Sports Med 2008; 38 (10): 795-805 0112-1642/08/0010-0795/$48.00/0
CURRENT OPINION
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Meeting the Global Demand of Sports Safety The Intersection of Science and Policy in Sports Safety Toomas Timpka,1 Caroline F. Finch,2 Claude Goulet,3 Tim Noakes4 and Kaissar Yammine5 for the Safe Sports International Board 1 Department of Medicine and Health, Linko¨ping University, Linko¨ping, Sweden 2 School of Human Movement and Sport Sciences, University of Ballarat, Ballarat, Victoria, Australia 3 Department of Physical Education, Laval University, Que´bec City, Que´bec, Canada 4 Sports Science Centre, University of Cape Town, Cape Town, Republic of South Africa 5 Lebanese Association for Sports Injury Prevention and Antonine University, Beirut, Lebanon
Abstract
Sports and physical activity are transforming, and being transformed by, the societies in which they are practised. From the perspectives of both competitive and non-competitive sports, the complexity of their integration into today’s society has led to neither sports federations nor governments being able to manage the safety problem alone. In other words, these agencies, whilst promoting sport and physical activity, deliver policy and practices in an uncoordinated way that largely ignores the need for a concurrent overall policy for sports safety. This article reviews and analyses the possibility of developing an overall sports safety policy from a global viewpoint. Firstly, we describe the role of sports in today’s societies and the context within which much sport is delivered. We then discuss global issues related to injury prevention and safety in sports, with practical relevance to this important sector, including an analysis of critical policy issues necessary for the future development of the area and significant safety gains for all. We argue that there is a need to establish the sports injury problem as a critical component of general global health policy agendas, and to introduce sports safety as a mandatory component of all sustainable sports organizations. We conclude that the establishment of an explicit intersection between science and policy making is necessary for the future development of sports and the necessary safety gains required for all participants around the world. The Safe Sports International safety promotion programme is outlined as an example of an international organization active within this arena.
1. Sport in Contemporary Society Sports and physical activity are transforming, and being transformed by, the societies in which they are practised. Competitive sport has become the centre of a multinational industry producing
services and products with strong links to media networks. Globally, broadcasts of major sport events provide forms of entertainment in the media market and provide opportunities to display new consumer goods, ranging from sports equipment to a variety of products that are marketed to be
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associated with a sporting and rewarding lifestyle, e.g. soft drinks, home electronics and cars. For instance, the televised 2007 US SuperBowl game was watched by more than 90 million viewers globally and attracted advertisers willing to spend $US2.5 million on each 30-second commercial. The downside of these advertising and media imperatives, which rely on the entertainment value of fierce sporting competition and the charisma of sporting stars, is that little attention is paid to the risk for ‘industrial diseases’ caused by both direct extreme physical loads and indirect consequences of economic exploitation among professional athletes. At the same time, public health agencies are actively promoting physical activity in adults, while physicians and educators are joining forces in bringing play, particularly physically challenging unstructured outdoor play, back into children’s daily lives.[1] Too often, however, these efforts neglect to ensure that the exercise is performed without unnecessary injury risk. For example, the facts that physical exercise programmes for the elderly may be associated with risks for falls, and that promotion of new activity opportunities for children and adolescents (such as home trampolines and skateboard parks) introduces new injury risks are often ignored. There seems to be a perception that if physical activity advocates were to talk about safety issues, people would not be active. In fact, the converse is true, as unsafe activity is one of the major barriers towards ongoing physical activity.[2] It seems clear that preventing injuries from occurring in the first place, and thereby delivering safe sport, should be a major positive physical activity promotion goal and incorporated into broad health promotion agendas. From the perspectives of both competitive and non-competitive sports, the complexity of their integration into today’s society has led to neither sports federations nor (local) governments being able to manage the safety problem alone. In other words, these agencies, whilst promoting sport and physical activity, deliver policy and practices in an incomplete way that largely ignores the need for a concurrent overall policy for sports safety. This article reviews and analyses the possibilities of developing overall policies for sports safety from a global viewpoint. Because this paper is more of a position paper than a critical review of the ª 2008 Adis Data Information BV. All rights reserved.
literature, a systematic review was not undertaken. PubMed was employed to search the MEDLINE databases using the terms ‘sports injuries’, ‘sports injury prevention’, ‘sports safety’ and ‘sports policy’. From the basic set of abstracts of 6200 articles published since 1996, 350 articles were chosen as being potentially relevant to this the review. The reference lists of these articles were used to identify additional books and previously published materials relevant for the aim of the analysis. From this accumulated literature, only the articles of direct relevance to the positions and views presented in this review are referred to in this paper. The concluding analysis of the relevant texts was summarized in sections describing the social role of sports, global sports safety concerns, the structural underpinnings for promotion of sports safety, and the importance of the intersection between science and policy making in the formation of safe sport practices. Finally, the Safe Sports International (SSI) [www.safesportinternational.org] safety promotion programme, a new globally focused initiative to progress these issues, is outlined as an example of an international organization active in this intersection. 1.1 The Social Role of Sports: From Gameplay to Sports Industry
Even a cursory glance at the global news and media coverage would suggest that sport and physical activity have a more important position in social life today than ever before. Despite this attention, many modern public health concerns are associated with an increasingly sedentary lifestyle. For instance, in developed countries, the global obesity epidemic is reflected in a rapid increase in the prevalence of obesity and overweight, and their associated chronic medical conditions.[3] The irony of this is that this ‘epidemic’ has evolved in spite of long recognition of the beneficial role of participation in games and sports for physical, mental and social development[4] and the prevention of health problems.[5,6] One explanation for this paradox can be found in the growing gap between physical activity and competitive sport. With increasing competition, the amount of practice required forces children to choose between sports at an earlier age, and less competitive individuals may be altogether removed from sports development Sports Med 2008; 38 (10)
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groups in adolescence.[7] These circumstances may well be leading to fewer young people participating in traditional sports, and those who do participate being expected to compete for positions as professional athletes at increasingly younger ages. Humankind has always played games based on physical challenges. Studies of traditional practices among Australian Aborigines and East African hunters suggest that these groups spent about one-quarter of their time finding and preparing food, and used the remaining time for different forms of play and music.[8] In Homo Ludens (Man the Player),[9] the Dutch anthropologist Johann Huizinga provided a comprehensive account of play in human culture. He recognized that when a person steps in or out of a game, he/she crosses a predetermined boundary that defines that game in time and space. To qualify as a game, participants should be able to cross this ‘boundary for play’ at their free will. Gameplay is thus circumscribed by a virtual or physical shield – Huizinga called this the ‘magic circle’ – which is a psychological boundary that stands between the participant and the ‘real world’.[10] In his further analysis, Huizinga linked the joyful and combative nature of play to education, art, religion and other essential elements of human culture and asserted that play ‘‘is a significant function’’ – that is to say, there is something ‘at play’ that transcends the immediate needs of life and imparts meaning to the action.[9] Today, the notion of a significant function of play has gained new, and differentiated, meanings adapted to the pre- and post-industrial societies. On the one hand, sports and physical activity is actively promoted by public health agencies and the maintenance of exercise habits with increasing age is encouraged. Progressively during the 20th century, however, sport as gameplay for fun and pleasure, has become accompanied by an emphasis on competitive athletics and professional sports. These latter physical activities are characterized by a spirit of dedication, sacrifice and intensity and with a prime aim of victory in the contest.[11] In only a few decades, professional sport has become an important international industry that not only involves sportspersons, coaches and administrators, but also media companies, equipment manufacturers, marketers and advertisers. For example, the television rights for the 2006 FIFA (Fe´de´ration Internationale de ª 2008 Adis Data Information BV. All rights reserved.
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Football Association) football World Cup were sold for $US6 billion, and sports sponsorship at a global level was estimated to be already worth approximately $US20 billion in 1999.[12] In 1999, the Council of Europe estimated that 3% of world trade concerned recreational and competitive sports, while the European Commission estimated that 2 million sports-related jobs had been created in the region between 1990 and 1999.[13] In other words, the roles of sports in today’s societies, and the contexts within which sports are delivered, are heterogeneous and not straightforward to overview or comprehend. Accordingly, the identification of global issues related to injury prevention and safety in sports requires careful examination, in particular if the analysis is to lead to the recognition of critical policy issues necessary for the future development of the area and significant safety gains for all.
2. Global Sports Safety Concerns Just as safety became a significant problem that had to be addressed in the factories during the rapid industrial revolution of the late 19th century, so too are we witnessing a similar need in today’s sports as they become more ‘industrialized’. Safety has been defined by the WHO as the ‘‘state in which hazards and conditions leading to physical, psychological, or material harm are controlled in order to preserve the health and well-being of individuals and the community.’’[14] Because sports and physical activity challenge human physical ability, it is likely they may always be associated with some element of risk of harm, at least to some participants. Nonetheless, most of the risks associated with sport participation, particularly for community level participants, can be minimized or controlled with the adoption of suitable prevention strategies.[15] In the international literature, injury is regarded as a limiting condition resulting from physical or mental harm to what is considered a normal human being. The assumptions of an average and static human body, however, do not have natural pertinence to all contexts. In high performance sporting activity, for example, human physical ability is challenged within the boundaries of rulegoverned practices and games and is highly competitive. Accordingly, sports injuries are defined in Sports Med 2008; 38 (10)
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terms of how they adversely influence an athlete’s ability to excel in performance according to the rules of the game or whether they exclude an athlete from further participation in that activity.[16] Founded on this relative framework, sports injury is often defined in terms of ‘time lost’ from participation.[17-19] Even though such a definition may be sound with regard to the nature of competitive sports, it does not take into account the broader context of sport and physical activity in today’s societies, which encompasses a set of significantly different and dynamically changing activities, and which may or may not include an element of competition. Some professional and competitive sports have become burdened with their own injuries to such an extent that they now represent forms of ‘industrial diseases.’[20] Overall injury rates are higher in sports entailing more frequent and powerful body contact, particularly because of collisions. Studies in English professional football, for instance, have shown that the risk for injury among players is about 1000 times the risk in other occupations normally considered as high risk, such as mining or construction.[21] Each sport has its own characteristic injury profile. Even though catastrophic injuries are relatively rare, pole vaulting, gymnastics, ice hockey and American football are examples of sports with a high incidence of acute severe injuries.[22] Lower limb injuries are generally the most common in sports involving large amounts of running, jumping, landing and changing direction.[23] The development of osteoarthritis and other adverse health outcomes secondary to sports injury is also a particularly important concern because of its association with poorer health-related quality of life and reduced participation in physical activity after retirement from sport.[2,24] There is now irrefutable evidence that the sports injury problem is not restricted to professional sports. Economic evaluations in general populations have suggested that participation in community sports by 20- to 45-year-olds leads to more costs through injuries than benefits through positive health effects,[25] even though other studies have showed less conclusive results.[26] For more than two decades, about every fifth unintentional injury treated in a healthcare setting in industrialized countries has been associated with sports
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or physical activity.[27] In 2006, 31 in every 1000 adult Germans sustained a sports injury during the previous year;[28] the corresponding rate is 88 injured people per 1000 sports participants in the Canadian province of Que´bec.[29] In the US, an estimated 7 million people receive medical attention for sports injuries each year, corresponding to 26 injury episodes per 1000 persons.[30] Australia has recently reported 37 cases of medically treated sports injuries per 1000 active persons, with many injuries associated with adverse public health impacts.[31] Traditional sports safety approaches have been based on those for the prevention of general physical injury. However, a key point of the WHO definition of safety is that it has two dimensions: physical safety factors and an individual’s internal feelings of being safe.[14] This widening of the safety concept from merely the control of physical injury[32] is particularly pertinent for sports and physical activity. For instance, although sexual harassment and abuse have been recognized problems in the workplace for more than three decades, the prevalence of sexual exploitation in sports and the consequences for survivors have only recently started to emerge.[33] A particular set of safety issues concerns children involved in competitive athletics. Young athletes have been reported to be at increased risk for specific types of acute physical harm, e.g. growth plate and apophyseal injuries and heat illness.[34] Furthermore, their growing bodies are particularly susceptible to overuse injuries, e.g. little leaguer’s shoulder, spondylolisthesis, Osgood-Schlatter disease and Sever’s disease.[35] Child athletes must be guided by gradual skills development, adapted for their psychological maturity, to ensure that the sport environment is a wholesome and emotionally rewarding experience for all levels of participation and competition.[36] A focus on highly competitive sport has meant that since the 1970s, intensive training programmes have been provided to young people in sports such as gymnastics, figure skating, diving, football, ice hockey and tennis. In gymnastics, the average age for the best athletes has dropped from 25 years in 1965 to about 17 years at present.[37] Today, governments and professional clubs organize development programmes specifically directed at young athletes in sports academies and specialized athletic centres. The selection of
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talented children to the programmes’ later stages is mainly based on their achievements in competitions, exposing them to increased risks of extensive physical and mental stress.[38] Despite the fact that many youth sports programmes are well balanced and integrated with schooling, the economic exploitation of child athletes has been compared to child labour.[39] Given the personal and family sacrifices that are needed to attain competitive results, it is doubtful whether involvement of young children in some programmes could be described as gameplay. The International Labour Organisation (ILO) minimum age convention,[40] ratified by 146 nations over the world, prohibits work for children under the age of 15 years, but allows ‘light work’ for children aged ‡13 years. It may be possible to compare a Canadian or Swedish ice hockey player, aged 14 years, who skates for a hockey club for more than 3 hours, 6 days a week to a child of the same age working on a farm in the developing world. However, in no country has the labour legislation has been specific enough to address the situation of young athletes.[41] The United Nations (UN) convention on the Rights of the Child, adopted in 1989 and ratified by all nations except Somalia and the US, remains the most powerful regulation available to judge whether competitive sports are compatible with ‘the best interest of the child’.[41] This convention regulates children’s rights in relation to not only employers, but also parents, other adults, schools and healthcare delivery settings. Despite the fact that the convention has been in place for almost two decades, there are very few institutional programmes implemented for the surveillance of potential abuse of child athletes and taking action on child protection in sports (for an exception, see Sport England and the National Society for the Prevention of Cruelty to Children [NSPCC]).[42] Another area related to child sports safety is the dislocation of young people with sports talent from their family and friends. The shipping of young sportspersons between the developing world and professional clubs in Europe and the US has grown extensively during the last decade and has been described as ‘sports trafficking’.[43] For example, it is estimated that about 500–700 young baseball players are sent to the US from Latin America every year.[44] The number of young ª 2008 Adis Data Information BV. All rights reserved.
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football players travelling from Africa and South America to Europe is not known; in the late 1990s, it was estimated that about 400 young players left Uruguay to play in Europe.[45] Sports trafficking has only recently been brought to public attention, and reliable data to quantify this problem are largely lacking. 2.1 The Promotion of Sports Safety
The rapid development of sport and the global sports industry has occurred without concurrent development of safety initiatives. This means that the present safety-supporting environments for sport are largely under-developed or misplaced in comparison with aspects of societal duty of care. At the international policy level, in 2004 the UN issued the strongest statement available today on sports safety. In resolution 58/5,[46] it is acknowledged that the hazards associated with sports span much more than just physical injury. Threats to the health and well-being of young athletes were stated to be related to ‘‘child labor, violence, doping, early specialisation, over-training and exploitative forms of commercialisation, as well as less visible threats and deprivations, such as premature severance of family bonds and the loss of sporting, social and cultural ties.’’ Even though the international sports federations recognize these issues, few, if any, have the resources or the mandate to manage them on their own. Lessons learnt from coping with emerging safety issues during the industrial revolution suggest that the management and promotion of sports safety will require multi-professional skills and concerted efforts from many different agencies. Such efforts will need to be implemented in ‘glocalized’ communities, i.e. at local, national and international levels, along with joint efforts from individuals, companies, governments and other local agencies.[47] Importantly, in the sporting context, these must include the national and international federations, as well as professional and amateur sports clubs.[48] If sports safety is to repeat the success stories of safety improvements in factories and on roads, it must be prepared to modify physical, social, technological, political, and organizational structures and environments, as well as the perceptions and behaviours or organizations and individuals. Sports Med 2008; 38 (10)
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Advancing sports safety at the global level will require evidence-informed management and action by sports federations and clubs, on the one hand, and the authorities responsible for sports facilities and legislations in the civil society on the other. Such evidence-based sports safety promotion demands close involvement with researchers (to provide the evidence) and practitioners (to adopt the scientific knowledge into practice), which in turn requires a new methodological framework for sports safety research. The Translating Research into Injury Prevention Practice (TRIPP) model[49] builds on the fact that only research that is adopted by sports participants, their coaches and sporting bodies will prevent injuries. Importantly, advances in sports safety will only be achieved if research efforts are directed towards understanding the implementation context for injury prevention, as well as continuing to build the evidence base for their efficacy and effectiveness of interventions. An example of the development of an intervention that has followed these principals is the protective eyewear promotion for squash players in Australia.[50]
3. Science and Policies for Safe Sports As early as 1976, it was noted that ‘‘we place an undue emphasis on the gifted athletes 15 to 22, a preposterous emphasis on a few professionals aged 23 to 35, and never enough on the mass of our population.’’[51] Other observers have pointed out that the strong financial support directed towards elite sports can only have a significant negative impact on how sports are socially perceived and structured, over and above allowing the wealthiest teams to win.[52] For example, many communities invest in facilities for competitive sports, even if the investments simultaneously force them to cut resources in other areas for public spending.[53] The fiercest critics assert that increased commercialization will lead to violation of traditionally highly valued aspects of sport, e.g. downplay of enjoyment, disregard of fair play, and neglect of increasing violence.[54] Regardless of whether these critics are right or not, the demands that individuals, organizations and societies place on human physical and mental capabilities in different sporting contexts modify how injury risk is identified, accepted and managed. It is therefore imperative that injury ª 2008 Adis Data Information BV. All rights reserved.
prevention and safety promotion in sport is adapted to the specific social construct of sporting practice and the culture of its delivery. For instance, the Lebanese Association for Sports Injury Prevention has developed a safe sport policy suitable for Lebanon and the Middle East countries in terms of sports regulations, and legislation proposals based on the specific conditions in the region.[55] The context-dependence of the injury problem implies that there is a significant role for sports scientists to play if social and ecological fallacy is to be avoided when addressing safety issues in sports policy making. Traditionally focused sports injury prevention research has contributed to the building of an evidence base about the magnitude of the injury problem, identification of risk factors and efficacy of interventions.[56,57] Unfortunately, such approaches only indirectly impact on policy change, and from a global prevention perspective, contributions from traditional scientific knowledge may be insufficient.[48,49] Jackson et al.[58] argue that more research is needed into how to strengthen and garner community action before our health challenges can be effectively addressed. The management of the sports injury problem will require a constant intermingling between scientific findings, contextual factors and values in both the scientific and the policy processes. Very few would argue that science and policy making are separate entities in today’s societies.[59] Sports science and sports policy are not only intersecting, but also co-evolving social domains. As an example, the development and implementation of sports safety policies is significantly influenced by differences between the distribution of the intervention costs and the corresponding distribution of benefits among groups of sports participants or communities. Sports injury researchers should contribute to the balancing of this decision process by conducting cost-effectiveness studies. This is an area where little work has been done, but the example from Que´bec of face guards for ice-hockey players shows the power of this information. After 1 year of enforcement among adult recreational players, the full face protector use rate increased from 25% to 88%. It was estimated that the regulation resulted in a net saving of $Can1.9 million in healthcare costs alone, and a savings-cost ratio for the regulation of 1.87 : 1.[60] Having said this, it also has to be acknowledged that concentrated Sports Med 2008; 38 (10)
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interests still often outweigh the interests of larger populations in policy making, particularly in the absence of cost-effectiveness information. Government and organizational decision makers expect criticism for decisions that impose costs rather than expecting recognition for providing new benefits.[61] As a result, the most politically feasible environment for policy change is one of ‘client politics’, which offers visible benefits for a specific group while imposing diffuse costs and few disadvantages among other groups. In other words, the institutional environment predisposes for a bias among policy makers towards providing beneficial policy to organizations and population subgroups that both have a powerful societal voice and are, in the public opinion, regarded as ‘deserving’. In the sports safety context, researchers can contribute to decreasing this bias by evaluating sports safety policies with regard to outcomes among less resourceful groups and, in the global setting, in developing countries. For instance, building on experiences from other health policy areas,[62] influence from the media coverage of certain sports and sportspersons can neutralize scientific knowledge in decisions regarding safety policies. The issue is that sports journalists often glorify injuries, with major sports stars ‘battling on’, injury making them even bigger
heroes. The message given is that it is ‘alright to play with injury if you are going to win’[63] and ‘hero’ status is often afforded to athletes who do so. This message, however, tells parents and other significant stakeholders that sport is an inherently high-risk activity, and this may lead to parents actively preventing their children from playing certain sports.[64] In such situations, based on their experiences as media consumers, not only may those targeted by sports safety programmes respond negatively to the interventions themselves, but also the general public may regard them as ‘not deserving’.[65] This element of injury glorification in the dramaturgy of sports journalism is an example of influence on sports policy that can be counteracted by properly targeted sports safety research. If an intersection between sports science and sports policy can be established, a series of practical and theoretical issues associated with sports safety, such as the media reports of injuries, can be addressed by exchange of ideas and knowledge. To be able to manage such a shared arena, the basic processes in the intersection need to be made explicit. These processes can be defined as social courses of action that encompass relations between scientists and actors involved in sports policy making, and that allow for dialogue, co-evolution and joint improvement of policy making (table I).
Table I. Intersection between science and policy in the area of sports safety (adapted from van den Hove,[66] with permission from Elsevier. Copyright ª 2007) Manifestations of sports safety science
Examples of intersection with policy in sports
Outputs
Definitions of objective knowledge Integration of scientific knowledge in sports safety policy making (explanations, predictions) Sports safety research contributes to emergence of novel issues on sports policy agenda, and establishes safety during physical exercise at the health promotion agenda
Processes Defining and describing a sports safety problem, and designing potential solutions
Coordination between scientific and policy process
Organization and funding of research
Sports research policy is driven by political considerations, with appropriate funding and infrastructure support Results of sports safety research influence prioritisation in sports policy
Quality and validation processes
Requirement of scientific validation in sports policy processes
Education and training processes
Policy influence on orientation of education and training Influence of education and training on role of science in policy
Networking processes
Channelling scientific sports safety knowledge to policy makers and practitioners
Sports safety scientists
Scientific experts participating in policy processes Scientific experts influencing policy by reporting their values and interests
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3.1 Safe Sports International
International sports safety programmes are yet to critically evaluate sports safety policies and injury prevention programmes with regard to outcomes for a broad range of client groups, covering the spectrum of those who are socially disadvantaged to those from wealthy Western countries. At the global level, it is particularly important that the estimated and factual effects of institutional sports safety interventions in the third world country context be considered. SSI is an impartial non-profit programme for global promotion of sports safety that was established in 2006. It originates from the Safe Communities movement,[67] but is autonomous with regard to its policy and scope. An important underpinning for the operation of the SSI programme is the sports safety experience from Que´bec, Canada. In 1979, to significantly contribute to the establishment of safe environments, the government of Que´bec adopted the Act Respecting Safety in Sports, which created the Que´bec Sports Safety Board (QSSB).[68] The QSSB has not been in operation since 1998, but the Act is still in place. The Que´bec Ministry of Education, Leisure, and Sport is responsible for its application. The SSI management group includes representatives from all continents to ensure its global relevance. SSI has nine operational objectives covering general principles, scientific needs and policy goals. These are outlined in table II, table III and table IV. Through addressing these objectives, the ultimate goal of SSI is to establish a sports safety colloquium shared by sportspersons, sports scientists, sports officials, and agencies that are responsible for implementing and administering policies at national and international levels. Table II. General objectives of Safe Sport International (SSI) To bring community sports back into health, promoting the ‘magic circle of gameplay’, while also accommodating the pursuit of excellence by developing a scientifically informed international platform that brings together socially and geographically defined communities having an interest in increasing sports safety To advance the level of ‘industrial safety’ in professional sports by distribution of information and empowerment of athletes, and supporting sports federations and other agencies with responsibility for the establishment of safe sports environments To recognize and act on the synergies between global health promotion efforts and safety promotion
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Table III. Policy objectives of Safe Sport International (SSI) To advocate and promote international efforts in sports injury prevention research that significantly contribute to the evidence base for the effectiveness and efficacy of all sports safety prevention measures To care for the rights of child athletes to remain children (United Nations convention on the Rights of the Child, ILO C138) To assist developing countries in sports injury initiatives by disseminating information about the evidence base on sports safety and by establishing international networks To advocate national and international policy, and to guide governmental and sports body formal responses to the sports injury problem
A central tenet of SSI is that young sportspersons have the right to health and well-being, to be achieved by a balance of sports industry needs, safety-orientated scientific knowledge and evidence-based actions. The aim of the programme is 2-fold: to establish the sports injury problem firmly on the global health policy agenda, and to introduce sports safety as a mandatory component in the establishment of sustainable sports organizations. The programme is founded on a solid base of sports injury epidemiology and proceeds by accepting that the interaction between science and politics plays a critical role in health affairs, and that sports safety should not excluded from this interplay. It is recognized that in addition to scientific evidence, public perceptions regarding the severity and solvability of the sports safety problem, responsibility issues and the social position of affected populations all influence organizational and governmental responses.[69] The SSI programme aims to collate scientific evidence for identifying when large-scale transformation of sports safety policy can and should be implemented, thus dynamically highlighting the actual critical processes in the safety policy development. The programme also addresses how fragmented agencies, resistant commercial interests and other economic constraints can lead policy makers in sports to adopt a ‘minimal change’ strategy in safety policy rather than making comprehensive reforms when faced with urgent problems. SSI is adopting a working method that supports the formation of partnerships between sports safety researchers and socially defined sports-specific communities, addressing locally identified problems. In parallel, through co-operation with general safety promotion and injury prevention
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Table IV. Scientific objectives of Safe Sport International (SSI) To recognize that there are particular implementation challenges in the sports injury context that justify the employment of a contextspecific framework for the transfer of research results to practice settings and to develop innovative methodologies to allow this to occur To work towards the standardization of concepts and definitions such as sports injury and sports safety, as these are critical for adding to the research evidence base, the evaluation of implemented safety programmes and the monitoring of both spatial and temporal trends in injury rates To advocate and support, where appropriate, the formal evaluation of sports safety programmes, particularly those implemented in community settings
programmes, SSI mediates alliances with geographically defined communities in efforts to develop safe local environments for physical activities. The programme uses electronic media and the Internet strategically to reach its goals, as these have previously been successful as community mobilization strategies in health promotion.[70] In doing so, it takes advantage of recent advances in technical designs for computer networks for the supporting of broad health promotion programmes.[71] The formation of SSI is a direct response to the need to establish the sports injury problem as a critical component of general global health policy agendas, and to introduce sports safety as a mandatory component of all sustainable sports organizations. It is thereby recognized that the establishment of an explicit intersection between science and policy making is necessary for the future development of all sports and the necessary safety gains required for participants around the world. Accordingly, the SSI safety promotion programme is organized particularly to be active in this intersection.
4. Conclusion Although incremental responses to sports safety problems are starting to become established in many settings, particularly in the more wealthy Westernized countries, they are likely to remain restricted to local issues or to particular groups of athletes. At the community level, erroneous public beliefs that ‘sports injury is inevitable’ can lead to sports safety issues being downgraded in importance in favour of other health problems that are perceived to be more important or preventable. In the commercial sports industry setting, scientific ª 2008 Adis Data Information BV. All rights reserved.
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evidence can become outweighed by industry opposition and economic arguments. In recent years, there has been a growing activity around the topic of science-policy interfaces.[72] A key reason behind the emergence of this concept is that it captures a series of practical experiences and needs, and reflects theoretical and methodological interrogations. Organizations such as SSI can contribute to overcoming the inertia against the adoption of radical and comprehensive safety policies in sports by networking, empowerment of deprived groups, and impartial analyses of scientific evidence and accumulating information about the key components of partnerships for health promotion gains. Scientific evidence is the central asset in this process, as it can be applied to both particular safety policy processes (e.g. the use of protective equipments in specific sports) and general issues at a global scale (e.g. concerning children’s rights in the professional sports context). However, the mere availability of evidence is not enough for policy change to take place. A series of methodological issues in the interface between science and policy in sports safety still need to be solved before the interaction can become efficient. These problems include improvement of the interface transparency – in particular with regard to sportspersons and the public, translation of scientific knowledge into policy-relevant knowledge (and of policy statements into scientific evaluation questions), the development of dissemination channels for scientific knowledge to the various potential user groups, and the establishment of science-policy interfaces in a democratic context. In summary, opening windows of opportunity for sports safety policy change will require significant shifts in the public perception of the injury problem and in the distribution of control of the strategic power within sport.[73] This will only be achieved when there is a convergence of problem understanding among scientists and policy makers. The strategy for global sports safety organizations, such as SSI, must therefore be defined with regard to opportunities for accommodating and balancing scientifically validated policy alternatives against the priorities of political leaders, international sports organizations, commercial interests and the public opinion. Given the complex integration of sport in today’s societies, a viable constituency for sports safety can only be mobilized, and sustainable Sports Med 2008; 38 (10)
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policy innovations reached within reasonable periods, if a stable global infrastructure for negotiating such convergences can be established.
16.
Acknowledgements 17.
The Board of Safe Sports International also includes Professor JoonPil Cho, Ajou University, South Korea (representing Asia), and Professor Leif Svanstro¨m, Karolinska Institutet, Sweden (representing the Safe Communities movement). T. Timpka is supported by a research grant from Linko¨ping University, and C. Finch is supported by a National Health and Medical Research Council Principal Researcher Fellowship from the Government of Australia. The authors have no conflicts of interest that are directly relevant to the content of this article.
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19. 20.
21.
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Meeting the Global Demand of Sports Safety
35. Cassas KJ, Cassettari-Wayhs A. Childhood and adolescent sports-related overuse injuries. Am Fam Physician 2006 Mar 15; 73 (6): 1014-22 36. Dollard MD, Pontell D, Hallivis R. Preconditioning principles for preventing sports injuries in adolescents and children. Clin Podiatr Med Surg 2006 Jan; 23 (1): 191-207 37. Leglise M. The protection of young people involved in highlevel sport. Strasbourg: Committee for the Development of Sports, Council of Europe, 1997 38. Ryan J. Little girls in pretty boxes: the making of and breaking of elite gymnasts and figure skaters. New York: Doubleday, 1995 39. Donnely P. Child labour, sport labour: applying child labour laws to sport. Int Rev Sociology Sport 1997; 32: 389-406 40. International Labour Organisation (ILO). C138 Minimum Age Convention, 1973 [online]. Available from URL: http://www.ilo.org/ilolex/english/convdisp1.htm [Accessed 2008 Jul 25] 41. David P. Human rights in youth sports. A critical review of children’s rights in competitive sports. New York: Routledge, 2004 42. Sport England, NSPCC. Strategy for safeguarding children and young people in sport [online]. Available from URL: http:// www.sportengland.org/child__protection__cpsu_strat_2006_ to2012_pdf.pdf [Accessed 2008 25 Jul] 43. Regalado SO. Latin players on the cheap: professional baseball recruitment in Latin America and the neo-colonist tradition. Indiana J Global Legal Stud 2000; 8: 9-20 44. Breton M, Villegas JL. Away games: the life and time of Latin ball. Albuquerque (NM): University of New Mexico Press, 1999 45. Guilianotti R. Built in by the two Valeras: the rise and fall of football culture and national identity in Uruguay. Cult Sport Soc 1999; 2: 134-54 46. United Nations. General Assembly. Resolution 58/5. Sports as a means to promote education, health, development, and peace. New York: United Nations, 2003 47. Guilianotti R, Robertson R. The globalization of football: a study in the glocalization of the ‘serious life’. Br J Sociology 2004; 55: 545-68 48. Timpka T, Ekstrand J, Svanstrom L. From sports injury prevention to safety promotion in sports. Sports Med 2006; 36 (9): 733-45 49. Finch C. A new framework for research leading to sports injury prevention. J Sci Med Sport 2006; 9 (1-2): 3-9 50. Eime R, Owen N, Finch C. Protective eyewear promotion: applying principles of behaviour change in the design of a squash injury prevention programme. Sports Med 2004; 34 (10): 629-38 51. Michener JA. Sports in America. New York: Random House, 1976 52. Dunning E. The dynamics of sports consumption. In: Sport matters: sociological studies of sport, violence, and civilization. London: Routledge, 1999: 106-29 53. Manzenreiter W, Horne J. Public policy, sports investments, and regional development initiatives in Japan. In: Nauright J, Schimmel KS, editors. The political economy of sports. New York: Palgrave MacMillan, 2005: 152-82
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54. Walsh AJ, Guilianotti R. This sporting mammon: a normative critique of the commodification of sport. J Philosophy Sport 2001; 28: 53-77 55. Yammine K. A policy for sports injury prevention in Lebanon [abstract]. Safety 2006: 8th World Conference on Injury Prevention and Safety Promotion; 2006 Apr 2-5; Durban 56. Bahr R, Krosshaug T. Understanding injury mechanisms: a key component of preventing injuries in sport. Br J Sports Med 2005; 39: 324-9 57. van Mechelen W. To count or not to count sports injuries? What is the question? Br J Sports Med 1998; 32: 297-8 58. Jackson S, Perkins F, Khandor E, et al. Integrated health promotion strategies: a contribution to tackling current and future heath challenges. Health Promot Int 2006; 21 Suppl. 1: 75-83 59. Allison L. Sport and Politics. In: Allison L, editor. The politics of sport. Manchester: Manchester University Press, 1986: 17-21 60. Re´gnier G, Sicard C, Goulet C. Economic impact of a regulation imposing full-face protectors on adult recreational hockey players. Int J Consumer Safety 1995; 2: 191-207 61. Oliver TR, Paul-Shaheen P. Translating ideas into actions: entrepreneurial leadership in state health care reforms. Health Polit Policy Law 1997; 22: 721-88 62. Morone JA. Enemies of the people: the moral dimensions to public health. Health Polit Policy Law 1997; 22: 993-1020 63. Young K. Violence, risk and liability in male sports culture. Sociology Sports J 1993; 10: 373-96 64. Boufous S, Finch C, Bauman A. Parental safety concerns: a barrier to sport and physical activity in children? Aust N Z J Public Health 2004; 28 (5): 482-6 65. Schneider A, Ingram H. Social construction of target populations: implications for politics and policy. Am Polit Sci Rev 1993; 87: 334-47 66. Van den Hove S. A rationale for science-policy interfaces. Futures 2007; 39: 807-26 67. Timpka T, Lindqvist K. Evidence based prevention of acute injuries during physical exercise in a WHO safe community. Br J Sports Med 2001 Feb; 35 (1): 20-7 68. Regnier G, Goulet C. The Quebec Sports Safety Board: a governmental agency dedicated to the prevention of sports and recreational injuries. Inj Prev 1995 Sep; 1 (3): 141-5 69. Oliver TR. The politics of public health policy. Annu Rev Public Health 2006; 27: 195-233 70. Grierson T, van Dijk MW, Dozois E, et al. Using the Internet to build community capacity for healthy public policy. Health Promot Pract 2006 Jan; 7 (1): 13-22 71. Irestig M, Hallberg N, Eriksson H, et al. Peer-to-peer computing in health-promoting voluntary organizations: a system design analysis. J Med Syst 2005 Oct; 29 (5): 425-40 72. Funtowicz S, Ravetz J. Science for the post-normal age. Futures 1993; 25 (7): 735-55 73. Kingdon JW. Agendas, alternatives, and public policies. Boston (MA): Little & Brown, 1984
Correspondence: Prof. Toomas Timpka, Section of Social Medicine and Public Health Sciences, Linko¨ping University, SE-581 83 Linko¨ping, Sweden. E-mail:
[email protected]
Sports Med 2008; 38 (10)
Sports Med 2008; 38 (10): 807-824 0112-1642/08/0010-0807/$48.00/0
CURRENT OPINION
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Physical Activity and Prevention of Type 2 Diabetes Mellitus Jason M.R. Gill1 and Ashley R. Cooper2 1 Institute of Diet, Exercise and Lifestyle (IDEAL), Faculty of Biomedical and Life Sciences, University of Glasgow, Glasgow, UK 2 Department of Exercise, Nutrition and Health Sciences, University of Bristol, Bristol, UK
Abstract
The worldwide prevalence of type 2 diabetes mellitus is increasing at a rapid rate, predominantly because of changes in environmental factors interacting with individual genetic susceptibility to the disease. Data from 20 longitudinal cohort studies present a consistent picture indicating that regular physical activity substantially reduces risk of type 2 diabetes. Adjustment for differences in body mass index between active and inactive groups attenuates the magnitude of risk reduction, but even after adjustment, a high level of physical activity is associated with a 20–30% reduction in diabetes risk. The data indicate that protection from diabetes can be conferred by a range of activities of moderate or vigorous intensity, and that regular light-intensity activity may also be sufficient, although the data for this are less consistent. The risk reduction associated with increased physical activity appears to be greatest in those at increased baseline risk of the disease, such as the obese, those with a positive family history and those with impaired glucose regulation. Data from six large-scale diabetes prevention intervention trials in adults with impaired glucose tolerance or at high risk of cardiovascular disease indicate that increasing moderate physical activity by approximately 150 minutes per week reduces risk of progression to diabetes, with this effect being greater if accompanied by weight loss. However, this level of activity did not prevent all diabetes, with 2–13% of participants per annum who underwent lifestyle intervention still developing the disease. Thus, while 150 minutes per week of moderate activity confers benefits, higher levels of activity may be necessary to maximize diabetes risk reduction in those at high baseline risk of the disease. In contrast, those at low baseline risk of type 2 diabetes, e.g. people with a very low body mass index and no family history of diabetes, will remain at low risk of developing diabetes whether they are active or not. Thus, the amount of physical activity required to confer low risk of diabetes differs according to an individual’s level of baseline risk. Consequently, a ‘one size fits all’ mass-population strategy may not provide the most appropriate approach when designing physical activity guidelines for the prevention of type 2 diabetes. Producing tailored guidelines with the specific aim of reducing risk of diabetes in high-risk populations may provide an alternative approach.
