| Summary: | Introduction Coronary heart disease (CHD) is one of the leading global causes of morbidity and mortality. The underlying biological mechanisms are well understood, and a host of causal risk factors for the disease have been identified, mainly related to diet, smoking and physical activity. Evidence-based treatments for the disease are also available, reducing mortality and improving quality of life. The decline in CHD mortality rates observed in most developed countries since the 1960s represents a most remarkable epidemiological phenomenon. However, this decline is not universal, and may now be in jeopardy. Thus, the mortality decline has recently plateaued in young adults in the United States. Furthermore, the absolute burden of disease is set to increase mainly because of an increasingly ageing population, and will represent a heavy burden to high, middle and low income countries alike. Furthermore, CHD incidence may rise in future because of recent adverse trends in major CHD risk factors, namely the worldwide increases in obesity and diabetes prevalence observed since the 1980s. Moreover, new technology and improved treatments are decreasing case fatality in CHD patients, increasing life expectancy and thus expanding the pool of patients surviving with clinically apparent disease. Finally, and crucially, important socioeconomic inequalities persist, perhaps reflecting disease determinants. The complex interplay of these factors and potential changes over time together suggest that the CHD epidemic may still be evolving. Further attention is therefore essential. The analysis of time trends in disease specific mortality can thus potentially help us to understand the population dynamic of diseases such as CHD, warn about key changes and perhaps offer some novel insights for better prevention and control. However, most previous analyses have been focused on age-adjusted rates that might conceal important differences by age or by socioeconomic status, which might provide further understanding of trend drivers. Aims and objectives: My aim is to study recent coronary heart disease mortality time trends in different countries, in order to better understand the current state of the CHD epidemic. Furthermore, I will analyze the relative importance of CHD treatments and risk factors as drivers of the mortality trends. Finally, I will consider the Public Health implications of my findings. My objectives therefore are: 1. To summarize our current understanding of Coronary Heart Disease (CHD) causation 2. To describe recent CHD mortality time trends focusing on age and gender specific trends by identifying periods with similar rate of change in diverse populations (England & Wales, the Netherlands, Poland and Australia). 3. To describe recent CHD mortality time trends by Socio-Economic Status in England and Scotland. 4. To quantify the role of risk factors and evidence-based treatments as drivers of the CHD mortality trends, first using a modelling approach in Poland, and then in England while also considering socioeconomic factors. 5. To consider the public health policy implications of dynamic trends in coronary heart disease mortality. Methods CHD mortality trends were analysed using the joinpoint regression approach. Widely used in cancer epidemiology, but rarely in CHD, this method explores trend data to find points in time (“joinpoints”) that define segments where the trend has a constant pace of change. The key strength of this technique is objectivity- (it avoids the detection of potentially biased patterns when trends are described using time intervals defined subjectively by the researcher). Joinpoint avoids this potential bias by essentially removing the observer from the selection process, instead using a formal and objective exploration of the time-series data. My analysis therefore focused on age-adjusted rates, then age and gender specific rates. The analysis for Scotland and England also considered socio-economic status (using area-based measures of material deprivation). The contributions of risk factors and treatments to the observed CHJD mortality trends in Poland were studied using the IMPACT model, a comprehensive, population-based model of CHD epidemiology. The model goal is to quantify the decline in coronary heart disease deaths in the Polish population between 1991 and 2005 which might be explained by risk factor changes and by treatments. The model is comprehensive, incorporating all usual treatments for coronary heart disease and heart failure plus all major cardiovascular risk factors, including smoking, blood pressure, cholesterol, diabetes, obesity and physical activity. Similar analyses but also exploring the socio-economic differences were conducted in England, using a modified IMPACT model (IMPACTsec). That was used to estimate the contribution of risk factors and evidence based treatments to the observed decline in mortality in England between 2000 and 2007, for each quintile of the index of multiple deprivation. Results Age-adjusted trends in England and Wales, Scotland, Australia and the Netherlands conceal important recent age specific patterns. In these countries, the age-adjusted rates show continuing declines; however, among young adults a recent period of slowing down of the rate of decline in CHD mortality has been observed. Furthermore, trends are very dynamic, and the patterns can change surprisingly quickly. In the Netherlands, the sustained period of minimal change in young adults was followed by a period of further decline. Poland offers a strikingly different example of trend dynamism. After a period of constant increase, Poland showed a sudden, sharp decline in CHD mortality rates within a period of a very few years. This decline occurred in all age and gender groups, and still continues. The recent mortality trends are probably attributable more to changes in risk factors rather than medical treatments. For example, using the IMPACT model to study the decline phase of the Polish CHD epidemic, approximately 55% of the observed fall in mortality might be attributed to changes in risk factors, and only about a third to evidence based therapies. Because of the social patterning of risk factors levels, further insights on the role of risk factors as major contributors to trend changes can be obtained by studying trends in levels stratified by socioeconomic circumstances. Scotland and England offer particular opportunities for detailed studies of trends in CHD mortality using high quality data including socioeconomic status. The resulting picture is complex. The recent flattening in CHD mortality trends observed in young adults was confined to the most deprived groups in Scotland, but was more uniform in England. A marked deterioration of medical care is implausible, meaning that the most likely explanation for this recent flattening of CHD mortality must be adverse trends in major cardiovascular risk factors. The CHD mortality modelling in England produced intriguing results. As expected, socio-economic patterning of risk factor changes were observed. For example, decline in smoking levels contributed more to the observed decline amongst the more deprived groups. Social patterning was less clear among young adults in England. Moreover, the IMPACT SEC model analysis suggested that approximately half the CHD mortality fall was attributable to improved treatment uptake, with benefits occurring surprisingly equitably across all social groups. A similar analysis of the Scottish trends is therefore urgently needed to gain better insights on the drivers of the socioeconomic patterning underlying the observed trends. Conclusions The recent flattening in CHD mortality in young adults seen in many countries experiencing an overall decline in deaths strongly suggests that favourable trends can reverse.
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