Temporal variability in urinary concentrations of perchlorate, nitrate

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Published in final edited form as: J Expo Sci Environ Epidemiol. 2012 ; 22(2): 212–218. doi:10.1038/jes.2011.44.

Temporal variability in urinary concentrations of perchlorate, nitrate, thiocyanate and iodide among children NANCY MERVISHa, BEN BLOUNTb, LIZA VALENTIN-BLASINIb, BARBARA BRENNERa, MAIDA P. GALVEZa,c, MARY S. WOLFFa, and SUSAN L. TEITELBAUMa aDepartment of Preventive Medicine, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1057, New York, New York 10029, USA bDivision

of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USA cDepartment

of Pediatrics, Mount Sinai School of Medicine, New York, New York 10029, USA

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Abstract Perchlorate, nitrate and thiocyanate are ubiquitous in the environment, and human exposure to these chemicals is accurately measured in urine. Biomarkers of these chemicals represent a person's recent exposure, however, little is known on the temporal variability of the use of a single measurement of these biomarkers. Healthy Hispanic and Black children (6–10-year-old) donated urine samples over 6 months. To assess temporal variability, we used three statistical methods (n = 29; 153 urine samples): intraclass correlation coefficient (ICC), Spearman's correlation coefficient between concentrations measured at different timepoints and surrogate category analysis to assess how well tertile ranking by a single biomarker measurement represented the average concentration over 6 months. The ICC measure of reproducibility was poor (0.10–0.12) for perchlorate, nitrate and iodide; and fair for thiocyanate (0.36). The correlations for each biomarker across multiple sampling times ranged from 0.01–0.57. Surrogate analysis showed consistent results for almost every surrogate tertile. Results demonstrate fair temporal reliability in the spot urine concentrations of the three NIS inhibitors and iodide. Surrogate analysis show that single-spot urine samples reliably categorize participant's exposure providing support for the use of a single sample as an exposure measure in epidemiological studies that use relative ranking of exposure.

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Keywords

child exposure/health; dietary exposure; epidemiology

Introduction Normal thyroid function is essential for growth and neurological development in fetuses, infants and young children. The thyroid requires iodine to make thyroid hormone. Environmental toxicants, such as perchlorate, nitrate and thiocyanate, can disrupt normal

© 2011 Nature America, Inc. All rights reserved Address all correspondence to: Dr. Nancy Mervish, Department of Preventive Medicine, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1057, New York, NY 10029, USA. Tel.: + 1 212 824 7004. Fax: + 1 212 360 6965. [email protected]. Conflict of interest The authors declare no conflict of interest. Disclaimer The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

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thyroid function by competitively inhibiting iodide uptake by the sodium/iodide symporter (NIS; Braverman and Utiger, 2005). Human exposure to these chemicals occurs mainly through diet and drinking water (Michajlovski and Langer, 1958; National Academy of Sciences, 1995; Kirk et al., 2005; Dasgupta et al., 2006; Murray et al., 2008; Huber et al., 2010). Perchlorate is a naturally occurring anion that is formed in the atmosphere and is synthesized primarily as ammonium perchlorate for use as an oxidizer in producing solid propellant for rockets, missiles and fireworks, and is known as “rocket fuel”. Perchlorate, nitrate and thiocyanate can be found in soil, surface water or drinking water, leafy green vegetables and in milk (National Academy of Sciences, 1995; Dasgupta et al., 2006; Kirk et al., 2007; Murray et al., 2008; Huber et al., 2010). Nitrate can also be added to foods, such as meat and fish, as a preservative. Thiocyanate occurs in foods such as milk and cassava and is a metabolite of cyanide from sources such as cigarette smoke. Perchlorate, nitrate and thiocyanate are ubiquitous in food and in the environment leading to widespread human exposure.

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Perchlorate, nitrate and thiocyanate are detected in human urine (Valentin-Blasini et al., 2007), breast milk (Kirk et al., 2003, 2005; Pearce et al., 2004), amniotic fluid (Blount and Valentin-Blasini, 2006; Blount et al., 2009), serum and cord blood (Blount et al., 2009). However, all of these chemicals are primarily excreted in the urine, thus, urine is the most sensitive matrix to use for assessing exposure. In all, 70–100% of perchlorate and nitrate are excreted within a few hours unchanged in the urine (Lawrence et al., 2001; Greer et al., 2002) These three chemicals have been found in virtually 100% of the urine samples collected in a large, representative sample of the US population (Blount et al., 2007).

