Global, Regional, and National Burden of Pulmonary Arterial Hypertension in Children and Adolescents, 1990-2021, and Projections to 2050: A Systematic Analysis for the Global Burden of Disease Study 2021

Global, Regional, and National Burden of Pulmonary Arterial Hypertension in Children and Adolescents, 1990-2021, and Projections to 2050: A Systematic Analysis for the Global Burden of Disease Study 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Global, Regional, and National Burden of Pulmonary Arterial Hypertension in Children and Adolescents, 1990-2021, and Projections to 2050: A Systematic Analysis for the Global Burden of Disease Study 2021 Mengyun Tu, Jieyang Zhu, Jie Weng, Zhiyi Wang, Sipin Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5827730/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Pulmonary arterial hypertension (PAH) in children and adolescents is a significant global health challenge, leading to a range of severe medical complications and an increased risk of premature death. In this study, we assessed the trends and cross-country disparities in the burden of PAH among children and adolescents from 1990 to 2021, and further predicted its changes to 2050. Results GBD 2021 estimated 5,049 incident cases, 1,972 deaths, and 170,371 DALYs of PAH in children and adolescents globally in 2021. South Asia reported the highest numbers of incident, death, and DALYs cases, while Eastern Sub-Saharan Africa had the highest age-standardized incidence rate (ASIR), and the Caribbean recorded the highest age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR). Between 1990 and 2021, the ASIR in this population showed an overall increasing trend, whereas the ASMR and ASDR demonstrated a consistent decline. The ASIR, ASMR, and ASDR were found to decrease exponentially with rising SDI levels. DALYs were disproportionately concentrated in countries with lower sociodemographic development levels. The ASIR is projected to remain globally stable, while both the ASMR and ASDR are expected to decline annually through 2050. Conclusions The burden of PAH in children and adolescents is concentrated in low-SDI countries. While ASIR has increased, ASMR and ASDR have steadily declined and are projected to continue decreasing through 2050. Strengthening international collaboration, improving healthcare, and targeting high-risk regions are crucial to reducing the disease burden and promoting global health equity. pulmonary arterial hypertension children and adolescents global disease burden sociodemographic index health inequality Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Pulmonary arterial hypertension (PAH) is a progressive condition affecting the pulmonary vasculature, characterized by increased pulmonary arterial pressure and vascular resistance, ultimately leading to right heart failure. 1 Although PAH may present at any age from infancy to adulthood, when it manifests in children and adolescents, it becomes particularly complex and challenging. 2 Pediatric PAH often involves unique etiologies such as congenital heart disease or genetic predispositions, making its early diagnosis and intervention critical for improving outcomes and quality of life. 3 An epidemiological study conducted in a large insured pediatric population found that between 2010 and 2013, the annual incidence of PAH ranged from 4.8 to 8.1 cases per 1,000,000 child-years, while the annual prevalence ranged from 25.7 to 32.6 cases per 1,000,000 children. 4 A study from the Polish Registry of Pulmonary Hypertension reported the estimated incidence rate was 2.4 per million children/year, and the mean prevalence of PAH was 11.6 per million. 5 Overall, PAH is a rare disease, particularly in children and adolescents. Although targeted therapies for PAH have been developed and have contributed to improved morbidity and mortality, persistent disability and the continued high healthcare costs remain ongoing challenges for patients and healthcare systems. 6 , 7 Most available data are derived from national or regional registries, comprehensive global studies specifically targeting the epidemiology of PAH in children and adolescents remain limited. Beyond incidence, prevalence, and mortality, there has been almost no assessment of the disease burden in this population. Existing epidemiological studies on PAH based on the Global Burden of Disease (GBD) database mainly focus on the general population, largely neglecting children and adolescents as a distinct subgroup. In-depth investigation of the epidemiological trends of PAH in this age group is crucial for understanding the disease burden and assessing the feasibility of health goals. Therefore, a comprehensive global compilation of incidence, mortality, and disability-adjusted life years (DALYs) data in children and adolescents is urgently needed. Our study analyzed the global trends in incidence, mortality, and DALYs of PAH in children and adolescents using the GBD database, highlighting regional disparities in disease burden. This will inform early screening efforts and guide healthcare policies and resource allocation. Additionally, health inequality analysis was used to emphasize variations in disease burden across different socio-demographic index (SDI) regions, promoting targeted interventions The Bayesian Age-Period-Cohort (BAPC) model was applied to predict future trends, providing insights for policymakers and healthcare providers. These approaches aim to improve global health outcomes for children and adolescents with PAH. Methods Data acquisition The GBD 2021 utilized updated epidemiological evidence and refined methods to offer a comprehensive analysis of health loss across 371 distinct diseases, injuries, and impairments, as well as 88 risk factors by age and sex for 204 countries and territories. 8 The GBD incorporated diverse data sources, each uniquely identified and made available through the Global Health Data Exchange (GHDx). The gathered data were processed using spatiotemporal Gaussian process regression to allow for smoothing over age, time and location in locations lacking complete datasets. The Meta-Regression with Bayesian priors, Regularisation, and Trimming (MR-BRT) program was employed to adjust data bias due to variable case definitions and study protocols across countries. Comprehensive details regarding the study design and methodologies of GBD research have been thoroughly documented in the existing GBD literature. 9 – 11 In this study, estimates and their 95% uncertainty intervals (UIs) for the incidence, mortality, and DALYs associated with PAH among children and adolescents were obtained from GBD 2021. All rates were presented per 100,000 individuals. Additionally, the SDI was employed to reflect a composite measure encompassing income, education, and fertility, thereby quantifying the level of sociodemographic development in a given country or region. The SDI categorizes development into five quintiles: low, low-middle, middle, high-middle, and high. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. Ethics The institutional review board of Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University determined that ethical approval was not required for this study, as it involved only data analysis without any identifiable personal information. Descriptive analysis To comprehensively assess the burden of PAH in children and adolescents, a descriptive analysis was conducted at global, regional, and national levels. The global case numbers and age-standardized rates (ASRs) for incidence, mortality, and DALYs related to PAH in both sexes from 1990 to 2021 were visually represented. Furthermore, the case number and ASR for incidence, mortality, and DALYs in 1990 and 2021 were compared across global, regional, and national levels, as well as across five SDI quintiles. Trend analysis Exploring temporal trends in diseases is a vital component of epidemiology, as it aids in developing targeted preventive strategies. This study aimed to investigate the trends of PAH in children and adolescents from the overall and local scopes. Firstly, we used estimated annual percentage change (EAPC) to quantify the overall trend. The evolving disease burden was assessed using a statistical model to estimate EAPCs, calculated based on ASRs using the formula: y = α + βx, where x represents the calendar year and y represents the natural logarithm of the ASRs. The EAPC was then calculated as 100 × [exp(β)–1], indicating the annual percentage change. The linear regression model was also used to determine the 95% confidence interval (CI) for the EAPC. An increasing trend in ASR was identified if both the EAPC and the lower boundary of its 95% CI were greater than zero. Conversely, if both the EAPC estimate and the upper boundary of the 95% CI were less than zero, the ASR was deemed to show a decreasing trend. If neither condition was met, the ASR was classified as stable. Next, we employed Joinpoint regression analysis to examine local trends in the PAH burden among children and adolescents. Joinpoint regression analysis (Joinpoint Trend Analysis Software, 2022) identifies inflection points to segment the overall trend into multiple distinct segments, allowing for the evaluation of each subtrend by estimating the annual percentage change (APC) and its 95% CI. The Monte Carlo permutation method, using 4,499 randomly generated datasets, was employed to determine the average annual percentage change (AAPC) and its 95% CI, and the overall significance level was maintained through a Bon ferroni correction. An increasing trend during a specific period was recognized if both the APC/AAPC estimate and the lower bound of the 95% CI were greater than zero. Conversely, a decreasing trend was indicated if both the APC/AAPC estimate and the upper bound of the 95% CI were less than zero. If neither condition was satisfied, the trend was classified as stable. Statistical analysis of PAH burden and SDI relationship Smoothing splines models were used to examine the relationship between the burdens of PAH among children and adolescents and SDI across 21 regions. Expected values were determined through a calculation that takes into account the SDI and disease rates across all locations. The Locally Weighted Scatterplot Smoothing (LOWESS) method was applied to fit smooth splines, automatically adjusting the degree, number, and placement of knots based on the data characteristics and span parameter. Additionally, Spearman correlation analysis was conducted to estimate the correlation coefficients (R) and P values, identifying the association between ASR and SDI. All P values were 2-sided, and P < 0.05 was considered statistically significant. Cross-country inequality analysis To evaluate health inequalities in the burden of PAH among children and adolescents, we utilized two standard metrics: the slope index of inequality (SII) and the concentration index (CI), which measure absolute and relative gradient inequalities in health, respectively. The SII was derived through regression analysis, relating a country's DALY rates to its SDI relative position, defined by the population's midpoint in a cumulative distribution ranked by SDI. To account for heteroscedasticity, we used robust linear regression models. The CI was calculated by numerically integrating the area under the Lorenz curve, which aligns the cumulative proportion of DALYs with the population's cumulative distribution sorted by SDI. Together, these metrics offer a thorough understanding of how the PAH burden is unevenly distributed across different socioeconomic groups, supporting the development of targeted public health interventions. Predictive analysis In this study, we applied a BAPC model with integrated nested Laplace approximation (INLA) to project future trends in the burden of PAH among children and adolescents. Previous studies have demonstrated that the BAPC model, when combined with INLA, provides enhanced coverage and precision compared to alternative predictive methods. 12 , 13 The analysis was conducted using the World Health Organization's Health Equity Assessment Toolkit and R statistical software (Version 4.2.2). Role of the funding source The funder had no role in study design, data collection, data analysis, data interpretation, and writing of the manuscript. All authors had full access to the dataset. The corresponding authors had final responsibility for the decision to submit for publication. Results Descriptive analysis of PAH burden among children and adolescents at global, regional, and national levels Globally, from 1990 to 2021, both PAH incidence cases and age-standardized incidence rate (ASIR) among children and adolescents showed an increasing trend, while the death cases, DALYs cases, age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR) exhibited a sharp decline (eFigure 1). The case numbers and ASR of PAH incidence, mortality, and DALYs among children and adolescents in 1990 and 2021 were presented in Table 1 , eTable 1–5, respectively. Based on SDI quintiles, the low-middle SDI quintile had the highest number of incidence, death, and DALYs cases for children and adolescents in 2021. Regarding ASR, the highest ASIR, ASMR, and ASDR were observed in the low SDI quintile (Table 1 ; eTable 1–2). Regionally, South Asia had the highest number of PAH incidence, death, and DALYs cases among children and adolescents. Eastern Sub-Saharan Africa had the highest ASIR, whereas the Caribbean had the highest ASMR and ASDR (Table 1 ; eTable 1–2). Nationally, the incidence, mortality, and DALYs of PAH among children and adolescents varied remarkably across the world, with the highest number of incidence, death, and DALYs cases found in India, the highest ASIR in Ethiopia, and the highest ASMR and ASDR in Haiti (Fig. 1 ; eTable 3–5). Table 1 The number of PAH incidence and ASIR in 1990 and 2021 among children and adolescents by SDI quintiles and by GBD regions, with EAPC from 1990 to 2021. Location 1990 2021 EAPC (95% CI) 1990–2021 Number (95% Uls) ASIR (95% Uls) Number (95% Uls) ASIR (95% Uls) Global 4134.613 (2977.157 to 5628.527) 0.068 (0.049 to 0.092) 5049.038 (3617.783 to 6916.409) 0.071 (0.051 to 0.097) 0.13 (0.1 to 0.17) SDI quintiles High SDI 313.631 (225.446 to 432.465) 0.046 (0.033 to 0.064) 287.222 (205.089 to 396.145) 0.046 (0.033 to 0.063) -0.06 (-0.09 to -0.04) High-middle SDI 544.722 (392.803 to 745.113) 0.054 (0.039 to 0.074) 456.162 (328.209 to 626.834) 0.056 (0.04 to 0.076) 0 (-0.06 to 0.05) Middle SDI 1330.267 (952.547 to 1823.591) 0.064 (0.046 to 0.088) 1319.595 (941.263 to 1822.487) 0.065 (0.046 to 0.09) 0.07 (0.04 to 0.1) Low-middle SDI 1173.614 (843.609 to 1593.683) 0.073 (0.053 to 0.1) 1530.818 (1090.566 to 2106.016) 0.074 (0.053 to 0.102) -0.08 (-0.13 to -0.04) Low