Abstract
Background
Schizophrenia is a severe mental disorder with an increasing burden among adolescents and young adults (aged 10–24 years). However, age-specific epidemiological data remains limited. This study aims to analyze the incidence, prevalence, and disability-adjusted life years (DALYs) of schizophrenia in youth (aged 10–24 years) across the Group of Twenty (G20) countries and to project future trends from 2022 to 2035.
Methods
Data were sourced from the Global Burden of Disease (GBD) 2021 dataset, encompassing information on 369 diseases across 204 countries and regions from 1990 to 2021. Bayesian age-period-cohort (APC) modeling was employed to estimate future burden. Age-standardized incidence rates (ASIRs), prevalence rates (ASPRs), and DALY rates (ASDRs) were analyzed by country, sex, and sociodemographic index (SDI).
Result
From 1990 to 2021, the burden of schizophrenia among youth has increased across most G20 countries, with particularly sharp rises observed in China and India. The lowest burdens were reported in Canada, Saudi Arabia, and Australia, which also recorded the lowest DALYs. Russia exhibited marked increases in ASIR, ASPR, and ASDR, while the United States and the United Kingdom showed declines. Substantial variations were observed across gender, regions, and SDI levels. Projections indicate that ASPRs will continue to rise in Australia, China, and Japan through 2035, while declines are anticipated in the United States and Italy, and stability is expected in Argentina and Germany.
Conclusion
The burden of schizophrenia among youth in G20 countries is increasing, accompanied by substantial regional, gender, and socioeconomic disparities. Strengthening early intervention, enhancing diagnostic capacity, and implementing youth-targeted mental health policies are urgently needed.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12888-025-07563-z.
Keywords: Schizophrenia, GBD 2021, Youth, Disease burden, G20 countries
Introduction
Schizophrenia is a severe mental disorder characterized by a chronic disease course and progressive functional decline [1]. Clinically, it comprises a triad of positive symptoms (e.g., hallucinations and delusions), negative symptoms (e.g., affective flattening), and cognitive impairments [2, 3]. Recent epidemiological studies demonstrate a progressive, age-related increase in schizophrenia spectrum disorders that peaks during adolescence and early adulthood [4]. A study found that the proportion of schizophrenia-spectrum cases reaching onset was approximately 3% by age 14, 12.3% by age 18, and 47.8% by age 25, with a median peak age of 25 years (mean: 20.5 years) [5]. Because this early onset typically coincides with critical educational and social development stages, schizophrenia can severely disrupt academic, vocational, and family functioning [6, 7]. These consequences contribute to prolonged disability, increased social stigma, and persistently reduced quality of life. Despite this burden, most research focuses on general populations, leaving the youth-specific burden of schizophrenia critically understudied [8].
Global Burden of Disease (GBD) studies consistently rank schizophrenia among the leading causes of disability across psychiatric conditions. GBD 2021 (released in 2024) ranked schizophrenia the 18th among level 3 causes of global years lived with disability (YLDs) and the third highest among mental disorders [9]. Epidemiological data further indicate that individuals with schizophrenia face a 2- to 3-fold increased risk of premature mortality and an average reduction in life expectancy of 15 years [10, 11]. These outcomes make schizophrenia both a clinical challenge and a significant public health concern. Biologically, the peak onset during adolescence may be driven by a convergence of neurodevelopmental processes, neurotransmitter dysregulation, oxidative stress, and hormonal fluctuations [12–15]. Taken together, this evidence highlights adolescence and early adulthood as a critical window for prevention and early intervention.
Despite relatively advanced healthcare systems, the Group of Twenty (G20) countries, which account for 85% of the global GDP and 64% of the world population, shoulder a growing economic burden from schizophrenia, exemplified by doubled U.S. healthcare costs between 2013 and 2019 [16]. However, most epidemiological research focuses on all-age populations, with far less attention to adolescents and young adults (aged 10–24 years). This evidence gap limits the development of youth-specific prevention strategies and age-adjusted intervention protocols. Given the G20’s important role in shaping global health policies, robust data from these countries are essential for evidence-based resource allocation and cross-national benchmarking.
With this context, this systematic analysis of the schizophrenia burden across G20 countries provides critical insights for optimizing three policy areas: prioritizing health resources, implementing age- and gender-specific interventions, and developing sustainable mental healthcare systems. The findings inform strategies to safeguard family functioning, sustain workforce participation, and reduce the economic burden of schizophrenia. Moreover, they provide an evidence base for precision public health initiatives focused on this vulnerable population.
To address this gap, this study analyzes the schizophrenia burden among youth in G20 countries from 1990 to 2021, based on data from the GBD 2021. Specifically, it provides an analysis based on age-standardized incidence, prevalence, and DALYs, and explores disparities by gender and SDI. The study also projects the future trends in schizophrenia burden up to 2035.
