Does socioeconomic status affect risk of intentional self-harm?
Rates of hospitalisations for intentional self-harm tend to be higher for those living in lower socioeconomic (more disadvantaged) areas.
- the rate for the most disadvantaged areas (Quintile 1) was 135 hospitalisations per 100,000 population, which is 1.5 times higher than the rate for the least disadvantaged areas (Quintile 5; 90 per 100,000 population).
A similar pattern was seen in suicide rates in 2020, see Suicide by socioeconomic areas.
How have rates of intentional self-harm hospitalisations changed for socioeconomic areas?
From 2012–13 to 2020–21:
- the highest proportion of intentional self-harm hospitalisations was for people living in the lowest socioeconomic (most disadvantaged) areas; this proportion has remained relatively stable over the period at around 25%
- rates for males in the lowest socioeconomic areas, Quintile 1 and 2, increased from 115 and 98 hospitalisations per 100,000 to 129 and 110 in 2016–17, respectively, and then decreased to 98 and 79 in 2020–21
- rates for females in the lowest (most disadvantaged) socioeconomic areas also increased from 179 in 2012–13 to 206 in 2016–17 and then decreased to 171 in 2020–21.
For both males and females, the highest age-specific rates of hospitalisations between 2012–13 and 2020–21 were recorded for those aged 25–44 in the lowest socioeconomic areas (Quintile 1), with the highest age-specific rates recorded for females in this age group.
- there was an increase in hospitalisations for all socioeconomic areas in females aged 0-24 from 2019–20 to 2020–21
- rates for females aged 25–44 in Quintile 1 increased from 243 per 100,000 population in 2012–13 to 272 in 2016–17 before falling to 206 in 2020–21
- rates for males aged 25–44 in Quintile 1 ranged from 197 in 2012–13 to 213 in 2016–17 then fell to 162 in 2020–21.
An increase in the rate of hospitalisations due to intentional self-harm for all socioeconomic areas was reported in 2016–17, which may be due to increases in hospitalisations in 3 states. Variation in hospital admission policy and practices between states and territories may have contributed to differences in the reporting of hospitalisation data. For further information, see the data quality statement.