Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018

Epidemiology of autism spectrum disorders: Global burden of disease 2019 and bibliometric analysis of risk factors

BACKGROUND

To explore the geographical pattern and temporal trend of autism spectrum disorders (ASD) epidemiology from 1990 to 2019, and perform a bibliometric analysis of risk factors for ASD.

METHODS

In this study, ASD epidemiology was estimated with prevalence, incidence, and disability-adjusted life-years (DALYs) of 204 countries and territories by sex, location, and sociodemographic index (SDI). Age-standardized rate (ASR) and estimated annual percentage change (EAPC) were used to quantify ASD temporal trends. Besides, the study performed a bibliometric analysis of ASD risk factors since 1990. Publications published were downloaded from the Web of Science Core Collection database, and were analyzed using CiteSpace.

RESULTS

Globally, there were estimated 28.3 million ASD prevalent cases (ASR, 369.4 per 100,000 populations), 603,790 incident cases (ASR, 9.3 per 100,000 populations) and 4.3 million DALYs (ASR, 56.3 per 100,000 populations) in 2019. Increases of autism spectrum disorders were noted in prevalent cases (39.3%), incidence (0.1%), and DALYs (38.7%) from 1990 to 2019. Age-standardized rates and EAPC showed stable trend worldwide over time. A total of 3,991 articles were retrieved from Web of Science, of which 3,590 were obtained for analysis after removing duplicate literatures. "Rehabilitation", "Genetics & Heredity", "Nanoscience & Nanotechnology", "Biochemistry & Molecular biology", "Psychology", "Neurosciences", and "Environmental Sciences" were the hotspots and frontier disciplines of ASD risk factors.

CONCLUSIONS

Disease burden and risk factors of autism spectrum disorders remain global public health challenge since 1990 according to the GBD epidemiological estimates and bibliometric analysis. The findings help policy makers formulate public health policies concerning prevention targeted for risk factors, early diagnosis and life-long healthcare service of ASD. Increasing knowledge concerning the public awareness of risk factors is also warranted to address global ASD problem.

Usual care for youth with autism spectrum disorder: Community-based providers' reported familiarity with treatment practices

OBJECTIVE

To examine patterns and predictors of familiarity with transdisciplinary psychosocial (e.g., non-pharmacologic) practices for practitioners treating youths with autism spectrum disorder (ASD) in the United States.

METHOD

Practitioners (n = 701) from behavioral, education, medical, and mental health backgrounds who worked with youth (ages 7-22) with ASD completed the Usual Care for Autism Survey, which assessed provider demographics and self-reported familiarity with transdisciplinary treatment practices for the most common referral problems of ASD. We examined relations between provider-, setting-, and client-level characteristics with familiarity of key groups of the treatment practices (practice sets). Practice sets were identified using exploratory factor analysis (EFA), and demographic predictors of practice subsets were examined using generalized estimating equations (GEE).

RESULTS

The EFA yielded a three-factor solution: (1) environmental modifications/antecedent strategies; (2) behavior analytic strategies; and (3) cognitive strategies, with overall familiarity ranked in this order. Medical providers indicated the least familiarity across disciplines. More experience with ASD and treating those with intellectual disabilities predicted greater familiarity with only environmental modifications/antecedent strategies and behavior analytic, but not cognitive strategies. Experience treating low SES clients predicted familiarity with environmental modification and behavior analytic strategies while experience treating high SES clients predicted familiarity with behavior analytic and cognitive strategies.

CONCLUSION

This is the first study to identify transdisciplinary, interpretable sets of practices for treating youth with ASD based on community providers' reported familiarity. Results highlight factors associated with familiarity with practice sets, which is essential for mapping practice availability, and optimizing training and dissemination efforts for youth with ASD.

Feeding problems, age of introduction of complementary food and autism symptom in children with autism spectrum disorder

In this cross-sectional study, 84 children with autism spectrum disorder (ASD) and 77 healthy subjects showing typical development (TD) were reviewed. Parents reviewed the age of introduction of complementary foods (CFs), completed a demographic, diet behavior questionnaire and the Autism Behavior Checklist (ABC). The results showed that the age of introduction of CFs was later in children with ASD than their TD counterparts. The age of introduction of CFs in ASD group was positively correlated with feeding problem. While the correlation was not observed in TD group. Children in the ASD group had higher total scores of the diet behavior questionnaire and all four subdomains (poor eating ability, mealtime eating behavior, food selectivity, and parental feeding behavior). ASD symptoms were clearly associated with feeding problems. The sensory subdomain score in ABC was positively correlated with poor eating ability, mealtime behavior and total score of the diet behavior questionnaire. The social self-care subdomain score was positively correlated with food selectivity. The interaction subdomain score was negative correlated with parental feeding behavior and total score of the diet behavior questionnaire. Further studies are required to establish the utility of delayed CFs introduction and/or early feeding problems as potential indicators of ASD.

