@article{Gogoi_Rajpoot_Borah_2021, title={A Prospective Cohort Study to Predict Running-Related Lower Limb Sports Injuries Using Gait Kinematic Parameters}, volume={21}, url={https://tmfv.com.ua/journal/article/view/1470}, DOI={10.17309/tmfv.2021.1.09}, abstractNote={<p><strong>The study purpose</strong> was to follow a prospective cohort study design to use gait kinematic parameters to identify the risk factors and to develop a statistical model to predict running-related lower limb injuries of sportspersons.<span class="Apple-converted-space"> </span></p> <p><strong>Materials and methods.</strong> BTS G-WALK® gait analysis system was used to collect gait kinematic data of 87 subjects from an institute of physical education and sports science.<span class="Apple-converted-space"> </span></p> <p>The subjects were followed for a full academic season after which the researcher inquired about their injury occurrences. Binary logistic regression was used to develop a prediction model to predict lower limb injuries of sportspersons.</p> <p><strong>Results.</strong> The result of the study revealed that increasing Range of Obliquity, Range of Tilt and Range of Rotation were associated with increased likelihood of future running-related lower limb injury. However, the lower Symmetry Index was associated with increase in the likelihood of future running-related lower limb injury.</p> <p><strong>Conclusions.</strong> The study confirmed that it is possible to predict injury, but for practical implication further research is essential with a bigger sample size.</p>}, number={1}, journal={Physical Education Theory and Methodology}, author={Gogoi, Hemantajit and Rajpoot, Yajuvendra Singh and Borah, Poli}, year={2021}, month={Mar.}, pages={69–76} }