Journal of Sport and Health Science (Sep 2021)
A systematic review of running-related musculoskeletal injuries in runners
Abstract
Objective: Running-related musculoskeletal injuries (RRMIs), especially stemming from overuse, frequently occur in runners. This study aimed to systematically review the literature and determine the incidence and prevalence proportion of RRMIs by anatomic location and specific pathology. Methods: An electronic database search with no date beginning restrictions was performed in SPORTDiscus, PubMed, and MEDLINE up to June 2020. Prospective studies were used to find the anatomic location and the incidence proportion of each RRMI, whereas retrospective or cross-sectional studies were used to find the prevalence proportion of each RRMI. A separate analysis for ultramarathon runners was performed. Results: The overall injury incidence and prevalence were 40.2% ± 18.8% and 44.6% ± 18.4% (mean ± SD), respectively. The knee, ankle, and lower leg accounted for the highest proportion of injury incidence, whereas the knee, lower leg, and foot/toes had the highest proportion of injury prevalence. Achilles tendinopathy (10.3%), medial tibial stress syndrome (9.4%), patellofemoral pain syndrome (6.3%), plantar fasciitis (6.1%), and ankle sprains (5.8%) accounted for the highest proportion of injury incidence, whereas patellofemoral pain syndrome (16.7%), medial tibial stress syndrome (9.1%), plantar fasciitis (7.9%), iliotibial band syndrome (7.9%), and Achilles tendinopathy (6.6%) had the highest proportion of injury prevalence. The ankle (34.5%), knee (28.1%), and lower leg (12.9%) were the 3 most frequently injured sites among ultramarathoners. Conclusion: The injury incidence proportions by anatomic location between ultramarathoners and non-ultramarathoners were not significantly different (p = 0.798). The pathologies with the highest incidence proportion of injuries were anterior compartment tendinopathy (19.4%), patellofemoral pain syndrome (15.8%), and Achilles tendinopathy (13.7%). The interpretation of epidemiological data in RRMIs is limited due to several methodological issues encountered.
