Injury Occurrence in Amateur Rugby: Prospective Analysis of Specific Predictors over One Half-Season.

Background and objectives: The incidence of injuries in rugby is extremely high, but studies have rarely examined the predictors of injury in amateur players. This study aimed to systematically analyse sports and injury factors as potential predictors of musculoskeletal injuries in senior-level amateur rugby players. Methods: The participants in this study were 101 senior-level rugby players from Croatia (average of 24.64 years old). At baseline, all participants were tested on sociodemographic and anthropometric parameters (age, body height and mass), consumption of dietary supplements, preseason injury status and training volume, and sport factors (position in game). Data on injury occurrence (dependent variable), prevalence of pain, training status, and characteristics of the played match were surveyed prospectively once a week during the three-month period (one half-season). Results: The logistic regression revealed a higher injury occurrence in forward players of the 1st row, 2nd row (OR = 5.07; 95% CI: 1.64-15.69), and center (OR = 4.72; 95% CI: 1.28-14.31), with reference to outside back players. When observed univariately, higher body mass, higher level of competition, more weekly training sessions, self-perceived pain, and playing with pain were significant injury risk factors. The multivariate logistic regression identified pre-season injury (OR = 1.30, 95% CI: 1.09-1.52), higher level of the game/match (OR = 1.44, 95% CI: 1.13-1.76), higher body mass (OR = 1.03, 95% CI: 1.01-1.05), and pain prevalence (OR = 5.71, 95% CI: 3.22-7.70) as multivariate predictors of injury occurrence over the season. Conclusion: The results of this study showed that among sport factors, the playing position, level of competition, and training exposure represent major injury risk factors. Therefore, in order to reduce the number of injuries, special emphasis should be placed on the specific tackling technique of forward players, which could both increase their situational efficiency and protect them from injuries. Additionally, perceived pain, injury history, and playing with injury were noted among injury factors as the ones that can be predictors of future injuries. In that manner, it is important that coaching and medical staff monitor players with previous injuries and with pain symptoms in order to act preventively against injury occurrence.

(Low) Energy Availability and Its Association with Injury Occurrence in Competitive Dance: Cross-Sectional Analysis in Female Dancers.

Background and objectives: The risk of low energy availability is related to various health problems in sports. This cross-sectional study aimed to identify a possible association between various dance factors, anthropometrics/body build, and energy availability with injury occurrence in contemporary dancers. Materials and Methods: The participants were 50 female competitive dancers (19.8 ± 4.1 years of age). The independent variables included age, dance factors (amount of training and competitions per week-exposure time, experience in dance), anthropometrics/body composition (body height, mass, BMI, body fat percentage (BF%), and fat-free mass (FFM)), and energy availability score (EAS; evaluated by accelerometer-based measurement of energy expenditure and Dance Energy Availability Questionnaires). The dependent variables were the occurrence of (i) soft-tissue injuries and (ii) bone injuries. The measurements were obtained by experienced technicians during the pre-competition period for each specific dance discipline. Univariate and multivariate logistic regressions were calculated to identify the associations between independent variables and injury prevalence. Results: The results showed that EAS (OR = 0.81, 95% CI:0.65-0.91), age (OR = 1.65, 95% CI: 1.1-2.46), higher BF% (OR = 1.23, 95% CI: 1.04-1.46) and BMI (OR = 1.61, 95% CI: 1.05-2.47) were correlated with soft-tissue injuries. Dancers who suffered from bone injuries reported higher exposure time (OR = 1.21, 95% CI: 1.05-1.37) and had lower values of FFM (OR = 0.73, 95% CI: 0.56-0.98). Multivariate regression analyses evidenced a higher likelihood of soft-tissue injuries in older dancers (OR = 1.75, 95% CI: 1.21-2.95) and the ones who had lower EAS (OR = 0.84, 95% CI: 0.71-0.95) while the exposure time was associated with a higher likelihood of bone injuries (OR = 1.21, 95% CI: 1.05-1.39). Conclusions: In order to decrease the injury prevalence among dancers, special attention should be paid to maintaining adequate nutrition that will provide optimal available energy for the demands of training and performing. Additionally, the control of training volume should be considered in order to reduce traumatic bone injuries.

Change of Direction Speed and Reactive Agility in Prediction of Injury in Football; Prospective Analysis over One Half-Season.

Agility is an important factor in football (soccer), but studies have rarely examined the influences of different agility components on the likelihood of being injured in football. This study aimed to prospectively evaluate the possible influences of sporting factors, i.e., flexibility, reactive agility (RAG), and change of direction speed (CODS), on injury occurrence over one competitive half-season, in professional football players. Participants were 129 football professional players (all males, 24.4 ± 4.7 years), who underwent anthropometrics, flexibility, and RAG and CODS (both evaluated on non-dominant and dominant side) at the beginning of second half-season 2019/20 (predictors). Over the following half-season, occurrence of injury was registered (outcome). To identify the differences between groups based on injury occurrence, t-test was used. Univariate and multivariate logistic regressions were calculated to identify the associations between predictors and outcome. Results showed incidence of 1.3 injuries per 1000 h of training/game per player, with higher likelihood for injury occurrence during game than during training (Odds Ratio (OR) = 3.1, 95%CI: 1.63-5.88) Univariate logistic regression showed significant associations between players' age (OR = 1.65, 95%CI: 1.25-2.22), playing time (OR = 2.01, 95%CI: 1.560-2.58), and RAG (OR = 1.21, 95%CI: 1.09-1.35, and OR = 1.18, 95%CI: 1.04-1.33 for RAG on dominant- and non-dominant side, respectively), and injury occurrence. The multivariate logistic regression model identified higher risk for injury in those players with longer playing times (OR = 1.81, 95%CI: 1.55-2.11), and poorer results for RAG for the non-dominant side (OR = 1.15, 95%CI: 1.02-1.28). To target those players who are more at risk of injury, special attention should be paid to players who are more involved in games, and those who with poorer RAG. Development of RAG on the non-dominant side should be beneficial for reducing the risk of injury in this sport.