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Adiposity and diabetes are major, increasing, public health challenges globally, contributing to excess premature mortality from vascular and other metabolic causes. The determinants of such major cardio-metabolic diseases (e.g. diabetes, ischemic heart disease, stroke and other vascular causes) include modifiable lifestyle factors such as physical activity, dietary patterns, smoking and drinking habits. Understanding of the potential mechanisms underlying the associations between these lifestyle determinants and cardio-metabolic diseases would provide valuable insight in disease aetiology, and also facilitate the development of public health strategies for disease prevention.

Recent developments in high-throughput metabolomics assays, such as nuclear magnetic resonance (NMR) spectroscopy, permit assessment of the interplay between lifestyle habits, intermediate biomarkers and cardio-metabolic disease risk. The UK Biobank study includes  detailed information on lifestyle characteristics, traditional biochemistry measures, NMR-measured metabolites, genetic assays, and cardio-metabolic diseases among 0.5 million adults recruited in 2006-10 and followed prospectively.

This project will apply epidemiological techniques to examine the associations of various lifestyle characteristics with a wide range of novel and traditional NMR-biomarkers (e.g. lipids, including their classes and particle sizes, markers of inflammation, glucose, and liver function), in order to further understand the relevance of these lifestyle factors to incidence or mortality from different subtype of cardio-metabolic diseases. Mediation analyses will estimate how much of the associations of various lifestyle characteristics are explained by various biomarkers. Additionally, genetic approaches could be performed to assess potential novel causal pathways underlying the associations of interest.


The student will gain experience in non-communicable diseases epidemiology using large-scale prospective data. The project will provide an extensive range of training opportunities through attending specific courses, meetings, workshops and seminars, along with regular supervisory meetings. The student will develop skills in conducting systematic literature reviews, study design and planning, statistical programming, data analysis, including Mendelian randomisation and different types of mediation analyses, and presentation skills. The student will be supported to publish peer-reviewed papers as the lead author during 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 opportunities to present research work at relevant international/national conferences.


Candidates should have a good degree in clinical medicine, public health, biomedical or life sciences. Previous postgraduate training or experience in epidemiology or statistics and proficiency with STATA, SAS or R are desirable.