Adobe Flash Player is required to view this feature. If you are using an operating system that does not support Flash, we are working to bring you alternative formats. Special Article Explaining the Decrease in U.S. Deaths from Coronary Disease, 1980–2000 Earl S. Ford, M.D., M.P.H., Umed A.
Ajani, M.B., B.S., M.P.H., Janet B. Croft, Ph.D., Julia A. Critchley, D.Phil., M.Sc., Darwin R. Labarthe, M.D., M.P.H., Ph.D., Thomas E. Kottke, M.D., Wayne H. Giles, M.D., M.S., and Simon Capewell, M.D. N Engl J Med 2007; 356:2388-2398 DOI: 10.1056/NEJMsa053935.
Results From 1980 through 2000, the age-adjusted death rate for coronary heart disease fell from 542.9 to 266.8 deaths per 100,000 population among men and from 263.3 to 134.4 deaths per 100,000 population among women, resulting in 341,745 fewer deaths from coronary heart disease in 2000. Approximately 47% of this decrease was attributed to treatments, including secondary preventive therapies after myocardial infarction or revascularization (11%), initial treatments for acute myocardial infarction or unstable angina (10%), treatments for heart failure (9%), revascularization for chronic angina (5%), and other therapies (12%). Approximately 44% was attributed to changes in risk factors, including reductions in total cholesterol (24%), systolic blood pressure (20%), smoking prevalence (12%), and physical inactivity (5%), although these reductions were partially offset by increases in the body-mass index and the prevalence of diabetes, which accounted for an increased number of deaths (8% and 10%, respectively). Rates of death from coronary heart disease in the United States underwent profound secular changes during the 20th century. After peaking around 1968, age-adjusted rates were cut in half. Two factors may have contributed to this decline. First, there have been substantial decreases in the prevalence of some major cardiovascular risk factors, including smoking, elevated total cholesterol, and high blood pressure.
However, the prevalence of both obesity and diabetes has increased alarmingly. Second, there has been a revolution in the treatments for established coronary heart disease, with major breakthroughs in evidence-based therapies, including the use of thrombolysis, coronary-artery bypass grafting (CABG), coronary angioplasty and stents, and angiotensin-converting–enzyme (ACE) inhibitors and statins. The annual direct and indirect costs for coronary heart disease were $142.5 billion in 2006, and they continue to rise. Determining the respective contributions of prevention and therapy to the declines in mortality from coronary heart disease is therefore becoming increasingly important, for the purposes of both understanding past trends and planning future strategies. Estimates of the contribution from reductions in risk factors before 1990 have ranged from 50 to 54% in the United States and from 44 to 76% in other industrialized countries. However, to our knowledge, no U.S. Studies have considered the dramatic changes since 1990 or have attempted to quantify the relative contributions of specific therapies and trends in risk factors.
We therefore applied a model that has been used successfully in several other countries to examine trends in U.S. Deaths from coronary heart disease between 1980 and 2000. Mortality Model and Data Sources To examine the contributions of various factors to the changes in rates of death from coronary heart disease among U.S. Adults 25 to 84 years of age, we used an updated version of the IMPACT mortality model, which was previously validated in Europe, New Zealand, and China. This model has been described in detail elsewhere. It incorporates major population risk factors for coronary heart disease (smoking, high blood pressure, elevated total cholesterol, obesity, diabetes, and physical inactivity) and all usual medical and surgical treatments for coronary heart disease. Wherever possible, data sources specific to the U.S.
Population were used to construct the U.S. When more than one data source was available, we chose the source that we considered to be most representative, least biased, and most up-to-date. Detailed information on the IMPACT model and data sources for the U.S.
Analysis is provided in the, available with the full text of this article at www.nejm.org. Deaths Prevented or Postponed Data on the total U.S. Population and age distribution in 1980 and 2000 were obtained from the U.S.
Census Bureau. Deaths according to age and sex and mortality rates associated with coronary heart disease in 1980 and 2000 were obtained from the National Vital Statistics System of the National Center for Health Statistics.
