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Factors that Predice Serum PCB, PCDD, AND PCDF Concentrations in Michigan, USA

Garabrant, D*; Hong, B*; Chen, Q; Chang, C-W*; Jiang, X*; Franzblau, A*; Lepkowski, J; Adriaens, P§; Demond, A§; Hedgeman, E*; Knutson, K*; Towey, T§; Gillespie, B W

doi: 10.1097/01.ede.0000340275.84909.26
Abstracts: ISEE 20th Annual Conference, Pasadena, California, October 12–16, 2008: Contributed Abstracts
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*Risk Science Center and Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA; †Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA; ‡Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA; and §Department of Civil and Environmental Engineering, University of Michigan College of Engineering, Ann Arbor, MI, USA.

Abstracts published in Epidemiology have been reviewed by the organizations of Epidemiology. Affliate Societies at whose meetings the abstracts have been accepted for presentation. These abstracts have not undergone review by the Editorial Board of Epidemiology.

ISEE-1305

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Background:

We studied factors that predict serum concentrations of the 29 polychlorinated biphenyls (PCBs) polychlorinated dibenzodioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs) for which WHO Toxic Equivalency Factors (TEFs) exist, using data from 946 participants in the University of Michigan Dioxin Exposure Study (UMDES) in Michigan, USA. This study provides a valuable opportunity to identify potential environmental exposure pathways for PCBs, PCDDs and PCDFs.

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Methods:

Participants were interviewed regarding potential exposure pathways (sport caught fish and game, diet, activities in the contaminated area, occupations, residential locations), demographics, smoking, and breast feeding. Samples of blood, soil, and household dust were analyzed for PCBs, PCDDs and PCDFs using HRGC/HRMS. Data were analyzed using linear regression for complex survey data, in which the log10(serum PCB) was a linear function of predictors.

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Results:

Serum PCB concentrations were detectable in at least 98% of subjects for all congeners except PCB 81 (53% above LOD). The most important congener was PCB 126 because it typically contributes about 10% to the TEQ (using 2005 WHO TEFs), whereas all the other PCBs combined contribute less than 10% to the TEQ. Serum PCDD and PCDFs were detectable in a high proportion of participants for almost all congeners. The regression model for PCB 126 explained 52 percent of the variation in the serum concentration (adjusted R2). Most of the variation was explained by demographic factors (age, BMI, and sex), and smoking. Age was positively associated with serum levels, while smoking was inversely associated with serum levels. Neither living on contaminated soil nor contaminated household dust was associated with increased serum PCB 126 levels. Living on a farm in the 1940s–1950s and eating sport caught fish from outside the contaminated area were positively associated with serum levels of PCB 126. None of the other environmental exposure factors we investigated, whether related to the Midland/Saginaw area or not, were significant predictors of serum PCB 126 levels. The regression models explained between 60 and 70 percent of the variation in serum congener concentration (adjusted R2) for most congeners. Most of the variation in PCDD and PCDF levels was explained by demographic factors (age, sex, BMI, BMI loss or gain in the past year), breastfeeding, and smoking. Age was positively associated with serum levels, while breast feeding was inversely associated with serum levels. Smoking was inversely associated with 2378-TCDD but not other PCDD congeners. Household dust concentrations and soil concentrations of PCBs, PCDDs, and PCDFs showed no appreciable relationship to serum concentrations.

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Conclusions:

This study has strengths that make it valuable. Since it is a population-based study, the results apply to the general population of Midland and Saginaw Counties. Few other studies have concurrent measurements of serum, soil, and household dust PCBs, as we have, nor do they include as many subjects. Our serum analyses were based on large samples (80 ml of blood), which allowed us to have measurable PCB levels for almost all subjects. Few other studies have achieved these levels and, as a result, have been limited by large numbers of non-detectable serum levels.

© 2008 Lippincott Williams & Wilkins, Inc.