Methods
Data sources
The data used in this study were sourced from the GBD 2021, which provides estimates for 369 diseases in 204 countries and territories from 1990 to 2021. Estimates of incidence, prevalence, and disability-adjusted life years (DALYs) for schizophrenia in G20 countries were obtained from the Global Health Data Exchange query tool (http://ghdx.healthdata.org/gbd-results-tool), a publicly available online tool produced by the Institute for Health Metrics and Evaluation. Subgroup analyses were stratified by geographic region, sex (males and females), age group (10–14 years, 15–19 years, and 20–24 years), and SDI. In accordance with the GBD framework, G20 countries were categorized into five levels: low (< 0.45), low-middle (0.45–0.60), middle (0.61–0.68), high-middle (0.69–0.79), and high (≥ 0.80).
Statistical analysis
All statistical analyses and visualizations were conducted in R (version 4.2.1) and OriginPro 2024. We analyzed age-standardized incidence rates (ASIRs), prevalence rates (ASPRs), and disability-adjusted life years rates (ASDRs), expressing all estimates per 100,000 population, with 95% uncertainty intervals (UIs) from the GBD 2021, focusing on age-standardized rates to ensure cross-country and temporal comparability on a common 10–24-year age distribution. Temporal trends from 1990 to 2021 were summarized using the estimated annual percentage change (EAPC) [17], obtained by fitting log-linear regressions of rates on calendar year. To project future trends of schizophrenia in G20 countries from 2021 to 2035, we applied a Bayesian age-period-cohort (APC) model using the Bayesian age-period-cohort R package (version 0.0.36). We modeled log rates with additive age, period, and cohort effects under informative random walk priors of order 1 (RW1) to minimize bias, ensuring model convergence with the Gelman-Rubin diagnostic. Model adequacy was rigorously assessed using the deviance information criterion (DIC) and posterior predictive checks. To confirm the model’s predictive robustness, we performed an out-of-sample validation by setting the retro parameter to retrospectively project rates for the last 15-time units and comparing them against the observed GBD data for that period. The uncertainty of all models estimates and projections was subsequently quantified using 95% credible intervals (CIs) derived from the respective posterior distributions. For comparability with historical trends, projected temporal changes from 2021 to 2035 were assessed using the EAPC derived from least-squares log-linear regression. The EAPC was calculated by fitting a regression model to the natural logarithm of the rate, namely ln (rate)=α + β× (calendar year) +ε, and the EAPC is defined as 100× (exp [β] − 1). An EAPC >0 indicates an average annual increase; EAPC < 0 indicates a decrease.
Result
The incidence of schizophrenia among youth populations
Table 1 summarizes the incidence and ASIRs of schizophrenia among youth in G20 countries between 1990 and 2021. In 2021, India recorded the highest incidence (approximately 243,679 cases), followed by China (236,175 cases) and Indonesia (51,986 cases). In contrast, the lowest incidence was observed in Italy (6,834 cases), Australia (4,561 cases), and Canada (4,185 cases). Regarding ASIRs, Australia ranked the highest in 2021, followed by China and Indonesia, with values of 20.101, 18.363, and 17.138 per 100,000 population, respectively. The lowest ASIRs were observed in Canada, Russia, and the United Kingdom, with values of 13.217, 11.746, and 11.229 per 100,000 population, respectively.
Table 1.
Incidence and ASIRs of schizophrenia among youth in G20 countries,1990 and 2021
| Countries | Incidence | |||||
|---|---|---|---|---|---|---|