Jul 11, 2010. Veronika does decide to die, but it doesn't mean she succeeds. Somehow she wakes. Instead, the focus of the book is firmly upon Veronika and her feelings, which in this case, are actually quite complex. To begin a story. The thread of life. I give it 4.5/5 stars (because 'The Alchemist' deserves the full 5!).
We calculated the number of deaths from coronary heart disease that would have been expected in 2000 if the mortality rates in 1980 had remained unchanged by multiplying the age-specific mortality rates for 1980 by the population for each 10-year age stratum in the year 2000 (thus accounting for the aging of the population). Subtracting the number of deaths observed in 2000 from the number expected then yielded the drop in the number of deaths (prevented or postponed) in 2000 that the model would have to explain. Treatments and Mortality Reductions The prevalence of coronary heart disease by diagnosis, the estimated frequency of use of specific treatments, the case fatality rate by diagnosis, and the risk reduction due to treatment, all stratified by age and sex, were obtained from published sources (Tables 2 through 5 in the ). The number of deaths prevented or postponed as a result of each intervention in each group of patients in the year 2000 ( Table 1 Estimated Deaths Prevented or Postponed by Medical or Surgical Treatments in the United States in 2000. ) was calculated by multiplying the number of people in each diagnostic group by the proportion of those patients who received a particular treatment, by the case fatality rate over a period of 1 year, and by the relative reduction in the 1-year case fatality rate that was accounted for by the treatment.
For example, in the United States in 2000, approximately 102,280 men between the ages of 55 and 64 years were hospitalized with acute myocardial infarction. Some 84% were given aspirin, with an expected mortality reduction of 15%.
The expected age-specific, 1-year case fatality rate was approximately 5.4%. The number of deaths prevented or postponed for at least a year by the use of aspirin among men in this age group was then calculated as 102,280×0.84×0.15×0.054=696. Several adjustments were made to these basic analyses. Although most of the therapeutic measures studied were not in use in 1980, in some cases such use was already substantial (e.g., CABG for stable angina pectoris).
In such cases, the number of deaths prevented or postponed as a result of the therapy as used in 1980 was calculated and subtracted from the number of deaths for 2000 to calculate the net benefit. We assumed that compliance — the proportion of treated patients actually taking therapeutically effective levels of medication — was 100% among hospitalized patients, 70% among symptomatic patients in the community, and 50% among asymptomatic patients in the community. To avoid double counting of patients treated, we identified potential overlaps between different groups of patients and made appropriate adjustments (Table 9 in the ). For example, heart failure develops within 1 year after acute myocardial infarction in approximately one quarter of survivors, and approximately half the patients undergoing CABG have had a previous myocardial infarction. To address the potential effect on the relative reduction in the case fatality rate for individual patients receiving multiple treatments, we used the Mant and Hicks cumulative-relative-benefit approach: relative benefit = 1 − (1 − relative reduction in case fatality rate for treatment A) × (1 − relative reduction in case fatality rate for treatment B) ×... × (1 − relative reduction in case fatality rate for treatment N). Risk Factors and Mortality Reductions Two approaches were used to calculate the numbers of deaths prevented or postponed as a result of changes in risk factors.
We used a regression approach for systolic blood pressure, cholesterol, and body-mass index. The number of deaths prevented or postponed as a result of the change in the prevalence of or mean value for each of these risk factors ( Table 2 Deaths from Coronary Heart Disease That Were Prevented or Postponed as a Result of Changes in Population Risk Factors in the United States, 1980 to 2000. ) was estimated as the product of three variables: the number of deaths from coronary heart disease in 1980 (the base year), the subsequent reduction in that risk factor (Table 2 in the ), and the regression coefficient quantifying the change in mortality from coronary heart disease per unit of absolute change in the risk factor (Table 6 in the ). For example, in 1980, there were 26,352 deaths from coronary heart disease among 12,629,000 women who were 55 to 64 years of age. The mean systolic blood pressure in this group decreased by 3.09 mm Hg between 1980 and 2000. The largest meta-analysis showed an estimated age- and sex-specific reduction in mortality of 50% for every reduction of 20 mm Hg in systolic pressure, yielding a logarithmic (ln) coefficient of –0.035. The number of deaths prevented or postponed as a result of this change was then estimated as follows: number of deaths = (1 − e (coefficient×change)) × deaths in 1980 = (1 − e (−0.035×3.09)) × 26,352 = 2701.
