Since 1960, age distribution across Australia's population has observed a fairly significant change. The share of the population below 14 years has dropped from over 30 percent to less than 20 percent; while the share aged over 65 has almost doubled. However, Australia's under-14 population is still larger than its over-65 population. The bulk of the population is aged between 15 and 64 years, and this group had its largest share of the population in 2009 when it made up over two-thirds of the entire population. This gradual change has come as a result of decreasing fertility and higher life expectancy, causing the average age of the population to rise.

This statistic presents the results of a survey on perceived percentage of population over 65 years old by 2050 in Australia as of October 2018. According to data published by Ipsos, respondents in Australia overestimated the proportion of their population who will be over 65 in 2050. On average, the respondents thought that around 51 out of every 100 people in Australia will be over 65 years old in 2050, when the actual share of elderly population, according to projections by the World Bank, will be around 22 percent in Australia.

In June 2022, it was estimated that around 7.3 percent of Australians were aged between 25 and 29, and the same applied to people aged between 30 and 34. All in all, about 55 percent of Australia’s population was aged 35 years or older as of June 2022. At the same time, the age distribution of the country also shows that the share of children under 14 years old was still higher than that of people over 65 years old. A breakdown of Australia’s population growth Australia is the sixth-largest country in the world, yet with a population of around 26 million inhabitants, it is only sparsely populated. Since the 1970s, the population growth of Australia has remained fairly constant. While there was a slight rise in the Australian death rate in 2022, the birth rate of the country decreased after a slight rise in the previous year. The fact that the birth rate is almost double the size of its death rate gives the country one of the highest natural population growth rates of any high-income country.
National distribution of the population Australia’s population is expected to surpass 28 million people by 2028. The majority of its inhabitants live in the major cities. The most populated states are New South Wales, Victoria, and Queensland. Together, they account for over 75 percent of the population in Australia.

As of June 2023, in the state of Western Australia in Australia, about 7.7 percent of the population was between 35 and 39 years old. In comparison, just 1.9 percent of the population was over the age of 85.

As of June 2023 in the state of South Australia, about 6.8 percent of the population was between 25 and 29 years old. In comparison, just 2.6 percent of the population was over the age of 85.

This dataset, released February 2020, contains the total Population projections for years 2020, 2025 and 2030, by 5-year age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years.

The data is by Primary Health Network (PHN) 2017 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

There are 31 PHNs set up by the Australian Government. Each network is controlled by a board of medical professionals and advised by a clinical council and community advisory committee. The boundaries of the PHNs closely align with the Local Hospital Networks where possible.

For more information please see the data source notes on the data.

Source: These data are based on customised projections prepared for the Australian Government Department of Health by the Australian Bureau of Statistics and originally published by the Australian Institute of Health and Welfare. PHA data were compiled by PHIDU based on these customised projections for 2020, 2025, and 2030..

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

This dataset, released February 2020, contains the total Population projections for years 2020, 2025 and 2030, by 5-year age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years.

The data is by Local Government Area (LGA) 2016 geographic boundaries.

For more information please see the data source notes on the data.

Source: These data are based on customised projections prepared for the Australian Government Department of Health by the Australian Bureau of Statistics and originally published by the Australian Institute of Health and Welfare. PHA data were compiled by PHIDU based on these customised projections for 2020, 2025, and 2030..

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

This dataset, released November 2018, contains the total usual resident population by broad age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years, 2017. The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on ABS 3235.0 Population by Age and Sex, Regions of Australia.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

This dataset presents the footprint of the age-standardised percentage of adults who perform insufficient weekly physical activity. Insufficient physical activity is defined as those aged 18-64 years who did not complete over 150 minutes of physical activity, and at least 5 sessions over a week, and those aged 65+ years who did not complete 30 minutes of activity on at least 5 days in a week. As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the Australian Bureau of Statistics (ABS) using standard error estimates of the proportion. The data spans the financial year of 2014-2015 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).

