The impact of surveillance method and record source on autism prevalence: collaboration with Utah Maternal and Child

Judith Pinborough-Zimmerman1, Deborah Bilder, Robert Satterfield

  • 1Department of Psychiatry, University of Utah, Salt Lake City, UT, USA. judith.zimmerman@hsc.utah.edu

Insights

Autism spectrum disorder (ASD) prevalence in Utah varied significantly based on surveillance methods. Collaboration between health and education sectors is crucial for addressing the needs of children with ASD.

Area of Science:

  • Pediatric Health
  • Public Health Surveillance
  • Autism Spectrum Disorders (ASDs)

Background:

  • Increasing identification of children with autism spectrum disorders (ASDs) in Utah necessitates understanding prevalence and characteristics.
  • Maternal Child Health (MCH) programs require data to develop effective prevention, screening, and education strategies for ASDs.
  • Existing surveillance methods may impact reported ASD prevalence rates.

Purpose of the Study:

  • To describe the Utah autism registry developed in partnership with state MCH programs.
  • To assess how different record-based surveillance methods influence state ASD prevalence rates.
  • To examine case characteristics across different ascertainment methods.

Main Methods:

  • Utilized data from 212 ASD cases among 26,217 eight-year-olds in three Utah counties in 2002.
  • Employed two record-based surveillance approaches: administrative diagnoses and abstraction with clinician review.
  • Analyzed data from education, health, and combined record sources to determine ASD prevalence and case characteristics.

Main Results:

  • ASD prevalence varied significantly (P < .05) from 3.2 to 7.5 per 1000 children, depending on the surveillance method and record source.
  • Male-to-female ratios ranged from 4.7:1 to 6.4:1.
  • No significant differences were observed in 18 of 23 case characteristics, including socioeconomic factors and age at diagnosis, between the two ascertainment methods.

Conclusions:

  • Record-based surveillance methods and data sources significantly impact reported ASD prevalence rates.
  • Effective ASD management requires integrated support from both education and health sectors, alongside MCH program collaboration.
  • Continued monitoring and research are essential to address the growing needs of children and families affected by ASDs.

Related Concept Videos

Autism Spectrum Disorder01:19

Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
Modeling in Therapy01:26

Modeling in Therapy

Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...