Caution: Some people may find parts of this content confronting or distressing.
Please carefully consider your needs when reading the following information about suicide and self-harm. If this material raises concerns for you contact Lifeline on 13 11 14, or see other ways you can seek help.
The information included here places an emphasis on data, and as such, can appear to depersonalise the pain and loss behind the statistics. The AIHW acknowledges the individuals, families and communities affected by suicide each year in Australia.
Aboriginal and Torres Strait Islander readers are advised that information relating to Indigenous suicide and self-harm is included.
The AIHW supports the use of the Mindframe guidelines on responsible, accurate and safe suicide and self-harm reporting. Please consider these guidelines when reporting on statistics on the monitoring of suicide and self-harm.
Researchers from the Australian National University’s Centre for Social Research and Methods (CSRM), in close collaboration with the AIHW, have extended the analysis Regression risk models for selected census variables.
The CSRM researchers set out to address three key questions:
Modelling approaches are used to investigate the association of socioeconomic factors with suicide deaths, with a focus on changes to individuals' income (income uncertainty) and employment status over time.
Visit Technical notes for further information on the data and analytical methods used.
The modelling carried out includes only a subset of known factors that may influence deaths by suicide. Results from this analysis need to be interpreted with caution and within the context of the information provided. For example, due to data quality and availability, known associated factors such as ‘mental health status’ , ‘acute or chronic substance use’, and ‘past-history of self-harm’ are not included in this modelling.
The results from the analysis, confirmed findings from the Regression risk models for selected census variables study. It also produced new findings into associations between deaths by suicide, and income uncertainty.
This bar chart shows the expected probability of suicide by income and income uncertainty quintile, after adjusting for other social factors. Users can select or deselect income and income uncertainty quintiles to display in the bar chart. The chart shows a pattern of increasing probability with increasing levels of income uncertainty in each income quintile. Income quintile 1 (lowest income) has higher expected probability levels across the income uncertainty quintiles, compared to other income quintiles. Conversely, income quintile 5 (highest income) has the lowest expected probability levels.
Results of the analysis showed that from 2012 to 2016, when adjusting for other factors in the model:
The results of this analysis also reports sex and income difference stratified models. These multivariable models are separated by males, females, those who experienced an increase in income and those who experienced a decrease in income.
The estimates presented are odds ratios for the group of interest compared with a reference group. An odds ratio represents the estimated odds of death by suicide (the outcome) by a socioeconomic factor of interest (the exposure), compared to the odds of suicide occurring in the reference group (no exposure to factor of interest), after adjusting for all the other socioeconomic factors in the model.
Select the button at the top of this visualisation for more information on how to interpret.
This forest plot shows the results of a multivariable regression model, estimating the odds ratio (OR) of death by suicide by socioeconomic factor. The OR provides an estimate of the odds of suicide in group of people with a factor of interest, compared to a group without the factor of interest (the reference group). The estimates are adjusted for each variable in the model. The following factors had the highest adjusted odds of suicide compared to their reference group, indicating higher odds of suicide: income uncertainty quintile 5 (highest income uncertainty), continuous unemployment of 4 years, educational attainment at diploma or certificate level, being Indigenous, requiring assistance with daily tasks and living alone. The following factors had the lowest adjusted odds of suicide compared to their reference group, indicating lower odds of suicide: absolute income quintile 5 (highest income), continuous unemployment years of 1 year, being female and being aged below 18 years.
After adjusting for all the factors in the model, between 2012–2016:
After separating the regression model by sex and controlling for other factors, the results show that:
Stratified regression modelling was undertaken to investigate whether the effects of income uncertainty was different for those who experienced a reduction in income compared to those that experienced an increase in income. After adjusting for the other factors in the model, results from these models suggest that, from January 2012 to December 2016:
The full report Social and Economic Factors associated with Suicide in Australia: A Focus on Individual Income can be found on Releases.
Choi, S.B., Lee, W., Yoon, J.H., Won, J.U. and Kim, D.W., 2017. Risk factors of suicide attempt among people with suicidal ideation in South Korea: a cross-sectional study. BMC public health, 17(1), pp.1-11.
Chuanc, H.L. and Huang, W.C., 1997. Economic and social correlates of regional suicide rates: A pooled cross-section and time-series analysis. The journal of socio-economics, 26(3), pp.277-289.
Collewet, M. and Loog, B., 2014. The effect of weekly working hours on life satisfaction. In Technical Report, Working
Daly, M.C. and Wilson, D.J., 2009. Happiness, unhappiness, and suicide: An empirical assessment. Journal of the European Economic Association, 7(2-3), pp.539-549.
Dobbs, I.M., 1988. Risk Aversion, Gambling and the Labour‐Leisure Choice. Scottish Journal of Political Economy, 35(2), pp.171-175.
Durkheim, E., 2005. Suicide: A study in sociology. Routledge.
Ford, J.M. and Kaserman, D.L., 2000. Suicide as an indicator of quality of life: evidence from dialysis patients. Contemporary Economic Policy, 18(4), pp.440-448.
Hamermesh, D.S. and Soss, N.M., 1974. An economic theory of suicide. Journal of Political Economy, 82(1), pp.83-98.
Koo, J. and Cox, W.M., 2008. An economic interpretation of suicide cycles in Japan. Contemporary Economic Policy, 26(1), pp.162-174.
Lee, C. and Hong, J., 2017. Income, Health, and Suicide: Evidence from Individual Panel Data in Korea. Seoul Journal of Economics, 30(4).
Lee, S.U., Oh, I.H., Jeon, H.J. and Roh, S., 2017. Suicide rates across income levels: retrospective cohort data on 1 million participants collected between 2003 and 2013 in South Korea. Journal of epidemiology, 27(6), pp.258-264.
Lee, S.U., Roh, S., Kim, Y.E., Park, J.I., Jeon, B. and Oh, I.H., 2017. Impact of disability status on suicide risks in South Korea: analysis of national health insurance cohort data from 2003 to 2013. Disability and health journal, 10(1), pp.123-130.
Marcotte, D.E. and Zejcirovic, D., 2020. Economics of suicide. Handbook of Labor, Human Resources and Population Economics, pp.1-26.
Marcotte, D.E., 2003. The economics of suicide, revisited. Southern Economic Journal, 69(3), pp.628-643.
Mitchell, R.J. and Cameron, C.M., 2018. Self-harm hospitalised morbidity and mortality risk using a matched population-based cohort design. Australian & New Zealand Journal of Psychiatry, 52(3), pp.262-270.
Mitrou, F., Gaudie, J., Lawrence, D., Silburn, S.R., Stanley, F.J. and Zubrick, S.R., 2010. Antecedents of hospital admission for deliberate self-harm from a 14-year follow-up study using data-linkage. BMC psychiatry, 10(1), pp.1-11.
Molina, J.A. and Duarte, R., 2006. Risk determinants of suicide attempts among adolescents. American Journal of Economics and Sociology, 65(2), pp.407-434.
Neumayer, E., 2003. Socioeconomic factors and suicide rates at large-unit aggregate levels: a comment. Urban Studies, 40(13), pp.2769-2776.
Rodriguez, A., 2006. Inequality and suicide mortality: A cross-country study (No. 13/2006). Development Research Working Paper Series.
We'd love to know any feedback that you have about the AIHW website, its contents or reports.
The browser you are using to browse this website is outdated and some features may not display properly or be accessible to you. Please use a more recent browser for the best user experience.