Developmentally vulnerable on one or more domains

By State

The proportion of students who are developmentally vulnerable in 1 or more Australian Early Development Census (AEDC) domains is shown in the line chart below, illustrating trends from 2009 to 2024.

Click or select a state to view its corresponding data. Clicking on a state will toggle its visibility. Double-click on a state to display only that state’s line.

• The proportion of children aged 4-6 years who were developmentally vulnerable on 1 or more AEDC domains has remained relatively stable in South Australia over previous collection cycles.
• Since 2012, the proportion of children who are developmentally vulnerable has remained higher in South Australia than the national average.
• In 2024, 24.5% of South Australian children in their first year of full-time school were developmentally vulnerable on one or more AEDC domains, compared with 23.5% nationally. This rate was lower than those recorded in the Northern Territory, Australian Capital Territory, Tasmania, and Queensland for the same period.

By Statistical Area Level 3 (2024)

In the map above, regions are split by Statistical Area Level 3 (SA3) and shaded according to the proportion of children identified as developmentally vulnerable in one or more domains in 2021 under the AEDC. Darker shades indicate a higher level of vulnerability compared with the state average. Click or search a region on the plot to view more detailed information.

In 2024:

• Outback – North and East experienced the largest increase relative to the state average, with rates of developmental vulnerability in 1 or more domains 72% higher than the state average.
• Prospect – Walkerville showed the smallest difference, with rates 51% lower than the state average.

By Socio-Economic Indexes for Areas (SEIFA) and Remoteness (2024)

• Children in South Australia from the least disadvantaged areas consistently show lower levels of developmental vulnerability across 2018, 2021, and 2024, with a clear and stable gradient across SEIFA (IRSD) categories. In 2024, approximately 16% of children in the least disadvantaged areas were developmentally vulnerable in one or more domains, compared to around 35% in the most disadvantaged areas, highlighting a persistent socioeconomic gap.
• A similar pattern is observed by remoteness, where children living in more remote areas generally experience higher levels of developmental vulnerability compared to those in metropolitan and regional areas. In 2024, about 44% of children in very remote areas were developmentally vulnerable in one or more AEDC domains, significantly higher than the state average (24.4%), while children in major cities reported rates close to the average (around 24%).
  However, an exception is observed for remote areas. While developmental vulnerability was higher in remote South Australia in 2018 compared to metropolitan and regional areas, it declined in 2021 and remained relatively lower in 2024. This pattern deviates from the broader national trend, where higher remoteness is typically associated with increased developmental vulnerability. A similar shift has also been observed in Western Australia, suggesting that the relationship between remoteness and vulnerability may vary across states rather than follow a uniform pattern.

Data Source: Australian Early Development Census

Developmentally vulnerable on one or more domains

In South Australia, the proportion of Aboriginal children identified as developmentally vulnerable on one or more Australian Early Development Census (AEDC) domains has remained consistently higher than the state average (24.5% in 2024). While the percentage rose slightly from 47.1% in 2021 to 48.8% in 2024 (compared to 42.3% to 42.5% nationally), this represents no significant change over the period.

Data Source: Closing the Gap Data Dashboard, Socio-economic outcome area 4 – Aboriginal and Torres Strait Islander children thrive in their early years (Productivity Commission)

Background:

The data are presented by state, Statistical Area Level 3 (SA3), socio-economic status (measured using SEIFA based on the child’s area of residence), and remoteness, allowing comparisons across different geographic groups.

According to ABS, Statistical Areas Level 3 (SA3s) are geographic areas built from whole Statistical Areas Level 2 (SA2s). SA2s are medium-sized general-purpose areas built up from whole Statistical Areas Level 1 (SA1s). Their purpose is to represent a community that interacts together socially and economically. They are designed for the output of regional data, including 2021 Census of Population and Housing data. SA3s create a standard framework for the analysis of ABS data at the regional level through clustering groups of SA2s that have similar regional characteristics. Whole SA3s aggregate to form Statistical Areas Level 4 (SA4s).

Socio-Economic Indexes for Areas (SEIFA), developed by the ABS using Census data, summarise the socio-economic conditions of people living in an area. SEIFA consists of four indexes measuring different aspects of advantage and disadvantage.
In this analysis, the Index of Relative Socio-economic Disadvantage (IRSD) is used and presented in quintiles, ranging from Quintile 1 (most disadvantaged) to Quintile 5 (least disadvantaged), based on children’s area of residence. IRSD is constructed using Census variables that reflect disadvantage, such as low income, unemployed parents, low educational attainment, single-parent families, and people requiring assistance with core activities; further details of these variables are available from the Australian Bureau of Statistics SEIFA Technical Paper.