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It is estimated that 171 million people in the world currently have diabetes mellitus, and this number is expected to increase to 366 million by the year 2030,[1] with the majority of these cases being type 2 diabetes. This growing epidemic of type 2 diabetes is thought to be predominantly due to lifestyle factors, characterized by diminished physical activity, increased energy and fat intake, and increased obesity, interacting with genetic susceptibility, although the relative importance of each of these factors is unclear. Obesity is the most important independent modifiable predictor of type 2 diabetes. In prospective studies of predominantly White American adults, men and women with body mass indices (BMIs) of ‡35 kg/m2 had 42- and 93-fold increased risks of developing diabetes, compared with men with BMI <23 kg/m2 and women with BMI <22 kg/m2, respectively.[2,3] However, the degree of diabetes risk associated with obesity is likely to differ between populations. For example, Asian populations display increased risk factors for,[4] and develop,[5] type 2 diabetes at lower BMI values than White populations of European descent, a finding which may be due, in part, to the increased adiposity for a given BMI observed in many Asian compared with European populations.[6] It has therefore been proposed that lower BMI cut-points, within what is regarded as the ‘healthy weight’ range for White populations (e.g. 23 kg/m2), are required for public health action in these populations.[7] A major role of physical activity in the modulation of diabetes risk is through the prevention of obesity. However, physical activity influences diabetes risk both in the presence and absence of obesity, and this review investigates the influence of BMI on the magnitude of effect of physical activity for preventing type 2 diabetes. The amount of physical activity required to prevent obesity is, however, beyond the scope of this review; for more information on this topic, the interested reader is directed to the comprehensive review by Wareham and colleagues.[8] The American College of Sports Medicine (ACSM) and American Heart Association (AHA),[9] the American Diabetes Association[10] and the UK Chief Medical Officer[11] all recommend that adults participate in at least 150 ª 2008 Adis Data Information BV. All rights reserved.
Gill & Cooper
minutes of moderate-intensity physical activity (or at least 60–90 minutes of vigorous activity) per week to reduce risk of cardiovascular disease and type 2 diabetes. The most recent ACSM/AHA recommendation[9] provides a comprehensive guideline, updating the 1995 ACSM/Centers for Disease Control and Prevention recommendation that ‘‘every US adult should accumulate 30 minutes or more of moderate intensity physical activity on most, preferably all days of the week’’[12] by clarifying definitions of moderate-intensity activity, incorporating vigorous physical activity and muscle strengthening activities, and specifying that a combination of these activities is complementary in production of health benefits. However, this, like the other guidelines, has adopted a ‘one size fits all’ approach, and for physical activity and diabetes prevention, it is possible that one size does not fit all. The efficacy of physical activity in modulating diabetes risk could conceivably be influenced by factors that influence risk of the disease such as family history, sex, ethnicity, obesity status and degree of glucose tolerance/insulin resistance. Thus, to stimulate debate, we have reviewed the data from prospective cohort studies and controlled intervention trials to investigate whether there is evidence for differential physical activity guidelines for diabetes prevention in different populations. To identify articles we searched MEDLINE (1966 to September 2007) for papers published in English using the terms ‘physical activity’, ‘exercise’, ‘walking’, ‘sport’, ‘fitness’ or ‘lifestyle’, together with ‘diabetes’, ‘type 2 diabetes’, ‘Non insulin dependent diabetes mellitus’ or ‘NIDDM’. The reference lists of articles retrieved were also examined. Prospective cohort studies were included if incident diabetes was the outcome measure and the effect of physical activity was reported as the primary purpose of the study (i.e. excluding papers where diet and ‘lifestyle’ combinations were the focus). Diabetes prevention trials were included if they incorporated an intervention programme of at least 12 months’ duration with a physical activity component and the trial endpoint was development of type 2 diabetes. Sports Med 2008; 38 (10)
Physical Activity and Prevention of Diabetes
1. Prospective Cohort Studies A substantial number of prospective cohort studies have investigated the role of physical activity in the prevention of type 2 diabetes. For the current review, 20 studies were identified, representing 19 cohorts, and these are summarized in table I. Six studies included women only, eight included men only, with the remainder including both sexes. Two studies specifically recruited postmenopausal women.[13,14] The majority of participants were between 40 and 66 years old at recruitment (range 24–84 years), and were followed up after 4–16 years, thus being middleaged or older when diabetes was reported. Most participants were of White European descent (US, UK, Finland and Germany), and studies in Japanese-American,[15] Chinese[16] and Japanese[17] participants showed similar associations to those with White participants. In contrast, the San Antonio Heart Study[18] found no significant association between physical activity and diabetes risk in Mexican-American women, and similarly the Women’s Health Initiative found no significant association between diabetes risk and physical activity in African-American, Hispanic or Asian women.[13] Physical activity was assessed by self-reported questionnaires in all studies using a range of methodologies over time frames varying from 1 day to 1 year, although the majority reported weekly activity. The most common physical activity variables to be measured were frequency and estimated energy expenditure, and the dimensions of physical activity reported included vigorous, moderate and light activity, as well as physical activity accrued in walking, sport, stair climbing, and occupational and commuting activity. The large majority of studies were consistent in reporting an inverse association between physical activity and diabetes risk, with participants recording the highest levels of physical activity having an approximately one-third to one-half the risk of diabetes compared with the least physically active in age-adjusted analyses (figure 1a and 1c), although in addition to the two reports in women described above,[13,18] two studies in men[29,30] found no significant association between physical activity and diabetes risk, for reasons that are unclear. ª 2008 Adis Data Information BV. All rights reserved.
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Where physical activity level was categorized, most studies reported a dose-response relationship between amount of physical activity (either frequency or energy expenditure) and reduction in diabetes risk. In contrast, one report from the Nurses’ Health Study examined weekly frequency of vigorous exercise and risk of type 2 diabetes in women and found no graded response, with more than one bout of vigorous exercise per week appearing to confer maximum protection (33% lower risk of diabetes).[19] However, subsequent analyses from this cohort did report a graded relationship between both weekly hours of vigorous physical activity and weekly energy expenditure in activities including walking.[20] A threshold level of physical activity required to confer protection was described in only one study – the Kuopio Ischaemic Heart Disease Risk Factor Study. In this report, a threshold level of at least 40 minutes per week of activity at an intensity of at least 5.5 metabolic equivalents (METs) appeared to be required to confer protection from the development of type 2 diabetes, with activity of lower intensity not being protective, regardless of duration.[23] This is in contrast to other studies that reported that lower intensity activities such as walking significantly reduced diabetes risk,[20,24] and studies reporting that equivalent energy expenditures in low/moderate and vigorous activities conferred equivalent magnitudes of reduction.[25,28] The reasons for this discrepancy are unclear, but it should be noted that the Kuopio Ischaemic Heart Disease Risk Factor Study is the smallest of the studies reported, with only 897 participants and 46 incident cases of diabetes.[23] The influence of changing physical activity level on diabetes risk was investigated in the Nurses’ Health Study.[20] Relative to women who were sedentary (£2 MET-hours per week) at both baseline measures in 1986 and 1988, those who reported >10.4 MET-hours per week had a relative risk of diabetes of 0.59 (95% CI 0.46, 0.75). Those who were sedentary in 1986 but had increased activity by 1988 had a relative risk of 0.71 (95% CI 0.55, 0.93), indicating that adoption of physical activity confers reduced risk and strengthening the association between physical activity and risk of type 2 diabetes. Sports Med 2008; 38 (10)
Weekly EE in walking, stair climbing and sports (<500, 500–999, 1000–1499, 1500–1999, 2000–2499, 2500–2999, 3000–3499, ‡3500 kcal/wk)
Weekly vigorous exercise ‘enough to work up a sweat’ (0, 1, 2–4, ‡5 times/wk)
Retrospective 12-mo leisure-time history; frequency, duration and intensity (MET) of leisure time activities; MVPA defined as ‡5.5 MET
5990 men, 39–55þ y; 98 524 person-years of follow-up; 202 cases
21 271 men, 40–84 y; 5 y follow-up; 285 cases
897 men, 42–60 y; 4 y follow-up; 46 cases
37 878 women, mean age 55 y; 6.9 y follow-up; 1361 cases
University of Pennsylvania alumni[21] (US)
Physicians Health Study[22] (US)
Kuopio Ischaemic Heart Disease Risk Factor Study[23] (Finland)
Women’s Health Study[24] (US)
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Weekly EE in recreational activities; (0–199, 200–599, 600–1499, ‡1500 kcal/wk); weekly time spent walking (none, <1 h, 1–1.5 h, 2–3 h, ‡4 h/wk).
Weekly EE in physical activity (quintiles: 0–2, 2.1–4.6, 4.7–10.4, 10.5–21.7, ‡21.8 MET-h/wk); weekly EE in walking among those who did no vigorous (‡6 MET) physical activity; walking pace (easy/normal/brisk)
70 102 women, 40–65y; 8 y follow-up; 1419 cases
Nurses’ Health Study[20] (US)
Continued next page
Increasing weekly physical activity EE was associated with significantly reduced risk of diabetes (HR = 0.91, 0.86 and 0.82 for quartiles of increasing activity; p = 0.01, relative to the least active quartile). Meeting physical activity guidelines (>1000 kcal/wk) was associated with borderline significant reduction in diabetes risk (HR = 0.91 [0.80, 1.03]). Walking was associated with reduced risk of diabetes (HR = 0.95, 0.87, 0.66, 0.89, for quintiles of increasing walking; p = 0.004, relative to none). In 1877 women who walked ‡7 h/wk results were identical to those who walked ‡4 h/wk
Men who exercised at ‡5.5 MET for >40 min/wk had a significantly lower risk of diabetes compared with those who did not participate in moderate activities or who participated for shorter duration (OR = 0.44 [0.22, 0.88]. Activities <5.5 MET were not protective, regardless of duration
Vigorous exercise ‡1 time/wk was associated with lower risk compared with those who did not exercise weekly (RR = 0.71 [0.56, 0.91]; p = 0.006). Increasing frequency of exercise was associated with lower risk (RR = 0.78 [0.68, 0.71]; p = 0.009) relative to none
For all activities each 500 kcal increment in total weekly EE was associated with a 6% decrease in the age-adjusted risk for the development of diabetes. EE of ‡3500 kcal/wk was associated with »50% reduction in risk. Age-adjusted risk (relative to ‘none’) decreased significantly with increasing vigorous sport (RR = 0.90 [moderate], 0.69 [vigorous], 0.65 [moderate and vigorous]; p = 0.05). A weak inverse association (relative to ‘<5’) was seen with flights of stairs climbed (RR = 0.78 [5–14 flights], 0.75 [‡15]; p = 0.07). No association with city blocks walked
Highest quartile of weekly EE in physical activity was associated with significantly lower risk of diabetes compared with the lowest quartile (RR = 0.74 [0.62, 0.89]; p = 0.002). A similar risk reduction was seen for weekly EE in walking in women who did no vigorous activity (RR = 0.74 [0.59, 0.93]; p = 0.01). Faster than usual walking pace was associated with decreased risk; brisk vs easy (RR = 0.59 [0.47, 0.73])
Main findingsa Vigorous exercise ‡1 time/wk was associated with lower risk of diabetes compared with those who did not exercise weekly (RR = 0.84 [0.74, 0.93]; p = 0.002). No clear dose-response gradient according to frequency of exercise
Nurses’ Health Study[19] (US)
Physical activity assessments
Subjects
87 253 women, aged 34–59 y at baseline; 8 y follow-up; 1303 new cases of type 2 diabetes
Study (country) Weekly vigorous exercise ‘enough to work up a sweat’ (0, 1, 2, 3, 4, >4 times/wk)
Table I. Prospective cohort studies of physical activity and risk for developing type 2 diabetes mellitus
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Sports Med 2008; 38 (10)
Score based on duration and intensity of activities in 24 h (quintiles: 24.1–29.0, 29.1–30.7, 30.8–33.2, 33.3–36.2, 36.3–65.5)
6815 men, 45–68 y; 6 y follow-up
70 658 women, 40–70 y; 4.6 y follow-up; 1973 cases
6898 men, 7392 women, 35–64 y; 12 y follow-up; 373 cases
2017 men, 2352 women, 45–64 y; 9.4 y follow-up; 120 cases
2924 men, 35–59 y; 7 y follow-up; 168 cases
34 257 postmenopausal women, 55–69 y; 12 y follow-up
Honolulu Heart Program[15] (JapaneseAmericans)
Shanghai Women’s Health Study[16] (China)
Eastern and SouthWestern Finnish adults[26]
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Eastern and SouthWestern Finnish adults[27]
Japanese male office workers[17]
Iowa Women’s Health Study[14] (US)
Single question to assess any regular physical activity (yes/no), then if so frequency of moderate and vigorous physical activity (>6 MET) [rare or never, 1 time/wk or few times/mo, 2–4 times/wk, >4 times/wk]; responses combined as a physical activity index (low/medium/high)
Daily EE in 20 selected activities (<33.1, 33.1–36.7, 36.8–40.3, ‡40.4 kcal/kg/day)
Combinations of commuting, occupational and leisure-time physical activity merged to give low, moderate and high physical activity categories
Weekly LTPA (low [inactive]/moderate [moderate activity >4 h/wk]/high [vigorous activity >3 h/wk]); occupational physical activity (OPA) [light/moderate/active]; commuting (motorized/walking or cycling <30 min/day walking or cycling ‡30 min/day)
EE in regular (‡1 time/wk) exercise/sport (LTPA) during previous 5 y (MET-h/day/y); EE in DPA; walking, stair climbing etc.; CPA (bus or vehicle/walking or cycling 1–29 min/day walking or cycling ‡30 min/day); EE in OPA (high/medium/low)
Frequency and intensity of recreational activities (none, occasional, light, moderate, moderately vigorous, vigorous)
7577 men, 40–59 y; 12.8 y follow-up; 194 cases
British Regional Heart Study[25] (UK)
Physical activity assessments
Subjects
Study (country)
Table I. Contd
Continued next page
Regular physical activity was associated with significantly lower risk of diabetes (RR = 0.86 [0.78, 0.95]). Moderate and vigorous physical activity >4 times/wk were also associated with lower diabetes risk (RR = 0.73 [0.62, 0.85] and 0.64 [0.41, 1.01], respectively compared with rare or never. In 26 124 women who reported no vigorous activity, moderate activity was still associated negatively with diabetes. Physical activity index was associated negatively and strongly with diabetes incidence (RR = 0.79 [0.70, 0.90]. Association was similar across three strata of BMI
Increasing daily EE was significantly associated with reduced risk of diabetes (RR = 0.40 [0.27, 0.60]; highest vs lowest quartile)
Increasing weekly physical activity was significantly associated with lower diabetes risk (RR = 0.43 [0.25, 0.74]; high physical activity relative to low). Data shown for men and women combined
Increasing the levels of weekly LTPA was associated with lower risk of diabetes in multivariate adjustment until BMI was included (HR = 0.84 [0.57, 1.25]). OPA was significantly inversely associated with diabetes risk (HR = 0.74 [0.57, 0.95]; active vs light). Active commuting was significantly inversely associated with diabetes risk (HR = 0.64 [0.45, 0.92]; ‡30 min/day vs none). Data shown for men and women combined
Highest EE in physical activity (>1.99 MET-h/day/y) was associated with significantly lower risk of diabetes compared with none (RR = 0.83 [0.7, 0.97]). DPA was associated with moderately lower risk (0.86 [0.73, 0.99]; highest [>15.2 MET] vs lowest) as was CPA (0.67 [0.55, 0.82]; >5.5 MET vs lowest). OPA was not associated with diabetes risk (0.81 [0.48, 1.39]; high vs low)
Increasing physical activity score was associated with significantly reduced risk of diabetes compared with lowest quartile (RR = 0.58 [0.42, 0.78]; highest vs lower 4 quintiles)
Moderate levels of physical activity conferred significantly reduced risk of diabetes relative to inactive men (RR = 0.4 [0.2, 0.7]). No further decrease for vigorous intensity activity
Main findingsa
Physical Activity and Prevention of Diabetes 811
Sports Med 2008; 38 (10)
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891 men, 973 women, 35–63 y; 10 y follow-up; 118 cases
3052 men, 3114 women, 35–74 y; 7.6 y follow-up; 128 cases (men), 85 cases (women)
4069 men, 4034 women, 24–74 y; 7.4 y follow-up; 145 cases (men), 82 cases (women)
37 918 men, 40–75 y; 10 y follow-up; 1058 cases
6013 men, 35–60 y; 10 y follow-up; 444 cases
87 907 postmenopausal women; 5.1 y follow-up; 2271 cases
North-Eastern Finnish Adults[28]
MONICA Augsburg Cohort Study[29] (Germany)
MONICA/KORA Augsburg Cohort Study[30] (Germany)
Health Professional’s Follow-up Study[31] (US)
Osaka Health Survey (Japan)[32]
Women’s Health Initiative[13] (Caucasian, African American, Hispanic, Asian)
Values are multivariate adjusted (including BMI) risk [95% confidence intervals] unless otherwise stated.
Weekly EE from walking (0, 0.5–2.5, 2.6–5.0, 5.1–10.0, >10.0 MET-h/wk) and total physical activity (0–2.3, 2.3–7.4, 7.5–13.9, 14.0–23.4, >23.4 MET-h/wk)
Weekday and weekend LTPA (sedentary/moderate/vigorous)
Among Caucasian women, weekly EE from walking (HR = 0.74 [0.62, 0.89], highest vs lowest quintile) and total physical activity (HR = 0.67 [0.56, 0.81]) were significantly associated with lower diabetes risk. In fully adjusted analyses there was no significant association between physical activity and diabetes risk for African-American, Hispanic or Asian women
Physical activity ‡1 time/wk was associated with lower risk of diabetes compared with those who did not exercise weekly (RR = 0.75 [0.61, 0.93]). Vigorous activity 1/wk at weekends was associated with lower risk of diabetes (RR = 0.55 [0.35, 0.88] compared with sedentary men
Inverse association with diabetes risk across increasing quintiles of weekly EE (RR = 0.62 [0.50, 0.76] highest relative to lowest quintile). Time spent watching TV was significantly associated with higher risk for diabetes (RR = 2.31 [1.17, 4.56] highest relative to lowest)
Weekly sport ‡1 h/wk was associated with lower risk of diabetes in women (HR = 0.24 [0.06, 0.98]) but not men (HR = 0.83 [0.50, 1.36]). In subgroup analyses the protective effect of moderate to high physical activity was significant in women with a BMI <30 (HR = 0.24 [0.09, 0.65]) but not in women with a BMI ‡30 (HR = 0.97 [0.44, 2.11])
Weekly sport (none/low [<1 h/wk]/moderate/high [regular sport ‡1 h/wk])
Weekly EE in LTPA (0–5.9, 6.0–13.7, 13.8–24.2, 24.3–40.8, ‡40.9 MET-h/wk); weekly hours watching TV (0–1, 2–10, 11–20, 21–40, >40)
Inactivity during leisure time was a significant predictor of diabetes in women only (HR = 1.80 [1.04, 3.14])
Weekly sport (none/low [<1 h/wk]/moderate/high [regular sport ‡1 h/wk])
High weekly EE (low relative to high category) was associated with significant reduction in risk of diabetes for women (age-adjusted RR = 2.64 [1.28, 5.44]) but not men (RR = 1.54 [0.83, 2.84]). Vigorous activity ‡1 time/wk (reference) vs <1 time/wk was significantly associated with lower risk for women (RR = 2.23; p = 0.043) but not for men (RR = 1.63; p = 0.082)
In men, LTPA ‡1 time/week was associated with significantly lower diabetes risk (RR = 0.41 [0.18, 0.93]) compared with <1 time/wk. In women there was no significant association (RR = 1.43 [0.85, 2.41])
Main findingsa
BMI = body mass index; CPA = commuting physical activity; DPA = daily physical activity; EE = energy expenditure; HR = hazard ratio; LTPA = leisure-time physical activity; MET = metabolic equivalent (1 kcal/kg/h); MVPA = moderate to vigorous physical activity; OPA = occupational physical activity; OR = odds ratio; RR = relative risk.
a
Weekly ‘planned LTPA’
353 men, 491 women, 25–64 y; 8 y follow-up; 57 cases
San Antonio Heart Study[18] (MexicanAmerican) Weekly EE in LTPA. Men: low (0–1100), moderate (1101–1900), high (>1900) kcal/wk; women: low (0–900), moderate (901–1500), high (>1500) kcal/wk. Vigorous activity (‡6 MET) ‡1 time/wk or <1 time/wk
Physical activity assessments
Subjects
Study (country)
Table I. Contd
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a
813
Men age adjusted
b
1
1
0.8
0.8
0.6 Relative risk of type 2 diabetes
Men multivariate adjusted (including BMI adjusted)
0.4 0.2
0.6 Manson et al. (1992) Burchfiel et al. (1995) Hu et al. (2003) Nakanishi et al. (2004) Meisinger et al. (2005) Hu et al. (2001) Okada et al. (2000)
0.4 0.2
0 c
0 Women age adjusted
d
Women multivariate adjusted (including BMI adjusted)
1
1
0.8
0.8
0.6
0.6
0.4 0.2 0
Manson et al. (1992) Burchfiel et al. (1995) Hu et al. (2003) Nakanishi et al. (2004) Meisinger et al. (2005) Hu et al. (2001) Okada et al. (2000)
0.4
Manson et al. (1991) Hu et al. (1999) Weinstein et al. (2004) Hu et al. (2003) Folsom et al. (2000) Mesinger et al. (2005)
Lowest (reference)
0.2
Manson et al. (1991) Hu et al. (1999) Weinstein et al. (2004) Hu et al. (2003) Folsom et al. (2000) Mesinger et al. (2005)
0 Highest
Lowest (reference) Physical activity category
Highest
Fig. 1. Relative risks of developing type 2 diabetes mellitus for men (a and b) and women (c and d) between the lowest and highest physical activity categories in prospective cohort studies. (a) and (c) show age-adjusted data and panels (b) and (d) show multivariate-adjusted data, including adjustment for body mass index (BMI).[14,15,17,19,20,22,24,26,30-32]
Obesity is the major independent predictor of type 2 diabetes, and adjustment for BMI or other indicators of adiposity markedly attenuated the association between physical activity and risk for diabetes in most of the studies in which these data were reported, an effect that was more pronounced in women than in men (figure 1b and 1d). The magnitude of reduction in relative risk of diabetes as a result of adjustment for BMI was in the order of 20% for the highest versus lowest physical activity groups: for example, in the Nurses’ Health Study,[20] age-adjusted relative risk was attenuated from 0.54 to 0.74 with adjustment for BMI. Interestingly, in the Kuopio Ischaemic Heart Disease Study,[23] associations between lower intensity activity and diabetes risk were markedly attenuated by adjustment for BMI, although associations ª 2008 Adis Data Information BV. All rights reserved.
between higher intensity activity and diabetes were not. The authors suggested that effects of lower intensity physical activity may be mediated by changes in BMI but higher intensity activities may have a more direct metabolic impact. Similarly, in Japanese men,[17] associations between light physical activity and diabetes risk were severely attenuated by adjustment for potential confounders including BMI, with authors suggesting that daily life activities may indirectly reduce the risk of diabetes through decreased bodyweight. Taken together, the evidence suggests that at least some of the diabetes risk reduction observed in physically active individuals is mediated through effects on bodyweight, although in most cases, the associations between physical activity level and diabetes risk remained statistically significant after adjustment. It should Sports Med 2008; 38 (10)
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be noted, however, that BMI provides a relatively crude marker of adiposity, and that adjustment for more accurate indices of adiposity (if these were available) may have further attenuated the effects of physical activity per se, as opposed to physical activity-mediated effects on body composition, on diabetes risk. The protective effect of physical activity in reducing the risk of diabetes may be greater in the obese or other persons at increased risk of diabetes. In University of Pennsylvania alumni, the protective effect of physical activity was strongest in men at highest risk of diabetes, defined as those with a high BMI, a history of hypertension, or the offspring of diabetic parents.[21] Similarly, in the Kuopio Ischaemic Heart Disease Risk Factor study, participation in at least 40 minutes of physical activity per week at ‡5.5 MET elicited a 3.5-fold greater reduction in risk of type 2 diabetes in men at high risk of type 2 diabetes (i.e. with high BMI, parental history of diabetes and hypertension) compared with men at low diabetes risk.[23] In the Physicians’ Health Study, participation in vigorous physical activity reduced the risk of type 2 diabetes to the greatest extent in men with high BMI[22] (figure 2). However, in other reports, physical activity reduced diabetes risk across the BMI range. Studies where data were stratified by BMI showed a
Incidence of type 2 diabetes (per 100 000 person-years)
800 700
Vigorous exercise < once per week Vigorous exercise ≥ once per week
600 500 400 300 200 100 0 1 (low)
2
3
4 (high)
BMI quartile Fig. 2. Effect of participation in vigorous physical activity on incidence of type 2 diabetes mellitus in the Physicians’ Health Study according to quartiles of body mass index (BMI). BMI quartiles were as follows: 1: <23 kg/m2, 2: 23–24.4 kg/m2, 3: 24.5–26.4 kg/m2, 4: >26.4 kg/m2 (modified from Manson et al.,[22] with permission. Copyright ª 1992, American Medical Association. All rights reserved).
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graded (but relatively weak) protective effect of moderate-to-vigorous physical activity independent of BMI,[24,27,33] and in the Nurses’ Health Study, risk reduction with increasing vigorous exercise was observed in both obese and non-obese women.[19] One important point to consider is the concept of relative versus absolute disease risk. The relative diabetes risk reduction associated with increasing physical activity has been reported to be most pronounced in individuals at high risk (e.g. high BMI, family history of diabetes, other risk factors) in some[21,23] but not all[17] studies. However, it is important to emphasize that even when relative risk reductions between high- and low-risk groups are similar, the absolute risk reduction is greater in the high-risk group. Thus, the weight of evidence suggests that the beneficial effects of physical activity in preventing type 2 diabetes are greatest in those at highest risk of the disease. In women, both light/moderate and vigorous physical activity have been shown to confer lower risk of type 2 diabetes. In the Nurses’ Health Study[19] undertaking at least one bout of vigorous exercise per week conferred an approximately 33% reduction in risk in women, compared with no weekly exercise, with further exercise bouts providing no additional benefit. In a subsequent report from this cohort,[20] the highest category of weekly physical activity energy expenditure was associated with 46% reduction in diabetes risk compared with the lowest category. In this analysis, diabetes risk was reduced with participation in non-vigorous as well as vigorous activities. Faster than usual walking pace was associated with a 14–41% lower risk of diabetes, and equivalent energy expenditures from walking and vigorous activity resulted in comparable magnitudes of reduction.[20] Other studies have also reported reduced risk of diabetes in women associated with light/moderate intensity activities. In the Iowa Women’s Health Study[14] women who reported no vigorous activity but who were active more than four times per week had a diabetes risk 43% lower than those who rarely exercised, and in the Women’s Health Study[30] women who walked for at least 1 hour per week had significantly lower risk than those who did not. Women who walked Sports Med 2008; 38 (10)
Physical Activity and Prevention of Diabetes
at least 7 hours per week had no greater risk reduction than those walking at least 4 hours per week, and the association between time spent walking and diabetes risk was not influenced by BMI. Women who met the physical activity guideline of at least 1000 kcal/week also had a lower risk of diabetes, which just failed to remain statistically significant after adjustment for confounders including BMI. These data strongly support the utility of either light/moderate or vigorous activity in the prevention of diabetes in women. In men, vigorous physical activity is associated with a ~40–50% reduction in risk of diabetes. Moderate physical activity and energy expenditure in physical activity are also associated with reduced risk of diabetes in most studies, with the exception of the Kuopio Ischaemic Heart Disease Risk Factor study.[23] These associations were markedly weakened after adjustment for possible confounders. Walking (or cycling) for at least 30 minutes per day was associated with reduced risk in Finnish men,[26] but not in other populations.[17,21] In addition, high levels of sedentary behaviour (TV watching) have been associated with increased risk of diabetes in one study.[31] Studies involving both men and women showed similar associations to single-sex studies, with increasing physical activity independently and significantly associated with reduced risk of type 2 diabetes. Where men and women were compared independently, associations were stronger for women than for men,[28-30] with the exception of the San Antonio Heart Study,[18] where data in Mexican-American men and women indicated that the protective effect of leisure-time physical activity may be seen in men only. In summary, longitudinal cohort studies present a consistent picture of the protective effect of physical activity for the development of type 2 diabetes, with regular physical activity conferring a reduction in risk of 20–30% after adjustment for confounding factors including age, health status including family history of diabetes and presence of other risk factors, and BMI. Protection can be conferred by a range of activities of moderate or vigorous intensity, and regular, light-intensity activity may also be sufficient, although the data are less consistent. The data suggest that the proª 2008 Adis Data Information BV. All rights reserved.
