we report the most commonly used acronyms.

b

Also known as BALP.

c

Also known as BGP (bone-Gla-protein).

d

These markers are generally known as pyridinium cross-links or simply cross-links.

e

Also known as D-Pyr.

f

In humans, the total pools of urinary Pyr and Dpd are approximately 45% free, while the remaining fraction is bound to oligopeptides ranging from small linear peptides to very large cross-linked structures of over 10 kDa. The validity of the determination of the free fraction alone as surrogate for the total urinary amount is still debated.

BAP = bone alkaline phosphatase; CTx = carboxyterminal cross-linking telopeptide of type I collagen; CVG = interindividual variability; CVI = intraindividual variability; Dpd = deoxypiridinoline; ICTP = carboxyterminal cross-linked telopeptide of type I procollagen; NTx = aminoterminal cross-linking telopeptide of type I collagen; PICP = carboxyterminal propeptide of type I procollagen; PINP = aminoterminal propeptide of type I procollagen; Pyr = pyridinoline; OC = osteocalcin; TRAP5b = tartrate-resistant acid phosphatase (isoenzyme 5b); u = urinary.

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Studies were included in the analysis if they reported on healthy subjects, physically active subjects and athletes, along with some papers quoted in the references of papers selected from the PubMed database. Only studies on the use of established bone turnover biochemical markers, which could be measured by commercial methods, and describing the protocol treatment and ethical assessment, were taken into the final analysis. The biochemistry of collagenous markers is extensively described in the text and figures of a previously published review.[1] 1.1 Bone Formation Markers

Bone formation markers are direct or indirect products of osteoblast activity expressed during different phases of osteoblast differentiation and extracellular matrix deposition and maturation. Characteristically, all bone formation markers are measured in serum or plasma.[7] 1.1.1 Bone Alkaline Phosphatase

Alkaline phosphatase (AP), a ubiquitous membrane-bound enzyme, plays an important role in bone mineralization.[8] Total serum AP consists of a pool of enzymatic isoforms originating from various tissues (liver, bone, intestine, spleen, kidney, placenta). In adults with normal liver function, about 50% of the total AP activity in serum is derived from the liver and the remaining 50% arises from bone, whereas during skeletal growth the bone-specific isoenzyme predominates (up to 90%).[9] Serum total AP is the most widely used marker of bone metabolism, once liver disease is ruled out. In clinical practice, detection of bonespecific AP (BAP) isoenzyme is increasingly preferred because of its higher specificity.[1] Because BAP is involved in all phases of bone mineralization, measurement of BAP activity provides a specific indicator of osteoblast activity.[10,11] 1.1.2 Osteocalcin

Osteocalcin (OC [also named bone-Glaprotein]) is a 5.8 kDa hydroxyapatite-binding protein exclusively synthesized by osteoblasts, odontoblasts and hypertrophic chondrocytes.[12] ª 2010 Adis Data Information BV. All rights reserved.

OC possesses three vitamin K-dependent, g-carboxyglutamic acid (Gla) residues, which are responsible for the protein’s calcium-binding properties.[13] OC can also interact with other proteins and cell surface receptors, allowing it to carry out an active role in the organization of the extracellular matrix. Although its involvement in osteoid mineralization has been recognized, its precise function remains unclear. The total OC content in the bone accounts for 15% of the noncollagenous protein fraction and it is considered a specific marker of osteoblast function.[14] There is abundant evidence for the utility of OC as a bone formation marker.[12] However, the role of OC in bone extracellular matrix mineralization has not been confirmed by experiments in mice. Mice without OC have an abnormal bone extracellular matrix, while over expression of OC in bone does not affect mineralization. The role of OC could be transferred from a simple marker of bone formation to hormone-like regulators of energy metabolism. The fact that OC is synthesized by osteoblasts does not necessarily reflect the bone-forming activity of these cells. However, there is good evidence that OC plays an important role in energy metabolism. Therefore, any change in OC related to exercise may potentially be an adaptation to increased energy requirements in athletes.[15-18] The use of OC in bone status assessment is primarily limited by the absence of methodological standardization, rendering the comparison of data obtained with different methods difficult. The problem resides mainly in the presence of various types of OC-derived fragments circulating in the bloodstream, and the different analytical methods that recognize a different panel of fragments.[19] 1.1.3 N-Terminal and C-Terminal Propeptides of Type I Procollagen

Over 95% of bone collagen is constituted by type I and the remaining 5% by collagen types III and IV. Type I collagen is the principal component of bone, composing 90% of its matrix, but it is also a minor component of the extracellular matrix of other tissues such as skin, dentin, cornea, vessels and tendons.[20] Sports Med 2010; 40 (8)

Bone Metabolism Markers

The collagen precursors in a triple helical form present short-terminal peptides at both the amino and carboxy terminals that are enzymatically cleaved once the precursor molecule is secreted into the extracellular space, giving rise to the mature insoluble collagen molecule. Since the generation of aminoterminal propeptide of type I procollagen (PINP) and carboxyterminal propeptide of type I procollagen (PICP) stoichiometrically follows the synthesis of new collagen molecules, they are considered to be quantitative measures of newly formed type I collagen.[21,22] 1.2 Bone Resorption Markers

Most bone resorption markers are degradation products of bone type I collagen that can be measured in serum or urine, along with the osteoclastspecific enzyme tartrate-resistant acid phosphatase (TRAP). Other important resorption markers are the osteoclast-derived enzymes cathepsin K and L and the non-collagenous bone sialoproteins, whose clinical importance is under investigation. 1.2.1 Collagen Cross-Links – Pyridinoline and Deoxypiridinoline

