ORIGINAL ARTICLE

Jae-Yeon Jang á Pierre O. Droz

Ethnic differences in biological monitoring of several organic solventsII. A simulation study with a physiologically based pharmacokinetic model

Received: 14 October 1996 /Accepted: 29 November 1996

Abstract To improve the reliability of biological moni-toring and the development of biological limit values,ethnic di�erences in the biological monitoring of severalorganic solvents were studied in Orientals and Cauca-sians. Six Caucasian and six Oriental volunteers wereexposed to each organic solvent in an exposure chamberfor 6 h at rest. The exposure concentrations were 50 ppmfor perchloroethylene, 50 ppm for styrene, and 100 ppmfor m-xylene, respectively. Experimental results werecompared with simulation results of a physiologicallybased pharmacokinetic (PB-PK) model. Di�erencesbetween Orientals and Caucasians under occupationalexposure were also estimated by extrapolation. Thesimulation results obtained for the Caucasian groupshowed good agreement with the experimental results.However, the Oriental group did not show good agree-ment when the same metabolic parameters values ap-plied to Caucasians were used in the PB-PK model. Bymodi®cation of the metabolic parameters it was possibleto get a good ®t between the model and the results of theOriental group. The simulation results obtained for oc-cupational exposure also showed di�erences in biologi-cal levels between the two ethnic groups. Implications ofthese di�erences between experimental and simulationresults are discussed in the context of the application ofbiological monitoring and in the development of bio-logical limit values.

Key words Ethnic di�erence á Physiologically basedpharmacokinetic model á Organic solvent á Biologicalmonitoring

Introduction

In the development of biological monitoring, very limitedattention has been paid to the ethnic origin of the data thatare used in establishing biological limit values. Althoughsome studies mention the possibility of ethnic di�erencesbased on observations in workers (Inoue et al. 1986, 1988;Jang et al. 1993; Seiji et al. 1989), ethnic di�erences usuallyhave not been considered in the application of biologicalmonitoring. Ethnic di�erences have been reported in thekinetics of several organic solvents between Orientals andCaucasians in an experimental exposure study (Jang et al.1996). Di�erences in the kinetics of chemicals can be dueto several factors, which can be grouped into two cate-gories: physiological factors and metabolic factors (Drozand Savolainen 1990).

Di�erent ethnic groups have di�erent physiologicalfactors such as body size, body composition, and renalfunction. These factors might in¯uence the kinetics ofchemicals. Di�erent ethnic groups can also have di�er-ent enzymatic functions, which a�ect the metabolicprocesses. If the contribution of metabolism to ethnicdi�erences is small, these di�erences in the kinetics ofchemicals might be explained in terms of physiologicalfactors alone. However, if the contribution of metabo-lism to ethnic di�erences is great, this has to be con-sidered not only in the establishment of biologicalexposure limits but also in the application of thoselimits. More than physiological factors, di�erences inmetabolic processing of these chemicals potentially af-fect the relationships between the external exposure andthe internal dose as well as the systemic health e�ects. Itis di�cult to di�erentiate between the e�ects of thesetwo types of factors on the kinetics of chemicals becausetheir results are identical. However, this can be done by

Int Arch Occup Environ Health (1997) 70: 41±50 Ó Springer-Verlag 1997

J.-Y. Jang (&)Department of Occupational and Environmental Medicine,Ajou University, San 5, Wonchon-dong, Paldal-gu,Suwon 442-749, KoreaFax: +82-331-219-5294e-mail: jangjjy@chollian.dacom.co.kr

P.O. DrozThe Institute of Occupational Health Sciences,Lausanne University, Rue de Bugnon 19,CH-1005 Lausanne, Switzerland

simulation using a physiologically based pharmacoki-netic (PB-PK) model.

