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CDC Report Reveals Rise in Autism Rates in 2022 with Significant Changes Across Race, Ethnicity, and Sex

April 17, 2025
in Medicine
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In 2022, a comprehensive new report released by the Centers for Disease Control and Prevention (CDC) has shed unprecedented light on the prevalence and early identification of autism spectrum disorder (ASD) among children in the United States. This latest surveillance effort, which involved data collection from sixteen geographically and demographically diverse study sites nationwide, included valuable insights from Maryland, orchestrated through leading researchers at the Johns Hopkins Bloomberg School of Public Health’s Wendy Klag Center for Autism and Developmental Disabilities. Their findings provide a crucial update on the evolving epidemiology of autism, underscoring important demographic shifts and advancements in early detection.

The CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network, which has monitored autism prevalence in 8-year-old children since 2000 and expanded to include 4-year-olds in 2018, reported that in 2022, the overall autism prevalence among 8-year-olds across the network reached approximately 3.2%, equating to 1 in 31 children. Within Maryland’s surveillance area, which encompasses Baltimore, Carroll, Cecil, Harford, and Howard counties, the prevalence among 8-year-old children was slightly lower, estimated at 2.6% or 1 in 38 children. The prevalence among 4-year-olds in Maryland showed a comparable 2.4%, or 1 in 41 children, reinforcing the encouraging trend toward earlier diagnosis observed in recent years. This convergence of prevalence rates between the two age cohorts signifies meaningful progress for the early identification and intervention of autism spectrum disorder.

Autism spectrum disorder is characterized by core deficits in social communication and interaction, accompanied by restrictive and repetitive behaviors and interests. Diagnostic criteria have evolved over time, advancing understanding of autism’s heterogeneous presentation. The ADDM Network’s methodical data collection leverages multidisciplinary sources, including health, education, and early intervention records, to capture a more inclusive picture of ASD prevalence within defined population areas. However, the CDC emphasizes that the ADDM Network is not a nationally representative sample, and site-specific variability reflects differences in demographic compositions, diagnostic practices, and community awareness.

A particularly notable finding from the Maryland study site relates to racial and ethnic disparities in autism diagnosis rates. Black children residing in the five-county area exhibited the highest prevalence, with 1 in 27 8-year-old children identified with autism. This is followed closely by Asian/Pacific Islander children at 1 in 32, multiracial children at 1 in 34, Hispanic children at 1 in 35, and white children at 1 in 52. Such findings mark an important departure from previous narratives that predominantly associated autism diagnosis with white populations, indicating that autism affects a broad spectrum of racial and ethnic groups. These disparities underscore the critical need for culturally sensitive outreach and equitable access to diagnostic services and interventions.

Another significant demographic dimension explored in the CDC report concerns sex differences in autism prevalence. Consistent with past surveillance data, boys were found to be substantially more likely than girls to be diagnosed with autism. Across all 16 sites, the ratio stands at approximately 3.4 boys for every 1 girl among 8-year-olds, and 2.8 boys for every 1 girl among 4-year-olds. Notably, Maryland’s data reveal an even higher ratio of 3.9 boys per girl among 8-year-olds, though this disparity narrows somewhat among younger children, suggesting improvements in identifying autism in girls at younger ages. This trend raises important questions about the influence of sex-specific phenotypic expression of ASD and potential diagnostic biases, prompting ongoing research into tailored identification strategies.

The report highlights the first time that over 1% of 8-year-old girls in Maryland were identified as having autism, with a prevalence rate of 1 in 93 girls. This milestone reflects increased recognition and understanding of how autism manifests differently in females, who may present more subtle or varied symptom profiles compared to males. These nuanced symptomatologies often contribute to underdiagnosis or delayed diagnosis in girls, so rising rates may indicate success in refining diagnostic criteria and training clinicians to capture the female autism phenotype more effectively.

One of the most encouraging takeaways from this rigorous surveillance is the evidence of earlier autism identification, which has important implications for public health and clinical intervention strategies. Children who turned 4 years old in 2022 in Maryland were reported to be 1.8 times more likely to be identified with autism by 48 months of age compared to the cohort of 8-year-olds monitored in the same year. This closing gap between the ages at identification reflects broad systemic improvements in screening protocols, provider awareness, and parental education targeting earlier developmental milestones.

