The primary objective of this paper is to review the appropriate use of ratio variables in the study of pedestrian injury exposure. We provide a discussion that rejects the assumption that the relationship between a random variable (e.g., a population X) and a ratio (e.g., injury or disease per population Y/X) is necessarily negative. In the study of pedestrian risk, the null hypothesis is that pedestrian injury risk is constant with respect to pedestrian volume. This study employs a unique data set containing the number of pedestrian collisions, average annual pedestrian volume, average annual vehicle volume, and physical intersection characteristics for 247 intersections in Oakland, California. We use a GLM to estimate the expected injury risk given average annual pedestrian volume and other explanatory variables. Consistent with studies by Leden, Ekman and Jacobsen, the null hypothesis is rejected. Indeed, the risk of collision for pedestrians decreases with increasing pedestrian flows, and it increases with increasing vehicle flows. We also find that pedestrians are more likely to be struck by motorists in commercial and mixed areas than in residential areas.