| Full name | Abbreviated name | Number in 1990 (95% UI) | ASIR in 1990 (95% UI) | Numbers in 2021 (95% UI) | ASIR in 2021 (95% UI) | EAPC (95% CI) |
| Canada | CAN | 3541 (3303,3869) |
12.575 (11.805,13.608) |
4185 (3890,4572) |
13.217 (12.4,14.289) |
0.154 (0.111,0.198) |
| United States of America | USA | 47,067 (38456,57258) |
17.932 (14.644,21.634) |
50,622 (41824,60838) |
17.054 (13.903,20.518) |
-0.114 (-0.172,-0.055) |
| Indonesia | IDN | 33,903 (27688,40733) |
17.033 (14.303,20.372) |
51,986 (43248,62004) |
17.138 (14.317,20.427) |
0.07 (0.04,0.099) |
| Mexico | MEX | 12,591 (10117,15341) |
13.921 (11.492,16.726) |
19,105 (15711,23000) |
13.93 (11.445,16.779) |
-0.007 (-0.014,0.001) |
| Brazil | BRA | 22,094 (17891,26817) |
13.759 (11.332,16.596) |
31,484 (26105,38044) |
13.762 (11.382,16.589) |
0.001 (-0.006,0.007) |
| Saudi Arabia | SAU | 2481 (1822,3178) |
14.62 (11.183,18.506) |
6850 (5283,8654) |
14.537 (11.193,18.288) |
-0.034 (-0.045,-0.023) |
| Turkey | TUR | 8642 (7102,10505) |
13.999 (11.608,16.982) |
12,007 (10019,14671) |
13.964 (11.609,17.058) |
-0.025 (-0.031,-0.019) |
| India | IND | 133,991 (108496,164227) |
15.155 (12.455,18.273) |
243,679 (198452,295372) |
15.323 (12.549,18.602) |
0.047 (0.016,0.079) |
| South Africa | ZAF | 5523 (4507,6694) |
14.023 (11.632,16.896) |
8716 (7158,10523) |
13.954 (11.51,16.763) |
-0.008 (-0.012,-0.004) |
| China | CHN | 251,820 (215196,291261) |
18.191 (15.71,20.972) |
236,175 (201684,275708) |
18.363 (15.858,21.18) |
-0.04 (-0.07,-0.009) |
| Russian Federation | RUS | 16,601 (13670,20079) |
10.908 (9.007,13.121) |
14,842 (12311,17922) |
11.746 (9.71,14.115) |
0.345 (0.276,0.415) |
| Japan | JPN | 19,211 (16012,22886) |
15.413 (12.708,18.458) |
15,043 (12447,18174) |
15.582 (12.881,18.757) |
0.223 (0.104,0.343) |
| Republic of Korea | KOR | 7707 (5823,9876) |
14.411 (11.087,18.219) |
6909 (5429,8683) |
14.408 (11.128,18.479) |
0.004 (-0.001,0.009) |
| Australia | AUS | 3518 (3135,3977) |
20.035 (17.951,22.504) |
4561 (4021,5203) |
20.101 (17.781,22.492) |
0.017 (0.01,0.024) |
| France | FRA | 8385 (6550,10483) |
14.278 (11.063,17.726) |
8143 (6473,10167) |
14.227 (11.157,18.062) |
-0.019 (-0.027,-0.012) |
| Germany | DEU | 11,427 (9020,14122) |
13.796 (10.968,17.121) |
10,196 (8080,12574) |
13.797 (10.774,17.162) |
-0.013 (-0.028,0.001) |
| Italy | ITA | 8098 (6775,9704) |
13.86 (11.608,16.607) |
6834 (5726,8204) |
13.898 (11.59,16.694) |
0.009 (0.007,0.01) |
| United Kingdom | GBR | 7063 (5939,8474) |
12.378 (10.413,14.713) |
6888 (5835,8316) |
11.229 (9.449,13.447) |
-0.25 (-0.357,-0.143) |
| Argentina | ARG | 4902 (3699,6192) |
15.211 (11.552,19.252) |
7154 (5444,9081) |
15.226 (11.51,19.33) |
-0.016 (-0.024,-0.009) |
From 1990 to 2021, significant increases in ASIRs were observed in Russia (EAPC: 0.345), Japan (EAPC: 0.223), and Canada (EAPC: 0.154). In contrast, declines occurred in the United Kingdom (EAPC: -0.25), the United States (EAPC: -0.114), and China (EAPC: -0.04). No statistically significant changes in ASIRs were observed in the other G20 countries over the past three decades.
The prevalence of schizophrenia among youth populations
Table 2; Fig. 1 present the prevalence and age-standardized prevalence rates (ASPRs). In 2021, China recorded the highest number of prevalent cases (5,322,430 cases), followed by India (4,373,183 cases) and the United States (1,332,389 cases). In contrast, the lowest prevalence was observed in Canada (125,956 cases), Saudi Arabia (123,531 cases), and Australia (112,864 cases). Regarding ASPRs, Australia had the highest in 2021, at approximately 388.264 per 100,000 population, followed by the United States (354.426) and China (312.364). The lowest ASPRs were reported in South Africa (228.352), the United Kingdom (214.28), and Russia (207.013).
Table 2.
