The prevalence of autism spectrum disorder (ASD) among children in the United States has risen dramatically over the past two decades. In 2022, an estimated 32.2 out of every 1,000 8-year-old children were identified with ASD, marking a nearly fivefold increase from the rate of 6.7 per 1,000 children in 2000. This significant upward trend underscores the growing importance of understanding and addressing ASD in American society. Gender disparities in autism diagnosis The increase in ASD prevalence is not uniform across genders. From 2016 to 2019, male children were nearly four times more likely to be diagnosed with ASD than their female counterparts. Approximately 4.8 percent of boys aged 3 to 17 years had received an ASD diagnosis at some point in their lives, compared to only 1.3 percent of girls in the same age group. This substantial gender gap highlights the need for further research into potential biological and social factors influencing ASD diagnosis rates. Racial and ethnic variations in autism prevalence Autism prevalence also varies across racial and ethnic groups. Data from 2016 to 2019 show that non-Hispanic white children aged 3 to 17 years had an ASD prevalence of 2.9 percent, while around 3.5 percent of Hispanic children had ASD. While this statistic provides insight, it is essential to consider potential disparities in diagnosis and access to services among different racial and ethnic communities. Further research and targeted interventions may be necessary to ensure equitable identification and support for children with ASD across all populations.

The prevalence rate of autism spectrum disorder among four-year-old children in Missouri was around 24.8 per 1,000 children in 2022. Autism spectrum disorder is a developmental disability characterized by deficits in social communication and interaction as well as repetitive behavior, interest, or activity patterns. This statistic displays the estimated prevalence of autism spectrum disorder among children aged four years in select U.S. states in 2022.

The prevalence rate of autism spectrum disorder among children aged eight years in the state Georgia was estimated to be around **** per 1,000 children. Autism spectrum disorder is a developmental disability characterized by deficits in social communication and interaction as well as repetitive behavior, interest, or activity patterns. Autism spectrum disorder in childrenAmong 14 U.S. states with areas that were monitored for autism spectrum disorder in 2022, California had the highest prevalence rates of autism spectrum disorder (ASD) among children aged eight years. In 2022, California’s prevalence rate was estimated to be **** cases per 1,000 children, while the rate was about **** cases per 1,000 children in Indiana. ASD is more common among male than female children, with an estimated ** male cases per 1,000 children and ** female cases per 1,000 children in California in 2022. Limitations in a child with autism can vary between individuals and develop over time. In California, the median age of diagnosis among children with an ASD diagnosis with an IQ greater than 70 was ********* of age, in comparison to ********* for children with an ASD diagnosis and an IQ less than or equal to 70, indicating a co-occurring intellectual disability. The prevalence of ASD has increased significantly since the late 1960s by about ** to ** times. Many studies suggest that this is due to improved awareness and recognition, as well as diagnostic capabilities. Autism is likely caused by a combination of genetics and environmental factors, where people with ASD may have abnormal levels of brain serotonin, which could disrupt early brain development.

The prevalence rate of autism spectrum disorder among male children aged eight years in Georgia was estimated to be around ** per 1,000 children as of 2022. Autism spectrum disorder is a developmental disability characterized by deficits in social communication and interaction as well as repetitive behavior, interest, or activity patterns. This statistic displays the estimated prevalence of autism spectrum disorder among children aged 8 years in select U.S. states in 2022, by gender.

This table provides county-level prevalence for 2018 for seven US states using linked statewide health and education data. For full methods see: Shaw KA, Williams S, Hughes MM, Warren Z, Bakian AV, Durkin MS, et al. Statewide county-level autism spectrum disorder prevalence estimates — seven U.S. states, 2018. Annals of Epidemiology. 2023 Jan 18; Available from: https://www.sciencedirect.com/science/article/pii/S1047279723000182

Background: Whilst cannabis is known to be toxic to brain function and brain development in many respects it is not known if its increasing availability is associated with the rising US autism rates, whether this contribution is sufficient to effect overall trends and if its effects persist after controlling for other major covariates.

