Global Prevalence of Autism and Other Pervasive Developmental Disorders
TL;DR: In this paper, a systematic review of epidemiological surveys of autistic disorder and pervasive developmental disorders (PDDs) worldwide was provided, where the authors considered the possible impact of geographic, cultural/ethnic/ethnic, and socioeconomic factors on prevalence estimates and on clinical presentation of PDD.
Abstract: We provide a systematic review of epidemiological surveys of autistic disorder and pervasive developmental disorders (PDDs) worldwide. A secondary aim was to consider the possible impact of geographic, cultural/ethnic, and socioeconomic factors on prevalence estimates and on clinical presentation of PDD. Based on the evidence reviewed, the median of prevalence estimates of autism spectrum disorders was 62/10 000. While existing estimates are variable, the evidence reviewed does not support differences in PDD prevalence by geographic region nor of a strong impact of ethnic/cultural or socioeconomic factors. However, power to detect such effects is seriously limited in existing data sets, particularly in low-income countries. While it is clear that prevalence estimates have increased over time and these vary in different neighboring and distant regions, these findings most likely represent broadening of the diagnostic concets, diagnostic switching from other developmental disabilities to PDD, service availability, and awareness of autistic spectrum disorders in both the lay and professional public. The lack of evidence from the majority of the world's population suggests a critical need for further research and capacity building in low- and middle-income countries. Autism Res 2012, 5: 160–179. © 2012 International Society for Autism Research, Wiley Periodicals, Inc.
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Centers for Disease Control and Prevention1, University of North Carolina at Chapel Hill2, Vanderbilt University3, University of Arizona4, Rutgers University5, University of Colorado Denver6, Colorado Department of Public Health and Environment7, University of Wisconsin-Madison8, United States Department of Energy9, Johns Hopkins University10, University of Arkansas for Medical Sciences11, Washington University in St. Louis12, University of Minnesota13
TL;DR: This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD.
Abstract: Problem/condition Autism spectrum disorder (ASD). Period covered 2014. Description of system The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years whose parents or guardians reside within 11 ADDM sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). ADDM surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by professional service providers in the community. Staff completing record review and abstraction receive extensive training and supervision and are evaluated according to strict reliability standards to certify effective initial training, identify ongoing training needs, and ensure adherence to the prescribed methodology. Record review and abstraction occurs in a variety of data sources ranging from general pediatric health clinics to specialized programs serving children with developmental disabilities. In addition, most of the ADDM sites also review records for children who have received special education services in public schools. In the second phase of the study, all abstracted information is reviewed systematically by experienced clinicians to determine ASD case status. A child is considered to meet the surveillance case definition for ASD if he or she displays behaviors, as described on one or more comprehensive evaluations completed by community-based professional providers, consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for autistic disorder; pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism); or Asperger disorder. This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD. In 2013, the American Psychiatric Association published the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which made considerable changes to ASD diagnostic criteria. The change in ASD diagnostic criteria might influence ADDM ASD prevalence estimates; therefore, most (85%) of the records used to determine prevalence estimates based on DSM-IV-TR criteria underwent additional review under a newly operationalized surveillance case definition for ASD consistent with the DSM-5 diagnostic criteria. Children meeting this new surveillance case definition could qualify on the basis of one or both of the following criteria, as documented in abstracted comprehensive evaluations: 1) behaviors consistent with the DSM-5 diagnostic features; and/or 2) an ASD diagnosis, whether based on DSM-IV-TR or DSM-5 diagnostic criteria. Stratified comparisons of the number of children meeting either of these two case definitions also are reported. Results For 2014, the overall prevalence of ASD among the 11 ADDM sites was 16.8 per 1,000 (one in 59) children aged 8 years. Overall ASD prevalence estimates varied among sites, from 13.1-29.3 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and race/ethnicity. Males were four times more likely than females to be identified with ASD. Prevalence estimates were higher for non-Hispanic white (henceforth, white) children compared with non-Hispanic black (henceforth, black) children, and both groups were more likely to be identified with ASD compared with Hispanic children. Among the nine sites with sufficient data on intellectual ability, 31% of children with ASD were classified in the range of intellectual disability (intelligence quotient [IQ] 85). The distribution of intellectual ability varied by sex and race/ethnicity. Although mention of developmental concerns by age 36 months was documented for 85% of children with ASD, only 42% had a