Modeling Historic Arsenic Exposures and Spatial Risk for Bladder Cancer

Joseph Boyle, Mary H. Ward, Stella Koutros, Margaret R. Karagas, Molly Schwenn, Alison T. Johnson, Debra T. Silverman and David C. Wheeler ()
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Joseph Boyle: Virginia Commonwealth University
Mary H. Ward: National Cancer Institute
Stella Koutros: National Cancer Institute
Margaret R. Karagas: Department of Epidemiology, Dartmouth Geisel School of Medicine
Molly Schwenn: Maine Cancer Registry
Alison T. Johnson: Vermont Department of Health
Debra T. Silverman: National Cancer Institute
David C. Wheeler: Virginia Commonwealth University

Statistics in Biosciences, 2024, vol. 16, issue 2, No 4, 377-394

Abstract: Abstract Arsenic is a bladder carcinogen though less is known regarding the specific temporal relationship between exposure and bladder cancer diagnosis. In this study, we modeled time-varying mixtures of arsenic exposures at many historic temporal windows to evaluate their association with bladder cancer risk in the New England Bladder Cancer Study. We used arsenic exposure estimates up to 60 years prior to study entry and compared the goodness of fit of models using these mixtures to those using summary measures of arsenic exposures. We used the Bayesian index low rank kriging multiple membership model (LRK-MMM) to estimate the associations of these mixtures with bladder cancer and estimate cumulative spatial risk for bladder cancer using participants’ residential histories. We found consistent evidence that modeling arsenic exposures as a time-varying mixture provided better fit to the data than using a single arsenic exposure summary measure. We estimated several positive though not significant associations of the time-varying arsenic mixtures with bladder cancer having odds ratios (ORs) of 1.03–1.14 and identified many significant and positive associations for an interaction among those who consumed water from a private dug well (ORs 1.28–1.60). Arsenic exposures 40–50 years before study entry received elevated importance weights in these mixtures. Additionally, we found two small areas of elevated cumulative spatial risk for bladder cancer in southern New Hampshire and in south central Maine. These results emphasize the importance of considering time-varying mixtures of exposures for diseases with long latencies such as bladder cancer.

Keywords: Arsenic; Mixture analysis; Spatial analysis; Residential history; Bladder cancer; Bayesian (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12561-023-09404-7

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