Prevalence and ASPRs of schizophrenia among youth in G20 countries, 1990 and 2021
| Countries | Prevalence | |||||
|---|---|---|---|---|---|---|
| Full name | Abbreviated name | Number in 1990 (95% UI) | ASPR in 1990 (95% UI) | Numbers in 2021 (95% UI) | ASPR in 2021 (95% UI) | EAPC (95% CI) |
| Canada | CAN | 89,321 (88195,90356) |
287.974 (284.413,291.362) |
125,956 (124158,127804) |
288.173 (284.426,291.674) |
0.002 (0,0.003) |
| United States of America | USA | 1,042,439 (869138,1231897) |
370.358 (308.78,437.532) |
1,332,389 (1126997,1559304) |
354.426 (298.139,415.843) |
-0.097 (-0.149,-0.045) |
| Indonesia | IDN | 452,063 (367908,540858) |
278.847 (231.142,331.577) |
888,193 (736989,1054080) |
286.493 (238.102,339.267) |
0.133 (0.097,0.168) |
| Mexico | MEX | 167,905 (136618,202960) |
247.284 (204.858,294.291) |
343,771 (283935,410245) |
248.564 (205.576,296.671) |
0.014 (0.006,0.022) |
| Brazil | BRA | 318,174 (260160,382515) |
240.995 (199.855,286.74) |
607,171 (504438,720997) |
243.368 (202.189,289.746) |
0.038 (0.03,0.047) |
| Saudi Arabia | SAU | 32,839 (24669,42549) |
256.776 (198.367,323.563) |
123,531 (94130,159015) |
256.72 (199.109,326.644) |
-0.001 (-0.014,0.012) |
| Turkey | TUR | 123,013 (101106,148654) |
243.878 (201.933,290.922) |
231,008 (193585,273817) |
246.191 (205.152,293.801) |
0.018 (0.01,0.026) |
| India | IND | 2,083,453 (1715455,2473528) |
286.49 (238,336.768) |
4,373,183 (3639071,5178753) |
296.224 (246.513,349.918) |
0.13 (0.094,0.167) |
| South Africa | ZAF | 71,308 (58309,86001) |
227.337 (187.975,270.924) |
138,891 (113942,166760) |
228.352 (190.169,273.306) |
0.044 (0.035,0.053) |
| China | CHN | 3,558,619 (3076267,4080968) |
300.813 (260.978,343.186) |
5,322,430 (4637003,6043640) |
312.364 (271.692,356.386) |
0.067 (0.037,0.098) |
| Russian Federation | RUS | 322,860 (269208,383077) |
191.435 (158.968,228.103) |
358,774 (301905,422537) |
207.013 (171.727,246.757) |
0.377 (0.297,0.457) |
| Japan | JPN | 416,435 (348737,487572) |
283.327 (236.553,333.333) |
409,399 (348029,474911) |
279.018 (232.224,332.328) |
0.106 (0.005,0.207) |
| Republic of Korea | KOR | 118,524 (90446,153356) |
257.355 (201.394,326.368) |
173,644 (137978,214984) |
258.872 (203.3,324.915) |
0.015 (0.01,0.02) |
| Australia | AUS | 71,416 (65728,76938) |
388.265 (357.6,418.494) |
112,864 (103875,121735) |
388.264 (358.094,419.408) |
0.007 (0.004,0.009) |
| France | FRA | 168,054 (133665,209082) |
260.272 (205.292,325.528) |
197,666 (158868,247062) |
259.458 (202.48,330.575) |
-0.021 (-0.028,-0.014) |
| Germany | DEU | 235,239 (188844,290968) |
243.433 (194.114,303.901) |
253,730 (203539,312553) |
244.298 (192.458,309.407) |
-0.014 (-0.032,0.004) |
| Italy | ITA | 168,049 (142985,195424) |
251.791 (212.089,295.316) |
186,299 (160315,215636) |
251.902 (212.476,296.662) |
-0.004 (-0.007,-0.001) |
| United Kingdom | GBR | 158,755 (136151,182990) |
244.894 (207.32,284.794) |
171,821 (146894,199169) |
214.28 (180.737,250.43) |
-0.327 (-0.469,-0.186) |
| Argentina | ARG | 88,383 (68830,111524) |
277.334 (215.923,350.506) |
138,110 (107232,172805) |
277.587 (215.907,348.358) |
-0.005 (-0.013,0.003) |
Fig. 1.
ASPRs of schizophrenia burden among youth in G20 countries. (A) ASPRs in 1990. (B) Percentage change in ASPRs, 1990–2021. (C) ASPRs in 2021
From 1990 to 2021, Russia exhibited the steepest increase in ASPR, with an EAPC of 0.377, followed by Indonesia (EAPC: 0.133) and India (EAPC: 0.130). In contrast, significant declines were observed in the United Kingdom (EAPC: -0.327), the United States (EAPC: -0.097), and France (EAPC: -0.021).
The DALYs for schizophrenia among youth populations
Table 3 shows the DALYs and age-standardized DALY rates (ASDRs). In 2021, the highest DALYs were reported in China (3,445,845 cases), India (2,781,659 cases), and the United States (824,552 cases). In contrast, Canada (79,715 cases), Saudi Arabia (79,283 cases), and Australia (71,432 cases) reported the lowest. The highest ASDRs were found in Australia, the United States, and China, with values of 247.58, 221.403, and 203.879 per 100,000 population, respectively. Conversely, South Africa (141.772), the United Kingdom (135.938), and Russia (131.286) had the lowest.
Table 3.