comprehensive evaluation on record by age 36 months. The median age of earliest known ASD diagnosis was 52 months and did not differ significantly by sex or race/ethnicity. For the targeted comparison of DSM-IV-TR and DSM-5 results, the number and characteristics of children meeting the newly operationalized DSM-5 case definition for ASD were similar to those meeting the DSM-IV-TR case definition, with DSM-IV-TR case counts exceeding DSM-5 counts by less than 5% and approximately 86% overlap between the two case definitions (kappa = 0.85). Interpretation Findings from the ADDM Network, on the basis of 2014 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD among children aged 8 years in multiple communities in the United States. The overall ASD prevalence estimate of 16.8 per 1,000 children aged 8 years in 2014 is higher than previously reported estimates from the ADDM Network. Because the ADDM sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States. Consistent with reports from previous ADDM surveillance years, findings from 2014 were marked by variation in ASD prevalence when stratified by geographic area, sex, and level of intellectual ability. Differences in prevalence estimates between black and white children have diminished in most sites, but remained notable for Hispanic children. For 2014, results from application of the DSM-IV-TR and DSM-5 case definitions were similar, overall and when stratified by sex, race/ethnicity, DSM-IV-TR diagnostic subtype, or level of intellectual ability. Public health action Beginning with surveillance year 2016, the DSM-5 case definition will serve as the basis for ADDM estimates of ASD prevalence in future surveillance reports. Although the DSM-IV-TR case definition will eventually be phased out, it will be applied in a limited geographic area to offer additional data for comparison. Future analyses will examine trends in the continued use of DSM-IV-TR diagnoses, such as autistic disorder, PDD-NOS, and Asperger disorder in health and education records, documentation of symptoms consistent with DSM-5 terminology, and how these trends might influence estimates of ASD prevalence over time. The latest findings from the ADDM Network provide evidence that the prevalence of ASD is higher than previously reported estimates and continues to vary among certain racial/ethnic groups and communities. With prevalence of ASD ranging from 13.1 to 29.3 per 1,000 children aged 8 years in different communities throughout the United States, the need for behavioral, educational, residential, and occupational services remains high, as does the need for increased research on both genetic and nongenetic risk factors for ASD.
3,967 citations
TL;DR: In the past three decades, there has been no evidence to suggest an increase in the number of children in the community who meet criteria for ADHD when standardized diagnostic procedures are followed.
Abstract: Background: Previous studies have identified significant variability in attention-deficit / hyperactivity disorder (ADHD) prevalence estimates worldwide, largely explained by methodological procedures. However, increasing rates of ADHD diagnosis and treatment throughout the past few decades have fuelled concerns about whether the true prevalence of the disorder has increased over time. Methods: We updated the two most comprehensive systematic reviews on ADHD prevalence available in the literature. Meta-regression analyses were conducted to test the effect of year of study in the context of both methodological variables that determined variability in ADHD prevalence (diagnostic criteria, impairment criterion and source of information), and the geographical location of studies. Results: We identified 154 original studies and included 135 in the multivariate analysis. Methodological procedures investigated were significantly associated with heterogeneity of studies. Geographical location and year of study were not associated with variability in ADHD prevalence estimates. Conclusions: Confirming previous findings, variability in ADHD prevalence estimates is mostly explained by methodological characteristics of the studies. In the past three decades, there has been no evidence to suggest an increase in the number of children in the community who meet criteria for ADHD when standardized diagnostic procedures are followed.
1,078 citations
TL;DR: Clinicians can make a difference by providing timely and individualised help to families navigating referrals and access to community support systems, by providing accurate information despite often unfiltered media input, and by anticipating transitions such as family changes and school entry and leaving.
1,023 citations
24 Oct 2013
TL;DR: In this article, the authors conducted a meta-regression analysis to test the effect of year of study in the context of both methodological variables that determined variability in ADHD prevalence (diagnostic criteria, impairment criterion and source of information), and the geographical location of studies.
Abstract: BACKGROUND
Previous studies have identified significant variability in attention-deficit / hyperactivity disorder (ADHD) prevalence estimates worldwide, largely explained by methodological procedures. However, increasing rates of ADHD diagnosis and treatment throughout the past few decades have fuelled concerns about whether the true prevalence of the disorder has increased over time.
METHODS
We updated the two most comprehensive systematic reviews on ADHD prevalence available in the literature. Meta-regression analyses were conducted to test the effect of year of study in the context of both methodological variables that determined variability in ADHD prevalence (diagnostic criteria, impairment criterion and source of information), and the geographical location of studies.
