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Impact of tetrachloroethylene-contaminated drinking water on the risk of breast cancer: Using a dose model to assess exposure in a case-control study
BACKGROUND: A population-based case-control study was undertaken in 1997 to investigate the association between tetrachloroethylene (PCE) exposure from public drinking water and breast cancer among permanent residents of the Cape Cod region of Massachusetts. PCE, a volatile organic chemical, leached...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC554766/ https://www.ncbi.nlm.nih.gov/pubmed/15733317 http://dx.doi.org/10.1186/1476-069X-4-3 |
Sumario: | BACKGROUND: A population-based case-control study was undertaken in 1997 to investigate the association between tetrachloroethylene (PCE) exposure from public drinking water and breast cancer among permanent residents of the Cape Cod region of Massachusetts. PCE, a volatile organic chemical, leached from the vinyl lining of certain water distribution pipes into drinking water from the late 1960s through the early 1980s. The measure of exposure in the original study, referred to as the relative delivered dose (RDD), was based on an amount of PCE in the tap water entering the home and estimated with a mathematical model that involved only characteristics of the distribution system. METHODS: In the current analysis, we constructed a personal delivered dose (PDD) model that included personal information on tap water consumption and bathing habits so that inhalation, ingestion, and dermal absorption were also considered. We reanalyzed the association between PCE and breast cancer and compared the results to the original RDD analysis of subjects with complete data. RESULTS: The PDD model produced higher adjusted odds ratios than the RDD model for exposures > 50(th )and >75(th )percentile when shorter latency periods were considered, and for exposures < 50(th )and >90(th )percentile when longer latency periods were considered. Overall, however, the results from the PDD analysis did not differ greatly from the RDD analysis. CONCLUSION: The inputs that most heavily influenced the PDD model were initial water concentration and duration of exposure. These variables were also included in the RDD model. In this study population, personal factors like bath and shower temperature, bathing frequencies and durations, and water consumption did not differ greatly among subjects, so including this information in the model did not significantly change subjects' exposure classification. |
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