Grant: Operating Grant

What is the future risk (incidence) of cardiovascular disease (CVD) in Canada? What is the population CVD burden from all major health behaviours? What is the preventive benefit of achieving CVD health behaviour goals? To what degree can inequities in CVD be reduced through improvements in health behaviours? There are notable gaps in knowledge for all these questions. In the clinical setting, predictive risk algorithms are widely used to estimate individual risk of future disease. Risk prediction algorithms are also valuable for public health purposes, like predicting disease incidence trends and evaluating the impact of population health strategies. However, there are methodological challenges that have hampered more widespread development and use of multivariable population risk assessment. We propose a three-year series of research projects to improve the science and increase the use of multivariable population risk assessment - focusing on the case example of cardiovascular disease.