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Background: Previous studies of the frequency of cerebral palsy in the United States have found excess prevalence in black children relative to other groups. Whether the severity of cerebral palsy differs between black and white children has not previously been investigated.Methods: A population-based surveillance system in 4 regions of the United States identified 476 children with cerebral palsy among 142,338 8-year-old children in 2006. Motor function was rated by the Gross Motor Function Classification System and grouped into 3 categories of severity. We used multiple imputation to account for missing information on motor function and calculated the race-specific prevalence of each cerebral palsy severity level.Results: The prevalence of cerebral palsy was 3.7 per 1000 black children and 3.2 per 1000 white children (prevalence odds ratio [OR] = 1.2 [95% confidence interval = 1.0-1.4]). When stratified by severity of functional limitation, the racial disparity was present only for severe cerebral palsy (black vs. white prevalence OR=1.7 [1.1-2.4]). The excess prevalence of severe cerebral palsy in black children was evident in term and very preterm birth strata.Conclusion: Black children in the United States appear to have a higher prevalence of cerebral palsy overall than white children, although the excess prevalence of cerebral palsy in black children is seen only among those with the most severe limitations. Further research is needed to explore reasons for this disparity in functional limitations; potential mechanisms include racial differences in risk factors, access to interventions, and under-identification of mild cerebral palsy in black children. [ABSTRACT FROM AUTHOR]

Background: A 57% increase in the U.S. prevalence of autism spectrum disorders (ASD) for 8-year-old children born in 1994 versus 1998 was recently reported.Methods: To quantify the possible contributions of given risk/predictive factors on the recent ASD prevalence increase, we formulated a mathematical model based on the baseline risk factor prevalence (RFP), the proportionate change in RFP (cRFP), and the magnitude of the association between the risk factor and ASD [estimated relative risk (RR)]. We applied this model to several pregnancy-related factors (preterm, very preterm, low and very low birth weight, multiple birth, cesarean delivery, breech presentation, and assisted reproductive technology use). RFP and cRFP estimates for each factor were obtained from U.S. population-based surveillance datasets. Estimated RRs were obtained from a series of systematic literature reviews.Results: We estimate that each risk factor examined, alone or in various combinations, accounted for a very small proportion (<1%) of the ASD increase. Additionally, hypothetical scenarios indicate RFP, cRFP, and RR all need to be sizable for a risk factor to appreciably influence ASD prevalence.Conclusions: Thus, although various pregnancy factors have been found to be associated with ASDs, the contribution of many of these factors to the recently observed ASD increase is likely minimal. [ABSTRACT FROM AUTHOR]

Background: No data exist at the population level on what tests are used to aid in the diagnosis of autism spectrum disorder in community practice., Objectives: To describe autism spectrum disorder testing practices to inform autism spectrum disorder identification efforts., Methods: Data are from the Autism and Developmental Disabilities Monitoring Network, a multi-site surveillance system reporting prevalence estimates and characteristics of 8-year-old children with autism spectrum disorder. Percentages of children with autism spectrum disorder who received any autism spectrum disorder test or a 'gold standard' test were calculated by site, sex, race, median household income, and intellectual ability status. Risk ratios were calculated to compare group differences., Results: Of 5058 8-year-old children with autism spectrum disorder across 11 sites, 3236 (64.0%) had a record of any autism spectrum disorder test and 2136 (42.2%) had a 'gold standard' ADOS or ADI-R test. Overall, 115 children (2.3%) had both the ADOS and ADI-R in their records. Differences persisted across race, median household income, and intellectual ability status. Asian/Pacific Islander children had the highest percent receiving any ASD test (71.8%; other groups range: 57.4-66.0%) and White children had the highest percent receiving 'gold standard' tests (46.4%; other groups range: 35.6-43.2%). Children in low-income neighbourhoods had a lower percent of any test (62.5%) and 'gold standard' tests (39.4%) compared to medium (70.2% and 47.5%, respectively) and high (69.6% and 46.8%, respectively) income neighbourhoods. Children with intellectual disability had a lower percent of any ASD test (81.7%) and 'gold standard' tests (52.6%) compared to children without intellectual disability (84.0% and 57.6%, respectively)., Conclusions: Autism spectrum disorder testing practices vary widely by site and differ by race and presence of co-occurring intellectual disability, suggesting opportunities to standardise and/or improve autism spectrum disorder identification practices., (© 2024 John Wiley & Sons Ltd.)

Objective: Our objectives with this study were to describe the frequency of selected cooccurring health conditions and individualized education program (IEP) services and post-high school transition planning for adolescents with autism spectrum disorder and identify disparities by sex, intellectual ability, race or ethnicity, and geographic area., Methods: The study sample included 1787 adolescents born in 2004 who were identified as having autism through a health and education record review through age 16 years in 2020. These adolescents were part of a longitudinal population-based surveillance birth cohort from the Autism and Developmental Disabilities Monitoring Network from 2004 to 2020 in 5 US catchment areas., Results: Attention deficit hyperactivity disorder (47%) and anxiety (39%) were the most common cooccurring health conditions. Anxiety was less commonly identified for those with intellectual disability than those without. It was also less commonly identified among Black adolescents compared with White or Hispanic adolescents. There was wide variation across Autism and Developmental Disabilities Monitoring Network sites in the provision of school-based IEP services. Students with intellectual disability were less likely to receive school-based mental health services and more likely to have a goal for postsecondary independent living skills compared with those without intellectual disability. A total of 37% of students did not participate in standardized testing., Conclusions: We identified disparities in the identification of cooccurring conditions and school-based IEP services, practices, and transition planning. Working with pediatric health and education providers, families, and adolescents with autism will be important to identify contributing factors and to focus efforts to reduce disparities in the supports and services adolescents with autism have access to and receive., (Copyright © 2024 by the American Academy of Pediatrics.)

Objectives: Autism spectrum disorder (autism) is a heterogeneous condition that poses challenges in describing the needs of individuals with autism and making prognoses about future outcomes. We applied a newly proposed definition of profound autism to surveillance data to estimate the percentage of children with autism who have profound autism and describe their sociodemographic and clinical characteristics., Methods: We analyzed population-based surveillance data from the Autism and Developmental Disabilities Monitoring Network for 20 135 children aged 8 years with autism during 2000-2016. Children were classified as having profound autism if they were nonverbal, were minimally verbal, or had an intelligence quotient <50., Results: The percentage of 8-year-old children with profound autism among those with autism was 26.7%. Compared with children with non-profound autism, children with profound autism were more likely to be female, from racial and ethnic minority groups, of low socioeconomic status, born preterm or with low birth weight; have self-injurious behaviors; have seizure disorders; and have lower adaptive scores. In 2016, the prevalence of profound autism was 4.6 per 1000 8-year-olds. The prevalence ratio (PR) of profound autism was higher among non-Hispanic Asian/Native Hawaiian/Other Pacific Islander (PR = 1.55; 95 CI, 1.38-1.73), non-Hispanic Black (PR = 1.76; 95% CI, 1.67-1.86), and Hispanic (PR = 1.50; 95% CI, 0.88-1.26) children than among non-Hispanic White children., Conclusions: As the population of children with autism continues to change, describing and quantifying the population with profound autism is important for planning. Policies and programs could consider the needs of people with profound autism across the life span to ensure their needs are met., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Purpose: The objectives of this study were to describe child characteristics associated with later autism spectrum disorder (ASD) identification and the health status and educational transition plans of adolescents with ASD., Methods: Longitudinal population-based surveillance cohort from the Autism Developmental Disabilities Monitoring Network during 2002-2018 in five catchment areas in the United States. Participants included 3,148 children born in 2002 whose records were first reviewed for ASD surveillance in 2010., Results: Of the 1,846 children identified in the community as an ASD case, 11.6% were first identified after age 8 years. Children who were more likely to have ASD identified at older ages were Hispanic; were born with low birth weight; were verbal; had high intelligence quotient or adaptive scores; or had certain co-occurring neuropsychological conditions by age 8 years. By age 16 years, neuropsychological conditions were common with more than half of the adolescents with ASD having a diagnosis of attention-deficit/hyperactivity disorder or anxiety. Intellectual disability (ID) status was unchanged for the majority (>80%) of children from ages 8-16 years. A transition plan was completed for over 94% of adolescents, but disparities were observed in planning by ID status., Discussion: A high percentage of adolescents with ASD have co-occurring neuropsychological conditions, markedly higher than at age 8. While most adolescents had transition planning, this occurred less often for those with ID. Ensuring access to services for all people with ASD during adolescence and transition to adulthood may help to promote overall health and quality of life., (Published by Elsevier Inc.)

