Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Global burden of autism spectrum disorders among population aged 70 years and older from 1990–2021, with projections to 2040: findings from the Global Burden of Disease Study 2021

Molecular Psychiatry (2025)Cite this article

Subjects

Abstract

Autism spectrum disorders (ASD) is a lifelong neurodevelopmental condition that negatively affects older adults, yet it receives minimal priority and limited attention in research and healthcare services for this population. Using data from Global Burden of Diseases, Injuries, and Risk Factors Study 2021, we estimated the prevalence and disability-adjusted life-years (DALYs) of ASD among population aged ≥70 years globally from 1990–2021, with projections to 2040. Decomposition analysis was conducted. Globally, the number of ASD cases among individuals aged ≥70 years increased from 894.7 thousand in 1990 to 2478.9 thousand in 2021, corresponding to an increase of 177.1%, with population growth contributing to the largest increase, followed by increased age-specific prevalence rates. It is projected that by 2040, the number of cases will reach 5150.9 thousand worldwide, accounting for 864.7 thousand DALYs. Between 1990 and 2021, the prevalence rate of ASD among the older population increased by 13.2%, projecting to increase steadily by 2040. Males had a higher prevalence rate of ASD in 2021 (773.6 versus 287.8 per 100,000 people) than females. High sociodemographic index (SDI) countries had the highest rate and the greatest increase. Similar trend patterns were observed in the number of DALYs and DALY rates. To address this overlooked but increasingly severe challenge, more attention and timely development of effective interventions and management services are needed. High SDI countries should focus on developing effective intervention and treatment strategies, while middle and low SDI countries need to improve screening and diagnostic capacities and public awareness of ASD.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Trend of ASD in older population.
Fig. 2: Trend of ASD in older population by SDI.
Fig. 3: Prevalence and its percentage change of ASD in the older population.
Fig. 4: World map of ASD prevalence in the older population.
Fig. 5: Decompositon analysis.
Fig. 6: Projected burden of ASD in the older population.

Similar content being viewed by others

Data availability

The data used for the analyses in the study are publicly available at https://ghdx.healthdata.org/gbd-results-tool.

Code availability

Analysis code in R may be made available upon reasonable request by contacting the corresponding author.

References

  1. Solmi M, Song M, Yon DK, Lee SW, Fombonne E, Kim MS, et al. Incidence, prevalence, and global burden of autism spectrum disorder from 1990–2019 across 204 countries. Mol Psychiatry. 2022;27:4172–80.

    Article  PubMed  Google Scholar 

  2. Robison JE. Autism prevalence and outcomes in older adults. Autism Res. 2019;12:370–4.

    Article  PubMed  Google Scholar 

  3. Lai MC, Lombardo MV, Baron-Cohen S. Autism. Lancet. 2014;383:896–910.

    Article  PubMed  Google Scholar 

  4. Piven J, Rabins P. Autism spectrum disorders in older adults: toward defining a research agenda. J Am Geriatr Soc. 2011;59:2151–5.

    Article  PubMed  Google Scholar 

  5. Mukaetova-Ladinska EB, Perry E, Baron M, Povey C. Ageing in people with autistic spectrum disorder. Int J Geriatr Psychiatry. 2012;27:109–18.

    Article  CAS  PubMed  Google Scholar 

  6. Mason D, Stewart GR, Capp SJ, Happé F. Older age autism research: a rapidly growing field, but still a long way to go. Autism Adulthood. 2022;4:164–72.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Shattuck PT, Garfield T, Roux AM, Rast JE, Anderson K, Hassrick EM, et al. Services for adults with autism spectrum disorder: a systems perspective. Curr Psychiatry Rep. 2020;22:13.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Fombonne E. Epidemiology of autistic disorder and other pervasive developmental disorders. J Clin Psychiatry. 2005;66(Suppl 10):3–8.

    PubMed  Google Scholar 

  9. Brugha TS, McManus S, Bankart J, Scott F, Purdon S, Smith J, et al. Epidemiology of autism spectrum disorders in adults in the community in England. Arch Gen Psychiatry. 2011;68:459–65.

    Article  PubMed  Google Scholar 

  10. Rubenstein E, Tewolde S, Michals A, Fox M, Wang N. Prevalence of autism among medicaid-enrolled adults. JAMA Psychiatry. 2023;80:1284–7.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Dietz PM, Rose CE, McArthur D, Maenner M. National and State estimates of adults with autism spectrum disorder. J Autism Dev Disord. 2020;50:4258–66.

