Skip to main content Accessibility help
×
×
Home

Quantifying the effect of early retirement on the wealth of individuals with depression or other mental illness

  • Deborah J. Schofield (a1), Rupendra N. Shrestha (a1), Richard Percival (a2), Simon J. Kelly (a2), Megan E. Passey (a3) and Emily J. Callander (a4)...

Abstract

Background

In addition to the health burden caused by mental illnesses, these conditions contribute to economic disadvantage because of their impact on labour force participation.

Aims

To quantify the cost of lost savings and wealth to Australians aged 45–64 who retire from the labour force early because of depression or other mental illness.

Method

Cross-sectional analysis of the base population of Health&WealthMOD, a microsimulation model built on data from the Australian Bureau of Statistics' Survey of Disability, Ageing and Carers and STINMOD, an income and savings microsimulation model.

Results

People who are not part of the labour force because of depression or other mental illness have 78% (95% CI 92.2–37.1) and 93% (95% CI 98.4–70.5) less wealth accumulated respectively, compared with people of the same age, gender and education who are in the labour force with no chronic health condition. People who are out of the labour force as a result of depression or other mental illness are also more likely to have the wealth that they do have in cash assets, rather than higher-growth assets such as superannuation, home equity and other financial investments.

Conclusions

This lower accumulated wealth is likely to result in lower living standards for these individuals in the future. This will compound the impact of their condition on their health and quality of life, and put a large financial burden on the state as a result of the need to provide financial assistance for these individuals.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Quantifying the effect of early retirement on the wealth of individuals with depression or other mental illness
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Quantifying the effect of early retirement on the wealth of individuals with depression or other mental illness
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Quantifying the effect of early retirement on the wealth of individuals with depression or other mental illness
      Available formats
      ×

Copyright

Corresponding author

Deborah J. Schofield, NHMRC Clinical Trials Centre, 92–94 Parramatta Road, Camperdown NSW 1450, Australia. Email: deborah.schofield@ctc.usyd.edu.au

Footnotes

Hide All

Declaration of interest

None.

