Research background Childhood asthma is a chronic disease, known to be linked to prolonged exposure to air pollution. However, the identification of specific health hazards, associated with childhood asthma is not always straightforward, due to the presence of multiple sources of air pollution in urban areas. In this study, we test a novel approach to the spatial identification of environmental hazards that have the highest probability of association with the observed asthma morbidity patterns. Methods The effect of a particular health hazard on population morbidity is expected to weaken with distance. To account for this effect, we rank potential health hazards based on the strength of association between the observed morbidity patterns and wind-direction weighted proximities to these locations. We validate this approach by applying it to a study of spatial patterns of childhood asthma in the Greater Haifa Metropolitan Area (GHMA) in Israel, characterised by multiple health hazards. Results We identified a spot in the local industrial zone as the primary risk source for the observed asthma morbidity patterns. Multivariate regressions, controlling for socio-economic and geographic variables, revealed that the observed incidence rates of asthma tend to decline as a function of distance from the identified industrial location. Conclusion The proposed identification approach uses disease patterns as its main input, and can be used by researches as a preliminary risk assessment tool, in cases in which specific sources of locally elevated morbidity are unclear or cannot be identified by traditional methods.
|Number of pages||12|
|Journal||Science of the Total Environment|
|State||Published - 1 Oct 2017|
Bibliographical notePublisher Copyright:
© 2017 Elsevier B.V.
- Air pollution
- Childhood asthma
- Distance decay function (DDF)
- Distance gradient method (DGM)
- Health hazards
- Major metropolitan area
ASJC Scopus subject areas
- Environmental Engineering
- Environmental Chemistry
- Waste Management and Disposal