Global, regional, and national epidemiology of childhood epilepsy from 1990 to 2021: a systematic study based on the GBD 2021

Global, regional, and national epidemiology of childhood epilepsy from 1990 to 2021: a systematic study based on the GBD 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 Article Global, regional, and national epidemiology of childhood epilepsy from 1990 to 2021: a systematic study based on the GBD 2021 Kou Xu, Wenlong Qian, Wenjuan Xu, Wenming Yang, Yulong Yang, Yuqi Song, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6319907/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 Epilepsy is a major chronic neurological disorder in children, causing significant global disease burden due to neurodevelopmental impairments and socioeconomic impacts. This study assesses global childhood epilepsy trends (1990–2021), focusing on incidence, mortality, disability-adjusted life years (DALYs), risk factors, and regional disparities. Using Global Burden of Disease Study 2021 data, this cross-sectional analysis evaluated epilepsy epidemiology among children aged 0–14 across 204 regions. Incidence, mortality, DALYs, and estimated annual percentage changes (EAPCs) were stratified by geography, demographics, and Socio-demographic Index (SDI).In 2021, global childhood epilepsy incidence rose to 1,227,191 cases (26.34% increase since 1990), with incidence rates climbing from 55.85 to 61.00 per 100,000. Mortality and DALYs declined by 29.5% (1.48 to 0.90 per 100,000) and 14.89% (EAPC: −1.39 and − 0.94), respectively. Low SDI regions showed the highest mortality (1.46 per 100,000) and DALYs (244.53 per 100,000), while high SDI regions had the highest incidence (70.66 per 100,000). Ecuador (120.09 per 100,000) and Tajikistan (2.77 per 100,000) reported extreme incidence and mortality rates. Key mortality risks included alcohol consumption and behavioral factors (15% each). Despite declining mortality and DALYs, childhood epilepsy incidence continues to rise globally, highlighting persistent disparities. Health sciences/Neurology/Neurological disorders/Epilepsy Health sciences/Neurology/Neurological disorders/Paediatric neurological disorders Childhood epilepsy GBD Incidence Mortality DALYs rate Epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Epilepsy is among the most prevalent neurological disorders in childhood, with a global incidence ranging from approximately 33.3 to 82 cases per 100,000 individuals annually 1 . This condition not only exhibits recurrent episodes leading to neurological dysfunction but is also associated with cognitive deficits, behavioral abnormalities, and challenges in social adaptation 2 . Children with epilepsy frequently encounter substantial social difficulties as they transition into adulthood, including obstacles related to employment, marriage, interpersonal relationships, and diminished autonomy in daily life. Notably, even individuals with preserved neurological and intellectual functions face disproportionately high rates of social adversity, underscoring the profound implications of epilepsy on socioeconomic development 3 . Approximately 25% of epilepsy cases are preventable, and mitigating key seizure-triggering factors, such as perinatal complications, cerebrovascular insults, traumatic brain injuries, and neurotropic infections, constitutes a critical aspect of primary prevention strategies 4 . Over the past three decades, substantial progress has been made in the global prevention and management of epilepsy. Widespread immunization has significantly reduced the incidence of bacterial meningitis-associated epilepsy, while advancements in perinatal care, including therapeutic hypothermia for neonatal hypoxic-ischemic encephalopathy, have contributed to a decline in epilepsy risk 5,6 . However, these advancements exhibit pronounced regional disparities. In high-income countries, newborn screening and genetic testing facilitate the early identification of monogenic epilepsy, with approximately 80% of these cases being amenable to precision therapies. Conversely, in low-income regions, the epilepsy treatment gap exceeds 75%, with rural populations experiencing a markedly higher disparity in access to care than their urban counterparts 7,8 . In recent years, there has been a structural shift in the etiological spectrum of childhood epilepsy, with genetic factors playing an increasingly prominent role in developmental epileptic encephalopathy (DEE) 9 . Concurrently, advancements in neonatal care have improved survival rates among premature infants, presenting new clinical challenges. The mortality rate for extremely preterm infants (<28 weeks of gestation) ranges from 30% to 50%, and among survivors, 20% to 50% develop varying degrees of disability, including severe neurological sequelae 10 . These evolving trends necessitate ongoing epidemiological studies to dynamically monitor the changing landscape of risk factors. Additionally, the clinical management of pediatric epilepsy has faced substantial challenges during the COVID-19 pandemic, particularly in resource-limited settings. A study that conducted telephone interviews with caregivers of 213 pediatric epilepsy patients in underserved areas of Faisalabad, Punjab, Pakistan, found that 64.3% of respondents canceled follow-up appointments due to pandemic-related disruptions, exacerbating seizure conditions. Furthermore, 68.1% of caregivers reported an increased financial burden for antiepileptic medications during the lockdown, while 17.4% had to discontinue treatment due to loss of income 11 . In low- and middle-income countries, many individuals remain untreated, either due to a shortage of healthcare providers or the unaffordability of medications. In contrast, high-income countries have leveraged remote EEG monitoring and teleconsultations to ensure continuity of care 12 . These disparities underscore the urgent need to strengthen health system resilience to improve epilepsy management globally. Although the Global Burden of Disease (GBD) study provides a valuable framework for assessing the global impact of epilepsy, long-term trends in childhood epilepsy epidemiology remain unreported. To address this gap, this study analyzed trends in childhood epilepsy incidence, epilepsy-related mortality, and epilepsy-related disability-adjusted life years (DALYs) from 1990 to 2021 using the GBD database, alongside associated risk factors. This study anticipates that insights from the GBD 2021 dataset will contribute to the development of innovative therapeutic interventions and preventive strategies, providing an evidence-based foundation for precision medicine approaches in pediatric epilepsy management. Methodology 1.1 Materials and Methods Epidemiological data were compiled using the global health data exchange (GHDx) query tool developed by the GBD collaborative research network. This study systematically collected standardized datasets, including case definitions, prevalence metrics, and health outcome indicators, specifically for pediatric epilepsy (ages 0–14 years) across global populations. As part of the comprehensive GBD 2021 investigation (spanning 1990–2021), a standardized comparative risk assessment framework was applied to quantify disease burden parameters, including incidence rates, mortality statistics, and DALYs, for 371 categorized diseases and injuries. The analysis encompassed 204 geographically and socioeconomically diverse nations and regions. All epidemiological estimates were accompanied by 95% uncertainty intervals, calculated using Bayesian statistical modeling. To summarize the age distribution of the burden of childhood epilepsy, patients were categorized into four groups: under 1 year, 1–4 years, 5–9 years, and 10–14 years. Epidemiological data were analyzed across three distinct administrative levels—global, regional, and national—focusing on case numbers, incidence rates, mortality statistics, and DALYs. As the GBD database does not provide specific data on global risk factors contributing to childhood epilepsy-related mortality, global risk factor data for epilepsy mortality across all age groups were used as a reference. Additionally, average estimated annual percentage changes (EAPCs) were calculated using linear regression analysis. In accordance with academic research standards, this study utilized publicly accessible datasets that were exempt from ethical review by the Ethics Review Board of the First Affiliated Hospital of Anhui University of Chinese Medicine. The research methodology strictly adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines to ensure methodological rigor in observational epidemiological research. 1.2 Socio-demographic Index The Socio-demographic Index (SDI) is a composite metric that integrates three key socioeconomic dimensions: income per capita, educational attainment, and fertility rate. It is scaled from 0 (lowest) to 1 (highest) to quantify a region’s level of socioeconomic development 13 , 14 . In this epidemiological study, a stratified classification system was applied to categorize global regions into five SDI quintiles: low, low-middle, middle, high-middle, and high. This methodological approach facilitates a systematic assessment of the relationship between childhood epilepsy burden, including both incidence and disease impact and socioeconomic gradients across populations. 1.3 Statistical Analysis The incidence rate, mortality rate, and DALYs serve as key indicators for quantifying the burden of childhood epilepsy. In accordance with the standardized methodology of the GBD study, all rates in this research are calculated per 100,000 population, with each estimate reported alongside its corresponding 95% uncertainty interval 15 . Dynamic trends in childhood epilepsy were analyzed using the EAPC, calculated in R 4.4.2, and evaluated using a linear regression model 14 . The trend analysis of these rates was interpreted based on the following EAPC criteria and their 95% confidence intervals (CIs):(1) A statistically significant decline was identified if both the EAPC value and the upper boundary of its 95% CI were below zero; (2) A stable trend was indicated if the EAPC value and its 95% CI encompassed zero, suggesting no statistically significant change; (3) A statistically significant increase was confirmed if both the EAPC value and the lower boundary of its 95% CI exceeded zero 14 , 16 . To assess the relationship between EAPC, epilepsy incidence rates, and the Human Development Index (HDI), Gaussian curve analysis was applied 14 . Additionally, risk factors for epilepsy across all age groups were evaluated. A P -value < 0.05 was considered statistically significant. Results 2.1 Global Incidence Trends of Childhood Epilepsy 2.1.1 Incidence In 2021, the global incidence of childhood epilepsy reached 1,227,191 cases (95% UI: 786,363.03–1,734,488.13), reflecting a 26.34% increase compared to 1990 (95% UI: 6.81–51.19%). Between 1990 and 2021, the global incidence rate followed an upward trajectory, rising from 55.85 cases per 100,000 population (95% UI: 35.89–78.70) to 61.00 cases per 100,000 population (95% UI: 39.00–86.21). This increase corresponded to an EAPC of 0.20 (95% CI: 0.14–0.26). Over the three-decade period, a consistent rise in childhood epilepsy incidence was observed across all pediatric age groups. The most substantial increase occurred in adolescents aged 10–14 years (40.79% increase), whereas the smallest percentage increase was observed in infants under 12 months (8.81% increase). Interestingly, despite exhibiting the lowest percentage growth, the neonatal population (0–1 year) consistently had the highest absolute incidence rates throughout the study period. Additionally, a persistent gender disparity was observed in the neonatal group, with male infants consistently exhibiting higher incidence rates than females. (Details are provided in Table and Fig. 1 A). Table 1 Incidence of Epilepsy in Children Between 1990 and 2021 at the Global and Regional Level Rate per 100000 (95% UI) 