_1,

... 

I ... 

Health Hazar

Evaluation 

·· Report . ~ • .. 1

GENERAL DYNAMICS CORPORATION

' : ·· · GROTON, CONNECTICUT 

d 

HETA 84-474-1946 

ELECTRIC BOAT DIVISION 

___...._+ ----··----· - ---------­
PREFACE 


hnical Assistance Bran

lth hazards in the wo

nder the authori·tY of 

Act of 1970, 29 u.s.

....., 

.•... 

,: 

~ . 

The Bazard !valuations and Tec ch of NIOSH conducts field 

investigations of possible hea rkplace. These 

-investigations are conducted u Section 20(a)(6) .of,.the 

Occupational Safety and Health c. 669(a)(6) which;~ .•. ~ . authorizes the Secretary of Health and Human Services, following a written·· request from any employ~r or authorized representative of employees, to 

determine whether any substance normally found in the place of employment has 

potentially toxic effects in such concentrations as used or found. 

The Hazard Evaluations and Technical Assistance Branch also provides~ :-lipon .. request, medical, nursing, and industrial hygiene technical and conau:l'.tative 

assistance (TA) to Federal, state, and local agencies; labor; induat.ri·-.and 

other groups or individuals to control occupational health ·hazards and:;t·o· .. 

prevent related trauma and disease. . ·~·:. .~·;:~ ~. 

\, ·~:.... 

;; 

Mention of company names or products does not constitute endorsement by the 

Rational Institute for Occupational Safety and Health. 

1 
HETA 84-474-1946 	 NIOSH INVESTIGATORS: 

JANUARY 1989 	 Kevin P. McManus, I.H. 

ELECTRIC BOAT DIVISION 	 Clifford Moseley, C.I.H. 

GENERAL DYNAMICS CORPORATION 	 'Larry K. Lowry, Ph.D. 

GROTON, CONNECTICUT 	 Dale Battis, Ph.D. 

Richard Berg 

I. SUMMARY 

On August 14, 1984, the Rational Institute for Occupational Safety and _. 	 Health (RIOSH) received a request for a Health Hazard Evaluation from 

the painters union at Electric Boat Division of General Dynamics 

Corporation, Groton, Connecticut. The request concerned the potential 

for adverse reproductive effects among maie workers exposed to glycol 

ethers (Cellosolves, 2-et hoxyethanol, 2-butoxyethanol, 

2-methoxyethanol) during ship painting operations at this facility. 

The HIOSH study consisted of assessing exposures . A separate medical 

evaluation was conducted by Yale University and is reported elsewhere. 

2-ethoxyethanol (2EE) is the primary solvent in epoxy pai nts used this 

shipyard. Approximately 800 painters are potentially exposed to 2EE 

during the application of coatings at various stages in the 

construction ~f nuclear submarines. An industrial hygiene survey 

conducted by NIOSH between December 3-7, 1984, shoved full-shift 

breathing zone airborne exposures to 2EE ranging from non-detectable to 

84. 3 mg/m3, with a mea?f concentration of 9.9 mg/m3. Personal 

expotaures to 2-methoxyethanol (2ME) ranged from non-detectable to 

17.2 mg/m3, with a mean of 2 .6 mg/m3 . RIOSH recommends minimizing 

exposure to 2EE and other glycol ether solvents. Because of the 

potential for akin exposure to 2EE adding to the workers ' overall 

exposure, urine specimens were collected from workers being monitored 

before and after each work shift for measurement of the metabolite of 

2EE, ethoxyacetic acid (EAA) . ·Results showed urine excretion of EAA 

ranging from non-detectable to 144 mg/g creatinine. The difference 

between pre and post-shift EAA levels in urine indicated a correlation 

to the measured air exposure level, .as ,explained in the body of this 

report. 

Baaed on the results of thi s survey, RIOSH has determined that a 

potential health hazard existed as a result of workers' uposure to 

2-ethoxyethanol. Recommendations are made to minimize employee 

exposure .to 2EE .during painting operations ·in the shipyard. 

l:EYWORDS: SIC 3731 (Ship Building and Repairing), Celloaolve, _, 	 2-ethoxyethanol, et hylene glycol monoetbyl ether, 2-ethoxyacetic acid, 

reproductive health. 
Page 2 - Health Hazard Evaluation Report No . HETA 84-474 

II. INTRODUCTION 

On August 14, 1984, the National Institute for Occupational Safety and 

Health (NIOSH) received a request for a Health Hazard Eval uation from 

the International Brotherhood of Painters and Allied Trades of United 

States and Canada (painters union) at Electric Boat Divisi on of General 

Dynamics Corporation, Groton, Connecticut. The request was concerned 

with the potential for reproductive effects among male workers exposed 

to glycol ethers (Cellosolves: 2-ethoxyethanol, 2-methoxyethanol , 

2-butoxyethanol) during ship painting operations at this facility. The 

request was a result of published information implicating glycol ethers 

as having the potential for causing adverse reproductive effects in 

both male and females. 

2-ethoxyethanol (2EE) is the primary solvent in epoxy paints used at · this shipyard. Approximately 800 paint ers are potentially exposed to 

2EE during the application of coatings at variou~ stages in the 

construction of nuclear submarines. An industrial hygiene survey was 

conducted by NIOSH between December 3-7, 1984. A separate medical 

evaluation was conducted by Yale University and is reported elsewhere. 

III. BACKGROUND_ 

The Electric Boat Division of General Dynamics Corporation constructs 

and retrofits nuclear submarines under contractural agreement with the 

United States Navy. The two types of submarines manufactured at 

Electric Boat are the---Xrident class and the Fast Attack Cl ass. 

Electric .Boat employs about '2s,ooo workers (predominantly trades 

people), approximately 800 of whom are painters. 

Painters are engaged full-time in a variety of painting operations 

including brush painting, spray painting, mixing, and aand blasting. 

They use a significant amount of paints and thinners which contain from 

5-60X 2-ethoxyethanol (2EE) and 2-methoxyethanol {2ME). They of ten 

work in enclosed spaces. The glycol ethers are found as constit uents 

and thinners for epoxy paints. These paints are used extensively in 

ship building. At Electric Boat, over 40,000 gallons of one epoxy 

paint alone (Savapon), containing 10% 2ME have been used. The same 

paint contains 5% 2EE in the color component, 25X 2EE in the cur e 

component and 25% 2EE in the thinner. Epoxy paints are used to paint 

inside tanks and missile tubes, ·•s well aa the exterior of the shi.ps. 

Mixing and brush painting often take place without respiratory 

protection; apray painting is usually done with-an air supplied 

respirator. lUOSH previously conducted a health hazar d ..evaluation 

(BETA 78-135-1333) in this ahipyard and meaaured 108 mg/m3 of 2ME and 

27-475 mg/m3 of 2EE during painting operations. Industrial hygi ene 

aampling performed by General Dynamics indicated: up to 30 ppm 

(93 mg/m3) of 2ME during a mixing operation, levels up to 27 ppm 

(84 mg/m3) of 2ME in areas 10 feet from a apray operation, and one 

aample with 400 ppm (1474 mg/m3) of 2EE in a closed apace operation. 
Page 3 - Health Hazard Evaluation Report No~ HETA 84-474 

Respirators are required during spray painting in closed locations but 

not during mixing and brush painting operations or nearby the spray 

painting. Significant skin contact can occur in all of these 

operations. 

IV. EVALUATION DESIGN AND METHODS 

A. Envi ronmental 

In order to assess potential exposure to solvents during painting 

operations, personal breathing zone air samples were collected with 

activated charcoal sampling media and portable air sampling pumps. 

Air samples were collected at either 20 cc/min or 50 cc/min, 

depending on the type of sampling pump used . Pumps used included 

SKC Model 222 and Sipin low flow. Sampling pumps were calibrated 

before and after each sampl ing period. Employees reported to the 

paint shop at the beginning of each shift to pick up their 

assignments, and then reported directly to the industrial hygiene 

lab where they (1) provided a pre-shift urine specimen, and (2) 

were fitted with the air sampling apparatus. At the end of each 

shift, employees returned to the lab where the sampling train was 

removed and a post-shift urine specimen was collected. 

One hundred-two (102) air samples were collected during this 

survey. Samples were analyzed by gas chromatography according to 

NIOSH Method P&CAM 27.~ All air samples were analyzed for 2EE, 

.2ME and 2BE. 

For 2-4 consecutive days, ·a total ·of 36 workers were monitored. 

Information was gathered from each employee as to the amount of 

time actually spent painting during each ~hift, Whether or not a 

respirator was worn , whether other types of personal protective 

clothing were worn, and the temperature in the work area. A 

somewhat subjective rating was assigned to ~ach empl oyee's physical 

activity, and estimate of skin contact. Work areas were visited 

twice during each shift to check the operation of the sampling 

~umps, and work practice observations were noted at this time. A 

rating system of 0-3 was used to describe employees• physical 

activity, with 0 being sedentary, '8.Ild 3 being strenuous labor. 

Similarly, skin contact was assigned a rating based on O =no, 1 = 

little, 2 =significant, amounts of paint on the akin of the 

worker. Information was recorded as to the location of each worker 

while painting, how much time during the shift vaa actually •pent 

painting, whether or not the painter wore a respirator, What type 

of paint was used and how much paint the w~rter applied. 

Bulle samples were taken of 7 of the paints, representative of those 

moat used during the sampling period, and of a cleaner. Gas 

chromatography-mass spectrometry (GC-MS) analysis was used to 

assess the contents of 6 with distinctive chromatograms. 
,. 

Page 4 - Health Hazard Evaluation ieport No. HETA 84-474 

B. Biological 

r 	 Urine specimens were collected in a polyet hylene cup and then split 

i 	 into two separate scintillation vials, labeled and frozen for 

shipment to the analytical laboratory. Samples were analyzed for 

the glycol ether metabolites 2-ethoxyacetic acid (EAA), 

2-methoxyacetic acid (MAA) , and 2-butoxyacetic acid (BAA) 

accordingto the method d€veloped by Smallwood, et. al.2 Urine 

aamples were also analyzed for creatinine. (The urine creatinine 

concentration, by itself, has no medical interpretation, it is used 

to standardize the measured concentrations of the other 

substances.) Two hundred fifty-four (254) specimens were submitted 

for analysis (total 508 vials) . Pre- .and post-shift urine 

apecimens were collected from the 36 workers being air monitored on 

2-4 consecutive work days in an attempt ·to determine if any 

correlation could be demonstrated between exposure to the glycol 

ethers and excretion of the metabolites in urine. 

V. EVALUATION CRITERIA 

As a guide to the evaluation of the hazards posed by workplace 

exposures, NIOSH field staff employ environmental evaluation criteria 

for assessment of a number of chemical and physical agents. These 

criteria are intended to suggest levels of exposure to which most 

workers may be exposed up to 10 hours per day, 40 hours per week for a 

working lifetime without experiencing adverse health ~ffects . It ia, 

however, important to note that not all workers will be protected from 

adverse health effects if their exposures are maintained below these 

leVels. A amall percentage of workers may experience adverse health 

effects because of individual ausceptability, a pre-existing medical 

condition and/or by a hypersensitivity (allergy). 

In addition, some hazardous substances may act in ~ombination with 

other workplace· exposures, the general environment, or with medications 

or personal habits of the worker to produce health effects even if the 

occupational exposures •re controlled at the level set by the 

evaluation criteria. These combined effects are often not considered 

in the evaluation criterion. Also, some substances are absorbed by 

direct contact with the skin and mucous membranes, .and thus potentially 

increase the overall exposure. Finally, evaluation criteria may change 

over the years as new information on the toxic effects of an agent 

become available. 

The primary aources of environmental evaluation criteria considered for 

thia atudy were: (1) RIOSH criteria documents and reco11111endations, (2) 

the American Conference of Governmental Industrial Hygienists (ACGIH) 

Threshold Limit Values (TLV'a), and (3) the U.S. Department of Labor 

(OSHA) federal occupational health standards. Often, the lfIOSH 

recomendations and ACGIH TLV'a are lower than the .corresponding OSHA

atandards. Both IUOSB recODDendations and ACGIH TLv•a usually are 

baaed on more recent information than are the OSHA standards. The OSHA

standards also may be required to take into account the feasibility of 

I 

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controlling exposures in various industries where the agents are used; 

the NIOSH recommended exposure limits, by ~ontrast, are based primari ly 

on concerns relating to the prevention of occupational disease . In 

evaluating the exposure levels and the recommendations for reducing 

these levels found in this report, it should be noted that industry i s 

legally reguired to mee t those levels specified by an OSHA standard. A 

time weighted average (TWA) exposure refers to the average airbo~e 

concentration of a subst ance during a normal a-10 hour workday . Some 

substances have recommended short-term exposure limits or ceiliJl& 

values which are intended to supplement the TWA where there are 

recognized toxic effects from high short-term exposures . 

The Occupational Safety and Health Administration (OSHA) has 

promulgated an 8-hour time weighted average permissible exposure limi.t 

(PEL) of 200 ppm (740 mg/m3) for 2EE, 25 ppm (80 mg/m3) for 2ME, 

and 50 ppm (240 mg/m3) f or 2BE . 3 The ACGIH recommends a TLV of 

S ppm (19 mg/m3) for 2EE, S ppm (16 mg/ m3) for 2ME, and 25 ppm 

(120 mg/m3) for 2BE.4 Both the OSHA PEL's and ACGIH TLV's bear the 

"skin" notation i ndicating the potential for absorption of toxic 

amounts of 2EE , 2ME and 2BE through the intact skin (see also 

Reference #5). NIOSH does not recommend a specific exposure limit f or 

2EE, 2ME or 2BE, but recommends that exposure to glycol ethers be 

reduced to the lowest extent feasible . 6 

Toxicology 

2-Ethoxyethanol is one -'Of a family ·Of glycol ethers, several of which 

have been shown t o produce adverse reproductive effects in both male 

and female animals.6 With respect to the male reproductive toxicity 

·of 2EE, testicular atrophy and microscopic testicular changes . (including degeneration of seminiferous tubules &nd damage to dividing 

spermatocytes and spermatids) have been reported in rats given 900 

mg/kg 2EE in the diet for two years;1 .in rats and dogs treated orally 

with 186 mg 2EE/ kg/day for 13 weeks and rats given 372 and 744 mg 

2EE/kg/day subcutaneously for four weeks.8 

Similar effects were shown in .rats dosed orally with 460-1000 mg 

2EE/ kg/day for 11 days; in mice given 1000-2000 mg/kg/day orally for 

five weeks and in r abbits exposed to 400 ppm 2EE (6-hr/day, S 

days/week) by inhalation for 13 weeks . 9,10,ll,12 

Oudiz, et al intubat ed rats with 936, 1872, and 2808 mg 2EE/kg/ for 

five days and analyzed semen at periods ranging from 1-14 weeks after 

cessation of dosi ng, and found azoospermia or aevere oligiospermia 

among the two highest dose aroups and a aignificant increase i n 

abnormal sperm morphology in the lowest dose aroup by the seventh 

wee1t.l3 Partial or complete recovery of sperm counts and morphology 

were ob•erved by the fourteenth week. ·Finally, Lamb, et al found dose 

related decreases in aperm motility, an increase in the percentage of 

morphologically abnormal sperm and decreases in -testicular weight i n 

mice given 1-2% 2EE in their drinking water for 14 weeJts.14 A 

significant reduction in fertility (number of live pups per litter) 

among untreated females mated with males treated with 2% 2EE was .also 

observed. 
Page 6 - Health Bazard .Evaluation Report No. 'STA ·84-474 

Baaed on the animal evidence of the reproductive toxicity of 2EE, NIOSH 

has recoJ11Dended that the current OSHA PEL of 200 ppm (8-hour TWA) be 

reexamined and that exposures to 2EE be reduced to the lowest extent 

feasible.6 

VI . USULTS AND DISCUSSION 

.A. Environmental 

Glycol ethers were found only in those bulk sampies expected to 

contain glycol ethers although some discrepancies ·existed between 

hazard communication listings of components and those identified by 

analysis. 2-Methoxyethanol, for example, was not found in any of 

the bulks though it was expected, and appeared in some of the air 

samples. 

