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Surveillance of Injuries Among Kenya Rugby Union (KRU) Players — Season 2010

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Surveillance of Injuries Among Kenya Rugby Union (KRU) Players — Season 2010 The AnnAls of AfricAn surgery | www.sskenya.org Original Article Surveillance of injuries among Kenya Rugby Union (KRU) players — Season 2010 Authors: Muma N1 MBChB, MMed, Saidi H2 MBChB, MMed, FACS, Githaiga3 JW MBChB, MMed Affiliation: 1- Kijabe Hospital, Kenya 2- Department Human Anatomy, University of Nairobi 3- Department of Surgery, University of Nairobi. Correspondence: Dr. Muma Nyagetuba; Kijabe Hospital, Kenya Email Abstract Objective: To determine the incidence and characteristics of (mph), (44.2 for forwards and 40.8 for backs). Lower limb injuries were injury amongst Kenya rugby union players and associated the most common (41.2%). Players were most prone to injuries in the in factors. tackle scenario (63.7%), at the beginning of the season (47.1%), and in Design: A whole population prospective cohort study. the last quarter (50%) of a game. Methods: 364 registered Kenya rugby union (KRU) players were stud- Conclusion: The injury incidence recorded contrast the earlier Kenyan ied throughout the 2010 season. Data on their demographics, injury data but is comparable to international amateur level incidence, incidence, pattern and severity were gathered. The study tool used was uniqueness of the Kenyan environment notwithstanding. The higher the Rugby International Consensus Group (RICG) Statement. rates associated with the tackle/tackled scenario, earlier part of the season and later part of the game, suggest interventions can target Results: There were 173 backs and 191 forwards. One hundred and two player conditioning, and use of protective gear. 1 injuries for 60 league games (2400match player hours) were recorded. The incidence of injuries was 42.5/1000 match player hours Introduction Methodology Rugby is a high velocity and collision sport attended by The prospective whole population cohort study of 364 one of the highest rates of injuries in team sports (1-3). players was conducted in the 2010 15-aside season. It As is the trend in the global scene, rugby is increasingly a comprised of the Kenya cup (KC) division one and Eric popular sport in Kenya. Competition is higher, the game Shirley shield (ESS) division two leagues. All players faster and the players stronger. The combination of fac- were KRU registered and had to be above 18years of age. tors is fodder for rising rates of injury (1-7) with signifi- The clinical officers in charge of data collection were cant impact on player and team performance. trained for two weeks to use the instrument of data col- A ‘prevention is better than cure’ approach to rugby in- lection followed by a proficiency exam using preseason jury is made possible by understanding the characteris- matches. tics and magnitude of the problem. An earlier Kenyan Blood bin injuries defined by Law 3.11(a) of study suggested comparatively higher rates of rugby re- International Rugby Board ( IRB) were excluded unless a lated injuries but did not establish models of relation- training session or match was subsequently missed ships with risk factors (8). Internal and external factors because of the said injury. shown to influence the outcome of injury include player Age, height, weight, injury status at that time and posi- fitness, part of the season, phase of play, player position, tion played were documented preseason. state of the pitch and player physique (9-14). Accord- The players were clustered into forwards (positions 1 to ing to Brooks for example, injuries that cause the most 8) and backs (positions 9 to 15). significant absence from the field of play for forwards Data analysis was performed using SPSS version 17 soft- and backs are anterior cruciate ligament and hamstring ware. Incidence was calculated as injuries per 1000 match injury