Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom

Oldroyd, RA orcid.org/0000-0003-3422-7396, Hobbs, M, Campbell, M et al. (9 more authors) (2021) Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom. Applied Spatial Analysis and Policy, 14 (4). pp. 1025-1040. ISSN 1874-463X

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Data linkage; Collaboration; International; Geohealth; Health geography
Dates:
  • Accepted: 20 April 2021
  • Published (online): 29 April 2021
  • Published: December 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds)
Funding Information:
FunderGrant number
ESRC (Economic and Social Research Council)ES/S007164/1
Alan Turing InstituteNo ref given
Depositing User: Symplectic Publications
Date Deposited: 23 Apr 2021 14:55
Last Modified: 16 Jan 2023 16:26
Status: Published
Publisher: Springer
Identification Number: https://doi.org/10.1007/s12061-021-09381-8

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