Effectiveness of helmets in skiers and snowboarders: case-control and
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《英国医生杂志》
1 Alberta Centre for Injury Control and Research, Department of Public Health Sciences, Faculty of Medicine and Dentistry, University of Alberta, 4075 RTF, 8308-114 Street, Edmonton, AB, Canada T6G 2E1, 2 Departments of Pediatrics and Epidemiology and Biostatistics, 1020 Pine Avenue West, McGill University, Montreal, QC, Canada H3A 1A2, 3 Direction de la promotion de la sécurité, Ministère des Affaires municipales, du Sport et du Loisir, 100 rue Laviolette, suite 306, Québec Gouvernement, Trois-Rivières, QC, Canada G9A 5S9, 4 Institut national de santé publique du Québec, 4835, Christophe-Colomb, Montreal, QC, Canada H2J 3G8
Correspondence to: B E Hagel brent.hagel@ualberta.ca
Abstract
In 1983, Oh and Schmid argued that helmet use should be mandatory in skiers up to the age of 17 owing to the risk of severe head injuries.1 Guided by compelling evidence that helmets are effective at preventing head, brain, and facial injuries in bicyclists, helmet use would seem to be reasonable.2 Helmets are not yet widely recommended in skiers and snowboarders because of the paucity of information on their effectiveness. The best evidence suggests they are protective, but this was based on a study that was restricted to participants aged less than 13 years, had a small sample size, and lacked control for potential confounders.3 Helmets may increase the risk of spinal injury owing to the biomechanics of the association between the helmet and the head and neck4 5—a particular concern for children, who have a greater head to body ratio. A helmet may exert large bending or twisting forces on the neck in the event of an otherwise "routine" fall. We determined the effect of helmet use on the risk of head and neck injuries in skiers and snowboarders.
Methods
Of the 20 ski areas invited to participate in our study, one failed to return its accident report forms in time and was excluded from analysis. We sent out a questionnaire or scheduled a call to 1576 cases with head, face, or neck injuries and 4667 controls. The overall response rate was 70.1% (68.7% (1082 participants) for cases with head, face, and neck injuries and 70.6% (3295 participants) for controls), similar to snowboarders (71.9%, 2041 participants) and skiers (68.7%, 2335 participants), and age group (67.0%, 1582 participants to 73.0%, 1726 participants). Response rates varied between ski areas (55.1%, 27 participants to 84.7%, 133 participants).
Overall, 693 people had head injuries, with 69.7% (483) assessed as concussion. Of the 469 participants with isolated head injuries, 32.4% (152) were evacuated by ambulance; this proportion increased to 43.2% (107) when we considered only isolated head injuries assessed as concussion. In total, 44% (58) of the neck injuries were assessed as sprains, 16.0% (21) were assessed as fractures, and 6.9% (9) were assessed as muscle or nerve strains. Of the participants with isolated neck injuries, 56.1% (23) were evacuated by ambulance.
Table 1 lists the characteristics of the cases and controls at the time of injury. Cases with head injuries reported a collision or jump related injury more often than controls. Compared with controls, cases with neck injuries were more likely to be younger, to be female, to have participated for 11 or more days and for fewer hours before the injury, and to have had a previous head or neck injury.
Table 1 Characteristics of cases and controls and event around injury. Values are numbers (percentages)
The proportion of participants with head injuries or potentially severe head injuries who wore a helmet was similar to that of controls but was higher among those with neck injuries (table 2). The prevalence of helmet use decreased with increasing age for all groups. Cases aged less than 15 years with head injuries had a higher prevalence of helmet use than controls whereas cases aged less than 15 years with potentially severe head injuries had a lower prevalence of helmet use than controls. The proportion of helmet users among cases aged 15 to 25 with potentially severe neck injuries (37.5%; three participants) was greater than among controls (17.0%; 202 participants), although this result is based on only eight cases.
Table 2 Frequency of helmet use in cases with head and neck injuries and controls. Values are numbers (percentages)
All case-control sets among responders were well matched for ski area. Of the 1044 sets with one case and at least one control, 1026 (98.3%) were well matched for activity, and 428 (41%) were well matched for date of injury. Overall, 389 (37.3%) sets were well matched for age category and 329 (31.5%) were well matched for sex. We therefore considered age, sex, and environmental conditions for our conditional logistic regression model.
