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Prevalence and characteristics of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 sites, United States, 2018.
Open accessAbstract
PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2018. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD. This report focuses on the prevalence and characteristics of ASD among children aged 8 years in 2018 whose parents or guardians lived in 11 ADDM Network sites in the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. In 2018, children met the case definition if their records documented 1) an ASD diagnostic statement in an evaluation (diagnosis), 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. RESULTS: For 2018, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 16.5 in Missouri to 38.9 in California. The overall ASD prevalence was 23.0 per 1,000 (one in 44) children aged 8 years, and ASD was 4.2 times as prevalent among boys as among girls. Overall ASD prevalence was similar across racial and ethnic groups, except American Indian/Alaska Native children had higher ASD prevalence than non-Hispanic White (White) children (29.0 versus 21.2 per 1,000 children aged 8 years). At multiple sites, Hispanic children had lower ASD prevalence than White children (Arizona, Arkansas, Georgia, and Utah), and non-Hispanic Black (Black) children (Georgia and Minnesota). The associations between ASD prevalence and neighborhood-level median household income varied by site. Among the 5,058 children who met the ASD case definition, 75.8% had a diagnostic statement of ASD in an evaluation, 18.8% had an ASD special education classification or eligibility and no ASD diagnostic statement, and 5.4% had an ASD ICD code only. ASD prevalence per 1,000 children aged 8 years that was based exclusively on documented ASD diagnostic statements was 17.4 overall (range: 11.2 in Maryland to 29.9 in California). The median age of earliest known ASD diagnosis ranged from 36 months in California to 63 months in Minnesota. Among the 3,007 children with ASD and data on cognitive ability, 35.2% were classified as having an intelligence quotient (IQ) score ≤70. The percentages of children with ASD with IQ scores ≤70 were 49.8%, 33.1%, and 29.7% among Black, Hispanic, and White children, respectively. Overall, children with ASD and IQ scores ≤70 had earlier median ages of ASD diagnosis than children with ASD and IQ scores >70 (44 versus 53 months). INTERPRETATION: In 2018, one in 44 children aged 8 years was estimated to have ASD, and prevalence and median age of identification varied widely across sites. Whereas overall ASD prevalence was similar by race and ethnicity, at certain sites Hispanic children were less likely to be identified as having ASD than White or Black children. The higher proportion of Black children compared with White and Hispanic children classified as having intellectual disability was consistent with previous findings. PUBLIC HEALTH ACTION: The variability in ASD prevalence and community ASD identification practices among children with different racial, ethnic, and geographical characteristics highlights the importance of research into the causes of that variability and strategies to provide equitable access to developmental evaluations and services. These findings also underscore the need for enhanced infrastructure for diagnostic, treatment, and support services to meet the needs of all children.
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In the citing paper
“Surveillance was conducted using the same surveillance methods and case definitions used in 2018 and 2020 (6,13).”
From Prevalence and Early Identification of Autism Spectrum Disorder Among Children Aged 4 and 8 Years — Autism and Developmental Disabilities Monitoring Network, 16 Sites, United States, 2022 (2025) · cites this paper as [13]
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In the citing paper
“The 2018 estimate for children aged 4 years was lower than the 23.0 per 1,000 ASD prevalence among children aged 8 years (11), a finding consistent with previous reports (8,13).”
In the citing paper
“California has had the highest prevalence among children aged 4 years and 8 years since joining the ADDM Network in 2018 (6,10,11,13)”
In the citing paper
“No evidence of heterogeneity of the male-to-female ratio among children aged 4 years across sites was observed; however, the overall male-to-female ratio for children aged 4 years was lower than the 4.2 male-to-female ratio for children aged 8 years (11).”
In the citing paper
“The site in California had the highest cumulative incidence of ASD by age 48 months and the fewest cases of suspected ASD and was the only site where prevalence among children aged 4 years was higher than among children aged 8 years (11).”
In the citing paper
“The combined prevalence of ASD and suspected ASD (19.7 per 1,000 children aged 4 years) was still lower than ASD prevalence observed among children aged 8 years (23.0 per 1,000 children aged 8 years) (11).”
