1370.0 - Measures of Australia's Progress, 2004  
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Contents >> Multiple disadvantage

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?

It ends by considering how patterns of multiple disadvantage affect different subgroups, and examines the characteristics of places in Australia that experience relatively high levels of disadvantage across a range of key areas.


Measuring disadvantage
Whether or not someone is disadvantaged in an aspect of life depends on a range of circumstances, and there are no absolute definitions of disadvantage in any area with which everyone would agree. We focus on people who are disadvantaged relative to others, not, necessarily, people experiencing absolute disadvantage. We have chosen measures that, where possible, are tied closely to the headline indicators in Measures of Australia’s Progress:
  • Health: whether someone reported their health to be only fair or poor.
  • Education: whether someone was without non-school qualifications.
  • Work: whether someone was unemployed.
  • Financial hardship: where someone’s equivalised gross household income was in the bottom quintile (20%) of incomes.
  • Crime - assault and break-in: whether someone was the victim of actual or threatened violence and/or an actual or attempted break-in during the previous 12 months.
  • Family and community: whether someone felt that, in a time of crisis, they were unable to get support from someone outside their household.

There are, of course, other ways in which disadvantage might be measured or characterised including looking at things like proficiency in English, poor housing, family breakdown and transport difficulties.

Social exclusion
Around the world, researchers are becoming increasingly interested in the concept of social exclusion.1 Social exclusion is a form of social disadvantage encompassing economic and non-economic factors. Excluded individuals and groups are separated from institutions and wider society, and consequently from both rights and duties.2

The General Social Survey
In 2002, the ABS undertook a General Social Survey (GSS).3 The GSS asked a series of questions designed to capture key dimensions of social and economic outcomes for households and individuals. Demographic characteristics include age, sex and marital status. Social outcomes include health, education, crime and family and community support. Economic outcomes include income, wealth and financial stress.

The GSS was designed to support analyses of the linkages between the various dimensions of a person’s social and economic outcomes. Unlike other ABS surveys (such as the National Health Survey or the Survey of Income and Housing Costs) which concentrate on one or two specific ‘areas of social concern’, the GSS was designed to capture information across a range of areas. It is, therefore, a particularly useful data set if one wants to investigate multiple disadvantage. Much of the information in this article comes from the GSS.

Different surveys can yield different results and some of the estimates from the GSS - the crime victimisation rates for example - differ from other ABS figures.4

Disadvantage by household type
Health
Education
and training
Work
Crime
Financial
hardship
Family and
community
Fair/poor
health
Without a
non-school
qualification
Unemployed
Victim of
break-in or
violence
Lowest
income
quintile
Unable to get
support in time
of crisis
Household composition
%
%
%
%
%
%
(selected categories)
Couple only household,
one family
Person aged under 35
6.8
31.3
3.8
19.2
3.6
*3.3
Person aged 35-64
18.7
47.8
2.2
14.3
19.4
6.6
Person aged 65 or over
32.4
62.6
. .
7.5
44.9
6.3

One family household
with dependent children
Couple household
8.0
45.1
3.8
18.7
11.8
5.0
Lone parent
15.7
55.5
7.5
33.1
39.6
5.5

Lone person household
Man aged under 35
7.6
41.4
7.2
35.8
21.5
*4.5
Woman aged under 35
9.4
39.0
*6.2
31.4
21.2
*1.9

Man aged 35-64
25.3
46.0
7.2
25.6
32.9
11.2
Woman aged 35-64
26.4
50.1
4.2
21.0
43.0
3.8
Man aged 65 or over
34.3
60.8
. .
13.2
59.4
7.7
Woman aged 65 or over
34.8
79.9
. .
8.8
69.3
4.7

Person aged under 35
8.3
40.5
6.8
34.1
21.4
*3.5
Person aged 35-64
25.8
47.9
5.8
23.5
37.5
7.8
Person aged 65 or over
34.6
73.9
. .
10.2
66.1
5.6
All people
15.9
50.0
3.9
18.3
19.6
6.0
* estimate has a relative standard error of between 25% and 50% and should be used with caution.
Source: Data available on request, General Social Survey.

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
Health
Education
and training
Work
Crime
Financial
hardship
Family and
community
Fair/poor
health
Without a
non-school
qualification
Unemployed
Victim of
break-in or
violence
Lowest income
quintile
Unable to get
support in time
of crisis
%
%
%
%
%
%
Major cities
14.9
47.8
3.6
18.9
17.4
6.0
Inner regional
17.6
52.4
4.4
17.6
22.9
5.7
Outer regional, remote
and very remote
19.0
58.2
5.0
15.8
26.7
6.4
Australia
15.9
50.0
3.9
18.3
19.6
6.0
Source: Data available on request, General Social Survey.