Health risk factors are attributes, characteristics or exposures that increase the likelihood of a person developing a disease or health disorder. Examples of health risk factors include risky alcohol consumption, physical inactivity and high blood pressure. High-quality information on health risk factors is important in providing an evidence base to inform health policy, program and service delivery.

For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - Health Risk Factors in 2014-2015 Data Tables.

Please note:

• AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

• Age-standardisation is a method of removing the influence of age when comparing populations with different age structures - either different populations at the same time or the same population at different times. For this data the Australian estimated resident population of people aged 18 and over as at 30 June 2001 has been used as the standard population.

• Adults are defined as persons aged 18 years and over.

• Values assigned to "n.p." in the original data have been removed from the data.

• Data for PHN107 should be interpreted with caution, as the estimates have a relative standard error of 25% to 50%.

• Data for PHN701 (Northern Territory) should be interpreted with caution as the National Health Survey excluded discrete Aboriginal and Torres Strait Islander communities and very remote areas, which comprise around 28% of the estimated resident population of the Northern Territory living in private dwellings.

This dataset, released September 2020, contains male usual resident population by broad age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years, 2019. The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on ABS 3235.0 Population by Age and Sex, Regions of Australia, 30 June 2019.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

The number of Aboriginal males and their proportion of the total Aboriginal male population for 5 year age groups to 65+, 2015. Aboriginal as used in this workbook refers to Aboriginal and Torres …Show full descriptionThe number of Aboriginal males and their proportion of the total Aboriginal male population for 5 year age groups to 65+, 2015. Aboriginal as used in this workbook refers to Aboriginal and Torres Strait Islander people (all entries that were classified as not shown, not published or not applicable were assigned a null value; no data was provided for Maralinga Tjarutja LGA, in South Australia). The data is by LGA 2015 profile (based on the LGA 2011 geographic boundaries). For more information on Indigenous population estimates refer to: http://phidu.torrens.edu.au/. Source: Compiled by PHIDU based on data developed by Prometheus Information Pty Ltd, under a contract with the Australian Government Department of Health. Copyright attribution: Torrens University Australia - Public Health Information Development Unit, (2016): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Australia (CC BY-NC-SA 3.0 AU)

人口：占女性人口百分比：女性：年龄65岁及以上在12-01-2023达18.401%，相较于12-01-2022的18.055%有所增长。人口：占女性人口百分比：女性：年龄65岁及以上数据按年更新，12-01-1960至12-01-2023期间平均值为12.880%，共64份观测结果。该数据的历史最高值出现于12-01-2023，达18.401%，而历史最低值则出现于12-01-1971，为9.726%。CEIC提供的人口：占女性人口百分比：女性：年龄65岁及以上数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的澳大利亚 – Table AU.World Bank.WDI: Population and Urbanization Statistics。

We estimate population size in terms of the number of occupied nests for the Adélie penguin metapopulation in western Mac. Robertson Land, East Antarctica in 2009/10 and 2019/20. We also assessed demographic data from a single breeding site in the central part of this area (Béchervaise Island: 67°35'S, 62°49'E) including reproductive success, resight data, and fledgling mass from 1991/92 to 2019/20. We collated environmental covariates of potential drivers in this area over the same time period from sources described below. These are presented in the file “Time series demography and environmental covariates.xls”.

Environmental covariates:

Sea-ice concentration: Summer sea-ice concentration (SIC) was obtained for the area bounded by longitudes 60 - 65°E, to the south by the Antarctic coastline and the north by latitude 66.75°S. This approximately 250 km stretch of coastline incorporates the location of all Adélie penguin breeding sites across the metapopulation. The area defines the most northerly limit of fast-ice during chick rearing and encompasses the longitudinal range of the birds’ summer foraging activities. The sea-ice contained within this ‘near-shore’ region is predominantly composed of fast-ice (ice that is attached to land but covers seawater). Summer SIC was calculated as an average over the three-week period 25th December to 15th January when adults are guarding chicks for each breeding season.