SDI 769.182 (555.867 to 1037.897) 0.102 (0.074 to 0.137) 1451.571 (1043.958 to 1978.087) 0.092 (0.066 to 0.125) -0.34 (-0.41 to -0.26) GBD regions Andean Latin America 34.897 (24.998 to 47.347) 0.068 (0.049 to 0.092) 44.352 (31.752 to 60.393) 0.069 (0.05 to 0.094) 0.11 (0.04 to 0.18) Australasia 7.584 (5.386 to 10.358) 0.045 (0.032 to 0.061) 9.494 (6.751 to 12.994) 0.047 (0.033 to 0.064) 0.12 (0.1 to 0.14) Caribbean 23.186 (16.706 to 31.456) 0.057 (0.041 to 0.077) 25.445 (18.063 to 34.797) 0.062 (0.044 to 0.084) 0.32 (0.25 to 0.38) Central Asia 45.961 (33.562 to 60.475) 0.054 (0.039 to 0.071) 52.473 (38.136 to 70.138) 0.056 (0.041 to 0.075) 0.06 (-0.01 to 0.14) Central Europe 54.891 (39.855 to 74.191) 0.052 (0.038 to 0.07) 36.21 (26.23 to 49.162) 0.057 (0.041 to 0.077) 0.26 (0.19 to 0.32) Central Latin America 154.497 (111.187 to 209.731) 0.069 (0.05 to 0.094) 145.432 (103.788 to 201.128) 0.063 (0.045 to 0.087) -0.13 (-0.25 to -0.01) Central Sub-Saharan Africa 85.966 (62.557 to 114.186) 0.103 (0.075 to 0.136) 205.079 (148.853 to 277.938) 0.103 (0.075 to 0.14) 0.22 (0.05 to 0.39) East Asia 743.664 (533.853 to 1022.494) 0.06 (0.043 to 0.082) 545.747 (390.684 to 747.165) 0.059 (0.042 to 0.08) -0.06 (-0.11 to -0.02) Eastern Europe 92.38 (67.468 to 124.753) 0.051 (0.037 to 0.069) 67.786 (48.71 to 92.837) 0.054 (0.039 to 0.074) 0.13 (-0.04 to 0.3) Eastern Sub-Saharan Africa 375.472 (272.584 to 505.972) 0.125 (0.091 to 0.169) 707.212 (510.62 to 967.412) 0.115 (0.083 to 0.157) -0.14 (-0.22 to -0.05) High-income Asia Pacific 58.417 (41.288 to 81.304) 0.043 (0.03 to 0.06) 36.875 (26.184 to 51.212) 0.044 (0.031 to 0.062) 0.11 (0.1 to 0.13) High-income North America 74.052 (52.994 to 101.275) 0.034 (0.024 to 0.046) 88.657 (62.699 to 123.589) 0.037 (0.026 to 0.051) 0.26 (0.23 to 0.29) North Africa and Middle East 320.493 (228.945 to 431.444) 0.067 (0.048 to 0.09) 403.303 (289.881 to 548.869) 0.063 (0.045 to 0.086) -0.38 (-0.51 to -0.25) Oceania 6.23 (4.474 to 8.423) 0.068 (0.049 to 0.093) 12.433 (8.875 to 16.953) 0.072 (0.051 to 0.098) -0.04 (-0.11 to 0.04) South Asia 1002.74 (719.182 to 1363.277) 0.068 (0.049 to 0.093) 1288.985 (916.617 to 1786.641) 0.07 (0.05 to 0.097) -0.02 (-0.06 to 0.02) Southeast Asia 382.607 (273.676 to 524.044) 0.064 (0.046 to 0.088) 431.585 (309.223 to 596.082) 0.07 (0.05 to 0.096) 0.2 (0.17 to 0.23) Southern Latin America 23.09 (16.658 to 30.962) 0.044 (0.032 to 0.059) 23.089 (16.326 to 31.934) 0.044 (0.031 to 0.061) 0.03 (0 to 0.06) Southern Sub-Saharan Africa 70.084 (50.318 to 97.119) 0.098 (0.07 to 0.136) 77.068 (55.133 to 106.385) 0.091 (0.065 to 0.126) -0.08 (-0.17 to 0.02) Tropical Latin America 111.311 (79.064 to 153.338) 0.059 (0.042 to 0.082) 106.622 (76.356 to 145.97) 0.059 (0.042 to 0.081) -0.02 (-0.11 to 0.08) Western Europe 154.248 (110.236 to 213.644) 0.058 (0.041 to 0.08) 135.124 (96.799 to 185.615) 0.054 (0.039 to 0.075) -0.24 (-0.28 to -0.21) Western Sub-Saharan Africa 312.844 (227.171 to 419.572) 0.108 (0.078 to 0.144) 606.067 (437.241 to 818.474) 0.083 (0.06 to 0.113) -1.12 (-1.23 to -1.01) Abbreviations: ASIR, age-standardized incidence rate; PAH, pulmonary arterial hypertension; SDI, socio-demographic index; EAPC, estimated annual percentage change; UIs, uncertainty intervals; CI, confidence interval. Overall trends in PAH burden among children and adolescents using broad estimation method Globally, the ASIR of PAH among children and adolescents increased by an average of 0.13% (95% CI: 0.10–0.17) per year from 1990 to 2021, while the ASMR and ASDR decreased by an average of 2.49% (95% CI: -2.68 to -2.30) and 2.53% (95% CI: -2.72 to -2.33) per year, respectively (Table 1 ; eTable 1–2). In terms of SDI quintiles, the ASIR increased in the middle SDI quintile, decreased in the low, low-middle, and high SDI quintiles, and remained stable in the high-middle SDI quintile from 1990 to 2021. Additionally, the ASMR and ASDR showed a decreasing trend across all five SDI quintiles, with the most significant reductions observed in the high-middle SDI quintile (Table 1 ; eTable 1–2). Regionally, the most significant increase in ASIR among children and adolescents was observed in the Caribbean, whereas the greatest decrease occurred in Western Sub-Saharan Africa. The ASMR and ASDR increased in Oceania and Southern Sub-Saharan Africa but decreased in other regions, with the most notable reduction in the ASMR observed in Eastern Europe, and the largest decline in the ASDR seen in Southern Latin America (Table 1 ; eTable 1–2). Nationally, trends in the disease burden of PAH among children and adolescents varied significantly across the 204 countries and territories (Fig. 1 ; eTable 3–5). Slovakia had the highest EAPC of incidence, while Burkina Faso had the lowest. Mauritius had the highest EAPCs for both mortality and DALYs, whereas Puerto Rico had the lowest. Local trends in PAH burden among children and adolescents using joinpoint regression analysis The results of the joinpoint regression analysis for the burden of PAH among children and adolescents across different metrics are shown in Fig. 2 . Between 1990 and 2021, the ASIR among children and adolescents showed an overall increasing trend, with an AAPC of 0.15 (95% CI: 0.13–0.17), though trends varied over time (Fig. 2 A). Specifically, there was a significant increase from 1990 to 2000, followed by a slower rise from 2000 to 2011. The trend then began to decline from 2011 to 2016, with a notable decrease from 2016 to 2019, before slightly increasing again from 2019 to 2021. In contrast, the ASMR demonstrated a consistent decreasing trend, with an AAPC of -3.04 (95% CI: -3.13 to -2.94), and the steepest decline observed between 2019 and 2021 (Fig. 2 B). Similarly, the ASDR showed a significant decline throughout the study period, with an AAPC of -3.08 (95% CI: -3.18 to -2.98), with the sharpest reduction occurring from 2019 to 2021 (Fig. 2 C). These results highlight distinct trends in the ASIR, ASMR, and ASDR among children and adolescents: the ASIR generally increased, while the ASMR and ASDR consistently decreased. The correlation between PAH burden and SDI in children and adolescents The SDI, a comprehensive metric for evaluating regional development levels, was closely linked to population health. At the regional level, the ASIR, ASMR, and ASDR of PAH in children and adolescents decreased exponentially with rising SDI (eFigure 2A-C). Negative correlations were observed between SDI and ASIR (R = -0.82, P < 0.001), ASMR (R = -0.46, P < 0.001), and ASDR (R = -0.47, P < 0.001), respectively. Eastern Sub-Saharan Africa, Central Sub-Saharan Africa and Southern Sub-Saharan Africa had higher-than-expected ASIR of PAH based on their SDIs. Similarly, North Africa and Middle East and Caribbean had higher-than-expected ASMR and ASDR of PAH based on their SDIs. Despite having the highest ASIR, low SDI regions showed a significant decline in ASIR from 1990 to 2021. Additionally, all SDI regions experienced substantial reductions in ASMR and ASDR over the same period (eFigure 1 D-F). Age and sex patterns In 2021, the ASIR of PAH in children and adolescents showed an increase with age in the 0–4 year age group. However, in the 5–19 year age group, the ASIR remained relatively consistent across ages. For the 0–6 days and 7–27 days age groups, the ASIR ratios between males and females were similar; however, with advancing age, the ASIR was consistently higher in females compared to males within the same age group (eFigure 3A). Regarding both the ASMR and ASDR in children and adolescents, the 0–1 year and 15–19 year age groups exhibited higher rates. In the 0–9 year group, males had higher ASMR and ASDR than females, whereas in the 10–19 year group, females had higher ASMR and ASDR than males (eFigure 3B-C). Cross-country inequality analysis Significant absolute and relative SDI-associated inequalities in the burden of PAH among children and adolescents were observed, with a reduction in these disparities over time (Fig. 3 ). It is noteworthy that DALYs were disproportionately concentrated in countries with lower sociodemographic development levels. As indicated by the slope index of inequality, there was an excess of -3.89 (95% CI: -4.88 to -2.89) DALYs per 100,000 between the countries with the highest and lowest SDI in 1990, which decreased to -1.97 (95% CI: -2.35 to -1.59) in 2021. Furthermore, the concentration index, a measure of relative gradient inequality, was − 0.33 in 1990 and − 0.40 in 2021, reflecting an uneven distribution of the burden across countries with different SDI levels. Future forecasts of global burden of PAH in children and adolescents The global burden of PAH in children and adolescents is projected to evolve significantly from 2021 to 2050, with different trends across various measures. As shown in Fig. 4 A, the ASIR is expected to remain stable globally. Furthermore, we have forecasted the ASMR and ASDR (Fig. 4 B-C). Over time, both the ASMR and ASDR are predicted to decrease annually through 2050. Discussion This study provides the latest data on the incidence, mortality, and DALYs of PAH in children and adolescents at global, regional, and national levels from 1990 to 2021, highlighting significant disparities across different countries and regions. Further comprehensive assessments were conducted based on trends, inequalities, and predictive analysis. Overall, our findings indicate that from 1990 to 2021, although the incidence cases and ASIR among children and adolescents globally showed an increasing trend, the death cases, DALYs cases, ASMR, and ASDR have dramatically decreased during the same period. Cross- country inequality analysis indicates that low-SDI countries bear a disproportionate burden of PAH in children and adolescents, but SDI-related inequalities have decreased over time. Notably, while the ASIR is expected to remain stable annually from 2022 to 2050, both ASMR and ASDR are projected to decline each year. These trends suggest that the challenges in controlling and managing PAH among children and adolescents in the coming decades may be alleviated. PAH accounted for 5,049 incident cases, 1,972 deaths, and 170,371 DALYs cases among children and adolescents globally in 2021. Previous studies based on local or national registries have reported varying incidence rates of PAH in children and adolescents. In the United Kingdom, the annual incidence of childhood PAH was estimated at 1.6 per 1 million population, 14 while a 15-year nationwide study in the Netherlands reported an annual incidence of 3.0 per 1 million. 15 The current GBD incidence estimate of 0.7 cases of PAH per 1 million children and adolescents, based on a more standardized and comprehensive dataset, is lower than the average incidence rates reported in these previous studies. South Asia reported the highest case numbers for all three metrics, while Eastern Sub-Saharan Africa had the highest ASIR, and Caribbean had the highest ASMR and ASDR. It is important to note that attention should be given not only to regions with the highest current burden, but also to those that have experienced the largest increases over the past few decades. Accordingly, Caribbean, which experienced the largest increase in ASIR from 1990 to 2021, and Oceania, which saw the largest increases in both ASMR and ASDR during the same period, warrant particular concern. At the national level, the disparities in the burden of PAH among children and adolescents, along with the varying temporal trends across different countries, highlight the need for flexible health policies that are adapted to the specific contexts of each country and region. In 2021, Ethiopia had the highest ASIR, Haiti had the highest ASMR and ASDR, while India reported the highest cases of incidence, death, and DALYs. Schistosomiasis is a tropical parasitic infection prevalent in over 70 countries, with more than 80% of cases occurring in sub-Saharan Africa. 16 Ethiopia is one of the countries with a particularly high prevalence of schistosomiasis in this region. 17 A study conducted in the Alamata area of northern Ethiopia found a staggering schistosomiasis infection rate of 73.9%. 18 Schistosoma -associated PAH (SchPAH) are a fatal complication of chronic schistosomiasis infection and a major cause of global morbidity and mortality related to PAH. 19 Additionally, the infection rate of schistosomiasis is higher in children than in adults, 20 which may help explain why Ethiopia has the highest ASIR of PAH among children and adolescents. A study conducted in the Blantyre district of Malawi found that children attending schools closer to open water bodies had an increased risk of infection. 21 This suggests that improving sanitation and ensuring access to safe water supplies, as key factors in the control and elimination of schistosomiasis, could help reduce the incidence of PAH. Currently, there is no literature documenting the epidemiology of PAH in children and adolescents in Haiti. Our data show that, in Haiti, the ASMR and ASDR for PAH among children and adolescents are the highest in the world. This can be attributed to several factors, including extreme poverty, a lack of medical resources, inadequate infrastructure, and an underdeveloped public health system. 