Lisa D. Wiggins

Timing of Identification Among Children With an Autism Spectrum Disorder: Findings From a Population-Based Surveillance Study

OBJECTIVE At what age are children with an autism spectrum disorder (ASD) identified by community providers? What factors influence the timing of when children are identified with ASDs? This study examined the timing of when children with ASDs are identified. METHOD Data came from 13 sites participating in the Centers for Disease Control and Preventions 2002 multisite ongoing autism surveillance program, the Autism and Developmental Disabilities Monitoring Network. Survival analysis was used to examine factors that influence the timing of community-based identification and diagnosis. RESULT Data from health and education records reveal that the median age of identification was 5.7 years (SE 0.08 years). Parametric survival models revealed that several factors were associated with a younger age of identification: being male, having an IQ of 70 or lower, and having experienced developmental regression. Significant differences in the age of identification among the 13 sites were also discovered. CONCLUSIONS The large gap between the age at which children can be identified and when they actually are identified suggests a critical need for further research, innovation, and improvement in this area of clinical practice.

Examination of the time between first evaluation and first autism spectrum diagnosis in a population-based sample.

ABSTRACT. Early identification of young children with an autism spectrum disorder (ASD) can lead to earlier entry into intervention programs that support improved developmental outcomes. The purpose of the present study was to examine identification and diagnostic patterns of children with ASD who live in a large metropolitan area. One hundred fifteen 8-year-old children diagnosed with ASD were identified from a population-based surveillance system at the Centers for Disease Control and Prevention. Primary variables of interest included earliest age of evaluation and earliest age of diagnosis identified from surveillance records, type of initial ASD diagnosis, evaluation sources that documented first ASD diagnosis, characteristics of professionals assigning first ASD diagnosis, and diagnostic tools used to aid the diagnostic process. We found that children with ASD identified by the surveillance system were initially evaluated at a mean of 48 months but were not diagnosed with ASD until a mean age of 61 months. There were no differences in timing of diagnosis based on sex or racial/ethnic classification, although degree of impairment associated with ASD predicted mean age at first evaluation and mean age at first ASD diagnosis. Most children were identified at nonschool sources, such as hospitals and clinics; 24% of the sample did not receive a documented ASD diagnosis until entering school. Most practitioners (70%) did not use a diagnostic instrument when assigning the first ASD diagnosis. Implications for early identification of ASD are discussed.

Sex differences in the evaluation and diagnosis of autism spectrum disorders among children

BACKGROUND One of the most consistent features of the autism spectrum disorders (ASDs) is the predominance among males, with approximately four males to every female. We sought to examine sex differences among children who met case definition for ASD in a large, population-based cohort with respect to age at first developmental evaluation, age of diagnosis, influence of cognitive impairment on these outcomes, and sex-specific behavioral characteristics. METHODS We conducted a secondary analysis of data collected for a population-based study of the prevalence of ASD. The sample comprised 2,568 children born in 1994 who met the case definition of ASD as established by the Autism and Developmental Disabilities Monitoring (ADDM) Network for ASD surveillance. Children who had a history of developmental disability and behavioral features consistent with the DSM-IV-TR criteria for autistic disorder, Aspergers disorder, and Pervasive Developmental Disorder-Not Otherwise Specified in existing evaluation records were classified as ASD cases via two paths: streamlined and nonstreamlined. Streamlined reviews were conducted if there was an ASD diagnosis documented in the records. Data were collected in 13 sites across the United States through the ADDM Network, funded by the Centers for Disease Control and Prevention. RESULTS Males constituted 81% of the sample. There were no differences by sex in average age at first evaluation or average age of diagnosis among those with an existing documented chart diagnosis of an ASD. Girls were less likely than boys to have a documented diagnosis (odds ratio [OR] = 0.76, p = .004). This analysis was adjusted for cognitive impairment status. In the logistic model, with the interaction term for sex and cognitive impairment, girls with IQ of 70 or less were less likely than boys with IQ of 70 or less to have a documented diagnosis (OR = 0.70, 95% confidence interval [CI] = 0.50-0.97, p = .035). Boys with IQ greater than 70 were less likely than boys with IQ of 70 or less to have a documented diagnosis (OR = 0.60, 95% CI = 0.49-0.74, p < .001). This finding (less likely to have a documented diagnosis) was also true for girls with IQ greater than 70 (OR = 0.45, 95% CI = 0.32-0.66, p < .001). Girls were more likely to have notations of seizure-like behavior (p < .001). Boys were more likely to have notations of hyperactivity or a short attention span and aggressive behavior (p < .01). CONCLUSIONS Girls, especially those without cognitive impairment, may be formally identified at a later age than boys. This may delay referral for early intervention. Community education efforts should alert clinicians and parents to the potential of ASDs in boys and girls.