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Studies that use urinary biomarkers to examine the potential role of perchlorate, nitrate and thiocyanate in the impairment in the thyroid typically use a single-spot urine to assess exposure. Perchlorate, nitrate and thiocyanate biomarkers in urine accurately measure a person's recent exposure, however, as food intake can change substantially from day-to-day, and because of these chemicals' short half-lives, they are eliminated in the urine within a few hours or days after ingestion, a single sample may not be representative of one's long-term exposure. In addition, variability in urinary concentrations can reflect the timing of sample collection relative to recent food and water consumption (Silva et al., 2004), and excretion patterns. Data on the temporal variability of these chemicals is limited, so the timeframe that one sample can represent has not been established. There is one study that looked at temporal patterns in perchlorate, thiocyanate and iodide in breast milk, and found significant variation in levels among individuals over 4–14 days (Kirk et al., 2005). If we are to examine the effects of these chemicals on neurodevelopment and growth, it is important to understand the temporal variability of urinary concentrations of perchlorate, thiocyanate and nitrate. Epidemiological research on NIS inhibitors has not conclusively associated exposure with thyroid function. In general, associations between perchlorate exposure and thyroid or neurodevelopmental dysfunction have not been identified among pregnant women, children, newborns or occupationally exposed adults, all of whom had normal iodine intake (Crump et al., 2000; Lawrence et al., 2000, 2001; Greer et al., 2002; Chang et al., 2003; Lamm, 2003; Braverman et al., 2005, 2006; Tellez et al., 2005; Amitai et al., 2007). Positive associations between urinary perchlorate and TSH have been observed in the women (Blount et al., 2006a) and infants with low urinary iodide (Cao et al., 2010; Steinmaus et al., 2010). Highnitrate levels have been identified as a risk factor for altered thyroid metrics in both humans and animals (Gatseva and Argirova, 2005; Tajtakova et al., 2006). Two studies reported that maternal serum thiocyanate levels were strongly correlated with low iodine levels in breast milk (Laurberg et al., 2004; Kirk et al., 2007) and in another study, maternal thiocyanate was associated with impaired thyroid function and disturbed development of the offspring

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(Brauer et al., 2006). The use of a single sample to characterize usual exposure in these studies may lead to exposure misclassification that can bias results.

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Given the dependence on food consumed and the relatively short half-lives of NIS inhibitors, characterization of an individual's exposure based on a single urine sample needs to be examined. Furthermore, examining the impact of environmental agents on the thyroid should be done on the most susceptible populations, particularly children. To address this issue, we conducted a study of intra-individual temporal variability of perchlorate, nitrate, thiocyanate and iodide among New York City children.

Materials and methods Study Population

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The study population and methods have been previously described (Teitelbaum et al., 2008). Briefly, from June to October 2004, healthy Hispanic and Black children, between the age of 6 and 10 years who were visiting an East Harlem, NYC community health clinic, were invited to participate in this study. Thirty-five children were enrolled. Informed consent was obtained from each child's legal guardian and assent was obtained from each child. Interviews were conducted with the child's parent or legal guardian in Spanish or English. Children were asked to donate six serial urine samples over a period of 6 months, at initial interview (baseline), ~1, 2, 3 and 6 months after baseline as well as one additional sample donated ~2 weeks after any of the first four samples. At each timepoint, spot urine samples (~40 ml) were collected at the clinic or at home. Urine samples were aliquoted and frozen at −20 °C. Samples were analyzed at the National Center for Environmental Health of the Centers for Disease Control and Prevention (CDC) for perchlorate, thiocyanate, nitrate and iodide. This study was approved by the Institutional Review Boards of Mount Sinai School of Medicine and the CDC. Laboratory Analysis Perchlorate, nitrate, thiocyanate and iodide levels in urine were determined by isotope dilution and ion chromatography/tandem mass spectroscopy (IC/MS/MS), as reported previously (Valentin-Blasini et al., 2007). Briefly, urine samples were thawed to room temperature and mixed to suspend any particulate material. Urine (0.25 ml) was then transferred to an autosampler vial. The sample was diluted with 0.750 ml of deionized water

