Prevalence of and Factors Associated with Sports Injuries in 11,000 Japanese Collegiate Athletes
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Participants Characteristics
3.2. Injuries’ Characteristics
3.3. Injury Prevalence and Associated Factors
3.4. Factors Associated with Sustaining an Injury
4. Discussion
4.1. Prevalence of Sports Injuries
4.2. Time Lost and Severity of Injuries
4.3. Factors Associated with Sports Injuries
4.4. Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Pol, R.; Hristovski, R.; Medina, D.; Balague, N. From microscopic to macroscopic sports injuries. Applying the complex dynamic systems approach to sports medicine: A narrative review. Br. J. Sports Med. 2019, 53, 1214–1220. [Google Scholar] [CrossRef] [PubMed]
- Haraldsdottir, K.; Watson, A.M. Psychosocial impacts of sports-related injuries in adolescent athletes. Curr. Sports Med. Rep. 2021, 20, 104–108. [Google Scholar] [CrossRef] [PubMed]
- Hind, K.; Konerth, N.; Entwistle, I.; Theadom, A.; Lewis, G.; King, D.; Chazot, P.; Hume, P. Cumulative sport-related injuries and long-er term impact in retired male Elite-and Amateur-Level rugby code athletes and non-contact athletes: A retrospective study. Sports Med. 2020, 50, 2051–2061. [Google Scholar] [CrossRef] [PubMed]
- Schmikli, S.L.; Backx, F.J.G.; Kemler, H.J.; van Mechelen, W. National survey on sports injuries in the Netherlands: Target populations for sports injury prevention programs. Clin. J. Sport Med. 2009, 19, 101–106. [Google Scholar] [CrossRef] [PubMed]
- Putukian, M.; Lincoln, A.E.; Crisco, J.J. Sports-specific issues in men’s and women’s lacrosse. Curr. Sports Med. Rep. 2014, 13, 334–340. [Google Scholar] [CrossRef] [PubMed]
- Ross, A.G.; Donaldson, A.; Poulos, R.G. Nationwide sports injury prevention strategies: A scoping review. Scand. J. Med. Sci. Sports 2021, 31, 246–264. [Google Scholar] [CrossRef] [PubMed]
- Japan Sport Council. School Accident Database. n.d.-a. Available online: https://www.jpnsport.go.jp/anzen/anzen_school/anzen_school/tabid/822/Default.aspx (accessed on 17 September 2020).
- Sekine, Y.; Kamada, K.; Koyama, T.; Hoshikawa, S.; Uchino, S.; Komatsu, T. Descriptive epidemiology of injuries in Japanese colle-giate men’s basketball: 2013/2014 to 2019/2020. Inj. Epidemiol. 2022, 9, 4. [Google Scholar] [CrossRef]
- Mashimo, S.; Yoshida, N.; Moriwaki, T.; Takegami, A.; Suzuki, K.; Fong, D.T.; Myklebust, G.; Onishi, S. Injuries in Japanese university handball: A study among 1017 players. Res. Sports Med. 2021, 29, 475–485. [Google Scholar] [CrossRef]
- Finch, C. A new framework for research leading to sports injury prevention. J. Sci. Med. Sport 2006, 9, 3–9. [Google Scholar] [CrossRef]
- van Mechelen, W. Sports injury surveillance systems. Sports Med. 1997, 24, 164–168. [Google Scholar] [CrossRef]
- Finnish Institute for Health and Welfare. Finnish Environment Institute Helsinki Declaration to Protect Human and Planetary Health for 2020s. Available online: http://www.julkari.fi/handle/10024/139144 (accessed on 2 October 2020).