Collagen cross-links are non-reducible crosslinks of bony and cartilaginous collagens and, in a smaller fraction, are found in the extracellular matrix of other connective tissues. They function as molecular bridges cross-linking several collagen molecules, conferring them greater mechanical stability; following the resorptive action of osteoclast-derived proteolytic enzymes, these degradation products are released into the bloodstream and urine, where they can be measured.[1] Hydroxylysylpyridinoline (Pyr) and lysylpyridinoline (or deoxypyridinoline [Dpd]) are demonstrated markers of osteoclast activity but differ in their specificity; Pyr predominates in cartilage but is also found in bone, tendon and connective tissue of vessels, whereas Dpd is almost exclusively found in bone and dentin and is present only in smaller fractions in the aorta and ligaments.[23] Currently, Pyr and Dpd can be measured in both urine and serum, but the former still represents the gold standard. Pyr and Dpd are present in the bloodstream and, therefore, in ª 2010 Adis Data Information BV. All rights reserved.

701

urine in two different fractions: free or peptidebound. The validity of determination of the free fraction alone as a surrogate for the total urinary amount has not yet been defined.[24] 1.2.2 Cross-Linked Telopeptides of Type I Collagen

Cross-linked telopeptides result from the enzymatic degradation of the amino-terminal crosslinking telopeptide (NTx) and carboxy-terminal collagen cross-links (CTx) terminal regions of type I collagen. Characteristically, they are cross-linked by Pyr and Dpd bridges with the corresponding peptides of a tropocollagen trimer or belong to adjacent fibrils and, following proteolytic degradation, are released into the blood and then the urine.[25] NTx is completely cleared by the kidney and represents the main measurable factor containing Pyr and Dpd peptidic fragments. Early collagen telopeptide assays assessed the carboxyterminal cross-linked telopeptide of type I procollagen (ICTP) concentration in serum. Specifically, it is defined as a trivalent cross-link, including three phenylalanine-rich domains of the C-telopeptide region of the a1 chain of type I collagen.[26] CTx is another C-terminal telopeptide composed of an octapeptide of the C-terminus of the a1 type I collagen; the second amino acid of this peptide forms a cross-link with the first amino acid of the adjacent peptide within the tropocollagen molecule or belongs to another collagen molecule within the same fibril. The resulting compact structure cannot be further broken down during passage in the kidney.[27] Since collagen has a relatively long half-life, it is subject to various age-dependent modifications such as isomerization and racemization, which are also present in collagen degradation products. CTx molecules can be detected as four different isoforms: the native a-L form; the bisomer; b-L (also known as CrossLaps); and the respective racemized forms, a-D and b-D.[28] CTx levels can be assessed in urine (a and b isoforms) and in serum (b isoform only).[1] 1.2.3 Tartrate-Resistant Acid Phosphatase-5b

This enzyme belongs to a family of five known members of ubiquitous acid phosphatases. The Sports Med 2010; 40 (8)

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different isoforms are expressed in various tissues (prostate, bone, spleen, platelets, erythrocytes and macrophages) and they are inhibited by L(+)tartrate (except for band 5, which has been termed tartrate resistant). Band 5 consists of two different subforms that differ in their glycosylation patterns: 5a, which seems to be expressed by macrophages and other non-identified sources and contains sialic acid; and osteoclast-specific sialic acid-free 5b.[29] All the cells of the macrophage lineage, including osteoclasts, express high amounts of TRAP5.[30] Osteoclasts secrete TRAP5b into the bloodstream, and the serum concentration and activity of this enzyme are considered to be a potentially useful marker of bone resorption.[31] 1.3 Variability

As with all laboratory results, there are three basic causes of variability in the measurement of the level or of the activity in enzymes of bone turnover markers: (i) the analytical characteristics of the methodology in use (analytical variability); (ii) the different conditions of preparation of the subject and the sample (pre-analytical variability); and (iii) the biological condition appropriate to the subject (biological variability). Rigorous standardization of procedures for the pre-analytical and analytical phases is the first step to control and minimize the influence of these variables on the result.[6,32] The two components of biological variability are interindividual variability (CVG), which is the difference in the results obtained from different individuals who all have the same physiological condition due to the heterogeneity in the homeostatic points among them, and intraindividual variability (CVI), which is due to casual fluctuations in a body constituent measured at different times in the same subject in the region of its homeostatic point.[33] In the evaluation of biological bone marker variability among individuals, the main uncontrollable factor is genetic constitution, which accounts for about 70% of the total interindividual variance in bone density. However, lifestyle factors such as diet, calcium intake and, in particular, physical activity, are ª 2010 Adis Data Information BV. All rights reserved.

also important in the regulation of bone metabolism.[34] Laboratory reference ranges for bone turnover markers need to be established distinctly for both men and women, and also need to be distinguished between pre- and postmenopausal women.[35] Within the same scope, since skeletal tissue is highly metabolically responsive to mechanical stimulation both positively and negatively depending on the type and frequency of activity, as demonstrated by several studies,[36-46] it is of great practical interest to take into account the level and type of physical activity a subject performs in order to better interpret laboratory results when employing bone turnover markers. 1.4 Bone Metabolism and Energy Metabolism

Bone marker variability is linked to the hectic activity of bone tissue cells. Regulation of osteoblast and osteoclast activity has recently been viewed from an endocrine perspective, which includes a consistent link with energy metabolism and the sympathetic nervous system. Bone could be considered to be a tissue with endocrine production, through the release of OC, which plays a role in fat and glucose metabolism, insulin secretion and pancreatic b-cell proliferation. OC also acts on adipocytes to release adiponectin that reduces insulin resistance.[16] Energy sources such as energy metabolism, correct and adequate intake of nutrients and neuroendocrinological regulation, are fundamental for athletes and physically active individuals. Accordingly, bone metabolism and remodelling should be considered as part of a more complex system, involving hormones, cytokines and the sympathetic nervous system. Indeed, leptin, an adipocyte-derived hormone, is a regulator of osteoblasts; its action is mediated through two different neural pathways. The hormone binds to its receptors in the hypothalamus; sympathetic signalling in osteoblasts facilitates their differentiation versus osteoclasts by inducing receptor activator of nuclear factor kappa B ligand (RANKL), while cocaine- and amphetamine-regulated transcript inhibits RANKL Sports Med 2010; 40 (8)

