Download all data pages
PDF 11MB
Data

Social and economic factors associated with suicide in Australia: A focus on individual income

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:

  • What is the relationship between social factors and death by suicide (controlling for economic factors)?
  • Is income uncertainty associated with death by suicide (controlling for social) factors?
  • Are periods of continuous unemployment associated with death by suicide, (controlling for economic and social factors)? 

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.

Adjusted expected probability of suicide by income and income uncertainty quintiles, 2012 to 2016

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 probability of dying by suicide is greater in the lowest income group compared to the highest income group. This holds regardless of variation in income (income uncertainty). For example, for a specific income uncertainty quintile, a person with the lowest income will have a higher probability of dying by suicide compared to a person with a higher income who belongs to the same income uncertainty quintile.
  • Those with higher income uncertainty (highest income uncertainty quintile), had higher probability of suicide death relative to those with lower income uncertainty (lowest income uncertainty quintile), across all income levels.
  • For those with the lowest income uncertainty (income uncertainty quintile 1), an increase in income from the lowest to the highest quintile (from income level quintile 1 to quintile 5) reduced the expected probability of suicide by 74% (from 0.009 to 0.002).
  • For those with the highest income uncertainty, an increase in income from the lowest to the highest quintile (from income quintile 1 to quintile 5) reduced the expected probability of suicide by 72% (from 0.021 to 0.006).
  • For those in the lowest income group (income quintile 1), an increase in income uncertainty from the lowest to the highest quintile (from income uncertainty quintile 1 to quintile 5), increased the expected probability of suicide by 126% (from 0.009 to 0.021).
  • For those in the highest income group (income quintile 5), an increase in income uncertainty from the lowest to the highest quintile (from income uncertainty quintile 1 to quintile 5) increased the expected probability of suicide death by 148% (from 0.002 to 0.006).

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.

Estimated odds ratio by social & economic factor associated with suicide, 2012 to 2016

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:

  • The odds of dying by suicide were 1.91 times higher (95% CI 1.62 to 2.25) among those in the highest income uncertainty group, compared to those with the lowest fluctuation in income.
  • People who were unemployed throughout the period had higher odds of death by suicide. The odds of dying by suicide were 1.33 times higher (95% CI 1.25–1.40) for the unemployed group compared to those who had no periods of unemployment.
  • The odds of death by suicide were higher among those who experienced longer periods of unemployment. Relative to those with no periods of unemployment, the odds of dying by suicide were 1.96 (95% CI 1.61–2.57) for those unemployed for 5 years, 2.03 (95% CI 1.61–2.57) for those unemployed for 4 years, 1.75 (95%CI 1.36–2.26) for those unemployed for 3 years and 1.57 times higher (95% CI 1.21–2.05) for those unemployed for 2 years.

After separating the regression model by sex and controlling for other factors, the results show that:

  • Males whose educational attainment was a diploma/certificate or year 12 and below, had 1.4 times higher odds of death by suicide compared to males with a bachelor’s degree or higher. There was no statistically significant difference for educational attainment among females.
  • The odds of death by suicide decreased with increasing income among females. Females in income quintiles 2 and 3 had lower odds (0.71 and 0.53, respectively) of death by suicide compared to females in income quintile 1.

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:

  • For those whose income reduced, the odds of dying by suicide increased with as the level of income uncertainty increased (i.e., greater reductions in income) Compared to those with the smallest reduction in income (1st income uncertainty quintile), the odds of dying by suicide was 2.81 times higher (95% CI 2.18–3.59) for those in the highest income uncertainty quintile, 2.16 (95% CI 1.70–2.75) for those in the 4th income uncertainty quintile and 1.55 (95% CI 1.21–1.99) for those in the 3rd income uncertainty quintile. 
  • For those whose income increased, the odds of dying by suicide was higher among those with higher levels of income uncertainty (i.e., greater increases in income). Relative to those with the smallest increase in income (1st income uncertainty quintile), the odds of dying by suicide were 1.59 times higher (95% CI 1.21–2.09) for those in the highest income uncertainty quintile and  were 1.26 (95% CI 1.02–1.65) for those in the 4th income uncertainty quintile. There was no statistically significant differences for the odds of dying by suicide in the 2nd and 3rd income uncertainty quintiles compared to those with the lowest income uncertainty (1st income uncertainty quintile).

The full report Social and Economic Factors associated with Suicide in Australia: A Focus on Individual Income can be found on Releases.