- International Olympic Committee Injury and Illness Epidemiology Consensus Group; Bahr, R.; Clarsen, B.; Derman, W.; Dvorak, J.; Emery, C.A.; Finch, C.F.; Hägglund, M.; Junge, A.; Kemp, S.; et al. International Olympic Committee Consensus Statement: Methods for Recording and Reporting of Epidemiological Data on Injury and Illness in Sports 2020 (Including the STROBE Extension for Sports Injury and Illness Surveil-lance (STROBE-SIIS)). Orthop. J. Sports Med. 2020, 8, 2325967120902908. [Google Scholar] [CrossRef] [PubMed]
- Charan, J.; Biswas, T. How to calculate sample size for different study designs in medical research? Indian J. Psychol. Med. 2013, 35, 121–126. [Google Scholar] [CrossRef] [PubMed]
- Sunagawa, N. Recommended Methods for Sports Injury and Illness Surveillance: Japanese Society of Clinical Sports Medicine and Japanese Society for Athletic Training Consensus Document. Jpn. J. Clin. Sports Med. 2022, 30, 319–331. (In Japanese) [Google Scholar]
- Bowen, L.; Gross, A.S.; Gimpel, M.; Bruce-Low, S.; Li, F.-X. Spikes in acute:chronic workload ratio (ACWR) associated with a 5–7 times greater injury rate in English Premier League football players: A comprehensive 3-year study. Br. J. Sports Med. 2020, 54, 731–738. [Google Scholar] [CrossRef] [PubMed]
- Schneider, S.; Seither, B.; Tönges, S.; Schmitt, H. Sports injuries: Population based representative data on incidence, diagnosis, sequelae, and high risk groups. Br. J. Sports Med. 2006, 40, 334–339. [Google Scholar] [CrossRef] [PubMed]
- Bueno, A.M.; Pilgaard, M.; Hulme, A.; Forsberg, P.; Ramskov, D.; Damsted, C.; Nielsen, R.O. Injury prevalence across sports: A descrip-tive analysis on a representative sample of the Danish population. Inj. Epidemiol. 2018, 5, 6. [Google Scholar] [CrossRef] [PubMed]
- Ristolainen, L.; Toivo, K.; Parkkari, J.; Kokko, S.; Alanko, L.; Heinonen, O.J.; Korpelainen, R.; Savonen, K.; Selänne, H.; Vasankari, T.; et al. Acute and overuse injuries among sports club members and non-members: The Finnish Health Promoting Sports Club (FHPSC) study. BMC Musculoskelet. Disord. 2019, 20, 32. [Google Scholar] [CrossRef] [PubMed]
- Rosa, B.B.; Asperti, A.M.; Helito, C.P.; Demange, M.K.; Fernandes, T.L.; Hernandez, A.J. Epidemiology of sports injuries on collegiate athletes at a single center. Acta Ortop. Bras. 2014, 22, 321–324. [Google Scholar] [CrossRef]
- Prieto-González, P.; Martínez-Castillo, J.L.; Fernández-Galván, L.M.; Casado, A.; Soporki, S.; Sánchez-Infante, J. Epidemiology of sports-related injuries and associated risk factors in adolescent athletes: An injury surveillance. Int. J. Environ. Res. Public Health 2021, 18, 4857. [Google Scholar] [CrossRef]
- Shigematsu, R.; Katoh, S.; Suzuki, K.; Nakata, Y.; Sasai, H. Sports specialization and sports-related injuries in Japanese school-aged children and adolescents: A retrospective descriptive study. Int. J. Environ. Res. Public Health 2021, 18, 7369. [Google Scholar] [CrossRef]