Bone Metabolism Markers

expression. Furthermore, osteoblasts, through the release of OC, influence fat metabolism and weight gain or loss.[15,17,18,47] A common control of energy and bone metabolism is also conceivable given the high energy requirements of bone remodelling, a continuous process akin to survival functions.[17] This is especially important when micro- or macrodamage occurs, as often happens in athletes. Moreover, physical exercise is linked to increases in reactive oxygen species (ROS). The production of ROS by osteoclasts helps to accelerate the destruction of calcified tissue, thus assisting in bone remodelling. When the production of ROS by osteoclasts overwhelms the natural antioxidants’ defence mechanisms, the concomitant oxidant stress may lead to bone loss. The exact biochemical and cytological basis of the events ultimately responsible for bone resorption are unknown. It has been suggested that enhanced osteoclast activity may increase superoxide anion generation and/or inhibit superoxide dismutase and glutathione peroxidase activities. OC may break up into small peptides on exposure to superoxide.[48] 2. Effects of Single-Bout Training and Physical Exercise on Bone Metabolism Serum Markers Table II gives an overview of the acute effects of physical exercise on bone metabolism serum markers described in various studies. The data differ owing to various different training schemes and types of exercise applied. The experimental protocols were applied to sedentary volunteers or non-professional athletes, except for the study by Kristofferson et al.,[39] who studied ice hockey players competing in Swedish national leagues. With this caveat in mind, the observed data cannot be easily transferred to professional athletes or to individuals involved in continuous physical exercise programmes. Some researchers studied bone metabolism markers in the first few hours following exercise.[37,39,41] OC was found to rise significantly immediately after exercise and to fall back to baseline levels 1 hour after exercise (30 minutes of ª 2010 Adis Data Information BV. All rights reserved.

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treadmill) among non-athletes, while among athletes OC increased 1 hour after exercise.[37] The differences between athletic and non-athletic groups were attributed to the higher baseline values in athletes, because total alkaline phosphatase did not change. Changes in bone cell function, as reflected by serum bone marker modifications, are likely to occur up to 24 hours after exercise. Welsh et al.[41] examined the short-time effects (up to 32 hours) of moderate exercise in healthy male sedentary volunteers, aged 20–35 years, who performed a treadmill exercise equivalent to a brisk walking pace maintained at 60% of maximal heart rate for 30 minutes; an increase in bone resorption markers was found 32 hours after moderate exercise, without a significant effect on bone formation markers. There were no differences in OC and BAP over baseline values at any of the timepoints (0.5–32 hours after exercise). Rudberg et al.[45] found that jogging (4–7 km) in healthy young females was insufficient to change OC and BAP but was sufficient for isoform B2. In postmenopausal women, jogging had no effect on OC, whereas all bone isoforms of BAP (B/I, B, B2) had significantly increased at the end of jogging but normalized after 20 minutes. Ashizawa et al.[43] confirmed that OC and BAP were unchanged immediately after exercise. In this study, 14 male sedentary subjects performed a resistance exercise with weight-lifting and bench press. A nonsignificant increase in OC was found over the 3 days following the day of exercise, whereas BAP significantly decreased at days 2 and 3. A significant decrease in PICP was found on the day after a race (range 5–30 km) and after an ultramarathon.[40,51] Conversely, this marker remained unchanged after aerobic and resistance exercise according to Kristofferson et al.[39] and Whipple et al.[49] Only Thorsen et al.[42] described a marked change in PICP, with a decrease 1 hour after 45 minutes of jogging and an increase after 1 and 3 days. The variation in PICP did not follow changes in OC, which increased slightly 1 hour after exercise, as did bone resorption marker ICTP, which increased 1 and 3 days after jogging. A possible explanation for the Sports Med 2010; 40 (8)

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ª 2010 Adis Data Information BV. All rights reserved.

Table II. Effects of a single bout of physical exercise on bone serum markersa Sport (level)

No. of subjects

Sex; age (y) Type of exercise/protocol of blood drawings

Bone formation markers

Bone resorption markers

Nishiyama et al.[37]

Volleyball (amateur)

19 (9 trained, 10 untrained)

M; 20–24

Running ergometer for 30 min at 43–52% of maximum blood drawings before, immediately after and 1 h after exercise

OC increase after 1 h in trained subjects (from 7.3 – 1.1 to 8.1 – 2.1 ng/mL); p < 0.01; OC unchanged immediately after exercise in trained subjects; OC unchanged in untrained subjects

Malm et al.[38] Marathon (amateur)

23

15 F 8 M; 23–55

Blood drawings 10 days before, immediately after and at 1, 3 and 5 days after the race

Urinary; hydroxyproline not modified BAP decrease in women after the race (from 66.3 to 62.3 U/L) p < 0.05; OC decrease (from 4.9 to 3.9 ng/mL) immediately after the race in men (p < 0.01) and at day 1 in women (from 4.9 to 4.3 ng/mL) (p < 0.05)

Kristofferson et al.[39]

Ice hockey (national)

7

M; 19–26

Maximal work (Wingate test); blood drawings 1 h before and at 5 and 60 min after exercise

OC not modified; PICP not modified

Brahm et al.[40]