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containing labeled internal standards ( , 129I−) and queued for injection into the IC/MS/MS system. Each batch of unknown samples was bracketed by aliquots of quality control materials and blank samples for the purpose of assessing method accuracy, precision, and contamination. Quantification was based on the ratio of analyte to stable isotope-labeled internal standard using a set of 10 calibrators run with each set of samples. Absolute assay accuracy was verified by the blind analysis of four different reference solutions containing the different analytes at four different concentrations. Reported results met the accuracy and precision specifications of the quality control/quality assurance program of the Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention (Caudill et al., 2008). A total of 159 urine samples donated by the 35 participants were analyzed. Six children donated a single sample at baseline and are only included in the descriptive statistics presented in Table 1. Four children contributed 2–5 samples, but did not provide a urine specimen at the end of the 6-month period. The remaining 25 participants completed the 6month protocol donating between four and seven samples each for a total of 136 samples. Variable hydration of study participants is likely to lead to varying degrees of dilution of urine samples. Thus, differences in urinary analyte concentrations can be due to variable fluid intake and excretion. To account for this, all values were normalized to urinary J Expo Sci Environ Epidemiol. Author manuscript; available in PMC 2013 March 01.

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creatinine by dividing analyte concentration by the urinary creatinine concentration. As there is continued debate about the use of creatinine for correction of urine dilution, all analyses were performed on uncorrected (ng/ml) and creatinine-corrected (μg/g creatinine) values. Owing to the non-normal distribution of the analyte concentrations, all analyses were conducted on natural-log-transformed values using SAS version 9.2 (Cary, NC, USA). To assess temporal variability of perchlorate, nitrate, thiocyanate and iodide, we used three statistical methods (Teitelbaum et al., 2008). For reproducibility, we used the intraclass correlation coefficient (ICC) defined as the percent of total variance explained by betweenperson variance (Rosner, 2000). In addition, we computed Spearman's correlation coefficients (SCC) between concentrations determined at different times within the 6-month period. Finally, we performed a surrogate category analysis to assess how well tertile ranking by a single biomarker measurement (surrogate sample) represented the average concentration over 6 months (Willett, 1998; Hauser et al., 2004).

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Children providing at least two urine samples (N = 29 children; N = 153 samples) were included in the ICC and SCC calculations. The ICC was calculated from a one-way randomeffects ANOVA model estimated independently for each analyte (SAS Proc Mixed, V9.2). An ICC of at least 0.40 is considered as an indication of fair to good reproducibility and an ICC of 0.75 or greater is considered as excellent (Rosner, 2000) The SCC was calculated for samples collected at approximate intervals determined by collection dates (2, 4, 8, 12, 16, 20 and 24 weeks apart). Depending on the timing of urine donation, between 18 and 59 sample pairs were included in each interval-based SCC calculation.

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Finally, the surrogate category analysis was conducted for each analyte using data from 24 children who had urine samples collected at the following four timepoints: baseline; 8–10 weeks after baseline; 12–14 weeks after baseline; and 23–29 weeks after baseline. The “surrogate sample” is defined as the set of 24 samples collected at one of the four collection timepoints, that is, baseline. The 6-month mean concentration (mean of the four repeated measures over the 6-month period) was calculated to represent the average analyte exposure for this time period. We calculated tertile cutpoints using the analyte concentration distribution of the 24 baseline samples (one per child). These cutpoints were used to classify each child into low (0–33rd percentile), medium (34th–67th percentile) or high (>67th percentile) concentration groups. We then computed three tertile-specific 6-month grand means by averaging the 6-month mean concentrations of the children who were assigned to each tertile (N≅8). All calculations were performed on the natural-log-transformed data and were then back transformed to obtain geometric means. A monotonic increase in the geometric means across tertiles indicates that the concentration measured in a single sample is predictive of the 6-month average concentration. Using each of the other three surrogate sample sets, we calculated tertile cutpoints and tertile-specific grand means, and examined each for a monotonic increasing trend. In the absence of a formal statistical test for these trends, we calculated SCCs using the four sets of surrogate ranks (1, 2, or 3) and tertilespecific geometric means. A positive SCC was considered an indicator of an overall monotonically increasing trend.

Results Detectable levels of all analytes were found in all samples. Compared with NHANES data (children 6–11 years), urinary perchlorate, nitrate and thiocyanate concentrations were lower in our population (both creatinine corrected and uncorrected). Conversely, the urinary iodide concentration in our population was higher than the total urinary iodine levels measured in NHANES children (Table 1).

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Intraclass Correlation Coefficient

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As shown in Table 2, the ICC measure of reproducibility was poor (0.10–0.12) for perchlorate, nitrate and iodide, and fair for thiocyanate (0.36). The ICCs were fairly similar when based on uncorrected concentrations. Spearman's Correlation Coefficients The correlations for each biomarker across multiple sampling times ranged from 0.01 to 0.57 (Table 3). There were a few significant or borderline significant correlations among both the creatinine-corrected and uncorrected samples. However, there was no consistent pattern in correlations over time; the strength of association for shorter intervals was not different than that for longer intervals. Thiocyanate had the most consistently moderate, positive correlations and no negative correlations. In general, creatinine correction either strengthened or did not change the correlations among samples. Surrogate Category Analysis

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The surrogate category analysis showed consistent results for almost every surrogate tertile (Table 4). Creatinine-corrected results are discussed as the patterns were almost identical to uncorrected results. For iodide and thiocyanate, all surrogate samples (baseline, 8–10 weeks after baseline, 12–14 weeks after baseline, 23–29 weeks after baseline) produced monotonic increasing 6-month geometric means for the three exposure categories. For example, when study participants were assigned into three exposure categories based on baseline samples, the 6-month geometric mean for iodide was 210 μg/g creatinine among the children in the lowest intake group, 278 μg/g creatinine in the medium intake group and 397 μg/g creatinine in the highest intake group. Nitrate and perchlorate each had one surrogate sample with a non-monotonic increasing trend across geometric means. These observed trends were further supported by the high SCCs calculated between the surrogate rank and the geometric means. For all of the biomarkers, the SCCs were statistically significant (P0.91 for creatinine-corrected concentrations and >0.82 for the uncorrected concentrations.

Discussion

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Biomarkers are valuable for assessing exposure and potential health effects in epidemiology, as well as occupational and environmental medicine. There is a paucity of information on perchlorate, thiocyanate and nitrate concentrations in children and the differences observed between our population and NHANES highlight potential geographic and dietary variation among study populations. The results of the present study demonstrate fair temporal reliability in the spot urine concentrations of the three NIS inhibitors and iodide. All samples had detectable levels of all analytes indicating exposure was occurring, however, the inconsistent correlations across time support the assumption of varied and episodic intake of these chemicals over a 6-month interval (Blount et al., 2006b). In spite of this, the predictive ability of a single sample to reliably rank individuals according to their 6-month average analyte concentration is good. Although the absolute measures may not provide a reasonable representation of longer-term exposures, the surrogate category analysis provides some assurance that we can reliably rank individuals relative to each other based on analyte levels in a single-spot urine. ICCs (between-person variance divided by the sum of between- and within-person variance) is a measure of reproducibility (Rosner, 2000). In our population for all analytes, the withinchild variance was greater than the between-child variance, contributing to the overall low ICCs. The estimates of within-person variance reflect the sum of variances from both biological and methodological sources. Biological sources of within-person day-to-day variability are expected because the anions have short biological half-lives and are excreted J Expo Sci Environ Epidemiol. Author manuscript; available in PMC 2013 March 01.

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quickly. Foods contain varying amounts of these anions, and thus ingestion of these foods can also influence the day-to-day variability in exposure (Blount and Valentin-Blasini, 2006). In addition, variability found in our study is partly due to the fact that participants provided casual urine samples at various times of the day, and timing of samples relative to an individual's recent consumption have been found to add to variability in measures (Silva et al., 2004). Methodological variation of the laboratory methods also needs to be considered as a source of error; however, the coefficient of variation for these analytical methods was low (4–7.2%) Therefore, analytical imprecision is not a significant contributor to the low ICCs. True biological variance is most likely responsible for the magnitude of the withinperson variance component. The most plausible explanation is varied dietary intake and relatively rapid clearance. In addition, intra-individual variability in urinary creatinine over time might affect creatinine-corrected results (Barr et al., 2005). Regardless of the source and amount of within-person variance, one approach to minimize this bias would be to use an average concentration based on several urine samples obtained from each person, or to collect urine samples that integrate over longer time periods (e.g., 24 h urines). However, this approach is not always feasible.