Temporopolar volumes are associated with the severity of social impairment and language development in children with autism spectrum disorder with developmental delay

BACKGROUND

Children with autism spectrum disorder (ASD) and developmental delay (DD; ASD + DD) have more severe clinical symptoms than those with ASD without DD (ASD-only). However, little is known about the underlying neuroimaging mechanisms. The aim of this study was to explore the volumetric difference between patients with ASD + DD and ASD-only and investigate the relationship between brain alterations and clinical manifestations.

MATERIALS AND METHODS

A total of 184 children with ASD aged 2-6 years were included in this study, who were divided into two groups according to their cognitive development: ASD + DD and ASD-only. Clinical symptoms and language development were assessed using the Autism Diagnostic Observation Schedule (ADOS), Childhood Autism Rating Scale (CARS), and the Putonghua Communicative Development Inventory. Of the 184 children, 60 age-matched males (30 ASD + DD and 30 ASD-only patients) with high-resolution structural neuroimaging scans were included for further voxel-based morphometry analysis to examine the relationship between clinical symptoms and gray matter volumes.

RESULTS

The ASD + DD group had higher CARS and ADOS scores, lower gesture scores, and poorer performance in "responding to joint attention" (RJA) and "initiating joint attention" than the ASD-only group. Larger gray matter volumes in the temporal poles of the right and left middle temporal gyri were associated with the co-occurrence of DD in patients with ASD. Moreover, temporopolar volumes were correlated with CARS and ADOS scores, gesture scores, and RJA ability. Pre-language development significantly mediated the relationship between temporopolar volumes and both CARS and ADOS scores; RJA ability, but not gesture development, contributed to this mediating effect.

CONCLUSION

In this study, we found that temporopolar volumes were enlarged in patients with ASD who had comorbid DD, and these patients showed an association between symptom severity and language ability during the pre-language stage. Offering early interventions focused on RJA and the temporal pole may help improve clinical symptoms.

Application and research progress of machine learning in the diagnosis and treatment of neurodevelopmental disorders in children

The prevalence of neurodevelopment disorders (NDDs) among children has been on the rise. This has affected the health and social life of children. This condition has also imposed a huge economic burden on families and health care systems. Currently, it is difficult to perform early diagnosis of NDDs, which results in delayed intervention. For this reason, patients with NDDs have a prognosis. In recent years, machine learning (ML) technology, which integrates artificial intelligence technology and medicine, has been applied in the early detection and prediction of diseases based on data mining. This paper reviews the progress made in the application of ML in the diagnosis and treatment of NDDs in children based on supervised and unsupervised learning tools. The data reviewed here provide new perspectives on early diagnosis and treatment of NDDs.

A Multi-Center Study on the Relationship Between Developmental Regression and Disease Severity in Children With Autism Spectrum Disorders

INTRODUCTION

This study aimed to investigate the prevalence of developmental regression in children with Autism Spectrum Disorder (ASD) and to explore its relationship with disease severity.

METHODS

We finally included 1,027 ASD children aged 2-5 years from 13 cities in China: 138 with regressive ASD and 889 with non-regressive ASD. The Social Responsiveness Scale (SRS), Autism Behavior Checklist (ABC), Child Autism Rating Scale (CARS), and Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) were used to evaluate the core symptoms and developmental status of children in the two groups.

RESULTS

Among the 1,027 ASD children eventually included, 138 (13.44%) cases showed regressive behavior and the average regression occurring age was 24.00 (18.00-27.00) months. Among the regressive children, 105 cases (76.09%) had language regression, 79 cases (57.25%) had social regression, and 4 cases (2.90%) had motor regression. The total scores of ABC and the sub-score of sensory and stereotypic behavior (β = 5.122, 95% CI: 0.818, 9.426, P < 0.05; β = 1.104, 95% CI: 0.120, 2.089, P < 0.05; β = 1.388, 95% CI: 0.038, 2.737, P < 0.05), the SRS total scores and the sub-score of autistic mannerisms (β = 4.991, 95% CI: 0.494, 9.487, P < 0.05; β = 1.297, 95% CI: 0.140, 2.453, P < 0.05) of children in the regressive group were all higher than the non-regressive group. The total developmental quotient (DQ) of CNBS-R2016 and the DQ of gross motor, fine motor, adaptive behavior, language (β = -5.827, 95% CI: -11.529, -0.125, P < 0.05) and personal society in the regressive group were lower than the non-regressive group and the proportion of children with intelligent developmental impairment was higher the non-regressive group.

