Geospatial and epidemiological analysis of severe burns in New South Wales by residential postcodes

Burns. 2014 Jun;40(4):670-82. doi: 10.1016/j.burns.2013.09.005. Epub 2013 Nov 26.

Abstract

Background: Burns are a common trauma, affecting 1% of the Australian population annually and are associated with significant physical, psychological, social and economic burdens for victims and their families. There has been a recent paradigm shift from the treatment of burns to a more preventative approach.

Objectives: To examine the risk of severe burns by geographic region in New South Wales (NSW), Australia, using geospatial analytic techniques.

Method: Retrospective analyses were carried out to examine the 2006-2010 NSW burns data collected by the NSW Severe Burns Injury Service. Spatial analysis software was used to map the relative risk of burns by postcode areas. Spatial cluster analyses were then undertaken for the Greater Sydney Area (GSA) using Global Moran's I statistics and Getis-Ord analyses. High- and low-risk populations and areas were examined to ascertain differences by sociodemographic characteristics, etiology and the extent of burn.

Results: Scalds were the most common types of burns and men were at greater risk of burns than women. There was significant clustering of burns by postcode area, with a higher relative risk of severe burns seen in Western Sydney area and lower risk observed in Eastern and Southern Sydney. In high-risk areas burns occurred more frequently in the 13-24 months and the 20-29 years age groups, while in low-risk areas burns mostly affect the 20-29 and 30-39 years age groups. High-risk areas were characterized by socioeconomic disadvantage.

Implications: Mapping the risk of burns is a valuable tool for policy makers to plan and deliver targeted intervention strategies for burns prevention.

Keywords: Burns epidemiology; Prevention; Risk analysis.

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Burns / epidemiology*
  • Burns / etiology
  • Child
  • Child, Preschool
  • Cluster Analysis
  • Female
  • Geography
  • Humans
  • Infant
  • Infant, Newborn
  • Injury Severity Score
  • Male
  • Middle Aged
  • New South Wales / epidemiology
  • Occupations / statistics & numerical data
  • Retrospective Studies
  • Sex Distribution
  • Socioeconomic Factors
  • Spatial Analysis
  • Young Adult