ABSTRACT
BACKGROUND: Equestrian eventing involves competing in three phases: dressage, jumping, and cross-country. Competitors are ranked by number of penalties accrued-with those who have fewer penalties ranked higher. Completing the cross-country phase with zero obstacle penalties is commonly referred to as 'running clear'. Understanding factors associated with running clear can help athletes plan strategically for success, while also helping governing bodies to refine qualification criteria for elite levels. OBJECTIVES: This study was carried out to identify factors associated with running clear in the cross-country phase of Fédération Equestre Internationale (FEI) eventing. STUDY DESIGN: Retrospective cohort study of 107 348 horse starts worldwide in all FEI competitions between January 2008 and December 2018. METHODS: Multivariable logistic regression models constructed stepwise using a bi-directional process. Two study cohorts were assessed: a complete cohort that met all inclusion requirements and separately, a cohort that included only horses starting at the level above their previous start. RESULTS: Sixteen factors were associated with running clear. Factors associated with increased likelihood of doing so included lower event level, lower dressage score earlier in the event, fewer recent FEI event starts, and more clear runs in their previous three FEI events. For horses that had stepped up an event level, 14 of these factors were still associated with running clear. MAIN LIMITATIONS: Data available covered only FEI events, no national federation competitions were available for inclusion in horse histories. No prior veterinary information or data on training were available. CONCLUSIONS: This study provides a framework that allows stakeholders to potentially better understand the appropriate level of competition for any particular horse/rider combination, given the combination's recent history. This could provide an additional direct benefit in terms of safety by reducing the likelihood of a combination falling during cross-country.
ABSTRACT
BACKGROUND: The equestrian discipline of eventing tests athletes' and horses' skill over three phases: dressage, jumping and cross-country. Falls during cross-country can be particularly serious and result in serious or fatal injury for both horse and athlete. Cross-country course and fence design are crucial contributory factors to safety. OBJECTIVES: To provide descriptive statistics and identify fence-level risk factors for horses competing in Fédération Equestre Internationale (FEI) events worldwide. STUDY DESIGN: Retrospective cohort study. METHODS: Data were collected for every horse start worldwide in all international (CI), championship (CH), Olympics (OG) and World Equestrian Games (WEG) eventing competitions between January 2008 and December 2018 and univariable logistic regression, followed by multivariable logistic regression were applied. The final model was built in a stepwise bi-directional process, with each step assessed by the Akaike information criterion. RESULTS: Risk factors were identified at the fence level covering aspects of fence design and course design. Ten fence types were at increased odds of a fall occurring compared with square spread fences, and seven types were at reduced odds. Fences with an approach downhill (odds ratio [OR] 1.35, 95% confidence interval [CI] 1.19-1.52), with landing into water (OR 1.82, CI 1.62-2.01), frangible devices (OR 1.28, CI 1.15-1.41) and later elements of combined obstacles (OR 1.33 CI 1.25-1.42 for the second element, OR 1.21 CI 1.10-1.32 for later elements) were associated with increased risk of falls occurring. MAIN LIMITATIONS: Although the dataset covers every international competition worldwide, it does not include national-level competitions. CONCLUSIONS: It is recommended that the most challenging fences are placed near the beginning of the course, and not in downhill or water settings. The complexity of individual elements in combined fences should be reduced. Adopting evidence-based course design is a crucial intervention for reducing the incidence of horse falls and associated serious and fatal injuries to horse and human athletes.
Subject(s)
Accidental Falls , Sports , Humans , Horses , Animals , Retrospective Studies , Risk Factors , Logistic ModelsABSTRACT
BACKGROUND: Eventing is an equestrian sport that tests athletes' and horses' skill over three phases: dressage, jumping and cross-country. Falls during the cross-country phase can have very serious outcomes up to and including death for both horse and athlete. Therefore, understanding risk factors associated with falls is essential for improving equine and human welfare. OBJECTIVES: To provide descriptive statistics and identify risk factors at the horse-, athlete- and course-level affecting horses competing in Fédération Equestre Internationale (FEI) events worldwide. STUDY DESIGN: Retrospective cohort study. METHODS: Data collected by the FEI of every horse start worldwide in all international (CI), championship (CH), Olympics (OG) and World Equestrian Games (WEG) competitions between January 2008 and December 2018 were analysed. Descriptive statistics followed by univariable logistic regression to identify risk factor candidates for inclusion in the final multivariable logistic regression model. Models were constructed stepwise using a bi-directional process and assessed using the Akaike information criterion. RESULTS: Factors associated with increased risk of falls and or unseated rider included: higher event levels, longer course distances, more starters at cross-country phase and less experienced horses and athletes. MAIN LIMITATIONS: The data set is geographically comprehensive but covers only FEI competitions, not National Federation events, that is not every competition started by every individual horse. Nor does the data set include any prior veterinary information or data on training or schooling. CONCLUSIONS: This is the first large-scale epidemiological study of cross-country falls in FEI eventing. Results suggest that a potential risk profile can be constructed for each horse-athlete combination prior to entering a given competition, based on individual histories and course-level factors. This could lead to interventions that can reduce the number of falls, thus protecting equine and human welfare.