Cardiovascular diseases (CVDs) are common, readily preventable chronic diseases in New Zealand and there are major disparities between population groups. About 10-15% of New Zealanders probably account for over half the premature CVD events, but we are currently unable to identify them accurately to target preventive treatment effectively. Moreover available treatments can halve CVD risk but there are significant treatment disparities including under- and over-treatment. This programme will: i. develop better risk prediction tools to identify these high-risk patients; ii. quantify and map gaps and disparities in appropriate treatment; iii. model the impact of treatment disparities on CVD burden. To achieve this we will link encrypted personal data on over two million New Zealanders from research and routine databases to create three overlapping cohort studies. Providing accurate risk prediction algorithms, interactive atlases of treatment disparities, and evidence of the impact of disparities, will be directly relevant to practice and policy.