Environmental Chemicals in Urine and Blood: Improving Methods for Creatinine and Lipid Adjustment

O’Brien, Katie M.; Upson, Kristen; Cook, Nancy R.; Weinberg, Clarice R.

doi:10.1289/ehp.1509693

Cited by 370 publications

(261 citation statements)

References 12 publications

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“…Fourth, we modeled the most meaningful food intake predictors categorically (< 50, 50–99, 100–149,150–199, and ≥200 g) instead of continuously to demonstrate the dose-response relationship. Fifth, we fitted models with metabolite concentrations expressed as nmol/L urine adjusted for creatinine concentration as a separate covariate (O’Brien et al, 2015). Finally, we investigated whether the results were the same if missing confounder values were excluded rather than imputed.…”

Section: Methodsmentioning

confidence: 99%

Determinants of organophosphate pesticide exposure in pregnant women: A population-based cohort study in the Netherlands

Dries

Pronk²,

Guxens

et al. 2018

International Journal of Hygiene and Environmental Health

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Background In the Netherlands organophosphate (OP) pesticides are frequently used for pest control in agricultural settings. Despite concerns about the potential health impacts of low-level OP pesticides exposure, particularly in vulnerable populations, the primary sources of exposure remain unclear. The present study was designed to investigate the levels of DAP metabolites concentrations across pregnancy and to examine various determinants of DAP metabolite concentrations among an urban population of women in the Netherlands. Method Urinary concentrations of six dialkyl phosphate (DAP) metabolites, the main urinary metabolites of OP pesticides, were determined at < 18, 18–25, and > 25 weeks of pregnancy in 784 pregnant women participating in the Generation R Study (between 2004 and 2006), a large population-based birth cohort in Rotterdam, the Netherlands. Questionnaires administered prenatally assessed demographic and lifestyle characteristics and maternal diet. Linear mixed models, with adjustment for relevant covariates, were used to estimate associations between the potential exposure determinants and DAP metabolite concentrations expressed as molar concentrations divided by creatinine levels. Results The median DAP metabolite concentration was 311 nmol/g creatinine for the first trimester, 317 nmol/g creatinine for the second trimester, and 310 nmol/g creatinine for the third trimester. Higher maternal age, married/living with a partner, underweight or normal weight (BMI of < 18.5 and 18.5– < 25), high education, high income, and non-smoking were associated with higher DAP metabolite concentrations, and DAP metabolite concentrations tended to be higher during the summer. Furthermore, fruit intake was associated with increased DAP metabolite concentrations. Each 100 g/d difference in fruit consumption was associated with a 7% higher total DAP metabolite concentration across pregnancy. Other food groups were not associated with higher DAP metabolite concentrations. Conclusions The DAP metabolite concentrations measured in the urine of pregnant women in the Netherlands were higher than those in most other studies previously conducted. Fruit intake was the main dietary source of exposure to OP pesticides in young urban women in the Netherlands. The extent to which DAP metabolite concentrations reflect exposure to the active parent pesticide rather than to less toxic metabolites remains unclear. Further research will be undertaken to investigate the possible effects of this relatively high level OP pesticides exposure on offspring health.

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Section: Methodsmentioning

confidence: 99%

Determinants of organophosphate pesticide exposure in pregnant women: A population-based cohort study in the Netherlands

Dries

Pronk²,

Guxens

et al. 2018

International Journal of Hygiene and Environmental Health

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“…We modeled phenol biomarker concentrations accounting for urinary dilution using a Bayesian modification of the covariate-adjusted creatinine standardization approach described by O’Brien et al (O'Brien and others 2015). We modeled natural log creatinine as a random normal variable conditional on the following known predictors of creatinine concentrations that were associated with creatinine in our study population: maternal age, race/ethnicity, education, pre-pregnancy BMI, and height.…”

Section: Methodsmentioning

confidence: 99%

Prenatal exposure to environmental phenols and childhood fat mass in the Mount Sinai Children's Environmental Health Study