In the citing paper
“Children with co-occurring intellectual disability are more likely to be identified earlier than children without intellectual disability, as indicated by an earlier median age at identification among this group (11) as well as the consistently higher proportion of children with intellectual disability at age 4 years (8,13) than at age 8 years (9,11,17).”
In the citing paper
“Consistent with findings among children aged 8 years (11), a higher proportion of Black children aged 4 years with ASD have co-occurring intellectual disability.”
In the citing paper
“Adding the children identified with ASD to those suspected of having ASD at age 4 years is still less than the prevalence of ASD by age 8 years at all sites except California (11).”
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REMOVED: Deep learning with image-based autism spectrum disorder analysis: A systematic review
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“Autism spectrum disorder (ASD) is a neurodevelopmental condition currently affecting 1 out of every 44 children in the United States (Maenner et al., 2021).”
BackgroundChi, N., Washington, P. Y., Kline, A., Husic, A., Hou, C., He, C., Dunlap, K., & Wall, D. P. (2022) · JMIR Pediatrics and Parenting · doi:10.2196/35406 · Cited by 57
“Autism prevalence has rapidly increased in recent years: according to the Centers for Disease Control and Prevention, autism rates have tripled since 2000 to 1 in 44 children in 2018 [2].”
MethodSleep in Children with Autism Spectrum Disorder: A Narrative Review and Systematic Update
Schwichtenberg, A., Janis, A., Lindsay, A., Desai, H., Sahu, A., Kellerman, A., Chong, P., Abel, E. A., & Yatcilla, J. (2022) · Current Sleep Medicine Reports · doi:10.1007/s40675-022-00234-5 · Cited by 58
“The field is ready for a shift toward more (1) interventionbased and implementation science studies, (2) global and age representation, and (3) mechanistic understanding. A long line of work documents elevated rates of sleep problems and their association with several aspects of development 56 Current Sleep Medicine R…”
BackgroundInfluentialMeta-analysis of the Modified Checklist for Autism in Toddlers, Revised/Follow-up for Screening
Aishworiya, R., Ma, V. K., STEWART, S. L., Hagerman, R. J., & Feldman, H. M. (2023) · PEDIATRICS · doi:10.1542/peds.2022-059393 · Cited by 57
Chronic Effects of Dietary Pesticides on the Gut Microbiome and Neurodevelopment
Gama, J. S., Neves, B. C., & Pereira, A. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.931440 · Cited by 58
“Autism Spectrum Disorders (ASDs) are a group of developmental disabilities that can cause significant social, communication and behavioral deficits which affect approximately 1 in 44 children in the United States (Maenner et al., 2021).”
BackgroundInfluentialZhu, F.-L., Wang, S., Liu, W., Zhu, H., Li, M., & Zou, X. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1039293 · Cited by 59
“Inclusion criteria for toddlers with DD included the following: (1) isolated developmental delay (involving single domain); (2) multiple developmental delays—two or more domains or developmental lines affected; (3) global developmental delay (GDD)—significant delay in most of the developmental domains (21).”
BackgroundInfluentialLi, X., Ruan, C., Zibrila, A. I., Musa, M., Wu, Y., Zhang, Z., Liu, H., & Salimeen, M. (2022) · Medicine · doi:10.1097/md.0000000000032061 · Cited by 54
“The Centers for Disease Control and Prevention (CDC) currently estimated that 1 in 68 children are diagnosed with ASD[21] with a male-to-female ratio of 4:1, resulting in numbers of 1 in 42 boys and 1 in 189 girls.”
BackgroundCasseus, M., Kim, W. J., & Horton, D. B. (2023) · Autism Research · doi:10.1002/aur.2894 · Cited by 53
“Increased neurodevelopmental disorders, greater level of ASD severity, repetitive behaviors, and language and social deficits were also observed in children with ASD + ADHD (Gadow et al., 2009; Gordon-Lipkin et al., 2018; Mulligan et al., 2009).”