All of the blank samples (not exposed to 2EE but handled as field 

aamples) were analyzed as non-detectable. Fourteen blank aamples 

were submitted for analysis. The absence of any detectable 

quantities of 2EE on the blank samples confirms the absence of 

contamination either in J)reparation, shipping, .nd laboratory 

analysis. 

The results of environmental air samples for 2-ethoxyethanol are 

shown in·Table 1. The Table also includes the results of pr e and 

post-shift concentrations of ethoxyacetic acid for each worker. 

Other variables p~esented in the Table include: numerical values 

ratings for physical activity, akin exposure, and respirator usage; 

method of painting; which paint was used; temperat ure in the work 

environment ; actual number of hours spent painting; -and the 

location where the painting took place. 

Of the 102 samples analyzed for ~EE, 14 were below the detection 

limit of 0.01 mg/sample. With the same analytical sensitivity for 

2ME, 50 out of 102 samples were undetectable. Dnly one sample, 

that of a painter performing brush painting out-of-doors, contained 

butoxy ethanol (6.01 mg/m3). Thia aample contained no detectable 

2EE or 2ME. 

None of the sample results exceeded the <>SHA PEL'a for 2EE, 2ME, or 

2BE. Only one (1) sample exceeded the ACGIH TLV for 2ME, but ­ eleven (11) aample ~eaults .exceeded the TLV for 2EE. 

A aummary of exposure by .work location appear• in ·Table 3. 

However, aince workers' assignment• are conatantly changing, this 

information is of little use in determining cunulative expoaure 

potential. On any given day; any worker. could be •••ianed to any 

area. Bonetheleaa, the higheat aeaaured expo1urea aeeaed to .cluster in the moat confined spaces and in those being intensively 

painted. · ~. 

r. I '· 4;~t 1

;.:: .. . :1: ~ " " ~. .J ! 
ro6~ / ­ n~Ai~n nazaru ~va~uat1on xeport ~o • .w:;rA 84-474 

A review of the subjective .ratings of skin contact at the end of 

each shift revealed that the vast majority of workers had "little" 

or "no" skin contact with the paints. 

B. .Biological 

The urine samples collected during this study allowed NIOSB to 

validate a biological monitoring method which can detect human 

exposure to glycol ethers. The method is described in a separate 

publication by Smallwood, et al (1988).15 

The results of the ethoxyacetic acid (EAA) metabolite in urine 

analyses are presented in Table 1 along with the environmental 

data. All EAA excretion data were corrected for variation in the 

rate of excretion of water by dividing the measured EAA 

concentrations by the concentration of creatinine in the urine 

sample. 

The purpose of these analyses was to evaluate potential worker 

biological exposure to EE by various routes ~f occupational 

exposure, specifically through breathing air containing EE and skin 

contacts with EE. Here, biological exposure refers to the entry of 

EE into the blood stream, from which it could interact with the 

body and possibly cause health effects. This evaluation was 

carried out by determining how the concentration of ethoxyacetic 

acid (EAA, a chemical that is produced from EE in the body) in 

workers' urine is Telated to EE exposure in the workplace. Thia 

was done by considering the available data and the current 

scientific knowledge about the human body's ability to process and 

react to EE. .$ince both dat~ and knowledge are limited, these 

analyses should not be considered precise, although they do 

represent the best effort possible by Hattie and Berg. For a more 

detailed explanation of these analyses, aee pages 8-36 in the 

Hattie and Berg report that is attached as Appendix 1. 

The results and conclusions of these analyses can be found on page 

37-70 of Appendix 1. Basically, Hattie and Berg showed that there 

was evidence of biological exposure from breathing and having akin 

contact with EE.. Further, their study showed that the largest . portion of the biological exposure was explained by breathing air 

containing EE, although their study indicated that a smaller 

portion of the biological exposure may come from akin contact vith 

EE. The importance of this study is not only that it demonstrates 

that biological exposure does result from both breathing and having 

akin contact with EE, but that it also ahowa this method aay help 

in the future in estimating the total biological exposure resulting 

from various routes of occupational exposure. If adverse health 

effects are proven to result from occupational exposure to EE, then 

the results of studies of biological exposure may be useful in the 

future to help assure a safe working environment. · · 
Page 8 - Health Hazard Evaluation Report No. 11ETA 84-474 

The data was also analyzed to compare the activity adjusted air 

concentration to the effect of vearing a respirator vs. not wearing 1 

a respirator. The results indicated a respiratory protection 

factor of somewhat less than two, which is at the lower end of 

in-use protection factors measured for other agents in other 

industries.17,18,19 This finding could be explained i f skin absorpt 

ion proved to be a significant route of entry for EE in these workers 

A aimilar analysis of the data was performed to assess the rel ative 

importance of direct inhalation exposure and skin absorption (as 

indicated by visible contamination of the skin with paint at the 

end of the shift) on total EE absorption. Overall, the researchers 

reported that although some skin absorption was indicated, ~h s 

factor did not achieve statistical significance. It was estimat-ed 

that of the total amount of EE absorbed, inhalation was likely to 

have been 3-5 times as large a source as dermal absorption for this 

group of workers. It would not be inconsistent to report that 

direct air inhalation could have accounted for essentially all of 

the total EE absorption observed. 

VII. CONCLUSIONS AND RECOMMENDATIONS 

Conclusions 

Based on the results of this investigation it is concluded that a 

potential health haza~d existed at the time of this study due to 

painters' exposure to 2-ethoxyethanol. 

In tbe effort to study the health effects of workplace chemical 

exposures, estimation of the dose received is always the most elusive 

term. Historical exposure data is o'ften scarce, inadequat e, not 

comparable with current methods of data collection, or inaccessible. 

In a shipyard situation such as this, accurate assessment of even 

current exposures is exceptionally hard to attain because of ~he 

extreme variability of conditions. Different materials are used and 

even the configuration of the work spaces changes as a ship progresses 

toward completion. Even the number of painters assigned t o the aame 

apace can change exposure levels. Because of the variability of the 

jobs, with painters moved freely from location to location, and working 

with different paints, it is a difficult task to attempt t o categorize 

a worker's potential exposure level by any of these factors. As a 

result of this investigation, 1'IOSH has developed an addit ional tool to 

aid in ·the evaluation of worker exposure to glycol ethers: a 

biological monitoring method. Thia method, together with the 

pharmacokinetic models teated by Dr. Battis, ~t al, provides a ~aeful 

measure of an employee's total exposure to these solvents. 

Recommendations 

1. 	 Worker exposure to glycol ethers should be reduced to the l owest 

extent feasible. In this regard, substitution for the glycol 

ethers with less toxic materi als would achieve the opt imum result. 
rugt: ~ - n e aJ.-cn .nazara !ival uation "Report No. BETA 84-474 

However, it is understood that the paints must meet strict 

Department of the Navy specifications and substitution may not be 

possible until the Navy changes their specifications. 

2. 	 Employees who a r e required to use glycol ether based paints should 

be provided with, and required to use , proper personal protective 

equipment, including respirator with organic vapor cartridge, 

impervious coveralls and gloves . 

3. 	 A continuous program of industrial hygiene assessment should be 

instituted for the painters. Since solvents are used in varying 

quantities and conditions, frequent sampling for exposures is 

essential. 

VIII. REFERENCES 

1. 	 Rational Insti tute for Occupational Safety and Health. RIOSH 

Method P&CAM 127 . NIOSB Manual of Analytical Methods Vol. l, DREW 

NIOSH Publicati on No. 77-157A, April 1977. 

2. 	 Smallwood. AW, DeBord, KE and Lowry, LK. Analyses of Ethylene 

Glycol Monoalkyl Ethers and Their Proposed Metabolites in Blood 

and Urine. Environmental Health Perspectives, 57:249-253, 1984. 

3. 	 U.S. Department of Labor, Occupational Safety and Health 

Administration. General Industry Standards. Publication No. 

2206, 29 CFR . 1910·.·1000, .. Washingt on, D.C., 1981. 

4. 	 American Conference of Governmental Industrial Hygienists: 

Threshold Limit Values for Chemical Substances and Physical Agents 

in the Work Environment with Intended Changes for 1987-88, 

Cincinnati, Ohi o, 1987. 

5. 	 Dugard, PH, Wal ker, M, Mawdsley, SJ and Scott, RC. Absorption of 

some glycol ethers through human skin in vitro. Environmental 

Health Perspectives, 57:193-197, 1984. 

6. 	 RIOSH Current Intelligence Bulletin No . 39 . Glycol Ethers: 

2-methoxyethanol and 2-ethoxyethanol . · DHHS (NIOSH) Publication 

NO. 83-112, 1983. 

7. 	 Morris, HJ, Nelson, AA, and Calvery, HO. Observations on the 

chronic toxici ties of propylene glycol, ethylene glycol, 

diethylene glycol, ~thylene glycol monoethyl ether, and diethylene 

glycol monoethyl ether. J. Pharmacology Exp. Ther. 74:266-273, 

1942. 

8. 	 Stenger, EG, Aeppli, L, 'Muller; 1>, Peheim, E and Thomann, P. The 

toxicity of ethylene glycol monoethyl -ether. Arzneim. Forsch. 21 

880-885, 1971. 

--­ -.. - --..-·-----­
Page 10 - Health Hazard Evaluation Report No. HETA 84-474 

9. 	 Foster, PMD, Creasy, .DM, Foster, JR, Thomas, LV, Cook, MW and 

Gan.golli, SD. Testicular toxicity of ethylene glycol monomethyl 

and momoethyl ethers in the rat. Toxicology and· Appl ied 

Pharmacology. 69:385-389, 1983. 

10. 	 Cheever, KL, Weigel, WW, Richards, DE, Lal, JB and Pl otnick , HB. 

Testicular effects of bis (2-methoxyethyl) ethers in the adult 

rat: equimolar dose comparison with 2-methoxyethanol and 

2-ethox:yethanol. The Toxicologist. 5:140, 1985 . 

11. 	 Nagano, K, Nakayama, E, Koyano, M, Oobayaski, H and Yamada , T. 

Mouse testicular atrophy induced by ethylene glycol monoalkyl 

ethers. Japanese Journal of Industrial Health. 21:29-35, 1979. 

12. 	 Barbee, SJ, Terrill, JB, Desousa, DJ· and Conaway, CC . Subchronic 

inhalation toxicology of ethylene glycol monoethyl ether in the 

rat and rabbit. Environmental Health Perspectives. 57:157-163, 

1984 • 

.13. ·oudiz, DJ, Zenic, H, Niewenhuis, RJ and McGinnis, PM. Male 

reproductive toxicity and recovery associated with acute 

ethox:yethanol exposure in rats. J. Toxicol. Environ . Health. 

13:763-775, 1984. 

14. 	 Lamb, IV, GC, Gulati, DK, Russell , VS, Hommel, L and 

Sabharwal, PS . Reprocductive toxicity of ethylene glycol 

monoethyl ether tested by continuous breeding of CD-1 mice. 

Environmental Health Perspectives. 57:85-90, 1984. 

15. 	 Smallwood, AW, DeBord, K, Burg, J, Moseley, C .and Lowry, L. 


Determination of Urinary 2-Ethox:yacetic Acid as an Indicator of 


Occupational Exposure to 2-Etho:xyethanol. Applied Industrial 


Hygiene, Vol. 3, No. 2:47-50, 1988 . 


16. 	 Battis, D and Berg, R. Pharacokinetics of Ethoxyethanol in 


Humans. Contract report to BIOSH CTPID 88-1, February 1988. 


17. 	 Barris, HE, DeSieghardt, WC, Burgess, WA and Reist, PC. 

Respirator Usage and Effectiveness in Bituminous Coal Mining 

Operations. American Industrial Hygiene Association Journal , Vol. 

35, pp. 159-164, 1974. 

18. 	 Goble, R, Battis, D, Ballew, M and Thurston, D. Impl etnentation of 

the Occupational Lead Exposute Stanc!ard, M.I.T. Center for Policy 

Alternatives, CPA/83-11, Cambridge, MA, 1983. 

19. 	 Smith, TJ, et al. Inhalation Expoaure of -Cadmium Workers: Effects 

of Respirator Usage. American Industrial Hygiene Association 

Journal, Vol. 41, pp. 624-634W a395M. 
:; 

.

. 

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Page 11 - Health Hazard Evaluation Report No. HETA 84-474 

IX. AUIHORSHIP AND ACKNOWLEDGEMENTS -. 

Report Prepared by: Kevin P. McManus 

Regional Industrial Hygienist 

fiIOSH - Boston Office 

Environmental Evaluation Assistance: Clifford Mosely, CIR 

ATSDR 

Atlanta, Georgia 

Formerly of HETAB, DSHEFS 

NIOSH - Cincinnati, Ohio 

Biological Analyses : Larry K. Lowry, Ph.D. 

Di~ision of Biomedical and 

Behavioral Sciences 

NIOSH - Cincinnati, Ohio 

Statistical Analyses: Dale Battis, Ph.D. 

Principal Research Associate 

Center for Technology, Policy 

and Industrial Development 

Massachusetts Institute of 

Technology 

Cambridge, MA 

Richard Berg 


Research Associate 


CTPID - MIT 


Cambridge, MA 


Originating Office: Hazard Evaluations and Technical 

Assistance Branch 

Division of Surveillance, Hazard 

Evaluations, and Field Studies 

X. DISTRIBUTION ANP AVAILABILITY OF REPORT 

Copies of this report are temporarily available upon request from RIOSH, 

Hazard Evaluations and Technical Assistance Branch, 4676 Columbia 

Parkway, Cincinnati , Ohio 45226. After 90 days, the report will be 

available through the Rational Technical Information Service (RTIS), 

5285 Port Royal, Springfield, Virginia 22161. Information regarding 

i ts availability through RTIS can be obtained from RIOSB Publications 

Office at the Cincinnati address. Copies of this report have been aent 

t o: 

1. Electric Boat Division, General Dynamics 

2. Paint.era• Union, Groton, Connecticut 

3. RIOSH, Boston Region Office 

4. OSHA, Region I 

For the .purpose of i nforming affected employees, copies o.f this report 

shall ·be posted by the employer in a pr ominent place accessible to the 

employees for a period of 30 calendar .days. 
UU.J 

Table 1 

Electric Boat Division 

General Dynamics Corporation 

Groton, Connecticut 

ID DAY PRE FOST -AIR CON Activity SrIH EX RESP USE Typt Piint TEftP HOURS loc1ti1'TI 

19 EEA/ 19 EEAI 19 EE/ 1~1 ight O•none l=no 

g :rut g crut cu • 3=he1vy 2=signif rtspir1tor 

----------------------------------------------------------------- y ·------------------------------­ ., 6 1. 70 3 1 brush S•v•pon 80 3 ER 719 

4 (7 <C 4.10 1 1 0 brush Sn1pon 80 5 EVIi 719 

5 ND ND :.18 0 0 brush S1v1pon 85 5 ER 719 

6 <3 ' 

4 30 64 '4

, jl 2 1 1 brush S1npon 80 4 ER 719 

2 5 61 54 16.99 0 1 brush S1npon 85 4 ER 720 

6 57 44 <1.1 1 0 1 nont nont n 0 ER 720 7 39 

4 ND <S ~.23 1 1 brush 83'84 35 3 S1il 720

, 5 ND 11 56.03 0 1 brush " S•v1pon 45 4 S•il 720 

6 16 13 4.E~ 1 brush 83'84 45 5 S1il 720 

7 7 

4 l4 11 :1.: 1 1 1 brush SiVipon BO 4 A"R 719 

4 ~ 7 l7 i:12 2 2 1 brush S1vipon 85 6 ER 719 

(10 '3.:J 1 0 1 brush S1npon 85 6 ff 71'9

.,' 20 

~ ~,! 22.94 2 1 1 brush S1v1pon 80 3 A"R 720 ., 5 5 A,! 7.14 . 1 1 brush S1v1pon 85 l APIR 720 

no 0 1 ' 

• 36 ~ 7.58 2 1 1 brush Hi Hut 80 ~Rue 720 . 6 ~ 47 47 6.~e 2 1 1 brush S1vapon BS 3 ER 720 

6 55 e.3o 0 1 nont nont 85 0 torp720 7 34 

3 <B 6 2.91 0 1 brush Sn1pon 80 2 ER 719 

7 4 ND 6 4.79 1 t brush S1vapon 80 3 ER 732 

5 <10 9 L~~ 1 0 0 brush SIVl$)on 85 3 ER 732 

6 <11 13 

4 ND 110 <3.1 1 1 1 llrush S1vipo11 35 5 S1il 719 

8 5 ND 110 1.06 2 1 1 brush 'S1v,8~ 45 

'4 S1i1 719 

6 ND ND 1.55 1 1 1 brush Slv,83• 85 2 ER 719 

7 MD 

3 (6 ti!) 6.21 2 0 1 spray fn1pon 6 MR 719 

9 4 (8 21 18.89 2 2 1 brush S1v, Di 80'° 7 ER 731 

5 23 18 

8.63 2 1 1 llrush Slnpon 85 3 ER 731

6 15 14 

4 ID 

'ID 1.10 1 0 'O brush 

·s1v1pon 80 i4 MR 7141 

10 5 110 ND <1.1 2 2 t bni1h S1v1pon 85 6 ut 719 

6 ND ND <7.4 1 1 1 brush Sav1pon 85 6 UL 719 

7 ND 

!­
f 

t 


' 

- -- ··- ·-·----~ -----·--­

TABLE 1 - Ele~ ric Boat - HETA 64-474 (Continued) 


ID DAY FRE POST AIP. CON Activity SKIN EJ RESP USE Type Paint T£"P HOURS Location 

1g EEk/ cg EE4/ 1g EE/ l=light O=none l=no 

g treat g erect CU I 3=heivy 2=signif re5piritor 

----------------------------~-------------------------------------------------------------------

4 12 14 3.'19 2 1 1 brush Savapon 80 5 ER 724 

11 5 13 12 2.43 1 0 1 brush Savapon 85 5 ER 725 

6 12 1.% 1 0 1 brush Sav1pon 85 5 ER 725 

7 9 

4 ND <9 <B.8 2 1 0 spr1y oil 90 5 ER 719 12 	 5 ND <1.1 1 0 1 brush Savapon 85 4 H 719 

6 5 (1.4 0 1 brush Inter1i 85 4 EVW 719 

7 ND 

4 69 39.05 1 1 brush Savapon 80 3 Torp 720 

13 	 5 144 no ") 2 .. 1 brush Savapon 85 4 720 

t. 3.8~ 1 0 1 none none 85 0 Aft 720 

7 tt. 

