Dementia in Australia

The number of people living with dementia was estimated for this report based on the methodology used in the previous AIHW 2012 Dementia in Australia report (AIHW 2012), with some data source adjustments. 

Prevalence rates for those aged 60 and over were derived from the Alzheimer’s Disease International 2015 report. At the time of writing, this report provided the most up-to-date global estimates of dementia prevalence, with published prevalence rates based on a systematic review of dementia prevalence literature globally (Alzheimer’s Disease International 2015). Age-specific (and where possible sex-specific) estimates were presented by world regions (for example, Australasia, North America, and Western Europe) for people aged 60 and over. Prevalence rates for Australasia alone were based on just three outdated regional studies and are not as reliable as those of other regions. To overcome this challenge, prevalence rates presented here were derived from a combination of the Australasian, North American and Western European prevalence rates. North America and Western European rates were based on a large number of more recent studies, and the estimated dementia prevalence rates for these two regions were most similar to Australasia.

Since sex-specific rates for Australasia were not available in the Alzheimer’s Disease International 2015 report, sex-specific rates for Australasia were calculated by averaging sex rate-ratios from Western Europe and North America and applying them to the Australasian sex-specific rates. Age and sex-specific rates for Australia were then calculated by averaging rates from Australasia, Western Europe, and North America, giving each region the same weight.

As the Alzheimer’s Disease International 2015 report does not present prevalence rates for people aged under 60, and it is known that there are people living with dementia in Australia in this age group, an alternative data source was used to calculate prevalence rates in this age group. Prevalence rates for people aged under 60 were based on a recent large-scale Australian study by Withall et al. (2014). The authors used a methodology consistent with the 2003 UK study by Harvey et al. that was used to estimate dementia prevalence in the AIHW 2012 Dementia in Australia report. Since the Withall et al. study does not report age-specific prevalence rates by sex, we applied sex rate-ratios from the Harvey et al. (2003) study to derive sex-specific rates.

The newly calculated sex and age-specific rates for people aged 60 and over, and sex-specific rates for people aged under 60 for Australia were then applied to the ABS Australian population estimates to estimate the total number of people with dementia in Australia overall and by geographic areas, including remoteness, jurisdiction, socioeconomic area, Primary Health Network (PHN) and statistical area 2 (SA2). While the prevalence estimates are synthetic and have no potential for being disclosive in smaller areas, cell sizes smaller than 5 estimated people have been suppressed due to unreliability.

The number of people estimated to be living with dementia by place of residence (living in community or living in cared accommodation) was calculated using a number of different data sources. This report uses the definition of ‘cared accommodation’ from the 2018 ABS Survey of Disability Ageing and Carers (SDAC). People living in cared accommodation includes people who are a resident, or expected to be a resident, for three months or more in hospitals, nursing homes, aged care hostels, cared components of retirement villages, psychiatric institutions, and other 'homes' such as group homes.

To calculate the number of people with dementia living in cared accommodation, the number of people with dementia who were living in residential aged care facilities between 1 July 2021 and 30 June 2022 by sex and 5 year age groups from the Aged Care Funding Instrument was inflated using data from the 2018 Survey of Disability Ageing and Carers to obtain the number of people with dementia living in cared accommodation (and not just in residential aged care facilities). According to the 2018 Survey of Disability Ageing and Carers, 2.1% of people with dementia living in cared accommodation were not living in a residential aged care facility but living in another type of cared accommodation setting.

The number of people with dementia living in the community was calculated by subtracting the estimates of people living in cared accommodation from the total number of Australians estimated to be living with dementia in 2022.

This method suggests that in 2022, 67% of Australians with dementia are living in the community and 33% are living in cared accommodation. These proportions are consistent with findings from an Alzheimer’s Disease International survey in high-income countries, which indicated that 30% of people with dementia lived in ‘care homes’ (WHO 2012).

Due to data quality issues, in this report the total number of carers of people with dementia who live in the community is presented as a range. The estimate includes people aged 15 and over who provide consistent care for a person with dementia who is living in the community. It excludes people who provide formal assistance (on a regular paid basis, usually associated with an organisation) to a person with dementia, as well as people who provide ongoing care to a family member or friend with dementia living in residential aged care.

The minimum number of unpaid carers of people with dementia was estimated by applying the rate of carers of people with dementia from the SDAC 2018 to the estimated residential population aged 15 and over. However, the SDAC will be an underestimate as only carers who lived in the same household as the care recipient with dementia (co-resident carer) were included. In addition, the SDAC also underestimates the number of people with dementia living in the community.

