Edited by: Lydia Bazzano, Tulane University School of Public Health and Tropical Medicine, United States
Reviewed by: Ronny Westerman, Bundesinstitut für Bevölkerungsforschung, Germany; Mostafa Qorbani, Alborz University of Medical Sciences, Iran
This article was submitted to Cardiovascular Epidemiology and Prevention, a section of the journal Frontiers in Cardiovascular Medicine
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Cardiovascular disease (CVD) is the largest single contributor to global mortality and morbidity, imposing a severe burden in terms of lost productivity and disability in adults (
A thorough knowledge of the different epidemiological characteristics of MC and cardiomyopathy among various countries and populations can help public health decision- and policy-makers develop and implement targeted programs aimed at the prevention and management of the diseases. However, reliable and accurate epidemiological data regarding MC and cardiomyopathy are predominantly available from developed countries which apply well-established and consolidated diagnostic evaluations and criteria (
This study is part of GBD 2017, which was designed to provide a systematic assessment of health loss due to diseases and injuries at the global, regional, and national levels. In the latest iteration, GBD 2017, seven super-regions, 21 regions, and 195 countries and territories were included; and estimates for 359 diseases and injuries, 282 causes of death, and 84 risk factors were reported. The detailed methodology used for the estimation process can be found in previous GBD 2017 papers (
MC, AC and OC were ascertained using the International Classification of Diseases version 9 (ICD-9) and version 10 (ICD-10) codes. Diseases coded as 422–422.9 in ICD-9 or B33.2, I40–I41.9, and I51.4 in ICD-10 were identified as MC; diseases coded as 425.5 in ICD-9 or I42.6 in ICD-10 were identified as AC; and diseases coded as 425.0–425.3, 425.7–425.8, and 429.0 in ICD-9 or I42.1–I42.5, I42.7–I42.8, and I43–I43.9 in ICD-10 were identified as OC (
Death estimates were derived from vital registration data sources for MC and OC, and from vital registration and verbal autopsy data sources for AC. The ICD codes listed above were used to identify the diseases from the data sources. Data points that were implausibly high and discontinuous with the rest of the time series, or unable to be disaggregated appropriately were treated as outliers. Deaths due to MC, AC, and OC were estimated using standard Cause of Death Ensemble model (CODEm), a highly systematized tool that runs many different models using location-level predictive covariates and chooses an ensemble of models that best reflects all the available input data (
The prevalence of MC, AC, and OC was estimated using DisMod-MR 2.1, a Bayesian mixed-effects meta-regression tool developed for GBD analyses (
YLDs were calculated by multiplying the prevalence (in number of cases) of each disease by the disability weight that quantifies the magnitude of heath loss associated with disease (
Socio-demographic Index (SDI) was a composite variable used to quantity the development level for each location-year (
YLLs were calculated by multiplying the number of deaths in each age group with a standard life expectancy at that age (
Worldwide, there were 1.80 million (95% UI 1.64–1.98) cases of MC, 1.62 million (95% UI 1.37–1.90) cases of AC and 4.21 million (95% UI 3.63–4.87) cases of OC in 2017. The age-standardized prevalence rates of MC, AC, and OC per 100,000 people in 2017 were 23.2 (95% UI 21.0–25.5), 19.9 (95% UI 16.8–23.3), and 53.9 (95% UI 46.7–62.1), respectively (
Age-standardized prevalence, death, YLD, and YLL rates of myocarditis, alcoholic cardiomyopathy, and other cardiomyopathy, and their percentage changes from 1990 to 2017, by sex and SDI quintile.
