• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Glob Heart. Author manuscript; available in PMC Dec 1, 2013.
Published in final edited form as:
Glob Heart. Dec 1, 2012; 7(4): 315–329.
Published online Dec 5, 2012. doi:  10.1016/j.gheart.2012.10.004
PMCID: PMC3652434

Assessing the Global Burden of Ischemic Heart Disease

Part 1: Methods for a Systematic Review of the Global Epidemiology of Ischemic Heart Disease in 1990 and 2010



Ischemic heart disease (IHD) is the leading cause of death worldwide. The GBD (Global Burden of Disease, Injuries, and Risk Factors) study (GBD 2010 Study) conducted a systematic review of IHD epidemiology literature from 1980 to 2008 to inform estimates of the burden on IHD in 21 world regions in 1990 and 2010.


The disease model of IHD for the GBD 2010 Study included IHD death and 3 sequelae: myocardial infarction, heart failure, and angina pectoris. Medline, EMBASE, and LILACS were searched for IHD epidemiology studies in GBD high-income and low- and middle-income regions published between 1980 and 2008 using a systematic protocol validated by regional IHD experts. Data from included studies were supplemented with unpublished data from selected high-quality surveillance and survey studies. The epidemiologic parameters of interest were incidence, prevalence, case fatality, and mortality.


Literature searches yielded 40,205 unique papers, of which 1,801 met initial screening criteria. Upon detailed review of full text papers, 137 published studies were included. Unpublished data were obtained from 24 additional studies. Data were sufficient for high-income regions, but missing or sparse in many low- and middle-income regions, particularly Sub-Saharan Africa.


A systematic review for the GBD 2010 Study provided IHD epidemiology estimates for most world regions, but highlighted the lack of information about IHD in Sub-Saharan Africa and other low-income regions. More complete knowledge of the global burden of IHD will require improved IHD surveillance programs in all world regions.

Ischemic heart disease (IHD) is caused by insufficient oxygen delivery to meet the metabolic demands of heart muscle. IHD can be caused by a failure to adequately perfuse cardiac myocytes with oxygenated blood (failure of supply) and/or to increase myocyte oxygen demand [1]. Failure of oxygen supply most commonly occurs due to a fixed narrowing or acute rupture or dissection of an atherosclerotic coronary artery, or less commonly due to coronary artery spasm, embolism, or vasculitis. Inadequate oxygen supply may also occur due to severe anemia or systemic hypotension. Ischemia due to increased oxygen demand may be caused by sustained tachycardia, uncontrolled hypertension, or heart failure. Less commonly, IHD may occur due to cardiac revascularization procedures [1]. IHD can lead to acute myocardial necrosis (acute myocardial infarction [AMI]), fatal arrhythmia, or to a number of chronic sequelae, most prominently stable angina pectoris or heart failure (Fig. 1).

Fig. 1
Epidemiologic model of IHD

IHD was the leading cause of deaths and life-years lost from any cause worldwide in 2010 [2], and IHD was the leading cause of death and disability among the major cardiovascular diseases. IHD is not only a disease of the elderly in wealthy countries, but also past analyses by the GBD (Global Burden of Diseases, Injuries, and Risk Factors) study and other studies indicate that IHD has a major global impact on working-age adults and is a growing problem in low- and middle-income countries [35].

IHD is among the major diseases globally, but regional importance varies due to differences in IHD incidence, prevalence, and mortality, as well as the impact of competing diseases. The GBD study was started in 1991 as an effort to inform health policy making by using standard methods to comprehensively assess the mortality and disability burden of the world’s major diseases, injuries, and risk factors by world region for the year 1990. GBD estimates were updated in 2004 [6], but the current study represents the first comprehensive and de novo analysis since the original study. The GBD embarked in 2007 to improve and update GBD methods and analyze the burden of diseases, risk factors, and injuries for the years 1990 and 2005 in 21 world regions (Fig. 2) [7]. The latest GBD analysis required comprehensive and systematic reviews of the epidemiologic literature for the major global diseases. Here, we present the methods and summary data for the GBD IHD epidemiology systematic review. The goals were to: 1) establish GBD case definitions for IHD and its sequelae; 2) define an epidemiologic model of IHD and data types to be included in the review; 3) document the systematic review methods including novel literature search and validation strategies; and 4) present the quantity and quality of the data retrieved.

Fig. 2
Map of the 21 GBD regions

IHD diagnosis and treatment have changed since the GBD last gathered primary epidemiologic data and established its IHD analysis methods. Most importantly, the universal case definition of MI [1, 8] evolved to account for widespread use of biomarkers of MI [9] such as troponins [10] and creatine kinase-myocardial band mass, and cardiac imaging in high-income regions [11, 12]. In regions where use of high-sensitivity biomarker measurement became common, many previously undiagnosed cases of AMI were identified. The advent of troponin measurements needs to be accounted for when estimating AMI incidence in high-income nations in 1990 and 2010, but troponin measurement cannot be required for AMI diagnosis in regions where troponin measurement is prohibitively expensive and are therefore not routinely performed [13].

Ongoing event surveillance of a defined population is the gold standard for obtaining accurate population-based IHD incidence and prevalence estimates. Outside of the MONICA (Multinational Monitoring of Trends and Determinants in Cardiovascular Disease) study [14], and a handful of similar surveillance studies [15, 16], such estimates have been rare, especially in developing regions. The GBD Study has developed methods for estimating IHD epidemiologic parameters for regions with sparse data, but its estimated results will never substitute for rigorous and direct population surveillance. Therefore, this report will serve not only to quantify the available body of IHD epidemiologic research over the >25 years past, but it will also identify regional gaps in knowledge and highlight future challenges for global IHD epidemiology research.


