Abstract
Background
Mental disorders among school-age children represent a significant global health issue and substantially contribute to the global disease burden. This study aimed to examine the patterns and trends of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and conduct disorder (CD), which are commonly observed in school-age children, from 1990 to 2021, offering valuable insights for health policy formulation, medical resource allocation, and optimization of patient management strategies.
Methods
We analyzed data from the Global Burden of Disease (GBD) 2021 study for 21 regions and 204 countries, focusing on prevalence, disability-adjusted life years (DALYs), gender, and different time periods to gain a deeper understanding of the health burden. We assessed correlations with the Socio-demographic Index (SDI) and employed autoregressive integrated moving average modeling to forecast developments up to 2040, enabling us to better comprehend the burden and trends of these mental disorders.
Results
In 2021, the prevalence rates of ADHD, ASD, and CD per 100,000 population among children aged 5–14 years were 2,374.8, 847.13, and 2,146.48, respectively; DALY rates were 29.17, 162.85, and 262.53, respectively. Compared to 1990, prevalence and DALY rates exhibited changes of −0.06, 0.03, and 0.04, respectively. Australia, Japan, and the UK exhibited particularly notable burdens, with the UK continuing to show rapid growth in ASD, while ADHD and CD increased rapidly in China and India, respectively. Gender and age analyses revealed a higher burden among males. Regions with high SDI displayed higher epidemiological indicators. For the 2040 forecast, the indicators for ADHD in terms of prevalence and DALYs are projected to be 3,796.65 and 44.33 for males, and 1,343.18 and 16.23 for females. For ASD, they are projected to be 1,103.04 and 215.23 for males, and 552.01 and 106.40 for females. For CD, they are projected to be 2,650.69 and 325.64 for males, and 1,593.57 and 200.41 for females.
Conclusion
This study underscores the complex epidemiological landscape of ADHD, ASD, and CD, revealing variations in burden across gender and geographical regions. It emphasizes the urgent need for healthcare professionals and policymakers to devise innovative prevention and healthcare strategies based on the current and evolving burden of these mental disorders, with the aim of alleviating the global disease burden.
Keywords: Attention-deficit/hyperactivity disorder, Autism spectrum disorder, Conduct disorder, Global Burden of Disease, Epidemiology, Trend analysis
Introduction
Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and conduct disorder (CD) pose a significant global health challenge, particularly among school-aged children, and their burden manifests differently across various regions [1–5]. ADHD, characterized by inattention, hyperactivity, and impulsivity, affects approximately 5.3% of children worldwide, with notable variations across income groups [2]. ASD, a neurodevelopmental disorder, is marked by impairments in social communication and the presence of restricted, repetitive patterns of behavior, interests, or activities [3]. CD, a prevalent and highly impairing mental disorder, is characterized by severe antisocial and aggressive behaviors and frequently co-occurs with ADHD [4]. Additionally, these disorders impose substantial direct and indirect costs, encompassing healthcare expenses, lost productivity, and diminished quality of life. For instance, the annual total costs for the USA are estimated to range between 143 billion and 266 billion, including healthcare and educational services for children and income and productivity losses for adults [6].In China, based on 2020 prices, the lifetime discounted cost for individuals with ASD without intellectual disability was 2.65 million and 4.61 million for those with co-occurring intellectual disability; the total cost of ASD in 2020 amounted to USD 41.8 billion [7]. However, there is currently a lack of comprehensive global burden estimates for these three neurodevelopmental disorders among school-aged children. Therefore, the objective of this analysis was to characterize the global burden of ADHD, ASD, and CD across 21 regions and 204 countries and territories worldwide. The 2021 Global Burden of Disease (GBD) study conducted an in-depth assessment of health hazards, supported by over 11,500 collaborators from 164 countries and territories [8–10]. Utilizing the GBD 2021 framework, we estimate prevalence rates, disability-adjusted life years (DALYs), accounting for socioeconomic disparities. By employing validated forecasting models, we project disease burdens up to 2040, addressing gaps in current literature and informing targeted policy interventions.
Methods
Data Source
The present study extracted global prevalence and DALYs (one DALY represents the loss of 1 year of full health due to premature death or disability), along with their 95% uncertainty intervals, spanning from 1990 to 2021 from the GBD database (https://vizhub.healthdata.org/gbd-results/).
Socio-Demographic Index Analysis
The Socio-demographic Index (SDI) was utilized as a metric to assess the socioeconomic status of countries, where a higher score signifies more robust socioeconomic development. Based on GBD studies, regions were stratified into five quintiles: high SDI, high-middle SDI, middle SDI, low-middle SDI, and low SDI [8, 9]. In this study, locally estimated scatterplot smoothing (loess) models, specifically the “geom_smooth” function from the “ggplot2” package, were employed to fit the correlations between SDI and the burdens of ADHD, ASD, and CD.
Trend Prediction
The autoregressive integrated moving average (ARIMA) model is a common epidemiology technique for forecasting time-series data [11]. Specifically, the ARIMA model combines autoregressive and moving average elements with differencing (d) to stabilize the series. In an ARIMA (p, d, q) model, “p” represents the number of autoregressive terms, “d” denotes the order of differencing, and “q” signifies the number of moving average terms.
Statistics Analysis
