1.1 Analyse the current health status of Australians from Australia’s Health and other health reports, tables and graphs

1. What does the data tell us?

1.1 Epidemiology and health status

Epidemiology is the study of the distribution and determinants of health-related states or events, including disease, in a population. Distribution means the pattern or spread of a health issue through a population. Determinants are the factors that influence health.

In practical terms, epidemiology uses population data to show what health issues are occurring, who is most affected, and how patterns change over time. In Australia, this information comes from sources such as Australia’s Health and other health reports, tables and graphs.

Epidemiological data helps identify the current health status of Australians. It can show the seriousness of a health issue, the extent of the issue, whether it is becoming more or less common, and whether particular groups are affected more than others. It can also help show whether a health issue appears linked to a common determinant, whether some causes are modifiable, and whether a health issue should be prioritised in prevention, treatment or health promotion.

No single indicator explains health status on its own. A stronger analysis combines different measures so that the data shows how many people are affected, what people are dying from, how long people are living, and how much healthy life is being lost through both death and disability.

1.2 Morbidity, prevalence, incidence and distribution

Morbidity refers to illness, disease, injury and other forms of ill health in a population. It is commonly interpreted through prevalence, incidence and distribution which answer different questions.

These measures do not always move in the same direction. For some chronic conditions, incidence may stay stable while prevalence rises. This can happen because people are living longer with the condition, diagnosis is improving, or treatment is extending survival.

Example: Type 2 diabetes may show stable incidence in one period, but prevalence may still rise because more people are living longer after diagnosis and receiving ongoing treatment.

1.3 Mortality, infant mortality and life expectancy

Mortality, infant mortality and life expectancy are closely related measures that help explain patterns of death and survival in a population. Each measure answers a different question about health status, so they are most useful when interpreted together.

Taken together, mortality, infant mortality and life expectancy help show whether Australians are surviving longer, whether early death is being reduced, and whether health gains are being shared across the population.

1.4 Burden of disease

Measures of death alone do not fully explain health status. Many conditions cause long-term disability without causing death. This is why Australia also uses burden of disease measures.

The main burden measure is Disability-Adjusted Life Years (DALYs). One DALY equals one year of healthy life lost. DALYs combine:

• Years of Life Lost (YLL), which are healthy years lost due to premature death
• Years Lived with Disability (YLD), which are healthy years lost due to living with illness, injury or impairment

This matters because some conditions cause major health loss even when they are not leading causes of death. A person may live for many years with severe back pain, anxiety disorders, or another long-term condition that reduces movement, participation, independence or quality of life.

In 2022, Australians experienced slightly more burden from living with illness than from premature death, with YLD accounting for 52% of total burden and YLL accounting for 48%. This supports an important interpretation of current health status: Australians are living longer, but a large share of health loss now comes from long-term conditions and disability, not only early death.

Example: A person with chronic back pain may not die from the condition, but they may lose healthy years through pain, reduced mobility, lower work capacity and poorer quality of life. This contributes to YLD, not YLL.

1.5 Reading health reports, tables and graphs

Health reports, tables and graphs are most useful when they are treated as evidence for trends and comparisons, not as isolated facts.

When you read a table or graph, first check whether the data is shown as a count or a rate. Counts show total numbers. Rates are usually more useful for comparison because they account for population size. You should also check whether the data is age-standardised, which means it has been adjusted to remove the effect of different age structures. This makes comparisons more accurate.

The next step is to describe the trend clearly. The data may show an increase, decrease, plateau, or a short-term spike or dip. After that, compare relevant groups such as males and females, different age groups, or populations living in metropolitan, regional or remote areas.

National reporting shows several broad patterns. These include major declines in deaths from some leading causes, such as coronary heart disease, alongside rising prevalence of some chronic conditions and mixed trends in health behaviours, such as declining smoking but increasing overweight and obesity and greater e-cigarette use.

Example: Reading a trend rather than memorising a number: A life expectancy graph that rises steadily for decades and then shows a small dip across 2020–22 indicates long-term improvement interrupted by a short-term shock (COVID-19). The key learning is the direction and disruption, not the exact figure.

1.6 Limitations of health data and reporting

Epidemiological data is very useful, but it does not tell us everything about health status. It is strongest at showing what is happening. It is less complete when explaining why it is happening.

There are several important limitations:

• Time lag means national data often takes time to collect, check and publish, so a recent report may still be based on data from earlier years.
• Undercounting happens because not everyone who is ill goes to a doctor or hospital.
• Self-report bias happens when people do not accurately report behaviours such as alcohol intake, weight or physical activity.
• Identification and recording issues can make some data less accurate for particular groups.
• Health data often does not fully capture quality of life, emotional experience, cultural meaning, or the day-to-day impact of illness.