GBD 2005 study definitions of IHD

IHD may result in death or 3 general chronic sequelae: angina pectoris; nonfatal MI; or heart failure (Fig. 1).

IHD death

The International Statistical Classification of Diseases and Related Health Problems (ICD) is the international standard for classifying causes of death and nonfatal conditions. ICD rules require identification of the disease initiating the causal chain ending in deaths-that is, the underlying cause of death. ICD codes identifying IHD as the underlying cause of death since 1950 were grouped under the subcategory “cardiovascular and circulatory diseases” within the category “noncommunicable diseases” as part of the GBD list of 56 major causes of death (Table 1). IHD has consistently been classified as an underlying cause of death across multiple revisions of the ICD over time [17]. IHD deaths typically fall into 1 of 2 broad categories: death attributable to AMI; and sudden cardiac deaths. Whereas AMI deaths usually meet a number of objective diagnostic criteria, many sudden cardiac deaths are not witnessed and their association with IHD can only be inferred [14, 18].

Table 1
GBD cause of death and sequelae definitions for IHD

The ICD also encompasses nonfatal conditions not meant to be underlying causes of death (e.g., essential hypertension) and conditions intermediate in the causal chain between an underlying cause and death (e.g., heart failure). When such codes are inappropriately listed as underlying causes of death on death certificates, they are termed “garbage codes” that need to be reassigned to legitimate underlying causes of death. Frequent use of garbage codes in some nations has led to under-estimation of IHD mortality rates [19, 20]. The GBD has developed methods for reallocating garbage codes to legitimate underlying causes of death [17]. Deaths assigned nonspecific cause, signs, and symptoms ICD codes not meant to represent underlying causes are allocated to legitimate underlying cause codes in proportions equal to the relative magnitude of underlying cause-, age-, and sex-specific death rates. For ICD conditions intermediate in the causal chain between an underlying cause and death, statistical methods, literature review, or expert opinion are used to distribute the garbage-coded deaths to causally associated underlying causes. Intermediate causes associated with IHD deaths are described in Table 1 and Supplemental Tables 1 and 2. Because IHD is the most prevalent cause of death worldwide, especially in older adults, and the biggest proportion of garbage codes are assigned to deaths in the elderly, a large proportion of garbage-coded deaths have been reallocated to IHD.

Nonfatal IHD sequelae

AMI is a sudden and sustained loss of perfusion to heart muscle resulting in cardiac necrosis. Prior GBD analyses followed past World Health Organization (WHO) MONICA study criteria [14], which required any 2 of the following 3 criteria: ischemic symptoms; electrocardiographic changes; and elevated serum biomarkers. Newer biomarkers of cardiac ischemia, especially troponins, have improved the sensitivity of AMI diagnosis without a loss in specificity [9, 10]. Another recent addition to the definition of AMI is evidence of perfusion or wall motion abnormalities, which depends on routine use of cardiac imaging technology (echocardiography, radionuclide scanning, angiography, or other technologies). Advances in AMI diagnostics led recent consensus panels to recommend a modified case definition of AMI based primarily on abnormal biomarker levels, especially troponins (Table 2)[1, 8]. More AMI cases are diagnosed with the addition of the more sensitive troponin measures [2124], leading to an apparent increase in AMI incidence without a change in the true incidence [25, 26]. Trend analyses need to correct for the additional AMI diagnosed due to troponin measures in recent years in high income regions [8, 13]. The additional AMI cases identified using the new troponin-based criteria, but not captured by the old criteria may carry a prognosis no better than “old criteria” AMI, perhaps because the troponin-only cases occur more often in older patients with more co-morbidities [25].

Table 2
GBD case definitions for AMI, adapted from WHO 2008 to 2009 consensus panel definitions (adapted from Mendis et al. [13])

A potential consequence of an AMI definition more dependent on serum biomarkers and imaging (and less dependent on clinical symptoms) is a widening “diagnosis gap” between high-diagnostic capacity regions and low-diagnostic capacity regions. A WHO expert panel recently acknowledged this problem and proposed a 3-tiered definition of AMI (Table 2) [13]. WHO AMI category A is identical to the troponin-based European Society of Cardiology/American Heart Association/World Heart Federation definition and was the standard used by the GBD review for high-income regions. WHO AMI categories B and C were used as the standard for the GBD review for low- and middle-income region studies that lacked the resources necessary for cardiac biomarker measurement or cardiac imaging. It was decided a priori that GBD IHD analyses would have to adjust estimates at the individual study level for troponin measurement status.

The epidemiology of MI is best measured by capturing acute MI cases at the time of diagnosis. Survey methods used to measure the prevalence of MI survivors (using self-reported diagnosis or resting ECG changes typical of past MI, especially “Q“ waves) are subject to measurement error in low incidence populations and past prevalent MI survey studies are of uneven quality [27]. Therefore, MI prevalence survey studies were not used directly to formulate GBD MI epidemiologic estimates. Silent myocardial infarctions occur without the usual signs and symptoms of an AMI but are recognized later using ECG or imaging criteria for prior MI [28]. Because the GBD intends to quantify only deaths and symptomatic disease states, the GBD definition of prior MI excludes silent MI.

Angina pectoris is a pressure-like pain in the chest induced by exertion or stress and relieved within minutes after cessation of effort or treatment with anti-anginal medications. Stable angina is chest pain not associated with an acute coronary event that is reliably and reproducibly induced by the same level of exertion and is generally managed in the outpatient setting. Stable angina may be slightly (approximately 20%) more prevalent in women compared with men internationally[29]. Unstable angina is a sudden and/or accelerating onset in chest pain or new chest pain at rest, and represents a clinical state associated with high risk of AMI and death. In international registries, unstable angina historically constitutes approximately one-third to one-half of acute coronary syndrome presentations, but has declined in use as an “acute coronary syndrome” category [30]. Subsequent IHD deaths or nonfatal MI in unstable angina patients were captured in either of the IHD mortality or MI categories.

