Abstract
The health of populations is routinely monitored and analysed in order to identify inequalities and risk factors, and organise responses. To do this, data are typically aggregated into groups and units but the way in which those aggregate units are defined can have considerable impacts on what conclusions are drawn. The importance of this phenomenon is visited in the context of dental and mental health, demonstrating how different aggregations can yield different results. Automated zoning tools are used to calculate summary results of both association studies and mapping exercises, which are derived from a wide variety of scale-appropriate aggregations.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Award date | 24 May 2021 |
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| Publication status | Unpublished - 2020 |
Access to Document
- THESIS - DOCTOR OF PHILOSOPHY - YAP Matthew - 2020
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