1990 2021 1990–2021 Location Incident cases Incidence rate Incident cases Incidence rate Cases change EAPC a Global 971368.10 (624226.22, 1368635.97) 55.85 (35.89, 78.70) 1227191.11 (786363.03, 1734488.13) 61.00 (39.09,86.21) 26.34 (6.81, 51.19) 0.20 (0.14, 0.26) East Asia 102871.53 (60049.82, 153795.36) 31.19 (18.21, 46.63) 102941.40 (61944.68, 155014.51) 38.50 (23.17,57.98) 0.07 (-28.43, 38.59) 0.15 (-0.07,0.39) Southeast Asia 86339.14 (52646.84, 130261.43) 50.57 (30.83, 76.29) 96587.04 (59801.82, 147584.91) 55.94 (34.64,85.48) 11.87 (-18.09, 53.68) 0.31 (0.26, 0.36) Oceania 1108.96 (474.30, 1996.95) 41.38 (17.70, 74.52) 2089.18 (756.55, 3753.51) 41.12 (14.89,73.88) 88.39 (-23.87, 348.24) -0.02 (-0.04,0.00) Central Europe 18777.38 (11119.12, 28328.86) 63.69 (37.71, 96.08) 11674.26 (6917.09, 17585.38) 65.95 (39.08,99.35) -37.83 (-54.00, -16.03) 0.21 (0.16, 0.25) Central Asia 18185.34 (10470.13, 27657.40) 72.77 (41.90, 110.67) 20307.52 (11098.81, 30456.70) 73.38 (40.10,110.05) 11.67 (-31.66, 81.31) -0.06 (-0.14,0.02) Eastern Europe 27201.27 (16827.24, 40171.85) 52.86 (32.70, 78.06) 16376.83 (9617.39, 24685.87) 46.20 (27.13,69.65) -39.79 (-52.90, -23.25) -0.43 (-0.51, -0.35) Australasia 3005.66 (1105.80, 5061.93) 65.54 (24.11, 110.38) 3631.90 (1342.82, 6247.72) 63.37 (23.43,109.01) 20.84 (-51.56, 189.87) -0.27 (-0.33, -0.20) Western Europe 55148.02 (33151.58, 81906.36) 77.65 (46.68, 115.33) 57086.48 (32083.43, 87093.88) 83.80 (47.10,127.86) 3.52 (-25.72, 37.52) 0.26 (0.21, 0.31) Southern Latin America 8808.11 (4162.97, 14118.48) 59.01 (27.89, 94.59) 9970.39 (4211.20, 17278.36) 68.78 (29.05,119.20) 13.20 (-48.32, 133.79) 0.49 (0.39, 0.59) Central Latin America 61379.06 (36581.50, 90377.31) 95.34 (56.82, 140.38) 57735.11 (36541.73, 86874.45) 90.94 (57.56,136.84) -5.94 (-31.57, 28.13) -0.34 (-0.39, -0.28) High-income Asia Pacific 20378.57 (11274.01, 31574.11) 57.89 (32.03, 89.70) 14441.00 (8282.52, 22209.74) 64.40 (36.93,99.04) -29.14 (-51.21, 0.92) 0.02 (-0.16,0.21) High-income North America 34225.25 (20574.85, 51553.06) 55.49 (33.36, 83.58) 38338.38 (20507.57, 59593.07) 58.43 (31.25,90.82) 12.02 (-13.35, 35.41) 0.12 (-0.03,0.27) Caribbean 8300.47 (4565.18, 12610.53) 72.73 (40.00, 110.50) 8269.95 (4332.50, 12885.99) 71.88 (37.66,112.00) -0.37 (-40.23, 58.61) -0.05 (-0.10, -0.00) North Africa and the Middle East 96450.22 (56519.15, 144633.80) 68.65 (40.23, 102.95) 132128.53 (77661.22, 204905.83) 72.07 (42.36,111.77) 36.99 (-4.97, 94.51) 0.29 (0.19, 0.39) Andean Latin America 13264.71 (6002.37, 21311.55) 89.31 (40.41, 143.49) 16943.20 (8153.32, 27210.55) 93.64 (45.06,150.38) 27.73 (-38.26, 180.13) -0.53 (-0.73, -0.32) Tropical Latin America 44768.73 (26146.99, 69218.74) 83.50 (48.77, 129.11) 35251.85 (21286.95, 52134.37) 70.23 (42.41,103.87) -21.26 (-43.46, 13.87) -0.39 (-0.73, -0.04) Eastern Sub-Saharan Africa 68995.75 (36520.18, 107964.24) 76.18 (40.32, 119.20) 137605.70 (80028.81, 201246.18) 77.12 (44.85,112.79) 99.44 (45.27, 208.08) -0.25 (-0.32, -0.18) Central Sub-Saharan Africa 21551.10 (7515.69, 38447.04) 85.19 (29.71, 151.97) 46824.10 (17837.41, 81337.93) 79.79 (30.40,138.61) 117.27 (-10.64, 523.76) -0.00 (-0.13,0.13) South Asia 193523.30 (111840.24, 294495.64) 44.66 (25.81, 67.96) 229608.54 (141040.53, 332358.07) 45.29 (27.82,65.55) 18.65 (-14.93, 80.80) -0.03 (-0.15,0.09) Western Sub-Saharan Africa 72292.14 (42172.47, 109107.71) 82.26 (47.99, 124.16) 172799.03 (107800.40, 248211.19) 80.46 (50.19,115.57) 139.03 (86.71, 225.55) -0.19 (-0.38, -0.01) Southern Sub-Saharan Africa 14793.40 (8830.74, 22184.10) 71.50 (42.68, 107.22) 16580.71 (10046.76, 25436.86) 68.90 (41.75,105.70) 12.08 (-24.76, 64.98) -0.38 (-0.58, -0.19) High-middle SDI 131788.23 (82694.18, 188452.97) 48.16 (30.22, 68.87) 122321.80 (72912.35, 188315.93) 52.98 (31.58,81.56) -7.18 (-27.45, 16.19) 0.24 (0.12, 0.36) Low-middle SDI 255940.09 (151098.03, 382225.39) 54.21 (32.00, 80.96) 341687.50 (215945.36, 481879.10) 58.93 (37.24,83.11) 33.50 (-0.91, 85.62) 0.24 (0.17, 0.31) High SDI 119259.76 (76300.87, 178953.18) 64.18 (41.06, 96.31) 121917.97 (67742.29, 188732.86) 70.66 (39.26,109.39) 2.23 (-18.17, 21.36) 0.28 (0.19, 0.37) Low SDI 150783.90 (80733.23, 230378.87) 65.87 (35.27, 100.64) 306197.53 (185486.33, 438447.02) 66.53 (40.30,95.27) 103.07 (58.81, 182.49) -0.11 (-0.16, -0.06) Middle SDI 312668.14 (193388.77, 442722.43) 54.17 (33.50, 76.70) 334091.53 (209540.17, 485226.46) 58.94 (36.97,85.60) 6.85 (-13.67, 34.35) 0.14 (0.06, 0.23) EAPC: estimated annual percentage change; SDI: Sociodemographic Index; UI: uncertainty interval. EAPC values are expressed as 95% CIs. 2.1.2 Mortality Between 1990 and 2021, global epilepsy-related childhood mortality exhibited a significant decline, with total deaths decreasing by 29.5%, from 25,768 cases (95% UI: 17,567–30,914) in 1990 to 18,171 cases (95% UI: 13,891–21,418) in 2021. The mortality rate also followed a consistent downward trend, declining from 1.48 per 100,000 population (95% UI: 1.01–1.78) in 1990 to 0.90 per 100,000 population (95% UI: 0.69–1.06) in 2021. This decline corresponds to an EAPC of -1.39 (95% CI: -1.48 to -1.30) (see Supplementary Table 1). Mortality rates declined across all pediatric age groups, with the most substantial decrease observed in children aged 2–4 years (37.88% reduction). In 1990, the highest number of epilepsy-related deaths occurred in infants under 1 year old (6,178 deaths), whereas in 2021, the highest number of deaths was recorded among children aged 10–14 years (5,249 deaths). Additionally, in 2021, boys consistently exhibited higher mortality rates than girls across all age groups. The lowest epilepsy-related mortality rate was observed in children aged 5–9 years (0.55 per 100,000 population) (Fig. 1 B). 2.1.3 DALYs Between 1990 and 2021, the global burden of childhood epilepsy, as measured by DALYs, exhibited a significant decline. DALYs decreased from 4,188,140 (95% UI: 3,112,385–5,405,104) in 1990 to 3,564,497 (95% UI: 2,700,944–4,753,410) in 2021, reflecting an overall reduction of 14.89% over the 31-year observation period. The corresponding EAPC was − 0.94 (95% CI: -1.00 to -0.88) (see Supplementary Table 1). Except for children aged 10–14 years, who exhibited a 4.05% increase in epilepsy-related disability DALYs, all other pediatric age groups experienced a decline in DALYs due to epilepsy-related disability. The most substantial reduction (30.31%) was observed among infants under 1 year old. In 1990, the highest epilepsy-related disability burden was recorded in the 5–9 age group (1,157,772 DALYs), whereas in 2021, the highest burden shifted to the 10–14 age group (1,145,807 DALYs). Additionally, in 2021, boys aged 0–14 consistently exhibited higher epilepsy-related DALYs than girls across all age groups. The lowest DALYs due to disability were observed in the 5–9 age group for both boys (164.55 per 100,000 population) and girls (135.31 per 100,000 population) (Fig. 1 C). 2.2 Trends in the Incidence of Pediatric Epilepsy across SDI Regions 2.2.1 Incidence In 2021, low-middle SDI regions exhibited the highest case burden, with 341,688 cases (95% UI: 215,945–481,879). Between 1990 and 2021, the incidence of childhood epilepsy in low SDI regions increased by 103.07%, representing the most significant proportional rise among all SDI categories. However, the greatest increase in incidence rates was observed in high SDI regions, with an EAPC of 0.28 (95% CI: 0.19–0.37) (see Table 1 and Fig. 2 A). 2.2.2Mortality Across all five SDI regions, childhood epilepsy-related mortality rates demonstrated a downward trend over time. In 2021, low-middle SDI regions bore the highest mortality burden, with 6,740 fatalities (95% UI: 4,812–8,160), whereas the lowest mortality burden was observed in high SDI regions, with 513 deaths (95% UI: 473–548). Between 1990 and 2021, the most significant reduction in mortality occurred in high-middle SDI regions, showing a 70.99% decline. Epidemiological analysis revealed an inverse SDI gradient, where childhood epilepsy-related mortality rates were highest in low SDI regions (1.46 per 100,000; 95% UI: 1.07–1.80) and lowest in high SDI regions (0.30 per 100,000; 95% UI: 0.27–0.32). The steepest mortality decline was observed in high-middle SDI regions, with an EAPC of -3.45 (95% CI: -3.53 to -3.37) (see Fig. 2 B and Supplementary Table 1). 2.2.3 DALYs In 2021, the global distribution of childhood epilepsy-related DALYs exhibited significant socioeconomic disparities. Low-middle SDI regions bore the highest burden, recording 1,199,709 DALYs (95% UI: 892,917–1,592,918). Longitudinal analysis (1990–2021) revealed divergent trends: Low SDI regions experienced a 46.84% increase in DALYs; All other SDI regions demonstrated progressive reductions in DALYs; High-middle SDI regions showed the greatest improvement, with a 53.40% decrease in pediatric epilepsy-related DALYs (See Fig. 2 C and Supplementary Table 1 for details). 2.3 Geographical Trends in the Incidence of Childhood Epilepsy 2.3.1 Incidence In 2021, among 21 geographical regions, South Asia reported the highest number of childhood epilepsy cases, with an estimated 229,609 cases (95% UI, 141,041–332,358), whereas Oceania had the lowest burden, with 2,089 cases (95% UI, 757–3,754). The Andean Latin America region exhibited the highest incidence rate of childhood epilepsy at 93.64 per 100,000 population (95% UI, 45.06–150.38), while East Asia had the lowest incidence, at 38.50 per 100,000 (95% UI, 23.17–57.98). Longitudinal analysis of childhood epilepsy epidemiology from 1990 to 2021 revealed marked geographical disparities in incidence trajectories. When stratified by developmental status, South Latin America showed the most significant increase in incidence (EAPC, 0.49; 95% CI, 0.39–0.59), whereas Andean Latin America experienced the steepest decline (EAPC, -0.53; 95% CI, -0.73 to -0.32). Notably, incidence rates in high-income Asia-Pacific regions remained largely stable (EAPC, 0.02; 95% CI, -0.16 to -0.21). A cross-sectional analysis of the disease burden in 2021 estimated a global incidence rate of 61 cases per 100,000 population (95% UI, 39.09–86.21). Regional stratification indicated that 15 regions, including Andean and Central Latin America, exceeded this global average, while six regions, such as East Asia and Oceania, reported incidence rates below the worldwide mean (Fig. 3 A). 2.3.2 Mortality In 2021, the distribution of epilepsy-related fatalities among children varied significantly across regions. South Asia recorded the highest number of deaths, with 6,846 fatalities (95% UI, 4,809–8,554), whereas Australasia reported the lowest, with only 16 deaths (95% UI, 14–19). Mortality rates were highest in Eastern Sub-Saharan Africa, reaching 2.06 per 100,000 population (95% UI, 1.56–2.59), which was nearly ten times greater than the rate in Southeast Asia (0.20 per 100,000; 95% UI, 0.13–0.25). A long-term analysis spanning 1990 to 2021 revealed contrasting mortality trends across different regions. High-income North America exhibited an increasing trend in epilepsy-related deaths (EAPC, 0.96; 95% CI, 0.46–1.46), whereas Eastern Europe experienced the most significant decline (EAPC, -4.65; 95% CI, -5.33 to -3.97). In 2021, seven regions, including Eastern Sub-Saharan Africa, had mortality rates above the global average of 0.90 per 100,000, while 14 regions, such as Eastern Europe, reported rates below this threshold (Fig. 3 B and Supplementary Table 1). 