Another important point is that ethnic di�erences inthe kinetics of some organic solvents identi®ed on short-term experimental exposure (Jang et al. 1996) might besmaller than what is found in workers. This is due to thelower exposure doses applied in experimental protocolsas opposed to levels of industrial exposure (repetition ofexposure, physical work load). PB-PK models can beused to extrapolate from isolated to repeated exposure.Droz and Savolainen (1990) simulated the e�ect ofphysiological and metabolic di�erences between di�er-ent ethnic groups using a PB-PK model. Although it wasa speculative study, the principle and method applied inthat study can be used to explain the implications ofother experimental studies. In this paper we further ex-amine di�erences in the metabolic rates of some organicsolvents between Caucasians and Orientals. A PB-PKmodel is used to explain these di�erences and to predictdi�erences that could be observed in occupational ex-posure situations. The contributions of physiologicaland metabolic e�ects to the total ethnic di�erences areestimated.

Subjects and methods

Exposure and biological monitoring

Six male Caucasians (four Swiss, one Yugoslavian, and one Ar-gentine) and six male Orientals (four Vietnamese and two Koreans)who had been living in Switzerland for at least 6 months volun-teered for this study. The average body height and weight of thevolunteers were 167.8 cm and 61.8 kg for Orientals and 179.8 cmand 75.6 kg for Caucasian, respectively. The solvents studied wereperchloroethylene, styrene, and m-xylene. The exposure targetconcentrations were 50 ppm for perchloroethylene (PCE), 50 ppmfor styrene, and 100 ppm for m-xylene. The exposures were carriedout with the subjects at rest and lasted for 6 h.

The determinants of biological monitoring were solvents inexhaled air and venous blood, trichloroacetic acid (TCA) in urinefor PCE exposure, mandelic acid (MA) and phenylglyoxylic acid(PGA) in urine for styrene exposure, and methylhippuric acid(MHA) in urine for m-xylene exposure. Urine samples were col-lected at 3-h intervals from the beginning of exposure until 9 h afterexposure and on the following morning. The volume of urine wasmeasured for all urine samples collected, and urinary metaboliteswere expressed in terms of the urinary excretion rate for each in-terval. Further details on exposure conditions, biological moni-toring, and analytical methods have been described in a companionpaper (Jang et al. 1996).

Simulation model

The simulations of the behavior of the organic solvents and theirmetabolites in the human body were done using a PB-PK modelcontaining seven compartments (Droz 1992; Droz et al. 1989; Jangand Droz 1996). Table 1 presents the physiological parameters forCaucasians and Orientals that were used in the PB-PK model.Body weight and body height were average values for the volun-teers who participated in this study. Other physiological parametersfor both ethnic groups were calculated together with body heightand body weight by equations suggested in a previous paper (Droz

1992). Table 2 presents the tissue-gas partition coe�cients of thesolvents and metabolic parameters used in the PB-PK model. Thetissue-gas partition coe�cients were calculated from water, oliveoil, and blood-gas partition coe�cients using equations suggestedby Droz et al. (1989).

Styrene and m-xylene were considered to be metabolized viaMichaelis-Menten enzymatic systems. The peak volume (Vmax) andthe Michaelis constant (Km) for m-xylene and styrene were ob-tained from respective animal experiments (Ramsey and Andersen1984; Tardif et al. 1993). Nonlinearities for PCE have also beenreported by several authors. However, the Vmax and Km values usedin PB-PK models by other investigators show large variations(Hattis et al. 1990). For purposes of simplicity and because of thelow exposure levels considered, metabolism was simulated as alinear process governed by ®rst-order kinetics. The intrinsic meta-bolic clearance for PCE was obtained by best ®t of the data on thetotal amount of TCA excreted in the Caucasian group. Urinaryexcretion rates for MHA and MA were obtained from human ex-periments (Sedivec et al. 1983; Senczuk and Orlowski 1978). Uri-nary PGA was usually observed to show excretion rates slowerthan those of MA (Guillemin and Bauer 1979; Perbellini et al. 1990;Sedivec et al. 1983). This slower excretion of PGA relative to MA,however can, come from di�erent rates of formation. In the presentstudy the PGA excretion rate used was obtained by best ®t(0.347 h)1).

