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Hui Song,1,&ast; Lingzhi Fang,2,&ast; Hongwei Li3 1Acute Psychiatry Ward 1, The Third Hospital of Mianyang·Sichuan Mental Health Center, Mianyang, People’s Republic of China; 2Brain Therapy Center, The Third Hospital of Mianyang·Sichuan Mental Health Center, Mianyang, People’s Republic of China; 3Department of Radiology, The Third Hospital of Mianyang·Sichuan Mental Health Center, Mianyang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Hui Song, Acute Psychiatry Ward 1, The Third Hospital of Mianyang·Sichuan Mental Health Center, No. 190, East Section of Jiannan Road, Mianyang, Sichuan, 621000, People’s Republic of China, Tel +86 15892628201, Email hhhhhssuisong@163.com Hongwei Li, Department of Radiology, The Third Hospital of Mianyang·Sichuan Mental Health Center, No. 190, East Section of Jiannan Road, Mianyang, Sichuan, 621000, People’s Republic of China, Tel + 86 13696265720, Email lhwhhhhongweili@163.comBackground: Schizophrenia is a chronic mental disorder that profoundly impairs quality of life. Its burden in China is being reshaped by rapid socioeconomic development and demographic shifts.Objective: To examine temporal trends in China’s schizophrenia burden from 1990 to 2023 and to project trends from 2024 to 2052.Methods: Leveraging GBD 2023 data, trends in incidence, prevalence, and disability-adjusted life-years (DALYs) for schizophrenia in China were analyzed. Spearman correlation analysis and Generalized Additive Models (GAMs) were used to assess the associations between the sociodemographic index (SDI) and disease burden. Decomposition analysis quantified drivers of changes. Bayesian Age-Period-Cohort (BAPC) and Age-Period-Cohort (APC) models projected the disease burden for 2024– 2052. A retrospective validation framework incorporating Mean Absolute Error, Root Mean Square Error, and Mean Absolute Percentage Error (MAPE) was introduced to evaluate the robustness of the predictive models.Results: From 1990 to 2023, the total numbers of incident cases, prevalent cases, and DALYs for schizophrenia in China showed an increasing trend. Prevalent cases and DALYs in females increased by 59.876% and 57.522%, respectively, which were substantially higher than the increases in males (51.864% and 49.517%). Correlation analysis revealed no significant linear association between the age-standardized incidence rate and SDI. However, GAMs confirmed significant non-linear positive associations between all burden indicators and SDI (P < 0.001). Decomposition analysis identified population growth as the primary positive driver of the increasing burden. While population aging had a negative moderating effect on new incident cases structurally (contribution rate − 12.800%), it significantly drove up the total prevalent cases (contribution rate 20.190%). Model validation demonstrated the high predictive accuracy of the BAPC model, with MAPE for all indicators below 2.0% (0.12– 1.92%). Projections indicate that the schizophrenia burden in China will continue to increase from 2024 to 2052, with females experiencing a higher average annual increase (net drift) than males. Incidence rates are projected to peak in the 20– 24 age group, while prevalence and DALYs rates peak in the 40– 44 age group. Furthermore, disease risk shows a rapid upward trend for birth cohorts after 2014.Conclusion: Although the incidence rate remains relatively stable, driven by demographic shifts, the absolute burden of schizophrenia in China continues to rise, with a particularly pronounced cumulative impact on females and young to middle-aged adults. National policies should prioritize establishing routine mental health screening mechanisms for first-year university students and developing specialized community rehabilitation support programs for middle-aged female patients.Keywords: epidemiology, schizophrenia, China, global burden of disease study