An investigation of the utilisation of health impact assessments (HIAs) in Irish public policy making

It is the aim of this thesis to investigate Health Impact Assessment (HIA) use in public policy formulation in Northern Ireland and in the Republic of Ireland. The influences affecting the use of HIAs will be examined in this study. Four case studies, where HIA has been conducted, will be used for research analysis. This includes HIAs conducted on traffic and transport in Dublin, Traveller accommodation in Donegal, a draft air quality action plan in Belfast and on a social housing regeneration project in Derry. HIA aims to identify possible intended and unintended consequences that a project, policy or programme will have on the affected population’s health. Although it has been acknowledged as a worthwhile tool to inform decision-makers, the extent to which it is used in policy in Ireland is subject to scrutiny. A theoretical framework, drawing from institutionalist, impact assessment and knowledge utilisation theories and schools of literature, underpin this study. The investigation involves an examination of the unit of analysis which consists of the HIA steering groups. These are made up of local authority decision makers, statutory health practitioners and community representatives. The overarching structure and underlying values which are hypothesized as present in each HIA case are investigated in this research. Chapters 2 and 3 outline the main literature in the area which includes theories from the public health and health promotion paradigm, the policy sciences and impact assessment techniques. Chapter 4 describes the methodology in this research which is a multiple case study design. This is followed by an analysis of the cases and then concludes with practical recommendations for HIA in Ireland and theoretical conclusions of the research.

Statistical considerations in the kinetic analysis of PET-FDG brain tumour studies

Dynamic positron emission tomography (PET) imaging can be used to track the distribution of injected radio-labelled molecules over time in vivo. This is a powerful technique, which provides researchers and clinicians the opportunity to study the status of healthy and pathological tissue by examining how it processes substances of interest. Widely used tracers include 18F-uorodeoxyglucose, an analog of glucose, which is used as the radiotracer in over ninety percent of PET scans. This radiotracer provides a way of quantifying the distribution of glucose utilisation in vivo. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue function. As the residue represents the amount of tracer remaining in the tissue, this can be thought of as a survival function; these functions been examined in great detail by the statistics community. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as ow, ux and volume of distribution. This thesis presents a Markov chain formulation of blood tissue exchange and explores how this relates to established compartmental forms. A nonparametric approach to the estimation of the residue is examined and the improvement in this model relative to compartmental model is evaluated using simulations and cross-validation techniques. The reference distribution of the test statistics, generated in comparing the models, is also studied. We explore these models further with simulated studies and an FDG-PET dataset from subjects with gliomas, which has previously been analysed with compartmental modelling. We also consider the performance of a recently proposed mixture modelling technique in this study.