Grant: Travel Awards - Institute Community Support
University of Toronto
$2,000.00
Advanced data science methods to examine trends and predict the risk of multimorbidity in individuals with asthma
EF 2024-25
Résumé
Background: One in three Canadians have multimorbidity, which means having more than one chronic illness at the same time. The proportion of Canadians who have multimorbidity has increased over time, especially among young adults. More people are getting multimorbidity at a younger age and this puts a big strain on them, their caregivers, and the health system. Asthma, the third most common chronic illness in Canada, usually starts at a young age, therefore people with asthma may be at a higher risk of developing other chronic illnesses. Having more than one chronic illness (multimorbidity) can make asthma worse and may lead to getting admitted to the hospital or even death. This is particularly worse for young people who work and could lose their income. Although we know that asthma usually starts at a young age, and multimorbidity is happening more in younger people, we have not had studies looking at multimorbidity in people with asthma in Canada. Such studies are needed since young people with asthma may be at a much higher risk of multimorbidity than others.
Our objectives for this study are to: 1) find out what proportion of people with asthma have more than one chronic illness (multimorbidity); and 2) predict the future risk of having multimorbidity in people with asthma.
Approach: We will use information on people who live in Ontario to find out what proportion of people with asthma also have multimorbidity. We will measure the proportions at different times, find out the most common chronic illnesses that people with asthma have, and which population groups are most affected. We will also use a method called machine learning to predict the risk of having multimorbidity in people with asthma. The findings of this research will help us understand which chronic illnesses occur in people with asthma, how to prevent them, and which population groups need more attention.
Programme
Travel Awards - Institute Community Support
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
CIHR Funding Decisions Database
Tel que publié
Id
521540
Name
Itanyi Ijeoma U
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Population and Public Health
Theme2
Social / Cultural / Environmental / Population Health
Prcname2
Travel Awards - Institute Community Support
Projecttitle
Advanced data science methods to examine trends and predict the risk of multimorbidity in individuals with asthma
Programtype2
Undefined
Orgnameinp2
University of Toronto
Cihramount2
$2,000
Cihrequipment2
$0
Programname2
Travel Awards - Institute Community Support
Keyworddelim
Ics Travel Awards
Abstract
Background: One in three Canadians have multimorbidity, which means having more than one chronic illness at the same time. The proportion of Canadians who have multimorbidity has increased over time, especially among young adults. More people are getting multimorbidity at a younger age and this puts a big strain on them, their caregivers, and the health system. Asthma, the third most common chronic illness in Canada, usually starts at a young age, therefore people with asthma may be at a higher risk of developing other chronic illnesses. Having more than one chronic illness (multimorbidity) can make asthma worse and may lead to getting admitted to the hospital or even death. This is particularly worse for young people who work and could lose their income. Although we know that asthma usually starts at a young age, and multimorbidity is happening more in younger people, we have not had studies looking at multimorbidity in people with asthma in Canada. Such studies are needed since young people with asthma may be at a much higher risk of multimorbidity than others.
Our objectives for this study are to: 1) find out what proportion of people with asthma have more than one chronic illness (multimorbidity); and 2) predict the future risk of having multimorbidity in people with asthma.
Approach: We will use information on people who live in Ontario to find out what proportion of people with asthma also have multimorbidity. We will measure the proportions at different times, find out the most common chronic illnesses that people with asthma have, and which population groups are most affected. We will also use a method called machine learning to predict the risk of having multimorbidity in people with asthma. The findings of this research will help us understand which chronic illnesses occur in people with asthma, how to prevent them, and which population groups need more attention.
Competitiondate
202501
Approvedterm2
1 yr 0 mth
Pinamesdelim
Itanyi, Ijeoma U
Approvedterm
1 an 0 mois
Cihrcontribution2
IPPH~ $2,000~ $0~