About
Great concern has been paied on the public health issues of stroke and stroke-related diseases globally. It is critical to identify the characteristics and specific dietary risk factors for recommendations of evidence-based stroke interventions and prevention. It has been shown that stroke incidence are associated with several individual dietary lifestyles, such as coffee, tea, and fish consumption. However, it remains to be investigated for other important associations through large-sample cohort study. Valuable predictive models have not been developed for subtypes of stroke and related diseases.
In this 3-year project, we aim to identify potential dietary habits associated with stroke and stroke-related diseases (cerebral and precerebral atheroslerosis, intracranial aneurysm, vascular dementia, et al) using data of the UK Biobank cohort. With big data analytics applied in medical community, the cohort data of a large sample size and large scale of variables can be conducted to assess the incidence, hospitalization and mortality risk of stroke and stroke-related diseases with a higher accuracy, further to promote the accuracy and precision of stroke prevention. The obtained results will be free access to research community.