- Lin, C.Y.; Casey, E.; Herman, D.C.; Katz, N.; Tenforde, A.S. Sex differences in common sports injuries. PM&R 2018, 10, 1073–1082. [Google Scholar] [CrossRef]
- Fraser, M.A.; Grooms, D.R.; Guskiewicz, K.M.; Kerr, Z.Y. Ball-contact injuries in 11 National Collegiate Athletic Association Sports: The injury surveillance program, 2009–2010 through 2014–2015. J. Athl. Train. 2017, 52, 698–707. [Google Scholar] [CrossRef] [PubMed]
- Baugh, C.M.; Meehan, W.P., III; McGuire, T.G.; Hatfield, L.A. Staffing, financial, and administrative oversight models and rates of in-jury in collegiate athletes. J. Athl. Train. 2020, 55, 580–586. [Google Scholar] [CrossRef] [PubMed]
- Lystad, R.P.; Alevras, A.; Rudy, I.; Soligard, T.; Engebretsen, L. Injury incidence, severity and profile in Olympic combat sports: A comparative analysis of 7712 athlete exposures from three consecutive Olympic Games. Br. J. Sports Med. 2021, 55, 1077–1083. [Google Scholar] [CrossRef] [PubMed]
- Clarsen, B.; Krosshaug, T.; Bahr, R. Overuse injuries in professional road cyclists. Am. J. Sports Med. 2010, 38, 2494–2501. [Google Scholar] [CrossRef] [PubMed]
- Kay, M.C.; Register-Mihalik, J.K.; Gray, A.D.; Djoko, A.; Dompier, T.P.; Kerr, Z.Y. The epidemiology of severe injuries sustained by National Collegiate Athletic Association student-athletes, 2009–2010 through 2014–2015. J. Athl. Train. 2017, 52, 117–128. [Google Scholar] [CrossRef] [PubMed]
- Tsukahara, Y.; Kamada, H.; Torii, S.; Yamasawa, F.; Macznik, A.K. Controlling behavior, sex bias and coaching success in Japanese track and field. Sports 2023, 11, 32. [Google Scholar] [CrossRef] [PubMed]
- Palmer, D.; Cooper, D.J.; Emery, C.; Batt, M.E.; Engebretsen, L.; Scammell, B.E.; Schamasch, P.; Shroff, M.; Soligard, T.; Steffen, K.; et al. Self-reported sports injuries and later-life health status in 3357 retired Olympians from 131 countries: A cross-sectional sur-vey among those competing in the games between London 1948 and PyeongChang 2018. Br. J. Sports Med. 2021, 55, 46–53. [Google Scholar] [CrossRef] [PubMed]
- Moore, M.A.; Vann, S.; Blake, A. Learning from the experiences of collegiate athletes living through a season- or career-ending injury. J. Amat. Sport 2021, 7, 45–63. [Google Scholar] [CrossRef]
- Nagano, Y.; Oyama, T. Association of sports sampling and training frequency with injury among school-age athletes in Japan. Phys. Sportsmed. 2023, 51, 20–26. [Google Scholar] [CrossRef]
- McLellan, M.; Allahabadi, S.; Pandya, N.K. Youth Sports Specialization and Its Effect on Professional, Elite, and Olympic Athlete Performance, Career Longevity, and Injury Rates: A Systematic Review. Orthop. J. Sports Med. 2022, 10, 23259671221129594. [Google Scholar] [CrossRef]
