Year:
Applicant:
Institution:
Email:
geoff.anderson@utoronto.ca
Keywords:
cardiovascular disease (CVD)
clustering
cognitive decline
frailty
mild cognitive impairment (MCI)
supervised learning
trajectories
unsupervised learning
Project ID:
2304010
Approved Project Status:
Project Summary
Declines in various aspects of cognition such as memory, language skills and reasoning are normal parts of aging. However, not everybody follows this normal trajectory of age-related cognitive decline. In some, there are premature changes in specific aspects of cognition, or mild overall changes in cognition that do not interfere with normal social function. In others, changes can be more rapid, broad-based, and profound, resulting in substantial impairment of social function and independence that requires extensive care and support. We will use CLSA data and health system data to better define these different cognitive decline trajectories, to identify risk factors associated with each trajectory and to measure health and healthcare utilization of people in each trajectory. The goal is to provide evidence on risk factors for mild cognitive impairment and dementia that can guide research on prevention and evidence on needs and outcomes to help plan services for our aging population.