Analysis Of Head Injuries Using A Bayesian Vector Generalized Additive Model

The potential of cycle helmets to reduce head injury remains controversial. Although several case-control studies have been published, ecological analyses of head injury remain commonplace, presumably because of the availability of data and policy-makers’ preference for ‘whole population’ studies. Given that such population-level analysis will be conducted, this paper models the odds ratio between different road-user groups over time. We use a Bayesian implementation of a vector generalized additive model in order to examine the odds ratio for head injury when comparing male cyclists with female cyclists, male pedestrians with male cyclists, and female pedestrians with female cyclists over a period when helmet-wearing rates were thought to diverge by gender.