Urinary Arsenic Excretion as a Biomarker of

Arsenic Exposure in Children

YAW-HUEI HWANGInstitute of Occupational Medicine

and Industrial HygieneCollege of Public HealthNational Taiwan UniversityTaipei, Taiwan, Republic of China

ROBERT L BORNSCHEINJOANN GROTEWILLIAM MENRATHSANDY RODADepartment of Environmental HealthCollege of MedicineUniversity of CincinnatiCincinnati, Ohio

ABSTRACT. Urinary arsenic concentration has been used generally for the determination ofexposure, but mucb concern has been raised over the most appropriate expression for uri-nary arsenic levels. In this study, we examined the influence of various adjustments ofexpressing urinary arsenic data. All children who were less than 72 mo of age and who werepotty trained were invited to participate in the present study. Urine, soil, and dust sampleswere collected, and arsenic measurements were made. The geometric mean of speciated uri-nary arsenic among children who provided first-voided urine samples on 2 consecutivemornings was 8.6 (ig/I (geometric standard deviation = 1.7, n = 289). Speciated urinaryarsenic was related significantly to soil arsenic in bare areas (p < .0005). Use of a singleurine sample versus the average of two first-voided urine samples collected on 2 consecu-tive mornings did not significantly alter the relationship between environmental arsenic andurinary arsenic levels. Furthermore, none of tbe adjustments to urinary concentrationimproved the strength of correlation between urinary arsenic and soil arsenic levels. Con-centration adjustments may not be necessary for urinary arsenic levels obtained from youngchildren who provide first-void samples in the morning.

IN ADDITION TO the arsenic that is distributed nat-urally in air, water, soil, and food, arsenic exposure alsoresults from some human environmental activities (e.g.,mining and processing of metals). In epidemiologicalstudies, occupational inhalation of arsenic has beenassociated with lung cancer.^"'' In addition, uptake ofarsenic via ingestion is associated with several cancers(e.g., skin, liver, bladder, kidney).'*"^'^ Risk assessmenttherefore becomes an important issue in the preventionof potential hazards from environmental arsenic expo-sure. In this type of assessment, correct measurement ofexposure of arsenic is essential for the accurate deter-mination of dose.

Urinary arsenic concentration has been used for de-

termination of exposure and for estimation of healthrisks. Not only is a urine sample the most readily avail-able biological medium for estimating exposure, but75% of the ingested inorganic arsenic, mono-methylarsenic (MMA), or di-methyl arsenic (DMA) is excretedin urine within 3 d after exposure.""'^ Several methodsof hydration adjustment have been developed for theestimation of urinary concentrations of these exoticsubstances.'"'"'^ Adjustment for urinary creatinine ex-cretion is the most commonly used in published stan-dards (e.g., biological exposure indices [BEI] of theAmerican Conference of Governmental Industrial Hy-gienists).'•* Other methods, such as specific gravity ad-justment and determination of timed excretion rate of

March/April 1997 [Vol. 52 (No. 2)] 139

substances in urine, have been developed and are usedwidely for exposure evaluations.'^'*> In addition, severalinvestigators have recently proposed that urinary flow-adjusted creatinine ratio controls for the effect of urinaryexcretion rate on the urinary concentration.'^"*'^0'^'Nonetheless, the most appropriate method for express-ing urinary concentration remains a topic on whichthere is little agreement. Furthermore, most of the pub-lished literature is based on data from adults and notfrom children. Therefore, in this study we took theopportunity to evaluate urinary arsenic concentrationadjustment methods, especially in children.

This study took place in Anaconda, Montana, in thesummer of 1992 through the summer of 1993. Weexamined the influence of various methods of express-ing urinary arsenic on the strength of association withenvironmental arsenic. For this purpose, we adjustedthe urinary arsenic, based upon the most commonlyused urinary adjustments. We compared these adjustedurinary arsenic concentrations with respect to theirstrengths of correlation with soil arsenic concentration.It was hypothesized that creatinine adjustment wouldbest explain the variance in urinary arsenic levels.

Material and Method

The study area was the town of Anaconda, Montana,and the surrounding vicinity. Almost 100 y of smelteroperations produced waste materials, including tailingsand flue dust, that now cover approximately 4 000acres." The entire smelter complex ceased operationsin September 1980. In 1983, the Environmental Protec-tion Agency placed this site on the Superfund NationalPriority List (NPL) for priority cleanup.

