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Many aspects of disadvantage go hand in hand. The links, for example, between a poor education and low income are well known, while low income is, in turn, associated with poor health and inferior housing.
The progress indicators within this publication focus on progress at the national, or aggregate level. Although an indicator of progress might have reached a certain level for Australia as a whole, we recognise in the Some differences within Australia section of each commentary, that that level might be different among the various subgroups of the population: for example, different groups of people have different average life expectancy, different unemployment rates or different levels of educational attainment. And so, for most progress dimensions, the commentaries shed some light on the relative advantage and disadvantage of some population subgroups.
But, because the commentaries discuss each dimension in turn, they do not include information on the extent to which various sub-groups of the population experience more than one form of disadvantage.
Information on the patterns and incidence of multiple disadvantage in Australia can be important to an understanding of Australia's progress.
Those experiencing multiple disadvantage have poor outcomes across a range of dimensions of life. The effects of several disadvantages acting in tandem can be more difficult to overcome than just a single aspect of disadvantage. And this multiple disadvantage can be perpetuated across generations. Multiple disadvantage can also lead to exclusion from society (see box opposite) and a lack of access to goods, services, activities and resources.
This article discusses multiple disadvantage in Australia. It begins by comparing levels of disadvantage across a range of areas of concern for different population subgroups - men and women of different ages; different household types; and people in different states and territories or remote and non-remote areas.
It goes on to examine the associations between disadvantage in one dimension and disadvantage in another: to what extent, for example, is a low level of education associated with a high level of unemployment, and do the associations differ in different subgroups of the population?
Disadvantage by household type
Disadvantage among different subgroups
In 2002, the ABS General Social Survey (GSS) asked a series of questions about people's social and economic outcomes. We focus here on several areas that are also headline dimensions of progress - health, education and training, work, financial hardship, crime, and family and community. And we examine the extent to which various subgroups in the population experience relatively poor outcomes in these areas. We examine subgroups defined by their age and sex; their living arrangements; and where they live. A one page box discusses disadvantage among Australia's Aboriginal and Torres Strait Islander peoples.
Couples and people living alone
There were considerable differences in patterns of disadvantage among the different households set out in the table above.
In 2002, people living with a partner (of any age) but no children were less likely to experience many aspects of disadvantage than people in the same age group who were living alone. For instance, among those aged 18-34, some 31% of people living in a couple only household were without a non-school qualification, compared to 41% of people in the same age group and living alone; 4% were unemployed (compared to 7%); 19% had been the victim of an assault or break-in (compared to 34%); and only 4% had equivalised household income in the bottom quintile (compared to 21%).
In the 35-64 age group, 26% of people living alone were in fair or poor health, compared to 19% of their counterparts living in couple-only relationships. People in this age group and living alone also reported higher unemployment (6%) and were more likely to have been the victim of an assault or break-in (24%) than their counterparts in a couple only relationship, 2% of whom reported being unemployed and 14% of whom reported being the victim of a crime. People in this age group living alone were nearly twice as likely to have equivalised income in the bottom quintile as those living in a couple only relationship (37.5% and 19.4%). There was, however, little difference in educational attainment between the two groups.
Among people older than 64, there were fewer large differences between those living alone and those living in couple only relationships. The largest differences for this age group were in the proportions of people without post-school qualifications and with low income. About 74% of people older than 64 and living alone were without a non-school qualification and 66% had equivalised income in the bottom quintile. The figures stood at 63% and 45%, respectively, of people older than 64 who were living in a couple only relationship.
Men living alone were less likely to have support in a time of crisis than either their female counterparts or people in the same age group living in a couple relationship. Lack of support was most prevalent among men aged 35-64 and living alone: 11% of them felt they would not have support from outside their household.
Families with dependent children: couples and lone parents
Differences in disadvantage between couple and one parent families with dependent children were noticeable in 2002, with couple families less likely to experience disadvantage in any area.
People living in a couple family were about half as likely to be in fair or poor health as single parents were; and while 45% of people in couple families reported not having a non-school qualification, this rose to 55% among lone parents. Unemployment among lone parents was twice as high as among couple families, which made a small contribution to the large difference between the two groups in the proportions of people with a relatively low income: about 12% of people in couple families reported an equivalised household income in the bottom 20%, compared to about 40% of lone parents. Lone parents were almost twice as likely to have been the victim of an assault or break-in than people in a couple family (33.1% and 18.7%).
