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.
Generally, results from the modelling show important differences in the relationship between deaths by suicide and the different socioeconomic factors, relative to comparison groups, as seen in the forest plot below.
Univariate and multivariate competing risk models were used (Fine and Gray, 1999). Results of sex stratified models are also reported, these are multivariate models split by males and females to investigate the interactions within the sex.
See Technical notes for further information on the data and methods used.
Estimates presented are hazard ratios for the group of interest compared with a reference group. Reference group values are indicated as the dotted line at 1. A hazard ratio (HR) indicates how many times higher the probability of an event is in one group of people with a particular characteristic than in another group without that characteristic, after adjusting for other factors in the model. The size of the reported hazard ratio indicates the strength of the relationship a social factor has to deaths by suicide, relative to the reference group.
Ninety-five per cent (95%) confidence intervals are also presented to indicate the statistical precision and significance. The result is interpreted as having a statistically significant impact (that is, not due to chance) if the interval does not cross the value of 1.
This chart shows the output from competing-risks regression models to explore the association between socioeconomic factors and deaths by suicide. For simplicity and ease of understanding, the model estimates are reported as hazard ratios.
Results from four models: univariate, multivariate, stratified: males and stratified: females can be displayed in this chart. The univariate model does not adjust for the other socioeconomic factors, while multivariate model adjusts for all other factors. The stratified: males and stratified: females models are multivariate models for only males and females, respectively.
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, associated factors such as 'mental health status', 'acute or chronic substance use', and 'past-history of self-harm' are not included in this modelling.
Results of the multivariate analysis showed that from September 2011 to December 2017, when adjusting for other factors in the model:
When separated by sex and adjusting for other factors, important differences were:
This analysis was carried out in consultation with the Australian National University, the University of Melbourne and the University of Western Sydney.
Austin PC & Fine JP 2017. Practical recommendations for reporting Fine‐Gray model analyses for competing risk data. Statistics in Medicine 36: 4391–4400.
Australian Bureau of Statistics (ABS) 2021. Table 4. Estimated Resident Population, States and Territories (Number) [time series spreadsheet], National, state and territory population, accessed 24 August 2021.
ABS 2019. Microdata: Multi-Agency Data Integration Project, Australia, ABS website, accessed 17 August 2021.
ABS 2016. Research Paper: Death Registrations to Census Linkage Project - A Linked Dataset for Analysis, Mar 2016, ABS website, accessed 17 August 2021.
Biddle N & Marasinghe D 2021. Using census, social security and tax data from the Multi-Agency Data Integration Project (MADIP) to impute the complete Australian income distribution. Tax and Transfer Policy Institute – Working Paper 8/2021.
Fine J & Gray R 1999. A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association 94(446): 496-509.
Hernan MA 2010. The hazards of hazard ratios. Epidemiology 21(1): 13–15.
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