2.3.3 DALYs The global burden of pediatric epilepsy in 2021 exhibited considerable regional variations. South Asia accounted for the highest disease burden, with 1,034,317 DALYs (95% UI, 766,837–1,348,291), whereas Australasia had the lowest impact, with 5,002 DALYs (95% UI, 2,309–10,005). A 4.3-fold disparity in DALY rates was observed across regions, with Eastern Sub-Saharan Africa reporting the highest rate (306.53 per 100,000; 95% UI, 228.15–407.97), while Eastern Europe recorded the lowest (70.56 per 100,000; 95% UI, 42.52–116.77). Longitudinal analysis from 1990 to 2021 revealed distinct trends across different regions. While Oceania (EAPC, 0.08; 95% CI, -0.02 to 0.19) and high-income North America (EAPC, 0.10; 95% CI, 0.04–0.16) showed relatively stable or slightly increasing trends, 78% of regions demonstrated declining DALY rates. The most significant reduction was observed in East Asia (EAPC, -3.18; 95% CI, -3.27 to -3.10), whereas South Latin America exhibited only a marginal decline (EAPC, -0.15; 95% CI, -0.25 to -0.05). A comparison with the global DALYs rate benchmark of 177.17 per 100,000 in 2021 indicated that 10 regions, including Eastern Sub-Saharan Africa, had rates above this threshold, while 11 regions, such as Eastern Europe, fell below the global average (Fig. 3 C and Supplementary Table 1). 2.4 Trends in the Incidence of Childhood Epilepsy in Various Countries 2.4.1 Incidence Epidemiological data from 2021 highlighted significant variations in childhood epilepsy incidence across 204 countries. India had the highest number of cases, totaling 160,607 (95% UI: 97,445–232,485). In terms of incidence rates, Ecuador reported the highest rate at 120.09 per 100,000 population (95% UI: 37.04–214.83), while the Democratic People's Republic of Korea had the lowest at 32.15 per 100,000 (95% UI: 8.47–61.82) (Refer to Fig. 4 A, Supplementary Table 2, and Supplementary Fig. 1A). Between 1990 and 2021, Equatorial Guinea experienced the most pronounced increase in incidence (EAPC, 1.43; 95% CI: 1.18–1.68), whereas Burundi saw the greatest decline (EAPC, -1.39; 95% CI: -1.63 to -1.15) (See Supplementary Table 2 and Supplementary Fig. 2A for details). In 2021, the global incidence rate was estimated at 61.00 per 100,000 (95% UI: 39.09–86.21). A total of 150 countries (70.6%) reported incidence rates exceeding this global benchmark, whereas 54 nations (25.4%) had lower-than-average rates, reflecting persistent disparities in healthcare accessibility and management of childhood epilepsy worldwide (Refer to Supplementary Fig. 3A). 2.4.2 Mortality In 2021, India accounted for the highest absolute mortality burden, reporting 4,601 deaths (95% UI: 2,699–6,252) (Refer to Fig. 4 B and Supplementary Table 2). Notably, Tajikistan recorded the highest mortality rate at 2.77 per 100,000 (95% UI: 1.84–4.08), which was 92.3 times greater than Vietnam's rate of 0.03 per 100,000 (95% UI: 0.01–0.11), representing the widest epidemiological disparity (See Supplementary Table 2 and Supplementary Fig. 1B). Between 1990 and 2021, the Northern Mariana Islands experienced a concerning surge in mortality (EAPC: 3.17; 95% CI: 2.37–3.98), whereas Estonia achieved the most significant reduction (EAPC: -6.48; 95% CI: -7.35 to -5.59) (Refer to Supplementary Table 2 and Supplementary Fig. 2B). Globally, the 2021 mortality rate was 0.69 per 100,000 (95% UI: 0.69–1.06), with 53 countries (25.9%) exceeding this benchmark and 151 (74.1%) reporting lower rates, underscoring persistent disparities in child health outcomes across different developmental contexts (Refer to Supplementary Fig. 3B). 2.4.3 DALYs India also bore the highest absolute DALYs burden in 2021, with 701,175 DALYs (95% UI: 474,784–935,405), whereas Niue recorded the lowest burden (0.79 DALYs; 95% UI: 0.48–1.23), marking an 887,563-fold difference (See Fig. 4 C and Supplementary Table 2). DALYs rates varied 6.3-fold across regions, peaking in Zambia (403.33 per 100,000; 95% UI: 235.24–637.11) and reaching the lowest level in Sweden (64.36 per 100,000; 95% UI: 27.54–128.69) (Refer to Supplementary Table 2 and Supplementary Fig. 1C). From 1990 to 2021, Lesotho exhibited the most concerning upward trend in DALYs (EAPC: 0.98; 95% CI: 0.84–1.12), while China demonstrated the most substantial improvement (EAPC: -3.24; 95% CI: -3.33 to -3.15) (See Supplementary Table 2 and Supplementary Fig. 2C). The global DALYs rate for 2021 was 177.17 per 100,000 (95% UI: 134.25–236.27), with 79 countries (38.7%) surpassing this threshold and 125 (61.3%) reporting sub-average rates (Refer to Supplementary Fig. 3C). 2.5 Risk Factors for Childhood Epilepsy The GBD database does not provide specific data on global risk factors for childhood epilepsy-related deaths. Therefore, global risk factor data for epilepsy mortality across all age groups was used as a reference. According to the GBD database, two primary risk factors were identified worldwide: high alcohol use and behavioral risk factors, each contributing equally (0.15; 95% UI: 0.11–0.20). In 2021, these risk factors individually accounted for 12,067 epilepsy-related deaths (95% UI: 8,599–15,696) globally. A comparative risk factor analysis across 21 global regions revealed Australasia had the highest proportion of epilepsy mortality attributed to combined behavioral factors and alcohol use, contributing 20.15 DALYs per 100,000 (95% UI: 14.98–25.59). Conversely, the North Africa and Middle East regions exhibited the most favorable risk profiles, with a significantly lower burden (1.28; 95% UI: 0.88–1.80). Notably, six regions had epilepsy-related mortality rates due to high alcohol use and behavioral risk factors below the global average (0.15; 95% UI: 0.11–0.20) (Refer to Supplementary Fig. 4). Discussion Over the three-decade observational period (1990–2021), global childhood epilepsy epidemiology exhibited a persistent upward trajectory in incidence rates, leading to increasing socioeconomic burdens through rising healthcare expenditures and heightened demands on societal resources. This progressive trend has positioned pediatric epilepsy as a critical global health priority, necessitating urgent multisectoral intervention. A systematic evaluation of 204 nations and territories quantified three principal disease burden metrics: incidence rates, epilepsy-attributable mortality, and DALYs among children aged 0–14 years. Using GBD Study methodologies, modifiable risk factor profiles were further delineated across different developmental spectrums. The resultant data provided detailed epidemiological insights, revealing divergent trends, with low- and middle-income countries experiencing accelerated burden escalation despite global prevention efforts. These findings highlight the necessity for dynamic surveillance systems capable of detecting emerging epidemiological shifts. A comprehensive understanding of childhood epilepsy's spatiotemporal burden distribution enables health policymakers to develop evidence-based intervention frameworks while clinicians can implement precision diagnostic protocols. Notably, the identification of high-burden regions facilitates targeted resource allocation to areas exhibiting stagnant or worsening epidemiological trends. Between 1990 and 2021, despite a significant decline in mortality and DALY rates, the incidence rate of childhood epilepsy has continued to rise, exhibiting substantial regional disparities. In 2021, global childhood epilepsy cases increased by 26.34% compared to 1990. Low SDI regions exhibited high mortality (1.46 per 100,000) and DALYs rates (244.53 per 100,000), underscoring the persistent challenge of unequal medical resource distribution. This trend exhibits a negative correlation with SDI, as evidenced by the largest declines in mortality rates occurring in high SDI regions. Socioeconomic advancements have contributed to a reduced disease burden by enhancing healthcare access and treatment technologies, including the widespread availability of antiepileptic drugs and improvements in neonatal care 8 , 17 , 18 . However, low SDI regions continue to experience substantial treatment gaps (> 75%) and financial barriers to epilepsy care. The COVID-19 pandemic further exacerbated these challenges, leading to higher treatment discontinuation rates and disrupted follow-ups, thereby intensifying health disparities 8 , 11 , 12 . The evolving spectrum of childhood epilepsy etiologies warrants attention. Genetic factors play an increasingly prominent role in developmental epileptic encephalopathy, while the risk of neurological sequelae (30–50%) has risen due to improved survival rates among premature infants, posing a new clinical challenge 9 , 10 . Advancements in specialized epilepsy care have improved patient prognosis. Interventions targeting prenatal and perinatal care have significantly reduced epilepsy incidence in some regions. However, epilepsy treatment in developing countries remains hindered by insufficient medical resources, unstable drug supplies, and a shortage of specialized healthcare professionals, contributing to a persistent burden of preventable cases 19 – 21 . Risk factor analysis indicates that high alcohol consumption (15% of epilepsy-related deaths) and behavioral risk factors (15%) contribute to epilepsy mortality across all age groups, highlighting the indirect influence of familial and social environments on disease prognosis 22 . The highest proportion of epilepsy-related risk factors is observed in Central and Eastern Europe (50%), whereas North Africa and the Middle East exhibit the lowest (2%). This disparity may be linked to social determinants, including differences in mental health service accessibility 23 . Multiple factors contribute to regional disparities in childhood epilepsy. South Asia reports the highest incidence, with 229,609 new cases (95% UI, 172,340–292,450). Meanwhile, Eastern Sub-Saharan Africa exhibits the highest mortality, with a rate of 2.06 per 100,000 person-years (95% UI, 1.52–2.71). A substantial treatment gap persists in low- and middle-income countries, where limited healthcare resources contribute to higher epilepsy prevalence and incidence. In contrast, high-income countries employ advanced management strategies, including telemedicine and electroencephalogram monitoring, to mitigate epilepsy-related mortality and enhance patient quality of life 12 , 24 – 26 . The positive correlation between the SDI and childhood epilepsy incidence (70.66 per 100,000 person-years in high-SDI regions) likely reflects improved diagnostic accuracy rather than true etiological changes. This association is supported by greater neuroimaging accessibility and broader EEG monitoring availability in advanced healthcare systems 27 . Notably, infantile epilepsy (< 1 year) exhibits a male predominance, which may be attributed to genetic or ethnic factors rather than socioeconomic status 28 . However, this study also has several limitations. First, reliance on the GBD database introduces potential inaccuracies due to incomplete epilepsy registration systems and underreporting of undiagnosed cases. This limitation is particularly pronounced in low-SDI regions, where diagnostic under-coverage may lead to an underestimation of the true disease burden 20 . Second, risk factor analysis encompasses all age groups and does not isolate child-specific contributors, such as birth injuries or genetic mutations, potentially limiting the relevance of the findings. Third, epilepsy subtypes (such as focal and generalized) and etiologies (such as structural and metabolic) remain unclassified, hindering the development of targeted prevention and management strategies 29 . Finally, the impact of COVID-19 on epilepsy management, including disruptions in the medication supply chain, remains unquantified, potentially affecting the comprehensiveness of trend analysis. Conclusions Between 1990 and 2021, the global burden of childhood epilepsy exhibited a paradoxical trend of rising incidence alongside declining mortality, influenced by advancements in medical care, population growth, and improved survival rates of preterm infants. However, low-SDI regions continue to experience disproportionately high mortality rates and DALYs, underscoring the need for targeted interventions. Moving forward, priority should be given to strengthening early screening systems, improving access to antiepileptic drugs, and enhancing grassroots medical training in low-income countries. Additionally, integrating genetic testing and telemedicine technologies can optimize epilepsy management. Public health education on alcohol abuse and behavioral risks remains essential