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tective effect of physical activity may be greater in women than in men in age-adjusted analyses, but that adjustment for BMI causes more substantial attenuation of the association in women (figure 1), and that the risk reduction associated with increased physical activity appears to be greater in those at increased baseline risk of the disease. 2. The Diabetes Prevention Trials In addition to the epidemiological data, over recent years there have been a number of controlled clinical trials,[34-39] many with ‘gold-standard’ randomization on an individual basis[36,39] demonstrating that lifestyle intervention, including increasing physical activity, reduces risk of developing diabetes in men and women with impaired glucose tolerance (IGT)[34-38] or at high risk for coronary heart disease (CHD).[39] These trials are shown in table II. Lifestyle interventions that incorporated a moderate-intensity physical activity component reduced the incidence of diabetes by 28–63% in subjects with IGT[34,38] and by 18% in normoglycaemic non-smokers at high risk of CHD,[39] although an unexplained increase in diabetes incidence was seen in normoglycaemic smokers at high risk for CHD.[39] Greater risk reductions were generally seen in interventions that induced weight loss.[34,36,37] However, in the Indian Diabetes Prevention Programme,[38] a 28.5% reduction in diabetes incidence was achieved without weight loss or reduction in waist circumference and in the exercise intervention arm of the Da Qing IGT and Diabetes Study,[35] a 46% reduction in diabetes incidence was achieved without weight loss in the participants who remained diabetes-free at follow-up. It is difficult to disentangle the separate effects of increased physical activity per se versus weight loss in reducing diabetes risk. In the Finnish Diabetes Prevention Study,[40] increases in total moderate-to-vigorous (‡3.5 MET) and low-intensity (<3.5 MET) leisuretime physical activity, and walking over the course of the intervention all predicted reduced incidence of diabetes in a dose-dependent manner, independently of changes in diet and BMI. The tertile with greatest increase in total physical Sports Med 2008; 38 (10)
Subjects
181 Swedish men with IGT aged 47–49 y with BMI 26.6 – 3.1 kg/m2 on entry in the intervention group and 79 Swedish men with IGT aged 47–49 y with BMI 26.7 – 4.0 kg/m2 on entry in the control group. Group allocation was not randomized. 14.9% of the intervention group and 17.7% of the control group were taking antihypertensive medication at baseline
530 Chinese adults (283 men, 247 women) with IGT randomly assigned according to clinic attended to control (n = 133, age 46.5 – 9.3 y, BMI 26.2 – 3.9 kg/m2), exercise (n = 141, age 44.2 – 8.7 y, BMI 25.4 – 3.7 kg/m2), diet (n = 130, age 44.7 – 9.4 y, BMI 25.3 – 3.8 kg/m2) or diet plus exercise (n = 126, age 44.4 – 9.2 y, BMI 26.3 – 3.9 kg/m2) groups
522 (172 men, 350 women) Finnish adults with IGT randomly assigned to control (n = 265, age 55 – 7 y, BMI 31.3 – 4.6 kg/m2) or intervention (n = 257, age 55 – 7 y, BMI 31.0 – 4.5 kg/m2) groups
Study
Malmo¨ feasibility study[34]
Da Qing IGT and Diabetes Study[35]
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Finnish Diabetes Prevention Study[36] Mean follow-up 3.2
6
6
Duration (y)
Intervention goals: reduce body mass by ‡5%, increase moderate exercise by ‡30 min/d, reduce total fat intake to £30%, reduce saturated fat intake to £10%, increase fibre intake to ‡15 g per 1000 kcal
Increase leisure-time exercise by at least 1 unit/d, where 1 unit 30 min of mild exercise (e.g. slow walking) or 20 min of moderate exercise (e.g. brisk walking) or 10 min of strenuous exercise (e.g. slow running or climbing stairs) or 5 min of very strenuous exercise (e.g. jumping rope, basketball)
60 min of various activities (callisthenics, walking-jogging, soccer and badminton playing) twice per wk. ‘‘More intense exercise was not performed for a longer duration except very late in training period’’
Exercise intervention
Table II. Major diabetes prevention trials (published in English) incorporating a physical activity intervention
Continued next page
Incidence of diabetes was 78 cases per 1000 person-years in the control group and 32 cases per 1000 person-years in the intervention group. Cumulative incidence of diabetes was 58% lower in the intervention group than the control group (63% lower in men and 54% lower in women). In the intervention group, among subjects who lost <5% of body mass, subjects who increased exercise by >4 h/wk had an odds ratio for diabetes of 0.3 (95% CI 0.1, 0.7) compared with those who did not achieve this exercise target after adjusting for baseline BMI
Mean cumulative incidence of diabetes over follow-up was 65.9% for control clinics, 44.2% for exercise clinics, 47.1% for diet clinics and 44.6% for diet plus exercise clinics. Thus, exercise, diet, and diet plus exercise reduced diabetes incidence by 46%, 31% and 42% respectively, relative to control. The intervention effects did not differ between lean and overweight subgroups. Actual increase in exercise was »0.6 units/d in the exercise group and »0.8 units/d in the diet plus exercise group
Incidence of diabetes at follow-up 28.4% in the control group and 10.6% in the intervention group. Relative risk of diabetes in the intervention compared with control group was 0.37 (95% CI 0.20, 0.68)
Main findings
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531 Asian Indian adults with IGT (421 men, 110 women) randomized to control (n = 136, age 45.2 – 5.7 y, BMI 26.3 – 3.7 kg/m2), lifestyle (n = 133, age 46.1 – 5.7 y, BMI 25.7 – 3.7 kg/m2), metformin (n = 133, age 45.9 – 5.9 y, BMI 25.6 – 3.7 kg/m2) and lifestyle plus metformin (n = 129, age 46.3 – 5.7 y, BMI 25.6 – 3.3 kg/m2) groups
11 827 men without diabetes or IGT at high risk for CHD, randomized into usual care (n = 5893) or special intervention (n = 5934) groups
Indian Diabetes Prevention Programme[38]
MRFIT[39]
Special intervention: nutritional counselling to reduce saturated fat and dietary cholesterol and increase polyunsaturated fat intake; in men at ‡115% of desirable weight, reductions in energy intake and increases in moderate physical activity recommended; in smokers, behavioural intervention programme to facilitate cessation; elevated blood pressure treated pharmacologically if target not achieved by weight loss and restriction of salt intake
In non-smokers, incidence of diabetes was 18% lower in the special intervention group than the usual care group (10.0% vs 12.0%; p = 0.03), but in smokers, incidence of diabetes was 26% higher in the special intervention group than the usual care group (12.4% vs 10.1%; p = 0.001). These findings are based on a post hoc analysis of the data. The MRFIT study was not specifically designed to address this issue
Cumulative incidences of diabetes at year 3 were 55.0%, 39.3%, 40.5% and 39.5% in the control, lifestyle, metformin and lifestyle plus metformin intervention groups, respectively. Incidence of diabetes in the lifestyle group was 28.5% lower than the control group. Subjects in the lifestyle intervention group showed a small (<1 kg), but statistically significant, increase in body mass at 24 mo. Small (<1 kg) but significant increases in body mass were observed at 12, 24 and 30/36 mo in the control group. Waist circumference did not change over the intervention in any group
Incidence of diabetes was 11.0, 7.8 and 4.8 cases per 100 person-years for placebo, metformin and lifestyle intervention groups, respectively. Incidence of diabetes in the lifestyle group was 58% lower than the placebo group and 39% lower than the metformin group. Effects of lifestyle intervention were similar in men and women, across ethnic groups and throughout the BMI and age range. Subjects in the intervention group increased physical activity by »8 MET-h/wk and lost 5.6 kg over the intervention (c.f. 0.1 kg loss of body mass in the placebo and 2.1 kg in the metformin group)
Main findings
BMI = body mass index; CHD = coronary heart disease; IGT = impaired glucose tolerance; MRFIT = Multiple Risk Factor Intervention Trial.
6
Lifestyle intervention: increase walking by ‡30 min/d if sedentary or engaged in light physical activity at baseline. Maintain activity if walking or cycling >30 min/d or involved in physical labour at baseline
Lifestyle intervention: reduce body mass by ‡7%; increase moderate intensity physical activity by ‡150 min/ wk
Mean follow-up 2.8
3
Exercise intervention
Duration (y)
Subjects
3234 US adults with IGT (32.3% men, 67.7% women, 54.7% White, 19.9% AfricanAmerican, 15.7% Hispanic, 5.3% American-Indian, 4.4% Asian) randomly assigned to placebo (n = 1082, age 50.3 – 10.4 y, BMI 34.2 – 6.7 kg/m2), metformin (n = 1073, age 50.9 – 10.3 y, BMI 33.9 – 6.6 kg/m2) or lifestyle (n = 1079, age 50.6 – 11.3 y, BMI 33.9 – 6.8 kg/m2) groups
Study
US Diabetes Prevention Program[37]
Table II. Contd
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activity (þ1.8 to þ19 hours per week) had a relative risk of diabetes incidence of 0.34 (95% CI 0.19, 0.62) compared with the reference tertile (who decreased activity).[40] Dose-response relationships for reduced risk of diabetes for increases in low and moderate-to-vigorous physical activity were similar.[40] In contrast, data from the US Diabetes Prevention Program suggested that the reduction in diabetes risk elicited by the lifestyle intervention was largely attributable to weight loss, with changes in physical activity not making a significant contribution to diabetes risk.[41] It is, however, important to remember that while bodyweight was measured objectively in these trials, physical activity was determined using subjective questionnaires, which provide limited reliability, validity and sensitivity compared with objective activity measures.[42] Poor measurement of a variable introduces a regression dilution bias, which diminishes the apparent effect of the variable on an outcome. Thus, the relative importance of increasing physical activity compared with losing weight in reducing diabetes risk may have been underestimated in these analyses. Therefore, while more data are needed before firm conclusions can be made, the weight of available evidence from the diabetes prevention trials suggests, in agreement with the epidemiological data, that changes in both physical activity and bodyweight influence risk of diabetes. Thus, when formulating guidelines to reduce the risk of diabetes, it is important to consider physical activity and adiposity in tandem; physical activity guidelines for prevention of diabetes should also take into consideration levels of physical activity needed to achieve and maintain a healthy bodyweight. 3. How Much Activity Do You Need To Do? How Little Can You Get Away With? It is difficult to provide a straightforward answer to these questions, as the amount of physical activity needed to prevent diabetes is likely to differ in different population groups. Evidence from prospective cohort studies suggests that those at the highest risk of developing diabetes are likely to experience the greatest risk reductions from becoming more active, but the absolute diabetes ª 2008 Adis Data Information BV. All rights reserved.
risk of an active person with a high-risk background is still likely to be higher than the risk of someone from a low-risk background, whether they are active or not. Furthermore, while it is possible to make broad qualitative judgments about physical activity and diabetes risk from the present epidemiological data (e.g. risk reduction increases with increasing volume of activity, highrisk groups benefit more), it is difficult to determine a precise quantitative dose-response relationship for physical activity and diabetes risk from the available data. All of the physical activity data from the cohort studies have been obtained by questionnaires, which provide limited reliability, validity and sensitivity.[42] In particular, sensitivity of questionnaires to detect vigorous activities is rather better than their sensitivity to detect routine low-intensity activities;[43] thus, questionnaire-based methods are likely to underestimate the importance of light and moderate activities in modulating diabetes risk. Use of more objective measures of physical activity, such as accelerometry and heart rate monitoring in physical activity epidemiology is needed to resolve this issue. However, it is important to note that the imprecision of questionnaire-based physical activity measurements would act to attenuate the apparent effect of physical activity on diabetes risk, thus the actual beneficial effects of physical activity may be larger than the present evidence suggests. Notwithstanding these limitations, data from the majority of studies indicate that any increase in physical activity over and above the activity level of the least active group appears to confer a numerical reduction in the relative risk of type 2 diabetes, although the difference in risk between the least active and next least active group is not always statistically significant. Thus, there does not appear to be an obvious threshold of physical activity needed before a benefit becomes apparent. The clinical trials investigating the effects of lifestyle intervention on diabetes incidence were not undertaken on randomly selected members of the general population. Indeed, given the low conversion rate to diabetes in individuals not previously identified as being at high risk of diabetes, such trials would be unfeasible. Sports Med 2008; 38 (10)
Physical Activity and Prevention of Diabetes
Relative risk of type 2 diabetes
Individuals recruited to the diabetes prevention trials were at high risk of developing type 2 diabetes, with conversion rates to diabetes of 3–18% per annum in the control/usual care intervention arms of these trials.[34-39] Thus, estimates of the physical activity doses needed to prevent or delay diabetes derived from data in this group are likely to be higher than for those in the population at lower absolute risk for diabetes. This is supported by epidemiological data which suggest that both the magnitude of potential benefit of increased physical activity and the dose of physical activity required to elicit this benefit are greater in adults with IGT than in those who are normoglycaemic[27] (figure 3). Taken together, the intervention trials indicate that increasing moderate physical activity by approximately 150 minutes per week reduces risk of progression to diabetes, with this effect being greater if accompanied by weight loss. However, while the interventions substantially reduced risk of diabetes compared with controls, they did not prevent all diabetes, with 1.7–13.1% of subjects per year in the lifestyle intervention groups still developing the disease.[34-39] There are no data available to determine whether increasing physical activity levels beyond the level prescribed in the interventions would have induced further reductions in diabetes incidence. It is therefore not possible at this stage to determine the optimal level of physical activity for diabetes prevention in high-risk groups.
16 14 12
Low physical activity Moderate physical activity High physical activity
10 8 6 4 2 0 Normoglycaemic
Impaired glucose regulation
Fig. 3. Relative risk of type 2 diabetes mellitus for Finnish adults with normoglycaemia or impaired glucose regulation according to physical activity level (modified from Hu et al.,[27] with permission. Copyright ª 2004, American Medical Association. All rights reserved).
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Higher activity doses than those used in these trials may confer additional protection. At the other extreme, an individual with a BMI of 20 kg/m2, who is of European ethnic origin, is normoglycaemic and has no family history of diabetes, has a low absolute risk of developing diabetes whether they are active or not (see figure 2). Therefore, it is probably unnecessary to recommend such individuals the same physical activity dose as higher risk groups if the sole aim is to prevent diabetes. Between the very lean low-risk person and the high-risk obese individual with IGT, there is a continuum of diabetes risk, with a number of identifiable groups towards the higher end of the diabetes risk spectrum. For example, adults with the metabolic syndrome (a clustering of risk factors related to insulin resistance and central adiposity), who are estimated to comprise ~15–30% of the middle-aged adult population in Europe and the US,[44,45] have at least a 5-fold increased risk of developing diabetes compared with those without the condition.[46,47] Those with a family history of diabetes have approximately three times the risk of developing the disease as those with no family history,[48,49] and those who were small babies,[50] the overweight and obese[27] and those from certain ethnic groups – such as Asian (particularly South Asian) and Aboriginal populations[4,51] – are also at substantially increased absolute risk of developing diabetes. The currently available data for physical activity and diabetes prevention in these high-risk groups, who form a substantial portion of the population, are limited. However, in addition to the data from cohort studies described earlier in this review,[21-23] data from the Kuopio Ischemic Heart Disease Risk Study indicate that in middle-aged men, participation in vigorous leisure-time physical activity virtually abolishes the increased risk of the metabolic syndrome associated with being a small or thin baby.[52] Thus, the available data do suggest that benefits of physical activity for diabetes prevention are likely to be greater in ‘high-risk’ than in ‘low-risk’ groups. Figure 4 shows the likely relationships (based on the available evidence) for the change in risk of type 2 diabetes with increasing physical activity in ‘high-risk’ and ‘low-risk’ populations. Sports Med 2008; 38 (10)
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Risk of type 2 diabetes
High-risk populations Low-risk populations
Low absolute diabetes risk Low
High Physical activity level
Fig. 4. Relationship between physical activity level and risk of type 2 diabetes mellitus for populations at high and low baseline risk of the disease.
In addition, when considering an appropriate ‘dose’ of physical activity for the prevention of type 2 diabetes, it is impossible to ignore the influence of adiposity, particularly abdominal adiposity, on diabetes risk, as it appears that, whilst offering some protection, a high level of physical activity cannot completely protect against the elevated risk of type 2 diabetes associated with obesity. In addition, a large proportion of the protective effect of physical activity against type 2 diabetes appears to be mediated by its effects on body fatness (although this may not necessarily lead to a change in bodyweight). The most recent recommendations for physical activity and the prevention/treatment of obesity, suggest that the level of physical activity recommended for general good health (~150 minutes of moderate physical activity or 60–90 minutes of vigorous physical activity per week)[9,10] is likely to be insufficient to prevent obesity in those who struggle to maintain a healthy bodyweight, with some people needing to undertake 60 minutes or more of activity per day to prevent obesity.[9-11,53] Thus, those who are prone to weight gain will likely need to engage in reasonably large amounts of physical activity (‡60 minutes per day of moderate physical activity) and/or restrict their dietary intake in order to obtain optimal protection from type 2 diabetes. For those at low risk of type 2 diabetes (e.g. lean, no diabetes family history, of White European descent), the benefits of physical activity specifically for the prevention of type 2 diabetes ª 2008 Adis Data Information BV. All rights reserved.
are fairly modest (i.e. moving somebody from low risk to very low risk), and the other health benefits of activity are quantitatively more important (e.g. cardiovascular disease prevention, improved mental health). Thus, these individuals should aim to be physically active for general good health, and largely for reasons other than specifically for diabetes prevention. It is, however, important for individuals in low-risk groups to undertake sufficient physical activity to maintain a healthy bodyweight in order to minimize future diabetes risk. Achieving the current physical activity guidelines for general health will also reduce risk of type 2 diabetes in groups at increased risk of type 2 diabetes (as clearly demonstrated by the diabetes prevention trials), but individuals in such groups are likely to obtain further benefits from participation in greater levels of physical activity because of the likely shape of the dose-response relationship for physical activity and diabetes risk in such groups (see figure 4), and because larger amounts of exercise facilitate weight loss, which appears to be the single most important factor for the reduction of diabetes risk.
4. Should We Have Targeted Physical Activity Guidelines for Diabetes Prevention? There are two general approaches that can be adopted for disease prevention in public health: a ‘mass population’ risk reduction strategy that aims to reduce the risk of everybody in the population, and a ‘high-risk’ population risk reduction strategy that aims to reduce the risk of individuals at highest risk of the condition. Taking cholesterol reduction as an example, prescribing cholesterollowering statins to those with elevated blood cholesterol levels would be an example of the latter strategy, whereas working with food manufacturers to reduce the amounts of cholesterolraising trans fatty acids in processed foods would be an example of the former. The two approaches are clearly not mutually exclusive, but for the cholesterol-lowering example, a recent modelling analysis indicated that targeting those at high baseline risk was more effective at reducing overall Sports Med 2008; 38 (10)
Physical Activity and Prevention of Diabetes
cardiovascular disease mortality than a mass population approach.[54] ‘One size fits all’ physical activity guidelines adopt the mass population risk reduction approach. However, this approach is only moderately effective: in Europe and the US, one-quarter to two-fifths of the population undertake no moderate-intensity physical activity in a typical week and only about one-third to half the population undertake moderate physical activity on 4 or more days of the week.[9,55] In contrast, the available evidence suggests that, for diabetes prevention, those at high risk of diabetes are likely to benefit from high levels of activity to a greater extent than those at low risk, in whom more modest activity levels are likely to be adequate. Thus, a high-risk population risk reduction strategy would be consistent with the evidence base. In addition, such an approach would enable targeting of limited resources to the populations who would particularly benefit from becoming more active and may increase motivation to become more active amongst those at high risk, as they would be aware of their increased risk and that physical activity is particularly beneficial for them. Thus, this targeted high-risk population strategy could conceivably have a greater overall effect on diabetes prevention at a population level than the traditional mass population risk reduction approach. However, the potential benefits of such a strategy would need to be weighed against the potential adverse effects on participation that a more complicated physical activity message may have. In addition, the appropriate emphasis on mass population versus high-risk population risk reduction strategies is likely to differ between children and adults. Clearly, the best option is to prevent individuals from becoming high risk in the first place, and thus population-based approaches to increase physical activity levels in school-aged children are likely to play an important role in preventing diabetes in future generations. 5. How Can We Identify Groups at High and Low Risk of Diabetes for Physical Activity Targeting? From figure 4 it is evident that ‘high-risk’ groups need to engage in larger amounts of ª 2008 Adis Data Information BV. All rights reserved.
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physical activity than ‘low-risk’ groups to enjoy a low absolute risk of diabetes. While it is clear that, in reality, a continuum exists between high- and low-risk categories, identification of populations at elevated risk of type 2 diabetes, who would particularly benefit from an augmented physical activity recommendation is helpful both for informing debate on appropriate physical activity for health guidelines and to inform healthcare and exercise practitioners making physical activity recommendations to individuals. Since a guideline needs to be as simple as possible to be effective, we make the initial suggestion to dichotomously define ‘high’ and ‘low’ risk according to a BMI threshold (although using a waist threshold would be an alternative approach), and whether a person has IGT. However, the BMI threshold for high risk would differ for different groups. For normoglycaemic men and women, with no diabetes family history, who are not of Asian descent, we suggest a threshold of 27 kg/m2, based on the level at which diabetes risk starts to increase exponentially.[2,3] For Asian populations, who have increased risk of diabetes at a given BMI level compared with other populations,[4] and for those with a first-degree relative with type 2 diabetes, we propose a lower threshold of 23 kg/m2. All those with IGT would fall into the high-risk group. It should be noted that individuals who were small or thin at birth likely fall into the group at increased risk of type 2 diabetes. However, at this stage there is no consensus regarding how such individuals could be identified. Thus, they are not specifically mentioned in the suggested definition, but could be in the future if a clear way of identifying this group was devised. We suggest that those in the low-risk groups aim to achieve current physical activity for health guidelines (i.e. ~150 minutes of moderate physical activity or 60–90 minutes of vigorous physical activity per week[9-11]) for their general health, rather than specifically for diabetes prevention. However, while those in high-risk groups would also clearly reduce their risk of type 2 diabetes by achieving this level of physical activity, they are likely to gain further diabetes risk reduction by increasing their physical activity beyond this level. Given the key role that weight loss and prevention Sports Med 2008; 38 (10)
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of weight gain play in the prevention of type 2 diabetes, and the evidence that at least some of the beneficial effects of physical activity occur via its effects on adiposity, we suggest that a level of activity in line with the current physical activity recommendations for obesity prevention (i.e. ~300 minutes per week of moderate intensity activity,[9-11,53] or 120–150 minutes of vigorous physical activity) would represent an appropriate ‘augmented’ physical activity guideline to achieve greater levels of diabetes risk reduction for those at high risk of the disease. We acknowledge that 300 minutes of moderate physical activity per week will represent a substantial increase in physical activity for virtually all individuals at high risk of diabetes. Studies examining the long-term success of interventions to increase physical activity to this level in those at high risk of diabetes are limited, although it has been reported that increases in physical activity levels of ‡300 minutes per week are sustainable for 12 months in middle-aged and older men and women, at least in the context of a controlled intervention trial.[56] There is therefore an urgent need for intervention trials to evaluate the long-term effectiveness of targeted guidelines recommending higher levels of physical activity for those at high risk of developing type 2 diabetes and for the development of successful methods for the promotion of physical activity in these groups. 6. Conclusions There is clear evidence from prospective cohort studies and controlled intervention trials that physical activity can play a role in prevention of type 2 diabetes, with at least some of this effect occurring via effects on adiposity. While data from the majority of studies suggest that there is no clear minimum threshold of activity that needs to be achieved before benefits are accrued (all levels of activity above a sedentary baseline appear to be beneficial), the weight of available evidence does suggest that those at the highest risk of developing diabetes are likely to particularly benefit from undertaking high levels of physical activity. Whether physical activity guidelines should reflect the fact that the amount of physical activity needed to confer low risk of diaª 2008 Adis Data Information BV. All rights reserved.
betes is likely to differ between different populations is a matter for discussion and debate. Acknowledgements The authors received no funding for this work and have no conflicts of interest directly relevant to its contents.
References 1. Wild S, Roglic G, Green A, et al. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004; 27 (5): 1047-53 2. Chan JM, Rimm EB, Colditz GA, et al. Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care 1994; 17 (9): 961-9 3. Colditz GA, Willett WC, Rodnitzky A, et al. Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med 1995; 122: 481-6 4. Razak F, Anand SS, Shannon H, et al. Defining obesity cut points in a multiethnic population. Circulation 2007; 115 (16): 2111-8 5. UK Prospective Diabetes Study Group. UK Prospective Diabetes Study: XII, differences between Asian, AfroCaribbean and white Caucasian type 2 diabetic patients at diagnosis of diabetes. Diabet Med 1994; 11 (7): 670-7 6. Chandalia M, Lin P, Seenivasan T, et al. Insulin resistance and body fat distribution in South Asian men compared to Caucasian men. PLoS ONE 2007; 2 (8): e812 7. World Health Organization. WHO expert consultation: appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363 (9403): 157-63 8. Wareham NJ, van Sluijs EMF, Ekelund U. Physical activity and obesity prevention: a review of the current evidence. Proc Nutr Soc 2005; 64: 229-47 9. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007; 39 (8): 1423-34 10. Sigal RJ, Kenny GP, Wasserman DH, et al. Physical activity/exercise and type 2 diabetes: a consensus statement from the American Diabetes Association. Diabetes Care 2006; 29 (6): 1433-8 11. Chief Medical Officer. At least five a week: evidence on the impact of physical activity and its relationship to health. London: Department of Health, 2004 12. Pate RR, Pratt M, Blair SN, et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995; 273 (5): 402-7 13. Hsia J, Wu L, Allen C, et al. Physical activity and diabetes risk in postmenopausal women. Am J Prev Med 2005; 28 (1): 19-25 14. Folsom AR, Kushi LH, Hong CP. Physical activity and incident diabetes mellitus in postmenopausal women. Am J Public Health 2000; 90 (1): 134-8
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15. Burchfiel CM, Sharp DS, Curb JD, et al. Physical activity and incidence of diabetes: the Honolulu Heart Program. Am J Epidemiol 1995; 141 (4): 360-8 16. Villegas R, Shu XO, Li H, et al. Physical activity and the incidence of type 2 diabetes in the Shanghai women’s health study. Int J Epidemiol 2006; 35 (6): 1553-62 17. Nakanishi N, Takatorige T, Suzuki K. Daily life activity and risk of developing impaired fasting glucose or type 2 diabetes in middle-aged Japanese men. Diabetologia 2004; 47 (10): 1768-75 18. Monterrosa AE, Haffner SM, Stern MP, et al. Sex difference in lifestyle factors predictive of diabetes in MexicanAmericans. Diabetes Care 1995; 18 (4): 448-56 19. Manson JE, Rimm EB, Stampfer MJ, et al. Physical activity and incidence of non-insulin-dependent diabetes mellitus in women. Lancet 1991; 338 (8770): 774-8 20. Hu FB, Sigal RJ, Rich-Edwards JW, et al. Walking compared with vigorous physical activity and risk of type 2 diabetes in women: a prospective study. JAMA 1999; 282 (15): 1433-9 21. Helmrich SP, Ragland DR, Leung RW, et al. Physical activity and reduced occurrence of non-insulin-dependent diabetes mellitus. N Engl J Med 1991; 325 (3): 147-52 22. Manson JE, Nathan DM, Krolewski AS, et al. A prospective study of exercise and incidence of diabetes among US male physicians. JAMA 1992; 268 (1): 63-7 23. Lynch J, Helmrich SP, Lakka TA, et al. Moderately intense physical activities and high levels of cardiorespiratory fitness reduce the risk of non-insulin-dependent diabetes mellitus in middle-aged men. Arch Intern Med 1996; 156 (12): 1307-14 24. Weinstein AR, Sesso HD, Lee IM, et al. Relationship of physical activity vs body mass index with type 2 diabetes in women. JAMA 2004; 292 (10): 1188-94 25. Perry IJ, Wannamethee SG, Walker MK, et al. Prospective study of risk factors for development of non-insulin dependent diabetes in middle aged British men. BMJ 1995; 310 (6979): 560-4 26. Hu G, Qiao Q, Silventoinen K, et al. Occupational, commuting, and leisure-time physical activity in relation to risk for Type 2 diabetes in middle-aged Finnish men and women. Diabetologia 2003; 46 (3): 322-9 27. Hu G, Lindstrom J, Valle TT, et al. Physical activity, body mass index, and risk of type 2 diabetes in patients with normal or impaired glucose regulation. Arch Intern Med 2004; 164 (8): 892-6 28. Haapanen N, Miilunpalo S, Vuori I, et al. Association of leisure time physical activity with the risk of coronary heart disease, hypertension and diabetes in middleaged men and women. Int J Epidemiol 1997; 26 (4): 739-47 29. Meisinger C, Thorand B, Schneider A, et al. Sex differences in risk factors for incident type 2 diabetes mellitus: the MONICA Augsburg cohort study. Arch Intern Med 2002; 162 (1): 82-9 30. Meisinger C, Lowel H, Thorand B, et al. Leisure time physical activity and the risk of type 2 diabetes in men and women from the general population: the MONICA/KORA Augsburg Cohort Study. Diabetologia 2005; 48 (1): 27-34
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31. Hu FB, Leitzmann MF, Stampfer MJ, et al. Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med 2001; 161 (12): 1542-8 32. Okada K, Hayashi T, Tsumura K, et al. Leisure-time physical activity at weekends and the risk of type 2 diabetes mellitus in Japanese men: the Osaka Health Survey. Diabet Med 2000; 17 (1): 53-8 33. Hu FB, Manson JE, Stampfer MJ, et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med 2001; 345 (11): 790-7 34. Eriksson KF, Lindgarde F. Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise: the 6-year Malmo¨ feasibility study. Diabetologia 1991; 34 (12): 891-8 35. Pan XR, Li GW, Hu YH, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da Qing IGT and Diabetes Study. Diabetes Care 1997; 20 (4): 537-44 36. Tuomilehto J, Lindstrom J, Eriksson JG, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001; 344 (18): 1343-50 37. Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346 (6): 393-403 38. Ramachandran A, Snehalatha C, Mary S, et al. The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1). Diabetologia 2006; 49 (2): 289-97 39. Davey Smith G, Bracha Y, Svendsen KH, et al. Incidence of type 2 diabetes in the randomized Multiple Risk Factor Intervention Trial. Ann Intern Med 2005; 142 (5): 313-22 40. Laaksonen DE, Lindstrom J, Lakka TA, et al. Physical activity in the prevention of type 2 diabetes: the Finnish diabetes prevention study. Diabetes 2005; 54 (1): 158-65 41. Hamman RF, Wing RR, Edelstein SL, et al. Effect of weight loss with lifestyle intervention on risk of diabetes. Diabetes Care 2006; 29 (9): 2102-7 42. Shephard RJ. Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med 2003; 37 (3): 197-206 43. Tudor-Locke CE, Myers AM. Challenges and opportunities for measuring physical activity in sedentary adults. Sports Med 2001; 31 (2): 91-100 44. Laaksonen DE, Niskanen L, Lakka HM, et al. Epidemiology and treatment of the metabolic syndrome. Ann Med 2004; 36 (5): 332-46 45. Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2005; 365 (9468): 1415-28 46. Sattar N, Gaw A, Scherbakova O, et al. Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation 2003; 108 (4): 414-9 47. Laaksonen DE, Lakka HM, Niskanen LK, et al. Metabolic syndrome and development of diabetes mellitus:
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48.
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50. 51. 52.
application and validation of recently suggested definitions of the metabolic syndrome in a prospective cohort study. Am J Epidemiol 2002; 156 (11): 1070-7 Ohlson LO, Larsson B, Bjorntorp P, et al. Risk factors for type 2 (non-insulin-dependent) diabetes mellitus: thirteen and one-half years of follow-up of the participants in a study of Swedish men born in 1913. Diabetologia 1988; 31 (11): 798-805 Kobberling J, Tillil H. Empirical risk factors for first degree relatives of non insulin dependent diabetes. In: Kobberling J, Tattersall RB, editors. The genetics of diabetes mellitus. London: Academic Press, 1982: 201-209 Hales CN, Barker DJ. The thrifty phenotype hypothesis. Br Med Bull 2001; 60: 5-20 Peterson S, Peto V, Rayner M. Coronary heart disease statistics. London: British Heart Foundation, 2003 Laaksonen DE, Lakka HM, Lynch J, et al. Cardiorespiratory fitness and vigorous leisure-time physical activity modify the association of small size at birth with the metabolic syndrome. Diabetes Care 2003; 26 (7): 2156-64
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53. Saris WH, Blair SN, van Baak MA, et al. How much physical activity is enough to prevent unhealthy weight gain? Outcome of the IASO 1st Stock Conference and consensus statement. Obes Rev 2003; 4 (2): 101-14 54. Manuel DG, Lim J, Tanuseputro P, et al. Revisiting Rose: strategies for reducing coronary heart disease. BMJ 2006; 332 (7542): 659-62 55. Allender S, Peto V, Scarborough S, et al. Diet, physical activity and obesity statistics. Oxford: British Heart Foundation Statistics Database, 2006 56. McTiernan A, Sorensen B, Irwin ML, et al. Exercise effect on weight and body fat in men and women. Obesity (Silver Spring) 2007; 15 (6): 1496-512
Correspondence: Dr Jason M.R. Gill, Institute of Diet, Exercise and Lifestyle (IDEAL), Faculty of Biomedical and Life Sciences, University of Glasgow, University Avenue, West Medical Building, Glasgow, G12 8QQ, UK. E-mail:
[email protected]
Sports Med 2008; 38 (10)
Sports Med 2008; 38 (10): 825-838 0112-1642/08/0010-0825/$48.00/0
REVIEW ARTICLE
ª 2008 Adis Data Information BV. All rights reserved.
Oxygen Consumption during Functional Electrical Stimulation-Assisted Exercise in Persons with Spinal Cord Injury Implications for Fitness and Health Dries M. Hettinga1 and Brian J. Andrews2 1 School of Health Sciences and Social Care, Brunel University, London, UK 2 Nuffield Department of Surgery, Oxford University and School of Technology, Oxford Brookes University, Oxford, UK
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Exercise and Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Health in Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Exercise in Spinal Cord Injury. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Aims of the Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Peak Oxygen Consumption during Functional Electrical Stimulation (FES)-Exercise. . . . . . . . . . . 4.2 Sub-Peak Oxygen Consumption during FES-Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Cardio-Respiratory Training Effects of FES-Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Potential Health Benefits of FES-Exercise Training. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Comparison with Upper Body Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Limitations of the Review and Included Studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Recommendations for Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
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A lesion in the spinal cord leads in most cases to a significant reduction in active muscle mass, whereby the paralysed muscles cannot contribute to oxygen . consumption (VO2) during exercise. . Consequently, persons with spinal cord injury (SCI) can only achieve high VO2 values by excessively stressing the upper body musculature, which might increase the risk of musculoskeletal overuse injury. Alternatively, the muscle mass involved may be increased by using functional electrical stimulation (FES). FES-assisted cycling, FES-cycling combined with arm cranking (FES-hybrid exercise) and FES-rowing have all been suggested as candidates for cardiovascular training in SCI. . . . In this article, we review the levels of VO2 (peak [VO2peak] and sub-peak [VO2sub-peak]) that have been reported for SCI subjects using these FES exercise modalities. A systematic literature search in MEDLINE, EMBASE, AMED, CINAHL, SportDiscus and .the authors’ own files revealed 35 studies that reported on 499 observations of VO2 levels achieved during FES-exercise in SCI. The results
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. show that VO2peak during FES-rowing (1.98 L/min, n = 17; 24.1 mL/kg/min, n = 11) and FES-hybrid exercise (1.78 L/min, n = 67; 26.5 mL/kg/min, n = 35) is considerably higher than during FES-cycling (1.05 L/min, n = 264; 14.3 mL/kg/ . min, n = 171). VO2sub-peak values during FES-hybrid exercise were higher than during FES-cycling. FES-exercise training can produce large increases in . VO2peak; the included studies report average increases of þ11% after FESrowing training, þ12% after FES-hybrid exercise training and þ28% after FEScycling training. . This review shows that VO2 during FES-rowing or FES-hybrid exercise is considerably higher than during FES-cycling. These observations are confirmed by a limited number of direct comparisons; larger studies to test the differences in effectiveness of the various types of FES-exercise as cardiovascular exercise are needed. The results to date suggest that FES-rowing and FES-hybrid are more suited for high-intensity, high-volume exercise training than FES-cycling. In able-bodied people, such exercise programmes have shown to result in superior health and fitness benefits. Future research should examine whether similar high-intensity and high-volume exercise programmes also give persons with SCI superior fitness and health benefits. This kind of research is very timely given the high incidence of physical inactivityrelated health conditions in the aging SCI population.