Five- to fourteen-year prevalence rates and 5- to 14-year DALY rates were expressed as predicted values per 100,000 population, including their 95% uncertainty interval. All analytical procedures and graphical representations were executed using the statistical software R (version 4.4.1).
Results
Global Level
ADHD
In 2021, the global prevalence cases were 32,147,397, with the rate of 2,374.8. Between 1990 and 2021, the change of the rate decreased by −0.06. The global DALYs totaled 394,935 with the rate of DALYs of 29.17, and the change of the rate decreased by −0.06 from 1990 to 2021 (Table 1).
Table 1.
Prevalence cases, 5- to 14-year prevalence rates, DALYs, and 5- to 14-year rates of DALYs for ADHD in 1990 and 2021 for both sexes and rate change of 5- to 14-year rates by GBD
| | 1990 | 2021 | 1990–2021 | ||
|---|---|---|---|---|---|
| 5- to 14-year cases | 5- to 14-year rates per 100,000 | 5- to 14-year cases | 5- to 14-year rates per 100,000 | rate change in 5- to 14-year rates | |
| N (95% UI) | N (95% UI) | N (95% UI) | |||
| Global | |||||
| Prevalence | 28,329,239 (19,368,647, 41,317,882) | 2,531.17 (1,730.56, 3,691.69) | 32,147,397 (21,839,023, 46,703,774) | 2,374.8 (1,613.3, 3,450.11) | −0.06 (−0.09, −0.04) |
| DALYs | 347,461 (178,245, 612,001) | 31.05 (15.93, 54.68) | 394,935 (201,520, 686,587) | 29.17 (14.89, 50.72) | −0.06 (−0.09, −0.03) |
| SDI | |||||
| High SDI | |||||
| Prevalence | 4,347,716 (2,909,009, 6,328,354) | 3,503.52 (2,344.17, 5,099.57) | 4,523,461 (3,014,052, 6,512,602) | 3,811.15 (2,539.43, 5,487.05) | 0.09 (0.04, 0.13) |
| DALYs | 53,457 (27,252, 94,655) | 43.08 (21.96, 76.28) | 55,638 (28,162, 97,592) | 46.88 (23.73, 82.22) | 0.09 (0.04, 0.14) |
| High-middle SDI | |||||
| Prevalence | 6,025,672 (4,167,330, 8,823,534) | 3,334.25 (2,305.95, 4,882.42) | 5,938,001 (4,088,112, 8,597,989) | 3,691.74 (2,541.64, 5,345.49) | 0.11 (0.05, 0.17) |
| DALYs | 74,136 (37,817, 130,783) | 41.02 (20.93, 72.37) | 73,175 (38,148, 127,798) | 45.49 (23.72, 79.45) | 0.11 (0.06, 0.18) |
| Middle SDI | |||||
| Prevalence | 11,280,549 (7,761,861, 16,452,683) | 1,238.61 (823.09, 1,825.75) | 11,757,748 (8,057,394, 17,111,829) | 3,012.92 (2,064.71, 4,384.91) | 0.01 (−0.04, 0.06) |
| DALYs | 138,449 (71,076, 242,416) | 15.05 (7.67, 25.87) | 144,641 (73,506, 250,040) | 37.06 (18.84, 64.07) | 0.01 (−0.04, 0.06) |
| Low-middle SDI | |||||
| Prevalence | 4,933,011 (3,305,660, 7,171,843) | 1,651.89 (1,106.94, 2,401.59) | 6,232,983 (4,172,962, 9,205,068) | 1,605.35 (1,074.78, 2,370.83) | −0.03 (−0.06, 0) |
| DALYs | 60,246 (30,883, 103,530) | 20.17 (10.34, 34.67) | 76,386 (38,736, 132,146) | 19.67 (9.98, 34.04) | −0.02 (−0.06, 0.01) |
| Low SDI | |||||
| Prevalence | 1,710,738 (1,136,831, 2,521,686) | 2,994.75 (2,060.61, 4,367.84) | 3,663,037 (2,437,900, 5,384,097) | 1,243.18 (827.39, 1,827.28) | 0 (−0.02, 0.03) |
| DALYs | 20,787 (10,596, 35,729) | 36.76 (18.87, 64.36) | 44,700 (22,341, 76,717) | 15.17 (7.58, 26.04) | 0.01 (−0.03, 0.05) |
| GBD Regions | |||||
| Andean Latin America | |||||
| Prevalence | 427,696 (288,114, 628,014) | 4,468.88 (3,010.43, 6,561.96) | 539,039 (363,175, 792,106) | 4,514.95 (3,041.92, 6,634.61) | 0.01 (0.01, 0.01) |
| DALYs | 5,239 (2,626, 9,106) | 54.74 (27.44, 95.14) | 6,615 (3,373, 11,499) | 55.41 (28.25, 96.31) | 0.01 (−0.04, 0.07) |
| Australasia | |||||
| Prevalence | 208,832 (143,684, 296,954) | 6,861.17 (4,720.74, 9,756.39) | 278,228 (198,917, 376,842) | 7,106.54 (5,080.77, 9,625.35) | 0.04 (−0.09, 0.22) |
| DALYs | 2,566 (1,333, 4,395) | 84.3 (43.81, 144.39) | 3,421 (1,826, 5,509) | 87.38 (46.65, 140.72) | 0.04 (−0.1, 0.24) |
| Caribbean | |||||
| Prevalence | 455,762 (316,671, 663,846) | 6,259.59 (4,349.27, 9,117.5) | 482,277 (329,074, 714,661) | 6,315.08 (4,308.99, 9,357.97) | 0.01 (−0.02, 0.03) |
| DALYs | 5,573 (2,955, 9,598) | 76.55 (40.59, 131.83) | 5,902 (3,037, 10,283) | 77.29 (39.76, 134.65) | 0.01 (−0.03, 0.05) |
| Central Asia | |||||
| Prevalence | 325,518 (221,231, 483,834) | 2,104.64 (1,430.37, 3,128.24) | 375,161 (255,069, 557,784) | 2,122.1 (1,442.8, 3,155.1) | 0.01 (0.01, 0.01) |
| DALYs | 3,993 (1,965, 6,924) | 25.82 (12.71, 44.77) | 4,608 (2,247, 8,106) | 26.07 (12.71, 45.85) | 0.01 (−0.05, 0.07) |
| Central Europe | |||||
| Prevalence | 440,064 (293,145, 641,675) | 2,162.25 (1,440.37, 3,152.87) | 263,212 (175,432, 383,837) | 2,172.52 (1,447.99, 3,168.14) | 0 (0, 0.01) |
| DALYs | 5,412 (2,665, 9,540) | 26.59 (13.09, 46.87) | 3,237 (1,617, 5,656) | 26.72 (13.34, 46.68) | 0 (−0.03, 0.05) |
| Central Latin America | |||||
| Prevalence | 1,261,835 (849,201, 1,807,792) | 3,050.62 (2,053.03, 4,370.52) | 1,331,075 (906,047, 1,932,548) | 3,067.38 (2,087.93, 4,453.43) | 0.01 (−0.02, 0.03) |
| DALYs | 15,484 (8,090, 26,093) | 37.43 (19.56, 63.08) | 16,356 (8,472, 28,101) | 37.69 (19.52, 64.76) | 0.01 (−0.03, 0.05) |
| Central Sub-Saharan Africa | |||||
| Prevalence | 162,862 (107,762, 241,959) | 1,091.99 (722.55, 1,622.34) | 413,805 (273,736, 614,853) | 1,100.1 (727.73, 1,634.59) | 0.01 (0.01, 0.01) |
| DALYs | 1,981 (999, 3,424) | 13.28 (6.7, 22.96) | 5,068 (2,592, 8,913) | 13.47 (6.89, 23.7) | 0.01 (−0.1, 0.16) |
| East Asia | |||||
| Prevalence | 8,854,438 (6,101,442, 13,173,894) | 4,135.95 (2,850.01, 6,153.58) | 9,279,170 (6,421,932, 13,339,218) | 4,954.75 (3,429.08, 7,122.67) | 0.2 (0.1, 0.3) |
| DALYs | 108,935 (56,203, 193,086) | 50.88 (26.25, 90.19) | 114,468 (59,754, 198,510) | 61.12 (31.91, 106) | 0.2 (0.1, 0.31) |
| Eastern Europe | |||||
| Prevalence | 741,554 (487,730, 1,087,421) | 2,167.03 (1,425.29, 3,177.75) | 553,100 (363,430, 809,023) | 2,184 (1,435.06, 3,194.55) | 0.01 (0, 0.01) |
| DALYs | 9,127 (4,644, 16,044) | 26.67 (13.57, 46.88) | 6,809 (3,462, 11,812) | 26.89 (13.67, 46.64) | 0.01 (−0.03, 0.04) |
| Eastern Sub-Saharan Africa | |||||
| Prevalence | 599,063 (394,340, 883,693) | 1,099.52 (723.77, 1,621.92) | 1,267,750 (836,224, 1,862,744) | 1,105.9 (729.47, 1,624.93) | 0.01 (0, 0.01) |
| DALYs | 7,274 (3,724, 12,470) | 13.35 (6.84, 22.89) | 15,475 (7,893, 26,903) | 13.5 (6.89, 23.47) | 0.01 (−0.03, 0.06) |
| High-income Asia Pacific | |||||
| Prevalence | 758,601 (507,074, 1,118,629) | 3,036.39 (2,029.63, 4,477.45) | 476,444 (322,731, 688,744) | 2,982.74 (2,020.43, 4,311.82) | −0.02 (−0.06, 0.03) |
| DALYs | 9,325 (4,729, 16,575) | 37.33 (18.93, 66.34) | 5,866 (2,960, 10,196) | 36.72 (18.53, 63.83) | −0.02 (−0.07, 0.04) |