Methods: Longitudinal epidemiological study using national autism census data from the US Department of Education Individuals with Disabilities Act (IDEA) 1991-2011 and nationally representative drug exposure (cigarettes, alcohol, analgesic, and cocaine abuse, and cannabis use monthly, daily and in pregnancy) datasets from National Survey of Drug Use and Health and US Census (income and ethnicity) and CDC Wonder population and birth data. Geotemporospatial and causal inference analysis conducted in R.

Results: 266,950 autistic of a population of 40,119,464 eight year olds 1994-2011. At the national level after adjustment daily cannabis use was significantly related (β-estimate=4.37 (95%C.I. 4.06-4.68), P<2.2x10-16) as was cannabis exposure in the first trimester of pregnancy (β-estimate=0.12 (0.08-0.16), P=1.7x10-12). At the state level following adjustment cannabis use was significant (from β-estimate=8.41 (3.08-13.74), P=0.002); after adjustment for varying cannabis exposure by ethnicity and other covariates (from β-estimate=10.88 (5.97-15.79), P=1.4x10-5). Cannabigerol (from β-estimate=-13.77 (-19.41—8.13), P = 1.8x10-6) and Δ9-tetrahydrocannabinol (from β-estimate=1.96 (0.88-3.04), P=4x10-4) were also significant. Geospatial state-level modelling showed an exponential relationship between ASMR and both Δ9-tetrahydrocannabinol and cannabigerol exposure; effect size calculations reflected this exponentiation. Exponential coefficients for the relationship between modelled ASMR and THC- and cannabigerol- exposure were 7.053 (6.39-7.71) and 185.334 (167.88-202.79; both P<2.0x10-7).

In inverse probability-weighted robust generalized linear models ethnic cannabis exposure (from β-estimate=3.64 (2.94-4.34), P=5.9x10-13) and cannabis independently (β-estimate=1.08 (0.63-1.54), P=2.9x10-5) were significant. High eValues in geospatial models indicated that uncontrolled confounding did not explain these findings. Therefore the demonstrated relationship satified the criteria of causal inference. Dichotomized legal status was geospatiotemporally linked with elevated ASMR.

Conclusions: Data show cannabis use is associated with ASMR, is powerful enough to affect overall trends, and persists after controlling for other major drug, socioeconomic, and ethnic-related covariates. Selected cannabinoids are exponentially associated with ASMR. The cannabis-autism relationship satisfies criteria of causal inference.

In the academic year of 2022/23, there were approximately ******* individuals 3- to 21-years-old with autism in the United States who were covered by the Individuals with Disabilities Education Act (IDEA). This is an increase from the previous year, when ******* individuals with autism were covered under IDEA.

The prevalence rate of autism spectrum disorder among children aged eight years in Missouri was **** per 1,000 children in 2010. In 2022, this rate was estimated to be **** per 1,000 eight-year-olds. Autism spectrum disorder is a developmental disability characterized by deficits in social communication and interaction as well as repetitive behavior, interest, or activity patterns. This statistic displays the estimated prevalence of autism spectrum disorder among children aged 8 years in select U.S. states from 2010 to 2022.

autism prevalence studies

  Description

This data table provides a collection of information from peer-reviewed autism prevalence studies. Information reported from each study includes the autism prevalence estimate and additional study characteristics (e.g., case ascertainment and criteria). A PubMed search was conducted to identify studies published at any time through September 2020 using the search terms: autism (title/abstract) OR autistic (title/abstract) AND… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/autism-prevalence-studies.

