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 prevalence (title/abstract). Data were abstracted and included if the study fulfilled the following criteria: • The study was published in English; • The study produced at least one autism prevalence estimate; and • The study was population-based (any age range) within a defined geographic area.

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.

As of 2023, almost ***** percent of those living in the state of West Virginia had a cognitive disability, such as Down syndrome, autism, or dementia. This statistic shows the percentage of people in the U.S. who had a cognitive disability as of 2023, by state.

The aim of this publication is to provide information about the key differences in healthcare between people with a learning disability and those without. It contains aggregated data on key health issues for people who are recorded by their GP as having a learning disability, and comparative data about a control group who are not recorded by their GP as having a learning disability. Six new indicators were introduced in the 2022-23 reporting year for patients with and without a recorded learning disability. These relate to: • Patients with an eating disorder • Patients with both an eating disorder and autism diagnosis • Patients with a diagnosis of autism who are currently treated with antidepressants More information on these changes can be found in the Data Quality section of this publication. Data has been collected from participating practices using EMIS and Cegedim Healthcare Systems GP systems.

This statistic displays the prevalence rate of autism spectrum disorders in Italy from 2010 to 2017. According to data, the rate slightly decreased over the period of consideration. As of 2017, among the Italian population about *** out of 100,000 individuals suffered from some autism spectrum disorder.

IntroductionAutism spectrum disorder (ASD) is a neurodevelopmental disorder clinically characterized by abnormalities in eye contact during social exchanges. We aimed to clarify whether the amount of gaze fixation, measured at the age of 6 years using Gazefinder, which is an established eye-tracking device, is associated with ASD symptoms and functioning.MethodsThe current study included 742 participants from the Hamamatsu Birth Cohort Study. Autistic symptoms were evaluated according to the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and the functioning of the participating children in real life was assessed using the Japanese version of the Vineland Adaptive Behavior Scales, Second Edition (VABS-II). The Gazefinder system was used for gaze fixation rates; two areas of interest (eyes and mouth) were defined in a talking movie clip, and eye gaze positions were calculated through corneal reflection techniques.ResultsThe participants had an average age of 6.06 ± 0.14 years (males: 384; 52%). According to ADOS, 617 (83%) children were assessed as having none/mild ASD and 51 (7%) as severe. The average VABS-II scores were approximately 100 (standard deviation = 12). A higher gaze fixation rate on the eyes was associated with a significantly lower likelihood of the child being assigned to the severe ADOS group after controlling for covariates (odds ratio [OR], 0.02; 95% confidence interval [CI], 0.002–0.38). The gaze fixation rate on the mouth was not associated with ASD symptoms. A higher gaze fixation rate on the mouth was associated with a significantly lower likelihood of the child being assigned to the low score group in VABS-II socialization after controlling for covariates (OR, 0.18; 95% CI, 0.04–0.85). The gaze fixation rate on the eyes was not associated with functioning.ConclusionWe found that children with low gaze fixation rates on the eyes were likely to have more ASD symptoms, and children with low gaze fixation rates on the mouth were likely to demonstrate poorer functioning in socialization. Hence, preschool children could be independently assessed in the general population for clinically relevant endophenotypes predictive of ASD symptoms and functional impairments.

In 2017, the highest DALY rates attributed to autism spectrum disorders was seen in Bihar, categorized as a low SDI state with **. DALYs or disability adjusted life years is a metric used to quantify the overall disease burden which is the number of years that are lost as a result of ill-health, disability or premature death. Furthermore, in Arunachal Pradesh, a medium SDI state also recorded a DALY rate of **. By contrast, the lowest DALY rate relative to autism spectrum disorders was seen in Himachal Pradesh, which is a high SDI state with **.

Counts of variants represents the aggregated variants in each population group. Variant frequency is the count of variant divided by total number of individuals in each population group. Proportion of variants between cases and controls in male and female are also calculated. Proportion is calculated based on variant frequency in each population group. (XLSX)

Autism spectrum disorder often co-occurs with other psychiatric disorders. Although a high prevalence of autistic-like traits/symptoms has been identified in the pediatric psychiatric population of normal intelligence, there are no reports from adult psychiatric population. This study examined whether there is a greater prevalence of autistic-like traits/symptoms in patients with adult-onset psychiatric disorders such as major depressive disorder (MDD), bipolar disorder, or schizophrenia, and whether such an association is independent of symptom severity. The subjects were 290 adults of normal intelligence between 25 and 59 years of age (MDD, n=125; bipolar disorder, n=56; schizophrenia, n=44; healthy controls, n=65). Autistic-like traits/symptoms were measured using the Social Responsiveness Scale for Adults. Symptom severity was measured using the Positive and Negative Symptoms Scale, the Hamilton Depression Rating Scale, and/or the Young Mania Rating Scale. Almost half of the clinical subjects, except those with remitted MDD, exhibited autistic-like traits/symptoms at levels typical for sub-threshold or threshold autism spectrum disorder. Furthermore, the proportion of psychiatric patients that demonstrated high autistic-like traits/symptoms was significantly greater than that of healthy controls, and not different between that of remitted or unremitted subjects with bipolar disorder or schizophrenia. On the other hand, remitted subjects with MDD did not differ from healthy controls with regard to the prevalence or degree of high autistic-like traits/symptoms. A substantial proportion of adults with bipolar disorder and schizophrenia showed high autistic-like traits/symptoms independent of symptom severity, suggesting a shared pathophysiology among autism spectrum disorder and these psychiatric disorders. Conversely, autistic-like traits among subjects with MDD were associated with the depressive symptom severity. These findings suggest the importance of evaluating autistic-like traits/symptoms underlying adult-onset psychiatric disorders for the best-suited treatment. Further studies with a prospective design and larger samples are needed.

It has been suggested that differences in binocular rivalry switching rates and mixed percept durations in ASD could serve as a biomarker of excitation/inhibition imbalances in the autistic brain. If so, one would expect these differences to extend to neurotypical groups with high vs. low levels of autistic tendency. Previous studies did not detect any correlations between binocular rivalry dynamics and Autism Spectrum Quotient (AQ) scores in neurotypical control groups; however it is unclear whether this was due to the characteristics of the rivalry stimuli that were used. We further investigated this possibility in a sample of neurotypical young adults. The binocular rivalry stimuli were simple gratings, complex objects, or scrambled objects, which were presented dichoptically, either at fixation or in the periphery. A Bayesian correlation analysis showed that individuals with higher AQ scores tended to have lower perceptual switching rates for the centrally presented, simple grating rival stimuli. However, there was no evidence of a relationship between AQ and switching rates, reversal rates or mixed percept durations for any of the other binocular rivalry conditions. Overall, our findings suggest that in the non-clinical population, autistic personality traits are not a strong predictor of binocular rivalry dynamics.