Winter SIC was determined in the following three areas of the penguins’ winter migratory route as defined previously. Each area was defined between specific longitudes and from 50°S south to the Antarctic coastline. The sea-ice contained within this area is composed of fast-ice near the coastline and pack-ice (all sea-ice that is not fast-ice) beyond the fast-ice edge. Two sectors defined the outward journey as they travelled westward towards their winter foraging grounds (50 - 65°E during March, and 30 - 50°E during April), a winter area (15 - 30°E during May-Jul) was considered as the sea ice became more extensive with both 15-100% SIC and 15-80% SIC which is considered more in line with suitable winter foraging ice conditions. The final area was associated with their eastwards journey towards the colony (30 - 50°E during Aug-Sep). For each area and time period, an average SIC was determined for each year in each of these areas.

SIC values reflect the total area (km2) covered in sea-ice between either 15-100% or 15-80% SIC in each year and time period using 25x25km pixels. Sea-ice data were obtained from the National Snow and Ice Data Center (NSIDC) (Cavalieri et al. 1996) using Raadtools (Sumner 2017).

Broad-scale climatic indices and local weather conditions: We determined the weather conditions during periods reflecting the end of the austral summer when the penguins were leaving their colonies (Feb-Mar) and the inter-breeding winter period (Apr-Sep). The Southern Oscillation Index (SOI) and the Southern Annular Mode (SAM) were included as broad indicators of climatic conditions, and local weather conditions included air and windchill temperatures. SOI was obtained from the Australian Bureau of Meteorology (www.bom.gov.au) and SAM from the NOAA Climate Prediction Centre (http://www.cpc.noaa.gov/products/precip/CWlink/daily_ao_index/aao/aao_index.html).

Mawson Station local weather: Local weather data recorded at Mawson Station were obtained from the Australian Bureau of Meteorology. We considered two covariates: windchill and air temperatures both reported in °C. Windchill temperatures were determined from the ambient air temperature, wind speed and the relative humidity: AT= Ta +0.33e-0.7ws-4.0, where Ta is the dry bulb temperature (°C), e is the water vapour pressure (hPa), and ws is the windspeed (ms-1) at 10 m elevation. Water vapour pressure was determined from: (see the actual equation in the download file - "Emmerson_AADC Metadata Records_GCB_2022.docx" - unable to be reproduced here), where rh is the relative humidity (%). This formula follows the Australian Bureau of Meteorology calculation (www.bom.gov.au/info/thermal_stress/).

Seabird population parameters:

Pre-fledging mass "adjusted.fledge.mass.5_Feb": We determined pre-fledging mass (g) of chicks on the 5th February by either measuring their mass on that date, or by standardising to that date from measurements made between the 3rd and 14th February.

Total chick productivity "tot.chick.prod.past.5.yrs": Cumulative five-year total chick productivity (total chicks) was calculated for each year using total counts across Béchervaise Island from the preceding five years. This represents the cumulative pool of pre-breeders on the basis that Adélie penguins typically recruit into the breeding population between the ages of one and five years.

Breeding success "bs.3.yr.ave": at Béchervaise Island was measured as the number of chicks crèched (end-January) in relation to the number of nests occupied at the start of incubation (late November and beginning of December). Units of measurement are chicks per occupied nest. Nest and chick counts were obtained annually from on-ground island-wide surveys. Because reproductive performance fluctuates dramatically across years, we calculated three-year rolling averages centred on the year of interest.

Resight data: Age of first return to the colony or recruitment into the breeding population “Age first.nesting.all.6.years” were based on resights of birds in their natal colony. Marked birds were resighted via colony-wide detection from a tag reader when they were on nests. Files for each year contain data from resighting with hand-held tag readers across Béchervaise Island including date of resight and the tag number with each file named as “2003_04 resights.xls” for the resights in 2003/04 split-season for example. For resight data outside the years available in this data repository, please contact Data Custodians.

