GBD 2021 data are employed in this study to approximate the worldwide burden of ischemic heart disease due to AP risk factor in people aged 60 and older. The GBD 2021 estimates are publicly available through the Global Health Data Exchange (GHDx) platform,¹ providing open access to detailed global and regional health indicators. GBD 2021 provides estimates for 371 diseases and injuries, covering incidence, prevalence, deaths, YLDs, YLLs and DALYs. Additionally, it includes 88 risk factors related to behavioral, environmental, occupational, and metabolic domains. The calculation methods of YLLs, YLDs, and DALYs have been described in other literature (12), but in short, YLLs were calculated by multiplying the number of deaths at each age by the standard life expectancy at that age, based on the reference life table used in GBD 2021 (13), and YLDs were estimated by multiplying the prevalence of each sequela by its corresponding disability weight, reflecting the severity of health loss associated with that condition (14). DALYs, a composite metric of disease burden, were calculated as the sum of YLLs and YLDs, capturing both premature mortality and non-fatal health outcomes (15). The Social Development Index (SDI) is a composite measure of socioeconomic development, incorporating total fertility rates, average years of schooling, and lagged per capita income for populations aged 15 and older. Countries and regions are classified into five SDI groups—high, middle-high, middle, low-middle, and low—based on SDI scores ranging from 1 to 0 (16). GBD 2021 classifies 204 countries and territories into seven super-regions, which are further divided into 21 regions based on geographic proximity and epidemiological characteristics (17). This study analyzes data from 204 countries and regions between 1990 and 2021. The report provides a comprehensive trend analysis and assessment of the global burden of IHD attributable to AP in people aged 60 and older.

The dataset was filtered to include only indicators relevant to the impact of AP on ischemic heart disease in individuals aged 60 years and older. Primary variable indicator included: measure (deaths, YLDs, YLLs and DALYs), sex subgroups (both sexes, females and males), age subgroups (60–64, 65–69, 70–74, 75–79, 80–84, 85–89, 90–94, and 95 + years), location subgroups 1 (five SDI groups), location subgroups 2 (seven super-regions, further divided into 21 regions), location subgroups 3 (204 countries) metric (number, rate and percent), risk factor (air pollution), and time period (1990–2021).

To evaluate temporal trends, the estimated annual percentage change (EAPC) was calculated using a log-linear regression model. A new categorical variable, direction, was introduced to represent whether the measure (deaths, YLDs, YLLs and DALYs) trend was increasing or decreasing over time based on the EAPC value.

Temporal trends in deaths, DALYs, YLDs, and YLLs attributable to air pollution were assessed for different geographic units using the EAPC. The EAPC represents the average annual percentage change in age-standardized rates (ASRs), quantifying the temporal trend over the study period (18–20).

A linear regression model was applied to estimate EAPC, with ASR as the dependent variable and calendar year (t) as the independent variable:

where α is the intercept, β represents the annual rate of change in ASRs, and ε is the error term (19, 21, 22).

The EAPC was then calculated as follows:

where 𝛽 is the slope obtained from the linear regression of the natural logarithm of ASR. with 95% confidence intervals (CIs) used to determine the statistical significance of the trends.

SDI categories were used to compare the disease burden across different levels of socioeconomic development. The relationship between SDI and the burden of IHD attributable to AP was examined by calculating SDI-specific disease death rates (23). The `ggplot2` and `ggrepel` packages in R were employed for data manipulation and visualization.

For better public health policy-making and medical resource distribution, we stratified the population by gender subgroups (both sexes, females and males) and used the Bayesian-Aperiodic-People-Cohort (BAPC) model to predict future trends in deaths, YLLs, YLDs, and DALYs for IHD for the next 15 years. By including age-specific trends and time-related changes, these models provide a credible and detailed projection of future IHD burden (24–26). Studies have found that it is possible to make effective approximations of marginal posterior distributions by combining the Integrated Nested Laplace Approximation (INLA) with the BAPC model and avoiding mixing and convergence issues that are typical of the Markov Chain Monte Carlo (MCMC) sampling method used by traditional methods. This model provides flexible, accurate, and computationally efficient projections, making it well-suited for analyzing long-term trends in chronic diseases and environmental health risks (27). BAPC model is appropriate for studying environmental risk factor (such as AP), chronic diseases (such as IHD) and health trends in specific populations (such as people aged 60 years and older).

