Background. Football accounts for 30% of all sports injuries. Muscle injuries in football are the most common non-traumatic and non-contact injuries. A comprehensive approach to injury prevention must consider the design of the footwear and the environmental conditions in which the match is played. Objective. To assess the risk of injury as a function of footwear and field of play in non-professional football players and to identify the best predictive model of muscle injury in these athletes. Method. Ambispective cohort study. Ninety-seven players will be recruited. The primary variable will be the number of lower limb muscle injuries in the last 3 seasons. Secondary and modifying variables will be: age, body mass index, boot type, pitch turf, training load and field position. Potential confounding variables will be motivation for choice of footwear, date of muscle injuries, time playing in the category and presence in the starting team. The analysis will calculate the risk of adverse effects in these patients and assess the influence of confounders and trend analysis on the primary variable, stratified by potential confounders. Expected outcomes. To calculate the risk of muscle injury as a function of anthropometric variables, and footwear and turf type. To identify the predictive model of muscle injuries in football players.
Study Type
OBSERVATIONAL
Enrollment
156
The data collection will be carried out by the two researchers, in accordance with current data protection regulations, scrupulously complying with the anonymous collection of clinical data, and without collecting any data that could allow the identification of the athletes whose data are collected. The members of the research group will not have access to personal data that could facilitate the identity of any person on the basis of the data collected. The data collected in this study, anonymised from the outset, will be exported to an Excel file. Access to the Excel file will require password access and will be managed from a computer of the University of Oviedo (Department of Surgery and Medical-Surgical Specialities).
University of Oviedo
Oviedo, Principality of Asturias, Spain
Asses the number of lower limb muscle injuries in the last 3 competition seasons
The primary variable, the number of lower limb muscle injuries in the last 3 seasons, will be assessed as a quantitative variable.
Time frame: Screening visit
Assess the age
The secondary variable, age (in years completed), will be assessed as a quantitative variable.
Time frame: Screening visit
Assess the body mass index
The secondary variable, body mass index (in kg/m2), will be assessed as a quantitative variable.
Time frame: Screening visit
Assess the type of training and competition boot in the last 3 competition seasons
The secondary variable, type of training and competition boot (rubber cleat/metal cleat), will be assessed as a nominal qualitative variable.
Time frame: Screening visit
Assess the type of training and competition pitch in the last 3 competition seasons
The secondary variable, type of training and competition pitch (sand pitch / artificial turf pitch / natural grass pitch), will be assessed as a nominal qualitative variable.
Time frame: Screening visit
Assess the type of muscle injury in the last 3 competition seasons
The secondary variable, type of muscle injury (fibrillar / musculotendinous / strain), will be assessed as an ordinal qualitative variable.
Time frame: Screening visit
Assess the weekly training load in the last 3 competition seasons
The secondary variable, weekly training load (hours/week), will be assessed as a quantitative variable.
Time frame: Screening visit
Assess the position on the field in the last 3 competition seasons
The secondary variable, position on the field (goalkeeper / defender / midfielder / striker), will be assessed as an ordinal qualitative variable.
Time frame: Screening visit
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