Burden, Trends, Risk Factors, and Forecast of Ischemic Heart Disease, Rheumatic Heart Disease, and Atrial Fibrillation and Flutter From 1990 to 2040: A Comparative Analysis of China, the United States, and Europe Based on the Global Burden of Disease Study and the Potential Impact of the COVID-19 Pandemic

Abstract

Background

Understanding the global burden of cardiovascular diseases is essential for developing effective preventive strategies and guiding policy measures worldwide. Despite significant advances in diagnosis and treatment, cardiovascular diseases remain the leading cause of morbidity and mortality across all regions. Assessing their temporal trends and regional disparities can provide valuable insights for optimizing resource allocation and improving global health outcomes.

Methods

We used data from the Global Burden of Disease 2021 (GBD 2021) to analyze the incidence, prevalence, deaths, Years Lived with Disability (YLDs), Years of Life Lost (YLLs), and Disability-Adjusted Life Years (DALYs) of three major cardiovascular diseases—Atrial Fibrillation and Flutter (AFF), Ischemic Heart Disease (IHD), and Rheumatic Heart Disease (RHD)—globally and in the People’s Republic of China, Europe, and the United States of America (USA). Comparative analyses and projections were performed through 2040.

Results

Globally, age-standardized incidence rates (ASIRs, per 100,000 population) from 1990 to 2021 slightly declined for AFF (52.51 to 52.12) and IHD (419.54 to 372.9) but increased for RHD (44.87 to 50.74). In China and the USA, AFF incidence rose (42.63 to 44.92 and 75.22 to 89.18, respectively), and IHD incidence in China increased (315.31 to 365.67). RHD incidence declined across all three regions. Notably, AFF and IHD trends increased after 2019, potentially related to COVID-19.

Conclusion

This study reveals distinct global and regional trends in the burden of AFF, IHD, and RHD from 1990 to 2021. The burden of AFF and IHD declined in most regions but showed a potential increase during the COVID-19 pandemic, while RHD continued to rise, particularly in low-SDI (Sociodemographic Index) countries. These findings provide valuable evidence to guide targeted prevention strategies and optimize resource allocation in global cardiovascular health policy.

Introduction

Cardiovascular diseases, characterized by high incidence, chronic progression, and limited curative options, have become a major global health burden. They are not only associated with elevated mortality rates but also contribute significantly to economic costs worldwide.^1–3

IHD imposes a substantial burden on global health. As a collective term encompassing various heart conditions encompassing conditions such as angina pectoris, myocardial infarction, ischemic cardiomyopathy, and related ischemic syndromes,^4–6 it represents the classical form of cardiovascular disease and is primarily caused by coronary atherosclerosis endemic.^7,8 RHD is a poverty-related condition that has become rare in high-income countries but continues to impose a significant burden on low- and middle-income regions.^9–11 Effective control of RHD relies on the early detection and treatment of Group A β-hemolytic Streptococcus infections.^12,13 AFF are the most common types of cardiac arrhythmia, with incidence rates increasing significantly with advancing age. Although effective treatment options are available, the associated healthcare costs remain substantial.^14,15 These three diseases differ in their etiologies and clinical characteristics, each representing a distinct category within the spectrum of cardiovascular conditions. Accordingly, we chose these three representative cardiovascular diseases to assess their distinct epidemiological profiles across different global regions.¹⁶

The GBD 2021 provides comprehensive estimates of incidence, prevalence, deaths, YLDs, YLLs, DALYs, both as absolute counts and age-standardized rates.¹⁷ These estimates cover seven super-regions, 21 regions, 204 countries and territories (including 21 subnational locations), and 811 subnational units worldwide. DALYs are calculated as the sum of YLDs and YLLs. The dataset includes estimates across 25 age groups and disaggregates results by sex. In addition, all indicators are stratified by the Sociodemographic Index (SDI), a composite metric that reflects a location’s level of development, based on measures of per capita income, average educational attainment among individuals aged 15 years or older, and total fertility rate in females under the age of 25.^18–20

Previous analyses of cardiovascular diseases based on the Global Burden of Disease Study 2019 (GBD 2019) have been conducted.²¹ This study revealed that the burden of different types of cardiovascular diseases varies globally by age, sex, and SDI, with higher burdens observed in low-SDI countries and a continued increase in diseases such as RHD. Using GBD 2021 data, we further analyzed these patterns. However, the emergence of the COVID-19 pandemic in 2020 had a profound impact on the epidemiology of diseases worldwide.^22–24 This disruption underscores the need for updated assessments to capture changes before and after the pandemic. In this study, we extracted and analyzed data from 1990 to 2021 to evaluate these temporal trends. Understanding the global epidemiological impact of cardiovascular diseases is essential for addressing the worldwide burden and for gaining insights into national trends. Given their global significance in terms of economy, population size, and geopolitical influence, China, USA, and Europe were selected as representative regions for detailed comparative analysis in this study. The GBD database collects information on global disease trends and regional burdens, enabling a comprehensive understanding of the variations in disease burden across different regions. This provides valuable references for the formulation of future public health policies.

Methods

Estimation Framework of the Disease Burden of Cardiovascular Diseases Across All Ages and Age-Standardized Metrics in 204 Countries and Territories in GBD 2021

We visualized the global distribution of six major burden indicators for all ages and both sexes across 204 countries and territories. To improve regional clarity, five key areas were enlarged: the Caribbean and Central America, the Persian Gulf, the Balkans, Southeast Asia, and West Africa.

To show temporal trends from 1990 to 2021, we mapped both age-standardized and all-age percentage changes by country, illustrating global patterns in disease burden over time.

Frontier Analysis by Sociodemographic Index (SDI)

The primary goal of frontier analysis is to evaluate how disease burden relates to sociodemographic development using SDI, helping identify the potential for burden reduction across countries.

Decomposition Analysis

We extracted disease burden indicators for the five SDI regions as well as for the global population. A decomposition analysis was applied to partition each burden indicator into its component contributors, allowing for the identification and quantification of the relative contributions of various factors to the observed changes in disease burden over time.

Age-Group Distribution Analysis of Cardiovascular Diseases Prevalence

To explore age-specific patterns of ischemic heart disease (IHD), we extracted prevalence data by age group for 1990 and 2021 across 21 GBD regions, five SDI categories (low, low-middle, middle, high-middle, and high), and the global level. We visualized the proportional distribution of prevalence, incidence, deaths, YLDs, YLLs, and DALYs within each age group using stacked bar charts.

Proportional Contribution of Cardiovascular Diseases Across Regions

To assess CVD mortality composition, we calculated the 2021 percentage contribution of three major CVDs across regions including Europe, China, the USA, five SDI levels, and globally. Stacked bar charts were used to show regional differences across six indicators.

Temporal Trends in Cardiovascular Disease Burden by Indicator

To illustrate global trends from 1990 to 2021, we generated stacked bar charts for six indicators stratified by condition. All values were presented as age-standardized rates per 100,000 population.

Age-Specific Patterns of Cardiovascular Disease by SDI and Sex

We plotted prevalence, incidence, and DALYs of Cardiovascular Disease across 5-year age groups (<5 to 95+) for both sexes and SDI levels, as well as the global average.

Population Structure and Temporal Trends of Cardiovascular Disease by Sex

To compare demographic patterns and trends of CVDs, we plotted age-sex pyramids and age-specific burden curves, along with time series of prevalence, incidence, and DALYs (1990–2021) for China, Europe, and the USA. Each disease was shown separately by sex and year, with shaded areas indicating 95% UIs.

BAPC-Based Projection of Cardiovascular Disease Burden in China, USA, and Europe

To estimate long-term trends and future projections of CVD burden, we applied the Bayesian age-period-cohort (BAPC)²⁵ model to CVDs in China, USA, and Europe. We modeled both the absolute number of age-standardized cases and the corresponding ASR from 1990 through 2040. The projections incorporate uncertainty intervals and are visualized to reflect temporal shifts and anticipated burden trajectories.^26,27

Joint Trend Analysis of Cardiovascular Disease in China, USA, and Europe

A joint time-series analysis was conducted to assess trends in six key indicators across China, USA, and Europe from 1990 to 2021. All indicators were plotted simultaneously using color-coded lines for each disease within each location, enabling integrated comparisons of burden dynamics and shifts across both disease types and metrics.^28,29

Assessment of Risk Factors Attributable to Cardiovascular Disease

To assess the impact of modifiable risk factors on CVD burden, we used GBD 2021 data, focusing on IHD and AFF, as RHD lacks risk factor estimates. Risk factors were grouped into behavioral, environmental, and metabolic categories. We have also specifically extracted the risk factors influencing the incidence and mortality rates of cardiovascular diseases in China, Europe, and the United States, categorizing them into behavioral, environmental, and metabolic factors.

