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Your Environment. Your Health.

Progress Reports: Boston University: Early Life Exposure to Tetrachloroethylene (PCE)-Contaminated Drinking Water and Social Stressors may Interact to Increase the Risk of Substance Use Later in Life

Superfund Research Program

Early Life Exposure to Tetrachloroethylene (PCE)-Contaminated Drinking Water and Social Stressors may Interact to Increase the Risk of Substance Use Later in Life

Project Leader: Ann Aschengrau
Co-Investigators: Lisa Gallagher, Richard Saitz, Renee Boynton-Jarrett
Grant Number: P42ES007381
Funding Period: 2000-2020
View this project in the NIH Research Portfolio Online Reporting Tools (RePORT)

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Progress Reports

Year:   2019  2018  2017  2016  2015  2014  2013  2012  2010  2009  2008  2007  2006  2005  2004  2003  2002  2001  2000 

This retrospective cohort study is testing the hypothesis that perchloroethylene (PCE) found in public drinking water supplies in Cape Cod, Massachusetts, is associated with serious reproductive and developmental disorders, including sperm and menstrual abnormalities, impaired fecundity, secondary infertility, spontaneous abortion, intrauterine growth retardation, pre-term delivery, low birth weight, congenital malformations, and developmental disorders of learning and attention. The source of the contamination was a vinyl liner applied to the inner surface of certain asbestos cement water distribution pipes in eight towns. The study population is composed of families exposed to PCE-contaminated drinking water during 1969-1983 and a comparable group of unexposed families. All study families had at least one child during this period.

During the past year, Dr. Aschengrau and her team of researchers have made progress in the areas of data cleaning, outcome validation, exposure assessment, data analysis, and manuscript preparation. In particular, all survey data were cleaned, and the researchers obtained medical record releases requesting verification of reported birth outcomes. They are currently in the process of reviewing birth records that have been received and conducting PCE exposure assessments.

Project researchers have developed an innovative exposure assessment method to model complex interconnected geometries for a town’s entire water distribution system. They are using a combination of an exposure algorithm created by Webler and Brown (1993) and EPANET, an EPA software package that simulates hydraulic and water quality characteristics within pressurized pipe networks. Using the Geographic Information System developed for their prior studies, they produced digital maps for each study town that identify the subjects’ residences and water pipe network. These maps enabled them to create a pipe network schematic in EPANET that consists of nodes, or points where water consumption occurs, and pipes, including information on their diameter and length. Each residence was assigned to the pipe node that serves it. With the EPANET program, the researchers can simulate the flow of water within the pipe distribution network and calculate the flow rate in each pipe segment. The result is a more accurate depiction of water flow, including its rate and direction.

The researchers are currently incorporating the water quality modeling capability of EPANET with the leaching rate provided by the original Webler-Brown exposure algorithm to calculate the PCE concentration at each node. This involves using the EPANET flow calculations to determine the residence time of water in each pipe segment. The amount of PCE entering the water during the residence time is a function of the pipe’s age, the initial PCE loading in the pipe liner, and the leaching rate of PCE from the liner into the drinking water. This information is included in the EPANET simulation, which calculates the PCE concentration at each node and as well as the subjects’ residences associated with the node.

Preliminary epidemiological and statistical analyses are currently underway that examine the relationship between PCE exposure and the occurrence of low birth weight, pre-term delivery, intrauterine growth retardation, spontaneous abortion, congenital anomalies, and learning disabilities. These analyses take into account confounding variables as well as the correlation between sets of siblings. Several manuscripts on these topics are currently being prepared.

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