RESULTS
We identified 154 original studies and included 135 in the multivariate analysis. Methodological procedures investigated were significantly associated with heterogeneity of studies. Geographical location and year of study were not associated with variability in ADHD prevalence estimates.
CONCLUSIONS
Confirming previous findings, variability in ADHD prevalence estimates is mostly explained by methodological characteristics of the studies. In the past three decades, there has been no evidence to suggest an increase in the number of children in the community who meet criteria for ADHD when standardized diagnostic procedures are followed.
768 citations
TL;DR: Genetics studies of autism spectrum disorder (ASD) have identified several risk genes that are key regulators of synaptic plasticity, and when deleterious mutations occur, inefficient genetic buffering and impaired synaptic homeostasis may increase an individual's risk for ASD.
Abstract: Genetics studies of autism spectrum disorder (ASD) have identified several risk genes that are key regulators of synaptic plasticity. Indeed, many of the risk genes that have been linked to these disorders encode synaptic scaffolding proteins, receptors, cell adhesion molecules or proteins that are involved in chromatin remodelling, transcription, protein synthesis or degradation, or actin cytoskeleton dynamics. Changes in any of these proteins can increase or decrease synaptic strength or number and, ultimately, neuronal connectivity in the brain. In addition, when deleterious mutations occur, inefficient genetic buffering and impaired synaptic homeostasis may increase an individual's risk for ASD.
730 citations
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TL;DR: An issue concerning the criteria for tic disorders is highlighted, and how this might affect classification of dyskinesias in psychotic spectrum disorders.
Abstract: Given the recent attention to movement abnormalities in psychosis spectrum disorders (e.g., prodromal/high-risk syndromes, schizophrenia) (Mittal et al., 2008; Pappa and Dazzan, 2009), and an ongoing discussion pertaining to revisions of the Diagnostic and Statistical Manuel of Mental Disorders (DSM) for the upcoming 5th edition, we would like to take this opportunity to highlight an issue concerning the criteria for tic disorders, and how this might affect classification of dyskinesias in psychotic spectrum disorders.
Rapid, non-rhythmic, abnormal movements can appear in psychosis spectrum disorders, as well as in a host of commonly co-occurring conditions, including Tourette’s Syndrome and Transient Tic Disorder (Kerbeshian et al., 2009). Confusion can arise when it becomes necessary to determine whether an observed movement (e.g., a sudden head jerk) represents a spontaneous dyskinesia (i.e., spontaneous transient chorea, athetosis, dystonia, ballismus involving muscle groups of the arms, legs, trunk, face, and/or neck) or a tic (i.e., stereotypic or patterned movements defined by the relationship to voluntary movement, acute and chronic time course, and sensory urges). Indeed, dyskinetic movements such as dystonia (i.e., sustained muscle contractions, usually producing twisting and repetitive movements or abnormal postures or positions) closely resemble tics in a patterned appearance, and may only be visually discernable by attending to timing differences (Gilbert, 2006).
When turning to the current DSM-IV TR for clarification, the description reads: “Tic Disorders must be distinguished from other types of abnormal movements that may accompany general medical conditions (e.g., Huntington’s disease, stroke, Lesch-Nyhan syndrome, Wilson’s disease, Sydenham’s chorea, multiple sclerosis, postviral encephalitis, head injury) and from abnormal movements that are due to the direct effects of a substance (e.g., a neuroleptic medication)”. However, as it is written, it is unclear if psychosis falls under one such exclusionary medical disorder. The “direct effects of a substance” criteria, referencing neuroleptic medications, further contributes to the uncertainty around this issue. As a result, ruling-out or differentiating tics in psychosis spectrum disorders is at best, a murky endeavor.
Historically, the advent of antipsychotic medication in the 1950s has contributed to the confusion about movement signs in psychiatric populations. Because neuroleptic medications produce characteristic movement disorder in some patients (i.e. extrapyramidal side effects), drug-induced movement disturbances have been the focus of research attention in psychotic disorders. However, accumulating data have documented that spontaneous dyskinesias, including choreoathetodic movements, can occur in medication naive adults with schizophrenia spectrum disorders (Pappa and Dazzan, 2009), as well as healthy first-degree relatives of chronically ill schizophrenia patients (McCreadie et al., 2003). Taken together, this suggests that movement abnormalities may reflect pathogenic processes underlying some psychotic disorders (Mittal et al., 2008; Pappa and Dazzan, 2009).