Table 3 shows the results of the conditional logistic regression analyses for the matched cases and controls. We found no evidence of effect modification by age either statistically (2 = 0.01) or practically (odds ratio for age groups: 26, 0.75; 15-25, 0.71; < 15, 0.73). The ideal model with the 27 covariates produced a helmet effect estimate of 0.73 (95% confidence interval 0.49 to 1.08).7 A backward deletion strategy produced a final adjusted helmet effect estimate of 0.71 (0.55 to 0.92). A forward selection strategy produced an adjusted helmet effect estimate for potentially severe head injuries of 0.44 (0.24 to 0.81).6 7
Table 3 Effect of helmet use
We found no evidence of effect modification by age for neck injuries when we fit a model with helmet use, age, sex, and two product terms for age by helmet use (< 15 and 15-25; 2 = 0.01). For those aged less than 15 years the estimate of the helmet effect was 0.92. After removal of the product terms from the model and using a forward selection strategy starting with helmet use, age and sex, our final model for any neck injury included age, sex, and days of participation that season. This gave a helmet effect of 0.62 (0.33 to 1.19).
We carried out no adjustments beyond matching due to the limited number (n = 13) of discordant sets for those sustaining neck injuries who were evacuated by ambulance. The conditional logistic regression estimate was 1.29 (0.41 to 4.04).
For the case crossover analysis we focused on 35 participants with head injuries who had discordant helmet use on the day of injury compared with their previous outing (estimated odds ratio for helmet use 0.6, 0.28 to 1.22). The odds ratio decreased to 0.43 (0.09 to 1.83) when we restricted the analysis to those injured during recreational participation.
Sensitivity analysis
After we included information on non-responders based on the accident report form and after adjusting for age, sex, and days of participation, we obtained a helmet effect estimate for any head injury of 0.73 (0.59 to 0.89).
The estimates for potentially severe head injuries (0.58, 0.36 to 0.94) and any neck injuries (0.94, 0.24 to 0.81) moved closer to the null after we included non-responders and after adjusting for age, sex, and days of participation. The helmet effect increased to 2.37 (0.89 to 6.32) when we added non-responders to the analysis of potentially severe neck injuries and after adjustment for age only (20 discordant sets).
When we omitted the three observations that produced the largest influence on the final estimated odds ratio (with their matched sets) for the outcome of any head injuries and refitted the model with the same variables, the estimate changed to 0.68 (0.52 to 0.88). The odds ratio changed to 0.34 for potentially severe head injuries, 0.43 for any neck injuries, and 1.66 for potentially severe neck injuries.
Discussion
Oh S, Schmid UD. Head injuries in childhood caused by skiing accidents and optimal prevention. Z Kinderchir 1983;38: 66-72.
Thompson DC, Rivara FP, Thompson R. Helmets for preventing head and facial injuries in bicyclists. Cochrane Injuries Group. Cochrane Database Syst Rev 2000;2: CD001855.
Macnab AJ, Smith T, Gagnon FA, Macnab M. Effect of helmet wear on the incidence of head/face and cervical spine injuries in young skiers and snowboarders. Inj Prev 2002;8: 324-7.
Deibert M, Aronsson D, Johnson R, Ettlinger C, Shealy J. Skiing injuries in children, adolescents, and adults. J Bone Joint Surg 1998;80-A: 25-32.
Katagi K. A heady debate. Ski Magazine 2000;Oct: 219-23.
Rothman K, Greenland S. Modern epidemiology. 2nd ed. Philadelphia, PA: Lippincott-Raven, 1998.
Kleinbaum DG. Logistic regression. New York: Springer-Verlag, 1996.
Harrell FE Jr. Tutorial in biostatistics. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15: 361-87.
Greenland S, Schwartzbaum JA, Finkle WD. Problems due to small samples and sparse data in conditional logistic regression analysis. Am J Epidemiol 2000;151: 531-9.
Parkinson GW, Hike KE. Bicycle helmet assessment during well visits reveals severe shortcomings in condition and fit. Pediatrics 2003;112: 320-3.
Davidson T, Laliotis A. Alpine skiing injuries: a nine-year study. West J Med 1996;164: 310-4.
Cadman R, Macnab AJ. Age and gender: two epidemiological factors in skiing and snowboarding injury. In: Mote CD Jr, Johnson RJ, Hauser W, Schaff PS, eds. Skiing trauma and safety, 10th Vol. ASTM STP 1266. Philadelphia, PA; American Society for Testing and Materials, 1996: 58-65.
Hagel BE, Meeuwisse WH, Mohtadi NGH, Fick GH. Skiing and snowboarding injuries in the children and adolescents of southern Alberta. Clin J Sport Med 1999;9: 9-17.
Hagel BE, Pless IB, Goulet C, Platt RW, Robitaille Y. Quality of information on risk factors reported by ski patrols. Inj Prev 2004;10: 275-9.
