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SIDE- AND AGE-SPECIFIC POSTURAL ADAPTATIONS OF MALE ELITE JUNIOR SOCCER PLAYERS (UNDER 16, 17 & 19)

Background Playing soccer at professional level may induce functional and structural adaptations of the neuro-musculoskeletal system based on soccer specific movement coordination due to continuous asymmetrical loadings. This may predispose young athletes in particular to pathologic conditions and increased injury risk at early stages within their careers. Objective The purpose was to quantify the static standing profile. It was hypothesized that the alignment differs between limbs (footedness) and age groups. Design Experimental, prospective cohort study. Setting Biomechanical assessment in clinical practice. Patients (or Participants) 102 uninjured male elite junior soccer players aged between 16 and 19 years old reporting no former joint injury. Interventions (or Assessment of Risk Factors) Three-dimensional motion capture (SIMI Motion 3D) analysing the static standing profile. Main Outcome Measurements 3D kinematic data of the thoracic (TH 12) and lumbar spine (L3), pelvis and hips, knees and ankles bilateral, comprising 27 variables. Results Kinematic data indicate age-specific differences for the amount of thoracic extension, knee adduction and external rotation of the supporting leg (p<0.05). Side-specific adaptations can be proven for functional scoliosis at the thoracolumbar junction and height of iliac crest (p<0.05). K-means analyses show significant differences for hip abduction and external rotation for the kicking leg (p<0.05). By means of correspondence analysis U19 players can be associated with lumbar scoliosis, knee varus for the supporting leg and knee valgus for the kicking leg. Conclusions The older the players, the more complex the functional postural adaptations. The results provide plausible explanations for increased injury risk of ACL injuries on the kicking leg, groin pain, and the need for more sophisticated injury prevention programs. From a methodological point of view, comprehensive 3D-static analysis using appropriate statistical analyses seems to be well suited for the assessment of postural deviations for large scale cohorts.