Peter Bearman, from Columbia University, presented work at the Harvard Inequality Seminar on pathways for the spread of autism. Bearman is most interested in hypotheses about toxic causes of autism (one of his theories of a likely suspect is pesticides, based on a higher prevalence of autism diagnoses for youth who lived along golf fairways, especially along private golf courses, but he has not been able to prove that yet). Bearman and collaborators hoped to use incidence of autism among Hispanics in the pesticide-rich Central Valley to prove this, but hispanic autism rates were too highly volatile depending on whether autism diagnoses could put families at risk for deportation or being reported to the INS.
What Bearman did present on was findings resulting from pairing millions of birth records with autism diagnoses in California; he and coauthors found that over 50% of the increase in autism in California in recent years may be spread through social networks and proximity to other autistically-diagnosed youth.
Bearman does not know friendship networks specifically but does know place at birth or during various years of childhood. He finds, controlling for environmental factors and risk factors (like age of mother at birth, gender, education of mother, etc.) that people who lived within 250 meters (basically the length of a cul-de-sac) of someone with an autism diagnosis who shared a social institution (mall, park or preschool) were 38% more likely to be diagnosed as autistic in the following year whereas those who were the same distance apart from someone diagnosed with autism who shared a non-social institution (cemetary, radiation specialist, dentist, etc.) were not any more likely to be diagnosed with autism.
The only persistent cluster in California for higher incidence of autism from 2000-2005 by place of birth (controlling for all known factors) was one in north Hollywood Hills, near Northridge. Bearman suspects it was an environmental risk that people were exposed to (a nuclear meltdown that occurred there in 1964) that increased number of autism diagnoses slightly, followed by a four-decade-long cascade caused by social processes: parents who lived close to someone diagnosed with autism were sensitized to these factors and were more likely to diagnose their own child as autistic and work with doctors to verify this diagnosis. The biggest increases were at opposite ends of the spectrum: both among high-functioning individuals and similarly among low-functioning individuals (who pushed doctors for an autism-mental retardation classification, which offered greater access to services and resources, than a sole mental retardation classification). The diagnosis of autism was generally done between the ages of 3 and 5 and done only on the basis of self-presentation and parental explanation. These social networks helped parents find physicians and navigate the California bureaucratic process. He doesn’t think that it was the influence of doctors since closer distance from a doctor that had diagnosed children as autistic did not predict these children being more likely to be diagnosed as autistic themselves. (And density of pediatricians did not have an effect.)
Bearman ducked a question of whether this outcome was a desirable one. For the low-functioning autistic children, they would have gotten special ed services regardless of whether they were classified solely as mentally retarded or as autistic-MR, but for the high-functioning children classified as having autism, they would have gotten more in the way of special ed services, presumably at the expense of all other children (as special ed costs absorbed a higher percentage of the budget). Bearman focused on the benefit to parents of children who got a high-functioning autistic diagnosis and didn’t address whether this concentrated school resources on a small number of high functioning “autistic” children at the possible expense of other same age children who were not diagnosed with special education needs. He said that children diagnosed at age 3 with autism do not seem to show any higher final performance outcomes than children diagnosed with autism at age 6; the latter group catches up in outcomes to the earlier-diagnosed autistic children by age 9. He does not believe there is any kind of objective standard of which of these higher-functioning kids is truly autistic or not.
One person asked whether the Internet would obviate the effect of this physical proximity. Bearman thinks it will not and that we use the Internet for decisions like choosing a restaurant or finding the cheapest place to buy something but not for picking a doctor or navigating bureaucracy. That geographic proximity continues to play a role in 2000 or 2004 is testament to the staying power of localized real interactions in the age of the Internet.
Bearman notes that there is no relationship between vaccine use as children and autism, but notes that the spread of Autism Advocacy Organizations (which spread as the number of individuals in a zipcode who are diagnosed with autism) is associated with a higher refusal of vaccines. Thus he expects that in the future we will see a relationship between these advocacy organizations and the downstream increase in mumps, rubella, measles, etc. as more children opt out of these vaccines.
Bearman noted that in recent years, the rates of increase in California among higher-SES households has slowed, presumably he remarked because such families now see other diagnoses that offer a better array of services for their special need children, and because as the SES-gradient has declined, an autism diagnosis conveys less status.
To read some of this work, see for example “Social Influence and the Autism Epidemic“, American Journal of Sociology, 115(5): 1387-14343 (2010).