Global | 23.2 (21.0 to 25.5) | −6.9% (−7.8 to −5.9) | 0.6 (0.5 to 0.7) | −6.2% (−15.0 to 3.4) | 1.7 (1.2 to 2.4) | −7.2% (−8.6 to −5.9) | 16.6 (14.5 to 18.5) | −23.5% (−32.6 to −11.4) |
Male | 21.3 (19.4 to 23.4) | −4.7% (−5.6 to −3.7) | 0.7 (0.5 to 0.8) | 6.6% (−8.5 to 26.0) | 1.5 (1.0 to 2.1) | −4.7% (−6.1 to −3.2) | 18.3 (15.2 to 22.1) | −9.7% (−25.3 to 17.2) |
Female | 24.9 (22.4 to 27.4) | −8.1% (−9.2 to −6.9) | 0.6 (0.5 to 0.6) | −15.6% (−24.4 to −0.3) | 1.9 (1.3 to 2.6) | −8.6% (−10.3 to −6.8) | 14.8 (12.7 to 16.7) | −35.5% (−44.9 to −22.8) |
Low SDI | 17.3 (15.8 to 19.0) | 1.6% (0.5 to 2.7) | 0.5 (0.3 to 0.6) | −16.6% (−30.7 to 2.7) | 1.2 (0.8 to 1.6) | 2.7% (0.2 to 5.1) | 14.6 (10.2 to 19.1) | −30.1% (−43.7 to −10.3) |
Low-middle SDI | 19.6 (17.8 to 21.5) | 3.3% (2.2 to 4.3) | 0.6 (0.5 to 0.8) | −1.3% (−18.5 to 17.8) | 1.4 (0.9 to 1.9) | 4.3% (2.0 to 6.5) | 18.3 (14.7 to 22.5) | −22.0% (−36.6 to −2.6) |
Middle SDI | 25.6 (23.0 to 28.3) | 3.1% (2.0 to 4.2) | 0.8 (0.6 to 0.9) | 17.6% (3.8 to 33.5) | 1.9 (1.3 to 2.6) | 4.4% (2.1 to 6.8) | 20.0 (16.8 to 23.5) | −19.8% (−30.6 to −5.0) |
High-middle SDI | 25.7 (23.1 to 28.4) | 1.2% (−0.3 to 2.8) | 0.7 (0.6 to 0.8) | −14.2% (−26.9 to 7.0) | 1.9 (1.3 to 2.6) | 4.0% (0.9 to 7.4) | 17.0 (15.8 to 19.5) | −19.1% (−29.7 to −0.7) |
High SDI | 27.1 (24.7 to 29.5) | −17.8% (−19.6 to −15.6) | 0.5 (0.4 to 0.5) | −13.1% (−36.9 to −1.5) | 2.1 (1.4 to 2.9) | −18.9% (−21.5 to −16.2) | 12.3 (10.1 to 13.2) | −14.8% (−35.6 to −5.1) |
Global | 19.9 (16.8 to 23.3) | −26.2% (−28.2 to −24.0) | 1.1 (1.0 to 1.2) | −19.6% (−34.0 to −11.3) | 1.7 (1.2 to 2.4) | −25.7% (−28.0 to −23.2) | 34.7 (31.7 to 37.5) | −7.6% (−20.7 to 3.2) |
Male | 27.7 (23.4 to 32.4) | −22.2% (−24.6 to −19.4) | 1.7 (1.5 to 1.9) | −6.2% (−18.7 to 6.6) | 2.4 (1.6 to 3.3) | −21.8% (−24.6 to −18.6) | 55.2 (47.0 to 60.4) | 3.3% (−14.4 to 17.4) |
Female | 12.6 (10.6 to 14.7) | −33.6% (−35.4 to −31.6) | 0.5 (0.4 to 0.6) | −45.7% (−53.6 to −40.6) | 1.1 (0.7 to 1.5) | −32.8% (−35.2 to −30.1) | 14.8 (13.6 to 16.9) | −32.8% (−36.7 to −26.5) |
Low SDI | 11.8 (9.6 to 14.3) | 3.6% (1.0 to 6.2) | 0.4 (0.3 to 0.7) | −28.9% (−48.8 to −0.4) | 1.0 (0.7 to 1.5) | 4.2% (0.1 to 8.6) | 12.0 (7.8 to 17.8) | −31.5% (−49.8 to −5.1) |
Low-middle SDI | 9.4 (7.8 to 11.3) | 5.8% (2.6 to 9.0) | 0.4 (0.3 to 0.5) | −22.3% (−41.3 to 1.9) | 0.8 (0.6 to 1.2) | 6.1% (0.4 to 12.1) | 11.5 (9.4 to 14.4) | −21.9% (−40.2 to 1.2) |
Middle SDI | 7.1 (5.9 to 8.4) | 13.5% (11.5 to 15.5) | 0.3 (0.3 to 0.4) | 8.9% (−14.7 to 33.2) | 0.6 (0.4 to 0.9) | 13.5% (10.7 to 16.4) | 9.1 (7.4 to 11.1) | 12.3% (−11.5 to 34.0) |
High-middle SDI | 27.2 (22.8 to 31.9) | −32.0% (−33.5 to −30.4) | 3.1 (2.9 to 3.5) | 5.9% (−14.5 to 31.2) | 2.3 (1.6 to 3.3) | −31.5% (−33.6 to −29.2) | 108.4 (101.1 to 120.6) | 19.6% (−3.8 to 52.9) |
