OBJECTIVE: To analyse risk factors leading to injuries during snowboarding. DESIGN: A case-control multicentre survey of injured and non-injured snowboarders. SETTING: One tertiary and two secondary trauma centres in Bern, Switzerland. METHODS: All snowboard injuries admitted to our tertiary and two affiliated secondary trauma centres from 1 November 2007 to 15 April 2008 were analysed on the basis of a completed questionnaire incorporating 15 variables. The same questionnaire was applied in non-injured controls at valley stations after a snowboarding day during the same period. A multiple logistic regression was performed (dichotomous variables). Patterns of combined risk factors were calculated by inference trees. RESULTS: 306 patients and 253 controls were interviewed. The following variables were statistically significant for the injured PATIENTS: low readiness for speed (OR 0.20, 95% CI 0.06 to 0.64, p=0.0037), bad weather/visibility (OR 19.06, 95% CI 2.70 to 134.73, p=0.0031) and old snow (OR 0.11, 95% CI 0.02 to 0.68, p=0.0323). Not wearing a helmet and riding on icy slopes emerged as a combination of risk factors associated with injury. CONCLUSIONS: Several risk factors and combinations exist, and different risk profiles were identified. Future research should be aimed at more precise identification of groups at risk and developing specific recommendations for each group-for example, a snow-weather conditions index at valley stations.
OBJECTIVE: To analyse risk factors leading to injuries during snowboarding. DESIGN: A case-control multicentre survey of injured and non-injured snowboarders. SETTING: One tertiary and two secondary trauma centres in Bern, Switzerland. METHODS: All snowboard injuries admitted to our tertiary and two affiliated secondary trauma centres from 1 November 2007 to 15 April 2008 were analysed on the basis of a completed questionnaire incorporating 15 variables. The same questionnaire was applied in non-injured controls at valley stations after a snowboarding day during the same period. A multiple logistic regression was performed (dichotomous variables). Patterns of combined risk factors were calculated by inference trees. RESULTS: 306 patients and 253 controls were interviewed. The following variables were statistically significant for the injured PATIENTS: low readiness for speed (OR 0.20, 95% CI 0.06 to 0.64, p=0.0037), bad weather/visibility (OR 19.06, 95% CI 2.70 to 134.73, p=0.0031) and old snow (OR 0.11, 95% CI 0.02 to 0.68, p=0.0323). Not wearing a helmet and riding on icy slopes emerged as a combination of risk factors associated with injury. CONCLUSIONS: Several risk factors and combinations exist, and different risk profiles were identified. Future research should be aimed at more precise identification of groups at risk and developing specific recommendations for each group-for example, a snow-weather conditions index at valley stations.
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