Epidemiology of child pedestrian casualty rates: Can we assume spatial independence?

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Abstract

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.

Section snippets

Background

There is a plentiful literature modelling child pedestrian casualty rates, in particular these demonstrate a strong association with areal socio-economic status (Kendrick, 1993, Jolly et al., 1993, Braddock et al., 1991, Roberts et al., 1992, Chichester et al., 1998, Lyons et al., 2003) Recently, a study released in the UK by the Institute of Public Policy Research (IPPR) offered an econometric analysis of child pedestrian casualty rates (Grayling et al., 2002) and claimed there was little

Methods

For the purposes of this study a child is defined as being in the age range 0–15 years.

Diagnostic tests for spatial dependence

There are conceptual reasons for believing that there may be lack of independence in terms of the casualty home location rather than the collision location (MacNab, 2004). For example, if there are indeed casualty related covariates influencing risk, these would tend to be taken with the casualty to other locations. One initial investigative measure for spatial independence is the Geary C statistic (Cliff and Ord, 1981) Results are given in Table 4 which suggest a value of 1.0272 for the

Discussion

There have been attempts recently using multilevel modelling in order to attempt to disentangle areal effects from individual effects (Reading et al., 1999, Haynes et al., 2003, Jones and Jorgensen, 2003) which would go a long way toward addressing ecological concerns surrounding this kind of analysis. However, the situation remaining is clearly one where there is considerable confounding and interaction between individual and environmental factors. It would be therefore most interesting to

Conclusions

Ecological analyses are popular largely because the data are widely available, there are both cost and confidentiality reasons which limit the amount of research conducted at an individual level and are likely to continue to provide part of the body of evidence used to guide interventions. Firstly it needs to be noted that the underlying data are based entirely on an administrative abstraction of an observed phenomenon. Secondly, it is important that methodological developments underpinning

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