The maximum number of unpaid carers of people with dementia was estimated by applying the average number of carers of a person with dementia as reported in the SDAC 2018 to the number of people with dementia living in the community in 2022 as estimated by AIHW. Using this method the estimated maximum number of informal carers of people with dementia is 2.5 times higher than the minimum estimate derived from the SDAC.

As there is no single source of data to report total expenditure due to dementia, a number of different data sources of varying quality were used, and are detailed below, to estimate health and aged care expenditure attributable to dementia. Data on the dementia-specific programs, packages and services were sourced from the Australian Government Department of Health and Aged Care.

Due to data limitations, the dementia expenditure estimates presented in this report do not include expenditure for:

• specialised mental health care services
• state and territory government expenditure on aged care
• private aged care services (both home care and supported residential services and facilities)
• indirect expenditure – such as travel costs for patients, the social and economic burden on carers and family, and lost wages and productivity.

Aged care expenditure

The majority of the aged care estimates are based on direct government expenditure. Non-government-expenditure (for example, by individuals, private health insurers and other non-government sources) is however, included in health expenditure estimates in relation to hospital services, out-of-hospital medical services and prescription medications.

Aged care expenditure is allocated to dementia using the proportion of care delivered within programs to clients with dementia diagnoses and supplements. For the purposes of this report, spending on community-based respite care for people with dementia (which is part of the Commonwealth Home Support Program) is shown separately.

Due to limited data availability relating to diagnoses managed through some aged care programs, the Home Care Program (HCP) dementia supplement data were used to estimate dementia spending in the Commonwealth Home Support Programme (CHSP) and the DVA Community Nursing Program.

• CHSP program dementia spending was estimated using the proportion of days in 2018-19 that clients received dementia supplements in HCP levels 1 and 2.
• DVA Community Nursing Program dementia spending was estimated using the proportion of days in 2018-19 that clients with a DVA entitlement received dementia supplements in HCP levels 2 and 3.

Data from the National Screening and Assessment Form (NSAF) were used to allocate spending on residential and community based respite care, the transition care program, aged care assessments, and Veterans Home Care Program.

• Residential respite care expenditure for dementia was estimated by determining the proportion of approvals for respite care (residential and mixed) that were associated with a dementia diagnosis, for clients not currently living in residential care.
• Community based respite care expenditure for dementia was estimated according to the proportion of approvals for respite care (community and mixed) that were associated with a diagnosis of dementia, among clients not currently living in residential care.
• Transition care program expenditure for dementia was estimated by determining the proportion of approvals for transition care that were associated with a dementia diagnosis, for clients not currently living in residential care.
• Aged care assessment expenditure for dementia was estimated according to the proportion of aged care assessments where a record included a dementia diagnosis.
• Veterans Home Care Program expenditure for dementia was estimated according to the proportion of clients with a DVA entitlement who are diagnosed with dementia.
• National Aboriginal and Torres Strait Islander Flexible Aged Care Program expenditure on dementia was estimated by determining the proportion of First Nations clients with a dementia diagnosis from the Aged Care Funding Instrument (ACFI) data.

Estimating expenditure in residential aged care facilities directly attributable to dementia

To determine what portion of total funding for a permanent resident in an aged care facility is directly related to dementia, information on the resident’s comorbidities is required. While some information on health conditions is collected within the Aged Care Funding Instrument (ACFI), these data do not include a complete list of comorbidities, nor do they indicate the relative severity of these conditions. It is therefore not possible to use data collected through the ACFI to separate the cost attributable solely to dementia from the total cost of caring for people with dementia in residential aged care facilities. To allow the estimation of the costs due to dementia, data from the 2018 Australian Bureau of Statistics Survey of Disability Ageing and Carers (SDAC) were used to supplement ACFI data. This approach is consistent with the approach taken for the previous Dementia in Australia report (AIHW 2012), and is outlined below.

Data from the 2018 SDAC relating to people living in residential aged care facilities were used to estimate the differences in care needs and funding between people with and without dementia. SDAC questions relating to need for assistance were mapped to related ACFI questions, such that an estimated ACFI score was created for each SDAC respondent living in residential aged care facilities.

Health conditions recorded in the SDAC were allocated across eight categories, grouped according to similarities in the likely need for assistance for the condition. For example, arthritis was grouped with hip damage from injury in the group ‘Conditions affecting mobility’. The groups were defined by the ABS categorisations within the SDAC, and include: Dementia and Alzheimer disease, stroke, conditions affecting mobility, mental health, other cardiovascular disease, hearing loss, Parkinson disease, and other conditions. Each group was only counted once, which means that an individual with multiple conditions within a group is treated the same as an individual with one condition in the group.

A regression model was fitted to the data using the estimated ACFI scores as the dependent variable, and all possible combinations of the eight condition groups (more than 200) as the independent variables. The resultant model had 187 degrees of freedom, an F value of 14.40 (Pr < 0.0001) and an adjusted R² of 0.29. From this model, a predicted ACFI score was generated for each combination of condition groups, which provided an average ACFI score and level of funding for each combination of condition groups within the model.

Comparisons were then made between combinations of conditions with dementia and without dementia, to quantify the impact of dementia on predicted ACFI scores and associated levels of funding. For example, the predicted ACFI score for a resident with dementia, stroke and mobility problems was compared to that of a resident with just stroke and mobility. The higher the ACFI score for a resident, the more complex their care needs and the more funding they receive. The average predicted ACFI score of a resident with dementia was 125, compared to 95 for those without dementia. This translates to 24% of costs for residents with dementia allocated directly to dementia.

These results were applied to 2018–19 data for ACFI residents, with age and sex taken into account, and used to estimate the proportion of Australian Government funding for permanent residents in residential aged care that was attributable to dementia.

Health expenditure

Health care expenditure estimates were sourced from the AIHW Disease Expenditure database. In this database, expenditure across the various components of the health system is estimated and then allocated to the health conditions based on a range of available diagnostic and service use data. Further information on the AIHW Disease Expenditure database can be found at Disease Expenditure in Australia 2018–19.

Estimating expenditure for hospitalisations where a dementia diagnosis was recorded

The approach for estimating expenditure on admitted patients with dementia in this report is similar to what has been used in previous reports, but uses more detailed cost data.

In public hospitals, admitted patient expenditure for dementia is estimated based on the National Hospital Cost Data Collection, and allocated to public hospital separations in the National Hospital Morbidity Database on the basis of principal diagnosis, Diagnosis Related Group (DRG) code, facility, and state. The DRG code is based on a range of data collected about the admitted patient, including the diagnosis and procedures undertaken during the hospitalisation.

In private hospitals, admitted patient expenditure for dementia is estimated based on the Private Hospital Data Bureau data, and allocated to private hospital separations in the National Hospital Morbidity Database on the basis of principal diagnosis, DRG, and state. This data collection includes all costs except for medical charges. Medical charges are allocated to separations using the MBS items recorded for the separation, and the average in-hospital fee charged for each MBS item by state.

Allocation of total expenditure for a separation to additional diagnoses was based on modelling the estimated separation cost and diagnoses record for a patient. A regression model was used to estimate the fraction of each public hospital separation cost that is due to each condition being treated, to take into account the impact of comorbidities on costs, and more accurately reflect the expenditure for each condition.

The excess expenditure for each principal diagnosis due to comorbidities was modelled with a log-linear regression model that estimated expenditure for each principal diagnosis (grouped by condition reported in the Australian Burden of Disease Study), with indicators of additional diagnoses as independent variables. The estimated coefficients of the models quantify the impact of additional diagnoses on expected expenditure; that is, the extent to which the charge associated with a given separation for a given principal diagnosis is expected to increase in the presence of additional diagnoses. The results from the regression model were used to estimate the predicted proportion of expenditure associated with each diagnosis within each separation in the hospital data.

Further information is published in Disease Expenditure in Australia 2018–19

AIHW (Australian Institute of Health and Welfare) (2012) Dementia in Australia 2012, AIHW, Australian Government, accessed 17 August 2022.

ADI (Alzheimer’s Disease International) (2015) World Alzheimer report 2015: the global impact of dementia: an analysis of prevalence, incidence, cost and trends, ADI, accessed 17 August 2022.

Harvey RJ, Skelton-Robinson M & Rossor MN (2003) 'The prevalence and causes of dementia in people under the age of 65 years', Journal of Neurology, Neurosurgery and Psychiatry, 74(9):1206–9, doi:10.1136/jnnp.74.9.1206.

Withall A, Draper B, Seeher K & Brodaty H (2014) 'The prevalence and causes of younger onset dementia in Eastern Sydney, Australia', International Psychogeriatrics, 26(12):1955–1965, doi:10.1017/S1041610214001835.

WHO (World Health Organisation) (2012) Dementia a public health priority, WHO, accessed 18 August 2022.