All statistical analyses and data visualizations were performed using R (version 4.3.2). Descriptive statistics were generated for all key variables, and results were expressed as means with 95% CIs. For trend analyses, p-values < 0.05 were considered statistically significant. We generated data visualizations, including bi-lateral and two-axis plots, using the ‘ggplot2’ and ‘Benchmarking’ packages in R.

Between 1990 and 2021, IHD burden attributable to AP in individuals aged above 60 years presented a rising trend in Disability-Adjusted Life Years (DALYs), deaths, Years Lived with Disability (YLDs), and Years of Life Lost (YLLs). Conversely, the corresponding Age-Standardized Rates (ASRs) demonstrated a downward trend (Figure 1). By 2021, the global figures for DALYs, deaths, YLDs, and YLLs due to AP-related IHD were 34,564,173 (95% Uncertainty Interval [UI]: 25,887,530 to 43,130,304), 2,005,125 (95% UI: 1,484,963 to 2,514,494), 777,285 (95% UI: 440,728 to 1,219,129), and 33,786,889 (95% UI: 25,257,005 to 42,183,966), respectively. The corresponding ASRs were 3,242.22 (95% UI: 2,424.71 to 4,048.51), 193.65 (95% UI: 143.12 to 243.06), 72.13 (95% UI: 40.91 to 113.06), and 3,170.09 (95% UI: 2,366.06 to 3,960.79). These figures represent an increase of 56.3, 64.1, 94, and 55.6%, respectively, compared to 1990. The estimated annual percentage changes (EAPC) were −1.41 (95% CI: −1.50 to −1.31), −1.41 (95% CI: −1.51 to −1.31), −0.6 (95% CI: −0.68 to −0.53), and −1.42 (95% CI: −1.52 to −1.32), respectively (Tables 1–4).

Between 1990 and 2021, both the burden of IHD attributed to AP and the ASRs were consistently higher in men than in women, with this gender disparity remaining largely unchanged over the period. In 2021, the disease burden ratios for men relative to women were 1.29:1 for DALYs, 1.15:1 for deaths, 1.3:1 for YLDs, and 1.29:1 for YLLs (Figure 2A). Regarding age groups, higher ASRs were observed in older age categories in 2021, although the 85 + age group exhibited a relatively lower disease burden compared to other age groups. From 1990 to 2021, the burden of disease increased across all age groups, while ASRs showed a general decline, with the most significant decreases occurring in older age groups (Figure 2B; Supplementary Figure S1A). With respect to the Socio-Demographic Index (SDI), disease burdens rose in all regions except those with a High SDI, where a decrease in burden was noted. This trend was especially prominent in the densely populated Middle and Low-Middle SDI regions, which together accounted for 63.6% of DALYs, 61.3% of deaths, 58.4% of YLDs, and 63.7% of YLLs. ASRs decreased across all SDI regions, with higher SDI regions experiencing more pronounced reductions, while Low SDI regions saw more limited declines. These changes were significantly correlated with the healthcare infrastructure and public awareness in each region (Figure 3A). As for health indicators, DALYs and YLLs remained at elevated levels over an extended period, suggesting that AP-induced IHD primarily results in health loss rather than a marked reduction in life expectancy (Supplementary Figures S1B,C).

