Evidence map›Paper›PMID 25888924›Full record

ArticleInternational journal of health geographics2015

A multi-criteria spatial deprivation index to support health inequality analyses.

Pablo Cabrera-Barona, Thomas Murphy, Stefan Kienberger, Thomas Blaschke

Open access · goldAbstract read
In one paragraph

Article in International journal of health geographics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 4 pooled it
14.4field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 4 syntheses or guidelines pooled it, 71 citations in OpenAlex.

  1. Pooled it
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  5. Article
  6. A multicriteria vulnerability index for equitable resource allocation in public health funding.Canadian journal of public health = Revue canadienne de sante publique · 2024
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  9. Prevalence of adult smokers in Brazilian capitals according to socioeconomic deprivation.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2023
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  12. Inequalities in Health: Methodological Approaches to Spatial Differentiation.International journal of environmental research and public health · 2021
    Article
  13. Uveal Melanoma: Refusal of Treatment.Ocular oncology and pathology · 2021
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  14. Article
  15. Elderly Health Inequality in China and its Determinants: A Geographical Perspective.International journal of environmental research and public health · 2019
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Pablo Cabrera-BaronaInterfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Schillerstraße 30, 5020, Salzburg, Austria. pablo.cabrera-barona@stud.sbg.ac.at.
Thomas MurphyInterfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Schillerstraße 30, 5020, Salzburg, Austria. thomas.murphy@sbg.ac.at.
Stefan KienbergerInterfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Schillerstraße 30, 5020, Salzburg, Austria. stefan.kienberger@sbg.ac.at.
Thomas BlaschkeInterfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Schillerstraße 30, 5020, Salzburg, Austria. thomas.blaschke@sbg.ac.at.
University of Salzburg · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDeprivation indices are useful measures to analyze health inequalities. There are several methods to construct these indices, however, few studies have used Geographic Information Systems (GIS) and Multi-Criteria methods to construct a deprivation index. Therefore, this study applies Multi-Criteria Evaluation to calculate weights for the indicators that make up the deprivation index and a GIS-based fuzzy approach to create different scenarios of this index is also implemented.

methodsThe Analytical Hierarchy Process (AHP) is used to obtain the weights for the indicators of the index. The Ordered Weighted Averaging (OWA) method using linguistic quantifiers is applied in order to create different deprivation scenarios. Geographically Weighted Regression (GWR) and a Moran's I analysis are employed to explore spatial relationships between the different deprivation measures and two health factors: the distance to health services and the percentage of people that have never had a live birth. This last indicator was considered as the dependent variable in the GWR. The case study is Quito City, in Ecuador.

resultsThe AHP-based deprivation index show medium and high levels of deprivation (0,511 to 1,000) in specific zones of the study area, even though most of the study area has low values of deprivation. OWA results show deprivation scenarios that can be evaluated considering the different attitudes of decision makers. GWR results indicate that the deprivation index and its OWA scenarios can be considered as local estimators for health related phenomena. Moran's I calculations demonstrate that several deprivation scenarios, in combination with the 'distance to health services' factor, could be explanatory variables to predict the percentage of people that have never had a live birth.

conclusionsThe AHP-based deprivation index and the OWA deprivation scenarios developed in this study are Multi-Criteria instruments that can support the identification of highly deprived zones and can support health inequalities analysis in combination with different health factors. The methodology described in this study can be applied in other regions of the world to develop spatial deprivation indices based on Multi-Criteria analysis.

Indexed as

Geographic Information SystemsSpatial AnalysisEcuadorHealthcare DisparitiesHumans

Identifiers

PMID25888924
PMCPMC4376370
OpenAlexW2142723509

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.