1. Exercise and Health 1.1 Health in Spinal Cord Injury
Regular physical exercise plays a key role in the prevention of obesity, cardiovascular disease and type 2 diabetes mellitus. Large-scale epidemiological studies in the general population indicate that there is a dose-response relationship for exercise and health, and furthermore, minimal exercise intensities and volumes have been identified for obtaining significant reductions in a number of risk factors for chronic diseases.[1-4] For example, results from the Health Professionals Follow-up Study suggest that superior health benefits can only be expected from physical activity programmes that include exercises exceeding intensities of 21 mL/kg/min.[1] Furthermore, Durstine et al.[3] reported that exercise programmes only influence blood lipids and lipoproteins if the exercise volume exceeds 1200–2000 kcal/week. It would appear reasonable to assume that similar processes are also involved in persons with spinal cord injury (SCI); however, this remains to be confirmed. In general, physically active individuals with SCI score better than inactive SCI patients on ª 2008 Adis Data Information BV. All rights reserved.
numerous health parameters, including lipid profile.[5,6] However the optimal exercise intensity and volume remains to be confirmed. Two small intervention studies have reported superior health effects of higher intensity exercise in SCI,[7,8] but the weight of this evidence is insufficient for specific recommendations on optimal exercise volume and intensity in SCI. Detailed investigations into which exercise interventions give optimal health benefits for persons with SCI are crucial, since the SCI population show an abundance of elevated risk factors for obesity, cardiovascular disease and diabetes.[9] Persons with SCI have a 3- to 5-fold increased risk for type 2 diabetes[10,11] and a 60% increased risk of heart attack[5] compared with their able-bodied peers. This could imply that existing levels of physical activity in the SCI population are insufficient to reduce these risk factors. In the absence of large-scale evidence to support this, the authors suggest a conservative approach and use the values identified in able-bodied persons as exercise targets for the SCI population. It would therefore be of interest to explore the possibilities for persons with SCI to adhere to guidelines intended for the able-bodied. Sports Med 2008; 38 (10)
. VO2 in FES-Exercise for Spinal Cord Injury
1.2 Exercise in Spinal Cord Injury
Following a lesion in the spinal cord, significant changes occur to the motor, sensory and autonomic nervous systems and consequently, the exercise response in persons with SCI is considerably different to that in able-bodied people. Cardiovascular control during exercise is influenced by factors such as neural feedback from the muscles and autonomic innervation of the heart, which is particularly impaired in persons with higher lesions. Subsequent limitations in cardiac output challenge the exercise tolerance of persons with SCI.[12] Furthermore, the significant reduction in the amount of muscle mass that can be involved in voluntary physical . exercise limits the total oxygen consumption (VO2.). Consequently, high-intensity exercise (i.e. high VO2) can only be achieved with proportionally higher loading of the preserved upper limb musculature. Although this may be possible for some, it could exacerbate the risk of upper limb overuse injury, which has a very high incidence in manual wheelchair users.[13] The repetitive use of the muscles on the front of the chest and shoulders during manual wheelchair propulsion could contribute to a muscular imbalance between shoulder protractors and shoulder retractors. Such imbalances might explain the shoulder pain experienced by many wheelchair-bound individuals.[14] This may suggest that exercise programmes should avoid repetitive use of the shoulder protractors or include exercises aimed at restoring the muscular balance in the shoulder. However, it should be noted that, to the authors’ knowledge, there is no evidence from large follow-up studies that supports this. One technique to avoid repetitive use of the upper extremity is functional electrical stimulation (FES) to activate the paralysed musculature for exercise. The regular use of FES has a number of additional benefits, such as improved circulation, muscle hypertrophy and muscle fibre type conversion.[15] Furthermore, FES of the large muscle groups in the lower extremities could improve venous return and limit blood pooling in the legs.[16] This might increase the exercise capacity of the upper body.[17] To date, three types of FES-exercise systems have been developed and evaluated for cardiovascular training; FES-cycling, FES-hybrid exercise (FESª 2008 Adis Data Information BV. All rights reserved.
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cycling combined with simultaneous arm cranking) and FES-rowing. Jerrold Petrofsky first introduced FES-cycling in the early 1980s, initially as a free range adapted tricycle, the Zap-Mobile,[18,19] and then as a stationary ergometer[20] (commercialized as the ERGYS system by Therapeutic Alliances Inc., Fairborn, OH, USA). More recently, other FEScycling ergometers (e.g. the RT-300 by Restorative Therapies Inc., Baltimore, MD, USA) and FES-tricycles (e.g. the RehaBike by HasoMed GmbH, Magdeburg, Germany) have been introduced. Most of these FES-cycling systems apply electrical stimulation to the quadriceps, hamstrings and glutei to perform a cyclical. movement with the legs. To augment VO2, FES-cycling has been combined with arm cranking.[21,22] Such FES-hybrid exercise is mostly performed on ergometers, although a roadworthy outdoor hybrid bike is also available (the BerkelBike by BerkelBike bv, Nijmegen, the Netherlands). Whole-body exercise can also be performed with FES-rowing ergometers, which consist of standard rowing ergometers adapted for FES use. Self-controlled stimulation of the hamstrings and quadriceps induce leg movement, which, combined with voluntary upper body movement, results in whole-body rowing action.[23,24] The number of FES-exercise research publications and commercial spin-offs imply that FESexercise is a popular form of exercise for researchers and users. It would therefore be of interest to review the cardio-respiratory values that can be achieved with these various forms of FESexercise, especially given that: FES-exercise could prevent repetitive use of the upper body as seen during wheelchair ergometry; . FES-exercise could augment VO2 during exercise, which could result in superior fitness and health benefits; regular FES-exercise use could prevent many of the changes seen after long-term paralysis, such as decreased bone mineral density, muscle atrophy and decreased blood circulation.[15,25] To the authors’ knowledge, only one study has made a direct comparison between all three types of [26] FES-exercise. Verellen . et .al. found in five SCI subjects that peak VO2 (VO2peak) during FES-cycling (13.3 . – 3.9 mL/kg/min) was significantly lower than VO2peak during FES-rowing (25.6 – 3.0 Sports Med 2008; 38 (10)
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mL/kg/min) .or FES-hybrid exercise (25.4 – 6.0 mL/kg/min). VO2peak during FES-rowing and FES. hybrid exercise was higher than VO2peak during arm cranking (21.6 – 4.6 mL/kg/min), although not significantly. Although this study needs replication in larger subject groups, it gives an indication of the added value of a whole-body exercise compared with a lower or upper body exercise. . Although the above study describes VO . 2peak, it would .also be valuable to investigate VO2 subpeak (VO2sub-peak) values, since these represent an intensity that can be sustained over prolonged periods of time. For that. reason, this review con. siders both VO2peak and VO2sub-peak values. 1.3 Aims of the Review
The aim of this review is to identify what levels . of VO2 peak and sub-peak can be achieved during FES-exercise in SCI. The results will be useful in answering two questions: 1. Can persons with SCI achieve the high exercise intensities and volumes that have been associated with significant health benefits in the general population? 2. What type of exercise should be used to further explore the validity of adopting the able-bodied exercise recommendations in the SCI population? To answer these questions, anextensiveliterature search was . conducted . to identify studies that reported VO2peak or VO2sub-peak values during FEScycling, FES-hybrid exercise and/or FES-rowing. 2. Methods A literature search was conducted in MEDLINE, EMBASE, AMED, CINAHL and . SportDiscus to identify studies that reported VO 2peak or . VO2sub-peak values during FES-exercise in SCI. Studies had to be in the English language and published between 1980 and January 2007. The literature search was conducted using the following strategy: (‘functional neuromuscular stimulation’ OR ‘FES’ OR ‘functional electrical stimulation’) AND (‘VO2’ OR ‘oxygen consumption’) AND (‘spinal cord injur*’ OR ‘paraplegi*’ OR ‘tetraplegi*’ OR ‘quadriplegi*’). Based on titles and abstracts, the search results . were scanned to check whether they reported VO2 ª 2008 Adis Data Information BV. All rights reserved.
values (peak or sub-peak) during FES-cycling, FES-hybrid exercise (consisting of FES-cycling in combination with arm cranking) or FES-rowing in . persons with SCI. Studies that reported VO2 values in cohorts consisting predominantly of subjects with motor incomplete lesions were excluded. Reference lists were cross-checked and the authors’ own collections were used to identify additional articles. Conference proceedings were not included to prevent data from being included twice. The following data were extracted from the individual studies: subject characteristics (paraplegia/tetraplegia, level of lesion, bodyweight, age, gender), sample size, timing of measurement (pretraining, post-training or cross-sectional), . . absolute VO2 peak and sub-peak, relative VO2 peak and sub-peak. Since most studies did not report individual subject data, published group averages . were used. Where relative VO2 was not presented, . this was calculated based on absolute VO2 and reported bodyweight of the subjects in that study. . Average VO2 values per exercise modality were calculated, but standard deviation could not be calculated since individual subject. data were not available. Instead, the range in VO2 values reported in the various studies was determined and displayed graphically. Absence of individual subject data did not allow for sub-group analysis. 3. Results The literature search resulted in 53 articles. Based . on titles and abstracts, 21 articles reported on VO2 values (peak or sub-peak) during FES-cycling, FEShybrid exercise (consisting of FES-cycling in combination with arm cranking) or FES-rowing in persons with SCI. Cross-checking references and the authors’ own collections revealed an additional 14 articles. In total, 35 studies were. included that reported on 353 observations on VO2peak . during FES-exercise and 146 observations on VO2sub-peak during FES-exercise. Most of these . observations reported both absolute and relative VO 2, or . . relative VO2 could be calculated from absolute VO2 and reported bodyweight. For nine studies, only relative . or absolute VO2 was available. Table. I shows all the identified studies that reported VO2peak during FES-cycling, FES-hybrid Sports Med 2008; 38 (10)
. VO2 in FES-Exercise for Spinal Cord Injury
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. Table I. Peak oxygen consumption (VO2peak) values during functional electrical stimulation (FES)-cycling, FES-hybrid exercise and FESrowing . Study (year) Subjects n Time of Absolute Relative VO2peak . measurementa VO2peak (L/min) (mL/kg/min) FES-cycling Barstow et al.[27] (1996)
7 para, 2 tetra (C5–L1)
9
Pre
1.28 – 0.31
16.8b
9 males 9
Post
1.42 – 0.34
8
Cross
1.27 – 0.27
7
Cross
0.65 – 0.18
4 para, 2 tetra (C4–T10)
6
Pre
0.55
4 males, 2 females
6
Post
1.00
Cross
0.78 – 0.28
10.4b
Pre
0.79 – 0.23
12.7b
Barstow et al.[28] (2000)
8 para (T4–L1)
Bhambhani et al.[29] (2000)
4 para, 3 tetra (C5–T12)
17.4b
8 males 6 males, 1 female Burke-Gurney et al.[30] (1998) Figoni et al.[31] (1990)
13 para, 17 tetra (C5–T11)
30
unknown gender Goss et al.[32] (1992) Hjeltnes et al.[33] (1997) Holme et al.[34] (2001)
3 para, 2 tetra (C5–T10)
5
3 males, 2 females
5
Post
1.01 – 0.25
5 tetra (C5–C7)
5
Pre
0.57b
5 males
5
Post
4 para, 3 tetra (T1–C5)
7
Cross
1.36 – 0.1
17.8b 10.2b
7.5 – 1.3 12.5 – 1.5
6 males, 1 female Hooker et al.[35] (1992) Hooker et al. (1995)[36] Kjaer et al.[37] (2001)
Krauss et al.
[21]
(1993)
Mohr et al.[38] (1997) Mutton et al.[22] (1997) Pollack et al.[39] (1989) Verellen et al.[26] (2007)
8 para, 10 tetra (C5–T11)
18
Pre
0.78 – 0.01
17 males, 1 female
18
Post
0.95 – 0.01
6 para, 2 tetra (C5–L1)
8
Pre
1.29 – 0.3
17.7 – 5.8
8 males
8
Post
1.42 – 0.39
19.4 – 7.5
4 para, 6 tetra (C6–T4)
10
Pre
1.20
15.4b
8 males, 2 females
10
Post 1
1.43
18.3b
10
Post 2
1.26
16.2b
7 para, 1 tetra (C7–T1)
8
Pre
0.51 – 0.05
7 males, 1 female
8
Post
0.83 – 0.06
4 para, 6 tetra (C6–T4)
10
Pre
1.20 – 0.08
8 males, 2 females
10
Post
1.43 – 0.09
9 para, 2 tetra (C5–L1)
11
Pre
1.30 – 0.27
11 males
11
Post
1.42 – 0.34
4 para, 7 tetra (C4–T6)
11
Pre
0.79 – 0.15
7 males, 4 females
11
Post
1.04 – 0.13
16.2
Cross
1.10 – 0.25
13.3 – 3.9
1.05 (n = 264)
14.3 (n = 171)
4 para, 1 tetra (C7–T12)
5
5 males . Average VO2peak during FES-cycling
16.8b 12.7
FES-hybrid exercise Heesterbeek et al.[40] (2005) Krauss et al.[21] (1993) Mutton et al.[22] (1997)
10 para (T2–T12)
10
Pre
1.88b
25.7 – 5.8
9 males, 1 female
10
Post
2.05b
28.1 – 7.5
7 para, 1 tetra (C7–L1)
8
Pre
1.3 – 0.15
7 males, 1 female
8
Post
1.49 – 0.14
Unknown level of lesion
8
Pre
1.69 – 0.64
8 males
8
Post
1.91 – 0.85
Continued next page
ª 2008 Adis Data Information BV. All rights reserved.
Sports Med 2008; 38 (10)
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830
Table I. Contd Study (year)
Subjects
n
Time of measurementa
Absolute . VO2peak (L/min)
. Relative VO2peak (mL/kg/min)
Raymond et al.[41] (1999)
10 para (T5–T12)
10
Cross
1.81 – 0.1
26.2b
5
Cross
2.13 – 0.44
25.4 – 6.0
1.78 (n = 67)
26.5 (n = 35)
10 males Verellen et al.[26] (2007)
4 para, 1 tetra (C7–T12) 5 males
. Average VO2peak during FES-hybrid exercise FES-rowing Verellen et al.[26] (2007)
4 para, 1 tetra (C7–T12)
5
Cross
2.15 – 0.20
25.6 – 3.0
6
Pre
1.81 – 0.41
22.8b
6
Post
5 males Wheeler et al.[24] (2002)
5 para, 1 tetra (C7–T12)
6 males . Average VO2peak during FES-rowing
2.01 – 0.38 1.98 (n = 17)
24.1 (n = 11)
a
Time of measurement: cross-sectional data, pre-training, or post-training. . b VO2 values have been calculated by the reviewer based on average bodyweight reported in the original study. . para = paraplegic; tetra = tetraplegic; VO2 = oxygen consumption.
exercise and/or FES-rowing. Table . II shows all the identified studies that reported VO2sub-peak during FES-cycling, FES-hybrid exercise and/or FES. rowing. Both absolute and relative VO2peak during FES-rowing and FES-hybrid exercise were considerably higher than during FES-cycling. . VO2sub-peak during FES-hybrid exercise was considerably higher than during FES-cycling, while the number of FES-rowing observations was too small to make reliable comparisons. Figure 1 . shows the average and range in absolute VO2peak for FES-cycling, FES-hybrid exercise and FESrowing reported in the included studies. The range is the range in reported group averages. . Figure 2 is a similar graph for average . relative VO2peak. The average increase in VO2peak after training was 28% for FES-cycling (11 studies, n = 101), 12% for FES-hybrid exercise (3 studies, n = 26) and 11% for FES-rowing (1 study, n = 6). 4. Discussion 4.1 Peak Oxygen Consumption during Functional Electrical Stimulation (FES)-Exercise
. Pooling all observations on VO2peak during FES-exercise, as identified in this systematic re. view, shows that VO2peak during FES-rowing (1.98 L/min, n = 17)[24,26] and FES-hybrid exercise ª 2008 Adis Data Information BV. All rights reserved.
(1.78 L/min, n = 67)[21,22,26,40,41] is considerably higher than during FES-cycling (1.05 L/min, n = 264).[21,22,26-30,32-39] The FES-cycling studies . that report the highest VO2peak values . still report values that are at the lower end of the VO2peak range seen in FES-rowing and FES-hybrid exercise (see figure 2). Although not displayed in the tables, . differences in VO2peak cannot be explained be differences . in age. A large proportion of the FES-cycling VO2peak data came from subjects with tetraplegia (41%), while only 6% of the FES-hybrid exercisers and 18% of the FES-rowers were tetraplegic. The more extensive consequences of the injury in persons with higher lesions may results in different exercise responses, e.g. difference in vasal control and.hormone secretion. This might explain the higher VO2peak values seen in the FES-hybrid exercise and FES-rowing conditions. Differences in the ratio of male to female subjects might also have played a role, since 13% of the FES-cycling observations, 4% of the FES-hybrid exercise observations and 0% of the FES-rowing observations came from female subjects. The larger percentage of men in the FES-rowing and hybrid-FES exercise studies might have contributed to the higher . VO2peak values. Since not all studies reported the completeness of the lesion in the subjects, insufficient data was available to. determine the effect of completeness of lesion on VO2peak responses. Sports Med 2008; 38 (10)
. VO2 in FES-Exercise for Spinal Cord Injury
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. Table II. Sub-peak oxygen consumption (VO2sub-peak) values during functional electrical stimulation (FES)-cycling, FES-hybrid exercise and FES-rowing Study (year)
Subjects
n
Time of measurementa
. Absolute VO2sub-peak (L/min)
7 para, 5 tetra (C5–T4)
12
Cross
0.92 – 0.44
6
Cross
1.03 – 0.16
13.1b
8
Cross
0.93 – 0.19
12.7b 7.4b
. Relative VO2sub-peak (mL/kg/min)
FES-cycling Arnold et al.[42] (1992)
10 males, 2 females Barstow et al.[43] (1995)
4 para, 2 tetra (C6–T9) 6 males, 2 females
Barstow et al.[28] (2000)
8 para (T4–L1)
Faghri et al.[44] (1992)
8 para, 5 tetra (C4–T10)
13
Pre
0.57
12 males, 1 female
13
Post
0.69
7
Cross
0.9 – 0.07 1.39
8 male
11.4b
Kjaer et al.[45] (1999)
3 para, 4 tetra (C6–T4)
Kjaer et al.[37] (2001)
4 para, 6 tetra (C5–T7)
10
Cross
8 males, 2 females
10
Cross
0.92
9
Cross
1.03 – 0.15
6
Cross
0.71 – 0.3
8
Cross
2.5 – 0.2
34.7b
6
Cross
0.75 – 0.11
10.4b
5
Cross
0.47 – 0.09
7.1b
0.98 (n = 113)
13.8 (n = 53)
6 males, 1 female
Mohr et al.[46] (1998)
2 para, 7 tetra (C5–T4) 9 males
Nash et al.[47] (1995)
6 tetra (C5–C6) 6 males
Petrofsky and Stacey[48] (1992)
8 para (T4–T11)
Raymond et al.[49] (2002)
6 para (T5–T9)
unknown gender 6 males Theisen et al.[50] (2002)
5 para (T4–T9)
5 males . Average VO2sub-peak during FES-cycling FES-hybrid exercise Hooker et al.[51] (1992)
8 tetra (C5–C8)
Phillips and Burkett[17] (1998)
5 para, 3 tetra
8
Cross
1.02 – 0.02
14.0b
8
Cross
1.24*
18 – 5
7
Cross
1.58 – 0.12
23.4b
1.27 (n = 23)
18.3 (n = 23)
7 males, 1 female (C6–T12) 7 males, 1 female Raymond et al.[52] (1997)
7 para (T4–T12) 5 males, 2 females
. Average VO2sub-peak during FES-hybrid exercise FES-rowing Laskin et al.[53] (1993)
2 para, 6 tetra (C6–T6)
8
Cross
1.02 – 0.05
16.3 – 0.7
2
Cross
2.12 – 0.07
28.9 – 3.0
1.24 (n = 10)
18.8 (n = 10)
7 males, 1 female Hettinga and Andrews[54] (2007)
2 para (T4–T8) 2 males
. Average VO2sub-peak during FES-rowing
a
Time of measurement: cross-sectional data, pre-training, or post-training.
b
Values have been calculated by the reviewer based on average bodyweight reported in the original study.
para = paraplegic; tetra = tetraplegic.
Differences in total bodyweight . have been controlled for by calculating relative VO2peak. Unfortunately, not all studies have reported bodyª 2008 Adis Data Information BV. All rights reserved.
weight, and consequently, such a comparison is based on a smaller sample size; FES-cycling: 14.3 mL/kg/min (n = 171),[22,26-28,32-37,39] FES-hybrid Sports Med 2008; 38 (10)
Hettinga & Andrews
2.5 2 1.5 1 0.5 0 n = 264 FES-cycling
n = 67 FES-hybrid exercise
n = 17 FES-rowing
. Fig. 1. Average absolute peak oxygen consumption (VO2peak) reported in the literature for functional electrical stimulation (FES)-cycling (16 studies, 264 observations), FES-hybrid exercise (5 studies, 67 observations) and FES-rowing (2 studies, 17 observations). Grey columns represent average of all included studies, black lines represent the range in reported average values.
exercise: 26.5 mL/kg/min (n = 35)[26,40,41] and FESrowing: 24.1 mL/kg/min (n = 11).[24,26] Relative . VO . 2peak during FES-cycling is well below relative VO2peak during FES-hybrid exercise and FESrowing, while the possible differences between FES-rowing and FES-hybrid exercise need to be further explored. The results from this review confirm direct comparisons between various FES-exercises. . Verellen et al.[26] reported significantly lower VO2peak values during FES-cycling than during FES-rowing or FES-hybrid exercise, while the difference between the latter two did not reach statistical significance. Hooker et al.[51] found similar results for . the superior VO2 levels for FES-hybrid exercise at sub-peak intensities. Krauss et al.[21] and Mutton et al.,[22] studied FES-hybrid exercise training after completion of a FES-cycling training programme. Both concluded that higher levels of energy expenditure can be achieved using the hybrid variant.
sample size, especially for FES-rowing, limits generalization of these sub-peak values. The sub-peak values observed in the FES-cycling studies represent 90–93% of the reported . VO2peak values, which is a relatively high proportion of the peak values. The FES-hybrid exercise and FES-rowing sub-peak intensities are 69–71% and 63–78% of their respective peak values. It should be noted though that the peak and sub-peak values were not all reported in the same subject populations, which limits a direct comparison. If . the VO2sub-peak values during FES-cycling truly represent 90–93% of the peak value, then it is surprising that such an intensity can be sustained for a full session (i.e. 20–30 minutes). However, the results could. also suggest that the protocols used to achieve VO2peak during FES-cycling are in. adequate and no true VO2peak is achieved during the tests. Perhaps it is the low specificity of (transcutaneous) stimulation, the high resistance of the skin and subcutaneous tissue and the inverse recruitment order (i.e. large motor units are recruited first)[55,56] that make step-wise increases in power output very difficult to achieve in FES-exercise. Moreover, the early onset of peripheral fatigue in the electrically stimulated muscle groups might . impair VO2peak, especially in novice FES users.[56] Although the whole-body exercises in this review . . result in higher VO2peak and VO2sub-peak values, subjective measures for intensity indicate differently. Laskin et al.[53] reported that FES-rowing was perceived to be easier than arms-only rowing, even
4.2 Sub-Peak Oxygen Consumption during FES-Exercise
. Absolute VO2 at sub-maximal intensities are considerably lower during FES-cycling (0.98 L/ min, n = 113)[28,37,42-50] than during FES-hybrid exercise (1.27 L/min, n = 23)[17,51,52] or FES-rowing (1.24 L/min, n = 10).[53,54] A similar conclusion . can be drawn based on relative VO2sub-peak: FEScycling: 13.8 mL/kg/min (n = 53),[28,43-45,48-50] FES-hybrid exercise: 18.3 mL/kg/min (n = 23)[17,51,52] and FES-rowing: 18.8 mL/kg/min (n = 10).[53,54] However, it should be noted that the small ª 2008 Adis Data Information BV. All rights reserved.
.
Relative VO2peak (mL /kg/min)
.
Absolute VO2peak (L/min)
832
30 25 20 15 10 5 n = 171 FES-cycling
n = 35 FES-hybrid exercise
n = 11 FES-rowing . Fig. 2. Average relative peak oxygen consumption (VO2peak) reported in the literature for functional electrical stimulation (FES)-cycling (12 studies, 171 observations), FES-hybrid exercise (3 studies, 35 observations) and FES-rowing (2 studies, 11 observations). Grey columns represent average of all included studies, black lines represent the range in reported average values.
Sports Med 2008; 38 (10)
. VO2 in FES-Exercise for Spinal Cord Injury
. although the VO2 during FES-rowing was significantly higher. This suggests that FES-rowing is well accepted and can be sustained for prolonged periods of time, although further research is needed to confirm these observations. Moreover, similar data should also be collected when comparing FES-rowing with other FES-exercise modalities. 4.3 Cardio-Respiratory Training Effects of FES-Exercise
Long-term training with FES-exercise results in . considerable increases in VO2peak. FES-rowing training (1 study, n = 6) results in an 11% increase . in VO2peak,[24,57] which is comparable to the 12% increase seen after FES-hybrid exercise training (3 studies, n = 26).[21,22,40] However, the in. crease in VO2peak after FES-cycling training is considerably higher. 11 FES-cycling .studies reported an average increase of 28% in VO2peak (n = 101).[21,22,27,30,32,33,35-39] This difference in training response could be explained by differences in subject characteristics; 42% of the subjects in FES-cycling training studies were tetraplegic, while in the FES-rowing studies, only 18% were tetraplegic. A similar trend is visible in the FES-hybrid exercise subjects, although there are only data from eight subjects. Tetraplegics are more likely to have a low aerobic capacity before training[58] and the FES-activated muscle mass is large in comparison to their voluntarily controlled muscle. mass. Moreover, a certain absolute increase in VO2peak represents a large percentage of their low pre-train. ing VO2. This implies that FES-exercise training could be a very effective cardiovascular training for tetraplegics. A third possible reason for the differ. ence in VO2 increases after training could be that the pre-training levels of fitness in the FES-cycling group were lower than in the FES-hybrid exercise or FES-rowing groups. The higher intensity during whole-body exercise might be more attractive to those who are fitter, while less fit individuals might prefer the more passive FES-cycling. . It is noteworthy, however, that post-training VO2 values in FES-cycling studies remain well below pre-training values of FES-hybrid exercise and FES-rowing studies. This confirms the findings from Krauss et al.[21] and Mutton et al.[22] ª 2008 Adis Data Information BV. All rights reserved.
833
. who reported additional increases in VO2peak with FES-hybrid exercise training after an FES-cycling training period. This suggests that superior levels of cardio-respiratory fitness can be achieved with whole-body FES-exercise. 4.4 Potential Health Benefits of FES-Exercise Training
From studies in the general population, it is known that superior health benefits of physical activity are achieved when physical activity programmes include exercises exceeding intensities of 21 mL/kg/min (6 MET [metabolic equivalent]) and total exercise volume exceeds 1200–2200 kcal/ week.[1-3] Furthermore, dose-response relationships that favour high-intensity and high-volume exercise training have been identified.[1,3] Although similar data are not yet available in the SCI population, it seems reasonable to adopt the able-bodied recommendations. The results of this review imply that FES-rowing and FES-hybrid exercise would be the preferred modalities if optimal reduction in the risk for obesity, cardiovascular disease and type 2 . diabetes is to be achieved. The average VO2sub-peak reported during FES-hybrid exercise (18.3 mL/ kg/min) and FES-rowing (18.8 mL/kg/min) are close to the recommended 21 mL/kg/min, while the intensity during FES-cycling (13.8 mL/kg/min) is insufficient. Furthermore, the high intensities seen during FES-rowing and FES-hybrid exercise are a time-effective method of achieving large exercise volumes. FES-rowing or FES-hybrid exercise training results in a 33% higher energy expenditure than FES-cycling training over the same time period. Such a time saving will be significant advantage for many individuals. It is, however, not unthinkable that some health benefits can be obtained by exercising at intensities below 6 METs. The results of a pilot study by Olenik et al.[59] suggest that FES-rowing carries one additional advantage. They recorded electromyographic activity in the muscle around the shoulder during rowing, backwards wheeling and a special retractor exercise, and concluded that rowing is as effective as the special retractor exercise in recruiting the retractor muscle in the shoulder. Since retractor-protractor imbalances have been Sports Med 2008; 38 (10)
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834
suggested as a key element in the aetiology of shoulder complaints in long-term wheelchair users,[14] rowing or other pulling exercises might be the preferred exercise modality.[59,60] The high-intensity and high-volume exercise programmes that give superior fitness and health benefits might cause compliance problems in some users. It would therefore be desirable to explore strategies to stimulate training compliance. Various options have been explored. Outdoor training: FES-tricycles and FEShybrid exercise systems have been used on the road instead of stationary ergometers.[61] Sport competitions: in 2006, an FES sports day was organized in the UK, during which both FES-cycling and FES-rowing competitions were organized. Moreover, FES-rowing has been included in the British Indoor Rowing Championships since 2004, where FES-rowers compete with able-bodied rowers on an equal basis. Competition provides a goal for training, which provides some with the motivation to train harder and for longer.[54] Virtual reality: computer interface software and hardware can add an extra dimension to training on ergometers, either via Internet competitions (e.g. e-Row by Concept 2 Inc., Morrisville, VT, USA) or simulated races (e.g. the virtual reality systems by Tacx bv, Wassenaar, the Netherlands). The full potential of FES-exercise and associated technology is still to be investigated. Given the high prevalence of physical inactivity associated conditions in the SCI population and the theoretical superior benefits of FES-exercise, such research is highly relevant. If the superior health benefits of higher intensity exercises in the able-bodied are also valid in the SCI population, then the results of this review suggest that FES-rowing and FES-hybrid exercise are the preferred exercise modalities for future studies on the health benefits of FES-exercise. 4.5 Comparison with Upper Body Exercise
Upper body exercises such as arm cranking and wheelchair propulsion are more widely available than FES-exercises. Since FES-exercise often requires special equipment and supervision, the costs ª 2008 Adis Data Information BV. All rights reserved.
and efforts in setting up and running an FESexercise programme can be more substantial than upper body exercises. Any potential benefits of FES-exercise would therefore have to outweigh these costs and efforts. Although upper body exercises were not included in the search strategy of this paper, others have published comprehensive reviews on upper body exercise in SCI. Haisma et . al.[58] conducted a systematic review on VO2peak in SCI during wheelchair exercise tests and arm cranking or hand cycling. In tetraplegia, they reported a weighted mean of 0.89 L/min for wheelchair pushing and 0.87 L/min for arm cranking. In paraplegia, this wasconsiderably higher: 2.10 L/min and 1.51 L/min, respectively. Since individual patient data were not available for many of the studies includedin the present review, no separate values for tetraplegia . and paraplegia can be calculated. The average VO2peak in FES-cycling was 1.05 L/min, which was derived from a sample consisting of 41% tetraplegics. There were fewer tetraplegics in the FES-rowing and FES-hybrid exercise group (1.98 L/min, 18% tetraplegics and 1.78 L/min, 6% tetraplegics, respectively). Based on the paraplegia : tetraplegia ratio, a weighted mean for the . VO2peak during wheelchair exercise and arm cranking can be derived (table III). This shows . that wheelchair propulsion gives the highest VO2peak values, followed by FES-rowing and FES-hybrid . exercise. It should be noted, however, that these VO2 values were achieved in different subject groups. There are a limited number . of studies that show a direct comparison of VO2peak responses during these exercise modalities. As mentioned in section . 1.2, Verellen et al.[26] found that VO2peak during FES-cycling was significantly lower than during FES-rowing, FES-hybrid exercise or arm cranking. . The latter resulted in considerably lower VO2peak than FES-rowing or FES-hybrid exercise, but this did not reach statistical significance. FES-hybrid exercise and FES-cycling have also been . compared in other studies, which report higher VO2peak values for FES-hybrid exercise.[21,22,51] None of these studies included a wheelchair exercise modality and . therefore the higher VO2peak values during this modality need to be confirmed in future studies. There are, however, concerns regarding the long-term effects of the use of manual wheelchairs. Sports Med 2008; 38 (10)
. VO2 in FES-Exercise for Spinal Cord Injury
835
. Table III. Peak oxygen consumption (VO2peak; L/min) in a group of persons with spinal cord injury during five different exercise modalities Exercise modality
Wheelchair propulsion Arm cranking
Characteristics of subject population 100% tetra
100% para
41% tetra, 59% para
18% tetra, 78% para
6% tetra, 94% para
0.89a
2.10a
1.60b
1.80b
2.03b
a
a
b
b
1.47b
0.87
1.51
1.25
FES-cycling
1.33
1.05
FES-hybrid exercise
1.78
FES-rowing 1.98 . a VO2peak data during wheelchair propulsion and arm cranking as reported in the review by Haisma et al.[58]
b
Calculated by reviewers based on para and tetra data from Haisma et al.[58]
FES = functional electrical stimulation; para = paraplegic; tetra = tetraplegic.
A large proportion of manual wheelchair users report chronic overuse in the shoulder, elbow and/or wrist. One of the suggested mechanisms behind the high prevalence of shoulder complaints is the chronic unbalanced loading of the shoulder during wheelchair propulsion. As a result of the pushing motion, shoulder protractor activity exceeds activity of the shoulder retractors and this may result in musculoskeletal imbalances around the shoulder joint. Secondly, wheelchair propulsion is known to increase pain in half the SCI population.[62] Both these findings suggest that wheelchair exercise may not be the most suitable exercise modality. However, some have reported a lower prevalence of shoulder pain amongst wheelchair athletes than the general wheelchair population, although this could also be explained by selection bias (‘athletes with pain retire’) or reporting bias (‘athletes are tough and complain less’). The exact relationship between wheelchair exercise and musculoskeletal overuse of the upper extremities is still a topic of research, but at this point in time, it seems reasonable to use wheelchair exercise in moderation and explore alternative cardiovascular exercise modalities. Furthermore, FES-exercise has a range of unique benefits that cannot be achieved with upper body exercise. Long-term electrical stimulation of paralysed body parts results in considerable morphological and physiological changes in the peripheral tissue, for example, muscle hypertrophy, improved blood circulation and improved colouration of the skin. A comprehensive review of these local changes has been published elsewhere.[15,25] ª 2008 Adis Data Information BV. All rights reserved.
4.6 Limitations of the Review and Included Studies
Many of the studies included in this review did not . report all parameters that may have influenced VO2 values. Bodyweight is an important confounder, and some . studies ignored this by only presenting absolute VO . 2 values (in L/min). In a number of cases, relative VO2 (in mL/kg/min) could be calculated based on reported bodyweight, and these have been marked in the tables. Other subject characteristics, such as gender, age, time since injury, duration of FES use, level of lesion and completeness of lesion . may also have had an impact on the reported VO2 values. Gender and level of lesion have most often been reported and these have been discussed in this review. The other subject characteristics have only been reported in a minority of the studies. Of particular interest is the period the subjects have used FES before the tests. The paralysed muscles of persons with SCI are often greatly deconditioned, and a certain FES training period is required to build up power and stamina. Any test in this period of inadequate power and stamina would be greatly impaired due to muscular fatigue. In general, level of fitness (for example, obtained from non-FES exercise regimes) may have influenced the results. This may also have resulted in selection bias, especially in the FES-hybrid exercise and FES-rowing studies, since fit individuals may prefer these exercise modalities. Furthermore, at least one study that reported on FES-hybrid exercise[21] used an exercise regime in which an FES-cycling programme preceded the
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FES-hybrid exercise regime. The training effect from the FES-cycling programme may therefore explain some of the higher values reported with FES-hybrid exercise. Testing protocol . could also have had an impact on the reported VO2 data. However, to the authors’ knowledge, no consensus or critique has been published on the validity and reliability of existing . VO2peak testing protocols in FES-cycling, FES-hybrid exercise or FES-rowing. In the absence of such studies, the authors decided not to consider testing protocol, but future work should address this, especially since the results of this review indicated that existing peak-test protocols might not be suitable. Although the numberof. observations might limit . generalization of some VO2peak and VO2sub-peak results, the findings are consistent. Moreover, . direct comparisons confirm the differences in VO2 between FES-cycling, FES-hybrid exercise and FES-rowing.[21,22,26] The small number of FESrowing observations is supported by unpublished observations in seven SCI subjects undergoing 12 weeks of training. Before training, the average . VO2peak was 1.53 – 0.15 L/min (21.0 – 2.9 mL/kg/ min), which increased by 10% after training to 1.68 – 0.20 L/min (22.9 – 2.4 mL/kg/min).[57] More research is needed though to confirm these findings. Finally, as indicated in the introduction, the thresholds and dose-response relationships for exercise and health that have been identified in the able-bodied population, have not been validated for the SCI population. It is not unthinkable that thresholds are lower for persons with SCI, who are on the lower end of the fitness spectrum. However, if that is the case, aiming for higher values would not necessarily be a negative thing. Two small exercise studies in SCI reported that a higher exercise intensity resulted in significantly larger improvements in lipid profile than a similar exercise programme at a lower intensity.[1,7,8] Although these studies do not determine the minimal exercise threshold, they do suggest that higher exercise intensities are preferred if optimal health benefits are to be achieved. 4.7 Recommendations for Future Research
. Comparing VO2peak values between studies has been impaired by differences in testing protocols. Although most studies use an incremental exercise protocol, other uncontrolled parameters may ª 2008 Adis Data Information BV. All rights reserved.
have influenced the results; for example, stimulation parameters. The fact that the reported subpeak values are a high proportion of the reported peak values may suggest that the reported peak values were not the true peak values. This suggests . that there is a need for a reliable and valid VO2 testing protocol in FES-exercise and future research should address this. Such a testing protocol should try to minimize the effect of muscular fatigue, since this is often a limiting factor in FESexercise, especially in novice FES users. Secondly, future research should compare the various FES-exercise modalities in a single subject group. A limited number of studies have done this, but larger scale studies are needed in order to increase the validity . of the comparisons. Furthermore, VO2 values should be reported both in absolute values (L/min) and relative values (mL/kg/min). Bodyweight can be a strong confounder and it is therefore preferable to control for . bodyweight when reporting VO2. More research is also needed to explore the potential health benefits and risks associated with the higher intensities seen in FES-hybrid exercise and FES-rowing.
5. Conclusion This review shows that persons with SCI can . achieve a VO2peak of 1.98 L/min (24.1 mL/kg/min) during FES-rowing, 1.78 L/min (26.5 mL/kg/min) during FES-hybrid exercise and 1.05 L/min (14.3 mL/kg/min) during FES-cycling. FES-rowing and FES-hybrid exercise result in considerably higher metabolic demands than FES-cycling, which could be important if high exercise intensities and large exercise volumes are to be achieved. Although the number of observations for FES-rowing and FES-hybrid exercise are limited, the findings are consistent with direct comparisons between these exercise modalities. The results indicate that FES-rowing and FES-hybrid exercise would be the preferred modalities if the thresholds in exercise intensity (21 mL/kg/min) that were identified in able-bodied subjects are also applicable to the SCI population. However, further improvements in technology or training programmes would be welcomed, since the reported . VO2sub-peak values are around 18 mL/kg/min. Sports Med 2008; 38 (10)
. VO2 in FES-Exercise for Spinal Cord Injury
However, these averages are taken from both pre- and post-training values and the large in. creases in VO2peak after FES-exercise training (FES-cycling: þ28%, FES-hybrid exercise: þ12%, FES-rowing: þ11%) imply that there is considerable merit in using FES-rowing or FES-hybrid exercise training to achieve the recommended exercise intensity. Moreover, this would be a timeeffective method of achieving large exercise volumes. FES-rowing has the additional benefit that it could restore muscular balances in the shoulder, which might prevent shoulder overuse injuries. This review shows that FES-exercise has great potential to improve fitness and health in persons with SCI. The fitness benefits have been shown, but more research is needed to fully map the health benefits. Results from studies in able-bodied subjects suggest that FES-rowing and FES-hybrid exercise would be of most value because of the high . VO2 values seen during these exercises. Acknowledgements The Henry Smith Charity (UK) provided funding for a post-doctoral position for D.M. Hettinga. Neither the authors nor the funding body have any conflicts of interest in relation to the content of this review. B.J. Andrews received grants from Inspire (UK) and The Henry Smith Charity (UK) for FES-rowing research projects.
References 1. Tanasescu M, Leitzmann MF, Rimm EB, et al. Exercise type and intensity in relation to coronary heart disease in men. JAMA 2002; 288: 1994-2000 2. Saris WH, Blair SN, van Baak MA, et al. How much physical activity is enough to prevent unhealthy weight gain? Outcome of the IASO 1st Stock Conference and consensus statement. Obes Rev 2003; 4: 101-14 3. Durstine JL, Grandjean PW, Davis PG, et al. Blood lipid and lipoprotein adaptations to exercise: a quantitative analysis. Sports Med 2001; 31: 1033-62 4. Mayer-Davis EJ, D’Agostino Jr R, Karter AJ, et al. Intensity and amount of physical activity in relation to insulin sensitivity: the Insulin Resistance Atherosclerosis Study. JAMA 1998; 279: 669-74 5. Brenes G, Dearwater S, Shapera R, et al. High density lipoprotein cholesterol concentrations in physically active and sedentary spinal cord injured patients. Arch Phys Med Rehabil 1986; 67: 445-50 6. Dallmeijer AJ, Hopman MT, van der Woude LH. Lipid, lipoprotein, and apolipoprotein profiles in active and sedentary men with tetraplegia. Arch Phys Med Rehabil 1997; 78: 1173-6
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7. Hooker SP, Wells CL. Effects of low- and moderate-intensity training in spinal cord-injured persons. Med Sci Sports Exerc 1989; 21: 18-22 8. de Groot PC, Hjeltnes N, Heijboer AC, et al. Effect of training intensity on physical capacity, lipid profile and insulin sensitivity in early rehabilitation of spinal cord injured individuals. Spinal Cord 2003; 41: 673-9 9. Bauman WA, Spungen AM. Metabolic changes in persons after spinal cord injury. Phys Med Rehabil Clin N Am 2000; 11: 109-40 10. Bauman WA, Spungen AM, Raza M, et al. Coronary artery disease: metabolic risk factors and latent disease in individuals with paraplegia. Mt Sinai J Med 1992; 59: 163-8 11. Bauman WA, Spungen AM. Disorders of carbohydrate and lipid metabolism in veterans with paraplegia or quadriplegia: a model of premature aging. Metabolism 1994; 43: 749-56 12. Dela F, Mohr T, Jensen CM, et al. Cardiovascular control during exercise: insights from spinal cord-injured humans. Circulation 2003; 107: 2127-33 13. Gironda RJ, Clark ME, Neugaard B, et al. Upper limb pain in a national sample of veterans with paraplegia. J Spinal Cord Med 2004; 27: 120-7 14. Burnham RS, May L, Nelson E, et al. Shoulder pain in wheelchair athletes. The role of muscle imbalance. Am J Sports Med 1993; 21: 238-42 15. Jacobs PL, Nash MS. Modes, benefits, and risks of voluntary an electrically induced exercise in persons with spinal cord injury. J Spinal Cord Med 2001; 24: 10-8 16. Phillips W, Burkett LN, Munro R, et al. Relative changes in blood flow with functional electrical stimulation during exercise of the paralyzed lower limbs. Paraplegia 1995; 33: 90-3 17. Phillips WT, Burkett LN. Augmented upper body contribution to oxygen uptake during upper body exercise with concurrent leg functional electrical stimulation in persons with spinal cord injury. Spinal Cord 1998; 36: 750-5 18. Gaffney T. Jerrold Petrofsky: Biomedical pioneer. Chicago (IL): Childrens Press, 1984 19. Petrofsky JS, Heaton HH, Phillips CA. Outdoor bicycle for exercise in paraplegics and quadriplegics. J Biomech Eng 1983; 5: 292-6 20. Petrofsky JS, Phillips CA. The use of functional electrical stimulation for rehabilitation of spinal cord injured patients. Cent Nerv Syst Trauma 1984; 1: 57-74 21. Krauss JC, Robergs RA, Depaepe JL, et al. Effects of electrical stimulation and upper body training after spinal cord injury. Med Sci Sports Exerc 1993; 25: 1054-61 22. Mutton DL, Scremin AM, Barstow TJ, et al. Physiologic responses during functional electrical stimulation leg cycling and hybrid exercise in spinal cord injured subjects. Arch Phys Med Rehabil 1997; 78: 712-8 23. Davoodi R, Andrews BJ, Wheeler GD, et al. Development of an indoor rowing machine with manual FES controller for total body exercise in paraplegia. IEEE Trans Neural Syst Rehabil Eng 2002; 10: 197-203 24. Wheeler GD, Andrews B, Lederer R, et al. Functional electric stimulation-assisted rowing: increasing cardiovascular fitness through functional electric stimulation rowing training in persons with spinal cord injury. Arch Phys Med Rehabil 2002; 83: 1093-9 25. Andrews BJ, Wheeler GD. Functional and therapeutic benefits of electrical stimulation after spinal injury. Curr Opin Neurol 1995; 8: 461-6 26. Verellen J, Vanlanderwijck Y, Andrews B, et al. Peak physical work capacity during arm ergometry, FES-cycling, and two hybrid exercise conditions in spinal cord injured. Disabil Rehabil Assist Tech 2007; 2: 127-32
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27. Barstow TJ, Scremin AM, Mutton DL, et al. Changes in gas exchange kinetics with training in patients with spinal cord injury. Med Sci Sports Exerc 1996; 28: 1221-8 28. Barstow TJ, Scremin AM, Mutton DL, et al. Peak and kinetic cardiorespiratory responses during arm and leg exercise in patients with spinal cord injury. Spinal Cord 2000; 38: 340-5 29. Bhambhani Y, Tuchak C, Burnham R, et al. Quadriceps muscle deoxygenation during functional electrical stimulation in adults with spinal cord injury. Spinal Cord 2000; 38: 630-8 30. Burke-Gurney A, Robergss RA, Aisenbrey J, et al. Detraining from total body exercise ergometry in individuals with spinal cord injury. Spinal Cord 1998; 36: 782-9 31. Figoni SF, Rodgers MM, Glaser RM, et al. Physiologic responses of paraplegics and quadriplegics to passive and active leg cycle ergometry. J Am Paraplegia Soc 1990; 13: 33-9 32. Goss FL, McDermott A, Robertson RJ. Changes in peak oxygen uptake following computerized functional electrical stimulation in the spinal cord injured. Res Q Exerc Sport 1992; 63: 76-9 33. Hjeltnes N, Aksnes AK, Birkeland KI, et al. Improved body composition after 8 wk of electrically stimulated leg cycling in tetraplegic patients. Am J Physiol 1997; 273: R1072-9 34. Holme E, Mohr T, Kjaer M, et al. Temperature responses to electrically induced cycling in spinal cord injured persons. Med Sci Sports Exerc 2001; 33: 431-5 35. Hooker SP, Figoni SF, Rodgers MM, et al. Physiologic effects of electrical stimulation leg cycle exercise training in spinal cord injured persons. Arch Phys Med Rehabil 1992; 73: 470-6 36. Hooker SP, Scremin AM, Mutton DL, et al. Peak and submaximal physiologic responses following electrical stimulation leg cycle ergometer training. J Rehabil Res Dev 1995; 32: 361-6 37. Kjaer M, Mohr T, Biering-Sorensen F, et al. Muscle enzyme adaptation to training and tapering-off in spinal-cordinjured humans. Eur J Appl Physiol 2001; 84: 482-6 38. Mohr T, Andersen JL, Biering-Sorensen F, et al. Long-term adaptation to electrically induced cycle training in severe spinal cord injured individuals. Spinal Cord 1997; 35: 1-16 39. Pollack SF, Axen K, Spielholz N, et al. Aerobic training effects of electrically induced lower extremity exercises in spinal cord injured people. Arch Phys Med Rehabil 1989; 70: 214-9 40. Heesterbeek PJ, Berkelmans HW, Thijssen DH, et al. Increased physical fitness after 4-week training on a new hybrid FES-cycle in persons with spinal cord injury. Technol Disabil 2005; 17: 103-10 41. Raymond J, Davis GM, Climstein M, et al. Cardiorespiratory responses to arm cranking and electrical stimulation leg cycling in people with paraplegia. Med Sci Sports Exerc 1999; 31: 822-8 42. Arnold PB, McVery PP, Farrell WJ, et al. Functional electric stimulation: its efficacy and safety in improving pulmonary function and musculoskeletal fitness. Arch Phys Med Rehabil 1992; 73: 665-8 43. Barstow TJ, Scremin AM, Mutton DL, et al. Gas exchange kinetics during functional electrical stimulation in subjects with spinal cord injury. Med Sci Sports Exerc 1995; 27: 1284-91 44. Faghri PD, Glaser RM, Figoni SF. Functional electrical stimulation leg cycle ergometer exercise: training effects on cardiorespiratory responses of spinal cord injured subjects at rest and during submaximal exercise. Arch Phys Med Rehabil 1992; 73: 1085-93 45. Kjaer M, Pott F, Mohr T, et al. Heart rate during exercise with leg vascular occlusion in spinal cord-injured humans. J Appl Physiol 1999; 86: 806-11
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46. Mohr T, Van Soeren M, Graham TE, et al. Caffeine ingestion and metabolic responses of tetraplegic humans during electrical cycling. J Appl Physiol 1998; 85: 979-85 47. Nash MS, Bilsker MS, Kearney HM, et al. Effects of electrically-stimulated exercise and passive motion on echocardiographically-derived wall motion and cardiodynamic function in tetraplegic persons. Paraplegia 1995; 33: 80-9 48. Petrofsky JS, Stacy R. The effect of training on endurance and the cardiovascular responses of individuals with paraplegia during dynamic exercise induced by functional electrical stimulation. Eur J Appl Physiol Occup Physiol 1992; 64: 487-92 49. Raymond J, Davis GM, van der Plas M. Cardiovascular responses during submaximal electrical stimulation-induced leg cycling in individuals with paraplegia. Clin Physiol Funct Imaging 2002; 22: 92-8 50. Theisen D, Fornusek C, Raymond J, et al. External power output changes during prolonged cycling with electrical stimulation. J Rehabil Med 2002; 34: 171-5 51. Hooker SP, Figoni SF, Rodgers MM, et al. Metabolic and hemodynamic responses to concurrent voluntary arm crank and electrical stimulation leg cycle exercise in quadriplegics. J Rehabil Res Dev 1992; 29: 1-11 52. Raymond J, Davis GM, Fahey A, et al. Oxygen uptake and heart rate responses during arm vs combined arm/ electrically stimulated leg exercise in people with paraplegia. Spinal Cord 1997; 35: 680-5 53. Laskin JJ, Ashley EA, Olenik LM, et al. Electrical stimulation-assisted rowing exercise in spinal cord injured people: a pilot study. Paraplegia 1993; 31: 534-41 54. Hettinga DM, Andrews BJ. The feasibility of FES indoor rowing for high-energy training and sport. Neuromodulation 2007; 10: 291-7 55. Hainaut K, Duchateau J. Neuromuscular electrical stimulation and voluntary exercise. Sports Med 1992; 14: 100-13 56. Mizrahi J. Fatigue in muscles activated by functional electrical stimulation. Crit Rev Phys Rehabil Med 1997; 9: 93-129 57. Hettinga DM, Andrews BJ, Wheeler GD, et al. Functional electrical stimulation assisted rowing for persons with spinal cord injury; can health benefits be achieved? Proceedings of VISTA 2003 conference; 2003 Sep 19-21; Bolnass 58. Haisma JA, Van der Woude LHV, Stam HJ, et al. Physical capacity in wheelchair-dependent persons with a spinal cord injury: a critical review of the literature. Spinal Cord 2006; 44: 642-52 59. Olenik LM, Laskin JJ, Burnham R, et al. Efficacy of rowing, backward wheeling and isolated scapular retractor exercise as remedial strength activities for wheelchair users: application of electromyography. Paraplegia 1995; 33: 148-52 60. Jacobs PL. Pulling shoulder pain away. Sports ‘n Spokes 2004; 30: 38-42 61. Perkins TA, de NDN, Hatcher NA, et al. Control of legpowered paraplegic cycling using stimulation of the lumbo-sacral anterior spinal nerve roots. IEEE Trans Neural Syst Rehabil Eng 2002; 10: 158-64 62. Nichols PJ, Norman PA, Ennis JR. Wheelchair user’s shoulder? Shoulder pain in patients with spinal cord lesions. Scand J Rehabil Med 1979; 11: 29-32
Correspondence: Prof. Brian J. Andrews, Nuffield Department of Surgery, John Radcliffe Hospital, Headley Way, Headington, Oxford, OX3 9DU, UK. E-mail:
[email protected]
Sports Med 2008; 38 (10)
Sports Med 2008; 38 (10): 839-862 0112-1642/08/0010-0839/$48.00/0
REVIEW ARTICLE
ª 2008 Adis Data Information BV. All rights reserved.
The Role of Motion Analysis in Elite Soccer Contemporary Performance Measurement Techniques and Work Rate Data Christopher Carling,1 Jonathan Bloomfield,2 Lee Nelsen3 and Thomas Reilly4 1 LOSC Lille Me´tropole Football Club, Centre de Formation, Centre de Formation, Domain de Luchin, Camphin-en-Pe´ve`le, France 2 Sports Institute of Northern Ireland, University of Ulster, Jordanstown, Northern Ireland, UK 3 School of Sport and Exercise Sciences, Loughborough University, Loughborough, Leicestershire, UK 4 Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Henry Cotton Campus, Liverpool, UK
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Contemporary Techniques for Work Rate Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Individual Player Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Multiple Player Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Main Issues in Contemporary Motion Analysis Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Validity, Objectivity and Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Interpretation of Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Contemporary Motion Analysis Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Analysis of Data on Overall Work Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Categories of Movements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Determining Positional Demands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Use of Motion Analysis in Studies of Fatigue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Other Uses of Motion Analysis Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
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The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game, especially due to the increased physical demands of match-play. The monitoring of players’ work rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university-based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players’ physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role that motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research
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conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, and identify practical implications of the established body of knowledge, while highlighting areas that require further exploration.
A significant body of research into the host of factors contributing to optimal performance in sport has emerged over the past two decades.[1] This increased research activity has been particularly evident in soccer (association football), where the importance of scientific research and applied work has become increasingly accepted in the professional game.[2] Over this period, comprehensive reviews have been published on the physiology,[3,4] psychology,[1,5] biomechanics[6] and interdisciplinary[7] aspects of soccer. This growing acceptance of sports science is unsurprising considering the performance-enhancing role that it can offer elite soccer coaches continually searching for a competitive edge against rival teams.[8] Among the traditional sport science disciplines, exercise physiology has arguably had the greatest impact upon practices within professional soccer. The optimization of physical fitness is now an integral facet of player and team preparation. The physiological demands of contemporary professional soccer implicate an increased work rate, a higher frequency of competition, and as a consequence, players are obliged to work harder than in previous decades.[9,10] The monitoring of players’ work rate profiles during competition was originally achieved using manual video-based motion analysis techniques such as that developed by Reilly and Thomas.[11] The employment of such methods elicited essential scientific observations, but the perceived complexity and consumption of time required for coding, analysing and interpreting the output formed barriers to their adoption by performance analysts.[12] The original techniques were also restricted to the analysis of a single player, so therefore limited to university-based research projects. Over the past decade, technological advances have included the introduction of increasingly sophisticated motion analysis systems that are now being used in elite soccer. These systems enable the ª 2008 Adis Data Information BV. All rights reserved.
simultaneous analysis of all players to be completed in a relatively short period, and provide a valuable pool of data that can inform and influence the daily practices of coaches. The use of these advanced approaches furthers our understanding of positionspecific work rate profiles of soccer players and their fitness requirements, the intensities of discrete activities during match-play and the occurrence of a reduced work rate among players.[13,14] Moreover, these contemporary methods employed by elite clubs can be used to make objective decisions for structuring the conditioning elements of training and subsequent match preparation. In recognition of the important role that motion analysis now plays as a tool for measuring the physical performance of soccer players, we begin by critically appraising the various methods of motion analysis available to researchers and practitioners in soccer. Throughout, we highlight that many of the latest computerized systems are not only logistically practical, but also offer a greater breadth of analysis compared with the more traditional labour-intensive methods. However, many of these systems still require scientific validation to ensure that data derived from these methods are both accurate and reliable. A presentation and critical appraisal of various validation protocols used for assessing contemporary motion analysis technologies is provided in an attempt to prompt further research into this area of investigation. Also considered are various issues concerning the interpretation of the data obtained through techniques of motion analysis. In the remainder of this review, motion analysis research into work rate profiles within competitive games, exercise patterns, positional demands, fatigue and other uses, is considered. Collectively, this review should serve to increase awareness of practitioners and researchers concerning the various motion analysis systems and the body of accumulated knowledge acquired using these approaches, whilst identifying areas that require further exploration. Sports Med 2008; 38 (10)
Motion Analysis in Elite Soccer
1. Contemporary Techniques for Work Rate Analysis 1.1 Individual Player Analysis
Motion analysis has been applied for over 30 years to the study of work rates in professional soccer, since the classical study of Reilly and Thomas.[11] Research studies undertaken in the last 5 years by Scandinavian and Italian researchers[15-19] on top-level soccer have incorporated similar approaches to that employed over a decade earlier by Bangsbo and co-workers.[20] This original method involved the positioning of video cameras near the side of the pitch, at the level of the midfield line, at a height of approximately 15 m and at a distance of 30–40 m from the touchline. Each camera was used to film a separate player. After the game, the subjects were videotaped for reference purposes whilst performing specific activities (from walking to sprinting) in order to provide calibration values. The video tapes were played back on a television monitor and coded for various match activities. The duration of each activitywas recorded, total time summed and frequency of activity calculated according to separate time blocks. The distance covered at each activity within each time block was the product of meanvelocity and totaltime spent in the activity. The total distance covered during a match was calculated as the sum of the distances covered during each individual type of locomotor activity. The main technological advancement evident in subsequent studies has been the employment of better quality cameras and more advanced input coding methods as a result of contemporary computer software. To this end, Bloomfield et al.[21] used the ‘PlayerCam’ facility (Sky Sports Interactive Service, British Sky Broadcasting Group, UK) to provide high-quality close-up video footage focusing on a single player’s movements and actions. The footage was digitized and synchronized for manual coding using the Noldus Observer 5.0 Video-Pro behavioural analysis system,[22] which in turn automatically calculated the time spent in the defined movement activities. These particular video-based methods used for manually measuring work rates have generally demonstrated, in the studies that have been reported to use them, high levels of reliability, objectivity and validity.[8] For example, a previous report that ª 2008 Adis Data Information BV. All rights reserved.
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employed these methods stated that no systematic differences were reported in a test-retest analysis of a match, and the mean intraindividual difference in total distance covered was less than 0.2 km (coefficient of variation [CV] = 1%).[15] Nevertheless, human error through inaccurate data entry is possible due to the subjective nature of human movement recognition, variable observer reaction to events being performed by the player under scrutiny, and different interpretations of performance indicators relating to work rate and movement by different observers.[23] In addition, the methods previously described are restricted to the filming and analysis of a single player per camera. Video-based motion analysis may also be subject to errors due to changes in gait during game movements,[24] and provides only low spatial and temporal resolutions.[25] Furthermore, these techniques do not allow real-time analysis and are extremely labour-intensive in terms of the capture and analysis of data. In this respect, the detailed manual methodology used by Bloomfield et al.[26] to code manually and determine the physical demands of English Premier League football was described by the authors as extremely time-consuming and laborious. This criticism applied even for the collection of data from only 5 minutes of match footage because of the frequent changes of movement type, direction and/or intensity. A total of 1563 ‘purposeful movement’ passages were observed for 55 players during 15-minute periods of Premier League soccer, which involved 23 487 changes in movement, direction, perceived intensity or individual soccer-specific events (e.g. pass, dribble, shoot). Players performed a mean of 28.4 – 4.3 passages of purposeful movement for each 15-minute period of the match at a mean duration of 13.1 – 3.2 seconds. These figures equate toa mean of15.03changes inactivity for eachpassage at a rate of 0.87 per second. No significant differences were found between the amount of purposeful movement passages by match period or playing position, although strikers had a significantly shorter mean duration and frequency of passages lasting >15 seconds. Because of the level of detail in this manual-based time-motion analysis, the application and use of such methods of motion analysis are generally restricted to academic research projects because the intense competitive schedules of elite soccer clubs require data to be available usually within 24–36 hours post-match. The difficulties Sports Med 2008; 38 (10)
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encountered in manually coding movements may lead some researchers to analyse a single selected period of action per player per game. Attempts can then be made to extrapolate the data from these periods to a projection for the entire match. However, incomplete recordings are limited in their ability to provide detailed individual work rates, as the work rate pattern is highly variable throughout a game and is therefore not so easily predictable.[27] As technology has advanced, time-motion analysis has begun to incorporate electronic devices, mathematical modelling procedures for automatic tracking, sophisticated computer processes and satellite tracking. An overview of contemporary systems used to analyse workload in soccer is given in table I. Many contemporary approaches are based essentially on an original method designed by Ohashi et al.,[40] which employed the calculation of players’ position and speed through trigonometric techniques. For example, the motion characteristics of elite Japanese soccer players have been recently measured throughout a game’s entirety using a triangular surveying method.[33] This method entailed recording the player’s movement as angular changes, which were measured by two potentiometers linked to cameras mounted outside and overlooking the field of play. Coordinates for
the player were calculated using the angular data from the cameras and were monitored every 0.5 seconds. The distance between two consecutive coordinates was calculated continuously to obtain the total distance covered. The major limitation of this particular methodology was that it did not allow simultaneous analyses of more than one player.[8] Limiting the analysis of the activity profile to one player per game does not allow comparisons to be drawn between the concomitant work rate profiles of team mates or those of opposing players, and can limit full understanding of the tactical importance of work rate.[27] A further technological advancement in this field has been the development of the system ‘Trakperformance’ (Sportstec, Warriewood, NSW, Australia), which provides a means of mechanically following a single player using a conventional computer pen and commercially available drawing tablet on a scaled version of the specific playing field.[24,38] This method is an improvement from the classical cartographic approach previously used by Japanese researchers where movements of soccer players were traced onto a scaled map of the pitch presented on paper sheets.[41] The Trakperformance system functions by using ground markings around the pitch, which are employed as reference points for tracking the players. The
Table I. Contemporary systems and studies of their workings used to analyse work rate in contemporary elite soccer Company/institution (country)
System
System type
Website
References
Citech Holdings Pty Ltd (Australia)
Biotrainer
Electronic transmitter
http://www.citechholdings.com
28
Chukyo University (Japan)
Direct Linear Transformation
Automatic video tracking
INMOTIO Object Tracking BV (Netherlands)
LPM Soccer 3D
Electronic transmitter
http://www.abatec-ag.com
Feedback Sport (New Zealand)
Feedback Football
Automatic video tracking
http://www.feedbacksport.com
31
GPSports (Australia)
SPI Elite
GPS tracking
http://www.gpsports.com
24
Hiroshima College of Sciences (Japan)
Direct Linear Transformation
Automatic video tracking
National Defense Academy (Japan)
Triangular surveying
Triangular surveying
Noldus (Netherlands)
Observer Pro
Manual video coding
http://www.noldus.com
21,23,26
Performance Group International (UK)
DatatraX
Automatic video tracking
http://www.datatrax.tv
34
ProZone Holdings Ltd (UK)
ProZone
Automatic video tracking
http://www.pzfootball.co.uk
35
RealTrackFootball (Spain)
Real Track Football
GPS tracking
http://www.realtrackfutbol.com
36
Sport-Universal Process SA (France)
AMISCO Pro
Automatic video tracking
http://www.sport-universal.com
37
Sportstec (Australia)
TrakPerformance
Computer pen and tablet
http:// www.sportstecinternational.com
24,38
TRACAB (Sweden)
Tracab
Automatic video tracking
http://www.tracab.com
University of Campinus (Brazil)
Dvideo
Automatic video tracking
ª 2008 Adis Data Information BV. All rights reserved.
29 30
32 33
39 25
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miniaturized playing field is calibrated so that a given movement of the mouse or mouse-pen corresponds to the linear distance travelled by the player. This computerized system has demonstrated acceptable levels of accuracy and intra- and inter-observer reliability. For example, an error measurement level of 5% for player distances has been presented and a test of inter-observer reliability between three separate observers reported a Pearson’s correlation of r = 0.98 for total distance travelled.[38] A further advantage is that movements can also be tracked in real-time (although operator skill does need to be very high and a sustained training period is needed for familiarization with the technique) and cost is significantly reduced compared with other commercially available tracking systems. Finally, the portability of this system means it can be readily employed to analyse work rates of players within training contexts. 1.2 Multiple Player Analysis
Few systems have the ability to analyse all the players in a team throughout a whole match, tracking each player both on and off the ball.[42] The AMISCO Pro system developed in the late 1990s by Sport-Universal Process in collaboration with the French Football Federation was the first system to achieve the simultaneous analysis of the work rate of every player in a team throughout the entirety of a match.[37] This system measures on video the movements of every player, the referee and the ball by sampling activity up to 25 times per second during the whole game.[8,43] This process leads to the collection of around 4.5 million datapoints for position on the pitch as well as over 2000 ball touches per match. Along with the ProZone system,[35,44] its chief commercial European competitor, these pioneer multi-player video tracking systems based on state-of-the-art computer and video technology are currently the most comprehensive and widely used commercial tracking systems in professional European soccer. These systems provide a detailed analysis of each player’s work rates over the entire match, and create a 2-dimensional animated reconstruction of player movements together with an interactive graphical representation of all playing actions such as passes and duels.[45] ª 2008 Adis Data Information BV. All rights reserved.
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Video-based multi-player tracking systems such as AMISCO Pro and ProZone generally require the permanent installation of several cameras fixed in optimally calculated positions to cover the entire surface of play. This layout ensures that every player is captured on video, whatever the position and the moment in time. The number, position, orientation, zoom and field of vision of the cameras depend on factors such as the dimensions of the pitch and the structure of the stadium. The stadium and pitch are calibrated in terms of height, length and width and transformed into a 2-dimensional model to allow player positions (x, y coordinates) to be calculated from the camera sources. Complex trigonometry, propriety mathematical algorithms, image-object transformation methods for obtaining 2- or 3-dimensional space coordinates such as Direct Linear Transformation (DLT)[32] from video footage of soccer play, as well as various image processing and filtering techniques, can be used to identify each player’s location on the pitch. The individual’s movements can then be tracked on the video by computer software through either manual operation or automatic tracking processes, at every single moment of the game. The technology is facilitated by supportive information such as shirt colour, optical character recognition of shirt numbers and prediction of running patterns to help maintain accurate player identification and tracking. During set-play actions such as corners or free kicks, play can become compressed, so such supportive information may be required to help maintain accuracy in tracking individual players. For a further description of the workings of video-based player tracking, see Di Salvo et al.[35] and Barros et al.[25] Despite being largely computer automated, these pioneer tracking systems still require some manual input as well as continual verification by an operator to make sure that players are correctly tracked by the computer program. Automatic tracking may not always be possible because of changes in light quality as well as occlusions due to a crowd of players gathering in a small zone at one time. In this case, it becomes necessary for an operator to correct these mistakes manually. Nevertheless, the Dvideo system designed at the University of Campinus, Brazil, is reported to have a 95% automatic tracking rate.[25] However, this system uses a lower number of digital film images Sports Med 2008; 38 (10)
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per second (7.5 Hz) than other video tracking systems such as AMISCO Pro in order to reduce the amount of data to be processed. This footage would lower its capacity to measure in detail changes in running speed and direction. Work by Fernandes and Caixinha[46] has also shown when determining the positions of soccer player from digital video footage that a low frequency of images per second (2 Hz, for example) may lead to a higher rate of error when calculating distances covered.[46] A recent DLT-based video-tracking system used to analyse the work rates of professional Japanese players reportedly requires the use of a single digital camcorder, making it more cost effective compared with multi-camera systems.[29] However, it also employs a limited number of image frames per second (2 Hz) and requires manual frame-byframe analysis of play. Furthermore, no information is available on the time required to analyse physical performance using this system and its reliability has not been investigated. Most of these video tracking systems used to date in elite soccer do not provide real-time analysis, the results generally being available within 24–36 hours of the final whistle. This time lag, however, seems acceptable for the many top-level clubs who have adopted these systems over the last decade. The most recent commercial video-based automatic tracking systems such as DatatraX[34] and the TRACAB image tracking system[39] now provide real-time analysis, albeit using similar tracking methodologies based on multi-camera and image processing techniques. According to commercial information available from the supplier,[39] the TRACAB system exploits enhanced techniques for video image processing and by using mathematical algorithms originally designed for object tracking and guiding missiles in the military industry. Similarly, DatatraX uses pixel recognition to track the players automatically and voice recognition to code the match-specific events. Three manual operators are required to manage the process, two people to correct tracking mistakes in real-time for each team and one to perform the voice recognition coding procedure. The main benefit of both systems is that they provide coaches with a high level of instantly available detail concerning match performance, allowing informed decisions to be made during the match that may influence the eventual outcome. Although both ª 2008 Adis Data Information BV. All rights reserved.
Carling et al.
companies claim to have high levels of accuracy for their systems, the validity and reliability have again yet to be scientifically established. A major advantage of both the manual and automatic video-based tracking systems is that they do not require players to carry any electronic transmitting device. Carrying such material is strictly forbidden by various governing bodies of soccer. Their major disadvantage, however, resides in the high costs and the necessity of installing multiple cameras and a computerized network with at least one dedicated operator to organize the data collection and further operators to perform the analysis.[35] This apparent lack of portability means that teams can only employ these systems for matches in their home stadium. However, the DatatraX and Feedbacksport[31] systems can apparently still be operated at away venues using two portable cameras from the stadium gantry and some mathematical corrections for errors created when players are further away from the camera lens. In addition, the introduction of reciprocal contractual agreements has led to clubs being able to access work rate data when playing in opposition stadiums that are equipped with the same service provider’s system. Electronic transmitting devices have previously been described as the future of the computerized analysis of sport and are taking match analysis one step further in terms of data processing speed and accuracy.[8] These wireless and telemetric communication systems allow remote real-time data acquisition, and record movements and positions of every player and the ball up to several hundreds times per second. A small lightweight microchip transmitter is worn in clothing or in a strap around the chest of each player. The identification signal of the transmitter is registered in a fraction of a second by several antennae positioned around and outside the playing field. The reception time of the signal source to the recipient is synchronized and as a result the position is determined. These data are relayed to a central computer and immediately processed for immediate analysis. The LPM Soccer 3D system developed by INMOTIO in collaboration with PSV Eindhoven Football Club provides positional measurements at over a 100 times per second, leading to the production of highly detailed and previously unavailable information on player accelerations, decelerations and changes in
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direction.[30] This system also combines physical data with physiological measurements through heart rate monitoring (built into the transmitter) as well as synchronized video footage to provide a comprehensive picture of the daily, weekly and monthly workloads experienced in training. Constraints of such systems include potential electronic interference, strength of the electronic signals from players due to the size of playing surfaces and the energy source required to accomplish this signal transfer.[24] Furthermore, no investigation has yet attempted to determine scientifically the reliability of these electronic measuring systems. Global positioning system (GPS) technology has also begun to impact on the analysis of performance in elite soccer. As with electronic transmitting devices, its use is restricted to measuring player efforts during training sessions or friendly matches, although it is now permitted in competition for other codes of professional football such as Australian Rules Football. The GPS technology requires a receiver to be worn by each athlete, which draws on signals sent from at least four Earthorbiting satellites to determine positional information and calculate movement speeds, distances and pathways as well as altitude.[47] The latest SPI Elite GPS receiver designed by GPSports has been adopted by several teams competing in the English Premier Football League and comes with propriety software for simultaneous analysis of data from all players.[48] Similarly, a company in Spain known as RealTrack Football has also made commercial GPS specifically available for soccer teams.[36] It is possible to purchase kits with over 11 trackers in a set, with potential applications to training contexts and to the other football codes. Although automatic tracking devices have established methods of providing data on work rate characteristics such as total distance run and time spent in various categories of movement, the latest systems are advancing the analysis of sports performance through a superior level of coordinated biofeedback to accompany the traditional physical feedback. In this respect, the SPI Elite GPS is capable of monitoring heart rate and recording information on the frequency and intensity of impacts such as tackles and collisions by means of a built-in tri-axis accelerometer which also depicts three direction types (forwards, sideways and backwards). The accuracy and reliability of GPS ª 2008 Adis Data Information BV. All rights reserved.
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receivers is relatively high: results of a test of accuracy showed a 4.8% error rate in measuring total distance covered and a test of intra-tester reliability reported a technical error of measurement (TEM) of 5.5%.[24] These TEM values can therefore be taken into consideration when interpreting the raw data. Recent technological developments have also led to increased miniaturization and portability.[49] An alternative device known as the Biotrainer is also being produced by Citech Holdings Pty Ltd.[28] This system is described as a disposable patch, similar to a band-aid, worn by the athlete, which provides GPS tracking data both indoors and outdoors, as well as reportedly supplying real-time biofeedback on nine physiological outputs such as heart rate, body temperature and hydration level. Nevertheless, GPS receivers are still subject to problems of accuracy; the magnitude of error depends on land configuration and the number of available satellite connections. Furthermore, data in previous systems were usually collected at one measurement per second, which was insufficient in frequency for measuring detailed variations in speed and direction. However, the latest GPS receivers[48] are now reportedly capable of logging data at frequencies of 50 measurements per second. Although this development has potential to provide much more precise data and could be very useful in speed and agility assessments, the volume is therefore 50 times larger and creates potential problems in unit size, storage capacity and battery life. This new facility may also require extra manual work in data interpretation, which could ultimately delay any feedback. It therefore becomes the challenge for developers and researchers to investigate the optimal measurement frequency to provide appropriate data. Although the price of individual GPS units means they are now more within the reach of the non-elite player, purchasing enough receivers to cover the needs of every member of a squad of players may still be beyond all but the wealthiest of clubs.
2. Main Issues in Contemporary Motion Analysis Technologies 2.1 Validity, Objectivity and Reliability
The methodologies employed to collect motion analysis data must meet the requirements for Sports Med 2008; 38 (10)
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scientific criteria for quality control.[8] These specifications include reliability, objectivity and validity. There is a need for a detailed analysis of the errors associated with the analytical procedures used by the systems.[27] To date, many of the contemporary commercial motion analysis systems discussed in section 1 have not undergone satisfactory quality control checks. Other than manufacturers’ statements, very little scientific evidence exists to verify validity claims.[24] The lack of a single validation test protocol considered the ‘gold standard’ for testing the validity, reliability and objectivity of motion analysis data collection methodologies may be one reason for this low number of validation studies. Any validation protocol itself must also have undergone quality control testing and be easily transferable across the range of systems currently used in elite soccer. However, there are various issues that can play a part in preventing researchers from designing and undertaking validation projects. For example, researchers may face logistical problems such as gaining access to test systems using the playing facilities within soccer stadiums. The current laws of the game also prohibit players from wearing electronic equipment for testing the reliability of movement measurements within competition conditions. If human input for data collection is still required when using a contemporary system, interand intra-observer reliability testing of the same competitive match(es) must be undertaken to assess measurement error. When automatic data collection processes such as tracking movement on video or via a GPS are employed, it is important to test the intra-reliability of the system itself by analysing the same match several times. It is also necessary to check the reliability of data by examining within-subject (player) error across a number of games, which has rarely been achieved in the literature.[27] Similarly, to ensure full validation of a system, comparison of the measurements obtained using contemporary analysis software and equipment should be made with those obtained from already established methods. There are also statistical considerations to be taken into account when examining the reliability of a system. The statistical procedures used to compare reliability measurements and the amount of disagreement between measurements deemed to be acceptable
ª 2008 Adis Data Information BV. All rights reserved.
Carling et al.
must be suitably defined at the outset of the study. In addition, the statistical test selected should aim to show agreement between observer measurements rather than differences. For more detailed information on reliability checks in match analysis, see the review by Drust et al.[27] A validation procedure of a commercial match analysis system was designed by Di Salvo et al.[35] to compare data on running speeds of soccer players obtained via video-based tracking against those obtained from timing gate measurements. The subjects were asked to perform a series of short runs at different determined speeds over several marked courses. Correlation coefficients and absolute reliability coefficients between velocity measurements over runs of 50 and 60 m obtained from both systems were high (r = 0.999; total error 0.05, limits of agreement 0.12), indicating that the system can be confidently used to provide an accurate recording of running speed during soccer play. However, as this type of semi-automatic tracking system requires manual input, it would have been beneficial to have compared the reliability of data obtained from the runs by distinguishing between human and automatic tracking of the subjects’ movement. Similarly, an intra- and inter-observer reliability study comparing the data from the whole duration of several matches played under real competitive conditions is necessary to gain an idea of the overall reliability of the system output. Validation protocols of video-based tracking systems that use marked courses or zones to evaluate running speed and distance should ensure the inclusion of all the different types of running actions previously identified by means of motion analyses. For example, as well as running in a straight line, moving in backwards and sideways directions, turning, shuffling and jumping actions, and dribbling should be carried out by test subjects. Similarly, adding and removing players to the area analysed is advisable to ensure analysis conditions are close to those observed in real competition. Validation procedures should also be carried out under different climatic conditions (such as variations in light), since environmental variables can affect the quality of the video recordings used for computer tracking.[8] It is important to assess the reliability of data for each individual class of movement intensity. In a previous study, data obtained from manual coding using a computer interface of the time spent in
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high-intensity running by English Premier League players (during the same match) were compared between two different observers.[50] There was a relatively low level of inter-observer reliability between measurements and a significant systematic bias between observers for the percentage of time spent performing high-intensity activity (p < 0.01), with one observer recording much higher values than the other. The validation of a motion analysis system employing photogrammetric techniques to obtain the x and y positional coordinates from digital video images of soccer games has recently been achieved.[51] The test subjects were instructed to run at paced speeds following pre-established trajectories over predefined distances, and the measurements were subsequently compared with the distances obtained by means of the photogrammetric method. Results showed an error in distance measurement of <1.5% for each of the movement categories. In the same study, the accuracy of the system to determine general position and distance of targets was also determined. For this process, 40 markers were randomly distributed over a football pitch and the pitch was filmed from the main stand. The position of these markers was determined using a pre-calibrated 50 m measuring tape and later obtained through digitization of the frames. A low root mean square error for reconstruction of the coordinates in the x- and y-axis was obtained (0.23 and 0.17 m, respectively). Similarly, the authors reported an error of <2% for reconstructing the distance between two individual coordinates. Whilst the accuracy of this system in determining distances covered by players over set running courses seems sufficient, it would also have been pertinent to compare results from whole competitive games against hand-based motion analysis methods,[11,20] which have previously demonstrated high levels of reliability and validity (coefficients >0.9). This validation requirement should apply even if the measurement error in novel experimental technology may be less than that for a reference method such as that used by Reilly and Thomas.[11] In a recent comparison of GPS and manual computer-based tracking systems for measuring player movement distance during Australian Rules Football games,[24] a number of ways were used to determine the validity and reliability of these methods for measuring distance covered. ª 2008 Adis Data Information BV. All rights reserved.
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Validity checks for both systems were undertaken by comparing the data obtained by each system for distance covered by players running over a predetermined marked circuit against the distance calculated by a calibrated trundle-wheel pedometer. Intra-tester reliability of the distance calculated by both systems was also assessed over a range of running courses. Inter-tester reliability of distance covered from the tracking system was assessed by comparing data obtained both in competition and over a marked course. A comparison of the two tracking technologies for measuring movement distances was performed when data were collected simultaneously. Players wearing a GPS receiver ran around circuits of different lengths and geographic layout whilst two observers simultaneously tracked their movements. A calibrated trundle-wheel pedometer was then used to verify the actual track distance following the completion of the circuit. Both the GPS and the tracking system were found to overestimate the true distances (on average by <7%) travelled by players. The authors considered that these relatively small overestimations combined with an acceptable level of relative technical error of measurement both within and between trackers should not prevent the use of either of these technologies to monitor player movements. However, this particular manual tracking system relies on the subjective skills of observation and visual judgement on the part of the tracker. An omission was therefore the lack of testing of the reliability of data for the individual classes of movement and notably for movements at high intensities, which tend to be overestimated.[50] 2.2 Interpretation of Results
Ultimately, contemporary measurement systems are based on gathering data concerning the events in a match and the physical efforts of the players. In terms of the latter, the workload of the players is derived from data collected on speed, distance and time and compiled to form an assessment of physical exertion. However, the distance covered by players has been an area that has been adversely affected by methodological differences. This includes a lack of standardized approaches and a need for a more rigorous analysis of data. Furthermore, it is important to recognize that physiological evaluation is limited because Sports Med 2008; 38 (10)
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the method makes the general assumption that energy is expended only when the player travels to a new location on the pitch, with sprinting usually classified as the most exertive motion. This is an important issue, which causes underestimation of the total energy expenditure of the players because several high-intensity movements are performed in soccer match-play without obvious changes of location on the pitch, for example a vertical jump, competing for possession or a highspeed shuffle. Furthermore, many contemporary systems assume players only travel in a forward direction and therefore do not provide detailed information on backward, sideways or other unorthodox movements that have been reported as more physiologically demanding than movements performed forwards at the same velocity.[8,9] To this end, other parameters such as agility (acceleration, deceleration, changing direction), physical contact, ‘on-the-ball’ activity and, critically, the sequence in which these activities happen, also contribute to physiological energy expenditure. Considering the dynamic nature of movements in soccer, this lack of information restricts a truly valid and thorough assessment of a player’s expenditure in match-play. However, if the file containing the raw positional data can be accessed, as in the case of contemporary GPS receivers for team sports,[48] then algorithmic filtering may be employed to obtain these missing data. Some major limitations exist with systems that centre on measuring distance covered through measurement of time spent in motion at different speeds. To this end, there is no agreement on what speed thresholds should be used in soccer; for example, thresholds for sprints have been reported set at speeds of >30 km/h,[15] >23 km/h[35] and >24 km/h.[52] These discrepancies in the definition of speed thresholds make it difficult to compare work rate data between different studies. However, the latest software used to analyse work rate data allows end-users to define their own speed thresholds, permitting a more objective means of analysing and comparing the physical efforts of players according to different intensities of movement.[43] One of the main concerns with motion analysis data is the stringency of the speed thresholds used to categorize the motion types. Essentially, results are created by objective measurement systems by acknowledging the frequency of the occasions that
ª 2008 Adis Data Information BV. All rights reserved.
Carling et al.
a player enters a certain threshold and then the time that player spends within that threshold, and subsequently calculating distance covered. However, if a player were to perform a single effort at speeds on the boundary of a particular threshold, it is quite possible that the data would reveal that multiple efforts have been performed if the boundaries have been crossed. For example, if a threshold for ‘sprinting speed’ was set at efforts >24 km/h and a 1 Hz (second-by-second) raw output over 7 seconds reads 22-23-24-26-23-25-23, it is interpreted that this player sprinted on two occasions when realistically (subjectively), it could and perhaps should be only interpreted as once. Furthermore, it should also be noted that the interpretation here is that the player ‘sprinted’ for a certain duration, although this only accounts for the time spent at a speed >24 km/h. This result is easily misinterpreted, as it fails to account for the speeds £24 km/h that account for the acceleration phase of this ‘sprint’. Instead, the interpretation should be that the player achieved speeds >24 km/h for a certain duration. This fact therefore applies to all motion category thresholds used to evaluate performance because it will also affect total frequencies and mean durations of each motion type. One way of combating this error is to filter or smooth the data using mathematical algorithms to make inferences on the data. For example, this may also be used to illustrate differences between rapid or gradual accelerations or decelerations by determining how quickly a player has moved through different threshold zones. However, this use of multiple equations within a data set requires further validation of the system. Similarly, although differences have been identified in total distance covered in various levels of performance, with higher levels of performance corresponding with longer distances,[15] caution must also be taken when assessing a player’s match performance based on the total distance covered. In this respect, players may be inefficient with their movement and in essence ‘waste energy’ by performing unnecessary movements, which may actually be detrimental to the team tactic, but result in a large distance covered, and may therefore be open to misinterpretation. Alternatively, a player may remain in low-intensity motion for a significant percentage of a match through being highly efficient in movement selection. This would produce a
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below-average total distance covered, number of sprints, workload and work rate, yet this player may have had the highest impact on the team’s performance. In turn, an opposing player who is responsible for marking this type of player may also appear to have produced a lower workload than normal. Finally, the overall reporting of results is usually provided macroscopically and in isolation. Traditionally, values for total overall distance, as well as total frequency and mean distance, time and/or percentage time spent in each motion type are reported.[9] This huge amount of data for each match can be a challenge in itself for professional soccer staff to make true assessments of match performance, monitor workloads and plan appropriate physical fitness regimes. In this respect, a recent programmed exercise protocol for netball based on mean ‘bursts’ of high-intensity activity and ‘recoveries’ of low to moderate intensity derived from time-motion analysis proved to be ineffective in enhancing match-play specific physical fitness.[53] To this end, a full range of ‘bursts’ and ‘recoveries’ are sought to design physical conditioning programmes that are specific to soccer match-play. Consequently, ratio scales should be used to present data based on levels of intensity.[54] The holistic approach of reporting work rate data ignores the interaction between and within motions, movements and playing activities. Therefore, it is also important to perform temporal pattern (T-pattern) detection to identify patterns within the data. In this respect, the detection of patterns that are not identifiable through simple observation has great benefit not only in soccer match-play variables, but also in establishing the specific physical performance demands.[55] A T-pattern is essentially a combination of events where the events occur in the same order, with the consecutive time distances between consecutive pattern components remaining relatively invariant with respect to an expectation assuming, as a null hypothesis, that each component is independently and randomly distributed over time. The method of T-patterning has already been employed to establish playing patterns in soccer by identifying complex intra- and interindividual patterns for both individuals and teams using the detected behavioural patterns in combination with elementary statistics.[56] Figure 1 displays a player’s movement ª 2008 Adis Data Information BV. All rights reserved.
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pattern which identifies a varied range of motion. In this particular pattern, the player starts by shuffling backwards and then sprints forward. After this, he decelerates and finishes with a highintensity shuffle, indicating that he slows down very rapidly. From this point, he skips sideways left at low intensity, turns left and jogs forward at low intensity, gradually increasing pace into a run and changing direction by moving diagonally left to complete the complex pattern. Preliminary investigation of pattern complexity between player positions suggests that a higher number of different patterns and pattern occurrences are detected for defenders than for forwards or midfielders.[55] The same also seems to apply for length of patterns. These findings, and their significance, need further examination, although they could be very useful for creating specific training programmes according to individual positional requirements.
3. Contemporary Motion Analysis Research 3.1 Analysis of Data on Overall Work Rate
There is a growing interest amongst practitioners within elite soccer in the work rate characteristics of soccer players using the data obtained from the various techniques and technologies described in the previous sections. Generally, the overall work rate in field sports can be expressed as distance covered in a game, given that this measure determines the energy expenditure irrespective of the speed of movement and the individual contribution towards the total team effort.[9] This activity can then be broken down into discrete actions for each player across the whole game for classification according to intensity, duration and frequency. Although caution should be taken when comparing the results of various studies because of the differing methodologies employed to obtain data, contemporary outfield male elite soccer players cover on average 9–12 km per match,[15,25,57,58] whilst some players may attain distances of around 14 km (see table II).[59] Observers of elite female soccer players have generally reported lower results than elite male players in terms of overall distance covered (8.7–12 km) but a similar level of physiological strain.[16,19,60-62] From a coaching perspective, it may be of value to compare the overall distance run by individual Sports Med 2008; 38 (10)
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Carling et al.
Fig. 1. An example of a temporal pattern (T-pattern) incorporating regularity of movements by a centre forward in a Premier League match (reproduced from Bloomfield et al.,[55] with permission from IOS Press).
players with that of team mates or opposition players to ascertain relative exertion rates. However, this distance may not be a fair reflection of a player’s performance, as playing style, team formation, technical actions and tactical role also influence overall work rate. For example, Rienzi et al.[65] presented evidence that the distance covered by South American players was about 1 km less than the output of professionals in the English Premier League. The authors suggested that the higher sustained pace by players in the English game could explain this disparity. However, no motion analysis study has yet been conducted to compare the distances run by elite soccer players belonging to teams across a larger range of national championships. Measuring the total distance run may also help in examining the evolution of work rates over sevª 2008 Adis Data Information BV. All rights reserved.
eral seasons to determine if the physical requirements of the game are the same and whether current training programmes and fitness tests are still optimal. Professionals in the English Premiership tend to cover greater distances during matches than those in the former First Division (pre-1992), which has had obvious consequences on contemporary fitness training programmes.[13] Data presenting the total distance run by 300 professional European midfield players have recently confirmed this upward trend.[43] Although contemporary elite players are running further than in previous years, the effects of playing position on distance run is consistent across the last three decades.[9] A pertinent coaching issue may be to look at a division of the total distance run into data for defending (opposition in possession) and Sports Med 2008; 38 (10)
ª 2008 Adis Data Information BV. All rights reserved.
12 400
14 12 12 11 11 6 5
Elite Danish (female)
English professionals (male)
Under 19 professionals (male)
International Swedish/Danish (female)
Elite Swedish/Danish (female)
English professionals (male)
9
8 638
1
6
9 140
10 659
11 000
12 793
10 461
9 010b
14 199b
10 642
11 410
8 800b
10 980a
11 433
12 636
fullback
9 029
10 627
10 020
9 740a
10 650
11 099
central defender
Results did not distinguish between fullbacks and central defenders.
NP = not provided.
c Combined results for central and external midfield players.
b
Japanese professionals (male) 1 10 460 a Results for each playing position were calculated from a combination of data obtained for both groups of players.
Triangulation/camera potentiometer
International Australian (female)
Global positioning system
NP
French professional (male)
English professionals (male)
3
10 864
18 18
European professionals (male)
Champions League matches (male)
Portuguese first division (male)
10 012
55
Brazilian first division (male)
11 393
791
300
Professional European leagues (male)
11 010
10 335
10 100
9 700
10 000
9 741
10 274
10 300
Champions League matches (male)
Automatic tracking on video
36
Professional Australians (male)
Elite Norwegian juniors (male)
Manual computer pen and tablet
Elite English (female)
10 104
17
South American professionals (male)
10 860
10 150
10 800
23
23
Danish Premier League (male)
10 330
18
24
Elite Danish (male)
11 264
Swedish Premier League (male)
24
English professionals (male)
9 890
11 979
total
Distance covered (m)
Italian professionals (male)
30 29
International English (female)
Number of players
Italian junior professionals (male)
Manual video analysis
League/competition level (sex)
9 640
11 000
12 958
8 510
11 224
43 9 612
10 537c
33
60
69
37
46
68
44
25
67 11 254
66
38
61
65
19
19
58
58
16
65
15
64
64
15
13
17
63
Reference
11 570
9 900
10 480a
11 804
forward
12 009c
10 100
11 000a
12 075
12 971
midfielder
Table II. Summary of motion analysis data from different systems of the total distances run and according to playing position by contemporary soccer players, 1999–2007
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attacking (own team in possession) play. This comparison may help to determine whether players are working as much in a defensive role as they are in attack. At present, this factor has not been examined in the scientific literature. Results are likely to be affected by the tactical role of players, for example a ‘holding’ midfielder deployed on mainly defensive duties will no doubt cover less distance than other midfielders when his/her team is attacking. Another concern may be to identify whether physical demands are comparable between different levels within elite soccer, for example, between the various divisions in professional leagues. A comparison of professional Italian and elite Danish players showed that the former covered a significantly higher distance during games.[15] A motion analysis study of the total distance run by the same elite females competing at both national (for their clubs) and at international level (for their national team) established that these players ran significantly greater distances when competing at international level.[19] The observation highlights the need to take the level of competition, and perhaps the importance of the game, into consideration when interpreting data on motion analysis of match-play. It is not feasible to use the total distance run to compare the overall physical contributions of players when there is a difference in the overall duration of games. For example, different categories of age in youth soccer generally play games of different durations, and other types of soccer such as futsal are limited to a total of 40 minutes play. An alternative means of comparing the overall physical contributions of players is to calculate a relative measurement of performance by correcting the absolute value (total distance covered) for the match to a minute-by-minute analysis of distance run. Recent studies have shown that the intensity of play in professional futsal[70] was higher than for elite players competing in the Australian National league.[38] The futsal players covered on average 117 m per minute compared with 111 m per minute for the Australian players, indicating that the intensity of the game of futsal may be higher than that for traditional soccer games, although analysis of data on players in professional European Laegues is needed to substantiate this claim. ª 2008 Adis Data Information BV. All rights reserved.
3.2 Categories of Movements
In field sports such as soccer, movement activities are generally coded according to their intensity, which is determined by the speed of actions. When evaluating performance, the frequency of each type of movement and the time spent or distance run in each movement can be analysed. The main categories generally used to analyse soccer work rate are classed as standing, walking, jogging, cruising (striding) and sprinting. These categories have recently been extended to include other activities such as skipping and shuffling.[26] Most activities in soccer are carried out at a submaximal level of exertion, but there are many other gamerelated activities that must be taken into account such as alterations in pace, changes in direction, execution of specific game skills, and tracking opponents (which are examined later in this section). Elite players spend the majority of the total game time in the low-intensity motions of walking, jogging and standing.[13,15,43] In comparison, highintensity efforts (cruising and sprinting) constitute around 10% of the total distance covered.[3,9] This finding compares with analysis of performance in professional futsal games where the percentage of the total distance covered spent in high intensity is almost one-quarter (22.6%) and can, on occasions, exceed one-third.[70] Research on female performance has shown that these players spend more time in lower intensity activities compared with males, which may be explained by biological differences such as endurance capacity.[71] In soccer, activities at lower levels of intensity such as jogging and walking tend to dominate work rate profiles. However, the impact of high-intensity efforts in match-play cannot be over-emphasized, and it has been suggested that this feature may be the most appropriate means of evaluating and interpreting physical performance.[16,57] Measurement of high-intensity exercise, for example every 5 minutes during the course of the game, is an alternative way for coaches to evaluate overall work rate. High-intensity exercise is a constant feature across matches[9] and games are often won or lost on successful attempts at scoring carried out at high speed.[71] The high-intensity category of work rate includes the addition of cruising and sprinting actions, which are predetermined according to running speed. In elite soccer, players Sports Med 2008; 38 (10)
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generally have to run at a high intensity every 60 seconds and sprint all-out once every 4 minutes.[13] However, Di Salvo and co-workers[43] presented evidence that the number of sprints made per player ranges greatly (3–40). These authors suggested that this finding strongly depended upon individual playing position. Because of the intermittent nature of the game, performance can be enhanced through improving players’ ability to perform high-intensity work repeatedly. The timing of anaerobic efforts, their quality (distance, duration) and the capacity to repeat these efforts, whether in possession of the ball or without, are crucial since the success of their deployment plays a critical role in the outcome of games.[8] Players in successful teams competing within the same elite league were reported to perform more high-speed running and sprinting in the most intense periods of the game and more sprinting over the whole 90 minutes than less successful teams.[64] In elite soccer, the average distance and duration of sprints is short, as evidence has shown that these activities are rarely more than 20 m in length and tend to last around 4 seconds.[3,43,58] These findings imply that when a player is required to sprint, his or her acceleration capabilities may be of greater importance than their maximal running speed, as the tactical demands of the game probably render it unnecessary to attain maximal speeds. Improving performance in these actions will help players in many aspects of their game, such as being first to the ball or getting away from a marker. For example, if a player tends to lose out by poor acceleration or lack of speed over a short distance, the trainer could suggest an individual speed development programme. A more detailed motion analysis study on the characteristics of sprint patterns of players during competition could be beneficial. For example, no information is available on whether sprints commence from a variety of starting speeds such as a standing start or when jogging and, if so, does such differentiation also exist between playing positions. A recent study on elite rugby union players showed that forwards commenced these actions most frequently from a standing start (41%), whereas backs sprinted from standing (29%), walking (29%), jogging (29%) and occasionally striding (13%) starts.[72] Practitioners designing conditioning programmes would no
ª 2008 Adis Data Information BV. All rights reserved.
853
doubt benefit from this information by ensuring that training sessions involve the actual movement patterns performed in matches. The programme can then provide sufficient overload through careful manipulations of the match demands in preparation for competition. This may involve alterations in playing time, size of pitch or number of players involved in order to increase the training intensity. In soccer, only a small percentage of the total distance covered by players is with possession of the ball. Nevertheless, evidence from a field test of maximum oxygen consumption has shown that running with the ball significantly raises oxygen consumption and energy expenditure and should be taken into account when evaluating player efforts.[73] The vast majority of actions are ‘off the ball’, either in running to contest possession, supporting team-mates, tracking opposing players, executing decoy runs, making counter-runs by marking a player, or challenging an opponent. These actions often require frequent changes in movement activities, such as accelerations and decelerations, changes of direction, turns and unorthodox movement patterns (backwards and sideways runs), and contribute significantly to additional energy expenditure.[8] The latest GPS systems reportedly enable the quantification of the stress placed upon players from accelerations, decelerations, changes of direction and impacts, permitting the individualization and optimization of exercise and recovery programmes[48] – although this claim has yet to be scientifically validated. A challenge for future researchers is to investigate and combine data both on contacts, collisions and tackles and on motion analysis categories into a single index of training and competition loading. Two studies have recently been undertaken to investigate deceleration[74] and turning[75] movements in professional soccer. Players were shown to perform an average of 54.1 deceleration movements and 558 turning movements during ‘purposeful movement’ passages from Premier League matches. The authors suggested that both these types of actions are a common and highly important part of the modern game, and there is a particular need for developing specific deceleration and turning exercises in strength and conditioning training sessions. An investigation into whether the inclusion of an enforced deceleration phase on
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repeated sprint efforts would cause greater fatigue and slower sprint times compared with efforts undertaken without this phase may be of interest in further understanding match performance and optimizing fitness training programmes. The activity profile of players may be influenced by the style of play used by individual clubs and by regional differences. Such regional differences in performance are important because players moving between countries will probably need time to adapt both physically and tactically to the particular style of the different leagues. Nevertheless, there is still a lack of studies attempting to address either cultural or geographical differences in the work rate pattern,[27] especially at international level or between various professional leagues. Similarly, motion analysis research on the work rate performance characteristics of female and, in particular, younger players is still relatively limited in the literature. Results of a recent study on elite Brazilian youth players belonging to under 15, under 17 and under 20 age groups indicated significant differences in both overall workload and individual playing positions according to player age.[76] The age of players should therefore be a relevant factor when evaluating work rate profiles. 3.3 Determining Positional Demands
Understanding the workload imposed on toplevel soccer players according to their positional role during competitive matches is necessary to develop a sport-specific training protocol.[43] Contemporary data[13,15,43] generally confirm the previously identified trend[11,20] that midfield players generally cover greater distances in a game than defenders or forwards. Goalkeepers usually cover much lower distances (around 4 km) per match. However, individual differences in the distance covered are not just related to a division into basic traditional team positions of defenders, midfielders and attackers. For each playing position, there may be a significant variation in the physical demands, depending on the tactical role and the physical capacity of the players. For example, Barros et al.[25] and Di Salvo et al.[43] showed that in professional Brazilian and European soccer, fullbacks ran significantly further than central defenders. Similar results between defensive positions have also been obtained for ª 2008 Adis Data Information BV. All rights reserved.
international female soccer players.[62] These results highlight that individual differences in playing style and physical performance should be taken into account when planning training and nutritional strategies.[77] Again, marked differences in the intensity of various running activities exist across the various playing positions. A detailed analysis of English Premier League players showed that playing position (defender, midfielder and attacker) had a significant influence on the time spent sprinting, running, shuffling, skipping and standing still.[21] Rienzi et al.[65] observed that defenders perform more backward running than strikers. Similarly, it has been reported that Premier League midfielders and strikers engaged in significantly more of the ‘other’ type of movements (jumping, landing, diving, sliding, slowing down, falling and getting up) than the other positions.[21] Analysis of work rate categories also suggests that training and fitness testing should be tailored specifically to positional groups (e.g. separation between central and external midfielders) rather than simply differentiating between forwards, midfielders and defenders because each positional group has its own unique physical demands. For example, a variation of 1.9 km in the distances covered at high intensities by midfield players in the same game has been observed.[15] Variations in work rate between players may imply that not all positions are taxed to full capacity in every game. Findings from a study comparing 123 professional European players showed that central defenders sprinted significantly less distance than fullbacks.[43] A large-scale study of professional Spanish soccer players reported a significant difference in the total distance sprinted by wide midfielders compared with central midfielders.[78] This research again demonstrates the need for a criterion model in order to tailor training programmes and strategies to suit the particular needs of individual playing positions. Research dividing the high-intensity efforts of players for defending and attacking play would be pertinent to determine whether positional role determines the physical contribution of players according to whether their team is in possession or not. Motion analysis and its application to training must also take into account the relationship between the physical and technical demands of games. For example, match data on professional English Sports Med 2008; 38 (10)
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855
players show that forwards tend to receive the ball more frequently when cruising and sprinting than defenders and midfielders, indicating that the ability required to implement technical skills at pace when attacking is important for this position.[79] 3.4 Use of Motion Analysis in Studies of Fatigue
In motion analyses of soccer, data may be split into distinct time-frames to help establish whether work rate varies with time or task. According to analyses and performance measures during elite match-play, fatigue manifested as a decreased performance seems to occur at three different stages in a game: (i) after short-term intense periods in both halves; (ii) in the initial phase of the second half; and (iii) towards the end of the game.[57] Simple comparisons of the overall work rate between first and second halves of matches can indicate the occurrence of fatigue, although it may be more closely identified if activities during the game are broken up into 5- or 15-minute segments.[8] Minute-by-minute analysis of work rate throughout a game has also been employed as a possible means of identifying a drop-off in physical performance.[25] In soccer, the evidence of a difference in the total distance covered between halves is inconsistent and a significant decrement does not necessarily occur in all players, especially if players operate below their physical capacities in the first half. Therefore, a simple comparison of the overall distance run per half may not be a valid means to allow interpretation on whether or not a player has experienced fatigue. Nevertheless, table III presents data from various studies comparing the total distance run by
elite soccer players for the two halves of the game. An average difference of 3.1% in the total distance run between halves (range 9.4% to þ0.8%) can be observed across all studies on elite soccer. The largest difference between the total distance run in the first half compared with the second half was reported for players participating in the Australian National Football League.[38] Professional Brazilian players have also been reported to cover significantly more distance in the first half,[25] whereas more recent data showed no significant difference in work rates between halves for elite Spanish players and other European players participating in Spanish League and the Union of European Football Associations (UEFA) Champions League games.[43] In this latter study, the data may have been confounded, as no mention was made as to the inclusion of substitutes and the effect their work rates may have had on the results. Nevertheless, individual teams and players may pace their efforts in order to finish the game strongly. A comparison of total distance run between match halves of the winners (Barcelona) and losers (Arsenal) of the 2005–06 UEFA Champions League final showed that the Spanish players covered more distance in the second half than in the first half (5121 vs 5218 m).[68] In contrast, players belonging to the losing team who completed the whole match covered slightly less ground in the second half (5297 vs 5252 m) than in the first half, suggesting they may have been forced into a fatigued state. In this study, the data may have been confounded as Arsenal was forced to play with ten players for the majority of the game due to the dismissal of the goalkeeper.
Table III. Comparison of distances covered by elite soccer players during the first and second halves of competitive match-play Study
Nationality
Distance run (m)
Difference (%)
total
1st half
2nd half
Barros et al.[25]
Brazilian
10 012
5173
4808
Burgess et al.[38]
Australian
10 100
5300
4800
9.4
Di Salvo et al.[43]
European
11 393
5709
5684
0.4
Miyagi et al.[33]
Japanese
10 460
5315
5141
3.3
Mohr et al.[15]
Italian
10 860
5510
5350
2.9
Danish
10 330
5200
5130
1.3
7.1
Rienzi et al.[65]
South American/English
9 020
4605
4415
4.1
Zubillaga et al.[68]
English
10 549
5297
5252
0.9
Spanish
10 339
5121
5218
þ1.9
ª 2008 Adis Data Information BV. All rights reserved.
