| Biomechanical Predictors of Overuse Injuries in Endurance Runners: Insights from Longitudinal Studies – A Narrative Review |
| Paper ID : 1472-SPORTCONGRESS (R1) |
| Authors |
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amir hossein vaghari gargari *1, akram Eskandari2 1دانشجوی دکترای آسیب شناسب ورزشی وحرکات اصلاحی پردیس بین المللی کیش دانشگاه تهران 2دانشجوی دکترای آسیب شناسی ورزش و جرکات اصلاحی پردیس کاسپین دانشگاه تهران |
| Abstract |
| Background:Endurance running is widely practiced for its well-established cardiovascular, musculoskeletal, and general health benefits, but repetitive high-load exposure predisposes athletes to overuse injuries (OIs), particularly in the lower limbs. Methods: A qualitative narrative synthesis was conducted on longitudinal and cohort studies published between 2018 and 2025, retrieved from Scopus, Web of Science, and Google Scholar. Eligible studies prospectively tracked running-related injuries while measuring at least one objective biomechanical parameter, including stride length, cadence, tibial acceleration, or kinematic/kinetic variables. Emphasis was placed on integrating conceptual trends across studies, including prior injury, training load, biomechanical deviations, and physiological or health-related factors, rather than aggregating statistical results. Results: Across the reviewed literature, previous injury consistently emerged as the strongest predictor of OIs. Training load and variability were influential, with higher weekly mileage and abrupt changes in load increasing injury risk. Deviations in stride mechanics, such as reduced cadence (<160 steps/min) and increased vertical tibial acceleration, were associated with elevated injury probability. Female runners with low BMI and runners with cumulative chronic health burdens also demonstrated increased susceptibility. In contrast, static factors, including moderate foot pronation and lower limb alignment, were not independently predictive. Machine learning approaches enabled modeling of nonlinear interactions between biomechanical, physiological, and environmental factors, supporting the development of individualized cumulative risk profiles and highlighting the multifactorial nature of injury susceptibility. Conclusion: Overuse injuries in endurance runners arise from complex interactions among prior injuries, dynamic biomechanical patterns, training load, and individual physiological resilience. Static models are insufficient for precise prediction; instead, multifactorial, data-driven strategies integrating wearable sensor data, bone and metabolic markers, and machine learning analytics are essential. Personalized assessment of cumulative risk allows targeted, adaptive preventive interventions, offering a paradigm shift in reducing injury burden among endurance runners. |
| Keywords |
| Running-related injuries, Biomechanical risk factors, Endurance runners |
| Status: Abstract Accepted (Poster Presentation) |
