Relationship between training load and law enforcement recruit injuries during academy training

Daniel Maupin, Elisa Fontenelle Dumans Canetti, Evelyne Rathbone, Ben Schram, J. Jay Dawes, Robert Lockie, Rob Marc Orr

Research output: Contribution to journalMeeting AbstractResearchpeer-review


Introduction: Law enforcement is a profession interspersed with periods of high intensity, physically demanding occupational requirements such as chasing suspects. To prepare for this occupation, law enforcement agencies typically utilise training periods known as academies. These academies represent a sudden increase in physical training load, and mental stress. It is therefore unsurprising that these periods of training typically result in high rates of injury. The aim of this research was to assess the relationship between training load factors and injury risk in law enforcement recruits.Methods: A retrospective desktop analysis was conducted to profile training load across seven law enforcement academy classes. Estimates were based on a cohort, rather than an individual level and there for represent an overall workload instead of individualized. This method was validated with acceptable levels of agreement, through the use of a Bland-Altman Plot, compared to Polar Team Pro Sensors. A generalized linear mixed model with maximum likelihood estimation, based on an adaptive Gauss-Hermite approximation, was utilized to explore the relationship between included variables and the binomial outcome, injury. The variables assessed were distance covered, weekly change in distance, cumulative distance, hours spent in various forms of physical training (e.g., aerobic and anaerobic), physical fitness assessment scores, and occupational task assessment scores. A stepwise approach was utilised to choose the best fitting model whereby each variable was modelled individually. The best fitting model, as measured by Akaike and Bayesian information criterion, was carried forward. This was repeated until the addition of new variables did not significantly improve, with the aforementioned information criterion, model fit.Results: Data was collected from 547 participants (431 male, 116 female). There were 76 injuries (53 male, 23 female) that occurred during this time-period. Recruits covered approximately 15 to 23 km in a week, with large weekly increases (~ 10 km) occurring early in the academy. The best fitting model utilised weekly distance, week of training, and sex (χ2= 38.26, p-value < 0.001). The model results suggest that for every 80 m covered, the odds of sustaining an injury are increased by a factor of 1.08 (OR: 1.08, 95%CI 1.04 – 1.12). As the academy progresses, injury risk decreases across subsequent weeks (OR = 0.94, 95%CI 0.91 – 0.98), while males were less likely to sustain an injury (OR = 0.55, 95% CI 0.34 – 0.91).Discussion: The aim of this research was to assess the relationship between training load variables and injury risk in a law enforcement recruit population. Distance covered, week of training, and sex significantly increased the risk of injury. Recruits in this population typically engage in a ‘one size fits no-one’ training program that is centred around body weight exercises and long-distance running. Adjusting this program to an ability-based style of training, where workload is adjusted based on fitness, may be able to decrease injury risk in this population. Further, including more physical training around muscular strength and power could improve fitness components that are vital to law enforcement while decreasing the distance run and potentially mitigating injury risk.Conflict of interest: My co-authors and I acknowledge that we have no conflict of interest of relevance to the submission of this abstract
Original languageEnglish
Article numberO100058
Pages (from-to)S45
JournalJournal of Science and Medicine in Sport
Issue numberSupplement 2
Publication statusPublished - 16 Nov 2022
Event2022 SMA Conference - RACV Royal Pines Resort, Gold Coast, Australia
Duration: 16 Nov 202219 Dec 2022


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