The Mechanisms Relating Fruit and Vegetable Consumption to Cardiovascular Disease in UK Biobank
Meta-analyses of prospective cohort studies have suggested that compared to those eating fewer than 3 servings of fruit or vegetables a day, the risk of cardiovascular disease (CVD) was approximately 17-26% lower for those eating more than 5 servings a day (1-2). However, the mechanisms underlying the association between fruit and vegetable intake and CVD are unclear; and effects of residual confounding, measurement error and heterogeneity in subclasses of fruit/vegetable consumption need to be investigated as well.
This project will address these questions using the UK Biobank cohort study of 0.5 million participants with information on general dietary intake, with up to five 24-hour dietary recalls in a sub-sample of 210,000 participants. Blood and urine biomarkers, and prospective follow up with hospital and mortality data are also available.
1. Assess the reliability of urinary potassium as a biomarker of self-reported fruit and vegetable intake on UK Biobank’s measurements of dietary intake. (Year 1)
2. Examine if fruit/vegetable intake is associated with cardiovascular risk factors such as serum cholesterol, blood pressure and inflammatory markers. (Years 1-2)
3. Examine the associations of different subclasses of fruit and vegetables with blood biomarkers. (Year 2)
4. Assess if the associations between fruit/vegetable intake and intermediate biomarkers mediate the association between fruit/vegetable intake and incident CVD events. (Year 2-3)
5. Evaluate if the associations between fruit/vegetable intake, intermediate biomarkers and CVD remain independent when other aspects of healthy lifestyles and dietary intake are controlled. (Year 3)
1. He, F., et al., J human hypertension, 2007. 21(9).
2. He, F.J., C.A. Nowson, and G.A. MacGregor. The Lancet. 367(9507).
Research experience, research methods and training
The student will be provided with training in statistical and epidemiological methods, literature reviews and writing academic papers for peer-reviewed journals. The project is based in the NDPH CTSU which has excellent computational facilities, infrastructure and a strong interdisciplinary team with expertise in epidemiology, statistics, nutrition, clinical medicine and biochemistry. The NDPH has regular seminars and workshops, and strongly supports attendance at meetings to present research findings and develop further expertise.
Students will require previous programming experience using statistical analysis packages and analysis of large datasets. An interest in nutritional epidemiology and/or cardiovascular disease would be an advantage.