The CDC encourages parents and healthcare providers to maintain ongoing monitoring of developmental progress from birth until age 5 to facilitate timely autism screening and diagnosis. Resources such as free checklists and educational materials are publicly available through the CDC’s “Learn the Signs. Act Early.” initiative, which strives to empower families and professionals alike to recognize early signs of developmental delays and secure interventions sooner. Early diagnosis is crucial, as it affords the possibility of implementing supportive therapies during critical periods of brain development, thereby optimizing long-term outcomes for affected children.

While the overall prevalence of autism is increasing, the variability observed between sites in the ADDM Network is attributable to numerous factors, including differences in healthcare access, cultural attitudes, and diagnostic infrastructure. For instance, within the 16 sites reporting in 2022, prevalence ranged widely from under 1% in Laredo, Texas, to an alarming high of 5.3% in California, indicating that autism detection is influenced by region-specific characteristics. These variations highlight the challenges inherent in creating a uniform national surveillance system and point to the necessity for localized public health strategies.

From a technical standpoint, the ADDM Network employs a rigorous methodology that combines record review and abstraction, followed by clinical coding and confirmation by trained experts. This dual-phase methodology ensures high specificity in ASD case identification, while allowing for robust cross-site comparisons in epidemiological trends. This methodological transparency is vital for interpreting surveillance data within the broader context of changing diagnostic thresholds and evolving healthcare landscapes.

The Maryland center’s vigilant monitoring of autism, spanning over two decades for 8-year-olds and more recently including 4-year-olds, represents a vital resource for understanding both longstanding and emerging trends. Researchers like Dr. Christine Ladd-Acosta and Dr. Elise Pas emphasize the importance of translating epidemiological findings into practical frameworks for early screening, inclusive services, and tailored interventions. The ultimate goal is to equip children with ASD and their families with accessible and effective supports that foster development, inclusion, and improved quality of life.

Looking forward, ongoing surveillance through the ADDM Network, now expanded from 11 to 16 sites, continues to be instrumental in capturing the complex epidemiology of autism in the United States. The collaborative efforts between federal agencies, academic research institutions, and local jurisdictions create a nuanced picture that informs policy, clinical practice, and community engagement. As the field advances, integrating genetics, environmental factors, and health services research will further elucidate the multifactorial nature of autism and drive innovations in early diagnosis and personalized care.

In conclusion, the 2022 CDC report, with pivotal contributions from the Johns Hopkins Bloomberg School of Public Health’s Maryland site, depicts a dynamic landscape in autism prevalence and identification. Increased rates among diverse racial and ethnic populations, rising recognition among girls, and significant strides toward earlier diagnosis collectively represent critical progress. These findings challenge outdated stereotypes and advocate for sustained investment in screening, public awareness, and support services tailored to the varied needs of children with autism and their families nationwide.


Subject of Research: Autism Spectrum Disorder prevalence and early identification among children aged 4 and 8 years in the United States, with a focus on Maryland.

Article Title: Prevalence and Early Identification of Autism Spectrum Disorder Among Children Aged 4 and 8 Years—Autism and Developmental Disabilities Monitoring Network, 16 Sites, United States, 2022

News Publication Date: April 14, 2024

Web References:
https://www.cdc.gov/mmwr/volumes/74/ss/ss7402a1.htm?s_cid=ss7402a1_w
http://www.cdc.gov/ActEarly

References: CDC Autism and Developmental Disabilities Monitoring (ADDM) Network 2022 surveillance report

Keywords: Autism, Autism Spectrum Disorder, Early Identification, Epidemiology, Developmental Disabilities, Prevalence, CDC, ADHD Network, Maryland Autism Surveillance, Racial and Ethnic Disparities in Autism

Tags: advancements in autism detectionautism monitoring networkautism prevalence statisticsautism rates by age groupautism spectrum disorder epidemiologyCDC autism report 2022children's health statisticsdemographic shifts in autism ratesearly identification of autismMaryland autism surveillance datapublic health implications of autism trendsracial and ethnic disparities in autism
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