An Exploratory Study of Socioeconomic Status, Air Pollution, and 13 Other Variables as Predictors of U.S. State...

Area of Science:

• Environmental Health
• Public Health
• Epidemiology

Background:

• Autism spectrum disorder (ASD) prevalence varies significantly across U.S. states.
• Identifying predictors of ASD prevalence at the aggregate level is crucial for public health interventions.
• Previous research has identified numerous individual-level predictors, but their predictive power for state-level prevalence is less understood.

Purpose of the Study:

• To determine which of 14 selected individual-level predictors are associated with autism spectrum disorder (ASD) prevalence rates in U.S. states.
• To examine the predictive power of these factors with and without statistical control for socioeconomic status (SES).
• To identify key aggregate-level factors influencing ASD prevalence.

Main Methods:

• Exploratory study using 2017 state-level ASD prevalence rates.
• Regression analyses were performed on 15 potential predictors, including SES, race, personality traits, IQ, urbanization, air pollution, healthcare access, and policy variables.
• Analyses included controlling for SES and examining predictors both individually and simultaneously.

Main Results:

• Initially, 12 of 15 predictors correlated significantly with ASD rates; however, only race, personality, urbanization, air pollution, PN-3 policy, and maternal age remained significant when SES was controlled.
• In a simultaneous regression, only SES and air pollution emerged as significant predictors of ASD prevalence.
• SES and air pollution together explained 55.7% of the variance in state ASD prevalence rates, with higher levels of both associated with higher ASD prevalence.

Conclusions:

• Socioeconomic status (SES) and air pollution are significant aggregate-level predictors of autism spectrum disorder (ASD) prevalence.
• These findings suggest that both socioeconomic factors and environmental exposures, such as air pollution, warrant consideration in understanding ASD prevalence.
• The study highlights the importance of considering SES and air pollution in both aggregate-level and individual-level analyses related to autism.