Prior to initiation of the current study, we undertooka door-to-door census in April and May, 1992, to deter-mine how many families and children (< 72 mo of age)were in the proposed study area. All families with age-appropriate and eligible children (i.e., < 11 mo of ageand potty trained) were invited to participate. The chil-dren had to have resided at their current addresses forat least 3 mo. Study participation was strictly voluntary.Following verbal and written descriptions of the study,we asked participants to sign an informed consent state-ment.

In addition to the initial census survey, we adminis-tered questionnaires during the study period to collectdetailed individual and familial information on partici-pating children's demographic and behavioral charac-teristics; participating families' socioeconomic status,residence location, housing condition, and housing his-tory; and general environmental conditions with respectto potential arsenic exposure. At the times the monitor-ing team collected soil, dust, and urine samples, teammembers completed corresponding forms on whichdetailed collection information about each child-specif-ic sample (e.g., date, time, place, area) was recorded.

Sample collection included soil, interior dust, andurine samples from study children. Exterior soil samplesof the top 2 cm of soil were collected with a coringdevice. Five different types of soil samples were col-

lected from each residential parcel occupied by the par-ticipating family. These five types of soil samples includ-ed the following perimeter soil samples collected fromfour sides of the residence; bare-area composite soilsamples collected from all bare areas in a yard; garden-area composite soil samples collected from all gardenareas; if present, sand box or dirt play area samples; andgravel or hardpack drive/parking area samples. After airdrying and sieving with a 250-^m mesh, we used aKevex Delta Analyst Energy Dispersive x-ray spectrom-eter to measure the arsenic in approximately 2 g of aloose soil sample.

Interior surface dust, which was collected in the resi-dence in accordance with a previously developedmethod,-^ was a composite of at least three subsamplestaken from (a) an area adjacent to the main entrance, (b)a floor area in the room most used by the subject child,and (c) a floor area in the subject child's bedroom. Thedried and weighed dust sample was processed for aciddigestion with 7N nitric acid and I N nitric acid, afterwhich we submitted it for arsenic determination by aPerkin Elmer graphite furnace atomic absorption spec-trometer (AAS).

The first-voided morning (FVM) urine samples werecollected from each child participant on 2 consecutived. After collection, we placed the sample and frozenblue ice in the small cooler. These samples were trans-ferred later to a 125-ml polyethylene bottle that con-tained nitric acid for acidification; the samples werethen frozen for storage. A stratified random sample of25 children drawn from the main study cohort wasrecruited, and these children provided 24-h urine sam-ples. During this collection period, the children had toremain at home (i.e., on the property) for 24 h. Duringthis 24-h period, each child provided 3 urine samples:two samples were the first urine voids provided on 2consecutive mornings (described earlier), and the thirdwas designated as the mid-day urine sample. The thirdsample represented a composite of subsamples voidedbetween the two consecutive first voids of the morn-ings.

At the field office, we analyzed urine samples for spe-cific gravity by an optical refraction method.-"^ At thelaboratory of Environmental Sciences Associates (ESA),researchers measured creatinine with a colorimetricmethod, using the Sigma Diagnostics Creatinine Kit.^^Routine urine sample analysis for arsenic was per-formed at the ESA laboratory. We used two methods tomeasure urinary arsenic. First, we used a modifieddigestion method to analyze total urinary arsenic,which includes inorganic arsenic, methylated arsenic,and fish arsenic (e.g., arsenobetaine, arsenocho-line).^^'^^The samples—which were acid digested witha mixture of nitric, perchloric, and sulfuric acids—wereanalyzed on a hydride-generation system attached to aflame AAS, Perkin-Elmer Model 2380 Flame AAS with aPerkin-Elmer MHS-10 [HG-FAAS]). We used the secondmethod to determine combined As^\ As^^ monomethy-larsonic acid (MMA), and dimethylarsinic acid (DMA),ail of which are the major arsenic species and/ormetabolites found in urine after exposure to inorganic

140 Archives of Environmental Health

arsenic, and they are referred to collectively as speciat-ed urinary arsenic. These arsenic urinary compoundscan be reduced by sodium borohydride and they pro-duce a volatile hydride, whereas other organic arsenicscannot.^^ Therefore, the analytical method for the spe-ciated urinary arsenic was based on the direct analysisof the urine sample, which was pretreated with 3%sodium borohydride, on the HG-FAAS.