in reducing preventable cases. Finally, global cooperation and equitable resource distribution will be critical in ensuring progress toward childhood epilepsy prevention and control. Abbreviations GBD Global Burden of Disease SDI Socio-Demographic Index EAPC Estimated Annual Percentage Change DALYs Disability-Adjusted Life Years UI Uncertainty Interval CI Confidence Interval Declarations Author Contributions: K.X., W.Q. and W.X. contributed to designing the study, formal analysis, and writing of the original draft. Y.Y., S.Z. and F.Z. contributed to the review and editing of the manuscript. K.X., W.Q., and Y.S. performed the formal analysis. Y.L., Z.Y., W.H. and W.W. performed the data curation and investigation. W.Y. contributed to the supervision of the manuscript. All authors have accessed and verified the data reported in the manuscript. All authors reviewed the drafted manuscript and approved the final version. Data availability : The data used for analysis can be accessed from the Health Data website (http://www.healthdata.org/) and the Institute for Health Metrics and Evaluation (http://ghdx.healthdata.org/gbd-results-tool). Fundings: This research was supported by the National Natural Science Foundation's Regional Innovation Development Joint Fund (No. U22A20366), the Key Discipline Construction Project of High-Level Traditional Chinese Medicine (No. Guo Zhong Yi Yao Ren Jiao Han [2023] No. 85), the Special Project for Traditional Chinese Medicine Science and Technology in Anhui Province (No. 202303a07020004), and the Collaborative Innovation Project of Anhui Province Universities (No. GXXT-2020-025). Acknowledgments: The authors extend their sincere gratitude to our esteemed colleagues for their invaluable support and expertise, particularly for providing access to the comprehensive dataset meticulously compiled through rigorous research efforts, as well as the specialized JD_GBDR analytical software that significantly facilitated data processing tasks. This collaborative contribution has been instrumental in advancing the methodological framework of our investigation, and we wish to formally acknowledge the substantive value these resources have added to our scholarly inquiry. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests References Fine, A. & Wirrell, E. C. Seizures in Children. Pediatr Rev 41 , 321-347, doi:10.1542/pir.2019-0134 (2020). Berg, A. T. et al. Determinants of Social Outcomes in Adults With Childhood-onset Epilepsy. Pediatrics 137 , doi:10.1542/peds.2015-3944 (2016). Camfield, C. S. & Camfield, P. R. Long-term social outcomes for children with epilepsy. Epilepsia 48 Suppl 9 , 3-5, doi:10.1111/j.1528-1167.2007.01390.x (2007). Edmond, K. et al. Global and regional risk of disabling sequelae from bacterial meningitis: a systematic review and meta-analysis. 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Nat Rev Neurol 10 , 249-260, doi:10.1038/nrneurol.2014.58 (2014). Additional Declarations No competing interests reported. Supplementary Files Supplementary.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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Epilepsy Incidence, Deaths, and DALYs Among Children From 1990 to 2021. (A) Trends in incident cases and incidence rate. (B) Trends in death cases and death rate. (C) Trends in DALYs cases and DALYs rate.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6319907/v1/799830c9d0a3a4ccc9ffccbf.png"},{"id":82311139,"identity":"1acc89d0-6e6b-48da-871b-88bc07103024","added_by":"auto","created_at":"2025-05-09 01:53:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1427964,"visible":true,"origin":"","legend":"\u003cp\u003eEpidemiologic Trends of Incidence, Death, and DALYs Rates in 5 Socio-demographic Index (SDI) Regions of Childhood Epilepsy From 1990 to 2021. (A) Trends in incidence rate. (B) Trends in death rate. (C) Trends in DALYs rate.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6319907/v1/91fa3ebdc5b8a59422ec6e70.png"},{"id":82311186,"identity":"faaef04c-0aff-42a4-b616-3b5159b8659c","added_by":"auto","created_at":"2025-05-09 01:53:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3603866,"visible":true,"origin":"","legend":"\u003cp\u003eIncidence, Death, and DALYs Rates for Childhood Epilepsy From 1990 to 2021. (A). Incidence rate. (B), Death rate. (C). DALYs rate.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6319907/v1/564ddf9ac3c5e85015d9add6.png"},{"id":82311158,"identity":"cdd6f991-6169-40b2-8a6b-8003ff82981d","added_by":"auto","created_at":"2025-05-09 01:53:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":6982026,"visible":true,"origin":"","legend":"\u003cp\u003eIncident, Death, and DALYs Cases of Epilepsy in Children in 204 Countries and Territories. (A) Incident cases. (B) Death cases. 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This condition not only exhibits recurrent episodes leading to neurological dysfunction but is also associated with cognitive deficits, behavioral abnormalities, and challenges in social adaptation \u003csup\u003e2\u003c/sup\u003e. Children with epilepsy frequently encounter substantial social difficulties as they transition into adulthood, including obstacles related to employment, marriage, interpersonal relationships, and diminished autonomy in daily life. Notably, even individuals with preserved neurological and intellectual functions face disproportionately high rates of social adversity, underscoring the profound implications of epilepsy on socioeconomic development \u003csup\u003e3\u003c/sup\u003e. Approximately 25% of epilepsy cases are preventable, and mitigating key seizure-triggering factors, such as perinatal complications, cerebrovascular insults, traumatic brain injuries, and neurotropic infections, constitutes a critical aspect of primary prevention strategies \u003csup\u003e4\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOver the past three decades, substantial progress has been made in the global prevention and management of epilepsy. Widespread immunization has significantly reduced the incidence of bacterial meningitis-associated epilepsy, while advancements in perinatal care, including therapeutic hypothermia for neonatal hypoxic-ischemic encephalopathy, have contributed to a decline in epilepsy risk \u003csup\u003e5,6\u003c/sup\u003e. However, these advancements exhibit pronounced regional disparities. In high-income countries, newborn screening and genetic testing facilitate the early identification of monogenic epilepsy, with approximately 80% of these cases being amenable to precision therapies. Conversely, in low-income regions, the epilepsy treatment gap exceeds 75%, with rural populations experiencing a markedly higher disparity in access to care than their urban counterparts \u003csup\u003e7,8\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn recent years, there has been a structural shift in the etiological spectrum of childhood epilepsy, with genetic factors playing an increasingly prominent role in developmental epileptic encephalopathy (DEE) \u003csup\u003e9\u003c/sup\u003e. Concurrently, advancements in neonatal care have improved survival rates among premature infants, presenting new clinical challenges. The mortality rate for extremely preterm infants (\u0026lt;28 weeks of gestation) ranges from 30% to 50%, and among survivors, 20% to 50% develop varying degrees of disability, including severe neurological sequelae \u003csup\u003e10\u003c/sup\u003e. These evolving trends necessitate ongoing epidemiological studies to dynamically monitor the changing landscape of risk factors. Additionally, the clinical management of pediatric epilepsy has faced substantial challenges during the COVID-19 pandemic, particularly in resource-limited settings. A study that conducted telephone interviews with caregivers of 213 pediatric epilepsy patients in underserved areas of Faisalabad, Punjab, Pakistan, found that 64.3% of respondents canceled follow-up appointments due to pandemic-related disruptions, exacerbating seizure conditions. Furthermore, 68.1% of caregivers reported an increased financial burden for antiepileptic medications during the lockdown, while 17.4% had to discontinue treatment due to loss of income \u003csup\u003e11\u003c/sup\u003e. In low- and middle-income countries, many individuals remain untreated, either due to a shortage of healthcare providers or the unaffordability of medications. In contrast, high-income countries have leveraged remote EEG monitoring and teleconsultations to ensure continuity of care \u003csup\u003e12\u003c/sup\u003e. These disparities underscore the urgent need to strengthen health system resilience to improve epilepsy management globally.\u003c/p\u003e\n\u003cp\u003eAlthough the Global Burden of Disease (GBD) study provides a valuable framework for assessing the global impact of epilepsy, long-term trends in childhood epilepsy epidemiology remain unreported. To address this gap, this study analyzed trends in childhood epilepsy incidence, epilepsy-related mortality, and epilepsy-related disability-adjusted life years (DALYs) from 1990 to 2021 using the GBD database, alongside associated risk factors. This study anticipates that insights from the GBD 2021 dataset will contribute to the development of innovative therapeutic interventions and preventive strategies, providing an evidence-based foundation for precision medicine approaches in pediatric epilepsy management.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Materials and Methods\u003c/h2\u003e \u003cp\u003eEpidemiological data were compiled using the global health data exchange (GHDx) query tool developed by the GBD collaborative research network. This study systematically collected standardized datasets, including case definitions, prevalence metrics, and health outcome indicators, specifically for pediatric epilepsy (ages 0\u0026ndash;14 years) across global populations. As part of the comprehensive GBD 2021 investigation (spanning 1990\u0026ndash;2021), a standardized comparative risk assessment framework was applied to quantify disease burden parameters, including incidence rates, mortality statistics, and DALYs, for 371 categorized diseases and injuries.\u003c/p\u003e \u003cp\u003eThe analysis encompassed 204 geographically and socioeconomically diverse nations and regions. All epidemiological estimates were accompanied by 95% uncertainty intervals, calculated using Bayesian statistical modeling. To summarize the age distribution of the burden of childhood epilepsy, patients were categorized into four groups: under 1 year, 1\u0026ndash;4 years, 5\u0026ndash;9 years, and 10\u0026ndash;14 years. Epidemiological data were analyzed across three distinct administrative levels\u0026mdash;global, regional, and national\u0026mdash;focusing on case numbers, incidence rates, mortality statistics, and DALYs.\u003c/p\u003e \u003cp\u003eAs the GBD database does not provide specific data on global risk factors contributing to childhood epilepsy-related mortality, global risk factor data for epilepsy mortality across all age groups were used as a reference. Additionally, average estimated annual percentage changes (EAPCs) were calculated using linear regression analysis.\u003c/p\u003e \u003cp\u003eIn accordance with academic research standards, this study utilized publicly accessible datasets that were exempt from ethical review by the Ethics Review Board of the First Affiliated Hospital of Anhui University of Chinese Medicine. The research methodology strictly adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines to ensure methodological rigor in observational epidemiological research.