This dataset, released February 2021, contains the statistics of premature mortality for females, males and persons below 75 years, over the years 2014 to 2018.

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: Data compiled by PHIDU from deaths data based on the 2014 to 2018 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population is the ABS Estimated Resident Population (ERP) for Australia, 30 June 2014 to 30 June 2018.

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available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells.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 premature deaths from all causes in males, females and total people aged 0 to 74 years and their corresponding mortality rates/ratios with respective confidence intervals, 2010 – 2014 …Show full descriptionThe number of premature deaths from all causes in males, females and total people aged 0 to 74 years and their corresponding mortality rates/ratios with respective confidence intervals, 2010 – 2014 (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 statistics used please refer to the PHIDU website, available from: http://phidu.torrens.edu.au/. Source: Data compiled by PHIDU from deaths data based on the 2010 to 2014 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population at the small area level is the ABS Estimated Resident Population (ERP), 30 June 2010 to 30 June 2014, Statistical Areas Level 2; the population standard is the ABS ERP for Australia, 30 June 2010 to 30 June 2014. 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)

This dataset, released July 2018, contains Deaths of males aged 0 to 74 years, 2011 to 2015; Deaths of females aged 0 to 74 years, 2011 to 2015; Total deaths, 0 to 74 years, 2011 to 2015. 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. Show full descriptionThis dataset, released July 2018, contains Deaths of males aged 0 to 74 years, 2011 to 2015; Deaths of females aged 0 to 74 years, 2011 to 2015; Total deaths, 0 to 74 years, 2011 to 2015. 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: Data compiled by PHIDU from deaths data based on the 2011 to 2015 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population at the small area level is the ABS Estimated Resident Population (ERP), 30 June 2011 to 30 June 2015, Statistical Areas Level 2; the population standard is the ABS ERP for Australia, 30 June 2011 to 30 June 2015. Please note: AURIN has spatially enabled the original data. "*" - Indicates statistically significant, at the 95% confidence level. "**" - Indicates statistically significant, at the 99% confidence level. "~" - Indicates modelled estimates have Relative Root Mean Square Errors (RRMSEs) from 0.25 to 0.50 and should be used with caution. "~~" - Indicates modelled estimates have RRMSEs greater than 0.50 but less than 1 and are considered too unreliable for general use. '?' - Indicates modelled estimates are considered too unreliable. Blank cell - Indicates data was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data). Abbreviation Information: "ASR per #" - Indirectly age-standardised rate per specified population. "SDR" - Indirectly age-standardised death ratio. "95% C.I" - upper and lower 95% confidence intervals. Copyright attribution: Torrens University Australia - Public Health Information Development Unit, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Australia (CC BY-NC-SA 3.0 AU)

Australia Welfare Costs of Premature Deaths from Exposure to Lead:(GDP) Gross Domestic ProductEquivalent data was reported at 0.630 % in 2019. This records an increase from the previous number of 0.620 % for 2018. Australia Welfare Costs of Premature Deaths from Exposure to Lead:(GDP) Gross Domestic ProductEquivalent data is updated yearly, averaging 0.805 % from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 1.060 % in 1990 and a record low of 0.610 % in 2017. Australia Welfare Costs of Premature Deaths from Exposure to Lead:(GDP) Gross Domestic ProductEquivalent data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Australia – Table AU.OECD.GGI: Social: Air Quality and Health: OECD Member: Annual.

Premature mortality by selected causes and sex by LGA 2011, from 2008 to 2012.

Burden Of Disease by state and territory

Rate were age-standardised to the 2001 Australian Standard Population, and expressed per 1000 people Rate ratios compare the state/territory rate of burden with the Australian rate of burden * The value is less than the value shown
DALY (disability-adjusted life years): Measure (in years) of healthy life lost, either through premature death defined as dying before the expected life span at the age of death (YLL) or, equivalently, through living with ill health due to illness or injury (YLD). YLD (years lived with disability): A measure of the years of what could have been a healthy life but were instead spent in states of less than full health. YLD represent non-fatal burden. YLL (years of life lost): Years of life lost due to premature death, defined as dying before the global ideal life span at the age of death. YLL represent fatal burden.

