Testing a Tailored Social-Ecological Model for Autism Spectrum Disorders

Area of Science:

• Public Health
• Pediatrics
• Social Epidemiology

Background:

• Autism Spectrum Disorder (ASD) diagnosis rates and contributing factors require nuanced understanding.
• Social-ecological models offer a framework to explore multifaceted influences on health outcomes.

Purpose of the Study:

• To develop and test a tailored social-ecological model for Autism Spectrum Disorder (ASD).
• To investigate the relationships between individual, family, and community variables and ASD diagnosis in a national sample.

Main Methods:

• Utilized the 2016/2017 National Survey of Children's Health data.
• Employed iterative multivariable logistic regressions for individual, family, and community/neighborhood variables.
• Conducted state-level fixed effects regression to analyze macro-level policy influences.

Main Results:

• Female gender, higher disability severity, public or mixed insurance, and lower household income were associated with higher odds of ASD diagnosis.
• Females had significantly lower odds of diagnosis compared to males (aOR: 0.27).
• Children with co-occurring disabilities had 7.61 times higher odds of ASD diagnosis.

Conclusions:

• ASD diagnosis patterns are influenced by individual and family characteristics.
• Environmental factors demonstrate a relationship with reported ASD diagnoses.
• Healthcare professionals should consider environmental context during ASD assessments.