Analytical Methods

All figures and tables in this study were generated using R software (version 4.4.0). Data from the GBD 2021 (https://vizhub.healthdata.org/gbd-results/). Figure S1 shows overall analytical framework of the study.

Result

Estimation Framework of the Disease Burden

Atrial Fibrillation and Flutter

As shown in Figure S2, the global distribution of the crude incidence rate (CIR) of AFF in 2021 (Figure S2A) exhibited marked regional differences, with the highest rates observed in North America, Northern and Western Europe, and Australia. Figure S2B illustrates the relative change in CIR from 1990 to 2021, revealing sharp increases in many low- and middle-income countries, such as China and Southeast Asia, whereas several high-income countries showed relatively stable or declining trends. Figure S2C displays the estimated annual percentage change (EAPC) of age-standardized CIR, where positive trends were seen mainly in Northern Europe and East Asia, while negative or minimal changes were more prevalent in Western countries, suggesting regional disparities in the temporal dynamics of AFF burden. Figure S2J shows that AFF-related deaths were most concentrated in high-income regions such as North America, Europe, and Australia. Figure S2K presents the percentage change in AFF deaths from 1990 to 2021, highlighting substantial increases in Africa and parts of Asia. Figure S2L displays the EAPC of age-standardized death rates, revealing upward trends in Southeast Asia, South Asia, and parts of Eastern Europe, while Western countries experienced stable or declining trends. In 2021 (Figure S2G), high DALY burdens were observed in Europe, North America, and Australia. From 1990 to 2021 (Figure S2H), DALYs increased significantly in many low-income countries, especially in Africa. Panel I shows that the age-standardized DALY rates rose in most regions, particularly in Southeast Asia and parts of Africa.

Ischemic Heart Disease

Figure S3 depicts the global distribution and trends of CIR for IHD. In 2021 (Figure S3A), higher CIRs were concentrated in Eastern Europe, Central Asia, and parts of the Middle East. P Figure S2B shows that from 1990 to 2021, many high-income countries experienced a decline in CIRs, while increases were observed in China and several African nations. Figure S2C presents the EAPC, with significant rises seen across most of Asia and Africa, in contrast to decreases in North America and parts of Europe. In 2021 (Figure S3J), the highest numbers of deaths were observed in Eastern Europe, Russia, and parts of Central Asia. Figure S3K shows the change in deaths from 1990 to 2021, highlighting sharp increases in China and some Asian countries, while many high-income and African countries experienced decreases. Figure S3L displays the EAPC, indicating that age-standardized death rates declined in most high-income regions but increased in South and Southeast Asia, parts of Africa, and Eastern Europe. In 2021 (Figure S3G), Eastern Europe, Russia, and Central Asia exhibited the highest DALY numbers. Figure S3H illustrates the percentage change in DALYs from 1990 to 2021, with substantial increases in countries such as China, while many high-income regions and sub-Saharan Africa showed declines. Figure S3I presents the EAPC of age-standardized DALYs, revealing upward trends in most low- and middle-income countries and downward trends in high-income countries like Australia and parts of Europe.

Rheumatic Heart Disease

In Figure S4A shows the highest CIR in sub-Saharan Africa and Oceania. Figure S4B highlights major declines in incidence from 1990 to 2021, especially in Europe and East Asia. Figure S4C shows rising EAPC in many low- and middle-income countries, notably in Africa and South Asia. Figure S4J–L indicate falling death numbers and rates globally over the past 30 years, but high mortality persists in South Asia and sub-Saharan Africa, with India and parts of Central/Eastern Africa still showing high and rising death burdens. Figure S4G–I reveal DALYs remain highest in South Asia and sub-Saharan Africa. Despite improvements in high-income countries, low- and middle-income nations—especially India, China, and parts of Africa—continue to face high burdens and slow progress.

Proportional Contribution Across Regions

As shown in Figure 1A–F, we visualized the regional distribution of cardiovascular disease burden across different SDI regions and countries in terms of six key GBD metrics. For deaths (Figure 1A), YLLs (Figure 1B) and YLDs (Figure 1C), ischemic heart disease overwhelmingly dominated across all regions and SDI levels, accounting for the majority of cardiovascular mortality. DALYs (Figure 1D), IHD remain the primary contributor in most regions. When examining incidence (Figure 1E) and prevalence (Figure 1F), AFF and RHD played more visible roles. IHD leading in fatal outcomes and AFF contributing more prominently to chronic morbidity, particularly in high-SDI regions.

Figure 1.

Global burden and temporal trends of cardiovascular diseases (CVDs) from 1990 to 2021. (A–F) show the global distribution of deaths (A), YLLs (B), YLDs (C), DALYs (D), incidence (E), and prevalence (F) of CVDs by cause in 2021. (G–L) illustrate the trends over time (1990–2021) for the same six indicators: deaths (G), YLLs (H), YLDs (I), DALYs (J), incidence (K), and prevalence (L). (M–O) present age-specific incidence, prevalence, and DALYs of atrial fibrillation and flutter (AFF, (M)), ischemic heart disease (IHD, (N)), and rheumatic heart disease (RHD, (O)), stratified by sex and SDI level in 2021. (P–R) display frontier analysis of age-standardized DALYs for AFF (P), IHD (Q), and RHD (R) across 204 countries from 1990 to 2021, with SDI on the x-axis and DALYs on the y-axis. Dots are colored by increasing or decreasing trend.

Temporal Trends Burden

We summarize age-standardized trends for deaths (Figure 1G), YLLs (Figure 1H), YLDs (Figure 1I), and DALYs (Figure 1J), incidence (Figure 1K), prevalence (Figure 1L), over 1990–2021. Incidence and prevalence stayed largely flat, with a slight rise for AFF. Age-standardized deaths and YLLs fell steadily—mainly reflecting better IHD management—while YLDs changed little, indicating limited progress in disability reduction. Consequently, DALYs declined chiefly because of lower mortality. Throughout the period IHD carried the greatest share of CVD burden, whereas AFF’s share rose gradually.

Age-Specific Patterns by SDI and Sex

Across all three CVDs, burden increased with age. For AFF (Figure 1M), rates rose after age 50, peaking in the elderly, especially in high and high-middle SDI regions for both sexes. IHD (Figure 1N) showed a stronger age-related increase, with males carrying a consistently higher burden. RHD (Figure 1O) peaked in adolescence and early adulthood in low-SDI regions, then declined with age—reflecting early exposure and limited care. A small rise in elderly RHD burden was also noted in high-SDI regions, possibly due to long-term effects or better diagnosis.

Frontier Analysis

Figure 1P–R show the relationship between age-standardized DALY rates and SDI from 1990 to 2021. For AFF (Figure 1P), high-SDI countries had rising DALY trends, while low-SDI countries were stable or declined, indicating a shift toward developed regions. For IHD (Figure 1Q), DALY rates increased in high-SDI countries but declined in some middle-SDI countries. For RHD (Figure 1R), DALY rates remained high in low-SDI countries.

Decomposition Analysis

Atrial Fibrillation and Flutter

We analyzed the decomposition of incidence (Figure 2A), prevalence (Figure 2B), death (Figure 2C), YLLs (Figure 2D), YLDs (Figure 2E) and DALYs (Figure 2F) for AFF across different SDI regions, highlighting the relative contributions of population growth, changes in age structure, and age-specific rate variation. As shown in Figure 2, the increase in incidence was primarily driven by population growth, particularly in high and high-middle SDI regions. The variation in mortality was mainly attributable to changes in age structure, especially in high and middle SDI regions. Both population growth and age structures played dominant roles in shaping the overall burden of AFF across all SDI levels.

Figure 2.

Decomposition of changes in cardiovascular disease burden from 1990 to 2021 by component (population growth, population aging, and epidemiological change) across SDI regions and globally. (A–F) Atrial fibrillation and flutter: (A) Decomposition of incidence changes. (B) Decomposition of prevalence changes. (C) Decomposition of death changes. (D) Decomposition of YLLs (Years of Life Lost) changes. (E) Decomposition of YLDs (Years Lived with Disability) changes. (F) Decomposition of DALYs (Disability-Adjusted Life Years) changes. (G–L) Ischemic heart disease: (G) Decomposition of incidence changes. (H) Decomposition of prevalence changes. (I) Decomposition of death changes. (J) Decomposition of YLLs changes. (K) Decomposition of YLDs changes. (L) Decomposition of DALYs changes. (M–R) Rheumatic heart disease: (M) Decomposition of incidence changes. (N) Decomposition of prevalence changes. (O) Decomposition of death changes. (P) Decomposition of YLLs changes. (Q) Decomposition of YLDs changes. (R) Decomposition of DALYs changes.

