Diego J. Aguilar-Ramírez

Supervisors: Prof Jonathan Emberson, Dr William Herrington, Dr Natalie Staplin and Prof Colin Baigent

I am a physician from Mexico City, where I did my undergraduate degree in medicine. After a few years of work as a research assistant in public health, I came to Oxford to attend the MSc in Global Health Science and Epidemiology. Deciding then to pursue a research degree, I was successful in applying to the DPhil programme in Population Health, beginning my studies and joining Lincoln College in Michaelmas 2018.

Apart from offering an excellent platform for learning about and doing research, Oxford has been full of opportunities and support for me as an international student. I was fortunate to receive scholarships from the Nuffield Department of Population Health and the British Heart Foundation Centre for Research Excellence to fund my studies fully, an opportunity without which I would not have been able to pursue post-graduate education.

My research focuses on assessing the relevance to cardio-metabolic disease mortality of dozens of nuclear magnetic resonance spectroscopy-measured metabolic biomarkers in blood using data from 150,000 adults from Mexico City recruited into a cohort study in 1998-2004 – the largest epidemiological study of a Hispanic population worldwide. Doing research that is relevant for my home country has proved to be powerfully motivating and deeply valuable. Apart from research, I collaborate as a teaching assistant on the Statistics module taught within the MSc in Global Health Science and Epidemiology offered by the department.

Undergraduate degree: Medicine, Universidad Panamericana, Mexico City

Studentship dates: 2018 - 2021

Diego is now an Early Career Research Fellow at the Mexico City Prospective Study group, within the Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) at the University of Oxford. His research focuses on investigating the metabolic profiles of obesity, diabetes, kidney disease, and heart disease in the Mexican population, using observational and genetic epidemiology methods.