    Article  PubMed  PubMed Central  Google Scholar 

  12. GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403:2133–61.

    Article  Google Scholar 

  13. GBD 2021 Causes of Death Collaborators. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403:2100–32.

    Article  Google Scholar 

  14. Zigic N, Pajevic I, Hasanovic M, Avdibegovic E, Aljukic N, Hodzic V. Neurodevelopmental disorders in ICD-11 classification. Eur Psychiatry. 2023;66:S737.

    PubMed Central  Google Scholar 

  15. American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5™, 5th ed, text version. Washington, DC: American Psychiatric Association Publishing; 2013.

    Book  Google Scholar 

  16. Harrison JE, Weber S, Jakob R, Chute CG. ICD-11: an international classification of diseases for the twenty-first century. BMC Med Inf Decis Mak. 2021;21:206.

    Article  Google Scholar 

  17. Cheng X, Tan L, Gao Y, Yang Y, Schwebel DC, Hu G. A new method to attribute differences in total deaths between groups to population size, age structure and age-specific mortality rate. PLoS One. 2019;14:e0216613.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Cheng X, Yang Y, Schwebel DC, Liu Z, Li L, Cheng P, et al. Population ageing and mortality during 1990-2017: a global decomposition analysis. PLoS Med. 2020;17:e1003138.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Global Burden of Disease Study 2021 Autism Spectrum Collaborators. The global epidemiology and health burden of the autism spectrum: findings from the Global Burden of Disease Study 2021. Lancet Psychiatry. 2025;12:111–21.

    Article  Google Scholar 

  20. Duchan E, Patel DR. Epidemiology of autism spectrum disorders. Pediatr Clin North Am. 2012;59:27–43. ix-x

    Article  PubMed  Google Scholar 

  21. King M, Bearman P. Diagnostic change and the increased prevalence of autism. Int J Epidemiol. 2009;38:1224–34.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Elsabbagh M, Divan G, Koh YJ, Kim YS, Kauchali S, Marcín C, et al. Global prevalence of autism and other pervasive developmental disorders. Autism Res. 2012;5:160–79.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Zeidan J, Fombonne E, Scorah J, Ibrahim A, Durkin MS, Saxena S, et al. Global prevalence of autism: a systematic review update. Autism Res. 2022;15:778–90.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lyall K, Croen L, Daniels J, Fallin MD, Ladd-Acosta C, Lee BK, et al. The changing epidemiology of autism spectrum disorders. Annu Rev Public Health. 2017;38:81–102.

    Article  PubMed  Google Scholar 

  25. Newschaffer CJ, Croen LA, Daniels J, Giarelli E, Grether JK, Levy SE, et al. The epidemiology of autism spectrum disorders. Annu Rev Public Health. 2007;28:235–58.

    Article  PubMed  Google Scholar 

  26. Matson JL, Kozlowski AM. The increasing prevalence of autism spectrum disorders. Res Autism Spectr Disord. 2011;5:418–25.

    Article  Google Scholar 

  27. The World Bank. Population ages 65 and above, total - Global. 2024. https://data.worldbank.org/indicator/SP.POP.65UP.TO?end=2023&start=1990. Accessed 22 Aug 2024.

  28. The World Bank. Population ages 65 and above (% of total population) - Global. 2024. https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS?end=2023&start=1990. Accessed 22 Aug 2024.

  29. The United Nations. World social report 2023: leaving no one behind in an ageing world. 2024. https://www.un.org/development/desa/dspd/wp-content/uploads/sites/22/2023/01/WSR_2023_Chapter_Key_Messages.pdf. Accessed 22 Aug 2024.

  30. Woolfenden S, Sarkozy V, Ridley G, Coory M, Williams K. A systematic review of two outcomes in autism spectrum disorder - epilepsy and mortality. Dev Med Child Neurol. 2012;54:306–12.

    Article  PubMed  Google Scholar 

  31. Hirvikoski T, Mittendorfer-Rutz E, Boman M, Larsson H, Lichtenstein P, Bölte S. Premature mortality in autism spectrum disorder. Br J Psychiatry. 2016;208:232–8.