Self-report of chest pain is subjective and there is no gold standard for estimating angina prevalence in most population surveys. The Rose questionnaire (Supplemental Table 3, sometimes referred to as the London School of Hygiene cardiovascular questionnaire), has been used as a standard community-based survey measure of angina prevalence. With evidence of inducible myocardial ischemia on exercise electrocardiogram plus nuclear coronary artery perfusion scanning as the gold standard of angina diagnosis, the Rose questionnaire has been found to have 40–67% sensitivity and 56–80% specificity, with markedly lower positive predictive value in women compared with men [31, 32]. It has been proposed that a higher portion of stable angina in women may be due to impaired coronary micro-circulation not detectable with conventional coronary perfusion scans [29]. Nonetheless, because of the questionable accuracy of the Rose questionnaire, the GBD also reviewed surveys of physician-diagnosed angina reported by either the patient (survey respondent) or the physician. It was decided a priori that angina prevalence estimates would be adjusted at the individual study level for angina measurement method.

Anginal symptoms may be alleviated or diminished by antianginal medications, most commonly nitrates, beta-blockers, or calcium channel blockers. Alternately, anginal symptoms may be treated and partially or fully relieved by elective revascularization (i.e., percutaneous coronary interventions or coronary artery bypass graft surgery) (Fig. 1). Past GBD methods assumed revascularization led to complete remission of angina. The Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial randomized angina patients to either maximal pharmaceutical or pharmaceutical therapy plus revascularization demonstrated that either treatment completely relieved angina symptoms in at best 60% of patients in either treatment arm [33], so the present study assumed that medical management or coronary revascularization leads to complete remission in only a corresponding proportion of angina patients.

Heart failure is a chronic long-term sequela for IHD but may also result from hypertensive heart disease, valvular heart disease, or cardiomyopathies. The proportion of heart failure attributed to IHD as a cause varies by region [34] and has changed over time within regions [35]. The probability of developing heart failure after AMI was obtained from long term follow up studies of MI patients [36, 37]. Over the past decades, most epidemiologic studies have based a diagnosis of heart failure on either the functional classification developed by the New York Heart Association (NYHA)[38]. Framingham Heart Study heart failure criteria [39] (Appendix Table 4), or hospital discharge diagnosis ICD code. Framingham criteria are more rigorous, combining symptoms and physical examination. The GBD decided to capture only symptomatic cases of heart failure meeting Framingham criteria or inclusive of New York Heart Association class II or higher or hospitalized cases with heart failure as the principal discharge diagnosis (ICD-9 428, ICD-10 I50). Heart failure symptoms may be alleviated by diuretic and other medications, and survival time with heart failure can be prolonged by medications (angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, beta-blockers, and others).

An epidemiologic model of IHD

For the purposes of identifying the main epidemiologic parameters involved with IHD and the diagnostic measures to target in the systematic review, we constructed an epidemiologic model of IHD based on the GBD definitions (Fig. 1). Causal arrows in the IHD model are unidirectional because there was an assumption that once a diagnosis of IHD is made, though symptoms may be alleviated, there is no complete remission to a state of not having IHD. “Asymptomatic IHD” describes persons who survived an initial IHD event and are living in an interval without symptoms of AMI, heart failure, or angina. Cardiac arrhythmias associated with IHD that occur outside the setting of AMI were described and measured by the GBD arrhythmia group and were not reviewed. As explained herein, some aspects of IHD are accounted for, but not specifically described in the model, such as unstable angina (because AMI following an episode of unstable angina would be captured in the model) or silent MI.

The GBD IHD disease model illustrates the inter-relation between IHD states: for persons in any given IHD state, there is a probability of transition to another IHD state (e.g., the probability of AMI after angina onset or the probability of heart failure after AMI) and a probability of dying (an IHD or non-IHD death). Standard relationships between disease model parameters (incidence, case fatality, mortality, and prevalence) were incorporated in a unique GBD software program, DisMod-MR (Disease Model Meta-Regression; Institute for Health Metrics and Evaluation, Seattle, WA, USA). DisMod-MR is particularly useful in imputing missing or incomplete estimates by fitting them to known estimates within a disease-specific model context. From the epidemiologic model, a list of the key epidemiologic parameters and study types were generated (Supplemental Table 5).

Summary methods for the systematic review of IHD epidemiology studies published from 1980 to 2008

Supplemental Appendix A and Figure 3 describe the systematic review methods in detail. In brief, 3 electronic databases were searched: MEDLINE (via PubMed), EMBASE, and LILACS. Searches were initially performed in MEDLINE and refined there before being adapted for EMBASE and LILACS. English language and non-English language articles were included; years were restricted to 1980 to 2008; articles were limited to human studies; and no age limits were applied. The PubMed search was performed using Medical Subject Heading (MeSH) terms related to IHD, and additional search terms related to IHD and IHD sequelae and geographic region terms were added to the search and restricted to the title or abstract of the citations. An inclusive, high-sensitivity approach was employed for low- and middle-income regions and a restrictive, high-specificity approach for high-income regions (Supplemental Appendix A). MeSH terms “developed” and “developing” were combined with specific country name key words in order to replicate GBD high-income and low- and middle-income region groupings. Comparable search strategies were executed in EMBASE and LILACS.