Harlow SD, Linet MS. Agreement between questionnaire data and medical records: the evidence for accuracy of recall. Am J Epidemiol 1989;129: 233-48.
Bridges EJ, Rouah F, Johnston KM. Snowblading injuries in eastern Canada. Br J Sports Med 2003;37: 511-5.(Brent E Hagel, assistant professor1, I B)
Correspondence to: B E Hagel brent.hagel@ualberta.ca
Abstract
In 1983, Oh and Schmid argued that helmet use should be mandatory in skiers up to the age of 17 owing to the risk of severe head injuries.1 Guided by compelling evidence that helmets are effective at preventing head, brain, and facial injuries in bicyclists, helmet use would seem to be reasonable.2 Helmets are not yet widely recommended in skiers and snowboarders because of the paucity of information on their effectiveness. The best evidence suggests they are protective, but this was based on a study that was restricted to participants aged less than 13 years, had a small sample size, and lacked control for potential confounders.3 Helmets may increase the risk of spinal injury owing to the biomechanics of the association between the helmet and the head and neck4 5—a particular concern for children, who have a greater head to body ratio. A helmet may exert large bending or twisting forces on the neck in the event of an otherwise "routine" fall. We determined the effect of helmet use on the risk of head and neck injuries in skiers and snowboarders.
Methods
Of the 20 ski areas invited to participate in our study, one failed to return its accident report forms in time and was excluded from analysis. We sent out a questionnaire or scheduled a call to 1576 cases with head, face, or neck injuries and 4667 controls. The overall response rate was 70.1% (68.7% (1082 participants) for cases with head, face, and neck injuries and 70.6% (3295 participants) for controls), similar to snowboarders (71.9%, 2041 participants) and skiers (68.7%, 2335 participants), and age group (67.0%, 1582 participants to 73.0%, 1726 participants). Response rates varied between ski areas (55.1%, 27 participants to 84.7%, 133 participants).
Overall, 693 people had head injuries, with 69.7% (483) assessed as concussion. Of the 469 participants with isolated head injuries, 32.4% (152) were evacuated by ambulance; this proportion increased to 43.2% (107) when we considered only isolated head injuries assessed as concussion. In total, 44% (58) of the neck injuries were assessed as sprains, 16.0% (21) were assessed as fractures, and 6.9% (9) were assessed as muscle or nerve strains. Of the participants with isolated neck injuries, 56.1% (23) were evacuated by ambulance.
Table 1 lists the characteristics of the cases and controls at the time of injury. Cases with head injuries reported a collision or jump related injury more often than controls. Compared with controls, cases with neck injuries were more likely to be younger, to be female, to have participated for 11 or more days and for fewer hours before the injury, and to have had a previous head or neck injury.
Table 1 Characteristics of cases and controls and event around injury. Values are numbers (percentages)
The proportion of participants with head injuries or potentially severe head injuries who wore a helmet was similar to that of controls but was higher among those with neck injuries (table 2). The prevalence of helmet use decreased with increasing age for all groups. Cases aged less than 15 years with head injuries had a higher prevalence of helmet use than controls whereas cases aged less than 15 years with potentially severe head injuries had a lower prevalence of helmet use than controls. The proportion of helmet users among cases aged 15 to 25 with potentially severe neck injuries (37.5%; three participants) was greater than among controls (17.0%; 202 participants), although this result is based on only eight cases.
Table 2 Frequency of helmet use in cases with head and neck injuries and controls. Values are numbers (percentages)
All case-control sets among responders were well matched for ski area. Of the 1044 sets with one case and at least one control, 1026 (98.3%) were well matched for activity, and 428 (41%) were well matched for date of injury. Overall, 389 (37.3%) sets were well matched for age category and 329 (31.5%) were well matched for sex. We therefore considered age, sex, and environmental conditions for our conditional logistic regression model.
Table 3 shows the results of the conditional logistic regression analyses for the matched cases and controls. We found no evidence of effect modification by age either statistically (2 = 0.01) or practically (odds ratio for age groups: 26, 0.75; 15-25, 0.71; < 15, 0.73). The ideal model with the 27 covariates produced a helmet effect estimate of 0.73 (95% confidence interval 0.49 to 1.08).7 A backward deletion strategy produced a final adjusted helmet effect estimate of 0.71 (0.55 to 0.92). A forward selection strategy produced an adjusted helmet effect estimate for potentially severe head injuries of 0.44 (0.24 to 0.81).6 7
Table 3 Effect of helmet use
We found no evidence of effect modification by age for neck injuries when we fit a model with helmet use, age, sex, and two product terms for age by helmet use (< 15 and 15-25; 2 = 0.01). For those aged less than 15 years the estimate of the helmet effect was 0.92. After removal of the product terms from the model and using a forward selection strategy starting with helmet use, age and sex, our final model for any neck injury included age, sex, and days of participation that season. This gave a helmet effect of 0.62 (0.33 to 1.19).