DALYs and ASDRs of schizophrenia among youth in G20 countries, 1990 and 2021
| Countries | DALYs | |||||
|---|---|---|---|---|---|---|
| Full name | Abbreviated name | Number in 1990 (95% UI) | ASDR in 1990 (95% UI) | Numbers in 2021 (95% UI) | ASDR in 2021 (95% UI) | EAPC (95% CI) |
| Canada | CAN |
57,359 (43499,68429) |
185.071 (140.214,220.786) |
79,715 (60208,95298) |
184.218 (139.652,220.832) |
-0.01 (-0.015,-0.005) |
| United States of America | USA |
660,739 (489984,841532) |
235.032 (173.665,299.908) |
824,552 (617697,1040824) |
221.403 (164.64,281.524) |
-0.133 (-0.194,-0.072) |
| Indonesia | IDN |
294,863 (217975,382498) |
180.41 (133.438,230.685) |
578,068 (429388,731017) |
186.052 (138.802,235.109) |
0.157 (0.122,0.191) |
| Mexico | MEX |
107,876 (80611,139851) |
157.221 (116.588,202.944) |
218,631 (162671,281593) |
157.988 (117.616,203.562) |
0.007 (-0.002,0.016) |
| Brazil | BRA |
202,377 (150092,260203) |
152.119 (112.463,195.518) |
382,072 (278550,489511) |
153.377 (112.546,197.286) |
0.052 (0.037,0.068) |
| Saudi Arabia | SAU |
21,257 (14541,29473) |
164.027 (114.766,224.601) |
79,283 (54248,110828) |
163.166 (114.143,224.141) |
-0.011 (-0.026,0.003) |
| Turkey | TUR |
79,588 (58712,103792) |
156.824 (115.864,203.589) |
147,441 (109038,191910) |
157.39 (116.536,204.673) |
0.012 (0.005,0.018) |
| India | IND |
1,325,494 (982326,1705183) |
180.737 (133.568,231.612) |
2,781,659 (2073729,3593445) |
187.66 (140.051,241.669) |
0.157 (0.122,0.191) |
| South Africa | ZAF |
45,409 (33237,58393) |
143.6 (106.852,184.974) |
86,535 (64068,111295) |
141.772 (105.168,181.779) |
-0.012 (-0.026,0.001) |
| China | CHN |
2,329,187 (1763156,2915190) |
195.666 (147.783,244.068) |
3,445,845 (2572495,4306768) |
203.879 (152.53,255.666) |
0.084 (0.056,0.111) |
| Russian Federation | RUS |
203,951 (150343,263148) |
121.27 (89.498,156.279) |
225,240 (165472,287814) |
131.286 (97.228,168.51) |
0.403 (0.317,0.49) |
| Japan | JPN |
268,804 (198622,344319) |
183.662 (136.646,236.573) |
261,724 (192639,329975) |
181.144 (134.289,232.069) |
0.112 (0.012,0.212) |
| Republic of Korea | KOR |
76,586 (54116,105995) |
165.189 (117.008,227.063) |
111,195 (77617,151722) |
167.374 (114.462,230.945) |
0.031 (0.022,0.039) |
| Australia | AUS |
45,472 (33577,55294) |
247.44 (182.603,301.433) |
71,432 (53871,86605) |
247.58 (186.197,300.204) |
0.01 (0.004,0.016) |
| France | FRA |
106,480 (73897,141321) |
165.575 (114.483,221.152) |
124,342 (86698,164639) |
165.089 (115.782,224.031) |
-0.017 (-0.025,-0.009) |
| Germany | DEU |
148,843 (105716,199877) |
154.84 (109.682,208.604) |
159,031 (113354,210122) |
155.108 (111.223,207.983) |
-0.016 (-0.035,0.002) |
| Italy | ITA |
106,325 (78674,136009) |
160.308 (117.861,205.622) |
117,386 (86079,149280) |
161.14 (119.532,206.724) |
0.022 (0.018,0.027) |
| United Kingdom | GBR |
100,550 (74668,126989) |
155.914 (115.268,198.071) |
107,987 (79459,136407) |
135.938 (100.048,173.078) |
-0.335 (-0.479,-0.192) |
| Argentina | ARG |
56,543 (39203,76069) |
177.48 (123.118,238.577) |
87,785 (60579,118096) |
176.758 (121.754,238.354) |
-0.007 (-0.017,0.003) |
Between 1990 and 2021, most G20 countries showed increasing ASDRs. Russia experienced the steepest increase with an EAPC of 0.403, followed by India and Indonesia (EAPC: 0.157 for both countries). In contrast, declining trends were detected in the United Kingdom (EAPC: -0.335), the United States (EAPC: -0.133), and France (EAPC: -0.017).