Ischemic Heart Disease

We analyzed the decomposition of incidence (Figure 2G), prevalence (Figure 2H), death (Figure 2I), YLLs (Figure 2J), YLDs (Figure 2K) and DALYs (Figure 2L) for IHD. The increase in incidence was primarily attributable to changes in age structure and population growth. The overall decline in deaths was closely associated with reductions in age-specific mortality rates, particularly in high and high-middle SDI regions, reflecting substantial improvements in cardiovascular care. The overall change in DALYs was driven by a combination of decreasing age-specific mortality and the growing demographic burden caused by population aging and growth. Globally, the burden of IHD has been partially alleviated by declining age-specific rates yet the demographic pressure, particularly aging, continues to elevate the total burden in many regions.

Rheumatic Heart Disease

We analyzed the decomposition of incidence (Figure 2M), prevalence (Figure 2N), death (Figure 2O), YLLs (Figure 2P), YLDs (Figure 2Q) and DALYs (Figure 2R) for RHD. The increase in incidence was mainly driven by population growth, particularly in low- and low-middle SDI regions, while age-specific rates slightly decreased in high SDI areas. Remarkably, age-specific mortality rates showed a notable decline across all SDI levels, especially in high and middle SDI regions, which contributed significantly to the reduction in deaths. In summary, while improvements in age-specific mortality have mitigated the burden of RHD to some extent—especially in higher SDI areas—ongoing population growth and aging remain dominant forces driving the overall disease burden in low- and middle-SDI regions.

Age-Group Distribution Analysis

Rheumatic Heart Disease

From 1990 to 2021, a notable shift in the incidence (Figure 3A) and prevalence (Figure 3B) of RHD was observed toward older age groups in most regions, particularly in high and high-middle SDI areas, indicating an aging trend in disease onset and diagnosis. In contrast, deaths (Figure 3C), YLLs (Figure 3D), YLDs (Figure 3E) and DALYs (Figure 3F) remained heavily concentrated in younger populations in low-SDI and some sub-Saharan regions, reflecting persistent early mortality in settings with limited healthcare access. However, high-SDI regions showed a more evenly distributed mortality pattern across age groups.

Figure 3.

Age distribution of cardiovascular disease burden by location in 1990 and 2021. (A–F) Age distribution of the burden of rheumatic heart disease by location and year. (A) Incidence; (B) Prevalence; (C) Deaths; (D) YLLs; (E) YLDs; (F) DALYs. (G–L) Age distribution of the burden of ischemic heart disease by location and year. (G) Incidence; (H) Prevalence; (I) Deaths; (J) YLLs; (K) YLDs; (L) DALYs. (M–R) Age distribution of the burden of atrial fibrillation and flutter by location and year. (M) Incidence; (N) Prevalence; (O) Deaths; (P) YLLs; (Q) YLDs; (R) DALYs.

Ischemic Heart Disease

From 1990 to 2021, a gradual shift in the incidence (Figure 3G) and prevalence (Figure 3H) of IHD toward older age groups was evident across most global regions, with the most pronounced changes occurring in high and high-middle SDI areas. In contrast, deaths (Figure 3I), YLLs (Figure 3J), YLDs (Figure 3K) and DALYs (Figure 3L) were also predominantly concentrated in older populations but showed a marked intensification in the 70+ years age group by 2021, suggesting continued vulnerability in elderly demographics.

Atrial Fibrillation and Flutter

From 1990 to 2021, the incidence (Figure 3M) and prevalence (Figure 3N) of AFF exhibited a marked shift toward older age groups in nearly all regions, most notably in high and high-middle SDI settings. Deaths (Figure 3O) and YLLs (Figure 3P), YLDs (Figure 3Q) and DALYs (Figure 3R) remained predominantly concentrated in the elderly population, particularly those aged 70 years and above, with this trend intensifying over time.

Population Structure and Temporal Trends

Atrial Fibrillation and Flutter

Figure S5 present the age-specific and temporal burden of AFF in China (Figure S5A and B), Europe (Figure S5C and D), and USA (Figure S5E and F). Across all regions, the number of incident and prevalent cases in 2021 increased sharply with age, with a greater burden observed among males. From 1990 to 2019, China and USA experienced substantial growth in both crude incidence and prevalence, primarily driven by population aging and growth, whereas the age-standardized rates showed only modest changes. In contrast, Europe demonstrated a relatively stable burden, with minimal fluctuations in both absolute numbers and age-standardized rates.

Ischemic Heart Disease

We further examined the burden of IHD in Figure S6 in China (Figure S6A and B), Europe (Figure S6C and D), and the USA (Figure S6E and F). The incidence and prevalence of IHD were predominantly concentrated in older adults, particularly males. From 1990 to 2019, China and USA exhibited marked increases in the absolute number of cases, while the age-standardized incidence and prevalence rates remained relatively stable In Europe, a gradual decline in age-standardized incidence was observed, whereas prevalence trends showed minimal change over time.

Rheumatic Heart Disease

The burden of RHD in Figure S7 in China (Figure S7A and B), Europe (Figure S7C and D), and USA (Figure S7E and F) showed distinct age and temporal patterns. Unlike AFF and IHD, the peak incidence and prevalence of RHD occurred in adolescence and early adulthood, particularly in low- and middle-income populations. In 2021, the burden remained disproportionately higher among females across all three regions. From 1990 to 2019, the age-standardized rates of RHD steadily declined in both Europe and USA, while China experienced a slower but consistent decrease. Despite overall reductions in standardized rates, the absolute number of cases remained relatively stable in China due to population growth and aging.

BAPC-Based Projection

BAPC projections (Figure 4) showed distinct future trends across China (Figure 4A, D, G), the USA (Figure 4B, E, H) and Europe (Figure 4C, F, I).

Figure 4.

BAPC modeling projections of atrial fibrillation and flutter, ischemic heart disease, and rheumatic heart disease in China, the United States, and Europe from 1990 to 2040. (A–C) Projected number of age-standardized cases and age-standardized rates per 100,000 population for atrial fibrillation and flutter. (A) China; (B) United States of America; (C) Europe. (D–F) Projections for ischemic heart disease in the same regions. (D) China; (E) United States of America; (F) Europe. (G–I) Projections for rheumatic heart disease. (G) China; (H) United States of America; (I) Europe.

For AFF, age-standardized incidence is projected to stay stable in China, but total cases will rise in all regions, especially in China and the USA, with a widening male–female gap.

IHD incidence is expected to decline across all regions, most notably in Europe; however, China may see a modest rise in case numbers, while the USA and Europe remain stable.

For RHD, both standardized rates and total cases are projected to decline in Europe and the USA, whereas China may experience an increase in case numbers despite stable rates.

Joint Trend Analysis of Cardiovascular Disease

Atrial Fibrillation and Flutter

Figure 5A–F illustrates the jointpoint trend analysis of deaths (Figure 5A), YLLs (Figure 5B), YLDs (Figure 5C), and DALYs (Figure 5D), incidence (Figure 5E), prevalence (Figure 5F) related to AFF from 1990 to 2021. The age-standardized mortality rate of AFF in Europe demonstrated an overall increasing trend throughout the period, while the USA also experienced a slight upward trajectory in mortality. Regarding incidence, a marked increase was observed in the USA after 2005. In terms of prevalence, the United States consistently exhibited the highest rates among the three regions, with a sustained upward trend over time.

Figure 5.

Joint analysis of age-standardized burden trends and temporal inflection points for atrial fibrillation and flutter (AFF), ischemic heart disease (IHD), and rheumatic heart disease (RHD) from 1990 to 2021 across China, the United States, and Europe. A–F: Trends in age-standardized mortality (A), YLLs (B), YLDs (C), DALYs (D), incidence (E), and prevalence (F) for atrial fibrillation and flutter from 1990 to 2021. (G–L) Temporal trends of ischemic heart disease burden, including age-standardized mortality (G), YLLs (H), YLDs (I), DALYs (J), incidence (K), and prevalence (L) in the three regions. (M–R) Trends for rheumatic heart disease, presenting age-standard mortality (M), YLLs (N), YLDs (O), DALYs (P), incidence (Q), and prevalence (R). * Indicates p < 0.05.

