Recent advances in the theory and application of spatial statistics, as well as new kinds of data management techniques and analytical approaches made possible through the development of GIS software, hold tremendous promise for ex ante enhancing study design in environmental health sciences. ? In this R21 proposal, we seek to devise a general approach for collecting environmental and biological samples that incorporates optimal spatial design.
Specific aims are to: ? 1. Develop a spatially-based sampling procedure that improves upon traditional random or categorical sampling approaches. ? 2. Incorporate optimality into the procedure with regard to information gain concerning the nature of the relationship between contaminant and explanatory variables as well as the spatial pattern in the contaminant levels. ? 3. Develop a system for sampling sequentially and adaptively to take full advantage of the information made available through the sampling process. ? 4. Demonstrate innovative spatial design approaches by collecting environmental samples in the field. ? 5. Assess the importance of the spatial resolution at which analyses and sampling protocols are undertaken (i.e., small changes in location may in fact equate to large changes in exposure). ? We will use mercury as a prototype contaminant for exploring how to advance these new methods. We are concerned primarily with developing a general framework for applying these methods to optimized sampling design across a wide variety of contaminants. This research will help researchers improve estimates of exposures, sample more strategically, update models more efficiently, and draw better and more meaningful links between environmental contaminants and health endpoints. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21ES013776-02
Application #
7057882
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Gray, Kimberly A
Project Start
2005-05-01
Project End
2008-04-30
Budget Start
2006-05-01
Budget End
2008-04-30
Support Year
2
Fiscal Year
2006
Total Cost
$187,977
Indirect Cost
Name
Duke University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Miranda, Marie Lynn; Edwards, Sharon E (2011) Use of spatial analysis to support environmental health research and practice. N C Med J 72:132-5
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua et al. (2011) Spatial modeling for groundwater arsenic levels in North Carolina. Environ Sci Technol 45:4824-31