Objectives: The study objectives were to examine the contents of individualized education programs (IEPs) of adolescents with autism spectrum disorder (ASD), including postsecondary transition goals, services, and changes in special education classification over time., Methods: This study involved a longitudinal population-based surveillance cohort from the Autism Developmental Disabilities Monitoring Network from 2002 to 2018 in 3 catchment areas in the United States. The sample included 322 adolescents who were born in 2002, identified with ASD, and had an IEP available for review at ages 15-16 years., Results: We found that 297 (92%) adolescents with ASD had an IEP including a transition plan. Those without intellectual disability (ID) were more likely to have postsecondary education and employment goals and have those goals be to pursue higher education or competitive employment compared with those with ID. Forty-one percent of adolescents with ASD had a postsecondary living arrangement goal. Although 28% of adolescents with ASD received school-based mental health services, none of these adolescents were Black; additionally, 15% of those with ID received mental health services compared with 34% without ID. The percentage of adolescents with ASD served under an autism classification increased from 44% at age 8 years to 62% by age 16., Conclusions: We identified gaps and disparities in school-based postsecondary transition planning. Working with education partners, families, and adolescents will be important to identify what challenges contribute to these findings and what supports are needed to improve the equity and quality of the transition planning process for adolescents with ASD so they are prepared for adulthood., (Copyright © 2023 by the American Academy of Pediatrics.)

Purpose: The Metropolitan Atlanta Developmental Disabilities Surveillance Program tracks autism spectrum disorder (ASD) in selected counties within Georgia as part of the Autism and Developmental Disabilities Monitoring (ADDM) Network. ADDM Network analyses have historically found a higher prevalence of ASD in areas of higher socioeconomic status., Methods: We linked 2018 data from Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to two Metropolitan Atlanta Developmental Disabilities Surveillance Program counties by census tract, grouped census tracts into tertiles representing low, medium, and high social vulnerability, and calculated ASD prevalence for each tertile, overall and by each of four SVI themes., Results: We found that overall prevalence was higher in areas of low compared to high vulnerability for the socioeconomic status and transportation themes, and in areas of medium compared to high vulnerability for all themes. This pattern was consistent among males but varied for females and by race or ethnicity., Conclusions: Linking ASD prevalence to SVI metrics can improve the understanding of inequities among children with ASD in racial and ethnic minority groups or those living in low-resource settings. These methods can be applied to other ADDM Network surveillance sites and public health surveillance programs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2020., Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years. In 2020, there were 11 ADDM Network sites across the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. A child met the case definition if their record documented 1) an ASD diagnostic statement in an evaluation, 2) a classification of ASD in special education, or 3) an ASD International Classification of Diseases (ICD) code., Results: For 2020, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 23.1 in Maryland to 44.9 in California. The overall ASD prevalence was 27.6 per 1,000 (one in 36) children aged 8 years and was 3.8 times as prevalent among boys as among girls (43.0 versus 11.4). Overall, ASD prevalence was lower among non-Hispanic White children (24.3) and children of two or more races (22.9) than among non-Hispanic Black or African American (Black), Hispanic, and non-Hispanic Asian or Pacific Islander (A/PI) children (29.3, 31.6, and 33.4 respectively). ASD prevalence among non-Hispanic American Indian or Alaska Native (AI/AN) children (26.5) was similar to that of other racial and ethnic groups. ASD prevalence was associated with lower household income at three sites, with no association at the other sites.Across sites, the ASD prevalence per 1,000 children aged 8 years based exclusively on documented ASD diagnostic statements was 20.6 (range = 17.1 in Wisconsin to 35.4 in California). Of the 6,245 children who met the ASD case definition, 74.7% had a documented diagnostic statement of ASD, 65.2% had a documented ASD special education classification, 71.6% had a documented ASD ICD code, and 37.4% had all three types of ASD indicators. The median age of earliest known ASD diagnosis was 49 months and ranged from 36 months in California to 59 months in Minnesota.Among the 4,165 (66.7%) children with ASD with information on cognitive ability, 37.9% were classified as having an intellectual disability. Intellectual disability was present among 50.8% of Black, 41.5% of A/PI, 37.8% of two or more races, 34.9% of Hispanic, 34.8% of AI/AN, and 31.8% of White children with ASD. Overall, children with intellectual disability had earlier median ages of ASD diagnosis (43 months) than those without intellectual disability (53 months)., Interpretation: For 2020, one in 36 children aged 8 years (approximately 4% of boys and 1% of girls) was estimated to have ASD. These estimates are higher than previous ADDM Network estimates during 2000-2018. For the first time among children aged 8 years, the prevalence of ASD was lower among White children than among other racial and ethnic groups, reversing the direction of racial and ethnic differences in ASD prevalence observed in the past. Black children with ASD were still more likely than White children with ASD to have a co-occurring intellectual disability., Public Health Action: The continued increase among children identified with ASD, particularly among non-White children and girls, highlights the need for enhanced infrastructure to provide equitable diagnostic, treatment, and support services for all children with ASD. Similar to previous reporting periods, findings varied considerably across network sites, indicating the need for additional research to understand the nature of such differences and potentially apply successful identification strategies across states., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2020., Description of System: The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates prevalence and characteristics of ASD and monitors timing of ASD identification among children aged 4 and 8 years. In 2020, a total of 11 sites (located in Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) conducted surveillance of ASD among children aged 4 and 8 years and suspected ASD among children aged 4 years. Surveillance included children who lived in the surveillance area at any time during 2020. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement in an evaluation, 2) a special education classification of autism (eligibility), or 3) an ASD International Classification of Diseases (ICD) code (revisions 9 or 10). Children aged 4 years were classified as having suspected ASD if they did not meet the case definition for ASD but had a documented qualified professional's statement indicating a suspicion of ASD. This report focuses on children aged 4 years in 2020 compared with children aged 8 years in 2020., Results: For 2020, ASD prevalence among children aged 4 years varied across sites, from 12.7 per 1,000 children in Utah to 46.4 in California. The overall prevalence was 21.5 and was higher among boys than girls at every site. Compared with non-Hispanic White children, ASD prevalence was 1.8 times as high among Hispanic, 1.6 times as high among non-Hispanic Black, 1.4 times as high among Asian or Pacific Islander, and 1.2 times as high among multiracial children. Among the 58.3% of children aged 4 years with ASD and information on intellectual ability, 48.5% had an IQ score of ≤70 on their most recent IQ test or an examiner's statement of intellectual disability. Among children with a documented developmental evaluation, 78.0% were evaluated by age 36 months. Children aged 4 years had a higher cumulative incidence of ASD diagnosis or eligibility by age 48 months compared with children aged 8 years at all sites; risk ratios ranged from 1.3 in New Jersey and Utah to 2.0 in Tennessee. In the 6 months before the March 2020 COVID-19 pandemic declaration by the World Health Organization, there were 1,593 more evaluations and 1.89 more ASD identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. After the COVID-19 pandemic declaration, this pattern reversed: in the 6 months after pandemic onset, there were 217 fewer evaluations and 0.26 fewer identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. Patterns of evaluation and identification varied among sites, but there was not recovery to pre-COVID-19 pandemic levels by the end of 2020 at most sites or overall. For 2020, prevalence of suspected ASD ranged from 0.5 (California) to 10.4 (Arkansas) per 1,000 children aged 4 years, with an increase from 2018 at five sites (Arizona, Arkansas, Maryland, New Jersey, and Utah). Demographic and cognitive characteristics of children aged 4 years with suspected ASD were similar to children aged 4 years with ASD., Interpretation: A wide range of prevalence of ASD by age 4 years was observed, suggesting differences in early ASD identification practices among communities. At all sites, cumulative incidence of ASD by age 48 months among children aged 4 years was higher compared with children aged 8 years in 2020, indicating improvements in early identification of ASD. Higher numbers of evaluations and rates of identification were evident among children aged 4 years until the COVID-19 pandemic onset in 2020. Sustained lower levels of ASD evaluations and identification seen at a majority of sites after the pandemic onset could indicate disruptions in typical practices in evaluations and identification for health service providers and schools through the end of 2020. Sites with more recovery could indicate successful strategies to mitigate service interruption, such as pivoting to telehealth approaches for evaluation., Public Health Action: From 2016 through February of 2020, ASD evaluation and identification among the cohort of children aged 4 years was outpacing ASD evaluation and identification 4 years earlier (from 2012 until March 2016) among the cohort of children aged 8 years in 2020 . From 2016 to March 2020, ASD evaluation and identification among the cohort of children aged 4 years was outpacing that among children aged 8 years in 2020 from 2012 until March 2016. The disruptions in evaluation that coincided with the start of the COVID-19 pandemic and the increase in prevalence of suspected ASD in 2020 could have led to delays in ASD identification and interventions. Communities could evaluate the impact of these disruptions as children in affected cohorts age and consider strategies to mitigate service disruptions caused by future public health emergencies., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest.

