Prevalence of disability among the major cities in Australia 2012 with geographical representation of distribution in Western Australia

Health Promot J Austr. 2020 Jan;31(1):121-127. doi: 10.1002/hpja.265. Epub 2019 Jun 22.

Abstract

Issue addressed: The aim of this study was to use a novel approach to geographically model the relationship between socio-economic disadvantage and prevalence of profound and severe disability.

Method: This study used national census data and the survey of disability, ageing and carers data to geographically model the relationship between socio-economic disadvantage and prevalence of profound and severe disability.

Result: The results in this study show that there were more people living in the least disadvantaged areas (wealthiest) when compared to the most disadvantaged (poorest) areas. Whereas for people with a disability as the relative socio-economic disadvantage of the area increased, the number of people reporting any disability also increased, with the highest number coming from the most disadvantaged areas. The maps show a significant distribution with fewer cases of disability in metropolitan areas and relatively higher number in the rural area along with the higher proportion of people with disability living in the relatively more disadvantaged areas.

Conclusion: Socio-economic profile is one of the key factors influencing the various aspects of health and hence should hold an important place during policy making. Policy should be formulated and implemented to help reduce the inequality by either directly aiming at the most disadvantaged group or by trying to bridge the gap between them. SO WHAT?: This paper provides a geographic visualisation of the distribution of people with profound and severe disability to help identify priority areas with high prevalence of disability.

Keywords: Australia; DAC; IRSAD; SEIFA; census; disability; social gradient.

MeSH terms

  • Australia / epidemiology
  • Cities / epidemiology
  • Disabled Persons / statistics & numerical data*
  • Humans
  • Prevalence
  • Severity of Illness Index
  • Socioeconomic Factors*
  • Spatial Analysis