This is why health data should be interpreted alongside the social determinants of health, which are the living and working conditions that shape health, such as housing, education, income, discrimination and access to services.

2. What are the major causes of morbidity and mortality, and the life expectancy for males, females and the general population?

2.1 Long-term trends in life expectancy

One of the clearest indicators of Australia’s health status is the long-term increase in life expectancy. Across the last century, Australians have generally lived longer because of improvements in sanitation, nutrition, housing, vaccination, safer working conditions, road safety and medical care.

For Australians born in 2022 to 2024, life expectancy at birth is approximately 81.1 years for males and 85.1 years for females. For the general population, the figure is about 83.2 years.

A clear long-term pattern is that females live longer than males. Another clear pattern is that life expectancy rose steadily until 2019, then dipped slightly in 2020 to 2022 because more people died during those years. This shows that sudden events can temporarily lower life expectancy, but they do not necessarily reverse the broader upward trend.

Example: If a pandemic (e.g. COVID-19) causes a short-term increase in deaths, life expectancy may fall for a few years. If health conditions then stabilise, the longer-term trend of improvement may continue.

2.2 Long-term trends in mortality

Australia’s mortality profile has changed significantly over time. Far fewer people now die from infectious diseases, while most deaths are now caused by non-communicable diseases, which are long-term conditions such as heart disease and cancer.

One major long-term trend is the reduction in deaths from coronary heart disease. Mortality rates from coronary heart disease have fallen by more than 80% since the 1960s peak. Cancer mortality has also fallen, decreasing by about 32% over the last 30 years. These improvements are linked to lower smoking rates, better screening, earlier diagnosis, improved treatment and stronger prevention.

This means fewer Australians are dying early from several major causes than in the past. However, mortality has not disappeared as an issue. Instead, its pattern has changed.

2.3 Trends in morbidity and disease burden

Morbidity patterns are more complex than mortality patterns. As people live longer, they often spend more years living with ongoing health problems.

Australia has a high burden from long-term conditions, including musculoskeletal conditions, mental health conditions, respiratory disease, diabetes and cardiovascular risk factors. This shifts health system priorities towards long-term management, prevention of complications, and improving quality of life and wellbeing, not only preventing death.

This pattern is clearer when interpreted through DALYs, because DALYs capture both premature death and disability. Burden also changes across the life course. Mental health problems and alcohol and other drug issues contribute more to burden in younger people. Bone and joint problems, heart disease and cancer contribute more in middle and older age. Dementia becomes much more common in older age groups.

Morbidity analysis is strongest when it connects these patterns to population ageing and long-term exposure to risk factors such as poor diet, physical inactivity, smoking history, and alcohol and other drug use. It should also recognise mixed behaviour trends, such as declines in daily smoking alongside increases in obesity and e-cigarette use.

Example: A retired adult may live for many years after diagnosis with osteoarthritis. They may not die from the condition, but they may experience pain, reduced mobility and lower independence. This raises morbidity and contributes to disease burden.

2.4 Major causes of mortality in Australia

In recent years, the main causes of death in Australia have mostly been chronic conditions. The leading causes commonly include coronary heart disease, dementia, cerebrovascular disease such as stroke, lung cancer, and chronic lower respiratory diseases.

During the pandemic, COVID-19 became one of the leading causes of death and changed the usual rankings. This shows that a new infectious disease can still reshape mortality patterns very quickly.

Mortality patterns also differ by sex. During the pandemic years, the top causes were similar for males and females, but not in the same order. Coronary heart disease ranked highest for males, while dementia ranked highest for females. This is linked to the fact that females generally live longer, so more females reach very old age, when dementia becomes more common.

A useful ranked snapshot of leading causes of death in Australia is:

1. Ischaemic heart disease (9.2% of deaths)
2. Dementia, including Alzheimer’s disease (9.1% of deaths)
3. Cerebrovascular disease
4. Lung cancer
5. Chronic lower respiratory diseases

The gap between the top two causes in 2023 was only 237 deaths, which shows how close these rankings can be.

Example: As life expectancy rises, more people survive into older age. This can increase deaths from age-related conditions such as dementia, even while deaths from earlier-life causes such as heart disease continue to fall.

2.5 Major causes of morbidity and burden of disease

The main causes of burden (health problems that reduce quality of life) aren’t always the same as the main causes of death. This is because living with disability or illness can have a substantial impact on healthy life, even when it doesn’t lead to death. In Australia, both deadly conditions and non-deadly conditions contribute to the overall burden.

Back pain and other musculoskeletal problems contribute strongly to disability and make it harder for people to work and stay active, but they rarely cause death. Anxiety disorders contribute substantially to years lived with disability, particularly in younger age groups. Coronary heart disease and dementia rank highly in total burden because they contribute to both mortality and long-term illness that requires ongoing care.