22 , 23 The absence of timely PAH screening and diagnostic tools leads to many cases remaining undetected until the disease has advanced. Improving healthcare resources and infrastructure in Haiti, along with enhancing the nutrition of children and adolescents, may help reduce the disease burden associated with PAH. There is limited information on patients under the age of 18 in PAH registries from middle and low-income regions. Our study found that India has the highest incidence, mortality, and DALYs cases for PAH in children and adolescents globally. The large population may be the primary contributing factor. Additionally, limited healthcare resources, especially in rural areas, impede timely diagnosis and treatment. Malnutrition, particularly in impoverished regions, further exacerbates the problem. Together, these factors contribute to the significant disease burden in Indian children and adolescents. In light of this, if India implements policies to enhance the diagnosis, treatment, and prevention of PAH in children and adolescents, it would not only benefit the country itself but also provide valuable lessons for other middle- and low-SDI countries facing similar health challenges. Furthermore, as reflected by the EAPC, India showed an overall decreasing trend in the incidence, mortality, and DALYs of PAH in children and adolescents from 1990 to 2021, while Ethiopia and Haiti exhibited rising incidence trends, along with decreasing mortality and DALY trends during the same period. It suggests that Ethiopia and Haiti still face significant challenges in controlling the incidence of PAH in children and adolescents, despite improvements in mortality and DALYs. In addition, although the current burden of PAH in children and adolescents is not the highest in Slovakia and Mauritius, Slovakia has seen the most notable increase in incidence, while Mauritius has experienced the most significant rise in mortality and DALYs from 1990 to 2021. These trends underscore the need for increased investment in PAH prevention to address the growing burden in these countries. Our study found that from 1990 to 2021, the number and ASR of PAH incidence in children and adolescents globally increased, while the number and ASRs of mortality and DALYs declined significantly. This suggests that improvements in regional awareness, diagnostic capabilities, and reporting systems may lead to an increase in incidence, but the reduction in global mortality and DALYs is likely due to advancements in healthcare policies. Our results are consistent with a study on all age groups, which shows a moderate improvement in the global PAH burden over time. 24 This study specifically focused on the pediatric population and shows that in low-income countries like Ethiopia and Haiti, the disease burden remains high. These countries still require increased healthcare resources, and strengthening infrastructure along with improving early screening and treatment capabilities may be key to addressing this challenge. When the overall trend was segmented into multiple periods, we observed a surprising decline in the ASIR of PAH in children and adolescents between 2011 and 2019. However, the change in the ASIR during this period was minimal compared to the peak reached in 2011, with the ASIR in 2019 still substantially higher than in 1990. Additionally, the ASIR began to increase once again after 2019. This highlights the urgent need for measures to reduce the incidence of PAH among children and adolescents. It is noteworthy that between 2010 and 2021, the ASMR and ASDR of PAH in children and adolescents significantly decreased. Another study based on GBD data also showed that over time, the disease burden for PAH across all age groups gradually decreased, with cause-specific mortality improving slowly. 24 Prior to the advent of targeted therapies, a study reported a median survival time of only 0.8 years for children diagnosed with IPAH. 25 A large retrospective registry study in the Netherlands, spanning two periods before and after the introduction of targeted therapies (1991–2006), reported survival for all patients with progressive PAH: 1-, 3-, and 5-year survival rates of 73%, 63%, and 60%, respectively. 15 In the targeted therapy era, the long-term survival rates for children with PAH improved significantly, with 1-, 3-, and 5-year survival rates ranging from 86–96%, 82–85%, and 64–74%, respectively. 26 – 28 These data indicate that targeted therapies have had a significant impact on the survival rates of children with PAH. Sildenafil is the only targeted therapy drug tested in randomized controlled trials for pediatric PAH, and the European Medicines Agency (EMA) approved its use for treating children aged 1–17 with PAH in 2011. This approval aligns with the period when ASMR and ASDR began to decline significantly. Furthermore, the treatment strategy for pediatric PAH is guided by risk stratification. To address this urgent issue, the 2013 World Symposium on Pulmonary Hypertension (WSPH) Paediatric Task Force summarized the risk factors affecting children's prognosis and established low- and high-risk criteria, recommending the use of this model for risk assessment in pediatric patients. 29 It was later modified by the WSPH in 2018 3 . The 2019 updated consensus statement on the diagnosis and treatment of pediatric pulmonary hypertension proposed a risk stratification model and specific scoring methods for pediatric PAH. 30 In conclusion, the application of targeted therapies and the development of risk stratification guidelines have likely contributed to the improvement of the disease burden in children and adolescents with PAH. Summarily, our analysis reveals that after 2019, the ASIR of PAH in children and adolescents increased, while both the ASMR and ASDR showed the most significant decline. Overall, despite the rising incidence, there have been substantial improvements in treatment and management. However, further strengthening prevention and control measures remains essential to reducing the disease burden. The observed correlation between SDI and the burden of PAH in children and adolescents underscores the importance of regional development in shaping disease outcomes. Higher SDI regions tend to exhibit better disease management, including early diagnosis, access to advanced treatments, and robust healthcare systems, which contribute to improved outcomes in terms of both mortality and disability. Conversely, lower SDI regions face significant challenges. It is estimated that approximately 80% of patients with pulmonary hypertension (PH) reside in low- and middle-income countries (LMICs). 28 However, there is limited data on the epidemiology of PH in sub-Saharan Africa. Nevertheless, available evidence suggests that the prevalence and mortality rates of PH in this region may be higher than those observed in Western countries. This disparity can largely be attributed to the high burden of risk factors, such as rheumatic heart disease, schistosomiasis, and human immunodeficiency virus (HIV) infection, which are more prevalent in sub-Saharan Africa. 31 , 32 Furthermore, patients in this region typically present at later stages of the disease (WHO functional classes III and IV), which is a key factor contributing to the significantly higher mortality rates in sub-Saharan Africa. 29 , 30 It is currently recognized that female sex is a risk factor for PAH, yet females generally exhibit better survival rates than males. 33 , 34 Our study found that, within the pediatric and adolescent age groups, the incidence of PAH is higher in females than in males. This aligns with a large study conducted in the United States, which reported a female-to-male ratio of 1.7:1 for pediatric PAH, a phenomenon that may be linked to hormonal factors in children. 26 , 35 Additionally, we were surprised to find that, while females had a lower mortality rate than males in the 0–9 year age group, the opposite was true in the 10–19 year age group, although the exact reasons for this difference remain unclear. Moreover, the increased ASMR and ASDR in the 0–1 year and 15–19 year age groups highlight significant challenges: the higher rates in the 0–1 year group may be related to severe neonatal conditions, while the elevated rates in the 15–19 year group may be influenced by the higher prevalence of autoimmune diseases in females. Quantifying the cross-country inequalities in the disease burden of pediatric PAH across different SDI gradients can reveal patterns of burden distribution and help identify countries where PAH prevention and treatment need to be improved. It is generally believed that in countries with higher SDI, people have greater access to healthcare services, and the performance of healthcare systems is better, which may lead to a lower disease burden. As we expected, the disease burden of pediatric PAH is predominantly concentrated in low-SDI countries. Similarly, research by Babar Hasa et al. has pointed out that, compared to high-income regions, the global prevalence of PAH is significantly higher in middle- and low-income regions (MLRs), especially for PAH associated with untreated congenital heart disease, HIV, or schistosomiasis. 36 Furthermore, in low-SDI countries, the management and prognosis of PAH face numerous challenges, including late diagnosis, comorbidities, a lack of resources and expertise, and limited options for lung transplantation. To alleviate this inequality, low-SDI countries should adopt more targeted policies to optimize the allocation of healthcare resources. First, these countries should invest more in healthcare infrastructure to enhance early diagnosis and treatment capabilities. Second, raising public awareness of pediatric PAH and implementing early screening and interventions are crucial. In addition, international organizations such as the World Health Organization and the United Nations should strengthen their support for low-SDI countries by providing necessary technical assistance and funding to help enhance their disease prevention and control capacities. The projected global burden of PAH in children and adolescents from 2022 to 2050 reveals significant trends with important implications for public health and medical practice. While the ASIR is expected to remain stable globally, the decreasing ASMR and ASDR over time suggest that the management and treatment of PAH in children and adolescents are likely to improve. The stability of the ASIR indicates that the incidence of PAH may not significantly decrease in the coming decades, possibly due to factors such as increased awareness, better diagnostic capabilities, and the continued presence of risk factors like congenital heart disease, HIV, and schistosomiasis in certain regions. However, the sustained decline in ASMR and ASDR reflects advancements in medical interventions, particularly the widespread use of targeted therapies and improvements in clinical management. Overall, early diagnosis, robust healthcare systems, and enhanced treatment protocols play a crucial role in mitigating the severe consequences of PAH, including mortality and disability. However, sustained global efforts are vital to address the underlying causes and risk factors of PAH and to further advance the clinical management of this complex condition. Limitations Several limitations should be noted in this study focusing on children and adolescents with PAH. First, in underdeveloped countries, limited medical resources often contribute to misdiagnosis, underdiagnosis, and missing data, potentially leading to an underestimation of the true burden of PAH in this age group. Second, the raw data input into the GBD is derived from various countries, resulting in inevitable variability in data quality. For instance, heterogeneity in the measurement of PAH may lead to disease misclassification, complicating cross-population comparisons. Fortunately, the GBD collaborators have implemented rigorous data cleaning, adjustments, and advanced statistical modeling techniques, which have significantly mitigated these limitations. However, this introduces another challenge: the findings are heavily dependent on modeled data, particularly at the national level, as only a small number of countries provide actual data. Furthermore, while there is considerable interest in exploring the subtypes of PAH, this remains unattainable with the current GBD database. To address these limitations, increased international collaboration, the widespread adoption of standardized diagnostic criteria, particularly in underdeveloped countries, and the efficient collection of health data from diverse sources, especially at the national level, are essential. Incorporating information on PAH subtypes into data collection processes would further enrich our understanding of the disease and its variations across populations. These efforts would collectively improve the reliability of disease burden estimates and enhance the accuracy of studies based on these data. Despite these limitations, the study demonstrates several notable strengths. By conducting comprehensive and in-depth analyses—including descriptive, trend, health inequality, and predictive investigations—it has significantly enriched our understanding of PAH epidemiology in children and adolescents. This research provides a solid foundation for the development of targeted public health policies and the equitable allocation of medical resources worldwide. Conclusions In summary, PAH in children and adolescents poses a significant global public health challenge, with marked differences in incidence, mortality, and DALYs observed across countries. Between 1990 and 2021, the incidence of PAH has increased globally, while mortality and DALYs have shown an overall decline, particularly in the last decade. Countries with low SDI continue to face a disproportionately heavy burden, underscoring the pressing need for targeted interventions in these regions. Moreover, variations in disease burden by gender and age emphasize the necessity of developing prevention and treatment strategies that address the specific needs of these groups. To tackle these issues, global health policymakers should focus on tailored and flexible solutions that improve healthcare systems and address the unique medical needs of different countries. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author Contribution T.M.Y. and Z.J.Y. are considered co–first authors. T.M.Y. and Z.J.Y. designed and analyzed the research study; Z.J.Y., and W.J. collected the data; Z.J.Y., and W.J. validation and visualization the data. T.M.Y. and H.S.P wrote and revised the manuscript. All authors have read and approved the manuscript. Acknowledgements This study was funded by the Zhejiang Provincial Medical and Health Science and Technology Program (2025KY1169), the Zhejiang Provincial Traditional Chinese Medicine Science and Technology Program (2025ZR175). We acknowledge the Institute for Health Metrics and Evaluation (University of Washington), the GBD Collaborators, and all staff who provided the data necessary for this study. The opinions expressed here are those of the authors and do not necessarily represent the official position of the organizations with which they are affiliated. Data Availability The data from this study can be accessed openly through the GBD 2021 online database, as outlined in the Methods section. References Lai YC, Potoka KC, Champion HC, Mora AL, Gladwin MT. Pulmonary arterial hypertension: the clinical syndrome. Circ Res. 2014;115(1):115–30. Barst RJ, Ertel SI, Beghetti M, Ivy DD. Pulmonary arterial hypertension: a comparison between children and adults. Eur Respir J. 2011;37(3):665–77. Rosenzweig EB, Abman SH, Adatia I et al. Paediatric pulmonary arterial hypertension: updates on definition, classification, diagnostics and management. Eur Respir J 2019;53(1). Li L, Jick S, Breitenstein S, Hernandez G, Michel A, Vizcaya D. Pulmonary arterial hypertension in the USA: an epidemiological study in a large insured pediatric population. Pulm Circ. 2017;7(1):126–36. Kwiatkowska J, Zuk M, Migdal A et al. Children and Adolescents with Pulmonary Arterial Hypertension: Baseline and Follow-Up Data from the Polish Registry of Pulmonary Hypertension (BNP-PL). J Clin Med 2020;9(6). Ezekian JE, Hill KD. Management of Pulmonary Arterial Hypertension in the Pediatric Patient. Curr Cardiol Rep. 2019;21(12):162. Gu S, Hu H, Dong H. Systematic Review of the Economic Burden of Pulmonary Arterial Hypertension. PharmacoEconomics. 