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Context: The Association of State and Territorial Health Officials (ASTHO) and the National Association of County and City Health Officials (NACCHO) applied funding issued by the US Centers for Disease Control and Prevention (CDC) to implement the Public Health Disability Specialists Program, part of a project to address the needs of people with disabilities during the COVID-19 pandemic. Disability specialists (subject matter experts) were embedded within state, territorial, and city/county health departments to help ensure disability inclusion in emergency planning, mitigation, and recovery efforts., Objective: To evaluate the success of the Disability Specialists Program in improving emergency response planning, mitigation, and recovery efforts for people with disabilities within participating jurisdictions., Design: Disability specialists worked with their assigned jurisdictions to conduct standardized baseline health department needs assessments to identify existing gaps and inform development and implementation of improvement plans. CDC, ASTHO, and NACCHO implemented a mixed methods framework to evaluate specialists' success., Setting: State, territorial, and local health departments across 28 jurisdictions between January 2021 and July 2022., Main Outcome Measures: Average number of categories of gaps addressed and qualitative documentation of strategies, barriers, and promising practices., Results: Specialists identified 1010 gaps (approximately 36 per jurisdiction) across eight needs assessment categories, most related to mitigation, recovery, resilience, and sustainability efforts (n = 213) and communication (n = 193). Specialists addressed an average of three categories of gaps identified; common focus areas included equitable COVID-19 vaccine distribution and accessible communications. Specialists commonly mentioned barriers related to limited health agency capacity (eg, resources) and community mistrust. Promising practices to address barriers included sharing best practices through peer-to-peer networks and building and strengthening partnerships between health departments and the disability community., Conclusions: Embedding disability specialists within state, territorial, and local health departments improved jurisdictional ability to meet evolving public health needs for the entire community, including people with disabilities., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: To assess the impact of COVID-19 on health service utilization of adults with intellectual and developmental disabilities (IDDs) through an analysis of Medicaid claims data., Design: Retrospective cohort study of Medicaid claims., Setting and Participants: Medicaid members aged 25 to 64 years from January 1, 2018, to March 31, 2021, from the states of Louisiana, Pennsylvania, and Wyoming., Intervention: We analyzed data from two 12-month time periods (pre-COVID-19 and during COVID-19) and assessed the potential impact of the COVID-19 pandemic on health service utilization and service intensity for 3 cohorts: (1) IDD with preexisting mental health diagnoses, (2) IDD without mental health diagnoses, and (3) all other Medicaid members., Main Outcome Measure: Health service utilization determined by specific claims data classifications., Results: The analysis showed reduced utilization for nonmental health service types with differing utilization patterns for IDD with preexisting mental health diagnoses, IDD without mental health diagnoses, and all other Medicaid members. Change in utilization varied, however, for mental health service types. Measures of service intensity showed decreased numbers of members utilizing services across most service types and increased Medicaid claims per person across most mental health service categories but decreased Medicaid claims per person for most nonmental health services., Conclusions: Results suggest a need for mental health services among all Medicaid members during the COVID-19 pandemic. By anticipating these needs, communities may be able to expand outreach to Medicaid members through enhanced case management, medication checks, and telemedicine options., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright ©.)

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 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.

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.

The objectives of our study were to (a) report how many children met an autism spectrum disorder (ASD) surveillance definition but had no clinical diagnosis of ASD in health or education records and (b) evaluate differences in demographic, individual, and service factors between children with and without a documented ASD diagnosis. ASD surveillance was conducted in selected areas of Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin. Children were defined as having ASD if sufficient social and behavioral deficits and/or an ASD diagnosis were noted in health and/or education records. Among 4,498 children, 1,135 (25%) had ASD indicators without having an ASD diagnosis. Of those 1,135 children without a documented ASD diagnosis, 628 (55%) were not known to receive ASD services in public school. Factors associated with not having a clinical diagnosis of ASD were non-White race, no intellectual disability, older age at first developmental concern, older age at first developmental evaluation, special education eligibility other than ASD, and need for fewer supports. These results highlight the importance of reducing disparities in the diagnosis of children with ASD characteristics so that appropriate interventions can be promoted across communities. Autism Res 2020, 13: 464-473. © 2019 International Society for AutismResearch,Wiley Periodicals, Inc. LAY SUMMARY: Children who did not have a clinical diagnosis of autism spectrum disorder (ASD) documented in health or education records were more likely to be non-White and have fewer developmental problems than children with a clinical diagnosis of ASD. They were brought to the attention of healthcare providers at older ages and needed fewer supports than children with a clinical diagnosis of ASD. All children with ASD symptoms who meet diagnostic criteria should be given a clinical diagnosis so they can receive treatment specific to their needs., (© 2019 International Society for Autism Research, Wiley Periodicals, Inc.)

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2012., Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence and characteristics of ASD among children aged 8 years whose parents or guardians reside in 11 ADDM Network sites in the United States (Arkansas, Arizona, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, South Carolina, Utah, and Wisconsin). Surveillance to determine ASD case status is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional service providers in the community. Data sources identified for record review are categorized as either 1) education source type, including developmental evaluations to determine eligibility for special education services or 2) health care source type, including diagnostic and developmental evaluations. The second phase involves the review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors that are consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides ASD prevalence estimates for children aged 8 years living in catchment areas of the ADDM Network sites in 2012, overall and stratified by sex, race/ethnicity, and the type of source records (education and health records versus health records only). In addition, this report describes the proportion of children with ASD with a score consistent with intellectual disability on a standardized intellectual ability test, the age at which the earliest known comprehensive evaluation was performed, the proportion of children with a previous ASD diagnosis, the specific type of ASD diagnosis, and any special education eligibility classification., Results: For 2012, the combined estimated prevalence of ASD among the 11 ADDM Network sites was 14.5 per 1,000 (one in 69) children aged 8 years. Estimated prevalence was significantly higher among boys aged 8 years (23.4 per 1,000) than among girls aged 8 years (5.2 per 1,000). Estimated ASD prevalence was significantly higher among non-Hispanic white children aged 8 years (15.3 per 1,000) compared with non-Hispanic black children (13.1 per 1,000), and Hispanic (10.2 per 1,000) children aged 8 years. Estimated prevalence varied widely among the 11 ADDM Network sites, ranging from 8.2 per 1,000 children aged 8 years (in the area of the Maryland site where only health care records were reviewed) to 24.6 per 1,000 children aged 8 years (in New Jersey, where both education and health care records were reviewed). Estimated prevalence was higher in surveillance sites where education records and health records were reviewed compared with sites where health records only were reviewed (17.1 per 1,000 and 10.4 per 1,000 children aged 8 years, respectively; p<0.05). Among children identified with ASD by the ADDM Network, 82% had a previous ASD diagnosis or educational classification; this did not vary by sex or between non-Hispanic white and non-Hispanic black children. A lower percentage of Hispanic children (78%) had a previous ASD diagnosis or classification compared with non-Hispanic white children (82%) and with non-Hispanic black children (84%). The median age at earliest known comprehensive evaluation was 40 months, and 43% of children had received an earliest known comprehensive evaluation by age 36 months. The percentage of children with an earliest known comprehensive evaluation by age 36 months was similar for boys and girls, but was higher for non-Hispanic white children (45%) compared with non-Hispanic black children (40%) and Hispanic children (39%)., Interpretation: Overall estimated ASD prevalence was 14.5 per 1,000 children aged 8 years in the ADDM Network sites in 2012. The higher estimated prevalence among sites that reviewed both education and health records suggests the role of special education systems in providing comprehensive evaluations and services to children with developmental disabilities. Disparities by race/ethnicity in estimated ASD prevalence, particularly for Hispanic children, as well as disparities in the age of earliest comprehensive evaluation and presence of a previous ASD diagnosis or classification, suggest that access to treatment and services might be lacking or delayed for some children., Public Health Action: The ADDM Network will continue to monitor the prevalence and characteristics of ASD among children aged 8 years living in selected sites across the United States. Recommendations from the ADDM Network include enhancing strategies to 1) lower the age of first evaluation of ASD by community providers in accordance with the Healthy People 2020 goal that children with ASD are evaluated by age 36 months and begin receiving community-based support and services by age 48 months; 2) reduce disparities by race/ethnicity in identified ASD prevalence, the age of first comprehensive evaluation, and presence of a previous ASD diagnosis or classification; and 3) assess the effect on ASD prevalence of the revised ASD diagnostic criteria published in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

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.

