Deprived children or deprived neighbourhoods? A public health approach to the investigation of links between deprivation and injury risk with specific reference to child road safety in Devon County, UK

BMC Public Health. 2004 May 10:4:15. doi: 10.1186/1471-2458-4-15.


Background: Worldwide, injuries from road traffic collisions are a rapidly growing problem in terms of morbidity and mortality. The UK has amongst the worst records in Europe with regard to child pedestrian safety. A traditional view holds that resources should be directed towards training child pedestrians. In order to reduce socio-economic differentials in child pedestrian casualty rates it is suggested that these should be directed at deprived children. This paper seeks to question whether analysis of extant routinely collected data supports this view.

Methods: Routine administrative data on road collisions has been used. A deprivation measure has been assigned to the location where a collision was reported, and the home postcode of the casualty. Aggregate data was analysed using a number of epidemiological models, concentrating on the Generalised Linear Mixed Model.

Results: This study confirms evidence suggesting a link between increasing deprivation and increasing casualty involvement of child pedestrians. However, suggestions are made that it may be necessary to control for the urban nature of an area where collisions occur. More importantly, the question is raised as to whether the casualty rate is more closely associated with deprivation measures of the ward in which the collision occurred than with the deprivation measures of the home address of the child.

Conclusion: Conclusions have to be drawn with great caution. Limitations in the utility of the officially collected data are apparent, but the implication is that the deprivation measures of the area around the collision is a more important determinant of socio-economic differentials in casualty rates than the deprivation measures of the casualties' home location. Whilst this result must be treated with caution, if confirmed by individual level case-controlled studies this would have a strong implication for the most appropriate interventions.

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adolescent
  • Child
  • Child Welfare / economics*
  • Child Welfare / statistics & numerical data
  • Child, Preschool
  • England / epidemiology
  • Health Surveys
  • Humans
  • Infant
  • Infant, Newborn
  • Poisson Distribution
  • Poverty Areas*
  • Residence Characteristics / classification*
  • Residence Characteristics / statistics & numerical data
  • Rural Population / classification*
  • Rural Population / statistics & numerical data
  • Safety*
  • Socioeconomic Factors
  • Urban Population / classification*
  • Urban Population / statistics & numerical data
  • Walking*