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Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?

BACKGROUND: Geographical health inequalities are naturally described by the variation in health outcomes between areas (e.g. mortality rates). However, comparisons made between countries are hampered by our lack of understanding of the effect of the size of administrative units, and in particular th...

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Autores principales: Jackson, Andrew L, Davies, Carolyn A, Leyland, Alastair H
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2933682/
https://www.ncbi.nlm.nih.gov/pubmed/20718968
http://dx.doi.org/10.1186/1471-2288-10-74
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author Jackson, Andrew L
Davies, Carolyn A
Leyland, Alastair H
author_facet Jackson, Andrew L
Davies, Carolyn A
Leyland, Alastair H
author_sort Jackson, Andrew L
collection PubMed
description BACKGROUND: Geographical health inequalities are naturally described by the variation in health outcomes between areas (e.g. mortality rates). However, comparisons made between countries are hampered by our lack of understanding of the effect of the size of administrative units, and in particular the modifiable areal unit problem. Our objective was to assess how differences in geographic and administrative units used for disseminating data affect the description of health inequalities. METHODS: Retrospective study of standard populations and deaths aggregated by administrative regions within 20 European countries, 1990-1991. Estimated populations and deaths in males aged 0-64 were in 5 year age bands. Poisson multilevel modelling was conducted of deaths as standardised mortality ratios. The variation between regions within countries was tested for relationships with the mean region population size and the unequal distribution of populations within each country measured using Gini coefficients. RESULTS: There is evidence that countries whose regions vary more in population size show greater variation and hence greater apparent inequalities in mortality counts. The Gini coefficient, measuring inequalities in population size, ranged from 0.1 to 0.5 between countries; an increase of 0.1 was accompanied by a 12-14% increase in the standard deviation of the mortality rates between regions within a country. CONCLUSIONS: Apparently differing health inequalities between two countries may be due to differences in geographical structure per se, rather than having any underlying epidemiological cause. Inequalities may be inherently greater in countries whose regions are more unequally populated.
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spelling pubmed-29336822010-09-07 Do differences in the administrative structure of populations confound comparisons of geographic health inequalities? Jackson, Andrew L Davies, Carolyn A Leyland, Alastair H BMC Med Res Methodol Research Article BACKGROUND: Geographical health inequalities are naturally described by the variation in health outcomes between areas (e.g. mortality rates). However, comparisons made between countries are hampered by our lack of understanding of the effect of the size of administrative units, and in particular the modifiable areal unit problem. Our objective was to assess how differences in geographic and administrative units used for disseminating data affect the description of health inequalities. METHODS: Retrospective study of standard populations and deaths aggregated by administrative regions within 20 European countries, 1990-1991. Estimated populations and deaths in males aged 0-64 were in 5 year age bands. Poisson multilevel modelling was conducted of deaths as standardised mortality ratios. The variation between regions within countries was tested for relationships with the mean region population size and the unequal distribution of populations within each country measured using Gini coefficients. RESULTS: There is evidence that countries whose regions vary more in population size show greater variation and hence greater apparent inequalities in mortality counts. The Gini coefficient, measuring inequalities in population size, ranged from 0.1 to 0.5 between countries; an increase of 0.1 was accompanied by a 12-14% increase in the standard deviation of the mortality rates between regions within a country. CONCLUSIONS: Apparently differing health inequalities between two countries may be due to differences in geographical structure per se, rather than having any underlying epidemiological cause. Inequalities may be inherently greater in countries whose regions are more unequally populated. BioMed Central 2010-08-18 /pmc/articles/PMC2933682/ /pubmed/20718968 http://dx.doi.org/10.1186/1471-2288-10-74 Text en Copyright ©2010 Jackson et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Jackson, Andrew L
Davies, Carolyn A
Leyland, Alastair H
Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
title Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
title_full Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
title_fullStr Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
title_full_unstemmed Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
title_short Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
title_sort do differences in the administrative structure of populations confound comparisons of geographic health inequalities?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2933682/
https://www.ncbi.nlm.nih.gov/pubmed/20718968
http://dx.doi.org/10.1186/1471-2288-10-74
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