Abstract

Background: Within-person variations in urinary phthalate metabolite concentrations are substantial, but little is known about what predicts these variations. This knowledge is important to the design, analyses and interpretation of epidemiologic studies. We examined whether within-person change in urinary phthalate metabolite concentrations between 1999/2000 and 2002/2003 differed by population characteristics in a cohort of mid-life women. Methods: We measured 11 urinary phthalate metabolites (monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), monobenzyl phthalate (MBzP), mono(2-ethylhexyl) phthalate, mono(2-ethyl-5-hydroxyhexyl) phthalate, mono(2-ethyl-5-oxohexyl) phthalate, mono(2-ethyl-5-carboxypentyl) phthalate, mono-carboxyoctyl phthalate (MCOP), mono-carboxy-isononyl phthalate, and mono(3-carboxypropyl) phthalate (MCPP)) in 1221 women who had baseline demographics (age, race/ethnicity, study site, income, education) and dietary data (daily total calorie intake, dietary fat content), menopausal status and hormone therapy (HT) use at both time points. We used multiple linear regression to predict within-person change in metabolite concentrations, defined as the three-year difference in log-transformed metabolite concentrations, with baseline demographics and within-person changes in diet, menopausal status and HT use. Results: Over three years, concentrations of most metabolites significantly decreased, except for MiBP and di(2-ethylhexyl) phthalate (DEHP) metabolites. Income and education were associated with differential changes in MCOP, MCPP, MBzP and DEHP metabolites, but the associations were not monotonic. Increasing intake of dietary fat was significantly associated with smaller decreases in MnBP and MBzP. Compared to women who remained pre-menopausal with no HT use, women who started HT had greater decreases in MnBP and MCPP, while those who used HT at baseline had smaller decreases in MEP. Conclusion: Urinary phthalate metabolite concentrations changed differentially by population characteristics. Secular changes in sources of exposure may not apply uniformly to all socioeconomic groups. Changing behaviors may further alter metabolite concentrations. Given this, taking the mean or constructing trajectories of repeatedly sampled metabolite concentrations may better characterize phthalate exposure over an extended period.

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