4 4£ {7 <1.1 1 1 l brush Sav,83& 35 4 top 720 

H 5 31 45 0.'16 1 ·- - 1 1 brush A1erc.o. 45 4 Top 720 

ti 36 :n no 1 . 1 brush Savapon 45 5 Top 720 

7 2.­

4 9 7.38 :! 1 1 brush Savapon 80 4 A"R 720 

15 	 5 11 15 19.51 	 0 0 brush Savapon 85 5 A"R 720 

6 9 3.09 	 0 1 none none 85 0 A"R 720 

7 9 

3 <5 ND ~ 0.52 1 0 brush Vinyl 1 40 5 Ooae 719 "' 16 	 4 <5 8 84.34 1 0 0 brush Savapon 8(1 4 A"R 719 

5 11 9 7.88 1 0 1 brush Sanpon 85 4 A"R 719 

6 13 11 

4 9 11 6.64 2 1 0 brush Savapon 80 4 ER 719 

17 5 <7 14 2.15 2 1 0 brush Savapon 85 7 ER 71'1 

6 11 17 5.74 1 0 1 brush Snapon 85 7 ER 719 

7 10 

3 9 79.00 2 0 0 spr1y S1V1pon 90 1 APIR 719 

18 	 4 31 23 1.05 1 0 l brush S1vapon 80 · 2 A"R 719 

5 13 10 11.52 1 ·O 1 1pr1y ,Sn1pon 85 ·AftR 719 

6 27 12 

3 ND <6 2.19 1 0 1 brush Sn1pon 70 6 11R 731 

19 4 ND llD 2 , .. .08 3 t 0 brush S1v1pon 35 .. 7 Dr:itt 731 

5 <4 ND o.oo .2 2 0 brush Sav1pon 40 4 Dock 731 

b ND (4 

4 26 26 40.12 2 1 (I brush S.vapon 90 4 Torp 719 

20 	 5 66 - 49 59.20 1 1 1 brush S1npon 85 5 Torp 719 

6 41 38 9.29 ;jf 1 t,J. • 1 brush oil 85 5 Torp 719 

7 43 ~. !<t. ' 

" 	 . - .. ,.

~ 

' 


.. 

TABLE 1 - Ele:tr1c Bcit - HETA B•-474 (Cor.t1nued ) 

ID DAY PF: POST AlR CON Activity ~lN EX RESP US: Type Paint TEftr HOURS Loc•tion 

ag EEti/ 19 EEA ' I Q EE/ l=hqht O=none l=r.o 

9 cre•t 9 crnt cu • ;=hei\'Y 2=sign1f respir•to:­

----------------------- --- ------ --- ----- --~-----------------------------------------------­

3 26 lb 7.17 1 0 1 spr•y S1v, Un BO 1 AftR 719 

32 4 35 10 3.02 2 2 0 spr•y 011 BO 6 Fin 719 

s 27 24 S.71 2 0 0 SDr•y oil es 4 h n 719 

6 26 20 

4 18 14 ((r.45 2 0 1 brush S•npon . BO 2 AftR720 

33 5 25 16 10.% 1 0 1 brust. Sav•Don 85 3 AftR 720 

6 20 13 3.60 1 0 1 none none 85 0 AflR 720 

3 <6 13 3.Z ~ 0 1 brush Bl•c Po 75 6 O' hud 73 ., 34 	 4 ND 13 2.11 .. 1 1 brush Bhc Po BO 6 Fin 731 

5 <6 6 4. 00 1 1 brush Bhc Po es 6 Fan 731 

6 ND 6 

3 (8 (7 2.28 1 0 1 brush S1npon 80 4 ER 720 

35 4 (7 10 4B.61 2 0 0 brush S•v1pon 80 7 ER 720 

5 12 15 1.h! (: 0 none none 85 4 UL 72v 

6 10 

'3 till <4 .Y.~ l 0 1 brush S•v•pon 80 l co 732 3~ • tlD <3 5.04 1 (\ l brush S1v1pon 80 4 EVIi 732 ( tlD (7 11.13 2 1 1 brush Sn1pon 85 4 ER 732 " 

6 8 10 

" ~ 
I Summary of Airborne Exposures 

2-ethoxyethanol 2-.etbox,ethanol 

{ppm) (ppm)

u 90 81 

Hean :!:. S.D. 9.9+15.7 (2 ·6:!:.4 .2) - 2.6+3.2 (0.8+1.0) . 

Median 4.4 (1.2) 1.4 (0.44) 

l&nge o-84.3 (0-21.5) 0-17.2 (0-5.6) 

Geometric Mean* l.6 1.1 

Geometric S.D. 1.1 0.1 

~cmettic autistics baaed on non-zero terms only• 

•

• 
• • 

~u--.•y u~ a.;r.roorue i:;xposures Dy Loca~on

2-ethoxyethanol 2-methoxyethanol 

•&l-3 (ppm) (ppm)

TORPEDO ROOM 

n 

Mean+ S.D. 

Median 

R.an&e 

Geometric Mean* 

Geoaetric S.D. 

5 

30.o+21.3 (8.0+5.7) 

37.1 (9.9) 

8.1-58.3 (2.2-15.6) 

3.1 

0.9 

5 

60.0+4.5 (l.9+1.4) 1.3 (2.3) 

0-11.0 (0-3.5) 

1.9 

0.6 

Mean+ S.D. 

Median 

Range 

Geometric Mean* 

Geometric S.D. 

17 

13. 9+19.5 (3.7+5.2)

-7.3 (1.9) 

0-84.3 (0-21.5) 

2.1 

1.1 

16 

l.6+4.5 c1.1+1. 4> 

-2.4 (0.8) 

0-11.2 (0-5.6) 

1.4 

0.7 

ER 

u 

Mean + S.D. 

Median 

_i.ange 

Geometric Hean* 

Geoai.ettic S.D. 

33 

7.4+10.4 - 3.9 

l.o-45.6 - i.5 

0.9 

(2.0+2.8) 

(1.0) 

(0.3-12.2) 

26 

1.9+2.6 (0.6+o.8) 

-1.1 (0.3)

0-a.1 co-2.1> 

0.8 

0.8 

OTBER 

n 

Mean + S.D. 

Median 

Range 

Geometric Mean* 

Geometric S.D. 

35 

7.4+15.1 (2.0+4.0) 

3.9 (l.O) 

{.)-77.8 (0-20.7)

1.3· 

1.0 

34 

2.1+2.4 (0.7+o. 7) 

-1.6 (0.5) 

. 0-9.4 (0-3.0) 

l.O 

0.6 

*Geometric statistics based on non-zero terllB only • 

i 

..... ~ ~:. 

~·- ··-... ~ *' 

t 	
Table 3.1 

Shipyard Painter Database 

WORKER DAY PRESHFT POSTSHIFI' ..AIRCONC ACTIVITY RESPUS£ .SJCINEX 

NUMBER m1 :E.66. miE~~ m1£E (1aSW\ding (1 •No CO• none 

&crcalinine &ae.atinine cubic me&er 3 • heavy lifL.) respintor) 2ssicnil.) 

1 3 ..99• 6 1.70 3 1 l 

4 s 3 4.10 1 0 1 

s 2 1 2.18 2 0 0 

9•• -·9 . 6 2 -99 -99.00 9 

2 4 36 64 44.01 2 1 1 

5 61 54 16.99 1 1 0 

6 57 44 .60 1 1 0 

7 39 -99 -99.00 9 9 9 -

3 4 I 4 5.23 1 I l 

s 1 11 S6.03 1 1 0 

6 16 13 4.83 1 1 1 

7 7 -99 -99.00 9 9 9 

. 4 4 14 11 .60 1 1 1 

s 7 17 2.12 2 . .. - I 

6 7 -99 3.23 1 1 0 

7 20 ...99 ·99.00 9 -9 9 

s 4 -99 -99 22.94 2 1 1 

5 -99 -99 7.14 2 l 1 

6 -99 -99 -99.00 1 1 0 

6 4 36 38 7.58 2 1 1 

s 47 47 6.38 2 1 1 

6 -99 SS 8.30 1 1 0 

7 34 -99 .-99.00 9 9 9 

7 3 s 6 2.91 1 1 0 

4 -99 6 4.79 . 1 1 1 

s 6 9 6.58 1 0 0 

- 6 8 13 -99.00 9 ·9 9 

• -99 signifies missing data for the urinary measurements ofethoxyacctic acid and the air 


measurements of ethoxyethanol. 
 •• 9 signifies missing data for the activity, respirator use, and skin exposure ratings. 

WO

RKER 

~'t MBE.R 

DAY 

Table 3.1, Continued 


PRESHFT POSTSHIFT AIRCONC ACTIVTJ"Y R.ESPUSE 

m i: E.A 6 mi: Et.~ mi: EE {l• SWld.ing 

(I • No 

&cn:atininc &crcatininc cubic mc&.c.r 3 •heavy li!L) respirator) 

SKI?\"'EX

(0 •none 

2-sianif.) 

8 	 4 

5 

1 2 1.60 1 1 

2 1 1.06 2 1 

1

1 

6 

7 	

1 2 1.55 1 1 

1 .99 -99.00 9 9 

1 

9 

9 	 3 4 2 6.21 2 1 

o. 4 6 21 18.89 2 1 2 

5 23 18 

8.63 2 1 1 

6 15 14 -99.00 9 9 9 

10 	 4 l 2 1.10 1 0 0 

5 2 2 .60 2 1 2 

6 3 1 3.70 l l 1 

7 2 -99 -99

.00 9 9 9 

11 	 4 

s 

12 

14 3.99 2 1 

13 

12 2.43 1 I 

l

0 

6 12 -99 1.96 1 1 0 

7 9 -99 -99

.00 9 9 9 

12 	 4 

5 

6 

7 

2 6 4.40 2 0 

2 -99 .60 1 1 

5 ..99 .70 1 1 

1 -99 ·99

.00 9 9 

1 

0 0

9 

13 	 4 

-99 69 39.05 1 1 1 

s 

6 

7 

-99 144 -99.00 2 1 ..99 ..99 3.82 1 1 

66 .99 -99.00 9 9 

2 

0 

9 

14 	 4 46 47 .60 1 1 1 

s 31 45 .96 1 1 

1

6 

7 

36 33 -99.00 1 1 

24 ..99 -99.00 9 9 

1 

9 

• ' 	

Table 3.1, Continued 

WORKER DAY PR.ESHFr POSTSHifT A.IRCONC ACTIVITY RESPUSE SKINEX 

NUMBER m~EAA m&EAA m1EE .(l•SWlding (l •No (0 •none 

1 cn.atinine g crcatinine cubic meicr 3 • huvy lift) rcspimor) 2-si;nif.) 

23 3 12 14 8.19 1 1 0 

4 16 10 3.13 2 1 1 

s 16 10 7.29 1 1 0 

6 16 8 -99.00 9 9 9 

24 4 1 1 4.11 1 1 1 

s 2 s 2.17 1 1 0 

6 s 2 .99 1 1 0 

7 1 .99 -99.00 9 9 9 

25 3 -99 6 .92 3 1 1 

4 6 s 1.05 1 1 0 

5 7 6 6.85 1 1 1 

6 5 10 -99.00 9 9 9 

4 6 8 3.08 2 1 1 

s 11 16 6.27 1 1 0 

6 10 16 9.48 l 1 0 

7 13 -99 -99.00 9 9 9 

27 3 5 16 7.45 3 1 1 

4 .99 5 2.17 1 1 0 

s 10 -99 -99.00 9 9 9 

28 3 I 1 2.60" 1 1 0 

4 2 s 3.21 2 0 2 

s 1 1 '3.91 2 0 2 

6 1 1 -99.00 9 9 9 

29 3 l 3 11.64· 1 1 0 

4 6 8 3.33 2 1 1 

s 2 s 1.31 2 1 0 

• 6 3 4 -99.00 9 9 9 
l l:ll!UJ 

t 

WORKER 

~"UMBER 

30 

DAY 

3 

4 

Tobie 3.1, Continued 

PRESHFT POSTSHIFT AIRCO~C ACl1VlTY RESPUSE mi:E.!..!i ma EAA mt EE O•swiding Cl • No 

&crc.atinine & aeatinine cubic metu 3 c heavy li!L) respirator) 

-99 4 

8.95 1 1 

1 4 7.64 2 0 

S~"EX 

(0 •none 

2-signif.) 

0 

0 s s 3 4.08 1 1 0 

6 -99 6 -99.00 9 9 9 

31 4 S1 47 .23 2 1 1 

s 

6 

78 42 1.00 2 1 

54 .99 .60 1 1 

l 

0 

7 39 .99 ·99

.00 9 9 9 

32 3 

4 

5 

6 

26 16 7.

17 1 1 

35 10 

3.02 2 0 .. 27 24 5.71 2 0 

26 1.0 -99.00 9 9 

0 

2 

0 

9 

33 4 18 14 .23 2 l 0 

5 25 

16 10.96 1 I 0 

6 20 13 

3.60 l 1 0 

34 3 4 13 3.20 1 1 0 

4 2 1'3 2.

11 2 1 1 

5 4 6 

4.00 1 1 1 

6 2 6 -99

.00 9 9 9 

35 3 6 s 2.28 1 1 0 

4 5 10 48.61 2 0 0 

s 12 15 

2.67 l 0 0 

6 10 .99 -99.00 9 9 9 

36 3 2 3 9.09 1 1 0 

4 2 2 5.04 1 1 0 

s 3 s 11.13 2 l 1 

r 

! 

~ 

• 
Center for TechnoJ02y. Policy and Industrial De,·elopment 


Massachusetts Institute of Technolo~" 

Camhridf:e. 1\1A 02139 


PHARMACOKINETICS OF 


IlHOHYETHRNOL IN HUMANS 

February, 1988 CTP ID 88-1 

Dale Hattis, Ph. D. 

