|
Activity Number:
|
127
|
|
Type:
|
Invited
|
|
Date/Time:
|
Monday, July 30, 2007 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Section on Statistics and the Environment
|
| Abstract - #307857 |
|
Title:
|
Bayesian Modeling and Surveillance for Adverse MRDD Outcomes Associated with Soil Chemical Exposures
|
|
Author(s):
|
Ji-In Kim*+ and Andrew B. Lawson
|
|
Companies:
|
University of South Carolina and University of South Carolina
|
|
Address:
|
Dept. of Epidemiology & Biostatistics, Columbia, SC, 29208,
|
|
Keywords:
|
environmental exposure ; logistic ; spatial ; MRDD ; clustering interpolation
|
|
Abstract:
|
The relation between early childhood development and maternal exposures to environmental chemicals during pregnancy is an important issue when considering the residential exposure risk. In this study we examine a range of modeling methods where we have geo-coded residential addresses for mothers during the different months of pregnancy and mental retardation and development delay (MRDD) outcome measures for the babies for a Medicaid population in South Carolina. We also have available measures of soil chemistry (e.g. total microtox EC50) on a network of sites. Our modeling involves interpolation methods for spatially-referenced measures to locations of residence that vary with time. We also develop a logistic spatial model for the MRDD outcome and clustering in that outcome which can be time-dependent or designed to be a function of the cumulative exposure over all addresses resided in.
|
