Autism spectrum disorder reporting in lower socioeconomic neighborhoods.
Autism surveillance systematically misses children in Hispanic and lower-education neighborhoods, so BCBAs must actively screen these families rather than relying on previous records.
01Research in Context
What this study did
McIntyre et al. (2017) looked at how well autism cases are found in different neighborhoods. They checked both mom's education level and the education level of the whole neighborhood. They also looked at how many Hispanic families lived in each area.
The study wanted to see if some neighborhoods miss more autism cases than others.
What they found
Neighborhoods with more educated moms and more educated neighbors found autism better. But neighborhoods with more Hispanic families found fewer cases, even when moms had the same education.
The gap wasn't because autism happens less in these areas. It was because the system misses kids who live there.
How this fits with other research
Pettygrove et al. (2013) found the same problem first. Kids found only through schools got diagnosed almost a year later than kids seen by doctors. This matches what McIntyre et al. (2017) found about education gaps.
Byers et al. (2013) showed Latino children get diagnosed later and receive fewer services. The new study adds that even the neighborhood's Hispanic makeup matters, not just the child's ethnicity.
Hutchins et al. (2020) extended this to language barriers. They found Texas schools report fewer autism cases in non-English-speaking homes. This helps explain why Hispanic neighborhoods show lower numbers - language makes it harder to get identified.
Why it matters
When you screen a child, ask about both mom's education and the neighborhood. If the family lives in a mostly Hispanic area or mom didn't finish high school, the child might have been missed before. Don't trust a clean record - screen anyway. Share Spanish materials and build trust with Hispanic families so they complete the process. Early identification depends on you seeing past these systemic blind spots.
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02At a glance
03Original abstract
Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.02-1.09). Results from our examination of sociodemographic factors of tract populations from which cases were drawn also showed that after controlling for other covariates, statistical significance remained for associations between optimal ascertainment and percentage of Hispanic residents (adjusted odds ratio = 0.93, 95% confidence interval = 0.88-0.99) and percentage of residents with at least a bachelor's degree (adjusted odds ratio = 1.06, 95% confidence interval = 1.01-1.11). We identified sociodemographic factors associated with autism spectrum disorder prevalence estimates including race, ethnicity, education, and income. Determining which specific factors influence disparities is complicated; however, it appears that even in the presence of education, racial and ethnic disparities are still apparent. These results suggest disparities in access to autism spectrum disorder assessments and special education for autism spectrum disorder among ethnic groups may impact subsequent surveillance.
Autism : the international journal of research and practice, 2017 · doi:10.1177/1362361316650091