| High-income North America | |||||
| Prevalence | 1,775,975 (1,179,026, 2,592,823) | 4,440.4 (2,947.87, 6,482.73) | 2,151,356 (1,395,276, 3,153,470) | 4,768.04 (3,092.34, 6,989.02) | 0.07 (−0.03, 0.16) |
| DALYs | 21,830 (11,141, 37,604) | 54.58 (27.85, 94.02) | 26,452 (13,196, 46,674) | 58.63 (29.25, 103.44) | 0.07 (−0.03, 0.17) |
| North Africa and Middle East | |||||
| Prevalence | 2,410,917 (1,660,901, 3,539,791) | 2,701.13 (1,860.83, 3,965.89) | 3,030,546 (2,076,365, 4,466,142) | 2,480.29 (1,699.36, 3,655.23) | −0.08 (−0.12, −0.04) |
| DALYs | 29,572 (14,689, 51,862) | 33.13 (16.46, 58.11) | 37,254 (18,580, 63,992) | 30.49 (15.21, 52.37) | −0.08 (−0.13, −0.03) |
| Oceania | |||||
| Prevalence | 40,260 (27,474, 58,452) | 2,402.61 (1,639.6, 3,488.28) | 75,628 (51,608, 109,809) | 2,403.63 (1,640.21, 3,489.96) | 0 (0, 0) |
| DALYs | 492 (251, 866) | 29.38 (14.98, 51.71) | 925 (461, 1,658) | 29.4 (14.65, 52.69) | 0 (−0.09, 0.1) |
| South Asia | |||||
| Prevalence | 3,318,847 (2,159,646, 4,927,750) | 1,201.02 (781.53, 1,783.24) | 4,229,061 (2,773,388, 6,221,698) | 1,213.76 (795.97, 1,785.65) | 0.01 (−0.07, 0.09) |
| DALYs | 40,425 (20,715, 70,721) | 14.63 (7.5, 25.59) | 51,715 (25,730, 89,218) | 14.84 (7.38, 25.61) | 0.01 (−0.07, 0.1) |
| Southeast Asia | |||||
| Prevalence | 2,343,336 (1,599,033, 3,409,791) | 2,083.75 (1,421.89, 3,032.06) | 2,293,760 (1,536,524, 3,402,940) | 1,971.11 (1,320.39, 2,924.27) | −0.05 (−0.1, −0.03) |
| DALYs | 28,742 (14,563, 49,839) | 25.56 (12.95, 44.32) | 28,207 (14,155, 49,479) | 24.24 (12.16, 42.52) | −0.05 (−0.11, −0.01) |
| Southern Latin America | |||||
| Prevalence | 289,888 (190,855, 430,779) | 2,964.24 (1,951.59, 4,404.92) | 302,900 (200,989, 445,428) | 2,964.65 (1,967.19, 4,359.64) | 0 (−0.1, 0.1) |
| DALYs | 3,564 (1,834, 6,188) | 36.45 (18.75, 63.27) | 3,725 (1,887, 6,507) | 36.46 (18.47, 63.69) | 0 (−0.11, 0.13) |
| Southern Sub-Saharan Africa | |||||
| Prevalence | 144,788 (95,234, 213,800) | 1,095.51 (720.58, 1,617.69) | 177,549 (116,911, 262,415) | 1,107.14 (729.02, 1,636.34) | 0.01 (0.01, 0.01) |
| DALYs | 1,769 (889, 3,098) | 13.39 (6.73, 23.44) | 2,173 (1,098, 3,855) | 13.55 (6.85, 24.04) | 0.01 (−0.06, 0.08) |
| Tropical Latin America | |||||
| Prevalence | 1,597,430 (1,086,383, 2,344,488) | 4,372.35 (2,973.56, 6,417.14) | 1,453,768 (974,790, 2,127,795) | 4,407.3 (2,955.21, 6,450.71) | 0.01 (−0.08, 0.11) |
| DALYs | 19,531 (10,097, 33,442) | 53.46 (27.64, 91.54) | 17,800 (9,131, 31,228) | 53.96 (27.68, 94.67) | 0.01 (−0.08, 0.11) |
| Western Europe | |||||
| Prevalence | 1,586,088 (1,095,747, 2,255,536) | 3,300.12 (2,279.88, 4,693.01) | 1,613,224 (1,069,708, 2,317,398) | 3,440.51 (2,281.36, 4,942.29) | 0.04 (−0.02, 0.1) |
| DALYs | 19,507 (10,159, 33,557) | 40.59 (21.14, 69.82) | 19,821 (9,952, 34,706) | 42.27 (21.23, 74.02) | 0.04 (−0.03, 0.11) |
| Western Sub-Saharan Africa | |||||
| Prevalence | 585,485 (382,678, 881,905) | 1,123.01 (734.01, 1,691.56) | 1,560,342 (1,020,340, 2,328,116) | 1,157.48 (756.9, 1,727.02) | 0.03 (−0.03, 0.08) |
| DALYs | 7,117 (3,575, 12,300) | 13.65 (6.86, 23.59) | 19,037 (9,472, 32,594) | 14.12 (7.03, 24.18) | 0.03 (−0.03, 0.1) |
DALYs, disability-adjusted life years; GBD, Global Burden of Disease; UI, uncertainty interval.
ASD
In 2021, the global prevalence was 11,467,574 with the rate of 847.13. From 1990 to 2021, the change of the rate increased by 0.03. The global DALYs totaled 2,204,464 with the rate of 162.85, and the change of the rate increased by 0.03 from 1990 to 2021 (Table 2).
Table 2.
Prevalence cases, 5- to 14-year prevalence rates, DALYs, and 5- to 14-year rates of DALYs for ASDs in 1990 and 2021 for both sexes and rate change of 5- to 14-year rates by GBD
| | 1990 | 2021 | 1990–2021 | ||
|---|---|---|---|---|---|
| 5- to 14-year cases | 5- to 14-year rates per 100,000 | 5- to 14-year cases | 5- to 14-year rates per 100,000 | rate change in 5- to 14-year rates | |
| N (95% UI) | N (95% UI) | N (95% UI) | |||
| Global | |||||
| Prevalence | 9,237,314 (7,774,085, 10,907,105) | 825.34 (694.6, 974.53) | 11,467,574 (9,673,020, 13,488,180) | 847.13 (714.57, 996.4) | 0.03 (0.01, 0.04) |
| DALYs | 1,771,081 (1,209,660, 2,493,484) | 158.24 (108.08, 222.79) | 2,204,464 (1,491,505, 3,105,760) | 162.85 (110.18, 229.43) | 0.03 (0.01, 0.05) |
| SDI | |||||
| High SDI | |||||
| Prevalence | 1,388,447 (1,170,651, 1,624,824) | 1,118.85 (943.35, 1,309.33) | 1,325,084 (1,114,777, 1,560,806) | 1,116.42 (939.23, 1,315.02) | 0 (−0.02, 0.02) |
| DALYs | 268,139 (184,278, 375,724) | 216.07 (148.5, 302.77) | 255,608 (175,785, 357,214) | 215.36 (148.1, 300.96) | 0 (−0.03, 0.02) |
| High-middle SDI | |||||
| Prevalence | 1,513,367 (1,268,360, 1,789,524) | 837.41 (701.84, 990.22) | 1,376,900 (1,156,155, 1,623,403) | 856.04 (718.8, 1,009.29) | 0.02 (−0.01, 0.05) |
| DALYs | 292,255 (199,881, 412,334) | 161.72 (110.6, 228.16) | 266,404 (180,614, 374,627) | 165.63 (112.29, 232.91) | 0.02 (−0.01, 0.06) |
| Middle SDI | |||||
| Prevalence | 2,787,198 (2,340,054, 3,302,978) | 739.94 (621.23, 876.87) | 2,986,339 (2,504,174, 3,519,879) | 765.25 (641.69, 901.97) | 0.03 (0.01, 0.05) |
| DALYs | 535,511 (364,276, 751,949) | 142.17 (96.71, 199.63) | 576,051 (390,977, 809,825) | 147.61 (100.19, 207.52) | 0.04 (0.01, 0.07) |
| Low-middle SDI | |||||
| Prevalence | 2,313,645 (1,949,488, 2,738,303) | 774.75 (652.81, 916.96) | 3,094,217 (2,607,555, 3,629,044) | 796.94 (671.59, 934.69) | 0.03 (0.01, 0.05) |
| DALYs | 441,000 (303,267, 621,794) | 147.67 (101.55, 208.22) | 593,330 (403,620, 836,831) | 152.82 (103.96, 215.53) | 0.03 (0, 0.07) |
| Low SDI | |||||
| Prevalence | 1,226,384 (1,031,312, 1,448,625) | 887.93 (746.69, 1,048.83) | 2,676,756 (2,244,761, 3,155,214) | 908.45 (761.84, 1,070.83) | 0.02 (0, 0.04) |
| DALYs | 232,587 (161,201, 327,996) | 168.4 (116.71, 237.48) | 511,477 (348,035, 722,102) | 173.59 (118.12, 245.07) | 0.03 (0, 0.06) |
| GBD regions | |||||
| Andean Latin America | |||||
| Prevalence | 69,794 (58,539, 83,135) | 729.26 (611.66, 868.65) | 88,517 (74,077, 104,896) | 741.41 (620.46, 878.6) | 0.02 (−0.03, 0.07) |
| DALYs | 13,348 (9,184, 19,084) | 139.47 (95.96, 199.41) | 17,088 (11,496, 24,139) | 143.12 (96.29, 202.19) | 0.03 (−0.05, 0.13) |
| Australasia | |||||