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A 14% slower overall speed in the second half of the game when compared with the first half has been reported in elite Australian soccer players.[38] This result was attributed to fewer observations of the low-intensity movements (9.0% less walking and 12.4% less jogging) and more stationary periods. Engagement in game events such as kicking and passing was also 11.2% less frequent in the second versus the first half of games. Similarly, a recent study of work rates in professional Italian players examined the effects of fatigue on technical performance.[80] A significant decline between the first and second half was found for both physical performance and some technical scores (involvements with the ball, short passes and successful short passes). Minute-by-minute analysis of total distances covered by Brazilian players revealed significant differences after the fifth minute of the game, with highly significant differences after the eighth.[25] The authors suggested that this more detailed analysis may allow a better understanding of fatigue. However, these results should be treated with caution as it is highly unlikely that players experience fatigue so soon during a match. This reduction in performance is more likely to be linked to play settling down after the frantic first few minutes of the game where engagement is at its most intense. Indeed, a study by Rahnama et al.[67] yielded evidence that the majority of critical game incidents and the highest intensity of activities were observed in the first 15 minutes of the game. A significant reduction in the distance run at medium[43] and high intensity[37,63] between halves has been reported in players competing in elite European soccer games and tournaments. In elite Scandinavian soccer players, the amount of highintensity running was lower (35–45%) in the last 15 minutes than in the first 15 minutes of the game, with more than 40% of the players having their lowest amount of intense exercise in the last 15 minutes.[15] This trend was confirmed in a study of elite female players where a marked decrease in the amount of high-intensity running within each half was observed and 13 of 14 players did their least amount of high-intensity running in the last 15minute period of the first or second half.[16] Similarly, GPS-based tracking of activity patterns in professional futsal players has shown that during the last period of the game, the number of bouts of high-intensity exercise significantly decreased.[81]
ª 2008 Adis Data Information BV. All rights reserved.
Carling et al.
However, the total distance covered or the amount of sprinting may be unaffected between playing halves in certain players,[25] and the distance covered in high-intensity activities may even increase between halves[82] and in the last few minutes of the game.[8] Players carrying out fewer actions at low or moderate intensity may be ‘sparing’ their efforts for the final few crucial actions as their energy levels become depleted. Some players demonstrating no decrease in performance between halves or in the final quarter of the match may have paced themselves in order to finish the game strongly. A pertinent study may be to examine whether the type of competitive match affects work rate and any subsequent reduction in performance. For example, it would be relevant to determine whether players tend to work harder or demonstrate greater fatigue during Cup games than during League games or when playing against teams from lower standards of play. In addition, research to investigate work rates in the extra-time period during Cup matches would provide useful information on the occurence of fatigue and which players tend to cope better. Another method of examining fatigue may be to concentrate on the maximal speed or duration of individual sprints to determine whether a player’s sprint performance is declining (e.g. is the player slower?) towards the end of the match. The maximal sprint speed of an international midfield soccer player averaged every 5 minutes throughout the match has been reported to decrease significantly towards the end of the match.[82] However, as the data were drawn from a case study of one player, it is difficult to draw conclusions about the relationship between maximal sprinting speed and fatigue. In addition, soccer players may not always reach maximal speed during sprinting actions, because of the tactical demands of the particular situations restricting the length of these runs. Work rate analysis to determine whether there is a decrease in the capacity to accelerate rather than in maximal sprint speed towards the end of a game may be a more pertinent means of evaluating the occurrence of fatigue, although no study has as yet examined this feature. Nevertheless, work rate information indicating fatigue towards the end of the game could lead the coach to change tactics or even make a substitution to avoid the opposition exploiting this emerging physical weakness. Substituting players before the onset of fatigue towards the end of the
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game may restore the imbalances in work rate. Substitute players have been shown to cover significantly more ground at high intensity during the final 15 minutes than the other players already present on the pitch.[15] The latest video-tracking systems allow coaches to analyse work rate in realtime and make objective evidence-based decisions when attempting to identify players who may need replacing. Evaluating fatigue during match-play may lead coaches to examine whether the intensity of the following sprint is affected by the intensity of the previous sprint (e.g. if the sprint is long and at maximal speed). It may also be useful to look at the relationship between successive sprints and whether the intensity of the subsequent activities is affected, for example if moderate-intensity exercise has more of a negative impact on ensuing sprint performance than efforts at low intensity. Individual sprints often depend on the requirements of the game situation, and particularly the recovery allowed by the unpredictable nature of play. After the 5-minute period during which the amount of high-intensity running peaked in one study, performance was reduced by 12% in the following 5 minutes compared with the game average in elite players.[15] Further data on Fourth Division Danish players have shown that performance of the third, fourth and fifth sprints carried out after a period of intense exercise during the first half was reduced compared with before the game.[83] This finding together with the observation that sprint performance measured at the end of the first half was the same as before the match, provided direct evidence that fatigue occurs temporarily during a game. Fatigue may be evident as a prolonged recovery during the game, for example increased time spent in low-intensity activities. The reason for this decline in performance could be repeated pressure from the opposition on an individual player, eventually leading to an inability to respond to game demands. Rampinini et al.[84] recently observed that the work rate of a team of professional soccer players was significantly influenced by the activity profile of opponents. Fatigue during match-play may be transient, the player recovering once there is respite from the opponents. In this instance, tactical support for the player targeted is vital so that the offence from the opponents is not relentless. However, the same study[84] showed that
ª 2008 Adis Data Information BV. All rights reserved.
857
the total distance covered and the amount of highintensity running during matches were higher against ‘better’ opponent teams than against ‘lesser’ opponent teams. This finding suggests that players can increase or decrease their work rate according to both the demands of individual matches and to the quality of the opposition. A study of the relationship between match scoreline and work rate in soccer showed that players performed significantly less high-intensity activity when winning than when the score was level.[85] Players also performed significantly less high-intensity activity when losing than when the score was level. The authors suggested that players on teams that are winning relax their work rate, allowing opponents back into the game, and that players on teams that are trailing may lose the motivation to maintain a sufficient work rate. When a team is ahead, however, forward players perform significantly more exercise – although this only appears to relate to the ~10-minute period directly after a goal has been scored, and the elevated work rate is not ultimately sustained.[86] This phenomenon merits further investigation, together with the impact of the time in the match at which goals are scored, the actual score-line, the significance of goal to score-line, as well as the impact of dismissals, specific formations and tactics on the work rate of players. Work rates may vary between successive matches and different phases of the season, with players periodically experiencing a possible decline in performance. Distance covered per match may vary, which again suggests that players may not always be fully utilizing their physical capacity.[8] Reasons may include the specific tactical role chosen by the coach for the player or the self-imposed physical demands chosen by the player. Analysis of the total distance run by top-level players has been shown to vary significantly for individual players at different stages of the season with players covering greater distances at the end of the season.[15] These discrepancies may be partly explained by changes in the physical condition of the players as the work rate profile fluctuates in conjunction with the amount of training that is completed by teams.[27] During an intense schedule of three competitive matches in 5 days in the English Premier League, total distance run did not vary significantly,[69] suggesting this measurement may not be always be
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a valid indicator of a drop-off in performance during the season. Analysis of the physical efforts made in the various categories of movement may yield information on whether the performance of a player is decreasing across different games. A case report comparing the performance of an international French player over five successive weekend matches showed little variation in the distance covered within the different categories of running.[45] In top-class Danish soccer, the CV in high-intensity running has been shown to be 9.2% between successive matches, whereas it was 24.8% between different stages of the season.[15] The seasonal variation is most likely due to alterations in fitness as the competitive schedule reaches a peak. However, few reports have included the ambient conditions under which the games analysed were played.[27] As soccer is often played across all four seasons of the year, a future study to examine the relationship between physical performance and playing conditions is recommended. Similarly, a study comparing work rate performance between games played at varying times of the day would be pertinent. Teams may be required to play several games within a very short time-frame and there is potential for residual fatigue and incomplete recovery to affect the movement patterns of players during subsequent games. English Premiership soccer players were reported to demonstrate a significant increase in recovery time between high-intensity efforts during an intense period of three matches in 5 days.[69] Further work is needed to identify whether performance is affected significantly between playing positions. Nevertheless, this finding indicates that motion analysis data can play an important role in the approach to training and preparation before and during intense playing schedules. A future study could be designed to look at a possible relationship between work rate and injury occurrence. For example, a decline in high-intensity performance over several consecutive matches may suggest that recuperation of a player is needed to avoid becoming susceptible to ‘overtraining’. Similarly, players returning after injury could have their profiles scrutinized to see how they have recovered from intense periods of play, or have their performance compared against a benchmark profile obtained from previous matches. Once a susceptibility to fatigue is identified in individual players, the possible reasons for its ª 2008 Adis Data Information BV. All rights reserved.
Carling et al.
occurrence should be explored. A reduction in activity has been identified at the beginning of the second half compared with the first half.[57] During the break, players tend to rest, leading to a drop in muscle temperature and subsequently to reduced performance levels. Mohr and co-workers[87] presented evidence that undertaking a few minutes of low- to moderate-intensity exercise during the pause may help players to ‘ready’ themselves and to perform better physically straight after the break. As previously mentioned, fatigue can also occur as the end of a game draws near. Reduced exercise performance at the end of soccer games may be associated with lowered glycogen levels in individual muscle fibres.[77] Therefore, adequate attention to nutritional preparation (before, during and after matches) for competition is necessary. The effectiveness of nutritional interventions could be monitored using motion analysis in match-play. Monitoring efforts during training by means of heart rate monitors may also help coaches to avoid over-exerting players before matches and lowering their energy stores. This information can now be combined with motion analysis data from electronic transmitters worn by players to determine individual physiological workload during training. 3.5 Other Uses of Motion Analysis Research
Physiological studies and motion analysis research on elite soccer players have provided evidence that the total amount of work done during matchplay is related to the maximal aerobic power of players, which underlines the need for a high level of aerobic fitness.[17,88] This fact is especially important for certain playing positions such as midfield players who are expected to work harder than the other outfield positions. Motion analysis studies may be employed to determine the effects of a training intervention on competition work rate. Evidence shows thatimprovements in maximal oxygen uptake after an 8-week period of aerobic interval training corresponded to significant increases in the total distance covered during a match in elite junior players.[66] Players who are aerobically well trained can maintain their work rates better towards the end of the game than those of poorer aerobic fitness.[9] Increasing maximal aerobic power may also aid recovery following successive bouts of high-intensity anaerobic efforts, which produce transient fatiSports Med 2008; 38 (10)
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gue.[45] Its role is paramount because the recovery during repeated-sprint bouts in soccer is often of an active nature. A 6-week programme of aerobic interval training undertaken by a group of amateur senior players led to an 18% increase in high-intensity activities during competition.[17] However, there is still a limited amount of knowledge on the effects of training programmes on actual performance of players in matches at elite level. In addition, no motion analysis study in elite soccer has as yet assessed the degree to whether the physical demands of the game are adequately replicated in training. For example, it may be worthwhile determining whether players undertake comparable amounts of high-intensity exercise (e.g. number and duration of sprints) in training as in match-play. Over recent years, researchers have attempted to examine the validity of selected field tests by establishing links withon-field physicalperformance. The results from such tests can help to determine the physical capacity of players and whether they may be susceptible to experiencing fatigue during matchplay. The results from a ‘repeated sprint ability’ test have been highly correlated to the total distance covered in competition when sprinting.[44] Similarly, a strong correlation has been observed between an intermittent recovery test and both total distance run and sprint performance in elite females.[16] Mohr et al.[15] assessed the relationship between physical fitness and match performance at two standards of soccer. They compared the performance of top class soccer players versus moderate level players both in an intermittent recovery test and in work rates in match-play. The top players demonstrated superior performance in the intermittent test and carried out significantly more high-intensity running and sprinting during match-play. These results justify the use of field and laboratory fitness testing of players and linking the fitness data to work rate assessments. However, the majority of research has been carried out on top-level Scandinavian players and further research (and on a larger scale) is needed to test these relationships in higher level professional leagues and for differing age groups. Furthermore, although various tests have been related closely with the physiological load imposed through match-play, they still appear to lack ecological validity with respect to the motion types, directions, turns and intensities correspondª 2008 Adis Data Information BV. All rights reserved.
859
ing to the physical demands of the game and do not provide sufficiently adapted protocols for the individual playing positions within soccer.[21] These questions may be resolved using motion analysis methods for determining precise locomotor activities during matches. Motion analysis data drawn from match-play have also been employed to help design laboratorybased protocols to simulate soccer-specific intermittent exercise and examine factors such as the effects of training interventions,[89] nutritional strategies,[90] temperature[91] and fatigue on performance. In the application to fatigue, an intermittent-exercise protocol was designed to simulate the exercise intensities associated with playing a match in order to monitor the functional characteristics of lower limb muscles at half-time and at the end of the 90 minutes.[92] Results showed a progressive increase in muscle fatigue due to a decline in muscle strength as exercise continued. Findings therefore had implications for competitive performance and further understanding of the reported increased risk of injury towards the end of the game. A future focus on the relationship between injury occurrence and fatigue during actual competitive match-play should be beneficial. For example, motion analysis techniques could be employed to examine whether players are more at risk of injury after periods of high-intensity exercise.
4. Conclusions A thorough understanding of the physical demands of soccer via information on player work rates is required so that optimal training and preparation strategies can be constructed. As shown in the present review, an ever-increasing number of scientific investigations based on motion analysis techniques are providing important information on elite soccer play. These investigations have identified the activity profiles and physical requirements of contemporary elite soccer as well as the demands of individual playing positions. Motion analysis research has also allowed investigators to determine the extent of fatigue experienced by players during competition as well as variations in physical performance over the course of the season. There are also possibilities to link fitness data to work rate assessments and to determine the effects of training interventions on match performance. Sports Med 2008; 38 (10)
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Many of these investigations into work rate have been possible thanks to major advances in computer and video technology, which are providing more efficient ways of obtaining and analysing data, especially on a larger scale. A plethora of commercial analysis systems are now available, albeit with a price range varying by many thousands of dollars. The cost of many systems currently used in elite soccer is often prohibitive to all but the wealthiest clubs. Similarly, many researchers are still using older techniques, given that they do not have access to these more advanced technologies due to the large costs associated with using them. Using information derived from these latest techniques, academics could start to test and build upon existing research by exploring some of the gaps and questions identified throughout this review. Furthermore, conducting research into how these technologies are actually being put into use within coaching contexts would be pertinent, as there is little appreciation about how effectively and efficiently they are being translated and adopted by practitioners to prepare and develop members of their squad. This reservation applies to both the operators’ comprehension and the coaches’ use of data derived from these tools. Additionally, the measurement precision and reliability of systems proven on the basis of sound scientific evidence has not always been satisfactorily demonstrated. No current method has been accepted as the ‘gold’ standard approach to work rate analysis, and few investigators have attempted to make comparisons between different methodologies and technologies. It is imperative that researchers investigate the scientific legitimacy of these systems so that applied practitioners and the academic community can be assured of their accuracy when employing these methods. Nevertheless, the perfecting of motion analysis technologies will no doubt continue as it has done over recent years, with real-time analysis and application becoming the norm.
Acknowledgements The authors have received no funding for the preparation of this article. The authors have no conflicts of interest that are directly relevant to the content of this review except that Christopher Carling and Lee Nelsen have previously participated in the development of the AMISCO Pro match analysis system and Jonathan Bloomfield was previously employed by Prozone Group Limited.
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77. Bangsbo J, Mohr M, Krustrup P. Physical and metabolic demands of training and match-play in the elite football player. J Sports Sci 2006 Jul; 24 (7): 665-74 78. Zubillaga A, Gorospel G, Mendo AH, et al. Analysis of high intensity activity in soccer highest level competition [abstract no. O-013]. J Sports Sci Med 2007; 6 Suppl. 10: 10 79. Williams A, Williams AM, Horn R. Physical and technical demands of different playing positions. Insight FA Coaches Assoc J 2003; 2 (1): 24-8 80. Rampinini E, Impellizzeri FM, Castagna C, et al. Technical performance during soccer matches of the Italian Serie A league: effect of fatigue and competitive level. J Sci Med Sport. In press 81. A´lvarez JCB, Castagna C. Activity patterns in professional futsal players using global position tracking system [abstract]. J Sports Sci Med 2007; 6 Suppl. 10: 208 82. Carling C. Football: a game of chance or does match analysis have the answers? Insight FA Coaches Assoc 2002; 5 (3): 16-7 83. Krustrup P, Mohr M, Steensberg A, et al. Muscle and blood metabolites during a soccer game: implications for sprint performance. Med Sci Sports Exerc 2006; Jun; 38 (6): 1165-74 84. Rampinini E, Coutts AJ, Castagna C, et al. Variation in top level soccer match performance. Int J Sports Med 2007; Dec; 28 (12): 1018-24 85. O’Donoghue PG, Tenga A. The effect of score-line on work rate in elite soccer. J Sports Sci 2001; 19 (2): 25-6 86. Bloomfield JR, Polman RCJ, O’Donoghue PG. Effects of score-line on work-rate in midfield and forward players in FA Premier League soccer. J Sports Sci 2004; 23 (2): 191-2 87. Mohr M, Krustrup P, Nybo L, et al. Muscle temperature and sprint performance during soccer matches: beneficial effects of re-warm-up at half time. Scand J Med Sci Sports 2004 Jun; 15 (3): 136-43 88. Reilly T. Motion analysis and physiological demands. In: Reilly T, Williams AM, editors. Science and soccer. London: Routledge, 2003: 59-72 89. Sari-Sarraf V, Reilly T, Doran DA. Salivary IgA responses to intermittent and continuous exercise. Int J Sports Med 2006; 27: 849-55 90. Clarke ND, Drust B, MacLaren DPM, et al. Strategies for hydration and energy provision during soccer-specific exercise. Int J Sports Nutr Exerc Metab 2005; 15: 625-40 91. Drust B, Cable NT, Reilly T. Investigation of the effects of pre-cooling on the physiological responses to soccer-specific intermittent exercise. Eur J App Phys 2000; 81: 11-7 92. Rahnama N, Reilly T, Lees A, et al. Muscle fatigue induced by exercise simulating the work rate of competitive soccer. J Sports Sci 2003; 21: 933-42
Correspondence: Christopher Carling, LOSC Lille Me´tropole, Centre de Formation, Domain de Luchin, Grand Rue-BP79, Camphin-en-Pe´ve`le, 59780, France. E-mail:
[email protected]
Sports Med 2008; 38 (10)
Sports Med 2008; 38 (10): 863-878 0112-1642/08/0010-0863/$48.00/0
REVIEW ARTICLE
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A Review of Femoroacetabular Impingement in Athletes Michael J. Keogh1 and Mark E. Batt2 1 Faculty of Medicine and Health Sciences, University of Nottingham Medical School, Queens Medical Centre, Nottingham, UK 2 Centre for Sports Medicine, Nottingham University Hospitals, Nottingham, UK
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 864 1. Anatomy of the Hip Joint. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 864 2. Specific Anatomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865 2.1 The Labrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865 2.2 Labral Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 865 3. Presentation of Femoroacetabular Impingement (FAI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 866 3.1 History. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 866 3.2 FAI in Sport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 866 3.3 Physical Examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867 4. Biomechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867 4.1 CAM FAI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867 4.2 Pincer FAI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 868 5. Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 870 6. CAM Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 870 6.1 Pincer Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 7. Histology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 7.1 Acetabular Labrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 7.2 Cartilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 8. Investigating FAI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 8.1 Bone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 8.1.1 Disadvantages of CT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 873 8.2 Imaging Labrum and Cartilage in FAI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 873 8.3 Diagnostic Arthroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 874 9. Treatment Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 874 9.1 Conservative Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 874 9.2 Operative Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 874 9.2.1 Open. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 874 9.2.2 Arthroscopic Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 875 10. Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 875
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Abstract
There are a multitude of well recognized hip and groin injuries that commonly affect athletes; however, a more recently recognized and possibly often overlooked cause of hip pain is that of femoroacetabular impingement (FAI). FAI is characterized by abutment of the femoral neck against the acetabular rim, which may occur by two mechanisms known as ‘CAM’ or ‘pincer’ impingement, although most commonly by a mixture of both. CAM impingement is characterized by abutment of the femoral neck against the acetabulum due to a morphological abnormality of the femoral head-neck junction. Pincer impingement occurs where an abnormality of the acetabulum results in impingement against an often normal femoral neck. Both CAM and pincer impingement are known to result in pathological consequences of cartilage delamination and labral lesions, leading to significant pain and disruption to athletic performance and activities of daily living in athletes. There are currently several methods of assessing the degree of impingement by use of CT and magnetic resonance imaging scans, which can be used in conjunction with magnetic resonance arthrography and arthroscopy to assess the damage caused to the underlying structures of the hip. Both open and arthroscopic surgical methods are used, with recent reports in athletes showing excellent results for lifestyle improvement and frequency of returning to sport. In cases of hip and groin pain in athletes, it is important to remember to look for typical history, and examination and imaging findings that may suggest a diagnosis of hip impingement. This article goes some way to explaining the principles, consequences and management of FAI.
Hip and groin injuries are suggested to account for 5–6% of all adult athletic injuries and are a significant cause of morbidity in athletes. Conditions such as myositis ossificans, piriformis syndrome, stress fractures, strains and snapping hip are established and well reported causes of such athletic injuries. However, although first reported in 1957,[1] we are currently seeing greater reporting of acetabular labral tears and intra-articular cartilage damage in athletes, and a cause of both these problems is femoroacetabular impingement (FAI). FAI, as explained in detail in section 4, has two different aetiologies, termed ‘CAM’ and ‘pincer’ impingement, which may occur together or in isolation. CAM impingement is primarily an abnormality of the femoral head-neck junction, whereas the pincer type is principally an ª 2008 Adis Data Information BV. All rights reserved.
abnormality of the acetabulum causing impingement against the femoral neck. Both of these subtypes vary slightly in their pathological consequences, but both have been shown to cause cartilage delamination, labral tears, and have been linked to early osteoarthritis of the hip.[2-4] 1. Anatomy of the Hip Joint The hip joint is a ball and socket joint consisting of the femoral head and the acetabulum of the pelvis, and enables a wide range of movement with three degrees of freedom. Articular cartilage, composed predominantly of type II collagen, covers the vast majority of the femoral head. The articular surface of the acetabulum is also composed of articular cartilage distributed Sports Med 2008; 38 (10)
A Review of Femoroacetabular Impingement in Athletes
Head of femur Ilium Ant. inf. iliac spine Spine of ischium
Fovea capitis Ligamentum teres Isc
hiu
m
Pubis
Iliofemoral ligament
Lesser trochanter Femur
Fig. 1. Lateral diagram of the hip joint. Reproduced from the 39th edition of Gray’s Anatomy[5] (Churchill Livingstone), with permission. Copyright ª Elsevier 2004. Ant. inf. = anterior inferior.
acetabulum and runs circumferentially around its periphery. The labrum ceases at the lower edge of the acetabulum, but the ring is completed by the transverse ligament of the acetabulum, which acts as a heavy fibrous band in continuity with the labrum. The distal free edge of the labrum is narrower than its insertion to the acetabulum, creating a triangular cross-section. It functions to enable the acetabulum to cup slightly more than half of the sphere of the femoral head. The labrum has several surfaces with varying characteristics in the hip joint. The external surface is in contact with the joint capsule, an internal surface, which is involved in articulation with the femoral head, and the previously mentioned proximal attachment to the acetabular rim. The distal edge defines the outer limit of the acetabulum. 2.2 Labral Function
The acetabular labrum is similar in structure to the glenoid labrum of the shoulder, and both
Capsular ligament
Acetabulum
around its periphery. The central acetabular floor is non-articular, being a fatty layer, and is termed the pulvinar. The ligamentum teres joins the femoral head to the acetabulum, and may play a role in maintaining joint stability. Circumferentially around the acetabulum lies the acetabular labrum, which is discussed in more detail in section 2.1, and is important to an understanding of FAI (figure 1 and figure 2). Three major ligaments surround the hip joint capsule. Anteriorly lies the iliofemoral ligament, which tightens on hip extension. Inferomedially lies the pubofemoral ligament, the weakest, which tightens in hip extension and abduction. Finally, the ischiofemoral ligament runs horizontally and posteriorly, its fibres tightening with hip extension and limiting internal rotation.
865
Cotyloid ligament Capsular ligament Ligamentum teres
2. Specific Anatomy 2.1 The Labrum
The acetabular labrum is a fibrocartilagenous rim, which is attached to the bony edge of the ª 2008 Adis Data Information BV. All rights reserved.
Fig. 2. Anterior angle diagram of the bones and ligaments of the hip joint. Reproduced from the 39th edition of Gray’s Anatomy[5] (Churchill Livingstone), with permission. Copyright ª Elsevier 2004.
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act to deepen the respective depths of their socket. However, the deepening effect of the acetabular labrum is thought to be less important than its effect of enhancing stability by providing a negative intra-articular pressure within the hip joint during joint distraction.[6] In 1995, Kim and Azuma[7] suggested that the acetabulum was involved in nocioception and proprioception after analysing 23 human cadaveric labrums, and more recently, work has looked at the involvement of the acetabular labrum in fluid pressurization. Ferguson et al.[8,9] showed that in the absence of an intact labrum, hydrostatic pressures within the joint decreased, also affecting joint lubrication within the hip joint. Hence, the labrum can be thought of as acting to prevent damage to the articular cartilage by sealing the joint and preventing fluid loss.[10] However, it should be noted that in 1998, Konrath et al.[11] showed that in cadaveric hips in which the labrums had been removed, no appreciable change with regard to contact area, load or mean pressure could be noted after removal of the labrum. 3. Presentation of Femoroacetabular Impingement (FAI) 3.1 History
FAI usually presents in young and middle-aged adults, typically men, with insidious onset groin pain that may be preceded by minor trauma, although many patients will report no history of any specific precipitating factor. During the early stages, the pain is intermittent and may be exacerbated by physical activities and exercise, and hence, a misdiagnosis of hip or groin pain of soft-tissue origin may occur. The pain experienced may also be brought on by prolonged sitting. An incorrect diagnosis at this stage may then lead to several weeks or months of inappropriate management. 3.2 FAI in Sport
Although FAI is a relatively recent concept, there is a growing body of evidence to support this ª 2008 Adis Data Information BV. All rights reserved.
condition as an established cause of hip and groin pain in athletes. FAI is a process by which morphological abnormalities of the hip causes damage to the surrounding acetabular labrum and cartilage of the hip.[12,13] With regard to sport, it has been known since 1979 that bony abnormaalities of the femoral neck cause hip pain in athletes,[14] and more recently, FAI has been shown to be a major source of hip pain, decreased range of movement and reduced performance in athletes.[15] The aetiology of the condition is still unclear, and it remains to be seen whether certain sports induce femoral neck abnormality through osteophyte-type formation or simply exaggerate a problem by utilizing specific ranges of motion, crucially that of internal rotation whilst in hip flexion (e.g. hockey goalkeeping stance). The pain exhibited on internal rotation in flexion in patients with FAI is due to the abutment and impingement of the femoral neck against the acetabular labrum, and it could be postulated that sports in which this mechanism is utilized would be in those in which FAI is most common, such as hockey, tennis, martial arts, weight lifting, soccer and horse riding. There are very few published data demonstrating the prevalence of FAI in the general population, but studies such as that by Murray[16] in 1971 showed that what we now know to be the ‘CAM’ type FAI was probably present in 24% of high-activity athletes, which is higher than the estimated 10–15% prevalence in the general population.[12] It is also known that conditions such as malunion of femoral neck fractures can be related to sport[17] and lead to CAM impingement.[18,19] These figures give rise to the possibility that certain sports increase the risk of developing the condition, not simply of becoming symptomatic, and also may explain why young men are most at risk for this condition. It is important to note the severe impact that this condition may have on athletes. Reports describe significant impairment in activities of Sports Med 2008; 38 (10)
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daily living,[15] together with severe limitations in sporting activities, particularly high-demand sports involving cutting or sprinting. In these activities, 88% of athletes reported moderate to total inability to perform. Bizzini et al.[20] reported that the loss of range of motion (ROM) in hip rotation, especially internal rotation, was the main performance-limiting factor in their study. It is therefore important that FAI becomes a more widely appreciated cause of hip pain, especially in sports involving internal rotation in flexion, and should be considered as a cause of hip and groin pain in these athletes. Thus, this article focuses on the underlying pathology, clinical assessment, and radiographic and diagnostic imaging findings.
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that hip flexion on the affected side was 91 less than the opposite limb, together with mean reductions of adduction (31 less), and internal rotation (41 less). They also showed that the impingement test was positive in 99% of athletes, and the FABER (Flexion ABduction and External Rotation) test was positive in 97%. Although anterior impingement is common, pincer impingement (posteroinferior lesions) is also often found; however, the most common pathology is often reported to be a combination of the two.[12] To test for posteroinferior impingement, the patient lies supine and extends their leg over the edge of the examination couch. The physician then provides external rotation of the hip whilst the leg is extended, which will reproduce their symptoms of groin pain should a posteroinferior lesion be present (figure 3).
3.3 Physical Examination
Hip impingement tests in patients with FAI have been shown to be almost always positive, and are therefore of paramount importance to evaluation.[15,21,22] The use of these tests in hip examination should help lead to an earlier diagnosis of FAI. This is clinically relevant, as Philippon et al.[15] recently described that the average time from onset of symptoms to treatment in a cohort of athletes was 29.6 months, and Bizzini et al.[20] reported an average time of 13 months in athletes. The impingement test is performed with the patient lying supine, as the physician adducts and flexes the affected hip to 901 whilst gently internally rotating, thus causing the femoral neck to abut against the acetabular rim. Additional internal rotation in this position will cause a sharp pain if a labral, chondral or both types of lesion are present.[22] Thus, limitation of internal rotation and pain at end range are critical to the early diagnosis of this condition. A positive impingement test is the common sole clinical finding of the CAM type impingement (anterosuperior lesion). Recently, Philippon et al.[21] reported their examination findings of the clinical presentations of FAI, which showed ª 2008 Adis Data Information BV. All rights reserved.
4. Biomechanics
4.1 CAM FAI
It has also been suggested that FAI may occur with a femoral head-neck junction that is morphologically and anatomically normal, but in these instances, impingement occurs as a result of excessive and extreme ranges of motion.[23] This may well be the case in some athletes, and is possibly related to hyperextensibility, which may be deemed advantageous in certain sports. There are, however, several other predisposing conditions that may result in an anatomical deformity of the femoral head-neck, resulting in anterior or CAM impingement. Conditions such as rotational malunion due to previous femoral neck fracture,[18] flattening of the femoral head due to femoral head necrosis,[24] and posterior tilt of the femoral head due to slipped capital femoral epiphysis[25] have all been implicated as causes of FAI, as well as iatrogenic causes such as femoral osteotomies, where there is a reduction in joint clearance post-operatively (figures 4-7). Sports Med 2008; 38 (10)
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Fig. 3. Images of the impingement test from two angles. The affected leg is flexed, adducted and internally rotated, causing the abnormal anterolateral portion of the femoral head-neck junction to abut against the acetabular rim. This causes pain and is therefore a positive impingement test in patients with femoroacetabular impingement.
4.2 Pincer FAI
In cases of pincer impingement, the femoral head may be morphologically normal; however, abutment results from an acetabular abnormality. A common cause is acetabular overcoverage of the femoral head known as coxa profunda. In this instance, the centre-edge or ‘Wiberg’s’ angle, which measures the lateral covering of the femoral head by the acetabular roof is greater than 401[28] with a normal range for adults stated as being 20–461[29] (figure 8). Other causes of pincer impingement are protrusio acetabuli, in which the medial wall of the acetabulum invades the pelvic cavity with associated medial displacement of the femoral head. This is associated with a variety of conditions, most noticeably Marfan’s syndrome.[30,31] Again, Wiberg’s angle is greater than 401, ª 2008 Adis Data Information BV. All rights reserved.
and other features, such as crossing of the ilioischial line by the acetabular line, occur medially.[32]
Fig. 4. Diagram of a normal hip joint with normal contours and anatomy (reproduced from Lavigne et al.,[26] with permission).
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Fig. 5. Diagram of a hip with CAM impingement. Shaded area of increased bony excrescence resulting in reduced femoral head-neck offset – CAM impingement (reproduced from Lavigne et al.,[26] with permission).
Another cause of pincer impingement is thought to be acetabular retroversion, in which the acetabulum is posteriorly orientated with reference to the sagittal plane.[33] It may be an isolated abnormality, or associated with other developmental abnormalities and, whilst initially recognized as a cause of hip pain, is now thought to be a cause of FAI.
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Fig. 7. Abutment of the labrum: when in flexion, the reduced headneck offset comes into contact with the acetabular labrum, causing labral and articular damage (reproduced from Beck et al.,[27] with permission).
In cases of pincer impingement, continued impaction of the acetabular rim against the femoral head is thought to induce degeneration of the labrum and eventual ossification of the acetabular rim, which leads effectively to a further deepening of the acetabulum and worsening overcoverage. This results in both anterior im-
30˚
E
C2
Fig. 6. Diagram of CAM impingement in extension. This diagram shows that the section of the femoral neck with reduced head-neck offset is not impinging on the acetabular labrum in this position (reproduced from Beck et al.,[27] with permission).
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C1
Fig. 8. Diagram of centre-edge (CE) or Wiberg’s angle. The vertical line is perpendicular to the horizontal line extending between the centre of each femoral head (C1 and C2). The edge (E) point is the most lateral point of the acetabulum. The CE (Wiberg’s) angle is measured between the vertical line passing through C1 and C2 and E.
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pingement and often an additional posteroinferior lesion due to an affective leverage of the femoral head, resulting in what Parvizi and Ganz[23] called a ‘contre-coup’ lesion of the cartilage in the posteroinferior acetabulum (figures 9-11). 5. Pathology The biomechanics described in section 4 explain how FAI may damage the acetabular labrum and cartilage. Acetabular labral disorders have been linked to being a source of hip pain[2,7,34] and have also been linked to the development of osteoarthritis of the hip.[2,35,36] 6. CAM Pathology In CAM impingement, Beck et al.[12] showed that separation of the acetabular cartilage from the labrum occurs in the anterosuperior region, which has also been shown to be the most common site of injury in several other studies.[22,27,37-40] In the study by Beck et al.,[12] all patients with a pure CAM impingement showed cartilage damage in the antero-superior area, maximal at the 1 o’clock position to a mean depth of 11 mm, which is roughly one-third of the depth of the cartilage at this point.
Fig. 10. Diagram of pincer impingement in normal extension. In normal extension, there is no abutment of the overcoverage against the femoral head-neck junction (reproduced from Beck et al.,[27] with permission).
The pathological findings can be explained by looking at the structure of the normal acetabulum. In a normal hip, the acetabular labrum merges with the acetabular cartilage through a transition zone of roughly 1–2 mm,[39] but in all patients with CAM impingement, separation of the acetabular cartilage from the labrum was seen. As the labrum has a stable fixation to the acetabular rim, it appears that the abutment of the ‘CAM’ causes a pathological under-surface separation of cartilage from labrum across this ‘transition zone’. 6.1 Pincer Pathology
Fig. 9. Diagram of acetabular overcoverage causing pincer impingement. The shaded area shows acetabular overcoverage of the femoral head, deepening the acetabulum-pincer impingement (reproduced from Lavigne et al.,[26] with permission).
