Future studies should also consider measures of ME and MS as a function of upper body , lower body , and core strength , and their potential association with specific , rather than general ,
Abstract de la Motte , SJ , Gribbin , TC , Lisman , P , Murphy , K , and Deuster , PA .
A systematic review of the association between physical fitness and musculoskeletal injury risk : part 2—muscular endurance and muscular strength .
Ability of Preseason Body Composition and Physical Fitness to Predict the Risk of Injury in Male Collegiate Hockey Players
Background : Injuries in collegiate ice hockey can result in significant time lost from play . The identification of modifiable risk factors relating to a player ’s physical fitness allows the development of focused training and injury prevention programs targeted at reducing these risks . Purpose : To determine the ability of preseason fitness outcomes to predict in-season on-ice injury in male collegiate ice hockey players . Study Design : Prognostic cohort study . Level of Evidence : Level 3 . Methods : Athlete demographics , percentage body fat , aerobic capacity ( 300-m shuttle run ; 1- , 1.5- , 5-mile run ) , and strength assessment ( sit-ups , push-ups , grip strength , bench press , Olympic cleans , squats ) data were collected at the beginning of 8 successive seasons for 1 male collegiate ice hockey team . Hockey-related injury data and player-level practice /game athlete exposure ( AE ) data were also prospect ively collected . Seventy-nine players participated ( 203 player-years ) . Injury was defined as any event that result ed in the athlete being unable to participate in 1 or more practice s or games following the event . Multivariable logistic regression was performed to determine the ability of the independent variables to predict the occurrence of on-ice injury . Results : There were 132 injuries ( mean , 16.5 per year ) in 55 athletes . The overall injury rate was 4.4 injuries per 1000 AEs . Forwards suffered 68 % of the injuries . Seventy percent of injuries occurred during games with equal distribution between the 3 periods . The mean number of days lost due to injury was 7.8 ± 13.8 ( range , 1 - 127 days ) . The most common mechanism of injury was contact with another player ( 54 % ) . The odds of injury in a forward was 1.9 times ( 95 % CI , 1.1 - 3.4 ) that of a defenseman and 3 times ( 95 % CI , 1.2 - 7.7 ) that of a goal ie . The odds of injury if the player ’s body mass index ( BMI ) was ≥25 kg/m2 was 2.1 times ( 95 % CI , 1.1 - 3.8 ) that of a player with a BMI < 25 kg/m2 . The odds ratios for bench press , maximum sit-ups , and Olympic cleans were statistically significant but close to 1.0 , and therefore the clinical relevance is unknown . Conclusion : Forwards have higher odds of injury relative to other player positions . BMI was predictive of on-ice injury . Aerobic fitness and maximum strength outcomes were not strongly predictive of on-ice injury
Future studies should also consider measures of ME and MS as a function of upper body , lower body , and core strength , and their potential association with specific , rather than general ,
Abstract de la Motte , SJ , Gribbin , TC , Lisman , P , Murphy , K , and Deuster , PA .
A systematic review of the association between physical fitness and musculoskeletal injury risk : part 2—muscular endurance and muscular strength .