BackgroundThe effectiveness of helmets in reducing the risk of severe head injury in motorcyclists who were involved in a crash is well established. There is limited evidence however, regarding the extent to which helmets protect riders from facial injuries. The objective of this study was to determine the effect of helmet type, components and fixation status on the risk of facial injuries among Malaysian motorcyclists.Method755 injured motorcyclists were recruited over a 12-month period in 2010–2011 in southern Klang Valley, Malaysia in this case control study. Of the 755 injured motorcyclists, 391participants (51.8%) sustained facial injuries (cases) while 364 (48.2%) participants were without facial injury (control). The outcomes of interest were facial injury and location of facial injury (i.e. upper, middle and lower face injuries). A binary logistic regression was conducted to examine the association between helmet characteristics and the outcomes, taking into account potential confounders such as age, riding position, alcohol and illicit substance use, type of colliding vehicle and type of collision. Helmet fixation was defined as the position of the helmet during the crash whether it was still secured on the head or had been dislodged.ResultsHelmet fixation was shown to have a greater effect on facial injury outcome than helmet type. Increased odds of adverse outcome was observed for the non-fixed helmet compared to the fixed helmet with adjusted odds ratio (AOR) = 2.10 (95% CI 1.41- 3.13) for facial injury; AOR = 6.64 (95% CI 3.71-11.91) for upper face injury; AOR = 5.36 (95% CI 3.05-9.44) for middle face injury; and AOR = 2.00 (95% CI 1.22-3.26) for lower face injury. Motorcyclists with visor damage were shown with AOR = 5.48 (95% CI 1.46-20.57) to have facial injuries compared to those with an undamaged visor.ConclusionsA helmet of any type that is properly worn and remains fixed on the head throughout a crash will provide some form of protection against facial injury. Visor damage is a significant contributing factor for facial injury. These findings are discussed with reference to implications for policy and initiatives addressing helmet use and wearing behaviors.

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A very low prevalence of motorcyclists combined with relatively higher rates of larger time gaps to other vehicles around motorcycles may help explain their overrepresentation in injury crashes where another vehicle fails to give way. An increased risk of injury in the event of a crash exists for a small but greater proportion of motorcyclists (compared to other vehicle types) who were exceeding the speed limit. An apparent shift toward older age of the active rider population may be reducing injury crash risk relative to exposure time. There is significant scope to improve the physical conspicuity of motorcyclists and the frequency of motorcycle specific protective clothing use. These results can be used to inform policy development and monitor progress of current and future road safety initiatives.

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BackgroundMotorcycle sales, registration and use are increasing in many countries. The epidemiological literature on risk factors for motorcycle injury is becoming outdated, due to changes in rider demography, licensing regulations, traffic mix and density, road environments, and motorcycle designs and technologies. Further, the potential contribution of road infrastructure and travel speed has not yet been examined.Methods/designA population based case–control study together with a nested case-crossover study is planned. Cases will be motorcycle riders who are injured but not killed in a motorcycle crash on a public road within 150 km radius of Melbourne, Australia, and admitted to one of the study hospitals. Controls will be motorcycle riders who ride through the crash site on the same type of day (weekday or weekend) within an hour of the crash time. Data on rider, bike, and trip characteristics will be collected from the participants by questionnaire. Data on crash site characteristics will be collected in a structured site inspection, and travel speed for the cases will be estimated from these data. Travel speed for the controls will be measured prior to recruitment with a radar traffic detection device as they ride through the crash site. Control sites for the case-crossover study will be selected 1 km upstream from the crash site and matched on either intersection status or road curvature (either straight or cornered). If the initial site selected does not match the case site on these characteristics, then the closest matching site on the case route will be selected. Conditional multivariate logistic regression models will be used to compare risk between the matched case and control riders and to examine associations between road infrastructure and road environment characteristics and crash occurrence. Interactions between type of site and speed will be tested to determine if site type is an effect modifier of the relationship between speed and crash risk. The relationship between rider factors and travel speed generally will be assessed by multivariate regression methods.DiscussionIn the context of the changing motorcycling environment, this study will provide evidence on contemporary risk factors for serious non-fatal motorcycle crashes.