Purpose: Autism spectrum disorder (ASD) prevalence information is necessary for identifying community needs such as addressing disparities in identification and services., Methods: Seven Autism and Developmental Disabilities Monitoring (ADDM) Network sites participated in a pilot project to link statewide health and education data to generate statewide and county-level prevalence estimates for a broader age range for their states for the first time., Results: Statewide prevalence of ASD for ages 3-21 years in 2018 ranged from 1.5% in Tennessee and Wisconsin to 2.3% in Arizona. The median county-level prevalence of ASD was 1.4% of residents ages 3-21 years. More boys than girls had ASD at all sites, and prevalence was lower among non-Hispanic Black, Hispanic, Asian/Pacific Islander, and American Indian/Alaska Native residents compared to non-Hispanic White residents at most sites. ASD prevalence estimates for children aged 8 years were similar to 2018 ADDM Network estimates that used record review to provide more in-depth information, but showed greater variation for children aged 4 years., Conclusions: Linkage of statewide data sets provides less detailed but actionable local information when more resource-intensive methods are not possible., (Published by Elsevier Inc.)

Objective: Early identification can improve outcomes for children with autism spectrum disorder (ASD). We sought to assess changes in early ASD identification over time and by co-occurring intellectual disability (ID) and race/ethnicity., Method: Using data for 2002-2016 from a biennial population-based ASD surveillance program among 8-year-old children in the United States, we defined identification as a child's earliest recorded ASD diagnosis or special education eligibility. Unidentified children had characteristics meeting the ASD surveillance case definition but no recorded identification by age 8 years. We calculated median age at identification among identified children, median age at identification including unidentified children, and cumulative incidence of identification by age 48 months., Results: ASD identification by age 48 months was 4 times (95% CI: 3.6-4.3) as likely in 2016 as in 2002, with the largest increases among children without ID. Median age at ASD identification among identified children decreased 3 months during this time. Children of every race/ethnicity were more likely to be identified over time. There were racial disparities stratified by ID: in 2016, Black and Hispanic children without ID were less likely to be identified with ASD than were White children (both groups risk ratio: 0.7; 95% CI: 0.5-0.8), but Black children were 1.5 times (95% CI: 1.3-1.9) as likely as White children to be identified with ASD and ID., Conclusion: Substantial progress has been made to identify more children with ASD early, despite minimal decrease in median age at diagnosis. Considerable disparities remain in early ASD identification by race/ethnicity and co-occurring intellectual disability., (Published by Elsevier Inc.)

Developmental delays, disorders, or disabilities (DDs) manifest in infancy and childhood and can limit a person's function throughout life* (1-3). To guide strategies to optimize health for U.S. children with DDs, CDC analyzed data from 44,299 participants in the 2014-2018 National Health Interview Survey (NHIS). Parents reported on 10 DDs, † functional abilities, health needs, and use of services. Among the approximately one in six (17.3%) U.S. children and adolescents aged 3-17 years (hereafter children) with one or more DDs, 5.7% had limited ability to move or play, 4.7% needed help with personal care, 4.6% needed special equipment, and 2.4% received home health care, compared with ≤1% for each of these measures among children without DDs. Children with DDs were two to seven times as likely as those without DDs to have taken prescription medication for ≥3 months (41.6% versus 8.4%), seen a mental health professional (30.6% versus 4.5%), a medical specialist (26.0% versus 12.4%), or a special therapist, such as a physical, occupational, or speech therapist, (25.0% versus 4.5%) during the past year, and 18 times as likely to have received special education or early intervention services (EIS) (41.9% versus 2.4%). These percentages varied by type of disability and by sociodemographic subgroup. DDs are common, and children with DDs often need substantial health care and services. Policies and programs that promote early identification of children with developmental delays and facilitate increased access to intervention services can improve health and reduce the need for services later in life. § Sociodemographic inequities merit further investigation to guide public health action and ensure early and equitable access to needed care and services., Competing Interests: Catherine E. Rice reports compensation for professional training workshops on the diagnostic assessment of autism; uncompensated educational and clinical work related to licensure as a psychologist in Georgia; and uncompensated service on advisory boards for the Atlanta Autism Consortium, New Jersey State Scientific Advisory Panel for Autism, and HANDS in Autism Program during the last 36 months. No other potential conflicts of interest were disclosed.

Mental health encompasses a range of mental, emotional, social, and behavioral functioning and occurs along a continuum from good to poor. Previous research has documented that mental health among children and adolescents is associated with immediate and long-term physical health and chronic disease, health risk behaviors, social relationships, education, and employment. Public health surveillance of children's mental health can be used to monitor trends in prevalence across populations, increase knowledge about demographic and geographic differences, and support decision-making about prevention and intervention. Numerous federal data systems collect data on various indicators of children's mental health, particularly mental disorders. The 2013-2019 data from these data systems show that mental disorders begin in early childhood and affect children with a range of sociodemographic characteristics. During this period, the most prevalent disorders diagnosed among U.S. children and adolescents aged 3-17 years were attention-deficit/hyperactivity disorder and anxiety, each affecting approximately one in 11 (9.4%-9.8%) children. Among children and adolescents aged 12-17 years, one fifth (20.9%) had ever experienced a major depressive episode. Among high school students in 2019, 36.7% reported persistently feeling sad or hopeless in the past year, and 18.8% had seriously considered attempting suicide. Approximately seven in 100,000 persons aged 10-19 years died by suicide in 2018 and 2019. Among children and adolescents aged 3-17 years, 9.6%-10.1% had received mental health services, and 7.8% of all children and adolescents aged 3-17 years had taken medication for mental health problems during the past year, based on parent report. Approximately one in four children and adolescents aged 12-17 years reported having received mental health services during the past year. In federal data systems, data on positive indicators of mental health (e.g., resilience) are limited. Although no comprehensive surveillance system for children's mental health exists and no single indicator can be used to define the mental health of children or to identify the overall number of children with mental disorders, these data confirm that mental disorders among children continue to be a substantial public health concern. These findings can be used by public health professionals, health care providers, state health officials, policymakers, and educators to understand the prevalence of specific mental disorders and other indicators of mental health and the challenges related to mental health surveillance., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

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., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2018., Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD. This report focuses on the prevalence and characteristics of ASD among children aged 8 years in 2018 whose parents or guardians lived in 11 ADDM Network sites in the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. In 2018, children met the case definition if their records documented 1) an ASD diagnostic statement in an evaluation (diagnosis), 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code., Results: For 2018, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 16.5 in Missouri to 38.9 in California. The overall ASD prevalence was 23.0 per 1,000 (one in 44) children aged 8 years, and ASD was 4.2 times as prevalent among boys as among girls. Overall ASD prevalence was similar across racial and ethnic groups, except American Indian/Alaska Native children had higher ASD prevalence than non-Hispanic White (White) children (29.0 versus 21.2 per 1,000 children aged 8 years). At multiple sites, Hispanic children had lower ASD prevalence than White children (Arizona, Arkansas, Georgia, and Utah), and non-Hispanic Black (Black) children (Georgia and Minnesota). The associations between ASD prevalence and neighborhood-level median household income varied by site. Among the 5,058 children who met the ASD case definition, 75.8% had a diagnostic statement of ASD in an evaluation, 18.8% had an ASD special education classification or eligibility and no ASD diagnostic statement, and 5.4% had an ASD ICD code only. ASD prevalence per 1,000 children aged 8 years that was based exclusively on documented ASD diagnostic statements was 17.4 overall (range: 11.2 in Maryland to 29.9 in California). The median age of earliest known ASD diagnosis ranged from 36 months in California to 63 months in Minnesota. Among the 3,007 children with ASD and data on cognitive ability, 35.2% were classified as having an intelligence quotient (IQ) score ≤70. The percentages of children with ASD with IQ scores ≤70 were 49.8%, 33.1%, and 29.7% among Black, Hispanic, and White children, respectively. Overall, children with ASD and IQ scores ≤70 had earlier median ages of ASD diagnosis than children with ASD and IQ scores >70 (44 versus 53 months)., Interpretation: In 2018, one in 44 children aged 8 years was estimated to have ASD, and prevalence and median age of identification varied widely across sites. Whereas overall ASD prevalence was similar by race and ethnicity, at certain sites Hispanic children were less likely to be identified as having ASD than White or Black children. The higher proportion of Black children compared with White and Hispanic children classified as having intellectual disability was consistent with previous findings., Public Health Action: The variability in ASD prevalence and community ASD identification practices among children with different racial, ethnic, and geographical characteristics highlights the importance of research into the causes of that variability and strategies to provide equitable access to developmental evaluations and services. These findings also underscore the need for enhanced infrastructure for diagnostic, treatment, and support services to meet the needs of all children., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-year-old children in multiple US communities. From 2000 to 2016, investigators at ADDM Network sites classified ASD from collected text descriptions of behaviors from medical and educational evaluations which were reviewed and coded by ADDM Network clinicians. It took at least 4 years to publish data from a given surveillance year. In 2018, we developed an alternative case definition utilizing ASD diagnoses or classifications made by community professionals. Using data from surveillance years 2014 and 2016, we compared the new and previous ASD case definitions. Compared with the prevalence based on the previous case definition, the prevalence based on the new case definition was similar for 2014 and slightly lower for 2016. Sex and race/ethnicity prevalence ratios were nearly unchanged. Compared with the previous case definition, the new case definition's sensitivity was 86% and its positive predictive value was 89%. The new case definition does not require clinical review and collects about half as much data, yielding more timely reporting. It also more directly measures community identification of ASD, thus allowing for more valid comparisons among communities, and reduces resource requirements while retaining measurement properties similar to those of the previous definition., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2021. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Published healthcare cost estimates for children with autism spectrum disorder (ASD) vary widely. One possible contributor is different methods of case ascertainment. In this study, ASD case status was determined using two sources of parent reports among 45,944 children ages 3-17 years in the Medical Expenditure Panel Survey (MEPS) linked to the National Health Interview Survey (NHIS) Sample Child Core questionnaire. In a two-part regression model, the incremental annual per-child cost of ASD relative to no ASD diagnosis was $3930 (2018 US dollars) using ASD case status from the NHIS Child Core and $5621 using current-year ASD case status from MEPS. Both estimates are lower than some published estimates but still represent substantial costs to the US healthcare system.