Running (amateur)

20

10 M; 22–53: 10 F; 22–55

Race of 28 km for M, and of 15 km for F; blood drawings before, and at 1 and 2 days after the race

BAP not modified; OC decrease at day 1 in ICTP increase at day 2 in M (from M (from 12.1 – 1.1 to 10.3 – 1.1 ng/mL); 3.75 – 0.36 to 3.98 – 0.35 ng/mL); p < 0.01; PICP decrease at day 1 in F (from p < 0.01 170 – 17 to 158 – 17 ng/mL); p < 0.05

Welsh et al.[41]

Sedentary

10

M; 20–35

Brisk treadmill walking at 60% BAP not modified; OC not modified of maximum heart rate; blood drawings at 0.5, 1, 8, 24, 32 h after exercise

Pyr increase by 38% after 32 h. Dpd increase by 42% after 32 h

Thorsen et al.[42]

Sedentary

14

F; 24–26

Jogging for 45 min; blood OC increase 1 h after (from 8.2 to drawings 15 min before and at 8.8 ng/mL); p < 0.05; PICP decrease 1 h 1, 24, 72 h after exercise after; p < 0.05; increase at 24 and 72 h after; p < 0.01

ICTP increase at 24 and 72 h after; p < 0.05

Ashizawa et al.[43]

Sedentary

14

M; 24–26

Press and extension resistance exercise using weights; blood drawings before and at 1, 2 and 3 days after exercise

Langberg et al.[44]

Marathon (amateur)

17

M; 23–48

Blood drawings 1 wk before, PICP decrease immediately after (from immediately after, and at 1, 2, 176 – 17 to 156 – 9 ng/mL); p < 0.05; 3, 4, 5, 6 days after the race increase at day 3 (from 176 – 17 to 197 – 8 ng/mL); p < 0.05

ICTP increase immediately after (from 3.5 – 0.4 to 5.1 – 0.6 mg/L); p < 0.05

Rudberg et al.[45]

Sedentary

7

F; 21–27

Jogging for 30–40 min; blood BAP (isoform B2) increase at end of drawings before, immediately exercise (from 1.18 – 0.45 to after and 20 min after exercise 1.49 – 0.45 mkatal/L); p < 0.01; OC not modified

ICTP not modified

ICTP not modified

BAP decrease at day 2; p < 0.01; at day 3; Pyr decrease at day 3; p < 0.05; TRAP p < 0.05; OC not modified; PICP decrease decrease at day 1; p < 0.01 at day 1; p < 0.05

Continued next page

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Sports Med 2010; 40 (8)

Study

Study

Sport (level)

No. of subjects

Bone formation markers

Bone resorption markers

Guillemant et al.[46]

Triathlon (elite)

12

BAP not modified

CTx increase 30 (46%), 60, 120 min after exercise; p < 0.05

Whipple et al.[49]

Sedentary

9

M; 20–23

Resistance exercise for 45 min; blood drawings before, immediately after and at 1, 8, 24, 48 h after exercise

BAP not modified; PICP not modified

NTx decrease at 1 and 8 h vs basal values and controls (from 15 to 9 mmol/L); p < 0.01

Herrmann et al.[50]

16 athletes from running, soccer, cycling (amateur) 16 sedentary

32

15 M, 17 F; 17–39

Cycloergometer test for 60 min at 75%, 95%, 110% AT; blood drawings before and at 3 and 24 h after exercise

OC decrease at 75% AT after 3 and 24 h; CTx increase at 95% and 110% AT p < 0.05; PINP decrease at 75% AT after 3 after 3 and 24 h in M athletes; p < 0.05; and 24 h (both M and F athletes); p < 0.05; TRAP not modified in athletes OC increase at 95% AT after 3 h in M athletes and 24 h in F athletes; p < 0.05

Mouzopoulos et al.[51]

Ultramarathon, 245 km (amateur)

16

M; 25–48

BAP decrease at days 0 and 1 (from Blood drawings before, immediately after and 1, 3 and 66 – 8.2 to 61.5 – 7.7 and 61 – 7.3 U/L); p < 0.05; OC decrease at days 0 and 1 5 days after the race (from 4.6 – 1.2 to 3.8 – 0.8 and 3.4 – 0.5 ng/mL); p < 0.05; PICP decrease at day 0 (from 168 – 15.3 to 153 – 12.8 ng/mL); p < 0.05

Lippi et al.[52]

Half-marathon, 21 km (amateur)

15

M; 30–55

Blood drawings 2 days and OC increase immediately after the race 30 min before, immediately (from 22.0 – 2.5 to 27.3 – 3.0 ng/mL); after and at 3, 6 and 24 h after p < 0.01 the race

Pomerants et al.[53]

Sedentary

60 M; 10–18 (Group I: 20 prepubertal [Tanner stage 1]; Group II: 20 pubertal stage 2–3; Group III: 20 pubertal stage 4–5)

a

Cycloergometer mean PINP not modified in the three groups pedalling rate 70 rpm Group I: increments of 20 W each 2-min stage, start at 80 W Groups II and III: increments of 30 W each 2-min stage, start at 100 W, 30 min exercise at 95% of individual ventilatory threshold

ICTP not modified; hydroxyproline decrease at day 0 and increase at days 1, 3 and 5 (from 70 – 6.8 to 65 – 6.2, 78 – 7.1, 80 – 7.3 and 84 – 7.6 mmol/min); p < 0.05

ICTP not modified in the three groups

The absolute values or percentage variations of bone markers are reported when given in the studies. In some papers the variations are reported in the figure diagrams given in the studies. Studies are listed according to publication year (from 1997 to 2008).