Background and ObjectivesStudy of the impact of socioeconomic status on autism spectrum disorders (ASD) and severe intellectual disabilities (ID) has yielded conflicting results. Recent European studies suggested that, unlike reports from the United States, low socioeconomic status is associated with an increased risk of ASD. For intellectual disabilities, the links with socioeconomic status vary according to the severity. We wished to clarify the links between socioeconomic status and the prevalence of ASD (with or without ID) and isolated severe ID.Methods500 children with ASD and 245 children with severe ID (IQ

Denominatora = number of 8-year-old children living in the surveillance area between 2003 and 2012 (based on an estimation of the population with 2007 census data carried over to the 10 generations studied).bp = prevalence for 1,000 eight -year-old children living in the surveillance area.c 95% confidence interval.Cases Included in the Study and Prevalence of ASD (with and without ID) and Severe ID for 1,000 Eight-Year-Old Children Living in the Surveillance Area between 2003 and 2012.

The global Autism Spectrum Disorder (ASD) market, valued at $7.78 billion in 2025, is projected to experience robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 7.6% from 2025 to 2033. This expansion is driven by several key factors. Increased awareness and early diagnosis of ASD are leading to higher treatment rates. Advances in therapeutic interventions, including both pharmacological and non-pharmacological approaches, offer improved outcomes for individuals with ASD and their families. Furthermore, the growing prevalence of ASD globally, coupled with increased investment in research and development of new treatments, fuels market growth. The market is segmented by therapy type (pharmacological and non-pharmacological) and age group (pediatric and adult), reflecting the diverse needs of the ASD population. Pharmacological therapies currently hold a larger market share, due to the established efficacy of certain medications in managing ASD-related symptoms. However, the non-pharmacological segment is experiencing significant growth, driven by rising interest in behavioral therapies and other holistic approaches. The adult segment shows increasing demand as individuals with ASD live longer and require continued support. Regionally, North America and Europe currently dominate the market due to established healthcare infrastructure, higher awareness, and greater access to specialized services. However, Asia-Pacific is expected to witness significant growth in the coming years, fueled by rising disposable incomes, improved healthcare access, and increasing diagnostic capabilities. Competitive pressures within the market are intense, with leading companies focusing on developing innovative therapies, expanding their geographical reach, and strengthening their market positioning through strategic collaborations and acquisitions. Challenges remain, including the high cost of treatments, accessibility issues in certain regions, and the need for more effective treatments for specific ASD-related symptoms. Despite these challenges, the long-term outlook for the ASD market remains positive, driven by sustained investment in research, growing awareness, and an increasing focus on improving the lives of individuals with ASD.

This statistic shows the estimated prevalence of autism spectrum disorder among children aged 3 to 17 years in the U.S. from 2016 to 2019, by gender. In that period, around 4.8 percent of male children and 1.3 percent of female children had been diagnosed with autism spectrum disorder at some point in their life.

a n = number of cases in the census unit group defined by tertile of distribution of each indicator in the general population.b PRR = prevalence risk ratio.Census units were divided into tertiles according to the distribution of each indicator, the first tertile being the least deprived and used as a baseline for the computing of risk ratios.

BackgroundAutism is associated with high rates of genomic aberrations, including chromosomal rearrangements and de novo copy-number variations. These observations are reminiscent of cancer, a disease where genomic rearrangements also play a role. We undertook a correlative epidemiological study to explore the possibility that shared risk factors might exist for autism and specific types of cancer.Methodology/Principal FindingsTo determine if significant correlations exist between the prevalence of autism and the incidence of cancer, we obtained and analyzed state-wide data reported by age and gender throughout the United States. Autism data were obtained from the U.S. Department of Education via the Individuals with Disabilities Education Act (IDEA) (2000–2007, reported annually by age group) and cancer incidence data were obtained from the Centers for Disease Control and Prevention (CDC) (1999–2005). IDEA data were further subdivided depending on the method used to diagnose autism (DSM IV or the Code of Federal Regulations, using strict or expanded criteria). Spearman rank correlations were calculated for all possible pairwise combinations of annual autism rates and the incidence of specific cancers. Following this, Bonferroni's correction was applied to significance values. Two independent methods for determining an overall combined p-value based on dependent correlations were obtained for each set of calculations. High correlations were found between autism rates and the incidence of in situ breast cancer (p≤10−10, modified inverse chi square, n = 16) using data from states that adhere strictly to the Code of Federal Regulations for diagnosing autism. By contrast, few significant correlations were observed between autism prevalence and the incidence of 23 other female and 22 male cancers.ConclusionsThese findings suggest that there may be an association between autism and specific forms of cancer.

