Public Health Sciences (Aging, Health and Well-Being) - Doctor of Philosophy (PhD) at University of Waterloo

Focus on aging, health and well-being for your PhD in Public Health Sciences with this unique collaborative program offered by the Faculty of Health. Through an interdisciplinary approach, you’ll develop a broad understanding of issues related to the health and well-being of our aging population while using research as a tool to design, implement, and evaluate health programs, policies, and services. The first collaborative PhD program in Canada with a focus on aging, health and well-being, it provides opportunities for cross-departmental collaborations, access to diverse course offerings and resources including dissertation committee members who can add unique perspectives in addressing emerging research problems.

Faculty: Faculty of Health  |  Department: School of Public Health Sciences  |  Duration: 48 months (full-time)  |  Study mode: full-time  |  Intake: Fall (September - December); application deadlines: February 1 (for admission in September)  |  Location: Waterloo, Ontario, Canada

What you will study

Research fields: Health information management, Illness and injury prevention, Dementia and dementia care, Social and environmental aspects of aging, Health services and continuum of care, Nutrition and healthy lifestyles, Vascular aging and cerebrovascular disease, Epidemiology and aging, Mobility and aging, Gender, sexuality, ethnicities and aging, Research project opportunities for this program, Exploring the Impact of Finite Sample Size and Missing Data on Statistical Modeling Decisions, Statistical models play a critical role in data applications for explanatory and predictive purposes. The model-building process involves use of various statistical tools, some of which make certain assumptions to yield good statistical properties like consistency. Such properties enable researchers to make reliable statistical inferences. However, when samples are small to moderate in size, issues arise when applying common model-building tools due to deviations from underlying assumptions. Such deviations can lead to unreliable parameter estimates, reduced statistical power, thereby affecting data-driven decisions. The process of model-building and conducting statistical tests is further impeded when data are incomplete due to missing values.. Study option(s): Thesis.

Career pathways

You’ll learn how to use research to improve the management and accountability of health promotion programs and health systems, preparing you for a career in research (industry, government and academia), health promotion, health planning, policy and health information analysis, research management, healthcare coordination, epidemiology, program evaluation and many others.

Official programme page