The population-attributable risk fraction was used to determine the effect of changes in the prevalence of smoking, diabetes, and physical inactivity. The population-attributable risk fraction was calculated conventionally as [P×(RR−1)]÷[(1+P)×(RR−1)], where P is the prevalence of the risk factor (Table 2 in the ) and RR is the relative risk of death from coronary heart disease associated with that risk factor (Table 7 in the ).
The number of deaths prevented or postponed was then estimated as the number of deaths from coronary heart disease in 1980 (the base year) multiplied by the difference between the population-attributable risk fraction in 1980 and that in 2000 ( ). For example, the prevalence of diabetes among men 65 to 74 years of age increased from 14.5% in 1980 to 20.7% in 2000. Given a relative risk of 1.93, the population-attributable risk fraction increased from 0.119 to 0.161. Additional deaths from coronary heart disease in 2000 that were attributable to an increased prevalence of diabetes were therefore calculated as follows: deaths from coronary heart disease in 1980 = (123,055) × (0.161 − 0.119) = 5168. Imagequant Tl Iqtl Software Ge Healthcare Logo. Because independent regression coefficients and relative risks for each risk factor were obtained from multivariate analyses, we assumed that there was no further synergy between the treatment and risk-factor sections of the model or among the major risk factors. The number of deaths prevented or postponed as a result of changes in risk factors was systematically quantified for each specific patient group to account for potential differences in effect. Lag times between the change in the risk-factor rate and the change in the event rate were not modeled; it was assumed that these lag times would be relatively unimportant over a period of two decades.
Comparison of Estimated and Observed Mortality Changes The model estimates for the total number of deaths prevented or postponed by each treatment and for each risk-factor change were rounded to the nearest multiple of 5 (e.g., 696 became 695). All these figures were then summed and compared with the observed changes in mortality for men and women in each age group. Any shortfall in the overall model estimate was then presumed to be attributable either to inaccuracies in our calculated estimates or to other, unmeasured risk factors. Sensitivity Analyses We tested all the above assumptions and variables in a multiple-way sensitivity analysis, using the analysis-of-extremes method. For each variable in the model, we assigned a lower value and an upper value, using 95% confidence intervals when available and otherwise using ±20% (for the number of patients, use of treatment, and compliance).
For example, for aspirin treatment in men 55 to 64 years of age who were hospitalized with acute myocardial infarction, the best estimate was 696 deaths prevented or postponed. The minimum estimate from the multiple-way sensitivity analysis was 259, and the maximum estimate was 1501 ( Table 3 Example of a Multiple-Way Sensitivity Analysis. Results From 1980 to 2000, the age-adjusted rate of coronary heart disease fell from 542.9 to 266.8 cases per 100,000 population among men aged 25 to 84 years and from 263.3 to 134.4 among women aged 25 to 84 years. In 1980, a total of 462,984 deaths among people in this age group were recorded as due to coronary heart disease, according to the International Classification of Diseases, 9th Revision (codes 410–414 and 429.2). In 2000, a total of 337,658 such deaths were recorded, according to the International Classification of Diseases, 10th Revision (codes I20–I25). However, had the age-specific death rates from 1980 remained in 2000, an additional 341,745 deaths from coronary heart disease would have occurred.
