خوشه فضایی تولدهای اوتیسم و اشاره تشخیص به محرک های زمینه ای افزایش شیوع

Autism prevalence has risen dramatically over the past two decades in California. Although often suggested to have been crucial to the rise of autism, environmental and social contextual drivers of diagnosis have not been extensively examined. Identifying the spatial patterning of autism cases at birth and at diagnosis can help clarify which contextual drivers are affecting autism's rising prevalence. Children with autism not co-morbid with mental retardation served by the California Department of Developmental Services during the period 1992–2005 were matched to California's Birth Master Files. We search for spatial clusters of autism at time of birth and at time of diagnosis using a spatial scan approach that controls for key individual-level risk factors. We then test whether indicators of neighborhood-level diagnostic resources are associated with the diagnostic clusters and assess the extent of clustering by autism symptom severity through a multivariate scan. Finally, we test whether children who move into neighborhoods with higher levels of resources are more likely to receive an autism diagnosis relative to those who do not move with regard to resources. Significant birth and diagnostic clusters of autism are observed independent of key individual-level risk factors. While the clusters overlap, there is a strong positive association between the diagnostic clusters and neighborhood-level diagnostic resources. In addition, children with autism who are higher functioning are more likely to be diagnosed within a cluster than children with autism who are lower functioning. Most importantly, children who move into a neighborhood with more diagnostic resources than their previous residence are more likely to subsequently receive an autism diagnosis than children whose neighborhood resources do not change. We identify birth and diagnostic clusters of autism in California that are independent of individual-level autism risk factors. Our findings implicate a causal relationship between neighborhood-level diagnostic resources and spatial patterns of autism incidence but do not rule out the possibility that environmental toxicants have also contributed to autism risk.

Autism prevalence has risen dramatically over the past two decades (Mitka, 2010). In California, the increase has been precipitous – over 600% from the 1992 to 2002 birth cohorts (Keyes et al., 2011). Similar rates of increase have been observed elsewhere in the United States and in other industrialized countries (Baio, 2002; Madsen et al., 2003). Numerous biological, environmental and social factors have been implicated in the rise of autism, but there is no general consensus as to the roles that each have played. The majority of empirical studies have focused on potential genetic causes of autism (Abrahams & Geschwind, 2008) and other individual level risk factors, such as male sex, advanced parental age, prenatal and perinatal complications, and maternal exposures to viruses and other teratogens (Kolevzon, Gross, & Reichenberg, 2007; Patterson, 2009). Although often suggested to have been crucial to the rise of autism, environmental and social contextual drivers of diagnosis, such as local environmental toxicants (Windham, Zhang, Gunier, Croen, & Grether, 2006), diagnostic accretion (King & Bearman, 2009), legislative change (Fountain & Bearman, 2011), neighborhood level resources (King & Bearman, 2011) and increased awareness (Liu, King, & Bearman, 2010), have been studied less extensively. This article utilizes administrative data from California to consider how identifying the spatial patterning of autism cases at birth and at diagnosis can inform the study of contextual drivers of autism. We have previously identified a spatial cluster of autism cases at birth (henceforth “birth cluster”) located in the West Hollywood (Mazumdar, King, Liu, Zerubavel, & Bearman, 2010). Given that not all families live at the same residences from the time of their children's births to diagnoses, examining the spatial clustering of autism at these two moments in time can help disentangle the contextual mechanisms involved. For example, it is possible for a birth cluster to form as a result of the neighborhood-level clustering of an autism risk factor that is particularly relevant around the time of birth, such as an environmental toxicant. Meanwhile, a different set of mechanisms that are independent of those generating birth clusters could be responsible for clustering at diagnosis. Such “diagnostic clusters” could be observed if parents who suspect that their children may have autism select neighborhoods based on available services or neighborhoods that parents select to move to are associated with an increased risk of acquiring an autism diagnosis. In California, salient neighborhood-level characteristics that could be associated with an increased risk of autism diagnosis include: socioeconomic status (SES), pediatrician density, advocacy organization density, and spending by the Department of Developmental Services (DDS). Children residing in high SES neighborhoods are at greater risk of receiving an autism diagnosis (King & Bearman, 2011; Liu et al., 2010), a finding that is consistent with the effect of neighborhood SES on a wide range of other health outcomes. For example, neighborhood SES is a predictor of the stage at which cancer is diagnosed (Breen & Figueroa, 1996; Shipp et al., 2005). The exact mechanisms underlying the associations between neighborhood SES and health outcomes are debated, but a likely component is that neighborhood SES is a good proxy for local resources and the availability of health-related information (Eng et al., 1998). Meanwhile, the number of pediatricians in a neighborhood provides a more specific measure of available resources. There is extensive literature that shows that physician density (Ananthakrishnan, Hoffmann, & Saeian, 2010; Léonard, Stordeur, & Roberfroid, 2009; Roll, 2012) is associated both with the timely diagnosis of certain disorders and with increased consumption of medical services (Menken & Sheps, 1985). While a sufficient supply of pediatricians may be able to address the need for diagnostic services, advocacy organizations are key to spreading awareness of symptoms among caregivers. An increased density of advocacy organizations should, therefore, be associated with an increased likelihood of autism diagnosis in a given neighborhood. In addition, advocacy organizations can influence legislation and funding. Lastly, California's DDS coordinates autism services through a network of 22 regional centers. Residents of California are assigned to regional centers by zip code, and services are available to children diagnosed with autism and other mental disorders free of charge. It has been argued that the availability of free services may encourage parents whose children exhibit mild autism symptoms to actively pursue a diagnosis (Zarembo, 2011). Yet, variations in regional center funding may increase or decrease this incentive differentially by area. Together, the above characteristics capture neighborhood resources from different perspectives associated with access to diagnostic services and awareness of diagnostic symptoms.