- Title
- Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers
- Creator
- Colby, Marcus; Dawson, Brian; Peeling, Peter; Heasman, Jarryd; Rogalski, Brent; Drew, Michael; Stares, Jordan; Zouhal, Hassane; Lester, Leanne
- Date
- 2017
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/165121
- Identifier
- vital:13207
- Identifier
-
https://doi.org/10.1016/j.jsams.2017.05.010
- Identifier
- ISBN:1440-2440
- 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.
- Publisher
- Elsever Ltd
- Relation
- Journal of Science and Medicine in Sport Vol. 20, no. 12 (2017), p. 1068-1074
- Rights
- Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 1106 Human Movement and Sports Science; 1116 Medical Physiology; 1117 Public Health and Health Services; Injury prevention; Team sports; Load monitoring; Acute:chronic workload ratio
- Full Text
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