# Regression risk models for selected census variables

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 rate ratios (or simply 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.

### Which social factors are associated with an increased risk of death by suicide?

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:

• Males had a higher risk of death by suicide than females (HR = 3.12; 95% CI: 2.93 to 3.32).
• Those who were widowed, divorced or separated (HR = 1.95; 95% CI: 1.79 to 2.12), and those who never married (HR = 1.82; 95% CI: 1.69 to 1.96), as well as those in lone person households (HR = 1.72; 95% CI: 1.57 to 1.87), had a higher risk of suicide compared with people who were married or in a de facto relationship and couples with no children, respectively
• The risks of suicide among people who were unemployed; or not in labour force were both higher compared with those who were employed (HR = 1.75; CI: 1.55 to 1.99 and HR = 1.80; CI: 1.64 to 1.99, respectively).
• The risks of suicide among people whose highest educational attainment was secondary education or lower (including no education); or diploma and certificate, were both higher than those who had at least a bachelor degree (HR= 1.27; CI: 1.17 to 1.38 and HR = 1.34; CI: 1.24 to 1.46, respectively).
• Those with lower incomes had higher risk of suicide, with HRs of 1.59 (95% CI:1.45 to 1.74), 1.70 (95% CI: 1.57 to 1.85) and 1.28 (95% CI: 1.19 to 1.38) for low, medium-low and medium-high income earners compared with high income earners, respectively.
• People who worked as machinery operators and drivers (HR = 1.51; 95% CI: 1.36 to 1.69) or labourers (HR = 1.36; 95% CI: 1.22 to 1.52) were more likely to die by suicide compared with managers and professionals.
• Those aged 35 to 44 (HR = 1.25; 95% CI: 1.16 to 1.36) and 45 to 54 (HR = 1.33; 95% CI: 1.22 to 1.44, had a higher risk of death by suicide compared with the reference age group (25 to 34 years); however, there was no difference for those aged 55 to 64 (HR = 0.99; 95% CI: 0.90 to 1.08).

Comparing the results of the univariate and multivariate analyses for Aboriginal and Torres Strait Islander (First Nations) people shows that:

• The univariate analysis estimated that First Nations people had higher risk of suicide, compared with non-Indigenous Australians, with approximately double the hazard rate (HR = 2.05; 95% CI: 1.81 to 2.31). This is consistent with ABS mortality data, which show that the age-standardised rate of death by suicide for First Nations people is roughly twice that of non-Indigenous Australians.
• However, when controlling for the sociodemographic factors included in the multivariate analysis the difference in risk between First Nations people and non-Indigenous Australians was reduced. (HR = 1.31; 95% CI: 1.13 to 1.51).
• The 36% reduction in the hazard ratio for First Nations people between the univariate and multivariate models demonstrates the significant effect of the sociodemographic factors for suicide risk that are included in the multivariate model on First Nations people.

When separated by sex and adjusting for other factors in the models stratified by males and females, important differences were:

• Females who needed help with core activities of daily living had higher risk of suicide compared with females who did not need help with core activities of daily living (Stratified: female model, HR = 2.44; 95% CI: 2.07 to 2.89). There was no significant difference observed for males (Stratified: male model).
• Males who were single parents had higher risk of suicide compared with males in a couple without children (Stratified: male model, HR = 1.27; 95% CI: 1.13 to 1.44); however, there was no difference between females with the same household compositions (Stratified: female model).

This analysis was carried out in consultation with the Australian National University, the University of Melbourne, and Western Sydney University.