Fig. 3
Literature review and data abstraction flow chart for IHD systematic review

To validate the initial search strategy, selected IHD epidemiology experts representing 15 of the 21 GBD regions (Eastern Europe, East Asia, South Asia, North America, 4 Sub-Saharan Africa regions, Australasia, Middle East and North Africa, 4 Latin American regions, and the Caribbean) were asked to identify key IHD epidemiology papers from their region(s) of expertise published between January 1, 1980, and July 1, 2008. The initial electronic database search results were checked against the final validation list of 51 key IHD studies submitted by the selected experts (Supplemental Appendix B). The initial search included 71% of the validation set papers. The initial search strategy was modified to include additional search terms identified in the expert panel’s papers not retrieved in the first search. The electronic search was repeated in each of the 3 electronic databases, leading to inclusion of 82% of the experts’ validation list.

Papers were selected for detailed full text review if the study met all of the following criteria: 1) it reported on an IHD epidemiologic parameter of interest to the GBD study (incidence, prevalence, case-fatality, or mortality); 2) it was population-based; 3) data was reported for an age range including at least 45 to 54 years; 4) the study observation period ended after 1980; 5) fatal IHD was defined using ICD or MONICA coding; and 6) nonfatal IHD conformed to one of the GBD IHD sequelae definitions. Pairs of study investigators personally reviewed eligible papers published in English, Spanish, Portuguese, or Chinese. Papers published in any other languages were translated by multilingual health researchers hired by the GBD study, and the resulting translations were reviewed by pairs of study investigators with the original paper’s results in hand. Final inclusion or exclusion was based on the criteria stated herein, and papers were reviewed and discussed until consensus was reached about inclusion.

Inclusion of selected unpublished IHD epidemiology estimates

The gold standard for most of the IHD epidemiology estimates needed for the GBD study is a high-quality IHD surveillance study of a large, stable, geographically defined population representative of a GBD region. It was decided a priori in the interest of parsimony and quality assurance that epidemiologic estimates for the North America High Income, Western Europe, and East Asia regions would be derived primarily from high-quality surveillance or cohort studies that span the observation interval of interest (approximately 1980 until present). To obtain estimates surrounding the GBD target years of 1990 and 2005, 2 basic observation intervals were identified for pooled data: 1985 to 1997 and 1998 to present or most recent year.

For MONICA study data on IHD death and MI incidence, the first period of observation was defined as the period of the main MONICA study (approximately 1983 to 1993). Data after 1994 were contributed by ongoing surveillance studies that originated in MONICA sites in Sweden (north of country), Finland (FinRISK, national), Belgium (Ghent), Italy (Brianza), France (Strausbourg, Lille, and Toulouse), Lithuania (Kaunas), and China (Beijing, through to 2004) (Supplemental Table 6). Unpublished United States data (the Atherosclerosis Risk in Communities Study (ARIC), Framingham Heart Study, Cardiovascular Health Study, and others) were obtained from the National Heart, Lung, and Blood Institute 2006 Chartbook [40]. Published estimates from the Rochester Epidemiology Project [15] and American Heart Association annual statistics reports [41] were also used. Unpublished national MI incidence data were also provided for Mexico (A. Lara Esqueda, September 2009), and Australia (T. Vos, June 2010).

In order to supplement stable angina prevalence data (especially for younger adults) and quantify the effect of different measurement methods on angina prevalence estimation, original analyses were conducted of the international World Health Survey (WHS, 2002-04)[42], and three United States surveys: the Behavioral Risk Factor Surveillance System (BRFSS, 2005-10)[43], the National Health and Nutrition Examination Survey (NHANES, 2001-02,2004-09)[44], and the Medical Expenditure Panel Survey (MEPS, 2002-09)[45]. Because the WHS provided angina prevalence data for 47 countries, most of them low- and middle-income countries, the WHS was a potentially valuable source of information on the pattern of angina prevalence worldwide. Information on the surveys and questionnaire questions used to identify stable angina cases in these surveys are listed in Supplemental Appendix C.

For the analysis of ischemic heart failure, hospital individual record data from Europe (European Hospital Morbidity Database, 1999 to 2007), United States (Healthcare Cost and Utilization Project and National Hospital Discharge Surveys, 1979 to 2006), Canada (Discharge Abstract Database, 2004 to 2009), Mexico (National Health Information System, 2000 to 2009), Ecuador (National Statistics Institute Database, 1996 to 2006), and Brazil (Hospital Information System of the National Unified Health System, 2006 to 2009) were analyzed to find the distribution of underlying heart failure causes in patients admitted with the principal diagnosis of heart failure. Additionally, deaths due to the major underlying causes of heart failure, as well as cases assigned heart failure as the cause of death from cause-of-death data, were used to inform the composition of heart failure causes.


The final electronic search yielded 40,205 papers, of which 1,801 initially met inclusion criteria (Fig. 3). Careful review of full-text papers led to final inclusion of 137 studies (some studies’ results were reported in more than one publication). Using 2012 World Bank country income categories [40], 114 high-income country studies, 77 middle-income country studies, and 15 low-income country studies were included (Supplemental Table 7). For published studies, 90 originated from high-income countries, 46 from middle-income countries, and one from low-income countries. All of the low-income countries studies reported on angina prevalence; there were no AMI or heart failure studies included from low-income countries. Despite extensive efforts to obtain full-text papers from both the Columbia University and Harvard University libraries and their affiliated collections or directly from regional experts, a number of publications were unobtainable. Most remarkably, in the Latin American and Caribbean regions, 56 full-text papers (3% of all eligible papers) were not retrievable: 97% of nonretrievable articles were indexed in LILACS and 78% were published prior to 1995. Unpublished data from 19 additional data sources on MI and heart failure epidemiology were added for the North America, Western Europe, Eastern Europe, Australasia, Central Latin America, Tropical Latin America, Andean Latin America, and East Asia regions. Angina prevalence estimates were obtained by study investigators for 18 GBD regions using the U.S. NHLBI 2006 Chartbook and population-weighted estimates from the WHS, BRFSS, NHANES, and MEPS surveys.