2016;34(6):533–50. Diseases GBD, Injuries C. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403(10440):2133–61. Murray CJL, Collaborators GBD. Findings from the Global Burden of Disease Study 2021. Lancet. 2024;403(10440):2259–62. White RG, Rao JP. Towards improving the quality and usefulness of GBD tuberculosis estimates. Lancet Infect Dis. 2024;24(7):667–8. Collaborators GBDNSD. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol. 2024;23(4):344–81. Knoll M, Furkel J, Debus J, Abdollahi A, Karch A, Stock C. An R package for an integrated evaluation of statistical approaches to cancer incidence projection. BMC Med Res Methodol. 2020;20(1):257. Riebler A, Held L. Projecting the future burden of cancer: Bayesian age-period-cohort analysis with integrated nested Laplace approximations. Biom J. 2017;59(3):531–49. Constantine A, Dimopoulos K, Haworth SG, Muthurangu V, Moledina S. Twenty-Year Experience and Outcomes in a National Pediatric Pulmonary Hypertension Service. Am J Respir Crit Care Med. 2022;206(6):758–66. van Loon RL, Roofthooft MT, Hillege HL, et al. Pediatric pulmonary hypertension in the Netherlands: epidemiology and characterization during the period 1991 to 2005. Circulation. 2011;124(16):1755–64. McManus DP, Dunne DW, Sacko M, Utzinger J, Vennervald BJ, Zhou XN. Schistosomiasis. Nat Rev Dis Primers. 2018;4(1):13. Adenowo AF, Oyinloye BE, Ogunyinka BI, Kappo AP. Impact of human schistosomiasis in sub-Saharan Africa. Braz J Infect Dis. 2015;19(2):196–205. Abebe N, Erko B, Medhin G, Berhe N. Clinico-epidemiological study of Schistosomiasis mansoni in Waja-Timuga, District of Alamata, northern Ethiopia. Parasit Vectors. 2014;7:158. Graham BB, Bandeira AP, Morrell NW, Butrous G, Tuder RM. Schistosomiasis-associated pulmonary hypertension: pulmonary vascular disease: the global perspective. Chest. 2010;137(6 Suppl):S20–9. Gryseels B, Polman K, Clerinx J, Kestens L. Human schistosomiasis. Lancet. 2006;368(9541):1106–18. Kapito-Tembo AP, Mwapasa V, Meshnick SR, et al. Prevalence distribution and risk factors for Schistosoma hematobium infection among school children in Blantyre, Malawi. PLoS Negl Trop Dis. 2009;3(1):e361. Taylor L. Haiti's hospitals plan to close amid fuel shortages. BMJ. 2022;379:o2379. Taylor L. Haiti: Hospitals burn to ground as violence rages. BMJ. 2024;384:q663. Collaborators GBDPAH. Global, regional, and national burden of pulmonary arterial hypertension, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Respir Med 2024. D'Alonzo GE, Barst RJ, Ayres SM, et al. Survival in patients with primary pulmonary hypertension. Results from a national prospective registry. Ann Intern Med. 1991;115(5):343–9. Barst RJ, McGoon MD, Elliott CG, Foreman AJ, Miller DP, Ivy DD. Survival in childhood pulmonary arterial hypertension: insights from the registry to evaluate early and long-term pulmonary arterial hypertension disease management. Circulation. 2012;125(1):113–22. del Cerro Marin MJ, Sabate Rotes A, Rodriguez Ogando A, et al. Assessing pulmonary hypertensive vascular disease in childhood. Data from the Spanish registry. Am J Respir Crit Care Med. 2014;190(12):1421–9. Fraisse A, Jais X, Schleich JM, et al. Characteristics and prospective 2-year follow-up of children with pulmonary arterial hypertension in France. Arch Cardiovasc Dis. 2010;103(2):66–74. Ivy DD, Abman SH, Barst RJ, et al. Pediatric pulmonary hypertension. J Am Coll Cardiol. 2013;62(25 Suppl):D117–126. Hansmann G, Koestenberger M, Alastalo TP, et al. 2019 updated consensus statement on the diagnosis and treatment of pediatric pulmonary hypertension: The European Pediatric Pulmonary Vascular Disease Network (EPPVDN), endorsed by AEPC, ESPR and ISHLT. J Heart Lung Transpl. 2019;38(9):879–901. Mocumbi AO, Thienemann F, Sliwa K. A global perspective on the epidemiology of pulmonary hypertension. Can J Cardiol. 2015;31(4):375–81. Thienemann F, Dzudie A, Mocumbi AO, et al. The causes, treatment, and outcome of pulmonary hypertension in Africa: Insights from the Pan African Pulmonary Hypertension Cohort (PAPUCO) Registry. Int J Cardiol. 2016;221:205–11. Hoeper MM, Humbert M, Souza R, et al. A global view of pulmonary hypertension. Lancet Respir Med. 2016;4(4):306–22. D'Agostino A, Guindani P, Scaglione G, et al. Sex- and Gender-Related Aspects in Pulmonary Hypertension. Heart Fail Clin. 2023;19(1):11–24. Mair KM, Wright AF, Duggan N, et al. Sex-dependent influence of endogenous estrogen in pulmonary hypertension. Am J Respir Crit Care Med. 2014;190(4):456–67. Hasan B, Hansmann G, Budts W, et al. Challenges and Special Aspects of Pulmonary Hypertension in Middle- to Low-Income Regions: JACC State-of-the-Art Review. J Am Coll Cardiol. 2020;75(19):2463–77. Additional Declarations No competing interests reported. Supplementary Files supplement.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5827730","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":402437216,"identity":"4cfc33ff-9156-4d00-9a02-9688d5ddbf12","order_by":0,"name":"Mengyun Tu","email":"","orcid":"","institution":"Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mengyun","middleName":"","lastName":"Tu","suffix":""},{"id":402437217,"identity":"a1d98beb-001c-4b5b-8c38-6e5bb7cb600b","order_by":1,"name":"Jieyang Zhu","email":"","orcid":"","institution":"The First Hospital of Jiaxing","correspondingAuthor":false,"prefix":"","firstName":"Jieyang","middleName":"","lastName":"Zhu","suffix":""},{"id":402437218,"identity":"fe90bfb7-10a1-4225-a6c9-452b46d89c4e","order_by":2,"name":"Jie Weng","email":"","orcid":"","institution":"Yuying Children's Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Weng","suffix":""},{"id":402437219,"identity":"4185880f-40b8-4daf-9e86-905b8791765b","order_by":3,"name":"Zhiyi Wang","email":"","orcid":"","institution":"Yuying Children's Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhiyi","middleName":"","lastName":"Wang","suffix":""},{"id":402437220,"identity":"9867a588-6c0c-4c34-b101-84849f84dab8","order_by":4,"name":"Sipin Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACAwhlA8TMDQwMB4jXksbAwMZImpbDJGgxl8gxk/y547ycwf3GxgcfzjDI84sR0Gc5I8dMmvfMbWODY4zNhjNuMBjOnJ1AwGE3gFoY224nbjjG2CbN84EhweA2EVokf7adI1GLBG/bAaiWG8RoOfOs2Jr3TLKx5LFEoF/OSBDhl+PJG2/+3GEnx3f48MEHH47ZyPNLE9ACBqAYgQIJIpSjaRkFo2AUjIJRgAkAjRFGeAkKsGYAAAAASUVORK5CYII=","orcid":"","institution":"The Second Clinical Medical College of Zhejiang Chinese Medical University","correspondingAuthor":true,"prefix":"","firstName":"Sipin","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2025-01-14 14:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5827730/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5827730/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74282821,"identity":"689481c4-8f97-427f-85b2-82ed07b26e8a","added_by":"auto","created_at":"2025-01-20 15:52:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":8505647,"visible":true,"origin":"","legend":"\u003cp\u003e(A) The ASIR in 2021; (B) The trend in ASIR (EAPC) from 1990 to 2021; (C) The ASMR in 2021; (D) The trend in ASMR (EAPC) from 1990 to 2021; (E) The ASDR in 2021; (F) The trend in ASDR (EAPC) from 1990 to 2021; of PAH among children and adolescents worldwide.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASDR, age-standardized DALYs rate; EAPC, estimated annual percentage change; DALYs, disability-adjusted life-years; PAH, pulmonary arterial hypertension.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5827730/v1/e6858040ef2dd67836fec9a3.png"},{"id":74282818,"identity":"53ce80b2-8f56-472e-bf29-bf637cb2eca1","added_by":"auto","created_at":"2025-01-20 15:52:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1380630,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal trends in ASRs of PAH among children and adolescents from 1990 to\u0026nbsp;2021.\u0026nbsp;(A) ASIR. (B) ASMR. (C) ASDR.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASDR, age-standardized DALYs rate; AAPC, average annual percent change; APC, annual percent change; DALYs, disability-adjusted life years; PAH, pulmonary arterial hypertension.\u0026nbsp;\u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026nbsp;\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5827730/v1/f0450fc66891f49b3b9cbacf.png"},{"id":74282820,"identity":"464988b7-2e09-4856-afe2-62de3c2d20e2","added_by":"auto","created_at":"2025-01-20 15:52:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3640802,"visible":true,"origin":"","legend":"\u003cp\u003eThe inequality slope index and concentration index for DALYs of PAH among children and adolescents worldwide in 1990 and 2021. (A) the inequality slope index; (B) the concentration index.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ASDR, age-standardized DALYs rate; DALYs, disability-adjusted life years; PAH, pulmonary arterial hypertension; SII: slope index of inequality; CI: concentration index.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5827730/v1/5d060bfc48fa1129dcbf1e73.png"},{"id":74282823,"identity":"60e39007-3830-4109-bd8f-30f1a947241a","added_by":"auto","created_at":"2025-01-20 15:52:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1487354,"visible":true,"origin":"","legend":"\u003cp\u003eFuture forecasts of global burden of PAH among children and adolescents. (A) The predicted ASIR to 2050; (B) The predicted ASMR to 2050; (C) The predicted ASDR to 2050; of PAH globally.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASDR, age-standardized DALYs rate; DALYs, disability-adjusted life years; PAH, pulmonary arterial hypertension.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5827730/v1/e512fb100a2f69598b1eb843.png"},{"id":74828774,"identity":"44fe858a-65c8-4fa3-9018-5d45db4d21cb","added_by":"auto","created_at":"2025-01-27 10:09:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14572421,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5827730/v1/ac8825a9-3bbd-477f-9631-cff1aeb02c04.pdf"},{"id":74282822,"identity":"d9023df3-ff4f-498f-9e28-c272d01f8232","added_by":"auto","created_at":"2025-01-20 15:52:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1650601,"visible":true,"origin":"","legend":"","description":"","filename":"supplement.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5827730/v1/97ad623fa62adf3bf4353e47.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global, Regional, and National Burden of Pulmonary Arterial Hypertension in Children and Adolescents, 1990-2021, and Projections to 2050: A Systematic Analysis for the Global Burden of Disease Study 2021","fulltext":[{"header":"Background","content":"\u003cp\u003ePulmonary arterial hypertension (PAH) is a progressive condition affecting the pulmonary vasculature, characterized by increased pulmonary arterial pressure and vascular resistance, ultimately leading to right heart failure.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Although PAH may present at any age from infancy to adulthood, when it manifests in children and adolescents, it becomes particularly complex and challenging.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Pediatric PAH often involves unique etiologies such as congenital heart disease or genetic predispositions, making its early diagnosis and intervention critical for improving outcomes and quality of life.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAn epidemiological study conducted in a large insured pediatric population found that between 2010 and 2013, the annual incidence of PAH ranged from 4.8 to 8.1 cases per 1,000,000 child-years, while the annual prevalence ranged from 25.7 to 32.6 cases per 1,000,000 children.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e A study from the Polish Registry of Pulmonary Hypertension reported the estimated incidence rate was 2.4 per million children/year, and the mean prevalence of PAH was 11.6 per million.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Overall, PAH is a rare disease, particularly in children and adolescents. Although targeted therapies for PAH have been developed and have contributed to improved morbidity and mortality, persistent disability and the continued high healthcare costs remain ongoing challenges for patients and healthcare systems.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Most available data are derived from national or regional registries, comprehensive global studies specifically targeting the epidemiology of PAH in children and adolescents remain limited. Beyond incidence, prevalence, and mortality, there has been almost no assessment of the disease burden in this population.\u003c/p\u003e \u003cp\u003eExisting epidemiological studies on PAH based on the Global Burden of Disease (GBD) database mainly focus on the general population, largely neglecting children and adolescents as a distinct subgroup. In-depth investigation of the epidemiological trends of PAH in this age group is crucial for understanding the disease burden and assessing the feasibility of health goals. Therefore, a comprehensive global compilation of incidence, mortality, and disability-adjusted life years (DALYs) data in children and adolescents is urgently needed. Our study analyzed the global trends in incidence, mortality, and DALYs of PAH in children and adolescents using the GBD database, highlighting regional disparities in disease burden. This will inform early screening efforts and guide healthcare policies and resource allocation. Additionally, health inequality analysis was used to emphasize variations in disease burden across different socio-demographic index (SDI) regions, promoting targeted interventions The Bayesian Age-Period-Cohort (BAPC) model was applied to predict future trends, providing insights for policymakers and healthcare providers. These approaches aim to improve global health outcomes for children and adolescents with PAH.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData acquisition\u003c/h2\u003e \u003cp\u003eThe GBD 2021 utilized updated epidemiological evidence and refined methods to offer a comprehensive analysis of health loss across 371 distinct diseases, injuries, and impairments, as well as 88 risk factors by age and sex for 204 countries and territories.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The GBD incorporated diverse data sources, each uniquely identified and made available through the Global Health Data Exchange (GHDx). The gathered data were processed using spatiotemporal Gaussian process regression to allow for smoothing over age, time and location in locations lacking complete datasets. The Meta-Regression with Bayesian priors, Regularisation, and Trimming (MR-BRT) program was employed to adjust data bias due to variable case definitions and study protocols across countries. Comprehensive details regarding the study design and methodologies of GBD research have been thoroughly documented in the existing GBD literature.