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Background
Diabetes is highly prevalent in Mexico and is associated with substantially increased risks of cardiovascular and kidney disease. Mexico has one of the highest diabetes mortality rates worldwide, yet national mortality statistics report lower rates of vascular mortality than might be expected given the prevalence of diabetes and obesity.
One possible explanation is differences in death certification. When people with diabetes die from vascular or kidney disease, diabetes may be recorded as the underlying cause of death more often than in other countries. Similar coding practices have also been reported for kidney disease, making comparisons across countries and over time difficult.
The Mexico City Prospective Study (MCPS) provides a unique opportunity to investigate this issue. Among approximately 30,000 deaths, clinicians have systematically reviewed death certificates and re-adjudicated underlying causes of death according to international coding standards. These data provide an exceptional resource for understanding how death certification influences estimates of vascular, kidney, and diabetes mortality and for improving national mortality statistics.
This DPhil will combine MCPS data with publicly available national multi-cause mortality data to investigate how death certification practices influence estimates of cause-specific mortality in Mexico.
The project is expected to include:
- Estimating national and regional mortality rates using multi-cause mortality data;
- Developing statistical approaches to improve cause-of-death classification using clinician-adjudicated MCPS data;
- Quantifying the impact of coding practices on vascular, kidney, and diabetes mortality estimates; and
- Comparing revised mortality patterns in Mexico with those in other Latin American countries
Research experience, research methods and skills training
The student will develop expertise in epidemiology, advanced statistical analysis, data science, and scientific writing while working with one of the world's largest prospective cohort studies. They will be supported by an interdisciplinary team of epidemiologists, clinicians, statisticians, and demographers, and encouraged to develop aspects of the project in line with their own research interests.
Field work, secondments, industry placements and training
The project will be based with the MCPS group at the Oxford Big Data Institute. On-site training opportunities will focus on epidemiology, statistical programming, reproducible research, and scientific writing. The student will have opportunities to present their work at conferences, publish in peer-reviewed journals, and, where appropriate, visit collaborators in Mexico.
Prospective Student
We welcome applications from candidates with a Bachelor's or Master's degree in epidemiology, statistics, demography, mathematics, public health, biomedical sciences, or another quantitative discipline. The ideal candidate will have strong quantitative and analytical skills, an interest in the analysis of large-scale health data, and experience of statistical programming (e.g. R, Python, Stata, or SAS). An interest in epidemiology, mortality statistics, or global health would be an advantage.
Unit representative
DPhil in Population Health
The DPhil in Population Health provides students with training in research, to develop in-depth knowledge and understanding of their chosen population health research project, and to prepare them for a career in academia.
Applications for entry in October 2027 open on 16 September and close at noon on 1 December 2026.
Full details of the entry requirements for admission to the DPhil in Population Health are available on the DPhil in Population Health Graduate Admissions webpage.
