The Population Health Area (PHA) data include totals for the Greater Capital City Statistical Areas/ Rest of States/NT, States/ Territories and Australia; and for the Statistical Areas Level 3 and …Show full descriptionThe Population Health Area (PHA) data include totals for the Greater Capital City Statistical Areas/ Rest of States/NT, States/ Territories and Australia; and for the Statistical Areas Level 3 and Level 4. Attribution: Torrens University Australia

This dataset includes number of Hospital admissions by mental health diagnosis; Community mental health service contacts by Statistical Local Area e.g. incl. Health Region, Metro Adelaide & Country SA.

Dataset to be attributed to Public Health Information Unit (PHIDU) located at The University of Adelaide. http://phidu.torrens.edu.au/social-health-atlases

Data spreadsheets (xls), based on the Remoteness Graphs, and presenting the latest Social Health Atlas indicators, where available, are produced by Remoteness Area (Remoteness Graphs) for Australia and the State/ Territory areas. The Remoteness Graphs show variations, for each indicator, by Remoteness Areas (RAs). The RA categories are defined in terms of ‘remoteness' - the physical distance of a location from the nearest Urban Centre (indicative of access to goods and services) based on population size. More information can be found at: http://phidu.torrens.edu.au/social-health-atlases

Dataset to be attributed to Public Health Information Unit (PHIDU) located at The University of Adelaide.

Data workbooks presenting the latest Social Health Atlases of Australia. Attribution: Torrens University of Australia. Data workbooks presenting the latest Social Health Atlases of Australia. Attribution: Torrens University of Australia.

The Health Atlas for the City of Los Angeles 2021 presents a data-driven snapshot of health conditions and outcomes in the City of Los Angeles. It illustrates geographic variation in socio-economic conditions, demographic characteristics, the physical environment, and access to support systems and services, and provides a context for understanding how these factors contribute to the health of Angelenos.The data underscore a key issue: where Angelenos live often influences their health and well-being. Los Angeles is a city with great health disparities and the patterns of inequality are reflected in many of the indicators highlighted in the Health Atlas. The spatial characteristics of physical and social determinants of health have roots in structural racism and historic and ongoing discrimination. Historic policies such as redlining have had lasting effects in Los Angeles. The analysis is a first step in understanding the areas of the City burdened with the most adverse health-related conditions in order to improve health outcomes and environmental justice for all Angelenos.The Health Atlas contains 115 maps covering regional context, demographic and social characteristics, economic conditions, education, health conditions, land use, transportation, food systems, crime, housing, and environmental health. In addition to displaying US Census Bureau, City, County, and other data, the Health Atlas contains several indices to facilitate comparisons across the city on subjects including environmental hazards (Map 113: Pollution Burden Index), transportation quality (Map 84: Transportation Index), and economic conditions (Map 19: Hardship Index). The Health Atlas culminates in a Community Health and Equity Index (Maps 114 and 115) which combines many of the above variables into a single index to compare health conditions across the City of Los Angeles. The Community Health and Equity Index can be used to understand the areas of the city with the highest vulnerabilities and cumulative burdens as compared to other portions of the City.The Health Atlas for the City of Los Angeles was originally developed in 2013 as an early step in the process to develop a Health, Wellness, and Equity Element of the General Plan (also known as the Plan for a Healthy Los Angeles). This data set is an update of the Health Atlas, completed in 2021. The Health Element and both editions of the Health Atlas are available as PDFs on the Los Angeles City Planning website, https://planning.lacity.gov.

Dataset replaced by Social Health Atlas of Australia: Compensable Injury in South Australia.\r \r Visit the archive for Medical Locals:\r http://www.phidu.torrens.edu.au/social-health-atlases/data-archive\r \r Data spreadsheets (xls) presenting the latest Social Health Atlas indicators are available by Medicare Local (ML).\r Medicare Locals (MLs), produced by the Australian Government, comprise 61 primary health care organisations which were established to coordinate primary health care delivery and tackle local health care needs and service gaps. Note: ML boundaries do not always coincide with SLA boundaries.\r \r Dataset to be attributed to Public Health Information Unit (PHIDU) located at The Torrens University Adelaide.

Data spreadsheets (xls), based on the Inequality Graphs, and presenting the latest Social Health Atlas indicators, where available, are produced by Quintile of Socioeconomic Disadvantage of Area …Show full descriptionData spreadsheets (xls), based on the Inequality Graphs, and presenting the latest Social Health Atlas indicators, where available, are produced by Quintile of Socioeconomic Disadvantage of Area (Inequality Graphs). The Quintiles of Socioeconomic Disadvantage of Area, referred to as Inequality Graphs, and associated data are based on either the 2006 ASGC or 2011 ASGC ABS Index of Relative Socioeconomic Disadvantage, as noted for each data indicator. More information can be found on http://phidu.torrens.edu.au/social-health-atlases Dataset to be attributed to Public Health Information Unit (PHIDU) located at The Torrens University Adelaide.

A Social Health Atlas of Compensable Injury in South Australia was commissioned by TRACsa with funding from the Motor Accident Commission and WorkCover Corporation of South Australia. It is the …Show full descriptionA Social Health Atlas of Compensable Injury in South Australia was commissioned by TRACsa with funding from the Motor Accident Commission and WorkCover Corporation of South Australia. It is the first health atlas to bring population data on compulsory third party and workers' compensation claims together with information on social, economic and demographic characteristics, health status and health service utilisation.

The "Health Atlas" is a project initiated by the Federal Ministry of Social Affairs, Health, Care and Consumer Protection (BMSGPK) and implemented by Gesundheit Österreich GmbH (GÖG). It provides easy and quick access to quality-assured information on the health situation of the Austrian population and on relevant determinants of health and serves to visualise health data.