Trends in the Prevalence of Autism Spectrum Disorder, Cerebral Palsy, Hearing Loss, Intellectual Disability, and Vision Impairment, Metropolitan Atlanta, 1991–2010

This study examined the prevalence and characteristics of autism spectrum disorder (ASD), cerebral palsy (CP), hearing loss (HL), intellectual disability (ID), and vision impairment (VI) over a 15–20 year time period, with specific focus on concurrent changes in ASD and ID prevalence. We used data from a population-based developmental disabilities surveillance program for 8-year-olds in metropolitan Atlanta. From 1991–2010, prevalence estimates of ID and HL were stable with slight increases in VI prevalence. CP prevalence was constant from 1993–2010. The average annual increase in ASD prevalence was 9.3% per year from 1996–2010, with a 269% increase from 4.2 per 1,000 in 1996 to 15.5 per 1,000 in 2010. From 2000–2010, the prevalence of ID without ASD was stable; during the same time, the prevalence of ASD with and without co-occurring ID increased by an average of 6.6% and 9.6% per year, respectively. ASD prevalence increases were found among both males and females, and among nearly all racial/ethnic subgroups and levels of intellectual ability. Average annual prevalence estimates from 1991–2010 underscore the significant community resources needed to provide early intervention and ongoing supports for children with ID (13.0 per 1,000), CP, (3.5 per 1,000), HL (1.4 per 1,000) and VI (1.3 in 1,000), with a growing urgency for children with ASD.

Developmental regression in children with an autism spectrum disorder identified by a population-based surveillance system

This study evaluated the phenomenon of autistic regression using population-based data. The sample comprised 285 children who met the autism spectrum disorder (ASD) case definition within an ongoing surveillance program. Results indicated that children with a previously documented ASD diagnosis had higher rates of autistic regression than children who met the ASD surveillance definition but did not have a clearly documented ASD diagnosis in their records (17—26 percent of surveillance cases). Most children regressed around 24 months of age and boys were more likely to have documented regression than girls. Half of the children with regression had developmental concerns noted prior to the loss of skills. Moreover, children with autistic regression were more likely to show certain associated features, including cognitive impairment.These data indicate that some children with ASD experience a loss of skills in the first few years of life and may have a unique symptom profile.

Racial disparities in community identification of autism spectrum disorders over time; Metropolitan Atlanta, Georgia, 2000-2006.

Objective: Past research indicates that non-Hispanic black (NHB) children are less likely than non-Hispanic white (NHW) children to have an autism spectrum disorder (ASD) diagnosis, even if they seem to meet criteria for the disorder. This study examined differences in community identification of ASDs between NHB and NHW children identified by a population-based surveillance system. Methods: Participants were identified as an ASD surveillance case by the Metropolitan Atlanta Developmental Disabilities Surveillance Program in surveillance years 2000, 2002, 2004, and 2006. Health and education records were abstracted and reviewed to determine ASD surveillance case status; community identification was defined by a documented ASD diagnosis, special education eligibility, and behaviors noted in records. Children were placed in 1 of 5 mutually exclusive categories on the basis of ASD specificity. Results: Total ASD prevalence was higher for NHW than NHB children, but NHB children were more likely than NHW children to have autistic disorder and autism eligibility at a public school documented in records. NHB children were less likely than NHW children to have pervasive developmental disorder-not otherwise specified and Aspergers disorder documented in records, even after controlling for socioeconomic status. NHB children were more likely than NHW children to have co-occurring intellectual disability. Conclusion: NHB children were less likely than NHW children to have been identified with less severe ASDs, which might have prevented or delayed intervention services that would have catered to their needs. This study illustrates the need for continued professional education, particularly concerning milder ASDs in minority groups.