Background: Children with intellectual disability (ID), characterized by impairments in intellectual functioning and adaptive behavior, benefit from early identification and access to services. Previous U.S. estimates used administrative data or parent report with limited information for demographic subgroups., Objective: Using empiric measures we examined ID characteristics among 8-year-old children and estimated prevalence by sex, race/ethnicity, geographic area and socioeconomic status (SES) area indicators., Methods: We analyzed data for 8-year-old children in 9 geographic areas participating in the 2014 Autism and Developmental Disabilities Monitoring Network. Children with ID were identified through record review of IQ test data. Census and American Community Survey data were used to estimate the denominator., Results: Overall, 11.8 per 1,000 (1.2%) had ID (IQ ≤ 70), of whom 39% (n = 998) also had autism spectrum disorder. Among children with ID, 1,823 had adaptive behavior test scores for which 64% were characterized as impaired. ID prevalence per 1,000 was 15.8 (95% confidence interval [95% CI], 15.0-16.5) among males and 7.7 (95% CI, 7.2-8.2) among females. ID prevalence was 17.7 (95% CI, 16.6-18.9) among children who were non-Hispanic black; 12.0 (95% CI, 11.1-13.0), among Hispanic; 8.6 (95% CI, 7.1-10.4), among non-Hispanic Asian; and 8.0 (95% CI, 7.5-8.6), among non-Hispanic white. Prevalence varied across geographic areas and was inversely associated with SES., Conclusions: ID prevalence varied substantively among racial, ethnic, geographic, and SES groups. Results can inform strategies to enhance identification and improve access to services particularly for children who are minorities or living in areas with lower SES., Competing Interests: Declaration of competing interest The authors have no potential conflicts of interest to disclose., (Published by Elsevier Inc.)

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2016., Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition., Results: For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (39% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively) [corrected]. Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months)., Interpretation: The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children., Public Health Action: These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Zachary Warren reports personal fees from Hoffman La Roche, grants and personal fees from Adaptive Technology Consulting, grants from Autism Speaks, grants from Cognoa, and grants from Simons Foundation; all fees and grants received are outside the submitted work. John Constantino reports a grant from Western Psychological Services outside the submitted work.

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2016., Description of System: The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network, a subset of the overall ADDM Network, is an active surveillance program that estimates ASD prevalence and monitors early identification of ASD among children aged 4 years. Children included in surveillance year 2016 were born in 2012 and had a parent or guardian who lived in the surveillance area in Arizona, Colorado, Missouri, New Jersey, North Carolina, or Wisconsin, at any time during 2016. Children were identified from records of community sources including general pediatric health clinics, special education programs, and early intervention programs. Data from comprehensive evaluations performed by community professionals were abstracted and reviewed by trained clinicians using a standardized ASD surveillance case definition with criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)., Results: In 2016, the overall ASD prevalence was 15.6 per 1,000 (one in 64) children aged 4 years for Early ADDM Network sites. Prevalence varied from 8.8 per 1,000 in Missouri to 25.3 per 1,000 in New Jersey. At every site, prevalence was higher among boys than among girls, with an overall male-to-female prevalence ratio of 3.5 (95% confidence interval [CI] = 3.1-4.1). Prevalence of ASD between non-Hispanic white (white) and non-Hispanic black (black) children was similar at each site (overall prevalence ratio: 0.9; 95% CI = 0.8-1.1). The prevalence of ASD using DSM-5 criteria was lower than the prevalence using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria at one of four sites that used criteria from both editions. Among sites where ≥60% of children aged 4 years had information about intellectual disability (intelligence quotient ≤70 or examiner's statement of intellectual disability documented in an evaluation), 53% of children with ASD had co-occurring intellectual disability. Of all children aged 4 years with ASD, 84% had a first evaluation at age ≤36 months and 71% of children who met the surveillance case definition had a previous ASD diagnosis from a community provider. Median age at first evaluation and diagnosis for this age group was 26 months and 33 months, respectively. Cumulative incidence of autism diagnoses received by age 48 months was higher for children aged 4 years than for those aged 8 years identified in Early ADDM Network surveillance areas in 2016., Interpretation: In 2016, the overall prevalence of ASD in the Early ADDM Network using DSM-5 criteria (15.6 per 1,000 children aged 4 years) was higher than the 2014 estimate using DSM-5 criteria (14.1 per 1,000). Children born in 2012 had a higher cumulative incidence of ASD diagnoses by age 48 months compared with children born in 2008, which indicates more early identification of ASD in the younger group. The disparity in ASD prevalence has decreased between white and black children. Prevalence of co-occurring intellectual disability was higher than in 2014, suggesting children with intellectual disability continue to be identified at younger ages. More children received evaluations by age 36 months in 2016 than in 2014, which is consistent with Healthy People 2020 goals. Median age at earliest ASD diagnosis has not changed considerably since 2014., Public Health Action: More children aged 4 years with ASD are being evaluated by age 36 months and diagnosed by age 48 months, but there is still room for improvement in early identification. Timely evaluation of children by community providers as soon as developmental concerns have been identified might result in earlier ASD diagnoses, earlier receipt of evidence-based interventions, and improved developmental outcomes., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. John Constantino reports grants from Western Psychological Services outside the submitted work.

Objectives: To study the national prevalence of 10 developmental disabilities in US children aged 3 to 17 years and explore changes over time by associated demographic and socioeconomic characteristics, using the National Health Interview Survey., Methods: Data come from the 2009 to 2017 National Health Interview Survey, a nationally representative survey of the civilian noninstitutionalized population. Parents reported physician or other health care professional diagnoses of attention-deficit/hyperactivity disorder; autism spectrum disorder; blindness; cerebral palsy; moderate to profound hearing loss; learning disability; intellectual disability; seizures; stuttering or stammering; and other developmental delays. Weighted percentages for each of the selected developmental disabilities and any developmental disability were calculated and stratified by demographic and socioeconomic characteristics., Results: From 2009 to 2011 and 2015 to 2017, there were overall significant increases in the prevalence of any developmental disability (16.2%-17.8%, P < .001), attention-deficit/hyperactivity disorder (8.5%-9.5%, P < .01), autism spectrum disorder (1.1%-2.5%, P < .001), and intellectual disability (0.9%-1.2%, P < .05), but a significant decrease for any other developmental delay (4.7%-4.1%, P < .05). The prevalence of any developmental disability increased among boys, older children, non-Hispanic white and Hispanic children, children with private insurance only, children with birth weight ≥2500 g, and children living in urban areas and with less-educated mothers., Conclusions: The prevalence of developmental disability among US children aged 3 to 17 years increased between 2009 and 2017. Changes by demographic and socioeconomic subgroups may be related to improvements in awareness and access to health care., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2019 by the American Academy of Pediatrics.)

