Respiratory diseases in diverse populations: patterns, trends, and risk factors
Worldwide, respiratory diseases cause more than 9 million deaths each year, with chronic obstructive pulmonary disease (COPD) and lung cancer being the most common causes of respiratory death. In many low-resource settings, acute (e.g. influenza, pneumonia) and chronic (e.g. tuberculosis) respiratory infections are still a major cause of death. Despite the health burden, there remain large knowledge gaps about the epidemiology of respiratory diseases in different populations. Large prospective cohort studies from geographically and genetically diverse populations are well-positioned to address these evidence gaps.
This project will utilise comprehensive data from the prospective China Kadoorie Biobank (CKB) and the UK Biobank (UKB), each of 0.5 million adults. Both studies have collected extensive exposure (e.g. lung function) and long-term health outcome (e.g. more than 1.5 million hospital episodes of >5000 different conditions in CKB) data. In addition, NDPH hosts other large cohort studies, including the Mexico City Prospective Study (150,000 participants), which could potentially be included in this multi-ethnic integrated analysis.
RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING
The specific project will be developed according to the student’s interests and aptitude, but will be likely to cover some of the following components:
- to examine and compare the incidence, patterns, and trends of different (acute and chronic) respiratory diseases in CKB and UKB;
- to characterise individuals with occurrence of multiple respiratory diseases and their long-term prognosis;
- to assess the associations of various modifiable and non-modifiable risk factors with risks of different respiratory diseases;
- to explore the potential role of co-existing chronic conditions in the susceptibility to various respiratory diseases (and vice versa).
The student will work within a multi-disciplinary team, and will gain in-house training research experience in systematic literature review, study design and planning, data analysis and scientific writing. By the end of the DPhil, the student will be competent to plan, undertake and interpret analyses of large and high dimensional datasets, and to report research findings, including publications as the lead author in peer-reviewed journals and presentation at national/international conferences.
FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING
The project will be based within the CKB research group in the Big Data Institute. There are excellent facilities and a world-class community of population health, data science and genomic medicine researchers. There may be opportunities to work with external partners from industry and other research institutions.
The ideal candidate should have an MSc in epidemiology, statistics, biomedical science, or a related discipline, with a strong interest in respiratory disease.