Thesis Format
Integrated Article
Degree
Master of Science
Program
Epidemiology and Biostatistics
Collaborative Specialization
Machine Learning in Health and Biomedical Sciences
Supervisor
Stephanie Frisbee
Abstract
Cardiovascular risk factors (CVRFs) are known to contribute to vascular cognitive impairment and dementia in later life. Their modifiability provides a promising avenue for reducing the risk of cognitive decline and dementia. This thesis summarizes the associations the current literature identifies between CVRFs, cognition and dementia while including control and management, identifies the associations between diabetes, control and cognition in the Canadian Longitudinal Study on Aging (CLSA), and employs machine learning (ML) for hypothesis generation and examining the most significant contributors to cognitive function and impairment in the CLSA. Our review found managing diabetes and hypertension improves cognitive outcomes, while therapeutic control remains inconclusive. The cross-sectional analysis of the CLSA illustrated uncontrolled diabetes results in poorer cognitive outcomes, while ML models highlighted social determinants of health as key contributors. Future research should explore CVRFs longitudinally in neuro-healthy populations, utilize ML to generate hypotheses, and address social determinants for at-risk groups.
Summary for Lay Audience
With projections that Canada’s senior population (aged 65 and older) will grow by 68% by 2040, there is great urgency to address the health conditions that affect the elderly. As Western populations age, there are significant societal and economic burdens that grow in proportion. Chronic diseases such as diabetes, hypertension, cardiovascular disease and dementia are all pervasive among the elderly, and severely hinder the quality of life of those living with these diseases, since often, disability is not far to follow. Disability resulting from chronic diseases places a burden on those suffering from the disease, due to reductions in autonomy, and on caregivers and healthcare systems. However, as our society lives more comfortably, we see obesity, inactivity, poor nutrition and chronic conditions like diabetes, hypertension and high cholesterol (otherwise known as cardiovascular risk factors, CVRFs) in not only the elderly, but young and middle-aged adults. Such factors early on in life can have health consequences like stroke, dementia and cognitive impairment in the long term. These factors are coined as “vascular contributions to cognitive decline and dementia” or VCID.
VCID is important because many of the diseases that precede it are treatable and preventable. By addressing vascular health problems earlier on, through leading healthier lifestyles, or ensuring adequate management of diabetes and hypertension, it may be possible to keep cognitive performance intact for longer, and curb dementia. This research highlights what we already know about the relationships between CVRFs, their management and control with medication, and cognitive function and dementia, the relationship between diabetic patients that either meet or do not meet their blood sugar targets and cognition in a sample of the 45-80-year-old Canadian population, and what machine learning indicates as important contributors to cognition in the same Canadian sample and the research questions this raises. Together, this thesis intends to inform its readers on both what we know about the therapeutic control and management of CVRFs in the prevention of cognitive decline and dementia and where we can and must go in the future to effectively implement prevention strategies and promote healthy aging.
Recommended Citation
Alimorad, Gabrielle, "The Associations Between Cardiovascular Disease Risk Factors and Cognitive Function" (2024). Electronic Thesis and Dissertation Repository. 10650.
https://ir.lib.uwo.ca/etd/10650