CONCLUSION

Regressive autism is mainly manifested as language and social regression. Children with regressive ASD have more severe core symptoms, lower neurodevelopmental level DQ, and more serious disease degree than children with non-regressive ASD, which requires further etiological examinations and more clinical attention.

Sleep in Children with Autism Spectrum Disorder: A Narrative Review and Systematic Update

Purpose of Review

Sleep problems are a common comorbidity for children with autism spectrum disorder (ASD), and research in this area has a relatively long history. Within this review, we first outline historic patterns in the field of sleep and ASD. Second, we conducted a systematic update and coded these studies based on their alignment with historic patterns. Research on ASD and sleep over the past two decades has primarily focused on four principal areas: (1) documenting the prevalence and types of sleep problems; (2) sleep problem treatment options and efficacy; (3) how sleep problems are associated with other behavioral, contextual, or biological elements; and (4) the impact of child sleep problems on families and care providers. The systematic update in this paper includes empirical studies published between 2018 and 2021 with terms for sleep and ASD within the title, keywords, or abstract.

Recent Findings

In sum, 60 studies fit the inclusion/exclusion criteria and most fit within the historic patterns noted above. Notable differences included more global representation in study samples, studies on the impacts of COVID-19, and a growing body of work on sleep problems as an early marker of ASD. The majority of studies focus on correlates of sleep problems noting less optimal behavioral, contextual, and biological elements are associated with sleep problems across development for children with ASD.

Summary

Recommendations for future directions include continued expansion of global and age representation across samples, a shift toward more treatment and implementation science, and studies that inform our mechanistic understanding of how sleep and ASD are connected.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40675-022-00234-5.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018

PROBLEM/CONDITION

Autism spectrum disorder (ASD).

PERIOD COVERED

2018.

DESCRIPTION OF SYSTEM

The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates ASD prevalence and monitors timing of ASD identification among children aged 4 and 8 years. This report focuses on children aged 4 years in 2018, who were born in 2014 and had a parent or guardian who lived in the surveillance area in one of 11 sites (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) at any time during 2018. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement (diagnosis) in an evaluation, 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. Suspected ASD also was tracked among children aged 4 years. Children who did not meet the case definition for ASD were classified as having suspected ASD if their records contained a qualified professional's statement indicating a suspicion of ASD.

RESULTS

For 2018, the overall ASD prevalence was 17.0 per 1,000 (one in 59) children aged 4 years. Prevalence varied from 9.1 per 1,000 in Utah to 41.6 per 1,000 in California. At every site, prevalence was higher among boys than girls, with an overall male-to-female prevalence ratio of 3.4. Prevalence of ASD among children aged 4 years was lower among non-Hispanic White (White) children (12.9 per 1,000) than among non-Hispanic Black (Black) children (16.6 per 1,000), Hispanic children (21.1 per 1,000), and Asian/Pacific Islander (A/PI) children (22.7 per 1,000). Among children aged 4 years with ASD and information on intellectual ability, 52% met the surveillance case definition of co-occurring intellectual disability (intelligence quotient ≤70 or an examiner's statement of intellectual disability documented in an evaluation). Of children aged 4 years with ASD, 72% had a first evaluation at age ≤36 months. Stratified by census-tract-level median household income (MHI) tertile, a lower percentage of children with ASD and intellectual disability was evaluated by age 36 months in the low MHI tertile (72%) than in the high MHI tertile (84%). Cumulative incidence of ASD diagnosis or eligibility received by age 48 months was 1.5 times as high among children aged 4 years (13.6 per 1,000 children born in 2014) as among those aged 8 years (8.9 per 1,000 children born in 2010). Across MHI tertiles, higher cumulative incidence of ASD diagnosis or eligibility received by age 48 months was associated with lower MHI. Suspected ASD prevalence was 2.6 per 1,000 children aged 4 years, meaning for every six children with ASD, one child had suspected ASD. The combined prevalence of ASD and suspected ASD (19.7 per 1,000 children aged 4 years) was lower than ASD prevalence among children aged 8 years (23.0 per 1,000 children aged 8 years).

