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The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?

BACKGROUND: Country averages for health outcomes hide important within-country variations. This paper probes into the geographic Belgian pattern of all-cause mortality and wishes to investigate the contribution of individual and area socio-economic characteristics to geographic mortality differences...

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Autores principales: Van Hemelrijck, Wanda M. J., Willaert, Didier, Gadeyne, Sylvie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897960/
https://www.ncbi.nlm.nih.gov/pubmed/27280020
http://dx.doi.org/10.1186/s13690-016-0135-y
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author Van Hemelrijck, Wanda M. J.
Willaert, Didier
Gadeyne, Sylvie
author_facet Van Hemelrijck, Wanda M. J.
Willaert, Didier
Gadeyne, Sylvie
author_sort Van Hemelrijck, Wanda M. J.
collection PubMed
description BACKGROUND: Country averages for health outcomes hide important within-country variations. This paper probes into the geographic Belgian pattern of all-cause mortality and wishes to investigate the contribution of individual and area socio-economic characteristics to geographic mortality differences in men aged 45–64 during the period 2001–2011. METHODS: Data originate from a linkage between the Belgian census of 2001 and register data on mortality and emigration during the period 2001–2011. Mortality rate ratios (MRRs) are estimated for districts and sub-districts compared to the Belgian average mortality level using Poisson regression modelling. Individual socio-economic position (SEP) indicators are added to examine the impact of these characteristics on the observed geographic pattern. In order to scrutinize the contribution of area-level socio-economic characteristics, random intercepts Poisson modelling is performed with predictors at the individual and the sub-district level. Random intercepts and slopes models are fitted to explore variability of individual-level SEP effects. RESULTS: All-cause MRRs for middle-aged Belgian men are higher in the geographic areas of the Walloon region and the Brussels-Capital Region (BCR) compared to those in the Flemish region. The highest MRRs are observed in the inner city of the BCR and in several Walloon cities. Their disadvantage can partially be explained by the lower individual SEP of men living in these areas. Similarly, the relatively low MRRs observed in the districts of Halle-Vilvoorde, Arlon and Virton can be related to the higher individual SEP. Among the area-level characteristics, both the percentage of men employed and the percentage of labourers in a sub-district have a protective effect on the individual MRR, regardless of individual SEP. Variability in individual-level SEP effects is limited. CONCLUSIONS: Individual SEP partly explains the observed mortality gap in Belgium for some areas. The percentage of men employed and the percentage of labourers in a sub-district have an additional effect on the individual MRR aside from that of individual SEP. However, these socio-economic factors cannot explain all of the observed differences. Other mechanisms such as public health policy, cultural habits and environmental influences contribute to the observed geographic pattern in all-cause mortality among middle-aged men. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13690-016-0135-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-48979602016-06-09 The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences? Van Hemelrijck, Wanda M. J. Willaert, Didier Gadeyne, Sylvie Arch Public Health Research BACKGROUND: Country averages for health outcomes hide important within-country variations. This paper probes into the geographic Belgian pattern of all-cause mortality and wishes to investigate the contribution of individual and area socio-economic characteristics to geographic mortality differences in men aged 45–64 during the period 2001–2011. METHODS: Data originate from a linkage between the Belgian census of 2001 and register data on mortality and emigration during the period 2001–2011. Mortality rate ratios (MRRs) are estimated for districts and sub-districts compared to the Belgian average mortality level using Poisson regression modelling. Individual socio-economic position (SEP) indicators are added to examine the impact of these characteristics on the observed geographic pattern. In order to scrutinize the contribution of area-level socio-economic characteristics, random intercepts Poisson modelling is performed with predictors at the individual and the sub-district level. Random intercepts and slopes models are fitted to explore variability of individual-level SEP effects. RESULTS: All-cause MRRs for middle-aged Belgian men are higher in the geographic areas of the Walloon region and the Brussels-Capital Region (BCR) compared to those in the Flemish region. The highest MRRs are observed in the inner city of the BCR and in several Walloon cities. Their disadvantage can partially be explained by the lower individual SEP of men living in these areas. Similarly, the relatively low MRRs observed in the districts of Halle-Vilvoorde, Arlon and Virton can be related to the higher individual SEP. Among the area-level characteristics, both the percentage of men employed and the percentage of labourers in a sub-district have a protective effect on the individual MRR, regardless of individual SEP. Variability in individual-level SEP effects is limited. CONCLUSIONS: Individual SEP partly explains the observed mortality gap in Belgium for some areas. The percentage of men employed and the percentage of labourers in a sub-district have an additional effect on the individual MRR aside from that of individual SEP. However, these socio-economic factors cannot explain all of the observed differences. Other mechanisms such as public health policy, cultural habits and environmental influences contribute to the observed geographic pattern in all-cause mortality among middle-aged men. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13690-016-0135-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-08 /pmc/articles/PMC4897960/ /pubmed/27280020 http://dx.doi.org/10.1186/s13690-016-0135-y Text en © Van Hemelrijck et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Van Hemelrijck, Wanda M. J.
Willaert, Didier
Gadeyne, Sylvie
The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?
title The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?
title_full The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?
title_fullStr The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?
title_full_unstemmed The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?
title_short The geographic pattern of Belgian mortality: can socio-economic characteristics explain area differences?
title_sort geographic pattern of belgian mortality: can socio-economic characteristics explain area differences?
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897960/
https://www.ncbi.nlm.nih.gov/pubmed/27280020
http://dx.doi.org/10.1186/s13690-016-0135-y
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