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In their article, Waldman et al1 present a novel hypothesis that examines the association between autism and environmental factors using ecologic data from California, Oregon, and Washington. Their findings suggest a positive association between mean annual precipitation and autism prevalence at the county level. Although the authors address confounding, we believe they should have better addressed the potential effect of confounding by county-level urbanicity and the potential for cross-level bias (ecologic fallacy) when interpreting their results.
First, inadequate control for urbanicity may have confounded the county-level estimates. Most of the counties with the highest prevalence of autism and annual precipitation are also the most populated counties. Weiss2 has noted that agencies in the western parts of Oregon and Washington may have identified a greater proportion of children with autism than their eastern counterparts. Urbanicity has a strong association with autism at the ecologic level; urban school districts exhibit an autism prevalence 5 times as high as that in rural districts.3 High correlations between urbanicity, autism, and rainfall in these data warrant careful control and specification of county-level urban status. Greenland and Robins4 demonstrated that misspecification of confounders in ecologic studies can result in substantial changes in the effect estimate of interest. Waldman et al used log-transformed county population as a proxy for county-level urbanicity. It is unlikely that county population completely characterizes the degree of urbanicity and access that residents have to diagnostic and medical services. Given the relatively small effect size that annual precipitation had on autism prevalence, it is possible that better control for urbanicity would have eliminated any observed association.
Second, the authors gave individual-level interpretation to their county-level estimates without addressing the ecologic fallacy. Even with perfect control of county-level urbanicity, the potential for cross-level bias still exists. Within-group heterogeneity of county-level urbanicity and annual precipitation will not be captured solely by county-level information.5 Urbanicity likely acts as a proxy for neighborhood and individual-level factors, including better access to diagnostic and medical services. Only studies that can collect exposure information and control for confounders, such as accessibility to diagnostic services, at the individual level can lead to causal conclusions. Thus, we are concerned about the authors' conclusion that autism prevalence would be reduced by 30% to 40% if the mean annual precipitation were reduced by 35.6 inches. Such interpretation implies that causation at the individual level has been established, which is certainly outside the realm of this ecologic, hypothesis-generating study.
Correspondence: Mr Braun, Department of Epidemiology, University of North Carolina–Chapel Hill, Campus Box 7435, McGavran-Greenberg Hall, Chapel Hill, NC 27514 (jmbraun@unc.edu).
Author Contributions:Study concept and design: Braun. Analysis and interpretation of data: Kalkbrenner. Drafting of the manuscript: Braun. Critical revision of the manuscript for important intellectual content: Braun and Kalkbrenner.
Financial Disclosure: None reported.
Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature
Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal
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