Inequalities in mortality associated with housing conditions in Belgium between 1991 and 2020.


Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
20 12 2022
Historique:
received: 04 02 2022
accepted: 07 12 2022
entrez: 20 12 2022
pubmed: 21 12 2022
medline: 23 12 2022
Statut: epublish

Résumé

Poor housing conditions have been associated with increased mortality. Our objective is to investigate the association between housing inequality and increased mortality in Belgium and to estimate the number of deaths that could be prevented if the population of the whole country faced the mortality rates experienced in areas that are least deprived in terms of housing. We used individual-level mortality data extracted from the National Register in Belgium and relative to deaths that occurred between Jan. 1, 1991, and Dec. 31, 2020. Spatial and time-specific housing deprivation indices (1991, 2001, and 2011) were created at the level of the smallest geographical unit in Belgium, with these units assigned into deciles from the most to the least deprived. We calculated mortality associated with housing inequality as the difference between observed and expected deaths by applying mortality rates of the least deprived decile to other deciles. We also used standard life table calculations to estimate the potential years of life lost due housing inequality. Up to 18.5% (95% CI 17.7-19.3) of all deaths between 1991 and 2020 may be associated with housing inequality, corresponding to 584,875 deaths. Over time, life expectancy at birth increased for the most and least deprived deciles by about 3.5 years. The gap in life expectancy between the two deciles remained high, on average 4.6 years. Life expectancy in Belgium would increase by approximately 3 years if all deciles had the mortality rates of the least deprived decile. Thousands of deaths in Belgium could be avoided if all Belgian neighborhoods had the mortality rates of the least deprived areas in terms of housing. Hotspots of housing inequalities need to be located and targeted with tailored public actions.

Sections du résumé

BACKGROUND
Poor housing conditions have been associated with increased mortality. Our objective is to investigate the association between housing inequality and increased mortality in Belgium and to estimate the number of deaths that could be prevented if the population of the whole country faced the mortality rates experienced in areas that are least deprived in terms of housing.
METHODS
We used individual-level mortality data extracted from the National Register in Belgium and relative to deaths that occurred between Jan. 1, 1991, and Dec. 31, 2020. Spatial and time-specific housing deprivation indices (1991, 2001, and 2011) were created at the level of the smallest geographical unit in Belgium, with these units assigned into deciles from the most to the least deprived. We calculated mortality associated with housing inequality as the difference between observed and expected deaths by applying mortality rates of the least deprived decile to other deciles. We also used standard life table calculations to estimate the potential years of life lost due housing inequality.
RESULTS
Up to 18.5% (95% CI 17.7-19.3) of all deaths between 1991 and 2020 may be associated with housing inequality, corresponding to 584,875 deaths. Over time, life expectancy at birth increased for the most and least deprived deciles by about 3.5 years. The gap in life expectancy between the two deciles remained high, on average 4.6 years. Life expectancy in Belgium would increase by approximately 3 years if all deciles had the mortality rates of the least deprived decile.
CONCLUSIONS
Thousands of deaths in Belgium could be avoided if all Belgian neighborhoods had the mortality rates of the least deprived areas in terms of housing. Hotspots of housing inequalities need to be located and targeted with tailored public actions.

Identifiants

pubmed: 36539802
doi: 10.1186/s12889-022-14819-w
pii: 10.1186/s12889-022-14819-w
pmc: PMC9769013
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2397

Subventions

Organisme : Belgian Federal Science Policy Office
ID : B2/191/P3/ELLIS

Informations de copyright

© 2022. The Author(s).

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Auteurs

Martina Otavova (M)

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

Christel Faes (C)

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

Thierry Eggerickx (T)

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

Jean-Paul Sanderson (JP)

Center for Demographic Research, UCLouvain, Louvain-La-Neuve, 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.

Bruno Masquelier (B)

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

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