Developing improved methods for mapping epidemiologic data on reproductive and developmental outcomes while adjusting for known risk factors.
Geographic Information Systems now allow the use of analytic techniques in spatial epidemiology previously not feasible. As a result the mapping of routinely collected health data is now common and often provokes concern when patterns of disease rates appear to have “hot spots,” although it is well understood by epidemiologists that the results may be biased by failure to collect and control for many known risk factors that are unevenly distributed over the area of the map.
Principal Investigator: Thomas Webster, Boston University SPH
Resources available:
Generalized Concentration Addition to Visualize and Test Combination Data
NEW: This R code uses the Generalized Concentration Addition (GCA) method (Howard and Webster 2009) to visualize and test combination data. These programs are for use with the R environment. This work is available for use under the General Public License.
Howard, G. J., Schlezinger, J. J., Hahn, M. E., & Webster T. F. (2010). Generalized concentration addition predicts joint effects of aryl hydrocarbon receptor agonists with partial agonists and competitive antagonists. Environmental Health Perspectives, 118(5), 666-672. Howard, G. J., & Webster, T. F. (2009). Generalized concentration addition: a method for examining mixtures containing partial agonists. Journal of Theoretical Biology, 259(3), 469-477. PMCID: PMC2737481.Generalized Additive Model for Spatial Epidemiology
NEW: Summary of Recent Cape Cod Breast Cancer Publication, a short summary of Gallagher, L. G., Webster, T. F., Aschengrau, A., & Vieira, V. M. (2010). Using residential history and groundwater modeling to examine drinking water exposure and breast cancer. Environmental Health Perspectives, 118(6), 749-755.
The following code and synthetic data for testing the Generalized Additive Model method is available. This work is available for use under the General Public License.
- syndata_Scode.txt: text file of S-Plus code for reproducing our analysis using synthetic data
- syndata.xls (204 kb):excel file of synthetic data
- syndata-figs.doc (71 kb): word file of crude and adjusted maps of the synthetic data (output from S-Plus mapped using ArcView)
The following article discusses methods and analyzes both a synthetic and real data set:
Webster, T., Vieira, V., Weinberg, J., & Aschengrau, A. (2006). Method for mapping population-based case-control studies using generalized additive models. International Journal of Health Geographics, 5:26. PMCID: PMC1526437. The following article discussed methods and analyzes a real data set:
Vieira, V., Aschengrau, A., & Ozonoff, D. M. (2005). Impact of tetrachloroethylene-contaminated drinking water on the risk of breast cancer: Using a dose model to assess exposure in a case-control study. Environmental Health, 4:3.
