Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Turf track surface interaction with speed and musculoskeletal injury risk in Thoroughbred racehorses(John Wiley and Sons Ltd on behalf of EVJ Ltd, 2025-07-24) Legg KA; Gibson MJ; Gee EK; Rogers CWBackground: Injury modelling based on changes in speed and stride characteristics of racehorses has become a primary industry focus for the Thoroughbred racing industry. However, speed and stride characteristics are strongly associated with track condition; therefore, reliable quantification of surface variables for use in future models is imperative. Objectives: This study aimed to understand the interaction of objective turf track condition score (TCS) measurement with racing speed and injury in flat racing Thoroughbred horses. Study Design: Retrospective time series analysis. Methods: Race-day data from 16 flat racing seasons (2008/9–2023/24, n = 40,824 races) were used to compare monthly TCS (based on penetrometer measurements), the coefficient of variability (CV) for TCS, race speed (over the final 600 m) and the number of race starts. Injury data from 7 seasons (2015–17, 2019–24) were used to calculate the monthly incidence rate (IR per 1000 race starts) of musculoskeletal injury (MSI). A mixed effects linear model was used to assess the relationship between speed, TCS, race distance and horse rating. Results: Race starts (n = 437,506), TCS and speed showed strong seasonal fluctuations, with more starts, lower and more variable TCS (4, IQR 3–5, CV = 0.44) and higher race speed (16.7 m/s, IQR 16.1–17.2) in summer compared with winter (TCS 10, IQR 8–10, CV = 0.22, p < 0.001 and speed 15.1 m/s, IQR 14.3–15.8, p < 0.001). Race speed had a strong negative quadratic relationship with TCS (β₂ = −0.03, p < 0.001), a negative linear correlation with race distance and was positively correlated with horse rating. There were 433 MSI (IR = 2.22, 95% CI 2.20–2.44), with an immediate (0 lag time) positive association with seasonal changes in TCS (r = −0.28). Main Limitations: Low monthly numbers of MSI constrained analysis of interaction with track variables. Conclusions: TCS provides a reliable quantitative measure of track condition which could be used to refine future models of injury risk in racing Thoroughbreds.Item A Bioeconomic Model for the Thoroughbred Racing Industry-Optimisation of the Production Cycle with a Horse Centric Welfare Perspective(MDPI (Basel, Switzerland), 2023-01-30) Legg KA; Gee EK; Breheny M; Gibson MJ; Rogers CWThe Thoroughbred racing industry faces new and competing pressures to operate within a modern, changing society. Three major moderators drive the focus and productivity of the industry worldwide: economic sustainability, horse biology and social licence to operate. This review proposes that despite the apparent homogeneity in the structure of racing across jurisdictions due to international regulation of the sport, there are significant differences within each jurisdiction in each of the three moderators. This creates challenges for the comparison of injury risk factors for racehorses within the industry across different jurisdictions. Comparison of the relative distribution of racing and gambling metrics internationally indicates that the Asian jurisdictions have a high focus on gambling efficiency and high economic return of the product, with a high number of starts per horse and the highest relative betting turnover. In contrast, the racing metrics from the USA have proportionally low racing stakes and fewer horses per race. These differences provide insight into the sociology of horse ownership, with a shift from the long-term return on investment held by most jurisdictions to a short-term transitional view and immediate return on investment in others. Wastage studies identify varying risks influenced by the predominant racing culture, training methods, production focus and environment within individual jurisdictions. Increasing societal pressure to maintain high racehorse welfare and reduce the negative impact of gambling poses fluctuating risks to each jurisdiction's social licence to operate. Based on the data presented within this review, the authors propose that the use of a bioeconomic model would permit consideration of all three moderators on industry practice and optimisation of the jurisdiction-specific production cycle with a horse-centric welfare perspective.Item Preliminary Examination of the Biological and Industry Constraints on the Structure and Pattern of Thoroughbred Racing in New Zealand over Thirteen Seasons: 2005/06-2017/18(MDPI (Basel, Switzerland), 2021-10) Legg KA; Gee EK; Cochrane DJ; Rogers CW; Peterson MThis study aimed to examine thirteen seasons of flat racing starts (n = 388,964) in the context of an ecological system and identify metrics that describe the inherent characteristics and constraints of the New Zealand Thoroughbred racing industry. During the thirteen years examined, there was a 2-3% per year reduction in the number of races, starts and number of horses. There was a significant shift in the racing population with a greater number of fillies (aged 2-4 years) having a race start, and subsequent longer racing careers due to the inclusion of one more racing preparation post 2008 (p < 0.05). Additionally, there was an increasingly ageing population of racehorses. These changes resulted in more race starts in a career, but possibly because of biological constraints, there was no change in the number of race starts per season, starts per preparation, or days spelling between preparations (p < 0.05). There was no change in the proportion of horses having just one race start (14% of new entrants), indicating that the screening for suitability for a racing career remained consistent. These data identify key industry parameters which provide a basis for future modelling of intervention strategies to improve economic performance and reduce horse injury. Consideration of the racing industry as a bio-economic or ecological model provides framework to test how the industry may respond to intervention strategies and signal where changes in system dynamics may alter existing risk factors for injury.