High SDI | 40.0 (34.5 to 46.1) | −17.7% (−21.7 to −12.9) | 0.8 (0.7 to 0.9) | −45.4% (−58.2 to −37.5) | 3.4 (2.3 to 4.7) | −17.7% (−22.5 to −12.5) | 22.8 (18.7 to 24.7) | −41.8% (−52.7 to −35.3) |
Global | 53.9 (46.7 to 62.1) | −15.5% (−18.4 to −12.7) | 3.1 (2.8 to 3.3) | −30.7% (−35.2 to −17.8) | 4.5 (3.1 to 6.3) | −15.0% (−17.8 to −12.1) | 71.1 (64.0 to 77.0) | −20.8% (−26.6 to −12.2) |
Male | 53.1 (45.9 to 61.2) | −9.5% (−12.8 to −6.1) | 3.6 (3.1 to 3.9) | −22.9% (−30.5 to 7.8) | 4.5 (3.0 to 6.2) | −9.3% (−12.6 to −5.8) | 86.9 (77.0 to 95.1) | −11.9% (−21.0 to 3.5) |
Female | 54.5 (47.1 to 62.6) | −18.7% (−21.6 to −15.9) | 2.6 (2.4 to 2.8) | −37.5% (−40.8 to −30.9) | 4.6 (3.1 to 6.3) | −18.1% (−21.1 to −15.1) | 55.7 (49.4 to 60.8) | −31.1% (−36.0 to −23.2) |
Low SDI | 48.6 (40.5 to 57.6) | 4.9% (2.2 to 7.5) | 3.0 (2.3 to 4.0) | −4.0% (−16.0 to 13.8) | 4.1 (2.7 to 5.8) | 5.6% (1.6 to 9.6) | 80.2 (61.5 to 105.9) | −15.5% (−28.0 to 0.6) |
Low-middle SDI | 42.1 (35.5 to 49.5) | 7.6% (4.8 to 10.1) | 3.0 (2.6 to 3.4) | 4.0% (−10.6 to 23.0) | 3.5 (2.4 to 5.0) | 8.2% (4.4 to 11.9) | 76.3 (67.9 to 86.7) | −4.8% (−17.6 to 10.7) |
Middle SDI | 32.2 (27.5 to 37.4) | 15.6% (13.8 to 17.6) | 2.1 (1.8 to 2.2) | 10.7% (0.9 to 25.5) | 2.7 (1.9 to 3.8) | 16.0% (13.7 to 18.5) | 50.6 (44.7 to 54.6) | −2.9% (−13.3 to 7.9) |
High-middle SDI | 38.3 (33.0 to 44.3) | −3.6% (−6.2 to −0.8) | 3.7 (3.1 to 3.9) | 7.1% (−4.9 to 15.7) | 3.2 (2.2 to 4.5) | −2.5% (−5.7 to 0.7) | 88.0 (72.1 to 93.7) | 17.4% (−3.5 to 30.0) |
High SDI | 97.8 (85.8 to 111.0) | −18.6% (−22.4 to −14.3) | 3.2 (3.0 to 3.4) | −51.0% (−55.0 to −33.2) | 8.2 (5.6 to 11.2) | −18.5% (−22.3 to −14.0) | 64.1 (61.2 to 74.7) | −45.2% (−49.5 to −26.4) |
Age-specific numbers and rates of prevalent cases and deaths for myocarditis and alcoholic cardiomyopathy by sex, 2017.
The prevalence of MC, AC, and OC in 2017 varied widely across geographic locations (
Age-standardized prevalence rates of myocarditis
In 2017, the global numbers of deaths attributable to MC, AC, and OC were 46,486 (95% UI 39,709–51,824), 88,890 (95% UI 80,935–96,290) and 233,159 (95% UI 213,677–248,289), respectively. The age-standardized death rates of MC, AC, and OC per 100,000 people in 2017 were 0.6 (95% UI 0.5–0.7), 1.1 (95% UI 1.0–1.2), and 3.1 (95% UI 2.8–3.3), respectively (
Across 21 world regions, Oceania had the highest age-standardized death rates of MC [2.6 (95% UI 2.0–3.4) per 100,000 people], whereas the highest age-standardized death rates of AC and OC were seen in Eastern Europe [17.2 (95% UI 16.2–19.1) per 100,000 people] and Central Europe [10.4 (95% UI 9.6–11.0) per 100,000 people], respectively (
Age-standardized death rates of myocarditis, alcoholic cardiomyopathy, and other cardiomyopathy for 21 world regions, both sexes, 2017.
