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background

Following a rapid increase in the prevalence of diabetes in recent decades it is estimated to affect 110 million adults in China, equivalent to over a quarter of the adult diabetes population worldwide. Diabetes appears to be associated with a higher risk of infections, but most evidence comes from studies in Western populations. Few studies have examined this association in low- and middle-income countries, including China, where differences in the typical diabetes phenotype, diabetes management and patterns of infectious diseases, compared with Western populations, may have important implications for the burden of diabetes-associated infectious diseases.

The China Kadoorie Biobank (CKB) is a prospective cohort study of 0.5 million adults recruited from 10 diverse localities in China between 2004 and 2008 (http://www.ckbiobank.org/). At baseline, extensive data were collected by questionnaire and physical measurements, and blood samples were collected for long-term storage, with genomics and metabolomics data already available on a subset of participants. All CKB participants are followed-up for cause-specific mortality and data are collected on hospitalisations. 6% of participants had self-reported or screen-detected diabetes at baseline, and by January 2016 approximately 12,000 infectious disease events were recorded.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

This DPhil project will use data from the CKB to examine various aspects of the association of diabetes with infectious diseases among adults in rural and urban areas in China. The specific focus of the project can be refined to match the interests of the candidate.

The student will work within a multi-disciplinary team, and will gain experience in conducting systematic literature reviews, study design and planning, epidemiological and statistical methodology, statistical programming, and data analysis and presentation.

field work, secondments, industry placements and training

Training opportunities will be offered as required, for example, in advanced statistical and epidemiological methods and programming. Attendance at seminars, conferences and courses provided by the Department and the University of Oxford will be encouraged.

By the end of the DPhil, it is expected that the student will be competent to plan, undertake and interpret statistical analysis of large-scale epidemiological data. The student will be expected to publish 3-5 peer-reviewed papers, and to report their findings at relevant meetings. 

prospective candidate

Candidates should have a good degree in the biomedical or life sciences and training or experience in epidemiology or statistics, including programming.

Supervisors