Richard Berg 

The research underlying this report was supported by the U.S. National 

Institute for Occupational Safety and Health. Any opinions, findings, 

conclusions, or recommendations are those of lhe authors and do not . 

necessarily reflect the views of NIOSH, the Center for Technology, Policy 

and Industrial Development, or the Massachusetts Institue of Technology. · 
ACKNOWLEDGEMENTS 


We deeply appreciate the willingness of K. McManus, Laura Welch, J. 

Sparer, S. Schrader, L. Lowry, and D. Lakatua to share their data and 

prepublication manuscripts of papers. 

•• j 
S-1 


SUMMARY · - · 

This is the fourth in a series of research effons to improve the state of 

the an of risk assessment by making use of more detailed infonnation on the 

biological mechanisms by which specific agents are processed and cause harm 

in biological systems. Based on clinical experiments of Groseneken et al. 

(l986a,b) we have constructed four different p~acokinetic models of the 

uptake ofethoxyethanol (EE, ethylene glycol ethyl ester), metabolism of EE 

via ethoxyacetaldehyde to ethoxycacetic acid (EAA}, and the urinary 

excretion of EAA.• 

• The four models fall into two groups. Our two "simplest" models are both constructed 

with only a single kinetically homogeneous body companment for ethoxyacetaldchyde and 

EAA. Within this group, ' 

For the "best-estimate simplest" model we chose values of our rwo adjustable 

parameters (cthoxyacctal9~hydc oxidation and EAA excretion) that Uiinimi7.Cd the 

sum of the squares of the logarithms of the ratios of our model "predictions" and the 

EAA excretion observations ofGroscncken et al. This resulted in a half-time for 

EAA excretion of 26 hours, and an estimate that about 49% ofretained EE.is 

metabolized by the aldehyde dehydroganase pathway. The peak ofEAA excretion, 

however, occurcd only an hour and fony minutes after the end of exposure-in 

contrast to the 3-4 hours than Grosencken et 81. (1986b) observed. 

To achieve a laterpeak EAA excretion time, our "alternative simplest'' model ·· incorporated a much slower rate ofethoxyacetaldchyde oxidation than was found .optimal for the "best-estimate simplest" model. The result, however, was a peak 

time that was still only 2 hours and 20 minutes after the end of exposure. The halftime for EAA excrctiori became 31 hours, and 54% ofretained EE was estimated to 

be metabolized by the aldehyde dchydrogenase pathway. 

By contrast, for cthoxyacetaldehyde and EAA, our two "less simple" models incorporated 

tissue comparunents and diurnally-varying blood flows adapted from our earlier 

physiologically-based pharmacokinetic models for perchloroethylene (Hanis et 1986). Tissue/blood partition coefficients were estimated from observations ofother hydrophilic 

chemicals (FlSCrOVa-Bergcrova and Diaz, 1986). Within this group, . . Our overall best-estimate 1ess simple" model was tunm to the Groseneken et al. · (1986b) urinary EAA excretion observations as above without further adornment 

This resulted in a~of urinary EAA just under three hours after the end of · exposure, and a half-time for urinary EAA excretion of 33 hours. About 42% of 

retained EE was estimated to.be metaboli1.Cd via the aldehyde dehydrogenase pathway. 

Fmally, we noticed that comparisons otthe two points in the Groseneken et al. 

(1986b) data that were cxactlr, 24 hours apan led tO a much longer estimate for the 

: urinary EAA excretion half-life-about·70 homs. We therefore consttuctcda:zil: 

hour mociel" assuming this was the true excretion half-time, .but that EAA excretion 

·• · is 20% greaterduring waking hours than during sleep~ 1b:is resultedin apeak of 
I 

l 

I 

l 

l 

l 

t 

l 

I 

f 

I 

I 

~ 

S-2 

We tested the perfonnance of these models with data on the EE 

exposure, and preshift and postshift urinary EAA excretion/g creatinine in a 

group of 36 painters studied over several successive days by McManus (1987) 

and DeBord and Lowry (1986). In many cases the data allowed two separate 

estimates to be made of EE absorption on a particular workshift for each 

model--one estimate based on a comparison of preshift urinary EAA with 

postshift urinary EAA, and another estimate based on comparison of preshift 

urinary EAA with EAA excretion in the next day's preshift urine collection. 

In each case, the dynamic models were used to predict the EAA excretion that 

would have been expected at variO!-JS subsequent times ifthere had been no 

further exposure to EE during the workshift. The observed excess of urinary 

EAA over this prediction was then used with the same model to _infer the 

indicated moles of EE that had been absorbed during the workshift. 

Unfortunately, when we initially used this methodology to compare the 

aggregate moles of EE estimat~d to have beCn absorbed on all available 

worker-days with complete llifonn~tion, we found that all of the models 

produced estimates of EE absorption from the preshift-postshift comparison 

that were only about 31-33% of the corresponding estimates made from .the 

preshift-next day's preshift comparison. This difficulty was greatly reduced 

when we corrected our estimation procedures for diurnal changes in urinary 

creatinine-excretion using the observations of Lak.atua et al. (1982). After 

correction, the aggregate absorption estimated by the models for the preshiftpostshift comparison was 70 - 118% of the aggregate absorption estimated for 

the preshift-next day's preshift comparison. For subsequent regression 

analyses of the effects of various environmental factors on EE absorption, we 

used the average of the preshift-postshift and preshift-next day's preshift 

absorption estimates as, our dependent variable. . . 

A second criterion that was used to compare.the performance of the 

different models was the strength of the association between measured EE air 

concentrations• and estimated absorption.· On this teS 4ill of the models 

produced highly statistically sigtiifica,nt relationshipst• although the '70-hour" • ,.!,(,j ' ,, .... ~ ...

EAA excretion three and a halfhours after the end ofexpo5ure for the Groseneken et

al. (1986b) exposure J>attem, and an estimate that a much greater proportion (72%) ,ofietalluid EE is metabolized.by tha aldehyde dchydrogenase padlway. 

~ With a modest adjustment .for differmt actiYity levels. . * . , : . 
 .. Ratios ofthe.regression coefficients to theirstlDdant.emnianged,from 4.27 to 4..78-­

seeTable 3.5 on p.54. · · 

S-3 


model perfonned a little more poorly than the ·Others. In the end we could not 

completely rule out any of the models on the bases of the available data. Because 

the 70-hour model results in a greater conversion of EE to activated 

ethoxyacetaldyde and EAA metabolites, and also for a greater persistence of 

EAA in the body, it may serve in· later work to provide a plausible high estimate 

of internal body exposure to testicular toxins. 

Ofall the models we believe the '1ess simple" model is somewhat to be 

preferred to the others for the following reasons: 

o 	It incorporates plausible features used in full physiologically-based 

pharmacokinetic models (blood flows and organ sizes) and is 

therefore inherently somewhat more plausible. 

o 	It fits no worse to the primary Groseneken et al. (1986b) urinary 

EAA excretion data than the "best estimate-simplest" model, and 

somewhat better than the "alternative-simplest" model using the 

logarithmic least.::-squares criterion. 

o 	It shows a later peak of urinary EAA excretion than the two 

"simplest" models, which is more in keeping with the peak times 

observed by Groseneken et al. (1986b and 1987b). 

o 	It perfoms slightly better than the two "simplest" models in 

reconciling the moles EE absorbed as calculated l>y the two methods 

explored in Section 3.3 (comparing post~shift with preshift urinary 

EAA vs. comparing next-day's prcshift urinary EAA with preshift 

EAA.) 

Multiple regression.analyses relating model estimates of absorbed EE 


to activity-adjusted air concentrations and ratings of visil;>le skin absorption 


were perfonned for worker-days where respirators were and were not used. 


Surprisingly, the regression coefficients for absorption as a function of 


adjusted air concentration for worker days where respirators were worn was 


about 60% of the coefficient found for the worker days when respirators 


were not worn. The indicated respiratory protection factor of somewhat less 


than two-fold is at the lower end of in-use protection factors measured for 

I 

l 

l 

1 

l 

I 

I 

l 

II 

I 

I 

I 

I 

l 

I 

I 

S-4 

other agents in other industries (Smith, ·et al., 1980; Harris et al., 1974; Goble 

>Ct al., 1983). 

The same regression analyses were used to assess the relative 

imponance of direct inhalation exposure and skin absorption (as indicated by 

visible contamination of the skin with paint at the end of the shift) on EE 

absorption. Overall the "skin" regression coefficients, although indicative of 

some skin absorption did not quite achieve statistical significance. The 

relative magnitudes of the adjusted air and skin coefficients suggested that

direct air inhalation is likely to have been 3-5 times as large a source of EE 

absorption as dennal absorption for the group of shipyard painters that were 

studied. Calculations comparing the total absorption inicated by the models

with the total adjusted air exposures were not inconsistent with the possibility

that direct air inhalation could have accounted for essentially all of the 

observed absorption. 

The relatively long half life of EAA in the body, and the delayed 

appearance of peak EAA e~~tion after the end of exposure means that the 

use of urinary EAA concentrations to estimate worker exposure requires a 

dynamic model. There is appreciable carryover of EAA from day to day,• 

and it can be expected that EAA excretion rates build up in the course of a 

work-week with constant 8-hour exposure on each day. Table S-1 shows the 

day to day buildup as predicted by our favored "less simple" model, and the 

'70-hour" model. This table also shows the effects of expressing EAA 

excretion in ug/min vs mg/g creatinine, given the diurnal changes in 

creatinine excretion. In Section 4.4 (p. 64 below) we recommend fonnulas 

for calculating equivalent TWA EE air exposure levels from urinary EAA 

excretion data. 

The modeling we have done with the infonnation available to date has 

left many unanswered questions about the phannacokinetics ofethoxyethanol 

and related compounds. For the construction of full physlologcially-based 

pharmacokinetic models it would be desirable to have: 

I 

• See Table 2.9 on page 36 for the panrm ofexcretion expected after asin&}e day's exmurc. Also see Figures 1.2 and 1.3 for the original observations of Grosencken et al. 

(1 86b and l987b). 
S-5 

Teble S-1 . 

Predicted Urinary EHcretlon Of EthoHyecetic Reid et Various Times 


During Successive Doily 8-Hour Occupotional EHposure to 5.65 ppm 


EthoHyethanol (20 mg/m3) 


Tune.After "Less Simple Model" Prcdic­ "70-Hr Model PredicStan of tions (Best Estimate Model). · tions (Plausible Upper Bound) 

Exposure (ugEANmin. (mgEANg (ug EANmin. (mg EAA/g 

(min.) excreted) crcatinine•) excreted) crcatinine) 

Day 1 Post-shift 15.73 12.52 12.39 9.86 

(420mint• 

Day 2 Pre-shift 12.67 12.54 13.27 13.14 

(1380 mint.. 

Day 2 Post-shift 24.33 19.37 24.65 19.62 

(1860min) 

Day 3 Pre-shift 20.37 20.17 23.72 23.48 

(2&20min) 

Day 3 Post-shift 30.88 24.58 34.32 '27.32 

(3300min) 

Day 4 Pre-shift 25.04 24.79 31.96 31.64 

(4260min) 

Day 4 Post-shift 34.85 27.75 41.93 33.38 

(4740min) 

Day SPre-shift 27.88 .27.60 38.46 38.08 

(5700min) 

Day 5 Post-shift 37.27 29.67 47.93 38.16 

(6180min) 

4 Day Ave Pre-shift 21.49 21.28 26.85 26.59 

5 Day Ave Post-shift 28.61 22.78 32.24 25.67 

• Assuming 1.7 g per day of overall crcatinine excretion. and diurnal changes in crcatinine 

exccrction as given by Lakatua ct al. (1982)--Sce Table 3.3 on p. 50. This results in 

expected acatinine excretion rates of (.8559*1700 mg/day)/1440 min/day= 1.01 mg/min 

f<".' the two hours prccecding a 9:00 A.M. "prcshift" collection. ·and (l.034*1700)11440 = 

1.256 mg/min for the two hours prcceeding a 5:00 P.M. "postShift" collection. . 

•• The data given bcrc arc the expected instantaneous rates of dclivay of cthoxyacctic acid 

to the bladder. The 420 minute point is approximately the average rate that might be seen in 

a urine collection after an 8 hour shift, assuming that the urine has accumulated in the 

bladder between the 6- and 8-hour time points after the swt of the workday. . 

••• By the same reasoning as given for the post-shift time points. the pre-shift urine 

samples arc assumed to represent a two-hour accumulation of urine that was delivered to the 

bladder_on average 23 hours after the stan of the previous day's workshifl 

·--·---·------------·-···-·· . 
S-6 

(1) Measurements of relevant blood/air and tissue/air partition 

coefficents for EE, ethoxyacetaldehyde, and EAA. 

(2) In clinical settings such as those used by Grosenekent et al. 

(1986a,b; 1987a,b}, measurements of blood concentrations of 

cthoxyacetaldehyde and EAA. This might allow more definitive 

estimation of 

(a) rates of the two steps of metabolism for the aldehyde · 

dehydrogenase pathway (from EE to ethoxyacetaldeyde, and 

from ethoxyacetaldehyde to EAA), 

(b) the fraction of EE that is metabolized via the aldehyde 

dehydrogenase vs "other" pathway(s) 

(c) rates of tissue storage and release of ethoxyacetaldehyde, and 

return from storage. (Some aspects of the Groseneken et al. 

1986a,b results suggest that the usual phannacokinetic 

modeling assumption of equilibration between tissue levels 

of EE, ethoxyacetaldehyde, and EAA, and the levels in 

venous blood exit1ng the tissues may be leading to 

inaccuracies.) 

(3) Analogous phannacokinetic studies in animal systems where male 

and female reproductive effects have been measured. 

(4) Observations in human workers of the decline in urinary EAA 

excretion rates over several days of no exposure (iilcluding diurnal 

fluctuations in excretion). This would both allow resolution of 

some important uncertainties in the construction of human 

phannacokinetic models, and assessment of human interinidividual 

variability in EAA excretion. 

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1 . 
, TABLE OF CONTENTS 


Page 

1. 	Introduction 1 


1.1 Goals of the Analysis 	 1 


1.2 	Data Available for Analysis, and Structure of the Report 2 


2. 	Building Phannacokinetic Models Using the Groseneken et al. 8 


( l 986a,b) Data 


2.1 Basic Description of the Groseneken et al. (1986a,b) 8 


Experiments 


2.2 	Initial Puzzles and Possible Interpretations of the 10 


Exhalation Data 


2.3 	Initial Inferences from the Data on Urinacy Excretion of 16 


Ethoxyacetic Acid (EAA) and Consttuction of the "Simplest" 


Phannacokinetic ModelS · 


2.4 	Defining and Fitting Alternative Models to the Groseneken .22 


et al. (l986b) Urinary EAA Excretion Data 


2.4.1 	 Numerical Data and Fitting Techniques 22 


2.4.2 	Fitting the Adjustable Parameters for the "Best 24 


Estimate" and "Alternative" "Simplest" Models 


2.4.3 	Defining and Fitting the Adjustable Parameters 26 


for the "Less Simple" Models (With and Without 


Diurnal Changes in EAA Excretion) 


2.4.3.1 "Less Simple" Model Without Diurnal 26 


Changes in EAA Excretion ' 


2.4.3.2 	"Less Simple Model With Diurnal_Changes 28 


in EAA Excietion (The •70-Hour" .Model) 


2.5 	Long Tenn Excretion of EAA Under Different Models 35 


After a Single Day of Occupational Exposure to 


Ethoxyethanol 

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3. Assessing the Perfonnance of the Models Using the Shipyard 37 

Painter Data (Sparer et al., 1987, McManus, 1987, Debord and 

Lowry, 1986, and Welch et al., 1987) 

3.1 Basic Description of the Data Set 	 37

3.2 Methodology for Inferring Ethoxyethanol Absorption 44 

From the Urinary Data and the Alternative Models 

3.3 Comparison of Model Performance Using Criterion#!: 46 

Similarity of Absorption Calculated from Preshift/Postshift 

and Preshift/Next-Day-Preshift Data 

3.3.1 	Analysis Without Correction for Diurnal Cycles 46 

of Creatinine ·Excretion 

3.3.2 Analysis With Correction for Diurnal Cycles of 48 

Creatinine Excretion 

3.4 	Comparison of Model Performance Using Criterion#2: 53 

Strength of Association Between Air Concentration 

Measurements and.Total Calculated Absorption 

3.5 Conclusions on Model Perfonnance 	 58 

4. Inferences From the Models and the Shipyard Data 	 60 

4.1 The Effects of Activity Levels on EE Absorption Via Air 60 

and Dennal Routes . 