Sixty-two studies were included for MI incidence estimation, including 10 unpublished studies. With the exceptions of Central and Eastern Europe and East Asia, few good-quality studies on MI incidence were available representing low- and middle-income regions (Fig. 4). Especially in low- and middle-income regions, the majority of case-fatality studies were single-institution studies of in-hospital case fatality. Complete in- and out-of-hospital case-fatality was rarely reported [4650]. In the end, only 29 studies reporting on acute MI case fatality were included in the GBD analysis (Fig. 5).

Fig. 4
Number of included studies used for myocardial infarction incidence estimation, by GBD region
Fig. 5
Number of included studies used for acute myocardial infarction case fatality estimation, by GBD region

IHD prevalence surveys were unusually common in the South Asia, Southeast Asia, Eastern Europe, and North Africa/Middle East regions. The systematic review yielded 42 studies reporting on stable angina prevalence. After adding the NHLBI Chartbook data, the WHS and 3 U.S. surveys analyzed for angina prevalence, led to 47 angina prevalence studies (Fig. 6). Of 42 heart failure studies used in the analysis, 9 were unpublished.

Fig. 6
Number of included studies used for stable angina pectoris prevalence estimation, by GBD region

Sub-Saharan African regions, especially Central and East Africa, were remarkable for almost total lack of IHD epidemiology data of any type. Almost all of the IHD estimates for Sub-Saharan Africa came from South Africa. South Africa studies of IHD epidemiology exclusively in the white population (typical of studies published prior to the end of apartheid) were excluded because they were deemed not representative of the general population of the region. Until the advent of recent studies like the Heart of Soweto Study [51], studies from Sub-Saharan Africa were all of low quality or complicated by uncertainty. For example, the only two IHD incidence papers for the entire region represented the township of Soweto, South Africa. The first incidence paper (Walker et al.) did not state a case definition for IHD[52], and for both incidence estimates, the proportion of cases living in Soweto and the population of Soweto lack precise quantification [51, 52]. The Eastern Europe region stood out because the majority of studies (75%) from that region sampled men only.

The only IHD incidence data spanning the years from approximately 1985 until 2005 using similar methods over time were gathered from following studies: 8 ongoing MONICA sites (Fin-MONICA [now FinAMI], Ghent-MONICA [Belgium], 3 French MONICA sites [Toulouse, Strasbourg, Lille], Brianza-MONICA [Italy], Sino-MONICA [Beijing, China], and Kaunas-MONICA [Lithuania]), the Northern Sweden surveillance study (not part of the original MONICA study, but employs MONICA methods), and in the United States, ARIC, the Framingham Heart Study, the Cardiovascular Health Study, and the Rochester Epidemiology Project.

Of the AMI incidence studies included, 4 of 7 high-income region studies gathering data after 2000 and reporting detailed diagnostic criteria included troponin measurements in their MI outcome diagnostic definitions. None of the developing region AMI incidence studies included positive troponin in the case definition of AMI.



A systematic review of IHD literature in 21 world regions demonstrated that it is feasible to gather IHD epidemiology literature using a high-sensitivity approach for developing regions and a high-specificity approach for high-income regions. Despite this design, the review revealed scant IHD epidemiology data from most low- and middle-income regions, particularly Sub-Saharan Africa. In contrast, complete high-quality estimates were available from East Asia and Central Europe, which are on average middle-income regions. Even for high-income regions, most of the comprehensive estimates including the years surrounding 1990 and 2005 were gathered from unpublished data. From this review of IHD epidemiology, a number of key methodologic challenges were identified: the need to reallocate IHD deaths erroneously assigned to ill-defined cardiovascular causes, the need to adjust past incidence to fit with the new, troponin-based definition of AMI, measurement limitations of population survey estimation of stable angina and IHD prevalence, estimation of the fraction of all heart failure attributable to IHD and the more general problems of missing data, random error, and bias.

IHD death

Effective allocation of global public health resources depends on accurate vital statistics, including national cause-of-death data. The problem of “bridging” cause-of-death data across changing ICD definitions has been simplified by creating a list of GBD 291 major causes of death. GBD investigators have been able to consistently trace IHD as an underlying cause of death from the earliest ICD up until the current ICD-10. Frequent use of garbage codes may bias cause specific mortality rates. In particular, past studies have shown that IHD death rates are substantially underestimated for some nations if garbage-coded deaths are not accounted for [19, 20]. The GBD has recently refined the method for re-allocating garbage coded deaths to IHD and other underlying causes, ensuring optimal use of available national cause-of-death data for the purpose of estimating the mortality portion of the global burden of IHD [17].


The recommended case definition of AMI was recently changed to include a primary emphasis on positive biomarker measurements, specifically troponin [1]. Troponin measurements were introduced in high-income nations during the mid-1990s. We found no low- or middle-income region studies of AMI incorporating positive troponin in the case definition published during 1980 to 2008. Even in high-income regions, the troponin-based definition of MI has been used in epidemiologic studies only since approximately 2000. Moving forward, in comparing past AMI incidence estimates to estimates after 2000, past estimates will require adjustment to reflect the additional incidence that would have been added had troponin been available [25, 26]. The GBD main epidemiologic and burden estimates will adjust AMI incidence using a study-level troponin measurement variable for data published after approximately 2000. Regarding MI case fatality, numerous published single-center studies of in-hospital case fatality were identified, but population-based and multicenter studies were rare, leading to only 29 AMI case-fatality studies included in the analysis; 15 of these were from low-or middle-income regions.

