The Index of Wellbeing for Older Australians, commissioned by The Benevolent Society and prepared by The National Centre for Social and Economic Modelling (NATSEM), maps how older people are faring nationally across five domains, including education, health, resources and wealth, including housing. The most significant finding of the research is that secure and affordable housing is the most crucial factor affecting an older person’s wellbeing.
Accompanying the index are interactive online maps that identify the areas where older people with the lowest level of wellbeing live, and the factors that contribute most to their low wellbeing. The online maps are available at http://web.natsem.canberra.edu.au/maps/AUS_OSE/atlas.html
The index is a tool for governments, planners and services for monitoring the wellbeing of older people within local areas and for comparing the effectiveness of policies and programs across different areas.
More information and links to the online maps and reports is available at http://benevolent.org.au/media/latest--news/2016/02/10/index--of--wellbe...
Wellbeing is an important concept in society, and there has been much international research recently about the importance of measuring wellbeing in a society. The Organisation for Economic Co‐operation and Development (OECD) How’s Life? 2015: Measuring wellbeing (OECD, 2015a) states that wellbeing is multi‐dimensional, ranging from civic engagement to housing, from income to work‐life balance, and from skills to health status. It is a concept that includes both positive and negative aspects of life (capabilities and vulnerabilities), rather than just negative aspects, like an index of disadvantage. The indicators are then usually combined to form an index (see www.oecdbetterlifeindex.org). Other indexes of wellbeing include the OECD’s Human Development Index (HDI), Bhutan’s Gross National Happiness measure and, in Australia, the proposed Australian National Development Index (ANDI). All of these indexes take a broad approach to wellbeing, using a number of different indicators in a number of domains.
Generally the technique used to develop an index of wellbeing is to identify a number of indicators of wellbeing (which may be for the total population, but can also be for a sub‐group), and then combine these into a single index. This provides a summary measure that represents each of the component indicators to some extent. An index of wellbeing for older people is going to use different indicators to an index of wellbeing for children or youth because the two groups are at different stages of the life cycle and have different priorities. As an example, an index of wellbeing for older people may have whether they are employed, where this will not be relevant for a child.
These indicators and indexes may be national (like the HDI and ANDI mentioned above), or for small areas. Examples of small area indexes include indexes of social exclusion at a small area level created for children (see Barnes et al, 2008; Bradshaw et al, 2008;Tanton et al, 2010 and Miranti et al, 2015), and for youth (see Abello et al., 2015). This report extends this work to develop an index of wellbeing for older Australians at a small area level.
This work has identified a number of indicators of wellbeing for older people, and then brought these together into an index. This index shows that areas where older people experience low wellbeing tend to be in cities rather than regional Australia and that areas with the highest proportion of older people experiencing low wellbeing are on the outskirts of capital cities. Generally older people in regional areas experience reasonable levels of wellbeing and areas with the highest levels of wellbeing are in the cities. So areas with very high and very low areas of wellbeing are in the cities, whereas older people living in areas outside the cities generally experience moderate wellbeing.
One interesting point is that there are clusters of low wellbeing on the outskirts of capital cities, whereas low wellbeing in regional areas is not as clustered – it is interspersed with areas of moderate and high wellbeing. Further work looking at spatial clusters of low wellbeing using spatial analysis is planned to further investigate this.
The other major finding is that low wellbeing has a lot to do with housing. Housing stress contributed the most weight to the index, and rent assistance also had a very high weight. This has implications for income support policies and housing policies like rental assistance for older people. Older people still paying rent after retirement are some of the most vulnerable in our society to changes in circumstances, as a great deal of their income is going on housing costs, reducing their ability to deal with other costs like health or transport.