Gender differences in the incidence rate, prevalence rate, and DALY rate of schizophrenia
From 1990 to 2021, incidence, prevalence, and DALY rates of schizophrenia were generally higher in males than in females (Fig. 2), with exceptions including Korea and South Africa. In 1990, among the G20 countries, males had higher ASIRs than females in most cases, except in Korea (female: 14.617; male: 14.214), South Africa (female: 14.211; male: 13.837), and Russia (female: 10.984; male: 10.856). By 2021, this pattern was only observed in Korea (female: 14.665; male: 14.17) and South Africa (female: 14.148; male: 13.778). Throughout the study period, Australia displayed the most consistent gender disparities with markedly higher values among males across all indicators.
Fig. 2.
Sex-stratified burden of schizophrenia among youth in G20 countries for 1990 (A) and 2021 (B). Age standardized rates are shown per 100,000 population with 95% UIs including incidence, prevalence, and DALYs
ASPRs patterns were more mixed. In 2021, females showed higher rates than males in several countries, including the United States (female: 358.349; male: 350.041), Korea (female: 270.626; male: 246.67), Germany (female: 255.013; male: 232.882), South Africa (female: 234.975; male: 221.311), and Russia (female: 207.944; male: 206.088).
Similarly, higher ASDRs in females were noted in Korea (female: 173.456; male: 160.958), South Africa (female: 143.414; male: 139.967), and Germany (female: 158.732; male: 150.927).
Association of schizophrenia and SDI
Figure 3A and B illustrate the prevalence of schizophrenia across G20 countries, stratified by the SDI level for the years 1990 and 2021, respectively. The analysis shows that across all SDI groups, prevalence increased with age, peaking in the 20–24 age group. In 2021, high-middle SDI countries exhibited the highest prevalence, while middle-SDI countries had the lowest. Compared to 1990, rates rose in nearly all categories by 2021, except for the stable patterns among the 20–24 age group in high SDI and low-middle SDI countries.
Fig. 3.
Age-and SDI-specific ASPRs of schizophrenia burden among youth in G20 countries in 1990 (A) and 2021 (B). SDI: Sociodemographic index. Bars show rates per 100,000 population for 10–14, 15–19 and 20–24 years
Projections in G20 countries over the next 15 years
Based on data from the 2021 GBD study, we projected the future trends in ASPRs of schizophrenia in G20 countries from 2022 to 2035. The ten G20 countries exhibiting the most notable changes are shown in Fig. 4. According to these projections, G20 countries can be classified into three categories:
Fig. 4.
Projections of ASPRs of schizophrenia burden among youth in 10 representative G20 countries 2021–2035. Shaded areas represent 95% UIs derived from the posterior predictive distribution of the Bayesian age-period-cohort model. Countries are grouped by projected trend direction: increasing (AUS, CHN, JPN, RUS, MEX, TUR), decreasing (USA, ITA), and stable (ARG, DEU)
Countries with increasing ASPRs: Australia (AUS), China (CHN), Japan (JPN), Russia (RUS), Mexico (MEX), and Turkey (TUR).
Countries with decreasing ASPRs: the United States (USA) and Italy (ITA).
Countries with stable ASPRs: Argentina (ARG) and Germany (DEU).
Discussion
This study offers a systematic assessment of schizophrenia burden among youth across G20 countries and provides data-driven projections to 2035. Our findings document a rising youth burden that exhibits pronounced regional, gender, and socioeconomic heterogeneity. Unlike previous reports that generalized across all age groups, this study focuses exclusively on the heterogeneity and public health significance of the 10–24 age range.
Cross-country variation partly reflects underlying demographic structure. In populous nations (e.g., China and India), expansive youth cohorts inflate higher absolute case counts even when age-standardized rates are similar. Additionally, our findings reveal that these countries have the highest DALYs associated with schizophrenia. Over half of the G20 countries showed upward trends, indicating increasing demand for youth-focused mental health services. Although the overall youth burden is increasing, its distribution remains uneven across regions, SDI levels, and gender.
Regional disparities were notable. Australia consistently exhibited the highest youth burden, whereas Russia and the United Kingdom recorded the lowest ASIRs, ASPRs, and ASDRs. Over three decades, incidence and prevalence increased in some countries, such as Russia and Japan (indicated by a positive EAPC), whereas the United Kingdom and the United States displayed declining trends (negative EAPC). Several factors may account for these regional differences. First, well-established mental health systems in high-income countries (e.g., the United States and the United Kingdom) facilitate early detection and intervention, plausibly suppressing incidence [18–20]. Conversely, potential mental health policy gaps or diagnostic practice changes in countries such as Russia and Japan may have inflated recorded cases. Second, rapid urbanization in countries like China and India, show a growing burden. Urbanicity has been linked to increased schizophrenia risk, with study reporting a doubled risk of schizophrenia onset among individuals who migrate from rural to urban areas during childhood [21]. Moreover, evidence indicates that even after controlling drug use, ethnicity, and social group size, urban living remains a major risk factor for schizophrenia. Mechanistic hypotheses include reduced green space, high plot density and other built-environment stressors [22, 23]. Third, economic transitions and social instability in some countries may further amplify risk. In many developing regions, limited access to psychiatric services [24, 25] and higher social stigma can lead to underdiagnosis, rather than truly lower incidence. Evidence suggests that the treatment gap for mental disorders remains as high as 89% [7, 26].