Ischemic Heart Disease

Figure 5G–L presents Joinpoint regression analyses deaths (Figure 5G), YLLs (Figure 5H), YLDs (Figure 5I), and DALYs (Figure 5J), incidence (Figure 5K), prevalence (Figure 5L) for IHD from 1990 to 2021. For mortality, Europe exhibited a steady decline since 1994, while China experienced a moderate upward trend with a notable increase from 2001 to 2004. In the United States, mortality also declined overall, particularly after 2003. For incidence, the US had the sharpest decline, followed by Europe, whereas China showed a rising trend, especially between 2000 and 2015. Lastly, prevalence significantly increased in China, remained relatively stable in Europe, and showed a modest upward trend in the US, indicating a growing disease burden.

Rheumatic Heart Disease

Figure 5M–R presents Joinpoint regression analyses deaths (Figure 5M), YLLs (Figure 5N), YLDs (Figure 5O), and DALYs (Figure 5P), incidence (Figure 5Q), prevalence (Figure 5R) for RHD from 1990 to 2021. For mortality and YLLs, a substantial and consistent decline was observed in China, with average annual percent changes, respectively. In contrast, Europe exhibited more modest decreases, while the USA had the smallest reduction. In terms of incidence, a declining trend was noted in Europe and China, whereas in the USA the incidence rate remained relatively stable overall, with a recent increasing trend after 2015.

Assessment of Risk Factors Attributable

Atrial Fibrillation and Flutter

Figure 6A–D presents the proportion of disease burden attributable to modifiable risk factors for AFF in 2021.

Figure 6.

Regional patterns of risk factors attribute to atrial fibrillation and flutter burden in 2021. (A) Deaths attributable to major modifiable risk factors, including metabolic risks (high systolic blood pressure, high body-mass index), behavioral risks (dietary risks, alcohol use, tobacco), and environmental/occupational risks (lead exposure, ambient particulate matter pollution) across global regions. (B) YLLs due to AFF attributable to the same set of risk factors across regions. (C) YLDs due to AFF are attributable to risk factors. (D) DALYs attributable to risk factors for AFF.

Ischemic Heart Disease

Figure 7A–D presents the proportion of disease burden attributable to modifiable risk factors for IHD in 2021.

Figure 7.

Regional patterns of risk factors attributable to ischemic heart disease burden in 2021. (A) Deaths attributable to modifiable risk factors. (B) YLLs attributable to modifiable risk factors. (C) YLDs attributable to modifiable risk factors. (D) DALYs attributable to modifiable risk factors.

Overall Trend

Globally, ASIR of AFF showed a slight decline, from 52.51 per 100,000 in 1990 to 52.12 per 100,000 in 2021. The incidence rates were comparable between males and females; however, countries with high SDI levels exhibited markedly higher ASIRs than those with low and middle SDI levels. Regionally, China experienced a slight increase in incidence (ASIR increased from 42.63 to 44.92), whereas the United States showed a more pronounced rise (from 75.22 to 89.18), and Europe demonstrated a modest decline (from 59.88 to 59.26) (Table 1). For deaths and DALYs, age-standardized rates declined in China, but increased in both the United States and Europe, with the United States experiencing the most substantial growth (Table 2).

Table 1.

Global Trends and China, USA and Europe in the Incidence and Age-Standardized Rates of Heart Diseases From 1990 to 2021

			1990		2021	1990-2021
Disease	Category	Incident cases *102 (95% UI)	ASIR per 100,000 (95% UI)	Incident cases *102 (95% UI)	ASIR per 100,000 (95% UI)	EAPC (95% CI)
Atrial fibrillation and flutter	Overall	20065.71 [15549.71–26403.79]	52.51 [40.39–69.01]	44849.26 [36106.2–57060.19]	52.12 [41.85–66.23]	−0.07 [−0.1 to −0.04]
	Sex
	Female	9912.84 [7542.61–13185.01]	47.43 [35.96–62.83]	21891.16 [17231.1–28216.48]	47.26 [37.38–60.87]	−0.14 [−0.19 to −0.09]
	Male	10152.87 [7868.76–13194.75]	58 [44.89–75.8]	22958.11 [18536.79–28994.36]	57.11 [46.19–72.14]	−0.01 [−0.04 to 0.02]
	Socio-demographic index
	High SDI	7229.78 [5538.15–9439.82]	64.54 [50.18–83.44]	13347.3 [11393.77–15726.38]	65.1 [56.11–76.05]	−0.07 [−0.13 to −0.02]
	High-middle SDI	4763.4 [3652.94–6285.45]	48.86 [37.88–63.69]	9341.74 [7404.17–11989.77]	47.16 [37.67–60.25]	−0.17 [−0.22 to −0.12]
	Middle SDI	4540.2 [3519.91–5968.01]	48.88 [37.12–64.96]	13303.76 [10316.39–17522.11]	51.11 [39.2–67.85]	0.13 [0.1 to 0.16]
	Low-middle SDI	2680.77 [2067.34–3547.28]	49.52 [37.34–65.82]	6828.85 [5230.53–9120.36]	50.99 [38.44–67.86]	0.1 [0.09 to 0.1]
	Low SDI	827.42 [633.53–1096.75]	41.74 [31.59–55.83]	1984.94 [1532.4–2619.39]	43.25 [32.7–57.75]	0.12 [0.11 to 0.14]
	Region
	China	3065.85 [2342.43–4048.68]	42.63 [32.4–56.46]	9161.8 [7073.84–12013.81]	44.92 [34.96–59.42]	0.16 [0.07 to 0.25]
	Europe	6284.6 [4820.9–8201.71]	59.88 [46.4–77.32]	9210.25 [7438.12–11341.37]	59.26 [48.17–72.45]	−0.15 [−0.19 to −0.11]
	United States of America	2450.56 [1806.93–3250.21]	75.22 [57.39–99.34]	5282.08 [4871.91–5747.43]	89.18 [82.53–96.66]	0.54 [0.48 to 0.61]
Ischemic heart disease	Overall	158136.19 [131805.29–188494.79]	419.54 [351.07–498.15]	318727.78 [262849.21–382678.34]	372.9 [307.95–444.19]	−0.44 [−0.47 to −0.41]
	Sex
	Female	67429.85 [55918.21–80763.77]	329.74 [273.29–392.76]	139111.48 [114469.46–166785.74]	301.57 [248.57–360.73]	−0.42 [−0.47 to −0.37]
	Male	90706.33 [75343.43–108891.7]	522.16 [436.31–617.87]	179616.3 [148608.52–215215.48]	450.39 [373.66–534.62]	−0.48 [−0.5 to −0.46]
	Socio-demographic index
	High SDI	37681.11 [31893.22–44753.54]	343.51 [290.81–407.03]	39898.35 [33840.24–47091.26]	195.63 [164.52–231.53]	−2.04 [−2.29 to −1.8]
	High-middle SDI	42425.18 [35429.99–50364.34]	462.74 [386.71–546.34]	78741.12 [64572.44–94487.68]	404.44 [331.92–480.98]	−0.58 [−0.69 to −0.47]
	Middle SDI	36549.18 [29656.34–44465.96]	382.77 [314.26–459.87]	104994 [85674.8–127025.96]	403.84 [330.37–481.69]	0.22 [0.15 to 0.29]
	Low-middle SDI	31250.85 [25743.08–38053.66]	531.54 [440.44–637.69]	72928.6 [61211.19–87021.4]	515.6 [433.64–614.95]	−0.09 [−0.13 to −0.05]
	Low SDI	10043.67 [8146.79–12369.51]	471.41 [384.07–572.6]	21909.23 [18079.6–26737.92]	444.61 [362.9–537.75]	−0.3 [−0.36 to −0.24]
	Region
	China	23016.44 [18619.69–27921.93]	315.31 [255.53–382.49]	73045.73 [58153.13–89499.95]	365.67 [293.32–440.07]	0.66 [0.5 to 0.82]
	Europe	46402.39 [40146.06–53698.52]	455.18 [394.15–523.33]	55146.2 [46618.07–64683.26]	349.27 [294.42–412.24]	−1.05 [−1.14 to −0.95]
	United States of America	14525.72 [11310.39–18258.93]	461.63 [361.24–582.38]	9679.9 [8143.13–11342.12]	170.36 [143.9–197.67]	−3.66 [−3.95 to −3.37]
Rheumatic heart disease	Overall	25827.97 [20485.75–32064.38]	44.87 [36.01–55.32]	38546.86 [30560.85–47837.98]	50.74 [40.1–63.06]	0.46 [0.43 to 0.5]
	Sex
	Female	13820.55 [11062.46–17177.86]	48.68 [39.39–59.79]	20589.77 [16415.01–25567.96]	55.11 [43.62–68.68]	0.45 [0.41 to 0.5]
	Male	12007.42 [9384.31–14944.52]	41.07 [32.66–50.42]	17957.09 [14170–22319.91]	46.52 [36.51–57.84]	0.49 [0.45 to 0.52]
	Socio-demographic index
	High SDI	860.02 [764.86–973.51]	8.29 [7.42–9.32]	1240.69 [1125.96–1365.07]	6.78 [6.18–7.44]	−0.93 [−1.1 to −0.77]
	High-middle SDI	2826.02 [2384.77–3381.28]	26.47 [22.41–31.39]	2418.75 [2088.15–2825.76]	20.36 [16.96–24.6]	−0.77 [−0.83 to −0.7]
	Middle SDI	9774.49 [7581.71–12313.35]	48.73 [38.49–60.75]	10453.44 [8287.84–13004.82]	45.89 [36.14–57.57]	−0.1 [−0.16 to −0.03]
	Low-middle SDI	7599.37 [5937.9–9482.18]	56.32 [44.67–69.87]	12780 [9996.19–16116.2]	60.46 [47.74–75.48]	0.24 [0.23 to 0.25]
	Low SDI	4747.72 [3637.8–6034.63]	79.92 [62.65–100.01]	11625.74 [8903.16–14798.26]	84.89 [66.11–106.36]	0.27 [0.25 to 0.3]
	Region
	China	6201.96 [4845–7785.36]	48.92 [38.62–60.36]	4454.73 [3603.94–5440.37]	39.86 [31.52–49.65]	−0.46 [−0.61 to −0.32]
	Europe	1033.43 [949.38–1123.82]	11.39 [10.5–12.36]	847.62 [772.74–932.96]	7.23 [6.61–7.98]	−1.63 [−1.69 to −1.58]
	United States of America	314.58 [268.3–372.76]	10.27 [8.82–12.04]	580.65 [519.5–643.25]	10.04 [9.06–11.04]	−0.83 [−1.29 to −0.37]