Burden also differs by sex. Australian burden patterns show coronary heart disease and suicide and self-inflicted injuries as prominent contributors for males, while dementia and anxiety disorders are prominent contributors for females. Back pain and problems are a major contributor for both.

Quick ranked snapshot of leading burden contributors by sex (top 3)

Note: the exact order can vary slightly by year and the specific AIHW burden table used.

2.6 Overall health status trends

Essentially, the current health status of Australians is: Australians are living longer, but many are also spending more time living with chronic illness, disability and reduced healthy life.

This is why it is not enough to look only at death rates. A full analysis must also consider what conditions Australians are living with, how those conditions affect daily life, and whether health gains are being shared equally across different groups.

Example: A rise in life expectancy can look like a simple health improvement. However, if many of those extra years are lived with dementia, arthritis or chronic respiratory disease, the health system must respond not only to longer life, but also to greater long-term care needs.

3. What are the sociological causes of risky health behaviours?

Risky health behaviours are not explained by individual choice alone. A sociological view looks at the way behaviour is shaped by the social conditions in which people live, learn, work and interact. The NESA glossary defines sociological causes as societal influences, including social relationships, social interaction and culture in everyday life, while WHO and AIHW both emphasise that health is shaped by broader social determinants and the systems around people, not just personal decisions. This means behaviours such as smoking, vaping, harmful alcohol use, poor diet and physical inactivity are often responses to what is available, what is normal, what is rewarded, and what is made easier or harder by social structures.

3.1 Socioeconomic factors

Socioeconomic factors include education, employment and income. These factors influence what people know about health, what they can afford, and what choices are realistically available.

Example: A shift worker on a low income may rely on cheaper takeaway food because fresh food is more expensive, supermarkets are closed after work, and fatigue reduces time for meal preparation. In that situation, diet is being shaped by socioeconomic factors, not just personal choice.

3.2 Sociocultural factors

Sociocultural factors include family, peers, media, religion and culture. These factors shape values, expectations and what feels normal in everyday life.

Example: If a friendship group treats vaping as normal at weekend gatherings, a young person may start vaping to feel included, even when they understand that it carries health risks.

3.3 Environmental factors

Environmental factors include location, housing, and access to services and technology. These shape whether healthy or unhealthy behaviours are easy, affordable and available.

Example: A recreational runner living in a neighbourhood with safe footpaths, lighting and a local park is more likely to stay active than a person living in an area with heavy traffic, no footpaths and no nearby green space.

4. Where do inequities exist and what can we do about them?

Health inequities are unfair and avoidable differences in health outcomes between groups. They are not random. They reflect unequal access to resources, opportunities, support, safety and healthcare. They are closely linked to the social determinants of health, meaning the conditions in which people are born, grow, live, work and age. Analysing inequities requires linking the pattern in the data (who is worse off) to causes (why the difference exists) and then to responses (what can reduce the gap).

4.1 Where health inequities exist in Australia

Australia’s high overall life expectancy can hide large differences within the population. Inequities are clearest when data is examined by Indigenous status, socioeconomic position and remoteness, then interpreted alongside access to services, education, employment, housing, racism and other determinants.

Aboriginal and Torres Strait Islander Peoples

Aboriginal and Torres Strait Islander Peoples experience some of the clearest and most persistent health inequities in Australia. These inequities include lower life expectancy, higher burden from chronic disease, and poorer outcomes across many indicators of health and wellbeing. ABS reports that life expectancy at birth for 2020 to 2022 was 71.9 years for males and 75.6 years for females, which was 8.8 years and 8.1 years lower than for non-Indigenous Australians. These gaps are larger in some places and are lower in Remote and Very Remote Areas than in Major Cities.

These inequities are not explained by biology. They are shaped by the ongoing effects of colonisation, racism, dispossession, intergenerational trauma, socioeconomic disadvantage, overcrowded housing and barriers to culturally safe healthcare. This means the health gap is closely tied to historical and structural causes, not simply to individual behaviour.

Socioeconomically disadvantaged people

People living in socioeconomically disadvantaged situations experience a clear health gradient, which means health outcomes generally worsen as disadvantage increases. Lower income, lower educational attainment and lower occupational status are linked to greater exposure to risk factors, less control over daily life, and reduced access to prevention, treatment and recovery.

This helps explain why people in more disadvantaged circumstances are often more likely to experience smoking, poorer diet, lower physical activity, greater psychological distress and higher chronic disease burden. The issue is not simply that one group makes “worse choices”. It is that one group has fewer resources, fewer buffers against stress and fewer realistic options.

Rural and remote communities

People living in rural and remote communities experience poorer average health outcomes than people in metropolitan areas. AIHW reports that Australians outside major cities have shorter lives, higher levels of disease and injury, and poorer access to and use of health services. They are also more likely to face workforce shortages, long travel distances, delays in diagnosis and treatment, and fewer local health services.

