Autism Diagnosis Marginally Affected by IncomeLast Updated: April 25, 2011. As the prevalence rate of autism slowed, socioeconomic status seems to have become less of an impact on the likelihood of diagnosis than during times of increasing prevalence, according to a study published in the April issue of the American Sociological Review.
MONDAY, April 25 (HealthDay News) -- As the prevalence rate of autism slowed, socioeconomic status (SES) seems to have become less of an impact on the likelihood of diagnosis than during times of increasing prevalence, according to a study published in the April issue of the American Sociological Review.
Marissa D. King, Ph.D., from Yale University in New Haven, Conn., and Peter S. Bearman, Ph.D., from Columbia University in New York City, analyzed birth and diagnostic records for 4,906,926 children born in California between 1992 and 2000 to identify those diagnosed with autism. They examined the individual and community resources linked with the likelihood of an autism diagnosis, and variations over time.
The investigators found that the prevalence of autism increased significantly from 29 per 10,000 in 1992 to 49 per 10,000 in 2000, with 18,731 children diagnosed with autism during this period. Individual-level factors, such as low birth weight and higher parental economic resources and education were consistently associated with increased chances of diagnosis. Community economic resources affected autism diagnosis when prevalence rates were rapidly increasing; but, over time, as the prevalence decreased the community SES gradient weakened. The neighborhood SES effects remained strong for children born to parents with few economic resources, but were negligible for children born to educated parents and children not receiving Medi-Cal. The diagnostic rate of children born to wealthy parents in wealthy neighborhoods was higher initially but has remained stable since 1994, whereas prevalence rates among children in poor neighborhoods have increased steadily at a slower rate.
"Within this framework, it is easy to see how neighborhoods can dynamically shape health outcomes," the authors write.
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