3 datasets found
  1. Summaries of the posterior means of the area-specific relative risk...

    • plos.figshare.com
    xls
    Updated Jun 14, 2023
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    Ben Beck; Andrew Zammit-Mangion; Richard Fry; Karen Smith; Belinda Gabbe (2023). Summaries of the posterior means of the area-specific relative risk (‘Spatial’) and the area specific yearly multiplicative change in risk (‘Temporal’) grouped by the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), classified from 1 (most disadvantage), to 5 (most advantaged). [Dataset]. http://doi.org/10.1371/journal.pone.0266521.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 14, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ben Beck; Andrew Zammit-Mangion; Richard Fry; Karen Smith; Belinda Gabbe
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summaries of the posterior means of the area-specific relative risk (‘Spatial’) and the area specific yearly multiplicative change in risk (‘Temporal’) grouped by the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), classified from 1 (most disadvantage), to 5 (most advantaged).

  2. w

    Proportion of population living below national poverty line, by sex and age

    • data.wu.ac.at
    • data.gov.au
    csv
    Updated Jul 13, 2018
    + more versions
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    Sustainable Development Goals (2018). Proportion of population living below national poverty line, by sex and age [Dataset]. https://data.wu.ac.at/schema/data_gov_au/YWRiNmQ5ODMtMmYzZC00OTE5LTg3MzgtMjA5YTBlMDNmYjc3
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    csv(130.0)Available download formats
    Dataset updated
    Jul 13, 2018
    Dataset provided by
    Sustainable Development Goals
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The most common poverty measures, including that used by the OECD, focus on income based approaches. One of the most common measures of income poverty is the proportion of households with income less than half median equivalised disposable household income (which is set as the poverty line); this is a relative income poverty measure as poverty is measured by reference to the income of others rather than in some absolute sense. Australia has one of the highest household disposable incomes in the world, which means that an Australian relative income poverty line is set at a high level of income compared to most other countries.

    OECD statistics on Australian poverty 2013–2014 (based on ABS Survey of Income and Housing data and applying a poverty line of 50% of median income) determined the Australian poverty rate was over 26% before taxes and transfers, but falls to just under 13% after taxes and transfers. Though measuring poverty through application of solely an income measure is not considered comprehensive for an Australian context, however, it does demonstrate that the Australian welfare system more than halves the number of Australians that would otherwise be considered as at risk of living in poverty under that measure.
    It is important to consider a range of indicators of persistent disadvantage to understand poverty and hardship and its multidimensional nature. Different indicators point to different dimensions of poverty. While transient poverty is a problem, the experience of persistent poverty is of deeper concern, particularly where families experience intergenerational disadvantage and long-term welfare reliance. HILDA data from the Melbourne Institute of Applied Economic and Social Research shows the Distribution of number of years in poverty 2001–2015. The figure focuses on the longer term experience of working age adults and shows that while people do fall into poverty, only a small proportion of people are persistently poor.

  3. Table_1_Impact of health risk factors on healthcare resource utilization,...

    • frontiersin.figshare.com
    docx
    Updated Nov 27, 2023
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    Jun Mi; Marie Ishida; Kanya Anindya; Barbara McPake; Bernadette Fitzgibbon; Anthony A. Laverty; An Tran-Duy; John Tayu Lee (2023). Table_1_Impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life of Australians: a population-based longitudinal data analysis.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2023.1077793.s001
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    docxAvailable download formats
    Dataset updated
    Nov 27, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Jun Mi; Marie Ishida; Kanya Anindya; Barbara McPake; Bernadette Fitzgibbon; Anthony A. Laverty; An Tran-Duy; John Tayu Lee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Australia
    Description

    BackgroundHealth risk factors, including smoking, excessive alcohol consumption, overweight, obesity, and insufficient physical activity, are major contributors to many poor health conditions. This study aimed to assess the impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life (HRQoL) in Australia.MethodsWe used two waves of the nationally representative Household, Income, and Labor Dynamics in Australia (HILDA) Survey from 2013 and 2017 for the analysis. Healthcare resource utilization included outpatient visits, hospitalisations, and prescribed medication use. Work-related outcomes were assessed through employment status and sick leave. HRQoL was assessed using the SF-6D scores. Generalized estimating equation (GEE) with logit or log link function and random-effects regression models were used to analyse the longitudinal data on the relationship between health risk factors and the outcomes. The models were adjusted for age, sex, marital status, education background, employment status, equilibrium household income, residential area, country of birth, indigenous status, and socio-economic status.ResultsAfter adjusting for all other health risk factors covariates, physical inactivity had the greatest impact on healthcare resource utilization, work-related outcomes, and HRQoL. Physical inactivity increased the likelihood of outpatient visits (AOR = 1.60, 95% CI = 1.45, 1.76 p < 0.001), hospitalization (AOR = 1.83, 95% CI = 1.66–2.01, p < 0.001), and the probability of taking sick leave (AOR = 1.31, 95% CI = 1.21–1.41, p < 0.001), and decreased the odds of having an above population median HRQoL (AOR = 0.48, 95% CI = 0.45–0.51, p < 0.001) after adjusting for all other health risk factors and covariates. Obesity had the greatest impact on medication use (AOR = 2.02, 95% CI = 1.97–2.29, p < 0.001) after adjusting for all other health risk factors and covariates.ConclusionOur study contributed to the growing body of literature on the relative impact of health risk factors for healthcare resource utilization, work-related outcomes and HRQoL. Our results suggested that public health interventions aim at improving these risk factors, particularly physical inactivity and obesity, can offer substantial benefits, not only for healthcare resource utilization but also for productivity.

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Ben Beck; Andrew Zammit-Mangion; Richard Fry; Karen Smith; Belinda Gabbe (2023). Summaries of the posterior means of the area-specific relative risk (‘Spatial’) and the area specific yearly multiplicative change in risk (‘Temporal’) grouped by the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), classified from 1 (most disadvantage), to 5 (most advantaged). [Dataset]. http://doi.org/10.1371/journal.pone.0266521.t004
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Summaries of the posterior means of the area-specific relative risk (‘Spatial’) and the area specific yearly multiplicative change in risk (‘Temporal’) grouped by the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), classified from 1 (most disadvantage), to 5 (most advantaged).

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 14, 2023
Dataset provided by
PLOShttp://plos.org/
Authors
Ben Beck; Andrew Zammit-Mangion; Richard Fry; Karen Smith; Belinda Gabbe
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Summaries of the posterior means of the area-specific relative risk (‘Spatial’) and the area specific yearly multiplicative change in risk (‘Temporal’) grouped by the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), classified from 1 (most disadvantage), to 5 (most advantaged).

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