Objective: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap., Materials and Methods: Using data gathered from a single surveillance site, we applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms' performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance., Results: Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures., Discussion: The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations., Conclusion: Deep learning models performed similarly to traditional machine learning methods at predicting the clinician-assigned case status for CDC's autism surveillance system. While deep learning methods had limited benefit in this task, they may have applications in other surveillance systems., Competing Interests: The authors have declared that no competing interests exist.

Objective: Geographic differences may provide insight into what factors influence the likelihood that a child is diagnosed with autism spectrum disorder (ASD) in the United States; yet, there have been few nationally representative surveys that have explored this topic. The current study expands the limited literature by analyzing regional differences in ASD prevalence, service utilization, and the presence of unmet needs within a nationally representative sample of children., Methods: Data were drawn from the 2014-2016 National Health Interview Survey (NHIS), a nationally representative household survey of the noninstitutionalized US population. Children 3 to 17 years of age were included in the analytic sample. Prevalence estimates accounted for the complex survey design of the NHIS, and differences between geographic regions were compared using logistic/linear regressions with and without adjustment for child/family characteristics., Results: The prevalence of ASD was highest in the Northeast (3.0%), followed by the Midwest (2.4%), South (2.4%), and West (2.3%). A significant difference was found between the Northeast and West (P < .05); however, after accounting for child and family characteristics, this difference was no longer significant. Children with ASD in the Northeast were the most likely to have seen a specialist in the past year. Approximately 1 in 8 children with ASD experienced at least 1 unmet need, but there were no differences found by geographic region., Conclusions: Although differences in prevalence were not significant after adjustment, service utilization differences remained. It appears that children with ASD in the Northeast utilize the greatest number of specialty services when compared to children with ASD from other parts of the country., (Published by Elsevier Inc.)

Problem/condition: Autism spectrum disorder (ASD) is estimated to affect up to 3% of children in the United States. Public health surveillance for ASD among children aged 4 years provides information about trends in prevalence, characteristics of children with ASD, and progress made toward decreasing the age of identification of ASD so that evidence-based interventions can begin as early as possible., Period Covered: 2010, 2012, and 2014., Description of System: The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network is an active surveillance system that provides biennial estimates of the prevalence and characteristics of ASD among children aged 4 years whose parents or guardians lived within designated sites. During surveillance years 2010, 2012, or 2014, data were collected in seven sites: Arizona, Colorado, Missouri, New Jersey, North Carolina, Utah, and Wisconsin. The Early ADDM Network is a subset of the broader ADDM Network (which included 13 total sites over the same period) that has been conducting ASD surveillance among children aged 8 years since 2000. Each Early ADDM site covers a smaller geographic area than the broader ADDM Network. Early ADDM ASD surveillance is conducted in two phases using the same methods and project staff members as the ADDM Network. The first phase consists of reviewing and abstracting data from children's records, including comprehensive evaluations performed by community professionals. Sources for these evaluations include general pediatric health clinics and specialized programs for children with developmental disabilities. In addition, special education records (for children aged ≥3 years) were reviewed for Arizona, Colorado, New Jersey, North Carolina, and Utah, and early intervention records (for children aged 0 to <3 years) were reviewed for New Jersey, North Carolina, Utah, and Wisconsin; in Wisconsin, early intervention records were reviewed for 2014 only. The second phase involves a review of the abstracted evaluations by trained clinicians using a standardized case definition and method. A child is considered to meet the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism), or Asperger disorder (2010, 2012, and 2014). For 2014 only, prevalence estimates based on surveillance case definitions according to DSM-IV-TR and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) were compared. This report provides estimates of overall ASD prevalence and prevalence by sex and race/ethnicity; characteristics of children aged 4 years with ASD, including age at first developmental evaluation, age at ASD diagnosis, and cognitive function; and trends in ASD prevalence and characteristics among Early ADDM sites with data for all 3 surveillance years (2010, 2012, and 2014), including comparisons with children aged 8 years living in the same geographic area. Analyses of time trends in ASD prevalence are restricted to the three sites that contributed data for all 3 surveillance years with consistent data sources (Arizona, Missouri, and New Jersey)., Results: The overall ASD prevalence was 13.4 per 1,000 children aged 4 years in 2010, 15.3 in 2012, and 17.0 in 2014 for Early ADDM sites with data for the specific years. ASD prevalence was determined using a surveillance case definition based on DSM-IV-TR. Within each surveillance year, ASD prevalence among children aged 4 years varied across surveillance sites and was lowest each year for Missouri (8.5, 8.1, and 9.6 per 1,000, for 2010, 2012, and 2014, respectively) and highest each year for New Jersey (19.7, 22.1, and 28.4 per 1,000, for the same years, respectively). Aggregated prevalence estimates were higher for sites that reviewed education and health care records than for sites that reviewed only health care records. Among all participating sites and years, ASD prevalence among children aged 4 years was consistently higher among boys than girls; prevalence ratios ranged from 2.6 (Arizona and Wisconsin in 2010) to 5.2 boys per one girl (Colorado in 2014). In 2010, ASD prevalence was higher among non-Hispanic white children than among Hispanic children in Arizona and non-Hispanic black children in Missouri; no other differences were observed by race/ethnicity. Among four sites with ≥60% data on cognitive test scores (Arizona, New Jersey, North Carolina, and Utah), the frequency of co-occurring intellectual disabilities was significantly higher among children aged 4 years than among those aged 8 years for each site in each surveillance year except Arizona in 2010. The percentage of children with ASD who had a first evaluation by age 36 months ranged from 48.8% in Missouri in 2012 to 88.9% in Wisconsin in 2014. The percentage of children with a previous ASD diagnosis from a community provider varied by site, ranging from 43.0% for Arizona in 2012 to 86.5% for Missouri in 2012. The median age at earliest known ASD diagnosis varied from 28 months in North Carolina in 2014 to 39.0 months in Missouri and Wisconsin in 2012. In 2014, the ASD prevalence based on the DSM-IV-TR case definition was 20% higher than the prevalence based on the DSM-5 (17.0 versus 14.1 per 1,000, respectively). Trends in ASD prevalence and characteristics among children aged 4 years during the study period were assessed for the three sites with data for all 3 years and consistent data sources (Arizona, Missouri, and New Jersey) using the DSM-IV-TR case definition; prevalence was higher in 2014 than in 2010 among children aged 4 years in New Jersey and was stable in Arizona and Missouri. In Missouri, ASD prevalence was higher among children aged 8 years than among children aged 4 years. The percentage of children with ASD who had a comprehensive evaluation by age 36 months was stable in Arizona and Missouri and decreased in New Jersey. In the three sites, no change occurred in the age at earliest known ASD diagnosis during 2010-2014., Interpretation: The findings suggest that ASD prevalence among children aged 4 years was higher in 2014 than in 2010 in one site and remained stable in others. Among children with ASD, the frequency of cognitive impairment was higher among children aged 4 years than among those aged 8 years and suggests that surveillance at age 4 years might more often include children with more severe symptoms or those with co-occurring conditions such as intellectual disability. In the sites with data for all years and consistent data sources, no change in the age at earliest known ASD diagnosis was found, and children received their first developmental evaluation at the same or a later age in 2014 compared with 2010. Delays in the initiation of a first developmental evaluation might adversely affect children by delaying access to treatment and special services that can improve outcomes for children with ASD., Public Health Action: Efforts to increase awareness of ASD and improve the identification of ASD by community providers can facilitate early diagnosis of children with ASD. Heterogeneity of results across sites suggests that community-level differences in evaluation and diagnostic services as well as access to data sources might affect estimates of ASD prevalence and age of identification. Continuing improvements in providing developmental evaluations to children as soon as developmental concerns are identified might result in earlier ASD diagnoses and earlier receipt of services, which might improve developmental outcomes., Competing Interests: Deborah Bilder reports personal fees from Audentes Therapeutics and personal fees from BioMarin Pharmaceuticals outside the submitted work. John Constantino receives royalties from Western Psychological Services for the commercial distribution of the Social Responsiveness Scale.

