The etiological mechanism underpinning any sports-related injury is complex and multifactorial. Frequently, athletes perceive "excessive training" as the principal factor in their injury, an observation that is biologically plausible yet somewhat ambiguous. If the applied training load is suddenly increased, this may increase the risk for sports injury development, irrespective of the absolute amount of training. Indeed, little to no rigorous scientific evidence exists to support the hypothesis that fluctuations in training load, compared to absolute training load, are more important in explaining sports injury development. One reason for this could be that prospective data from scientific studies should be analyzed in a different manner. Time-to-event analysis is a useful statistical tool in which to analyze the influence of changing exposures on injury risk. However, the potential of time-to-event analysis remains insufficiently exploited in sports injury research. Therefore, the purpose of the present article was to present and discuss measures of association used in time-to-event analyses and to present the advanced concept of time-varying exposures and outcomes. In the paper, different measures of association, such as cumulative relative risk, cumulative risk difference, and the classical hazard rate ratio, are presented in a nontechnical manner, and suggestions for interpretation of study results are provided. To summarize, time-to-event analysis complements the statistical arsenal of sports injury prevention researchers, because it enables them to analyze the complex and highly dynamic reality of injury etiology, injury recurrence, and time to recovery across a range of sporting contexts.
Keywords: injury prevention; methodology; statistics; time-varying variables.