Notes: “*10²” indicates that the values have been multiplied by 100 for presentation purposes. Numbers in parentheses are 95% uncertainty intervals (UI). EAPC, calculated using total data, indicates a trend: positive values for increase and negative values for decrease.

Table 2.

Incidence, Prevalence, YLDs, YLLs, Deaths and DALYs of Heart Diseases Across China, Europe, and the United States From 1990 to 2021

Disease	Location (year)	Measure	All ages			Age standardized
			Total	Male	Female	Total	Male	Female
Atrial fibrillation and flutter	China (1990)	Incidence	306585 (234243, 404868)	152972 (117441, 199656)	153613 (116453, 204458)	42.63 (32.4, 56.46)	42 (32.04, 55.8)	41.74 (31.35, 55.99)
		Deaths	16449 (13240, 20521)	5207 (3708, 6632)	11242 (8604, 14408)	4.93 (3.88, 6.17)	3.56 (2.57, 4.35)	5.54 (4.27, 7.06)
		YLLs	258323 (206440, 324098)	92356 (65832, 121036)	165967 (127098, 214154)	58.24 (46.17, 72.91)	44.06 (31.85, 54.21)	65.27 (50.22, 83.54)
		Prevalence	3195309 (2518983, 4168290)	1627899 (1274805, 2125145)	1567410 (1228170, 2055587)	3166.57 (2844.55, 3522.45)	2507.17 (2237.74, 2793.33)	3868.06 (3495.02, 4305.42)
		YLDs	250287 (154500, 364115)	129531 (80652, 186154)	120756 (73129, 176645)	35.04 (21.82, 51.09)	37.9 (23.4, 55.11)	32.45 (20.36, 47.54)
		DALYs	508610 (395853, 638618)	221887 (162651, 288078)	286723 (226415, 359765)	93.28 (75.14, 115.5)	81.96 (62.57, 101.66)	97.72 (78.59, 120.87)
	China (2021)	Incidence	916180 (707384, 1201381)	451,977 (348036, 591930)	464,203 (351459, 620287)	44.92 (34.96, 59.42)	45.23 (35.38, 59.31)	43.28 (32.9, 57.37)
		Deaths	64728 (51765, 77729)	21789 (16730, 28054)	42939 (32263, 54478)	4.33 (3.43, 5.23)	3.81 (2.99, 4.8)	4.58 (3.45, 5.83)
		YLLs	823137 (662614, 990070)	311682 (233650, 404226)	511455 (387808, 647737)	49.76 (39.75, 59.81)	45.03 (34.98, 57.51)	52.12 (39.43, 65.93)
		Prevalence	10775721 (8531627, 14014036)	5626767 (4446323, 7289510)	5148954 (4069341, 6741869)	524 (418.15, 681.23)	574.5 (456.9, 745.56)	473.4 (373.44, 613.68)
		YLDs	829980 (513493, 1191558)	441425 (274899, 641626)	388555 (240724, 566704)	40 (24.93, 57.6)	44.59 (27.63, 64.56)	35.56 (22.09, 51.7)
		DALYs	1653117 (1303681, 2056459)	753106 (569017, 959037)	900010 (695765, 1116492)	89.76 (72.13, 109.67)	89.62 (70.01, 111.29)	87.68 (67.72, 108.49)
	Europe (1990)	Incidence	628460 (482090, 820171)	292,365 (225991, 376482)	336,095 (248021, 446630)	59.88 (46.4, 77.32)	68.98 (53.67, 88.29)	51.62 (39.12, 67.56)
		Deaths	46117 (41923, 48556)	14409 (13581, 15046)	31709 (28197, 33804)	5 (4.48, 5.29)	5.03 (4.67, 5.28)	4.94 (4.35, 5.29)
		YLLs	623437 (576065, 652800)	219584 (208168, 229150)	403853 (365589, 426868)	63.76 (58.32, 67.02)	66.23 (62.25, 69.33)	61.5 (55.47, 65.23)
		Prevalence	7541663 (5933601, 9618858)	3676124 (2945792, 4663766)	3865538 (2968336, 5060474)	718.21 (567.84, 913.28)	926.27 (741.21, 1170.85)	573.94 (445.63, 744.93)
		YLDs	575415 (362715, 836314)	285534 (183437, 408054)	289881 (182578, 431827)	54.73 (34.55, 79.03)	71.38 (45.72, 102.53)	43.11 (27.34, 63.61)
		DALYs	1198852 (987948, 1467361)	505118 (400203, 628816)	693734 (579314, 833837)	118.48 (98.39, 143.79)	137.61 (111.58, 169.4)	104.61 (87.57, 124.87)
	Europe (2021)	Incidence	921025 (743812, 1134137)	474039 (387568, 578045)	446986 (352363, 564652)	59.26 (48.17, 72.45)	70.65 (58.29, 85.55)	48.86 (39.2, 60.84)
		Deaths	101544 (85514, 110332)	36578 (32676, 38726)	64966 (52558, 71802)	5.15 (4.37, 5.58)	5.35 (4.76, 5.68)	5 (4.1, 5.5)
		YLLs	1207732 (1046838, 1297686)	475325 (435078, 499042)	732407 (608901, 801667)	64.41 (56.46, 68.87)	68.9 (62.96, 72.43)	60.76 (51.56, 65.99)
		Prevalence	12501839 (10430278,15157563)	6734626 (5698623, 8012960)	5767213 (4679741, 7157816)	745.07 (623.4, 894.31)	974.68 (827.62, 1158.11)	562.75 (462.69, 695.71)
		YLDs	935281 (614152 1328631)	514399 (342137, 715656)	420882 (273546, 606423)	56.27 (37.16, 78.89)	74.63 (49.74, 103.75)	41.6 (26.92, 59.89)
		DALYs	2143013 (1803191, 2528795)	989724 (816271, 1190243)	1153289 (969680, 1359892)	120.68 (100.81, 143.89)	143.53 (118.42, 172.68)	102.36 (86.33, 121.16)
	USA (1990)	Incidence	245056 (180693, 325021)	135521 (101113, 177143)	109536 (79303, 148865)	75.22 (57.39, 99.34)	99.21 (75.97, 129.29)	56.33 (42.44, 75.54)
		Deaths	13044 (11221, 13964)	5574 (5042, 5836)	7470 (6145, 8154)	3.88 (3.33, 4.16)	5.1 (4.54, 5.38)	3.28 (2.72, 3.57)
		YLLs	173758 (154231, 183600)	81446 (75416, 84377)	92312 (78460, 99291)	52.02 (46.26, 54.96)	68.27 (62.43, 71.2)	42.5 (36.56, 45.51)
		Prevalence	2909341 (2226181, 3751437)	1603116 (1242416, 2054778)	1306225 (986746, 1714791)	875.02 (675.05, 1125.91)	1217.21 (950.67, 1557.62)	636.42 (484.97, 830.16)
		YLDs	220113 (137297, 321831)	122429 (76430, 177934)	97684 (60906, 144850)	66.43 (41.34, 96.59)	92.63 (57.75, 134.14)	47.91 (30.16, 70.62)
		DALYs	393871 (306983, 495874)	203876 (157343, 259680)	189996 (150648, 238082)	118.44 (92.41, 149.14)	160.9 (125.26, 203)	90.41 (71.3, 113.59)
	USA (2021)	Incidence	528208 (487191, 574743)	289049 (265676, 313986)	239159 (220045, 261261)	89.18 (82.53, 96.66)	107.52 (99.48, 116.41)	72.47 (66.95, 79.27)
		Deaths	35285 (28993, 38677)	16217 (14054, 17454)	19068 (14926, 21254)	5.26 (4.36, 5.74)	6.27 (5.41, 6.76)	4.55 (3.62, 5.04)
		YLLs	448232 (382044, 483512)	224576 (200722, 238403)	223656 (181713, 245322)	69.86 (60.13, 75)	85.49 (76.2, 90.94)	57.7 (47.86, 62.83)
		Prevalence	6373868 (5938751, 6852944)	3579917 (3343611, 3849751)	2793951 (2593554, 3027252)	1040.36 (973.52, 1116.25)	1329.13 (1246.51,1426.71)	796.08 (738.31, 858.04)
		YLDs	468413 (325708, 623079)	266264 (184022, 353081)	202148 (141765, 267663)	76.86 (53.38, 102.28)	98.94 (68.38, 131.64)	58.05 (40.63, 76.94)
