Spatial Relationship Quantification between Environmental, Socioeconomic and Health Data at Different Geographic Levels

Mahdi-Salim Saib 1, 2 Julien Caudeville 1 Florence Carre 1 Olivier Ganry 3 Alain Trugeon 4 André Cicolella 1
1 INERIS - Institut National de l'Environnement Industriel et des Risques
2 UPJV - Université de Picardie Jules Verne
3 CHU Amiens-Picardie
4 OR2S - Observatoire Régional de la Santé et du Social
Abstract : Spatial health inequalities have often been analyzed in terms of socioeconomic and environmental factors. The present study aimed to evaluate spatial relationships between spatial data collected at different spatial scales. The approach was illustrated using health outcomes (mortality attributable to cancer) initially aggregated to the county level, district socioeconomic covariates, and exposure data modeled on a regular grid. Geographically weighted regression (GWR) was used to quantify spatial relationships. The strongest associations were found when low deprivation was associated with lower lip, oral cavity and pharynx cancer mortality and when low environmental pollution was associated with low pleural cancer mortality. However, applying this approach to other areas or to other causes of death or with other indicators requires continuous exploratory analysis to assess the role of the modifiable areal unit problem (MAUP) and downscaling the health data on the study of the relationship, which will allow decision-makers to develop interventions where they are most needed.
Keywords : health inequalities socioeconomic status exposure indicator geographic level MAUP Geographically Weighted Regression
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Mahdi-Salim Saib, Julien Caudeville, Florence Carre, Olivier Ganry, Alain Trugeon, et al.. Spatial Relationship Quantification between Environmental, Socioeconomic and Health Data at Different Geographic Levels. International Journal of Environmental Research and Public Health, MDPI, 2014, 11 (12), pp.3765 - 3786. ⟨10.3390/ijerph110403765⟩. ⟨ineris-01710088⟩

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