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e1.2 Socio-demographic Index\u003c/h3\u003e\n\u003cp\u003eThe Socio-demographic Index (SDI) is a composite metric that integrates three key socioeconomic dimensions: income per capita, educational attainment, and fertility rate. It is scaled from 0 (lowest) to 1 (highest) to quantify a region\u0026rsquo;s level of socioeconomic development \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In this epidemiological study, a stratified classification system was applied to categorize global regions into five SDI quintiles: low, low-middle, middle, high-middle, and high. This methodological approach facilitates a systematic assessment of the relationship between childhood epilepsy burden, including both incidence and disease impact and socioeconomic gradients across populations.\u003c/p\u003e\n\u003ch3\u003e1.3 Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eThe incidence rate, mortality rate, and DALYs serve as key indicators for quantifying the burden of childhood epilepsy. In accordance with the standardized methodology of the GBD study, all rates in this research are calculated per 100,000 population, with each estimate reported alongside its corresponding 95% uncertainty interval \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Dynamic trends in childhood epilepsy were analyzed using the EAPC, calculated in R 4.4.2, and evaluated using a linear regression model \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The trend analysis of these rates was interpreted based on the following EAPC criteria and their 95% confidence intervals (CIs):(1) A statistically significant decline was identified if both the EAPC value and the upper boundary of its 95% CI were below zero; (2) A stable trend was indicated if the EAPC value and its 95% CI encompassed zero, suggesting no statistically significant change; (3) A statistically significant increase was confirmed if both the EAPC value and the lower boundary of its 95% CI exceeded zero \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. To assess the relationship between EAPC, epilepsy incidence rates, and the Human Development Index (HDI), Gaussian curve analysis was applied \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Additionally, risk factors for epilepsy across all age groups were evaluated. A \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Global Incidence Trends of Childhood Epilepsy\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Incidence\u003c/h2\u003e \u003cp\u003eIn 2021, the global incidence of childhood epilepsy reached 1,227,191 cases (95% UI: 786,363.03\u0026ndash;1,734,488.13), reflecting a 26.34% increase compared to 1990 (95% UI: 6.81\u0026ndash;51.19%). Between 1990 and 2021, the global incidence rate followed an upward trajectory, rising from 55.85 cases per 100,000 population (95% UI: 35.89\u0026ndash;78.70) to 61.00 cases per 100,000 population (95% UI: 39.00\u0026ndash;86.21). This increase corresponded to an EAPC of 0.20 (95% CI: 0.14\u0026ndash;0.26).\u003c/p\u003e \u003cp\u003eOver the three-decade period, a consistent rise in childhood epilepsy incidence was observed across all pediatric age groups. The most substantial increase occurred in adolescents aged 10\u0026ndash;14 years (40.79% increase), whereas the smallest percentage increase was observed in infants under 12 months (8.81% increase). Interestingly, despite exhibiting the lowest percentage growth, the neonatal population (0\u0026ndash;1 year) consistently had the highest absolute incidence rates throughout the study period. Additionally, a persistent gender disparity was observed in the neonatal group, with male infants consistently exhibiting higher incidence rates than females. (Details are provided in Table and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIncidence of Epilepsy in Children Between 1990 and 2021 at the Global and Regional Level\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eRate per 100000 (95% UI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1990\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncident cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncident cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCases change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEAPC\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e971368.10\u003c/p\u003e \u003cp\u003e(624226.22,\u003c/p\u003e \u003cp\u003e1368635.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.85\u003c/p\u003e \u003cp\u003e(35.89,\u003c/p\u003e \u003cp\u003e78.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1227191.11\u003c/p\u003e \u003cp\u003e(786363.03,\u003c/p\u003e \u003cp\u003e1734488.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.00\u003c/p\u003e \u003cp\u003e(39.09,86.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.34\u003c/p\u003e \u003cp\u003e(6.81,\u003c/p\u003e \u003cp\u003e51.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003cp\u003e(0.14,\u003c/p\u003e \u003cp\u003e0.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Asia\u003c/p\u003e \u003c/td\u003e \u003ctd 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align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.67\u003c/p\u003e \u003cp\u003e(-31.66,\u003c/p\u003e \u003cp\u003e81.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003cp\u003e(-0.14,0.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27201.27\u003c/p\u003e \u003cp\u003e(16827.24,\u003c/p\u003e \u003cp\u003e40171.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.86\u003c/p\u003e \u003cp\u003e(32.70,\u003c/p\u003e \u003cp\u003e78.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16376.83\u003c/p\u003e \u003cp\u003e(9617.39,\u003c/p\u003e \u003cp\u003e24685.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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\u003cp\u003e6247.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.37\u003c/p\u003e \u003cp\u003e(23.43,109.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.84\u003c/p\u003e \u003cp\u003e(-51.56,\u003c/p\u003e \u003cp\u003e189.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003cp\u003e(-0.33,\u003c/p\u003e \u003cp\u003e-0.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern Europe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55148.02\u003c/p\u003e \u003cp\u003e(33151.58,\u003c/p\u003e \u003cp\u003e81906.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.65\u003c/p\u003e \u003cp\u003e(46.68,\u003c/p\u003e \u003cp\u003e115.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57086.48\u003c/p\u003e \u003cp\u003e(32083.43,\u003c/p\u003e \u003cp\u003e87093.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.80\u003c/p\u003e \u003cp\u003e(47.10,127.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003cp\u003e(-25.72,\u003c/p\u003e \u003cp\u003e37.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003cp\u003e(0.21,\u003c/p\u003e \u003cp\u003e0.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8808.11\u003c/p\u003e \u003cp\u003e(4162.97,\u003c/p\u003e \u003cp\u003e14118.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.01\u003c/p\u003e \u003cp\u003e(27.89,\u003c/p\u003e \u003cp\u003e94.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9970.39\u003c/p\u003e \u003cp\u003e(4211.20,\u003c/p\u003e \u003cp\u003e17278.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.78\u003c/p\u003e \u003cp\u003e(29.05,119.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003cp\u003e(-48.32,\u003c/p\u003e \u003cp\u003e133.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003cp\u003e(0.39,\u003c/p\u003e \u003cp\u003e0.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61379.06\u003c/p\u003e \u003cp\u003e(36581.50,\u003c/p\u003e \u003cp\u003e90377.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.34\u003c/p\u003e \u003cp\u003e(56.82,\u003c/p\u003e \u003cp\u003e140.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57735.11\u003c/p\u003e \u003cp\u003e(36541.73,\u003c/p\u003e \u003cp\u003e86874.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.94\u003c/p\u003e \u003cp\u003e(57.56,136.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.94\u003c/p\u003e \u003cp\u003e(-31.57,\u003c/p\u003e \u003cp\u003e28.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003cp\u003e(-0.39,\u003c/p\u003e \u003cp\u003e-0.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income Asia Pacific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20378.57\u003c/p\u003e \u003cp\u003e(11274.01,\u003c/p\u003e \u003cp\u003e31574.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.89\u003c/p\u003e \u003cp\u003e(32.03,\u003c/p\u003e \u003cp\u003e89.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14441.00\u003c/p\u003e \u003cp\u003e(8282.52,\u003c/p\u003e \u003cp\u003e22209.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.40\u003c/p\u003e \u003cp\u003e(36.93,99.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-29.14\u003c/p\u003e \u003cp\u003e(-51.21,\u003c/p\u003e \u003cp\u003e0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003cp\u003e(-0.16,0.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-income North America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34225.25\u003c/p\u003e \u003cp\u003e(20574.85,\u003c/p\u003e \u003cp\u003e51553.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.49\u003c/p\u003e \u003cp\u003e(33.36,\u003c/p\u003e \u003cp\u003e83.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38338.38\u003c/p\u003e \u003cp\u003e(20507.57,\u003c/p\u003e \u003cp\u003e59593.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.43\u003c/p\u003e \u003cp\u003e(31.25,90.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.02\u003c/p\u003e \u003cp\u003e(-13.35,\u003c/p\u003e \u003cp\u003e35.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003cp\u003e(-0.03,0.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaribbean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8300.47\u003c/p\u003e \u003cp\u003e(4565.18,\u003c/p\u003e \u003cp\u003e12610.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.73\u003c/p\u003e \u003cp\u003e(40.00,\u003c/p\u003e \u003cp\u003e110.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8269.95\u003c/p\u003e \u003cp\u003e(4332.50,\u003c/p\u003e \u003cp\u003e12885.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.88\u003c/p\u003e \u003cp\u003e(37.66,112.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003cp\u003e(-40.23,\u003c/p\u003e \u003cp\u003e58.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003cp\u003e(-0.10,\u003c/p\u003e \u003cp\u003e-0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Africa and the Middle East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96450.22\u003c/p\u003e \u003cp\u003e(56519.15,\u003c/p\u003e \u003cp\u003e144633.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.65\u003c/p\u003e \u003cp\u003e(40.23,\u003c/p\u003e \u003cp\u003e102.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132128.53\u003c/p\u003e \u003cp\u003e(77661.22,\u003c/p\u003e \u003cp\u003e204905.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.07\u003c/p\u003e \u003cp\u003e(42.36,111.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.99\u003c/p\u003e \u003cp\u003e(-4.97,\u003c/p\u003e \u003cp\u003e94.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003cp\u003e(0.19,\u003c/p\u003e \u003cp\u003e0.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndean Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13264.71\u003c/p\u003e \u003cp\u003e(6002.37,\u003c/p\u003e \u003cp\u003e21311.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.31\u003c/p\u003e \u003cp\u003e(40.41,\u003c/p\u003e \u003cp\u003e143.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16943.20\u003c/p\u003e \u003cp\u003e(8153.32,\u003c/p\u003e \u003cp\u003e27210.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.64\u003c/p\u003e \u003cp\u003e(45.06,150.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.73\u003c/p\u003e \u003cp\u003e(-38.26,\u003c/p\u003e \u003cp\u003e180.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.53\u003c/p\u003e \u003cp\u003e(-0.73,\u003c/p\u003e \u003cp\u003e-0.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTropical Latin America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44768.73\u003c/p\u003e \u003cp\u003e(26146.99,\u003c/p\u003e \u003cp\u003e69218.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.50\u003c/p\u003e \u003cp\u003e(48.77,\u003c/p\u003e \u003cp\u003e129.