Remoteness is classified using the ABS Australian Statistical Geography Standard (ASGS) and the Accessibility/Remoteness Index of Australia Plus (ARIA+), which measure access to services based on geographic location. Areas are grouped into five categories: Major Cities, Inner Regional, Outer Regional, Remote, and Very Remote. For more information on how remoteness is distributed across South Australia, view the map.

Rationale:

This measure provides an early indication of children who may experience difficulties in learning, health, and wellbeing soon after they start school. Developmental vulnerability at school entry is associated with later educational disengagement, including poorer attendance and behavioural risks linked to outcomes such as school suspension (Bell M. F., 2017). Monitoring this measure helps identify population groups and geographic areas where children may require additional support and early intervention. Tracking changes over time also helps inform design and efficacy of policies and programs aimed at improving early childhood development and reducing inequalities in outcomes for children.

By State

The proportion of students who are developmentally on track across all five Australian Early Development Census (AEDC) domains is shown in the line chart below, illustrating trends from 2009 to 2024.

Click or select a state to view its corresponding data. Clicking on a state will toggle its visibility. Double-click on a state to display only that state’s line.

• In South Australia, the proportion of children aged 4-6 years who were developmentally on track across all 5 AEDC domains has remained relatively stable over previous collection cycles. Since 2012, the proportion of children who are developmentally on track has been increasing slightly and moving closer to the national average.
• After 2021 (post-COVID), most states have recorded a decline in the proportion of children developmentally on track, while South Australia has remained relatively stable over this period.
• In 2024, 53% of South Australian children in their first year of full-time school were developmentally on track across all AEDC domains, compared with 52.9% nationally. This rate was lower than those recorded in the Western Australia, Victoria, and New South Wales.

By Statistical Area Level 3 (2024)

In the map above, regions are split by Statistical Area Level 3 (SA3) and shaded based on the proportion of children assessed as developmentally on track across all AEDC domains. Darker shades indicate lower proportions, while lighter shades indicate higher proportions of children on track across all domains.

In 2024:

• Playford recorded the lowest proportion of children developmentally on track, at 23% below the state average.
• Prospect-Walkerville recorded the highest proportion of children developmentally on track, at 36% above the state average.

By Socio-Economic Indexes for Areas (SEIFA) and Remoteness (2024)

• • Children living in less disadvantaged areas (based on SEIFA IRSD) were more likely to be developmentally on track across all AEDC domains, showing a clear and consistent socioeconomic gradient. In 2024, around 61% of children in the least disadvantaged areas were developmentally on track, compared to approximately 41% in the most disadvantaged areas.
    This pattern is stable across 2018, 2021, and 2024, with only minor fluctuations over time. Children in the least and second least disadvantaged groups consistently demonstrate the highest proportions of being on track, while those in the most disadvantaged group remain the lowest. The persistent gap between the most and least disadvantaged groups highlights the strong association between socioeconomic disadvantage and developmental outcomes.
  • Across remoteness areas, children living in less remote parts of South Australia are generally more likely to be developmentally on track across all AEDC domains. In 2024, approximately 53.6% of children in major cities were developmentally on track, compared to only 38.1% in very remote areas. This highlights a clear disparity, with increasing remoteness associated with a lower proportion of children meeting developmental milestones. However, similar to the developmentally vulnerable measure, a different pattern is observed in remote areas, where higher proportions of children were reported as developmentally on track in 2021 and 2024.

Data Source: Australian Early Development Census

Aboriginal and Non-Aboriginal Children Developmentally on track across all AEDC domains

Nationally, in 2024, 33.9% of Aboriginal and Torres Strait Islander children commencing school were assessed as developmentally on track across all five Australian Early Development Census (AEDC) domains. This represents a decrease from 35.2% in 2018, indicating that progress towards the target has worsened over time.

In South Australia, the proportion of Aboriginal and Torres Strait Islander children assessed as developmentally on track across all five AEDC domains has shown little overall change between 2018 and 2024. However, there was a noticeable decline between 2021 and 2024, with the percentage of children developmentally on track falling from 31.3% in 2021 to 28.7% in 2024.

Note: These assessments of progress should be interpreted with caution, as they are based on trends derived from a limited number of data points.