Using Standardized Diagnostic Instruments to Classify Children with Autism in the Study to Explore Early Development

The Study to Explore Early Development (SEED) is a multi-site case–control study designed to explore the relationship between autism spectrum disorder (ASD) phenotypes and etiologies. The goals of this paper are to (1) describe the SEED algorithm that uses the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) to classify children with ASD, (2) examine psychometric properties of different ASD classification methods, including the SEED method that incorporates rules for resolving ADI-R and ADOS discordance, and (3) determine whether restricted interests and repetitive behaviors were noted for children who had instrument discordance resolved using ADI-R social and communication scores. Results support the utility of SEED criteria when well-defined groups of children are an important clinical or research outcome.

Retention of autism spectrum diagnoses by community professionals: findings from the autism and developmental disabilities monitoring network, 2000 and 2006.

Objective: Past research is inconsistent in the stability of autism spectrum disorder (ASD) diagnoses. The authors therefore sought to examine the proportion of children identified from a population-based surveillance system that had a change in classification from ASD to non-ASD and factors associated with such changes. Methods: Children with a documented age of first ASD diagnosis noted in surveillance records by a community professional (n = 1392) were identified from the Autism and Developmental Disabilities Monitoring Network. Children were considered to have a change in classification if an ASD was excluded after the age of first recorded ASD diagnosis. Child and surveillance factors were entered into a multivariable regression model to determine factors associated with diagnostic change. Results: Only 4% of our sample had a change in classification from ASD to non-ASD noted in evaluation records. Factors associated with change in classification from ASD to non-ASD were timing of first ASD diagnosis at 30 months or younger, onset other than developmental regression, presence of specific developmental delays, and participation in a special needs classroom other than autism at 8 years of age. Conclusions: Our results found that children with ASDs are likely to retain an ASD diagnosis, which underscores the need for continued services. Children diagnosed at 30 months or younger are more likely to experience a change in classification from ASD to non-ASD than children diagnosed at 31 months or older, suggesting earlier identification of ASD symptoms may be associated with response to intervention efforts or increased likelihood for overdiagnosis.

Comparison of a broad-based screen versus disorder-specific screen in detecting young children with an autism spectrum disorder:

The goals of our study were to (a) compare agreement between autism spectrum disorder diagnosis and outcome of the Modified Checklist for Autism in Toddlers and Parents Evaluation of Developmental Status in a sample of toddlers and (b) examine specific concerns noted for toddlers who screened negative on the Modified Checklist for Autism in Toddlers or Parents Evaluation of Developmental Status but were later diagnosed with autism spectrum disorder. Participants were administered the Modified Checklist for Autism in Toddlers and Parents Evaluation of Developmental Status during well-child visits. Families were invited for a clinical evaluation if autism spectrum disorder symptoms were noted on the Modified Checklist for Autism in Toddlers and Modified Checklist for Autism in Toddlers Follow-Up Interview or if autism spectrum disorder concerns were noted by the pediatrician. Fifty-two children completed the Modified Checklist for Autism in Toddlers, Parents Evaluation of Developmental Status, and a clinical evaluation, and 30 of these children were diagnosed with an autism spectrum disorder. Modified Checklist for Autism in Toddlers results showed higher agreement with autism spectrum disorder diagnosis than any individual Parents Evaluation of Developmental Status screen result, although the latter detected many children with other developmental concerns. Children who screened negative on the Modified Checklist for Autism in Toddlers or Parents Evaluation of Developmental Status but were diagnosed with autism spectrum disorder had concerns noted in sensory response and proto-declarative pointing that can be considered in the context of screen results. In sum, our findings support universal autism spectrum disorder–specific screening in addition to general developmental screening and offer considerations to encourage early identification of toddlers with autism spectrum disorder.

Factors Associated with Self-Injurious Behaviors in Children with Autism Spectrum Disorder: Findings from Two Large National Samples

In this study, we explored potential associations among self-injurious behaviors (SIB) and a diverse group of protective and risk factors in children with autism spectrum disorder from two databases: Autism and Developmental Disabilities Monitoring (ADDM) Network and the Autism Speaks-Autism Treatment Network (AS-ATN). The presence of SIB was determined from children’s records in ADDM and a parent questionnaire in AS-ATN. We used multiple imputation to account for missing data and a non-linear mixed model with site as a random effect to test for associations. Despite differences between the two databases, similar associations were found; SIB were associated with developmental, behavioral, and somatic factors. Implications of these findings are discussed in relation to possible etiology, future longitudinal studies, and clinical practice.