Men and women living alone
Differences in the prevalence of disadvantage between men and women who live alone are also shown in the table.
In all three age groups, there were only small differences in the proportions of men and women living alone who reported fair or poor health.
In recent years the proportion of women taking qualifications outside school has increased and this is reflected in the data here. Younger women living alone (those aged 18-34) were a little more likely to have a non-school qualification than their male counterparts. But the pattern changed in older age groups, with men aged 35-64 a little more likely to have a non-school qualification. Among older people (those aged 65 and over) the difference was quite substantial: about 40% of men older than 64 and living alone had a non-school qualification, compared to only 20% of women.
The chance of being a victim of crime decreased as people got older, but, regardless of age, men living alone reported a crime victimisation rate about four and a half percentage points higher than women living alone.
There was little difference in the proportions of men and women younger than 35 and living alone who had income in the bottom quintile. But in older age groups, the proportions of women reporting equivalised income in the bottom quintile were about 10 percentage points higher than the proportion of men who reported low income.
Men living alone were less likely than women living alone to have support in a time of crisis. The difference was most marked among those aged 35-64 where 11% of men and 4% of women felt they would not have support.
Disadvantage and location
Differences in patterns of disadvantage according to the remoteness of the areas in which people live are influenced by many factors. Those living in more remote areas tended to experience a higher rate of fair or poor health, a greater tendency to be without a non-school qualification, a higher unemployment rate and were more likely to have income in the bottom quintile. But people living in more remote Australia reported lower rates of crime victimisation than other Australians.
Disadvantage by remoteness
Associations between dimensions of disadvantage
Many aspects of disadvantage are associated with one another. This section investigates the links between some key areas of disadvantage by describing the associations between poor self-assessed health, absence of a non-school qualification, low income, an inability to get support in a time of crisis, unemployment, and whether someone had been the victim of a crime (the six dimensions of disadvantage considered in the previous section). Although we discuss the associations between areas it is not possible to postulate a causal relationship. For example, while there may be an association between poor health and low income, it is impossible to ascertain from the GSS data whether poor health leads to low income or vice versa.
Across the entire population, about 16% of people reported their health as fair or poor and about 25% reported excellent health. People who reported their health as fair or poor were generally more likely to experience other aspects of disadvantage.
Health: Self-assessed health status and disadvantage
Aboriginal and Torres Strait Islander Peoples: Selected indicators by remoteness
Aboriginal and Torres Strait Islander Peoples, aged 15- 64: Labour force status, occupation and income - by educational attainment
Education and training: Educational attainment and disadvantage, by age
Education and training
People with degrees reported lower levels of disadvantage in all areas (aside from crime victimisation) than their counterparts without a non-school qualification.
Whether or not people are unemployed, or participate in the labour force is mainly seen as an aspect of disadvantage for those younger than 65. And so the figures here focus on that age group.
Being unemployed or out of the labour force was associated with increased reporting of poor heath, and absence of a non-school qualification, with those outside the labour force most likely to experience disadvantage. Those outside the labour force were more likely than the unemployed to be in fair or poor health. And, in turn, the unemployed were more likely to experience fair or poor health than the employed.
Work: Labour force status and disadvantage, by age
Financial hardship: Household income and disadvantage, by age
Although we would ideally like to consider data about people in financial hardship, such data are unavailable (see box) and so we focus on people with low incomes, some of whom experience financial hardship.
There were some noticeable differences in rates of disadvantage between those with high and low incomes.
This article has examined patterns of, and associations between, aspects of disadvantage. The next table shows patterns of disadvantage among different subgroups by comparing how often people in different groups have one, two or three aspects of disadvantage. The three aspects are:
It is important to remember that people's health is closely related to their age, and educational attainment is lower in older generations.
Almost two-thirds (64%) of people reported at least one of these measures of disadvantage in the GSS, about one-fifth of people reported two of the three measures, while about 2% experienced all three. Groups reporting higher rates of at least one disadvantage include people older than 64, people in the bottom income quintile, lone parents and the unemployed (more than 70% of each group reported experiencing at least one measure).