The data is presented by the ACT Government for the purpose of disseminating information for the benefit of the public. The ACT Government has taken great care to ensure the information in this report is as correct and accurate as possible. Whilst the information is considered to be true and correct at the date of publication, changes in circumstances after the time of publication may impact on the accuracy of the information. Differences in statistical methods and calculations, data updates and guidelines may result in the information contained in this report varying from previously published information.

This dataset, released December 2016, contains statistics for deaths of people aged 0-74 years during the years 2010-2014 based on the following causes: cancer, diabetes, circulatory system diseases, respiratory systems diseases and external causes. 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 …Show full descriptionThis dataset, released December 2016, contains statistics for deaths of people aged 0-74 years during the years 2010-2014 based on the following causes: cancer, diabetes, circulatory system diseases, respiratory systems diseases and external causes. 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: Data compiled by PHIDU from deaths data based on the 2010 to 2014 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. Please note: AURIN has spatially enabled the original data. "*" - Indicates statistically significant, at the 95% confidence level. "**" - Indicates statistically significant, at the 99% confidence level. "~" - Indicates modelled estimates have Relative Root Mean Square Errors (RRMSEs) from 0.25 to 0.50 and should be used with caution. "~~" - Indicates modelled estimates have RRMSEs greater than 0.50 but less than 1 and are considered too unreliable for general use. '?' - Indicates modelled estimates are considered too unreliable. Blank cell - Indicates data was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data). Abbreviation Information: "ASR per #" - Indirectly age-standardised rate per specified population. "SDR" - Indirectly age-standardised death ratio. "95% C.I" - upper and lower 95% confidence intervals. Copyright attribution: Torrens University Australia - Public Health Information Development Unit, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Australia (CC BY-NC-SA 3.0 AU)

This dataset presents the footprint of statistics related to deaths due to all causes (combined) by sex. The reported statistics include year of death, total deaths, crude rates, age-standardised …Show full descriptionThis dataset presents the footprint of statistics related to deaths due to all causes (combined) by sex. The reported statistics include year of death, total deaths, crude rates, age-standardised rates, rate ratio, median age at death, premature deaths, potential years of life lost and potentially avoidable deaths. The data spans the years of 2012-2016 and is aggregated to Greater Capital City Statistical Area (GCCSA) geographic areas from the 2016 Australian Statistical Geography Standard (ASGS). Mortality Over Regions and Time (MORT) books are workbooks that contain recent deaths data for specific geographical areas, sourced from the Australian Institute of Health and Welfare (AIHW) National Mortality Database. They present various statistics related to deaths by all causes and leading causes of death by sex for each geographical area. For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - MORT Books. Please note: AURIN has spatially enabled the original data. Cause of Death Unit Record File data are provided to the AIHW by the Registries of Births, Deaths and Marriages and the National Coronial Information System (managed by the Victorian Department of Justice) and include cause of death coded by the Australian Bureau of Statistics (ABS). The data are maintained by the AIHW in the National Mortality Database. Year refers to the year of registration of death. Deaths registered in 2013 and earlier are based on the final version of the cause of death data; deaths registered in 2014 are based on revised version; deaths registered in 2015 and 2016 are based on preliminary versions. Revised and preliminary versions are subject to further revision by the ABS. Cause of death information are based on the underlying cause of death and are classified according to the International Classification of Diseases and Related Health Problems (ICD). Deaths registered in 1997 onwards are classified according to the 10th revision (ICD-10). Unknown/missing includes deaths where place of usual residence was overseas, no fixed abode, offshore and migratory, and undefined. Summary measures and cause of death data are not presented for any GCCSA with less than 10 deaths in a single year; they are not presented for 'Other territories' because there were only 42 deaths recorded in 2012-2016. Population counts are based on estimated resident populations at 30 June for each year. Australian estimated resident population data are sourced from Australian demographic statistics (ABS cat. no. 3101.0). Copyright attribution: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare, (2019): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 3.0 Australia (CC BY 3.0 AU)