In 2021, among Global Burden of Disease (GBD) regions, East Asia recorded the highest number of deaths and YLDs, while South Asia had the highest number of DALYs and YLLs, contributing to 31.1, 33.5, 32.2, and 32.4% of the global disease burden, respectively. Central Asia, North Africa, the Middle East, South Asia, and Oceania had the highest ASRs for disease burden, with disparities of more than 20-fold compared to the lowest regions, such as Australasia and High-Income North America. Between 1990 and 2021, except for a few Low SDI regions like East Asia, South Asia, and Eastern Sub-Saharan Africa, where the Age-Standardized Rates (EAPCs) for ASRs continued to rise, most regions saw a general decline, with High-Income North America and Western Europe experiencing the steepest decreases. The SDI regions showed the most rapid declines, with EAPCs for DALYs, deaths, YLDs, and YLLs in these regions at −6.8 (95% CI: −7.2 to −6.4), −6.4 (95% CI: −6.61 to −6.19), −6.74 (95% CI: −7.17 to −6.32), and −6.21 (95% CI: −6.44 to −5.97), respectively (Figure 3B; Tables 1–4).

In 2021, among 204 countries worldwide, China, India, Pakistan, Indonesia, and Egypt exhibited the highest disease burden, particularly in terms of DALYs and YLLs. Russia, with a significant number of deaths, ranked fourth globally, while Bangladesh reported the highest number of YLDs, following China and India. Although China and India had comparable DALYs, China’s deaths and YLDs were 1.3 and 1.6 times greater than those of India. Collectively, these two countries accounted for 53.3, 53.8, 52.9, and 53.4% of the global DALYs, deaths, YLDs, and YLLs, respectively. The ASRs for each disease burden indicator exhibited considerable variation between countries, with differences reaching up to 120-fold. For instance, Egypt’s Age-Standardized Death Rates (ASDRs) were as high as 15,876.89/100,000 (95% Uncertainty Interval [UI]: 11,637.94-20,532.18), while Iceland’s were just 137.08/100,000 (95% UI: 23.61–305.63). Similarly, Egypt’s YLLs had ASRs of up to 15,717.63/100,000 (95% UI: 11,477.1-20,344.03), while Iceland’s were only 132.00/100,000 (95% UI: 22.58–295.79). Countries such as Egypt, Afghanistan, Vanuatu, Solomon Islands, Uzbekistan, Sudan, Haiti, Yemen, and Tajikistan all had ASDRs greater than 1/10, over three times the global average, with corresponding ASRs for deaths and YLLs exceeding 600/100,000 and 0.9/10, respectively. For YLDs, global variations among countries were less pronounced, with the highest difference being approximately 40-fold. Kuwait, Qatar, Saudi Arabia, Sudan, and Bahrain had the highest ASRs, indicating that the management of AP-induced IHD in these countries requires particular attention. Additionally, we observed that the ASRs for each indicator in China were higher than the global average but notably lower than those in India (Figure 4; Tables 1–4).

From 1990 to 2021, the trends in age-standardized death rates of IHD attributed to AP varied noticeably across different SDI regions. In Central Asia, we observed a clear reversal in the ASDR trend, suggesting a shift in disease burden during the study period. Regions like Southern Sub-Saharan Africa, East Asia, and South Asia showed large fluctuations over time, indicating unstable patterns. In low-SDI countries, there was no strong correlation between SDI and ASR. However, in high-SDI regions, the expected negative association was evident—higher SDI levels were generally linked to lower ASR. Middle-SDI regions also showed a similar inverse trend, though it was less consistent compared to high-SDI areas (Figure 5A).

At the national level in 2021, most countries followed the anticipated negative relationship between SDI and ASR, with only a few outliers. Among these, Egypt had an unusually high ASR that significantly exceeded what would be expected based on its SDI level (Figure 5B).

To inform global strategies for the prevention and treatment of IHD caused by AP, we employed the BAPC model to forecast future trends in the global disease burden of IHD among individuals over 60 years of age. The projections suggest that in the coming decade, all disease burden indicators associated with AP-induced IHD will experience substantial increases, with growth rates surpassing 50%. Notably, YLDs may approach a one-fold increase. The corresponding ASRs are expected to shift from a steep decline to a more gradual reduction, with ASRs for YLDs potentially beginning to rise. These trends are anticipated to show minimal gender-based differences, although males will continue to experience higher rates than females (Figure 6).