Problem/condition: Autism spectrum disorder (ASD)., Period Covered: 2012., Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence and characteristics of ASD among children aged 8 years whose parents or guardians reside in 11 ADDM Network sites in the United States (Arkansas, Arizona, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, South Carolina, Utah, and Wisconsin). Surveillance to determine ASD case status is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional service providers in the community. Data sources identified for record review are categorized as either 1) education source type, including developmental evaluations to determine eligibility for special education services or 2) health care source type, including diagnostic and developmental evaluations. The second phase involves the review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors that are consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides ASD prevalence estimates for children aged 8 years living in catchment areas of the ADDM Network sites in 2012, overall and stratified by sex, race/ethnicity, and the type of source records (education and health records versus health records only). In addition, this report describes the proportion of children with ASD with a score consistent with intellectual disability on a standardized intellectual ability test, the age at which the earliest known comprehensive evaluation was performed, the proportion of children with a previous ASD diagnosis, the specific type of ASD diagnosis, and any special education eligibility classification., Results: For 2012, the combined estimated prevalence of ASD among the 11 ADDM Network sites was 14.6 per 1,000 (one in 68) children aged 8 years. Estimated prevalence was significantly higher among boys aged 8 years (23.6 per 1,000) than among girls aged 8 years (5.3 per 1,000). Estimated ASD prevalence was significantly higher among non-Hispanic white children aged 8 years (15.5 per 1,000) compared with non-Hispanic black children (13.2 per 1,000), and Hispanic (10.1 per 1,000) children aged 8 years. Estimated prevalence varied widely among the 11 ADDM Network sites, ranging from 8.2 per 1,000 children aged 8 years (in the area of the Maryland site where only health care records were reviewed) to 24.6 per 1,000 children aged 8 years (in New Jersey, where both education and health care records were reviewed). Estimated prevalence was higher in surveillance sites where education records and health records were reviewed compared with sites where health records only were reviewed (17.1 per 1,000 and 10.7 per 1,000 children aged 8 years, respectively; p<0.05). Among children identified with ASD by the ADDM Network, 82% had a previous ASD diagnosis or educational classification; this did not vary by sex or between non-Hispanic white and non-Hispanic black children. A lower percentage of Hispanic children (78%) had a previous ASD diagnosis or classification compared with non-Hispanic white children (82%) and with non-Hispanic black children (84%). The median age at earliest known comprehensive evaluation was 40 months, and 43% of children had received an earliest known comprehensive evaluation by age 36 months. The percentage of children with an earliest known comprehensive evaluation by age 36 months was similar for boys and girls, but was higher for non-Hispanic white children (45%) compared with non-Hispanic black children (40%) and Hispanic children (39%)., Interpretation: Overall estimated ASD prevalence was 14.6 per 1,000 children aged 8 years in the ADDM Network sites in 2012. The higher estimated prevalence among sites that reviewed both education and health records suggests the role of special education systems in providing comprehensive evaluations and services to children with developmental disabilities. Disparities by race/ethnicity in estimated ASD prevalence, particularly for Hispanic children, as well as disparities in the age of earliest comprehensive evaluation and presence of a previous ASD diagnosis or classification, suggest that access to treatment and services might be lacking or delayed for some children., Public Health Action: The ADDM Network will continue to monitor the prevalence and characteristics of ASD among children aged 8 years living in selected sites across the United States. Recommendations from the ADDM Network include enhancing strategies to 1) lower the age of first evaluation of ASD by community providers in accordance with the Healthy People 2020 goal that children with ASD are evaluated by age 36 months and begin receiving community-based support and services by age 48 months; 2) reduce disparities by race/ethnicity in identified ASD prevalence, the age of first comprehensive evaluation, and presence of a previous ASD diagnosis or classification; and 3) assess the effect on ASD prevalence of the revised ASD diagnostic criteria published in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

Prenatal and perinatal exposures to air pollutants have been shown to adversely affect birth outcomes in offspring and may contribute to prevalence of autism spectrum disorder (ASD). For this ecologic study, we evaluated the association between ASD prevalence, at the census tract level, and proximity of tract centroids to the closest industrial facilities releasing arsenic, lead or mercury during the 1990s. We used 2000 to 2008 surveillance data from five sites of the Autism and Developmental Disabilities Monitoring (ADDM) network and 2000 census data to estimate prevalence. Multi-level negative binomial regression models were used to test associations between ASD prevalence and proximity to industrial facilities in existence from 1991 to 1999 according to the US Environmental Protection Agency Toxics Release Inventory (USEPA-TRI). Data for 2489 census tracts showed that after adjustment for demographic and socio-economic area-based characteristics, ASD prevalence was higher in census tracts located in the closest 10th percentile compared of distance to those in the furthest 50th percentile (adjusted RR=1.27, 95% CI: (1.00, 1.61), P=0.049). The findings observed in this study are suggestive of the association between urban residential proximity to industrial facilities emitting air pollutants and higher ASD prevalence., (Copyright © 2015 Elsevier B.V. All rights reserved.)

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.)

