The health of a nation
The 2021 Census included a new question regarding long-term health conditions. Nenad looks at the national and state stories this new dataset tells us, and digs into how the data can inform local government decisions to improve their communities outcomes.
For the first time, the Census collected data about selected long-term health conditions in the community. The Census question asked respondents if they had been diagnosed with a specific condition from a list of ten conditions plus “other”. Combined, these ten conditions comprise approximately 60% of Australia’s deaths, and even those that are not deadly contribute substantially to the disease burden. Over 8 million people reported having a long-term health condition, with 4.8 million having one of the selected long-term health conditions. In addition, almost 800,000 people had three or more of the selected long-term health conditions. This information is very valuable to researchers, all levels of government, community health networks, minority groups and other health advocacy groups.
- What does the data tell us about our health?
- Mental health is Australia’s number 1 health condition
- First Nations Australians’ health statistics are different
- Confounding factors such as age influence health statistics greatly
- Expert analysis can add more depth and meaning to this information
- Informing Federal, State government and health advocacy groups
- The power of this dataset for local government
- We can help you get the most out of this information for your community
Almost a third of Australians had one or more long-term health conditions; that percentage is higher in States such as Tasmania (37.5% of the population), South Australia (35.1%), the ACT (33%) and Queensland (32.9%). Our two most populous States, NSW and Victoria, and younger States/Territories such as Western Australia and Northern Territory, had lower rates of long-term health conditions than the national average. Age is a confounding factor with many health conditions (described later in this blog) and would be part of why Tasmania and South Australia – with older populations – have higher proportions of residents with long-term health conditions.
The most prevalent long-term health condition Australians have been diagnosed with is mental health; 8.8% of respondents have this condition. In absolute terms, this translates to 2,231,552 Australians with a long-term mental health condition. Arthritis is the second most prevalent health condition affecting 8.5% of Australians (2,150,385 people). Arthritis is highly correlated with age. Beyond the age of 85, more than 1 in 3 Australians are diagnosed with arthritis. Asthma affects 8.1% of Australians (2,068,022), whereas "other conditions", which could include anything not listed, affect 8% of the population. Conditions that affect smaller proportions of the population are dementia (0.7% of the population), kidney disease (0.9%) and stroke (also 0.9%). Stroke, however, does have a higher mortality rate than many other listed conditions and is one of the five leading causes of death in Australia, accounting for 5% of all deaths (as an underlying condition) (Australian Institute of Health and Welfare, 2019).
Long-term health conditions for Aboriginal and Torres Strait Islanders differ from those of Australia. A valuable use of this new dataset is being able to separate and understand how First Nations Australians fare regarding long-term health conditions. For them, mental health was also the most common but at much higher rates (13.3%) than the overall population. Higher asthma rates are also recorded (13.2% compared to 8.1%) along with "other conditions" and diabetes. On the other hand, rates of arthritis are lower for Aboriginal and/or Torres Strait Islanders than the overall population. Arthritis is related to age and the proportion of Aboriginal and/or Torres Strait Islanders over 65 years is 5.9%, compared with 17.2% for Australia.
This information, especially at a local level, can help drive focus and prioritisation of health resources and infrastructure provision, but it pays to know how to "read" the information. One important reminder is that these statistics refer to prevalence of long-term health conditions which have been diagnosed, meaning that undiagnosed conditions (for example in areas without medical centres, in areas where people cannot afford doctor visits or where cultural barriers may mean diagnosis of some conditions such as mental health is taboo) are not included. Any in-depth analysis and resource allocation should use this Census dataset as a starting point, complemented with more local insight.
As previously mentioned, some long-term health conditions are highly correlated with age. The chart below illustrates Australia's top 5 most prevalent long-term health conditions by age. For arthritis, heart disease and diabetes, age is an apparent factor. Conditions such as mental health are more prevalent in younger age groups before increasing again for 85+-year-olds, whereas asthma is similar across all age groups.
With age as a confounding factor in rates of long-term health conditions, it is recommended that age adjustment be applied to crude rates to allow communities with different age structures to be compared. Crude rates of a condition such as dementia will always show older areas as those with higher rates of the condition. If you look at a thematic map of dementia rates, you are pretty much looking at a thematic map of 85+-year-olds.