The excretion rate for TCA is reported to be very slow: the half-lives of TCA used in PB-PK models by other authors range from50.6 to 96 h (Hattis et al. 1990). Most of these data came fromobservations of TCA on exposure to trichloroethylene (TCE).However, urinary TCA excretion on exposure to PCE appears topresent a di�erent kinetic behavior, the highest value being ob-tained at the end of exposure (Jang et al. 1996). If TCA had a longhalf-life, such as 50.6±96 h, urinary TCA would reach its maximumlong after exposure rather than at the end of exposure. Monster(1986) also reported that the amount of TCA excreted during theperiod of 0±22 h after exposure was much higher than that excretedduring the next period. He proposed that this was due to the

Table 1 Physiological parameters for Caucasians and Orientalsused in the PB-PK modela

Parameters Caucasians Orientals

Body height (cm)b 179.8 167.8Body weight (kg)b 75.6 61.8Body volume (1, BV) 55.25 46.82Tissue volume (1):Lung 0.50 0.42Liver 3.23 2.74Fat 16.12 11.20Muscle 38.01 32.21Kidney 0.29 0.25Brain 1.41 1.20Other tissue 0.57 0.48

Blood ¯ow rate (l/min):Liver 1.68 1.42Fat 0.35 0.25Muscle 1.25 1.06Kidney 1.33 1.13Brain 0.81 0.68Other tissue 1.61 1.36

Cardiac output(l/min) 0/50 W

7.03/11.01 5.90/9.92

Alveolar ventilation(l/min) 0/50 W

5.62/16.73 4.72/15.83

a Calculated by equations suggested by Droz et al (1989)b Data for body weight and body height are averages values for thevolunteers who participated in this study

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presence of an unknown compound with a short half-life, whichwas detected by the nonspeci®c colorimetric method used (Fuji-wara reaction). However, we observed the same phenomenon witha speci®c gas chromatography analysis (Jang et al. 1996). The longhalf-life of urinary TCA observed after exposure to TCE can beexplained by its slow formation. In the case of PCE, accumulationof the parent compound in tissues and its slow excretion into thecirculation system could be the determinant factors. In the presentstudy the TCA half-life used was 4 h as obtained by best ®t of thedata on urinary TCA.

Styrene has been reported to be absorbed through the skin andto be more rapidly absorbed from aqueous solutions than from thevapor phase (Berode et al. 1985; Wieczorek 1985). This suggeststhat styrene can also be absorbed in the bronchial tract. Prelimi-nary simulations showed that the values for all biological deter-minants were much higher than the experimental data.Experimental tests on rabbit trachea in vitro have shown that17.6% of styrene is retained in the trachea (Fiserova-Bergerova1983). Therefore, in the PB-PK model, 20% of styrene in inhaledair was assumed to be absorbed in the bronchial tract and elimi-nated unchanged with exhaled air and not to be absorbed in thecirculation system.

For the expression of urinary excretion of metabolites as cor-rected for creatinine the urinary excretion rate of creatinine wasassumed to be proportional to the lean body volume, with a valueof 1.8 g/24 h being established for a 70-kg, 170-cm-tall man (leanbody volume 50.7 l).

Results and discussion

Table 3 presents a comparison of simulation results withexperimental data for validation of the PB-PK modelused in this study for Caucasians. The results obtainedin the Caucasian group participating in this study wereused as the experimental data for short term exposure.The comparison of urinary metabolites is presented inFigs. 1±4 separately. Results of ®eld studies reported byseveral authors were used as the experimental data foroccupational exposure. For m-xylene, two experimentalsets of data were used for short-term exposure. It isdi�cult to ®nd occupational exposure data on purem-xylene because the commercial xylenes that are used

in industry consist of a mixture of isomers and ethyl-benzene, which is known to in¯uence its metabolism(Lynch, personal communication).

Most of the simulation results showed good agree-ment with the experimental data for short-term exposureas well as with several ®eld studies. Exceptions werestyrene in the venous blood for Caucasians and m-xy-lene in the breath in one experiment. Even the assump-tion of absorption of styrene in the bronchial tract didnot improve the blood-styrene results. Simulation resultsobtained for urinary metabolites were generally withinthe range of the Caucasian volunteers' experimentaldata. It would be possible to develop these data by ®t-ting them to a PB-PK model shows better agreementwith experimental data on human short-term exposure,but such a model would agree less well with occupa-tional exposure data.