These inequities are strengthened by the interaction between geography and disadvantage. Rural and remote communities may also experience fewer education and employment opportunities, more limited transport, and greater exposure to occupational risk in industries such as farming, mining and transport. This means remoteness affects health both directly, through service access, and indirectly, through broader social and economic conditions.

Culturally and linguistically diverse populations

Some culturally and linguistically diverse populations experience health inequities because language barriers, lower health literacy and unfamiliarity with Australian systems can make healthcare harder to access and navigate. AIHW notes that some people from CALD backgrounds face a greater risk of poorer quality health care, poorer service delivery and poorer health outcomes than other Australians.

This does not mean all CALD populations experience the same health pattern. These populations are highly diverse. However, inequities can emerge when health information is not available in accessible language, when interpreters are limited, when services are not culturally responsive, or when trust in health institutions is low. In these situations, prevention, screening, diagnosis and treatment can all be affected.

People with disability

People with disability experience health inequities through both health status and access barriers. AIHW reports that in 2020 to 2021, only 31% of adults with disability rated their health as excellent or very good, compared with 68% of adults without disability. It also reports much higher levels of psychological distress and bodily pain among adults with disability.

These inequities are not caused by disability alone. They are also shaped by reduced access to social and physical activities, difficulties accessing health services, and disadvantage across education, employment and social support. This means disability can interact with other determinants of health to deepen inequity over time.

Older Australians

Older Australians also experience important health inequities, particularly through higher levels of chronic disease, disability and care needs. AIHW reports that 80% of people aged 65 and over have at least one selected chronic condition, and that dementia was the leading cause of death among people aged 65 and over in 2022. It also reports that 1 in 5 people aged 65 and over had severe or profound disability in 2018.

Older Australians are not a uniform group. Many older people report good health, but inequities can still emerge through isolation, unmet care needs, financial pressure, ageism and the complexity of managing multiple chronic conditions. As the population ages, these inequities become increasingly important for both health policy and service delivery.

Sex and gender patterns

Sex and gender also shape inequity. Males experience higher rates of premature mortality for several causes, while females often live longer but may spend more years with illness and disability. Gender expectations can also affect help-seeking, diagnosis and treatment. For example, norms around toughness and self-reliance can discourage some men from seeking help early, while women may face delayed diagnosis in some parts of the health system. WHO identifies structural discrimination, including gender inequality, as a major driver of health inequity.

Example: Two people with the same heart symptoms may receive different outcomes if one seeks help early and the other delays because they believe they should “push through”. That difference in help-seeking can directly affect mortality and long-term health.

4.2 How determinants create inequities

4.3 What can be done about inequities

Individual and community action

Reducing inequities requires action at more than one level. At an individual level, this includes improving health literacy, supporting early help-seeking, increasing participation in screening and prevention, and helping people manage chronic conditions effectively.

At a community level, locally designed programmes can improve trust, relevance and participation. Community-led care is especially important for groups that have experienced exclusion or poor treatment within mainstream systems. Aboriginal Community Controlled Health Services are a strong example because they provide care that is community-led and culturally safe.

Communities can also reduce inequities through transport support, peer support, local food initiatives, outreach programmes and health information that reflects local language, values and priorities.

Example: A local outreach clinic that provides health checks, transport support and culturally safe staff can improve early diagnosis in a remote community where people would otherwise delay care.

Government and health system action

At a government and health system level, reducing inequities means changing the conditions that shape health, not simply telling people to make better choices.

Important responses include:

• improving access to services through telehealth, outreach and rural workforce support
• using inclusive practices such as translators, culturally safe care and anti-racism training
• addressing the broader social determinants of health, including poverty, housing stress, unemployment and education gaps
• funding public health campaigns and targeted strategies such as Closing the Gap
• improving research and data collection so that groups experiencing inequity are counted accurately and represented fairly

Example: Funding a new regional clinic can reduce travel distance, improve early diagnosis, increase chronic disease monitoring and lower preventable hospital admissions across the community.

4.4 Why multi-level action matters

Health inequities continue when responses focus on only one level. Individual behaviour change is much harder when people do not have safe housing, affordable food, transport, culturally safe care or nearby services. Community programmes are less effective when they are not backed by stable funding and broader policy support. Government policy is weaker when it does not match local needs.

This is why multi-level action is essential. Individual support, community-led action and government reform need to work together. When policy improves access, communities make care relevant and trusted, and individuals are supported within healthier conditions, inequities are more likely to reduce over time.

The broad pattern in Australian health is therefore twofold. Australians are living longer, but not all Australians are living equally well. Understanding that difference, and responding to it, is central to analysing the current health status of Australians.