The process of age-adjustment changes the amount that each age group contributes to the overall rate in each community, so that the overall rates are based on the same age structure. Rates that are based on the same age distribution can be compared to each other without the conflating factor of age. This means that within your LGA, you can compare a community with a community, a suburb with a suburb.
Another way to better understand health data in your area is to assess actual rates of a health condition against expected rates. If actual local rates for a condition are higher than expected, this might cause concern and focus for authorities wanting to influence and address health conditions.
Because this information is derived from the Census, the extent of the dataset covers all of Australia at all sorts of geographic levels. Results can be queried, analysed and compared at neighbourhood, suburb, municipality, regional, greater capital city or State and national levels. Agencies that have already begun to use this information include federal and state governments, departments of health, health advocacy groups and community health networks, among others. The long-term health conditions dataset improves planning and resource allocation of hospitals or medical centres, for example, and better understanding of coverage for existing health infrastructure.
This information will undoubtedly be valuable to health research, likely combined with other data. Organisations such as Arthritis Australia, Dementia Australia, Cancer Council or Mental Health Australia can now refer to the information from the 2021 Census (and future releases of long-term health data) to create or strengthen arguments for funding or targeting of service provision. Statistical analysis of long-term health conditions and comparison of those with demographic and socioeconomic characteristics is possible via crosstabulation. However, in these instances, awareness of correct techniques, whether hotspot analysis or spatial autocorrelation is essential as many incorrect conclusions can be made where correlation is mistaken for causation.
Long-term health condition data can be used in municipal public health and wellbeing plans, age-based planning, seasonal health or emergency management planning (e.g. knowing where your asthma sufferers are if you're in a bushfire-prone area) and community infrastructure planning (such as assessing the outdoor environment and public spaces and making improvements so they are accessible and conducive to physical activity by adults with certain conditions).
Safer, functional, more impactful infrastructure
Using this information can inform the creation of safe, functional pathways and resting areas in and around parks, recreation centres and other community venues for physical activity among adults with arthritis (Arthritis Foundation 2012). Just a couple of days ago I came across the City of Moreland's "Community Infrastructure Plan" and thought knowledge of health conditions could inform how their aquatic, leisure and recreation assets are used and resourced but also which services (e.g. hydrotherapy exercise classes) are provided. It is similar to how some councils use "need for assistance due to disability by age" information to plan the provision of playground equipment for children with disabilities.
Data-driven community outreach
Local government planning could focus on the need for clean air and provision of air quality monitoring in some indoor and outdoor community spaces for neighbourhoods with conditions such as asthma. Local government can also assist with the provision of mental health services or community outreach programs that aim to help those in most need. If the statistics suggest that certain parts of your LGA or certain segments of your population have above-average rates of reported long-term mental health conditions, focus can be placed here, backed by evidence.
Different health conditions require different approaches
Alzheimer’s Australia suggests that local government has a role in helping develop dementia-friendly communities in Australia to build awareness, acceptance and understanding of dementia in the community. For example, Indigo Shire rolled out dementia education and awareness initiatives to its teams, focusing on front line customer services staff. In addition, staff at the Beechworth Library teamed up with the Changing Minds Beechworth alliance to incorporate dementia-friendly design principles into the refurbishment of the library. This focus on the physical environment extended to the upgrading public toilet facilities, and there are plans to review the accessibility of other public amenities as part of longer-term planning. (Creating Dementia-friendly Communities: A Toolkit for Local Government, 2016).
Ultimately, Councils that look at long-term health conditions strategically and positively are not only able to mitigate pressure on their services but facilitate other innovative ways for people living with long-term health conditions to contribute to their community and in turn feel more valued and included.
As demographic experts who have worked with various health data sources and have experience in creating municipal public health and wellbeing plans for councils, we can help you get the most out of this exciting and valuable new Census dataset.
Long-term health conditions have been added to our Community Profile tool as part of the current 2021 Census rollout. We can delve deeper and provide age-standardised conditions for your communities, illustrate spatial distribution of all or selected conditions within your municipality, conduct catchment and service analysis to assess if current health infrastructure is adequate for all residents, or identify remote areas communities with noteworthy rates of health conditions.
We plan on incorporating long-term health conditions into our vulnerable communities analyses and can forecast some health conditions with a strong statistical relationship with age. If you work in local government and want to discuss how we can help or would like to learn more about the long-term health conditions Census dataset, use this link to easily book a 30-minute discussion or contact us at firstname.lastname@example.org.