Table 4 compares the results of simulations for sev-eral biological determinants with the experimental dataobtained in Orientals in this study. Figures 5±8 showlevels of urinary metabolites determined during and af-ter exposure. When simulations were carried out usingthe same metabolic parameter values applied to Cau-casians, large di�erences were observed between themodel results and the experimental data for Orientals.Therefore, simulations were also carried out usingmodi®ed intrinsic metabolic clearance values for theOriental group. These were estimated from the totalamount of metabolites excreted in urine during thepresent study.

Changes in the intrinsic metabolic clearance of PCEdid not a�ect the simulation results obtained for PCE inexhaled air or in venous blood. PCE is so poorly me-tabolized that changes in the metabolic rate do not in-¯uence the excretion of PCE via exhalation or itsconcentration in venous blood. However, changes in themetabolic rate can directly in¯uence the concentrationof TCA in urine. Therefore, simulation results obtainedfor urinary TCA are largely a�ected by changes in the

Table 2 Simulation parametersused in the PB-PK model (MAMandelic acid, PGA phe-nylglyoxylic acid, MCIS in-trinsic metabolic clearance ofsolvent)

m-Xylene Styrene PCE

Tissue-gas partition Lung 34 59 14coe�cienta Muscle and skin 61 84 29

Fat 3035 4100 1455Brain 124 169 59Kidney 62 84 30Liver 113 154 54Others 79 112 38

Metabolic constant Vmax (mg h)1 kg)1) 8.4b 8.36c ±

Km (mg/l) 0.2b 0.36c ±MCIS (l/min) ± ± 0.0045

Urinary excretion rate 1.386d 0.231e MA 0.173f

of metabolite (h)1) 0.347f PGA

a Droz et al. (1989)b Tardif et al. (1993)c Ramsey and Andersen (1984)d Senczuk and Orlowski (1978)e Sedivec et al. (1983)f Chosen for best ®t

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intrinsic metabolic clearance input into the model. Whenobtained using the same values applied to the Cauca-sians, the simulation results recorded for Orientals

showed large di�erences in relation to the experimentaldata. On the use of an intrinsic metabolic clearancevalue for Orientals that was half of that of Caucasians,

Table 3 Comparisons of the simulation results with the experimental results for Caucasians (creat. creatinine,MHA methylhippuric acid,MA mandelic acid, PGA phenylglyoxylic acid)

Parameter Sampling time Experiment Simulation

PCE:PCE in breath (ppm) End of shift 23 28 Occupational exposurePCE in breath (ppm) Next morning 8 9 (Monster 1986)PCE in blood (mg/l) End of shift 2.3 3.5 50 ppm, 8 h/day,PCE in blood (mg/l) Next Monday morning 0.82 0.85 5 days/weekTCA in urine (mg/g creat.) End of shift 9.7 10.0TCA in urine (mg/g creat.) Next Monday morning 4.9 3.2

PCE in breath (ppm) End of shift 9.5 13.5 Experimental exposurePCE in breath (ppm) Next morning 1.3 0.9 (Caucasian groupPCE in blood (mg/l) End of shift 1.60 1.92 of this study)TCA in urine (lg/min) End of shift 5.07 3.89 50 ppm, 6 hTCA in urine (lg/min) Next morning 1.46 1.59

m-Xylene:m-Xylene in breath (ppm) End of shift 2.3 0.9 Experimental exposurem-Xylene in blood (mg/1) End of shift 0.32 0.34 (Tardif et al. 1991)MHA in urine (mg/min) End of shift 1.21 1.26 40 ppm, 7 hMHA in urine (mg/min) Next morning 0.12 0.10

m-Xylene in breath (ppm) End of shift 2.2 2.4 Experimental exposurem-Xylene in breath (ppm) Next morning 0.2 0.1 (Caucasian groupm-Xylene in blood (mg/l) End of shift 0.61 0.87 of this study)MHA in urine (mg/min) End of shift 3.22 3.17 100 ppm, 6 hMHA in urine (mg/min) Next morning 0.06 0.04

Styrene:MA in urine (mg/g creat.) End of shift 942 1032 Occupational exposureMA in urine (mg/g creat.) Next morning 207 228 (Guillemin and Bauer 1979)PGA in urine (mg/g creat.) End of shift 322 418 50 ppm, 8 h/dayPGA in urine (mg/g creat.) Next morning 199 176 5 days/week

