Department of Public Health Sciences, School of Medicine, and Medical Investigations of Neurodevelopmental Disorders Institute, University of California-Davis, One Shields Avenue, Davis, CA 95616, USA.
Autism Res. 2010 Feb;3(1):19-29. doi: 10.1002/aur.110.
Prenatal environmental exposures are among the risk factors being explored for associations with autism. We applied a new procedure combining multiple scan cluster detection tests to identify geographically defined areas of increased autism incidence. This procedure can serve as a first hypothesis-generating step aimed at localized environmental exposures, but would not be useful for assessing widely distributed exposures, such as household products, nor for exposures from nonpoint sources, such as traffic. Geocoded mothers' residences on 2,453,717 California birth records, 1996-2000, were analyzed including 9,900 autism cases recorded in the California Department of Developmental Services (DDS) database through February 2006 which were matched to their corresponding birth records. We analyzed each of the 21 DDS Regional Center (RC) catchment areas separately because of the wide variation in diagnostic practices. Ten clusters of increased autism risk were identified in eight RC regions, and one Potential Cluster in each of two other RC regions.After determination of clusters, multiple mixed Poisson regression models were fit to assess differences in known demographic autism risk factors between the births within and outside areas of elevated autism incidence, independent of case status.Adjusted for other covariates, the majority of areas of autism clustering were characterized by high parental education, e.g. relative risks >4 for college-graduate vs. nonhigh-school graduate parents. This geographic association possibly occurs because RCs do not actively conduct case finding and parents with lower education are, for various reasons, less likely to successfully seek services.
产前环境暴露是正在探索的与自闭症相关的风险因素之一。我们应用了一种新的程序，结合多个扫描簇检测测试，以确定自闭症发病率升高的地理位置定义区域。该程序可作为针对局部环境暴露的第一步假设生成步骤，但不适用于评估广泛分布的暴露，如家庭产品，也不适用于非点源暴露，如交通。对加利福尼亚州 1996-2000 年出生记录中的 2453717 名母亲住所进行了地理编码，包括加利福尼亚州发育服务部 (DDS) 数据库中记录的 9900 例自闭症病例，这些病例通过 2006 年 2 月与相应的出生记录相匹配。由于诊断实践差异很大，我们分别分析了 21 个 DDS 区域中心 (RC) 集水区。在 8 个 RC 区域中发现了 10 个自闭症风险增加的集群，在另外 2 个 RC 区域中各发现了 1 个潜在集群。在确定集群后，针对自闭症的已知人口统计学风险因素，对集群内和集群外出生的病例进行了多混合泊松回归模型拟合，以评估发病率升高地区之间的差异，病例状态除外。调整其他协变量后，大多数自闭症聚类区域的父母教育程度较高，例如大学毕业的父母与非高中毕业的父母相比，相对风险> 4。这种地理关联可能是因为 RCs 不会主动进行病例发现，而教育程度较低的父母由于各种原因，不太可能成功寻求服务。
