Trends in the epidemiology of autism spectrum disorders, 2000-2016 in a large and diverse metropolitan area
Creators: name: Shenouda, Josephine
Publisher: name: No Publisher Supplied
Year: 2022

description: Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental disorder characterized by social impairments and restricted and/or repetitive behaviors. Delays in early development or regression in developmental milestones are evident by 18-months, and ASD can be reliably diagnosed by age 2-years. To date, the etiology of ASD remains unclear, however, the cause of ASD is likely multifactorial, and many researchers agree there is likely an interaction between genetic and environmental factors. Over the past several decades, ASD prevalence has risen multifold worldwide. In 2000, the Centers for Disease Control and Prevention (CDC) initiated a multi-state, population-based, active surveillance system, Autism and Developmental Disabilities Monitoring (ADDM) Network, to track ASD prevalence among 8-year-old children. In the initial surveillance cycle, ADDM Network reported ASD prevalence of 6.7 per 1,000 8-year-old children for children born in 1992, and by 2018, ASD estimates had risen to 23.0 per 1,000 for children born in 2010, rising 3.4-fold during this period. With rising ASD estimates, early identification and intervention have become a public health priority. However, the heterogeneity of ASD expression presents a considerable challenge to research on ASD etiology and interventions. Furthermore, mounting evidence demonstrates race-based and socioeconomic inequalities in ASD identification and access to early intervention services, worsening the outcomes for disadvantaged children. Using population based ADDM Network surveillance data from New Jersey across seven cycles of surveillance, this dissertation examined three trends in ASD prevalence and access to early intervention program (EIP) services and further examined variation in trends by sociodemographic factors including sex, race/ethnicity and socioeconomic status (SES).The first aim (Aim 1) of the dissertation was to examine local variation in ASD prevalence in public schools in New Jersey and to examine if ASD prevalence estimates vary by sex, race/ethnicity, SES, and school district size at the county and school district level in the most recent surveillance cycle, 2016. The second aim (Aim 2) assessed temporal trends in ASD with and without intellectual disability (ID) prevalence estimates by sociodemographic factors using seven surveillance cycles from 2000-2016. The third aim (Aim 3) of the dissertation used five surveillance cycles from 2006-2016 to examine the association between sociodemographic factors and participation in EIP, a federally mandated program serving ages 0-36 months children with disabilities. For Aim 1, local variations in ASD prevalence estimates were observed at the county level and school district level and differed by sex, race/ethnicity, SES and school district size. For example, while overall ASD prevalence across the participating counties was 36 per 1,000, in Ocean County, prevalence was 54 per 1,000. In 1 in 5 school districts, estimates were greater than 50 per 1,000, indicating higher than expected prevalence in multiple communities. As expected, ASD prevalence was significantly higher among males than females. Additionally, prevalence estimates among Hispanic children were significantly lower compared to their non-Hispanic White peers indicating possible disparities in ASD identification among Hispanic children. Unexpectedly, mid-SES districts had the highest ASD prevalence estimates; US studies have shown a positive relationship between SES and ASD prevalence. Analysis of the school district size in relation to ASD prevalence indicated that larger school districts were likely better at identification of ASD as they had the highest ASD prevalence estimates. In Aim 2, ASD prevalence varied by sociodemographic factors when considering intellectual ability. From 2000-2016, ASD without ID increased by 500% while ASD with ID increased by 200%. While increases in ASD prevalence are likely driven by better identification of ASD among children with borderline to average intellectual ability, race-based and socioeconomic disparities in ASD without ID identification were evident. Overall, temporal trends showed that across the study period, the majority of children with ASD had borderline to average intellectual ability. In Aim 3, we observed that only half of the ASD population participated in EIP programs. However, children from recent birth cohorts were more likely to participate in EIP compared to older birth cohorts, indicating improvement in EIP participation overtime. However, race-based and socioeconomic inequalities were evident in EIP participation. Non-Hispanic Black children were 40% less likely to participate in EIP compared to their White peers, and children residing in affluent areas were 60% more likely to participate in EIP as compared to children residing in underserved areas. Tracking ASD trends from defined and diverse populations can identify sociodemographic disparities and provide vital information on overall shifts in community health over time. The aims and findings of this dissertation document recent trends in ASD prevalence at the local level and sociodemographic patterns when considering intellectual ability. Furthermore, this dissertation provides the first analysis of EIP participation among children with ASD.