Population growth rates: Circum-Antarctic population growth rates: To allow a circum-Antarctic comparison of this populations growth rate with other sites or regions, we performed a literature review of published data or growth rates for estimating a consistent metric of growth rate. Data from this search are included in this dataset along with estimates of population growth rate in this study in file “Circum-Antarctic estimates of population growth rates for Adelie penguins Figure 2.pdf”.

Occupied nest counts Mac. Robertson Land: Adult counts were adjusted for phenology-related variable attendance and potential methodology bias to a standard metric (the number of occupied nests at the beginning of the incubation period). The adjustment process is described in detail in Southwell et al. (2013) and propagates the uncertainties from accounting for these biases through to the final estimate of occupied nests. Data include 1000 bootstrap estimates of occupied nests from this procedure for the Mac. Robertson Land area to standardise raw counts to the metric of occupied nests labelled as “O.N.bootstrap.estimates.2009_10” for 2009/10 and 2019/20 which we summarised with the median and 95 percentile limits. Please see manuscript for further details on the standardisation process. Data presented in file “W Mac. Robertson Land Adelie penguin population estimates.xls”.

Any data use from this repository in any publication, report or presentation, should include the following acknowledgement in each data file based on the following “Data from Béchervaise Island or Mac. Robertson Land were derived from Australian Antarctic Science projects 2205, 2552, 4088, 4086 and 4518. All procedures were approved through Australian Antarctic Division animal ethics and ATEP approvals.”

Please refer to the Seabird Conservation Team Data Sharing Policy for use, acknowledgement and availability of data prior to downloading data.

This dataset, released February 2020, contains the male Population projections for years 2020, 2025 and 2030, by 5-year age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years.

The data is by Local Government Area (LGA) 2016 geographic boundaries.

For more information please see the data source notes on the data.

Source: These data are based on customised projections prepared for the Australian Government Department of Health by the Australian Bureau of Statistics and originally published by the Australian Institute of Health and Welfare. PHA data were compiled by PHIDU based on these customised projections for 2020, 2025, and 2030..

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

LGA based data for Occupation by Total Personal Income (Weekly) by Age, in Working Population Profile (WPP), 2016 Census. Count of employed persons aged 15 years and over. W16 is broken up into 8 sections (W16a - W16h), this section contains 'Clerical and administrative workers $150-$299 Age 65-74 years' - 'Sales workers $1000-$1249 Age 75 years and over'. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

This dataset, released February 2020, contains the female Population projections for years 2020, 2025 and 2030, by 5-year age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years.

The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

For more information please see the data source notes on the data.

Source: These data are based on customised projections prepared for the Australian Government Department of Health by the Australian Bureau of Statistics and originally published by the Australian Institute of Health and Welfare. PHA data were compiled by PHIDU based on these customised projections for 2020, 2025, and 2030..

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

This dataset, released September 2020, contains female usual resident population by broad age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years, 2019. The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on ABS 3235.0 Population by Age and Sex, Regions of Australia, 30 June 2019.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

In 2021, over five percent of the population in Australia aged 65 years and over were living with cancer, compared to 0.3 percent for those aged 25 to 34 years. The share of the population living with cancer in Australia increased with age.

GCCSA based data for Status in Employment by Hours Worked by Age, in Working Population Profile (WPP), 2016 Census. Count of employed persons aged 15 years and over. W03 is broken up into 5 sections (W03a - W03e), this section contains 'Total 65-69 years Number of hours worked None' - 'Total Total Total'. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

This dataset, released December 2017, contains female usual resident population by broad age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years, 2016. The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

For more information please see the data source notes on the data.

Source: Compiled by PHIDU based on ABS 3235.0 Population by Age and Sex, Regions of Australia, 2016.

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.