Geospatial analyses to prioritize public health interventions: a case study of pedestrian and pedal cycle injuries in New South Wales, Australia
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Pedestrian and pedal cycle injuries are important causes of child morbidity and mortality. The combination of Bayesian methods and geographical distribution maps may assist public health practitioners to identify communities at high risk of injury.
Data were obtained on all hospitalizations of children from NSW (Australia), for pedestrian and pedal cycle injuries, from 2000–2001 to 2004–2005. Using Bayesian methods, posterior expected rate ratios (as an estimate of smoothed standardized hospitalization ratios for each injury mechanism) were mapped by local government area (LGA) across the state.
There were over 7,000 hospitalizations for pedestrian and pedal cycle injuries. High risk LGAs accounted for more than one third of hospitalized pedestrian and pedal cycle injuries in NSW.
LGAs at high risk for pedestrian injury tended to be urbanized metropolitan areas with a high population density, while high risk LGAs for pedal cycle injury tended to be either in urban regional areas, or on the margin of urbanized metropolitan areas. Geospatial analyses can assist policymakers and practitioners to identify high risk communities for which public health interventions can be prioritized.
KeywordsChild Wounds and injuries Accidents, traffic Bicycling Pedestrian Bayesian method
RP is supported by a National Health and Medical Research Council Capacity Building Grant in Injury, Trauma and Rehabilitation. SC and JO are supported by the NSW Injury Risk Management Research Centre (IRMRC), with core funding provided by the NSW Health Department, the NSW Roads and Traffic Authority and the Motor Accidents Authority. The authors would like to thank the Centre for Epidemiology and Research at the NSW Health Department for providing the NSW APDC data from the Health Outcomes and Information Statistical Toolkit (HOIST) analyzed in this study. The authors are also grateful to Dr Andrew Hayen (now at University of Sydney) for the statistical and methodological advice he provided to an earlier phase of this research.
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