4.2 Relative Importance of Inhalation vs. Dennal Routes of 60 

Exposure 

4.3 The Possible Effect of Ambient Temperature on EE 64 

Absorption . 

4.4 Recommendations for the Use of Urinary Metabolite 64 

Measurements to Infer Overall Exposure in Working 

Populations

,4.s Oppommities for Further Worlc 	 69 

References 	 71
,· 


-1­ I. ' . 

1. INTRODUCTION 

1.1 Goals of the Analvsis 

This is the founh in a series of research efforts to improve the state of 

the art of risk assessment by making use of more Qetailed infonnation on the 

biological processes by which specific agents are processed and cause harm in 

biological systems.• 

Ethoxyethanol (ethylene glycol ethyl ether) (EE) and other glycol 

ethers are widely used as solvents in inks, paints, varnishes and products used 

in servicing automobiles (Veulemans et al., 1987; US EPA, 1984). Extensive 

animal studies indicate that the aldehyde and/or acid metabolites of glycol 

ethers produce testicular toxicity and infertility in males (Beattie et al., 1984; 

Chapin and Lamb, 1984; Cn:~sy and Foster, 1984; Creasy et al., 1985; Foster 

et al., 1984, 1986, 1987; Hardin et al., 1984; Hurtt and Zenick, 1986; Moss et 

.al., 1985; Oudiz and Zenick, 1986) and embryoto~icity and developmen~ 

anomalies in pregnant females (Anderson et al., 1987; Andersen and Hardin et 

al., 1984, 1987; Hawley et al., 1984a,b; Hardin and Eisenman, 1987; Johnson 

et al., 1984; Nelson et al., 1984; Toraason et al., 1986; Tyler et al., 1984; 

Wier et al, 1987; Zenick et al., 1984). This report lays the groundwork for a 

quantitative assessment of these effects in human workers. We construct.and 

test a series of semi-empirical .. phannacokinetic models ofthe processing of 

• The three previous analyses (on pcrchloroethylene, buwliene, and ethylene oxide) all 


applied physiologically-based pharmacakinetic modeling techniques to chemicals where the 


primary concern is carcinogenesis. Moreover in each of those cases it was rcasonable"1o 


postulate a primacy genetic mechanism fer the carcinogenic action-direct reaction ofthe 


agent (ethylene oxide) or a metabolite (perchloroethylcnc, buw:licnc) with DNA. The ideal 


goal ofthe modeling in those cases was therefore to calculate the integrated sum of ­ coocentration X time ofDNA-reactive material available in the different species as.a function ' 


ofthe levels and durations of external exposure. -:Although the precise mechanism ofaction 


ofthe glycol ethers in producing reproductive effects is not known, it seems reasonable to 


suspect that damage may result from maintaining a critical c:onccnuation of active 


metabolites at the site(s) of action for a defined time. In this case, therefore, ~t may be much 


more important to have a dynamic model capable ofdetermining peak levels ofin=nal 


exposure. and the duration over \.Vhich altcmative }lypothcsir.cd critical intcmal 


concentrations are maintained. · , · , · · · · 


•• As discussed in Section 2, due to the complexity 'ofthe two-step metabolism of 


etboxycthanol (via ethoxyacctaldehyde to ethoxyacctic acid), some peculiarities of the· 


findings ofGrOscneken et al. 98~b), and the lack of relevant data on partition - I 

coefficients. c:onsuuction of a full physiologically-based pf)armacokinetic model would 

require estimation of too many unknown parameters for the available information. ·i 

1 
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ethoxyethanol into its putative active metabolites--ethoxyacetaldehyde and 

ethoxyacetic acid--and the measurable excretion of ethoxyacetic acid in the 

urine. The final results at this stage are:

o General fonnulas for assessment of overall human dosage as a 

function of dennal and inhalation exposure,

o Guidelines for the use of urinary metabolite excretion data to 

determine overall absorption of ethoxyethanol from both inhalation 

and dennal routes ofexposure. This may be helpful as a supplement 

for routine environmental air monitoring for control of exposures. 

o 	A case study of the likely relative imponance of dennal and 

inhalation routes of expo~ure, and the efficacy of respirator use in

reducing exposure, under at least one type of pattern of use

(painting). 

In later work we will also use the final models to help express the 

l1uman and animal delivered dosage of the putative active metaobolites 

(ethoxyacetaldehyde and ethoxyacetic acid) in comparable tenns for puiposes 

of interspecies projection of effects. 

· 1..2 Data Available for Analysjs and Structure of the Report 

We will use two primary sources of infonnation. First, Groseneken et 

al. (1986a,b) have provided data from experimental clinical studies of the 

absorption of ethoxyethanol at various dose- and activity-levels during·four 

hour exposure periods of exJ>osure. They also report the·pattern oflater 

excretion of the minor amount (.1-.4%) of cthoxye~ol that is exhaled . 

unchanged.(Figure 1.1). Finally~ '.in the same subjects, they also provide..-. 

extensive measurements ofthe urinary excretion of ethoxyacetic acid.;..-for a 

period of42 hours after the start of the expo~ures (Figure 1.2). Our 

phannacokinetic models will be primarily fit to the results of these well 

controled clinical experlinents. ·'Nevertheless,·as·will be seen, there are 

significant ambiguities that can lead to a number ofdifferent plausible 

interpretatiom of the data whicb weWill represent·in alternative m~ ~ 

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controled clinical experiments. Nevertheless, as will be seen, there are 

significant ambiguities that can lead to a number of different plausible 

interpretations of the data which we will ·represent in alternative model 

fonnulations. The construction and flitting of the alternative models from 

these data will be the subject of Section 2. Still more recently, the same 

research group has reported similar studies of the acetate ester of 

ethoxyethanol (Groseneken et al., 1987a,b), with _generally similar results 

(Figure 1.3).• We have not yet incorporated these new data into the processes 

for fitting the alternative models. 

The second primary source of data is a set of industrial hygiene and 

biological monitoring results for a group of painters using ethoxyethanolbased products in a shipyard (Sparer, et al., 1987; Welch et al., 1987; DeBord 

and Lowry, 1986; McManus, 1987). For 2-4 consecutive days, the authors 

measured pre- and post-shift concentrations of ethoxyacetic acid and 

creatinine in urine, and 8-hour time-weighted air concentrations of 

ethoxyethanol, in a group of36 male workers. In addition, the workers were 

£lassified according to their use of respirators, and ratings were made of the 

strenuousness of their activity during the workday and of the degree of 

hand/arm skin exposure that was apparent at the end of each shift. In Section 

3 we use these results to test the models, and then in Section 4 we use them 

together with the models to assess ethoxyethanol absorption in relation to air • 

and dennal exposure, activity levels, and the use of respirators. 

The shipyard painter data set offers two kinds of opportunities to use 

the different models to estimate daily w~rker absorption of ethoxyethanol. 

Each model can be used to predict 

(1) the decline in urinary excretion of ethoxyacetic acid that would I have been expected from each worker's preshift urine collection to 

the same day's postshift collectjon. Any excess of the observed to I 

the predicted postshift excretion can then be interpreted in terms of I ethoxyethanol absorption. I 

I 

• The acetate ester bond is evidently hydrolyttd quite rapidly relative to the time course of 

the oxidation to ethoxyacctic acid. Groscncken ct al. (1987a) estimate a half-life for the· ester hrdrolysis of about 8-11 minutes. 
Figure 1.1 


Groseneken et al., 1986a--Breath 


Concentrations of EthoHyethanol in Humans 


After 4-Hour EHposures 


250 

· Aftw' IXpolll ft to 

-- 0 

0 

1>mg/ml•·· .. 20mg/ml~-~ 

£0mg/ml~ 

120 ., 

TlrM (rrint 

F'113 R.apiratory ~liminatlon ofEGEE after uponir~ at 

r~lt. D1Jt~ ~t ~on ±SDfor fiw ~jttu. 

-4­

- ..... .. - .. ._.....__....... _ 


.. 
ExpoMdto \ 

e Cmglml 

020mg1m> 4'\ 

.._•_30_"'9_,_m_lJ \I(V • 

0 ' I 

Z> 3) 114 

.~"Figure 1.2 

Gr;oseneken et ·al., 1986b--Urinary 


EthoHyacetic Acid EHcretion During and 


After 4-Hour EHposures to EthoHyethanol 


tlft~r exr;o.tUTt to EGEE at rtst. Data art tMtllU ± SD for 

fi'N! sfAb_ff'C.(f St.:JAdFt, (Jl'Jio inciit:"lt$ e~pD::it.rt peric-d. 

15 

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0 

Fig 1 

Tnw(h) 

,..,..- -·
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-

Urinary txcrttion oftthoxya«tic acid during and 


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t < ,, . ~ . ... 
f igure 1.3 


Groseneken et al., 1987b--Urinary 


EthoHyacetic Reid EHcretion During and 


After 4-Hour EHposures to EthoHyethnnol 


Acetate 


16 


Fc =27·6 
 Fw:61 ·1. 

p<OOOl p<0·001

-c 


! 12 


s:

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t 0 • .._..___._..___• _____........___........_


0 10 20 30 40 0 20 30 40 I Time (h) I Fig I UrUuiry ~xa~tion of~tltoxyac~tic acid tbuinr and aft" afovr hovr ~xposvn to EGEE·Ac,..., wlriou.s tolldiliotu: 

\ Uwtr/ml re). 28mr/mJ (0 ). and50mg/mJ (()) 011rs1or28mr/m> at JO W r•J ant/60 W (Q). DtuoanlltltllU ± 

} SEMforfi~ SMb.fects. Statisticalda10 or~ F ratios from thrtt ""'Y ANOVA: c • uponu~ conttntration, w • wtwkload. 

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(2) 	the decline in urinary excretion of ethoxyacetic acid that would 

have been expected from each worker's preshif t urine collection to 

the next day's preshift collection. Again, any excess of observed 

over expected ethoxyacetic acid excretion can be used to make a 

second estimate of ethoxyethanol absorption during the workday. 

A key test of the models is whether, in aggretate, the absorption estimates of 

the first type (preshift-postshift) agree with the absorption estimates of the 

second type (preshift-next day's preshift). As it happens, for several months 

we were unable to obtain reasonable agreement (within a factor of two) on 

this test for any of the model variants we tried. In the end, however, we were 

able to obtain agreement for our simplest models when we used the data of 

Lakatua et al. (1982) to correct for dirunal changes in creatinine excretion. It 

appears that failure to correct for this dirunal rhythm led to a significant 

distortion in the model predictions of post-shift ethoxyacetic acid excretion 

from pre.shift measurements. · 

.. 


"'' ... 

•':. .• .,. ,...... ... 

~ \- ' 	 .. 4 .. 
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2. 	BUILDING PHARMACOKINETIC MODELS USING THE 

GROSENEKEN ET AL. {1986a,b) DATA 

2.1 Basic Descrjptjon of the Groseneken ~t al. Ct986a,bl 

Experiments 

As mentioned earlier, Groseneken et al. (l986a,b) have recently 

provided two series of experimental clinical studies on groups of S young 

male volunteers exposed to ethoxyethanol (EE). The first group was exposed 

under resting conditions (seated in an arm chair) to three different

concentrations (at three different sessions separated by at least a week)-I 0, 


20, and 40 mgtm3. The second group was exposed to 20 mg!m3.at each of

three different activity levels (0, 30 and 60 watts) on a bicycle ergometer. 

Each exposure session consisted of four 50-minute periods separated by 10

minute breaks. •.....i....- •.• 

During the exposures, the authors measured a number of respiratory 

parameters, including total ventilation and the percentage of inhaled 

ethoxyethanol that was retained (Table 2.1 ). A number of initial conclusions 

about the phannacokinetics of ethoxyethanol are apparent from these data: 

(1) The data in the final column for group i show no evidence of 

nonlinearities in the absorption of ethoxyethanol or ethoxyethanol 

acetate as a function of exposure level. 

(2) 	The data on the fraction of inhaled ethoxyethanol that is absorbed 

are very nearly what one would expect if nearly all ethoxyethanol 

that reaches the alveoli is absorbed. [Alveolar ventilation at rest is 

generally assumed to be about '1J3 oftotal ventilation. This is 

compatible with the .59-.65 fractions absorbed seen ~or Group 1 in 

Table 2.la. As for the data for Group 2, it is known that the · · 

fraction oftotal ventilation reaching the alveoli generally rises with 

increasing exercise. Therefore the increasing trend of fraction 

absorbed with energy expenditure (the differences are significant at · 

P < .05) further suppons the notion of nearly complete absorption 

from the alveoli.] 

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Table 2.1 a 


Uentllation and Absorption of EthoHyethanol 


During EHposure (Grosenelcen et el., 1986a,b) 


Group and Total Ventilation Fraction EE Air Cleared Total AbConditions (Liters/min.) Absorbed* (Liters/min.) sorbed (mg) 

Group 1 (at rest) 

10mg/m3 12.7 +/- 1.6 .617 7.90 +/- 1.5 16.7 +/- 4.2 

20mg/m3 13.0 +/- 1.6 .646 8.45 +/- 1.4 35.1 +/- 7.6 

40mg/m3 12A +/- 1.6 .590 7.34 +/- 1.4 64.1 +/-14.5 

Group 2 (20mg/m3) 

0 watts 13.1 +/- 2.0 .633 8.25 +/- 1.4 33.3 +/- 8.4 

30 watts 21.8 +/- 3.8 .696 15.18 +/- 2.7 57.0 +/-11.8 

60 watts · 31.3+/-4.4 .706 22.13+/- 3.3 94.4 +/-13.9 

Table 2.1 b 

Uentllatlon and Absorption of EthoHyethanol Acetate 

During EHposure (Grosenelcen et al., 1987a,b) . 

Group and Total Ventilation Fraction EEac Air Cleared Total AbConditions (Liters/min.) Absorbed•.. (Liters/min.) sorbed (mg) 

Group 1 (at rest) 

14mg/m3 14.4 +/- 0.9** .562 8.09 23.3 +/- 2.0 

28mg/m3 13.7 +/- 0.8 .585 8.01 44.9 +/- 1.3 

50mg/m3 13.2 +/- 1.1 .645 8.51 85.1 +/- 5.5 

Group 2 (28mg/m3) 

0 watts 12.2 +/- 1.1 .553 9.45 37.8 +/- 2.4 

30 watts 22.3 +/- 1.1 .676 15.07 84.4 +/- 2.4 

60 watts 29.1+/- 1.3 .746 21.7 · 1i1 .5 +/- S.5 

•The fraction retained is (Ci - Cc)/Ci where Ci= the concentration in inhaled air, and Ce is 

the concentration in expired air. · · · 

••9111e data in this column for fraction cl~ and the liters/minute clW'3:11ce in the·next 

column were not given by Groscnckcn ct al. (l987a) but were calculated by us fromthe data 

in the other three columns. · 

••.Standard deviation, based on Sobsezvations in QCh case. ··,··· : ·• ~ ='· · 
l. 


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2.2 Initial Puzzles and Possible Interpretations of the Exhalation 

Data 

The concentration of ethoxyethanol in expired air was measured over a 

four hour period after the end ofexposure (Figure 1.1 above). These data 

were fit to a classical (empirical) two-compartment phannacokinetic model. 

For group 1 (at rest) the best fitting equations wer.e: 

10 mg!m3 exposure--Ce = 114e-.l17t + 25 e-.0065t 


20 mg!m3 exposure--Ce = 218 e-.128t + 36 e-.0070t 


40 mg!m3 exposure--Ce = 417 e-.149t + 59 e-.0068t 


where t = time in minutes and Ce is the expired air concentration in ug!m3. 