Input datasets on Ohio Birth and Autism will not be made accessible to the public due to the fact that they include individual-level data with PII. Output data are all available in tabulated form within the published manuscript. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Input data can be obtained from Applications from owners of the data (Children's Hospital and Ohio Department of Health). The tabulated output data is found in the manuscript. Format: Input datasets on Ohio Birth and Autism will not be made accessible to the public due to the fact that they include individual-level data with PII. Output data are all available in tabulated form within the published manuscript (e.g., results of regression models, measures of central tendency, population characteristics, etc.).

This dataset is associated with the following publication: Kaufman, J., M. Wright, G. Rice, N. Connolly, K. Bowers, and J. Anixt. AMBIENT OZONE AND FINE PARTICULATE MATTER EXPOSURES AND AUTISM SPECTRUM DISORDER IN METROPOLITAN CINCINNATI, OHIO. ENVIRONMENTAL RESEARCH. Elsevier B.V., Amsterdam, NETHERLANDS, 171: 218-227, (2019).

Purpose: We aim to determine the prevalence and characteristics of developmental disabilities among the clinical population of children who receive hearing health care in the United States.Method: Using electronic health records of 131,709 children (0–18 years), we identified those with a diagnosis of attention deficit/hyperactivity disorder, autism spectrum disorder, vision differences, cerebral palsy, chromosomal abnormalities, delayed milestones, Down syndrome, or intellectual disability. We determined prevalence, age of first audiology encounter, age of diagnosis for the developmental disability, and hearing status based on the specific disability and the number of diagnoses. Binomial and multinomial logistic regressions were performed.Results: One in four children had a diagnosed developmental disability. The most common disabilities were delayed milestones (11.3%), vision differences (7.4%), attention-deficit/hyperactivity disorder (6.6%), and autism spectrum disorder (6.2%). Half of the children with developmental disabilities had at least one diagnosis before their first audiology encounter. Children with developmental disabilities were more likely to have a reduced hearing or an unknown hearing status than children without developmental diagnoses. For children with reduced hearing, those with developmental disabilities had higher rates of bilateral configurations and poorer hearing severity levels.Conclusions: Developmental disabilities are common among children who seek hearing health care. Moreover, developmental disabilities often co-occur with reduced hearing. Further research and advocacy efforts are critical for creating clinical practices that are inclusive of, and equitable for, children with complex and diverse developmental profiles.Supplemental Material S1. ICD-9/10 umbrella mappings for the specific developmental disabilities used in the study.Supplemental Material S2. Binomial logistic regression results for if a diagnosis of attention deficit/hyperactivity disorder (ADHD) was known at the time of the first audiology encounter.Supplemental Material S3. Binomial logistic regression results for if a diagnosis of autism spectrum disorder was known at the time of the first audiology encounter.Supplemental Material S4. Binomial logistic regression results for if a diagnosis of cerebral palsy was known at the time of the first audiology encounter.Supplemental Material S5. Binomial logistic regression results for if a diagnosis of a chromosomal abnormality was known at the time of the first audiology encounter.Supplemental Material S6. Binomial logistic regression results for if a diagnosis of delayed milestones was known at the time of the first audiology encounter.Supplemental Material S7. Binomial logistic regression results for if a diagnosis of Down syndrome was known at the time of the first audiology encounter.Supplemental Material S8. Binomial logistic regression results for if a diagnosis of an intellectual disability was known at the time of the first audiology encounter.Supplemental Material S9. Binomial logistic regression results for if a diagnosis of a vision difference was known at the time of the first audiology encounter.Bonino, A. Y., Goodwich, S. F., & Mood, D. (2025). Prevalence and characteristics of developmental disabilities among children who receive hearing health care. American Journal of Audiology, 34(1), 60–71. https://doi.org/10.1044/2024_AJA-24-00118

