Spatial-Temporal Analysis and Modeling for Prenatal Exposure: A Case Study of Erie County, New York.

摘要

According to the US Department of Health and Human Services, there were approximately 3.95 million births of babies in United States' hospitals in 2012. During each of these pregnancies, the maternal body and the developing fetus are exposed to different kinds of independent and interdependent stressors with variable positive and negative impact on the mother, fetus or both.;In order to capture the potential impact of complex, interacting environmental stressors and to better monitor or control the spatial and temporal exposure patterns of their occurrence on a geographical level, this research designed and populated a spatial and temporal data model for further analysis in terms of both community- and individual-level researches. Based on statistical methodologies for spatial and temporal analysis for prenatal exposure to drinking water, this research selected Erie County, New York, as study area at ZIP code level. Boil water advisories were chosen to demonstrate the data model and analyze the risk of being exposed to potential drinking water contamination.;The results showed that although the spatial pattern for pregnancy records in each year is not strong, clusters still can be detected in pregnancies, as well as in risks of community exposure to contaminated drinking water. Furthermore, there is statistically significant change in pregnant women exposed to drinking water contamination in some communities (East Aurora and Gowanda). This research also simulated a sample of individual data to assess the benefits of the data model for higher resolution datasets.;Based on the results, this research addressed some recommendations based on existing data for local government to guarantee the quality of drinking water in the community and some solutions in terms of the response to exposure events. As the final goal this research aims to outline a data gathering strategy producing more detailed data records that enables the application of more sophisticated spatial-temporal statistics to further enhance the living quality in the communities and to mitigate the risks in prenatal exposure to drinking water contamination or other stressors.