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Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA)
The presented dataset relates to a research project titled “My Home My Community” undertaken at University of Technology Sydney (UTS) which has been funded by the National Disability Insurance Agency (NDIA) Australia. The dataset reports estimated prevalence rates of Intellectual Disability in NSW b...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7243054/ https://www.ncbi.nlm.nih.gov/pubmed/32462063 http://dx.doi.org/10.1016/j.dib.2020.105673 |
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author | Carnemolla, Phillippa Srasuebkul, Preeyaporn Robertson, Hamish Trollor, Julian Nicholas, Nick |
author_facet | Carnemolla, Phillippa Srasuebkul, Preeyaporn Robertson, Hamish Trollor, Julian Nicholas, Nick |
author_sort | Carnemolla, Phillippa |
collection | PubMed |
description | The presented dataset relates to a research project titled “My Home My Community” undertaken at University of Technology Sydney (UTS) which has been funded by the National Disability Insurance Agency (NDIA) Australia. The dataset reports estimated prevalence rates of Intellectual Disability in NSW by local government area (LGA) from 2010 – 2015. The dataset is a re-examination of a cohort of 92, 542 people with intellectual disability from a larger linked research dataset built by the Department of Developmental Disability Neuropsychiatry, School of Psychiatry, UNSW. The dataset in this paper is presented in a multi-year cross-sectional format. The cohort of people with Intellectual Disability was analysed to estimate, quantify and visualise where people with intellectual disability live in New South Wales (NSW). The cohort analysed in this dataset had been generated in an earlier project undertaken by the UNSW-based authors. This dataset was generated to share with local governments in Australia and has the potential to be more widely used in a range of health policy and planning research, and city and regional planning research environments. It represents one of the only datasets currently available in Australia on Intellectual Disability describing prevalence rates at a local government area level. This dataset allows for population comparisons in other Australian states and internationally and can be examined in combination with other social and economic datasets to continue to build evidence about disability, planning and geography. |
format | Online Article Text |
id | pubmed-7243054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-72430542020-05-26 Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) Carnemolla, Phillippa Srasuebkul, Preeyaporn Robertson, Hamish Trollor, Julian Nicholas, Nick Data Brief Decision Science The presented dataset relates to a research project titled “My Home My Community” undertaken at University of Technology Sydney (UTS) which has been funded by the National Disability Insurance Agency (NDIA) Australia. The dataset reports estimated prevalence rates of Intellectual Disability in NSW by local government area (LGA) from 2010 – 2015. The dataset is a re-examination of a cohort of 92, 542 people with intellectual disability from a larger linked research dataset built by the Department of Developmental Disability Neuropsychiatry, School of Psychiatry, UNSW. The dataset in this paper is presented in a multi-year cross-sectional format. The cohort of people with Intellectual Disability was analysed to estimate, quantify and visualise where people with intellectual disability live in New South Wales (NSW). The cohort analysed in this dataset had been generated in an earlier project undertaken by the UNSW-based authors. This dataset was generated to share with local governments in Australia and has the potential to be more widely used in a range of health policy and planning research, and city and regional planning research environments. It represents one of the only datasets currently available in Australia on Intellectual Disability describing prevalence rates at a local government area level. This dataset allows for population comparisons in other Australian states and internationally and can be examined in combination with other social and economic datasets to continue to build evidence about disability, planning and geography. Elsevier 2020-05-12 /pmc/articles/PMC7243054/ /pubmed/32462063 http://dx.doi.org/10.1016/j.dib.2020.105673 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Decision Science Carnemolla, Phillippa Srasuebkul, Preeyaporn Robertson, Hamish Trollor, Julian Nicholas, Nick Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) |
title | Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) |
title_full | Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) |
title_fullStr | Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) |
title_full_unstemmed | Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) |
title_short | Prevalence of intellectual disability in New South Wales, Australia: a multi-year cross-sectional dataset by Local Government Area (LGA) |
title_sort | prevalence of intellectual disability in new south wales, australia: a multi-year cross-sectional dataset by local government area (lga) |
topic | Decision Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7243054/ https://www.ncbi.nlm.nih.gov/pubmed/32462063 http://dx.doi.org/10.1016/j.dib.2020.105673 |
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