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Modeling Historic Arsenic Exposures and Spatial Risk for Bladder Cancer
Joseph Boyle1, Mary H Ward2, Stella Koutros2
1Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Statistics in Biosciences
|September 9, 2024
Summary
This study highlights how past arsenic exposure, especially from private wells, increases bladder cancer risk. Modeling long-term, time-varying exposures offers better insights into cancer development over time.
Area of Science:
- Environmental Epidemiology
- Toxicology
- Spatial Analysis
Background:
- Arsenic is a known bladder carcinogen, but the precise timing of exposure's link to cancer diagnosis remains unclear.
- Understanding the temporal relationship between arsenic exposure and bladder cancer is crucial for public health.
- Previous studies often relied on summary measures of exposure, potentially missing critical temporal dynamics.
Purpose of the Study:
- To investigate the association between time-varying mixtures of arsenic exposures and bladder cancer risk.
- To compare the performance of time-varying mixture models versus summary exposure measures.
- To identify specific temporal windows of arsenic exposure most strongly associated with bladder cancer.
Main Methods:
- Utilized the Bayesian index low rank kriging multiple membership model (LRK-MMM) for exposure assessment.
- Modeled arsenic exposure mixtures across multiple historical temporal windows (up to 60 years prior).
- Analyzed residential histories to estimate cumulative spatial risk for bladder cancer.
Main Results:
- Time-varying mixture models demonstrated a better fit to the data than single summary measures of arsenic exposure.
- Positive, though not statistically significant, associations were found between time-varying arsenic mixtures and bladder cancer (ORs 1.03-1.14).
- Significant positive associations (ORs 1.28-1.60) were identified for an interaction between arsenic exposure and private well water consumption.
- Arsenic exposures 40-50 years prior to study entry showed elevated importance in the mixture models.
- Two localized areas of elevated cumulative bladder cancer risk were identified in New Hampshire and Maine.
Conclusions:
- Modeling arsenic exposure as a time-varying mixture is essential for understanding diseases with long latency periods, like bladder cancer.
- Past arsenic exposure, particularly from private wells, is a significant risk factor for bladder cancer.
- Identifying high-risk spatial areas can inform targeted public health interventions and environmental monitoring.