		DALYs	916645 (768611, 1080294)	490840 (408585, 582388)	425804 (359280, 503867)	146.72 (122.77, 172.78)	184.43 (153.85, 218.2)	115.75 (96.53, 137.25)
Ischemic heart disease	China (1990)	Incidence	2301644 (1861969, 2792193)	1244366 (991819, 1520020)	1057277 (852792, 1292714)	315.31 (255.53, 382.49)	348.59 (279.98, 423.58)	282.24 (229.4, 344.51)
		Deaths	547845 (486106, 617006)	280999 (235025, 331060)	266846 (223803, 318705)	94.14 (84.01, 105.89)	109.77 (95.03, 125.37)	84.41 (71.18, 99.75)
		YLLs	13326244 (11730014,15131303)	7383155 (6132725, 8722309)	5943089 (4990273, 7122839)	1733.76 (1538.1, 1950.12)	1999.89 (1696.57, 2336.54)	1517.35 (1273.61, 1808.91)
		Prevalence	19505463 (16754811,22537174)	10648703 (9142880, 12348341)	8856760 (7651263, 10222044)	2526.44 (2189.97, 2914.97)	2838.18 (2466.64, 3277.45)	2235.32 (1938.26, 2585.03)
		YLDs	297868 (190086, 426058)	173453 (110102, 251710)	124415 (80246, 175570)	37.37 (24.29, 53.14)	44.65 (28.83, 63.89)	30.71 (20.14, 43.16)
		DALYs	13624112 (12056606,15466092)	7556608 (6300651, 8936138)	6067504 (5114360, 7253345)	1771.13 (1574.76, 1990.67)	2044.54 (1742.46, 2379.74)	1548.06 (1305.17, 1839.24)
	China (2021)	Incidence	7304573 (5815313, 8949995)	3818580 (3034881, 4650552)	3485993 (2792003, 4259778)	365.67 (293.32, 440.07)	401.19 (321.97, 481.19)	328.08 (263.97, 397.25)
		Deaths	1956859 (1634478, 2280131)	1088197 (868768, 1332608)	868663 (676759, 1073178)	110.91 (92.42, 128.56)	148.4 (121.2, 178.97)	86.1 (67.1, 106.39)
		YLLs	34710229 (28756149,40825904)	20993464 (16394056,26305606)	13716764 (10799165,17040548)	1810.49 (1504.1, 2115.19)	2424.53 (1927.88, 2977.66)	1311.64 (1031.17, 1630.29)
		Prevalence	63331312 (53812324,76196537)	33571872 (28288613,40380503)	29759440 (25359422,35857849)	3042.35 (2601.68, 3629.87)	3379.15 (2895.87, 4036.35)	2724.16 (2320.22, 3259.05)
		YLDs	962398 (619745, 1348949)	536370 (343579, 753167)	426029 (278249, 585949)	46.02 (29.85, 63.64)	53.46 (34.48, 74.16)	38.98 (25.62, 53.31)
		DALYs	35672627 (29920273,41738946)	21529834 (1894342,26751533)	14142793 (11236414,17447300)	1856.51 (1548.73, 2159.82)	2477.99 (1979.87, 3018.01)	1350.62 (1068.58, 1666.75)
	Europe (1990)	Incidence	4640239 (4014606, 5369852)	2459840 (2117891, 2850063)	2180400 (1868678, 2558016)	455.18 (394.15, 523.33)	612.53 (533.34, 701.27)	337.06 (289.39, 392.26)
		Deaths	2118907 (1998637, 2173302)	1026939 (995758, 1043073)	1091968 (1000257, 1132792)	210.23 (197.05, 216.33)	277.39 (266.49, 282.78)	164.29 (150.18, 170.75)
		YLLs	40346887 (38870264,41133695)	23028790 (22578272,23330762)	17318097 (16205348,17829042)	3959.86 (3805.54, 4041.06)	5634.08 (5497.44, 5714.63)	2660.45 (2493.74, 2738.93)
		Prevalence	31430253 (28267509,34780799)	17118576 (15396567,18982705)	14311678 (12831812,16090780)	3020.08 (2723.72, 3331.26)	4116.51 (3718.97, 4536.76)	2238.61 (2012.94, 2513.31)
		YLDs	658630 (434192, 916966)	336698 (220005, 479609)	321932 (211155, 440796)	63.4 (42.21, 88.15)	82.62 (54.64, 115.85)	50.18 (33.21, 69.43)
		DALYs	41005517 (39476581,41816883)	23365488 (22905103,23706190)	17640029 (16548803,18173822)	4023.26 (3863.83, 4107.55)	5716.71 (5581.1, 5807.05)	2710.63 (2544.64, 2793.07)
	Europe (2021)	Incidence	5514620 (4661807, 6468326)	2914647 (2467211, 3458648)	2599973 (2207955, 3089403)	349.27 (294.42, 412.24)	442.04 (374.75, 524.54)	267.22 (223.67, 318.27)
		Deaths	1920715 (1733107, 2051869)	929642 (859493, 988836)	991073 (854377, 1083734)	108.32 (98.54, 115.49)	135.83 (125.57, 144.52)	85.44 (74.74, 93.08)
		YLLs	32106732 (29705571,34055214)	18239492 (17090785,19446776)	13867239 (12274320,15104857)	2006.94 (1868.74, 2127.06)	2754.1 (2580.17, 2936.74)	1351.67 (1207.97, 1474.79)
		Prevalence	43362824 (38502407,49198790)	24111581 (21280478,27459731)	19251243 (16954928,21982596)	2762.36 (2452.24, 3124.85)	3566.39 (3159.19, 4042.22)	2097.11 (1852.4, 2397.01)
		YLDs	867545 (570945, 1,207902)	469754 (306937, 658913)	397791 (264809, 548911)	53.98 (35.5, 75.07)	68.96 (45.03, 95.96)	42.02 (27.78, 58.46)
		DALYs	32974277 (30611437,34941291)	18709247 (17533558,19953263)	14265031 (12712840,15535579)	2060.93 (1922.14, 2182.85)	2823.06 (2645.13, 3010.14)	1393.68 (1256.4, 1514.63)
	USA (1990)	Incidence	1452572 (1131039, 1825893)	850914 (666042, 1075299)	601659 (469339, 751477)	461.63 (361.24, 582.38)	644.89 (507.07, 812.21)	314.65 (244.59, 396.43)
		Deaths	594729 (534529, 623664)	306772 (289889, 314728)	287957 (245590, 309062)	179.83 (162.05, 188.39)	243.95 (228.29, 251.5)	133.84 (115.57, 142.9)
		YLLs	10632665 (9910048, 10975599)	6278619 (6055539, 6390115)	4354046 (3863379, 4593741)	3350.25 (3138.37, 3451.35)	4786.29 (4592.17, 4883)	2204.44 (1987.66, 2308.71)
		Prevalence	9341216 (7880210, 10980079)	5570859 (4713511, 6529026)	3770357 (3160692, 4445306)	2912.81 (2469.35, 3410.96)	4136.39 (3511.82, 4825.45)	1976.29 (1671.41, 2331.66)
		YLDs	147621 (97917, 201629)	79099 (52123, 108244)	68521 (45921, 92950)	45.73 (30.79, 62.02)	58.94 (39.01, 80.44)	35.5 (23.96, 47.67)
		DALYs	10780286 (10063312,11136812)	6357718 (6132903, 6474062)	4422567 (3930878, 4669158)	3395.99 (3185.06, 3501.2)	4845.23 (4655.6, 4944.92)	2239.93 (2023.36, 2349.64)
	USA (2021)	Incidence	967990 (814313, 1134212)	577082 (484047, 674024)	390908 (329070, 462612)	170.36 (143.9, 197.67)	225.72 (190.67, 262.51)	121.68 (102.99, 143.32)
		Deaths	493222 (432451, 527139)	281455 (257072, 296030)	211767 (172597, 232441)	78.92 (69.93, 83.85)	108.1 (98.47, 113.83)	55.3 (46.05, 59.98)
		YLLs	8529674 (7804258, 8948110)	5397035 (5076959, 5613740)	3132639 (2705889, 3354937)	1489.68 (1376.98, 1557.2)	2123.1 (2002.24, 2208.63)	935.03 (829.96, 990.29)