AT = anaerobic threshold; BAP = bone alkaline phosphatise; CTx = carboxyterminal cross-linking telopeptide of type I collagen; Dpd = deoxypiridinoline; F = female; ICTP = carboxyterminal cross-linked telopeptide of type I procollagen; M = male; NTx = aminoterminal cross-linking telopeptide of type I collagen; PICP = carboxyterminal propeptide of type I procollagen; PINP = aminoterminal propeptide of type I procollagen; Pyr = Pyridinoline; OC = osteocalcin; TRAP = tartrate-resistant acid phosphatase; U/L = units per litre, . measurement units for enzyme activity; lkatal/L = mkatal per litre, measurement units for enzyme activity; VO2max = maximal oxygen uptake.

705

Sports Med 2010; 40 (8)

Sex; age (y) Type of exercise/protocol of blood drawings . M; 23–37 Ergometer cycle 80% VO2max for 1 h; blood drawings before the test, during the test every 30 min, until 2 h after

Bone Metabolism Markers

ª 2010 Adis Data Information BV. All rights reserved.

Table II. Contd

706

difference between the two bone formation markers was the release of a previously synthesized exercise-induced OC not yet incorporated into the bone. Also discordant are the published data for ICTP, a marker liberated during the degradation of type 1 collagen. Salvesen et al.,[54] studied the acute effects of exercise on ICTP; no changes in trained men and women immediately after an intense bout of exercise were found. Kristofferson et al.[39] confirmed that ICTP was unmodified by a Wingate test in young ice hockey players. Ashizawa et al.[43] suggested that while lactic acidosis could increase bone resorption, the markers did not increase after a single bout of resistance exercise. Increased urinary calcium excretion was not accompanied by increased pyridinoline excretion; the source of excreted calcium was not linked to osteoclast stimulation. A study by Herrmann et al.[50] demonstrated no relationship between blood pH, lactate and biochemical bone turnover markers after 60 minutes of anaerobic exercise. The hypothesis for stimulation of osteoclasts by acidosis was not supported by measurements of bone resorption markers; only CTx showed an increase in male athletes 3 and 24 hours after exercise at 110% of the individual anaerobic threshold, while TRAP was unchanged. Conversely, the second hypothesis was the acidosis-induced depression of osteoblast activity. Decreases in OC and PINP were evident at 75% of anaerobic threshold, but an increase at 95% of threshold was held, and there were inconsistent changes at 110% of threshold. The behaviour of bone formation markers after a race is controversial. BAP was reportedly unchanged 24 and 48 hours after a 5–30 km race[40] but showed an immediate and up to 5-day decrease after a marathon,[38] as well as an immediate and a 24-hour decrease after a 245 km race.[51] OC decreased 24 hours after a 30 km race[40] and a marathon[38] and immediately and 24 hours after an ultramarathon[51] but increased immediately after a half-marathon.[52] The transient suppression in osteoblast function occurring during an ultramarathon run, which has been attributed to increases in cortisol and parathyroid hormone (PTH) concentrations, might ª 2010 Adis Data Information BV. All rights reserved.

Banfi et al.

not occur during shorter-distance runs; differences in men after similar races (28 and 21 km) may be due to different pre-analytical conditions (sample matrix and storage) or run intensity.[52] Langberg et al.[44] described a decrease in bone formation that was reflected by PICP, accompanied by increased resorption and then reflected by ICTP after a marathon. In pubertal and prepubertal schoolboys, acute exercise did not modify bone formation or resorption markers, PINP and ICTP, respectively; the values were characteristically higher in the group in pubertal stages 2 and 3 than in prepubertal and pubertal stages 4 and 5.[53] Calcium homeostasis can be influenced by the strain of long-distance running, but even in halfmarathon studies differences in PTH modifications have been measured; the hormone was unmodified in one study[40] but increased immediately after the race in the other.[52] PTH was higher after an ultramarathon, but the strenuous exercise in this case led to considerable changes in calcium metabolism, as reflected by the significant decrease in urinary calcium up to 3 days after the race.[51] Calcium intake is crucial for determining or inhibiting collagen breakdown, as shown in the study by Guillemant et al.[46] Ingestion of calcium-rich mineral water prevented the increase of CTx in trained triathletes after an exhaustive exercise at the cycloergometer. Low protein intake (<1.2 g/kg) induced increased OC in response to short-term resistance training in elite football players, whereas high protein intake did not.[55] Despite the wide discrepancies among the studies, the following conclusions can be drawn:  Short exercise is insufficient for modifying serum concentrations of bone metabolism markers. Their variations are more evident various hours or days after the exercise.  Bone metabolism markers show variable patterns depending on the type of exercise and the study design.  Acute changes may be due to changes in plasma volume and renal function.  Stimulation of osteoblast and osteoclast functions are exercise dependent but immediate and delayed effects need to be distinguished. Sports Med 2010; 40 (8)

Bone Metabolism Markers

707

 Changes in OC may at least partly be due to changes in energy metabolism and increased osteoclast activity.  Resorption markers show an increase in most studies, whereas formation markers appear to decrease. 3. Effects of Training on Bone Metabolism Serum Markers The effects of a training period have been investigated in two studies (table III). Eliakim

et al.[56] studied 44 adolescent males (aged 15–17 years) assigned to two groups, the first without physical activity, the second following a 2-hour daily training (aerobic/endurance) programme for 5 weeks. In the trained males, bone formation markers (BAP, OC, PICP) were found to be increased, whereas no changes were detected in the controls. Only NTx, a bone resorption marker, was found to decrease. In the controls, the markers remained unchanged after the study period; comparison between the two groups showed no differences before the training programme. Brief

Table III. Effects of training on bone serum markersa Study

No. of subjects (M); age (y)

Sport

Type of exercise/protocol of blood drawings

Bone formation markers

Bone resorption markers

Eliakim et al.[56]

38 [20 trained subjects, 18 controls]; 15–17

Sedentary

Endurance-type exercise for 5 wk (2 h/day, 5 days/wk); blood drawings before and after training

BAP increase in trained subjects (from 43.9 – 4.95 to 51.5 – 5.2 U/L); p < 0.05; OC increase in trained subjects (from 92.7 – 12 to 103.1 – 12.7 ng/mL); p < 0.05; PICP increase in trained subjects (from 148.8 – 12.9 to 179.2 – 14 ng/mL); p < 0.05

Pyr not modified; CTx not modified; NTx decrease in trained subjects (from 323.3 – 58.5 to 267.8 – 53.9 nmol/L/mmol/L creatinine); p < 0.05

Woitge et al.[57]

34; 20–29

Sedentary

8 wk training for 3 groups; aerobic: endurance running . (60–85% VO2max); anaerobic: sprint session and weightlifting; controls; blood drawings before training at 4 and after 8 wk

BAP decrease at wk 4 (from 12.6 to 8.9 ng/mL; aerobic, p < 0.05); increase at wk 8 (aerobic from 8.9 to 12.1 ng/mL, and anaerobic vs 4 wk values, from 9.5 to 12.9 ng/mL, p < 0.05) decrease wk 4 (aerobic vs controls). OC decrease at wk 4 (from 8.8 to 5.3 ng/mL, aerobic, p < 0.05); increase at wk 8 (aerobic, from 5.3 to 10.1 ng/mL, and anaerobic, from 10.5 to 11.2 ng/mL, vs 4 wk values, p < 0.05) increase at wk 4 and 8 (anaerobic vs controls, p < 0.05). The reported values are medians

Pyr decrease at wk 4 vs baseline values and controls (from 23.7 to 20.2 mol/L/mmol/L creatinine; aerobic, p < 0.05); increase at wk 8 (from 22.0 to 21.9 nmol/L/mmol/L creatinine; anaerobic, p < 0.01); increase at wk 8 (anaerobic vs 4 wk values, from 21.9 to 27 nmol/L/mmol/L creatinine, and vs controls, p < 0.05). Dpd decrease at wk 4 (aerobic vs baseline, from 6.8 to 5.2 nmol/L/mmol/L creatinine, and controls, p < 0.05). Increase at wk 8 (from 7.0 to 8.4 nmol/L/mmol/L creatinine; anaerobic vs control values, p < 0.05). The reported values are medians

a

The absolute values or percentage variations of bone markers are reported when given in the studies. In some papers the variations are reported in the figure diagrams given in the studies. Studies are listed according to publication year (from 1997 to 2008).

BAP = bone alkaline phosphatase; CTx = carboxyterminal cross-linking telopeptide of type I collagen; Dpd = deoxypiridinoline; M = male; NTx = aminoterminal cross-linking telopeptide of type I collagen; PICP = carboxyterminal propeptide of type I procollagen; Pyr = Pyridinoline; . OC = osteocalcin; U/L = units per litre, measurement units for enzyme activity; VO2max = maximal oxygen uptake.

ª 2010 Adis Data Information BV. All rights reserved.

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708

endurance training in adolescent males stimulated bone formation independent of pubertyassociated production of the related markers, as was also observed in adolescent females where the increase in OC was more pronounced than in the males.[58] Woitge et al.[57] found reduced bone formation after 4 weeks of continuous aerobic training in healthy sedentary males, as measured by decreases in OC and BAP concentrations. At the same time, a significant reduction in urinary excretion of cross-links was reported that corresponded to a low bone resorption rate. Different types of training can influence bone marker concentrations; after 4 weeks the OC concentrations were higher in the anaerobically trained than in the aerobically trained group and after 8 weeks the excretion in urine of cross-links was higher in the anaerobic than in the aerobic group. The bone formation markers returned to baseline after 8 weeks of aerobic training, while bone resorption markers were higher than baseline values. Anaerobic exercise for a period of 8 weeks accelerated bone metabolism, and the resorption markers were correlated to the anaerobic performance indicators. This does not necessarily mean that anaerobic exercise exerts a negative effect on bone formation; the increase in OC over the basal values after 8 weeks was higher than the increase in pyridinoline excretion. Aerobic training induced a net increase in bone formation because of

decreased bone resorption, and anaerobic training increased bone turnover but not bone formation. From these two studies we can summarize that:  BAP changed 1 month after an exercise programme, OC after 2 months, while BAP normalized;  BAP is sensitive to aerobic exercise, OC to anaerobic exercise;  urinary pyridinolines are sensitive to anaerobic exercise;  among resorption markers, NTx is more sensitive than CTx in monitoring training intesity;  the comparison between trained and untrained subjects proved the influence of exercise on bone turnover. 4. Effects of Long-Term Training and Competition on Bone Metabolism Serum Markers and Sex-Related Effects The long-term (at least 6 months) training and competition time were studied in male triathlon athletes and rowers[59,60] and in sedentary trained women.[36] Only Ju¨rima¨e et al.[60] found an increase in OC in top-level rowers. Conversely, BAP was decreased in athletes,[59] but an increase was observed in sedentary trained subjects[36] (table IV).

Table IV. Effects of long-term training and competitions on serum bone markersa Study

No. of subjects

Sex; age (y)

Sport (level)

Study protocol

Biochemical markers

Shibata et al.[36]

28

F; 30–44

Sedentary

Blood drawings at beginning of training (daily walking for 17 subjects, daily walking and jumping for 11) and 1 y later

BAP increase (from 17.3 – 1.1 to 20.6 – 1.0 U/L); p < 0.05. BAP increase walking and jumping vs walking alone; p < 0.05. OC not modified. NTx not modified

Maimoun et al.[59]

7

M; 18–20

Triathlon (national)

Blood drawings at beginning of training and 32 wk later during competitions

OC not modified. BAP decrease (from 23.7 – 8.7 to 18.2 – 9.7 ng/mL); p < 0.05. CTx not modified

Ju¨rima¨e et al.[60]

12

M; 18–23

Rowing (international)

Blood drawings at beginning of training and 6 mo later during competitions

OC increase (from 25.8 – 7.31 to 30.09 – 7.61 ng/mL); p < 0.05

a

The absolute values or percentage variations of bone markers are reported when given in the studies. In some papers the variations are reported in the figure diagrams given in the studies. Studies are listed according to publication year (from 1997 to 2008).

BAP = bone alkaline phosphatase; CTx = carboxyterminal cross-linking telopeptide of type I collagen; F = female; M = male; NTx = aminoterminal cross-linking telopeptide of type I collagen; OC = osteocalcin; U/L = units per litre, measurement units for enzyme activity.

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Bone Metabolism Markers

The intensity of training and competitions could explain the discrepancies; also, the different performance levels of athletes need to be considered. In contrast, bone resorption markers were not modified in either the professional athletes or the sedentary trained subjects.[36,59] The number of studies performed during a whole season in athletes is too low for extrapolating decisions and recommendations; however, it appears that bone turnover is accelerated in trained healthy sedentary subjects, while it is more stable in elite and top-level athletes. In fact, no changes in bone mineral density (BMD) during the season were found; the authors noted a correlation between OC and insulin-like growth factor-1 (IGF-1), even in highly trained athletes with relatively high body mass and body fat.[60] The lack of BMD gain in the weight-bearing sites in triathletes over the course of a whole season confirmed this finding.[59] Furthermore, other studies, which did not report serum biomarkers, found no changes in BMD after the season in male and female triathletes[61] and female field hockey players.[62] A decrease in BMD was described only in male cyclists,[63] as partially expected in an intensive, non-weight-bearing sport.[64] During the season, calcium homeostasis and PTH did not vary in triathletes and rowers, while 1,25-dihydroxy cholecalcipherol concentration significantly rose in the triathletes but was stable in the rowers. The duration of sun exposure could explain these differences.[59,60] In summary, we may state that after prolonged training and competition:  bone formation markers change in sedentary subjects engaged in a physical activity programme;  professional athletes show changes in bone formation markers depending on programme intensity, whereas bone resorption appears to be stable;  during prolonged training, the characteristics of exercise (e.g. weight-bearing, impact) are crucial;  different training baseline levels due to prestudy training history may partly explain different results between athletes and sedentary controls. ª 2010 Adis Data Information BV. All rights reserved.

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Some studies investigated the sex-associated effects. Salvesen et al.[54] administered a running test until exhaustion to well trained men and women. Higher basal OC values were found in the men, while increased OC concentrations were observed immediately after exercise and no modifications were observed in the men. After anaerobic exercise, CTx was increased in the men but unchanged in the women.[50] Welsh et al.[41] found that baseline OC and cross-links were negatively related to the percentage of total body fat. Fat is protective against osteoporosis, as are estrogens the typical female hormones, which are also partially delivered from adipose tissue. This is good evidence for the new paradigm regarding the OC role.[15] Brahm et al.[40] found differences between men and women after a race (15 km for women, 28 km for men). OC decreased 1 day after the race only in the men and then normalized over the next 2 days, whereas PICP, the other bone formation marker, behaved similarly but only in the women. OC did not decrease in the women probably because of low basal concentrations, which could not be suppressed further. The baseline concentrations were significantly lower in the women than in men. The PTH levels after the race were unchanged in both groups, but the baseline levels were significantly higher in the women. In contrast, a decrease in OC was described in both men and women after a marathon, and the decrease persisted up to 24 hours after the race.[38] In general, the differences between male and female athletes are similar to those described in the general population. Herrmann and Herrmann[65] studied elite endurance female athletes. The blood drawings were performed during the follicular phase of the menstrual cycle (median day, 12). Subgroup analysis revealed that athletes using an oral contraceptive did present with increased bone resorption but it was not accompanied by a shift of osteoprotegerin and soluble tumour necrosis factor-a receptor antagonist ligand, suggesting a protective effect of the drug treatment. A specific problem of female athletes is amenorrhoea due to reduced energy availability and hypogonadotropic hypogonadism. Particularly Sports Med 2010; 40 (8)

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common among endurance athletes, amenorrhoea is linked to low BMD. Certain hormones and adipokines (e.g. leptin, ghrelin, peptide YY and adiponectin) reflect the state of energy availability. High levels of ghrelin and low levels of leptin were found in athletes with amenorrhoea. The peptide YY, an anorexigenic molecule produced by endocrine gut cells in response to intraluminal nutrients was also high in amenorrhoeic athletes, while adiponectin showed no difference with respect to controls. In amenorrhoeic adolescent endurance athletes evaluated during the early follicular phase of the menstrual cycle, Russell et al.[66] described lower concentrations of bone formation marker PINP than in controls. No differences for the resorption marker NTx were found. Peptide YY could be considered as an independent negative predictor of PINP. The linkage between low energy intake, amenorrhoea and reduced bone density in women athletes is mediated by endocrinological control, inducing variations in systemic bone formation markers. Since biological bone markers may fluctuate during the menstrual cycle, studies on females should report the time of blood sampling; it is performed in few studies.[49,65,66] Some describe the eumenorrhoeic status of athletes,[40,42,67] others do not;[36,38,45] the use of oral contraceptives by some subjects was only reported in two studies.[45,50] The evaluation before a year of training and competition did not show any significant increases in the excretion of pyridinolines in female track and field athletes when compared with nonphysically active controls as was also noted for the male group; however, a difference emerged for athletes belonging to disciplines characterized by high power who had higher excretion concentrations than endurance athletes. Endurance athletes reported fewer menses in the year preceding the study than the controls and during the 12-month study all 53 athletes, except two, were eumenorrhoeic.[68] Generally, the type of sport is more important than the athlete’s gender; there were differences between elite judokas, who had higher turnover and higher levels of urinary pyridinolines than swimmers or runners, but not between males and females for each different discipline.[69] ª 2010 Adis Data Information BV. All rights reserved.