ª 2008 Adis Data Information BV. All rights reserved.
In cases of a pincer FAI, a more circumferential pattern of disease[12] has been noted, and this type of impingement may help to explain why additional posterior lesions have been noted on arthroscopy in previous studies of labral tears.[41,42] Labral lesions were shown to be maximal between the 11 and 1 o’clock positions, although maximal cartilage damage was seen at the 12 o’clock position, with the mean depth of the cartilage lesion being 4 mm.[12] Beck et al.[12] also Sports Med 2008; 38 (10)
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matrix with no signs of inflammation. This shows that FAI is a chronic process that gradually produces a degenerative reaction at the site of impingement. Ironically, Ito et al.[43] expected to see more extensive labral tip involvement in the pincer group, due to the ‘bumper’ effect of the femoral neck against the labrum; however, this was not evident in their study. Furthermore, if discovered early, the lack of labral tip involvement provides the potential for labral reattachment with surgical intervention. 7.2 Cartilage Fig. 11. Pincer impingement in flexion showing abutment of the labrum against the femoral neck, and as the femoral head is levered out by the acetabulum, a posterior ‘contre-coup’ lesion also occurs (reproduced from Beck et al.,[27] with permission).
showed that 31% of pincer-impinged patients showed posteroinferior roughening of the femoral head, and 62% had cartilage damage posteroinferiorly. Again, this is due to posterior subluxation of the femoral head once further flexion occurs on an already impinging anterosuperior rim. Seldes et al.[39] also showed endochrondral ossification within the labrum, and Beck et al.[12] proposed that repeated microtrauma induces bone growth at the base of the labrum, further deepening the acetabulum and compounding the problem.
7. Histology 7.1 Acetabular Labrum
The normal acetabular labrum is composed of circumferential collagen fibres running parallel to the acetabular rim, together with small, flat, inactive fibroblasts. Studies have shown that aging produces labral tears with internal cleavage being demonstrated on histological examination.[39] Conversely, labral histological examination from patients with FAI showed no mechanical lesions in the matrix, and samples were consistent with a chronic degenerative process,[43] showing only a thickened and disorganized, occasionally cystic ª 2008 Adis Data Information BV. All rights reserved.
Cartilage in patients with FAI has been shown to be coarse with relatively low levels of proteoglycans. The heterotrophic bone shows large amounts of unmineralized osteoid formation with pseudocysts, attributable to increased osteoblastic activity at the site.[43] 8. Investigating FAI 8.1 Bone
Routine radiographic evaluation of potential FAI in an athlete should include an anteroposterior view of the pelvis with the patient lying supine with the leg in 151 of internal rotation.[44] The radiographer should then provide an image with a film focus distance of 1.2 m with the central beam directed to the mid-point between both anterior superior iliac spines and the superior border of the pubic symphysis.[44,45] For the cross-table lateral view, the leg should be internally rotated, with a film distance of 1.2 m and the beam directed at the inguinal fold.[46] An alternative view is that of a Dunn/Rippstein, where the hip is placed in 451 of flexion to show anterior femoral head-neck junction abnormalities.[47] The anteroposterior radiograph may show a reduced head-neck offset, or herniation pits, both of which have been linked to FAI.[23] It may also show the previously discussed specific deformities on x-ray such as pistol grip,[48,49] tilt[16] or Sports Med 2008; 38 (10)
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subclinical slipped capital femoral epiphysis[49] on anteroposterior and lateral radiographs, as well as other conditions associated with FAI, such as coxa profunda, protrusion acetabuli, coxa vara or extreme coxa valga. However, although any of the causes of FAI listed above may be seen on normal radiographs, many causes may also be missed[3,16,49-51] because their pathology appears to be absent in the frontal/coronal plane. It is therefore very important to obtain lateral films (figure 12a and 12b).
Fig. 12. (a) Left hip radiograph of a young girl with CAM impingement. Out of round bump on the head overloads the acetabular cartilage as it is rotated into the joint (arrow). (b) Right hip radiograph showing pincer impingement. Shortened head-neck offset abuts the rim of the acetabulum (lower arrow), eventually causing ossification of the labrum, which then looks similar to a shear-type fracture (upper arrow) [reproduced from Sampson,[52] with permission. Copyright ª Elsevier 2005].
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Magnetic resonance imaging (MRI) is also now commonly used in the evaluation of the painful non-arthritic hip,[53,54] and several methods of identifying FAI using MRI[3,50,55] and CT[56] have been developed, which also enable a quantifiable assessment of the deformity. An early method was developed by Ito et al.,[3] who used a 1.5T MRI scanner after intra-articular injection of gadalonium-diethylenetriamine penta-acetic acid[37] in the symptomatic hip to analyse 24 patients with positive impingement tests. They used fast low angled shot (FLASH) sequences and coronal oblique sections through the femoral head to show that patients with FAI had no difference in the mean angle of the femoral neck, but did have a significant reduction in femoral anteversion and head-neck offset in the anterior aspect of the femoral neck compared with controls. In 2002, Notzli et al.[50] developed a method of accurately measuring the anterior margin of the waist of the femoral neck and produced an angle, the alpha angle, using 39 patients with groin pain and positive impingement tests. Images were obtained using a 1T MRI scanner with a flexible transmit/receive surface coil after an MR contrast injection. Again, FLASH sequences were used, this time parallel to the axis of the femoral neck, passing through the centre of the femoral head, giving a view corresponding to a lateral radiograph with the plate parallel to the femoral neck. They showed that in patients with FAI, the alpha angle was an average of 741 compared with 421 for the control group, and defined an alpha angle of greater than 501 as potentially abnormal. CT is well established in the assessment of orthopaedic abnormalities of the hip,[57-59] and provides a better image of the bony contour due to the transparency of soft tissues on this modality. In 2001,[60] multi-dimensional image post-processing was used to determine the femoral neck axis to a higher degree of accuracy than previous conventional 2-dimensional CT, which had limitations in identifying subtle contours of the femoral head-neck axis.[13] Beaule at al.[56] have also used 3-dimensional CT to assess the Sports Med 2008; 38 (10)
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anterior and posterior concavity of the femoral head-neck junction in 30 patients (36 hips) with a positive impingement sign. They measured the alpha angle, showing that mean alpha angle in the symptomatic group was 66.41 versus 43.81 (p = 0.001). They also showed that symptomatic males had significantly greater alpha angles than symptomatic females (73.8 vs 58.7; p = 0.009). 8.1.1 Disadvantages of CT
CT scanning should be used judiciously as it puts patients at an increased risk of radiation compared with MRI. The dose of radiation from a CT pelvis is approximately 9 mSv, which is roughly equivalent to 3 years’ natural background radiation.[61] The radiation dose does vary across institutions and should be minimized to enhance the risk-benefit ratio that CT provides for superior bone imaging[62] (figure 13). 8.2 Imaging Labrum and Cartilage in FAI
Initially, it was thought that MRI would accurately assess and diagnose labral tears. MRI features suggestive of a labral tear include a thickened labrum with no recesses, an irregularly shaped or non-triangular labrum, a labrum with
Alpha angle
Fig. 13. CT measurement of alpha angle. A perfect circle was centred over the acetabular segment of the femoral head. The alpha angle was drawn from the transition of the head into the neck where the neck radius exceeds the head radius. The neck axis was made parallel to the anterior femoral neck cortex in line with the head centre (reproduced from Beaule et al.,[56] with permission of WileyLiss, Inc., a subsidiary of John Wiley & Sons, Inc.).
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increased signal intensities on T1 imaging, or detachment.[63] As a result of the tendency of the joint capsule to collapse against the acetabular rim, initial studies showed considerable difficulty in distinguishing discrete labral tears on MRI;[64,65] however, a recent study by James et al.[66] had excellent results using MRI scans in patients with FAI, detecting 100% of labral tears and between 89% and 94% of articular cartilage damage. They stated and highlighted the importance of using a surface coil in routine hip imaging. MR arthrography is an alternative and complimentary method of demonstrating cartilage and bony abnormalities within the hip joint[67] and is an accurate method of diagnosing and assessing tears in the acetabular labrum.[37,65,68] A joint effusion may improve delineation of intra-articular structures[69] by increasing the distance between these structures, and thus may be deemed helpful. Kassarjian et al.[70] assessed the triad of headneck morphology, cartilage and labral abnormalities in 42 hips of CAM type FAI using magnetic resonance arthrography (MRa). In their study, a 1.5T MRI scanner (with a torso or cardiac coil) was used to image the affected hip whilst the patient was supine, with the leg in slight internal rotation to bring the femoral neck into the coronal plane. Their study showed that of the 42 hips studied, all had a labral abnormality, 40 had a cartilage abnormality and 37 had all three (cartilage, labral and head-neck) abnormalities. A study by Czerny et al.[65] demonstrated that of 22 hips that underwent surgery for a labral tear diagnosed by MRa, 20 (91%) were accurately diagnosed. In a subsequent study by Leunig et al.,[37] 18 of 21 (86%) patients who had surgery for a labral tear had the correct preoperative diagnosis based on MRa. However, recent non-arthrographic MRI studies, such as that of James et al.,[66] have shown slightly better results than those of MRa for the detection of labral tears and intra-articular cartilage damage; thus, it remains to be seen whether the arthrogram component remains necessary. Sports Med 2008; 38 (10)
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8.3 Diagnostic Arthroscopy
Intra-articular hip injuries in athletes can cause significant functional disability and can ultimately be career ending. Arthroscopy enables direct observation of the joint and thus enhances diagnostic specificity. Arthroscopy of the hip has lagged behind that of the other joints, probably because of its technical challenges and previously perceived difficulties.[71] However, the technique is becoming increasingly adopted and is now regarded as an accepted or ‘gold standard’ of care.[72] Several authors have used diagnostic arthroscopy as their principle method of diagnosis of acetabular labral tears[73,74] despite the possible complication rate of 1.6–5%, which is mainly related to the traction forces applied, such as transient neuropraxis and fluid extravasation.[75] A study in 1999 of 328 patients by Baber et al.[76] showed that using hip arthroscopy altered the diagnosis in 53% of patients with hip pain, and the most commonly missed defects were osteoarthritis, osteochondral defects, labral tears and loose bodies. Their overall conclusions were that hip arthroscopy was a useful diagnostic tool in assessing and treating the adult patient with an uncertain cause of hip pain postMRI scan. However, as discussed above, the improvements in MR imaging may challenge the role for diagnostic arthroscopy in these patients.[37,65,66] 9. Treatment Options A synopsis of the current treatment possibilities for FAI is outlined below. 9.1 Conservative Treatment
A trial of activity modification, particularly a reduction of excessive end-range movements, together with appropriate anti-inflammatory medications and analgesics may reduce the pain. For some athletes, this may require specific technique modification with associated muscle balance work. Indeed, an initial period of conservative ª 2008 Adis Data Information BV. All rights reserved.
management is recommended, recognizing that many athletes may subsequently need surgical intervention. 9.2 Operative Treatment
The aim of surgery is to increase the clearance between the femoral head and the acetabulum to alleviate the abutment and halt the process of chondral and labral damage. Both open[27,38] and arthroscopic techniques[77-79] have been developed to improve hip clearance. 9.2.1 Open CAM
Open procedures involving surgical dislocation for FAI have long been recommended to provide a full and unobstructed view of the femoral head and acetabulum.[26] For CAM impingement with a non-spherical femoral head, surgical dislocation of the femoral head is performed,[80] followed by excision osteoplasty of small ‘sleeves’ of bone from the impinging section of the femoral head. Varying amounts of the anterolateral portion of the femoral headneck junction can be removed to alleviate the symptoms; however, removing more than 30% results in an increased rate of fracture in response to axial loading,[81] and is therefore to be avoided. Pincer
If the abnormality lies with the acetabulum, then a resection osteoplasty of the excessive acetabular rim may be undertaken, or the retroverted acetabulum may be reoriented by periacetabular osteotomy.[82] The side effects of open surgical dislocations have been shown to include post-operative stiffness, heterotrophic ossification, and sciatic nerve neuropraxis,[18] and thus it is not without significant risk. The post-operative management of patients undergoing these procedures involves approximately 6–8 weeks of ambulation with a toe-touch weight-bearing programme, with hip flexion Sports Med 2008; 38 (10)
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limited to 701.[26] After this phase, several phases involving controlled ambulation and ROM exercises have been used, with a view to returning to sport from 25 weeks post-operatively.[20] Only a few studies have reported the outcomes of open surgical procedures for FAI[27,38] with typically good results, but only recently have functional outcomes been assessed in athletes, showing a return to high-level sport in hockey players roughly 9 months after surgery,[20] which is promising.
9.2.2 Arthroscopic Treatment
Arthroscopic techniques for treating the CAM and/or pincer bony deformity, as well as repairing the resultant damage of the cartilage and labrum, have been described,[77-79] and the use of these techniques appears to be rapidly increasing. This procedure requires specific positioning of the patient in a modified supine position, with traction then applied to the break the vacuum of the hip joint prior to portal placement. First, the intra-articular pathology, such as chondral defects or labral repairs, is addressed. Following this, an osteoplasty is performed. For pincer impingement, there are three different methods described depending on the extent of overhang, the details of which are beyond the scope of this article. Post-operative management of arthroscopic treatment for FAI typically involves 4–8 weeks of 20 lbs (~9 kg) of flat foot weight bearing, with specific foot boots worn at night for 10 days to limit hip rotation,[79] with or without the use of a modified hip brace. The initial results of patients treated for FAI by arthroscopic surgery from both Sampson[52] and Guanche and Bare[83] were encouraging. Also, Philippon et al.[15] recently described their experiences with professional athletes, and reported 93% returning to professional sport after the procedure and 78% remaining active in professional sports 1.6 years later after arthroscopic decompression of their FAI. ª 2008 Adis Data Information BV. All rights reserved.
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10. Conclusion The diagnosis and management of groin pain in athletes can be challenging, and FAI should be considered in the differential diagnosis, especially in those athletes participating in sports that involve internal rotation and loading in hip flexion. History and careful physical examination, especially the importance of incorporating hip impingement tests will go some way to establishing a diagnosis in many of these athletes. Emerging methods of imaging are becoming of paramount importance in determining the effects and degree of impingement. As both open and arthroscopic surgical procedures continue to improve, it is important that the diagnosis of FAI is established to reduce morbidity in these patients and athletes. Acknowledgements No funding was provided for the preparation of this paper, and the authors have no conflicts of interest that are directly relevant to the contents of this review.
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26. Lavigne M, Parvizi J, Beck M, et al. Anterior femoroacetabular impingement: part I. Techniques of joint preserving surgery. Clin Orthop Relat Res 2004; (418): 61-6 27. Beck M, Leunig M, Parvizi J, et al. Anterior femoroacetabular impingement: part II. Midterm results of surgical treatment. Clin Orthop Relat Res 2004; (418): 67-73 28. Lequesne M, Morvan G. Description of the potential of an arthrometer for standard and reduced radiographs suitable to measurement of angles and segments of hip, knee, foot and joint space widths. Joint Bone Spine 2002; 69 (3): 282-92 29. Fredensborg N. The CE angle of normal hips. Acta Orthop Scand 1976; 47 (4): 403-5 30. Hohle B. Familial occurrence of protrusio acetabuli [in German]. Beitr Orthop Traumatol 1978; 25 (5): 261-5 31. Van de Velde S, Fillman SR, Yandow S. Current concepts review: protrusion acetabuli in Marfan syndrome: history, diagnosis and treatment. J Bone Joint Surg Am 2006; 88 (3): 639-46 32. Armbuster TG, Guerra Jr J, Resnick D, et al. The adult hip: an anatomic study. Part I: the bony landmarks. Radiology 1978; 128 (1): 1-10 33. Reynolds D, Lucas J, Klaue K. Retroversion of the acetabulum: a cause of hip pain. J Bone Joint Surg Br 1999; 81 (B): 281-8 34. Fitzgerald RH. Acetabular labrum tears: diagnosis and treatment. Clin Orthop Relat Res 1995; (311): 60-8 35. Altenberg AR. Acetabular labrum tears: a cause of hip pain and degenerative arthritis. South Med J 1977; 70 (2): 174-5 36. Harris WH, Bourne RB, Oh I. Intra-articular acetabular labrum: a possible etiological factor in certain cases of osteoarthritis of the hip. J Bone Joint Surg Am 1979; 61 (4): 510-4 37. Leunig M, Werlen S, Ungersbo¨ck A, et al. Evaluation of the acetabular labrum by MR arthrography. J Bone Joint Surg Br 1997; 79 (2): 230-4 38. Murphy S, Tannast M, Kim YJ, et al. Debridement of the adult hip for femoroacetabular impingement: indications and preliminary clinical results. Clin Orthop Relat Res 2004; (429): 178-81 39. Seldes RM, Tan V, Hunt J, et al. Anatomy, histologic features, and vascularity of the adult acetabular labrum. Clin Orthop Relat Res 2001; (382): 232-40 40. Leunig M, Casillas MM, Hamlet M, et al. Slipped capital femoral epiphysis: early mechanical damage to the acetabular cartilage by a prominent femoral metaphysis. Acta Orthop Scand 2000; 71 (4): 370-5 41. Hase T, Ueo T. Acetabular labral tear: arthroscopic diagnosis and treatment. Arthroscopy 1999; 15 (2): 138-41 42. Ikeda T, Awaya G, Suzuki S, et al. Torn acetabular labrum in young patients. Arthroscopic diagnosis and management. J Bone Joint Surg Br 1988; 70 (1): 13-6 43. Ito K, Leunig M, Ganz R. Histopathologic features of the acetabular labrum in femoroacetabular impingement. Clin Orthop Relat Res 2004; (429): 262-71
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A Review of Femoroacetabular Impingement in Athletes
44. Tannast M, Murphy SB, Langlotz F, et al. Estimation of pelvic tilt on anteroposterior x-rays: a comparison of six parameters. Skeletal Radiol 2006; 35 (3): 149-55 45. Tannast M, Siebenrock KA, Anderson SE. Femoroacetabular impingement: radiographic diagnosis: what the radiologist should know. AJR Am J Roentgenol 2007; 188 (6): 1540-52 46. Eijer H, Mahomed MN, Ganz R. Crosstable lateral radiograph for screening of an anterior femoral head-neck offset in patients with femoro-acetabular impingement. Hip Int 2001; 11: 37-41 47. Meyer DC, Beck M, Ellis T. Comparison of six radiographic projections to assess femoral head/neck asphericity. Clin Orthop Relat Res 2006; 445: 181-5 48. Stulberg SD. Unrecognized childhood hip disease: a major cause of idiopathic osteoarthritis of the hip. In: Cordell LD, Harris WH, Ramsey PL, et al., editors. Proceedings of the Third Open Scientific Meeting of the Hip Society. St Louis (MO): Mosby, 1975: 212-28 49. Goodman DA, Feighan JE, Smith AD, et al. Subclinical slipped capital femoral epiphysis. Relationship to osteoarthrosis of the hip. J Bone Joint Surg Am 1997; 79 (10): 1489-97 50. Notzli H, Wyss TF, Stoecklin CH, et al. The contour of the femoral head-neck junction as a predictor for the risk of anterior impingement. J Bone Joint Surg Br 2002; 87-B: 1012-8 51. Wedge JH, Wasylenko MJ, Houston CS. Minor anatomic abnormalities of the hip joint persisting from childhood and their possible relationship to idiopathic osteoarthrosis. Clin Orthop Relat Res 1991; (264): 122-8 52. Sampson TG. Hip morphology and its relationship to pathology: dysplasia to impingement. Tech Sports Med 2005; 13: 37-45 53. Edwards DJ, Lomas D, Villar RN. Diagnosis of the painful hip by magnetic resonance imaging and arthroscopy. J Bone Joint Surg Br 1995; 77 (3): 374-6 54. Recht M, Bobic V, Burstein D, et al. Magnetic resonance imaging of articular cartilage. Clin Orthop Relat Res 2001; (391 Suppl.): S379-96 55. Siebenrock KA, Wahab KH, Werlen S, et al. Abnormal extension of the femoral head epiphysis as a cause of cam impingement. Clin Orthop Relat Res 2004; (418): 54-60 56. Beaule PE, Zaragoza E, Motamedi K, et al. Three-dimensional computed tomography of the hip in the assessment of femoroacetabular impingement. J Orthop Res 2005; 23 (6): 1286-92 57. Gelberman RH, Cohen MS, Desai SS, et al. Femoral anteversion: a clinical assessment of idiopathic intoeing gait in children. J Bone Joint Surg Br 1987; 69 (1): 75-9 58. Reikeras O, Bjerkreim I, Kolbenstvedt A. Anteversion of the acetabulum and femoral neck in normals and in patients with osteoarthritis of the hip. Acta Orthop Scand 1983; 54 (1): 18-23 59. Reikeras O, Hoiseth A. Femoral neck angles in osteoarthritis of the hip. Acta Orthop Scand 1982; 53 (5): 781-4
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60. Kordelle J, Millis M, Jolesz FA, et al. Three-dimensional analysis of the proximal femur in patients with slipped capital femoral epiphysis based on computed tomography. J Pediatr Orthop 2001; 21 (2): 179-82 61. Aldrich JE, Mayo JR. Radiation doses to patients receiving computed tomography examinations in British Columbia. Can Assoc Radiol J 2006; 57 (2): 79-85 62. Moss M, McLean D. Paediatric and adult computed tomography practice and patient dose in Australia. Australas Radiol 2006; 50 (1): 33-40 63. Narvani AA, Tsiridis E, Tai CC, et al. Acetabular labrum and its tears. Br J Sports Med 2003; 37 (3): 207-11 64. Aydingoz U, Ozturk MH. MR imaging of the acetabular labrum: a comparative study of both hips in 180 asymptomatic volunteers. Eur Radiol 2001; 11 (4): 567-74 65. Czerny C, Hofmann S, Neuhold A, et al. Lesions of the acetabular labrum: accuracy of MR imaging and MR arthrography in detection and staging. Radiology 1996; 200 (1): 225-30 66. James SL, Ali K, Malara F, et al. MRI findings of femoroacetabular impingement. AJR Am J Roentgenol 2006; 187 (6): 1412-9 67. Schmid MR, No¨tzli HP, Zanetti M, et al. Cartilage lesions in the hip: diagnostic effectiveness of MR arthrography. Radiology 2003; 226 (2): 382-6 68. Petersilge CA, Haque MA, Petersilge WJ, et al. Acetabular labral tears: evaluation with MR arthrography. Radiology 1996; 200 (1): 231-5 69. Palmer WE. MR arthrography of the hip. Semin Musculoskelet Radiol 1998; 2 (4): 349-62 70. Kassarjian A, Yoon LS, Belzile E, et al. Triad of MR arthrographic findings in patients with cam-type femoroacetabular impingement. Radiology 2005; 236 (2): 588-92 71. Burman M. Arthroscopy or the direct visualisation of joints: an experimental cadaver study. J Bone Joint Surg 1931; 23: 669-95 72. Glick JM, Sampson TG, Gordon RB, et al. Hip arthroscopy by the lateral approach. Arthroscopy 1987; 3 (1): 4-12 73. Lage LA, Patel JV, Villar RN. The acetabular labral tear: an arthroscopic classification. Arthroscopy 1996; 12 (3): 269-72 74. McCarthy JC, Busconi B. The role of hip arthroscopy in the diagnosis and treatment of hip disease. Orthopedics 1995; 18 (8): 753-6 75. Sampson TG. Complications of hip arthroscopy. Clin Sports Med 2001; 20 (4): 831-5 76. Baber YF, Robinson AH, Villar RN. Is diagnostic arthroscopy of the hip worthwhile? A prospective review of 328 adults investigated for hip pain. J Bone Joint Surg Br 1999; 81 (4): 600-3 77. Sampson TG. Arthroscopic treatment of femoroacetabular impingement. Tech Orthop 2005; 20: 56-62 78. Weiland D, Philippon M. Arthroscopic technique of femoroacetabular impingement. Oper Techniques Orthop 2005; 15: 256-60 79. Philippon MJ, Schenker ML. Arthroscopy for the treatment of femoroacetabular impingement in the athlete. Clin Sports Med 2006; 25 (2): 299-308, ix
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80. Ganz R, Gill TJ, Gautier E, et al. Surgical dislocation of the adult hip a technique with full access to the femoral head and acetabulum without the risk of avascular necrosis. J Bone Joint Surg Br 2001; 83 (8): 1119-24 81. Mardones RM, Gonzalez C, Chen Q, et al. Surgical treatment of femoroacetabular impingement: evaluation of the effect of the size of the resection. J Bone Joint Surg Am 2005; 87 (2): 273-9 82. Siebenrock KA, Schoeniger R, Ganz R. Anterior femoroacetabular impingement due to acetabular retroversion:
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treatment with periacetabular osteotomy. J Bone Joint Surg Am 2003; 85-A (2): 278-86 83. Guanche CA, Bare A. Arthroscopic treatment of femoroacetabular impingement. Arthroscopy 2006; 22 (1): 95-106
Correspondence: Dr Mark E. Batt, Centre for Sports Medicine, West Block, Queen’s Medical Centre, C Floor, Nottingham, NG7 2UH, UK.
Sports Med 2008; 38 (10)
Sports Med 2008; 38 (10): 879 0112-1642/08/0010-0879/$48.00/0
CORRESPONDENCE
ª 2008 Adis Data Information BV. All rights reserved.
Warm-Up and Stretching in the Prevention of Muscular Injury I recently read the article by Woods et al.[1] with interest. There are a couple of issues that require clarification. First, the authors appear to have missed several articles cited in other reviews.[2,3] More importantly, the authors fail to distinguish between studies that examined stretching immediately prior to exercise (e.g. Pope et al.[4]) from those that examined stretching at other times (e.g. Hartig and Henderson[5]), or that included multiple interventions (e.g. Bixler and Jones[6]). For a variety of reasons described elsewhere, there are strong theoretical reasons to believe that stretching before exercise is not the same intervention as stretching at other times. In brief, one could use the analogy of weight lifting. An acute bout of weight lifting causes a decrease in measured force similar to an acute bout of stretching. A long-term weight-training programme produces an increase in force, similar to a long-term programme of stretching. Therefore, one would expect injury rates to be different depending on the timing of the intervention. Although there are not many studies on the long-term effects of stretching, the clinical evidence suggests that this may indeed be the case. Secondly, a focus on only muscle injuries and excluding other types of injuries is not advisable because the effects of stretching are not limited to muscle. If stretching affects neuromuscular function, one would expect an increase in falls or collisions and the injury may not necessarily occur at the muscle level. Therefore, the intervention could decrease (or increase) muscle injuries and have the opposite effect for total injuries. In other medical areas, difficult lessons were learned when investigators focused only on disease-specific outcomes and pronounced beneficial effects of medications, and later found that overall mortality increased because of unanticipated effects. Finally, the authors suggest that long-term stretching may increase the length of the muscle at the point of failure. Although I agree that
long-term stretching is likely beneficial, the underlying reason remains unknown. For example, the prevailing theory is that most muscle strains occur during eccentric loading within the normal range of motion. This can occur because there is heterogeneity in sarcomere length during muscle activity – some sarcomeres lengthen while others shorten. Therefore, the ‘‘length at failure’’ during passive tests may not be relevant. Ian Shrier Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, SMBD-Jewish General Hospital, Montreal, Quebec, Canada
Acknowledgements No sources of funding were used to assist in the preparation of this letter. The author has no conflicts of interest that are directly relevant to the content of this letter.
References 1. Woods K, Bishop P, Jones E. Warm-up and stretching in the prevention of muscular injury. Sports Med 2007; 37 (12): 1089-99 2. Shrier I. Pre-exercise stretching may not prevent injuries: a critical review of the literature. Clin J Sport Med 1999; 9: 110 3. Shrier I. Does stretching help prevent injuries? In: MacAuley D, Best T, editors. Evidence-based sports medicine. Vol. 2. London: BMJ Publishing Group, 2007 4. Pope RP, Herbert RD, Kirwan JD, et al. A randomized trial of preexercise stretching for prevention of lower-limb injury. Med Sci Sports Exerc 2000; 32: 271-7 5. Hartig DE, Henderson JM. Increasing hamstring flexibility decreases lower extremity overuse injuries in military basic trainees. Am J Sports Med 1999; 27: 173-6 6. Bixler B, Jones RL. High-school football injuries: effects of a post-halftime warm-up and stretching routine. Fam Pract Res J 1992; 12: 131-9
The Author’s Reply Although Dr Shrier’s review[1] was not published at the time our article was accepted for publication, we are sure the information presented will add to this current discussion. Dr Shrier questions the comparison of multiple studies. He uses the phrase ‘‘multiple interventions’’ in referring to only one referenced study. If he will
Sports Med 2008; 38 (10): 879 0112-1642/08/0010-0879/$48.00/0
CORRESPONDENCE
ª 2008 Adis Data Information BV. All rights reserved.
Warm-Up and Stretching in the Prevention of Muscular Injury I recently read the article by Woods et al.[1] with interest. There are a couple of issues that require clarification. First, the authors appear to have missed several articles cited in other reviews.[2,3] More importantly, the authors fail to distinguish between studies that examined stretching immediately prior to exercise (e.g. Pope et al.[4]) from those that examined stretching at other times (e.g. Hartig and Henderson[5]), or that included multiple interventions (e.g. Bixler and Jones[6]). For a variety of reasons described elsewhere, there are strong theoretical reasons to believe that stretching before exercise is not the same intervention as stretching at other times. In brief, one could use the analogy of weight lifting. An acute bout of weight lifting causes a decrease in measured force similar to an acute bout of stretching. A long-term weight-training programme produces an increase in force, similar to a long-term programme of stretching. Therefore, one would expect injury rates to be different depending on the timing of the intervention. Although there are not many studies on the long-term effects of stretching, the clinical evidence suggests that this may indeed be the case. Secondly, a focus on only muscle injuries and excluding other types of injuries is not advisable because the effects of stretching are not limited to muscle. If stretching affects neuromuscular function, one would expect an increase in falls or collisions and the injury may not necessarily occur at the muscle level. Therefore, the intervention could decrease (or increase) muscle injuries and have the opposite effect for total injuries. In other medical areas, difficult lessons were learned when investigators focused only on disease-specific outcomes and pronounced beneficial effects of medications, and later found that overall mortality increased because of unanticipated effects. Finally, the authors suggest that long-term stretching may increase the length of the muscle at the point of failure. Although I agree that
long-term stretching is likely beneficial, the underlying reason remains unknown. For example, the prevailing theory is that most muscle strains occur during eccentric loading within the normal range of motion. This can occur because there is heterogeneity in sarcomere length during muscle activity – some sarcomeres lengthen while others shorten. Therefore, the ‘‘length at failure’’ during passive tests may not be relevant. Ian Shrier Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, SMBD-Jewish General Hospital, Montreal, Quebec, Canada
Acknowledgements No sources of funding were used to assist in the preparation of this letter. The author has no conflicts of interest that are directly relevant to the content of this letter.
References 1. Woods K, Bishop P, Jones E. Warm-up and stretching in the prevention of muscular injury. Sports Med 2007; 37 (12): 1089-99 2. Shrier I. Pre-exercise stretching may not prevent injuries: a critical review of the literature. Clin J Sport Med 1999; 9: 110 3. Shrier I. Does stretching help prevent injuries? In: MacAuley D, Best T, editors. Evidence-based sports medicine. Vol. 2. London: BMJ Publishing Group, 2007 4. Pope RP, Herbert RD, Kirwan JD, et al. A randomized trial of preexercise stretching for prevention of lower-limb injury. Med Sci Sports Exerc 2000; 32: 271-7 5. Hartig DE, Henderson JM. Increasing hamstring flexibility decreases lower extremity overuse injuries in military basic trainees. Am J Sports Med 1999; 27: 173-6 6. Bixler B, Jones RL. High-school football injuries: effects of a post-halftime warm-up and stretching routine. Fam Pract Res J 1992; 12: 131-9
The Author’s Reply Although Dr Shrier’s review[1] was not published at the time our article was accepted for publication, we are sure the information presented will add to this current discussion. Dr Shrier questions the comparison of multiple studies. He uses the phrase ‘‘multiple interventions’’ in referring to only one referenced study. If he will
880
review our article in more detail, it will be apparent that most, if not all, studies reviewed included some type of ‘‘multiple intervention.’’ For example, as was clearly stated in our review, it is difficult to distinguish the benefits of stretching or warm-up individually because protocols almost always involve some type of warm-up prior to the stretching regimen. This is because, as is widely accepted, it is more advantageous to stretch a warmed muscle than a ‘cold’ one. He also mentions the timing of the stretching within the study. Again, if our article is reviewed in more detail, it is apparent that, of the studies involving stretching/warm-up and physical activity and injury rates, all conducted their stretching prior to the physical activity in question. Dr Shrier states that injury rates will be different depending on the timing of the intervention. This is precisely our point – muscular injury rates are different (reduced) when a warm-up and stretching regimen is incorporated prior to physical activity. Our article was interested in the application of warm-up and stretching in the prevention of muscular injury occurring during physical activities. As was clearly pointed out in our review, the warm-up and stretching regimens for reducing muscular injury during activity would stand little chance of reducing major traumatic injuries to bones, for example, that may occur as a result of direct trauma during a sporting event, such as American football or ice hockey.
ª 2008 Adis Data Information BV. All rights reserved.
Letter to the Editor
The ‘prevailing theory’ is one reason why this topic was addressed. Eccentric loading within the normal range of motion (assuming that the load is a force that muscle cannot withstand) may cause injury. If heterogeneity in sarcomere length is the sole underlying cause of injury, then sarcomere function (sarcomere lengthening vs shortening) at the critical moment for providing appropriate muscular force is important during ‘‘length at failure.’’ Length at failure and possible homogeneity of sarcomere length, as discussed from the standpoint of an increased range of motion and a subsequent increase in a theorized ‘‘non-injury zone,’’ are possible reasons for the benefits of longterm stretching. Therefore, the length at failure is indeed relevant if the muscle is able to stretch further before heterogeneity in sarcomere length is achieved during dynamic muscular activity. Krista Woods M.A. Human Performance Laboratory, University of Alabama, Tuscaloosa, Alabama, USA
Acknowledgements No sources of funding were used to assist in the preparation of this letter. The author has no conflicts of interest that are directly relevant to the content of this letter.
Reference 1. Shrier I. Does stretching help prevent injuries? In: MacAuley D, Best T, editors. Evidence-based sports medicine. Vol 2. London: BMJ Publishing Group, 2007
Sports Med 2008; 38 (10)