For group 2 (exposures to 20 mg/m3 at various activity levels) the best fitting 

equations were: 

0 watts-- Ce= 191 e-.122t + 34 e-.0074t 


30 watts-- Ce= 224 e-.108t + 33 e-.0069t 


60 watts-- Ce =246 e-.122t +44 e-.0084t 


The most recent data (Groseneken et al., 1987a), of exposure to ethoxyethanol 

acetate, show a quite similar pattern. For exposure at rest: · 

14 mg!m3 exposure--Ce =128 e-.107t + 54 e-.0078t 


28 mg!m3 exposure--Ce = 232 e-.112t + 86 e-.0072t 


SO mg!m3 exposure--Ce = 414 e-.139t + 119 e-.0080t 


For exposure to 28 mg!m3: 

30 watts-- Ce= 332e-.l19t + 108 e-.0083t 


60watts-- Ce= 246 e-.109t + 93 e-.0075t 


These equations and Figure 1.1 both indica~ thatEEis lost very 

I rapidly from the central circulation following the end of exposure. 'The 

average exponent of .131 in the group 1equations for the first (faster) ··­

1. comparunent in the original (Groseneken 1986a) experiments corresponds to 

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a half-life of only about five minutes. The average exponent for the second 

(presumably peripheral) compartment of .0068 corresponds to a half-life of 

slightly over 100 minutes. 

Theoretically, the rapid loss of EE from the central circulation could 

be the result of (1) exhalation of unchanged EE, (2) storage of EE in tissues 

with a high tissue/blood partition coefficient, or (3) metabolism. The first of 

these can be ruled out as a major contributor immediately. Groseneken et al. 

(1986a) report that in all groups the total amount of EE exhaled accounts for 

less than 0.4% of the amount retained. 

On the basis of the modeling we have done, it seems that the second 

process, reversible storage, is also unlikely to be a major contributor to the 

rapid depletion of the central compartment. In order for continuing storage 

in the periphery to significantly deplete the central compartment (relative to 

metabolism) after .the end of exposure, the second compartment must be 

relatively far from its equilibrium level at that time. With the second 

comparttneni having a half life of on the order of 100 minutes, however, the 

200 minutes of total exposure in the Groseneken et al. experiments can be 

expected to bring the system fairly near to equilibrium, unless transfer from 

the central to the peripheral compartment is extraordinarily slow relative to 

the capacity of the second comparonent. With slow transfer to the second 

compartment, however, it is difficult for the continuing transfer to still be an 

appreciable fraction of the.approximately 0.131 min-1 total loss rate from the 

central compartment. 

The EE exhalation equations reproduced above pose some other serious 

puzzles for modeling, however. In the equati<;>ns for group 1, although the 

amount of EE stored in the first comparnnent at the end of exposure appears 

to go up linearly with the external exposure level (with coefficients of 114, 

218, and 417 for the 10, 20 and 40 mg!m.3 sessions) the coefficients for the 

second compartment do not quite show the same fourfold increase with the 

fourfold increase in exposure. This is also seen in the equations for exposure · 

to ethoxyethanol acetate from Groseneken et al. (l987a). ·It is not certain 

from the papers whether the departure from llDearity for this coefficient is 

statistically significant, but given tWo separate observations of the same 

phenomenon, it would seem likely. Even more puzzling is the failure ofthe 

exhalation equations for the "group 2's'' (with exercise) to linearly reflect the · 

nearly three-fold increase in overall absorption that occurs with increasing 

.. y r .... ~ ~ ,,.. .. .. .., .......,.... ~ ' ' ·~ .,,... 

. -12

exercise (compare with the data in the last column of Tables 2.la and 2.lb). 

There are a couple of possible explanations for this:

·(1) The exercising subjects could have increased their rates of 

metabolism of, EE during exposure, so that the increased absorption 

was not reflected in any appreciable increase in EE in the body at 

the end of the exposure periods. One possible type of mechanism, 

for this might involve metabolism of EE in muscle tissue (muscle 

receives a greatly increased amount of blood flow with increasing 

exercise). Arguing against this is the very low activity of muscle 

tissue of alchohol dehydrogenase--the enzyme responsible for the 

initial oxidation of both ethanol and EE (Romer et al., 1986). 

(2.) The physiological conditions produced by increasing exercise 

(perhaps the greater transfer of alcoholic sugars etc. to be burned 

in muscle tissue) might somehow interfere with the transfer of 

ethoxyethanol to ·the slower-exchanging compartment. A relative 

increase in metabolism occurs because with the decrease in transfer 

to the peripheral c'c5mparp-nent, relatively more ethoxyethanol is 

available in the central compartment (where metabolism 


presumably takes place) 


Whatever the true explanation, after trying out a number of 

possibilities, we concluded that we simply did not have enough infonnation to 

build a full physiologically-based phannacokinetic model that would 

reproduce this particular behavior. Moreover, because of the relatively rapid 

metabolism of ethoxyethanol when compared to the dynamics of excretion of 

ethoxyacctic acid (see below), it was our judgment that the modest suggested 

nonlinearities in the distribution ofethoxyethanol between the central and 

peripheral compartments are not critical for our main problem-which· is the 

prediction of ethoxyacctic acid excretion. 1be key point is that the net· 

absorption of ethoxyethanol and ethoxyethanol acetate is linear with external 

air concentration. Therefore, the enzymes responsible for metabolism-·cannot 

be appreciably saturated. For presentpurposes we believe it is sufficient to 

represent the uptake and storage ofethoxyethailol in our models with a simple 

empirical equation derived from the Groseneken (l986a) results. -We named 

the models consttucted on this basis our "simplest" models. 

The usual way in which two-compartment empirical pharmacokinetic 

models are represented is with a central compannent that receives material 

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from the external exposure, and a peripheral compartment that exchanges 

with the central compartment: 

--0 

In building our "simplest" models, we found that-a somewhat modified · 

structure would be more tractable mathematically: 

UPTAKE2 
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As can be seen in this ~onnulation, ethoxyethanol is delivered directly from 

the external air to both central and peripheral compartments, although all 

metabolism and exhalation depend only on the material in the central 

compartment. 

The advantage of this is that the rate constant for transfer from the slow 

to the central compartment ("return to central" or "k21 ") is simply the 

regression coefficient found for the slower compartment in the Groseneken et 

al. (1986a) regression equations--about .0068 on average. Further, the sum 

of the metabolism and exhalation rate constants must simply be the regression 

coefficient found for the faster companment--about .131 on average. The 

exhalation rate constant needed to achieve reasonable correspondence with the 

absolute levels of exhaled ethoxyethanol was JXJ27 or about 0.2% of the total 

loss from the central companment (this is compatible with the reported range 

of total recovery of ethoxyethanol in exhaled air of 0.1-0.4%). The ratio of 

"uptakel" to total absorption ("uptake!"+ "uptake2") needed to achieve the 

right balance of accumulation in the two compartments at the end of exposure 

was found to be about 83%. Table 2\2 shows the overall correspondence of 

the pattern of exhalation exhibited by our "simplest" models to the composite 

equation derived from the Groseneken et al. (l986a) experiments. The . 

overall fit is clearly good enough that we will not be making gross errors by 

using this fonnlation to represent the availability over time of ethoxyethanol 

in the central compartment. This is what is required for the subsequent 

modeling of metabolism and excretion. 

As can be seen in the notes at the bottom of Table 2.2, the results for 

our "simplest" model fonnulation suggest that the great bulk of absorbed 

ethoxyethanol is metabolized quite rapidly-90% or so is processed by the end 

of the exposure period. The remainder is delivered to the central 

compartment and metabolized at a modest rate, according to the dynamics of 

the slower "peripheral" compartment At the end of the exposure, about 70% 

of the unmetabolized ethoxyethanol is contained in the peripheral 

compartment. 
-15

Table 2.2 

Correspondence Between The Pattern of Air 

EHhalati on for the ·simplest• Model end the · 

Composite Equatlon·.For the 6rosenelcen et a·1. 

( 1986&) Obseruatlons 

(EE £Hhalatlon after 20 mg/m3 eHposre for four 50­

mlnute periods separated by ten minute breaks.) 

Time After End Composite Equation "Simplest" Model 

of Exposure (min.) ug!m3 Exhaled ug!m3 Exhaled 

10 94.25 97.82 

20 47.29 48.20 

30 33.64 33.47 

40 28.58 28.18 

50 25.94 . 25.50 

·60 24.02 23.60 

80 20.90 20.53 

100 18.24 17.91 

120 15.92 15.63 

140 13.89 13.65 

160 12.13 11.91 

180 10.59 10.40 

200 9.24 9.07 

220 8.06 7.92 

240 7.04 6.91 

Total Absorption = 3.896 X 1 o-4 moles 


Total EE remaining unmetabolized at the end ofexposure--10.4% 


Total EE remaining unmetabolized one hour after exposure--5.9% . 


·­

-. ..... .. ..,_,...,~·:.\; , ·. :t - '': ,,., 

... : • lo . "'"" " --~ ... 

~ . -. .. ,,. 

,..Air c~alation =218 c<131t +36 c•.0068t. -~~~ 

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2.3 InitjaJ Inferences from the Data on Urjnary Exccetjon of 

Ethoxyacetjc Acid fEAAl and Construction of the "Simplest" 

Pharmacokinetic rtlodels 

Table 2.3 shows the total recovery of EAA in the urine over 4 2 hours 

of observation from the start of exposure in the two series of experiments 

(Groseneken et al., 1986b, 1987b ). Again it can be seen that the excretion of 

EAA is.essentially linear with absorbed dose. There is no evidence, ·. · ; 

therefore, that either the processes of metabolism ofethoxyethanol or the 

excretion of EAA are appreciably saturated at the doses studied. Overall, 

23.6% of the absorbed ethoxyethanol was recovered as EAA in the original 

experiments, and 22.2% of the absorbed ethoxyethanol acetate was recovered 

.as EAA in the later experiments. In order to reproduce this result, in addition 

to the pattern of decline of EAA excretion with time, we found it necessary to 

postulate that not all of the absorbed EE is metabolized to EAA. • In 

constructing the models, we. adjusted the fraction of EE processed by the 

alcohol dehydrogenase vs "other" pathways to agree with the average of 

23.6% excretion as EAA by 42 hours after the start of exposure observed by 

Groseneken et al. (1986b). 

Figu~es 1.2 and 1.3 on pp. 4-5 above show the dynamics of urinary 

EAA excretion observed by Groseneken et al (1986b and 1987b ). 

·Qualitatively the observations indicate that urinary excretion.(and thus the 

body levels of EAA) do not reach their peak until about three to four hours 

after the end of the exposures.•• Thereafter, they decline slowly-with a 

half-life of approximately 21-24 hours according to Groseneken et al. 

(1986a). As will be seen below, our analysis of the same data suggests that the 

half-life ofEAA may be even somewhat longer than this. ~ i . :(} \,, 

, ; 

• One alternative route ofmetabolism might involve primary attaek on the ether linJclie, 

possibly yielding ethanol and ethylene glycol. In rats Cheever et al (1984) found 

approximately 75-80% ~r administered 14c-1abeled EE was eventually excreted in the urine 

as EAA and a glycine ester ofEAA. 

••The more recent data (Groscneken 1987b), where exposure was to ethoxyethanol acetate, 

suggest that there may even be a second peak ofexcretion a few hours after the first. This 

suggests that like ethoxyethanol, EAA may be distributed between a central and peripheral 

pharmacokinetic compartment and that the dynamics oftranster among the compartments 

may be unusual (involve some discrete lags). However, to dale we have been unable to 

develop a twc:H:ompmttoent mOdel fer ethoxyacetic acid excredaa that.appreciably ~es 

on the perfonnance of the models in fitting tbeOmseneken et.al. (1986b) ob~··-· · -· .... • •. .,I :..~ .. • 
--

, ,. ·· fable 2.3a .· 

.Ouerall EHcretion of EthoHyacetlc ·Reid Duer·42 Hours In 

Relation to the Absorption of EthoHyethnnol {Gr.oseneken 

,l at .al., 'l 986b) \•· . , 

Group and EE Absorbed EAA Excreted in 42 hr % of Absorbed Dose 

Conditions (mg) (mg-Equiv of EE) Excreted As EAA in 

42Hr 

Group 1 (at rest) 

10mg/m3 16.7+/-4.2· 3.5+/-0.9 21.1+/-7.5 

20mg/m3 35.1 +/-7.6 7.4+/-0.7 21.7+/-3.9 

40mg/m3 64.l+/-14.5 12.2+/-2.4 21.0+/-7.8 

Group 2 (20mg/m3) 

0 watts 33.3 +/- 8.4 8.4+/-2.1 25.6+/-5.2 

30 watts 57.0 +/-11.8 16.2+/-4.4 28.5+/-5.5 

60 watts 94.4 +/-13.9 21.0+/-5.9 23.5+/-5.5 

Average 23.6 % 

Table 2.3b 


Ouerall EHcretlon of EthoHyacetlc Reid Duer 42 Hours In 


Relatlo.n to the .Rbsorptlon of EthoHyethanol Rcetate 


(Groseneken et .al., 1987b) 


Group and EE-Ac EAA Excreted in 42 hr % of Absorbed Dose 

Conditions Absorbed (mg) (mg-Equiv of EE-Ac) Excreted As EAA in . 42Hr 

Group I (at rest) 

14mg/m3 23.3+/-2.1 5.34+/-0.64 ·~\- 22.9+/-1.3" 

28mg/m3 44.9+/-1.3 8.76+/-0.88 . .19.7+/-2.4· 

50mg/m3 85.1 +/-5.5 . 15.47+/-0.68 18.3+/-0. 7 . 

Group 2 (28mg/m3) 

, 0 watts 37.1 +/- 2.4 . ;._,.::. "8.77+/-0.85 r:·,:~.?:, ... "' 23.2+/-l.6 

30 watts 84.4 +/- 2.5 '··.· ·19.94+/-1.86 ·23.5+/-I.9: 

60 watts 121.5 +/- 5.4 ~-·, ,.30.83+/-3.32 ; .; .,'";: , .. 25.9+/-3.4 

' ic'• .... • ..... 

• The nmnbers following the +/- symbols arc the standard errors of the means for eac4. 

group. . 
-18­

When combined with the findings of the previous section--that nearly 90% of 

the absorbed ethoxyethanol may have already been metabolized at the end of 

exposure--the delayed peak of EAA excretion after exposure implies that 

either there may be appreciable storage of an intennediate fonn between EE 

and EAA or there may be a lag in the delivery of EAA from the tissues where 

it is metabolized to the renal excretory aparatus. 

On the basis of the known metabolism of EE by aldehyde 

dehydrogenase, the intennediate fonn is presumably ethoxyacetaldehyde. 

Ethoxyacetaldehyde is potentially of considerable toxicological interest in the 

light of recent in vitro findings by Foster et al. (1986) which imply that 

methoxyacetaldehyde may be on·the order of fifty times more potent than 

methoxyacetic acid in causing detachment of Sertoli-genn-cells (presuming 

that this is a good model of toxicity in vivo). For some time it has been known 

that metabolism is essential for the toxic action of glycol ethers on testicular 

cells (Moss et al., 1985). 

Unfortunately there no measurements of the levels of 

ethoxyacetaldehyde or ethoxyacetic acid in human blood, exhaled air, or any 

other body tissue. There are also no measurements of partition coefficients, 

or association constants for the reversible reactions fonning covalent linkages 

to -SH, -NH2 or -OH groups (on proteins or other molecules in blood or 

elsewhere). In short, we have little to go on to help us construct a full 

physiologically based phannacok.inetic model involving the aldehyde 

derivatives of glycol ethers. For our "simplest" models, we have therefore 

chosen to represent the oxidation ofethoxyethanol to ethoxyacetaldehyde and 

then to ethoxyacetic acid, and the later excretion of the EAA, in the most 

straightforward possible way-as simple linear rate constants, acting total 

body stores. of ethoxyacetaldehyde and EAA in each case. The full diagram of 

our "simplest" model is·shown in Figure 2.1, and the corresponding equations 

are given in Table 2.4. . 