		Prevalence	8655574 (7305087, 10307537)	5324037 (4473347, 6366223)	3331536 (2819229, 3971637)	1488.78 (1263.92, 1756.36)	2019.28 (1708.93, 2385.81)	1034.55 (877.06, 1230.76)
		YLDs	222063 (155613, 296909)	125771 (87607, 168821)	96292 (67626, 129291)	37.65 (26.36, 50.4)	47.6 (33.16, 63.88)	29.06 (20.43, 39.13)
		DALYs	8751736 (8013896, 9182128)	5522806 (5189026, 5736898)	3228930 (2813850, 3461789)	1527.33 (1412.25, 1595.15)	2170.7 (2039.57, 2256.04)	964.09 (862.85, 1022.67)
Rheumatic heart disease	China (1990)	Incidence	620196 (484500, 778536)	309982 (241505, 388551)	310213 (243357, 391512)	48.92 (38.62, 60.36)	47.23 (36.97, 58.72)	50.63 (40.12, 62.14)
		Deaths	134209 (109949, 157944)	49775 (38713, 60161)	84434 (64516, 106961)	19.07 (15.78, 22.57)	16.22 (12.85, 19.56)	21.95 (16.99, 27.84)
		YLLs	3920439 (3205912, 4641189)	1482407 (1153212, 1785589)	2438033 (1843830, 3075570)	441.29 (360.98, 519.54)	349.94 (275.44, 419.77)	536.61 (408.87, 678.93)
		Prevalence	8926340 (6909494, 11186050)	4393738 (3351389, 5540576)	4532602 (3553768, 5650180)	708.27 (558.87, 875.81)	671.01 (521.45, 834.05)	746.6 (595.04, 913.56)
		YLDs	438234 (271611, 671661)	215660 (132686, 333809)	222574 (139266, 339283)	35.04 (22.28, 53.48)	33.21 (20.82, 51.12)	36.9 (23.69, 56.07)
		DALYs	4358673 (3628079, 5149013)	1698067 (1340353, 2017820)	2660606 (2060532, 3311171)	476.33 (398.17, 563.39)	383.15 (303.99, 452.36)	573.52 (443.41, 715.37)
	China (2021)	Incidence	445473 (360394, 544037)	225077 (180333, 276567)	220396 (180354, 267413)	39.86 (31.52, 49.65)	38.66 (30.46, 48.19)	41.22 (32.8, 51.44)
		Deaths	78911 (61703, 100718)	34295 (24922, 43755)	44616 (30952, 63572)	4.21 (3.3, 5.37)	4.31 (3.17, 5.45)	4.26 (2.96, 6.05)
		YLLs	1604175 (1241963, 2053543)	712625 (512243, 920123)	891550 (609672, 1273647)	81.3 (63.31, 103.28)	79 (57, 101.56)	84.85 (58.23, 121.04)
		Prevalence	9073096 (7393886, 10994319)	4307615 (3447803, 5250525)	4765481 (3937950, 5741995)	619.85 (492.05, 763.74)	578.73 (450.72, 715.03)	662.73 (532.65, 814.44)
		YLDs	447012 (281933, 669657)	211733 (132377, 318277)	235279 (150593, 351737)	30.39 (19.02, 45.81)	28.37 (17.6, 42.8)	32.49 (20.52, 48.95)
		DALYs	2051187 (1658964, 2526905)	924358 (702505, 1165543)	1126829 (842053, 1517994)	111.69 (90.42, 136.81)	107.37 (82.13, 134.03)	117.34 (88.99, 155.46)
	Europe (1990)	Incidence	103343 (94938, 112382)	41092 (37531, 45059)	62250 (57061, 67492)	11.39 (10.5, 12.36)	10.01 (9.18, 10.92)	12.59 (11.61, 13.66)
		Deaths	42239 (40417, 44678)	14880 (14395, 15727)	27359 (25829, 29129)	4.24 (4.05, 4.49)	3.63 (3.52, 3.82)	4.6 (4.36, 4.91)
		YLLs	1157924 (1121536, 1226477)	466766 (451327, 493814)	691158 (663002, 736384)	120.23 (116.52, 127.4)	109.18 (105.51, 115.27)	127.13 (122.29, 136.06)
		Prevalence	1429194 (1298299, 1585130)	503595 (455583, 558614)	925599 (841142, 1027368)	147.66 (134.44, 163.09)	119.01 (107.95, 131.69)	169.19 (153.61, 186.9)
		YLDs	70801 (46611, 101269)	25036 (16255, 36050)	45765 (30298, 65134)	7.37 (4.84, 10.52)	5.95 (3.89, 8.53)	8.44 (5.56, 12.05)
		DALYs	1228725 (1182656, 1298688)	491802 (473461, 520960)	736923 (701671, 785286)	127.6 (122.87, 134.81)	115.13 (110.92, 121.75)	135.57 (129.39, 144.8)
	Europe (2021)	Incidence	84762 (77274, 93296)	33875 (30926, 37238)	50887 (46184, 55872)	7.23 (6.61, 7.98)	6.49 (5.87, 7.18)	7.89 (7.2, 8.68)
		Deaths	25074 (21569, 27188)	8321 (7635, 8861)	16752 (13991, 18459)	1.44 (1.26, 1.55)	1.25 (1.14, 1.33)	1.55 (1.32, 1.69)
		YLLs	428685 (383888, 458969)	164652 (153056, 174263)	264033 (228351, 286610)	28.56 (26.06, 30.46)	26.4 (24.57, 27.92)	29.77 (26.7, 32.17)
		Prevalence	1248721 (1116584, 1394771)	467051 (418904, 523793)	781670 (698155, 877736)	99.53 (89.37, 111.1)	84.18 (75.39, 93.97)	112.5 (100.86, 125.1)
		YLDs	62697 (41048, 89218)	23416 (15308, 33602)	39280 (25756, 56061)	5.02 (3.3, 7.22)	4.25 (2.78, 6.08)	5.67 (3.74, 8.13)
		DALYs	491382 (444444, 532617)	188069 (174359, 203476)	303313 (267647, 331226)	33.58 (30.78, 36.64)	30.65 (28.29, 33.28	35.44 (32.12, 38.92)
	USA (1990)	Incidence	31458 (26830, 37276)	12205 (10413, 14470)	19253 (16387, 22772)	10.27 (8.82, 12.04)	9.18 (7.86, 10.81)	11.27 (9.7, 13.2)
		Deaths	7395 (6743, 7746)	2267 (2162, 2346)	5128 (4585, 5419)	2.28 (2.09, 2.39)	1.74 (1.65, 1.8)	2.65 (2.4, 2.78)
		YLLs	162073 (152910, 167996)	55979 (53953, 57582)	106094 (98260, 110668)	52.98 (50.25, 54.85)	41.92 (40.38, 43.17)	61.5 (57.73, 63.89)
		Prevalence	422078 (360766, 499632)	154160 (131916, 181005)	267918 (229048, 316065)	133.79 (114.03, 156.01)	116.66 (99.75, 136.6)	147.76 (125.36, 172.31)
		YLDs	20242 (12614, 29359)	7322 (4554, 10628)	12921 (8122, 18726)	6.48 (4.04, 9.38)	5.54 (3.46, 7.99)	7.24 (4.54, 10.39)
		DALYs	182315 (171402, 192443)	63301 (59976, 66820)	119014 (110722, 126050)	59.46 (56.05, 62.69)	47.47 (44.97, 50.07)	68.74 (64.5, 72.54)
	USA (2021)	Incidence	58065 (51950, 64325)	26040 (23389, 28904)	32026 (28529, 35488)	10.04 (9.06, 11.04)	9.9 (8.94, 10.93)	10.21 (9.22, 11.24)
		Deaths	5079 (4122, 5601)	1763 (1451, 1938)	3316 (2663, 3680)	0.83 (0.68, 0.91)	0.7 (0.58, 0.77)	0.93 (0.76, 1.02)
		YLLs	89851 (75708, 97669)	34831 (28908, 37989)	55020 (46117, 59804)	16.88 (14.43, 18.26)	14.87 (12.39, 16.2)	18.45 (16, 19.86)
		Prevalence	714196 (651024, 787358)	308519 (280075, 342544)	405677 (369965, 445834)	123.44 (112.81, 135.61)	119.57 (109.25, 131.6)	127.15 (116.53, 139.05)
		YLDs	32285 (21031, 45479)	13870 (9008, 19511)	18415 (11966, 25897)	5.68 (3.72, 8.02)	5.44 (3.55, 7.67)	5.9 (3.87, 8.3)
		DALYs	122136 (105563, 136333)	48701 (41222, 55057)	73435 (63657, 81372)	22.56 (19.64, 25.08)	20.32 (17.23, 22.89)	24.35 (21.32, 26.88)