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35251.85\u003c/p\u003e \u003cp\u003e(21286.95,\u003c/p\u003e \u003cp\u003e52134.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.23\u003c/p\u003e \u003cp\u003e(42.41,103.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-21.26\u003c/p\u003e \u003cp\u003e(-43.46,\u003c/p\u003e \u003cp\u003e13.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003cp\u003e(-0.73,\u003c/p\u003e \u003cp\u003e-0.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68995.75\u003c/p\u003e \u003cp\u003e(36520.18,\u003c/p\u003e \u003cp\u003e107964.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.18\u003c/p\u003e \u003cp\u003e(40.32,\u003c/p\u003e \u003cp\u003e119.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137605.70\u003c/p\u003e \u003cp\u003e(80028.81,\u003c/p\u003e \u003cp\u003e201246.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.12\u003c/p\u003e \u003cp\u003e(44.85,112.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.44\u003c/p\u003e \u003cp\u003e(45.27,\u003c/p\u003e \u003cp\u003e208.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003cp\u003e(-0.32,\u003c/p\u003e \u003cp\u003e-0.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21551.10\u003c/p\u003e \u003cp\u003e(7515.69,\u003c/p\u003e \u003cp\u003e38447.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.19\u003c/p\u003e \u003cp\u003e(29.71,\u003c/p\u003e \u003cp\u003e151.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46824.10\u003c/p\u003e \u003cp\u003e(17837.41,\u003c/p\u003e \u003cp\u003e81337.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.79\u003c/p\u003e \u003cp\u003e(30.40,138.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e117.27\u003c/p\u003e \u003cp\u003e(-10.64,\u003c/p\u003e \u003cp\u003e523.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003cp\u003e(-0.13,0.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Asia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193523.30\u003c/p\u003e \u003cp\u003e(111840.24,\u003c/p\u003e \u003cp\u003e294495.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.66\u003c/p\u003e \u003cp\u003e(25.81,\u003c/p\u003e \u003cp\u003e67.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e229608.54\u003c/p\u003e \u003cp\u003e(141040.53,\u003c/p\u003e \u003cp\u003e332358.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.29\u003c/p\u003e \u003cp\u003e(27.82,65.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.65\u003c/p\u003e \u003cp\u003e(-14.93,\u003c/p\u003e \u003cp\u003e80.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e(-0.15,0.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72292.14\u003c/p\u003e \u003cp\u003e(42172.47,\u003c/p\u003e \u003cp\u003e109107.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.26\u003c/p\u003e \u003cp\u003e(47.99,\u003c/p\u003e \u003cp\u003e124.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172799.03\u003c/p\u003e \u003cp\u003e(107800.40,\u003c/p\u003e \u003cp\u003e248211.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.46\u003c/p\u003e \u003cp\u003e(50.19,115.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e139.03\u003c/p\u003e \u003cp\u003e(86.71,\u003c/p\u003e \u003cp\u003e225.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003cp\u003e(-0.38,\u003c/p\u003e \u003cp\u003e-0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Sub-Saharan Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14793.40\u003c/p\u003e \u003cp\u003e(8830.74,\u003c/p\u003e \u003cp\u003e22184.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.50\u003c/p\u003e \u003cp\u003e(42.68,\u003c/p\u003e \u003cp\u003e107.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16580.71\u003c/p\u003e \u003cp\u003e(10046.76,\u003c/p\u003e \u003cp\u003e25436.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.90\u003c/p\u003e \u003cp\u003e(41.75,105.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.08\u003c/p\u003e \u003cp\u003e(-24.76,\u003c/p\u003e \u003cp\u003e64.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003cp\u003e(-0.58,\u003c/p\u003e \u003cp\u003e-0.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131788.23\u003c/p\u003e \u003cp\u003e(82694.18,\u003c/p\u003e \u003cp\u003e188452.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.16\u003c/p\u003e \u003cp\u003e(30.22,\u003c/p\u003e \u003cp\u003e68.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122321.80\u003c/p\u003e \u003cp\u003e(72912.35,\u003c/p\u003e \u003cp\u003e188315.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.98\u003c/p\u003e \u003cp\u003e(31.58,81.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.18\u003c/p\u003e \u003cp\u003e(-27.45,\u003c/p\u003e \u003cp\u003e16.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003cp\u003e(0.12,\u003c/p\u003e \u003cp\u003e0.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-middle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255940.09\u003c/p\u003e \u003cp\u003e(151098.03,\u003c/p\u003e \u003cp\u003e382225.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.21\u003c/p\u003e \u003cp\u003e(32.00,\u003c/p\u003e \u003cp\u003e80.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e341687.50\u003c/p\u003e \u003cp\u003e(215945.36,\u003c/p\u003e \u003cp\u003e481879.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.93\u003c/p\u003e \u003cp\u003e(37.24,83.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.50\u003c/p\u003e \u003cp\u003e(-0.91,\u003c/p\u003e \u003cp\u003e85.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003cp\u003e(0.17,\u003c/p\u003e \u003cp\u003e0.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119259.76\u003c/p\u003e \u003cp\u003e(76300.87,\u003c/p\u003e \u003cp\u003e178953.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.18\u003c/p\u003e \u003cp\u003e(41.06,\u003c/p\u003e \u003cp\u003e96.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121917.97\u003c/p\u003e \u003cp\u003e(67742.29,\u003c/p\u003e \u003cp\u003e188732.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.66\u003c/p\u003e \u003cp\u003e(39.26,109.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003cp\u003e(-18.17,\u003c/p\u003e \u003cp\u003e21.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003cp\u003e(0.19,\u003c/p\u003e \u003cp\u003e0.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150783.90\u003c/p\u003e \u003cp\u003e(80733.23,\u003c/p\u003e \u003cp\u003e230378.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.87\u003c/p\u003e \u003cp\u003e(35.27,\u003c/p\u003e \u003cp\u003e100.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e306197.53\u003c/p\u003e \u003cp\u003e(185486.33,\u003c/p\u003e \u003cp\u003e438447.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.53\u003c/p\u003e \u003cp\u003e(40.30,95.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e103.07\u003c/p\u003e \u003cp\u003e(58.81,\u003c/p\u003e \u003cp\u003e182.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003cp\u003e(-0.16,\u003c/p\u003e \u003cp\u003e-0.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle SDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312668.14\u003c/p\u003e \u003cp\u003e(193388.77,\u003c/p\u003e \u003cp\u003e442722.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.17\u003c/p\u003e \u003cp\u003e(33.50,\u003c/p\u003e \u003cp\u003e76.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e334091.53\u003c/p\u003e \u003cp\u003e(209540.17,\u003c/p\u003e \u003cp\u003e485226.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.94\u003c/p\u003e \u003cp\u003e(36.97,85.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.85\u003c/p\u003e \u003cp\u003e(-13.67,\u003c/p\u003e \u003cp\u003e34.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003cp\u003e(0.06,\u003c/p\u003e \u003cp\u003e0.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eEAPC: estimated annual percentage change; SDI: Sociodemographic Index; UI: uncertainty interval.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eEAPC values are expressed as 95% CIs.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003e2.1.2 Mortality\u003c/h3\u003e\n\u003cp\u003eBetween 1990 and 2021, global epilepsy-related childhood mortality exhibited a significant decline, with total deaths decreasing by 29.5%, from 25,768 cases (95% UI: 17,567\u0026ndash;30,914) in 1990 to 18,171 cases (95% UI: 13,891\u0026ndash;21,418) in 2021. The mortality rate also followed a consistent downward trend, declining from 1.48 per 100,000 population (95% UI: 1.01\u0026ndash;1.78) in 1990 to 0.90 per 100,000 population (95% UI: 0.69\u0026ndash;1.06) in 2021. This decline corresponds to an EAPC of -1.39 (95% CI: -1.48 to -1.30) (see Supplementary Table\u0026nbsp;1). Mortality rates declined across all pediatric age groups, with the most substantial decrease observed in children aged 2\u0026ndash;4 years (37.88% reduction). In 1990, the highest number of epilepsy-related deaths occurred in infants under 1 year old (6,178 deaths), whereas in 2021, the highest number of deaths was recorded among children aged 10\u0026ndash;14 years (5,249 deaths). Additionally, in 2021, boys consistently exhibited higher mortality rates than girls across all age groups. The lowest epilepsy-related mortality rate was observed in children aged 5\u0026ndash;9 years (0.55 per 100,000 population) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e\n\u003ch3\u003e2.1.3 DALYs\u003c/h3\u003e\n\u003cp\u003eBetween 1990 and 2021, the global burden of childhood epilepsy, as measured by DALYs, exhibited a significant decline. DALYs decreased from 4,188,140 (95% UI: 3,112,385\u0026ndash;5,405,104) in 1990 to 3,564,497 (95% UI: 2,700,944\u0026ndash;4,753,410) in 2021, reflecting an overall reduction of 14.89% over the 31-year observation period. The corresponding EAPC was \u0026minus;\u0026thinsp;0.94 (95% CI: -1.00 to -0.88) (see Supplementary Table\u0026nbsp;1). Except for children aged 10\u0026ndash;14 years, who exhibited a 4.05% increase in epilepsy-related disability DALYs, all other pediatric age groups experienced a decline in DALYs due to epilepsy-related disability. The most substantial reduction (30.31%) was observed among infants under 1 year old. In 1990, the highest epilepsy-related disability burden was recorded in the 5\u0026ndash;9 age group (1,157,772 DALYs), whereas in 2021, the highest burden shifted to the 10\u0026ndash;14 age group (1,145,807 DALYs). Additionally, in 2021, boys aged 0\u0026ndash;14 consistently exhibited higher epilepsy-related DALYs than girls across all age groups. The lowest DALYs due to disability were observed in the 5\u0026ndash;9 age group for both boys (164.55 per 100,000 population) and girls (135.31 per 100,000 population) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Trends in the Incidence of Pediatric Epilepsy across SDI Regions\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Incidence\u003c/h2\u003e \u003cp\u003eIn 2021, low-middle SDI regions exhibited the highest case burden, with 341,688 cases (95% UI: 215,945\u0026ndash;481,879). Between 1990 and 2021, the incidence of childhood epilepsy in low SDI regions increased by 103.07%, representing the most significant proportional rise among all SDI categories. However, the greatest increase in incidence rates was observed in high SDI regions, with an EAPC of 0.28 (95% CI: 0.19\u0026ndash;0.37) (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.2.2Mortality\u003c/h2\u003e \u003cp\u003eAcross all five SDI regions, childhood epilepsy-related mortality rates demonstrated a downward trend over time. In 2021, low-middle SDI regions bore the highest mortality burden, with 6,740 fatalities (95% UI: 4,812\u0026ndash;8,160), whereas the lowest mortality burden was observed in high SDI regions, with 513 deaths (95% UI: 473\u0026ndash;548). Between 1990 and 2021, the most significant reduction in mortality occurred in high-middle SDI regions, showing a 70.99% decline. Epidemiological analysis revealed an inverse SDI gradient, where childhood epilepsy-related mortality rates were highest in low SDI regions (1.46 per 100,000; 95% UI: 1.07\u0026ndash;1.80) and lowest in high SDI regions (0.30 per 100,000; 95% UI: 0.27\u0026ndash;0.32). The steepest mortality decline was observed in high-middle SDI regions, with an EAPC of -3.45 (95% CI: -3.53 to -3.37) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.2.3 DALYs\u003c/h2\u003e \u003cp\u003eIn 2021, the global distribution of childhood epilepsy-related DALYs exhibited significant socioeconomic disparities. Low-middle SDI regions bore the highest burden, recording 1,199,709 DALYs (95% UI: 892,917\u0026ndash;1,592,918). Longitudinal analysis (1990\u0026ndash;2021) revealed divergent trends: Low SDI regions experienced a 46.84% increase in DALYs; All other SDI regions demonstrated progressive reductions in DALYs; High-middle SDI regions showed the greatest improvement, with a 53.40% decrease in pediatric epilepsy-related DALYs (See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and Supplementary Table\u0026nbsp;1 for details).