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Medicine & Science in Sports & Exercise:
doi: 10.1249/MSS.0b013e31827a1c4c
Clinical Sciences

Functional Movement Screen and Aerobic Fitness Predict Injuries in Military Training

LISMAN, PETER1; O’CONNOR, FRANCIS G.1; DEUSTER, PATRICIA A.1; KNAPIK, JOSEPH J.2

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Abstract

Purpose: This study investigated associations between injuries and individual components of the Marine Corps physical fitness test (PFT), self-reported exercise and previous injury history, and Functional Movement Screen (FMS) scores.

Methods: A cohort of 874 men enrolled in either 6 wk (n = 447) or 10 wk (n = 427) of Marine Corps officer candidate training was recruited. They completed an exercise history questionnaire, underwent an FMS during medical in-processing, and completed the standardized PFT (pull-ups, abdominal crunch, and 3-mile run) within 1 wk of training. Injury data were gathered throughout training from medical records and classified into overuse, traumatic, and any injury.

Results: Three-mile run time (RT) was the only PFT component predictive of injury: candidates with RT ≥20.5 min were 1.7 times (95% confidence interval = 1.29–2.31, P < 0.001) more likely to experience an injury compared with those with RT <20.5 min. Prior injury, frequency of general exercise and sport participation, and length of running history were predictive of any, overuse, and traumatic injuries, respectively. Combining slow RT and low FMS scores (≤14) increased the predictive value across all injury classifications: candidates scoring poorly on both tests were 4.2 times more likely to experience an injury. The pull-up to exhaustion test was related to four of the seven FMS tests and the only PFT test positively related to total FMS score, although correlations were generally low (r ≤ 0.11).

Conclusion: Slow RT was associated with increased injury risk, and combining poor RT and low FMS scores significantly increased the injury predictive value. Additional research is warranted to further clarify what combination of PFT and FMS tests are most suitable for predicting injuries.

©2013The American College of Sports Medicine

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