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.

Health

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.
  • People of all ages in fair or poor health were much less likely to have a non-school qualification, with rates of attainment in the region of 20 percentage points lower than those in excellent health. They were also more likely to have been the victim of an assault or break-in (the difference was most marked among those aged 18-34, where victimisation rates for assaults and break-ins were more than double the rate among people in excellent health). And they were more likely to have income in the lowest 20% of all incomes (the difference was most marked among people aged 35-64).
  • People under 65 in fair or poor health were less likely to feel they could get support in a time of crisis than those in excellent health.
  • Younger people (aged 18-34) in fair or poor health were nearly three times more likely to be unemployed.

Health: Self-assessed health status and disadvantage
Self-assessed health status by age
Excellent
Fair/poor
18-34 years
35-64 years
65+ years
18-34 years
35-64 years
65+ years
Disadvantage
%
%
%
%
%
%
Without a non-school qualification
44.6
36.3
59.2
63.0
58.6
77.2
Unemployed
4.6
2.8
. .
12.9
3.4
. .
Victim of assault or break in
17.8
16.1
5.5
40.2
22.5
10.9
Unable to get support in time of crisis
2.9
5.4
11.7
10.0
11.7
8.6
Lowest income quintile
9.4
9.1
36.6
26.2
35.4
51.3
Source: Data available on request, General Social Survey.

Aboriginal and Torres Strait Islander Peoples

Indigenous Australians are disadvantaged across many areas of social concern relative to non-Indigenous people, and this disadvantage is highlighted elsewhere in this publication (see, for example, the commentaries Health, Financial hardship, Work, Education and training, and Housing). When compared with the non-Indigenous population, the Indigenous population has on average: lower life expectancy, lower income, lower educational attainment, lower labour force participation, and lower levels of home ownership. And Aboriginal and Torres Strait Islander peoples are more likely to commit suicide, be the victim of crime (including homicide) or to be in prison.

For Indigenous Australians there is evidence of greater socioeconomic disadvantage with increasing geographic remoteness. According to the 2001 Census, Indigenous Australians in remote areas have lower rates of educational attendance and labour force participation than those who live in major cities or regional areas. They are also more likely to work in low-skilled occupations and to have low incomes.

In 2001, around one in five Indigenous Australians aged 15-64 years had a non-school qualification. Those with a non-school qualification had far better outcomes in labour force participation, occupation and income, than the majority without a qualification. More extensive information on multiple disadvantage will be available from the forthcoming Indigenous Social Survey (results due in 2004).

Aboriginal and Torres Strait Islander Peoples: Selected indicators by remoteness
Major cities
Inner
regional
Outer
regional
Remote
Very remote
Total
Non-Indigenous
Estimated resident population (‘000s)
138.5
93.0
105.9
40.2
81.0
458.5
18,954.7
%
%
%
%
%
%
%
Proportion (% Indigenous within each area)
1.1
2.3
5.3
12.4
45.4
2.4
Not attending education aged 15-19 years (% of all 15–19)
41.5
39.8
42.3
54.6
72.5
47.9
23.9
No non-school qualification (% of people aged 15 and over)
66.5
69.4
72.3
74.2
83.4
72.1
55.3
Not in the labour force (% of people aged 15–64)
40.9
46.2
47.3
47.3
51.6
45.9
26.7
Low skill occupations (% of employed)
53.1
58.1
60.5
61.6
72.3
59.8
42.5
Proportion of people in lowest income quintile
35.2
43.5
44.9
46.1
63.2
45.0
19.3


Aboriginal and Torres Strait Islander Peoples, aged 15- 64: Labour force status, occupation and income - by educational attainment
No non-school qualification
Has non-school qualification
Total
Men
Women
Total
Men
Women
Total
Men
Women
Total
Labour force
%
%
%
%
%
%
%
%
%
Employed, not CDEP
33.9
26.6
30.0
67.6
61.9
64.8
38.9
32.4
35.6
Employed CDEP(a)
11.6
6.7
9.0
4.4
3.1
3.8
9.5
5.9
7.7
Unemployed
14.8
8.4
11.4
11.5
8.3
10.0
13.6
8.2
10.8
Not in the labour force
39.7
58.3
49.6
16.5
26.7
21.5
37.9
53.5
45.9
Total
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
People (‘000s)
80.3
90.8
171.1
22.0
20.8
42.8
115.5
122.1
237.6
Occupation skill level
%
%
%
%
%
%
%
%
%
High skill
8.4
10.6
9.4
23.8
36.5
29.6
13.0
18.5
15.5
Medium skill
18.6
14.9
16.9
41.4
22.4
32.7
25.4
17.1
21.6
Low skill
73.0
74.5
73.7
34.8
41.1
37.7
61.6
64.3
62.8
Total
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
People (000s)
36.2
30.0
66.2
15.8
13.4
29.2
54.3
45.3
99.6
Income
$
$
$
$
$
$
$
$
$
Median equivalised gross weekly income
341.0
328.0
334.0
502.0
488.0
495.0
350.0
343.0
346.0
(a) The Community Development Employment Project.
Source: Data available on request, Census of Population and Housing 2001.