- Ahlquist, S.; Cash, B.M.; Hame, S.L. Associations of early sport specialization and high training volume with injury rates in national collegiate athletic association division I athletes. Orthop. J. Sports Med. 2020, 8, 2325967120906825. [Google Scholar] [CrossRef]
- McHugh, M.P. Oversized young athletes: A weighty concern. Br. J. Sports Med. 2010, 44, 45–49. [Google Scholar] [CrossRef]
- Kim, J.; Yoon, J.H. Does Obesity Affect the Severity of Exercise-Induced Muscle Injury? J. Obes. Metab. Syn-Drome 2021, 30, 132. [Google Scholar] [CrossRef]
Characteristic | All | Males | Females | Sex Unspecified |
---|---|---|---|---|
n = 11,000 | n = 6848 | n = 4096 | n = 56 | |
100% | 62.3% | 37.2% | 0.5% | |
Age, years; mean ± SD | 19.9 ± 1.3 | 19.9 ± 1.4 | 19.8 ± 1.3 | 20.1 ± 1.4 |
Year at university; n (%) | ||||
Year 1 | 3626 (33.0) | 2268 (33.1) | 1343 (32.8) | 15 (26.8) |
Year 2 | 2794 (25.4) | 1765 (25.8) | 1018 (24.8) | 12 (21.4) |
Year 3 | 2348 (21.3) | 1496 (21.8) | 838 (20.4) | 15 (26.8) |
Year 4 | 2145 (19.5) | 1250 (18.3) | 881 (21.5) | 14 (25.0) |
Year 5 | 51 (0.5) | 44 (0.6) | 7 (0.2) | 0 (0) |
Year 6 | 34 (0.3) | 25 (0.4) | 9 (0.2) | 0 (0) |
Height, cm; mean ± SD | 168.3 ± 8.6 | 173.1 ± 6 | 160.2 ± 5.8 | 165.7 ± 10 |
Weight, kg; mean ± SD | 66.2 ± 14.1 | 72.7 ± 13.3 | 55.5 ± 7.1 | 61.4 ± 13.7 |
BMI; mean ± SD | 23.2 ± 3.6 | 21.6 ± 2.3 | 21.6 ± 2.3 | 22.3 ± 3.9 |
Sporting experience, years; mean ± SD | 8 ± 4.9 | 8.1 ± 5 | 7.9 ± 4.8 | 7.7 ± 4.5 |
Sports; n (%) | ||||
Lacrosse | 1689 (15.4) | 701 (10.2) | 978 (23.9) | 10 (17.9) |
Softball | 1243 (11.3) | 300 (4.4) | 994 (22.8) | 9 (16.1) |
Baseball | 1212 (11.0) | 1208 (17.6) | 1 (0.0) | 3 (5.4) |
American Football | 896 (8.1) | 887 (13.0) | 5 (0.1) | 4 (7.1) |
Soccer | 884 (8.0) | 697 (10.2) | 184 (4.5) | 3 (5.4) |
Rugby | 829 (7.5) | 794 (11.6) | 34 (0.8) | 1 (0.0) |
Judo | 564 (5.1) | 376 (5.5) | 183 (4.5) | 5 (8.9) |
Track | 531 (4.8) | 386 (5.6) | 143 (3.5) | 2 (3.6) |
Basketball | 433 (3.9) | 117 (1.1) | 314 (7.7) | 2 (3.6) |
Volleyball | 334 (3.0) | 105 (1.5) | 225 (5.5) | 4 (7.1) |
Other (74 sports) | 2385 (21.7) | 1277 (18.6) | 1095 (26.7) | 13 (23.2) |
Practice days per week; mean ± SD | 5.2 ± 1.3 | 5.2 ± 1.3 | 5.1 ± 1.3 | 4.8 ± 1.5 |
Matches/competitions per season; n(%) | ||||
1–5 matches | 6494 (58.1) | 3711 (54.2) | 2648 (64.6) | 37 (66.1) |
6–10 matches | 2462 (22.4) | 1673 (24.4) | 781 (19.1) | 8 (14.3) |
11–15 matches | 872 (7.9) | 600 (8.8) | 270 (2.5) | 2 (3.6) |
16–20 matches | 509 (4.6) | 363 (5.3) | 143 (3.5) | 3 (5.4) |
21–25 matches | 256 (2.3) | 171 (2.5) | 83 (2.0) | 2 (3.6) |
26–30 matches | 153 (1.4) | 98 (1.4) | 54 (1.3) | 1 (1.8) |
>30 matches | 352 (3.2) | 232 (3.4) | 117 (2.9) | 3 (5.4) |
Hand dominance; n (%) | ||||
right | 9786 (89.0) | 6038 (88.2) | 3704 (90.4) | 46 (82.1) |
left | 968 (8.8) | 670 (9.8) | 296 (7.2) | 2 (3.6) |
both | 210 (1.9) | 119 (1.7) | 85 (2.1) | 6 (10.7) |
Leg dominance; n (%) | ||||
right | 9256 (84.2) | 5879 (85.8) | 3340 (81.5) | 39 (69.6) |