Angina pectoris

The primary GBD angina case definition relies on the classic Rose questionnaire descriptions, but studies included from the systematic review employed a variety of measures of angina prevalence, including self-reported diagnosis, diagnosis made by a study physician, and even use of specific antianginal medications (e.g., nitrates). Several studies suggest that the Rose questionnaire has poor specificity, especially in women (range 56—76%)[31, 32, 53], leading to inflated prevalence estimates in females compared with males. Others argue that higher angina prevalence in females compared with males persists when a more rigorous diagnostic method is used [54], and Rose-diagnosed angina implies a poor prognosis and should not be dismissed by clinicians or epidemiologists [29]. Based on the review literature, we concluded that angina prevalence estimation should account for measurement method and that lack of a diagnostic gold standard calls for caution in interpreting estimates of angina prevalence.

Ischemic heart failure

IHD is only one of several causes of heart failure in the GBD. Estimation of ischemic heart failure prevalence required a 2-step process: 1) estimating the total heart failure envelope, inclusive of heart failure cases of all causal origins; and 2) estimating the proportion of heart failure attributable to IHD specific to region, age group, and sex. Data from the systematic review were included in both steps of the analysis.

Study limitations

Though this systematic review conformed to most of the standard guidelines for systematic reviews (PRISMA checklist Appendix G)[55], it is possible that many of the included studies reported data collected with bias, and for many estimates no measures of uncertainty (in the form of standard deviations or errors, confidence intervals, etc.) were reported. Though many of the studies contributing data to the GBD review were population-based studies or national cause-of-death or hospital registries, some may not be regionally representative: in some instances national or provincial surveys or cohort studies were selected that may fail to accurately represent an epidemiologically heterogeneous regional population. A study of national IHD mortality trends in several selected world regions demonstrated that there may be variability within broad geographic regions [56]. Some of this variance may be due to methodologic differences in vital statistics registration, but some may be due to epidemiologic heterogeneity that is obscured when reporting estimates for broad regions. Especially for publications from the Latin American and Caribbean region papers published before 1995, a substantial proportion of published papers selected for review were not obtainable. Selected unpublished data were obtained, but these predominantly represent high-income regions. It is likely that we are missing a great deal of unpublished data from government and large health system records; it was beyond the scope of this review to quantify the volume of unpublished data missed by using standard electronic database search methods.


Health policy decisions and resource allocation are ideally made based on high-quality epidemiologic data. The scale and pervasiveness of IHD in the majority of world regions makes estimation of IHD mortality, incidence, prevalence, and case fatality crucially important to public health worldwide. A main objective of the GBD is provision of accurate, unbiased estimates of disease burden gathered and analyzed with standard methods and reported with transparency. This GBD systematic review of IHD demonstrated that it is feasible to complete a large-scale review of the IHD epidemiology literature using search methods tailored to emphasize sensitivity in developing regions and specificity in high-income regions. Despite this broad search and careful screening, the quantitative results of the review demonstrate the scarcity of high-quality IHD epidemiologic data to support policy making and resource allocation, particularly in low- and middle-income regions. Assessment of qualitative results of the IHD epidemiology review leads to the conclusion that there is no substitute for high-quality, standardized surveillance studies of IHD. Ongoing surveillance studies deserve support, and the founding of new surveillance studies should be a high priority, especially in low- and middle-income regions.

Supplementary Material



The authors thank the researchers who generously provided unpublished data to the study investigators, especially Drs. Agustín Lara Esqueda and Araceli Arevalo (Mexico data), Dr. Dong Zhao (Bejing, China, data), Dr. Abdonas Tamosiunas (Kaunas, Lithuania, data), Drs. Marco Ferrario, Giancarlo Cesana, and Giovanni Veronesi (Brianza, Italy, data), Drs. Dominique Arveiler, Aline Wagner and Bernadette Haas (Strasbourg, France, data), Drs. Philippe Amouyel and Michele Montaye (Lille, France, data), Drs. Jean Ferrieres and Jean-Bernard Ruidavets (Toulouse, France, data), Drs. Pierre Ducimetiere and Annie Bingham (Coordinating Centre of the French CHD Registries), Dr. Dirk De Bacquer (Ghent, Belgium, data), Drs. Mats Eliasson and Stefan Söderberg (Northern Sweden data), and Dr. Theo Vos (Australia data). We are thankful for the language translation work of the many health professionals in Seattle, Washington, who expanded the literature review substantially. We offer our sincere thanks to the thousands of study participants and investigators contributing the science reviewed.

This research was supported by the Bill and Melinda Gates Foundation and by a Lucy Falkiner Award, the Medical Foundation of the University of Sydney and U.S. National Heart, Lung, and Blood Institute Award K08 HL089675-01A1 to A.E.M.



Supplemental data related to this article can be found at http://dx.doi.org/10.1016/j.gheart.2012.10.004