The below section shows proportion of children who are developmentally on track across all AEDC domains further disaggregated by sex, SEIFA (IRSD), and remoteness. Select a disaggregation below to view the corresponding results.

 

Data Source: Productivity Commission. (2025). Closing the Gap data dashboard: Children thrive in their early years.

Background:

The data are presented by state, Statistical Area Level 3 (SA3), socio-economic status (measured using SEIFA based on the child’s area of residence), and remoteness, allowing comparisons across different geographic groups.

According to ABS, Statistical Areas Level 3 (SA3s) are geographic areas built from whole Statistical Areas Level 2 (SA2s). SA2s are medium-sized general-purpose areas built up from whole Statistical Areas Level 1 (SA1s). Their purpose is to represent a community that interacts together socially and economically. They are designed for the output of regional data, including 2021 Census of Population and Housing data. SA3s create a standard framework for the analysis of ABS data at the regional level through clustering groups of SA2s that have similar regional characteristics. Whole SA3s aggregate to form Statistical Areas Level 4 (SA4s).

Socio-Economic Indexes for Areas (SEIFA), developed by the ABS using Census data, summarise the socio-economic conditions of people living in an area. SEIFA consists of four indexes measuring different aspects of advantage and disadvantage.
In this analysis, the Index of Relative Socio-economic Disadvantage (IRSD) is used and presented in quintiles, ranging from Quintile 1 (most disadvantaged) to Quintile 5 (least disadvantaged), based on children’s area of residence. IRSD is constructed using Census variables that reflect disadvantage, such as low income, unemployed parents, low educational attainment, single-parent families, and people requiring assistance with core activities; further details of these variables are available from the Australian Bureau of Statistics SEIFA Technical Paper.

Remoteness is classified using the ABS Australian Statistical Geography Standard (ASGS) and the Accessibility/Remoteness Index of Australia Plus (ARIA+), which measure access to services based on geographic location. Areas are grouped into five categories: Major Cities, Inner Regional, Outer Regional, Remote, and Very Remote. For more information on how remoteness is distributed across South Australia, view the map.

Rationale:

Early childhood development is a key predictor of health, wellbeing, and educational outcomes later in life. The Australian Early Development Census (AEDC) provides important information on how children are developing across five key domains soon after they start school. Monitoring the proportion of Aboriginal and Torres Strait Islander children who are developmentally on track helps identify gaps in early development and highlights areas where additional support may be needed.

In line with the Closing the Gap target, the aim is to increase the proportion of Aboriginal and Torres Strait Islander children assessed as developmentally on track in all five AEDC domains to 55% by 2031, supporting improved long-term outcomes in education, health, and wellbeing.

In 2024, the proportions of children (birth to five years) attending an approved childcare service was:
• 21.4% of all children in SA attending an approved childcare service were from low-income families (18.7% in 2018). Nationally, the proportion was 22.1% in 2024 (20.5% in 2018).
• 15.3% of all children in SA attending an approved childcare service were from regional areas (18.2% in 2018). Nationally, the proportion was 22.5% in 2024 (23.0% in 2018).
• 2.3% of all children in SA attending an approved childcare service were from remote areas (2.4% in 2018). Nationally, the proportion was 1.0% in 2024 (1.0% in 2018).

In 2021, the proportions of children (birth to five years) attending an approved childcare service in SA were:
• 6.7% of all children in SA attending an approved childcare service were children with disability (3.2% in 2016). Nationally, the proportion was 5.4% (3.4% in 2016).
• 15.7% of all children in SA attending an approved childcare service were children from families with a non-English speaking background (15.5% in 2016). Nationally, the proportion was 21.7% (22.3% in 2016).

Note: Children attending approved childcare services may be counted more than once if they attended more than one childcare service in the relevant period.

Data Source: Report on Government Services (ROGS)

 

 

In 2023, 85.3% of SA four-year-old children were enrolled in a preschool program (89.3% in 2018).
Nationally, the proportion was 87.7% in 2023 (84.2% in 2018).

Data Source: ABS, Preschool Education

Data coming soon

The National Disability Insurance Scheme (NDIS) provides funding to eligible Australians, including children and young people, with permanent and significant disability for the supports and services they need.
In quarter 4 of 2021-22 in SA:
• 6,472 children (birth to six years inclusive) had an approved NDIS plan (5,651 in quarter 4, 2020-21).
• 899 children (birth to six years inclusive) received early childhood early intervention supports (680 in quarter 4, 2020-21).

Data Source: NDIS Tailored Data Request