The Health Atlas visualises data on selected indicators that can be adapted in terms of regional differentiation, data year and for specific population groups. It presents information on the health situation of the Austrian population and on relevant health determinants, which are shown both in regional comparison (as a map and in the benchmark) and in their development over time (trend). The Health Atlas also enables the observation of regional developments over time (playback function).

This dataset, released January 2020, contains an Estimated number of people aged 15 years and over, who reported their self-assessed health as fair or poor, 2017-18.

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: Estimates for Population Health Areas (PHAs) are modelled estimates and were produced by the ABS; estimates at the LGA and PHN level were derived from the PHA estimates.

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 Aboriginal & Torres Strait Islander Social Health Atlas data presenting the latest Aboriginal & Torres Strait Islander (ATSI) Social Health Atlas indicators are available by Indigenous Areas, including totals for the Capital cities/ Rest of States/Territories, States/ Territories and Australia. Note: The Department of Health has approved for release a set of population estimates by Indigenous status for 2011, and projections to 2016 by Statistical Areas Level 2, Indigenous Region and Primary Health Network. To obtain these data, please contact us. Attribution: Torrens University Australia

This dataset, released July 2018, contains the community strength of areas based on Voluntary work for an organisation or group - people aged 15 years and over, 2016; Estimated number of people aged 18 years and over who did unpaid voluntary work in the last 12 months through an organisation (modelled estimates), 2014; Estimated number of people aged 18 years and over who are able to get support in times of crisis from people outside the household (modelled estimates), 2014; Estimated number of people aged 18 years and over (or their partner) who provide support to other relatives living outside the household (modelled estimates), 2014; Estimated number of people aged 18 years and over who disagree/strongly disagree with acceptance of other cultures (modelled estimates), 2014; Estimated number of people aged 18 years and over who, in the past 12 months, felt that they had experienced discrimination or have been treated unfairly by others (modelled estimates), 2014.

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 the ABS Census of Population and Housing, August 2016; Estimates for Population Health Areas (PHAs) are modelled estimates and were produced by the ABS from the 2014 General Social Survey; estimates at the LGA and PHN level were derived from the PHA estimates; Estimates for Quintiles and Remoteness Areas were compiled by PHIDU based on direct estimates from the 2014 General Social Survey, ABS Survey TableBuilder.

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.

Representation of the connection between health and social structure and temporal development since 2013 (GESIx /GESIx Trend) from the Health and Social Structure Atlas Berlin 2022 at the level of the planning areas. The data is based on 20 indicators from the dimensions of working life, social situation and health. Subindices are calculated for these three dimensions and are combined to form the GESIx. In connection with the development over time (GESIx trend), for example, areas can be identified that require special attention due to their average health and social structure and negative dynamics.

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.

The data set contains the index values ​​of the Health and Social Structure Atlas Berlin 2022 at the level of the forecast areas. The data is based on 20 indicators, which are mainly based on official statistics, from the dimensions of working life (labour market data), social situation (microcensus, rent index, school enrollment examinations, social welfare statistics) and health (hospital diagnosis statistics, population statistics, population register). Sub-indices are calculated for these three dimensions, which are finally merged into a health and social index (GESIx). A detailed description of the methods can be found in the Atlas of Health and Social Structures Berlin 2022: https://www.berlin.de/sen/gesundheit/service/gesundheitsb reporting/gesundheit-und-sozialstruktur/

This dataset, released May 2017, contains data pertaining to Overweight and obesity (children) (modelled estimates), 2014-15; Fruit consumption (children) (modelled estimates), 2014-15. 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: Estimates for Population Health Areas (PHAs) are modelled estimates and were produced by the ABS;estimates at the LGA and PHN level were derived from the PHA estimates.

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 dataset contains the index values ​​of the Health and Social Structure Atlas Berlin 2022 at district level. The data is based on 20 indicators, which are mainly based on official statistics, from the dimensions of working life (labour market data), social situation (microcensus, rent index, school enrollment examinations, social welfare statistics) and health (hospital diagnosis statistics, population statistics, population register). Sub-indices are calculated for these three dimensions, which are finally merged into a health and social index (GESIx). A detailed description of the methods can be found in the Atlas of Health and Social Structures Berlin 2022: https://www.berlin.de/sen/gesundheit/service/gesundheitsb reporting/gesundheit-und-sozialstruktur/

Human health and social work activities share in GVA of Tyumen Region slumped by 5.56% from 1.8 % in 2017 to 1.7 % in 2018. Since the 5.26% drop in 2017, human health and social work activities share in GVA dropped by 5.56% in 2018. Industry structure of Russian regions gross value added, industry GVA at current prices as a percentage of total region GVA.

The dataset contains the index values of the Health and Social Structure Atlas Berlin 2022 at the level of district regions. The data are based on 20 indicators, mainly based on official statistics, from the dimensions of working life (labour market data), social situation (microcensus, rent, enrolment studies, social assistance statistics) and health (hospital diagnostic statistics, demographic statistics, population registers). For these three dimensions, sub-indices are calculated, which are eventually merged into a Health and Social Index (GESIx). A detailed description of the methods can be found in the Health and Social Structure Atlas Berlin 2022: https://www.berlin.de/sen/gesundheit/service/gesundheitsberichterstattung/gesundheit-und-sozialstruktur/

This dataset, released April 2017, contains Estimated number of people aged 15 years and over, who reported their self-assessed health as fair or poor, 2014-15. 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: Estimates for Population Health Areas (PHAs) are modelled estimates and were produced by the ABS;estimates at the LGA and PHN level were derived from the PHA estimates.

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.