I 

i 

, ­ ~ : ~~'- ·~"""'"""' ~ 

. The system shown has two parameters that can be adjusted to fitthe 

cthoxyacetic acid excretion data (in addition to the proportion of · 

ethoxyethanol that is metaboliz.ed by alcohol dehydn,genase vs~ hypothesized 

other routes-which was discussed earlier): 

(1) the rate of oxidation ofethoxyacetaldehyde to ethoxyacetic acid 

(2) the rate of urinary excretion of body stores ofethoxyacetic.acid. • •. .. t • . ' • 
Figure 2.1 


Diagram for the .. Simplest" Models 


RINE EAA 

URINARY EXCRETtON 

BODY EAA 

EALD_OXIOATION 

-19­

­

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-20­

Table 2.3 

Equations for the "Best-Estimate Simplest" Model 

Equations for Accumulators; 

BODY_EAA =BODY_EAA + dt • ( EALD_OXIDATION - URINARY_EXCRETION) 

INIT(BODY_EAA) =O{initial value...} 

BODY_EALD =BODY_EALD +dt • ( EE_ADH_OXIDATION -EAl.D_OXIDATION) 

INIT(BODY_EALD) =0{ initial value •.. } . 

· 

Ccntral_EE = Ccntral_EE + dt • ( UYrAKE - EE_ADH_OXIDATION 

NON_ADH_METAB - EXHALATION+ k21 } 

INIT(Central_EE) =O{initial value ... } 

EE2_Compamncnt =EE2_Compamnent +dt • ( -k21 + UPTAKE2) 

INIT(EE2_Compartmcnt) =O{initial value ... )

EXHALED_EE =EXHALED_EE + dt *(EXHALATION)

INIT(EXHALED_EE) =0 {initial value ... } 

01HER_METABOLITES = 01HER_METABOLITES +dt • ( NON_ADH_'METAB ) 

lNIT(OTiiER_MET ABOLITES) = 0{initial value... } 

TOTAL_ABS=TOTAL_ABS+dt•(ABSORPTION) 

lNIT(TOTAL_ABS) =O{initial value ... } 


URINE_EAA =URINE_EAA + dt • (URINARY _EXCRETION ) 


INIT(URINE_EAA) =O{initial value ... } 


E9uatjons for Converters; 

ABSORPTION= UPTAKE+ UPTAKE2 {MOLES/MIN} 

EALD_OXIDATION = .14*BODY_EALD {MOLES/MIN} 

EE_ADH_OXIDATION = .0624*Central_EE 

EXHALATION= IF (EXPOSURE= 0) THEN (2.7E-3)•Centtal_EE ELSE 0 

{MOLES/MIN} 

EXPOSURE= IF (TIME <= 480) THEN 5.65 ELSE 0 {PPM} 

.Jal =.0068*EE2_Companmcnt 

NON_ADH_METAB =.0659*Central_EE (HYPO'IHESIZED ALTERNATIVE ROUTE 

OF METABOLISM}

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Tnble 2.3, CONTINUED , 

EQUATIONS FOR THE 11 Best-Estimnte SIMPLEST" MODEL 

UGM3_EXHALED =IF (EXPOSURE = 0) AND (TIME <= 960) 11IEN 

(EXHALATION/12.7)*9.0lElO ELSE IF (EXPOSURE= 0) 1HEN 

.74•(EXHALATIONNALV)*9.01El0 ELSE 0 

{ASSUMES 35% DEAD SPACE, AND TIIBREFORE CORRRESPONDING Dll..UTION 

OF ALVOLAR A.JR CONC. 1/1.35 = .74} 

twrAKE = .83*VALV*EXPOSURE*lE-6/25.45 {MOLES/MIN} 

UPI'AKE2= .17*EXPOSURE*VALV* lE-6125.45 {MOLES/MIN} 

URINARY _EXCRETION= (3.7E-4)*BODY_EAA 

URINE_UG_PER_MIN = URINARY_EXCRE~ON*l.041E8 

VAL V =IF (TIME<= 960) OR (1440 <TIME) AND (TIME<= 2400) OR (2880 <TIME) 

AND (TIME<= 3840) OR (4320 <TIME) AND 

(TIME <= 5280) OR (5760 <TIME) AND (TIME<= 6720) OR 

(7200 <TIME) AND (TIME<= 8160) OR (8640 <TIME) AND 

(TIME <= 9600) THEN 11.38 ELSE 4. · 

·' . .• , ......... .... 


·. 

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-22­

The fitting of these two parameters to the available urinary excretion 

data is outlined in the next section. 

2.4 Defining and Fitting Alternative Models to the Groseneken et 

al. Cl986b) Urjnary EAA Excretion Data 

2.4.1 Numerical Data and Fitting 'Tecniques 

Table 2.4 shows the Groseneken et al. (1986b) ethoxyacetic acid 

excretion data in numerical form, as well as we could recover them from the 

figures in their paper. It can be seen that the standard deviations of the 

measurements of urinary EAA tended to be larger for larger absolute 

concentrations of EAA. This suggested that the measurement errors are more 

likely to be well described as lognonnal, rather than normal distributions. In 

fitting the data, we therefore wished to choose values of our adjustable 

parameters so as to minimize the sum of the squares of the Io2arithms of the 

ratios of the observed and model-"predicted" EAA excretion rates. In 

addition, it can be seen in the final column of the second part of Table 2.4 that 

the coefficients of variation for the very earliest time point (30 minutes after 

the start of exposure) were considerably larger than was seen for later time 

points. Rather than develop a complex weighting scheme for this one set of 

points, we elected to exclude the 30 minute points from the model fitting. 

The fitting process was facilitated by the fact that there are no elements 

in the models that produce nonlinearities with absorbed dose of EE. This 

allowed us to run each model variant only once (for the 20 mg!m3 exposure at 

rest condition) and then use the results at each time point to linearly project. 

the ethoxyacetic acid excretion rates as a function of time for other exposure 

conditions. A similar linear adjustment was made to bring the average 

urinary excretion for all six exposure conditions to 23.6% as discussed in 

Section 2.3 (implicitly this was simply.an adjustment of the proportion of total 

absorbed EE that was processed via the alcohol dehydrogenase p~thway.) 

l . 

· Table 2.4 

Urinary EthoHyacetlc Reid EHcretlon .Obseruatlons 

&rosenelcen et al. (1986b) 

Groups Exposed At Rest ........... Groups Exposed to 20 ugtm3 


Time After 10 uglm3 20 uglm3 40 ug/m3 O.W 30.W 60.W 

Stan of Exposure (min.) 

30 .15 .39 .88 .76 .99 1.48 

90 .88 1.48 2.96 2.05 2.47 5.21 

150 1.35 2.45 4.41 4.08 4.39 8.76 

210 1.87 2.96 5.66 4.59 7.23 12.27 

270 2.69 3.89 . 7.87 . 4.86 8.91 14.49 

330 2.51 4.51 7.73 5.82 11.34 15.97 

390 2.74 5.13 8.21 5.80 12.55 17.51 

450 3.16 4.91 8.52 6.00 10.79 17.13 

540 '2.42 2.96 8.25 5.55 8.97 12.37 

660 2.19 3.56 7.96 S.06 9.98 13.43 

780 1.93 3.75 8.36 5.09 9.40 12.99 

1080 1.10 2.72 4.57 3.53 7.73 8.35 

1560 1.18 1.87 5.24 3.78 ·8.71 9.11 

2040 1.47 3.03 5.57 3.33 6.17 8.49 

2520 .89 1.79 3.48 2.67 4.86 7.87 

Standard Deuiatlons of the Measurements (5 Subjects): 

Groups Exposed At Rest Groups Exposed to 20 ugtm3 

TuncAftcr 10uglm3 20ug!m3 40ugtm3 O.W · 30.W 60.W 

Start ofExposure (min.) 

30 .26 .28 .53 .so .42 .97 

90 .39 .67 1.03 .42 1.65 3.80 

150 .37 1.11 2.14 .69 1.19 5.34 

210 .64 1.49 .94 1.51 3.60 8.15 

270 1.42 1.04 2.16 1.76 4.49 6.76 

330 1.12 1.57 3.60 1.51 3.56 4 .29 

390 .90 2.32 1.57 2.18 3.36 4 .49 

450 1.02 2.20 1.65 1.66 4.62 3.73 . 

540 .37 .79 1.60 2.12 1.60 4.24' 

660 1.16 1.42 2.10 1.40 --S.18 5.56 

780 1.22 1.37 .,:2.59 1.14 3.61 4 .79 

1080 .57 .91 1.52 1.63 2.94 2.89 

1560 .67 .90 .. 1.31 . 1.38 '2.86 2.02 

2040 ·.. •99 -.61 ,.84 1.68 1.51 3.06. 2520 .24 .81 ,2.94 1.18 1.68 .84 

Grand Geometric Mean (Excluding 30 Min. Point) 

Geom. Mca 

Cocf. Var.· i 

.718 

.437 

.345 

.382 


.386 


.341 


.300 


.300 


.239 


..391 ~ 

·.362 


.390 


.349 


.311 


.345 


. • 345 

• The coefficient of variation is the standard deviation of each measurement divided by the 

mean (in the corresponding position in the upperpart of the table). The numbers in this 

column represent the geometric means ofallsix coefficients ofvarlati~ at each timepadiL 

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2.4.2 Fitting the Adjustable Parameters for the "Best 

Estimate" and "Alternative" "Simplest" Models 

The upper part of Table 2.5 shows the sums of the squares of the 

differences between the loganhms10 of the observed and model-predicted

EAA el.cretion rates for our "simplest" models for various trial values of the 

rate constants for ethoxyacetaldehyde oxidation and EAA excretion. To place 

these numbers in perspective, a sum of log squares of 5 represents, for the 

average of the 84 points, a ratio of about 1.75 between a typical point and the 

model prediction.• Similarly, a sum of log squares of 4..3 (the best fit we 

achieved) represents a typical ratio of 1.68. It can be seen that the optimum 

value for the ethoxyacetaldehyde oxidation rate is affected by the value chosen 

for the EAA excretion rate. 

The lower portion ofTable 2.5 shows the times at which EAA 

excretion reached its peak, f~! the various combinations of parameter values. 

We were not entirely pleased to notice that optimizing on our primary . 

criterion for fit--minimizing the sum of the squared log deviations--drove us 

to set the ethoxyaldehyde oxidation rate at such a high level that the peak of 

EAA excretion was predicted to happen at 330 minutes--only an hour and

forty minutes after the end of exposure. It will be recalled that Groseneken et 

al. (1986a) observed the true peak at 3-4 hours after the end of exposure. We 

therefore decided to explore in parallel the implications of an "Alternative" 

variant of the "Simplest" model in which the ethoxyacetaldehyde oxidation 

rate was set at a relatively low value (.03/min), which, after optimization of 

the EAA excretion rate, led to a peak EAA excretion at 370 minutes (2 hours 

and 20 minutes after the end ofexposure). 

For the "Best Estimate-Simplest" model, the requirement for 23.6% 

EAA excretion over 42 hours led us to allocate 48.6% of the metabolii.ed EE 

to the alcohol dehydrogenase pathway (rate constants of .0624/min. 8Jld_:· - , 

.0659/min. for the·ADH and non-ADH pathways, respectively). For the: 

"Alternative-Simplest" model, 53.5% was allocated to the ADH pathway (rate 

constan:s of .0687/min. and .0596/min. for the ADH and non-ADH routes). 

• 10(5/84)112 =1.754 
· Table 2.5 

Fitting the Adjustable· Parameters for the "Simplest" ·Models 

(First criterion: the sum of the squares of the differences between the 

model-predicted and observed log10(EAA excretion rates): 

Ethoxyacctaldehyde 

Oxidation Rate Urinary EAA Excretion Rate (x lo-4)/min. 

!Jnin::l.~)~~3~.2~6--~3~·-5~~~3,~7~~--4~,0----~--4-.4--.~-4~,-5~---5..... 0 

.025 6.412 

.03 5.742 5.145 5.059* 

.035 5.343 

.04 5.089 

.045 4.914 

.05 4.805 

.06 4.658 

.07 4.576 

.09 4.496 4 .3860 

.10 4.486 4.400 ~.3814 4.433 4.710 5.234 

.11 4.460 

:12 4 .3809.. 

(Second Criterion: the times of peak EAA excretion--minutes after start of np~un) · 

Ethoxyacetaldehyde 

Oxidation Rate Urinary EAA Excretion Rate (x to-4)/min. 

!min::l) 3.26 3.5 3.7 4.0 4,4 4.5 5.0 

.025 415 

.03 395 375 ~70* 360 

.035 385 

.04 375 

.045 370 

.05 365 

.06 355 

.07 355 

.09 350 335 

.10 350 340 335 320 . ·305 . 300 

.11 34C 

.12 330** 

•This combination of cthoxyacctaldchydc oxidation rate and urinary EAA excretion rate was 

chosen as the "Alternative-Simplest" model. ~ -· . _ 

"This combination ofethoxyacetaldehyde oxidation rate and urinaryEAAcxaetion rate · was chosen as the "Best Estimate-Simplest" model. ··· , 

-25­
-26­

The calculated optimal urinary excretion rates correspond to tenninal 

half-lives for urinary excretion of 31.2 hours in the case of the "Best 

Estimate-Simplest" model and 26.2 hours in the case of the "AltemativeSimplest" model. The latter is somewhat closer to the range of 21-24 hours 

reported by Groseneken et al. (l986b) themselves (using calculation methods 

that unfortunately were not described). 

2.4.3 	 Defining and Fitting the Adjustable Parameters for 

the "Less Simple" Models (With and Without Diurnal 

Changes in EAA Excretion) 

2.4.3. 1 "Less Simple" Model Without Diurnal Chan&es in EAA 

Excretion 

We were still not entirely happy with the relatively early appearance of 

the peak in EAA excretion,.even in the "Alternative-Simplest" model. We 

therefore explored the implications of a "less simple" model structure (Figure 

2.2) which has many features borrowed from our earlier physiologicallybased phannacokinetic models. By having both steps of metabolism occur in 

the liver, while excretion originated in the central "vessel-rich-group" 

compartment, we hoped to allow some ethoxyacetic acid to be excreted at 

early time points after the stan of exposure while still producing a broadening 

of the time pattern of release o.f the EE metabolites from the large combined 

muscle/fat compartment, and hence a later peak EAA excretion time. 

Tissue/blood partition coefficients for the model were derived from 

Fiserova-Bergerova et al. (1986) assuming that ethoxyacetaldehyde and EAA 

would both have parition coefficients equal to the average for the seven 

hydrophilic chemicals studied by those authors:• 

Liver and Vessel-Rich Group ..749 • 

Fat Group ~68 

·Muscle Group :726 

Muscle/Fat Groups Combined (weighted average) .712 

• 

. 

"

.. ..._ 

'-*' 

. ~ ~ 

, ,;S ,J /. '°' . 

, ._11.

-. .. 

• This assumption is particularly questionable in die case.of ethoxyaceta1dchyde because of 

the possibility ofreversible covalent binding lrith ~~sulflydryl. .and hydroxY.l': gtoup~ . 

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Figure 2.2 


DiBgrBm for the "Less Simple" Models 


EE_AOH_Oxidation NonAOH_EE_metab 

URINE_EAA : :.; 1" r;:~ --;:. •. :- -. ·i' ~;' :i,i' < ; '·~ .. t.... .:..r-2°':~ :.t.... ~ 

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These models also incorporate a daily change of blood flow and alveolar 

ventilation rates between waking and sleeping periods. 

The optimization of the adjustable parameters for this model structure 

is shown in Table 2.6, and the resulting equations are given in Table 2. 7. It 

can be seen that with this structure, we were able to achieve a peak as late as 

400 minutes, with no worse an overall fit to the EAA excretion data, as judged 

by the sum of the squares of the log ratios criterion. For this model, the 

tenninal half-life for urinary excretion of EAA was 33.4 hours, and 42.4% of 

the metabolized EE was allocated to the alcohol dehydrogenase pathway (rate 

constants of .05445/min. and .07385/min. for the ADH and non-ADH 

pathways, respectively). 