BackgroundResultInfluentialThe Gut-Brain-Immune Axis in Autism Spectrum Disorders: A State-of-Art Report
Puricelli, C., Rolla, R., Gigliotti, C. L., Boggio, E. M., Beltrami, E., Dianzani, U., & Keller, R. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.755171 · Cited by 64
Are the diagnostic rates of autistic females increasing? An examination of state‐wide trends
Harrop, C., Tomaszewski, B. R., Putnam, O. C., Klein, C. B., Lamarche, E., & Klinger, L. G. (2024) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13939 · Cited by 65
Maternal tobacco smoking and offspring autism spectrum disorder or traits in ECHO cohorts
Hertz‐Picciotto, I., Korrick, S., Ladd‐Acosta, C., Karagas, M. R., Lyall, K., Schmidt, R. J., Dunlop, A. L., Croen, L., Dabelea, D., Daniels, J. L., et al. (2022) · Autism Research · doi:10.1002/aur.2665 · Cited by 53
Primary Care Framework to Monitor Preterm Infants for Neurodevelopmental Outcomes in Early Childhood
Davis, B. E., Leppert, M. L. O., German, K. R., Lehmann, C. U., Adams-Chapman, I. S., Noritz, G. H., Agrawal, R., Foster, J. E. A., Fremion, E., Frierson, S. L., et al. (2023) · PEDIATRICS · doi:10.1542/peds.2023-062511 · Cited by 59
Gaze Patterns in Children With Autism Spectrum Disorder to Emotional Faces: Scanpath and Similarity
Zhou, W., Yang, M., Tang, J., Wang, J., & Hu, B. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3361935 · Cited by 51
“The Morbidity and Mortality Weekly Report (MMWR) [2] from Centers for Disease Control and Prevention (CDC) released that the overall ASD prevalence rose to 23.0 per 1000 (one in 44) children aged 8 years.”
BackgroundInfluentialShan, L., Feng, J., Wang, T., Xu, Z., & Jia, F. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.794238 · Cited by 50
“Previous studies have mostly explored the comorbidities of GDD/ID in children with ASD from the perspective of ASD (5, 8).”
BackgroundMethodOsman, A., Mervosh, N. L., Strat, A. N., Euston, T. J., Zipursky, G., Pollak, R. M., Meckel, K. R., Tyler, S. R., Chan, K. L., Grice, A. B., et al. (2020) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.08.020 · Cited by 49
Early identification of autism spectrum disorder based on machine learning with eye-tracking data
Wei, Q., Dong, W., Yu, D., Wang, K., Yang, T., Xiao, Y., Long, D., Xiong, H., Chen, J., Xu, X., et al. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.04.049 · Cited by 57
A systematic review of social support for siblings of children with neurodevelopmental disorders
Kirchhofer, S. M., Orm, S., Haukeland, Y. B., Fredriksen, T., Wakefield, C. E., & Fjermestad, K. W. (2022) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2022.104234 · Cited by 54
Chen, Y.-H., Chen, Q.-S., Kong, L., & Liu, G.-D. (2022) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2022-100544 · Cited by 49
“We compared the prediction performance of the models using the augmented variables with our base case models.”
Neurological and psychiatric disorders among autistic adults: a population healthcare record study
Underwood, J. F. G., DelPozo‐Baños, M., Frizzati, A., Rai, D., John, A. M., & Hall, J. (2022) · Psychological Medicine · doi:10.1017/s0033291722002884 · Cited by 55
Yang, Y., Fang, F., Arnberg, F. K., Kuja‐Halkola, R., D'Onofrio, B. M., Larsson, H., Brikell, I., Chang, Z., Andreassen, O. A., Lichtenstein, P., et al. (2024) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2024.101105 · Cited by 55
“5,6 The current evidence on sex differences in psychiatric disorders is mainly based on prevalence studies, 7 – 9 without differentiating incident cases from prevalent and recurrent cases.”
CRISPR activation for SCN2A-related neurodevelopmental disorders
Tamura, S., Nelson, A. D., Spratt, P. W. E., Hamada, E. C., Zhou, X., Kyoung, H., Li, Z., Arnould, C., Barskyi, V., Krupkin, B., et al. (2025) · Nature · doi:10.1038/s41586-025-09522-w · Cited by 52
Nebel, M. B., Lidstone, D. E., Wang, L., Benkeser, D. C., Mostofsky, S. H., & Risk, B. B. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119296 · Cited by 50
Allen, K., Harrington, J. W., Quetsch, L. B., Masse, J. J., Cooke, C. G., & Paulson, J. F. (2022) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-022-05428-y · Cited by 62
“Since 2000, prevalence rates have increased by over 150% leading ASD to become an urgent public health concern (Maenner et al., 2021).”