INTERPRETATION

Groups with historically lower prevalence of ASD (non-White and lower MHI) had higher prevalence and cumulative incidence of ASD among children aged 4 years in 2018, suggesting progress in identification among these groups. However, a lower percentage of children with ASD and intellectual disability in the low MHI tertile were evaluated by age 36 months than in the high MHI group, indicating disparity in timely evaluation. Children aged 4 years had a higher cumulative incidence of diagnosis or eligibility by age 48 months compared with children aged 8 years, indicating improvement in early identification of ASD. The overall prevalence for children aged 4 years was less than children aged 8 years, even when prevalence of children suspected of having ASD by age 4 years is included. This finding suggests that many children identified after age 4 years do not have suspected ASD documented by age 48 months.

PUBLIC HEALTH ACTION

Children born in 2014 were more likely to be identified with ASD by age 48 months than children born in 2010, indicating increased early identification. However, ASD identification among children aged 4 years varied by site, suggesting opportunities to examine developmental screening and diagnostic practices that promote earlier identification. Children aged 4 years also were more likely to have co-occurring intellectual disability than children aged 8 years, suggesting that improvement in the early identification and evaluation of developmental concerns outside of cognitive impairments is still needed. Improving early identification of ASD could lead to earlier receipt of evidence-based interventions and potentially improve developmental outcomes.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018

PROBLEM/CONDITION

Autism spectrum disorder (ASD).

PERIOD COVERED

2018.

DESCRIPTION OF SYSTEM

The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates ASD prevalence and monitors timing of ASD identification among children aged 4 and 8 years. This report focuses on children aged 4 years in 2018, who were born in 2014 and had a parent or guardian who lived in the surveillance area in one of 11 sites (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) at any time during 2018. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement (diagnosis) in an evaluation, 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. Suspected ASD also was tracked among children aged 4 years. Children who did not meet the case definition for ASD were classified as having suspected ASD if their records contained a qualified professional's statement indicating a suspicion of ASD.

RESULTS

For 2018, the overall ASD prevalence was 17.0 per 1,000 (one in 59) children aged 4 years. Prevalence varied from 9.1 per 1,000 in Utah to 41.6 per 1,000 in California. At every site, prevalence was higher among boys than girls, with an overall male-to-female prevalence ratio of 3.4. Prevalence of ASD among children aged 4 years was lower among non-Hispanic White (White) children (12.9 per 1,000) than among non-Hispanic Black (Black) children (16.6 per 1,000), Hispanic children (21.1 per 1,000), and Asian/Pacific Islander (A/PI) children (22.7 per 1,000). Among children aged 4 years with ASD and information on intellectual ability, 52% met the surveillance case definition of co-occurring intellectual disability (intelligence quotient ≤70 or an examiner's statement of intellectual disability documented in an evaluation). Of children aged 4 years with ASD, 72% had a first evaluation at age ≤36 months. Stratified by census-tract-level median household income (MHI) tertile, a lower percentage of children with ASD and intellectual disability was evaluated by age 36 months in the low MHI tertile (72%) than in the high MHI tertile (84%). Cumulative incidence of ASD diagnosis or eligibility received by age 48 months was 1.5 times as high among children aged 4 years (13.6 per 1,000 children born in 2014) as among those aged 8 years (8.9 per 1,000 children born in 2010). Across MHI tertiles, higher cumulative incidence of ASD diagnosis or eligibility received by age 48 months was associated with lower MHI. Suspected ASD prevalence was 2.6 per 1,000 children aged 4 years, meaning for every six children with ASD, one child had suspected ASD. The combined prevalence of ASD and suspected ASD (19.7 per 1,000 children aged 4 years) was lower than ASD prevalence among children aged 8 years (23.0 per 1,000 children aged 8 years).

INTERPRETATION

Groups with historically lower prevalence of ASD (non-White and lower MHI) had higher prevalence and cumulative incidence of ASD among children aged 4 years in 2018, suggesting progress in identification among these groups. However, a lower percentage of children with ASD and intellectual disability in the low MHI tertile were evaluated by age 36 months than in the high MHI group, indicating disparity in timely evaluation. Children aged 4 years had a higher cumulative incidence of diagnosis or eligibility by age 48 months compared with children aged 8 years, indicating improvement in early identification of ASD. The overall prevalence for children aged 4 years was less than children aged 8 years, even when prevalence of children suspected of having ASD by age 4 years is included. This finding suggests that many children identified after age 4 years do not have suspected ASD documented by age 48 months.

