Income inequality and alcohol attributable harm in Australia
1 Monash Institute of Health Services Research, Monash University, Clayton, Victoria, 3800, Australia
2 Macfarlane Burnet Institute for Medical Research and Public Health (Burnet Institute), Melbourne, Victoria, 3004, Australia
3 National Drug Research Institute, Perth, Western Australia, 6845, Australia
4 Murdoch Children's Research Institute, Parkville, Victoria, 3052, Australia
5 Centre for Addictions Research of British Columbia, University of Victoria, Victoria, British Columbia, Canada
BMC Public Health 2009, 9:70 doi:10.1186/1471-2458-9-70Published: 25 February 2009
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.
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.
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.
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.