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Building spatial composite indicators to analyze environmental health inequalities on a regional scale

Overview of attention for article published in Environmental Health, August 2015
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28 Dimensions

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Title
Building spatial composite indicators to analyze environmental health inequalities on a regional scale
Published in
Environmental Health, August 2015
DOI 10.1186/s12940-015-0054-3
Pubmed ID
Authors

Mahdi-Salim Saib, Julien Caudeville, Maxime Beauchamp, Florence Carré, Olivier Ganry, Alain Trugeon, Andre Cicolella

Abstract

Reducing health inequalities involves the identification and characterization of social and exposure factors and the way they accumulate in a given area. The areas of accumulation then allow for prioritization of interventions. The present study aims to build spatial composite indicators based on the aggregation of environmental, social and health indicators and their inter-relationships. Preliminary work was carried out firstly to homogenize spatial coverage, and secondly to study spatial variation of environmental (EI), socioeconomic (SI) and health (HI) indicators. The aggregation of the different indicators was performed using several methodologies for which results and decision-makers' usability were compared. Four methodologies were tested: 1) A simple summation of normalized HI, EI and SI indicators (IC), 2) the sum of the normalized HI, EI and SI indicators weighted by the first principal component of a Principal Component Analysis (IC PCA), 3) the sum of normalized and weighted indicators of the first principal component of Local Principal Component Analysis (IC LPCA), and 4) the sum of normalized and weighted indicators of the first principal component of a Geographically Weighted Principal Component Analysis (IC GWPCA). The GWPCA is particularly adapted to taking into account the spatial heterogeneity and the spatial autocorrelation between SI, EI and HI. This approach invalidates the basic assumptions of many standard statistical analyses. Where socioeconomic indicators present high deprivation and where they are associated with potential modifiable health determinants, decision-makers can prioritize these areas for reducing inequalities by controlling the socioeconomic and health determinants.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 1%
Brazil 1 1%
Unknown 67 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 23%
Researcher 12 17%
Student > Ph. D. Student 9 13%
Student > Doctoral Student 4 6%
Other 4 6%
Other 12 17%
Unknown 12 17%
Readers by discipline Count As %
Social Sciences 14 20%
Environmental Science 9 13%
Medicine and Dentistry 9 13%
Engineering 5 7%
Mathematics 3 4%
Other 8 12%
Unknown 21 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 August 2015.
All research outputs
#15,344,095
of 22,824,164 outputs
Outputs from Environmental Health
#1,137
of 1,489 outputs
Outputs of similar age
#156,316
of 266,184 outputs
Outputs of similar age from Environmental Health
#19
of 22 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,489 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.3. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,184 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.