| Prevalence | 37,473 (31,313, 44,260) | 1,231.17 (1,028.79, 1,454.16) | 48,988 (40,875, 58,501) | 1,251.27 (1,044.03, 1,494.25) | 0.02 (−0.07, 0.09) |
| DALYs | 7,227 (4,981, 10,216) | 237.43 (163.64, 335.64) | 9,457 (6,548, 13,331) | 241.56 (167.25, 340.5) | 0.02 (−0.07, 0.12) |
| Caribbean | |||||
| Prevalence | 54,123 (45,424, 64,181) | 743.34 (623.87, 881.48) | 56,012 (47,090, 66,440) | 733.44 (616.61, 869.99) | −0.01 (−0.04, 0.02) |
| DALYs | 10,375 (7,240, 14,590) | 142.5 (99.43, 200.38) | 10,732 (7,206, 15,280) | 140.52 (94.36, 200.07) | −0.01 (−0.07, 0.05) |
| Central Asia | |||||
| Prevalence | 147,999 (124,008, 174,774) | 956.89 (801.78, 1,130) | 169,719 (142,592, 199,616) | 960.02 (806.57, 1,129.13) | 0 (−0.04, 0.04) |
| DALYs | 28,445 (19,347, 40,141) | 183.91 (125.09, 259.53) | 32,754 (22,007, 46,214) | 185.27 (124.48, 261.41) | 0.01 (−0.05, 0.07) |
| Central Europe | |||||
| Prevalence | 204,923 (173,090, 240,939) | 1,006.89 (850.48, 1,183.85) | 124,144 (104,269, 146,582) | 1,024.67 (860.62, 1,209.87) | 0.02 (−0.02, 0.05) |
| DALYs | 39,560 (26,907, 55,776) | 194.38 (132.21, 274.05) | 23,999 (16,637, 33,579) | 198.08 (137.32, 277.15) | 0.02 (−0.02, 0.06) |
| Central Latin America | |||||
| Prevalence | 338,275 (284,150, 400,811) | 817.82 (686.96, 969) | 357,652 (300,885, 422,471) | 824.19 (693.37, 973.56) | 0.01 (−0.02, 0.03) |
| DALYs | 65,047 (44,954, 91,212) | 157.26 (108.68, 220.51) | 69,060 (46,959, 98,334) | 159.14 (108.21, 226.6) | 0.01 (−0.02, 0.05) |
| Central Sub-Saharan Africa | |||||
| Prevalence | 144,582 (121,964, 171,514) | 969.42 (817.77, 1,150) | 368,769 (309,616, 436,356) | 980.38 (823.12, 1,160.05) | 0.01 (−0.04, 0.08) |
| DALYs | 27,504 (19,312, 38,722) | 184.41 (129.49, 259.63) | 70,589 (47,386, 98,373) | 187.66 (125.98, 261.52) | 0.02 (−0.07, 0.13) |
| East Asia | |||||
| Prevalence | 1,427,626 (1,197,067, 1,689,272) | 666.85 (559.16, 789.07) | 1,317,372 (1,101,422, 1,563,661) | 703.43 (588.12, 834.94) | 0.05 (0.02, 0.09) |
| DALYs | 276,039 (187,076, 388,599) | 128.94 (87.38, 181.52) | 255,708 (171,293, 362,302) | 136.54 (91.46, 193.46) | 0.06 (0.01, 0.11) |
| Eastern Europe | |||||
| Prevalence | 338,742 (285,241, 398,616) | 989.9 (833.56, 1,164.87) | 254,027 (213,038, 301,728) | 1,003.06 (841.21, 1,191.42) | 0.01 (−0.02, 0.04) |
| DALYs | 65,451 (44,240, 91,877) | 191.27 (129.28, 268.49) | 49,173 (33,733, 68,637) | 194.17 (133.2, 271.02) | 0.02 (−0.03, 0.06) |
| Eastern Sub-Saharan Africa | |||||
| Prevalence | 535,201 (449,216, 631,551) | 982.3 (824.49, 1,159.14) | 1,136,226 (958,548, 1,334,543) | 991.17 (836.17, 1,164.17) | 0.01 (−0.02, 0.04) |
| DALYs | 101,669 (70,028, 143,827) | 186.6 (128.53, 263.98) | 217,594 (147,597, 306,158) | 189.81 (128.75, 267.07) | 0.02 (−0.02, 0.06) |
| High-income Asia Pacific | |||||
| Prevalence | 384,370 (324,947, 449,082) | 1,538.49 (1,300.64, 1,797.51) | 262,179 (221,154, 308,365) | 1,641.35 (1,384.52, 1,930.49) | 0.07 (0.03, 0.1) |
| DALYs | 74,194 (50,830, 103,922) | 296.97 (203.45, 415.96) | 50,626 (34,788, 70,973) | 316.94 (217.79, 444.32) | 0.07 (0.02, 0.11) |
| High-income North America | |||||
| Prevalence | 461,545 (389,212, 542,370) | 1,153.98 (973.13, 1,356.07) | 527,670 (445,248, 622,703) | 1,169.47 (986.8, 1,380.09) | 0.01 (−0.01, 0.03) |
| DALYs | 89,169 (61,364, 124,914) | 222.95 (153.42, 312.32) | 101,693 (70,740, 142,626) | 225.38 (156.78, 316.1) | 0.01 (−0.03, 0.05) |
| North Africa and Middle East | |||||
| Prevalence | 731,129 (612,822, 862,053) | 819.14 (686.59, 965.82) | 1,000,058 (840,455, 1,175,493) | 818.48 (687.86, 962.06) | 0 (−0.03, 0.03) |
| DALYs | 140,335 (96,354, 196,850) | 157.23 (107.95, 220.55) | 192,575 (130,832, 270,747) | 157.61 (107.08, 221.59) | 0 (−0.04, 0.05) |
| Oceania | |||||
| Prevalence | 12,401 (10,399, 14,680) | 740.09 (620.58, 876.05) | 23,052 (19,413, 27,565) | 732.64 (616.98, 876.07) | −0.01 (−0.07, 0.05) |
| DALYs | 2,372 (1,604, 3,353) | 141.54 (95.71, 200.09) | 4,441 (3,144, 6,285) | 141.14 (99.93, 199.74) | 0 (−0.1, 0.1) |
| South Asia | |||||
| Prevalence | 2,083,727 (1,753,960, 2,461,170) | 754.06 (634.72, 890.64) | 2,610,585 (2,193,407, 3,052,686) | 749.25 (629.52, 876.13) | −0.01 (−0.03, 0.02) |
| DALYs | 396,144 (271,717, 555,246) | 143.36 (98.33, 200.93) | 499,688 (342,272, 703,367) | 143.41 (98.23, 201.87) | 0 (−0.03, 0.03) |
| Southeast Asia | |||||
| Prevalence | 817,026 (687,282, 966,344) | 726.52 (611.15, 859.29) | 856,611 (719,635, 1,012,042) | 736.12 (618.41, 869.68) | 0.01 (−0.01, 0.04) |
| DALYs | 156,857 (107,408, 221,725) | 139.48 (95.51, 197.16) | 165,302 (111,755, 231,068) | 142.05 (96.03, 198.56) | 0.02 (−0.01, 0.06) |
| Southern Latin America | |||||
| Prevalence | 110,388 (92,639, 130,977) | 1,128.76 (947.28, 1,339.31) | 116,335 (97,567, 137,074) | 1,138.64 (954.94, 1,341.61) | 0.01 (−0.06, 0.07) |
| DALYs | 21,313 (14,652, 29,761) | 217.93 (149.82, 304.32) | 22,441 (15,085, 31,152) | 219.64 (147.65, 304.9) | 0.01 (−0.09, 0.1) |
| Southern Sub-Saharan Africa | |||||
| Prevalence | 130,565 (109,991, 154,058) | 987.9 (832.23, 1,165.66) | 159,571 (134,477, 188,853) | 995.03 (838.56, 1,177.63) | 0.01 (−0.02, 0.04) |
| DALYs | 25,019 (17,056, 35,420) | 189.3 (129.05, 268) | 30,647 (21,008, 43,156) | 191.1 (131, 269.1) | 0.01 (−0.04, 0.05) |
| Tropical Latin America | |||||
| Prevalence | 245,336 (204,437, 290,501) | 671.51 (559.57, 795.13) | 221,479 (185,455, 262,903) | 671.44 (562.23, 797.03) | 0 (−0.03, 0.02) |
| DALYs | 46,979 (32,501, 65,810) | 128.59 (88.96, 180.13) | 42,483 (28,826, 59,680) | 128.79 (87.39, 180.93) | 0 (−0.05, 0.05) |
| Western Europe | |||||
| Prevalence | 456,724 (384,036, 537,592) | 950.29 (799.05, 1,118.55) | 446,986 (376,218, 524,483) | 953.28 (802.36, 1,118.56) | 0 (−0.03, 0.03) |
| DALYs | 88,175 (60,638, 125,245) | 183.46 (126.17, 260.59) | 86,174 (59,132, 121,333) | 183.78 (126.11, 258.77) | 0 (−0.04, 0.04) |
| Western Sub-Saharan Africa | |||||
| Prevalence | 505,365 (425,238, 595,981) | 969.33 (815.64, 1,143.14) | 1,321,623 (1,113,749, 1,555,084) | 980.39 (826.19, 1,153.58) | 0.01 (−0.01, 0.03) |
| DALYs | 95,857 (65,395, 134,569) | 183.86 (125.43, 258.11) | 252,240 (172,110, 353,311) | 187.11 (127.67, 262.09) | 0.02 (−0.01, 0.04) |
DALYs, disability-adjusted life years; GBD, Global Burden of Disease; UI, uncertainty interval.
