Background Injuries are a leading cause of death and disability around the world. Previous studies have shown that certain populations are consistently at greater risk of injury. Spatial epidemiological approach provides a way to better understand injury patterns and their associated risk factors at a population level. The aim of this research is to provide a systematic reivew of spatial epidemiological methods applied to injury research.
Methods A search was conducted in three major electronic databases (PubMed, Web of Science and Science Direct), for papers published between 2000–2015 inclusive. Included were papers reporting unintentional injury outcomes, which used geospatial methods for spatial epidemiological analysis. Findings are reported using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.
Results From over 10,000 articles, 88 articles met all inclusion criteria. The major categories of injury data that have been reported with geospatial methods were road traffic (52%), falls (11%), burns (12%), drowning (5%), workplace injuries (2%) and others (18%). Grouped by themes, mapping was the most frequently used method, with 74% of articles limited to this approach to investigate a spatial pattern of injuries. Cluster detection and ecological analysis methods were applied less commonly, being used in 26% and 3% of articles, respectively. The kernal density estimation for point data and local indicators of spatial autocorelation for areal data were the most frequently used cluster detection methods.
Conclusion In the last two decades, many geospatial methods have been developed and applied in injury research, primarily to investigate road traffic injuries. The depth of investigations has been largely limited to basic mapping. Use of more advanced geospatial methods will help to better understand injury aetiology. Researchers should be encouraged to adopt these advanced methods in their future studies.
- Spatial epidemiology
- cluster detection
- ecological analysis
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