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

Br J Psychiatry. 2011 Feb;198(2):123-8. doi: 10.1192/bjp.bp.110.081679.

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.

MeSH terms

  • Australia / epidemiology
  • Cost of Illness*
  • Depression / economics*
  • Depression / epidemiology
  • Employment / economics
  • Employment / psychology
  • Employment / statistics & numerical data*
  • Epidemiologic Methods
  • Female
  • Humans
  • Income*
  • Male
  • Mental Disorders / economics*
  • Mental Disorders / epidemiology
  • Middle Aged
  • Quality of Life
  • Retirement / economics
  • Retirement / psychology*
  • Retirement / statistics & numerical data
  • Social Security / economics
  • Social Security / statistics & numerical data