CD
In 2021, the global prevalence was 29,056,691 with the rate of 2,146.48. From 1990 to 2021, the rate increased by 0.04. The global DALYs were 3,553,816 with the rate of DALYs of 262.53, and the rate increased by 0.04 during this period (Table 3).
Table 3.
Prevalence cases, 5- to 14-year prevalence rates, DALYs, and 5- to 14-year rates of DALYs for CD in 1990 and 2021 for both sexes and rate change of 5- to 14-year rates by GBD
| | 1990 | 2021 | 1990–2021 | ||
|---|---|---|---|---|---|
| 5- to 14-year cases | 5- to 14-year rates per 100,000 | 5- to 14-year cases | 5- to 14-year rates per 100,000 | rate change in 5- to 14-year rates | |
| N (95% UI) | N (95% UI) | N (95% UI) | |||
| Global | |||||
| Prevalence | 23,116,972 (16,488,004, 30,042,912) | 2,065.47 (1,473.18, 2,684.29) | 29,056,691 (20,699,951, 37,794,448) | 2,146.48 (1,529.15, 2,791.96) | 0.04 (0.02, 0.05) |
| DALYs | 2,819,748 (1,541,526, 4,465,103) | 251.94 (137.73, 398.95) | 3,553,816 (1,945,041, 5,582,854) | 262.53 (143.68, 412.42) | 0.04 (0.02, 0.06) |
| SDI | |||||
| High SDI | |||||
| Prevalence | 2,848,733 (2,043,905, 3,648,070) | 2,295.59 (1,647.04, 2,939.72) | 2,773,421 (1,983,238, 3,574,650) | 2,336.69 (1,670.94, 3,011.75) | 0.02 (0, 0.04) |
| DALYs | 349,764 (193,485, 555,685) | 281.85 (155.92, 447.79) | 340,245 (186,865, 537,694) | 286.67 (157.44, 453.02) | 0.02 (−0.01, 0.04) |
| High-middle SDI | |||||
| Prevalence | 3,797,515 (2,701,888, 4,951,093) | 2,101.32 (1,495.06, 2,739.64) | 3,394,644 (2,420,703, 4,389,084) | 2,110.5 (1,504.99, 2,728.76) | 0 (−0.02, 0.03) |
| DALYs | 466,619 (255,052, 740,046) | 258.2 (141.13, 409.5) | 417,867 (227,302, 656,961) | 259.79 (141.32, 408.44) | 0.01 (−0.02, 0.04) |
| Middle SDI | |||||
| Prevalence | 7,614,316 (5,412,089, 9,929,274) | 2,021.44 (1,436.79, 2,636.01) | 8,209,662 (5,848,470, 10,744,956) | 2,103.73 (1,498.67, 2,753.4) | 0.04 (0.02, 0.06) |
| DALYs | 931,231 (500,633, 1,475,538) | 247.22 (132.91, 391.72) | 1,007,827 (547,050, 1,577,545) | 258.26 (140.18, 404.25) | 0.04 (0.02, 0.07) |
| Low-middle SDI | |||||
| Prevalence | 5,960,864 (4,294,333, 7,776,885) | 1,996.08 (1,438.02, 2,604.19) | 8,266,312 (5,847,024, 10,852,040) | 2,129.05 (1,505.94, 2,795.02) | 0.07 (0.04, 0.1) |
| DALYs | 722,704 (393,492, 1,149,082) | 242.01 (131.77, 384.79) | 1,008,509 (551,721, 1,591,151) | 259.75 (142.1, 409.81) | 0.07 (0.04, 0.11) |
| Low SDI | |||||
| Prevalence | 2,873,885 (2,065,320, 3,714,741) | 2,080.75 (1,495.33, 2,689.54) | 6,390,659 (4,544,432, 8,270,084) | 2,168.9 (1,542.31, 2,806.75) | 0.04 (0.03, 0.06) |
| DALYs | 346,783 (189,447, 544,048) | 251.08 (137.16, 393.9) | 776,678 (421,994, 1,207,909) | 263.59 (143.22, 409.95) | 0.05 (0.03, 0.08) |
| GBD regions | |||||
| Andean Latin America | |||||
| Prevalence | 205,006 (144,646, 267,194) | 2,142.05 (1,511.37, 2,791.84) | 258,880 (182,931, 337,522) | 2,168.36 (1,532.21, 2,827.06) | 0.01 (0.01, 0.01) |
| DALYs | 25,030 (13,659, 39,828) | 261.53 (142.72, 416.16) | 31,783 (17,154, 50,592) | 266.21 (143.68, 423.76) | 0.02 (−0.04, 0.09) |
| Australasia | |||||
| Prevalence | 76,017 (55,260, 97,658) | 2,497.54 (1,815.56, 3,208.54) | 96,813 (70,389, 123,100) | 2,472.81 (1,797.88, 3,144.23) | −0.01 (−0.07, 0.05) |
| DALYs | 9,322 (5,088, 14,286) | 306.27 (167.15, 469.37) | 11,894 (6,559, 18,793) | 303.8 (167.54, 480) | −0.01 (−0.1, 0.09) |
| Caribbean | |||||
| Prevalence | 155,696 (110,948, 203,949) | 2,138.38 (1,523.8, 2,801.11) | 165,017 (117,082, 216,255) | 2,160.79 (1,533.1, 2,831.71) | 0.01 (0, 0.02) |
| DALYs | 18,954 (10,258, 29,912) | 260.32 (140.89, 410.82) | 20,068 (10,960, 31,434) | 262.77 (143.52, 411.61) | 0.01 (−0.03, 0.05) |
| Central Asia | |||||
| Prevalence | 337,371 (240,025, 441,819) | 2,181.28 (1,551.88, 2,856.59) | 387,047 (275,477, 506,834) | 2,189.33 (1,558.24, 2,866.91) | 0 (0, 0.01) |
| DALYs | 41,345 (22,404, 66,114) | 267.32 (144.85, 427.46) | 47,458 (25,690, 76,184) | 268.45 (145.32, 430.93) | 0 (−0.04, 0.05) |
| Central Europe | |||||
| Prevalence | 480,012 (345,124, 628,489) | 2,358.54 (1,695.77, 3,088.08) | 287,441 (206,819, 376,198) | 2,372.5 (1,707.05, 3,105.09) | 0.01 (0, 0.01) |
| DALYs | 58,936 (31,604, 92,902) | 289.58 (155.29, 456.48) | 35,330 (19,161, 56,155) | 291.61 (158.15, 463.5) | 0.01 (−0.02, 0.03) |
| Central Latin America | |||||
| Prevalence | 922,664 (661,877, 1,203,154) | 2,230.63 (1,600.16, 2,908.75) | 981,595 (709,903, 1,279,517) | 2,262.02 (1,635.93, 2,948.57) | 0.01 (0, 0.03) |
| DALYs | 112,949 (60,531, 176,338) | 273.06 (146.34, 426.32) | 120,508 (65,187, 187,798) | 277.7 (150.22, 432.77) | 0.02 (−0.01, 0.04) |
| Central Sub-Saharan Africa | |||||
| Prevalence | 316,499 (224,448, 408,257) | 2,122.13 (1,504.93, 2,737.37) | 813,810 (576,370, 1,052,976) | 2,163.52 (1,532.28, 2,799.34) | 0.02 (0.01, 0.02) |
| DALYs | 38,199 (20,820, 60,040) | 256.12 (139.6, 402.57) | 99,067 (53,408, 157,535) | 263.37 (141.98, 418.81) | 0.03 (−0.04, 0.09) |
| East Asia | |||||
| Prevalence | 3,826,188 (2,714,055, 5,097,529) | 1,787.23 (1,267.75, 2,381.08) | 3,415,105 (2,414,989, 4,469,831) | 1,823.54 (1,289.52, 2,386.73) | 0.02 (−0.04, 0.09) |
| DALYs | 470,980 (251,322, 750,515) | 220 (117.39, 350.57) | 422,204 (226,380, 664,709) | 225.44 (120.88, 354.93) | 0.02 (−0.04, 0.1) |
| Eastern Europe | |||||
| Prevalence | 814,208 (594,984, 1,058,470) | 2,379.35 (1,738.71, 3,093.15) | 610,879 (445,317, 793,881) | 2,412.15 (1,758.4, 3,134.76) | 0.01 (0.01, 0.02) |
| DALYs | 100,066 (54,550, 153,865) | 292.42 (159.41, 449.64) | 75,156 (41,056, 115,470) | 296.76 (162.12, 455.95) | 0.01 (−0.01, 0.04) |
| Eastern Sub-Saharan Africa | |||||
| Prevalence | 1,210,115 (868,176, 1,555,155) | 2,221.03 (1,593.44, 2,854.32) | 2,594,783 (1,862,063, 3,343,425) | 2,263.52 (1,624.34, 2,916.58) | 0.02 (0.01, 0.03) |
| DALYs | 146,393 (80,010, 230,265) | 268.69 (146.85, 422.63) | 316,126 (173,432, 495,255) | 275.77 (151.29, 432.03) | 0.03 (0, 0.05) |
| High-income Asia Pacific | |||||
| Prevalence | 586,306 (420,014, 763,534) | 2,346.76 (1,681.16, 3,056.14) | 366,156 (264,531, 474,108) | 2,292.29 (1,656.07, 2,968.11) | −0.02 (−0.04, −0.01) |
| DALYs | 72,021 (39,017, 112,304) | 288.27 (156.17, 449.51) | 45,023 (24,588, 70,530) | 281.86 (153.93, 441.55) | −0.02 (−0.05, 0.01) |
| High-income North America | |||||
| Prevalence | 823,204 (580,846, 1,063,442) | 2,058.22 (1,452.26, 2,658.88) | 993,384 (701,876, 1,302,351) | 2,201.63 (1,555.56, 2,886.39) | 0.07 (0, 0.13) |
| DALYs | 101,049 (55,878, 161,865) | 252.65 (139.71, 404.7) | 121,683 (66,393, 193,160) | 269.69 (147.15, 428.1) | 0.07 (0, 0.13) |
| North Africa and Middle East | |||||
| Prevalence | 1,793,080 (1,253,239, 2,330,701) | 2,008.92 (1,404.1, 2,611.26) | 2,474,525 (1,721,875, 3,218,830) | 2,025.23 (1,409.24, 2,634.39) | 0.01 (0, 0.02) |
| DALYs | 218,997 (119,987, 342,416) | 245.36 (134.43, 383.63) | 302,924 (165,978, 479,167) | 247.92 (135.84, 392.17) | 0.01 (−0.02, 0.04) |
| Oceania | |||||
| Prevalence | 33,985 (24,132, 44,154) | 2,028.15 (1,440.13, 2,634.96) | 63,755 (45,283, 82,833) | 2,026.29 (1,439.21, 2,632.6) | 0 (0, 0) |
| DALYs | 4,142 (2,232, 6,513) | 247.2 (133.22, 388.66) | 7,809 (4,231, 12,542) | 248.2 (134.49, 398.61) | 0 (−0.06, 0.08) |
| South Asia | |||||
| Prevalence | 5,291,856 (3,810,448, 6,953,638) | 1,915.01 (1,378.92, 2,516.37) | 7,367,414 (5,142,520, 9,767,930) | 2,114.47 (1,475.92, 2,803.43) | 0.1 (0.05, 0.16) |
| DALYs | 639,953 (348,472, 1,018,421) | 231.59 (126.1, 368.54) | 897,476 (487,551, 1,419,931) | 257.58 (139.93, 407.53) | 0.11 (0.05, 0.18) |
| Southeast Asia | |||||
| Prevalence | 2,455,176 (1,733,121, 3,196,510) | 2,183.2 (1,541.13, 2,842.41) | 2,590,820 (1,825,300, 3,378,352) | 2,226.38 (1,568.54, 2,903.14) | 0.02 (0.01, 0.02) |
| DALYs | 299,970 (162,629, 472,355) | 266.74 (144.61, 420.03) | 318,258 (170,317, 503,332) | 273.49 (146.36, 432.53) | 0.03 (0, 0.05) |
| Southern Latin America | |||||
| Prevalence | 223,418 (157,516, 296,267) | 2,284.55 (1,610.68, 3,029.47) | 235,326 (165,927, 312,086) | 2,303.27 (1,624.02, 3,054.55) | 0.01 (0.01, 0.01) |
| DALYs | 27,500 (14,511, 43,448) | 281.2 (148.39, 444.27) | 28,910 (15,359, 45,598) | 282.96 (150.32, 446.29) | 0.01 (−0.05, 0.08) |
| Southern Sub-Saharan Africa | |||||
| Prevalence | 304,236 (216,069, 394,570) | 2,301.96 (1,634.85, 2,985.45) | 374,641 (265,178, 486,398) | 2,336.14 (1,653.57, 3,033.03) | 0.01 (0.01, 0.02) |
| DALYs | 37,060 (20,015, 58,157) | 280.41 (151.44, 440.03) | 45,793 (24,548, 71,164) | 285.55 (153.07, 443.75) | 0.02 (−0.02, 0.06) |
| Tropical Latin America | |||||
| Prevalence | 839,189 (603,548, 1,095,330) | 2,296.96 (1,651.98, 2,998.05) | 751,912 (537,100, 976,301) | 2,279.53 (1,628.29, 2,959.79) | −0.01 (−0.07, 0.04) |
| DALYs | 102,073 (54,729, 161,045) | 279.39 (149.8, 440.8) | 91,678 (50,648, 145,031) | 277.93 (153.55, 439.68) | −0.01 (−0.07, 0.05) |
| Western Europe | |||||
| Prevalence | 1,311,626 (934,177, 1,705,929) | 2,729.05 (1,943.71, 3,549.47) | 1,269,796 (912,524, 1,642,039) | 2,708.08 (1,946.13, 3,501.96) | −0.01 (−0.02, 0) |
| DALYs | 160,857 (88,712, 254,410) | 334.69 (184.58, 529.34) | 155,619 (85,353, 245,124) | 331.89 (182.03, 522.77) | −0.01 (−0.03, 0.02) |
| Western Sub-Saharan Africa | |||||
| Prevalence | 1,111,119 (790,626, 1,455,069) | 2,131.22 (1,516.48, 2,790.94) | 2,957,591 (2,119,756, 3,835,711) | 2,193.97 (1,572.45, 2,845.36) | 0.03 (0, 0.05) |
| DALYs | 133,953 (71,571, 208,799) | 256.93 (137.28, 400.49) | 359,048 (194,192, 555,179) | 266.35 (144.05, 411.84) | 0.04 (0, 0.07) |
DALYs, disability-adjusted life years; GBD, Global Burden of Disease; UI, uncertainty interval.
Regional Level
ADHD
In 2021, the prevalence rate of ADHD was highest in high SDI regions, reaching 3,811.15. Geographically, the Australasia region exhibited the highest prevalence rate at 7,106.54 (Table 1; Fig. 1a). From 1990 to 2021, the fastest increase in prevalence was high SDI regions, with a decrease of 0.09. Geographically, the East Asia region showed the most significant upward trend, at 0.2 (Table 1 and online suppl. Fig. S1A; for all online suppl. material, see https://doi.org/10.1159/000550297). The DALY rate was highest in high SDI regions, at 46.88. Geographically, the Australasia region had the highest DALY rate at 87.38 (Table 1; Fig. 1b). Between 1990 and 2021, the fastest increase in DALY rate was observed in high SDI regions, with an increase trend of 0.09. Geographically, East Asia showed the most significant upward trend in DALY rate, at 0.2 (Table 1, online suppl. Fig. S1B).
Fig. 1.
Global distribution of ADHD burden in 2021. a The rate of ADHD’s prevalence. b The rate of ADHD’s DALYs. c The rate of ASD’s prevalence. d The rate of ASD’s DALYs. e The rate of CD’s prevalence. f The rate of CD’s DALYs. DALYs, disability-adjusted life years.
ASD
In 2021, the prevalence rate of ASD was highest in high SDI regions, at 1,116.42. Geographically, the high-income Asia Pacific region exhibited the highest prevalence rate at 1,641.35 (Table 2; Fig. 1c). From 1990 to 2021, the fastest increase in prevalence was observed in middle SDI regions, with an increase of 0.03. Geographically, the high-income Asia Pacific region showed the most significant upward trend at 0.07 (Table 2; online suppl. Fig. S1C). The DALY rate was highest in high SDI regions, at 215.36. Geographically, the high-income Asia Pacific region had the highest DALY rate at 316.94 (Table 2; Fig. 1d). Between 1990 and 2021, the fastest increase in DALY rate was observed in middle SDI regions, with an increase trend of 0.04. Geographically, high-income Asia Pacific showed the fastest upward trend in DALY rate, at 0.07 (Table 2; online suppl. Fig. S1D).
CD
In 2021, the prevalence rate of CD was highest in high SDI regions, reaching 2,336.69. Geographically, the Western Europe region exhibited the highest prevalence rate at 2,708.08 (Table 3; Fig. 1e). From 1990 to 2021, the fastest increase in prevalence was observed in low-middle SDI regions, with an increase of 0.07. Geographically, the South Asia region showed the most significant upward trend, at 0.1 (Table 1; online suppl. Fig. S1E). The DALY rate was highest in high SDI regions, at 286.67. Geographically, the Western Europe region had the highest DALY rate at 331.89 (Table 1; Fig. 1f). Between 1990 and 2021, the fastest increase in DALY rate was observed in low-middle SDI regions, with an increase trend of 0.07. Geographically, South Asia showed the most significant upward trend in DALY rate, at 0.11 (Table 3; online suppl. Fig. S1F).
National and Territorial Level
ADHD
In 2021, Australia had the highest prevalence rate at 7,453.18 (online suppl. Table S1; Fig. 1a). Between 1990 and 2021, China experienced the fastest increase, with an upward trend of 0.2 (online suppl. Table S1; Fig. 1a). Furthermore, Australia had the highest DALY rate at 91.67 (online suppl. Table S1; Fig. 1b). Between 1990 and 2021, China experienced the fastest increase in DALYs, with an upward trend of 0.2 (online suppl. Table S1; Fig. 1b).
ASD
In 2021, Japan had the highest prevalence rate at 1,672.29 (online suppl. Table S2; Fig. 1c). Between 1990 and 2021, the UK experienced the fastest increase in prevalence, with an upward trend of 0.08 (online suppl. Table S1; online suppl. Fig. S1C). Furthermore, Japan had the highest DALY rate at 322.49 (online suppl. Table S1; Fig. 1d). Between 1990 and 2021, the UK experienced the fastest increase in DALYs, with an upward trend of 0.08 (online suppl. Table S2; Fig. 1d).
CD
In 2021, the UK had the highest prevalence rate at 2,837.73 (online suppl. Table S3; Fig. 1e). Between 1990 and 2021, India experienced the fastest increase in prevalence, with an upward trend of 0.12 (online suppl. Table S1; online suppl. Fig. S1E). Furthermore, the UK had the highest DALY rate at 347.9 (online suppl. Table S1; Fig. 1f). Between 1990 and 2021, India experienced the fastest increase in DALYs, with an upward trend of 0.13 (online suppl. Table S3; Fig. 1f).
Gender and Regional Analysis
In 2021, ADHD, ASD, and CD exhibited higher prevalence numbers, rates, and DALYs among males compared to females globally, across five SDI regions, and within 21 GBD regions (Figure 2, online suppl. Fig. S2). No significant gender differences were observed in the proportion of these three mental disorders. Regionally, the burden was generally heavier in areas with relatively higher levels of development. In terms of prevalence proportions, ADHD was more prevalent in East Asia, the Caribbean, Australasia, and Andean Latin America. ASD was more prevalent in high-income Asia Pacific and Sub-Saharan Africa, while CD also showed high prevalence in Sub-Saharan Africa and South Asia. Regarding the proportion of DALYs, the overall pattern was similar to that of prevalence for the three mental disorders, but the proportions of ASD and CD increased notably, particularly for ASD (Fig. 2, online suppl. Fig. S2).
Fig. 2.
Gender and region analysis of ADHD, ASD, and CD burden in 2021. a The rate of prevalence. b Proportional prevalence rate. c The rate of DALYs. d Proportional DALY rate. DALYs, disability-adjusted life years.
Overall Temporal Trends
Globally, the prevalence and DALYs of ADHD showed an increasing trend before 2000, followed by a decline, and then rose again after 2018. For ASD, both prevalence and DALYs exhibited a gradual upward trend. Similarly, the prevalence and DALYs of CD showed an overall increasing trend, with a more pronounced rise between 1995 and 2003. Specifically, the number of ADHD cases and DALYs increased significantly before 2000, declined between 2000 and 2010, and then increased again. For ASD and CD, there was a significant increase before 2000, with a plateau from 2000 to 2010, followed by another significant increase. In terms of prevalence and DALY rates for ADHD, most regions remained relatively stable, with East Asia showing a notable increase from sixth to third place before 1995. For ASD, the prevalence and DALY rates remained stable overall, but high-income Asia Pacific had significantly higher rates than other regions. Regarding CD, the prevalence showed fluctuations, with a significant increase in Eastern Europe before 2001 and a notable decline before 2017, followed by another increase. In terms of numbers, ADHD showed significant fluctuations in middle SDI, high-middle SDI, and East Asia, peaking between 1997 and 1999. For ASD prevalence and DALYs, high-income North America increased rapidly, rising from seventh in 1990 to third in 2021. The trends for CD were similar to those for ASD (Figure 3, online suppl. Fig. S3).
Fig. 3.
Overall temporal trend analysis of the ADHD, ASD, and CD, 1990–2021. a Prevalence rate of three mental disorders. b DALY rate of three mental disorders. c Prevalence rate of ADHD in different regions. d DALY rate of ADHD in different regions. e Prevalence rate of ASD in different regions. f DALY rate of ASD in different regions. g Prevalence rate of CD in different regions. h DALY rate of CD in different regions. DALYs, disability-adjusted life years.
Association between ASR and SDI
This section primarily explores the relationship between the two epidemiological indicators and the SDI. From 1990 to 2021, in the global context and across the 21 GBD regions, the overall prevalence and DALYs of ADHD increased with increasing SDI, but within the middle SDI and low-middle SDI ranges, changes were minimal with increasing SDI. For ASD, higher prevalence and DALYs were observed in low SDI and high SDI regions. CD showed overall fluctuations, increasing with decreasing SDI in the low SDI range, then increasing with increasing SDI, but decreasing again in the high SDI range (Fig. 4). For 204 countries and territories in 2021, the overall trend increased with SDI in the middle SDI range, followed by fluctuations. The pattern for ASD was similar globally and across the 21 GBD regions. CD remained relatively stable in the middle SDI range but increased significantly thereafter (online suppl. Fig. S4).
Fig. 4.
Association of the SDI and 5- to 14-year rate of prevalence and DALYs of ADHD, ASD, and CD in the globe and 21 regions. a 5- to 14-year prevalence rates of ADHD in the globe and regions. b 5- to 14-year DALY rates of ADHD in the globe and 21 regions. c 5- to 14-year prevalence rates of ASD in the globe and regions. d 5- to 14-year DALY rates of ASD in the globe and 21 regions. e 5- to 14-year prevalence rates of CD in the globe and regions. f 5- to 14-year DALY rates of CD in the globe and 21 regions. DALYs, disability-adjusted life years.
