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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 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 vegetarian diets, related dietary factors and biomarkers with risk of musculoskeletal conditions, using data from EPIC-Oxford and UK Biobank.

The specific objectives of this DPhil include:

  1. To investigate the risk of musculoskeletal conditions, including bone and joint health, in individuals following different dietary patterns, including meat eaters, fish eaters, vegetarians and vegans, in both EPIC-Oxford and UK Biobank.
  2. To examine how dietary components characteristic of vegetarian diets, such as intake of specific food groups, protein, individual amino acids or calcium, may underlie the associations between diet group and risk of musculoskeletal conditions. Dietary data are available in both EPIC-Oxford and UK Biobank. Data on intermediate markers of musculoskeletal health (e.g. bone mineral density, grip strength, muscle mass) are available in UK Biobank, and data on incidence of fractures and arthritis are available in both EPIC-Oxford and UK Biobank.
  3. To explore if biomarkers and metabolites related to diet group, including circulating levels of amino acids, vitamin D or insulin-like growth factor 1 may be related to risk of musculoskeletal conditions; these will be available in UK Biobank.

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 candidate

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