Multiple disadvantage prevalence rates, selected population subgroups
Reports of at least two of the three aspects of disadvantage were most common among people in the bottom income quintile and people older than 64 and living alone, with about one-third of people in each group reporting at least two aspects.
Far fewer people reported experiencing all three aspects of disadvantage, and differences in reporting rates between groups, in absolute terms, was small. But about 5% of people in one parent families and those in the bottom income quintile reported experiencing all three aspects, when the rate overall was 2%.
Multiple disadvantage by area
Using census data, transformed into Indexes of Relative Socio- Economic Advantage and/or Disadvantage (SEIFA), one can examine various aspects of multiple disadvantage.5
Health and multiple disadvantage
The links between poor health and other aspects of disadvantage are illustrated by considering the differing prevalence of health conditions in geographic areas grouped according to their level of other aspects of disadvantage. The graphs display information on illnesses from the 2001 National Health Survey.6
Diabetes and disadvantage
Mental and Behavioural problems and
Heart disease and disadvantage
Cancer and disadvantage
In each graph, the prevalence of a health condition is shown in each of five SEIFA groups (the SEIFA quintiles from the 1996 Census): each group is made up of areas with a similar level of general relative disadvantage. Areas in the first SEIFA quintile are the most disadvantaged, those in the fifth, the least disadvantaged.
There appears to be an association between disadvantage and both diabetes and mental and behavioural problems, with a higher prevalence of both conditions in more disadvantaged areas.
After adjusting for age differences, diabetes appears to be more common in the most disadvantaged areas than the least disadvantaged areas. The age standardised rate for diabetes is 3.6% of people in the most disadvantaged areas, compared to 2.1% in the least. Mental and behaviourial problems were also more prevalent in areas in the first SEIFA quintile than the fifth, with age standardised rates of 12.6% and 7.9% respectively.
The association between heart disease and disadvantage was less clear cut, although there appeared to be a general tendency for heart disease to decline with reduced disadvantage. At 4.2 per hundred, age-standardised rates of heart disease were almost one-third higher in the most disadvantaged areas compared to the least disadvantaged areas (3.3 per hundred).
These data did not show a strong association between those suffering cancer and disadvantage, although other researchers have found a link between deaths from cancer and SEIFA quintile.7
Other characteristics of the advantaged and disadvantaged areas
Proportion of people and labour force status,
SEIFA(a) top and bottom
Proportion of people and years of schooling, SEIFA(a) top and bottom
Proportion of people and equivalised
weekly household gross income, SEIFA(a)
top and bottom
These figures should be interpreted with caution because SEIFA is calculated by considering, among other things, levels of education, employment and income in an area. And so there will, by definition, be considerable differences in those characteristics among the most advantaged and disadvantaged CDs. This analysis highlights the strength of those differences. Again, the data are age standardised.
Those living in areas in the most disadvantaged 20% of CDs were much more likely to be unemployed (8%) than those residing in other areas (4%).
Fewer than half (47%) of those living in the bottom quintile were employed compared to 61% of people elsewhere, while 46% of those living in the bottom quintile were not in the labour force, compared to about a third (35%) of those living elsewhere.
About one-quarter of those living in the most disadvantaged 20% of CDs had a year 12 or equivalent education, while 45% of people living in other areas had completed year 12. Only 5% of those living in the bottom 20% of CDs had a degree compared to 16% of those living elsewhere. Those living in the bottom 20% were about twice as likely never to have gone to school (2% compared to 1%).
2. Jary, D. and Jary, J. 2000 Collins Dictionary of Sociology, Harper Collins Publishers.
3. Australian Bureau of Statistics 2003, General Social Survey: Summary Results, Australia, cat. no. 4159.0, ABS, Canberra.
4. Australian Bureau of Statistics 2003, Measuring Crime Victimisation, Australia: The Impact of Different Collection Methodologies, cat. no. 4522.0.55.001, ABS, Canberra.
5. Australian Bureau of Statistics 2003, Information Paper: Census of Population and Housing - Socio-Economic Indexes for Areas, Australia 2001, cat. no. 2039.0, ABS Canberra.
6. Australian Bureau of Statistics 2002, National Health Survey, 2001, cat. no. 4364.0, ABS Canberra.
7. Glover, J., Harris, K. and Tennant, S. 1999, A Social Health Atlas of Australia, Public Health Information Development Unit, Commonwealth of Australia.