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e In this study, estimates and their 95% uncertainty intervals (UIs) for the incidence, mortality, and DALYs associated with PAH among children and adolescents were obtained from GBD 2021. All rates were presented per 100,000 individuals. Additionally, the SDI was employed to reflect a composite measure encompassing income, education, and fertility, thereby quantifying the level of sociodemographic development in a given country or region. The SDI categorizes development into five quintiles: low, low-middle, middle, high-middle, and high. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthics\u003c/h3\u003e\n\u003cp\u003e The institutional review board of Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University determined that ethical approval was not required for this study, as it involved only data analysis without any identifiable personal information.\u003c/p\u003e\n\u003ch3\u003eDescriptive analysis\u003c/h3\u003e\n\u003cp\u003eTo comprehensively assess the burden of PAH in children and adolescents, a descriptive analysis was conducted at global, regional, and national levels. The global case numbers and age-standardized rates (ASRs) for incidence, mortality, and DALYs related to PAH in both sexes from 1990 to 2021 were visually represented. Furthermore, the case number and ASR for incidence, mortality, and DALYs in 1990 and 2021 were compared across global, regional, and national levels, as well as across five SDI quintiles.\u003c/p\u003e\n\u003ch3\u003eTrend analysis\u003c/h3\u003e\n\u003cp\u003eExploring temporal trends in diseases is a vital component of epidemiology, as it aids in developing targeted preventive strategies. This study aimed to investigate the trends of PAH in children and adolescents from the overall and local scopes. Firstly, we used estimated annual percentage change (EAPC) to quantify the overall trend. The evolving disease burden was assessed using a statistical model to estimate EAPCs, calculated based on ASRs using the formula: y\u0026thinsp;=\u0026thinsp;α\u0026thinsp;+\u0026thinsp;βx, where x represents the calendar year and y represents the natural logarithm of the ASRs. The EAPC was then calculated as 100 \u0026times; [exp(β)\u0026ndash;1], indicating the annual percentage change. The linear regression model was also used to determine the 95% confidence interval (CI) for the EAPC. An increasing trend in ASR was identified if both the EAPC and the lower boundary of its 95% CI were greater than zero. Conversely, if both the EAPC estimate and the upper boundary of the 95% CI were less than zero, the ASR was deemed to show a decreasing trend. If neither condition was met, the ASR was classified as stable.\u003c/p\u003e \u003cp\u003e Next, we employed Joinpoint regression analysis to examine local trends in the PAH burden among children and adolescents. Joinpoint regression analysis (Joinpoint Trend Analysis Software, 2022) identifies inflection points to segment the overall trend into multiple distinct segments, allowing for the evaluation of each subtrend by estimating the annual percentage change (APC) and its 95% CI. The Monte Carlo permutation method, using 4,499 randomly generated datasets, was employed to determine the average annual percentage change (AAPC) and its 95% CI, and the overall significance level was maintained through a Bon ferroni correction. An increasing trend during a specific period was recognized if both the APC/AAPC estimate and the lower bound of the 95% CI were greater than zero. Conversely, a decreasing trend was indicated if both the APC/AAPC estimate and the upper bound of the 95% CI were less than zero. If neither condition was satisfied, the trend was classified as stable.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis of PAH burden and SDI relationship\u003c/h3\u003e\n\u003cp\u003eSmoothing splines models were used to examine the relationship between the burdens of PAH among children and adolescents and SDI across 21 regions. Expected values were determined through a calculation that takes into account the SDI and disease rates across all locations. The Locally Weighted Scatterplot Smoothing (LOWESS) method was applied to fit smooth splines, automatically adjusting the degree, number, and placement of knots based on the data characteristics and span parameter. Additionally, Spearman correlation analysis was conducted to estimate the correlation coefficients (R) and \u003cem\u003eP\u003c/em\u003e values, identifying the association between ASR and SDI. All \u003cem\u003eP\u003c/em\u003e values were 2-sided, and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCross-country inequality analysis\u003c/h2\u003e \u003cp\u003eTo evaluate health inequalities in the burden of PAH among children and adolescents, we utilized two standard metrics: the slope index of inequality (SII) and the concentration index (CI), which measure absolute and relative gradient inequalities in health, respectively. The SII was derived through regression analysis, relating a country's DALY rates to its SDI relative position, defined by the population's midpoint in a cumulative distribution ranked by SDI. To account for heteroscedasticity, we used robust linear regression models. The CI was calculated by numerically integrating the area under the Lorenz curve, which aligns the cumulative proportion of DALYs with the population's cumulative distribution sorted by SDI. Together, these metrics offer a thorough understanding of how the PAH burden is unevenly distributed across different socioeconomic groups, supporting the development of targeted public health interventions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePredictive analysis\u003c/h3\u003e\n\u003cp\u003eIn this study, we applied a BAPC model with integrated nested Laplace approximation (INLA) to project future trends in the burden of PAH among children and adolescents. Previous studies have demonstrated that the BAPC model, when combined with INLA, provides enhanced coverage and precision compared to alternative predictive methods.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e The analysis was conducted using the World Health Organization's Health Equity Assessment Toolkit and R statistical software (Version 4.2.2).\u003c/p\u003e\n\u003ch3\u003eRole of the funding source\u003c/h3\u003e\n\u003cp\u003eThe funder had no role in study design, data collection, data analysis, data interpretation, and writing of the manuscript. All authors had full access to the dataset. The corresponding authors had final responsibility for the decision to submit for publication.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eDescriptive analysis of PAH burden among children and adolescents at global, regional, and national levels\u003c/h2\u003e\n \u003cp\u003eGlobally, from 1990 to 2021, both PAH incidence cases and age-standardized incidence rate (ASIR) among children and adolescents showed an increasing trend, while the death cases, DALYs cases, age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR) exhibited a sharp decline (eFigure 1).\u003c/p\u003e\n \u003cp\u003eThe case numbers and ASR of PAH incidence, mortality, and DALYs among children and adolescents in 1990 and 2021 were presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, eTable 1\u0026ndash;5, respectively. Based on SDI quintiles, the low-middle SDI quintile had the highest number of incidence, death, and DALYs cases for children and adolescents in 2021. Regarding ASR, the highest ASIR, ASMR, and ASDR were observed in the low SDI quintile (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 1\u0026ndash;2). Regionally, South Asia had the highest number of PAH incidence, death, and DALYs cases among children and adolescents. Eastern Sub-Saharan Africa had the highest ASIR, whereas the Caribbean had the highest ASMR and ASDR (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 1\u0026ndash;2). Nationally, the incidence, mortality, and DALYs of PAH among children and adolescents varied remarkably across the world, with the highest number of incidence, death, and DALYs cases found in India, the highest ASIR in Ethiopia, and the highest ASMR and ASDR in Haiti (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 3\u0026ndash;5).\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe number of PAH incidence and ASIR in 1990 and 2021 among children and adolescents by SDI quintiles and by GBD regions, with EAPC from 1990 to 2021.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eEAPC\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003cp\u003e1990\u0026ndash;2021\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003cp\u003e(95% Uls)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eASIR\u003c/p\u003e\n \u003cp\u003e(95% Uls)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003cp\u003e(95% Uls)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eASIR\u003c/p\u003e\n \u003cp\u003e(95% Uls)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlobal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4134.613\u003c/p\u003e\n \u003cp\u003e(2977.157 to 5628.527)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003cp\u003e(0.049 to 0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5049.038\u003c/p\u003e\n \u003cp\u003e(3617.783 to 6916.409)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003cp\u003e(0.051 to 0.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003cp\u003e(0.1 to 0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDI quintiles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e313.631\u003c/p\u003e\n \u003cp\u003e(225.446 to 432.465)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003cp\u003e(0.033 to 0.064)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e287.222\u003c/p\u003e\n \u003cp\u003e(205.089 to 396.145)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003cp\u003e(0.033 to 0.063)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003cp\u003e(-0.09 to\u003c/p\u003e\n \u003cp\u003e-0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh-middle SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e544.722\u003c/p\u003e\n \u003cp\u003e(392.803 to 745.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003cp\u003e(0.039 to 0.074)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e456.162\u003c/p\u003e\n \u003cp\u003e(328.209 to 626.834)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003cp\u003e(0.04 to 0.076)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e(-0.06 to 0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1330.267\u003c/p\u003e\n \u003cp\u003e(952.547 to 1823.591)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003cp\u003e(0.046 to 0.088)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1319.595\u003c/p\u003e\n \u003cp\u003e(941.263 to 1822.487)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003cp\u003e(0.046 to 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003cp\u003e(0.04 to 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow-middle SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1173.614\u003c/p\u003e\n \u003cp\u003e(843.609 to 1593.683)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003cp\u003e(0.053 to 0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1530.818\u003c/p\u003e\n \u003cp\u003e(1090.566 to 2106.016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003cp\u003e(0.053 to 0.102)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003cp\u003e(-0.13 to\u003c/p\u003e\n \u003cp\u003e-0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow SDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e769.182\u003c/p\u003e\n \u003cp\u003e(555.867 to 1037.897)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003cp\u003e(0.074 to 0.137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1451.571\u003c/p\u003e\n \u003cp\u003e(1043.958 to 1978.087)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003cp\u003e(0.066 to 0.125)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003cp\u003e(-0.41 to\u003c/p\u003e\n \u003cp\u003e-0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGBD regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAndean Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.897\u003c/p\u003e\n \u003cp\u003e(24.998 to 47.347)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003cp\u003e(0.049 to 0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.352\u003c/p\u003e\n \u003cp\u003e(31.752 to 60.393)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003cp\u003e(0.05 to 0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003cp\u003e(0.04 to 0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAustralasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.584\u003c/p\u003e\n \u003cp\u003e(5.386 to 10.358)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003cp\u003e(0.032 to 0.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.494\u003c/p\u003e\n \u003cp\u003e(6.751 to 12.994)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003cp\u003e(0.033 to 0.064)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003cp\u003e(0.1 to 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaribbean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.186\u003c/p\u003e\n \u003cp\u003e(16.706 to 31.456)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003cp\u003e(0.041 to 0.077)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.445\u003c/p\u003e\n \u003cp\u003e(18.063 to 34.797)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003cp\u003e(0.044 to 0.084)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003cp\u003e(0.25 to 0.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Asia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.961\u003c/p\u003e\n \u003cp\u003e(33.562 to 60.475)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003cp\u003e(0.039 to 0.071)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.473\u003c/p\u003e\n \u003cp\u003e(38.136 to 70.