This dataset presents the footprint of death data by sex, sourced from the AIHW National Mortality Database. They present statistics by sex for each geographical area, including counts, rates, median age at death, premature deaths, potential years of life lost and potentially avoidable deaths. The data spans the years 2010 to 2014 and is aggregated to Local Government Area (LGA) geographic areas from the 2011 Australian Statistical Geography Standard (ASGS).

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - MORT Books.

Please note:

• AURIN has spatially enabled the original data.

Background. Most previous mortality research in eating disorders involves individuals attending specialist treatment services. Data linkage across jurisdictional health databases at a population level improves the generalisability of findings. Aims. To investigate mortality risk and causes of death for people with an eating disorder across a large geographic region using administrative health datasets. Method. Using linked hospital, mental health and death records, a retrospective cohort study was conducted including individuals aged 10-59 years who received an eating disorder diagnosis during hospital-based encounters in Australia, over a 10-year period between 2010 and 2019. A contemporary cohort of people accessing community care only were also evaluated. Mortality rates and standardised morality ratios (SMR) compared to the general population were calculated for each state, and by sex and age groups. Cox regression models were used to assess the risk of sociodemographic characteristics on mortality. Results. Mortality in people hospitalised with an eating disorder (N=19,697) was more than four times higher than the general population (SMR: 4.54), and highest in people aged 30-39 years (SMR: 13.32). Men hospitalised for eating disorders had a higher risk of death. Mortality rates in anorexia nervosa were not higher than other eating disorder diagnoses. Almost three-quarters of deaths were caused by suicide/self-harm or cardio/respiratory illness. Conclusions. People accessing hospital care with eating disorders in Australia have a higher risk of premature death regardless of age, sex or eating disorder diagnosis. Gender and age group disparities can inform policy and resource allocation and support the development of targeted interventions.

Burden Of Disease by state and territory

Rate were age-standardised to the 2001 Australian Standard Population, and expressed per 1000 people Rate ratios compare the state/territory rate of burden with the Australian rate of burden * The value is less than the value shown
DALY (disability-adjusted life years): Measure (in years) of healthy life lost, either through premature death defined as dying before the expected life span at the age of death (YLL) or, equivalently, through living with ill health due to illness or injury (YLD). YLD (years lived with disability): A measure of the years of what could have been a healthy life but were instead spent in states of less than full health. YLD represent non-fatal burden. YLL (years of life lost): Years of life lost due to premature death, defined as dying before the global ideal life span at the age of death. YLL represent fatal burden.

The data is presented by the ACT Government for the purpose of disseminating information for the benefit of the public. The ACT Government has taken great care to ensure the information in this report is as correct and accurate as possible. Whilst the information is considered to be true and correct at the date of publication, changes in circumstances after the time of publication may impact on the accuracy of the information. Differences in statistical methods and calculations, data updates and guidelines may result in the information contained in this report varying from previously published information.

Dataset of 25,000 convicts who were transported to Van Diemen's Land (Tasmania) on 126 convict ships, 1812-1853. Contains around 100 variables on early life, crime and sentence, behaviour and punishment under sentence, family formation, post-sentence life, descendants, and date and details of death. Sources include convict records; birth, death and marriage registrations; census records; newspapers; police gazettes; and other administrative and historical sources. Part of the larger 'Founders and Survivors' Project.

This dataset, released December 2016, contains statistics for deaths of people aged 0-74 years during the years 2010-2014 based on the following causes: cancer, diabetes, circulatory system diseases, respiratory systems diseases and external causes. The data is by Local Government Area (LGA) 2016 geographic boundaries.

