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Predicting cognitive impairment using modifiable risk factors to inform population-level prevention

Description: As life expectancy increases and the population ages, Canada is facing a growing burden of dementia and cognitive decline. Cognitive impairment refers to a state between normal cognition and dementia and is characterized by problems with memory, language, thinking or judgement. Though some cognitive decline is associated with normal aging, those with cognitive impairment are at increased risk of developing dementia. People with cognitive impairment are also more likely to be hospitalized, have more difficulty performing daily tasks, and often have a reduced quality of life and poor well-being compared to those their age with normal cognition. There are currently no treatments to reverse cognitive decline or cure dementia, however there are known ways to reduce your risk of further decline and dementia development. These include engaging in regular physical activity, not smoking, and managing health conditions including diabetes and hypertension. Other ways of potentially preventing cognitive decline that require further exploration include use of hearing aids for those with hearing loss, maintenance of dental and oral health, and consistently getting a good night sleep. In this project we will explore at how modifiable risk factors (including physical activity, diet, smoking, hearing impairment, sleep, oral health, traumatic brain injury, and air pollution) influence the risk of developing cognitive impairment. We will then use this information to develop a risk prediction tool that can be used by policy makers to estimate the burden of cognitive decline in the Canadian population and evaluate risk reduction strategies.
Amount: CA$69,900
Funding type: research
Funder scheme: Catalyst Grant: Analysis of Canadian Longitudinal Study in Aging (CLSA) Data - IPPH Mandate
Start date: 2024-03-01
End date: 2025-02-28
Investigator: Douglas Manuel
Institution: Ottawa Hospital Research Institute
Field: Medicine
Funded outputs count: 0
Funder award ID: 192845_1
OpenAlex ID: G2280425296
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