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Obesity and diabetes are increasing globally, while vascular mortality decreased steeply in the last decades in most Western populations. As life expectancy among European populations increases, the burden of the comorbidities associated with excess adiposity and diabetes also increases. Some studies suggest important changes in the specific comorbid diseases associated with adiposity and diabetes in recent decades, but they relied largely on electronic records rather than individual-data from prospective cohorts. This projects aims to comprehensively describe the non-fatal and fatal co-morbid conditions associated with excess adiposity and diabetes in a large contemporary population from the UK Biobank.

The UK Biobank is a prospective cohort of 0.5 million adults recruited before 2010, with a wealth of information on lifestyle, medical history, measures of adiposity, biochemistry and metabolomics assays, genetics, clinical events, hospitalisation and cause-specific mortality.

The project will examine the association of excess adiposity and diabetes with various co-morbid conditions, including non-fatal events and specific causes of death. Observational epidemiology, Mendelian randomisation, and mediation analysis techniques, will assess the associations of interest, and differences in the potential pathways underlying these associations.


The student will gain experience in non-communicable disease epidemiology and analysis of large-scale prospective data. They will develop skills in conducting systematic literature reviews, analytical techniques, research planning, statistical programming, data analysis, and presentation skills. The student will be supported to publish peer-reviewed papers as the lead author during their DPhil.


Training in advanced statistics, epidemiological methods, statistical programming, and scientific writing will be provided. Attendance at seminars, workshops and courses provided by the Department and University will also be encouraged. The candidate will have the opportunity to present their research work at relevant international/national conferences.


Candidates should have a postgraduate degree in clinical medicine, public health, epidemiology, medical statistics or genetic epidemiology. Previous experience in conducting analyses with STATA, SAS or R is essential.