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Abstract
Geographic modeling is increasingly being used to estimate long-term environmental exposures in epidemiologic studies of chronic disease outcomes. However, without validation against measured environmental concentrations, personal exposure levels, or biologic doses, these models cannot be assumed a priori to be accurate. This article discusses three examples of epidemiologic associations involving exposures estimated using geographic modeling, and identifies important issues that affect geographically modeled exposure assessment in these areas. In air pollution epidemiology, geographic models of fine particulate matter levels have frequently been validated against measured environmental levels, but comparisons between ambient and personal exposure levels have shown only moderate correlations. Estimating exposure to magnetic fields by using geographically modeled distances is problematic because the error is larger at short distances, where field levels can vary substantially. Geographic models of environmental exposure to pesticides, including paraquat, have seldom been validated against environmental or personal levels, and validation studies have yielded inconsistent and typically modest results. In general, the exposure misclassification resulting from geographic models of environmental exposures can be differential and can result in bias away from the null even if non-differential. Therefore, geographic exposure models must be rigorously constructed and validated if they are to be relied upon to produce credible scientific results to inform epidemiologic research. To our knowledge, such models have not yet successfully predicted an association between an environmental exposure and a chronic disease outcome that has eventually been established as causal, and may not be capable of doing so in the absence of thorough validation.
Acknowledgements
The authors thank Gabor Mezei, M.D., Ph.D., for his critical review of sections of this manuscript, and Benjamin Cotts, Ph.D., for the magnetic field modeling of transmission lines.
Declaration of interest
This work was supported by an unrestricted grant from Syngenta Crop Protection, LLC. Syngenta was not involved in the preparation or approval of the manuscript. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the views of Syngenta.
In the past 5 years, JSM has been a consultant to Syngenta, JSM and HOA have co-authored peer-reviewed scientific manuscripts supported by unrestricted grants from Syngenta, and PB has been a member of Syngenta's ethics committee. PB has consulted on air pollution issues and is a member of an advisory group to the European Crop Protection Association. SHM has served as an expert witness in air pollution litigation and is a consultant to various industry and trade groups on air pollution issues. WHB is a consultant to state and provincial agencies and project applicants on the status of electromagnetic fields research in conjunction with environmental impact statements prepared for or by electric utilities and government agencies. ETC is a consultant on issues related to air pollution, electromagnetic fields, and pesticides. All authors received financial support from an unrestricted grant from Syngenta for the preparation of this manuscript. RIK declares no other potential conflicts of interest.