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A few studies in varying populations have examined the temporal variability of perchlorate, thiocyanate and iodide adjusted for creatinine by comparing 24 h urine samples to spot samples (Rasmussen et al., 1999; Ohira et al., 2008; Anderson et al., 2009; Vejbjerg et al., 2009). All of these studies show that a single sample does not estimate the mean concentration of a 24-h urine sample. The 24-h urine measurement is often considered as the “reference standard”, however, there are difficulties associated with collection (Vejbjerg et al., 2009), so for population-based studies, spot samples corrected for creatinine are most commonly used. Additionally, one of these studies (Ohira et al., 2008) focused on women who were secreting varied amounts of the analytes through breast milk, and thus complicating correlations between spot urine and 24-h urine concentrations. To improve the validity of spot samples, age- and gender-specific creatinine adjustments are suggested (Vejbjerg et al., 2009). Pharmacokinetic investigation of 24-h urinary nitrate excretion demonstrated that maximum urinary concentrations occur between 4 and 6 h after consumption of a nitrate bolus (Pannala et al., 2003). This result suggests that similar to perchlorate, thiocyanate and iodide, a morning spot urine sample of nitrate would be lower than a 24-h sample.

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Compared with the half-lives of perchlorate, nitrate and thiocyanate, other studies examining biomarkers with both longer (e.g., organochlorines and lead; Karmaus and Riebow, 2004) and similar half-lives (e.g., phthalates, phytoestrogens and phenols; Hoppin et al., 2002; Hauser et al., 2004; Fromme et al., 2007; Teitelbaum et al., 2008) have found less intraindividual variability over periods of days to months compared with our current examination of NIS inhibitors and iodide. The greater variation in NIS inhibitor biomarker concentrations may be due to larger fluctuations in exposure sources as compared with the ubiquitous and more constant exposure to some of these other chemicals such as phthalates. Perchlorate, nitrate and thiocyanate are competitive inhibitors of the NIS that can decrease iodine uptake by the thyroid (Braverman and Utiger, 2005); however, more epidemiological research is warranted to determine whether exposure at present levels is associated with negative thyroid-related health outcomes. To conduct these types of investigations, it is essential to assess exposure as accurately as possible within the limitations of an epidemiological setting. We find substantial within-person variability of NIS-inhibitor concentrations in spot urine specimen collected from children over a 6-month period. It is possible that less within-person variability and higher correlations in analyte concentrations over time would be observed in more highly exposed populations. Nonetheless, our surrogate analysis findings show that a single-spot urine sample reliably categorizes

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participants' exposure to perchlorate, nitrate, thiocyanate and iodide. Thus, our results support the use of a single sample as a measure of exposure in epidemiological studies where investigations of relative ranking of exposure are used.

Acknowledgments This research was supported by National Institute of Environmental Health Sciences (NIEHS)/National Cancer Institute ES012771; NIEHS ES12645; NIEHS/U.S. Environmental Protection Agency Children's Center Grants ES09584 and R827039, the New York Community Trust, and the Agency for Toxic Substances and Disease Registry 01A1ATSDR Grant no. ATU 300014 NYS Empire Clinical Research Investigator Program/CDC/ Association of Teachers of Preventive Medicine; the Pediatric Environmental Health Fellowship HD049311.

