This release is available in Spanish.
Spanish researchers have developed a new mathematical model that permits to predict sport injuries from a series of equations. Their work has proved that sport injuries that affect the lower limbs in high-impact sport, such as football, athletics or basketball, can be predicted through the use of equations of logistic regression.
This paper has been published in the journal Apunts. Medicina de L'esport and has had the participation of Antonio Fernández Martínez (University Pablo de Olavide), Juan Carlos de la Cruz Márquez, Belén Cueto Martín and Juan Carlos de la Cruz Campos (University of Granada, Spain) and Santiago Salazar Alonso (Institute Vicente Espinel of Malaga).
According to the researchers, the identification of the factors that provoke injuries could allow the trainers and sportsmen to modify training programs and prevent future damages. Although traditionally the research works of sports medicine have been greatly focused on the diagnosis and therapeutic aspects of sports injuries, their appropriate prevention, a fast diagnosis and the most suitable treatment may facilitate the sports career of sportsmen –according to the researchers- and help them to achieve their personal and professional goals in accordance with their real potential".
Factors that provoke injuries
The researchers point out that there are three general factors that play a primary role in the risk of suffering an injury: incorrect training techniques, unsuitable or damaged equipments and biomechanical and anthropometrical abnormalities. This last group of factors have been the starting point for their work, where they tried to find out the potential injury risk of a sportsman from certain anthropometric parameters in lower limbs.
The incidence of injuries in young sportsmen is quite high, according to the authors of this paper. Given that 998 out of every one thousand young persons who play basketball suffer an injury at any moment, this sport if the one in which more incidences are suffered, followed by handball, with 814 injured persons for every on thousand sportsmen, and volleyball, with 548. The paper reflects that 39% of the Spanish people play any sport, whereas only 6% of them do it daily. Half of such 6% will suffer any kind of slight injury all through their lives.
A recent research line
The studies about sports injuries are a relatively recent phenomenon. The first injury predictor rate was described by Shambaugh in 1991, using and dependant variables the weight imbalance in bipodal support and the deviation of quadriceps Q-angle.
The Spanish scientists, who have worked on the basis of his work and the findings of another author called Grubbs, have applied the rate of Shambaugh in basketball players with regard to the practical presentation, including individuals of both sexes. From these research works, the authors have analysed the different predictor variables in a different sports population, considering race and jump athletes of both sexes with ages between 14 and 18 years old. Their objective was to find a valid tool to predict the risk of injury in the above-mentioned population, obtaining a mathematical algorithm so-called 'Fernandez's Injury Rate', according to the following formula:
1/1 + e–(0,757 _ AQI – 0,647 _ DGM2)
where AQI is the Q-angle of the left lower limb inferior, and DGM2, the square of the difference between the thickness of both thighs.
These research works prove that the analysis by logistic regression can be a valid method in the discrimination of anthropometric parameters related to sports injuries. Nevertheless, the authors of this work warn that it is necessary to keep on doing research into this subject to consolidate the idea of that the analysis of the sportsman's corporal structure can be a good tool in the prognostic of future injuries, and could be helpful to improve both his sports achievements and his health.
Reference: Juan Carlos de la Cruz Márquez. Department of Physical Education of the University of Granada. Phone number: +34 958 244 378. E-mail: dlcruz@ugr.es
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