Socioeconomic development level appears to influence observed patterns of schizophrenia burden. A study based on GBD 2019 data indicates that countries with high SDI tend to report higher prevalence and DALY rates for schizophrenia, while those with low SDI report lower rates [27]. Consistent with this pattern, our study observed that in 2021, high-middle SDI countries showed the highest ASPRs among individuals aged 20–24 years, whereas middle SDI countries had the lowest. However, this gradient likely reflects differential detection capacity rather than a true lower disease burden. High SDI and high-middle SDI countries typically possess more robust mental health systems, broader diagnostic coverage, and greater access to healthcare services, all of which enhance case ascertainment and reporting prevalence and DALYs [28]. In contrast, underdiagnosis and misclassification remain common in countries with limited medical resources compared to high SDI and high-middle SDI countries, where stigma, limited access to healthcare, and insufficient epidemiological surveillance may obscure the true burden. Additionally, risk factors more prevalent in high SDI and high-middle SDI countries (such as advanced maternal age and societal stressors) may contribute to a true increase in disease burden [29, 30]. Environmental factors, such as air pollution, may further contribute to these observed differences. In more developed regions where air pollution levels are higher, recent evidence indicates that such exposure is positively associated with an increased risk of schizophrenia [31].
These differences should be interpreted within the constraints of the GBD methodology. While the framework enables standardized global comparison, it relies on statistical modeling to address gaps in national data. In regions without large-scale, nationally representative epidemiological surveys, particularly in low- and middle-income countries, the model outputs may be influenced as much by the framework’s assumptions as by empirical clinical evidence. Consequently, countries with advanced healthcare systems and diagnostic infrastructure may artefactually appear to carry a higher burden due to more complete detection and reporting, whereas others remain hampered by nascent sustainable and systematic data collection infrastructure [27]. This can lead to apparent overestimation in high SDI and high-middle SDI countries with robust detection systems.
Furthermore, this study confirms the presence of gender differences in the epidemiology of schizophrenia: males have a slightly higher incidence (male-to-female incidence ratio of 1.70 (95%CI: 1.46 to 1.97)) [32]. Among youth aged 10–24 years in G20 countries from 1990 to 2021, males consistently demonstrated higher ASIRs, ASPRs, and ASDRs compared to females. These results can be plausibly explained by several factors. First, previous epidemiological studies have shown that males are approximately 1.3–1.4 times more likely to develop schizophrenia than females, with the average age of onset occurring 3.2–4.1 years earlier in males [33–35]. This higher incidence and earlier onset of schizophrenia in males may be attributed to gender-dependent neurodevelopmental trajectories during late childhood and adolescence. Throughout this critical period, sex-specific differences in brain maturation (spanning morphological, neurochemical, and functional domains) interact with genetic vulnerability, hormonal influences, and environmental exposures. This interaction heightens susceptibility to aberrant neurodevelopment and accelerates the emergence of positive psychotic symptoms in young males [36–38]. In addition, males tend to exhibit more severe premorbid impairment and prominent negative symptoms than females, facilitating earlier clinical detection and inflating recorded prevalence. In contrast, females may exhibit a delayed onset and more effective coping mechanisms, resulting in a lower observed burden [39]. However, in Korea and South Africa, females showed slightly higher burden, possibly reflecting greater help-seeking propensity [40] and exposure to adverse social and structural conditions, including poverty, violence, unintended pregnancy and abortion, and entrenched sociocultural pressures [41–45].
Projections indicate continued increases in several countries, particularly China, Australia, and Japan. Notably, in countries with stable or declining trends, the overall schizophrenia burden remains substantial, as the prolonged survival of individuals with schizophrenia necessitates long-term treatment and sustained support [27, 46]. Moreover, behavioral changes commonly associated with schizophrenia, including sedentary lifestyles, unhealthy dietary habits, and smoking, can further elevate the risk of developing physical illnesses [27]. Global crises such as the COVID-19 pandemic may have lasting economic and psychological consequences, potentially influencing the onset and progression of schizophrenia and other mental disorders [47, 48].