In this study, we applied the four most commonlyused urinary concentration adjustment methods tocompare the resulting expressions of urinary arsenicconcentration that are described below.

1. Specific gravity adjustment, AsUsc (|Jg/I)- ^ Forthis method, we assumed that the excretion of xeno-biotics and urinary solutes (i.e., producers of urine'sspecific gravity) was stable. Only the elimination rate ofthe solvent (water) differed. The purpose of the specificgravity adjustment method is to remove the effect thatvarious hydration states have on the urinary concen-tration. All urinary concentrations are therefore ad-justed to the same specific gravity for further com-parison. The equation of this adjustment is as follows:

AsUsc = (Urinary Arsenic x 0.020)/(Specific Gravity- 1.000).

2. Creatinine adjustment, ASUCN ((ig/g).^^ Adjust-ment of urinary arsenic concentration to urinary crea-tinine excretion is accomplished simply by dividing themeasured urinary arsenic concentration (|ig/i) byurinary creatinine concentration (g/l), as shown below.Given that urinary volume is the denominator for bothconcentrations in this ratio, this volume factor is can-celed out, and, therefore, the hydration effect need notbe considered further.

AsUcN = (Urinary Arsenic, )ig/l)/(Creatinine, g/I).

3. Timed excretion rate, ASUTE (^g/8 h). ^ Timed ex-cretion rates are typically calculated for a 24-h period;this controls for any effects of diurnal rhythms. None-theless, 24-h urine collection is extremely inconvenientfor research study subjects, and it is difficult to preventthe loss of some of the serial samples. In the presentstudy, therefore, we used the first-voided urine sampleof the morning to represent the sleeping period. Thecorrected timed excretion rate was calculated as shownbelow and was normalized to an 8-h period for pur-poses of comparison.

ASUTE = KUrinary Arsenic, ng/l) x (Void Volume, I)X 8 hl/Elapsed Time Since Last Void, h.

4. Urinary flow rate adjusted creatinine ratio,AsUuFd^g/I)-^^'^" With respect to the urinary flow ad-justed creatinine ratio for arsenic, both urinary arsenicconcentration and urinary creatinine concentrationshould be adjusted to a urinary flow of 1 ml/min, ac-cording to the formula U * V'\ where U = measuredconcentration and V = urinary flow (ml/min).''' Thesetwo adjusted concentrations form a ratio (as was thecase for simple creatinine adjustment) that provides the

urinary flow rate adjusted creatinine ratio. The equationfor this calculation is as follows:

AsUuF = (Urinary Arsenic, \ig/\ -H Creatinine, g/l)X (Urinary Flow Rate, ml/min)*" ''^'-.

Urinary flow rate (ml/min) was calculated as totalvoid volume (ml) divided by the elapsed time since lastvoid (min). We calculated the bi and bj values, basedon the dataset of 24-h urine samples, by the leastsquares method and in accordance with the followingtwo equations (ai and 2 are intercepts for each regres-sion line):

log(Urinary Arsenic, |ig/l)= ai - 6i X logjUrinary Flow Rate, ml/min),

log(Creatinine, g/l)= a2 - bi X log(Urinary Flow Rate, ml/min).

We entered the data collected from questionnairesand results gleaned from laboratory analyses into theFoxBA5E-f-/Mac database system on a Macintosh per-sonal computer for storage and error checking.-^ Weused the Statistical Analysis System for Personal Com-puters (SAS-PC)^" to perform data analyses.

Given the log-normal distribution, we transformedurinary arsenic and environmental arsenic data to theirlog equivalents, and estimates of the sample geometricmean and geometric standard deviation were obtained.Simple bivariate correlations among the exposure vari-ables and dependent variables were then calculated.We also performed correlational analysis between thesefour methods for adjusting urinary arsenic and soilarsenic concentrations for the purpose of examining thestrength of association between each expression of uri-nary arsenic and soil arsenic. We assumed that themore the observed variance in urinary arsenic wasexplained by the environmental arsenic, the more validthe urinary adjustment method for expressing urinaryarsenic levels.

