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Factors Influencing the Relationship Between the Functional Movement Screen and Injury Risk in Sporting Populations:
Emma Moore1, Samuel Chalmers2,3, Steve Milanese4
1International Centre for Allied Health Evidence (iCAHE), University of South Australia, GPO Box 2471, Adelaide, SA, 5000, Australia. emma.moore@mymail.unisa.edu.au.
Background:
Studies investigating the association between the Functional Movement Screen (FMS) and sports injury risk have reported mixed results across a range of athlete populations.
Objectives:
The purpose of this systematic review was to identify whether athlete age, sex, sport type, injury definition and mechanism contribute to the variable findings.
Study Design:
Systematic review and meta-analysis.
Methods:
A systematic search was conducted in October 2018 using PubMed, EBSCOhost, Scopus, EmBase and Web of Science databases. Studies were included if they were peer reviewed and published in English language, included athletes from any competition level, performed the FMS at baseline to determine risk groups based on FMS composite score, asymmetry or pain, and prospectively observed injury incidence during training and competition. Study eligibility assessment and data extraction was performed by two reviewers. Random effects meta-analyses were used to determine odds ratio (OR), sensitivity and specificity with 95% confidence intervals. Sub-group analyses were based on athlete age, sex, sport type, injury definition, and injury mechanism.
Results:
Twenty-nine studies were included in the FMS composite score meta-analysis. There was a smaller effect for junior (OR = 1.03 [0.67-1.59]; p = 0.881) compared to senior athletes (OR = 1.80 [1.17-2.78]; p = 0.008) and for male (OR = 1.79 [1.08-2.96]; p = 0.024) compared to female (OR = 1.92 [0.43-8.56]; p = 0.392) athletes. FMS composite scores were most likely to be associated with increased injury risk in rugby (OR = 5.92 [1.67-20.92]; p = 0.006), and to a lesser extent American football (OR = 4.41 [0.94-20.61]; p = 0.059) and ice hockey (OR = 3.70 [0.89-15.42]; p = 0.072), compared to other sports. Specificity values were higher than sensitivity values for FMS composite score. Eleven studies were included in the FMS asymmetry meta-analysis with insufficient study numbers to generate sport type subgroups. There was a larger effect for senior (OR = 1.78 [1.16-2.73]; p = 0.008) compared to junior athletes (OR = 1.21 [0.75-1.96]; p = 0.432). Sensitivity values were higher than specificity values for FMS asymmetry. For all FMS outcomes, there were minimal differences across injury definitions and mechanisms. Only four studies provided information about FMS pain and injury risk. There was a smaller effect for senior athletes (OR = 1.28 [0.33-4.96]; p = 0.723) compared to junior athletes (OR = 1.71 [1.16-2.50]; p = 0.006). Specificity values were higher than sensitivity values for FMS pain.
Conclusion:
Athlete age, sex and sport type explained some of the variable findings of FMS prospective injury-risk studies. FMS composite scores and asymmetry were more useful for estimating injury risk in senior compared to junior athletes. Effect sizes tended to be small except for FMS composite scores in rugby, ice hockey and American football athletes.
Protocol Registration:
CRD42018092916.
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