Background: Participation in epidemiologic studies has declined, raising concerns about selection bias. While estimates derived from epidemiologic studies have been shown to be robust under a wide range of scenarios, additional empiric study is needed. The Georgia Study to Explore Early Development (GA SEED), a population-based case-control study of risk factors for autism spectrum disorder (ASD), provided an opportunity to explore factors associated with non-participation and potential impacts of non-participation on association studies., Methods: GA SEED recruited preschool-aged children residing in metropolitan-Atlanta during 2007-2012. Children with ASD were identified from multiple schools and healthcare providers serving children with disabilities; children from the general population (POP) were randomly sampled from birth records. Recruitment was via mailed invitation letter with follow-up phone calls. Eligibility criteria included birth and current residence in study area and an English-speaking caregiver. Many children identified for potential inclusion could not be contacted. We used data from birth certificates to examine demographic and perinatal factors associated with participation in GA SEED and completion of the data collection protocol. We also compared ASD-risk factor associations for the final sample of children who completed the study with the initial sample of all likely ASD and POP children invited to potentially participate in the study, had they been eligible. Finally, we derived post-stratification sampling weights for participants who completed the study and compared weighted and unweighted associations between ASD and two factors collected via post-enrollment maternal interview: infertility and reproductive stoppage., Results: Maternal age and education were independently associated with participation in the POP group. Maternal education was independently associated with participation in the ASD group. Numerous other demographic and perinatal factors were not associated with participation. Moreover, unadjusted and adjusted odds ratios for associations between ASD and several demographic and perinatal factors were similar between the final sample of study completers and the total invited sample. Odds ratios for associations between ASD and infertility and reproductive stoppage were also similar in unweighted and weighted analyses of the study completion sample., Conclusions: These findings suggest that effect estimates from SEED risk factor analyses, particularly those of non-demographic factors, are likely robust.

We compared the prevalence of various medical and behavioral co-occurring conditions/symptoms between 4- and 8-year-olds with autism spectrum disorder (ASD) from five sites in the Autism and Developmental Disabilities Monitoring Network during the 2010 survey year, accounting for sociodemographic differences. Over 95% of children had at least one co-occurring condition/symptom. Overall, the prevalence was higher in 8- than 4-year-olds for 67% of co-occurring conditions/symptoms examined. Further, our data suggested that co-occurring conditions/symptoms increased or decreased the age at which children were first evaluated for ASD. Similarly, among the 8-year-olds, the prevalence of most co-occurring conditions/symptoms was higher in children with a previous ASD diagnosis documented in their records. These findings are informative for understanding and screening co-occurring conditions/symptoms in ASD.

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] <70), 25% were in the borderline range (IQ 71-85), and 44% had IQ scores in the average to above average range (i.e., 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.

Objectives: To describe the association between indicators of socioeconomic status (SES) and the prevalence of autism spectrum disorder (ASD) in the United States during the period 2002 to 2010, when overall ASD prevalence among children more than doubled, and to determine whether SES disparities account for ongoing racial and ethnic disparities in ASD prevalence., Methods: We computed ASD prevalence and 95% confidence intervals (CIs) from population-based surveillance, census, and survey data. We defined SES categories by using area-level education, income, and poverty indicators. We ascertained ASD in 13 396 of 1 308 641 8-year-old children under surveillance., Results: The prevalence of ASD increased with increasing SES during each surveillance year among White, Black, and Hispanic children. The prevalence difference between high- and low-SES groups was relatively constant over time (3.9/1000 [95% CI = 3.3, 4.5] in 2002 and 4.1/1000 [95% CI = 3.6, 4.6] in the period 2006-2010). Significant racial/ethnic differences in ASD prevalence remained after stratification by SES., Conclusions: A positive SES gradient in ASD prevalence according to US surveillance data prevailed between 2002 and 2010, and racial and ethnic disparities in prevalence persisted during this time among low-SES children.

We compared early-diagnosed autism spectrum disorder (ASD) (defined as diagnosis by age 4 years) between the 2002 and 2006 birth cohorts, in five sites of the Autism and Developmental Disabilities Monitoring Network. In the 2002 cohort, the prevalence/1000 of early-diagnosed ASD was half the 8-year-old prevalence (7.2 vs. 14.7, prevalence ratio [PR] 0.5 [0.4-0.6]). Overall, the prevalence of early-diagnosed ASD did not differ between birth cohorts (PR 1.1 [0.9-1.3]). However, in three sites with complete case ascertainment, the prevalence of early-diagnosed ASD was higher for those born in 2006 versus 2002 (PR 1.3 [1.1-1.5]), suggesting possible improvement in early identification. The lack of change in two sites may reflect less complete case ascertainment. Studies in more recent cohorts are needed.

The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-year old children in multiple US sites. To classify ASD, trained clinicians review developmental evaluations collected from multiple health and education sources to determine whether the child meets the ASD surveillance case criteria. The number of evaluations collected has dramatically increased since the year 2000, challenging the resources and timeliness of the surveillance system. We developed and evaluated a machine learning approach to classify case status in ADDM using words and phrases contained in children's developmental evaluations. We trained a random forest classifier using data from the 2008 Georgia ADDM site which included 1,162 children with 5,396 evaluations (601 children met ADDM ASD criteria using standard ADDM methods). The classifier used the words and phrases from the evaluations to predict ASD case status. We evaluated its performance on the 2010 Georgia ADDM surveillance data (1,450 children with 9,811 evaluations; 754 children met ADDM ASD criteria). We also estimated ASD prevalence using predictions from the classification algorithm. Overall, the machine learning approach predicted ASD case statuses that were 86.5% concordant with the clinician-determined case statuses (84.0% sensitivity, 89.4% predictive value positive). The area under the resulting receiver-operating characteristic curve was 0.932. Algorithm-derived ASD "prevalence" was 1.46% compared to the published (clinician-determined) estimate of 1.55%. Using only the text contained in developmental evaluations, a machine learning algorithm was able to discriminate between children that do and do not meet ASD surveillance criteria at one surveillance site., Competing Interests: The authors have declared that no competing interests exist.

Purpose: To evaluate feasibility and impact of evidence-based medicine (EBM) educational prescriptions (EPs) in medical student clerkships., Methods: Students answered clinical questions during clerkships using EPs, which guide learners through the "four As" of EBM. Epidemiology fellows graded EPs using a rubric. Feasibility was assessed using descriptive statistics and student and fellow end-of-study questionnaires, which also measured impact. In addition, for each EP, students reported patient impact. Impact on EBM skills was assessed by change in EP scores over time and scores on an EBM objective structured clinical exam (OSCE) that were compared to controls from the prior year., Results: 117 students completed 402 EPs evaluated by 24 fellows. Average score was 7.34/9.00 (SD 1.58). 69 students (59%) and 21 fellows (88%) completed questionnaires. Most students thought EPs improved "Acquiring" and "Appraising". Almost half thought EPs improved "Asking" and "Applying". Fellows did not value grading EPs. For 18% of EPs, students reported a "change" or "potential change" in treatment. 56% "confirmed" treatment. EP scores increased by 1.27 (95% CI: 0.81-1.72). There were no differences in OSCE scores between cohorts., Conclusions: Integrating EPs into clerkships is feasible and has impact, yet OSCEs were unchanged, and research fellows had limitations as evaluators.

Introduction: Accurately identifying youth at highest risk of firearm violence involvement could permit delivery of focused, comprehensive prevention services. This study explored whether readily available city and state administrative data covering life events before youth firearm violence could elucidate patterns preceding such violence., Methods: Four hundred twenty-one individuals arrested for homicide, attempted homicide, aggravated assault, or robbery with a firearm committed in Wilmington, Delaware, from January 1, 2009 to May 21, 2014, were matched 1:3 to 1,259 Wilmington resident controls on birth year and sex. In 2015, descriptive statistics and a conditional logistic regression model using Delaware healthcare, child welfare, juvenile services, labor, and education administrative data examined associations between preceding life events and subsequent firearm violence., Results: In a multivariable adjusted model, experiencing a prior gunshot wound injury (AOR=11.4, 95% CI=2.7, 48.1) and being subject to community probation (AOR=13.2, 95% CI=5.7, 30.3) were associated with the highest risk of subsequent firearm violence perpetration, though multiple other sentinel events were informative. The mean number of sentinel events experienced by youth committing firearm violence was 13.0 versus 1.9 among controls (p<0.0001). Within the sample, 84.1% of youth experiencing a sentinel event in all five studied domains ultimately committed firearm violence., Conclusions: Youth who commit firearm violence have preceding patterns of life events that markedly differ from youth not involved in firearm violence. This information is readily available from administrative data, demonstrating the potential of data sharing across city and state institutions to focus prevention strategies on those at greatest risk., (Published by Elsevier Inc.)