BackgroundPenner, M., Senman, L., Andoni, L. Y., Dupuis, A., Anagnostou, E. A., Kao, S., Solish, A., Shouldice, M., Ferguson, G., & Brian, J. A. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.52879 · Cited by 45
Washington, P. Y., & Wall, D. P. (2023) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-020722-125454 · Cited by 52
“It is estimated that 1 In 44 children in the United States have autism [1], with the prevalence continuing to rise.”
BackgroundManter, M. A., Birtwell, K. B., Bath, J., Friedman, N. D. B., Keary, C. J., Neumeyer, A. M., Palumbo, M. L., Thom, R. P., Stonestreet, E., Brooks, H., et al. (2025) · BMC Medicine · doi:10.1186/s12916-024-03814-0 · Cited by 51
Barbaresi, W. J., Cacia, J., Friedman, S., Fussell, J. J., Hansen, R. L., Hofer, J., Roizen, N., Stein, R. E. K., Vanderbilt, D. L., & Sideridis, G. D. (2022) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2022.3605 · Cited by 44
Microglia: Synaptic modulator in autism spectrum disorder
Hu, C., Li, H., Li, J., Luo, X., & Hao, Y. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.958661 · Cited by 50
Wang, S., Chen, D., Yang, Y., Zhu, L., Xiong, X., & Chen, A. (2023) · Autism Research · doi:10.1002/aur.3004 · Cited by 56
Lagod, P. P., & Naser, S. A. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242417432 · Cited by 54
Shiani, A., Sharafi, K., Omer, A. K., Kiani, A., Matin, B. K., Massahi, T., & Ebrahimzadeh, G. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.159246 · Cited by 44
Maggio, M. G., Calatozzo, P., Cerasa, A., Pioggia, G., Quartarone, A., & Calabrò, R. S. (2022) · Brain Sciences · doi:10.3390/brainsci12111427 · Cited by 43
“ASD is more common among boys than among girls (3/4:1) [5], and the syndrome occurs early in life with symptoms appearing within the first 2 years.”
BackgroundMethodInfluentialSex, hormones and cerebrovascular function: from development to disorder
Collignon, A., Dion‐Albert, L., Ménard, C., & Coelho‐Santos, V. (2024) · Fluids and Barriers of the CNS · doi:10.1186/s12987-023-00496-3 · Cited by 50
Kuo, S. S., van der Merwe, C., Fu, J. M., Carey, C. E., Talkowski, M. E., Bishop, S. L., & Robinson, E. (2022) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2022.2423 · Cited by 50
Computer-Aided Autism Spectrum Disorder Diagnosis With Behavior Signal Processing
Cheng, M., Zhang, Y., Xie, Y., Pan, Y., Li, X., Liu, W., Yu, C., Zhang, D., Xing, Y., Huang, X., et al. (2023) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2023.3238712 · Cited by 41
Diversity and Classification of Genetic Variations in Autism Spectrum Disorder
Kereszturi, É. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242316768 · Cited by 51
Zhang, F., Zhang, Y., Li, G., & Luo, H. (2023) · Children · doi:10.3390/children11010041 · Cited by 52
“Moreover, the prevalence of ASD in children has continued to rise [67,68].”
BackgroundGut microbiome and serum amino acid metabolome alterations in autism spectrum disorder
Chang, X., Zhang, Y., Chen, X., Li, S., Mei, H., Xiao, H., Ma, X., Liu, Z., & Li, R. (2024) · Scientific Reports · doi:10.1038/s41598-024-54717-2 · Cited by 46
Racial Differences in the Prevalence of Autism Spectrum Disorder: A Systematic Review
Gallin, Z., Kolevzon, A. M., Reichenberg, A., Hankerson, S. H., & Kolevzon, A. L. (2024) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-024-06403-5 · Cited by 49
“…with the Centers for Disease Control (CDC) Autism and Developmental Disabilities Monitoring (ADDM) Network (Baio, 2012, 2014; Baio et al., 2018; Christensen et al., 2016; Dur-kin et al., 2017; Maenner et al., 2020, 2021, 2023; Mandell et al., 2009; Rice, 2007, 2009; Shaw et al., 2020, 2023).”
