Abstract

Background and Aim: The reduction in coronary heart disease (CHD) mortality in Europe has been associated with a<br />reduction in coronary risk factors, including dyslipidaemia. Statins reduce blood cholesterol levels and the risk of coronary<br />events. Their utilization has substantially increased over the years. Although statins should be prescribed according to clinical<br />guidelines, doctors’ decisions about treatment are usually made subjectively and are influenced by the population risk level.<br />The aim of this study was to investigate the relation between the time trend of population risk level and statin utilization in two<br />areas with different levels of coronary risk in the population.<br />Methods: CHD mortality, as a proxy of population coronary risk level, and statin utilization trends in the period 2001-2011,<br />were compared between a relatively high-risk CHD area, Stockholm county, and a low-risk area, Sicily.<br />Results: There was a reduction in CHD mortality and an increase in statin utilization in both areas. The mean annual reduction<br />in CHD mortality rate/100,000 was greater in Stockholm than in Sicily (-4.6, 95% CI -5.3 -4.0, and -1.9 95% CI -2.6 – 1.2,<br />respectively). The mean annual increase in statin DDD/TID utilization was larger in Sicily than in Stockholm (5.1, 95% CI 4.8 –<br />5.3, and 3.7, 95% CI 3.2 – 4.1, respectively). In Stockholm the increase in statin use was mainly due to increased utilization of<br />simvastatin, whereas it included a greater variety of statins in Sicily.<br />Conclusion: The relations between time trends of CHD mortality and statin utilization in Stockholm and in Sicily were<br />different. A larger increase in statins was observed in the low-risk area, associated with a slower reduction in CHD mortality,<br />whereas a smaller increase in statins was observed in the high-risk area, associated with a greater reduction in CHD mortality.<br />Other factors apart from the actual risk of the patients may explain these observations, such as differences in socioeconomic<br />factors, adherence to treatment, policies of drug cost-containment, and population CHD risk profiles.

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