Marcus J Colby1, Brian Dawson2, Peter Peeling3, Jarryd Heasman4, Brent Rogalski4, Michael K Drew5, Jordan Stares2, Hassane Zouhal6, Leanne Lester7. 1. School of Sport Science, Exercise and Health, The University of Western Australia, Australia; West Coast Eagles Football Club, Australia. Electronic address: marcus_colby@hotmail.com. 2. School of Sport Science, Exercise and Health, The University of Western Australia, Australia; West Coast Eagles Football Club, Australia. 3. School of Sport Science, Exercise and Health, The University of Western Australia, Australia; Western Australian Institute of Sport, Australia. 4. West Coast Eagles Football Club, Australia. 5. Australian Institute of Sport, Australia; Australian Centre for Research into Injury in Sport and its Prevention (ACRISP), Federation University Australia, Australia. 6. Movement, Sport and Health Sciences laboratory (M2S), UFR-APS, University of Rennes 2 - ENS Rennes, France. 7. School of Sport Science, Exercise and Health, The University of Western Australia, Australia.
Abstract
OBJECTIVES: To assess the association between workload, subjective wellness, musculoskeletal screening measures and non-contact injury risk in elite Australian footballers. DESIGN: Prospective cohort study. METHODS: Across 4 seasons in 70 players from one club, cumulative weekly workloads (acute; 1 week, chronic; 2-, 3-, 4-week) and acute:chronic workload ratio's (ACWR: 1-week load/average 4-weekly load) for session-Rating of Perceived Exertion (sRPE) and GPS-derived distance and sprint distance were calculated. Wellness, screening and non-contact injury data were also documented. Univariate and multivariate regression models determined injury incidence rate ratios (IRR) while accounting for interaction/moderating effects. Receiver operating characteristics determined model predictive accuracy (area under curve: AUC). RESULTS: Very low cumulative chronic (2-, 3-, 4- week) workloads were associated with the greatest injury risk (univariate IRR=1.71-2.16, 95% CI=1.10-4.52) in the subsequent week. In multivariate analysis, the interaction between a low chronic load and a very high distance (adj-IRR=2.60, 95% CI=1.07-6.34) or low sRPE ACWR (adj-IRR=2.52, 95% CI=1.01-6.29) was associated with increased injury risk. Subjectively reporting "yes" (vs. "no") for old lower limb pain and heavy non-football activity in the previous 7 days (multivariate adj-IRR=2.01-2.25, 95% CI=1.02-4.95) and playing experience (>9 years) (multivariate adj-IRR=2.05, 95% CI=1.03-4.06) was also associated with increased injury risk, but screening data were not. Predictive capacity of multivariate models was significantly better than univariate (AUCmultivariate=0.70, 95% CI 0.64-0.75; AUCunivariate range=0.51-0.60). CONCLUSIONS: Chronic load is an important moderating factor in the workload-injury relationship. Low chronic loads coupled with low or very high ACWR are associated with increased injury risk.
OBJECTIVES: To assess the association between workload, subjective wellness, musculoskeletal screening measures and non-contact injury risk in elite Australian footballers. DESIGN: Prospective cohort study. METHODS: Across 4 seasons in 70 players from one club, cumulative weekly workloads (acute; 1 week, chronic; 2-, 3-, 4-week) and acute:chronic workload ratio's (ACWR: 1-week load/average 4-weekly load) for session-Rating of Perceived Exertion (sRPE) and GPS-derived distance and sprint distance were calculated. Wellness, screening and non-contact injury data were also documented. Univariate and multivariate regression models determined injury incidence rate ratios (IRR) while accounting for interaction/moderating effects. Receiver operating characteristics determined model predictive accuracy (area under curve: AUC). RESULTS: Very low cumulative chronic (2-, 3-, 4- week) workloads were associated with the greatest injury risk (univariate IRR=1.71-2.16, 95% CI=1.10-4.52) in the subsequent week. In multivariate analysis, the interaction between a low chronic load and a very high distance (adj-IRR=2.60, 95% CI=1.07-6.34) or low sRPE ACWR (adj-IRR=2.52, 95% CI=1.01-6.29) was associated with increased injury risk. Subjectively reporting "yes" (vs. "no") for old lower limb pain and heavy non-football activity in the previous 7 days (multivariate adj-IRR=2.01-2.25, 95% CI=1.02-4.95) and playing experience (>9 years) (multivariate adj-IRR=2.05, 95% CI=1.03-4.06) was also associated with increased injury risk, but screening data were not. Predictive capacity of multivariate models was significantly better than univariate (AUCmultivariate=0.70, 95% CI 0.64-0.75; AUCunivariate range=0.51-0.60). CONCLUSIONS: Chronic load is an important moderating factor in the workload-injury relationship. Low chronic loads coupled with low or very high ACWR are associated with increased injury risk.
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