Mental disorders among children are described as "serious deviations from expected cognitive, social, and emotional development" (US Department of Health and Human Services Health Resources and Services Administration, Maternal and Child Health Bureau. Mental health: A report of the Surgeon General. Rockville, MD: US Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, and National Institutes of Health, National Institute of Mental Health; 1999). These disorders are an important public health issue in the United States because of their prevalence, early onset, and impact on the child, family, and community, with an estimated total annual cost of $247 billion. A total of 13%-20% of children living in the United States experience a mental disorder in a given year, and surveillance during 1994-2011 has shown the prevalence of these conditions to be increasing. Suicide, which can result from the interaction of mental disorders and other factors, was the second leading cause of death among children aged 12-17 years in 2010. Surveillance efforts are critical for documenting the impact of mental disorders and for informing policy, prevention, and resource allocation. This report summarizes information about ongoing federal surveillance systems that can provide estimates of the prevalence of mental disorders and indicators of mental health among children living in the United States, presents estimates of childhood mental disorders and indicators from these systems during 2005-2011, explains limitations, and identifies gaps in information while presenting strategies to bridge those gaps.

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

Surveillance and epidemiologic research on intellectual disability often do not incorporate adaptive functioning (AF) data. Exclusion of AF data leads to overestimation of the prevalence of intellectual disability, the extent of which is not known. In this study, the authors evaluated the effect of incorporating AF data on overall intellectual disability prevalence according to sociodemographic, economic, and severity characteristics. Between 2002 and 2006, the Metropolitan Atlanta Developmental Disabilities Surveillance Program identified 1,595 8-year-old children who met the study's intellectual disability surveillance-case definition of IQ ≤ 70. AF scores were not available for 9.2% of the case children, specifically those with mild intellectual disability and low socioeconomic backgrounds. Prevalence estimates showed few substantive changes when incorporating AF data. The authors conclude that use of IQ data alone appears to be appropriate for measuring population intellectual disability prevalence.

Background: From 30% to 60% of children with an autism spectrum disorder (ASD) have an IQ measure that falls in the intellectual disability (ID) range. It is not well studied whether, for children within this ASD subgroup, there is variation in the risk for low IQ based on a child's perinatal risk factors., Objective/hypotheses: We assessed whether preterm delivery and term small-for-gestational-age (tSGA) were associated with various measures of cognitive deficit among children with ASDs., Methods: A sample of 1129 singleton children born in 1994 and identified through school and health record review as having an ASD by age 8 years were selected from a U.S. population-based surveillance network. Mean IQ and dichotomous IQ outcomes indicating various levels of ID were examined according to whether a child was preterm (<37 weeks' gestation) or tSGA (term delivery and birth weight <10th percentile for gestational age of a U.S. referent). Results for the total sample and within race-ethnicity/maternal education strata were adjusted for child sex and ASD subtype classification., Results: Mean IQ was significantly (p < .05) lower in children delivered preterm (69.5) than term (74.5) and tSGA (69.3) than term appropriate-for gestational age (75.3). In stratified analyses, the preterm-IQ association was significant only among non-Hispanic white (NHW) children with maternal education at birth of high school or less; adjusted mean IQ was 8 points lower among those delivered preterm (65.4) than term (73.8). Term-SGA was associated with a significant 8-point deficit in adjusted mean IQ (75.5 vs. 83.8) in NHW children with maternal education greater than high school and a 6-point deficit that approached significance (68.4 vs. 74.5, p=0.10) in NHW children with maternal education of high school or less. Non-Hispanic black children in both maternal education groups had significantly lower mean IQs than NHW children with little variation by preterm or tSGA., Conclusions: In children with ASDs, the risk for concurrent ID or IQ deficit is associated with both preterm delivery and tSGA; these associations may vary by race-ethnicity and SES. Further studies of ASD-ID co-occurrence and the effectiveness of intervention strategies should consider both perinatal and sociodemographic factors., (Published by Elsevier Inc.)

