Abstract
Injury prevention is critical to the achievement of peak performance in elite sport. For professional tennis players, the topic of injury prevention has gained even greater importance in recent years as multiple of the best male players have been sidelined owing to injury. Identifying potential causative factors of injury is essential for the development of effective prevention strategies, yet such research is hampered by incomplete data, the complexity of injury etiology, and observational study biases. The present study attempts to address these challenges by focusing on competition load and time-loss to competition-a completely observable risk factor and outcome-and using a structural nested mean model (SNMM) to identify the potential causal role of cumulative competition load on the risk of time-loss. Using inverse probability of treatment weights to balance exposure histories with respect to player ability, past injury, and consecutive competition weeks at each time point; the SNMM analysis of 389 professional male players and 55,773 weeks of competition found that total load significantly increases the risk of time-loss (HR = 1.05 per 1,000 games of additional load 95% CI 1.01-1.10) and this effect becomes magnified with age. Standard regression showed a protective effect of load, highlighting the value of more robust causal methods in the study of dynamic exposures and injury in sport and the need for further applications of these methods for understanding how time-loss and injuries of elite athletes might be prevented in the future.
Highlights
Injury is one of the most significant threats to the longevity of elite athletes and, when injury ends the careers of the industry’s stars prematurely, can pose a significant threat to the business of sports [1]
We develop an structural nested mean model (SNMM) for the potential causal effect of cumulative load on time-loss risk in the presence of age modification using regression with residuals and an inverse probability of treatment weighting strategy
The present study found that standard methods, which do not protect against such biases, would lead to the conclusion that cumulative competition load was protective against absences from competition
Summary
Injury is one of the most significant threats to the longevity of elite athletes and, when injury ends the careers of the industry’s stars prematurely, can pose a significant threat to the business of sports [1]. Continued growth of the sports market has resulted in increasing commercial opportunities and, inevitably, greater physical demands on athletes to play harder, faster, and longer [2]. The growing pressure to stay competitive has made injury prevention a top priority of high-performance sport [3].
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