We carried out no adjustments beyond matching due to the limited number (n = 13) of discordant sets for those sustaining neck injuries who were evacuated by ambulance. The conditional logistic regression estimate was 1.29 (0.41 to 4.04).
For the case crossover analysis we focused on 35 participants with head injuries who had discordant helmet use on the day of injury compared with their previous outing (estimated odds ratio for helmet use 0.6, 0.28 to 1.22). The odds ratio decreased to 0.43 (0.09 to 1.83) when we restricted the analysis to those injured during recreational participation.
Sensitivity analysis
After we included information on non-responders based on the accident report form and after adjusting for age, sex, and days of participation, we obtained a helmet effect estimate for any head injury of 0.73 (0.59 to 0.89).
The estimates for potentially severe head injuries (0.58, 0.36 to 0.94) and any neck injuries (0.94, 0.24 to 0.81) moved closer to the null after we included non-responders and after adjusting for age, sex, and days of participation. The helmet effect increased to 2.37 (0.89 to 6.32) when we added non-responders to the analysis of potentially severe neck injuries and after adjustment for age only (20 discordant sets).
When we omitted the three observations that produced the largest influence on the final estimated odds ratio (with their matched sets) for the outcome of any head injuries and refitted the model with the same variables, the estimate changed to 0.68 (0.52 to 0.88). The odds ratio changed to 0.34 for potentially severe head injuries, 0.43 for any neck injuries, and 1.66 for potentially severe neck injuries.
Discussion
Oh S, Schmid UD. Head injuries in childhood caused by skiing accidents and optimal prevention. Z Kinderchir 1983;38: 66-72.
Thompson DC, Rivara FP, Thompson R. Helmets for preventing head and facial injuries in bicyclists. Cochrane Injuries Group. Cochrane Database Syst Rev 2000;2: CD001855.
Macnab AJ, Smith T, Gagnon FA, Macnab M. Effect of helmet wear on the incidence of head/face and cervical spine injuries in young skiers and snowboarders. Inj Prev 2002;8: 324-7.
Deibert M, Aronsson D, Johnson R, Ettlinger C, Shealy J. Skiing injuries in children, adolescents, and adults. J Bone Joint Surg 1998;80-A: 25-32.
Katagi K. A heady debate. Ski Magazine 2000;Oct: 219-23.
Rothman K, Greenland S. Modern epidemiology. 2nd ed. Philadelphia, PA: Lippincott-Raven, 1998.
Kleinbaum DG. Logistic regression. New York: Springer-Verlag, 1996.
Harrell FE Jr. Tutorial in biostatistics. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15: 361-87.
Greenland S, Schwartzbaum JA, Finkle WD. Problems due to small samples and sparse data in conditional logistic regression analysis. Am J Epidemiol 2000;151: 531-9.
Parkinson GW, Hike KE. Bicycle helmet assessment during well visits reveals severe shortcomings in condition and fit. Pediatrics 2003;112: 320-3.
Davidson T, Laliotis A. Alpine skiing injuries: a nine-year study. West J Med 1996;164: 310-4.
Cadman R, Macnab AJ. Age and gender: two epidemiological factors in skiing and snowboarding injury. In: Mote CD Jr, Johnson RJ, Hauser W, Schaff PS, eds. Skiing trauma and safety, 10th Vol. ASTM STP 1266. Philadelphia, PA; American Society for Testing and Materials, 1996: 58-65.
Hagel BE, Meeuwisse WH, Mohtadi NGH, Fick GH. Skiing and snowboarding injuries in the children and adolescents of southern Alberta. Clin J Sport Med 1999;9: 9-17.
Hagel BE, Pless IB, Goulet C, Platt RW, Robitaille Y. Quality of information on risk factors reported by ski patrols. Inj Prev 2004;10: 275-9.
Harlow SD, Linet MS. Agreement between questionnaire data and medical records: the evidence for accuracy of recall. Am J Epidemiol 1989;129: 233-48.
Bridges EJ, Rouah F, Johnston KM. Snowblading injuries in eastern Canada. Br J Sports Med 2003;37: 511-5.(Brent E Hagel, assistant professor1, I B)