Investigation of factors associated with successful completion of Fédération Équestre Internationale endurance rides and of risk factors for and prediction of post-race lameness and unacceptable performance in Thoroughbred flat racing at The Hong Kong Jockey Club

Abstract

Endurance riding and Thoroughbred flat racing are popular equestrian sports. Both involve exercise at speed over significant distances, which puts a substantial load on equine musculoskeletal systems and metabolism and contributes to the risk of injuries and other veterinary problems. The authorities for international-level endurance (Fédération Équestre Internationale) and Thoroughbred flat racing in Hong Kong (The Hong Kong Jockey Club) employ rules and measures to mitigate the risk of such events and safeguard horse health and welfare, including systems of pre-/in-ride and pre-race veterinary inspections aimed at early detection of at-risk horses and their elimination/withdrawal from the ride/race should they be deemed unfit to continue/partake in it. Despite implemented preventive measures, a proportion of starts made in both sports still result in deleterious outcomes. This motivates further work that contributes to the existing body of research, which is voluminous but includes many knowledge gaps. This thesis aimed to address three such gaps and, using frequentist and Bayesian generalized linear/additive multilevel models, identified multiple factors associated with the positive outcome of an international-level endurance ride – its successful completion and two adverse outcomes affecting racehorses in Hong Kong – ‘post-race lameness’ and ‘unacceptable performance’. The thesis also estimated the contribution of veterinary and training history-related data to the predictive ability and fit of the racehorse outcomes models, proposed a proof-of-concept for a pre-race risk prediction approach intended to aid in the identification of subpopulations of starts (horses) that might benefit from additional attention during the pre-race veterinary inspection or indeed exclusion from a race, and estimated the predictive ability of the racehorse outcomes models using new, previously unseen data. Knowledge of factors associated with the studied outcomes and being able to support the early detection of at-risk horses could help reduce the incidence of adverse outcomes and improve horse health and welfare.

Date of Award	18 Jun 2024
Original language	English
Awarding Institution	University of Bristol
Supervisor	Tim D H Parkin (Supervisor), Andrew Dowsey (Supervisor) & Euan Bennet (Supervisor)