Education and training: Educational attainment and disadvantage, by age



Educational attainment by age
Degree holders
Without a non-school qualification
18-34 years
35-64 years
65+ years
18-34 years
35-64 years
65+ years
Disadvantage
%
%
%
%
%
%
Fair/poor health
5.1
11.9
23.3
9.0
20.4
40.6
Unemployed
5.4
2.6
..
8.8
3.6
. .
Victim of assault
or break-in
22.4
19.3
9.4
25.2
16.0
7.8
Unable to get
support in time
of crisis
3.8
6.1
7.4
3.7
7.7
7.9
Lowest income quintile
7.8
10.6
32.2
13.9
21.3
46.9
Source: Data available on request, General Social Survey.


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.
  • Those without a non-school qualification were more likely to be unemployed, with unemployment rates three percentage points lower among 18-34 year olds with degrees than among 18-34 year olds without a non-school qualification.

  • Those without a non-school qualification were 70%-75% more likely to be in fair or poor health than their degree-qualified counterparts, and much more likely to have income in the bottom 20% of all incomes. For example, 11% of degree holders aged 35-64, reported income in the lowest quintile. The figure rises to 21% of people without a non-school qualification in that age range.

  • There was no marked difference in the proportions of people with degrees or without a non-school qualification who reported being the victim of a crime or unable to get support.

Work

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.
  • Reporting rates for poor or fair health were highest among 35-64 year olds outside the labour force (38%) compared to 8.5% of employed people in that age range.

  • People with jobs were much more likely than others to have a non-school qualification, and the unemployed were rather more likely than those outside the labour force to have such a qualification.

Work: Labour force status and disadvantage, by age
Labour force status
Employed
Unemployed
Not in the labour force
18-34 years
35-64 years
18-34 years
35-64 years
18-34 years
35-64 years
Disadvantage
%
%
%
%
%
%
Fair/poor health
4.8
8.5
12.9
17.3
14.5
38.0
Without a non-school qualification
44.4
39.4
61.2
53.0
65.1
62.6
Victim of assault or break-in
23.1
18.5
28.6
21.6
24.3
15.3
Unable to get support in time of crisis
2.8
5.7
5.1
14.6
7.7
9.5
Lowest income quintile
4.8
5.8
29.7
59.0
29.7
39.6
Source: Data available on request, General Social Survey.


Financial hardship: Household income and disadvantage, by age
Gross equivalised household income quintile
Highest quintile
Lowest quintile
18-34 years
35-64 years
65+ years
18-34 years
35-64 years
65+ years
Disadvantage
%
%
%
%
%
%
Fair/poor health
4.7
8.7
19.4
17.0
36.2
42.8
Withoutnon-school qualification
35.7
33.6
47.2
63.0
62.5
74.5
Unemployed
2.6
1.0
. .
19.2
11.7
. .
Victim of assault or break-in
22.6
18.4
11.1
29.0
19.3
8.7
Unable to get support in time of crisis
3.4
5.0
5.8
8.3
13.1
7.4
Source: Data available on request, General Social Survey.
    • Crime victimisation rates, however, were higher among the unemployed than other groups, although once again the employed were least likely to experience disadvantage.
    • The employed were, as one would expect, much less likely to have low incomes.
Financial hardship

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.
    • People with income in the bottom quintile were much more likely to be in low health than those in the top quintile. Reported rates of poor or fair health were about four times higher among people on low incomes, than those on high incomes, in the 18-65 age range.
    • People of all ages on low incomes were much less likely to have a non-school qualification, with rates about 30 percentage points lower than among those in the top income range.
    • Crime victimisation rates were higher among 18-34 year olds in the bottom income quintile than in the top quintile, were similar for 35-64 year olds and lower for those 65 and over.
    • Unemployment was, as one would expect, much more prevalent among people on the lowest income.
    • About 13% of 35-64 year olds in the lowest income quintile felt unable to seek support in a time of crisis, compared to only 5% of those in the top quintile.
Financial hardship and the bottom income quintile

The bottom quintile is not necessarily a good indicator of financial hardship for all households. It includes those who may temporarily have a low income (e.g. self-employed) but whose expenditure patterns are similar to those on higher incomes; it includes other households who may be ‘asset rich, income poor’ with expenditure patterns similar to those on higher incomes, and it includes households (such as those with older people) whose expenditure needs may be supported by their income even though that income may be relatively low. There will, therefore, be people in this quintile who are not in financial hardship. Conversely, there may be people in other quintiles who are in financial hardship.
    One, two and three aspects of disadvantage

    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:
      • Whether someone reported their health as fair or poor.
      • Whether someone was the victim of an actual or attempted assault or break-in during the previous 12 months.
      • Whether someone was without a non-school qualification.

