When officials ban body checking in non-elite adolescent ice hockey leagues, rates of injury and concussion decrease, according to a new study.
Banning Body Checking in Teen Ice Hockey Reduces Concussions
Previous studies like a 2016 study in Pediatrics have shown that concussions continue to be high in youth hockey, comparable to other collision sports.
The study, “Body checking in non-elite adolescent ice hockey leagues: it is never too late for policy change aiming to protect the health of adolescents,” published online on May 20, 2021 in the British Journal of Sports Medicine, focused on players that were 15 to 17 years old in non-elite divisions of play in Canada between 2015 and 2018.
The researchers collected baseline data, exposure-hours, and injury data from 44 non-body checking teams and 52 teams that allowed body-checking. Any player who was suspected to have a concussion was referred to a study physician for evaluation.
The primary outcomes include game-related injuries, game-related concussions, and game-related concussions.
In the body checking leagues, there were 213 injuries, 69 of which were concussions. In the non-body checking leagues, there were 40 injuries, 18 of which were concussions.
Mixed–effects Poisson regression analyses showed that the no body checking policy was associated with a lower rate of injury (incidence rate ration (IRR): 0.38 (95% CI 0.24 to 0.6) and concussion (IRR: 0.49; 95% CI 0.26 to 0.89).
Overall the policy change brought an absolute rate reduction of 7.82 injuries/1000 game-hours (95% CI 2.74 to 12.9) and the prevention of 7,326 injuries (95% CI 2570 to 12083) in Canada each year.
“The rate of injury was 62% lower (concussion 515 lower) in leagues not permitting body checking in non-elite 15-17 years old leagues highlighting the potential public health impact of policy prohibiting body checking in older adolescent ice hockey players,” the researchers wrote.

Discussion
This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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