Styrene in breath (ppm) End of shift 0.6 0.6 Experimental exposureStyrene in breath (ppm) Next morning 0.04 0.03 (Caucasian groupStyrene in blood (mg/l) End of shift 0.14 0.34 of this study)MA in urine (mg/min) End of shift 0.40 0.43 50 ppm, 6 hMA in urine (mg/min) Next morning 0.03 0.04PGA in urine (mg/min) End of shift 0.16 0.12PGA in urine (mg/min) Next morning 0.05 0.04

Fig. 1 Comparison of experimental data with simulation resultsobtained for trichloroacetic acid (TCA) in the Caucasian group. Theexposure concentration was 50 ppm PCE for 6 h at rest.Triangles andvertical lines represent mean values and standard deviations ofexperimental data, and the solid line represents simulation results

Fig. 2 Comparison of experimental data with simulation resultsobtained for methylhippuric acid (MHA) in the Caucasian group. Theexposure concentration was 100 ppm m-xylene for 6 h at rest.Triangles and vertical lines represent mean values and standarddeviations of experimental data, and the solid line representssimulation results

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the simulation results showed much better agreementwith the experimental data.

In the case of m-xylene, the simulation results cal-culated for MHA in the Oriental group using the sameintrinsic metabolic clearance value applied to the Cau-casians agreed with the experimental data. The smalldi�erences observed in excretion rates of MHA on ex-perimental exposure, i.e., 3.2 mg/min for the Caucasiangroup and 2.56 mg/min for the Oriental group (Tables 3,4), can therefore be explained by the e�ects of di�erentphysiological factors. When the intrinsic metabolic

clearance of Orientals was assumed to be lower than thatof Caucasians, the simulation results did not di�er(Fig. 6). m-Xylene is highly metabolized, and changes inits real metabolic clearance are therefore very smallwhen intrinsic metabolic clearance varies. It is thus dif-®cult to decide whether Orientals have the same meta-bolic parameter values as Caucasians.

Figure 7 shows that the simulation results calculatedfor MA in the Oriental group using the Caucasians'metabolic rate agree with the experimental data. How-ever, in the case of urinary PGA, the Oriental group

Fig. 3 Comparison of experimental data with simulation resultsobtained for mandelic acid (MA) in the Caucasian group. Theexposure concentration was 50 ppm styrene for 6 h at rest. Trianglesand vertical lines represent mean values and standard deviations ofexperimental data, and the solid line represents simulation results

Fig. 4 Comparison of experimental data with simulation resultsobtained for phenylglyoxylic acid (PGA) in the Caucasian group. Theexposure concentration was 50 ppm styrene for 6 h at rest. Trianglesand vertical lines represent mean values and standard deviations ofexperimental data, and the solid line represents simulation results

Table 4 Comparisons of the simulation results with the experimental data for Orientals (MCIS Intrinsic metabolic clearance of solvent,MCIM intrinsic metabolic clearance of metabolite)

Parameter Sampling time Experiment Simulation

Same parameter as Caucasian Modi®ed parameter

PCE: MCIS (1/min) = 0.0045 MCIS (1/min) = 0.0023PCE in breath (ppm) End of shift 8.3 14.9 15.0PCE in breath (ppm) Next morning 1.3 0.9 0.9PCE in blood (mg/l) End of shift 1.69 2.06 2.06TCA in urine (lg/min) End of shift 3.36 4.58 2.35TCA in urine (lg/min) Next morning 1.10 1.54 0.79

m-Xylene: Vmax (mg h)1 kg)1) = 2.74 Vmax (mg h

)1 kg)1) = 2.00Km (mg/l) = 0.2 Km (mg/l) = 0.2

m-Xylene in breath (ppm) End of shift 2.2 2.5 2.8m-Xylene in breath (ppm) Next morning 0.2 0.1 0.1m-Xylene in blood (mg/l) End of shift 0.57 0.89 0.99MHA in urine (mg/min) End of shift 2.56 2.76 2.64MHA in urine (mg/min) Next morning 0.07 0.03 0.03