Trend Analysis
Based on the ARIMA forecasting model, predictions were made for the period from 2022 to 2040. For ADHD, the prevalence rate among males is forecasted to reach 3,796.65 by 2040, with a DALY rate of 44.33. Among females, the prevalence rate is forecasted to be 1,343.18 by 2040, with a DALY rate of 16.23. For ASD, the prevalence rate among males is forecasted to reach 1,103.04 by 2040, with a DALY rate of 215.23. Among females, the prevalence rate is forecasted to be 552.01 by 2040, with a DALY rate of 106.40. For CD, the prevalence rate among males is forecasted to be 2,650.69 by 2040, with a DALY rate of 325.64. Among females, the prevalence rate is forecasted to reach 1,593.57 by 2040, with a DALY rate of 200.41 (online suppl. Fig. S5–7; online suppl. Table S4–6).
Discussion
ADHD, ASD, and CD represent significant public health challenge worldwide, with a substantial disease burden that has attracted considerable research and attention. This study comprehensively estimated the prevalence and DALYs of ADHD, ASD, and CD across 21 global regions, 204 countries and territories, providing a detailed picture of the disease burden. The main findings are as follows.
The global burden of ADHD, ASD, and CD exhibits significant regional variability, with higher prevalence and DALYs observed in high SDI regions. This burden is particularly evident in Australia, Japan, and the UK, with the UK still showing rapid growth in ASD cases. Meanwhile, ADHD and CD are increasing rapidly in China and India, respectively. This finding is consistent with previous studies that highlight the influence of socioeconomic factors on mental health outcomes, as high-income countries generally have higher rates of mental disorders, possibly due to better diagnostic infrastructure and increased awareness [1]. Similarly, for ADHD, prevalence is higher in regions with stronger healthcare systems, and there are also racial and regional disparities in primary care visits [2, 12, 13]. For ASD, through the Autism and Developmental Disabilities Monitoring (ADDM) Network, higher ASD prevalence is found in certain regions of the USA, with ASD prevalence per 1,000 8-year-old children ranging from 23.1 cases in Maryland to 44.9 cases in California [14]. Both ADHD and ASD are highly heritable neurodevelopmental disorders, with genetic influences playing a dominant role. They share some genetic etiologies but also exhibit differences in loci [15–17]. Additionally, the polygenic risk scores for ADHD and ASD show spatial heterogeneity across different populations. For example, the UK ALSPAC cohort study demonstrated that the impact of genetic risk on ADHD traits is more significant in low socioeconomic status environments [18]. The genetic risk of CD interacts significantly with family environment. For instance, children carrying the low-activity allele of MAOA are more likely to develop CD in abusive or impoverished environments, and in polygenic risk models, the prediction of CD requires integrating both genetic and environmental factors [19–21]. Therefore, differences in allele frequencies among populations in different regions may contribute to the variability in the incidence of ADHD, ASD, and CD across regions [15, 20]. Environmentally, environmental pollution in regions with different development levels may also contribute to disparities. For example, exposure to lead or manganese in highly polluted areas may exacerbate genetic susceptibility [22]. Meanwhile, the role of neurotoxicants in the etiology and associated symptoms of ADHD is an urgent area of research, as this type of disorder appears to disproportionately affect young people of color [23]. In addition, insufficient winter light exposure may disrupt melatonin circadian rhythms, impacting children’s sleep patterns. Good sleep quality may have a preventive effect on ASD, while sleep disturbances in ADHD appear to be a consequence of the disorder [24].
In terms of gender factors, males exhibited higher prevalence rates and DALYs for ADHD, ASD, and CD compared to females across all regions and SDI quintiles. Furthermore, the symptoms of ADHD and ASD vary by gender, with boys demonstrating more externalizing behaviors, such as aggression or hyperactivity, while girls exhibit higher internalizing behaviors, including anxiety, depression, or attention deficits [25]. From genetic and metabolic perspectives, the higher prevalence of ASD and ADHD in males has been linked to prenatal exposure to elevated testosterone levels and reduced aromatase expression. Additionally, high estrogen levels appear to alleviate ADHD symptoms [25]. At the societal level, this disparity is partially attributed to previous studies that included only a limited proportion of girls and primarily relied on subjective measurements of ADHD, which are highly susceptible to reporter bias [26]. In CD, research has revealed that males with CD exhibit lower superior marginal gyrus cortical thickness, while females with CD exhibit higher thickness. Furthermore, males with CD demonstrate higher gyrification and surface area in the superior frontal gyrus, whereas the opposite is true for females [27].
As for the study period and future trends, the temporal trends of ADHD, ASD, and CD indicate a complex dynamic, with fluctuations in prevalence and DALYs over the study period. ARIMA model forecasts suggest that the burden of ADHD and CD will rise overall, while the burden of ASD will decrease overall, although rebounds may occur, emphasizing the need for continued attention to these mental disorders in school-aged children. As for future, due to the current diversity and subjective influences in the diagnosis of mental disorders, for example, some studies are concerned that the current diagnostic criteria for ADHD, clinical practices, and excessive focus on performance may lead to increased prevalence [28]. In the future, more reliable and objective diagnostic indicators can avoid excessive self-treatment or enhance personalized interventions, such as subtype classification based on genetics and neuroimaging, which will optimize personalized interventions [29, 30]. Additionally, the future development of comorbidity research is also noteworthy. Research results indicate that implementing early developmental screening and monitoring for concurrent ASD and ADHD and coordinating strategies are crucial to meeting the clinical and socio-educational needs of these children [31, 32].
While this study provides valuable insights into the global burden of ADHD, ASD, and CD, several limitations must be acknowledged. First, data completeness and quality vary across regions, particularly in low-income areas where diagnostic infrastructure is limited. Second, the diverse diagnostic criteria for ADHD, ASD, and CD may lead to inconsistent inclusion criteria across regions. To address these challenges, multidimensional improvement measures are recommended: (1) strengthen global cooperation to enhance data coverage; (2) advance technological innovation, integrating AI assistance to establish a remote pathology consultation network; (3) develop culturally adapted screening education programs; (4) governments should increase human resource investment, prioritizing localized mental disorder data collection and analysis efforts. These systematic improvements will significantly enhance the quality of disease burden assessment and provide more reliable scientific evidence for global mental disorders among school-age prevention and control.
Acknowledgments
We appreciate the excellent works by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 collaborators.
Statement of Ethics
The data were extracted from GBD 2021 study. The privacy of patients in GBD 2021 study was protected, and identification information was concealed. There were no additional consent procedures from Institutional Ethics Committee. The Medical Ethics Committee of Southern Medical University determined that ethics approval was not required for this study, as the research utilized publicly available data. Written informed consent from participants (or their parent/legal guardian/next of kin) was not required for this study, since the data employed in this study are publicly available.
Conflict of Interest Statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Funding Sources
This work was supported by the Shenzhen Science and Technology Planning Project No. JCYJ20220530165014033, Medical research project of Shenzhen Longhua Medical Association No. 2023LHMA10, Special Fund for Science and Technology Innovation in Longhua District, Shenzhen No. 11501A20240704D87ABF8, Longhua District People's Hospital Research Start-up Grant No. LHYYKYQD20240308 and Shenzhen Medical Key Discipline No. MKD202508210305.
Author Contributions
P.W.: conceptualization, methodology, investigation, data collation, writing, reviewing, and editing. Y.S. and Z.L.: conceptualization, methodology, investigation, writing, reviewing, and editing. Y.Z.: conceptualization, methodology, writing, reviewing, and editing. J.W.: conceptualization, reviewing, and editing.
Funding Statement
This work was supported by the Shenzhen Science and Technology Planning Project No. JCYJ20220530165014033, Medical research project of Shenzhen Longhua Medical Association No. 2023LHMA10, Special Fund for Science and Technology Innovation in Longhua District, Shenzhen No. 11501A20240704D87ABF8, Longhua District People's Hospital Research Start-up Grant No. LHYYKYQD20240308 and Shenzhen Medical Key Discipline No. MKD202508210305.
Data Availability Statement
The data on the burden of disease are available from the Institute for Health Metrics and Evaluation at https://vizhub.healthdata.org/gbd-results/. Furthermore, the datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data on the burden of disease are available from the Institute for Health Metrics and Evaluation at https://vizhub.healthdata.org/gbd-results/. Furthermore, the datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
