Literature DB >> 11940459

The association between biomarker-based exposure estimates for phthalates and demographic factors in a human reference population.

Jung-Wan Koo1, Frederick Parham, Michael C Kohn, Scott A Masten, John W Brock, Larry L Needham, Christopher J Portier.   

Abstract

Population-based estimates of environmental exposures using biomarkers can be difficult to obtain for a variety of reasons, including problems with limits of detection, undersampling of key strata, time between exposure and sampling, variation across individuals, variation within individuals, and the ability to find and interpret a given biomarker. In this article, we apply statistical likelihoods, weighted sampling, and regression methods for censored data to the analysis of biomarker data. Urinary metabolites for seven phthalates, reported by Blount et al., are analyzed using these methods. In the case of the phthalates data, we assumed the underlying model to be a log-normal distribution with the mean of the distribution defined as a function of a number of demographic variables that might affect phthalate levels in individuals. Included as demographic variables were age, sex, ethnicity, residency, family income, and education level. We conducted two analyses: an unweighted analysis where phthalate distributions were estimated with changes in the means of these distributions as a function of demographic variables, and a weighted prediction for the general population in which weights were assigned for a subset of the population depending on the frequency of their demographic variables in the general U.S. population. We used statistical tests to determine whether any of the demographic variables affected mean phthalate levels. Individuals with only a high school education had higher levels of di-n-butyl phthalate than individuals with education beyond high school. Subjects who had family income less than $1,500 in the month before sampling and/or only high school education had higher levels of n-butyl benzyl phthalate levels than other groupings. Di(2-ethylhexyl) phthalate was higher in males and/or in urban populations and/or in people who had family income less than $1,500 per month. Our findings suggest that there may be significant demographic variations in exposure and/or metabolism of phthalates and that health-risk assessments for phthalate exposure in humans should consider different potential risk groups.

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Year:  2002        PMID: 11940459      PMCID: PMC1240804          DOI: 10.1289/ehp.02110405

Source DB:  PubMed          Journal:  Environ Health Perspect        ISSN: 0091-6765            Impact factor:   9.031


  40 in total

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3.  Study of the testicular effects and changes in zinc excretion produced by some n-alkyl phthalates in the rat.

Authors:  P M Foster; L V Thomas; M W Cook; S D Gangolli
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Authors:  F Walseth; R Toftgård; O G Nilsen
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5.  Effects of monoesters of O-phthalic acid on serum lipid composition of rats.

Authors:  S Oishi; K Hiraga
Journal:  Toxicol Lett       Date:  1982-11       Impact factor: 4.372

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Journal:  Drug Chem Toxicol       Date:  1981       Impact factor: 3.356

7.  The morphological development of di-N-pentyl phthalate induced testicular atrophy in the rat.

Authors:  D M Creasy; J R Foster; P M Foster
Journal:  J Pathol       Date:  1983-03       Impact factor: 7.996

8.  Carcinogenicity testing of phthalate esters and related compounds by the National Toxicology Program and the National Cancer Institute.

Authors:  W M Kluwe; E E McConnell; J E Huff; J K Haseman; J F Douglas; W V Hartwell
Journal:  Environ Health Perspect       Date:  1982-11       Impact factor: 9.031

Review 9.  Overview of phthalate ester pharmacokinetics in mammalian species.

Authors:  W M Kluwe
Journal:  Environ Health Perspect       Date:  1982-11       Impact factor: 9.031

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Authors:  C C Peck; P W Albro
Journal:  Environ Health Perspect       Date:  1982-11       Impact factor: 9.031

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9.  Prevalence and predictors of phthalate exposure in pregnant women in Charleston, SC.

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10.  Urinary phthalate metabolite concentrations among pregnant women in Northern Puerto Rico: distribution, temporal variability, and predictors.

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