Styrene: Vmax (mg h)1 kg)1) = 2.73 Vmax (mg h

)1 kg)1) = 2.00Km (mg/l) = 0.36 Km (mg/l) = 0.36MCIM (1/min) = 0.045 MCIM (1/min) = 0.030

Styrene in breath (ppm) End of shift 0.7 0.6 0.6Styrene in breath (ppm) Next morning 0.07 0.02 0.03Styrene in blood (mg/l) End of shift 0.18 0.35 0.36MA in urine (mg/min) End of shift 0.35 0.41 0.43MA in urine (mg/min) Next morning 0.02 0.02 0.03PGA in urine (mg/min) End of shift 0.10 0.12 0.08PGA in urine (mg/min) Next morning 0.04 0.03 0.02

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shows a di�erent trend (Fig. 8). The lower concentra-tions of urinary PGA recorded at the end of exposure inthe Oriental group indicate that the formation rate ofPGA is much lower in the Oriental group than in theCaucasian group. They also suggest that the metabolicclearance of styrene could be lower in the Oriental groupthan in the Caucasian group because MA showed sim-ilar results even though the formation rate of PGA fromMA may be higher in Caucasians. The simulation ofurinary PGA for the Oriental group was done usingmodi®ed metabolic parameters that were obtained bybest ®t. These results showed better agreement with theexperimental results than the results obtained using theCaucasians' metabolic parameters.

Table 5 summarizes the comparison of simulationresults recorded for the di�erent biological monitoringdeterminants under occupational exposure betweenOrientals and Caucasians. Workers were assumed to beexposed at the TLV during 8 hours per day and 5 daysper week. Workload was assumed to be 50 W duringworkshift and 0 W during non-working time. Body sizefor each ethnic group was assumed to be the same as theaverage of each ethnic group of this study. Simulationsfor Orientals were done with the values of metabolicparameters and modi®ed values presented in Table 4.

Fig. 5 Comparison of experimental data with simulation resultsobtained for trichloroacetic acid (TCA) in the Oriental group. Theexposure concentration was 50 ppm PCE for 6 h at rest.Triangles andvertical lines represent mean values and standard deviations ofexperimental data for the Oriental group, the dashed line representssimulation results obtained using the same metabolic parameter valuesapplied to the Caucasian group (MCIS = 0.0045 l/min), and the solidline represents simulation results obtained using the modi®edmetabolic parameter (MCIS = 0.0023 l/min)

Fig. 6 Comparison of experimental data with simulation resultsobtained forMHA in the Oriental group. The exposure concentrationwas 100 ppm m-xylene for 6 h at rest. Triangles and vertical linesrepresent mean values and standard deviations of experimental datafor the Oriental group, the dashed line represents simulation resultsobtained using the same metabolic parameter values applied to theCaucasian group (Vmax = 2.74 mg h)1 kg)1), and the solid linerepresents simulation results obtained using the modi®ed metabolicparameter (Vmax = 2.00 mg h)1 kg)1)

Fig. 7 Comparison of experimental data with simulation resultsobtained for mandelic acid (MA) in the Oriental group. The exposureconcentration was 50 ppm styrene for 6 h at rest.Triangles and verticallines represent mean values and standard deviations of experimentaldata for the Oriental group, the dashed line represents simulationresults obtained using the same metabolic parameter values applied tothe Caucasian group (Vmax = 2.73 mg h)1 kg)1, MCIM = 0.045 l/min), and the solid line represents simulation results obtained using themodi®ed metabolic parameters (Vmax = 2.00 mg h)1 kg)1, MCIM= 0.030 l/min)

Fig. 8 Comparison of experimental data with simulation resultsobtained for phenylglyoxylic acid (PGA) in the Oriental group. Theexposure concentration was 50 ppm styrene for 6 h at rest. Trianglesand vertical lines represent mean values and standard deviations ofexperimental data for the Oriental group, the dashed line representssimulation results obtained using the same metabolic parameter valuesapplied to the Caucasian group (Vmax = 2.73 mg h)1 kg)1,MCIM = 0.045 l/min), and the solid line represents simulationresults obtained using the modi®ed metabolic parameters(Vmax = 2.00 mg h)1 kg)1, MCIM = 0.030 l/min)

46

When simulations are carried out with the same meta-bolic parameters as for Caucasians, the results are rathersimilar, and they indicate that physiological parametershave a rather weak in¯uence. But when Orientals havedi�erent values of metabolic parameters, simulation re-sults show large di�erences, especially for urinary me-tabolites.

Figures 9±12 present simulation results obtained forurinary metabolites in Oriental and Caucasian workersindustrially exposed to these organic solvents. For PCEand styrene the intrinsic metabolic clearance values usedfor Orientals were the modi®ed values mentioned above.For m-xylene, it is di�cult to decide whether Orientalshave metabolic parameter values di�erent from those of

Caucasians. Therefore, both simulation results, i.e., thesame metabolic parameter values applied to Caucasiansand the modi®ed values, are indicated in Fig. 6 as theexpected results for MHA in Orientals. Similarly to whatwas observed in volunteers exposed to organic solventduring a short period, the simulation results obtained forurinary TCA in workers exposed to PCE and for urinaryPGA in workers exposed to styrene show large di�er-ences between Orientals and Caucasians. On the otherhand, the simulation results recorded for urinary MA inworkers exposed to styrene do not show di�erences

Table 5 Comparison of the simulation results of several biological monitoring determinants in occupational exposure between Orientalsand Caucasians (MICS Intrinsic metabolic clearance of solvent, MCIM intrinsic metabolic clearance of metabolite)

Parameter Sampling time Caucasians Orientals

Same parameter as Caucasian Modi®ed parameter

PCE: MCIS (l/min) = 0.0045 MCIS (l/min) = 0.0023PCE in breath (ppm) End of shift 27.6 29.2 29.3PCE in breath (ppm) Next morning 11.6 11.4 11.5PCE in blood (mg/l) End of shift 3.40 3.55 3.56TCA in urine (lg/min) End of shift 12.0 12.9 6.7TCA in urine (lg/min) Next morning 7.3 7.1 3.7

m-Xylene: Vmax (mg h)1 kg)1) = 2.74 Vmax (mg h

)1 kg)1) = 2.00Km (mg/l) = 0.2 Km (mg/l) = 0.2

m-Xylene in breath (ppm) End of shift 14.6 18.3 26.4m-Xylene in breath (ppm) Next morning 2.3 2.5 3.0m-Xylene in blood (mg/l) End of shift 3.9 4.5 5.5MHA in urine (mg/min) End of shift 5.08 4.46 3.29MHA in urine (mg/min) Next morning 1.08 0.97 1.16

Styrene: Vmax (mg h)1 kg)1) = 2.73 Vmax (mg h

)1 kg)1) = 2.00Km (mg/l) = 0.36 Km (mg/l) = 0.36MCIM (l/min) = 0.045 MCIM (l/min) = 0.030

Styrene in breath (ppm) End of shift 2.1 2.4 3.0Styrene in breath (ppm) Next morning 0.5 0.5 0.6Styrene in blood (mg/l) End of shift 1.1 1.2 1.5PGA in urine (mg/min) End of shift 0.52 0.53 0.36PGA in urine (mg/min) Next morning 0.25 0.19 0.16MA in urine (mg/min) End of shift 1.31 1.29 1.30MA in urine (mg/min) Next morning 0.31 0.24 0.33

Fig. 9 Simulation of urinary TCA in workers exposed to 50 ppmPCE (8 h/day, 5 days/week, 50-W work load)

Fig. 10 Simulation of urinary MHA in workers exposed to 100 ppmm-xylene (8 h/day, 5 days/week, 50-W work load). Orientals 2:Simulation results calculated with the same metabolic parametervalues applied to the Caucasian group (Vmax = 2.74 mg h)1 kg)1)Orientals 1: Simulation results obtained using the modi®ed metabolicparameter (Vmax = 2.0 mg h)1 kg)1)

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between Orientals and Caucasians as previously ob-served in short-term-exposure experiments.