During the Ebola virus outbreak of 2013-2016, the Viral Special Pathogens Branch field laboratory in Sierra Leone tested approximately 26 000 specimens between August 2014 and October 2015. Analysis of the B2M endogenous control Ct values showed its utility in monitoring specimen quality, comparing results with different specimen types, and interpretation of results. For live patients, blood is the most sensitive specimen type and oral swabs have little diagnostic utility. However, swabs are highly sensitive for diagnostic testing of corpses., (Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Background: The public health objective for cerebral palsy (CP) in the United States is to reduce the percentage of children with CP who were born low birthweight (LBW, <2500 g) by 10% between 2006 and 2020. This study reports the prevalence of CP in a constant surveillance area for the years 2006, 2008, and 2010 and describes initial progress towards the CP public health objective., Methods: Data on children with CP at age 8 years were ascertained by the Autism and Developmental Disabilities Monitoring (ADDM) Network, a population-based surveillance system that monitored CP in four areas of the United States., Results: CP prevalence in 2010 was 2.9 per 1000 [95% confidence interval (CI) 2.6, 3.2], down from 3.5 (95% CI 3.2, 3.9) in the same surveillance area in 2006. Among CP cases with no documented postneonatal aetiology, 49.1% (95% CI 42.9, 55.2) were born LBW in 2010 compared with 54.3% (95% CI 48.4, 60.1) in 2006. In 2010, 28.1% (95% CI 22.9, 30.4) were born very low birthweight (VLBW, <1500 g) compared with 35.4% (95% CI 30.0, 41.2) in 2006. The relative risks for associations between CP and both LBW and VLBW also declined, though not significantly, during the study period., Conclusions: Declines in the associations between CP and LBW categories may have contributed to declines during the study period in both the prevalence of CP and the percentage of children with CP who were born LBW or VLBW. Ongoing monitoring of these trends is warranted., (© 2016 John Wiley & Sons Ltd.)

In 2015, community event-based surveillance (CEBS) was implemented in Sierra Leone to assist with the detection of Ebola virus disease (EVD) cases. We assessed the sensitivity of CEBS for finding EVD cases during a 7-month period, and in a 6-week subanalysis, we assessed the timeliness of reporting cases with no known epidemiologic links at time of detection. Of the 12,126 CEBS reports, 287 (2%) met the suspected case definition, and 16 were confirmed positive. CEBS detected 30% (16/53) of the EVD cases identified during the study period. During the subanalysis, CEBS staff identified 4 of 6 cases with no epidemiologic links. These CEBS-detected cases were identified more rapidly than those detected by the national surveillance system; however, too few cases were detected to determine system timeliness. Although CEBS detected EVD cases, it largely generated false alerts. Future versions of community-based surveillance could improve case detection through increased staff training and community engagement.

This study examined associations between ASD diagnosis retention and non-ASD co-occurring conditions (CoCs) by child sex. The sample included 7077 males and 1487 females who had an ASD diagnosis documented in their school or health records in a population-based ASD surveillance system for 8-year-old children. ASD diagnosis retention status was determined when an initial ASD diagnosis was not later ruled out by a community professional. We found that ASD diagnosis remains fairly stable, with only 9% of children who had an initial documented ASD diagnosis later being ruled-out. Although most of the associations between the ASD diagnosis retention status and CoCs are similar in both sexes, the co-occurrence of developmental diagnoses (e.g., intellectual disability or sensory integration disorder) was predictive of ASD diagnostic changes in males, whereas the co-occurrence of specific developmental (e.g., personal/social delay) and neurological diagnosis (e.g., epilepsy) was associated with ASD diagnostic change in females. More ASD-related evaluations and less ASD-related impairment were associated with later ASD rule outs in both sexes. Our findings highlight that CoCs can complicate the diagnostic picture and lead to an increased likelihood of ambiguity in ASD diagnosis. Using sensitive and appropriate measures in clinical practice is necessary for differential diagnosis, particularly when there are co-occurring developmental conditions., Competing Interests: Conflicts of interest The sponsor for the data collection of the Autism and Developmental Disabilities Monitoring (ADDM) Network is the US Centers for Disease Control and Prevention (CDC). The sponsor had no involvement in (1) study design; (2) analysis, and interpretation of data; (3) the writing of the report; or (4) the decision to submit the paper for publication. The authors do not have any potential conflict of interest, real or perceived.

Purpose: Cerebral palsy (CP) and intellectual disability (ID) are developmental disabilities that result in considerable functional limitations. There are few recent and nationally representative prevalence estimates of CP and ID in the United States., Methods: We used two U.S. nationally representative surveys, the 2011-2012 National Survey of Children's Health (NSCH) and the 2011-2013 National Health Interview Survey (NHIS), to determine the prevalence of CP and ID based on parent report among children aged 2-17 years., Results: CP prevalence was 2.6 (95% confidence interval [CI]: 2.1-3.2) per 1000 in the NSCH and 2.9 (95% CI: 2.3-3.7) in the NHIS. ID prevalence was 12.2 (95% CI: 10.7-13.9) and 12.1 (95% CI: 10.8-13.7) in NSCH and NHIS, respectively. For both conditions, the NSCH and NHIS prevalence estimates were similar to each other for nearly all sociodemographic subgroups examined., Conclusions: Despite using different modes of data collection, the two surveys produced similar and plausible estimates of CP and ID and offer opportunities to better understand the needs and situations of children with these conditions., (Published by Elsevier Inc.)

To determine whether 2 readily available indicators predicted survival among patients with Ebola virus disease in Sierra Leone, we evaluated information for 216 of the 227 patients in Bo District during a 4-month period. The indicators were time from symptom onset to healthcare facility admission and quantitative real-time reverse transcription PCR cycle threshold (Ct), a surrogate for viral load, in first Ebola virus-positive blood sample tested. Of these patients, 151 were alive when detected and had reported healthcare facility admission dates and Ct values available. Time from symptom onset to healthcare facility admission was not associated with survival, but viral load in the first Ebola virus-positive blood sample was inversely associated with survival: 52 (87%) of 60 patients with a Ct of >24 survived and 20 (22%) of 91 with a Ct of <24 survived. Ct values may be useful for clinicians making treatment decisions or managing patient or family expectations.

Objectives: The developmental disabilities questions in the 2014 National Health Interview Survey (NHIS) were changed from previous years, including question reordering and a new approach to asking about autism spectrum disorder (ASD). This report examines survey-based estimates of the lifetime prevalence of ASD, intellectual disability (ID), and any other developmental delay (other DD) following the inclusion of a standalone ASD question, the inclusion of specific diagnoses in the ASD question, and the ASD question preceding the other DD question, and compares them with estimates from previous years., Methods: In NHIS, one child is randomly selected from each family to be the subject of detailed questions on health conditions, functional limitations, and health care utilization. Parents are asked if a doctor or health professional had ever told them that their child had each of a series of developmental disabilities. Prevalence estimates of ASD, ID, and other DD for children aged 3–17 years were calculated using data collected in 2011–2014., Results: The estimated prevalence of ASD based on 2014 data was 2.24%, a significant increase from the estimated annualized prevalence of 1.25% based on 2011–2013 data. In contrast, the prevalence of other DD declined significantly from 4.84% based on 2011–2013 data to 3.57% based on 2014 data. The prevalence of ID did not significantly change from 2011–2013 (1.27%) to 2014 (1.10%). The prevalence of having any of the three conditions was constant across survey years., Conclusions: The revised question ordering and new approach to asking about developmental disabilities in the 2014 NHIS likely affected the prevalence estimates of these conditions. In previous years, it is likely that some parents of children diagnosed with ASD reported this developmental disability as other DD instead of, or in addition to, ASD. Following these changes, the 2014 ASD estimate was more similar to ASD prevalence estimates from other sources., (All material appearing in this report is in the public domain and may be reproduced or copied without permission; citation as to source, however, is appreciated.)

Aim: To determine whether racial disparities in cerebral palsy (CP) risk among US children persist after controlling for socio-economic status (SES) (here indicated by maternal education) and perinatal risk factors., Method: A population-based birth cohort study was conducted using the Autism and Developmental Disabilities Monitoring Network surveillance and birth data for 8-year-old children residing in multi-county areas in Alabama, Georgia, Missouri, and Wisconsin between 2002 and 2008. The birth cohort comparison group included 458 027 children and the case group included 1570 children with CP, 1202 with available birth records. χ(2) tests were performed to evaluate associations and logistic regression was used to calculate relative risks (RR) and adjusted odds ratios (OR) with 95% confidence intervals (CI)., Results: The risk of spastic CP was more than 50% higher for black versus white children (RR 1.52, 95% CI 1.33-1.73), and this greater risk persisted after adjustment for SES (OR 1.35, 95% CI 1.18-1.55), but not after further adjustment for preterm birth and size for gestational age. The protective effect of maternal education remained after adjustment for race/ethnicity and perinatal factors., Interpretation: Maternal education appears to independently affect CP risk but does not fully explain existing racial disparities in CP prevalence in the US., (© 2015 Mac Keith Press.)

