Bayesian Risk Assessment of Cumulative Exposure to Organophosphates with Censored Observations

• Activity Number: 607
• Type: Topic Contributed
• Date/Time: Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Risk Analysis
• Author(s): Ayona Chatterjee*+ and Anne Riederer and Scott Bartell and Barry Ryan
• Companies: University of West Georgia and Environmental Protection Agency and University of California at Irvine and Emory University
• Keywords: latent gaussian ; cesnored observations ; bayesian model ; organophosphates

Abstract

Organophosphates are widely used pesticides that have negative effects on the human nervous system. The aim of this study is to assess the risk of exposure to combined levels of organophosphates for certain groups of individuals. Most organophosphate levels are left censored and two approaches are discussed when combining such censored data sets for risk assessment. A Bayesian approach is adopted to model the combined organophosphate levels. A latent Gaussian model and a two-step propensity model are developed to account for the left censored observations. This study looks at the cumulative exposure of two organophosphates, malathion and chlorpyrifos. Data are from the NHEXAS -MD diet study. The analysis identifies significant dietary predictors for high exposure levels of these organophosphates and also lifestyle choices that lead to high exposure levels. Model accuracy is discussed for the two censoring methods used and results are compared to the more popular Tobit approach for similar studies.