Globally, ASIR of IHD declined from 419.54 to 372.90, indicating substantial progress in prevention and control over the past three decades. Low-SDI regions exhibited a considerably lower incidence compared to middle- and high-SDI regions. However, China experienced an increase in ASIR (from 315.31 to 365.67), while both Europe (from 455.18 to 349.27) and the USA (from 461.63 to 170.36) showed marked declines (Table 1). In terms of age-standardized mortality rates, China demonstrated an upward trend, whereas both Europe and the USA exhibited significant declines (Table 2).

Globally, the ASIR of RHD increased from 44.87 per 100,000 to 50.74, indicating a rising global burden in contrast to the other two cardiovascular diseases. The burden remained substantially higher in low- and middle-SDI regions compared to high-SDI regions. Regionally, China (from 48.92 to 39.86), Europe (from 11.39 to 7.23), and the USA (from 10.27 to 10.04) all showed decreasing trends in ASIR (Table 1). In terms of age-standardized mortality, all three regions-China, the USA, and Europe-demonstrated significant declines (Table 2).

Discussion

AFF, IHD, and RHD are among the most representative cardiovascular diseases globally.^30–32 Although the prevalence and mortality burden of RHD are substantial and concentrated in low- and middle-SDI countries, its overall magnitude remains far lower than that of IHD. AFF, as the most common type of cardiac arrhythmia, poses a significant burden due to its rising incidence and considerable impact on health. IHD, being the leading cause of cardiovascular mortality, remains a critical public health concern requiring continuous vigilance. In contrast, RHD is closely associated with poverty and often manifests during childhood, particularly in underserved regions. While AFF and IHD predominantly affect populations in high-income countries, RHD remains highly prevalent in low- and middle-income regions.^33–38 The chronic and often fatal nature of cardiovascular diseases underscores the urgency for effective health planning. In this study, we utilized GBD data from 2021—the second year following the COVID-19^39,40 pandemic—to assess the current burden and trends of these diseases. We further conducted projections through 2040 and evaluated attributable risk factors. Given the global influence of China, the United States, and Europe, we extracted and compared data from these three major economies to provide targeted insights for health policy development.^41,42

AFF represents the most common type of cardiac arrhythmia.^34,43 These outcomes, especially under decomposition analysis, were significantly influenced by population growth and aging. BAPC to 2040 suggest that the burden of AFF may stabilize in Europe and the United States, while a potential upward trend is expected in China. Notably, joint analysis revealed a distinct inflection point in 2019, after which the incidence, prevalence, and YLDs of AFF began to rise in all three regions. This suggests that the COVID-19 pandemic may have exacerbated the burden of AFF.

In the assessment of AFF-related risk factors, elevated systolic blood pressure and the composite of metabolic risks emerged as the leading contributors globally. This highlights the critical importance of hypertension control and metabolic disease management in the global strategy for AFF prevention and control. Notably, in China, lead exposure and high body mass index (BMI) contributed a substantially higher proportion of attributable burden compared to the USA and Europe. In contrast, smoking and high alcohol consumption were the predominant risk factors in Europe and the USA.

Among the three cardiovascular conditions analyzed, IHD consistently contributed the highest burden across all six core indicators, particularly affecting the elderly population (Figure 1).

Decomposition analysis revealed that both demographic changes and epidemiological transitions had a profound impact on the disease burden of IHD. According to the BAPC model, the burden of IHD is expected to continue declining in Europe and the United States, while remaining relatively stable or slightly increasing in China. In joint burden analyses, an upward inflection points in prevalence and YLDs was observed around 2019 in the USA, suggesting that the COVID-19 pandemic may have had a modest aggravating effect on the burden of IHD.

Risk factor analysis revealed that behavioral risks represent the largest contributor to the global burden of IHD. In Europe and the USA, diet high in sugar-sweetened beverages and diet high in processed meat were substantially more prevalent than in China. In contrast, smoking and household air pollution from solid fuels contributed more significantly to IHD burden in China.

Globally, age-standardized incidence rates (ASIRs) from 1990 to 2021 slightly declined for AFF (52.51 to 52.12) and IHD (419.54 to 372.9) but increased for RHD (44.87 to 50.74). In China and the USA, AFF incidence rose (42.63 to 44.92 and 75.22 to 89.18, respectively), and IHD incidence in China increased (315.31 to 365.67). The burden remained substantially higher in low- and middle-SDI regions compared to high-SDI regions. Regionally, China (from 48.92 to 39.86), Europe (from 11.39 to 7.23), and the USA (from 10.27 to 10.04) all showed decreasing trends in ASIR (Table 1). In terms of age-standardized mortality, all three regions—China, the USA, and Europe—demonstrated significant declines (Table 2). Unlike AFF and IHD, RHD imposes a greater burden among adolescents and younger populations, particularly in low-SDI countries, while in high-SDI settings, the burden shifts toward older adults. DALYs increase progressively with age (Figure 1).

Decomposition analysis suggested that changes in population structure and epidemiology had a strong impact on RHD burden. The BAPC model indicate a possible upward trend in China, whereas both Europe and the USA are expected to continue declining. Notably, joint analysis did not identify any inflection points around 2019, suggesting that the COVID-19 pandemic had no substantial effect on the burden of RHD.^33,44

Conclusion

This study focused on AFF, IHD, and RHD, three major cardiovascular diseases with high global burden. In this study, we extracted data from GBD 2021 to analyze both disease burden indicators and attributable risk factors. Our findings revealed a global decline in the burden of AFF and IHD over the past three decades, while RHD showed a rising trend, particularly in low-SDI countries. According to GBD-based projections, the burdens of these three diseases are expected to remain stable or decline in Western regions, whereas China may experience a moderate increase over the coming decades.

AFF was primarily driven by elevated blood pressure and metabolic factors, while IHD was more strongly associated with behavioral risks such as smoking and alcohol use; nevertheless, dietary factors also play an equally important role in shaping cardiovascular risk profiles. RHD continues to impose a substantial burden globally, especially among children in resource-limited settings.

In future, we plan to incorporate the updated GBD 2023 dataset to refine our analyses and validate the current findings using forward-looking analytical models. Furthermore, we aim to provide evidence-based recommendations to support the development of more targeted and effective public health policies worldwide.

Funding Statement

Yulin Zou is funded by the Chinese Scholarship Council (YZ: CSC no. 202308210137). Yulin Zou received funding from the Jinzhou Medical University Teacher Reserve Program.

Data Sharing Statement

Data from the GBD 2021 (https://vizhub.healthdata.org/gbd-results/).

Ethics Statement

The Ethics Committee of Hebei North University reviewed this study and confirmed that it qualifies as a retrospective analysis based on publicly available datasets; thus, ethical approval was waived.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

All authors declare no competing interests in this work.