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Multiple Environmental Chemical Exposures to Lead, Mercury and Polychlorinated Biphenyls Among Childbearing-aged Women (NHANES 1999-2004): Body Burden and Risk Factors

Overview
Journal Environ Res
Publisher Elsevier
Date 2012 Nov 20
PMID 23158727
Citations 22
Authors
Affiliations
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Abstract

Background: Lead, mercury and polychlorinated biphenyls (PCBs) are neurotoxicants with intergenerational health consequences from maternal body burden and gestational exposures. Little is known about multiple chemical exposures among childbearing-aged women.

Objectives: To determine the percentage of women aged 16-49 of diverse races and ethnicities whose body burdens for all three xenobiotics were at or above the median; to identify mixed exposures; and to describe those women disproportionately burdened by two or more of these chemicals based on susceptibility- and exposure-related attributes, socioeconomic factors and race-ethnicity.

Methods: Secondary data analysis of National Health and Nutrition Examination Survey (1999-2004).

Results: The best-fit logistic regression model without interactions contained 12 variables. Four risk factors associated with body burden were notable (P≤0.05). An exponential relationship was demonstrated with increasing age. Any fish consumption in past 30 days more than doubled the odds. Heavy alcohol consumption increased the relative risk. History of breastfeeding reduced this risk. These women were more likely to have two xenobiotics at or above the median than one. More than one-fifth of these childbearing-aged women had three xenobiotic levels at or above the median.

Conclusions: These findings are among the first description of US childbearing-aged women's body burden and risk factors for multiple chemical exposures. This study supports increasing age, any fish consumption and heavy alcohol consumption as significant risk factors for body burden. History of breastfeeding lowered the body burden. Limited evidence was found of increased risk among minority women independent of other risk factors.

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