Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.728667
Title: Developing statistical models to assess the effects of socioeconomic position on the incidence of and outcome from type 2 diabetes in older adults
Author: Steele, Christopher James
ISNI:       0000 0004 6495 1331
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2017
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Abstract:
With the increasing prevalence of obesity and the increasing proportion of older adults, type 2 diabetes (T2D) is becoming a massive public health problem. T2D is associated with socioeconomic position (SEP) where individuals from lower SEP suffer a disproportionate burden of the disease and older adults may be particularly vulnerable to experiencing socioeconomic inequalities. Furthermore, T2O complications can cause vast increases in the expenditure of healthcare services and possibly detrimental effects on an individual’s health. During this thesis the effect of SEP on the incidence of T2D and outcome from T2D are investigated in older adults. To examine the relationship between SEP and T2D incidence in older adults, a mediator analysis Is implemented. This analysis is conducted to determine characteristics that influence the association in older adults, identifying possible targets for intervention that could reduce the socioeconomic gap in T2D incidence. Of the risk factors investigated, body mass index was identified as the risk factor that explained the greatest proportion of the association. A register based dataset of older adults with T2D is utilised to examine the effects* of SEP on the outcome from T2D. A novel Markov approach is introduced to model the rate that individuals with T2D transition from diagnosis to complication. By interpreting the underlying phases an insight into the position of an individual on the disease to complication pathway can be gained. The Markov model identified two distinct stages of the transition from T2D diagnosis to complication. Finally, a novel approach is presented in order to calculate a predictive time interval from T2D diagnosis until the occurrence of a complication, achieved using a combination of survival tree, parametric modelling and simulation techniques. Lower SEP individuals are consistently predicted to experience a complication of T2D earlier than a similar group of individuals in higher SEP.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.728667  DOI: Not available
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