Background: We sought to describe autism spectrum disorder (ASD) population characteristics and changes in identified prevalence across 3 time periods., Methods: Children with a potential ASD were identified through records abstraction at multiple sources with clinician review based on Diagnostic and Statistical Manual (DSM-IV-TR) criteria. Multisite, population-based data from the Autism and Developmental Disabilities Monitoring (ADDM) Network were analyzed from areas of Arizona (AZ), Georgia (GA), Maryland (MD), and South Carolina (SC). Participants were 8-year-old children (born in 1992, 1994, or 1996) in 2000, 2002, or 2004 (and children born in 1988 residing in metropolitan Atlanta in 1996) who had been evaluated for a variety of developmental concerns at education and/or health sources., Results: From 2000 to 2004, the identified prevalence of the ASDs per 1,000 8-year-old children showed significant increases of 38% in GA and 72% in MD and a nonsignificant increase of 26% in AZ. ASD prevalence was relatively stable in SC with a nonsignificant decrease of 17%. Males had a higher identified prevalence of ASD in all years. Increases among racial, ethnic, and cognitive functioning subgroups varied by site and surveillance year. More children were classified with an ASD by community professionals over time, except in AZ., Conclusions: There was a trend toward increase in identified ASD prevalence among 8-year-old children who met the surveillance case definition in 3 of the 4 study sites from 2000 to 2004. Some of the observed increases are due to improved ascertainment; however, a true increase in ASD symptoms cannot be ruled out. These data confirm that the prevalence of ASDs is undergoing significant change in some areas of the United States and that ASDs continue to be of urgent public health concern., (Published by Elsevier Inc.)

Autism spectrum disorders (ASDs) represent a range of behavioural phenotypes defined by impaired development in social interaction, communication, imagination, and range of interests or behaviours. The aetiology and epidemiology of these serious developmental disabilities (DDs) are poorly understood. Estimates of the population prevalence of ASDs have varied widely within the US and abroad, with increasing estimates in most of the recent studies. In an effort to improve our understanding of the prevalence, population characteristics and public health impact of these conditions, the Centers for Disease Control and Prevention has funded a multi-site surveillance network for ASDs and other DDs that consists of programmes known as the Autism and Developmental Disabilities Monitoring (ADDM) network which conducts surveillance activities and the Centers for Autism and Developmental Disabilities Research and Epidemiology (CADDRE) which also conducts surveillance in addition to special research studies related to the ASDs. This collaboration will be referred to hereafter as the ADDM Network. The ADDM Network is implementing a multiple-source surveillance programme to determine population prevalence and characteristics of ASDs and other DDs. This paper describes the collaborative efforts and explains the methods in developing this coordinated public health surveillance network to provide an ongoing source of high-quality data on ASDs.

Problem: Autism spectrum disorders (ASDs) encompass a spectrum of conditions, including autistic disorder; pervasive developmental disorders, not otherwise specified (PDD-NOS); and Asperger disorder. Impairments associated with ASDs can range from mild to severe. In 2000, in response to increasing public heath concern regarding ASDs, CDC established the Autism and Developmental Disabilities Monitoring (ADDM) Network. The primary objective of this ongoing surveillance system is to track the prevalence and characteristics of ASDs in the United States. ADDM data are useful to understand the prevalence of ASDs and have implications for improved identification, health and education service planning, and intervention for children with ASDs. Because complete, valid, timely, and representative prevalence estimates are essential to inform public health responses to ASDs, evaluating the effectiveness and efficiency of the ADDM methodology is needed to determine how well these methods meet the network's objective., Reporting Period: 2002., Description of System: The ADDM Network is a multiple-source, population-based, active system for monitoring ASDs and other developmental disabilities. In 2002, data were collected from 14 collaborative sites. This report describes an evaluation conducted using guidelines established by CDC for evaluating public health surveillance systems and is based on examination of the following characteristics of the ADDM Network surveillance system: simplicity, flexibility, data quality, acceptability, representativeness, sensitivity, predictive value positive (PVP), timeliness, stability, data confidentiality and security, and sources of variability., Results and Interpretation: Using multiple sources for case ascertainment strengthens the system's representativeness, sensitivity, and flexibility, and the clinician review process aims to bolster PVP. Sensitivity and PVP are difficult to measure, but the ADDM methodology provides the best possible estimate currently available of prevalence of ASDs without conducting complete population screening and diagnostic clinical case confirmation. Although the system is dependent on the quality and availability of information in evaluation records, extensive quality control and data cleaning protocols and missing records assessments ensure the most accurate reflection of the records reviewed. Maintaining timeliness remains a challenge with this complex methodology, and continuous effort is needed to improve timeliness and simplicity without sacrificing data quality. The most difficult influences to assess are the effects of changes in diagnostic and treatment practices, service provision, and community awareness. Information sharing through education and outreach with site-specific stakeholders is the best mechanism for understanding the current climate in the community with respect to changes in service provision and public policy related to ASDs, which can affect prevalence estimates., Public Health Actions: These evaluation results and descriptions can be used to help interpret the ADDM Network 2002 surveillance year data and can serve as a model for other public health surveillance systems, especially those designed to monitor the prevalence of complex disorders.

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