Chapter 1
Epidemiology of Sports Injuries and Illnesses
Debbie Palmer-Green
Senior Research Fellow, Arthritis Research UK, Centre for Sport, Exercise & Osteoarthritis, University of Nottingham, Nottingham, UK
OVERVIEW
- Sports injury and illness epidemiology research is continuing to grow
- Study design and methods can influence the conclusions made
- The definition of injury/illness, and rate and severity indices should be appropriate to the cohort of interest
- Identifying injury and illness causes will help to provide additional risk information
- Prevention initiatives should target the injury/illness issues posing the greatest risk
Introduction
Recognition of the importance of sports injury and illness epidemiology research has grown in the last 10 years with national and international governing bodies of sport regularly conducting surveillance at major sporting events. Most sports involve some element of risk with regard to athlete injury or illness, some significantly more so than other (Table 1.1).
Table 1.1 Rates of overall injuries and illnesses in the Olympic sports
| Sport | No. of athletes | No. of injuries (%) | No. of illnesses (%) |
| Archery | 128 | 2 (1.6) | 10 (7.8) |
| Athletics | 2079 | 368 (17.7) | 219 (10.5) |
| Diving | 136 | 11 (8.1) | 7 (5.1) |
| Swimming | 931 | 50 (5.4) | 68 (7.3) |
| Synchronised swimming | 104 | 14 (13.5) | 13 (12.5) |
| Water polo | 260 | 34 (13.1) | 21 (8.1) |
| Badminton | 164 | 26 (15.9) | 5 (3.0) |
| Basketball | 287 | 32 (11.1) | 9 (3.1) |
| Beach volleyball | 96 | 12 (12.5) | 18 (18.8) |
| Boxing | 283 | 26 (9.2) | 18 (6.4) |
| Canoe slalom | 83 | 2 (2.4) | 4 (4.8) |
| Canoe sprint | 249 | 7 (2.8) | 14 (5.6) |
| Road cycling | 210 | 19 (9.0) | 7 (3.3) |
| Track cycling | 167 | 5 (3.0) | 16 (9.6) |
| Equestrian | 199 | 9 (4.5) | 11 (5.5) |
| Fencing | 246 | 23 (9.3) | 13 (5.3) |
| Football | 509 | 179 (35.2) | 62 (12.2) |
| Artistic gymnastics | 195 | 15 (7.7) | 5 (2.6) |
| Rhythmic gymnastics | 96 | 7 (7.3) | 1 (1.0) |
| Trampoline | 32 | 2 (6.3) | 1 (3.1) |
| Handball | 349 | 76 (21.8) | 17 (4.9) |
| Hockey | 388 | 66 (17.0) | 29 (7.5) |
| Judo | 383 | 47 (12.3) | 16 (4.2) |
| Modern pentathlon | 72 | 6 (8.3) | 1 (1.4) |
| Rowing | 549 | 18 (3.3) | 40 (7.3) |
| Sailing | 380 | 56 (14.7) | 38 (10.0) |
| Shooting | 390 | 15 (3.8) | 17 (4.4) |
| Table tennis | 174 | 11 (6.3) | 12 (6.9) |
| Taekwondo | 128 | 50 (39.1) | 14 (10.9) |
| Tennis | 184 | 21 (11.4) | 4 (2.2) |
| Triathlon | 110 | 16 (14.5) | 7 (6.4) |
| Volleyball | 288 | 20 (6.9) | 8 (2.8) |
| Weightlifting | 252 | 44 (17.5) | 10 (4.0) |
| Wrestling | 343 | 41 (12.0) | 16 (4.7) |
Source: Adapted from Engebretsen et al. 2013. Reproduced with permission from BMJ Publishing Group Ltd.
Although much of the literature is focused on rehabilitation of athlete injuries (and illnesses), it is just as important to try and prevent them from occurring, or if it is not possible to prevent them completely at least lessen the severity and impact when injuries and illnesses do occur. In order to correctly prioritise and accurately target prevention initiatives to reduce injuries and illnesses in sport, it is important to understand the magnitude of the problem, that is, the rate and severity, and the causes. Conducting systematic monitoring of athlete injuries and illnesses in sport is essential to provide the evidence base to inform these prevention strategies. In order to get accurate and reliable data epidemiological study designs must be robust, and issues related to the design and implementation of injury and illness surveillance studies are discussed later, with illustrative examples provided.
Study design and population
The ability to describe the incidence, nature and causes of injuries and illnesses reliably has been recognised through the development of injury/illness surveillance consensus statements. Standardising study design and data collection makes it possible to compare results between studies. Firstly, the target population (or cohort) to be studied must be identified. Sometimes what defines a population is obvious, for example, in a study recording the number of injuries during the 2011 Rugby World Cup, the players competing during the World Cup are the population cohort. It is important to note the period of observation (i.e. again this may be naturally dictated by the cohort): who is going to record the data (i.e. team physician for medical data; coaches for training and competition exposure data), the methods of data collection (paper or electronic) and the type of study. Retrospective studies collect historical data over a set period of time, while prospective studies follow the cohort over a set future period of time. Prospective studies are generally more reliable than retrospective studies due to issues with the latter of memory recall bias, where even over short periods of time, more severe or more recent injuries and illness are likely to be remembered, but the less severe and more historical episodes are more likely to be forgotten.
Injury/illness definition
A universal definition of injury and illness, applicable to all sports, would be convenient and simple. Although this has not yet been achieved, the development of consensus statements has unified much of the research currently being undertaken (Table 1.2).
Table 1.2 Examples of injury and illness definitions used in epidemiological studies
| a. | Any physical complaint sustained by a player … irrespective of the need for medical-attention or time-loss from activities |
| b. | Any musculoskeletal complaint … that received medical-attention regardless of the consequence with respect to absence from competition and/or training |
| c. | Any physical complaint (not related to injury) that received medical-attention regardless of the consequence with respect to absence from competition and/or training |
| d. | Any physical complaint sustained by a player during a match or training … that prevented the player from taking a full part in all … activities … for more than 1 day following the day of injury |
Classification of injuries and illnesses
The majority of epidemiological studies have focused on the aetiology of ‘medical-attention’ and/or ‘time-loss’ definitions of injury and illness incidents, but few have related these events to an athlete's consequential physical limitations. For example, time-loss classifications are somewhat categorical in their use of the term (i.e. complete absence), when in reality many athletes continue to compete and train at high levels when experiencing pain and/or loss of function through injury or illness. Hence, there is a need to consider an additional level of classification focused on levels of impairment or performance restriction (Figure 1.1).
Figure 1.1 (a) Traditional hierarchy of injury/illness definition and classification, TL = time-loss. (b) Alternative hierarchy of injury/illness definition and classification
The classification and, therefore, the level of data collection required will need to be determined based on the study population, that is, recording all injuries including ‘medical-attention’ may not be appropriate for studies with large populations, or for contact sports (i.e. rugby) where the number of...
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