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Diabetes now affects over 100 million adults in China, accounting for over a quarter of the diabetes population worldwide. Individuals with diabetes are at a higher risk of developing infections, but evidence is rather limited in low- and middle-income countries, including China, where differences in detection and management of diabetes, patterns of infectious diseases and genetic susceptibility, compared with Western populations, may have important implications for the burden of diabetes-associated infections.

The China Kadoorie Biobank (CKB) is a prospective cohort study of >0.5 million adults recruited from 10 diverse urban and rural areas in China during 2004-08. At baseline ~6% of participants had previously-diagnosed or screen-detected diabetes. After 10-years of follow-up, >12,000 infectious disease events and >14,000 cases of new-onset diabetes have been recorded among CKB participants. These data are complemented by large-scale genetic data (800,000 SNPs currently available in 100,000 participants) and blood-related infectious markers data involving 20 pathogens in a subset of 2,000 participants.


The overall aim of this DPhil project will be to comprehensively assess the burden of, and risk factors for, diabetes-related infectious complications in Chinese adults. Using data from the CKB, the project objectives will include:

  • Characterisation of the frequency and patterns of infectious diseases among individuals with and without diabetes;
  • Examination of the association of diabetes with infectious diseases and how these associations are modified by other factors (e.g., smoking).

Depending on the interests of the student, the project may also include:

  • Investigation of the association of diabetes with prevalence of seropositivity of pathogens in a subset of participants;
  • Exploration of the role of genetic susceptibility in the association of diabetes with infection.

The student will work within a multi-disciplinary team, and will gain experience in conducting systematic literature reviews, study design and planning, statistical programming, and data analysis and presentation. The student will be expected to publish peer-reviewed papers as the lead author by the end of their DPhil. 


Training in advanced statistics, epidemiological methods, programming, and scientific writing will be provided. Attendance at seminars, workshops and courses provided by the department and university will also be encouraged. There will be opportunity to present research work at relevant international/national conference. 

Prospective candidate

Candidates should have a degree in clinical medicine, public health, biomedical or life sciences. Previous postgraduate training or experience in epidemiology or statistics is essential.