MBChB MSc DPhil FFPH
Senior Clinical Research Fellow
- Clinical Trial Service Unit & Epidemiological Studies Unit (‘CTSU’)
Ben Lacey studied medicine at the University of Edinburgh, qualifying in 2004. He trained as a specialist in public health in Oxford, during which time he received a master's degree in Global Health Science and a doctorate in Epidemiology. He is a Fellow of the Faculty of Public Health (UK) and an Honorary Consultant in Public Health Medicine at Oxford University Hospitals NHS Trust. He joined the Nuffield Department of Population Health in 2015, where he leads a programme of work using routine health data (including electronic health records) and large-scale prospective cohort studies to understand the burden and determinants of vascular disease.
Blood Pressure and Risk of Subarachnoid Hemorrhage in China.
McGurgan IJ. et al, (2018), Stroke
Body-mass index, blood pressure, and cause-specific mortality in India: a prospective cohort study of 500 810 adults.
Gajalakshmi V. et al, (2018), Lancet Glob Health, 6, e787 - e794
Age-specific association between blood pressure and vascular and non-vascular chronic diseases in 0·5 million adults in China: a prospective cohort study.
Lacey B. et al, (2018), Lancet Glob Health, 6, e641 - e649
Adiposity and risk of ischaemic and haemorrhagic stroke in Chinese men and women: a prospective study of 0.5 million adults
Chen Z. et al, (2018), The Lancet Global Health
Age-specific relation of blood pressure to vascular and non-vascular chronic disease in China: a prospective study of 0.5 million adults
Lacey BWH. et al, (2018), The Lancet Global Health
- Accurately estimating the burden of vascular disease using electronic health records
- Adiposity, body fat distribution and risk of chronic disease in Asian and European populations
- Analysing big data from electronic health records to understand the determinants of cardiovascular disease
- Deep phenotyping of vascular events in large-scale epidemiological studies using electronic health records
- Understanding and modelling the geographical variation in relative risks for smoking and other major risk factors for burden of disease analyses