Next Article in Journal
Flood Disaster Risk Assessment of Rural Housings — A Case Study of Kouqian Town in China
Next Article in Special Issue
What Causes Environmental Inequalities and Related Health Effects? An Analysis of Evolving Concepts
Previous Article in Journal
Exposures of 129 Preschool Children to Organochlorines, Organophosphates, Pyrethroids, and Acid Herbicides at Their Homes and Daycares in North Carolina
Previous Article in Special Issue
The Socioeconomic Determinants of Health: Economic Growth and Health in the OECD Countries during the Last Three Decades
Int. J. Environ. Res. Public Health 2014, 11(4), 3765-3786; doi:10.3390/ijerph110403765
Article

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

1,2,* , 1
, 1
, 3
, 4
 and 1
1 French National Institute for Industrial Environment and Risks, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte, France 2 University of Picardie Jules Verne, 33 rue St Leu, Amiens 80039, France 3 University Hospital of Amiens, Place Victor Pauchet Amiens 80054, France 4 Regional Observatory of Health and Social Issues in Picardie (OR2S), 3, rue des Louvels, Amiens 80036, France
* Author to whom correspondence should be addressed.
Received: 31 October 2013 / Revised: 18 March 2014 / Accepted: 19 March 2014 / Published: 3 April 2014
(This article belongs to the Special Issue Inequalities in Health)
View Full-Text   |   Download PDF [1696 KB, 19 June 2014; original version 19 June 2014]   |   Browse Figures

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 health inequalities; socioeconomic status; exposure indicator; geographic level; MAUP; Geographically Weighted Regression
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Export to BibTeX |
EndNote


MDPI and ACS Style

Saib, M.-S.; Caudeville, J.; Carre, F.; Ganry, O.; Trugeon, A.; Cicolella, A. Spatial Relationship Quantification between Environmental, Socioeconomic and Health Data at Different Geographic Levels. Int. J. Environ. Res. Public Health 2014, 11, 3765-3786.

View more citation formats

Related Articles

Article Metrics

Comments

Citing Articles

[Return to top]
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert