title: Risk factors and sources of variation in horse falls in steeplechase racing in the UK.
abstract: We identified risk factors associated with falling during steeplechase racing. We used retrospective data from all steeplechase runs on UK racecourses during 1999: 10,866 starts with 647 horse falls. The relationship between continuous variables and falling was assessed using generalised additive models (GAMs). Polynomial fits then were included in a multilevel, multivariable logistic-regression model. The number of runners had a linear, positive association with the risk of falling. The distance of the race had a non-linear relationship with the risk of falling; the risk steadily increased in races up to 23 furlongs (1furlong approximately equals 198 m), and then decreased in longer races. Age also had a significant, non-linear relationship with the risk of falling: a decreasing risk up to 12 years of age followed by an increasing risk in older horses. Horses that wore visors and had raced previously were associated with a decrease in the risk of falling. Intra-class correlation coefficients (ICCs) showed that although most of the variation resided at the start (level 1), a proportion of variation in the risk of falling could be attributed to horse and race. Trainer and jockey contributed very little to the variation in the risk of falling.
authors.affiliation: Epidemiology Group, Department of Veterinary Clinical Science and Animal Husbandry, University of Liverpool, Chester High Road, Leahurst, Neston CH64 7TE, South Wirral, UK. ginap@liv.ac.uk
authors.forename: G L
authors.initials: GL
authors.lastname: Pinchbeck
authors.forename: P D
authors.initials: PD
authors.lastname: Clegg
authors.forename: C J
authors.initials: CJ
authors.lastname: Proudman
authors.forename: K L
authors.initials: KL
authors.lastname: Morgan
authors.forename: J L N
authors.initials: JL
authors.lastname: Wood
authors.forename: N P
authors.initials: NP
authors.lastname: French
mesh_terms: D000058:Accidental Falls / Q000706:statistics & numerical data*; D000367:Age Factors; D000818:Animals; D005260:Female; D006736:Horses / Q000502:physiology*; D016015:Logistic Models; D008297:Male; D016017:Odds Ratio; D012307:Risk Factors; D013177:Sports; D006113:United Kingdom; D016474:Weight-Bearing