Measuring small-area level deprivation in Belgium: The Belgian Index of Multiple Deprivation.

Area-level deprivation Belgium Multiple deprivation

Journal

Spatial and spatio-temporal epidemiology
ISSN: 1877-5853
Titre abrégé: Spat Spatiotemporal Epidemiol
Pays: Netherlands
ID NLM: 101516571

Informations de publication

Date de publication:
Jun 2023
Historique:
received: 02 12 2022
revised: 02 03 2023
accepted: 17 04 2023
medline: 12 6 2023
pubmed: 11 6 2023
entrez: 10 6 2023
Statut: ppublish

Résumé

In the past, deprivation has been mostly captured through simple and univariate measures such as low income or poor educational attainment in research on health and social inequalities in Belgium. This paper presents a shift towards a more complex, multidimensional measure of deprivation at the aggregate level and describes the development of the first Belgian Indices of Multiple Deprivation (BIMDs) for the years 2001 and 2011. The BIMDs are constructed at the level of the smallest administrative unit in Belgium, the statistical sector. They are a combination of six domains of deprivation: income, employment, education, housing, crime and health. Each domain is built on a suite of relevant indicators representing individuals that suffer from a certain deprivation in an area. The indicators are combined to create the domain deprivation scores, and these scores are then weighted to create the overall BIMDs scores. The domain and BIMDs scores can be ranked and assigned to deciles from 1 (the most deprived) to 10 (the least deprived). We show geographical variations in the distribution of the most and least deprived statistical sectors in terms of individual domains and overall BIMDs, and we identify hotspots of deprivation. The majority of the most deprived statistical sectors are located in Wallonia, whereas most of the least deprived statistical sectors are in Flanders. The BIMDs offer a new tool for researches and policy makers for analyzing patterns of deprivation and identifying areas that would benefit from special initiatives and programs.

Sections du résumé

BACKGROUND BACKGROUND
In the past, deprivation has been mostly captured through simple and univariate measures such as low income or poor educational attainment in research on health and social inequalities in Belgium. This paper presents a shift towards a more complex, multidimensional measure of deprivation at the aggregate level and describes the development of the first Belgian Indices of Multiple Deprivation (BIMDs) for the years 2001 and 2011.
METHODS METHODS
The BIMDs are constructed at the level of the smallest administrative unit in Belgium, the statistical sector. They are a combination of six domains of deprivation: income, employment, education, housing, crime and health. Each domain is built on a suite of relevant indicators representing individuals that suffer from a certain deprivation in an area. The indicators are combined to create the domain deprivation scores, and these scores are then weighted to create the overall BIMDs scores. The domain and BIMDs scores can be ranked and assigned to deciles from 1 (the most deprived) to 10 (the least deprived).
RESULTS RESULTS
We show geographical variations in the distribution of the most and least deprived statistical sectors in terms of individual domains and overall BIMDs, and we identify hotspots of deprivation. The majority of the most deprived statistical sectors are located in Wallonia, whereas most of the least deprived statistical sectors are in Flanders.
CONCLUSION CONCLUSIONS
The BIMDs offer a new tool for researches and policy makers for analyzing patterns of deprivation and identifying areas that would benefit from special initiatives and programs.

Identifiants

pubmed: 37301602
pii: S1877-5845(23)00024-2
doi: 10.1016/j.sste.2023.100587
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

100587

Informations de copyright

Copyright © 2023. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Martina Otavova (M)

Center for Demographic Research, UCLouvain, Louvain-la-Neuve, Belgium; Data Science Institute, I-BioStat, Hasselt University, Belgium; Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium. Electronic address: martina.otavova@uclouvain.be.

Bruno Masquelier (B)

Center for Demographic Research, UCLouvain, Louvain-la-Neuve, Belgium.

Christel Faes (C)

Data Science Institute, I-BioStat, Hasselt University, Belgium.

Laura Van den Borre (L)

Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium; Interface Demography, Department of Sociology, Vrije Universiteit Brussels, Belgium.

Catherine Bouland (C)

Research Centre on Environmental and Occupational Health, School of Public Health, Université Libre de Bruxelles, Brussels, Belgium.

Eva De Clercq (E)

Department of Risk and Health Impact Assessment, Sciensano, Brussels, Belgium.

Bram Vandeninden (B)

Data Science Institute, I-BioStat, Hasselt University, Belgium; Research Centre on Environmental and Occupational Health, School of Public Health, Université Libre de Bruxelles, Brussels, Belgium; Department of Risk and Health Impact Assessment, Sciensano, Brussels, Belgium.

Andreas De Bleser (A)

Intermutualistic Agency, Brussels, Belgium.

Brecht Devleesschauwer (B)

Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium; Department of Translational Physiology, Infectiology and Public Health, Ghent University, Merelbeke, Belgium.

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