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

Source: Data compiled by PHIDU from deaths data based on the 2010 to 2014 Cause of Death Unit Record Filessupplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registriesof Births, Deaths and Marriages and the National Coronial Information System.

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.

Time series data for the statistic Adjusted savings: particulate emission damage (current US$) and country Australia. Indicator Definition:Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.The indicator "Adjusted savings: particulate emission damage (current US$)" stands at 300.02 Million usd as of 12/31/2021, the highest value since 12/31/2014. Regarding the One-Year-Change of the series, the current value constitutes an increase of 15.76 percent compared to the value the year prior.The 1 year change in percent is 15.76.The 3 year change in percent is 11.37.The 5 year change in percent is 30.22.The 10 year change in percent is 4.07.The Serie's long term average value is 193.96 Million usd. It's latest available value, on 12/31/2021, is 54.68 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2002, to it's latest available value, on 12/31/2021, is +181.81%.The Serie's change in percent from it's maximum value, on 12/31/2013, to it's latest available value, on 12/31/2021, is -3.61%.

This dataset, released February 2021, contains the statistics of premature mortality by various causes for people below 75 years, over the years 2014 to 2018. Causes for death include cancer (colorectal, lung, breast), diabetes, circulatory system diseases (ischaemic heart disease, cerebrovascular disease), respiratory system diseases (chronic obstructive pulmonary disease), and external causes (road traffic injuries, suicide and self-inflicted injuries)

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: Data compiled by PHIDU from deaths data based on the 2014 to 2018 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population is the ABS Estimated Resident Population (ERP) for Australia, 30 June 2014 to 30 June 2018.

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.

Estimated standardised crude probability of death from cancer, death from other causes and being alive, Aboriginal and Torres Strait Islanders and disparity in estimated probabilities of death, to other Australians, Australia, five years since diagnosis, by cancer type, Australia, 2005–2016.

A. The number of temperature-related deaths averted if Australia’s health system and the whole economy decarbonises by 2040 and 2050. B. The monetary equivalent welfare gain under a range of discount rates and emission trajectories.

In 2024, the average life expectancy in the world was 71 years for men and 76 years for women. The lowest life expectancies were found in Africa, while Oceania and Europe had the highest. What is life expectancy?Life expectancy is defined as a statistical measure of how long a person may live, based on demographic factors such as gender, current age, and most importantly the year of their birth. The most commonly used measure of life expectancy is life expectancy at birth or at age zero. The calculation is based on the assumption that mortality rates at each age were to remain constant in the future. Life expectancy has changed drastically over time, especially during the past 200 years. In the early 20th century, the average life expectancy at birth in the developed world stood at 31 years. It has grown to an average of 70 and 75 years for males and females respectively, and is expected to keep on growing with advances in medical treatment and living standards continuing. Highest and lowest life expectancy worldwide Life expectancy still varies greatly between different regions and countries of the world. The biggest impact on life expectancy is the quality of public health, medical care, and diet. As of 2022, the countries with the highest life expectancy were Japan, Liechtenstein, Switzerland, and Australia, all at 84–83 years. Most of the countries with the lowest life expectancy are mostly African countries. The ranking was led by the Chad, Nigeria, and Lesotho with 53–54 years.

This dataset, released July 2018, contains Deaths of males aged 0 to 74 years, 2011 to 2015; Deaths of females aged 0 to 74 years, 2011 to 2015; Total deaths, 0 to 74 years, 2011 to 2015. The data is by Local Government Area (LGA) 2016 geographic boundaries.

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

Source: Data compiled by PHIDU from deaths data based on the 2011 to 2015 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population at the small area level is the ABS Estimated Resident Population (ERP), 30 June 2011 to 30 June 2015, Statistical Areas Level 2; the population standard is the ABS ERP for Australia, 30 June 2011 to 30 June 2015.

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.

1849-1865 CE. Top 15 causes of death on emigrant voyages to South Australia from the United Kingdom from 1849-1865 (Total Deaths: 1141) [103].