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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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There are a number of factors that cause motor vehicles to rollover. However, the impacts of roadway characteristics on rollover crashes have rarely been addressed in the literature. This study aims to apply a set of crash prediction models in order to estimate the number of rollovers as a function of road geometry, the environment, and traffic conditions. To this end, seven count-data models, including Poisson (PM), negative binomial (NB), heterogeneous negative binomial (HTNB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models, were developed and compared using crash data collected on 448 segments of Malaysian federal roads. The results showed that the HTNB was the best-fit model among the others to model the frequency of rollovers. The variables Light-Vehicle Traffic (LVT), horizontal curvature, access points, speed limit, and centreline median were positively associated with the crash frequency, while UnPaved Shoulder Width (UPSW) and Heavy-Vehicle Traffic (HVT) were found to have the opposite effect. The findings of this study suggest that rollovers could potentially be reduced by developing road safety countermeasures, such as access management of driveways, straightening sharp horizontal curves, widening shoulder width, better design of centreline medians, and posting lower speed limits and warning signs in areas with higher rollover tendency.

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