background

Musculoskeletal conditions including fractures and arthritis affect a large proportion of the population (one in four adults in the United Kingdom). Several dietary factors, including dietary patterns and individual foods and nutrients have been proposed to be modifiable risk factors for these conditions. For example, current projects in our group suggest that vegetarians or vegans may have a higher risk of fractures than meat eaters, but it is not clear whether the differences might be driven by differences in calcium, protein, vitamin D or other factors. For arthritis, the role of diet in its development is poorly understand, though some limited evidence suggests that meat consumption may be positively linked to this outcome.

The overall aim of this DPhil project is to investigate the associations of dietary factors and biomarkers with risk of musculoskeletal conditions, using data from EPIC-Oxford, UK Biobank and the Million Women Study.

The specific objectives of this DPhil include:

  1. To investigate the associations of different dietary factors (including dietary patterns, food groups or nutrients) with musculoskeletal conditions, including bone and joint health, using data from large prospective studies (EPIC-Oxford, UK Biobank, Million Women Study).
  2. To examine associations of dietary factors with intermediate markers of musculoskeletal health (e.g. bone mineral density, grip strength, muscle mass) in the UK Biobank.
  3. To explore potential mediators of diet with risk of musculoskeletal conditions; these may include biomarkers and metabolites (e.g. circulating levels of amino acids, fatty acids, vitamin D, insulin-like growth factor 1) that are available in UK Biobank.
  4. To use genetic approaches (Mendelian ransomisation) to assess the causal relevance of selected biomarkers.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The student will be expected to perform a literature review on the topic, and to plan and conduct cross-sectional and longitudinal statistical analyses using large-scale datasets. The student will also be expected to present the results in internal meetings, as well as at national and international conferences, and to write papers for publication in peer-review journals.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

Support and training for specific research methods and statistical analyses will be provided within the department.

PROSPECTIVE STUDENT

The project will suit someone with an interest in nutritional epidemiology. The ideal candidate will have strong quantitative skills, a background in biological sciences, nutrition or related fields, and postgraduate level training in epidemiology, statistics or public health.

Supervisors