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Income inequality and alcohol attributable harm in Australia

BACKGROUND: There is little research on the relationship between key socioeconomic variables and alcohol related harms in Australia. The aim of this research was to examine the relationship between income inequality and the rates of alcohol-attributable hospitalisation and death at a local-area leve...

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Autores principales: Dietze, Paul M, Jolley, Damien J, Chikritzhs, Tanya N, Clemens, Susan, Catalano, Paul, Stockwell, Tim
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2658667/
https://www.ncbi.nlm.nih.gov/pubmed/19239715
http://dx.doi.org/10.1186/1471-2458-9-70
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author Dietze, Paul M
Jolley, Damien J
Chikritzhs, Tanya N
Clemens, Susan
Catalano, Paul
Stockwell, Tim
author_facet Dietze, Paul M
Jolley, Damien J
Chikritzhs, Tanya N
Clemens, Susan
Catalano, Paul
Stockwell, Tim
author_sort Dietze, Paul M
collection PubMed
description BACKGROUND: There is little research on the relationship between key socioeconomic variables and alcohol related harms in Australia. The aim of this research was to examine the relationship between income inequality and the rates of alcohol-attributable hospitalisation and death at a local-area level in Australia. METHOD: We conducted a cross sectional ecological analysis at a Local Government Area (LGA) level of associations between data on alcohol caused harms and income inequality data after adjusting for socioeconomic disadvantage and remoteness of LGAs. The main outcome measures used were matched rate ratios for four measures of alcohol caused harm; acute (primarily related to the short term consequences of drinking) and chronic (primarily related to the long term consequences of drinking) alcohol-attributable hospitalisation and acute and chronic alcohol-attributable death. Matching was undertaken using control conditions (non-alcohol-attributable) at an LGA level. RESULTS: A total of 885 alcohol-attributable deaths and 19467 alcohol-attributable hospitalisations across all LGAs were available for analysis. After weighting by the total number of cases in each LGA, the matched rate ratios of acute and chronic alcohol-attributable hospitalisation and chronic alcohol-attributable death were associated with the squared centred Gini coefficients of LGAs. This relationship was evident after adjusting for socioeconomic disadvantage and remoteness of LGAs. For both measures of hospitalisation the relationship was curvilinear; increases in income inequality were initially associated with declining rates of hospitalisation followed by large increases as the Gini coefficient increased beyond 0.15. The pattern for chronic alcohol-attributable death was similar, but without the initial decrease. There was no association between income inequality and acute alcohol-attributable death, probably due to the relatively small number of these types of death. CONCLUSION: We found a curvilinear relationship between income inequality and the rates of some types of alcohol-attributable hospitalisation and death at a local area level in Australia. While alcohol-attributable harms generally increased with increasing income inequality, alcohol-attributable hospitalisations actually showed the reverse relationship at low levels of income inequality. The curvilinear patterns we observed are inconsistent with monotonic trends found in previous research making our findings incompatible with previous explanations of the relationship between income inequality and health related harms.
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spelling pubmed-26586672009-03-20 Income inequality and alcohol attributable harm in Australia Dietze, Paul M Jolley, Damien J Chikritzhs, Tanya N Clemens, Susan Catalano, Paul Stockwell, Tim BMC Public Health Research Article BACKGROUND: There is little research on the relationship between key socioeconomic variables and alcohol related harms in Australia. The aim of this research was to examine the relationship between income inequality and the rates of alcohol-attributable hospitalisation and death at a local-area level in Australia. METHOD: We conducted a cross sectional ecological analysis at a Local Government Area (LGA) level of associations between data on alcohol caused harms and income inequality data after adjusting for socioeconomic disadvantage and remoteness of LGAs. The main outcome measures used were matched rate ratios for four measures of alcohol caused harm; acute (primarily related to the short term consequences of drinking) and chronic (primarily related to the long term consequences of drinking) alcohol-attributable hospitalisation and acute and chronic alcohol-attributable death. Matching was undertaken using control conditions (non-alcohol-attributable) at an LGA level. RESULTS: A total of 885 alcohol-attributable deaths and 19467 alcohol-attributable hospitalisations across all LGAs were available for analysis. After weighting by the total number of cases in each LGA, the matched rate ratios of acute and chronic alcohol-attributable hospitalisation and chronic alcohol-attributable death were associated with the squared centred Gini coefficients of LGAs. This relationship was evident after adjusting for socioeconomic disadvantage and remoteness of LGAs. For both measures of hospitalisation the relationship was curvilinear; increases in income inequality were initially associated with declining rates of hospitalisation followed by large increases as the Gini coefficient increased beyond 0.15. The pattern for chronic alcohol-attributable death was similar, but without the initial decrease. There was no association between income inequality and acute alcohol-attributable death, probably due to the relatively small number of these types of death. CONCLUSION: We found a curvilinear relationship between income inequality and the rates of some types of alcohol-attributable hospitalisation and death at a local area level in Australia. While alcohol-attributable harms generally increased with increasing income inequality, alcohol-attributable hospitalisations actually showed the reverse relationship at low levels of income inequality. The curvilinear patterns we observed are inconsistent with monotonic trends found in previous research making our findings incompatible with previous explanations of the relationship between income inequality and health related harms. BioMed Central 2009-02-25 /pmc/articles/PMC2658667/ /pubmed/19239715 http://dx.doi.org/10.1186/1471-2458-9-70 Text en Copyright © 2009 Dietze 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
Dietze, Paul M
Jolley, Damien J
Chikritzhs, Tanya N
Clemens, Susan
Catalano, Paul
Stockwell, Tim
Income inequality and alcohol attributable harm in Australia
title Income inequality and alcohol attributable harm in Australia
title_full Income inequality and alcohol attributable harm in Australia
title_fullStr Income inequality and alcohol attributable harm in Australia
title_full_unstemmed Income inequality and alcohol attributable harm in Australia
title_short Income inequality and alcohol attributable harm in Australia
title_sort income inequality and alcohol attributable harm in australia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2658667/
https://www.ncbi.nlm.nih.gov/pubmed/19239715
http://dx.doi.org/10.1186/1471-2458-9-70
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