Trail running injury risk factors: a living systematic review

ObjectiveTo review and frequently update the available evidence on injury risk factors and epidemiology of injury in trail running.DesignLiving systematic review. Updated searches will be done every 6 months for a minimum period of 5 years.Data sourcesEight electronic databases were searched from inception to 18 March 2021.Eligibility criteriaStudies that investigated injury risk factors and/or reported the epidemiology of injury in trail running.ResultsNineteen eligible studies were included, of which 10 studies investigated injury risk factors among 2 785 participants. Significant intrinsic factors associated with injury are: more running experience, level A runner and higher total propensity to sports accident questionnaire (PAD-22) score. Previous history of cramping and postrace biomarkers of muscle damage is associated with cramping. Younger age and low skin phototypes are associated with sunburn. Significant extrinsic factors associated with injury are neglecting warm-up, no specialised running plan, training on asphalt, double training sessions per day and physical labour occupations. A slower race finishing time is associated with cramping, while more than 3 hours of training per day, shade as the primary mode of sun protection and being single are associated with sunburn. An injury incidence range 0.7–61.2 injuries/1000 hours of running and prevalence range 1.3% to 90% were reported. The lower limb was the most reported region of injury, specifically involving blisters of the foot/toe.ConclusionLimited studies investigated injury risk factors in trail running. Our review found eight intrinsic and nine extrinsic injury risk factors. This review highlighted areas for future research that may aid in designing injury risk management strategies for safer trail running participation.PROSPERO registration numberCRD42021240832.

Sex-based Differences in Hamstring Injury Risk Factors

Hamstring injuries (HSI) are common in a number of different sports and can confer a significant burden to both male and female athletes. Though research on HSIs in the female athlete population is lacking, current literature suggests male athletes are between two to four times more likely than female athletes to sustain an HSI. Despite this discrepancy, the role of intrinsic sex differences in HSI risk factors has not been previously explored. This review aims to summarize these sex-based differences in HSI risk factors and their influence on the lower rate of HSIs seen in female athletes as compared to male athletes. Women exhibit increased hamstring flexibility and decreased hamstring musculotendinous stiffness as compared to men; women are also shown to be more resistant to skeletal muscle fatigue. Sex differences in the hamstring to quadriceps ratio and certain lower limb morphologies may also contribute to the sex discrepancy in HSI rates. This remains an area for future research in order to understand the multifaceted nature of HSI injury risk factors and optimize HSI rehabilitation and prevention programs for both male and female athletes.

Detecting Injury Risk Factors with Algorithmic Models in Elite Women’s Pathway Cricket

This exploratory retrospective cohort analysis aimed to explore how algorithmic models may be able to identify important risk factors that may otherwise not have been apparent. Their association with injury was then assessed with more conventional data models. Participants were players registered on the England and Wales Cricket Board women’s international development pathway (n=17) from April 2018 to August 2019 aged between 14–23 years (mean 18.2±1.9) at the start of the study period. Two supervised learning techniques (a decision tree and random forest with traditional and conditional algorithms) and generalised linear mixed effect models explored associations between risk factors and injury. The supervised learning models did not predict injury (decision tree and random forest area under the curve [AUC] of 0.66 and 0.72 for conditional algorithms) but did identify important risk factors. The best-fitting generalised linear mixed effect model for predicting injury (Akaike Information Criteria [AIC]=843.94, conditional r-squared=0.58) contained smoothed differential 7-day load (P<0.001), average broad jump scores (P<0.001) and 20 m speed (P<0.001). Algorithmic models identified novel injury risk factors in this population, which can guide practice and future confirmatory studies can now investigate.

Perceptions of experts on key injury risk factors in alpine ski racing as a function of stakeholder role and associated level of competition

Objectives(1) To update experts’ priorities of perceived key injury risk factors in alpine ski racing based on a framework and list derived 10 years ago, (2) to identify additionally emerging risk factors since then and (3) to compile a list with countermeasure suggestions.MethodsA sample of 532 expert stakeholders (athletes, coaches, team medical staff, Ski Racing Suppliers (SRS) and International Ski Federation (FIS) representatives) from the World Cup (WC), European Cup (EC) and FIS-race level participated in a cross-sectional online survey. Experts were asked to name those risk factors with the highest believed impact on injury risk and rank them according to their current priority from a predefined list. In addition, experts were encouraged to name additional (not listed) risk factors and to suggest countermeasures.ResultsRegardless of stakeholder role and competition level, snow-related factors appeared to have the highest perceived priority. However, WC athletes’ and coaches’ perceptions were also related to equipment, while at the EC and FIS-race level fatigue and physical fitness-related factors were considered important. Athletes’ perceptions were largely in agreement with SRS (ie, snow-related and equipment-related factors). At the same time, while coaches, team medical staff and FIS representatives additionally emphasised fatigue and physical fitness-related factors.ConclusionExperts’ perceptions on key injury risk factors in alpine ski racing depend on the stakeholder role and differ between the competition levels. Thus, to develop effective prevention measures and to successfully implement them, all relevant stakeholders should be given a voice, and prevention efforts should be targeted to the specific level.