We used a multiple regression analysis to find themost parsimonious model for predicting the urinaryarsenic level. We used a backward stepwise process toselect the important variables that contributed to themodel. Model predictors included arsenic level in barearea soil; child's age, height, weight, gender, and bodysurface area; an index of hand-to-mouth behavior; urinespecific gravity; and urine creatinine. Only variablessignificant at the .05 level remained in the final model.

Results

The resultsof the door-to-door census revealed a totalof 480 families that contained 642 children who wereless than 72 mo of age and who lived in or near Ana-conda. Some families refused to participate or hadmoved prior to environmental sampling; therefore, only412 (85.8%) families participated in the present study.We recruited only age-appropriate potty-trained chil-dren for urine collection. Thus, 414 children in 334families served as study subjects in the urine arsenicevaluation.

March/April 1997 [Vol. 52 (No. 2)] 141

As noted previously, we intended to collect urinesamples on 2 consecutive d to provide a more stableestimate of arsenic excretion. However, not all childrenprovided first-voided urine samples on 2 consecutivemornings. Also, if a sample contained an abnormallylow level of creatinine, indicative of a very dilute urinespecimen, the arsenic result was excluded from analy^sis because the arsenic concentration might be spuri-ously low. In addition, the sample sizes of speciated uri-nary arsenic and total urinary arsenic in the dataanalysis might be different because there were difficul-ties encountered in each analytic process. As a result,urinary arsenic levels were available for 404 children.Of these 404 children, total and speciated urinaryarsenic levels available on the 2 consecutive d wereobtained from 312 and 289 children, respectively. Theintent was to perform statistical analyses based on first-voided urine samples provided on 2 consecutive morn-ings; therefore, children who provided only one urinesample were excluded from the analyses. Nevertheless,there was no significant difference between the childrenwho provided two urine samples and the excluded oneswith respect to most demographic factors (e.g., height,weight, gender, race). Only the average age of the chil-dren who provided two urine samples (52.6 mo) wasslightly older than the average age of those who wereexcluded (47.8 mo).

Descriptive data for recruited children who providedfirst-voided urine samples on 2 consecutive morningsare provided in Table 1. The body surface area of eachchild was determined from a nomogram, which wasbased on children's height and weight.-*' With respect tothe urine samples, the average volume of the first urinevoid of the morning was 54.4 ml (standard deviation =23.6 ml). The mean urinary creatinine and specific grav-ity were similar to those of the general population inthis age range.

The results of the soil and dust arsenic measurementsand urine arsenic levels are shown in Table 2. Soilarsenic levels were summarized for five sample typesdescribed previously. The geometric means of arsenic indifferent types of soil ranged from 121 |ag/g to 236 ng/g(geometric standard deviations [GSDs] - 1.9-2.3).

Perimeter soils and bare area soils in yards tended tohave higher levels of arsenic contamination than soilsamples collected in hardpack areas, garden areas, andplay and/or sand box areas. Also shown in Table 2 is theinterior dust arsenic level. A total of 477 interior dustsamples were collected from the houses in the studyarea. The geometric mean of arsenic levels in all interi-or dust samples was Vi fig/g {GSD = 1.84).

We determined total and speciated urinary arseniclevels for each urine sample and averaged the two con-secutive urine samples for each child. Descriptive sta-tistics for total urinary arsenic levels of 312 children arepresented in Table 2. The geometric mean of total uri-nary arsenic for all children examined was 19.1 |jg/liGSD = 1.9). This level was slightly higher tban that ofchildren in the control communities of previous arsenicexposure studies (17 |ag/l). - Results of speciated urinaryarsenic analysis indicated that the geometric mean ofspeciated urinary arsenic was 8.6 (ig/l iCSD = 1.7). Thismean level was less than that reported in the Tacomastudy, in which the median of uncorrected speciatedurinary arsenic for children aged 0-6 y was 15.0 | ig / l . "

A correlation coefficient matrix of the pertinent bio-logical and environmental variables is shown in Table 3.This matrix evidences the simple relationships betweenarsenic exposure and urinary arsenic levels. Speciatedurinary arsenic was correlated moderately with totalurinary arsenic (r = .59). Correlations among arsenicconcentrations in various environmental sample types(e.g., soil arsenic, dust arsenic) were moderate to strong(i.e., r = .42 to .77). Soil in bare areas in yards had thehighest correlation with speciated urinary arsenic levels(r = .25), whereas weaker correlations existed for theotber four types of soil samples (r= .12 to .20). Also, thecorrelations between soil arsenic levels and total urinearsenic were not significant. On the other hand, and incontrast to initial expectations, arsenic in interior dustdid not correlate well with either type of urinaryarsenic.

On the basis of first and second morning first-voidedurine samples collected in the present study, we per-formed multiple regression analyses of various charac-terizations of urine arsenic levels (i.e., highest [HIGH-

Table 1.—Descriptive Statistics on Study Samples

Variable

Age (mo)Height (cm)Weight (kg)Gender (% male)Race (% white)Body surface area (m )First morning void (ml)Creatinine (g/l)Specific gravity

Note: N = 271 children.

X

52.6104.2

16.548.397.40.704

54.41.0921.026

5D

14.510.63.6

0.12323.60.3960.005

Only children with complete data for all

5thpercentile

28.688.311.4

0.51517.00.4801.017

nine variables

95thpercentile

74,0121.322.7

0.89594.0

1.8001.033

are presented.

142 Archives of Environmental Health

EST], lowest [LOWEST], two consecutive urine sampleaverage [AVERAGE], and day 1 [DAY 1 ] and day 2 [DAY2] urine datasets). Although we included nine variablesin the original model, only four variables were retainedafter backward elimination. The following is the best-fit-ted regression model with the selected variables:

ln(Speciated Urinary Arsenic)= a + pi ln(soll arsenic level in bare areas in yards)

+ p2 child's body surface area+ p3 ln(urinary creatinine)+ p4 child's hand-to-mouth behavior index.

The parameter estimates for different urinary arseniccharacterizations are shown in Table 4. The intercept,slope for each predictor, and percentage of explainedvariance for each model are provided. According to theslope values and the standard errors in the parentheses,these slopes did not differ significantly from one otherfor any of the predictors nor was there a significant dif-ference among the intercepts of these regression lines.Also, the percentages of explained variance (r-) in theseregression models were very similar to one another. Theresults suggest that, when evaluating the relationshipbetween speciated urinary arsenic and arsenic expo-sure variables, use of the highest, the lowest, the 2 con-secutive day average, the day 1 or the day 2 of urinesamples, does not affect the final result of the relation-ship studied. Thus a single first-voided morning samplemay be sufficient for the characterization of large pop-

ulations. Therefore, we used only the AVERAGE urinaryarsenic to show the descriptive statistics of the unad-justed and adjusted total and speciated urinary arsenicconcentrations (Table 5). Whereas the mean urinaryarsenic concentration varied according to the adjust-ment method used, the geometric standard deviationsof various expressions of urinary arsenic concentrationdid not differ much from one another, except for thegeometric standard deviations of the corrected time-

Table 2.—Arsenic MeasurementsSamples

Sample/area

Soil sample arsenic (|ig/g)Perimeter areaBare areaHardpack areaGarden areaSandbox area

Interior dust samplearsenic fMg g)

Tolal urinary arsenic ( ig/i)AverageHighest

Speciated urinary arsenic (jig/l)AverageHighest

in Soil,

n

435373237184354

477

312312

289289

Dust, and Urine

GM

236229121167177

73

19.123.5

8.610.4

CSD

1.91.92.22.32.3

1.8

1.92.0

1.71.8

Table 3.—Correlation Coefficient Matrix of Urinary Arsenic,

Total urinaryarsenic (|Jg/l)

Speciated urinaryarsenic (|ig/l)

Perimeter area soilarsenic ((j.g/1)

Bare area soilarsenic (|ig/l)

Hardpack area soilarsenic (iig/l)

Garden area soilarsenic (tig/l)

Sandbox area soilarsenic ( ig/l)

Interior dustarsenic (|ag/l)

Notes. All variables*p < .0005.+p< ,05.

Totalurinaryarsenic

0.59*(282)

0.04(282)

0.00(243)

-0.09(146)

0.10(132)

0.01(280)

0.01(3101

had been log

Speciatedurinaryarsenic

0.1 7t(260)

0.25*(226)

0.20+(134)

0.20+(121)

0.12+(257)

0.03(286)

Perimeterarea soilarsenic

0.77*(404)

0.60*(256)

0.64*(202)

0.65*(389)

0.45*(470)

Soil Arsenic, and Interior Dust Arsenic

Bare areasoil

arsenic

0.67'(224)

0.55*(165)

0.64*(335)

0.47'(404)

transformed before correlation analysis;

Hardpackarea soilarsenic

0.52'(112)

0.50'(206)

0.47'(256)

Gardenarea soilarsenic

0.56*(172)

0,42*(203)

sample sizes appear within

Sandboxarea soilarsenic

0.52*(391)

parentheses.

March/April 1997 [Vol. 52 (No. 2)] 143

excretion rates for both total and speciated urinaryarsenic. Perhaps this occurred because the adjustmentmethod involved two factors (i.e., urine volume andelapsed time), as well as urine arsenic concentration inits equation, whereas each of the other three methodsinvolved only one factor. The involvement of more fac-tors in the equation may have increased the variabilityof the derived data and the resulting geometric standarddeviations.

The correlation coefficients of various forms of cor-rected urinary arsenic concentrations and other perti-nent variables in this study are shown in Table 6. Log-transformed speciated urinary arsenic levels, eithercorrected or not corrected, were more correlated withsoil arsenic than were total urinary arsenic levels. Onthe other hand, explained variance in urinary arsenicafter these adjustments did not increase as expected.Generally, various procedures of adjustment on arseniclevels did not improve correlations between urinaryarsenic and environmental arsenic levels.

Discussion

It has been reported that 45%-85% of arsenic ingest-ed in the human body is excreted in urine within 1-3

dJ^"'^ Thus, urinary arsenic is considered a reliableinternal biomarker for recent arsenic exposure. Inor-ganic arsenic, rather than organic arsenic, is consideredto be the toxic form of arsenic; therefore, the metabo-lites of inorganic arsenic in urine ("speciated urinaryarsenic") are of prime interest.

The present study contained several features thatmaximized the probability that the highest urinaryarsenic levels would be observed, that the highestarsenic sources would be detected, and that the rela-tionship between environmental sources and urinaryarsenic be characterized correctly. As was mentionedearlier, the recruitment strategy focused on young chil-dren who were less than 71 mo of age (average = 52.6mo) —a group known to be at greatest risk for elevatedarsenic exposure. Urinary arsenic sampling was carriedout during the summer, a time when seasonal factorscombined to yield the highest urinary arsenic levels.The focus of measurement was on those sources andforms of arsenic that were immediately accessible to ayoung child (e.g., arsenic in interior house dust, in soilof bare areas in yards, in soil around the house perime-ter, in sand box and/or play area soil). During the courseof analyzing samples for arsenic content, attention wasfocused on that fraction of the environmental source

Table 4.—Comparison of Regression Models

Speciated_As

Highest

Lowest

Average

Day 1

Day 2

Intercept(a)

2.29(0.32)2.06(0.34)2.10(0.33)2.06

(0.34)2.54(0.35)

Notes: Intercept and slopes tortheses. Allregressionand day 2

Bodysize

(cm^)

-1.45(0.27)-1.51(0.28)-1.32(0.27)-1.39(0.28)-1.78(0.29}

each model

Slopes (/3)

Hand_mouth Creatinine(freq./wk)

0.09(0.02)0.08

(0.02)0.09(0.02)0,08(0.02)0.09(0.03)

(g/l)

0.65(0.08)0.55

(0.07)0.41

(0.07)0.63(0.07)0.78(0.08)

are shown, and standard errors

Soil B(Hg/I)

0.18(0.04)0.17(0.05)0.19(0.05)0.19(0.05)0.15(0.05)

r

0.35

0.34

0.30

0.36

0.40

appear within paren-intercepts and slopes for each model were significant at p < .005. We compared themodels by using the highest, thedatasets for speciated arsenic.

lowest, the 2-consecutive-day average, and the day 1

Table 5.—Descriptive

Correctedurinary arsenic

AsU (Mg/l)AsUsc (Hg/I)AsUcN (Mg/g)ASUTE (^g^8 hr)

AsUuF (^g/l)

Statistics

GM

19.217.912.50.54

19.0

for Uncorrected and

Tota

CSD

1.91.81.82.31.8

As (n = 287)

5thpercentile

7.07.05.00.147.8

Corrected

95thpercentile

63.047.032.5

1.7250.2

Urinary Arsenic Concentrations

GM

8.68.35.80.278.8

5peciated_As (n =

GSD

1.71.81.82.01.8

5thpercentile

4.03.02.60.083.5

263)

95thpercentile

23.021.015.30.73

22.5

144Archives of Environmental Health

Table 6.—Correlation Coefficienls of Corrected Urinary Arsenic

AsU*ASUSG'

ASUCN'ASUTE*

AsUuF*

AsU-AsUsc*AsUcN*ASUTE*

AsUuF*

Note: NA =

SoilB*

.28t

.24t

.21 +

.20+

.20+

.01

.08

.05

.03

.05

Age

-.25+-.32+-.44+-.11-.47+

-.13§-.26+-.40+-.04-.40+

not appropriate.'Log-transformed.ip < .0005*p < .005.§p < .05.

Height

-.26+-.32+-.44+-.09-A7f

-.13§-.24+-.38+-.04-.38+

WeightBodysize

and the Study Variables

Hand_mouth'

Speciated urinary arsenic (n = 205)

-.26+-.30+-.39+-.09-.43+

-.28+-.33 +-.43+-.11-.47+

.28+

.28+

.32+

.19§

.31 +

Total urinary arsenic (n = 222)

-.13§- . 2 1 *-.34+-.05-.35+

-.13§-.23+-.37+-.05-.37+

.18§

.26+

.29+

.12

.29+

Gender

.02

.05

.08

.09

.07

-.02.00.04

-.01.03

Sp-gravity

.19§NA

-.34+.18§

-.36+

.29+NA

-.20+.32+

-.19+

Creatinine*

.26+-.09

NA.29+NA

.32+-.09

NA.40+NA

tfiought to produce t!ie greatest risk to the c!ii!d (i.e.,arsenic in small partic!es !< 250 | im] found in surfacesoil and dust t!iat most readily adhered to hands andtoys) and that could be ingested inadvertently. !n gener-a!, the present study, which contained these features,offered us the best opportunity to eva!uate the re!ation-ship betvi/een environmenta! arsenic !eve!s and theinternal dose of chi!dren wi th arsenic exposure. Esti-mates of the impact of various independent variables{soil arsenic, dust arsenic, etc.) cou!d be developed,using regression techniques. Thus, with a sufficient!ywide range of exposure, which encompassed bac!<-ground exposure !evels, we cou!d obtain estimates ofthe impact of environmental arsenic sources via dataderived from wi th in the study areas. The effects of vari-ous urinary concentration adjustments can, therefore,be evaluated wel l .

Even [hough we demonstrated that soil arsenic levelswere correlated significant!y with urinary arsenic con-centration, the percentage of explainable variance in uri-nary arsenic was low. This situation might be attributedto the arsenic sources other than soil and dust, as well tothe low urinary arsenic !evels found in the study area.Not a!! arsenic in urine originated from mining relatedactivities. Some undefined fraction of arsenic a!so origi-nated from dietary arsenic {i.e., water and food), where-as arsenic exposure via inhalation and skin contact mayhave been a!ternative pathways for the environmentalsources. !n the study area, the air arsenic leve! was quitestab!e and was we!! !3e!ow the nationa! average leve! forremote areas.^^ Based upon an average air arsenic con-centration of 0.0021 ng/m^ during the year prior to thepresent study, we ca!cu!ated that the amount of estimat-ed respiratory arsenic accounted for on!y 0.7% of theaverage dai!y arsenic excreted in urine for chi!dren aged

24-72 mo. The va!ue is so smal! that its contribution tourine arsenic may be neg!ected. Wi th regard to waterarsenic, the measured water arsenic !eve! was 1.36 j ig/!in the municipal water-supply system, which supplied81.3% of the househo!ds studied. Most of the waterarsenic leve!s in private wel!s were below 5 j ig/! {aver-age = 2.5 fig/!). Despite the fact that concentrations werelow, water arsenic accounted for a significant por t ion—about 2 1 % - 4 5 % of the chi!dren's daily speciated uri-nary arsenic output—in the present study. However, weconsidered the arsenic that tap water contributed to tota!arsenic intake to be ref!ected in bac!<ground urinaryarsenic !evels—and not as the primary factor—for theexp!anation of differences in speciated urinary arsenic!evels among the study children. The !ow urinary arsenic!evels found in the study area were li!<e!y a reflection of!ow availability of some forms of arsenic in contaminat-ed soil. The resu!ts of recent micro-ana!ysis of soil parti-cles in the residentia! study area, for which an electronbeam microprobe was used, suggested !imitations ofbioavailability^^ of arsenic derived from mine mil l andsme!ter waste present in residential soi!s. A recentlycomp!eted anima! feeding study provided further evi-dence of !ow bioavailabi!ity of arsenic found in Anacon-da soils.^*'The resu!ts also indicated that arsenic in thiskind of soi! was !ikely to occur in a !ess-so!ub!eform andwas, therefore, !ess absorbable than sodium arsenate.These factors likely accounted for the re!atively low per-centage of variance in urinary arsenic exp!ained by theenvironmenta! soil arse- nic levels.

