Author(s) :

Suhui Kim.

Volume/Issue :

Abstract :

This study examined national and regional trends in autism spectrum disorder (ASD) prevalence in the United States. Publicly available data from the Centers for Disease Control and Prevention (CDC) Autism and Developmental Disabilities Monitoring (ADDM) Network were used for the data analysis. A population-level descriptive surveillance analysis was conducted using site-year observations of reported ASD prevalence per 1,000 8-year-old children from the early 2000s through the early 2020s. To summarize overall prevalence patterns, descriptive statistics were used. In addition, a linear time-trend model was generated and applied to quantify temporal change across reporting cycles. The analysis demonstrated a clear and sustained increase in reported ASD prevalence over time, with significant geographic variation across surveillance areas. There was a right-skewed distribution of prevalence estimates, indicating that a smaller number of regions showed significantly higher reported rates, while many regions reported moderate prevalence levels. In the time-trend model, ASD prevalence rose substantially across reporting years, supporting the interpretation that the increase in reported diagnoses reflects a long-term structural trend rather than isolated fluctuations. Geographic differences were interpreted with reference to prior studies suggesting that socioeconomic conditions, healthcare access, diagnostic capacity, and public awareness may contribute to variation in identification patterns across regions. Since the reproducible quantitative analysis was based on ADDM prevalence observations rather than a fully merged socioeconomic dataset, the findings in this study and their interpretations should be understood as ecological and descriptive rather than causal. Overall, the results emphasize the importance of considering structural influences when interpreting ASD prevalence trends and geographic disparities.