RÉSUMÉ
Although intrinsic and extrinsic risk factors for anterior cruciate ligament [ACL] injury have been investigated extensively, the neuromuscular and the biomechanical risk factors associated with this injury in female athletes are not yet well understood. This systematic review summarizes all the relevant biomechanical and neuromuscular risk factors associated with ACL injury. We used electronic databases of PubMed MEDLINE [1966- 2012], SCIENSEDIRECT [1982 - 2012] and Sport Discus [1985- 2012] for literature searching to identify the studies on ACL injury risk factors. We found a total of 152 articles. 52 of these studies had focused on neuromuscular and biomechanical risk factors. Investigation of the articles showed four neuromuscular imbalances: ligament dominance, quadriceps dominance, leg dominance, and trunk dominance. Existing evidence suggests that these four neuromuscular imbalances may be associated with the underlying ACL injury mechanisms. Also, review of the studies indicated that ACL injuries are more likely to occur during multi-planar rather than single-planar mechanisms of injury. Screening and detection of these imbalances are important in order to identify athletes at risk of ACL injury. Identification of faulty movement patterns would allow for implementation of specific interventions, targeted at prevention of these problems
Sujet(s)
Humains , Femelle , Facteurs de risque , Phénomènes biomécaniques , Muscles , AthlètesRÉSUMÉ
Grip strength [GS] is an important measure of general health to predict mortality, disability and function of the hand. The purpose of this study was to develop equations to predict grip strength based on several anthropometric measurements using a multiple regression analysis. Four hundred and eleven males and 671 females college students, ages 18-30 years, in good health, participated voluntarily in this study. This sample was randomly assigned to the model-development [n=867] and cross-validation [n=215] groups. Four equations were developed by using data from the model development group, then cross-validated on the second group. A hand-held dynamometer was used to measure grip strengths. All anthropometric measurements such as hand anthropometry, forearm circumference [FC], lean body mass, skeletal muscle mass and arm muscle area were taken according to standard techniques. It was found that grip strength has a significant correlation with all anthropometric measurements. Forearm length [FL] was correlated to grip [68% explained variance] in a linear relationship, followed by upper limb length and SM. All four equations were confirmed by cross-validation. Because of simplicity and easy-to-measure the following equations were selected for prediction grip: Dominant hand, A] 0.464xAge[yr]+0.392xHeight[cm]+0.681xBMI-13.035xSex[0 for men and 1 for women]-46.160, B] 0.029xFCxFL-8.634xsex+13.872; Non-dominant hand: C] 0.347xAge+0.386x Height+0.657xBMI-13.313xSex-44.243, D] 0.029xFCxFL-8.752xsex+13.788. The six easy-to-measure cofactors sex, age, height, BMI, forearm length and forearm circumference provide a highly accurate prediction of normative grip strength