InfluentialOh, J., Shin, H., Kannan, K., Busgang, S. A., Schmidt, R. J., Schweitzer, J. B., Hertz‐Picciotto, I., & Bennett, D. H. (2022) · Environmental Research · doi:10.1016/j.envres.2022.114322 · Cited by 41
Systematic Review of Virtual Reality in Behavioral Interventions for Individuals with Autism
Carnett, A., Neely, L. C., Gardiner, S., Kirkpatrick, M., Quarles, J. P., & Christopher, K. (2022) · Advances in Neurodevelopmental Disorders · doi:10.1007/s41252-022-00287-1 · Cited by 46
Metadata
- Authors
- Maenner, M. J., Shaw, K. A., Bakian, A. V., Bilder, D. A., Durkin, M. S., Esler, A., Furnier, S. M., Hallas, L., Hall-Lande, J., Hudson, A., Hughes, M. M., Patrick, M., Pierce, K., Poynter, J. N., Salinas, A., Shenouda, J., Vehorn, A., Warren, Z., Constantino, J. N., DiRienzo, M., Fitzgerald, R. T., Grzybowski, A., Spivey, M. H., Pettygrove, S., Zahorodny, W., Ali, A., Andrews, J. G., Baroud, T., Gutierrez, J., Hewitt, A., Lee, L.-C., Lopez, M., Mancilla, K. C., McArthur, D., Schwenk, Y. D., Washington, A., Williams, S., & Cogswell, M. E.
- Affiliations
- Centers for Disease Control and Prevention (US)
- University of Utah (US)
- University of Wisconsin–Madison (US)
- University of Minnesota (US)
- University of Arkansas for Medical Sciences (US)
- University of California San Diego (US)
- Rutgers New Jersey Medical School (US)
- Vanderbilt University Medical Center (US)
- Washington University in St. Louis (US)
- Johns Hopkins University (US)
- University of Arizona (US)
- United States Department of Health and Human Services (US)
- Corresponding author
- Maenner, Matthew J.
- ORCID
- Maenner, Matthew J.
- Bakian, Amanda V.
- Bilder, Deborah A.
- Durkin, Maureen S.
- Esler, Amy
- Furnier, Sarah M.
- Hughes, Michelle M.
- Patrick, Mary
- Pierce, Karen
- Poynter, Jenny N.
- Shenouda, Josephine
- Warren, Zachary
- Constantino, John N.
- DiRienzo, Monica
- Fitzgerald, Robert T.
- Pettygrove, Sydney
- Zahorodny, Walter
- Ali, Akilah
- Andrews, Jennifer G.
- Lee, Li-Ching
- Lopez, Maya
- McArthur, Dedria
- Washington, Anita
- Cogswell, Mary E.
- Venue
- MMWR. Surveillance Summaries
- Published
- 2021-12-03
- Volume
- 70
- Issue
- 11
- Pages
- 1-16
- ISSN
- 1545-8636 (ISSN-L)
- 1546-0738
- PMC
- PMC8639024
- OpenAlex
- W3216151710
- Cited by
- 1,818
- References
- 37
- Citations by year
- 2026: 101 · 2025: 270 · 2024: 438 · 2023: 553 · 2022: 438 · 2021: 8
- FWCI
- 193.23
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- public-domain
- Locations
- MMWR Surveillance Summaries (publishedVersion, public-domain)
- PubMed Central (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Funders
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50HD103537)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Health Sciences › Medicine › Psychiatry and Mental health › Child Nutrition and Feeding Issues
- Social Sciences › Psychology › Clinical Psychology › Family and Disability Support Research
- Keywords
- autism spectrum disorder, autism prevalence, special education eligibility, ICD-10 codes, sex differences, racial and ethnic disparities, American Indian and Alaska Native children, median household income, neighborhood socioeconomic status, United States states and territories
- MeSH terms
- Autism Spectrum Disorder, Race Factors, Child, Ethnicity, Female, Geography, Humans, Male, Population Surveillance, United States, Prevalence, Racial Groups, Health Status Disparities, Epidemiological Monitoring
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