Epidemiology of child pedestrian casualty rates: can we assume spatial independence?
Child pedestrian injuries are often investigated by means of ecological studies, yet are clearly part of a complex spatial phenomena. Spatial dependence within such ecological analyses have rarely been assessed, yet the validity of basic statistical techniques rely on a number of independence assumptions. Recent work from Canada has highlighted the potential for modelling spatial dependence within data that was aggregated in terms of the number of road casualties who were resident in a given geographical area. Other jurisdictions aggregate data in terms of the number of casualties in the geographical area in which the collision took place. This paper contrasts child pedestrian casualty data from Devon County UK, which has been aggregated by both methods. A simple ecological model, with minimally useful covaraties relating to measures of child deprivation, provides evidence that data aggregated in terms of the casualty's home location cannot be assumed to be spatially independent and that for analysis of these data to be valid there must be some accounting for spatial auto-correlation within the model structure. Conversely, data aggregated in terms of the collision location (as is usual in the UK) was found to be spatially independent. Whilst the spatial model is clearly more complex it provided a superior fit to that seen with either collision aggregated or non-spatial models. Of more importance, the ecological level association between deprivation and casualty rate is much lower once the spatial structure is accounted for, highlighting the importance using appropriately structured models.
Hewson
Paul J
PJ
Environment Directorate, Devon County Council Topsham Road, Exeter EX2 4QW, UK. paul.hewson@plymouth.ac.uk
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000203:Activities of Daily Living / Q000145:classification / Q000523:psychology; D000293:Adolescent; D000465:Algorithms; D002648:Child; D002657:Child Development / Q000145:classification; D002675:Child, Preschool; D004739:England / Q000453:epidemiology; D005843:Geography / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015233:Models, Statistical; D009010:Monte Carlo Method; D016012:Poisson Distribution; D013037:Spatial Behavior; D016138:Walking / Q000502:physiology / Q000706:statistics & numerical data*; D014947:Wounds and Injuries / Q000453:epidemiology*