Moreover, globally, there were 131,376 (95% UI 90,113–183,001) YLDs and 1.26 million (95% UI 1.10–1.42) YLLs attributable to MC, 139,087 (95% UI 95,134–196,130) YLDs and 2.84 million (95% UI 2.60–3.07) YLLs attributable to AC, and 353,325 (95% UI 237,907–493,908) YLDs and 5.51 million (95% UI 4.95–5.99) YLLs attributable to OC in 2017. As shown in
Between 1990 and 2017, the age-standardized prevalence rates of MC, AC and OC decreased by −6.9% (95% UI −7.8 to −5.9), −26.2% (95% UI −28.2 to −24.0), and −15.5% (95% UI −18.4 to −12.7), respectively, with greater decreases in females than males for all the diseases (
Similarly, the global numbers of deaths attributable to MC, AC and OC have increased by 71.4% (95% UI 54.9–90.5), 59.6% (95% UI 33.9–76.3), and 49.7% (95% UI 39.5–73.4), respectively from 1990 to 2017, despite the decreases in age-standardized death rates (
Temporal trends in age-standardized death rates of myocarditis
In this study, we utilized the GBD 2017 modeling framework to estimate the global burden generated by MC, AC, and OC, stratifying findings by age, sex, year (1990–2017), SDI, and geographic location. Most recently, a modeling study has estimated the death rate of AC in 2015 at the global, regional, and national levels, but without examining the prevalence, YLDs, and YLLs or exploring temporal trends of the burden over time (
As expected, the age-standardized prevalence and death rates of AC were found to be significantly higher in males than females, and the burden of AC mainly concentered in adults aged 40–70 years (
The burden of MC in 2017 varied significantly across geographic locations. Regionally, High-income Asia Pacific had the highest age-standardized prevalence rate of MC, which is probably because of the infection caused by hepatitis C virus (HCV) (
In addition, large geographic differences in the burden of AC and OC were also observed in the present study. The highest age-standardized prevalence rates of AC in Eastern Europe may be explained taking into account the high level of alcohol consumption, in terms of drinking pattern, frequency, quality and type of alcoholic beverage (
Concerning the temporal trends of burden from 1990 to 2017, the global numbers of prevalent cases and deaths for MC, AC, and OC have significant increased, contrasting with the decreases in age-standardized prevalence and death rates. The exact causes for the trends are unknown but may be in part due to population growth and aging (
As YLDs were calculated on the basis of prevalence (in number of cases), the patterns of YLDs by SDI and geographic location for MC, AC, and OC were similar to prevalence. The same relationship existed between YLLs and deaths. Globally, although the absolute numbers of YLDs were lower than YLLs for MC, the reductions in age-standardized YLD rates (−7.2%) during 1990–2017 have been much smaller than age-standardized YLL rates (−23.5%), suggesting that future MC treatment strategies should pay more attention to improve the quality of life of MC patients. Conversely, for males, the age-standardized YLD rates of AC have decreased by −25.7% during 1990–2017, while there was no significant change in age-standardized YLL rates of AC in the same timeframe, suggesting that future AC treatment strategies should still pay more attention to reduce the mortality of male patients with AC. However, for females, there was no difference between age-standardized YLD and YLL rates of AC.
Even though the GBD estimations fill a gap where data on the burden imposed by MC, OC, and AC are scarce or inaccessible, several limitations still exist and should be properly acknowledged. The first limitation is the low availability of data in some countries, although statistically robust approaches have been applied in order to overcome data scarcity and deal with uncertainty. In those countries for which data was missing or was deemed inaccurate and of low quality, results mainly relied on covariates known to be associated with these diseases, trends in neighboring countries, or a combination of both methods. Besides, differences in data collection and data sources quality across countries, delay and inaccuracy in reporting, misclassification and bias in coding, are unavoidable in this study, even though the GBD has attempted to enhance the reliability and comparability of related data. Moreover, diagnostic criteria may have changed over time and may reflect different regional use of coding. Various nomenclatures, classification schemes, and nosological taxonomies, indeed, exist, some of them being even confusing and contrasting, and have been differently employed in the literature (
In summary, MC, AC and OC remain important global public health problems; however, large national and regional variations in the burden were seen for all these diseases. Public health policy- and decision-makers should devise and implement more effective and geo-specific strategies aimed at counteracting and mitigating the future burden of these diseases. Further research is also warranted to expand our knowledge of potential risk factors associated with MC, AC, and OC and to improve the prevention, early detection and treatment of these diseases.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/
The studies involving human participants were reviewed and approved by University of Washington Institutional Review Board. Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.
HD involved in data collection, study design, statistical analysis, manuscript preparation, and supervision. DL and AM involved in study design, data interpretation, and manuscript review. AY involved in data interpretation and manuscript review. YL and NB involved in study design, statistical analysis, manuscript preparation, manuscript review, and supervision. JW involved in manuscript review and supervision. All authors have read and approved the final manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors would like to thank all members of the Institute for Health Metrics and Evaluation (IHME), and all collaborators involved in GBD 2017 study. This manuscript has been released as a pre-print at MedRxiv (
The Supplementary Material for this article can be found online at: