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## MEMORA**NDUM To:**  Tim Leighton, David Miller, Philip Villaneuva, EPA **From:** Jonathan Cohen, ICF International **Date:** 6 March , 2008 **Re:** EP -W -06- 091, WA 0 - 02, TAF CM 19: Computations of human triclosan dose based on

NHANES urine concentrations. 

## SUMM **AR Y**  The National Health and Nutrition Surveys (NHANES) are a series of US national surveys of the health and nutrition status of the non - institutionalized civilian population conducted by the Centers for Disease Control and Prevention. As part of the 2003 -20 04 NHANES, urinary concentrations (μg/L) of triclosan (2,4,4’ -trichloro-2’ - hydroxydiphenyl ether) were measured on a random sample of 2,517 participants of ages 6 and over. T hese measurements represent concentrations in spot urine samples, and the corresp onding human dose (μg/kg - day) was not measured or estimated by NHANES or CDC . Various methods have been proposed to estimate the dose from the measured concentration , but they can be categorized into two main groups: one that uses measured pesticide conce ntrations in urine directly and the other that standardizes urinary concentrations on the basis of creatinine, a by- product of metabolism wh ich is felt by some to be less variable than urinary output . A total of seven dose conversion variations are presen ted in this document (and are designated Dose1 to Dose7). These are summarized below:

 Mage Method: Mage et al . (2004, 2007) use the estimated daily creatinine excretion for a demographic group ; the triclosan concentration is divided by the creatinine co ncentration, multiplied by the daily creatinine excretion in μg/day, and divided by the body weight. There are three variations on this, designated as Dose1, Dose2, and Dose3 .  PANNA Method: Schafer et al (2004) use the estimated daily urine excretion in L/day and the average body weight for a demographic group; the triclosan concentration is multiplied by the daily urine excretion in L/day, and divided by the average body weight. There are two variations o n this method, designated as Dose4 and Dose5 .  Gei gy Method: For specific situations, some researchers at t he EPA Office of Research and Development (ORD) use the estimated daily urine excretion in L/kg - day for a demographic group; the triclosan concentration is multiplied by the estimated daily urine exc retion in L/kg - day. However, at this time, no ORD -wide approach has been adopted. The two variations on this method , using urine excretion data from Geigy (1981), are designated as Dose6 and Dose7. In this memorandum we describe the various conversion m ethods and compare the results by demographic group for the estimated triclosan dose. An important caveat to all the reported results should be noted: In this review, the pharmacok inetics of triclosan have not beenPage 2 of 30 Dose Conversion

ICF International accounted for in the dose estimate becau se the use of human data would require prior approval by the Human Studies Review Board (HSRB) . The calculations presented here assume 100 % of triclosan is excreted in urine. In fact, a pharmacokinetic study has shown that only about 50 % of triclosan is excreted in urine. On this basis, all the dose estimates presented in this memorandum ought to be doubled (approximately). This constant adjustment factor does not affect the comparative results. In general, all the proposed methods, excluding the Geigy upper bound method (Dose7) , give similar estimates for the geometric mean and median dose, but the overall means are up to 35% higher for the PANNA and Geigy methods compared to the Mage methods. The overall 99 th percentile is up to 75% higher. T he highest estimated dose, based on the upper bound Geigy case, was 138 μg/kg - day . 

## NHA**NES** Since the 1960s, the National Center for Health Statistics, a division of the Centers for Disease Control and Prevention has conducted the National Health and Nutrition Surveys (NHANES), a series of US national surveys of the health and nutrition status of the non - institutionalized civilian population. NHANES 2003 to 2004 included laboratory measurements on 9,643 subjects. This analysis uses urinary concentrations of triclosan (2,4,4’ -trichloro-2’ - hydroxydiphenyl ether) me asured in urine spot samples of 10 0 μL collected from a random onethird sample of 2,517 subjects of ages 6 and older. The dose conversion calculations also used the NHANES measurements of creatinine concentrations, body weight, body height, as well as the age, gender, and race of each sub ject. The NHANES 2003 -2004 data were obtained from the NHANES website: www.cdc.gov/nchs/nhanes.htm The NHANES use a complex multi -stage, stratified, clustered sampling design. Certain demographic groups were deliberately over-sampled, including Mexican -Americans and Blacks. The publicly released environmental phenols file L24_eph_c.xpt with the triclosan data includes survey weights to adjust for the one -third random sampling as well as for the over-sampl ing of certain demographic groups, non - response, and non - coverage. The statistical analyses used the laboratory survey weights (WTSCYR) to re- adjust the urinary triclosan data to represent the national population. NHANES also includes the strata and primary sampling unit (PSU) survey design parameters to account for the stratification and clustering, but (for confidentiality reasons) the public release version provides approximate pseudo-values for these parameters instead of the actual values. The statisti cal analyses used the pseudo-strata and pseudo- PSU values to properly account for the uncertainty of the survey estimates and thus to compute confidence intervals for the estimated dose. NHANES urinary metabolite concentration data are not collected in a way to directly determine the dose, and CDC has not reported dose estimates for triclosan based on NHANES measurement data. 

## T **RICLOSA N**  Triclosan is a synthetic, broad -spectrum antimicrobial that has been used extensively for more than 20 years in a variety of consumer products. Human exposure from triclosan is expected to occur either through ingestion or dermal absorption. For more detailed discussion on triclosan uses and exposure pathways, please see Calafat et al, 2007. The NHANES 2003 -2004 includedPage 3 of 30 Dose Conversion

ICF International me asured urinary concentrations of total triclosan (free plus conjugated species) on 2,517 randomly selected subjects of ages 6 years and over. Total triclosan was measured on 100 μL samples using on - line solid - phase extraction coupled to high performance li quid chromatography- isotope dilution -tandem mass spectrometry. The lower detection limit was 2.27 μg/L. 75% of the samples (survey-weighted) were above the detection limit. For these analyses, we followed the CDC recommended approach that substitute s the l imit of detection divided by the square root of 2 for all non - detects (values below the detection limit). Measured concentrations ranged from 2.3 to 3,790 μg/L. The geometric mean concentration (surveywe ighted) was 13 μg/L. More details about the NHANES triclosan data as well as summary statistics and regression analyses for triclosan (μg/L) and triclosan/creatinine (μg/g), are provided in Calafat et al, 2007. To confirm our calculations, we calculated the same summary statistics (geometric mean, 10 th , 25 th , 50 th , 75 th , 90 th , and 95 th percentiles, with 95 percent confidence intervals) for the same demographic groups , both for triclosan and triclosan/creatinine. Our tabulations are shown in the attached Excel file “dose.conversions. 030608 .xls.” W e used SAS and SUDAAN software for these calculations. The geometric means and confidence intervals either agreed exactly (most cases) or differed by 0.1. The differences for the percentiles were larger. For example, for all subjects, Cal afat et al (2007) report the 50 th percentile triclosan (μg/L) as 9.2 (7.9- 10.9) but our calculations gave 9.5 (8.7 - 11.0). Similarly, Cal afat et al (2007) report the 95 th percentile triclosan (μg/L) as 459.0 (386.0- 522.0) but our calculations gave 463.0 (393.0 - 527.0). These differences are likely due to the percentile calculation algorithm. W e tried various alternative approaches but we re not able to get exact agreement for any of the methods that we tried. To calculate the percentiles and their confidence intervals fo r triclosan, tric losan/creatinine, and the estimated dose we used the CDC method given in CDC 2005, Appendix C. First, the percentile is estimated using the survey weights and the SAS default method (in PROC UNIVARIATE). Second, SUDAAN is used to estimate the proportion of values below the estimated percentile, the standard error of the estimated proportion, and hence the degrees -offreedom - adjusted effective sample size (see Korn and Graubard, 199 9 , p . 65). Third, the Clopper- Pearson method is used to calculate a 95% confidence interval for the proportion in step 2. Fourth and finally, the percentiles corresponding to the estimated proportion and its lower and upper bound are estimated using the survey weights and the SAS default method. Confidence intervals around the me an, geometric mean, 90 th percentile, 95th percentile, and 99 th percentile do not fully account for the variability/uncertainty inherent in each of the parameters, and the combination of variability and uncertainty across all of the combined parameters, use d in estimating the dose. For example, the procedures use an assumption of steady state exposure. This may not be the actual situation for many or most individuals, so the variability associated with different exposures at different time intervals for different durations prior to measurement may not be captured. The impact of parameter variability and uncertainty are of particular concern for dose estimates made for an individual for many chemicals. On the other hand, because of the large NHANES sample size , some of the variability may already be captured in the data set. More work in this area is needed. W hile it is difficult at this time to generate accurate confidence intervals or uncertainty bounds, the se analyses only account for the statistical variab ility across the estimated dose estimates for the population ignoring any uncertainty and variability in the dose conversion equations themselves. By comparing the results across the different dose estimation methods, we address only some of the uncertainty in the dose conversion.Page 4 of 30 Dose Conversion

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## D **OSE CONVERSION** The NHANES triclosan data are spot urine samples for which the concentration in μg/L was measured. To interpret these concentrations is difficult because they cannot be directly related to a health effect. EPA evaluates health effects in terms of a reference dose that represe nts the daily intake in mg or μg per kilogram body weight that is not expected to be associated with an adverse health effect. The conversion of measured spot urine concentrations to daily doses is difficult because of highly variable dilution caused by wi de fluctuations in the fluid intake and excretion. Dose calculation is also difficult because there is no way to determine from the NHANES data how (oral, dermal, inhalation) and when (duration and time interval prior to measurement) the actual contact wit h the chemical occurred, and because of uncertainty and variability in the absorption, distribution, metabolism, and excretion (ADME) parameters. If NHANES collected total daily urine excretion for each participant, then that participant’s dose could be accurately estimated by multiplying the triclosan concentration by the total daily urine excretion and then dividing by the body weight. However, NHANES only collected spot urine samples so that total urine excretion was not measured. The Schafer et al (2004 ) dose conversion methods and the similar methods used by some ORD researchers estimate the daily urine excretion using average values for a given age/gender group. The Mage et al (2004, 2007) dose conversion methods are based on estimates of the daily cre atinine excretion (μg/day) from various studies relating the daily creatinine excretion to age, gender, race, weight, and height. The dose is estimated by multiplying the concentration per g of creatinine by the estimated daily creatinine excretion and the n dividing by the body weight. These alternative methods are detailed in this section. Wealso note that we have assumed throughout this discussion that triclosan and other analytes of interest are not metabolized so that all the ingested analyte is excreted in the urine . To apply these same methods to parent contaminants that are metabolized, it is necessary to make two further adjustments to estimate the dose. The first adjustment is the ratio of parent to metabolite molecular weight. The second adjustme nt is the ratio of mols of parent ingested to mols of metabolite excreted in the urine. Human pharmacok inetic data do exist for triclosan but would require prior approval by the HSRB before the Office of Pesticides Program (OPP) can use the data in risk assessments. As mentioned above, a pharmacokinetic study has shown that only about 50 % of triclosan is excreted in urine. On this basis, all the dose estimates presented in this memorandum ought to be doubled (approximately). 

## Mage **et al ( 2004** **): Dose1** Mag e et al (2004) derived creatinine excretion rates for adults 18 and older using creatinine clearance equations that were obtained by Cockcroft and Gault (1976) based on 24 - hour urine data from 249 male and 18 female adults in Canada. They obtained the foll owing equations: Creatinine Excretion (μg/day) = 1.93 (140 – Ag e) W eig ht 1.5 Height0.5 , M ales 18+ (1) Creatinine Excretion (μg/day) = 1.64 (140 – Ag e) W eig ht 1.5 Height0.5 , Females 18+ (2) In these equations, and throughout this memorandum, Age is age in years, We ig h t is weight in kg, H eight is height in cm. The dose conversion equation is given by:Page 5 of 30 Dose Conversion

ICF International Dose (μg/kg - day) = {Triclosan (μg/L) / Creatinine (μg/L)}  Creatinine Excretion (μg/day) / W eig ht (3) To compare this method to the other dose conversion methods, we applied the same equations to all adults and children, regardless of age. The creatinine conversion Equation 3 uses the concentration of creatinine to adjust for varying urine volumes, due to variation among the individuals in a demographic group and due to variation within the same individual, e.g., the higher levels of fluid intake and excretion in the hotter summer season. Creatinine is a natural metabolic byproduct of muscle tissue creatine. Creatinine is picked up by the blood at a rate roughly propo rtional to the amount of muscle tissue. Additional amounts of creatinine are obtained from dietary red meat intake or from creatine body- building supplements. Creatinine, triclosan, and other blood solutes are excreted from the blood into the urine by pas sive glomerular filtration and/or by secretion through the renal tubules. Assumptions:

 The subjects in the creatinine studies are representative of the demographic groups.  The spot sample triclosan/creatinine ratio is representative of the 24 - hour ave rage.  Subjects have reached steady state, equilibrium conditions with respect to creatinine and triclosan urinary concentrations (in particular, this assumes an approximately constant daily triclosan exposure).  For each demographic group, the absorption, distribution, metabolism, and excretion (ADME) parameters are the same across all individuals and are constant within individuals over time.  Subjects are omnivorous, neither eating excessive red meat nor being strictly vegetarian (since creatinine increase s with the amount of red meat eaten).  Subjects are moderately active (neither sedentary nor body builders).  Subjects are healthy (kidney disease or muscle wasting diseases such as Duchenne muscular dystrophy or Cushing’s syndrome reduce the creatinine exc retion rate).  Subjects do not exceed the triclosan’s tubular secretion transport maximum, so that the tubular secretion mechanism is not saturated and the process is (approximately) linear.  Subjects are not on medicines such as penicillin that reduce creat inine tubular secretion.  Subjects have not been significantly exposed to other contaminants, since if not, those contaminants might compete for the same carrier protein used to facilitate tubular secretion.  Subjects are not taking creatinine dietary supple ments.  Subjects have moderate muscle mass.  Subjects do not have febrile disorders.  Subjects do not have decreased renal function (e.g., caused by GFR or tubular disorders).  Female subjects are not pregnant (since pregnancy increases creatinine excretion).Page 6 of 30 Dose Conversion

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## Mage et al (2007) without obes **ity correction: Dose2**  Mage et al (2007) extended the analyses of Mage et al (2004) to include creatinine excretion rates for children and to make adjustments for race, obesity, and continuity. In this section we present t he equations without the extra adjustment for obesity. The list of assumptions needed for these analyses is the same as the list in the previous subsection “Mage et al (2004).” Since the demographic groups are smaller (including separate groups for childre n and by race), the assumption that the creatinine subjects are representative of their demographic groups is more valid. The Mage et al (2007) includes creatinine excretion equations for children up to 36 months (from Viteri and Alverado, 1970), child ren ages 3 to 18 years (from Remer et al, 2002), and adults 18 and older (from Cockcroft and Gault, 1976). In this memorandum we do not report or use the equations for children up to 36 months since the urinary triclosan concentration data, and, indeed, most of the NHANES concentration data, are only for persons ages 6 and older. The following creatinine excretion equations were used, together with the dose conversion E quation 3. Creatinine Excretion (μg/day), Males 3 - 14, Height 90 - 168 cm, = 1.085 Heigh t {6.265 + 0.0564 (Height – 168)} M  1000 (4) Creatinine Excretion (μg/day), Males 3 - 14, Height 168 - 186 cm, = 1.085 Height {6.265 + 0.2550 (Height – 168)} M  1000 (5) Creatinine Excretion (μg/day), Males 15 - 17, Height 90- 168 cm, = 1.085 He ight {6.265 + 0.0564 (Height – 168)} {1 + 0.045 (Age – 14) B} M  1000 (6) Creatinine Excretion (μg/day), Males 15 - 17, Height 168- 186 cm, = 1.085 Height {6.265 + 0.2550 (Height – 168)} {1 + 0.045 (Age – 14) B} M  1000 (7) Creatinine Excretion (μg/day), Males 18+, = 0.926  1.93 (140 – Ag e) We ig ht 1.5 Height0.5 (1 + 0.18 B) (8) Creatinine Excretion (μg/day), Females 3 - 14, = 1.008 Height {2.045 exp(0.01552 (Height – 90)} F  1000 (9) Creatinine Excretion (μg/day), Females 15 - 17, = 1.008 Hei ght {2.045 exp(0.01552 (Height – 90)} {1 + 0.045 (Age – 14) B} F  1000 (10) Creatinine Excretion (μg/day), Females 18+, = 0.993  1.64 (140 – Ag e) We ig ht 1.5 Height0.5 (1 + 0.18 B) (11) In these equations, B is the indicator for Black, Non - Hispanic, based on the NHANES variable RIDRETH2 that re- assigns the race to the main race category if a subject reports multiple races and also reports a primary race. Note that the NHANES public release data does not separate race and ethnicity. The available cate gories are: W hite, Non - Hispanic; Black, Non - Hispanic ; Mexican - American ; and Other. M and F are adjustments for children’s body surface area when their body weight does not equal the median weight for their age:Page 7 of 30 Dose Conversion

ICF International B = 1, if Black, Non - Hispanic B = 0, if not Black, Non - Hispanic (12) M = {We ig ht / [14 + 1.433 (Age – 3) + 0.22 (Age – 3) 2

– 0.00533 (Age – 3) 3] } 0.5 (13) F = {W eig ht / [14 + 0.4 (Age – 3) + 0.52 (Age – 3) 2

– 0.024 (Age – 3) 3] } 0.5 (14) A few comments are needed to explain how the Ma ge et al (2007) equations were interpreted. In Mage et al (2007) , E quations 5 and 6 are assumed to apply to males 15 - 18. The adjustment factors 1.085 and 0.926 in E quations 4 to 8 were chosen by Mage et al (2007) to make the equations continuous at age 18 for a male of the median height and weight. Thus E quation 8 is the continuity- and race-adjusted version of E quation 1. However, these adjustments do not make the equations consistent at age 18 for a male of a different height or weight. Therefore we assum e here that E quations 5 and 6 only apply to males 15 - 17 and not to males 18 or over (where E quation 8 applies). Similarly, for females, the factors 1.008 and 0.993 were chosen by Mage et al (2007) to make the E quations 9 to 11 continuous at age 18 for a fe male of the median height and weight, and we decided here to make E quations 9 and 10 apply to females 15 - 17 only. Another issue is that Mage et al (2007) do not state how the category Black, Non Hispanic is to be defined for NHANES data, although it is app arent from the text that the intended adjustment is for all Black persons but it has to be applied to the slightly smaller category Black, Non - Hispanic since Black is not reported as a separate category in the public release version. Weused the RIDRETH2 d efinition since it appears from the tabulated results that is the definition used in the triclosan paper by Calafat et al, 2007. The impacts of these choices are expected to be small since the number of NHANES subjects affected is small. 

## Mage et al (2007) **with obes ity**  **correction: Dose3** Mage et al (2007) noted that the creatinine excretion E quations 4 to 14 do not apply for the obese. Subjects with excessive weight for their height caused by ascites (abdominal fluid retention) or an increase in adipose tis sue (non - lean body mass) do not have excess creatinine since serous fluids and adipose tissue do not produce creatinine. Thus the original equations will tend to overestimate creatinine excretion in the obese. For this version of the dose conversion equati ons we applied the following equations from Mage et al (2007) for obese subjects: Creatinine Excretion (μg/day), Obese Males, = (137 – Ag e) (0.0805 + 3.42 / BMI) (15) Creatinine Excretion (μg/day), Obese Females, = (146 – Ag e) (0.081 + 2.75 / BMI) (16) BM I = Body Mass Index = W eig ht (kg) / [Height (m)] 2 (17) Although a more accurate definition of obesity could be obtained based on the waist circumference, and skinfold thicknesses (to separate muscularity from obesity), we used the simple definition of obesity as BMI > 30. Thus for the obesity- adjusted Mage et al (2007) equations we apply E quations 4 to 14 if BMI <= 30 and apply E quations 15 and 16 if BMI > 30.Page 8 of 30 Dose Conversion

ICF International Mage et al (2007) also offer an alternative obesity adjustment method based on estimating lean body mass; we did not use this alternative method. 

## Shafer et al **(2004): Dose4** Shafer et al (2004) , fo r the Pesticide Action Network of North America (PANNA), used a simpler approach based on scaling up the spot urine volumes to the estimated daily urine volume excreted (L/day). They used the following equation: Dose (μg/kg - day) = Triclosan (μg/L)  Urine Volume (L/day) / Average W eig ht (18) They used average urine excretion and weight values quoted from Snyder et al (1975), although those average values are not precisely reported in the tables and graphs in Snyder et al (1975) . Table 1. Urine volumes and body weights used in PANNA (2004), based on Snyder et al (1975) **Gender Ag**  **e Body**  **Weight (kg) Urine volume (L/day** **)** All 6 - 11 30 0.8 All 12 - 19 50 1.0 Female 20 - 59 55 1.1 Ma le 20 - 59 70 1.5 For these analyses we modified the Schafer et al (2004) equations so that the averages for ages 20 - 59 were assumed to apply to all adults 20 and over. Assumptions:

 The average urine volumes (L/day) and body weights (kg) are representative of the demographic groups. More precisely, since only the ratios are used, the assumption is that the ratio of average urine volume to average body weight is representative of the urine volume/weight ratios for the demographic groups.  Subjects have reached steady state, equilibrium conditions with resp ect to triclosan urinary concentrations .  For each demographic group, the absorption, distribution, metabolism, and excretion (ADME) parameters are the same across all individuals and are constant within individuals over time.  The spot sample triclosan con centration is representative of the 24 - hour average. Although the number of assumptions made is only four , these assumptions are very approximate. The first assumption is that body weight and daily urine volume are approximately constant for all subjects in each demographic group, but these values vary appreciably. Mage et al (2007) pointed out that Snyder et al (1975) say that “within an age group, the daily volume of urine probably increases with body size.” They also point out that the variability in da ily urine volume is much greater than the variability in daily urine excretion. For example, for males 9 - 13, they quote that the 5 th to 95 th percentile daily urine volume is from 12 to 43.2 mL/kg -day (Mattson and Lindstrom, 1995) but the daily creatinine excretion is from 11.3 to 27.7 mg/kg - day (Remer et al, 2002). Furthermore, urine volumes are not consistent from day to day and tend to be higher in hot weather; the Mage et al (2004, 2007) method uses the creatinine concentration to normalize this effect.Page 9 of 30 Dose Conversion

ICF International The Schafer et al (2004) approach can be expected to be more accurate if a finer demographic classification could be made available; this assumes that more detailed daily urine volume data can be made available. 

## Schafer et al **(2004) w ith actual body**  **w eig**  **hts: Dose5** The Schafer et al (2004) approach can be slightly improved if the actual body weight is used instead of the demographic group average body weight: Dose (μg/kg - day) = Triclosan (μg/L)  Urine Volume (L/day) / W eig ht (18) Weapplied this revised approach using the same demographic groups as in Table 1. The assumptions are similar:

 The average urine volumes in L/day are representative of the dem ographic groups.  Subjects have reached steady state, equilibrium conditions with respect to triclosan urinary concentrations .  For each demographic group, the absorption, distribution, metabolism, and excretion (ADME) parameters are the same across all indi viduals and are constant within individuals over time.  The spot sample triclosan concentration is representative of the 24 - hour average. 

## Geigy **Method –**  **Mean: Dose6** ORD has not established a standardized or recommended procedure for converting urinary co ncentrations to dose, but they routinely do not correct for creatin in e excretion (as, e.g . , M age does) Although no universally recommended ORD procedure exists, in some situations, some researchers from O RD have and do use a very similar approach to Schafer et al (2004). However, i nstead of using the demographic group average urine volume in L/day , they have us ed the demographic group average urine volume in L/kg - day. This gives the equation: Dose (μg/kg - day) = Triclosan (μg/L)  Average Urine Volume (L/kg -day) (19) Morgan et al (2008) applied this method to estimate the children’s dose of 2,4 - D. Since a default appropriate set of average urine excretion volumes has not been formalized by O RD , and the choice of such standard urine volumes may depend upon the study and the available urine volume data , we have attempted to simulate this method by using age group and body-weight urine excretion volume data from Geigy Scientific Tables (Geigy, 1981). Geigy (1981) provides two tables with urine volume data. Their Table 2 gives the mean (m) and standard deviation (s) of the urine volume (mL/kg -day) for the following groups of ages 6 and above. Since the groups overlap, we re - defined the groups to avoid overlaps:

 “ 5 - 7 years, ” redefined as ages 5 and 6. m = 25, s = 7.  “ 7 - 11 years, ” redefined as ages 7, 8, 9, and 10. m = 25, s = 7.  “ 11 - 14 years, ” redefined as ages 11, 12, and 13. m = 19, s = 3.Page 10 of 30 Dose Conversion

ICF International  ‘Young males, ” not used. To obtain data for adults we used their Table 1, which includes the mean and standard deviation of the urine volume (mL/day) for the following groups:

 “ 33 men, ” redefined as males ages 14 or over. m = 1360, s = 443.  “ 39 women, no ovulation inhibitors, ” redefined as females ages 1 4 or over. m = 1130, s = 423.  ‘ 30 women, ovulation inhibitors. ” m = 980, s = 449. Not used. Note that the two sets of data use different units (mL/kg -day and mL/day) . To calculate the mean and standard deviation for persons 14 and over, we divided the uri ne volume (mL/day) by the body weight. Wealso divided these rates by 1000 to convert from mL to L. Also note that for simplicity we chose not to separate the females according to their use of ovulation inhibitors, although such information can be extracte d from NHANES. For the Geigy – Mean approach we used the values of m to get the mean urine volumes for each age/gender group. Assumptions:

 The average urine volumes in L/kg - day are representative of the demographic groups.  Subjects have reached stead y state, equilibrium conditions with respect to triclosan urinary concentrations .  For each demographic group, the absorption, distribution, metabolism, and excretion (ADME) parameters are the same across all individuals and are constant within individuals over time.  The spot sample triclosan concentration is representative of the 24 - hour average. Just as for Schafer et al (2004), the first assumption is very approximate. 

## Geigy **Method –**  **U pper**  **B ound**  **: Dose7** Finally , we used the above - described (ORD - like) ap proach to get an upper bound estimate of the dose by using information on the variability associated with urine volumes (specifically, the standard deviation listed in the Geigy (1981) publication) . Assuming the urine volumes are normally distributed, the 95 th percentile urine volume is given by 95 th percentile urine volume = Mean + Z 95  Standard Deviation (20) Z 95 is the 95 th percentile of a standard normal distribution, approximately 1.68. The values of mean and standard deviation are estimated by the values of m and s in the subsection “Geigy Method – Mean.” To calculate the mean and standard deviation for persons 14 and over, we divided the m and s for urine volume (mL/day) by the body weight. The upper bound dose estimate is then given by: Dose (μg/kg - day) = Triclosan (μg/L)  95 th Percentile Urine Volume (L/kg - day) (21)Page 11 of 30 Dose Conversion

ICF International This estimate is not the 95 percentile estimated dose, but rather an upper bound estimate of the mean dose which was derived by using an 95 percentile urine volume. If a ll the dose conversion assumptions applied, if the triclosan concentration was exactly measured, and if the only uncertainty and variability was the urine volume, then this estimate would also be the 95 th percentile estimate dose for that subject. 

## RESULT**S** Weapplied the seven dose conversion methods listed in the previous section to the NHANES 2003 -2004 triclosan data. The attached Excel file “triclosan.data. 030608 .xls” contains the raw data and the estimated doses for each subject. The “Variables” worksheet lists and describes the variables in the database and the “TRICLOSAN” worksheet contains the data. The same data is provided in the SAS file “triclosan.sas 7 bdat.” The SAS code used is in the attached SAS program “convert. 030608 .sas.” Using the s ame demographic groupings as in Cal afat et al (2007), we calculated various summary statistics for the triclosan concentration, triclosan/creatinine, and the seven estimated dose values. W e computed the mean, geometric mean, and selected percentiles. Weal so computed 95% confidence intervals for these summary statistics. The detailed results are given in the attached Excel file “dose.conversions. 030608 .xls.” The means, geometric means, medians, and 99 th percentiles for each dose conversion method are compared in the attached Excel file “dose.conversions.short version. 030608 .xls” and in Table 2. Wecan examine Table 2 in detail to compare the dose conversion methods overall and for different demographic groups. Since the D ose7 method is intended to be an up per bound estimate, we will discuss the other six dose conversion methods. For all subjects, the means vary from 1.4 (Mage et al methods Dose2 and Dose 3) to 1.9 ( Schafer et al method Dose4 ) μg/kg -day, so that the maximum difference is 35%. However, the dif ferences in the means when population subgroups are considered range from 22% for females to 67% for children ages 6 - 11 and 72% for black, non - h ispanics. For the age group 6 - 11, the minimum is 0.6 for D ose1 (Mage et al (2004)) and the maximum is 1.1 for D ose5 ( Shafer et al (2004) with actual body weight). This difference is mainly because the Mage et al (2004) approach was based on data from adults and was intended to be applied to adults 18 and older. The Mage et al (2007 ) paper extends the analysis to chi ldren and these revised equations give a mean dose of 0.9 for children ages 6- 11. For the black, non - h ispanic group , the minimum estimated dose is 1. 07 ug/kg -day derived from Mage et al (2004) while the maximum estimated dose is 1.8 3 ug/kg day from the S chafer et al (2004) Dose 4 approach . Similar findings apply to the geometric means and medians. For all subjects the geometric means range from 0.22 to 0.27 (25% difference ) and the medians range from 0.15 to 0.20 (29% difference ). The biggest differences are for the black, n on - h ispanic subpopulation where the geometric means differ by 57% and the medians differ by 70%. In general the lowest estimated doses are for the three Mage et al . methods ( D ose1 - D ose3), and the highest estimated dose is for the Schafe r et al (2004) Dose4 method , with the ORD -type method (Dose6) providing intermediate estimates. The 99 th percentile dose estimates show even larger percentage differences. For all subjects, the 99 th percentiles range from 1 6 (Mage et al, 2007) to 27 ( Schafer et al , 2004), a 75%Page 12 of 30 Dose Conversion

ICF International difference. The biggest demographic group differences are 243% (7 to 25) for the 6 - 11 age group and 200% (12 to 36) for black, non - hispanics . The same comparisons are displayed graphically in Figures 1 to 13 . Figure s 1 to 3 di splay all the mean, geometric mean, and 99 th percentile dose estimates , respectively, fo r each demographic group. The dose is plotted on a linear scale. Figures 4 to 13 display the mean, geometric mean, 90 th , 95th , and 99 th percentile dose estimates fo r th ree methods on a logarithmic scale . Each of Figures 4 to 13 shows all the summary statistics fo r a different demographic group. The three methods shown are Mage et al (2007) with obesity correction (Dose3), Schafer et al (2004) with actual bodyweights (Dos e 5), and the Geigy Method – Mean (Dose6). As shown in Table 2 and Figures 1 - 3 , the Geigy Method – Upper Bound dose estimate is the highest of the seven estimated doses. This is, of course, expected, since this method was intended as an upper bound metho d. The maximum 99 th percentile estimate d dose was 62.4 μ g/kg -day for the Mexican -American group. The maximum estimated dose for all subjects was 138 μ g/kg -day.**Table 2. Selected summary statistics for estimated triclosan dose (ug/kg**  **- day), by calculation**  **method*, age, gender, and race.** **Mean Geometric Mean**  **Median 99th Percentile**  **Group 1**  **2 3**  **4 5**  **6 7**  **1 2**  **3 4**  **5 6**  **7 1**  **2 3**  **4 5**  **6 7**  **1 2**  **3 4**  **5 6**  **7** All 1.5 1.4 1.4 1.9 1.6 1.6 2.4 0.2 0.2 0.2 0.3 0.2 0.2 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.3 16.8 15.5 15.5 27.2 23.6 23.6 38.1 6 - 11 0.6 0.9 0.9 1.0 1.1 0.9 1.3 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.1 0.1 0.1 0.2 0.1 0.1 0.2 7.2 10.9 10.9 10.3 24.6 9.7 14.2 12 - 19 1.5 1.4 1.4 2.3 1.7 2.2 3.4 0.2 0.2 0.2 0.3 0.2 0.3 0.4 0.2 0.1 0.1 0.2 0.2 0.2 0.3 20.1 16.6 16.6 42.0 25.5 28.8 46.5 20 - 59 1.7 1.6 1.5 2.0 1.7 1.6 2.6 0.3 0.3 0.3 0.3 0.2 0.2 0.4 0.2 0.2 0.2 0.2 0.2 0.2 0.3 20.6 19.1 19.1 28.1 29.1 29.9 48.3 >= 60 1.1 1.1 1.0 1.5 1.2 1.2 1.8 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.1 0.1 0.1 0.1 0.1 0.1 0.1 14.4 14.1 14.4 21.4 17.1 14.8 22.7 Male 1.9 1.8 1.7 2.4 2.0 2.0 3.0 0.3 0.3 0.3 0.4 0.3 0.3 0.4 0.2 0.2 0.2 0.3 0.2 0.2 0.3 20.6 19.0 19.0 36.0 35.1 35.2 54.1 Female 1.1 1.1 1.1 1.3 1.1 1.2 1.9 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.1 0.1 0.1 0.2 0.1 0.1 0.2 14. 2 14.9 14.7 23.4 17.8 17.6 28.5 Mexican -American 2.0 2.0 1.9 2.6 2.3 2.2 3.5 0.3 0.3 0.2 0.3 0.3 0.3 0.4 0.2 0.2 0.1 0.2 0.2 0.2 0.3 26.0 24.0 20.6 44.4 42.4 40.6 62.4 Wh ite, Non - Hispanic 1.5 1.4 1.4 1.8 1.5 1.5 2.3 0.3 0.2 0.2 0.3 0.2 0.2 0.3 0.2 0.2 0. 2 0.2 0.2 0.2 0.2 15.0 15.0 15.0 23.4 16.3 19.0 29.1 Black, Non - Hispanic 1.1 1.2 1.1 1.8 1.6 1.5 2.3 0.2 0.2 0.2 0.3 0.2 0.2 0.4 0.2 0.2 0.1 0.2 0.2 0.2 0.3 12.1 14.0 13.7 36.3 26.1 28.3 45.6 * Calculation Method: 1. Mage et al (2004). 2. Mage et al (2007), without obes ity correction. 3. Mage et al (2007), with obes ity correction. 4. Schafer et al (2004). 5. Schafer et al (2004) with actual bodyweight. 6. Geigy Method - M ean. 7 . G eigy Method – Upper Bound .Page 27 of 30 Dose Conversion

ICF International 

## CONCLUSION NHANES urinary metabolite concentration data are not collected in a way to directly determine the dose, and CDC has n ot reported dose estimates for triclosan based on NHANES measurement data . The conversion of measured spot urine concentrations to daily doses is difficult because of highly variable dilution caused by wide fluctuations in the fluid intake and excretion. D ose calculation is also difficult because there is no way to determine from the NHANES data how (oral, dermal, inhalation) and when (duration and time interval prior to measurement) the actual contact with the chemical occurred, and because of uncertainty and variability in the absorption, distribution, metabolism, and excretion (ADME) parameters. We have presented several alternative methods of estimating human dose (μg/kg - day) from a spot urine concentration ( μg/L) of an analyte and applied these methods to NHANES 2003 -2004 triclosan concentrations . The analyses presented in this document assumes that total triclosan is fully excreted in the urine. Therefore, the use of these analyses for risk assessment purposes will require correction for human pharmacok inetics. There are essentially two main approaches for this conversion. The creatinine adjustment approach of Mage et al (2004, 2007) uses an estimate of the daily creatinine excretion (L/day) for each demographic group and applies this to the analyte/cre atinine concentration ratio. The urine volume adjustment approach using the methods of Schafer et al (2004) or the ORD -type methods (as used by some ORD researchers in some situations) appl ies the estimated daily urine volume in L/day or L/kg - day , respecti vely, to the analyte concentration. Wi thin these two main approaches, different versions use different sets of equations or tables for the estimated daily creatinine or urine excretion by demogra p hic group. In general the two main approaches give similar results for the mean, median, and geometric mean. The differences between the two main approaches are more pronounced at the 90 th and higher percentiles. T here are smaller differences between the different versions of these approaches. The ORD -type method i s preferable to the Schafer et al (2004) method since urine volumes can be expected to increase with increased body size. For triclosan, all subjects, the means are up to 35% higher for the urine volume adjustment methods compared to the Mage methods. The 99 th percentile is up to 75% higher. The Mage et al approach requires numerous assumptions for its validity:

 The subjects in the creatinine studies are representative of the demographic groups.  The spot sample analyte/creatinine ratio is representative of the 24 - hour average.  Subjects have reached steady state, equilibrium conditions with respect to creatinine and analyte urinary concentrations.  For eac h demographic group, the absorption, distribution, metabolism, and excretion (ADME) parameters are the same across all individuals and are constant within individuals over time.  Subjects are omnivorous, neither eating excessive red meat nor being strictly vegetarian .  Subjects are moderately active.Page 28 of 30 Dose Conversion

ICF International  Subjects are healthy .  Subjects do not exceed the analyte ’s tubular secretion transport maximum .  Subjects are not on medicines such as penicillin that reduce creatinine tubular secretion.  Subjects have not been significantly exposed to other contaminants .  Subjects are not taking creatinine dietary supplements.  Subjects have moderate muscle mass.  Subjects do not have febrile disorders.  Subjects do not have decreased renal function (e.g., caused by GFR or tubular disorders).  Female subjects are not pregnant. Of these assumptions the steady state assumption , the related assumption that the spot sample analyte/creatinine concentration ratio is representative of the concentration ratios over the 24- hour period, and the assumption about not reaching the tubular secretion transport maximum are difficult, if not impossible, to verify since there are no NHANES data available to check these assumptions . In particular, the recent paper by Scher et al (2007) throws some dou bt on the representativeness of spot urine samples. Using NHANES data, some of the other assumptions can be evaluated, and, if creatinine excretion data are available, further adjustments can be made for those subjects. W e note that a recent presentation by Dr. Allen discusses an additional 20% adjustment for pregnancy. The Mage et al approach is also relatively complex. The urine volume adjustment approach is simpler. The main assumption s are that the daily urine excretion is constant across each demograp hic group , and that absorption, distribution, metabolism, and excretion (ADME) parameters are the same across all individuals in a demographic group and are constant within individuals over time. The method also makes a steady state assumption and the related assumption that the spot sample analyte concentration is representative of the concentration over the 24- hour period. As applied by Schafer et al (2004) or by our analyses of the ORD -type method using the Geigy (1981) tables, the demographic groups appear to be too broad and would benefit from a large set of urine excretion data by demographic group so that the urine volume adjustment approach could be refined and more accurately applied. Ideally, this data would contain information on both intra and i nter- person variability in 24 hour urinary volumes so the issue of whether the urinary volume or creatinine excretion is more stable could be addressed. Mage et al (2007) point out some disadvantages of the urine volume adjustment approach . They note that the creatinine excretion rates are less variable than urine excretion rates for the same demographic groups , and also that the urine volume adjustment approach does not adjust for the within - person variability of urine excretion such as due to increased fluid intake in hot weather. Since Mage et al . normalize the analyte concentration by the creatinine concentration, the Mage et al approach better adjusts for the within - person variability. This assumes that (i) the Mage creatiine excretion equation more accurately predicts creatine excretion; and (ii) that intra- individual (e.g, day-to-day) percent variability in creatine excretion is smaller than the corresponding figure for urine volume. This could be addressed by looking at the intra - class correlatio n coefficient, if data are available. If the triclosan results hold more generally, the urine volume adjustment approach results in estimates of dose that are higher than the Mage et al creatinine adjustment approach . Therefore, the urine volume adjustm ent approach is more conservative (i.e. , more protective ofPage 29 of 30 Dose Conversion

ICF International human health) . A more conservative approach may be better given the uncertainties in the dose conversion from spot urine samples . However, it is not clear whether the same finding would apply to other analytes. Different readers will reach different conclusions about which method to recommend. My own feeling at this time is that the ORD -type method based on urine volume in L/kg - day is preferred for routine analyses, since it is simpler to apply a nd explain , requires fewer assumptions for its validity, and may well be more conservative. The crucial issue is to decide wh ich is a more accurate estimator for an given individual : a L/kg -day estimate based on the age group or of the individual of interest or a gram creatin in e excretion rate as estimated for that individual using the Mage et al (2007) equation. Also of value is to decide how consistent is within individual (day-to-day) variability of L/kg urine volume vs. day-to- day variability in creatinine excretion. However, for routine application of the ORD -type method it is necessary to find a compendium of urine excretion data for several demographic groups (by age, gender, race), since the Snyder et al (1975) and Geigy (1981) urine excretion d ata are more generalized . For less routine analyses, the Mage et al (2007) method can be used , but t he results should be compared to the ORD -type method. 

## ACKNOWLEDGEMENT This note acknowl edges the comments and editorial suggestions from the EPA OPP and ORD reviewers of the first draft. In several cases I have used their suggested additional text in this revised draft. 

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ICF International Mattsson S., Lindstrom S. 1995. Diuresis and voiding pattern in healthy schoolchildren. Br J Urol. 76:783 - 789. Morgan, Marsha K, Sheldon, L.S. ,Thomas, K.W. , Egeghy, P.P. ,C roghan, C. W. , Jones , P.A., Chuang, J.C. and W ilson N.K. 2008. Adult and children's exposure to 2,4 - D from multiple sources and pathways, J. Exp. Sci. Environ. Epid emiol. Advanced online publication 2 January 2008; doi: 10.1038/sj.jes.7500641 . Availab le at: http://www.nature.com/jes/journal/vaop/ncurrent/pdf/7500641a.pdf Remer T., Neubert A., Maser- Gluth C. 2002. Anthropometry- based reference values for 24 - h urinary creatinine excretion during growth and their use in endocrine and nutritional researc h. Am J Clin Nutr

. 75:561 - 569. Scher D.P., Alexander B.H., Adgate J.L., Eberly L.E., Mandel J.S., and Acquavella J.F., et al. 2007. Ag reement of pesticide biomarkers between morning void and 24 - h urine samples from farmers and their children. J Expo Sci E nviron Epidemiol. 17(4): 350–357. Viteri F.E., Alvarado J. 1970. The creatinine height index: its use in the estimation of the degree of protein depletion and repletion in protein calorie malnourished children. Pediatrics 46:696 - 706. Schafer, K.S., Reeves, M., Spitzer, S., Kegley, S. E. 2004. Chemical Trespass: Pesticides in Our Bodies and Corporate Accountability. Pesticide Action Network North America. May 2004. Snyder, W .S., Cook M.J., Nasset E.S., Karhausen, L.R., Howells, G.P., Tipton, I.H. 1975. International Commission on Radiological Protection, No. 23 . Report of the Task Group on Reference Man. Oxford, Pergamon Press .