This is a peer-reviewed supplementary table for the article 'A US national update of health condition prevalence among privately-insured autistic adults' published in the Journal of Comparative Effectiveness Research.Supplementary Table 1: Study definitions of mental and physical health conditions using Healthcare Cost and Utilization Project (HCUP) Beta Multilevel Clinical Classification Software (CCS) or specific International Classification of Diseases, 10th edition (ICD-10) diagnosis codes.Aim: Previous research using state or regional samples has shown that autistic adults have a higherprevalence of health conditions in comparison to the general population. Methods: To build upon thisimportant previous research, we conducted a cross-sectional retrospective study of 2019–2020 healthcareclaims to determine the prevalence of conditions in a US national sample of privately insured autistic adults(n = 30,258) and an age- and sex-matched population comparison (n = 60,516) group of adults withoutautism diagnoses. Results: Like previous studies, we found that autistic adults had significantly greaterodds of most mental and physical health conditions. However, our prevalence estimates differed fromprevious studies for several mental and physical health conditions. For example, our sample of autisticadults had higher prevalence of anxiety disorders (55%) and attention deficit hyperactivity disorders(34%), but lower prevalence of asthma (9%) and sleep disorders (3%) than previous studies. Discussion& conclusion: Our use of a large US national sample, more recent healthcare claims data, and differentmethods for identifying health conditions may have contributed to these differences. Our findings alerthealthcare providers and policymakers to the health conditions most common among the growingpopulation of autistic adults. We hope these findings lead to improved screening and management ofthese conditions, inform initiatives to improve access to healthcare, and guide future funding.

The global market for autism disorder treatment is experiencing significant growth, driven by increasing autism prevalence, rising awareness, and advancements in diagnostic tools and therapeutic interventions. The market, while currently substantial, is projected to expand considerably over the forecast period (2025-2033). Several factors contribute to this growth. Firstly, improved diagnostic capabilities are leading to earlier and more accurate identification of autism spectrum disorder (ASD) across various age groups (1-14, 15-25, 26-40, and over 40), leading to increased demand for treatment. Secondly, a shift towards personalized therapies and behavioral interventions, catering to the diverse needs of individuals with low-functioning and high-functioning autism, is driving market expansion. Finally, the ongoing research and development of novel pharmaceuticals and therapies offer promising avenues for future growth. Major pharmaceutical companies like Otsuka, AstraZeneca, Pfizer, and others are heavily invested in this area, further fueling market expansion. Geographic variations exist, with North America and Europe currently holding a larger market share due to higher healthcare spending and established healthcare infrastructure. However, developing regions in Asia-Pacific are expected to witness rapid growth owing to increasing awareness and rising disposable incomes. Market restraints include the high cost of treatment, limited access to specialized care in certain regions, and the lack of effective treatments for some severe cases. Despite these challenges, the overall outlook for the autism disorder treatment market remains highly positive. The segmentation of the market by age group (1-14, 15-25, 26-40, and over 40) and autism functioning level (low and high-functioning) highlights the need for tailored treatment approaches. This necessitates further research and development to address the unique needs of each sub-group. The competitive landscape is characterized by the presence of both large pharmaceutical companies and smaller biotech firms focusing on innovative therapies. Strategic partnerships and mergers and acquisitions are likely to shape the market dynamics in the coming years. The continued focus on early intervention programs, coupled with improved access to effective therapies, will be crucial in improving the quality of life for individuals with autism and their families. This market's future hinges on advancements in understanding the underlying causes of autism and the development of more targeted and effective therapies. A continued commitment to research and funding will be essential for achieving sustained growth and improved outcomes for this growing population.