Footnotes

References

Hide All
1 Boston Consulting Group. Improving Mental Health Outcomes in Victoria: The Next Wave of Reform. Boston Consulting Group, 2006.
2 Patel, A, Knapp, M. Costs of mental illness in England. Men Health Res Rev 1998; 5: 410.
3 Department of Health and Ageing. National Mental Health Report 2007: Summary of Twelve Years of Reform in Australia's Mental Health Services under the National Mental Health Strategy, 1993–2005. Commonwealth of Australia, 2007.
4 Waghorn, G, Lloyd, C. The Employment of People with a Mental Illness: A Discussion Document Prepared for the Mental Illness Fellowship of Australia. University of Queensland, 2005.
5 Schofield, DJ, Shrestha, RN, Passey, ME, Earnest, A, Fletcher, SL. Chronic disease and labour force participation among older Australians. Med J Aust 2008; 189: 447.
6 Miles, D. Modelling the impact of demographic change upon the economy. Econ J 1999; 109: 136.
7 Bloom, DE, Canning, D. The health and wealth of nations. Science 2000; 287: 1207–9.
8 Sala-i-Martín, X. On the health poverty trap. In Health and Economic Growth: Findings and Policy Implications (eds Lopez-Casasnovas, G & Currais, L). The MIT Press, 2005.
9 Zhang, J, Zhang, J. The effect of life expectancy on fertility, saving, schooling and economic growth: theory and evidence. Scand J Econ 2005; 107: 4566.
10 Brazenor, R. Disabilities and labour market earnings in Australia. Aust J Labour Econ 2002; 5: 319–34.
11 Rosen, HS, Wu, S. Portfolio choice and health status. J Financ Econ 2004; 72: 457–84.
12 Wenzlow, AT, Mullahy, J, Robert, SA, Wolfe, BL. An Empirical Investigation of the Relationship between Health and Wealth using the Survey of Consumer Preferences. Institute for Research on Poverty, University of Wisconsin-Madison, 2004.
13 Australian Bureau of Statistics. Information Paper – Basic Confidentialised Unit Record File: Survey of Disability, Ageing and Carers 2003 (reissue). Australian Bureau of Statistics, 2005.
14 Lambert, S, Percival, R, Schofield, D, Paul, S. An Introduction to STINMOD: A Static Microsimulation Model. Report No.: STINMOD Technical Paper No. 1. NATSEM, 1994
15 World Health Organization. The ICD–10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. WHO, 1992.
16 Organisation for Economic Co-operation and Development. Purchasing Power Parities: Consumer Price Levels. OECD, 2010.
17 Vos, T, Haby, M, Barendregt, J, Kruijshaar, M, Corry, J, Andrews, G. The burden of major depression avoidable by longer-term treatment strategies. Arch Gen Psychiatry 2004; 61: 1097.
18 Begg, S, Vos, T, Barker, B, Stevenson, C, Stanley, L, Lopez, AD. The Burden of Disease and Injury in Australia 2003. Australian Institute of Health and Welfare, 2007.
19 Australian Institute of Health and Welfare. Health System Expenditure on Disease and Injury in Australia 2000–01. AIHW, 2004.
20 Andrews, G, Hall, W, Teesson, M, Henderson, S. The Mental Health of Australians. Commonwealth Department of Health and Aged Care, 1999.
21 Centrelink Performance and Information Branch. Data Request BI3268: Health Conditions associated with Sickness Benefits and Disability Support Pension, 13 Jan 2006. Centrelink Performance and Information Branch, 2006.
22 Katona, C, Livingston, G. How well do antidepressants work in older people? A systematic review of number needed to treat. J Affect Disord 2002; 69: 4752.
23 Barretta, B, Byforda, S, Knappa, M. Evidence of cost-effective treatments for depression: a systematic review. J Affect Disord 2005; 84: 113.
24 Jonsson, B, Bebbington, PE. What price depression? The cost of depression and the cost-effectiveness of pharmacological treatment. Br J Psychiatry 1994; 164: 665–73.
25 Doyle, JJ, Casciano, J, Arikian, S, Tarride, J, Gonzalez, MA, Casciano, R. A multinational pharmacoeconomic evaluation of acute major depressive disorder (MDD): a comparison of cost-effectiveness between venlafaxine, SSRIs and TCAs. Value Health 2001; 4: 1631.
26 Cagetti, M. Wealth accumulation over the life cycle and precautionary savings. J Bus Econ Statist 2003; 21: 339–53.
27 Caner, A, Wolff, EN. Asset poverty in the United States 1984-99: evidence from the panel study of income dynamics. Rev Income Wealth 2004; 50: 493518.
28 Dvornak, N, Kohler, M. Housing wealth, stockmarket wealth and consumption: a panel analysis for Australia. Econ Rec 2007; 83: 117–30.
29 Covinsky, KE, Goldman, L, Cook, EF, Oye, R, Desbiens, N, Reding, D, et al. The impact of serious illness on patients' families. JAMA 1994; 272: 1839–44.
30 Swoboda, SM, Lipsett, PA. Impact of a prolonged surgical critical illness on patients' families. Am J Critical Care 2002; 11: 459–66.
31 Council of Australian Governments. National Action Plan on Mental Health 2006-2011. COAG, 2006.
32 Mental Health Division Department of Health. New Horizons: A Shared Vision for Mental Health. UK Department of Health, 2009.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

The British Journal of Psychiatry
  • ISSN: 0007-1250
  • EISSN: 1472-1465
  • URL: /core/journals/the-british-journal-of-psychiatry
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed

Quantifying the effect of early retirement on the wealth of individuals with depression or other mental illness

  • Deborah J. Schofield (a1), Rupendra N. Shrestha (a1), Richard Percival (a2), Simon J. Kelly (a2), Megan E. Passey (a3) and Emily J. Callander (a4)...
Submit a response

eLetters

No eLetters have been published for this article.

×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *