Australian Institute of Health and Welfare (2021) Older Australians, AIHW, Australian Government, accessed 08 December 2022.
Australian Institute of Health and Welfare. (2021). Older Australians. Retrieved from https://www.aihw.gov.au/reports/older-people/older-australians
Older Australians. Australian Institute of Health and Welfare, 30 November 2021, https://www.aihw.gov.au/reports/older-people/older-australians
Australian Institute of Health and Welfare. Older Australians [Internet]. Canberra: Australian Institute of Health and Welfare, 2021 [cited 2022 Dec. 8]. Available from: https://www.aihw.gov.au/reports/older-people/older-australians
Australian Institute of Health and Welfare (AIHW) 2021, Older Australians, viewed 8 December 2022, https://www.aihw.gov.au/reports/older-people/older-australians
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This report applied a person-centred model to facilitate consistent, comprehensive and structured reporting on the health and wellbeing of older Australians (Figure 11.1). This model is based on social–ecological frameworks of the determinants of health and wellbeing and was developed by the Australian Institute of Health and Welfare (AIHW) to measure and report on health and welfare of the general population. The approach identifies 7 information domains needed to understand the experiences of the population and its various cohorts. It reflects that a person’s health and welfare result from a complex interplay between biological, lifestyle, socioeconomic, societal and environmental factors, many of which can be modified to some extent by health care, financial support and other interventions. The person-centred model provides a way to understand these factors and their interactions.
While much is known about the health and wellbeing issues that affect older Australians, there are still notable gaps. This section explores some of the main data gaps, highlighting those where timely and valuable improvements and developments could be made.
Using the 7 domains as a framework, there is a range of elements that can be explored to build an understanding of each domain. These elements can be categorised as:
Table 11.1 outlines the elements within each category and for each domain that have been used in this report on the health and wellbeing of older Australians. The elements largely reflect the information currently available; that is, what is known about the current status, determinants and relevant services. The domains of the model provide a structure for organising the elements to enable systematic analysis, as well as identify areas where information on older people is sparse and could be filled to provide a more comprehensive picture. These elements can change over time, as analysis progresses and the evidence base grows.
Services (use, need, outcomes)
Causes of death
Burden of disease
Selected health conditions
Allied health care
Mental health services
Integration of health and aged care
Housing (tenure, dwelling type, suitability)
Homelessness and insecure housing
Social engagement and isolation
Education and skills
Highest level of educational attainment
Participation in education and training
Participating in the workforce
Underemployment and unemployment
Income and finance
Sources of income
Level of income
Income during retirement
Superannuation and other assets
Income support payments
Justice and safety
Note: Where a cell is empty, this indicates that information about the relevant domain's current status, determinants or services is not yet available.
Building a comprehensive picture of the health and wellbeing of older Australians requires information to be drawn from many different data sources, including administrative and survey data. The overarching challenge with much of the data used in this publication, and data available on older Australians in general, is that the data sources have been designed for other and/or wider purposes than exploring the health and wellbeing experiences of older Australians. It is not an issue of the underlying data quality of these data sources. As such, there are many improvement and development opportunities that can be easily implemented to achieve quick gains in building a comprehensive picture of older Australians.
It should also be noted that some of the challenges with existing data sources are not specific to data on older Australians and can occur when focusing on any specific population group (for example, limited disaggregation due to small cell sizes or high standard errors in survey data).
The main limitations identified with existing data include:
While much is known about older Australians across the 7 domains of the person-centred model discussed above, there continue to be notable data gaps and opportunities. While not exhaustive, key gaps exist in the domains of ‘Income and finance’ and ‘Justice and safety’. Data on the prevalence of financial stress experienced by older Australians, as well as the reasons for financial stress, are not readily available. A critical data gap exists around abuse experienced by older Australians, although a prevalence study by researchers at the Australian Institute of Family Studies (AIFS) is currently underway. For more information, see AIFS Elder Abuse Prevalence Study.
Much of the data available is also not person-centred – that is, showing the combination and clustering of factors within an individual – but rather population-wide, showing the prevalence of different variables. This results in an incomplete picture of the range of factors affecting people’s health and wellbeing, and the concentration of many factors within the same individual. Even considering health alone, data on the prevalence of different diseases are often presented without considering the common coexistence of multiple conditions within the same individual. In turn, health care for this person can be fragmented and unmanageable, with management approaches for different conditions competing for the person’s time, Medicare-funded services and other resources.
This report has illustrated that older Australians are not a homogenous group. There is great diversity within the older population, and data are needed to inform what we know about their health and wellbeing. For example, information is needed to identify what are the health-care needs of particular population groups, what are the barriers for accessing care and services, what interactions take place between the domains and how these affect pathways and outcomes.
Data from national surveys play an important role in providing information on the health and wellbeing of older Australians. Challenges exist in collecting data on population subgroups, including data quality and coverage. It can be difficult, for example, to obtain a large representative sample of some populations in national surveys – for example, culturally and linguistically diverse (CALD) or lesbian, gay, bisexual, transgender and intersex (LGBTI) communities – and data become less reliable and robust as sample size decreases.
Further, some surveys exclude certain geographical regions and, in doing so, decrease visibility of these population groups. For example, some surveys do not include populations living in very remote locations; this impacts the ability to comprehensively report on both population groups of older Indigenous Australians and older Australians living in rural and remote communities. Another example is that people living in residential aged care facilities may not be in scope for, or identified, in data collections such as surveys. People in such care settings can have very different needs compared with those living in private homes in the community. Similarly, people living with cognitive decline or dementia may face barriers to participating in data collections, and may have specific needs distinct from older people without these conditions.
While not specific to data related to older Australians, identification of specific older population groups of interest also needs improvement. As described in Older people from CALD backgrounds, there are various ways to describe cultural and linguistic diversity but available data sources only capture some of these concepts. For other population groups, such as older people who identify as LGBTI or otherwise diverse in gender, sex or sexuality, several data sources lack the option for older people to identify as such. Identification of sex and gender-diverse populations are particularly limited. Without standard ways of identifying people, there can be a lack of data quality and limited comparability across collections.
Many of the older populations of interest are designated as people with special needs in the Aged Care Act 1997. This designation adds further importance to improving both identification and coverage of these population groups across various data sources.
Often publicly available data on older Australians are presented with limited age disaggregation, sometimes as a single 65 and over age group. This is sometimes a result of the data that are collected. In other cases, the data exist, but are not published or available. Additional disaggregation of these age groups is important in understanding how the health and wellbeing of older people can differ at different ages. For example, the health and wellbeing of people aged 90 and over may be substantially different from people aged 65.
Further disaggregation by geographical areas is an additional area for improvement. Additional disaggregation by local areas would be particularly valuable. However, further disaggregation may raise concerns (as mentioned above) in relation to population groups, as well as concerns of confidentiality and statistical validity due to small population groups. The quality and consistency of geographical units also varies between data sources.
As well as summarising currently reported information, Table 11.1 illustrates gaps in the information available across the 7 health and wellbeing domains; in particular, in the social support, education and skills, employment, and justice and safety domains. There are also substantial gaps in information on service use, needs and outcomes across the majority of domains, including a lack of information on how multiple service sectors (for example, health and aged care) work together. Within individual domains there are also gaps relating to, for example, selected health conditions (such as dementia, mental health), use of health services (such as private dental practices/providers, palliative care), the cultural appropriateness or safety of aged care services and elder abuse. These data gaps limit the ability to fully understand the factors (and their interactions) that influence the health and wellbeing of older Australians.
There is great diversity within the older population and being able to report on ageing-related issues for population groups is important for building an understanding of their needs and how their life experiences differ. This analysis relies on the variables collected in the underlying data and, in many instances, this is missing, not comprehensive or inconsistent across the data sets. This is particularly the case in relation to data on Australians who identify as LGBTI or otherwise diverse in gender, sex or sexuality, and CALD populations. Similar data quality issues have also been reported in relation to older Aboriginal and Torres Strait Islander people.
Work can be done to not only improve what data are collected about older people, but what is reported. The existing data can also be harnessed in different ways to provide insights into pathways and outcomes.
For existing data sources, where the available data are reliable and robust, thought needs to be given to presenting as much detail as possible to describe the diversity within the older population, for example:
In the longer term, consideration of data improvements could include:
ABS (Australian Bureau of Statistics) 2021. Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables. ABS cat. no. 1200.0.55.012. Canberra: ABS. Viewed 19 August 2021.
AIHW (Australian Institute of Health and Welfare) 2020. GEN Aged care data snapshot 2020—third release. Canberra: GEN. Viewed 20 March 2021.
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