For m-xylene, when the Vmax value for Orientals wasassumed to be the same as that recorded for Caucasians,relatively small di�erences in urinary MHA were ob-served. Thus, these di�erences are due to the e�ects ofphysiological parameters. When the Vmax value forOrientals was assumed to be lower than that recordedfor Caucasians, a large di�erence appeared in urinaryMHA, although the results were very similar in short-term-exposure experiments. This ®nding can be ex-plained by saturation of the enzymatic system. m-Xyleneis highly metabolized. The amount of solvent absorbedinto the body during short-term exposure is small anddoes not saturate the enzymatic system, producing onlyvery small di�erences in the formation rates of metab-olites between Orientals and Caucasians on short-termexposure, even though the Vmax value used in the twodiscrete ethnic groups is di�erent. However, in occupa-tional exposure the amount of organic solvent absorbedinto the body is higher and can eventually saturate theenzymatic system. In that case, the formation rate ofmetabolites is dependent on Vmax. For MHA and MA inurine, even though ethnic di�erences are small in short-term experiments, it could well be that under occupa-tional exposure, large di�erences occur. From the presentstudy it is di�cult to select a Vmax value for Orientals.

Therefore, it is di�cult to predict the levels of urinaryMHA in Orientals under occupational exposure.

The e�ects of physiological and metabolic di�erencesbetween two ethnic groups on several biological moni-toring determinants were simulated using a PB-PKmodel. Calculated di�erences are presented in Figs. 13,14, and 15 for PCE, styrene, and m-xylene, respectively.The total di�erences between the two ethnic groups werecalculated from simulation results obtained for Cauca-sians and Orientals using the modi®ed metabolic valuespresented in Table 5. E�ects of physiological di�erencesbetween the two ethnic groups were calculated using theresults recorded for Caucasians and Orientals withidentical metabolic values presented in Table 5. E�ectsof metabolic di�erences were calculated by subtraction

Fig. 11 Simulation of urinary MA in workers exposed to 50 ppmstyrene (8 h/day, 5 days/week, 50-W work load)

Fig. 12 Simulation of urinary PGA in workers exposed to 50 ppmstyrene (8 h/day, 5 days/week, 50-W work load)

Fig. 13 Di�erences found in biological monitoring determinants forPCE between Orientals and Caucasians. E�ects of metabolic andphysiological parameters were simulated as shown in Tables 3 and 4(ES End of shift, BS prior to next shift)

Fig. 14 Di�erences found in biological monitoring determinants forstyrene between Orientals and Caucasians. E�ects of metabolic andphysiological parameters were simulated as shown in Tables 3 and 4(ES End of shift, BS prior to next shift)

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of the physiological e�ect from the total di�erences.There is uncertainty in the intrinsic metabolic clearanceof m-xylene for Orientals. Therefore, m-xylene is notdiscussed herein although maximal e�ects of metabolicdi�erences for m-xylene were calculated with the as-sumption that the Vmax value for m-xylene is 2.00 mg h

)1

kg)1. In the case of PCE, which is poorly metabolized,large ethnic di�erences were observed in urinary me-tabolites but not in PCE in exhaled air or blood. Fig-ure 14 shows that di�erences between the two ethnicgroups were elevated for most of the biological moni-toring determinants in the case of styrene. In practice,however, styrene in blood or exhaled air is rarely used asa quantitative determinant; the ethnic di�erences pre-dicted herein for PGA are therefore signi®cant only for®eld applications. In most determinants studied, meta-bolic parameters had much larger e�ects than didphysiological characteristics on the biological monitor-ing determinants of PCE and styrene. Therefore, meta-bolic di�erences between ethnic groups have to beconsidered in the establishment and the application ofbiological monitoring.

In conclusion, experimental exposure and simulationsusing a PB-PK model were applied to gain an under-standing of the ethnic di�erences in the kinetics of or-ganic solvents between Orientals and Caucasians.Although the simulation results obtained for the Cau-casian group showed good agreement with the experi-mental results, the simulation results recorded for theOriental group did not show good agreement when thesame metabolic parameters were used. With the use ofmodi®ed metabolic parameters it was possible to obtaina good ®t for the Oriental group. The simulations werealso carried out for occupational exposure situations soas to estimate the likely di�erences between the twoethnic groups. The experimental and simulation results

suggest that ethnic di�erences must be considered in theestablishment and application of biological monitoring.The method used in this study can be used to elucidatethe di�erences between populations.

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