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This project will be supported with an MRC PHRU Studentship if there is a suitable candidate.

Background

Multi-morbidity is defined as the presence of two or more chronic diseases, and is a major public health challenge. Previous research has largely focussed on the study of single diseases, but planning for effective treatment and efficient delivery of health services requires the study of the determinants and prognosis of major cardio-metabolic multi-morbidity. Although the prevalence of cardio-metabolic multi-morbidity is increasing worldwide, little is known about its determinants and consequences in China.

China Kadoorie Biobank (CKB) is a prospective, population-based cohort study of >0.5 million adults recruited from 10 diverse areas in China during 2004-08 (http://www.ckbiobank.org/), with extensive lifestyle and health-related data collected at baseline and periodic resurveys. During 10 years of follow-up, ~40,000 deaths and ~0.9 million episodes of hospitalisation for >1300 different disease types have been collected through electronic linkage with established disease/death registries and with national health insurance databases. Currently, the study includes >40,000 individuals with diabetes and >50,000 with major vascular events, which creates a unique resource to investigate the relevance of the emerging field of “syndemics” for cardio-metabolic diseases.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The aims of this DPhil project, using data from the CKB, will be to:

  • Assess the incidence of cardio-metabolic multi-morbidity, by age, sex, area and socioeconomic status;
  • Identify the key lifestyle and other determinants of cardio-metabolic multi-morbidity
  • Assess the risks for recurrent hospitalisation and death associated with cardio-metabolic multi-morbidity.

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, and attendance at seminars, workshops 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. It is anticipated that the candidate will publish their results by the end of their DPhil, and that they will report their findings at relevant national and international conferences.  

Prospective candidate

Candidates should have a good degree in medicine, public health, biomedical or life sciences and postgraduate training or experience in epidemiology or statistics.

Supervisors