5. Bone Metabolism Markers and Different Types of Sport A major distinction between types of sport is whether they are characterized by high impact and weight-bearing activities or by non-weight-bearing activities. For example, male cyclists ordinarily have a lower BMD than male runners.[64] Activities resulting in high skeletal impacts may be osteotropic for young women. Collegiate gymnasts showed increases in BMD during an 8- and 12-month longitudinal study in comparison with matched athletes exposed to lower loading patterns competing in running and swimming. In particular, BMD measured at the femoral neck and the lumbar spine was greater in gymnasts than in swimmers and runners and sedentary controls. The changes in BMD were independent of menstrual cycle regularity in the gymnasts.[67] Gymnasts had a significantly higher BMD at both pre-season and during season tests compared with cross-country runners.[70] Urinary pyridinolines were higher in power track and field female athletes than in endurance athletes; there was no difference between the same groups of male athletes.[68] NTx was highest among collegiate rowing athletes and higher in rowers and runners than in swimmers or controls. CTx was higher in runners than in rowers, swimmers or controls.[71] Bone resorption seems to be consistently higher in athletes, especially in those involved in endurance exercises; 25 females exhibited higher levels of bone resorption CTx than controls.[50] Male athletes engaged in rugby, soccer and martial arts had higher BMD values than other athletes, while swimmers, rowers and bodybuilders had lower values.[72] The differences among sports are also related to impact and jumping, as demonstrated in sedentary women trained for walking or walking and jumping.[36] Female athletes who participated in impact sports (volleyball, basketball) had higher BMD values and higher OC concentrations than swimmers, whereas no differences were observed for bone resorption, as measured by NTx concentrations.[73] However, Maimoun et al.,[74] in a study on male athletes practicing cycling (n = 11), swimming (n = 13) and triathlon Sports Med 2010; 40 (8)

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(n = 14) compared with non-athletes, concluded that bone turnover is sport-practice dependent but not sport-discipline dependent. The same authors showed that decathletes had higher BMD values than controls, as well as higher values of OC, CTx and vitamin D, whereas leptin values were lower in athletes when adjusted for body fat mass. However, the blunted leptin secretion in athletes did not seem to have a deleterious effect on bone metabolism.[75] If athletes have a higher premenopausal BMD they may still be partially protected. Theoretically, sport should protect against the risk of osteoporosis. However, this does not really happen. The high levels of physical activity observed in women athletes (n = 50, aged 18–69 years; swimmers, triathletes and runners) was not sufficient to prevent loss of bone with aging. BAP and Dpd did not differ from controls, and NTx was lower in the athletes.[76] Moreover, soccer exercise in men for over 6 hours per week does not appear to have additional benefits in bone turnover. Duration of exercise does not seem to confer additional benefits, as testified by former professional athletes who practised soccer for almost 8 years.[77] The published data suggest that athletes should be followed up after the competition season and during long-term detraining periods for various reasons, especially following injury. The use of bone resorption markers, particularly when measured in urine, could be a practical and easy tool to monitor bone metabolism in athletes and to prevent problems. Moreover, because of the huge differences in the demands a certain sport places on an athlete, considering athletes as a homogeneous group for bone metabolism studies would constitute a serious flaw in study design. 6. Conclusions The use of bone metabolism markers in athletes should be encouraged for studying bone turnover and general bone metabolism status. Because strenuous effort and physical stress, depending on the type of exercise and sport, can deeply affect bone cell activity, studies should ideally involve subjects enrolled in long-term and ª 2010 Adis Data Information BV. All rights reserved.

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standardized training programmes. When possible, such studies would be conducted over an entire competition season so as to define a common profile of bone markers in athletes, who are highly sensitive to the effects of detraining and off-field intervals, particularly among professionals following injury or technical decisions. Given the lack of homogeneous behaviour of bone markers in athletes, specific studies are needed that take into account the different effects a certain sport will have on bone metabolism. The use of bone metabolism markers rather than radiological examinations could be recommended for defining the bone status of amateur and professional athletes. In this cost-conscious era, one marker for bone formation and one for bone resorption would be sufficient. Intra- and interindividual variability of bone metabolism markers prevent the meaningful use of these markers in small studies. In addition, serial measurements should be performed whenever possible. A high level of pre-analytical standardization is essential to minimize variability. Based on available data, there exists no rationale for a general use of bone markers in athletes; considering the lack of evidence these parameters can not be recommended for the assessment and management of individual athletes unless a medical condition, such as hypothalamic hypogonadism, is present. The results are highly variable and only large and well controlled studies might help to further our understanding of bone metabolism in exercise and the role of biochemical markers. Acknowledgements We are indebted to Mr Kenneth Britsch, who reviewed the manuscript for style. No funding was used in the preparation of this review. The authors have no conflicts of interest directly relevant to the content of the review.

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Correspondence: Professor Giuseppe Banfi, IRCCS Galeazzi, School of Medicine, University of Milan, Via R Galeazzi, 4 - 20161 Milan, Italy. E-mail: [email protected]

Sports Med 2010; 40 (8)