A unique opportunity has arisen via the MRC GW4 BioMed Doctoral Training Partnership for a student with very strong quantitative skills to investigate the risk relationships between different ‘physical activity profiles’ and cardiometabolic disease outcomes. This project will help develop individualised prevention strategies, inform future policy and assist with technological innovation.
During 2013-14 there were 1.7 million hospital episodes related to cardiovascular disease in the UK, with £4.3 billion spent through NHS Clinical Commissioning Groups on treating cardiovascular disease. In the same time period there were also over 3.3 million diagnosed diabetes patients in the UK.
It is widely accepted that physical activity has a potentially important role in prevention of cardiometabolic disease, however, there is still a lack of consensus on the strength and dose-response relationship between physical activity and non-communicable disease outcomes. Convenience for analysis has often resulted in researchers collapsing the multidimensional nature of physical activity into a relatively small number of summary statistics, which has limited our understanding of the activity-health relationship to date. Examples of such summaries include time spent in vigorous intensity, moderate intensity, or light intensity activities, sedentary time, and overall energy expenditure. A key aim of this project is to explore statistical modeling approaches which make better use of the available data. Considering information from numerous physiologically important activity dimensions together may be critical in understanding associations with chronic disease and presents an important new area for epidemiological research.
This project brings together Bristol Physical Activity Epidemiologist (Dr Miranda Armstrong
), with expertise in large-scale prospective data analysis, Bath Statistician (Dr Nicole Augustin), with expertise in methods development for physical activity profile analysis, and Bath Exercise Physiologist (Prof. Dylan Thompson), who has conducted a trial using individual physical activity profiles in patients at high risk of developing cardiometabolic disease (Mi-PACT).
The project will be best suited to a student with very strong statistical/applied mathematics skills. The student will develop practical skills related to the processing of data in very large datasets, linkage to health records, and the refinement and use of novel statistical methods in survival analyses.
The project aims to:
- Refine statistical methods to represent accelerometry data as functional summaries and then use these in survival analyses.
- Apply these methods to the development of integrated physical activity profiles, that will be related to the incidence and mortality of cardiometabolic diseases identified from linkage to electronic health records.
- Develop a ‘scoring system’ that integrates information from across the activity dimensions to make it easier for people to understand the risks associated with their physical activity profiles, informed by the epidemiological results of the study.
The deadline for applications is 24 November 2017 and the first round of interviews is expected to take place between 3-12 January 2018.
For informal enquiries - Email: GW4BioMed@cardiff.ac.uk
For project related queries - Email: Miranda.Armstrong@bristol.ac.uk