    Article  PubMed  Google Scholar 

  32. Hertz-Picciotto I, Delwiche L. The rise in autism and the role of age at diagnosis. Epidemiology. 2009;20:84–90.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kim JY, Son MJ, Son CY, Radua J, Eisenhut M, Gressier F, et al. Environmental risk factors and biomarkers for autism spectrum disorder: an umbrella review of the evidence. Lancet Psychiatry. 2019;6:590–600.

    Article  PubMed  Google Scholar 

  34. Arango C, Dragioti E, Solmi M, Cortese S, Domschke K, Murray RM, et al. Risk and protective factors for mental disorders beyond genetics: an evidence-based atlas. World Psychiatry. 2021;20:417–36.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Rai D, Lee BK, Dalman C, Newschaffer C, Lewis G, Magnusson C. Antidepressants during pregnancy and autism in offspring: population based cohort study. BMJ. 2017;358:j2811.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Rai D, Lee BK, Dalman C, Golding J, Lewis G, Magnusson C. Parental depression, maternal antidepressant use during pregnancy, and risk of autism spectrum disorders: population based case-control study. BMJ. 2013;346:f2059.

    Article  PubMed  PubMed Central  Google Scholar 

  37. von Ehrenstein OS, Ling C, Cui X, Cockburn M, Park AS, Yu F, et al. Prenatal and infant exposure to ambient pesticides and autism spectrum disorder in children: population based case-control study. BMJ. 2019;364:l962.

    Article  Google Scholar 

  38. Sandin S, Schendel D, Magnusson P, Hultman C, Surén P, Susser E, et al. Autism risk associated with parental age and with increasing difference in age between the parents. Mol Psychiatry. 2016;21:693–700.

    Article  CAS  PubMed  Google Scholar 

  39. Bornstein E, Eliner Y, Chervenak FA, Grünebaum A. Concerning trends in maternal risk factors in the United States: 1989–2018. EClinicalMedicine. 2020;29-30:100657.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Hansen SN, Schendel DE, Parner ET. Explaining the increase in the prevalence of autism spectrum disorders: the proportion attributable to changes in reporting practices. JAMA Pediatr. 2015;169:56–62.

    Article  PubMed  Google Scholar 

  41. Lord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, et al. Autism spectrum disorder. Nat Rev Dis Primers. 2020;6:5.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Werling DM, Geschwind DH. Sex differences in autism spectrum disorders. Curr Opin Neurol. 2013;26:146–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Ferri SL, Abel T, Brodkin ES. Sex Differences in Autism Spectrum Disorder: a Review. Curr Psychiatry Rep. 2018;20:9.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Zhang Y, Li N, Li C, Zhang Z, Teng H, Wang Y, et al. Genetic evidence of gender difference in autism spectrum disorder supports the female-protective effect. Transl Psychiatry. 2020;10:4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Muscatello RA, Rafatjoo E, Mirpuri KK, Kim A, Vandekar S, Corbett BA. Salivary testosterone in male and female youth with and without autism spectrum disorder: considerations of development, sex, and diagnosis. Mol Autism. 2022;13:37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wigdor EM, Weiner DJ, Grove J, Fu JM, Thompson WK, Carey CE, et al. The female protective effect against autism spectrum disorder. Cell Genom. 2022;2:100134.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Beggiato A, Peyre H, Maruani A, Scheid I, Rastam M, Amsellem F, et al. Gender differences in autism spectrum disorders: divergence among specific core symptoms. Autism Res. 2017;10:680–9.

    Article  PubMed  Google Scholar 

  48. Lai MC, Szatmari P. Sex and gender impacts on the behavioural presentation and recognition of autism. Curr Opin Psychiatry. 2020;33:117–23.

    Article  PubMed  Google Scholar 

  49. Durkin MS, Maenner MJ, Meaney FJ, Levy SE, DiGuiseppi C, Nicholas JS, et al. Socioeconomic inequality in the prevalence of autism spectrum disorder: evidence from a U.S. cross-sectional study. PLoS One. 2010;5:e11551.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Thomas P, Zahorodny W, Peng B, Kim S, Jani N, Halperin W, et al. The association of autism diagnosis with socioeconomic status. Autism. 2012;16:201–13.

    Article  PubMed  Google Scholar 

  51. Durkin MS, Maenner MJ, Baio J, Christensen D, Daniels J, Fitzgerald R, et al. Autism spectrum disorder among US children (2002-10): socioeconomic, racial, and ethnic disparities. Am J Public Health. 2017;107:1818–26.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Bhasin TK, Schendel D. Sociodemographic risk factors for autism in a US metropolitan area. J Autism Dev Disord. 2007;37:667–77.