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003cp\u003e(0.041 to 0.075)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003cp\u003e(-0.01 to 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Europe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.891\u003c/p\u003e\n \u003cp\u003e(39.855 to 74.191)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003cp\u003e(0.038 to 0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.21\u003c/p\u003e\n \u003cp\u003e(26.23 to 49.162)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003cp\u003e(0.041 to 0.077)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003cp\u003e(0.19 to 0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154.497\u003c/p\u003e\n \u003cp\u003e(111.187 to 209.731)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003cp\u003e(0.05 to 0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145.432\u003c/p\u003e\n \u003cp\u003e(103.788 to 201.128)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003cp\u003e(0.045 to 0.087)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003cp\u003e(-0.25 to\u003c/p\u003e\n \u003cp\u003e-0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Sub-Saharan Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.966\u003c/p\u003e\n \u003cp\u003e(62.557 to 114.186)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003cp\u003e(0.075 to 0.136)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e205.079\u003c/p\u003e\n \u003cp\u003e(148.853 to 277.938)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003cp\u003e(0.075 to 0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003cp\u003e(0.05 to 0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEast Asia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e743.664\u003c/p\u003e\n \u003cp\u003e(533.853 to 1022.494)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003cp\u003e(0.043 to 0.082)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e545.747\u003c/p\u003e\n \u003cp\u003e(390.684 to 747.165)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003cp\u003e(0.042 to 0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003cp\u003e(-0.11 to\u003c/p\u003e\n \u003cp\u003e-0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEastern Europe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.38\u003c/p\u003e\n \u003cp\u003e(67.468 to 124.753)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003cp\u003e(0.037 to 0.069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.786\u003c/p\u003e\n \u003cp\u003e(48.71 to 92.837)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003cp\u003e(0.039 to 0.074)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003cp\u003e(-0.04 to 0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEastern Sub-Saharan Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e375.472\u003c/p\u003e\n \u003cp\u003e(272.584 to 505.972)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003cp\u003e(0.091 to 0.169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e707.212\u003c/p\u003e\n \u003cp\u003e(510.62 to 967.412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003cp\u003e(0.083 to 0.157)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003cp\u003e(-0.22 to\u003c/p\u003e\n \u003cp\u003e-0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh-income Asia Pacific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.417\u003c/p\u003e\n \u003cp\u003e(41.288 to 81.304)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003cp\u003e(0.03 to 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.875\u003c/p\u003e\n \u003cp\u003e(26.184 to 51.212)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003cp\u003e(0.031 to 0.062)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003cp\u003e(0.1 to 0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh-income North America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.052\u003c/p\u003e\n \u003cp\u003e(52.994 to 101.275)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003cp\u003e(0.024 to 0.046)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.657\u003c/p\u003e\n \u003cp\u003e(62.699 to 123.589)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003cp\u003e(0.026 to 0.051)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003cp\u003e(0.23 to 0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNorth Africa and Middle East\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e320.493\u003c/p\u003e\n \u003cp\u003e(228.945 to 431.444)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003cp\u003e(0.048 to 0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e403.303\u003c/p\u003e\n \u003cp\u003e(289.881 to 548.869)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003cp\u003e(0.045 to 0.086)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.38\u003c/p\u003e\n \u003cp\u003e(-0.51 to\u003c/p\u003e\n \u003cp\u003e-0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOceania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.23\u003c/p\u003e\n \u003cp\u003e(4.474 to 8.423)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003cp\u003e(0.049 to 0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.433\u003c/p\u003e\n \u003cp\u003e(8.875 to 16.953)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003cp\u003e(0.051 to 0.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003cp\u003e(-0.11 to 0.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouth Asia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1002.74\u003c/p\u003e\n \u003cp\u003e(719.182 to 1363.277)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003cp\u003e(0.049 to 0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1288.985\u003c/p\u003e\n \u003cp\u003e(916.617 to 1786.641)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003cp\u003e(0.05 to 0.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003cp\u003e(-0.06 to 0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoutheast Asia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e382.607\u003c/p\u003e\n \u003cp\u003e(273.676 to 524.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003cp\u003e(0.046 to 0.088)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e431.585\u003c/p\u003e\n \u003cp\u003e(309.223 to 596.082)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003cp\u003e(0.05 to 0.096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e(0.17 to 0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouthern Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.09\u003c/p\u003e\n \u003cp\u003e(16.658 to 30.962)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003cp\u003e(0.032 to 0.059)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.089\u003c/p\u003e\n \u003cp\u003e(16.326 to 31.934)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003cp\u003e(0.031 to 0.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003cp\u003e(0 to 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouthern Sub-Saharan Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.084\u003c/p\u003e\n \u003cp\u003e(50.318 to 97.119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003cp\u003e(0.07 to 0.136)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.068\u003c/p\u003e\n \u003cp\u003e(55.133 to 106.385)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003cp\u003e(0.065 to 0.126)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003cp\u003e(-0.17 to 0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTropical Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111.311\u003c/p\u003e\n \u003cp\u003e(79.064 to 153.338)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003cp\u003e(0.042 to 0.082)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106.622\u003c/p\u003e\n \u003cp\u003e(76.356 to 145.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003cp\u003e(0.042 to 0.081)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003cp\u003e(-0.11 to 0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWestern Europe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154.248\u003c/p\u003e\n \u003cp\u003e(110.236 to 213.644)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003cp\u003e(0.041 to 0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135.124\u003c/p\u003e\n \u003cp\u003e(96.799 to 185.615)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003cp\u003e(0.039 to 0.075)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003cp\u003e(-0.28 to\u003c/p\u003e\n \u003cp\u003e-0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWestern Sub-Saharan Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e312.844\u003c/p\u003e\n \u003cp\u003e(227.171 to 419.572)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003cp\u003e(0.078 to 0.144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e606.067\u003c/p\u003e\n \u003cp\u003e(437.241 to 818.474)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003cp\u003e(0.06 to 0.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.12\u003c/p\u003e\n \u003cp\u003e(-1.23 to\u003c/p\u003e\n \u003cp\u003e-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviations: ASIR, age-standardized incidence rate; PAH, pulmonary arterial hypertension; SDI, socio-demographic index; EAPC, estimated annual percentage change; UIs, uncertainty intervals; CI, confidence interval.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eOverall trends in PAH burden among children and adolescents using broad estimation method\u003c/h2\u003e\n \u003cp\u003eGlobally, the ASIR of PAH among children and adolescents increased by an average of 0.13% (95% CI: 0.10\u0026ndash;0.17) per year from 1990 to 2021, while the ASMR and ASDR decreased by an average of 2.49% (95% CI: -2.68 to -2.30) and 2.53% (95% CI: -2.72 to -2.33) per year, respectively (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 1\u0026ndash;2). In terms of SDI quintiles, the ASIR increased in the middle SDI quintile, decreased in the low, low-middle, and high SDI quintiles, and remained stable in the high-middle SDI quintile from 1990 to 2021. Additionally, the ASMR and ASDR showed a decreasing trend across all five SDI quintiles, with the most significant reductions observed in the high-middle SDI quintile (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 1\u0026ndash;2). Regionally, the most significant increase in ASIR among children and adolescents was observed in the Caribbean, whereas the greatest decrease occurred in Western Sub-Saharan Africa. The ASMR and ASDR increased in Oceania and Southern Sub-Saharan Africa but decreased in other regions, with the most notable reduction in the ASMR observed in Eastern Europe, and the largest decline in the ASDR seen in Southern Latin America (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 1\u0026ndash;2). Nationally, trends in the disease burden of PAH among children and adolescents varied significantly across the 204 countries and territories (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; eTable 3\u0026ndash;5). Slovakia had the highest EAPC of incidence, while Burkina Faso had the lowest. Mauritius had the highest EAPCs for both mortality and DALYs, whereas Puerto Rico had the lowest.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eLocal trends in PAH burden among children and adolescents using joinpoint regression analysis\u003c/h2\u003e\n \u003cp\u003eThe results of the joinpoint regression analysis for the burden of PAH among children and adolescents across different metrics are shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Between 1990 and 2021, the ASIR among children and adolescents showed an overall increasing trend, with an AAPC of 0.15 (95% CI: 0.13\u0026ndash;0.17), though trends varied over time (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). Specifically, there was a significant increase from 1990 to 2000, followed by a slower rise from 2000 to 2011. The trend then began to decline from 2011 to 2016, with a notable decrease from 2016 to 2019, before slightly increasing again from 2019 to 2021. In contrast, the ASMR demonstrated a consistent decreasing trend, with an AAPC of -3.04 (95% CI: -3.13 to -2.94), and the steepest decline observed between 2019 and 2021 (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). Similarly, the ASDR showed a significant decline throughout the study period, with an AAPC of -3.08 (95% CI: -3.18 to -2.98), with the sharpest reduction occurring from 2019 to 2021 (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). These results highlight distinct trends in the ASIR, ASMR, and ASDR among children and adolescents: the ASIR generally increased, while the ASMR and ASDR consistently decreased.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cstrong\u003eThe correlation between PAH burden and SDI in children and adolescents\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eThe SDI, a comprehensive metric for evaluating regional development levels, was closely linked to population health. At the regional level, the ASIR, ASMR, and ASDR of PAH in children and adolescents decreased exponentially with rising SDI (eFigure 2A-C). Negative correlations were observed between SDI and ASIR (R = -0.82, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ASMR (R = -0.46, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ASDR (R = -0.47, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively. Eastern Sub-Saharan Africa, Central Sub-Saharan Africa and Southern Sub-Saharan Africa had higher-than-expected ASIR of PAH based on their SDIs. Similarly, North Africa and Middle East and Caribbean had higher-than-expected ASMR and ASDR of PAH based on their SDIs. Despite having the highest ASIR, low SDI regions showed a significant decline in ASIR from 1990 to 2021. Additionally, all SDI regions experienced substantial reductions in ASMR and ASDR over the same period (eFigure 1 D-F).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eAge and sex patterns\u003c/h2\u003e\n \u003cp\u003eIn 2021, the ASIR of PAH in children and adolescents showed an increase with age in the 0\u0026ndash;4 year age group. However, in the 5\u0026ndash;19 year age group, the ASIR remained relatively consistent across ages. For the 0\u0026ndash;6 days and 7\u0026ndash;27 days age groups, the ASIR ratios between males and females were similar; however, with advancing age, the ASIR was consistently higher in females compared to males within the same age group (eFigure 3A). Regarding both the ASMR and ASDR in children and adolescents, the 0\u0026ndash;1 year and 15\u0026ndash;19 year age groups exhibited higher rates. In the 0\u0026ndash;9 year group, males had higher ASMR and ASDR than females, whereas in the 10\u0026ndash;19 year group, females had higher ASMR and ASDR than males (eFigure 3B-C).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eCross-country inequality analysis\u003c/h2\u003e\n \u003cp\u003eSignificant absolute and relative SDI-associated inequalities in the burden of PAH among children and adolescents were observed, with a reduction in these disparities over time (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). It is noteworthy that DALYs were disproportionately concentrated in countries with lower sociodemographic development levels. As indicated by the slope index of inequality, there was an excess of -3.89 (95% CI: -4.88 to -2.89) DALYs per 100,000 between the countries with the highest and lowest SDI in 1990, which decreased to -1.97 (95% CI: -2.35 to -1.59) in 2021. Furthermore, the concentration index, a measure of relative gradient inequality, was \u0026minus;\u0026thinsp;0.33 in 1990 and \u0026minus;\u0026thinsp;0.40 in 2021, reflecting an uneven distribution of the burden across countries with different SDI levels.