Predicting Injury Risk Over Changes in Physical Activity in Children Using the Acute:Chronic Workload Ratio.

Limited research exists on the relationship between changes in physical activity levels and injury in children. In this study, we investigated the prognostic relationship between changes in activity, measured by the acute:chronic workload ratio (ACWR), and injury in children. We used data from the Childhood Health, Activity, and Motor Performance School Study Denmark (2008-2014), a prospective cohort study of 1,660 children aged 6-17 years. We modeled the relationship between the uncoupled 5-week ACWR and injury, defined as patient-reported musculoskeletal pain, using generalized additive mixed models. These methods accounted for repeated measures, and they improved model fit and precision compared with previous studies that used logistic models. The prognostic model predicted an injury risk of approximately 3% between decreases in activity level of up to 60% and increases of up to 30%. Predicted risk was lower when activity decreased by more than 60% (minimum of 0.5% with no recreational activity). Predicted risk was higher when activity increased by more than 30% (4.5% with a 3-fold increase in activity). Girls were at significantly higher risk of injury than boys. We observed similar patterns but lower absolute risks when we restricted the outcome to clinician-diagnosed injury. Predicted increases in injury risk with increasing activity were much lower than those of previous studies carried out in adults.

Analyzing Activity and Injury: Lessons Learned from the Acute:Chronic Workload Ratio.

Injuries occur when an athlete performs a greater amount of activity than what their body can withstand. To maximize the positive effects of training while avoiding injuries, athletes and coaches need to determine safe activity levels. The International Olympic Committee has recommended using the acute:chronic workload ratio (ACWR) to monitor injury risk and has provided thresholds to minimize risk when designing training programs. However, there are several limitations to the ACWR and how it has been analyzed which impact the validity of current recommendations and should discourage its use. This review aims to discuss previously published and novel challenges with the ACWR, and strategies to improve current analytical methods. In the first part of this review, we discuss challenges inherent to the ACWR. We explain why using a ratio to represent changes in activity may not always be appropriate. We also show that using exponentially weighted moving averages to calculate the ACWR results in an initial load problem, and discuss their inapplicability to sports where athletes taper their activity. In the second part, we discuss challenges with how the ACWR has been implemented. We cover problems with discretization, sparse data, bias in injured athletes, unmeasured and time-varying confounding, and application to subsequent injuries. In the third part, conditional on well-conceived study design, we discuss alternative causal-inference based analytical strategies that may avoid major flaws in studies on changes in activity and injury occurrence.