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Monash University media release

First-of-its-kind study: Socioeconomic status determines how many years Australians live in good health

Monash University

Monash University media release
Monash University media release

Australia’s most socioeconomically disadvantaged population lives an average of 7.6 years less than the least disadvantaged population, and when quality of life is incorporated these gaps are even more profound.

Using data from the 2022 Australian Bureau of Statistics and Household, Income and Labour Dynamics in Australia HILDA survey, a first-of-its-kind study from Monash University published in Value in Health, has presented a summary of age and sex-specific ‘life expectancy’ and ‘quality-adjusted life expectancy’ based on socioeconomic status and location.

Quality-adjusted life expectancy (QALE) is a measure of quality of life in a health context. For example, one QALE year equates to one year in good health, so if your QALE years stop at 45 then your remaining years will involve living with chronic conditions and your overall life expectancy is reduced.

The study found that Australia's most socioeconomically deprived group at birth are estimated to experience 10.9 fewer QALE years than those in the most advantaged population for men and 12.3 fewer QALE years for women.

The study’s lead author, clinical pharmacist and Monash Centre for Medicine Use and Safety (CMUS) PhD candidate in Health Economics, Sheridan Rodda, said this is the first time an Australian study has shed light on the staggering gap in national QALE based on socioeconomic status and where an individual resides. 

“A baby boy born in the most socioeconomically disadvantaged group in Australia can expect 45.9 years of healthy life, compared to the nation's least disadvantaged who can expect 56.8 quality health years,” Ms Rodda said.

“The gap with women is even more staggering. If you are among Australia’s most disadvantaged women then your QALE at birth is estimated to be 41.9, compared with the least disadvantaged women who have an estimated  QALE of 54.2 years – an eye opening 12.3 year disparity.

“While women have an overall higher life expectancy than men, they generally report lower health-related quality of life – they are living longer but with chronic conditions and these gaps based on socioeconomic status remain unacceptably high,” Ms Rodda concluded.

The remoteness of an individual's location is also associated with overall health status. The study found that men living in inner regional to remote areas live 2.6 years less than men in major cities, while the gap for women is 2.1 years. 

By including quality of life, the QALE is even further impacted based on location, with men in remote and regional locations experiencing 3.7 less quality-adjusted life years compared with men in major cities, while the gap for women is 3.4 years.

Professor Zanfina Ademi, a senior author of the study, CMUS Health Economist and Head of the Health Economics and Policy Evaluation Research (HEPER) group within the Monash Institute of Pharmaceutical Sciences, said the study demonstrates major inequalities associated with socioeconomic disadvantage and remoteness for both life expectancy and QALE.

“This is the first time the distribution of QALE across equity subgroups, stratified by sex and age, has been reported for Australia, and the results are really quite astonishing,” Professor Ademi said. 

“This study has provided a snapshot of Australian health status and the distribution of health across two equity-relevant variables, opening up new opportunities for the evaluation of targeted interventions to address these disparities. The study notes that the results do not reflect disparities across other equity relevant strata such as non-binary gender identities, First Nations people or those disadvantaged due to ethnicity or migrant status. 

“There is considerable scope and justification to similarly investigate disparities among these groups in the future,” Professor Ademi said. 

“Equity-informative health technology assessments are still in their early stages. However, this study represents a crucial first step in advancing this approach. In particular, QALE estimates can serve as a foundation baseline for future equity-informative health technology assessments in Australia to inform future decision-making and health policy.”

-ENDS-

Research
Sheridan E. Rodda, Jedidiah Morton, Melanie Lloyd, Richard Norman, Zanfina Ademi.

Read the full paper in Value in Health, ‘Quality-Adjusted Life Expectancy by Socioeconomic Disadvantage and Remoteness Area; Population norms for Australia’.

DOI: 10.1016/j.jval.2025.02.016

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Declaration
This study was supported by a Monash University Graduate Scholarship, an Australian Government Research Training (RTP) Scholarship and a National Health and Medical Research Council Ideas Grant Application (ID: 2012582). The funders had no role in the design and conduct of the study; data collection, management, analysis, and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.

 

Appendix

IRSD quintile group

Male

Female

Combined

 

Life expectancy (years)

Quintile 1 (most disadvantaged)

76.3

81.3

78.7

Quintile 2

79.6

83.7

81.7

Quintile 3

81.1

85.3

83.2

Quintile 4

82.9

86.2

84.6

Quintile 5

84.7

87.8

86.3

Absolute difference

8.4

6.5

7.6

Relative difference

0.11

0.08

0.10

 

Quality-adjusted life expectancy (years)

Quintile 1 (most disadvantaged)

45.9 (44.1, 47.7)

41.9 (40.3, 43.6)

43.9 (42.6, 45.2)

Quintile 2

48.6 (46.8, 50.5)

47.0 (44.4, 49.8)

47.8 (46.0, 49.7)

Quintile 3

52.1 (49.9, 54.4)

49.9 (48.0, 51.7)

51.0 (49.4, 52.6)

Quintile 4

54.5 (52.5, 56.6)

52.3 (50.1, 54.5)

53.4 (51.9, 54.9)

Quintile 5

56.8 (54.5, 59.2)

54.2 (52.6, 55.9)

55.6 (54.1, 57.1)

Absolute difference

10.9 (10.4, 11.5)

12.3 (12.3,12.3)

11.7 (11.5, 11.9)

Relative difference

0.24 (0.24, 0.24)

0.29 (0.29, 0.29)

0.27 (0.26, 0.27)

Absolute gap = Q5 - Q1

 

 

 

Relative gap = (Q5/Q1)-1

 

 

 

 

 

 

 

Remoteness area group

Male

Female

Combined

 

Life expectancy (years)

Major cities

81.1

85.0

83.1

Inner regional

79.9

84.0

81.9

Outer regional, remote and very remote

78.5

82.9

80.5

Absolute difference

2.6

2.1

2.6

Relative difference

0.03

0.03

0.03

 

Quality-adjusted life expectancy (years)

Major cities

52.2 (50.9, 53.4)

49.2 (48.1, 50.4)

50.8 (49.8, 51.7)

Inner regional

49.7 (48.0, 51.4)

48.3 (46.6, 49.9)

49.0 (47.8, 50.2)

Outer regional, remote and very remote

48.5 (45.8, 51.3)

45.8 (42.0, 49.8)

47.0 (44.2, 49.7)

Absolute difference

3.7 (2.1, 5.1)

3.4 (0.6, 6.1)

3.8 (2.0, 5.6)

Relative difference

0.08 (0.04, 0.11)

0.07 (0.0, 0.15)

0.08 (0.04, 0.1)

Absolute gap = major cities - outer regional and remote

 

Relative gap = (major cities/outer regional and remote) -1

 

95% confidence intervals provided in parentheses. Uncertainty not provided for life expectancy as there is no sampling error.

 

IRSD; Index of Relative Socioeconomic Disadvantage

 

         

 

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