Interactions between running volume and running pace on injury occurrence in recreational runners: A secondary analysis.

Abstract

Abstract Context The combination of an excessive increase in running pace and volume is essential to consider when investigating associations between running and running-related injury. Objectives The purpose of the present study was to complete a secondary analysis on a dataset from a randomized trial, to investigate the interactions between relative or absolute weekly changes in running volume and running pace on running injury occurrence among a cohort of injury-free recreational runners in Denmark. Design Prospective cohort study Setting Running volume and pace were collected during a 24-week follow-up using global positioning systems (GPS) data. Training data was used to calculate relative and absolute weekly changes in running volume and pace. Patients or Other Participants A total of 586 recreational runners were included in the analysis. All participants were injury-free at inclusion. Main Outcome Measure(s) Running-related injury was the outcome. Injury data were collected weekly using a modified version of the OSTRC questionnaire. Risk difference (RD) was the measure of injury risk. Results A total of 133 runners sustained a running-related injury. A relative weekly change of progression >10% in running volume and progression in running pace (RD=8.1%, 95%CI: - 9.3;25.6%) and an absolute weekly change of progression >5km in running volume and progression in running pace (RD=5.2%, 95%CI: -12.0;22.5%), were not associated with a statistically significant positive interaction. Conclusions As coaches, clinicians and athletes may agree that excessive increase in running pace and excessive increase in running volume are important contributors to injury development, we analyzed the interaction between them. Although a statistically significant positive interaction on an additive scale in runners who progressed both running pace and running volume were not identified in the present study, readers of scientific articles should be aware that interaction is an important analytical approach that could be applied to other datasets in future publications.