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Objectives: Bicycle helmets have been advocated as a means of reducing injury among cyclists. This assertion, derived from a number of case controlled studies carried out in hospitals, conflicts with results from population level studies. In the Western countries where these case control studies have been performed, it appears that cycling morbidity is dominated by sports and leisure users. The generalizability of studies on helmet effectiveness in relation to utilitarian transport cycling is not clear. This study therefore considers population level data for reported road traffic injuries of cyclists and pedestrians.
Methods: Generalized linear and generalized additive models were used to investigate patterns of pedestrian and cyclist injury in the UK based on the police reported “Stats 19” data. Comparisons have been made with survey data on helmet wearing rates to examine evidence for the effectiveness of cycle helmets on overall reported road casualties. While it must be acknowledged that police casualty reports are prone to under-reporting, particularly of incidents involving lower severity casualties the attractive feature of these data are that by definition they only concern road casualties.
Results: There is little evidence in UK from the subset of road collisions recorded by the police corresponding to the overall benefits that have been predicted by the results of a number of published case controlled studies. In particular, no association could be found between differing patterns of helmet wearing rates and casualty rates for adults and children.
Conclusions: There is no evidence that cycle helmets reduce the overall cyclist injury burden at the population level in the UK when data on road casualties is examined. This finding, supported by research elsewhere could simply be due to cycle helmets having little potential to reduce the overall transport-related cycle injury burden. Equally, it could be a manifestation of the “ecological fallacy” where it could be conceived that the existence of various sub-groups of cyclists, with different risk profiles, may need to be accounted for in understanding the difference between predicted and realised casualty patterns.