Buckley

Herring

Wolff

et al. 2016

Environment International

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Early life exposure to endocrine disrupting chemicals may alter adipogenesis and energy balance leading to changes in obesity risk. Several studies have evaluated the association of prenatal bisphenol A exposure with childhood body size but only one study of male infants has examined other environmental phenols. Therefore, we assessed associations between prenatal exposure to environmental phenols and fat mass in a prospective birth cohort. We quantified four phenol biomarkers in third trimester maternal spot urine samples in a cohort of women enrolled in New York City between 1998 and 2002 and evaluated fat mass in their children using a Tanita scale between ages 4 and 9 years (173 children with 351 total observations). We estimated associations of standard deviation differences in natural log creatinine-standardized phenol biomarker concentrations with percent fat mass using linear mixed effects regression models. We did not observe associations of bisphenol A or triclosan with childhood percent fat mass. In unadjusted models, maternal urinary concentrations of 2,5-dichlorophenol were associated with greater percent fat mass and benzophenone-3 was associated with lower percent fat mass among children. After adjustment, phenol biomarkers were not associated with percent fat mass. However, the association between benzophenone-3 and percent fat mass was modified by child’s sex: benzophenone-3 concentrations were inversely associated with percent fat mass in girls (beta = −1.51, 95% CI = −3.06, 0.01) but not boys (beta = −0.20, 95% CI = −1.69, 1.26). Although we did not observe strong evidence that prenatal environmental phenols exposures influence the development of childhood adiposity, the potential antiadipogenic effect of benzophenone-3 in girls may warrant further investigation.

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“…The inclusion of age, gender, race/ethnicity, and other factors in addition to UCR concentration as independent variables allows the models to analyze a variance-covariance matrix of these independent variables and how the observed levels of the analyte of interest used as a dependent variable are affected by inter-dependencies of these independent variables. Thus, based on the mathematical logic, it seems that the model-based method of creatinine correction should be a method of choice as has also been recommended by Barr et al (2005) andO'Brien et al (2016). In order to do a complete, valid, and reliable model-based creatinine-corrected analysis, it is almost essential that variables representing all factors that affect and may affect both UCR and the analyte of interest be included in the model as independent variables.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, within the context of being able to predict an event of interest, from the observed values of urinary analyte concentrations, O'Brien et al (2016) evaluated the efficacy of seven different statistical modeling approaches under three different scenarios, namely, (i) when UCR is affected by hydration only; (ii) when UCR is affected by hydration as well as other factors like age, gender, race/ethnicity, etc., which in turn may also affect the probability of the occurrence of the event of interest; and (iii) when UCR is affected by hydration as well as other factors like age, gender, race/ethnicity, etc., which in turn may also affect the probability of the occurrence of the event of interest and the magnitude of environmental exposure. Almost uniformly, based on the results of several simulation studies with different known probabilities of the occurrence of the event, O'Brien et al (2016) was found to correctly predict the probability of the event of interest more often when UCR and other factors that can be considered to affect the probability of the event of interest are used as independent variables in regression models.…”

Section: Introductionmentioning

confidence: 99%

“…Almost uniformly, based on the results of several simulation studies with different known probabilities of the occurrence of the event, O'Brien et al (2016) was found to correctly predict the probability of the event of interest more often when UCR and other factors that can be considered to affect the probability of the event of interest are used as independent variables in regression models.…”

Section: Introductionmentioning

confidence: 99%

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Ratio-based vs. model-based methods to correct for urinary creatinine concentrations

Jain¹

2016

Environ Sci Pollut Res

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Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.

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Environmental Chemicals in Urine and Blood: Improving Methods for Creatinine and Lipid Adjustment

Cited by 370 publications

References 12 publications

Determinants of organophosphate pesticide exposure in pregnant women: A population-based cohort study in the Netherlands

Determinants of organophosphate pesticide exposure in pregnant women: A population-based cohort study in the Netherlands

Prenatal exposure to environmental phenols and childhood fat mass in the Mount Sinai Children's Environmental Health Study

Ratio-based vs. model-based methods to correct for urinary creatinine concentrations

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