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eFuture forecasts of global burden of PAH in children and adolescents\u003c/h2\u003e\n \u003cp\u003eThe global burden of PAH in children and adolescents is projected to evolve significantly from 2021 to 2050, with different trends across various measures. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA, the ASIR is expected to remain stable globally. Furthermore, we have forecasted the ASMR and ASDR (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB-C). Over time, both the ASMR and ASDR are predicted to decrease annually through 2050.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides the latest data on the incidence, mortality, and DALYs of PAH in children and adolescents at global, regional, and national levels from 1990 to 2021, highlighting significant disparities across different countries and regions. Further comprehensive assessments were conducted based on trends, inequalities, and predictive analysis. Overall, our findings indicate that from 1990 to 2021, although the incidence cases and ASIR among children and adolescents globally showed an increasing trend, the death cases, DALYs cases, ASMR, and ASDR have dramatically decreased during the same period. Cross- country inequality analysis indicates that low-SDI countries bear a disproportionate burden of PAH in children and adolescents, but SDI-related inequalities have decreased over time. Notably, while the ASIR is expected to remain stable annually from 2022 to 2050, both ASMR and ASDR are projected to decline each year. These trends suggest that the challenges in controlling and managing PAH among children and adolescents in the coming decades may be alleviated.\u003c/p\u003e \u003cp\u003ePAH accounted for 5,049 incident cases, 1,972 deaths, and 170,371 DALYs cases among children and adolescents globally in 2021. Previous studies based on local or national registries have reported varying incidence rates of PAH in children and adolescents. In the United Kingdom, the annual incidence of childhood PAH was estimated at 1.6 per 1\u0026nbsp;million population,\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e while a 15-year nationwide study in the Netherlands reported an annual incidence of 3.0 per 1\u0026nbsp;million.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e The current GBD incidence estimate of 0.7 cases of PAH per 1\u0026nbsp;million children and adolescents, based on a more standardized and comprehensive dataset, is lower than the average incidence rates reported in these previous studies. South Asia reported the highest case numbers for all three metrics, while Eastern Sub-Saharan Africa had the highest ASIR, and Caribbean had the highest ASMR and ASDR. It is important to note that attention should be given not only to regions with the highest current burden, but also to those that have experienced the largest increases over the past few decades. Accordingly, Caribbean, which experienced the largest increase in ASIR from 1990 to 2021, and Oceania, which saw the largest increases in both ASMR and ASDR during the same period, warrant particular concern.\u003c/p\u003e \u003cp\u003eAt the national level, the disparities in the burden of PAH among children and adolescents, along with the varying temporal trends across different countries, highlight the need for flexible health policies that are adapted to the specific contexts of each country and region. In 2021, Ethiopia had the highest ASIR, Haiti had the highest ASMR and ASDR, while India reported the highest cases of incidence, death, and DALYs. Schistosomiasis is a tropical parasitic infection prevalent in over 70 countries, with more than 80% of cases occurring in sub-Saharan Africa.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Ethiopia is one of the countries with a particularly high prevalence of schistosomiasis in this region.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e A study conducted in the Alamata area of northern Ethiopia found a staggering schistosomiasis infection rate of 73.9%.\u003csup\u003e18\u003c/sup\u003e \u003cem\u003eSchistosoma\u003c/em\u003e-associated PAH (SchPAH) are a fatal complication of chronic schistosomiasis infection and a major cause of global morbidity and mortality related to PAH.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Additionally, the infection rate of schistosomiasis is higher in children than in adults,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e which may help explain why Ethiopia has the highest ASIR of PAH among children and adolescents. A study conducted in the Blantyre district of Malawi found that children attending schools closer to open water bodies had an increased risk of infection.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e This suggests that improving sanitation and ensuring access to safe water supplies, as key factors in the control and elimination of schistosomiasis, could help reduce the incidence of PAH. Currently, there is no literature documenting the epidemiology of PAH in children and adolescents in Haiti. Our data show that, in Haiti, the ASMR and ASDR for PAH among children and adolescents are the highest in the world. This can be attributed to several factors, including extreme poverty, a lack of medical resources, inadequate infrastructure, and an underdeveloped public health system.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e The absence of timely PAH screening and diagnostic tools leads to many cases remaining undetected until the disease has advanced. Improving healthcare resources and infrastructure in Haiti, along with enhancing the nutrition of children and adolescents, may help reduce the disease burden associated with PAH. There is limited information on patients under the age of 18 in PAH registries from middle and low-income regions. Our study found that India has the highest incidence, mortality, and DALYs cases for PAH in children and adolescents globally. The large population may be the primary contributing factor. Additionally, limited healthcare resources, especially in rural areas, impede timely diagnosis and treatment. Malnutrition, particularly in impoverished regions, further exacerbates the problem. Together, these factors contribute to the significant disease burden in Indian children and adolescents. In light of this, if India implements policies to enhance the diagnosis, treatment, and prevention of PAH in children and adolescents, it would not only benefit the country itself but also provide valuable lessons for other middle- and low-SDI countries facing similar health challenges. Furthermore, as reflected by the EAPC, India showed an overall decreasing trend in the incidence, mortality, and DALYs of PAH in children and adolescents from 1990 to 2021, while Ethiopia and Haiti exhibited rising incidence trends, along with decreasing mortality and DALY trends during the same period. It suggests that Ethiopia and Haiti still face significant challenges in controlling the incidence of PAH in children and adolescents, despite improvements in mortality and DALYs. In addition, although the current burden of PAH in children and adolescents is not the highest in Slovakia and Mauritius, Slovakia has seen the most notable increase in incidence, while Mauritius has experienced the most significant rise in mortality and DALYs from 1990 to 2021. These trends underscore the need for increased investment in PAH prevention to address the growing burden in these countries.\u003c/p\u003e \u003cp\u003eOur study found that from 1990 to 2021, the number and ASR of PAH incidence in children and adolescents globally increased, while the number and ASRs of mortality and DALYs declined significantly. This suggests that improvements in regional awareness, diagnostic capabilities, and reporting systems may lead to an increase in incidence, but the reduction in global mortality and DALYs is likely due to advancements in healthcare policies. Our results are consistent with a study on all age groups, which shows a moderate improvement in the global PAH burden over time.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e This study specifically focused on the pediatric population and shows that in low-income countries like Ethiopia and Haiti, the disease burden remains high. These countries still require increased healthcare resources, and strengthening infrastructure along with improving early screening and treatment capabilities may be key to addressing this challenge.\u003c/p\u003e \u003cp\u003eWhen the overall trend was segmented into multiple periods, we observed a surprising decline in the ASIR of PAH in children and adolescents between 2011 and 2019. However, the change in the ASIR during this period was minimal compared to the peak reached in 2011, with the ASIR in 2019 still substantially higher than in 1990. Additionally, the ASIR began to increase once again after 2019. This highlights the urgent need for measures to reduce the incidence of PAH among children and adolescents. It is noteworthy that between 2010 and 2021, the ASMR and ASDR of PAH in children and adolescents significantly decreased. Another study based on GBD data also showed that over time, the disease burden for PAH across all age groups gradually decreased, with cause-specific mortality improving slowly.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Prior to the advent of targeted therapies, a study reported a median survival time of only 0.8 years for children diagnosed with IPAH.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e A large retrospective registry study in the Netherlands, spanning two periods before and after the introduction of targeted therapies (1991\u0026ndash;2006), reported survival for all patients with progressive PAH: 1-, 3-, and 5-year survival rates of 73%, 63%, and 60%, respectively.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e In the targeted therapy era, the long-term survival rates for children with PAH improved significantly, with 1-, 3-, and 5-year survival rates ranging from 86\u0026ndash;96%, 82\u0026ndash;85%, and 64\u0026ndash;74%, respectively. \u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e These data indicate that targeted therapies have had a significant impact on the survival rates of children with PAH. Sildenafil is the only targeted therapy drug tested in randomized controlled trials for pediatric PAH, and the European Medicines Agency (EMA) approved its use for treating children aged 1\u0026ndash;17 with PAH in 2011. This approval aligns with the period when ASMR and ASDR began to decline significantly. Furthermore, the treatment strategy for pediatric PAH is guided by risk stratification. To address this urgent issue, the 2013 World Symposium on Pulmonary Hypertension (WSPH) Paediatric Task Force summarized the risk factors affecting children's prognosis and established low- and high-risk criteria, recommending the use of this model for risk assessment in pediatric patients.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e It was later modified by the WSPH in 2018 \u003csup\u003e3\u003c/sup\u003e. The 2019 updated consensus statement on the diagnosis and treatment of pediatric pulmonary hypertension proposed a risk stratification model and specific scoring methods for pediatric PAH. \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e In conclusion, the application of targeted therapies and the development of risk stratification guidelines have likely contributed to the improvement of the disease burden in children and adolescents with PAH. Summarily, our analysis reveals that after 2019, the ASIR of PAH in children and adolescents increased, while both the ASMR and ASDR showed the most significant decline. Overall, despite the rising incidence, there have been substantial improvements in treatment and management. However, further strengthening prevention and control measures remains essential to reducing the disease burden.\u003c/p\u003e \u003cp\u003eThe observed correlation between SDI and the burden of PAH in children and adolescents underscores the importance of regional development in shaping disease outcomes. Higher SDI regions tend to exhibit better disease management, including early diagnosis, access to advanced treatments, and robust healthcare systems, which contribute to improved outcomes in terms of both mortality and disability. Conversely, lower SDI regions face significant challenges. It is estimated that approximately 80% of patients with pulmonary hypertension (PH) reside in low- and middle-income countries (LMICs).\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e However, there is limited data on the epidemiology of PH in sub-Saharan Africa. Nevertheless, available evidence suggests that the prevalence and mortality rates of PH in this region may be higher than those observed in Western countries. This disparity can largely be attributed to the high burden of risk factors, such as rheumatic heart disease, schistosomiasis, and human immunodeficiency virus (HIV) infection, which are more prevalent in sub-Saharan Africa.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Furthermore, patients in this region typically present at later stages of the disease (WHO functional classes III and IV), which is a key factor contributing to the significantly higher mortality rates in sub-Saharan Africa. \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIt is currently recognized that female sex is a risk factor for PAH, yet females generally exhibit better survival rates than males.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Our study found that, within the pediatric and adolescent age groups, the incidence of PAH is higher in females than in males. This aligns with a large study conducted in the United States, which reported a female-to-male ratio of 1.7:1 for pediatric PAH, a phenomenon that may be linked to hormonal factors in children.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Additionally, we were surprised to find that, while females had a lower mortality rate than males in the 0\u0026ndash;9 year age group, the opposite was true in the 10\u0026ndash;19 year age group, although the exact reasons for this difference remain unclear. Moreover, the increased ASMR and ASDR in the 0\u0026ndash;1 year and 15\u0026ndash;19 year age groups highlight significant challenges: the higher rates in the 0\u0026ndash;1 year group may be related to severe neonatal conditions, while the elevated rates in the 15\u0026ndash;19 year group may be influenced by the higher prevalence of autoimmune diseases in females.