Urinary concentrations of exotic chemica!s vary overa wide range. Each xenobiotic may need correction bya specific adjustment method, thus enabling examina-tion of the relationship to external exposure leve!s.!mprovements in methods of urinary concentration

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adjustment have increased the reliability of this biolog-ical monitoring process; however, no clear standardexists for the correction of varying effects of urinaryflow, dilution, and elapsed time of void. Among urinaryconcentration adjustment methods developed to date,we chose four of the most commonly used methods tocorrect the urinary arsenic concentration in the presentstudy, and we compared the effect of each adjustmenton the strength of association between environmentalarsenic exposure and corrected urinary arsenic concen-trations. None of them, however, improved the strengthof this association significantly.

Creatinine and specific gravity are the most com-monly used urinary concentration adjustments in clini-cal and industrial hygiene studies. Both of these adjust-ments attempt to correct for the variation in degree ofhydration.'-'^' It is assumed that creatinine is excretedat a constant rate; therefore, we assume further that cre-atinine can be used to normalize untimed urine sam-ples to the amount of creatinine found in a given vol-ume of urine. Nonetheless, creatinine excretion mayvary with many factors (e.g., diurnal variation, bodymass, age, gender, health, diuresis [urine flow], drugand alcohol use, diet, exercise).^^ Similarly, specificgravity adjustment may be a convenient surrogate fortimed samples, but it also suffers the same problems asdoes creatinine adjustment. Thus, both adjustments ap-pear to be relatively imprecise for the reflection of sub-stance concentrations. The present study provided sup-porting evidence for this viewpoint inasmuch as neitheradjustment improved the strength of association be-tween urinary arsenic and soil arsenic.

The third adjustment method, urinary flow-adjustedcreatinine ratio, has been developed recently. This tech-nique corrects for urinary flow rate and for urinary cre-atinine.'' Araki et al . ' " reported that the concentrationsof some metals and organic chemicals, including crea-tinine, were correlated with urinary flow rate. Theytherefore proposed a mathematical adjustment methodthat corrected for substance concentration to a standardurinary flow rate of 1 ml/min, based on a log-log rela-tionship between urinary flow rate and concentration ofthe studied substance. Unfortunately, on the basis of theresults of the present study, this method did not improvethe strength of association of soil arsenic with urinaryarsenic. It was shown that neither urinary arsenic con-centration nor urinary creatinine concentration wasassociated with urinary flow rate or urinary volume.This observation did not accord with the assumptions ofthis adjustment method. It should be noted that urinesamples used in the present study were first morningvoids. The time period prior to the voids most likely rep-resented the elapsed time of the sleeping period. Thus,the variability in activity level and food and water con-sumption during this period was relatively stable, com-pared with that during any other time period of the day.Effects of diet, state of hydration, and diuresis on urinaryflow were expected to be reduced. This might explainwhy this adjustment, based upon urinaty volume or uri-nary flow rate, did not affect the association of urinaryarsenic with environmental arsenic level.

In general, urinary concentration adjustments—rec-ommended for some other chemical substances—arenot necessary for urinary arsenic elimination, at leastnot for the young children's first morning void samplesat the exposure levels seen in the present study. Thissuggests that the appropriateness of urinary concentra-tion adjustments depends not only on the urinary flowbut also on the substance—and quite likely on the sam-pling protocol.

Submitted for publication April 11,1996; accepted tor publication)une25, 1996.

Requests for reprints should be sent to Dr. Y. H. Hwang, NationalTaiwan University College of Public Heaith, Room 1453, #1 Jen-AiRoad, Sec. 1, Taipei, Taiwan, ROC.

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