PUBLIC HEALTH ACTION

Children born in 2014 were more likely to be identified with ASD by age 48 months than children born in 2010, indicating increased early identification. However, ASD identification among children aged 4 years varied by site, suggesting opportunities to examine developmental screening and diagnostic practices that promote earlier identification. Children aged 4 years also were more likely to have co-occurring intellectual disability than children aged 8 years, suggesting that improvement in the early identification and evaluation of developmental concerns outside of cognitive impairments is still needed. Improving early identification of ASD could lead to earlier receipt of evidence-based interventions and potentially improve developmental outcomes.

The Gut-Brain-Immune Axis in Autism Spectrum Disorders: A State-of-Art Report

The interest elicited by the large microbial population colonizing the human gut has ancient origins and has gone through a long evolution during history. However, it is only in the last decades that the introduction of high-throughput technologies has allowed to broaden this research field and to disentangle the numerous implications that gut microbiota has in health and disease. This comprehensive ecosystem, constituted mainly by bacteria but also by fungi, parasites, and viruses, is proven to be involved in several physiological and pathological processes that transcend the intestinal homeostasis and are deeply intertwined with apparently unrelated body systems, such as the immune and the nervous ones. In this regard, a novel speculation is the relationship between the intestinal microbial flora and the pathogenesis of some neurological and neurodevelopmental disorders, including the clinical entities defined under the umbrella term of autism spectrum disorders. The bidirectional interplay has led researchers to coin the term gut-brain-immune system axis, subverting the theory of the brain as an immune-privileged site and underscoring the importance of this reciprocal influence already from fetal life and especially during the pre- and post-natal neurodevelopmental process. This revolutionary theory has also unveiled the possibility to modify the gut microbiota as a way to treat and even to prevent different kinds of pathologies. In this sense, some attempts have been made, ranging from probiotic administration to fecal microbiota transplantation, with promising results that need further elaboration. This state-of-art report will describe the main aspects regarding the human gut microbiome and its specific role in the pathogenesis of autism and its related disorders, with a final discussion on the therapeutic and preventive strategies aiming at creating a healthy intestinal microbial environment, as well as their safety and ethical implications.

Prevalence and Developmental Profiles of Autism Spectrum Disorders in Children With Global Developmental Delay

BACKGROUND

Previous studies have mostly explored the comorbidities of Global developmental delay (GDD) in children with Autism Spectrum Disorders (ASD) from the perspective of ASD. The study focus on the perspective of GDD to investigate the prevalence and developmental profiles of ASD in GDD and to explore the correlation between the developmental level and symptoms of autism.

METHODS

Clinical data of 521 children with GDD aged from 24 to 60 months were retrospectively analyzed. Analyses were performed first for the whole sample and then subdivided into two subgroups (GDD⁺ASD^-, GDD⁺ASD⁺) according to whether had ASD. Symptoms of autism were evaluated by the Autism Behavior Checklist and the Childhood Autism Rating Scale. The Chinese version of the Gesell Developmental Schedules was used to evaluate the level of children's mental development.

RESULT

The prevalence of ASD in children with GDD was 62.3%. The total average developmental quotient (DQ) of GDD was mildly deficient and was negatively correlated with symptoms of autism (p < 0.05); language ability was severe and extremely severe deficient (P < 0.05). GDD⁺ASD^- group and GDD⁺ASD⁺ group have some common points as well as differences in the developmental features. The language delay of children in both subgroups was the most obviously defected, thereafter followed by the item of personal social activity. In the GDD⁺ASD⁺ group, the DQ of gross motor skills>fine motor skills>adaptability (p < 0.05). There were no significant differences among the DQ of gross motor skills, fine motor skills and adaptability in GDD⁺ASD^- group (p > 0.05). The GDD⁺ASD^-group had better adaptability, fine motor skills, language ability, personal social activity than that of the GDD⁺ASD⁺ group, but the gross motor skills in GDD⁺ASD^- group were worse (p < 0.05).

CONCLUSION

GDD children have a high proportion of comorbid ASD, and GDD children with poorer developmental levels are more likely to have ASD symptoms. Development profiles in both GDD⁺ASD^- children and GDD⁺ASD⁺ children have common features but there are also differences. GDD⁺ASD⁺ group is worse than GDD⁺ASD^- group in terms of the overall development level.