left | 1422 (12.9) | 809 (11.8) | 605 (14.8) | 8 (14.3) |
both | 266 (2.4) | 137 (2.0) | 123 (3.0) | 6 (10.7) |
Characteristic | All | Males | Females | Sex Unspecified |
---|---|---|---|---|
n = 11,000 | n = 6848 | n = 4096 | n = 56 | |
100% | 62.3% | 37.2% | 0.5% | |
Reported injuries within a year; n (%) | 5500 (50.0) | 3562 (52.0) | 1910 (46.7) | 28 (50.0) |
one | 3280 (54.8) | 2128 (31.1) | 1138 (27.8) | 14 (50.0) |
two | 1458 (13.3) | 919 (13.4) | 532 (13.0) | 7 (12.5) |
three | 417 (3.7) | 276 (4.0) | 138 (3.3) | 3 (5.4) |
more | 345 (3.1) | 239 (3.5) | 102 (2.5) | 4 (7.1) |
none | 5500 (50.0) | 3286 (48.0) | 2186 (53.4) | 28 (50.0) |
Injury location; n | 8190 | 5317 | 2825 | 48 |
Missing 214 | Missing 3 | Missing 18 | Missing 0 | |
Head | ||||
Head | 246 | 204 * | 40 | 2 |
Face | 153 | 89 | 62 | 2 |
Trunk | ||||
Lumbo-sacral, spine, buttocks | 763 | 492 | 267 | 4 |
Chest | 80 | 58 | 22 | 0 |
Neck | 73 | 57 * | 15 | 1 |
Upper back | 46 | 28 | 18 | 0 |
Abdomen | 29 | 18 | 11 | 0 |
Upper limb | ||||
Shoulder | 749 | 561 * | 187 | 1 |
Elbow | 342 | 258 * | 83 | 1 |
Hand | 249 | 181 * | 66 | 2 |
Finger | 206 | 133 | 73 | 0 |
Wrist | 168 | 102 | 64 | 2 |
Thumb | 103 | 69 | 33 | 1 |
Arm | 83 | 57 | 26 | 0 |
Lower limb | ||||
Ankle | 1423 | 883 | 525 * | 15 |
Knee | 1167 | 682 | 476 * | 9 |
Thigh | 983 | 651 | 329 | 3 |
Toe | 747 | 453 | 289 | 5 |
Lower Leg | 386 | 221 | 165 * | 0 |
Hip joint | 99 | 57 | 42 | 0 |
Achilles | 92 | 60 | 32 | 0 |
Severity; n | 8211 | 5320 | 2843 | 48 |
Minimal (0 days lost) | 1215 | 630 | 577 * | 8 |
Mild (1D–1W lost) | 1680 | 1014 | 656 * | 10 |
Moderate (1W–1M lost) | 2650 | 1816 * | 821 | 13 |
Severe (1M–6M lost) | 2147 | 1535 * | 599 | 13 |
Very severe (>6 months lost) | 519 | 325 | 190 | 4 |
Type; n | 8211 | 5320 | 2843 | 48 |
new | 5629 | 3721 * | 1872 | 36 |
recurrent | 2266 | 1439 | 818 | 9 |
exacerbated | 316 | 160 | 153 * | 3 |
Onset (part of the season); n | ||||
pre-season | 3372 | 2136 | 1221 * | 15 |
in season | 4100 | 2791 * | 1288 | 21 |
post-season | 580 | 325 | 249 * | 6 |
other | 159 | 68 | 85 | 6 |
Onset (match or training); n | ||||
in match | 2283 | 1495 | 782 | 6 |
in training | 5928 | 3825 | 2061 | 42 |
Mechanism; n | ||||
direct | 3405 | 2458 * | 926 | 23 |
indirect | 929 | 620 | 304 | 5 |
non-contact | 3875 | 2242 | 1613 * | 20 |
Time lost; n | ||||
yes | 6771 | 4521 * | 2209 | 41 |
no | 1440 | 799 | 634 * | 7 |
Injured | Uninjured | |||
---|---|---|---|---|
n = 5472 * | n = 5472 * | Pearson’s χ2 | p value | |
Sex; n (%) | 50% | 50% | ||
Male | 3562 (65.1) | 3286 (60.1) | 29.5 | <0.001 |
Female | 1910 (34.9) | 2186 (39.9) | ||
Year at university; n (%) | ||||
Year 1 | 1421 (26.0) | 2190 (40.0) | 257.8 | <0.001 |
Year 2 | 1480 (27.0) | 1303 (23.8) | ||
Year 3 | 1338 (24.5) | 996 (18.2) | ||
Year 4+ | 1233 (22.5) | 983 (18.0) | ||
BMI; n (%) | ||||
Underweight (<18.5) | 160 (2.9) | 240 (4.4) | 179.2 | <0.001 |
