A Meta-Analysis of Injuries in Senior Men’s Professional Rugby Union
- 3.3k Downloads
Rugby Union has one of the highest reported incidences of match injuries amongst all professional team sports. The majority of research within this field has focused on elite male cohorts; in this study we present the first meta-analytic review of these data.
The aim of this study was to summarise the incidence and severity of injuries in senior men’s professional Rugby Union, and determine the overall effects of level of play, new versus recurrent injuries, playing position, type of injuries, location of injuries, severity of injuries, period of match, and injury incident.
Electronic databases were searched using keywords ‘Rugby Union’ and ‘inj*’. Fifteen papers addressing injuries in senior men’s professional Rugby Union (from 1995 through September 2012) were included in the review. A maximum of ten of these papers provided incidence data that could be modelled via a Poisson mixed-effects generalised linear model, while up to nine studies provided severity data that could be modelled via a general linear mixed model. Magnitude based inferences were used to assess differences between factors. A descriptive analysis was provided for studies that could not be included in the pooled analysis due to incongruent injury definitions.
The overall incidence of injuries in senior men’s professional Rugby Union matches was 81 per 1,000 player hours (95 % CI 63–105), and 3 per 1,000 player hours (95 % CI 2–4) during training. Estimated mean severity for match injuries was 20 days (95 % CI 14–27), and 22 days (95 % CI 19–24) for training injuries. A higher level of play was associated with a greater incidence of injuries in matches, with no clear difference in severity. New injuries occurred substantially more often than recurrent injuries, while the severity of recurrent injuries was, on average, 10 days (95 % CI 4–17) greater than new injuries. Trivial differences were found in injury incidence and severity between forwards and backs. Muscle/tendon and joint (non-bone)/ligament injuries were the two most prevalent injury groups, whereas fractures and bone stress injuries had the highest average severity. The lower limb was the body region with the highest injury incidence, while upper limb injuries were most severe. The third quarter (40–60 min) of matches had the highest injury rate, and injuries most commonly occurred as a result of being tackled.
This meta-analysis confirms match injury incidence rates in professional Rugby Union can be considered high in comparison with other team sports, but similar to other collision sports. In order to markedly reduce overall injury burden, efforts should target lower-limb injury prevention strategies and technique during contact, as these may render the largest effect.
KeywordsGeneral Linear Mixed Model Incidence Rate Ratio Injury Incidence Hamstring Injury Recurrent Injury
We thank Reidar Lystad from Macquarie University, Australia, for providing statistical advice.
Funding for this review was provided by the Rugby Football Union and University of Bath.
Conflict of interest
Simon Kemp was an author on some of the original studies reviewed, but was not involved in the assessment of study quality in the present meta-analysis.
- 1.Chadwick S, Semens A, Schwarz EC, et al. Economic impact report on global rugby. Part III: Strategic and emerging markets. 2010; http://www.irb.com/mm/document/newsmedia/mediazone/02/04/22/88/2042288_pdf.pdf (Accessed 31 Aug 2012).
- 11.Checkoway H. Data pooling in occupational studies. J Occup Environ Med. 1991;33(12):1257–60.Google Scholar
- 16.International Rugby Board. Men’s Next Senior National Represntative Team. 2012; http://www.irb.com/mm/Document/LawsRegs/Regulations/02/06/29/68/nsrt.pdf (Accessed 10 Oct 2012).
- 18.Hopkins WG. A spreadsheet for combining outcomes from several subject groups. Sportscience. 2006;10:51–3.Google Scholar
- 19.Hopkins WG. Linear models and effect magnitudes for research, clinical and practical applications. Sportscience. 2010;14:49–57.Google Scholar
- 20.Hopkins WG. A spreadsheet for deriving a confidence interval, mechanistic inference and clinical inference from a p value. Sportscience. 2007;11:16–20.Google Scholar
- 28.Fuller CW, Sheerin K, Targett S. Rugby World Cup 2011: International Rugby Board injury surveillance study. Br J Sports Med. 2012 (in press).Google Scholar
- 30.Kemp SPT, Brooks JHM, Fuller CW, et al. England Rugby Premiership Injury and Training Audit: 2010–2011 Season Report. 2011.Google Scholar
- 31.Takemura M, Okayama A, Takazawa Y, et al. Injury profile in the highest-level rugby union competition in Japan. In: 7th World congress on science and football (WCSF), 2011. Nagoya University, Japan; 2011.Google Scholar
- 41.Roberts SP, Stokes KA, Trewartha G, et al. RFU Community Rugby Injury Surveillance Project: 2011–2012 Season Report; 2012.Google Scholar
- 48.Finch, CF, Cook, J. Categorising sports injuries in epidemiological studies: the subsequent injury categorisation (SIC) model to address multiple, recurrent and exacerbation of injuries. Br J Sports Med. 2013.Google Scholar
- 60.Steffen K, Emery CA, Romiti M, et al. High adherence to a neuromuscular injury prevention programme (FIFA 11+) improves functional balance and reduces injury risk in Canadian youth female football players: a cluster randomised trial. Br J Sports Med. 2013.Google Scholar