Author ORCID Identifier
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Statistics, Computer Sciences, Epidemiology
Models to predict stroke risk with the aim of stroke prevention often use age as a factor in the model (Choudhury et al., 2015; Conroy et al., 2003; D’Agostino etal., 2008; Wolf et al., 1991). However, stroke risk scores often underestimate risk
for specific age groups, particularly younger age groups and the contribution of different risk factors to overall stroke risk changes over time (Boehme et al., 2017; Seshadri et al., 2006). Additionally, because age is a strong predictor of stroke, age can dominate the risk score (Leening et al., 2017). Longitudinal Studies such as the Irish Longitudinal study on Aging (TILDA) allow us to track these change
in risk factors (TILDA, 2019). We aim to determine risk factors using an age group specific analysis in order to reduce the underestimation of risk for certain
Hunter, E. & Kelleher, J.D. (2021) A Comparison of Risk Factors and Risk Models for Stroke by Age Group Using TILDA Data, Longitudinal Studies Conference, Wellcome Genome Campus, UK. 10-12th March 2021.
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