Spatio-temporal Analysis of the Impact of Socioeconomic Status on Admissions for Acute Myocardial Infarction and Related Procedures, in New South Wales, Australia

Abstract

P-385 Introduction: Our objective was to use spatio-temporal models to examine the relationship between socio-economic status and hospital admissions for heart disease and related procedures. We also quantified the effect of including other variables such as remoteness, Sydney postal areas and Indigenous status. Methods: The main source of outcome data was the New South Wales (NSW) Inpatient Statistics Collection, which is a census of all hospital admissions. Estimated population size from the Australian Bureau of Statistics (ABS) 2001 census, was used to calculate indirect sex and age standardised counts of the outcomes at the postal-area level for the period 1996–2002. Data on Index of Relative Social Disadvantage (IRSD), Accessibility and Remoteness Index for Australia (ARIA-plus), and proportion of Aboriginal & Torres Strait Islander (ATSI) data was also obtained from the ABS. We applied the Bernardinelli spatio-temporal model in our analysis, where both the area-specific intercepts and temporal trends were modelled as random effects. Results: We found an exposure-response relationship between IRSD and acute myocardial infarction (AMI) admissions. i.e. those living in socio-economically disadvantaged postal areas were more likely to be admitted for AMI. We also found that including ARIAP-plus to IRSD actually resulted in a lower percentage of spatial correlation (from 85% to 78%), indicating that accessibility and remoteness does seem to explain away some of the spatial variation in the admissions data, after adjusting for socio-economic status. There was no overall linear temporal increase in relative risks from 1996 to 2002, but we did find a small and significant interaction random effect, indicating that there could be some regions showing a temporal trend over time. We also examined the spatio-temporal distribution of related procedures such cardiac catheterisations, Coronary Artery Bypass Grafts and stents. These demonstrated an inverse relationship with disadvantage and, in some regions, this disparity appeared to worsen rather than improve over the study period. Discussion: We found strong spatially correlated effects in the risk estimates of heart disease and related procedures hospital admissions in NSW, Australia from 1996 to 2002. While low socio-economic status was associated with higher rates of admissions for AMI, it was also associated with low intervention rates. This disparity appears to be increasing in some regions.