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.


Heart failure is a common condition requiring hospitalisation that is associated with high risks of disability and early death. Previous studies have reported substantial disparities in survival among cases with heart failure, but little is known about the epidemiology of heart failure in Chinese adults.

This DPhil project will assess the incidence, determinants and prognosis of heart failure in the China Kadoorie Biobank (CKB). CKB is a prospective study of 0.5M adults aged 30-79 years, which has over 10-years of follow-up by linkage to death and disease registries and hospital admission records ( To date, there have been >10,000 incident cases of heart failure.  Currently, medical records (including clinical, imaging, biochemical data) have been retrieved on 1000 cases to confirm diagnoses and classify heart failure into sub-types (with preserved vs reduced ejection fraction). Validation of all remaining cases will be completed over the next 2-3 years.


This DPhil project aims to

  • Confirm diagnosis of heart failure and classify subtypes of heart failure;
  • Explore algorithms for diagnosis of subtypes of heart failure using electronic medical records;
  • Assess age and sex-specific incidence of heart failure overall, by area, and socioeconomic group;

Estimate the relative and absolute risks for incident and recurrent hospital admissions and death among individuals with heart failure.


The project will be based at CTSU, Nuffield Department of Population Health, in the Big Data Institute (BDI) building, which has excellent facilities and a world-class community of population health, genetic and data scientists. 

By the end of their DPhil, it is expected that the candidate will be able to plan, undertake, interpret, and report their findings in a concise manner. The candidate will have acquired transferable skills including the writing of project proposals and presenting the research findings at local, national, and international meetings. The candidate will be expected to publish peer-reviewed papers as the lead author by the end of their DPhil.

prospective candidate

Candidates should have a degree in medicine, public health, biomedical or life sciences, have postgraduate training or experience in epidemiology and medical statistics and a willingness to extend these skills.