Epidemiology and prediction models of injuries in male youth football players

Abstract

Abstract Despite the multiple health benefits, participation in a physically demanding sport such as football may also lead to an increased injury risk. The great efforts made by the scientific community and practitioners in recent years have not reached the reduction of the number and severity of football-related injuries. The inefficacy of the preventive measures implemented might be partly caused by the limitations present in the current literature. To help overcome these limitations, this doctoral thesis aims (a) to establish the extent of the injury problem in male youth football players, (b) to improve the understanding regarding the aetiology and mechanisms of injury through the analysis of the interaction between potential injury risk factors, and (c) to develop a robust prediction model to identify young football players at high or low risk of injury using a field-based screening battery. To this end, five studies are presented. The first study performs a systematic review and meta-analysis to quantify the overall, training and match injury incidences in youth football players, as well as the location, type, severity, and mechanism of football-related injuries. The second study describes the specific injury profile in young Spanish male football players. The third study analyses and compares the influence of chronological age and maturational stage on several lower extremity range of motion measures, describing the lower extremity range of motion profile using a comprehensive approach in youth football players. The fourth study (1) determines the inter-rater and intra-rater reliability of frontal (frontal plane projection angle) and sagittal (hip, knee and ankle flexion angles at initial contact and peak flexion) plane landing kinematic measures during drop vertical jump (DVJ) and tuck jump assessment (TJA) tasks in male youth football players, (2) assesses the concurrent validity between both tests for all landing kinematic measures, and (3) evaluates the ability of these jumping tasks to detect differences between players' stage of maturation. Finally, the fifth study develops a robust screening model based on pre-season measures to prospectively predict lower extremity soft-tissue (LE-ST) injuries in young football players after having applied supervised learning algorithms. The findings obtained in this doctoral thesis (1) corroborate a high incidence of injury among young football players, (2) show the relationship between the biological maturation process and some important injury risk factors such as range of motion and landing kinematics, and (3) present an injury prediction model using a subset of six pre-season field-based measures capable of identifying one in two and four in five young players at high and low risk of sustaining a soft tissue (muscle, tendon and ligament) injury of the lower extremity over the course of a sport season. Keywords: soccer, young, incidence, burden, landing, kinematic, neuromuscular control, range of motion, maturation, screening, prediction, machine learning.