respectively (6). player hours (mph) (95% CI). Student t-test was used to This paper explores the injury experience and the asso- compare the means between injured and non-injured for ciated risk profile during the Kenya 2010 15-side rugby continuous vari- ables i.e. age, weight, height, BMI. season. Match exposure was calculated on the basis of 15 players (8 forwards, 7 backs) per team exposed for 80 minutes (first(first half 00-20,–20, 20-40,20–40, second second half half 40-60,40–60, 60-80min 60–80min- The AnnAls of AfricAn surgery • Volume 9 • July 201225 88 The ANNALS of AFRICAN SURGERY. July 2012 Volume 9 Issue 2 Original Original article Articlearticle The ANNALS of AFRICAN SURGERY | www.sskenya.org SurveillancSuerveillanc of injuriee so f amon injuriegs K amonenya Rugg Kebnyy Unioa Rugn b(Ky UnioRU) npl a(KyersRU-) Seasoplayersn- 2010Seaso n 2010 Muma NyagetubaMumNyagetubaa Nyagetuba, Hassa M,n Saidi Saidi, Hassa H,, Githaig Githaigan Saidia JW, JWGithaig a JW Table 1: ComparisoTable 1n: Coomparisof anthropometrin of anthropometric measures bec measuretween KsC beandtw een KC and Table 3: IncidenTablce oef 3 injur: Incideny as ac efunctio of injurn yo fa locatios a function ofn body of locatio n of body ESS players ESS players Site Site Backs Backs Forward Forward Total Total CharacteristicCharac teristiKC(n=169c ) KC(n=169ESS (n=195)) ESS (n=195) Count % Coun95%Ct % I C95%Count I% 95%CCountI % 95%CI % % Mean(SD) Mean(SDMean(SD) ) Mean(SD95% CI) 95% CI Head face Head face1 1 10.78 11 4.7 t10.7o 16.88 124. 7 to 16.11.88 5. 152 to 1811. 82 35. 5 to 1822.5 23 22.5 Age Age 21.41 (3.07)21.4 24.41 (3.070 (3.78) )24.4 -3.60 (3.789 to -)2.28 -3.6 9 to -2.28 Neck Cervical SpinNecek Cervica0 l Spin0e 0 0 0 40 3.9 0.41 to 7.73. 9 4 0.1 to 7.3.97 4 3.9 Weight Weight 78.29 (12.2578.2) 85.99 (12.251 (11.70) 85.9) -10.11 (11.700 to -)5.13 -10.1 0 to -5.13 Sternum Ribs Sternum Rib0 s 0 0 0 0 30 2.9 -0.3 4 to 6.2.2 9 3 -0.4 to 6.2.92 3 2.9 Height Height 1.74 (0.072)1.7 41.7 (0.0727 (0.07) ) 1.7-70.0 (0.074 to) -0.01-0.0 4 to -0.01 Upper Back Upper Back BMI BMI 25.76 (3.78)25.7 267 (3.78.54 (3.44) ) 2 7 .5-2.54 (3.443 to -)1.03 -2.5 3 to -1.03 Abdomen Abdomen0 0 0 0 0 10 1.0 -0.1 9 to 2.1.9 0 1 -0.9 to 2.1 9 1 1 Lower back Lower bac1k 0.98 1 -0.90.9 to 2.8 9 3- 0.9 to 2.9 -30. 4 to 6.2.2 9 4 -0.4 to 6.3.92 4 3.9 Shoulder ClaviclShouldee r Clavicl11 e 10.78 11 4.7 t10.7o 16.8 8 74. 7 to 16.6.98 1.79 to 11.6.89 1 81. 9 to 11.178.6 18 17.6 Table 2: ComparatiTable 2v: eC anthropometromparative anthropometry between injurey betdw eeannd noninjure- d and non- Upper Arm Upper Arm1 0.98 1 -0.90.9 to 2.8 9 0- 0.9 to 02. 9 00 0 1 0 1 1 1 injured playersinjure d players Elbow Elbow 0 0 0 0 0 10 1 -10. 9 to 2.19 1 -0.9 to 2.1 9 1 1 CharacteristicCharacs teristicNon-injured(ns Non= 92)-injured(n = 92) Forearm Forearm 0 0 0 0 0 20 2 -20. 7 to 4.27 2 -0.7 to 4.27 2 2 Mean(SD) Mean(SDInjure) d (n=273)Injure d (n=273) Wrist Wrist 0 0 0 0 0 10 1 -10. 9 to 2.19 1 -0.9 to 2.1 9 1 1 Mean (SD) Mean (SD95)% CI 95% CI Hand Finger ThumHanbd Finge1 r Thum0.9b 8 1 -0.90.9 to 2.8 9 1- 0.9 to 12. 9 -10. 9 to 2.19 2 -0.9 to 2.2 9 2 2 Age Age 22.57(3.77) 22.57(3.7723.47 )(3.52 )23.4 -1.77 (3.528 to -)0.02 -1.7 8 to -0.02 Hip Groin Hip Groin3 2.94 3 -0.42.9 to 6.4 2 1- 0.4 to 16. 2 -10. 9 to 2.19 4 -0.9 to 2.3.99 4 3.9 Weight Weight 80.89 (13.06)80.8 84.69 (13.06)2 (10.60 84.6) -0.042 (10.601 to -)0.01 -0.04 1 to -0.01 Posterior ThighP osterior Thig2 h 1.96 2 -0.71.9 to 4.6 7 0- 0.7 to 04. 7 00 0 2 0 2 2 2 Height Height 1.74 (0.07) 1.741.7 (0.07)7 (0.06 ) 1.7-76.7 (0.060 to) -0.77-6.7 0 to -0.77 Knee Knee 9 8.82 9 3.3 t8.8o 14.2 4 73. 3 to 14.6.94 1.79 to 11.6.89 1 61. 9 to 11.15.78 16 15.7 BMI BMI 26.46 (3.87)26.4 26.96 (3.87)6 (3.26 )26.9 -1.36 (3.268 to -)0.39 -1.3 8 to -0.39 Ankle Ankle 10 9.8 10 4.0 t9.o 815. 6 64. 0 to 15.5.96 1.63 to 10.5.59 1 61. 3 to 10.15.75 16 15.7 Foot Toe Foot Toe 0 0 0 0 0 40 3.9 0.41 to 7.73.
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