Recent studies have reported an increased risk of autism among second-born children conceived <12 versus >36 months after the birth of a sibling. Confirmation of this finding would point to inter-pregnancy interval (IPI) as a potentially modifiable risk factor for autism. This study evaluated the relationship between IPI and autism spectrum disorder (ASD) risk in a Wisconsin birth cohort of 31,467 second-born children, of whom 160 resided in the study area and were found to have ASD at age 8 years. In adjusted analyses, both short (<12) and long (>84 month) IPIs were associated with a two-fold risk of ASD relative to IPIs of 24-47 months (p < 0.05). The long IPI association was partially confounded by history of previous pregnancy loss.

Lower (versus higher) IQ scores have been shown to increase the risk of early mortality, however, the underlying mechanisms are poorly understood and previous studies underrepresent individuals with intellectual disability (ID) and women. This study followed one third of all senior-year students (approximately aged 17) attending public high school in Wisconsin, U.S. in 1957 (n  =  10,317) until 2011. Men and women with the lowest IQ test scores (i.e., IQ scores ≤ 85) had increased rates of mortality compared to people with the highest IQ test scores, particularly for cardiovascular disease. Importantly, when educational attainment was held constant, people with lower IQ test scores did not have higher mortality by age 70 than people with higher IQ test scores. Individuals with lower IQ test scores likely experience multiple disadvantages throughout life that contribute to increased risk of early mortality.

Purpose: Numerous studies establish associations between adverse perinatal outcomes/complications and autism spectrum disorder (ASD). There has been little assessment of population attributable fractions (PAFs)., Methods: We estimated average ASD PAFs for preterm birth (PTB), small for gestational age (SGA), and Cesarean delivery (CD) in a U.S. population. Average PAF methodology accounts for risk factor co-occurrence. ASD cases were singleton non-Hispanic white, non-Hispanic black, and Hispanic children born in 1994 (n = 703) or 2000 (n = 1339) who resided in 48 U.S. counties included within eight Autism and Developmental Disabilities Monitoring Network sites. Cases were matched on birth year, sex, and maternal county of residence, race-ethnicity, age, and education to 20 controls from U.S. natality files., Results: For the 1994 cohort, average PAFs were 4.2%, 0.9%, and 7.9% for PTB, SGA, and CD, respectively. The summary PAF was 13.0% (1.7%-19.5%). For the 2000 cohort, average PAFs were 2.0%, 3.1%, and 6.7% for PTB, SGA, and CD, respectively, with a summary PAF of 11.8% (7.5%-15.9%)., Conclusions: Three perinatal risk factors notably contribute to ASD risk in a U.S. population. Because each factor represents multiple etiologic pathways, PAF estimates are best interpreted as the proportion of ASD attributable to having a suboptimal perinatal environment resulting in PTB, SGA, and/or CD., (Published by Elsevier Inc.)

Importance: The DSM-5 contains revised diagnostic criteria for autism spectrum disorder (ASD) from the DSM-IV-TR. Potential impacts of the new criteria on ASD prevalence are unclear., Objective: To assess potential effects of the DSM-5 ASD criteria on ASD prevalence estimation by retrospectively applying the new criteria to population-based surveillance data collected for previous ASD prevalence estimation., Design, Setting, and Participants: Cross-sectional, population-based ASD surveillance based on clinician review of coded behaviors documented in children's medical and educational evaluations from 14 geographically defined areas in the United States participating in the Autism and Developmental Disabilities Monitoring (ADDM) Network in 2006 and 2008. This study included 8-year-old children living in ADDM Network study areas in 2006 or 2008, including 644 883 children under surveillance, of whom 6577 met surveillance ASD case status based on the DSM-IV-TR., Main Outcomes and Measures: Proportion of children meeting ADDM Network ASD criteria based on the DSM-IV-TR who also met DSM-5 criteria; overall prevalence of ASD using DSM-5 criteria., Results: Among the 6577 children classified by the ADDM Network as having ASD based on the DSM-IV-TR, 5339 (81.2%) met DSM-5 ASD criteria. This percentage was similar for boys and girls but higher for those with than without intellectual disability (86.6% and 72.5%, respectively; P < .001). A total of 304 children met DSM-5 ASD criteria but not current ADDM Network ASD case status. Based on these findings, ASD prevalence per 1000 for 2008 would have been 10.0 (95% CI, 9.6-10.3) using DSM-5 criteria compared with the reported prevalence based on DSM-IV-TR criteria of 11.3 (95% CI, 11.0-11.7)., Conclusions and Relevance: Autism spectrum disorder prevalence estimates will likely be lower under DSM-5 than under DSM-IV-TR diagnostic criteria, although this effect could be tempered by future adaptation of diagnostic practices and documentation of behaviors to fit the new criteria.

Aim: The aim of this study was to report the prevalence and characteristics of children with cerebral palsy (CP)., Method: Children with CP (n=451) were ascertained by the Autism and Developmental Disabilities Monitoring (ADDM) Network, a population-based, record-review surveillance system monitoring CP in four areas of the USA. Prevalence was calculated as the number of children with CP among all 8-year-old children residing in these areas in 2008. Motor function was categorized by Gross Motor Function Classification System level and walking ability. Co-occurring autism spectrum disorders (ASD) and epilepsy were ascertained using ADDM Network surveillance methodology., Results: The period prevalence of CP for 2008 was 3.1 per 1000 8-year-old children (95% confidence interval 2.8-3.4). Approximately 58% of children walked independently. Co-occurring ASD frequency was 6.9% and was higher (18.4%) among children with non-spastic CP, particularly hypotonic CP. Co-occurring epilepsy frequency was 41% overall, did not differ by ASD status or CP subtype, and was highest (67%) among children with limited or no walking ability., Interpretation: The prevalence of CP in childhood from US surveillance data has remained relatively constant, in the range of 3.1 to 3.6 per 1000, since 1996. The higher frequency of ASD in non-spastic than in spastic subtypes of CP calls for closer examination., (© 2013 Mac Keith Press.)

We have estimated the prevalence of FMR1 premutation and gray zone CGG repeat expansions in a population-based sample of 19,996 male and female adults in Wisconsin and compared the observed sex ratios of the prevalence of FMR1 CGG premutation and gray zone expansions to theoretical sex ratios. The female premutation prevalence was 1 in 148 and comparable to past research, but the male premutation prevalence of 1 in 290 is somewhat higher than most previous estimates. The female:male premutation prevalence ratio is in line with the theoretically predicted sex ratio. The prevalence of CGG repeats in the gray zone (45-54 repeats) was 1 in 33 females and 1 in 62 males. The prevalence of the "expanded" gray zone (defined here as 41-54 CGG repeats) was 1 in 14 females and 1 in 22 males, leading to a female:male ratio of 1.62 (95% confidence interval 1.39-1.90). This female:male ratio was significantly lower than the expected ratio of 2.0. We examined results from three previously published FMR1 prevalence studies and found similar female:male ratios for CGG repeats in this "expanded" gray zone range (pooled female:male ratio across all four studies 1.66, 95% confidence interval 1.51-1.82). Further research is needed to understand the apparent excess prevalence of males with CGG repeats in this range., (Copyright © 2013 Wiley Periodicals, Inc.)

Aim: Differential migration and choice of denominator have been hypothesized to contribute to differences between period prevalence and birth prevalence of cerebral palsy (CP). The purpose of this study was to evaluate the effects of migration and choice of denominator on the prevalence of CP., Method: Data from the Metropolitan Atlanta Developmental Disabilities Surveillance Program and census and birth certificate files were used to calculate various CP prevalence estimates for 2000., Results: The overall CP period prevalence was 3.2 (95% confidence interval [CI] 2.7-3.8) per 1000 8-year-olds and was similar for those born in Atlanta who resided there at age 8 years (3.3; 95% CI 2.7-4.1) and those born outside Atlanta who moved into Atlanta by age 8 years (3.0; 95% CI 2.3-3.9). CP prevalence in these two migration strata was similar by sex and race/ethnicity. CP birth prevalence of 8-year-olds in Atlanta in 2000 was 2.0 (95% CI 1.6-2.5) per 1000 live births in 1992., Interpretation: The authors found no evidence to support the hypothesis that differential in-migration explained higher period than birth prevalence of CP in Atlanta. Comparability of CP prevalence across geographic areas will be enhanced if future studies report both period and birth prevalence., (© The Authors. Developmental Medicine & Child Neurology © 2013 Mac Keith Press.)