Creating a health/deprivation geodemographic classification system using k-means clustering methods /
This research case study presents the findings of work specifically designed to investigate the usefulness of using geodemographics to profile areas based on health outcome. It seeks to identify local authorities in England which may currently be at risk from problems linked to household deprivation...
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| Format: | eBook |
| Language: | Undetermined |
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[Place of publication not identified]
Sage Publications Ltd,
2017.
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | This research case study presents the findings of work specifically designed to investigate the usefulness of using geodemographics to profile areas based on health outcome. It seeks to identify local authorities in England which may currently be at risk from problems linked to household deprivation and matters regarding poor health/illness or those in danger of deterioration. Presented in this case study is a guide through seven phases of geodemographic system development. The phases range from identifying a clear purpose for the system through to clustering via the k-means algorithm, profiling, and better understanding the demographic composition of an area. All phases are evidenced through a 2009 study seeking to identify local authorities in England which may be "at risk" from matters linked to deprivation and poor general health. The work is presented as a methodological overview of geodemographic system development. Although results are presented and discussed, the primary purpose is to showcase geodemographics as a useful tool for data reduction, mining, and spatial presentation in the context of health and deprivation. This study makes use of the 2001 UK Census and illustrates how a broad selection of variables can be used to create a geodemographic system designed to reflect the socioeconomic conditions in each of Englands 388 local authorities. A hands-on opportunity is presented at the end of the case study providing details of how to replicate the classification using more recent 2011 census data. |
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| Item Description: | Title from content provider. |
| Physical Description: | 1 online resource |
| ISBN: | 9781473977839 1473977835 |