The functional movement screen predicts sports injuries in Chinese college students at different levels of physical activity and sports performance

Hua Liu; Huixian Ding; Junjie Xuan; Xing Gao; Xuejuan Huang

doi:10.1016/j.heliyon.2023.e16454

The functional movement screen predicts sports injuries in Chinese college students at different levels of physical activity and sports performance

Heliyon. 2023 May 20;9(6):e16454. doi: 10.1016/j.heliyon.2023.e16454. eCollection 2023 Jun.

Authors

Hua Liu¹, Huixian Ding², Junjie Xuan², Xing Gao², Xuejuan Huang³

Affiliations

¹ Laboratory of Physical Fitness Monitoring & Chronic Disease Intervention, Wuhan Sports University, Wuhan, 430079, China.
² Graduate School, Wuhan Sports University, Wuhan, 430079, China.
³ Department of Sports Engineering and Information Technology, Wuhan Sports University, Wuhan 430079, China.

Abstract

Background: Functional Movement Screen (FMS) is used to evaluate the movement quality of an individual. However, the FMS composite score used to predict sports injuries is currently ambiguous. Further refinement of the FMS scoring method may be required to more accurately predict sports injuries.

Objectives: To investigate whether FMS scores could accurately predict sports injuries in college students with different levels of physical activity (PA) and sports performance (SP).

Methods: One hundred eighty-seven college students aged 18 to 22 were prospectively screened by the FMS test and grouped by the levels of PA and SP. Sports injury occurrences were monitored and collected 12 months later. Spearman's rank coefficients and binary logistic regression were used to identify the risk factors for sports injuries. The receiver operating characteristic (ROC) curve and the total area under the curve (AUC) value were used to determine the optimal FMS cut-off point for sports injuries.

Results: The FMS composite score (sum of the seven FMS tests) exhibited a fair association with sports injuries (r = -0.434, P < 0.001). Those with an FMS cut-off point of 17.5 were more likely to acquire sports injuries. The AUC value of the ROC curves was 0.764 (95% CI: 0.618-0.909) in the low PA students, 0.781 (95% CI: 0.729-0.936) in the moderate PA students, and 0.721 (95% CI: 0.613-0.879) in the high PA students. Furthermore, students stratified by SP level showed an AUC value of 0.730 (95% CI 0.607-0.853) in the low SP group and 0.778 (95% CI 0.662-0.894) in the moderate SP group, while it declined to 0.705 (95% CI 0.511-0.800) in the high SP group. The FMS cut-off score successfully identified individuals who reported sports injuries at a higher rate in the low (PA, 84.62%; SP, 90.48%) and moderate (PA, 93.75%; SP, 77.78%) groups than in the high groups (PA, 65.52%; SP, 57.89%).

Conclusions: The FMS composite score could be used to predict sports injuries in college students with an FMS cut-off value of 17.5. Population stratification by the levels of PA and SP seems to influence the predictive accuracy of the FMS.

Keywords: Functional movement screen; Injury prevention; Physical activity; Sport injury; Sports performance.