Given the increasing schizophrenia burden among youth across G20 countries, policy should therefore move from generic service expansion to youth-specific pathways that reduce the duration of untreated psychosis, prevent relapses, and safeguard education and vocational trajectories. Systematic reviews demonstrate that early detection and intervention programs improve clinical and functional outcomes, even among high-risk individuals [49, 50]. Accordingly, routine school-based mental-health literacy and brief screening should be embedded in secondary and tertiary education settings, accompanied by clear consent and confidentiality procedures and rapid referral pathways to primary care and early psychosis services within defined timelines. To extend reach and sustain engagement, digital mental health interventions such as telepsychiatry and physical-health monitoring should be scaled with robust privacy and safety standards and integrated with physical-health monitoring, with the aim of reducing long-term DALYs. Addressing systemic healthcare disparities is essential to ensure equitable access across diverse economic settings. Integrating mental health interventions into other sectors, alongside technological innovations such as digital technology and telemedicine, has shown promise in early evaluations [51].
Our findings underscore the need to tailor mental health protection strategies to a country’s SDI levels and health system capacity. In populous, high schizophrenia burden countries (e.g., China and India), an effective approach is to embed mental health services into primary healthcare systems, like routine screening and early detection within community healthcare services. In middle SDI and low-middle SDI countries (e.g., South Africa, Indonesia), where burden is increasing but potentially underreported, priority should be given to task-sharing with primary care and school health services, integrating basic case-finding into routine checks, using low-cost tele supervision for non-specialist case managers, and building minimal surveillance datasets to track outcomes. In contrast, in high SDI and high-middle SDI countries experiencing stable or declining burden of schizophrenia, policy should pivot toward intensifying early intervention and relapse prevention programs. For example, expanding targeted services for high-risk groups, such as adolescents with a history of drug use, a family history of psychosis, or exposure to childhood trauma, and providing continuity of care. Furthermore, robust cross-sector collaborations that link healthcare with education, social services, and youth justice remain essential. Such efforts should leverage social media, school curricula, and community outreach to enhance schizophrenia literacy and reduce stigma at population scale.
Limitations
Based on GBD 2021 data, this study analyzed the epidemiological trends of schizophrenia among youth in G20 countries. However, several limitations should be noted. First, the reliability of the source data may be limited, as many countries lack high-quality, nationally representative epidemiological surveys on schizophrenia [26, 52]. To compensate, the GBD framework applies statistical modeling, which may introduce bias and lead to either underestimation or overestimation of incidence and prevalence in certain countries [9]. Second, diagnostic criteria for schizophrenia evolved over the study period (e.g., from DSM-III/IV to DSM-5 or ICD-10/11), and reporting practices vary across countries, which together may limit longitudinal comparability. Third, the use of EAPC and Bayesian age-period-cohort projections assumes approximately log-linear behavior anchored in historical data. This approach may not fully reflect emerging or non-linear risk factors, such as rapid urbanization, environmental exposures, or service disruptions during global crises (e.g., COVID-19, economic shocks). In addition, climate change may affect mental health risk through extreme heat, disasters, displacement, air pollution exposure, and food insecurity, with heterogeneous and non-linear impacts across settings. Additionally, as noted by Solmi et al. [27], the GBD framework does not include schizophrenia-related premature mortality (e.g., suicide) in its calculations, potentially leading to an underestimation of the true disease burden among youth. Taken together, these methodological limitations underscore the need for caution when interpreting absolute estimates, particularly in policy applications.
Conclusion
This study underscores a rising schizophrenia burden among individuals aged 10–24 years in G20 countries, accompanied by pronounced regional, socioeconomic, and gender disparities. To alleviate this burden, policy efforts should prioritize the implementation of early detection programs, the expansion of access to mental health care, and the promotion of stigma reduction initiatives. Tailored interventions should also account for local health system capacity, economic limitations, and gender-specific risk profiles.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We gratefully acknowledge the contribution of all members of the present study. This study would not have been possible without their contributions.
Author contributions
Wei Liao: Conceptualization, Data curation, Investigation, Writing-Original Draft, Writing-Review & Editing. Zhengrui Chen: Data Curation, Writing-Original Draft, Formal Analysis, Methodology, Software, Visualization. Wenhua Wu: Conceptualization, Methodology, Supervision, Project Administration. Xinyi He: Validation, Investigation, Visualization. Chunyan Lin: Supervision, Project Administration, Writing-Review & Editing.
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Data availability
The datasets generated or analyzed during the current study are available in the [GBD 2021] repository ([Global Burden of Disease Study 2021 (GBD 2021) Data Resources | GHDx] (https://ghdx.healthdata.org/gbd-2021)). Clinical trial number: not applicable.
Declarations
Ethical approval
This study is based on publicly accessible data from the GBD 2021 database. No identifiable personal information was accessed, and it does not require ethical approval and consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Wei Liao, Zhengrui Chen and Wenhua Wu contributed equally to this work.
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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 datasets generated or analyzed during the current study are available in the [GBD 2021] repository ([Global Burden of Disease Study 2021 (GBD 2021) Data Resources | GHDx] (https://ghdx.healthdata.org/gbd-2021)). Clinical trial number: not applicable.