Normal (18.5–24.9) | 3750 (68.5) | 4245 (77.6) | ||
Overweight (25.0–29.9) | 1175 (21.5) | 773 (14.1) | ||
Obese (>30.0) | 387 (7.1) | 214 (3.9) | ||
Practice days per week; n (%) | ||||
1 | 36 (0.7) | 217 (4.0) | 578.4 | <0.001 |
2 | 61 (1.1) | 242 (4.4) | ||
3 | 229 (4.2) | 605 (11.1) | ||
4 | 460 (8.4) | 709 (13.0) | ||
5 | 1314 (24.0) | 1095 (20.0) | ||
6 | 3129 (57.2) | 2420 (44.2) | ||
7 | 243 (4.4) | 184 (3.4) | ||
Matches/competitions per season; n (%) | ||||
1–5 matches | 3003 (54.9) | 3355 (61.3) | 54.9 | <0.001 |
6–10 matches | 1347 (24.6) | 1108 (20.2) | ||
11–15 matches | 393 (7.2) | 477 (8.7) | ||
16–20 matches | 270 (4.9) | 236 (4.3) | ||
21–25 matches | 127 (2.3) | 127 (2.3) | ||
26–30 matches | 73 (1.3) | 79 (1.4) | ||
>30 matches | 175 (3.2) | 174 (3.2) |
Factor | Odds Ratio | 95%CI | p Value |
---|---|---|---|
Age | 1.002 | 0.943–1.066 | 0.943 |
Sex | |||
Male | reference | ||
Female | 0.942 | 0.863–1.029 | 0.184 |
Year at university | |||
Year 1 | reference | ||
Year 2 | 1.741 | 1.538–1.970 | <0.001 |
Year 3 | 1.951 | 1.651–2.306 | <0.001 |
Year 4+ | 1.760 | 1.411–2.194 | <0.001 |
BMI | |||
Normal (18.5–24.9) | reference | ||
Underweight (<18.5) | 0.959 | 0.770–1.194 | |
Overweight (25.0–29.9) | 1.465 | 1.313–1.635 | <0.001 |
Obese (>30.0) | 1.700 | 1.415–2.044 | <0.001 |
Sports Experience | 1.021 | 1.012–1.030 | <0.001 |
Practice days per week | |||
1–4 | reference | ||
5–7 | 2.482 | 2.234–2.757 | <0.001 |
Matches/competitions per season; | |||
1–5 matches | reference | ||
6–10 matches | 1.099 | 0.995–1.214 | 0.063 |
11–15 matches | 1.081 | 0.930–1.257 | 0.309 |
16–20 matches | 1.034 | 0.855–1.252 | 0.728 |
21–25 matches | 0.842 | 0.648–1.095 | 0.200 |
26–30 matches | 0.778 | 0.558–1.086 | 0.141 |
>30 matches | 0.826 | 0.660–1.035 | 0.097 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kimura, T.; Mącznik, A.K.; Kinoda, A.; Yamada, Y.; Muramoto, Y.; Katsumata, Y.; Sato, K. Prevalence of and Factors Associated with Sports Injuries in 11,000 Japanese Collegiate Athletes. Sports 2024, 12, 10. https://doi.org/10.3390/sports12010010
Kimura T, Mącznik AK, Kinoda A, Yamada Y, Muramoto Y, Katsumata Y, Sato K. Prevalence of and Factors Associated with Sports Injuries in 11,000 Japanese Collegiate Athletes. Sports. 2024; 12(1):10. https://doi.org/10.3390/sports12010010
Chicago/Turabian StyleKimura, Takeshi, Aleksandra Katarzyna Mącznik, Akira Kinoda, Yuichi Yamada, Yuki Muramoto, Yoshinori Katsumata, and Kazuki Sato. 2024. "Prevalence of and Factors Associated with Sports Injuries in 11,000 Japanese Collegiate Athletes" Sports 12, no. 1: 10. https://doi.org/10.3390/sports12010010
APA StyleKimura, T., Mącznik, A. K., Kinoda, A., Yamada, Y., Muramoto, Y., Katsumata, Y., & Sato, K. (2024). Prevalence of and Factors Associated with Sports Injuries in 11,000 Japanese Collegiate Athletes. Sports, 12(1), 10. https://doi.org/10.3390/sports12010010