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Modelling the Impacts of Demographic Ageing on the Demand for Health Care Services

Clark, Stephen Darren (2015) Modelling the Impacts of Demographic Ageing on the Demand for Health Care Services. PhD thesis, University of Leeds.

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This thesis presents a methodology that predicts the number of individuals aged 50 and older who have one or more of three morbidities within each English local authority district to 2031. The three morbidities are cardiovascular disease, diabetes or high blood sugar and respiratory illnesses. The methodology uses spatial microsimulation to create a representative 2011 base population in each district. This population is then dynamically simulated through time using a process that: ages the population, changes its morbidity status, restructures its composition along demographic lines and replenishes the population at younger ages. An accounting system is used to examine how the demographic changes within each district influence its health status. In terms of prevalence counts and rates the prediction is for significant reductions in both these measures for CVD. For respiratory illness, the prevalence count remains fairly constant but due the increases in the size of the population at risk, the prevalence rate decreases. With diabetes or high blood sugar, both the prevalence counts and rates increase. Examination of the demographic changes affecting these prevalences shows that for the more ethnically diverse districts the changing ethnic structure has a large impact whilst for the more prospering districts the changing age structure has the largest impact. These results suggest that public health messages on circulatory and heart conditions and the reduction in smoking will have beneficial health effects in the future, which will help to mitigate the strains placed on the health care system in England. The prospects for diabetes or high blood sugar are however not so good and some considerations on how best to utilise scarce resources to prevent or treat this morbidity are urgently required.

Item Type: Thesis (PhD)
Keywords: Health Elderly Microsimualtion Forecasting
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds)
Identification Number/EthosID: uk.bl.ethos.678067
Depositing User: Mr Stephen Clark
Date Deposited: 27 Jan 2016 13:17
Last Modified: 26 Apr 2016 15:44
URI: http://etheses.whiterose.ac.uk/id/eprint/11676

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