    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
    Relative disadvantage: Fair/poor health;
    victim of assault or break-in;
    no non-school qualifications
    Percentage who experience
    One
    disadvantage    		Two
    disadvantages    		All three
    disadvantages
    Selected population subgroup
    %%%
    Family/household typeCouple only: person aged under 3547.39.01.0
    Couple only: person aged 65 or over72.927.42.2
    Couple family, with dependent children58.312.31.2
    One parent family, with dependent children71.827.65.0
    Lone person aged under 3562.417.72.8
    Lone person aged 65 or over83.431.34.0
    Remoteness areaDoes not live in a major city67.819.42.5
    IncomeBottom income quintile80.433.65.1
    Labour force statusUnemployed73.621.13.6
    Family and communityLow social attachment(a)71.724.43.5
    BenchmarkTotal population63.818.32.1
    (a) Having low social attachment is defined, here, as being either unable to ask for small favours, having no support in a time of crisis orhaving less than weekly contact with friends and family.
    Source Data available on request, General Social Survey.

    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

    The data are age standardised to take into account variations in the age profile of the different SEIFA quintiles.


    Socio-Economic Indexes For Areas

    The Population Census provides information on a broad range of social and economic aspects of the Australian population. Nearly fifty questions of social and economic interest are asked in the census. People using census data are often interested not just in these items taken one at a time, but in an overview or summary of a number of related items. Statistical techniques can be used to provide such summaries and the SEIFA indexes are one type of measure.

    The SEIFA indexes summarise data from the census to provide measures of disadvantage and advantage for an area. Variables summarised in the indexes are measures of socioeconomic status and measures of specific aspects of disadvantage, excluding health. The indexes are used to rank areas in terms of their advantage and disadvantage. For the health analysis in this article we use the Index of Relative Socio-Economic Disadvantage from the 1996 Census. The analysis of Collection District characteristics that follows uses the Index of Relative Socio-Economic Advantage/ Disadvantage from the 2001 Census.

    In 2001, Australia was divided into nearly 36,000 Census Collection Districts (CDs).
    Diabetes and disadvantage

    Graph - Diabetes and disadvantage

    Mental and Behavioural problems and
    disadvantage

    Graph - Mental and Behavioural problems and disadvantage

    Heart disease and disadvantage

    Graph - Heart disease and disadvantage

    Cancer and disadvantage

    Graph - 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

    The following analysis examines characteristics of Australia's more disadvantaged neighbourhoods, and uses data from the 2001 SEIFAs index of advantage/disadvantage. We compare average educational attainment, labour force status, and equivalised household income across SEIFA.

    Proportion of people and labour force status,
    SEIFA(a) top and bottom

    Graph - Proportion of people and labour force status, SEIFA(a) top and bottom

    Proportion of people and years of schooling, SEIFA(a) top and bottom


    SEIFA areas
    Years of schooling and
    educational
    qualification
    Top 80%
    Bottom
    20%
    No school
    1
    2
    Year Eight
    9
    16
    Year Nine
    8
    13
    Year Ten
    26
    32
    Year Eleven
    11
    11
    Year Twelve
    45
    26
    Degree
    16
    5


    Proportion of people and equivalised
    weekly household gross income, SEIFA(a)
    top and bottom

    Graph - 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%).

    Average weekly equivalised household gross income was $385 for those living in areas in the bottom 20% of CDs. For those living in the remaining 80% of CDs, average weekly equivalised income was $618. About two-fifths of those living in the top 80% of CDs had weekly equivalised income over $600, and a quarter of people in those CDs had an income over $800 a week. About 60% of those living in the most disadvantaged 20% of CDs had a weekly equivalised income less than $400. About 15% of people in these areas had an income over $600 a week and fewer than 8% had an income greater than $800 a week.

    Endnotes

      1. Saunders, P., 2003 Can social exclusion provide a new framework for measuring poverty?, SPRC Discussion Paper No. 127, Social Policy Research Centre, University of New South Wales, Sydney.

      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.




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