Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.


There is inconsistent evidence regarding the association between depression and dementia; it is unclear if depression is an independent risk factor for dementia or a prodromal symptom and what the role of antidepressant medication is. Prospective studies with long follow-up are needed to disentangle these associations.  


The main aim of the project is to examine risk of dementia in relation to depression and the use of anti-depressants, taking careful account of the potential for reverse causation. Further aims are to examine how any association between depression and dementia is modified by vascular risk factors and genetic determinants of depression and dementia. The project will involve analysis of data from the prospective Million Women Study, which includes over a million UK women recruited 20 years ago. Self-reported treatment for depression and history of depression was collected. The project allows adjustment for putative confounders such as education, alcohol intake and other life-style factors. The entire cohort has been followed for incidence of dementia and its subtypes. For the gene-interaction studies, the project may involve analysis of relevant data from the prospective UK Biobank.  The UK Biobank will further allow an in-depth evaluation of vascular metabolites.  Finally, the project aims to validate epidemiological findings using genetic data as instrumental variables (Mendelian Randomisation).


Training will be provided by the department as required on data analysis, record linkage between multiple research databases, and statistical methods, and if necessary, by external courses.

Prospective candidate

The candidate should have an MSc degree in public health, epidemiology or statistics.