Cardiovascular Disease Peer Review Journals
Cardiovascular disease (CVD) is a leading cause of death and disease burden across the world, and the burden is expected to increase as the population ages . CVD is the most expensive disease in Australia; it accounted for $7.9 billion, or 11%, of
health spending from 2009 to 2010 .
The most commonly used CVD risk prediction algorithms are those derived from the Framingham Risk Equation (FRE), which is used in
general practice (GP) to assess risks for individual patients . The trend in primary prevention of CVD in GPs has been to move away from assessment of relative CVD risk factors toward assessment and management of these factors as absolute CVD risk.
Best-value prevention strategies require knowledge and contextualized understanding of people, communities, and environments, as well as variations in CVD risk. Although clinically proven tools are available for assessing risk factors in individuals, most at-risk individuals never take part in such assessment until disease progression is under way. Although imprecise proxies for risk can be used to make community-based risk estimates, there is still a considerable knowledge gap; no fine-grained population tools exist to directly predict “hotspots” for future CVD risk from GP clinical data.
Few studies have attempted to examine spatial variation of CVD risk at a smaller geographic scale across the world. Noble et al examined the feasibility of mapping chronic disease risk in general and created a small-area map of
diabetes risk from GP clinical records in the United Kingdom. In Australia, Tideman et al compared the CVD risk of a population survey sample from northwest Adelaide with a nearby rural population but did not look at the variation within the survey population catchment.
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