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Geographical Trends in the Incidence of Childhood Epilepsy\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Incidence\u003c/h2\u003e \u003cp\u003eIn 2021, among 21 geographical regions, South Asia reported the highest number of childhood epilepsy cases, with an estimated 229,609 cases (95% UI, 141,041\u0026ndash;332,358), whereas Oceania had the lowest burden, with 2,089 cases (95% UI, 757\u0026ndash;3,754). The Andean Latin America region exhibited the highest incidence rate of childhood epilepsy at 93.64 per 100,000 population (95% UI, 45.06\u0026ndash;150.38), while East Asia had the lowest incidence, at 38.50 per 100,000 (95% UI, 23.17\u0026ndash;57.98). Longitudinal analysis of childhood epilepsy epidemiology from 1990 to 2021 revealed marked geographical disparities in incidence trajectories. When stratified by developmental status, South Latin America showed the most significant increase in incidence (EAPC, 0.49; 95% CI, 0.39\u0026ndash;0.59), whereas Andean Latin America experienced the steepest decline (EAPC, -0.53; 95% CI, -0.73 to -0.32). Notably, incidence rates in high-income Asia-Pacific regions remained largely stable (EAPC, 0.02; 95% CI, -0.16 to -0.21).\u003c/p\u003e \u003cp\u003eA cross-sectional analysis of the disease burden in 2021 estimated a global incidence rate of 61 cases per 100,000 population (95% UI, 39.09\u0026ndash;86.21). Regional stratification indicated that 15 regions, including Andean and Central Latin America, exceeded this global average, while six regions, such as East Asia and Oceania, reported incidence rates below the worldwide mean (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e2.3.2 Mortality\u003c/h2\u003e \u003cp\u003eIn 2021, the distribution of epilepsy-related fatalities among children varied significantly across regions. South Asia recorded the highest number of deaths, with 6,846 fatalities (95% UI, 4,809\u0026ndash;8,554), whereas Australasia reported the lowest, with only 16 deaths (95% UI, 14\u0026ndash;19). Mortality rates were highest in Eastern Sub-Saharan Africa, reaching 2.06 per 100,000 population (95% UI, 1.56\u0026ndash;2.59), which was nearly ten times greater than the rate in Southeast Asia (0.20 per 100,000; 95% UI, 0.13\u0026ndash;0.25).\u003c/p\u003e \u003cp\u003eA long-term analysis spanning 1990 to 2021 revealed contrasting mortality trends across different regions. High-income North America exhibited an increasing trend in epilepsy-related deaths (EAPC, 0.96; 95% CI, 0.46\u0026ndash;1.46), whereas Eastern Europe experienced the most significant decline (EAPC, -4.65; 95% CI, -5.33 to -3.97). In 2021, seven regions, including Eastern Sub-Saharan Africa, had mortality rates above the global average of 0.90 per 100,000, while 14 regions, such as Eastern Europe, reported rates below this threshold (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e2.3.3 DALYs\u003c/h2\u003e \u003cp\u003eThe global burden of pediatric epilepsy in 2021 exhibited considerable regional variations. South Asia accounted for the highest disease burden, with 1,034,317 DALYs (95% UI, 766,837\u0026ndash;1,348,291), whereas Australasia had the lowest impact, with 5,002 DALYs (95% UI, 2,309\u0026ndash;10,005). A 4.3-fold disparity in DALY rates was observed across regions, with Eastern Sub-Saharan Africa reporting the highest rate (306.53 per 100,000; 95% UI, 228.15\u0026ndash;407.97), while Eastern Europe recorded the lowest (70.56 per 100,000; 95% UI, 42.52\u0026ndash;116.77).\u003c/p\u003e \u003cp\u003eLongitudinal analysis from 1990 to 2021 revealed distinct trends across different regions. While Oceania (EAPC, 0.08; 95% CI, -0.02 to 0.19) and high-income North America (EAPC, 0.10; 95% CI, 0.04\u0026ndash;0.16) showed relatively stable or slightly increasing trends, 78% of regions demonstrated declining DALY rates. The most significant reduction was observed in East Asia (EAPC, -3.18; 95% CI, -3.27 to -3.10), whereas South Latin America exhibited only a marginal decline (EAPC, -0.15; 95% CI, -0.25 to -0.05). A comparison with the global DALYs rate benchmark of 177.17 per 100,000 in 2021 indicated that 10 regions, including Eastern Sub-Saharan Africa, had rates above this threshold, while 11 regions, such as Eastern Europe, fell below the global average (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Trends in the Incidence of Childhood Epilepsy in Various Countries\u003c/h2\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Incidence\u003c/h2\u003e \u003cp\u003eEpidemiological data from 2021 highlighted significant variations in childhood epilepsy incidence across 204 countries. India had the highest number of cases, totaling 160,607 (95% UI: 97,445\u0026ndash;232,485). In terms of incidence rates, Ecuador reported the highest rate at 120.09 per 100,000 population (95% UI: 37.04\u0026ndash;214.83), while the Democratic People's Republic of Korea had the lowest at 32.15 per 100,000 (95% UI: 8.47\u0026ndash;61.82) (Refer to Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, Supplementary Table\u0026nbsp;2, and Supplementary Fig.\u0026nbsp;1A).\u003c/p\u003e \u003cp\u003eBetween 1990 and 2021, Equatorial Guinea experienced the most pronounced increase in incidence (EAPC, 1.43; 95% CI: 1.18\u0026ndash;1.68), whereas Burundi saw the greatest decline (EAPC, -1.39; 95% CI: -1.63 to -1.15) (See Supplementary Table\u0026nbsp;2 and Supplementary Fig.\u0026nbsp;2A for details). In 2021, the global incidence rate was estimated at 61.00 per 100,000 (95% UI: 39.09\u0026ndash;86.21). A total of 150 countries (70.6%) reported incidence rates exceeding this global benchmark, whereas 54 nations (25.4%) had lower-than-average rates, reflecting persistent disparities in healthcare accessibility and management of childhood epilepsy worldwide (Refer to Supplementary Fig.\u0026nbsp;3A).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e2.4.2 Mortality\u003c/h2\u003e \u003cp\u003eIn 2021, India accounted for the highest absolute mortality burden, reporting 4,601 deaths (95% UI: 2,699\u0026ndash;6,252) (Refer to Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and Supplementary Table\u0026nbsp;2). Notably, Tajikistan recorded the highest mortality rate at 2.77 per 100,000 (95% UI: 1.84\u0026ndash;4.08), which was 92.3 times greater than Vietnam's rate of 0.03 per 100,000 (95% UI: 0.01\u0026ndash;0.11), representing the widest epidemiological disparity (See Supplementary Table\u0026nbsp;2 and Supplementary Fig.\u0026nbsp;1B).\u003c/p\u003e \u003cp\u003eBetween 1990 and 2021, the Northern Mariana Islands experienced a concerning surge in mortality (EAPC: 3.17; 95% CI: 2.37\u0026ndash;3.98), whereas Estonia achieved the most significant reduction (EAPC: -6.48; 95% CI: -7.35 to -5.59) (Refer to Supplementary Table\u0026nbsp;2 and Supplementary Fig.\u0026nbsp;2B). Globally, the 2021 mortality rate was 0.69 per 100,000 (95% UI: 0.69\u0026ndash;1.06), with 53 countries (25.9%) exceeding this benchmark and 151 (74.1%) reporting lower rates, underscoring persistent disparities in child health outcomes across different developmental contexts (Refer to Supplementary Fig.\u0026nbsp;3B).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e2.4.3 DALYs\u003c/h2\u003e \u003cp\u003eIndia also bore the highest absolute DALYs burden in 2021, with 701,175 DALYs (95% UI: 474,784\u0026ndash;935,405), whereas Niue recorded the lowest burden (0.79 DALYs; 95% UI: 0.48\u0026ndash;1.23), marking an 887,563-fold difference (See Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and Supplementary Table\u0026nbsp;2). DALYs rates varied 6.3-fold across regions, peaking in Zambia (403.33 per 100,000; 95% UI: 235.24\u0026ndash;637.11) and reaching the lowest level in Sweden (64.36 per 100,000; 95% UI: 27.54\u0026ndash;128.69) (Refer to Supplementary Table\u0026nbsp;2 and Supplementary Fig.\u0026nbsp;1C).\u003c/p\u003e \u003cp\u003eFrom 1990 to 2021, Lesotho exhibited the most concerning upward trend in DALYs (EAPC: 0.98; 95% CI: 0.84\u0026ndash;1.12), while China demonstrated the most substantial improvement (EAPC: -3.24; 95% CI: -3.33 to -3.15) (See Supplementary Table\u0026nbsp;2 and Supplementary Fig.\u0026nbsp;2C). The global DALYs rate for 2021 was 177.17 per 100,000 (95% UI: 134.25\u0026ndash;236.27), with 79 countries (38.7%) surpassing this threshold and 125 (61.3%) reporting sub-average rates (Refer to Supplementary Fig.\u0026nbsp;3C).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e2.5 Risk Factors for Childhood Epilepsy\u003c/h2\u003e \u003cp\u003eThe GBD database does not provide specific data on global risk factors for childhood epilepsy-related deaths. Therefore, global risk factor data for epilepsy mortality across all age groups was used as a reference. According to the GBD database, two primary risk factors were identified worldwide: high alcohol use and behavioral risk factors, each contributing equally (0.15; 95% UI: 0.11\u0026ndash;0.20).\u003c/p\u003e \u003cp\u003eIn 2021, these risk factors individually accounted for 12,067 epilepsy-related deaths (95% UI: 8,599\u0026ndash;15,696) globally. A comparative risk factor analysis across 21 global regions revealed Australasia had the highest proportion of epilepsy mortality attributed to combined behavioral factors and alcohol use, contributing 20.15 DALYs per 100,000 (95% UI: 14.98\u0026ndash;25.59). Conversely, the North Africa and Middle East regions exhibited the most favorable risk profiles, with a significantly lower burden (1.28; 95% UI: 0.88\u0026ndash;1.80). Notably, six regions had epilepsy-related mortality rates due to high alcohol use and behavioral risk factors below the global average (0.15; 95% UI: 0.11\u0026ndash;0.20) (Refer to Supplementary Fig.\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOver the three-decade observational period (1990\u0026ndash;2021), global childhood epilepsy epidemiology exhibited a persistent upward trajectory in incidence rates, leading to increasing socioeconomic burdens through rising healthcare expenditures and heightened demands on societal resources. This progressive trend has positioned pediatric epilepsy as a critical global health priority, necessitating urgent multisectoral intervention.\u003c/p\u003e \u003cp\u003eA systematic evaluation of 204 nations and territories quantified three principal disease burden metrics: incidence rates, epilepsy-attributable mortality, and DALYs among children aged 0\u0026ndash;14 years. Using GBD Study methodologies, modifiable risk factor profiles were further delineated across different developmental spectrums. The resultant data provided detailed epidemiological insights, revealing divergent trends, with low- and middle-income countries experiencing accelerated burden escalation despite global prevention efforts.\u003c/p\u003e \u003cp\u003eThese findings highlight the necessity for dynamic surveillance systems capable of detecting emerging epidemiological shifts. A comprehensive understanding of childhood epilepsy's spatiotemporal burden distribution enables health policymakers to develop evidence-based intervention frameworks while clinicians can implement precision diagnostic protocols. Notably, the identification of high-burden regions facilitates targeted resource allocation to areas exhibiting stagnant or worsening epidemiological trends.