IMPACT model explained approximately 308,965 (90%) of this decrease in the number of deaths from coronary heart disease. Under the assumptions of the sensitivity analysis, the minimum and maximum numbers of deaths from coronary heart disease that were explained were 175,230 (51%) and 545,755 (160%). The agreement between the number of estimated deaths and the number of observed deaths was reasonably good for men across all groups and for women under the age of 75 years ( Figure 1 Estimated and Observed Reductions in Deaths from Coronary Heart Disease in the United States between 1980 and 2000, Stratified According to Age and Sex. The bars show the observed decrease in deaths in each age group, and the vertical lines the extreme minimum and maximum estimates in the sensitivity analysis.
Changes in medical treatments accounted for approximately 47% and risk-factor changes accounted for approximately 44% of the decrease in deaths ( and ). Medical and Surgical Treatments Approximately 159,330 of the deaths from coronary heart disease that were prevented or postponed were attributable to medical therapies (minimum estimate, 58,065; maximum estimate, 347,395) ( ). The largest reductions in deaths came from the use of secondary-prevention medications or rehabilitation after acute myocardial infarction or after revascularization (a total reduction of approximately 35,800 deaths) and from the use of initial treatments for acute myocardial infarction or unstable angina (approximately 35,145 deaths), followed by treatments for heart failure and hypertension, statin therapy for primary prevention, and treatments for chronic angina. The use of revascularization for chronic angina resulted in a reduction of approximately 15,690 deaths in 2000, as compared with deaths in 1980, or approximately 5% of the total. Risk Factors Approximately 149,635 fewer deaths from coronary heart disease were attributable to changes in risk factors (minimum estimate, 117,165; maximum estimate, 198,360) ( ). Decreases in the total cholesterol concentration (by 0.34 mmol per liter), systolic blood pressure (by 5.1 mm Hg), and smoking prevalence (by 11.7%) were estimated to have prevented or postponed approximately 82,830, 68,800, and 39,925 deaths, respectively. The 2.3% decrease in physical inactivity prevented or postponed approximately 17,445 deaths.
In contrast, the increase in the body-mass index (the weight in kilograms divided by the square of the height in meters) of 2.6 and the 2.9% increase in the prevalence of diabetes resulted in approximately 25,905 and 33,465 additional deaths overall, respectively ( ). Proportional Contributions to the Decrease in Deaths Sensitivity analyses showed that the proportional contributions of specific treatments and risk-factor changes to the overall reduction in deaths from coronary heart disease in 2000 were relatively consistent ( and ). Thus, all initial treatments for acute myocardial infarction together accounted for approximately 21,570 fewer deaths, representing 6.3% of the total decrease of 341,745 deaths. The minimum estimated contribution was 9045 fewer deaths (2.6%), and the maximum was 37,720 (11.0%). The contribution of treatments for acute myocardial infarction therefore remained consistently smaller than that of secondary prevention or therapies for heart failure, irrespective of whether best, minimum, or maximum estimates were compared ( ). Discussion The burden of coronary heart disease in the United States remains enormous, even though associated mortality rates fell by more than 40% between 1980 and 2000. These two decades saw rapid growth in costly medical technology and pharmaceutical treatments for coronary heart disease, as well as substantial public health efforts to reduce the prevalence of major cardiovascular risk factors.
Establishing the relative contributions of these two approaches is therefore of considerable importance. We found that reductions in major risk factors probably accounted for approximately half the decrease in deaths from coronary heart disease, as in most other industrialized countries studied. Studies likewise suggested a contribution of approximately 54% of the reduction in deaths between 1968 and 1976 and approximately 50% between 1980 and 1990. Irrespective of the assumptions used, we found that the largest contributions from medical therapies consistently came from secondary prevention, followed by treatments for acute coronary syndromes, then heart failure.
Revascularization by means of CABG or angioplasty for stable or unstable disease together accounted for approximately 7% of the overall drop in deaths from coronary heart disease, a finding that is consistent with the results of previous studies in the United States and elsewhere. Although most of the changes in treatments and risk factors between 1980 and 2000 led to reductions in deaths from coronary heart disease, two major exceptions are noteworthy.
