Diana C Pacyga1, Diana K Haggerty2, Megan Nicol2, Melissa Henning2, Antonia M Calafat3, Joseph M Braun4, Susan L Schantz5, Rita S Strakovsky6. 1. Department of Food Science and Human Nutrition, East Lansing, MI 48824, USA; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48824, USA. 2. Department of Food Science and Human Nutrition, East Lansing, MI 48824, USA. 3. Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. 4. Department of Epidemiology, Brown University, Providence, RI 02912, USA. 5. Department of Comparative Biosciences, University of Illinois, Urbana-Champaign, IL 61801, USA; The Beckman Institute, University of Illinois, Urbana-Champaign, IL 61801, USA. 6. Department of Food Science and Human Nutrition, East Lansing, MI 48824, USA; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48824, USA. Electronic address: strakovs@msu.edu.
Abstract
BACKGROUND/ OBJECTIVES: Pregnant women are exposed to multiple phthalates and their replacements, which are endocrine disrupting chemicals associated with adverse maternal and child health outcomes. Identifying maternal characteristics associated with phthalate/replacement exposure during pregnancy is important. METHODS: We evaluated 13 maternal sociodemographic and lifestyle factors, enrollment year, and conception season as determinants of exposure biomarkers of phthalates and their replacements in 482 pregnant women from the Illinois Kids Development Study (I-KIDS, enrolled 2013-2018). We quantified 19 phthalate/replacement metabolites in pools of five first-morning urines collected across pregnancy. K-means clustering identified women with distinct patterns of biomarker concentrations and principal component analysis (PCA) identified principal component (PC) profiles of biomarkers that exist together. We used multivariable regression models to evaluate associations of predictors with identified k-means clusters and PCs. RESULTS: K-means clustering identified two clusters of women: 1) low phthalate/di(2-ethylhexyl) terephthalate (∑DEHTP) and 2) high phthalate/∑DEHTP biomarker concentrations. PCA identified four PCs with loadings heaviest for biomarkers of plasticizer phthalates [di-isononyl, di-isodecyl, di-n-octyl phthalates] (PC1), of other phthalates [dibenzyl, di-n-butyl, di-iso-butyl phthalates] (PC2), of phthalate replacements [∑DEHTP, di(isononyl) cyclohexane-1,2-dicarboxylate (∑DiNCH)] (PC3), and of monoethyl phthalate [MEP] (PC4). Overall, age, marital status, income, parity, pre-pregnancy BMI, caffeine intake, enrollment year, and conception season were independently associated with k-means cluster membership and at least one PC. Additionally, race/ethnicity, education, employment, pregnancy intention, smoking status, alcohol intake, and diet were associated with at least one PC. For instance, women who conceived in the spring, summer, and/or fall months had lower odds of high phthalate/∑DEHTP cluster membership and had lower plasticizer phthalate, phthalate replacement, and MEP PC scores. CONCLUSIONS: Conception season, enrollment year, and several sociodemographic/lifestyle factors were predictive of phthalate/replacement biomarker profiles. Future studies should corroborate these findings, with a special focus on replacements to which pregnant women are becoming increasingly exposed.
BACKGROUND/ OBJECTIVES: Pregnant women are exposed to multiple phthalates and their replacements, which are endocrine disrupting chemicals associated with adverse maternal and child health outcomes. Identifying maternal characteristics associated with phthalate/replacement exposure during pregnancy is important. METHODS: We evaluated 13 maternal sociodemographic and lifestyle factors, enrollment year, and conception season as determinants of exposure biomarkers of phthalates and their replacements in 482 pregnant women from the Illinois Kids Development Study (I-KIDS, enrolled 2013-2018). We quantified 19 phthalate/replacement metabolites in pools of five first-morning urines collected across pregnancy. K-means clustering identified women with distinct patterns of biomarker concentrations and principal component analysis (PCA) identified principal component (PC) profiles of biomarkers that exist together. We used multivariable regression models to evaluate associations of predictors with identified k-means clusters and PCs. RESULTS: K-means clustering identified two clusters of women: 1) low phthalate/di(2-ethylhexyl) terephthalate (∑DEHTP) and 2) high phthalate/∑DEHTP biomarker concentrations. PCA identified four PCs with loadings heaviest for biomarkers of plasticizer phthalates [di-isononyl, di-isodecyl, di-n-octyl phthalates] (PC1), of other phthalates [dibenzyl, di-n-butyl, di-iso-butyl phthalates] (PC2), of phthalate replacements [∑DEHTP, di(isononyl) cyclohexane-1,2-dicarboxylate (∑DiNCH)] (PC3), and of monoethyl phthalate [MEP] (PC4). Overall, age, marital status, income, parity, pre-pregnancy BMI, caffeine intake, enrollment year, and conception season were independently associated with k-means cluster membership and at least one PC. Additionally, race/ethnicity, education, employment, pregnancy intention, smoking status, alcohol intake, and diet were associated with at least one PC. For instance, women who conceived in the spring, summer, and/or fall months had lower odds of high phthalate/∑DEHTP cluster membership and had lower plasticizer phthalate, phthalate replacement, and MEP PC scores. CONCLUSIONS: Conception season, enrollment year, and several sociodemographic/lifestyle factors were predictive of phthalate/replacement biomarker profiles. Future studies should corroborate these findings, with a special focus on replacements to which pregnant women are becoming increasingly exposed.
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