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

Overview

Journal Int J Environ Res Public Health

Publisher MDPI

Specialties Environmental Health
Public Health

Date 2014 Apr 8

PMID 24705362

Citations 13

Authors

Mahdi-Salim Saib

Julien Caudeville

Florence Carre

Olivier Ganry

Alain Trugeon

Andre Cicolella

Affiliations

Soon will be listed here.

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.

Citing Articles

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Design of an Integrated Platform for Mapping Residential Exposure to Rf-Emf Sources.

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Pedros Barnils N, Eurenius E, Gustafsson P Int J Equity Health. 2020; 19(1):85.

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