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Ohira S, Kirk AB, Dyke JV, Dasgupta PK. Creatinine adjustment of spot urine samples and 24 h excretion of iodine, selenium, perchlorate, and thiocyanate. Environ Sci Technol. 2008; 42:9419– 9423. [PubMed: 19174925] Pannala AS, Mani AR, Spencer JP, Skinner V, Bruckdorfer KR, Moore KP, Rice-Evans CA. The effect of dietary nitrate on salivary, plasma, and urinary nitrate metabolism in humans. Free Radic Biol Med. 2003; 34:576–584. [PubMed: 12614846] Pearce EN, Pino S, He X, Bazrafshan HR, Lee SL, Braverman LE. Sources of dietary iodine: bread, cows' milk, and infant formula in the Boston area. J Clin Endocrinol Metab. 2004; 89:3421–3424. [PubMed: 15240625] Rasmussen LB, Ovesen L, Christiansen E. Day-to-day and within-day variation in urinary iodine excretion. Eur J Clin Nutr. 1999; 53:401–407. [PubMed: 10369497] Rosner, B. Fundamentals of Biostatistics. 5th edn.. Duxbury, Pacific Grove; CA: 2000. Silva MJ, Slakman AR, Reidy JA, Preau JL Jr, Herbert AR, Samandar E, Needham LL, Calafat AM. Analysis of human urine for fifteen phthalate metabolites using automated solid-phase extraction. J Chromatogr B Analyt Technol Biomed Life Sci. 2004; 805:161–167. Steinmaus C, Miller MD, Smith AH. Perchlorate in drinking water during pregnancy and neonatal thyroid hormone levels in California. J Occup Environ Med. 2010; 52:1217–1524. [PubMed: 21124239] Tajtakova M, Semanova Z, Tomkova Z, Szokeova E, Majoros J, Radikova Z, Sebokova E, Klimes I, Langer P. Increased thyroid volume and frequency of thyroid disorders signs in schoolchildren from nitrate polluted area. Chemosphere. 2006; 62:559–564. [PubMed: 16095667] Teitelbaum SL, Britton JA, Calafat AM, Ye X, Silva MJ, Reidy JA, Galvez MP, Brenner BL, Wolff MS. Temporal variability in urinary concentrations of phthalate metabolites, phytoestrogens and phenols among minority children in the United States. Environ Res. 2008; 106:257–269. [PubMed: 17976571] Tellez TR, Michaud CP, Reyes AC, Blount BC, Van Landingham CB, Crump KS, Gibbs JP. Longterm environmental exposure to perchlorate through drinking water and thyroid function during pregnancy and the neonatal period. Thyroid. 2005; 15:963–975. [PubMed: 16187904] Valentin-Blasini L, Blount BC, Delinsky A. Quantification of iodide and sodium-iodide symporter inhibitors in human urine using ion chromatography tandem mass spectrometry. J Chromatogr A. 2007; 1155:40–46. [PubMed: 17466997] Vejbjerg P, Knudsen N, Perrild H, Laurberg P, Andersen S, Rasmussen LB, Ovesen L, Jorgensen T. Estimation of iodine intake from various urinary iodine measurements in population studies. Thyroid. 2009; 19:1281–1286. [PubMed: 19888863] Willett, W. Nutritional Epidemiology. 2nd edn.. Oxford University Press; New York, NY: 1998.

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NIH-PA Author Manuscript 674 275 101

Thiocyanate (μg/g creatinine)

Iodide (μg/g creatinine)

Creatinine (mg/dl)

3.9 496 679 273

Perchlorate (ng/ml)

Nitrate (mg/l)

Thiocyanate (ng/ml)

Iodide (ng/ml)

295

720

530

3.87

113

265

712

500

3.71

Median

7.2

63.3

403

0.37

12.9

41.2

28.2

169

0.690

Min

2460

2500

354

73.6

241

2970

5410

2160

42.8

Max

1230

1400

1320

12.5

206

1350

2310

992

14.4

95th percentile

229

1400

640

4.60

94

615

4600

1300

16.0

181

800

246

5090

c

1350

20.0

b NHANES 95th percentile

1470

630

5.10

b

NHANES median

Third National Report on Human Exposure to Environmental Chemicals, 2003; 6–11 year age group (n = 374), 2001–2002 survey years.

NHANES measured total iodine.

c

b

All analytes 100% detected.

a

489

Nitrate (mg/g creatinine)

(B)

3.90

Perchlorate (μg/g creatinine)

(A)

Geometric mean

from 35 New York City children, 2004–2005.

a

Distribution of perchlorate, nitrate, thiocyanate and iodide concentrations: (A) creatinine corrected and (B) uncorrected in 159 urine samples collected

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Table 1 MERVISH et al. Page 10

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Table 2

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Components of variance and intraclass correlation coefficients for analyte concentrations: (A) creatinine corrected and (B) uncorrected. a Components of variance Between-child variance

Within-child variance

Intraclass correlation coefficient

Perchlorate (μg/g creatinine)

0.06

0.51

0.10

Nitrate (mg/g creatinine)

0.02

0.17

0.10

Thiocyanate (μg/g creatinine)

0.26

0.46

0.36

Iodide (mg/dl)

0.10

0.71

0.12

Perchlorate (ng/ml)

0.02

0.62

0.04

Nitrate (mg/l)

0.06

0.46

0.12

Thiocyanate (ng/ml)

0.27

0.48

0.36

Iodide (ng/ml)

0.08

0.71

0.10

(A)

(B)

a

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Variances are from a one-way random-effects ANOVA model using data from children with at least two samples over a 6-month period (N=29 children, 153 samples); calculations were performed on natural-log-transformed data; intraclass correlation coefficient=between-child variance/ total variance.

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NIH-PA Author Manuscript 35

Number of sample pairs

0.23

0.40** 0.26*

0.43* 0.01

Thiocyanate (mg/g creatinine)

Iodide (mg/dl)

0.24

P