Geographic Classification for Health - Concordance Files

These datasets are concordance files that link the Geographic Classification for Health (GCH) to statistical geographies and geographic units commonly used in health research and analysis in Aotearoa New Zealand (NZ). More information about the develppment of the GCH is available in our <strong>Open Access publication.</strong> 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: <strong>SA12018_to_GCH2018.csv </strong>This concordance file applies a GCH category to each SA1 in NZ <strong>SA22018_to_GCH2018.csv </strong>This concordance file applies a GCH category to each SA2 in NZ <strong>MoH_HDOM_to_GCH2018.csv</strong> This concordance file applies a GCH category to each Domicile in NZ. <em><strong>Please read the additional information below if you plan to use this concordance file.</strong></em> <strong>MoH_MB_to_GCH2018.csv </strong>This concordance file applies a GCH category to each Meshblock in NZ. <em><strong>Please read the additional information below if you plan to use this concordance file. </strong></em> <strong>Additional information relating to geographic units used by the Ministry of Health:</strong> <strong>MoH_HDOM_to_GCH2018.csv </strong>This file has been designed specifically to add GCH to the Ministry of Health (MoH) datasets containing Domicile codes. Use this file if your dataset contains only Domicile codes. If your dataset also contains Meshblock codes, then use the MoH Meshblock to GCH concordance file. This file includes 2006 and 2013 domicile codes. The 2013 domiciles are still current as of 2022, and this file will still work well with data outside those years. Domicile boundaries do not align well with SA1 boundaries, and longitudinal health data usually contains some older Domiciles which have been phased out and replaced with multiple smaller Domiciles. These deprecated Domiciles may overlap multiple SA1s. Usually, all such SA1s belong to the same GCH category. Occasionally, a Domicile will overlap more than one GCH category. When this happens, we have assigned the GCH category to which the majority of people living in that Domicile belong. By necessity, this will allocate a minority of people in those Domiciles to a GCH category to which they do not belong. <strong>MoH_MB_to_GCH2018.csv</strong> This file has been designed specifically to add GCH to Ministry of Health (MoH) datasets containing Meshblock codes. This file includes 2018, 2013, 2006, and 2001 Meshblock codes, but will still work well with data outside those years. Meshblock boundaries from census 2018 fit perfectly and completely within the Statistics New Zealand Statistical Area 1s (SA1) boundaries on which GCH is based. However, longitudinal health data usually contains some older Meshblocks which have been phased out and replaced by multiple smaller Meshblocks. These deprecated Meshblocks may overlap multiple SA1s. Usually, all such SA1s belong to the same GCH category. Occasionally, a Meshblock will overlap more than one GCH category. When this happens, we have assigned the GCH category to which the majority of people living in that Meshblock belong. By necessity, this will allocate a minority of people in those Meshblocks to a GCH category to which they do not belong. <br>本数据集为关联对照表，用于将健康地理分类（Geographic Classification for Health, GCH）与奥特亚罗瓦新西兰（Aotearoa New Zealand，简称新西兰）卫生研究与分析中常用的统计地理单元及行政区划进行匹配。有关健康地理分类（GCH）的开发详情，可参阅本团队的开源获取出版物。 本团队的长期目标是全面且精准地掌握国家及区域层面上健康结局与医疗服务利用的城乡差异。推动健康研究人员与卫生政策制定者广泛采用健康地理分类（GCH），是实现这一目标的最佳途径。 健康地理分类（GCH）操作简便，多数用户仅需获取对应的关联对照表即可。统计区域1级（Statistical Area 1, SA1，即承载人口数据输出的小型统计单元）被用作健康地理分类（GCH）的基础构建单元，也是使用GCH开展健康数据分析时的优先选用小型地理单元。 但需说明的是，多数健康数据无法获取SA1级别的粒度，因此本数据集同时提供针对居住单元（普查区域单元，Census Area Units, CAU）、统计区域2级（Statistical Area 2, SA2）以及网格块（Meshblock）的GCH关联对照表。 以下为Excel格式的关联对照表： <strong>SA12018_to_GCH2018.csv</strong>：本对照表可为新西兰境内的每一个SA1匹配对应的GCH分类。 <strong>SA22018_to_GCH2018.csv</strong>：本对照表可为新西兰境内的每一个SA2匹配对应的GCH分类。 <strong>MoH_HDOM_to_GCH2018.csv</strong>：本对照表可为新西兰境内的每一个居住单元匹配对应的GCH分类。<em><strong>若计划使用本对照表，请务必阅读下方的补充说明。</strong></em> <strong>MoH_MB_to_GCH2018.csv</strong>：本对照表可为新西兰境内的每一个网格块匹配对应的GCH分类。<em><strong>若计划使用本对照表，请务必阅读下方的补充说明。</strong></em> <strong>新西兰卫生部（Ministry of Health, MoH）所用地理单元补充说明：</strong> <strong>MoH_HDOM_to_GCH2018.csv</strong>：本文件专为将GCH分类添加至包含居住单元编码的新西兰卫生部（MoH）数据集而设计。若您的数据集仅包含居住单元编码，请使用本文件；若您的数据集同时包含网格块编码，请使用新西兰卫生部网格块-GCH关联对照表。本文件涵盖2006年及2013年的居住单元编码，截至2022年，2013年版居住单元仍在使用，本文件对对应年份外的数据同样适用。 居住单元边界与SA1边界无法较好匹配，且纵向健康数据通常包含部分已被淘汰、由多个更小居住单元替代的旧版居住单元。此类已淘汰的居住单元可能覆盖多个SA1，通常情况下，这些被覆盖的SA1均属于同一GCH分类；偶尔也会出现单个居住单元覆盖多个GCH分类的情况，此时我们将根据居住单元内绝大多数居住人口所属的GCH分类进行赋值。此举不可避免地会将部分居住在该单元内的人群划分至与其实际所属不符的GCH分类中。 <strong>MoH_MB_to_GCH2018.csv</strong>：本文件专为将GCH分类添加至包含网格块编码的新西兰卫生部（MoH）数据集而设计。本文件涵盖2018、2013、2006及2001年的网格块编码，对对应年份外的数据同样适用。2018年人口普查的网格块边界完全契合并包含于GCH所依托的新西兰统计局SA1边界内。 但纵向健康数据通常包含部分已被淘汰、由多个更小网格块替代的旧版网格块。此类已淘汰的网格块可能覆盖多个SA1，通常情况下，这些被覆盖的SA1均属于同一GCH分类；偶尔也会出现单个网格块覆盖多个GCH分类的情况，此时我们将根据该网格块内绝大多数居住人口所属的GCH分类进行赋值。此举不可避免地会将部分居住在该网格块内的人群划分至与其实际所属不符的GCH分类中。<br>