Objective: To model the impact of both population and high-risk strategies on cardiovascular disease (CVD) outcomes.
Design, setting and participants: A CVD risk-factor survey was carried out in rural south-eastern Australia from 2004 to 2006. Using a stratified random sample, data for 1116 participants aged 35-74 years were analysed. Applying the Framingham risk equations to risk-factor data, 5-year probabilities of a coronary heart disease event, stroke and cardiovascular event were calculated. The effect of different changes in risk factors were modelled to assess the extent to which cardiovascular diseases can be prevented by changing the risk factors at a population level (population strategy), among the high-risk individuals (high-risk strategy) or both.
Results: Among men, a population strategy could reduce cardiovascular events by 19.3% (193 per 1000 per 5 years), the high-risk strategy by 12.6% (126 per 1000) and a combined strategy by 24.1% (241 per 1000); and among women, by 21.9% (219 per 1000), 19.0% (190 per 1000) and 28.7% (287 per 1000), respectively.
Conclusions: For prevention of CVD in Australia, it is important both to treat high-risk individuals and to reduce the mean risk-factor levels in the population. We show how risk-factor survey data can be used to set targets for prevention and to monitor progress in line with the recommendations of the National Preventative Health Taskforce.