Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children |
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Authors: | Georgiana Onicescu Andrew B. Lawson Suzanne McDermott C. Marjorie Aelion Bo Cai |
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Affiliation: | 1. Department of Public Health Sciences, Medical University of South Carolina, Carolina, SC, 29425, USA 2. Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA 3. School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, 01003, USA 4. Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA
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Abstract: | In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother’s age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months. |
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