Abstract
These datasets are concordance files that link the Geographic Classification for Health (GCH23) to statistical geographies and geographic units commonly used in health research and analysis in Aotearoa New Zealand (NZ).
More information about the development of the GCH is available in our publication: Whitehead, J., et al. (2022). Defining rural in Aotearoa New Zealand: a novel geographic classification for health purposes. The New Zealand medical journal, 135(1559), 24–40. https://doi.org/10.26635/6965.5495
Our long-term aim is the comprehensive and accurate understanding of urban-rural variation in health outcomes and healthcare utilization at both national and regional levels. This is best achieved by the widespread uptake of the GCH by health researchers and health policy makers. The GCH is straightforward to use and most users will only need the relevant concordance file.
Statistical Area 1s (SA1s, small statistical areas which are the output geography for population data) were used as the building blocks for the Geographic Classification for Health (GCH) and are the preferred small areas when undertaking the analysis of health data using the GCH. It is however appreciated that a lot of health data is not available at the SA1 level and GCH concordance files are also available for Domicile (Census Area Units, CAU) and Statistical Area 2s (SA2) and Meshblock.
The following concordance files are available in excel format:
• SA12023_to_GCH2023.csv This concordance file applies a GCH category to each SA1 in NZ
• SA22023_to_GCH2023csv This concordance file applies a GCH category to each SA2 in NZ
• MoH_HDOM_to_GCH2023.csv This concordance file applies a GCH category to each Domicile in NZ. Please read the additional information on the Figshare dataset record if you plan to use this concordance file.
• MoH_MB_to_GCH2023.csv This concordance file applies a GCH category to each Meshblock in NZ. Please read the additional information on the Figshare dataset record if you plan to use this concordance file.