    Article  PubMed  Google Scholar 

  53. Adak B, Halder S. Systematic review on prevalence for autism spectrum disorder with respect to gender and socio-economic status. J Ment Disord Treat. 2017;3:1–9.

    Article  Google Scholar 

  54. Johnson CP, Myers SM. Identification and evaluation of children with autism spectrum disorders. Pediatrics. 2007;120:1183–215.

    Article  PubMed  Google Scholar 

  55. Liu J, Yang F, Liu M. Screening and services for autism among children in China. Lancet Psychiatry. 2022;9:e53.

    Article  PubMed  Google Scholar 

  56. Bölte S, Girdler S, Marschik PB. The contribution of environmental exposure to the etiology of autism spectrum disorder. Cell Mol Life Sci. 2019;76:1275–1297.

    Article  PubMed  Google Scholar 

Download references

Funding

This study is funded by Harbin Medical University Leading Talent Grant (31021220002). The funder of the study was not involved in the study design, data collection, analysis, interpretation, or report writing.

Author information

Authors and Affiliations

  1. Department of Cell Biology, School of Basic Medicine, Harbin Medical University, Harbin, China

    Wei Tian & Wenran Zhao

  2. School of Public Health, Harbin Medical University, Harbin, China

    Wei Tian, Guangcan Yan, Xinyi Zhang, Jing Zhang, Junyi Peng, Dong Shui & Maoyi Tian

  3. School of Public Health, Zunyi Medical University, Zunyi, China

    Wei Tian & Yuanzhong Zhou

  4. Institute for Hospital Management of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

    Yafeng Zhang

  5. Department of Chronic Non-Communicable Diseases, Guizhou Centre for Disease Control and Prevention, Guiyang, China

    Tao Liu

  6. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

    Pengpeng Ye

  7. Department of General Practice, The Second Affiliated Hospital of Harbin Medical University, Harbin, China

    Maoyi Tian

Authors
  1. Wei Tian
    View author publications

    Search author on:PubMed Google Scholar

  2. Guangcan Yan
    View author publications

    Search author on:PubMed Google Scholar

  3. Xinyi Zhang
    View author publications

    Search author on:PubMed Google Scholar

  4. Yafeng Zhang
    View author publications

    Search author on:PubMed Google Scholar

  5. Jing Zhang
    View author publications

    Search author on:PubMed Google Scholar

  6. Junyi Peng
    View author publications

    Search author on:PubMed Google Scholar

  7. Wenran Zhao
    View author publications

    Search author on:PubMed Google Scholar

  8. Dong Shui
    View author publications

    Search author on:PubMed Google Scholar

  9. Yuanzhong Zhou
    View author publications

    Search author on:PubMed Google Scholar

  10. Tao Liu
    View author publications

    Search author on:PubMed Google Scholar

  11. Pengpeng Ye
    View author publications

    Search author on:PubMed Google Scholar

  12. Maoyi Tian
    View author publications

    Search author on:PubMed Google Scholar

Contributions

WT, GY, PY and MT conceptualized the study. WT and GY coded the statistical analysis, tables, figures, and supplementary, and drafted the manuscript. WT, GY, JZ and PY were involved in the interpretation of the data. XZ, JZ, WZ, YZZ, TL, PY and MT provided critical comments on drafts of the manuscript and revised the manuscript. YFZ and DS checked the data and results. JP, PY and MT had access to and verified the underlying study data. MT obtained funding. GY, PY and MT contributed equally are guarantors for this study. All authors participated in the review of the manuscript and read and approved the final manuscript. All authors had access to the data in the study and had final responsibility to submit for publication.

Corresponding authors

Correspondence to Guangcan Yan, Pengpeng Ye or Maoyi Tian.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Not applicable. This study did not involve human participants, personal data, or any form of intervention. All data utilized are publicly available, with access links provided in the manuscript.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, W., Yan, G., Zhang, X. et al. Global burden of autism spectrum disorders among population aged 70 years and older from 1990–2021, with projections to 2040: findings from the Global Burden of Disease Study 2021. Mol Psychiatry (2025). https://doi.org/10.1038/s41380-025-03172-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41380-025-03172-0

Search

Advanced search

Quick links