Our analysis estimated that increases in the body-mass index accounted overall for about 26,000 additional deaths from coronary heart disease in 2000 and increases in the prevalence of diabetes for about 33,500 additional deaths; both figures are consistent with the results of other recent studies. Efforts to address these two risk factors should therefore receive particular attention in future measures to improve the public health. Modeling studies have a number of potential strengths, including the ability to transparently integrate and simultaneously consider huge amounts of data from many sources and then test explicit assumptions by means of sensitivity analyses. Our analysis of extremes suggested that the proportional contributions to the overall reductions in deaths from specific treatments and risk-factor changes remained reasonably consistent, irrespective of whether best, minimum, or maximum estimates were considered ( and ). This was reassuring, as was the general consistency with the results of most studies performed elsewhere ( Figure 2 Percentage of the Decrease in Deaths from Coronary Heart Disease Attributed to Treatments and Risk-Factor Changes in Our Study Population and in Other Populations. In the New Zealand study, 1974 to 1981 (Beaglehole ), the analysis focused on specific treatments and inferred contribution from risk factors. In the Finland study, 1972 to 1992 (Vartiainen et al.
), the analysis focused on risk factors and inferred contribution from treatments. However, all modeling analyses should be interpreted with appropriate caution.
All require the gathering of data from numerous sources, each with recognized limitations. We sometimes had to use data from studies that might have been limited by geographic, ethnic, or selection bias or by the need to extrapolate to older age groups. Risk estimates were not necessarily fully independent of each other. Furthermore, most interactions were averaged across broad groups. We therefore made the explicit assumptions detailed in the. Furthermore, we analyzed only the estimated reduction in deaths from coronary heart disease, not life-years gained or improvement in the quality of life. Analyses of these changes are warranted, as well as comparisons among racial and ethnic groups and economic analyses.
The estimates of changes in risk factors remain imprecise. Furthermore, we did not explicitly consider the effect of lag times; however, they may be relatively unimportant over a 20-year period. Although major efforts were made to address overlaps, residual double counting of some individual patients remains possible. We also assumed that, after adjustments for reduced dosing and imperfect compliance, the efficacy of treatments in randomized, controlled trials could be generalized to usual clinical practice. Both assumptions may have potentially overestimated the true treatment effect.
In conclusion, our analyses suggest that approximately half the recent decrease in deaths from coronary heart disease in the United States may be attributable to reductions in major risk factors and approximately half to evidence-based medical therapies. Future strategies for preventing and treating coronary heart disease should therefore be comprehensive, maximizing the coverage of effective treatments and actively promoting population-based prevention by reducing risk factors. Source Information From the Division of Adult and Community Health (E.S.F., U.A.A., W.H.G.) and the Division for Heart Disease and Stroke Prevention (J.B.C., D.R.L.), National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta; the Institute of Health and Society, Newcastle University, Newcastle upon Tyne (J.A.C.), and the Division of Public Health, University of Liverpool, Liverpool (S.C.) — both in the United Kingdom; and HealthPartners Research Foundation, Minneapolis (T.E.K.). Address reprint requests to Dr. Capewell at the Division of Public Health, University of Liverpool, Whelan Building, Quadrangle, Liverpool L69 3GB, United Kingdom,. References • 1 Rosamond W, Flegal K, Friday G, et al.
Heart disease and stroke statistics — 2007 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation 2007;115:e69-e171. [Erratum, Circulation 2007;115:e172]. • 2 Morbidity and mortality: 2004 chart book on cardiovascular, lung, and blood diseases.
Bethesda, MD: National Heart, Lung, and Blood Institute, 2004. (Accessed May 11, 2007, at.) • 3 Centers for Disease Control and Prevention. Percentage of adults who were current, former, or never smokers, overall and by sex, race, Hispanic origin, age, and education status: National Health Interview Surveys, selected years — United States, 1965–2004. (Accessed May 11, 2007, at.) • 4 Hajjar I, Kotchen TA. Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988-2000. JAMA 2003;290:199-206 • 5 Burt VL, Cutler JA, Higgins M, et al.