\u003c/p\u003e \u003cp\u003eQuantifying the cross-country inequalities in the disease burden of pediatric PAH across different SDI gradients can reveal patterns of burden distribution and help identify countries where PAH prevention and treatment need to be improved. It is generally believed that in countries with higher SDI, people have greater access to healthcare services, and the performance of healthcare systems is better, which may lead to a lower disease burden. As we expected, the disease burden of pediatric PAH is predominantly concentrated in low-SDI countries. Similarly, research by Babar Hasa et al. has pointed out that, compared to high-income regions, the global prevalence of PAH is significantly higher in middle- and low-income regions (MLRs), especially for PAH associated with untreated congenital heart disease, HIV, or schistosomiasis.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Furthermore, in low-SDI countries, the management and prognosis of PAH face numerous challenges, including late diagnosis, comorbidities, a lack of resources and expertise, and limited options for lung transplantation. To alleviate this inequality, low-SDI countries should adopt more targeted policies to optimize the allocation of healthcare resources. First, these countries should invest more in healthcare infrastructure to enhance early diagnosis and treatment capabilities. Second, raising public awareness of pediatric PAH and implementing early screening and interventions are crucial. In addition, international organizations such as the World Health Organization and the United Nations should strengthen their support for low-SDI countries by providing necessary technical assistance and funding to help enhance their disease prevention and control capacities.\u003c/p\u003e \u003cp\u003eThe projected global burden of PAH in children and adolescents from 2022 to 2050 reveals significant trends with important implications for public health and medical practice. While the ASIR is expected to remain stable globally, the decreasing ASMR and ASDR over time suggest that the management and treatment of PAH in children and adolescents are likely to improve. The stability of the ASIR indicates that the incidence of PAH may not significantly decrease in the coming decades, possibly due to factors such as increased awareness, better diagnostic capabilities, and the continued presence of risk factors like congenital heart disease, HIV, and schistosomiasis in certain regions. However, the sustained decline in ASMR and ASDR reflects advancements in medical interventions, particularly the widespread use of targeted therapies and improvements in clinical management. Overall, early diagnosis, robust healthcare systems, and enhanced treatment protocols play a crucial role in mitigating the severe consequences of PAH, including mortality and disability. However, sustained global efforts are vital to address the underlying causes and risk factors of PAH and to further advance the clinical management of this complex condition.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eSeveral limitations should be noted in this study focusing on children and adolescents with PAH. First, in underdeveloped countries, limited medical resources often contribute to misdiagnosis, underdiagnosis, and missing data, potentially leading to an underestimation of the true burden of PAH in this age group. Second, the raw data input into the GBD is derived from various countries, resulting in inevitable variability in data quality. For instance, heterogeneity in the measurement of PAH may lead to disease misclassification, complicating cross-population comparisons. Fortunately, the GBD collaborators have implemented rigorous data cleaning, adjustments, and advanced statistical modeling techniques, which have significantly mitigated these limitations. However, this introduces another challenge: the findings are heavily dependent on modeled data, particularly at the national level, as only a small number of countries provide actual data. Furthermore, while there is considerable interest in exploring the subtypes of PAH, this remains unattainable with the current GBD database. To address these limitations, increased international collaboration, the widespread adoption of standardized diagnostic criteria, particularly in underdeveloped countries, and the efficient collection of health data from diverse sources, especially at the national level, are essential. Incorporating information on PAH subtypes into data collection processes would further enrich our understanding of the disease and its variations across populations. These efforts would collectively improve the reliability of disease burden estimates and enhance the accuracy of studies based on these data. Despite these limitations, the study demonstrates several notable strengths. By conducting comprehensive and in-depth analyses\u0026mdash;including descriptive, trend, health inequality, and predictive investigations\u0026mdash;it has significantly enriched our understanding of PAH epidemiology in children and adolescents. This research provides a solid foundation for the development of targeted public health policies and the equitable allocation of medical resources worldwide.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, PAH in children and adolescents poses a significant global public health challenge, with marked differences in incidence, mortality, and DALYs observed across countries. Between 1990 and 2021, the incidence of PAH has increased globally, while mortality and DALYs have shown an overall decline, particularly in the last decade. Countries with low SDI continue to face a disproportionately heavy burden, underscoring the pressing need for targeted interventions in these regions. Moreover, variations in disease burden by gender and age emphasize the necessity of developing prevention and treatment strategies that address the specific needs of these groups. To tackle these issues, global health policymakers should focus on tailored and flexible solutions that improve healthcare systems and address the unique medical needs of different countries.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eT.M.Y. and Z.J.Y. are considered co\u0026ndash;first authors. T.M.Y. and Z.J.Y. designed and analyzed the research study; Z.J.Y., and W.J. collected the data; Z.J.Y., and W.J. validation and visualization the data. T.M.Y. and H.S.P wrote and revised the manuscript. All authors have read and approved the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis study was funded by the Zhejiang Provincial Medical and Health Science and Technology Program (2025KY1169), the Zhejiang Provincial Traditional Chinese Medicine Science and Technology Program (2025ZR175). We acknowledge the Institute for Health Metrics and Evaluation (University of Washington), the GBD Collaborators, and all staff who provided the data necessary for this study. The opinions expressed here are those of the authors and do not necessarily represent the official position of the organizations with which they are affiliated.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThe data from this study can be accessed openly through the GBD 2021 online database, as outlined in the Methods section.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLai YC, Potoka KC, Champion HC, Mora AL, Gladwin MT. Pulmonary arterial hypertension: the clinical syndrome. Circ Res. 2014;115(1):115\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarst RJ, Ertel SI, Beghetti M, Ivy DD. Pulmonary arterial hypertension: a comparison between children and adults. Eur Respir J. 2011;37(3):665\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenzweig EB, Abman SH, Adatia I et al. 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Twenty-Year Experience and Outcomes in a National Pediatric Pulmonary Hypertension Service. Am J Respir Crit Care Med. 2022;206(6):758\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Loon RL, Roofthooft MT, Hillege HL, et al. Pediatric pulmonary hypertension in the Netherlands: epidemiology and characterization during the period 1991 to 2005. Circulation. 2011;124(16):1755\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcManus DP, Dunne DW, Sacko M, Utzinger J, Vennervald BJ, Zhou XN. Schistosomiasis. Nat Rev Dis Primers. 2018;4(1):13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdenowo AF, Oyinloye BE, Ogunyinka BI, Kappo AP. Impact of human schistosomiasis in sub-Saharan Africa. Braz J Infect Dis. 2015;19(2):196\u0026ndash;205.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbebe N, Erko B, Medhin G, Berhe N. 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BMJ. 2022;379:o2379.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor L. Haiti: Hospitals burn to ground as violence rages. BMJ. 2024;384:q663.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollaborators GBDPAH. Global, regional, and national burden of pulmonary arterial hypertension, 1990\u0026ndash;2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Respir Med 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Alonzo GE, Barst RJ, Ayres SM, et al. Survival in patients with primary pulmonary hypertension. Results from a national prospective registry. Ann Intern Med. 1991;115(5):343\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarst RJ, McGoon MD, Elliott CG, Foreman AJ, Miller DP, Ivy DD. Survival in childhood pulmonary arterial hypertension: insights from the registry to evaluate early and long-term pulmonary arterial hypertension disease management. Circulation. 2012;125(1):113\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003edel Cerro Marin MJ, Sabate Rotes A, Rodriguez Ogando A, et al. Assessing pulmonary hypertensive vascular disease in childhood. Data from the Spanish registry. Am J Respir Crit Care Med. 2014;190(12):1421\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFraisse A, Jais X, Schleich JM, et al. Characteristics and prospective 2-year follow-up of children with pulmonary arterial hypertension in France. Arch Cardiovasc Dis. 2010;103(2):66\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIvy DD, Abman SH, Barst RJ, et al. Pediatric pulmonary hypertension. J Am Coll Cardiol. 2013;62(25 Suppl):D117\u0026ndash;126.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHansmann G, Koestenberger M, Alastalo TP, et al. 2019 updated consensus statement on the diagnosis and treatment of pediatric pulmonary hypertension: The European Pediatric Pulmonary Vascular Disease Network (EPPVDN), endorsed by AEPC, ESPR and ISHLT. J Heart Lung Transpl. 2019;38(9):879\u0026ndash;901.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMocumbi AO, Thienemann F, Sliwa K. A global perspective on the epidemiology of pulmonary hypertension. Can J Cardiol. 2015;31(4):375\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThienemann F, Dzudie A, Mocumbi AO, et al. The causes, treatment, and outcome of pulmonary hypertension in Africa: Insights from the Pan African Pulmonary Hypertension Cohort (PAPUCO) Registry. Int J Cardiol. 2016;221:205\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoeper MM, Humbert M, Souza R, et al. A global view of pulmonary hypertension. Lancet Respir Med. 2016;4(4):306\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Agostino A, Guindani P, Scaglione G, et al. Sex- and Gender-Related Aspects in Pulmonary Hypertension. Heart Fail Clin. 2023;19(1):11\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMair KM, Wright AF, Duggan N, et al. Sex-dependent influence of endogenous estrogen in pulmonary hypertension. Am J Respir Crit Care Med. 2014;190(4):456\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHasan B, Hansmann G, Budts W, et al. Challenges and Special Aspects of Pulmonary Hypertension in Middle- to Low-Income Regions: JACC State-of-the-Art Review. J Am Coll Cardiol. 2020;75(19):2463\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"pulmonary arterial hypertension, children and adolescents, global disease burden, sociodemographic index, health inequality","lastPublishedDoi":"10.21203/rs.3.rs-5827730/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5827730/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePulmonary arterial hypertension (PAH) in children and adolescents is a significant global health challenge, leading to a range of severe medical complications and an increased risk of premature death. In this study, we assessed the trends and cross-country disparities in the burden of PAH among children and adolescents from 1990 to 2021, and further predicted its changes to 2050.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eGBD 2021 estimated 5,049 incident cases, 1,972 deaths, and 170,371 DALYs of PAH in children and adolescents globally in 2021. South Asia reported the highest numbers of incident, death, and DALYs cases, while Eastern Sub-Saharan Africa had the highest age-standardized incidence rate (ASIR), and the Caribbean recorded the highest age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR). Between 1990 and 2021, the ASIR in this population showed an overall increasing trend, whereas the ASMR and ASDR demonstrated a consistent decline. The ASIR, ASMR, and ASDR were found to decrease exponentially with rising SDI levels. DALYs were disproportionately concentrated in countries with lower sociodemographic development levels. The ASIR is projected to remain globally stable, while both the ASMR and ASDR are expected to decline annually through 2050.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe burden of PAH in children and adolescents is concentrated in low-SDI countries. While ASIR has increased, ASMR and ASDR have steadily declined and are projected to continue decreasing through 2050. Strengthening international collaboration, improving healthcare, and targeting high-risk regions are crucial to reducing the disease burden and promoting global health equity.\u003c/p\u003e","manuscriptTitle":"Global, Regional, and National Burden of Pulmonary Arterial Hypertension in Children and Adolescents, 1990-2021, and Projections to 2050: A Systematic Analysis for the Global Burden of Disease Study 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-20 15:52:03","doi":"10.21203/rs.3.rs-5827730/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"248f33f9-9453-481d-a0b9-11773219158b","owner":[],"postedDate":"January 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-27T10:08:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-20 15:52:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5827730","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5827730","identity":"rs-5827730","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}