1. Thygesen K, Alpert JS, White HD, et al. Universal definition of myocardial infarction. Circulation. 2007;116(22):2634–2653. [PubMed]
2. Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380(9859):2197–2223. [PubMed]
3. Murray CJ, Lopez AD. Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet. 1997;349(9061):1269–1276. [PubMed]
4. Abegunde DO, Mathers CD, Adam T, Ortegon M, Strong K. The burden and costs of chronic diseases in low-income and middle-income countries. Lancet. 2007;370(9603):1929–1938. [PubMed]
5. Leeder S, Raymond S, Greenberg H, Liu H, Esson K. A Race Against Time: the Challenge of Cardiovascular Disease in Developing Countries. New York, NY: Columbia University Center for Global Health and Economic Development; 2004.
6. Mathers CD, Truelson T, Begg S, Satoh T. Global Burden of Disease 2000 Working Paper. Geneva: World Health Organization; 2004. Global burden of ischemic heart diseae in the year 2000.
7. Murray CJ, Lopez AD, Black R, et al. Global burden of disease 2005: call for collaborators. Lancet. 2007;370(9582):109–110. [PubMed]
8. Luepker RV, Apple FS, Christenson RH, et al. Case definitions for acute coronary heart disease in epidemiology and clinical research studies: a statement from the AHA Council on Epidemiology and Prevention; AHA Statistics Committee; World Heart Federation Council on Epidemiology and Prevention; the European Society of Cardiology Working Group on Epidemiology and Prevention; Centers for Disease Control and Prevention; and the National Heart, Lung, and Blood Institute. Circulation. 2003;108(20):2543–2549. [PubMed]
9. Jaffe AS, Babuin L, Apple FS. Biomarkers in acute cardiac disease: the present and the future. J Am Coll Cardiol. 2006;48(1):1–11. [PubMed]
10. Jaffe AS, Ravkilde J, Roberts R, et al. It's time for a change to a troponin standard. Circulation. 2000;102(11):1216–1220. [PubMed]
11. Udelson JE, Beshansky JR, Ballin DS, et al. Myocardial perfusion imaging for evaluation and triage of patients with suspected acute cardiac ischemia: a randomized controlled trial. JAMA. 2002;288(21):2693–2700. [PubMed]
12. Stowers SA, Eisenstein EL, Th Wackers FJ, et al. An economic analysis of an aggressive diagnostic strategy with single photon emission computed tomography myocardial perfusion imaging and early exercise stress testing in emergency department patients who present with chest pain but nondiagnostic electrocardiograms: results from a randomized trial. Ann Emerg Med. 2000;35(1):17–25. [PubMed]
13. Mendis S, Thygesen K, Kuulasmaa K, et al. World Health Organization definition of myocardial infarction: 2008–09 revision. Int J Epidemiol. 2011;40(1):139–146. [PubMed]
14. Tunstall-Pedoe H, Kuulasmaa K, Mahonen M, Tolonen H, Ruokokoski E, Amouyel P. Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project populations. Monitoring trends and determinants in cardiovascular disease. Lancet. 1999;353(9164):1547–1557. [PubMed]
15. Roger VL, Weston SA, Gerber Y, et al. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation. 2010;121(7):863–869. [PMC free article] [PubMed]
16. Rosamond WD, Chambless LE, Folsom AR, et al. Trends in the incidence of myocardial infarction and in mortality due to coronary heart disease, 1987 to 1994. N Engl J Med. 1998;339(13):861–867. [PubMed]
17. Naghavi M, Makela S, Foreman K, O'Brien J, Pourmalek F, Lozano R. Algorithms for enhancing public health utility of national causes-of-death data. Population health metrics. 2010;8:9. [PMC free article] [PubMed]
18. MONICA Coronary Event Registration Data Book 1980–1995. [accessed September 25, 2011];Appendix 1: Coronary heart disease diagnostic categories. 2011 http://www.ktl.fi/publications/monica/coredb/coredb.htm#definitions.
19. Lozano R, Murray CJL, Lopez AD, Satoh T. Global Programme on Evidence for Health Policy Working Paper No. 12. Geneva: World Health Organization; 2001. Miscoding and misclassification of ischaemic heart disease mortality.
20. Murray CJ, Kulkarni SC, Ezzati M. Understanding the coronary heart disease versus total cardiovascular mortality paradox: a method to enhance the comparability of cardiovascular death statistics in the United States. Circulation. 2006;113(17):2071–2081. [PubMed]
21. Ferguson JL, Beckett GJ, Stoddart M, Walker SW, Fox KA. Myocardial infarction redefined: the new ACC/ESC definition, based on cardiac troponin, increases the apparent incidence of infarction. Heart. 2002;88(4):343–347. [PMC free article] [PubMed]
22. Lin JC, Apple FS, Murakami MM, Luepker RV. Rates of positive cardiac troponin I and creatine kinase MB mass among patients hospitalized for suspected acute coronary syndromes. Clin Chem. 2004;50(2):333–338. [PubMed]
23. Ohman EM, Armstrong PW, Christenson RH, et al. Cardiac troponin T levels for risk stratification in acute myocardial ischemia. GUSTO IIA Investigators. N Engl J Med. 1996;335(18):1333–1341. [PubMed]
24. Apple FS, Johari V, Hoybook KJ, Weber-Shrikant E, Davis GK, Murakami MM. Operationalizing cardiac troponin I testing along ESC/ACC consensus guidelines for defining myocardial infarction: increasing rate of detection. Clin Chim Acta. 2003;331(1–2):165–166. [PubMed]
25. Salomaa V, Koukkunen H, Ketonen M, et al. A new definition for myocardial infarction: what difference does it make? Eur Heart J. 2005;26(17):1719–1725. [PubMed]
26. Roger VL, Killian JM, Weston SA, et al. Redefinition of myocardial infarction: prospective evaluation in the community. Circulation. 2006;114(8):790–797. [PubMed]
27. Moran A, Shen A, Turner-Lloveras D, et al. Utility of self-reported diagnosis and electrocardiogram Q-waves for estimating myocardial infarction prevalence: an international comparison study. Heart. 2012 [PubMed]
28. Kannel WB, Abbott RD. Incidence and prognosis of unrecognized myocardial infarction. An update on the Framingham study. N Engl J Med. 1984;311(18):1144–1147. [PubMed]
29. Hemingway H, Langenberg C, Damant J, Frost C, Pyorala K, Barrett-Connor E. Prevalence of angina in women versus men: a systematic review and meta-analysis of international variations across 31 countries. Circulation. 2008;117(12):1526–1536. [PubMed]