\u003c/p\u003e \u003cp\u003eBetween 1990 and 2021, despite a significant decline in mortality and DALY rates, the incidence rate of childhood epilepsy has continued to rise, exhibiting substantial regional disparities. In 2021, global childhood epilepsy cases increased by 26.34% compared to 1990. Low SDI regions exhibited high mortality (1.46 per 100,000) and DALYs rates (244.53 per 100,000), underscoring the persistent challenge of unequal medical resource distribution. This trend exhibits a negative correlation with SDI, as evidenced by the largest declines in mortality rates occurring in high SDI regions. Socioeconomic advancements have contributed to a reduced disease burden by enhancing healthcare access and treatment technologies, including the widespread availability of antiepileptic drugs and improvements in neonatal care \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, low SDI regions continue to experience substantial treatment gaps (\u0026gt;\u0026thinsp;75%) and financial barriers to epilepsy care. The COVID-19 pandemic further exacerbated these challenges, leading to higher treatment discontinuation rates and disrupted follow-ups, thereby intensifying health disparities \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe evolving spectrum of childhood epilepsy etiologies warrants attention. Genetic factors play an increasingly prominent role in developmental epileptic encephalopathy, while the risk of neurological sequelae (30\u0026ndash;50%) has risen due to improved survival rates among premature infants, posing a new clinical challenge \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Advancements in specialized epilepsy care have improved patient prognosis. Interventions targeting prenatal and perinatal care have significantly reduced epilepsy incidence in some regions. However, epilepsy treatment in developing countries remains hindered by insufficient medical resources, unstable drug supplies, and a shortage of specialized healthcare professionals, contributing to a persistent burden of preventable cases \u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Risk factor analysis indicates that high alcohol consumption (15% of epilepsy-related deaths) and behavioral risk factors (15%) contribute to epilepsy mortality across all age groups, highlighting the indirect influence of familial and social environments on disease prognosis \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The highest proportion of epilepsy-related risk factors is observed in Central and Eastern Europe (50%), whereas North Africa and the Middle East exhibit the lowest (2%). This disparity may be linked to social determinants, including differences in mental health service accessibility \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMultiple factors contribute to regional disparities in childhood epilepsy. South Asia reports the highest incidence, with 229,609 new cases (95% UI, 172,340\u0026ndash;292,450). Meanwhile, Eastern Sub-Saharan Africa exhibits the highest mortality, with a rate of 2.06 per 100,000 person-years (95% UI, 1.52\u0026ndash;2.71). A substantial treatment gap persists in low- and middle-income countries, where limited healthcare resources contribute to higher epilepsy prevalence and incidence. In contrast, high-income countries employ advanced management strategies, including telemedicine and electroencephalogram monitoring, to mitigate epilepsy-related mortality and enhance patient quality of life \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The positive correlation between the SDI and childhood epilepsy incidence (70.66 per 100,000 person-years in high-SDI regions) likely reflects improved diagnostic accuracy rather than true etiological changes. This association is supported by greater neuroimaging accessibility and broader EEG monitoring availability in advanced healthcare systems \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Notably, infantile epilepsy (\u0026lt;\u0026thinsp;1 year) exhibits a male predominance, which may be attributed to genetic or ethnic factors rather than socioeconomic status \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, this study also has several limitations. First, reliance on the GBD database introduces potential inaccuracies due to incomplete epilepsy registration systems and underreporting of undiagnosed cases. This limitation is particularly pronounced in low-SDI regions, where diagnostic under-coverage may lead to an underestimation of the true disease burden \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Second, risk factor analysis encompasses all age groups and does not isolate child-specific contributors, such as birth injuries or genetic mutations, potentially limiting the relevance of the findings. Third, epilepsy subtypes (such as focal and generalized) and etiologies (such as structural and metabolic) remain unclassified, hindering the development of targeted prevention and management strategies \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Finally, the impact of COVID-19 on epilepsy management, including disruptions in the medication supply chain, remains unquantified, potentially affecting the comprehensiveness of trend analysis.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eBetween 1990 and 2021, the global burden of childhood epilepsy exhibited a paradoxical trend of rising incidence alongside declining mortality, influenced by advancements in medical care, population growth, and improved survival rates of preterm infants. However, low-SDI regions continue to experience disproportionately high mortality rates and DALYs, underscoring the need for targeted interventions. Moving forward, priority should be given to strengthening early screening systems, improving access to antiepileptic drugs, and enhancing grassroots medical training in low-income countries. Additionally, integrating genetic testing and telemedicine technologies can optimize epilepsy management. Public health education on alcohol abuse and behavioral risks remains essential in reducing preventable cases. Finally, global cooperation and equitable resource distribution will be critical in ensuring progress toward childhood epilepsy prevention and control.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGBD \u0026nbsp; \u0026nbsp; Global Burden of Disease\u003c/p\u003e\n\u003cp\u003eSDI \u0026nbsp; \u0026nbsp; \u0026nbsp;Socio-Demographic Index\u003c/p\u003e\n\u003cp\u003eEAPC \u0026nbsp; \u0026nbsp;Estimated Annual Percentage Change\u003c/p\u003e\n\u003cp\u003eDALYs \u0026nbsp; Disability-Adjusted Life Years\u003c/p\u003e\n\u003cp\u003eUI \u0026nbsp; \u0026nbsp; \u0026nbsp; Uncertainty Interval\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; Confidence Interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eK.X., W.Q. and W.X. contributed to designing the study, formal analysis, and writing of the original draft. Y.Y., S.Z. and F.Z. contributed to the review and editing of the manuscript. K.X., W.Q., and Y.S. performed the formal analysis. Y.L., Z.Y., W.H. and W.W. performed the data curation and investigation. W.Y. contributed to the supervision of the manuscript. All authors have accessed and verified the data reported in the manuscript. All authors reviewed the drafted manuscript and approved the final version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eavailability\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe data used for analysis can be accessed from the Health Data website (http://www.healthdata.org/) and the Institute for Health Metrics and Evaluation (http://ghdx.healthdata.org/gbd-results-tool).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFundings:\u003c/strong\u003e This research was supported by the National Natural Science Foundation\u0026apos;s Regional Innovation Development Joint Fund (No. U22A20366), the Key Discipline Construction Project of High-Level Traditional Chinese Medicine (No. Guo Zhong Yi Yao Ren Jiao Han [2023] No. 85), the Special Project for Traditional Chinese Medicine Science and Technology in Anhui Province (No. 202303a07020004), and the Collaborative Innovation Project of Anhui Province Universities (No. GXXT-2020-025).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgments:\u003c/strong\u003eThe authors extend their sincere gratitude to our esteemed colleagues for their invaluable support and expertise, particularly for providing access to the comprehensive dataset meticulously compiled through rigorous research efforts, as well as the specialized JD_GBDR analytical software that significantly facilitated data processing tasks. This collaborative contribution has been instrumental in advancing the methodological framework of our investigation, and we wish to formally acknowledge the substantive value these resources have added to our scholarly inquiry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFine, A. \u0026amp; Wirrell, E. C. 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The challenges and innovations for therapy in children with epilepsy. \u003cem\u003eNat Rev Neurol\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 249-260, doi:10.1038/nrneurol.2014.58 (2014).\u003c/li\u003e\n\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":"Childhood epilepsy, GBD, Incidence, Mortality, DALYs rate, Epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-6319907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6319907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEpilepsy is a major chronic neurological disorder in children, causing significant global disease burden due to neurodevelopmental impairments and socioeconomic impacts. This study assesses global childhood epilepsy trends (1990\u0026ndash;2021), focusing on incidence, mortality, disability-adjusted life years (DALYs), risk factors, and regional disparities. Using Global Burden of Disease Study 2021 data, this cross-sectional analysis evaluated epilepsy epidemiology among children aged 0\u0026ndash;14 across 204 regions. Incidence, mortality, DALYs, and estimated annual percentage changes (EAPCs) were stratified by geography, demographics, and Socio-demographic Index (SDI).In 2021, global childhood epilepsy incidence rose to 1,227,191 cases (26.34% increase since 1990), with incidence rates climbing from 55.85 to 61.00 per 100,000. Mortality and DALYs declined by 29.5% (1.48 to 0.90 per 100,000) and 14.89% (EAPC: \u0026minus;1.39 and \u0026minus;\u0026thinsp;0.94), respectively. Low SDI regions showed the highest mortality (1.46 per 100,000) and DALYs (244.53 per 100,000), while high SDI regions had the highest incidence (70.66 per 100,000). Ecuador (120.09 per 100,000) and Tajikistan (2.77 per 100,000) reported extreme incidence and mortality rates. Key mortality risks included alcohol consumption and behavioral factors (15% each). Despite declining mortality and DALYs, childhood epilepsy incidence continues to rise globally, highlighting persistent disparities.\u003c/p\u003e","manuscriptTitle":"Global, regional, and national epidemiology of childhood epilepsy from 1990 to 2021: a systematic study based on the GBD 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 01:53:29","doi":"10.21203/rs.3.rs-6319907/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":"4e10a9db-8850-4628-b100-351a6baf9953","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48089853,"name":"Health sciences/Neurology/Neurological disorders/Epilepsy"},{"id":48089854,"name":"Health sciences/Neurology/Neurological disorders/Paediatric neurological disorders"}],"tags":[],"updatedAt":"2025-08-12T11:38:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 01:53:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6319907","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6319907","identity":"rs-6319907","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}