More specifically, because spontaneous hyperkinetic movements are believed to reflect abnormal striatal dopamine activity (DeLong and Wichmann, 2007), and dysfunction in this same circuit is also proposed to contribute to psychosis, it is possible that spontaneous dyskinesias serve as an outward manifestation of circuit dysfunction underlying some schizophrenia-spectrum symptoms (Walker, 1994). Further, because these movements precede the clinical onset of psychotic symptoms, sometimes occurring in early childhood (Walker, 1994), and may steadily increase during adolescence among populations at high-risk for schizophrenia (Mittal et al., 2008), observable dyskinesias could reflect a susceptibility that later interacts with environmental and neurodevelopmental factors, in the genesis of psychosis.
In adolescents who meet criteria for a prodromal syndrome (i.e., the period preceding formal onset of psychotic disorders characterized by subtle attenuated positive symptoms coupled with a decline in functioning), there is sometimes a history of childhood conditions which are also characterized by suppressible tics or tic like movements (Niendam et al., 2009). On the other hand, differentiating between tics and dyskinesias has also complicated research on childhood disorders such as Tourette syndrome (Kompoliti and Goetz, 1998; Gilbert, 2006).
We propose consideration of more explicit and operationalized criteria for differentiating tics and dyskinesias, based on empirically derived understanding of neural mechanisms. Further, revisions of the DSM should allow for the possibility that movement abnormalities might reflect neuropathologic processes underlying the etiology of psychosis for a subgroup of patients. Psychotic disorders might also be included among the medical disorders that are considered a rule-out for tics.
Related to this, the reliability of movement assessment needs to be improved, and this may require more training for mental health professionals in movement symptoms. Although standardized assessment of movement and neurological abnormalities is common in research settings, it has been proposed that an examination of neuromotor signs should figure in the assessment of any patient, and be as much a part of the patient assessment as the mental state examination (Picchioni and Dazzan, 2009).
To this end it is important for researchers and clinicians to be aware of differentiating characteristics for these two classes of abnormal movement. For example, tics tend to be more complex than myoclonic twitches, and less flowing than choreoathetodic movements (Kompoliti and Goetz, 1998). Patients with tics often describe a sensory premonition or urge to perform a tic, and the ability to postpone tics at the cost of rising inner tension (Gilbert, 2006). For example, one study showed that patients with tic disorders could accurately distinguish tics from other movement abnormalities based on the subjective experience of some voluntary control of tics (Lang, 1991). Another differentiating factor derives from the relationship of the movement in question to other voluntary movements. Tics in one body area rarely occur during purposeful and voluntary movements in that same body area whereas dyskinesia are often exacerbated by voluntary movement (Gilbert, 2006). Finally, it is noteworthy that tics wax and wane in frequency and intensity and migrate in location over time, often becoming more complex and peaking between the ages of 9 and 14 years (Gilbert, 2006). In the case of dyskinesias among youth at-risk for psychosis, there is evidence that the movements tend to increase in severity and frequency as the individual approaches the mean age of conversion to schizophrenia spectrum disorders (Mittal et al., 2008).
As revisions to the DSM are currently underway in preparation for the new edition (DSM V), we encourage greater attention to the important, though often subtle, distinctions among subtypes of movement abnormalities and their association with psychiatric syndromes.
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TL;DR: Algorithm sensitivities and specificities for autism and PD DNOS relative to nonspectrum disorders were excellent, with moderate differentiation of autism from PDDNOS.
Abstract: The Autism Diagnostic Observation Schedule-Generic (ADOS-G) is a semistructured, standardized assessment of social interaction, communication, play, and imaginative use of materials for individuals suspected of having autism spectrum disorders. The observational schedule consists of four 30-minute modules, each designed to be administered to different individuals according to their level of expressive language. Psychometric data are presented for 223 children and adults with Autistic Disorder (autism), Pervasive Developmental Disorder Not Otherwise Specified (PDDNOS) or nonspectrum diagnoses. Within each module, diagnostic groups were equivalent on expressive language level. Results indicate substantial interrater and test-retest reliability for individual items, excellent interrater reliability within domains and excellent internal consistency. Comparisons of means indicated consistent differentiation of autism and PDDNOS from nonspectrum individuals, with some, but less consistent, differentiation of autism from PDDNOS. A priori operationalization of DSM-IV/ICD-10 criteria, factor analyses, and ROC curves were used to generate diagnostic algorithms with thresholds set for autism and broader autism spectrum/PDD. Algorithm sensitivities and specificities for autism and PDDNOS relative to nonspectrum disorders were excellent, with moderate differentiation of autism from PDDNOS.
7,012 citations
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