30. Bertoni AG, Bonds DE, Thom T, Chen GJ, Goff DC., Jr Acute coronary syndrome national statistics: challenges in definitions. Am Heart J. 2005;149(6):1055–1061. [PubMed]
31. Garber CE, Carleton RA, Heller GV. Comparison of “Rose Questionnaire Angina” to exercise thallium scintigraphy: different findings in males and females. J Clin Epidemiol. 1992;45(7):715–720. [PubMed]
32. Bass EB, Follansbee WP, Orchard TJ. Comparison of a supplemented Rose Questionnaire to exercise thallium testing in men and women. J Clin Epidemiol. 1989;42(5):385–394. [PubMed]
33. Weintraub WS, Spertus JA, Kolm P, et al. Effect of PCI on quality of life in patients with stable coronary disease. N Engl J Med. 2008;359(7):677–687. [PubMed]
34. Khatibzadeh S, Farzadfar F, Oliver J, Ezzati M, Moran A. Worldwide risk factors for heart failure: A systematic review and pooled analysis. Int J Cardiol. 2012 [PMC free article] [PubMed]
35. Kannel WB, Ho K, Thom T. Changing epidemiological features of cardiac failure. Br Heart J. 1994;72(2 Suppl):S3–S9. [PMC free article] [PubMed]
36. Kannel WB. Epidemiology and prevention of cardiac failure: Framingham Study insights. Eur Heart J. 1987;8(Suppl F):23–26. [PubMed]
37. Hellermann JP, Goraya TY, Jacobsen SJ, et al. Incidence of heart failure after myocardial infarction: is it changing over time? Am J Epidemiol. 2003;157(12):1101–1107. [PubMed]
38. The Criteria Committee of the New York Heart Association. Nomenclature and criteria for diagnosis of diseases of the heart and blood vessels. Boston: Little Brown; 1964.
39. McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: the Framingham study. N Engl J Med. 1971;285(26):1441–1446. [PubMed]
40. National Heart, Lung, and Blood Institute, United States National Institutes of Health. [accessed October 4 2010];2006 NHLBI Incidence and Prevalence Chartbook. U.S. Department of Health and Human Services. http://www.nhlbi.nih.gov/resources/docs/cht-book_ip.htm.
41. Lloyd-Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics--2010 update: a report from the American Heart Association. Circulation. 2010;121(7):e46–e215. [PubMed]
42. The World Health Survey. [accessed June 21 2012];World Health Organization. 2002 http://www.who.int/healthinfo/survey/en/index.html.
43. Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System Survey Questionnaire. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; [accessed June 21 2012]. http://www.cdc.gov/brfss/index.htm.
44. U.S. Department of Health and Human Services (DHHS) National Heath and Nutrition Examination Survey: Questionnaires, Datasets, and Related Documentation. Hyattsville, MD: Centers for Disease Control and Prevention; [accessed June 21 2012]. National Center for Health Statistics. http://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm.
45. [accessed June 21 2012];Source: Medical Expenditure Panel Survey; Agency for Healthcare Research and Quality. http://meps.ahrq.gov/mepsweb/
46. Bata IR, Gregor RD, Eastwood BJ, Wolf HK. Trends in the incidence of acute myocardial infarction between 1984 and 1993 - The Halifax County MONICA Project. Can J Cardiol. 2000;16(5):589–595. [PubMed]
47. McGovern PG, Jacobs DR, Jr, Shahar E, et al. Trends in acute coronary heart disease mortality, morbidity, and medical care from 1985 through 1997: the Minnesota heart survey. Circulation. 2001;104(1):19–24. [PubMed]
48. Lowel H, Dobson A, Keil U, et al. Coronary heart disease case fatality in four countries. A community study. The Acute Myocardial Infarction Register Teams of Auckland, Augsburg, Bremen, FINMONICA, Newcastle, and Perth. Circulation. 1993;88(6):2524–2531. [PubMed]
49. Chambless L, Keil U, Dobson A, et al. Population versus clinical view of case fatality from acute coronary heart disease: results from the WHO MONICA Project 1985–1990. Multinational MONItoring of Trends and Determinants in CArdiovascular Disease. Circulation. 1997;96(11):3849–3859. [PubMed]
50. Rosamond W, Broda G, Kawalec E, et al. Comparison of medical care and survival of hospitalized patients with acute myocardial infarction in Poland and the United States. Am J Cardiol. 1999;83(8):1180–1185. [PubMed]
51. Sliwa K, Wilkinson D, Hansen C, et al. Spectrum of heart disease and risk factors in a black urban population in South Africa (the Heart of Soweto Study): a cohort study. Lancet. 2008;371(9616):915–922. [PubMed]
52. Walker AR, Sareli P. Coronary heart disease: outlook for Africa. J R Soc Med. 1997;90(1):23–27. [PMC free article] [PubMed]
53. Udol K, Mahanonda N. Comparison of the Thai version of the Rose questionnaire for angina pectoris with the exercise treadmill test. J Med Assoc Thai. 2000;83(5):514–522. [PubMed]
54. Hemingway H, McCallum A, Shipley M, Manderbacka K, Martikainen P, Keskimaki I. Incidence and prognostic implications of stable angina pectoris among women and men. Jama. 2006;295(12):1404–1411. [PubMed]
55. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. [PMC free article] [PubMed]
56. Mirzaei M, Truswell AS, Taylor R, Leeder SR. Coronary heart disease epidemics: not all the same. Heart. 2009;95(9):740–746. [PubMed]
57. Killip TKJT. Treatment of myocardial infarction in a coronary care unit: a two year experience of 250 patients. American Journal of Cardiology. 1967;20:457–464. [PubMed]
58. Hunt SA, Abraham WT, Chin MH, et al. ACC/AHA 2005 Guideline Update for the Diagnosis and Management of Chronic Heart Failure in the Adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure): developed in collaboration with the American College of Chest Physicians and the International Society for Heart and Lung Transplantation: endorsed by the Heart Rhythm Society. Circulation. 2005;112(12):e154–e235. [PubMed]
PubReader format: click here to try


Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...


  • PubMed
    PubMed citations for these articles

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...