Trends in the prevalence, awareness, treatment, and control of hypertension in the adult US population: data from the Health Examination Surveys, 1960 to 1991. Hypertension 1995;26:60-69[Erratum, Hypertension 19.] • 6 Johnson CL, Rifkind BM, Sempos CT, et al. Declining serum total cholesterol levels among US adults: the National Health and Nutrition Examination Surveys. JAMA 1993;269:3002-3008 • 7 Ford ES, Mokdad AH, Giles WH, Mensah GA. Serum total cholesterol concentrations and awareness, treatment, and control of hypercholesterolemia among US adults: findings from the National Health and Nutrition Examination Survey, 1999 to 2000. Circulation 2003;107:2185-2189 • 8 Prevalence of no leisure-time physical activity -- 35 states and the District of Columbia, 1988-2002. MMWR Morb Mortal Wkly Rep 2004;53:82-86 • 9 Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM.
Prevalence of overweight and obesity among US children, adolescents, and adults, 1999-2002. JAMA 2004;291:2847-2850 • 10 Harris MI, Hadden WC, Knowler WC, Bennett PH. Prevalence of diabetes and impaired glucose tolerance and plasma glucose levels in U.S. Population aged 20-74 yr. Diabetes 1987;36:523-534 • 11 Harris MI, Flegal KM, Cowie CC, et al. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. Adults: the Third National Health and Nutrition Examination Survey, 1988-1994.
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Circulation 2006;113:e85-e151[Erratum, Circulation 2006;113:e696, 114:e630.] • 13 Hunink MG, Goldman L, Tosteson AN, et al. The recent decline in mortality from coronary heart disease, 1980-1990: the effect of secular trends in risk factors and treatment. JAMA 1997;277:535-542 • 14 Goldman L, Cook EF. The decline in ischemic heart disease mortality rates: an analysis of the comparative effects of medical interventions and changes in lifestyle.
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(December 2017) () Veronika Decides to Die (: Veronika Decide Morrer) is a. It tells the story of 24-year-old Veronika, who appears to have everything in life going for her, but who decides to kill herself. This book is partly based on Coelho's experience in various (see the biography by Juan Arias), and deals with the subject of madness. The gist of the message is that 'collective madness is called sanity'. Veronika Decides to Die has been adapted for a number of times, and was also used in other artistic references. Plot summary [ ].
This section does not any. Unsourced material may be challenged and. (December 2017) () Veronika is a beautiful young woman from, who appears to have the perfect life, but nevertheless decides to die (commit suicide) by overdosing with sleeping pills. While she waits to die, she cancels the suicide letter she starts to her parents while suddenly provoked by a magazine article. The magazine article wittily asks 'Where is?'
, so she writes a letter to the press justifying her suicide, the idea being to make the press believe that she has killed herself because people don't even know where Slovenia is. Her plan fails and she wakes up in Villete, a in, where she is told she has only a few days to live due a heart condition caused by the overdose. Her presence there affects all of the mental hospital's patients, especially Zedka, who has; Mari, who suffers from; and Eduard, who has, and with whom Veronika falls in love. During her internment in Villete she realizes that she has nothing to lose and can therefore do what she wants, say what she wants and be who she wants without having to worry about what others think of her; as a mental patient, she is unlikely to be criticized.
Because of this new-found freedom Veronika experiences all the things she never allowed herself to experience, including hatred and love. In the meantime, Villete's head psychiatrist, Dr.
Igor, attempts a fascinating but provocative experiment: can you 'shock' someone into wanting to live by convincing her that death is imminent? Like a doctor applying paddles to a victim, Dr.
Igor's 'prognosis' jump-starts Veronika's new appreciation of the world around her. Film adaptations [ ] • has been adapted into a screenplay by Das Films with Muse Productions and Velvet Steamroller Entertainment. Shooting began on May 12, 2008 and the movie was released in 2009 with Emily Young directing. • The 2005 Japanese movie, 'ベロニカは死ぬことにした (Beronika wa shinu koto ni shita)' is also based on Veronika Decides to Die. References [ ].