2.4.3.2 "Less Simp1e" Model With Diurnal Chanies in EAA Excretion 

CThe."70-Hour" Model) 

In observing the pattern of deviations of the EAA excretion rates from 

the model predictions, we noticed that the points at 1560 and 2040 minutes 

after the start ofexposure tended to be higher than the adjacent points at 1080 

and 2520 minutes (see Figures 1.2 and 1.3, and Table 2.4). This suggested 

that there might be a diurnal pattern of change in the excretion of EAA. that 

could prove misleading. Ifwe compare the excretion half-life implied by 

pairs of the last four points in the Groseneken et al. (l986b) data set we see: 

Tune After Groups Exposed At Rest Groups Exposed to 20 ugtm3 Geom. 

Start ofEx- 10 uglm3 20 ugtm3 40 ugtm3 ow 30W row Mean 

poSUIC (min.) ofT112 

1080 i.io 2.72 4.S7 3.S3 7.73 8.35 

2S20 .89 1.79 3.48 2.61 4.86 7.87 

Tia• (hours) 78.S 39.8 61.0 . 59.6 3.5.8 28i 69.7 

1.5&) 1.18 1.87 · S.24 3.78 8.7i 9.11 

2S20 .89 1.79 3.48 2.67 4.86 7.87 

Tia• (hours) 39.32 2S4 27.1 31.9 19.0 75.8 48.1 

2040 1.47 3.03 S.51 3.33 6.17 8.49 

2S20 .89 . 1.79 3.48 2.67 4.86 7.87 

Tia• (hours) 11.0 :· ·10.s 11.8 25.l 23.2 281 19.7 

• Tia in hours= On 2)*(T2 - T1)1[60*ln (EAA excretion me at T'1/EAA excretion me at 

Tt), where the Ts are times af1er the start ofexposure in minutes. 

I 

1 
-29­

, 'Table 2.6 

Fitting the Adjustable Parameters for the "Less Simple" Model 

(Without Diurnal Changes in Urinary EAA Excretion) 

(First criterion: the sum of the squares of the differences ·between the 

model-predicted and observed log10(EAA excretion rates): 

Ethoxyacctaldchydc 

Oxidation Rate Urinary EAA Excretion Rate• 

<Moles EM ProdUCed .003 .0038 .004 . .006 

Mole Eald in liver-Min.) 

0.2 6.863 

0.3 8.238 5.266 

0.4 4.932 

0.5 5.956 4.846 4.929 

0.75 5.216 

1.0 4.972 4.430 4.378.. 5.438 

1.2 4.412 

' 

(Second Criterion: the times of peak EAA excretion-·minutes after start of 

exposure) 

.Ethoxyaccialdehyde 

Oxidation Rate Urinary EAA Excretion Rate (min.-1) 

(Moles EM pro<iuced .003 .0038 .004 .006 

Mole Eald in liver-Min.) 

0.2 545 

0.3 550 475 

0.4 440 

0.5 490 450 410 

0.75 450 

1.0 425 400 400•• 360 

1.2 395 ~ . ..,, 

, .. 

• Moles EAA excrctcd/(Moles EAA in the Vessel-Rich Group-Min.). · 

•• This combination of values for the adjustable parameters was scl~ as the best fit for 

the '1ess simple" model. 

--· -------. ­
I 

I 

l 

I 


l 


I 


I 


I 

1 

l 


I 


Teble 2.7 


Equations for the •Less Slmple• Model (Without 


·Dlurnali Changes In ERR EHcretlon) 


Eguatjons for Accumulators: . 

CENTRAL_EE =CENTRAL_EE + dt • ( Uptakel + EE2_EEl_Transfer - EE_Exhalation ­

­

­

EE_ADH_Oxidation - NonADH_EE_metab) 


INIT(CENTRAL_EE) =O(initial value ... } 


EE2 = EE2 + dt * ( Uptake2 - EE2_EEl_Transfer) 


INIT(EE2) = O{initial value ... ) 


ExhaledEE = Exhaled.EE + dt • ( EE_Exhalation ) 


lNIT(ExhaledEE) = 0{initial value ... ) 


Liver_E.4.A =Liver_EAA + dt • ( EAID_Oxidation - UVER_EAA_Elim + 


LIVER_EAA_Perf) 


lNIT(Liver_EAA) =O{initial value ... ) 


Liver_EALD = Liver_EALD + dt • ( EE_ADH_Oxidation - L_EAW_Elim+ 


LIVER_EAID_Perf- EALD_Oxidation ) 


INIT(Liver_EALD) =O{initial value ... ) 


MFG_EAA = MFG_EAA +dt • ( MFG_EAA_Perf - MFG_EAA_Elim) 


INIT(MFG_EAA) = O{initial value ... } 


MFG_EALD = MFG_EALD + dt • ( MG_EALD_Perf - MG_EALO_Elim) 


INIT(MFG_EALD) =O{initial value ... ) 


NonADH_Metabolites =NonADH_Metabolitcs + dt • ( NonADH_EE_metab ) 


INIT(NonADH_Metabolites) =O(initial value ...) 


TOTAL_ABSORBED =TOTAL_ABSORBED + dt • (Absorption ) 


INIT(TOTAL_ABSORBED) = 0 


URINE_EAA = URINE_EAA + dt • ( Urine_EAA_Excr) 


INIT(URINE_EAA) = 0{initial value.••I 


VRG_EAA = VRG_EAA + dt • ( UVER_EAA_Elim - UVER_EAA_Perf 

MFG_EAA_Perf +MFG_EAA_Elim - Urine_EAA_Excr) 


INIT(VRG_EAA) •O(initial value ••• ) 


VRG_EALD = VRG_EAID +dt • ( L_EALD_Elim- UVER_EALD_Perf 

MG_EALD_Perf + MG_EALD_Elim) 


INIT(VRG_EALD) =0 (initial value~.. ) 


Eguatjons for Convettors: 

Absorption 111: Uptake!+ Uptakc2 {Moles/min} 

AW AKE_TIME =960 {minutes} 

DAY= DAYl_S +RESTDAY +DA Y9_12 - 1 ··, "' ..• ~ ~.: 

-30­
-31­

table 2.7, ,Continued 


Equations for the •Less Simple• Model (Without 

Diurnal Changes In ERR EHcretlon) 

DAY1_5 =IF ~0) AND (TIME<l440) 1HEN 1 ELSE IF (TIME~ 1440 ) AND 

01ME< 2880) 11iEN 2 ELSE IF (TIME~ 2880) AND (TIME < 4320) nIEN 3 ELSE IF (TIME~ 4320)AND (TTh1E<5760) 1liEN4 ELSE IF ~760) AND (TIME<7200) 

1HEN 5 ELSE 0 

DAY9_12 =IF (TIME >= 11520) AND (TIME < 12960) 1HEN 9 ELSE IF (TIME 

>=12960) AND (TIME< 14400) 1HEN 10 ELSE IF (TIME>= 14400) AND (TIME< 

15840) TIIEN 11 ELSE IF (TIME >=15480)AND (TIME<l 7280) IBEN 12 ELSE 0 

EALD_Oxidation = Livcr_EAlD 


EE2_EE1_Transfcr = .0068*EE2 


EE_ADH_Oxidation = .0624*CENTRAL_EE 


EE_Exhalation =IF (EXPOSURE =0) 1HEN 2.7E-3*CENTR.AL_EE ELSE 0 


EXPOSURE= IF (TIME < 50rAND (pA Y < 1) or (60 <=TIME) and 


(TIME< 110) or (120 <=TIME) AND (TIME< 170) OR (180 <=TIME) AND (TIME< 


230) 1HEN 5.65 ELSE 0 {ppm} 


LIVER_EAA_Elim = UVER_FLOW*Livcr_EAA/(2.476*.749) 


LIVER_EAA_Perf =LIVER_FLOW*VRG_EAA/3.551 


LIVER_EALD_Perf =LIVER_FLOW*VRG_EALD/3.551 


LIVER_FLOW =IF (DAY * 24 *(J() <=TIME) AND 


(TIME< DAY * 24 * (J() +AWAKE_J'IME) 


TIIEN 1.25 ELSE 1.4 


L_EALD_Elim = Livcr_EALD*UVER_FLOW/(2.476*.749) 


MFG_EAA_Elim = MFG_EAA*MFG_FLOW/(49.78*.712) 


MFG_EAA_Perf = MFG_FLOW*VRG_EAAl.3.551 


MFG_FLOW =IF (DAY• 24 *(J() <=TIME) AND 


(TIME< DAY * 24 * (J() +AWAKE_TIME) 

TIIEN 2.91 ELSE 1.45 

MG_EALD_Elim = MFG_EAID*MFG_FLOW/(49.78*.712) 

MG_EALD_Pcrf = MFG_FLOW*VRG_EALD/3.551 

NonADH_EE_metab = .0659*CENTRAL_EE 
~ 

I 

I 

I 

I 

.. "' 

''t' ~ ... .• l ;o' .... "' 

·- .-. . ... 

l 

t l 

-32­

Teble 2.7, Continued

Equations for the •tess Simple• Model (Without 

Diurnal Changes In ERR EHcretlon) 

RESlDA Y =IF (TIME >=7200) AND (TIME<8640) 1llEN 6 ELSE IF (TIME >=8640) 

AND (TIME<10080) THEN 7 ELSE IF (TIME>= 10080) AND OiME<l 1520) 1HEN 8 

ELSE 'IF (TIME >=17280) AND (TIME<18720) TIIEN 13 ELSE IF (TIME>= I 8720) 

nIEN 14ELSEO 

UgEAA_Min = Urinc_EAA_Excr*l.04IE8 

UGM3_Exh = .74*(EE_Exhalation/V_ALV)*9.0IE10 


{Assumes 35% dead space, and therefore corresponding dilution of alveolar air cone. 


1/1.35 = .74} . 


UptakeI = .83*V_ALV*EXPOSURE* lE-6;25.45 

Uptake2 = . l 7*V _ALV*EXPOSURE* lE-6/25.45 

Urine_EAA_Excr =.004*VRG_EAA 

VRG_FLOW =IF (DAY• 24 •()()<=~)AND 

·(TIME<DAY * 24 • 60 +AWAKE_TIME) 

THEN 3.24 ELSE 2.95 

V_ALV =IF (TIME < 230) TIIEN 8.772 ELSE IF (DAY* 24 *()()<=TIME) AND (TIME 

<DAY *24 * 60 +AWAKE_TIME) 

TIIEN 8.5 ELSE 4.8 

l 
-33­

It can be seen that the comparison of the points that were separated by exactly 

twenty-four hours (both based on early morning urine collections) seems to 

yield much longer estimates of the half life of EAA in the body than the . 

comparisons between waking-hour urine collections and the final morning 

point. 

The suggested diurnal effect would not have to be very large to produce 

an appreciable distonion in the apparent half life ofEAA in the body. Ifwe 

assume that the true half life of EAA in the body is in fact about 70 hours, then 

the geometric mean of the ratio of the observed EAA excretion rates at 2520 

minutes to those that would have been predicted from the 1580 minute points 

is about .867. Similarly, ifwe calculate from the 2080 minute point, the EAA 

excretion at 2520 appears to be only about .772 of what we might expect from 

simple exponential decline with a 70 hour half life. In the end. we decided to 

base a variant of our "less simple" model on an assumption that the true EAA 

body half life is 70 hours, but that urinary excretion during 16 waking hours 

is 20% more than during 8 hours o.f sleep. This yields rates for EAA 

excretion of .00202*(VRG EAA)/minute during waking hours, and 

.00168*(VRG EAA)/minute while asleep. 

The fit of the remaining adjustable parameter (ethoxyacetaldehyde 

oxidation) using this assumption is shown in Table 2.8. It can be seen thatwith 

this model strucrure the peak of EAA excretion is extended to 440 minutes. 

although the best fit achieved to the EAA excretion data (with a rather high 

rate of ethoxyacetaldehyde oxidation) is a little worse than was achieved for 

the earlier model structures. An interesting feature of the 70-hour model is 

that it implies that a greater proportion (72.2%) of the metabolized EE will 

go via the non-ADH pathway (the rate constants for ADH and non-ADH 

metabolism are .0926/min. and .0357/min., respectively) . 

. -" 
I 	

I 	

t 

I 

l 

-34­

Table 2.8 .., 

Fitting the Adjustable Parameters for the • 70-Hour• 

Model (With Diurnal Changes In Urinary ERR EHcretion)

Ethoxyacetaldehyde Sum of the Squares of Peak EAA Excretion 

Oxidation Rate Differences Between Model Predicted Tune (minutes after 

CMolcs EM prociuccd and Observed log1o(EAA excretion rates) start of exposure) 

Mole F.ald in liver-Min.) 

.8 5.445 490 

1.0 5.193 470 

1.2 5.062 450 

1.5 4.953 450 

2.0 4.864* 440 

• This combination ofvalues for the adjustable parameters was selected as the best fit for the . 

"70-hour·~ model.

I 

l 

I 

! 

l 

I 

\ 

\ 

\ 	

1 

i 
-35­

2.5 Long Term Excretion of EAA Under the Different Models 

After a Single Day of Occupational Exposure to Ethoxvethanol 

Table 2.9 shows the different models' predicted EAA excretion rates at 

various times following exposure of model workers for eight hours to 20 

mg!m3 ethoxyethanol. • In the next major section, we will use these modelpredicted excretion rates (and rates for other time points) as alternative bases 

for inferring the amounts of EE absorbed by workers in the shipyard painter 

population. 

• After our earlier work, based on Brugnonc et al. (1980). we assume a normal alveolar 

ventilation rate of 11.38 liters/minute during oc.cupational exposure with relatively light 

exertion. Given nearly complete absorption ofthe EE reaching the alveoli, this leads to an 

expectation that 1.213 X 10-3 moles of EE would be absorbed. BCCtUSC the system as we 

have represented it is completely linear, greater or lesser air conc:enttations ofEE. or 

alveolar ventilation rates, would lead to proportionately greater or \esserEE absorption. 
-36­

Teble 2.9 


Predicted Urinary EHcretion Of EthoHyocetic Reid et 


Uorious Times Rfter 8-Hour Occup8tionol EHposure to 5.65 ppm 


EthoHyethenol (20 mg/m3) on a Single Doy 

TmieAfter 

Stan of 

Exposure 

(min.) 

Best Estimate 

ModelPrcd. 

(ug EAA/min. 

excreted) 

Alternative 

Model Pred. 

(ug EAA/min. 

excreted) 

Less Simple 

Model Prcd. 

(ugEAA/min 

excreted) 

Diurnal Excretion Model Pred. (ug/EAA/min 

excreted) 

Day 1 Post-shift 

(480 min) 

19.22 23.44 15.55 14.23 

Day 2 Pre-shift 

(1440min) 

14.79 18.08 12.41 13.18 

Day 2 Post-shift 

(1920min) 

12.39 14.64 10.55 12.13 

Day 3 Pre-shift 

(2880min) 

8.68 9.60 7.54 10.39 

Day 3 Post-shift 

(3360min) 

7.27 7.77 6.41 9.56 

Day 4 Pre-shlft 

(4320min) 

5.10 5.09 4.58 8.18 

Day 4 Post-shift 

(4800 min) 

4.27 4.12 3.89 7.54 

Day 5 Pre-shift 

(5760min) 

2.99 2.70 2.78 6.45 

Day 5 Post-shift 

(6240min) 

2.50 2.19 2.37 5.94 

' • . . t: 

.. "'! ..... ... .i:.· ..:.:... "' 
~ ,.... .... t. .. ,...,. ... :c.:.. . 

. 


;­

f 

£

• 

-37­

3. ASSESSING THE PERFORMANCE OF THE MODELS USING 


THE SHIPYARD PAINTER DATA 


(SPARER ET AL., 1987, MCMANUS, 1987, ,DEBORD AND 


LOWRY, 1986, AND WELCH ET AL., 1987) 


3.1 Basic Description of the Data Set 

In a series of studies sponsored by NIOSH in conjunction with a NIOSH 

Health Hazard Evaluation, Sparer et al. (1987), Welch et al. (1987), K. 

McManus (1987) and L. Lowry have measured a variety of indices of EE 

exposure, and semen characteristics in a group of painters working in a large 

shipyard. In this report we will only be examining data from an initial HHE 

study of 36 workers by K. McManus and C. Moseley. Data were taken from 

McManus (1987) and DeBord and Lowry (1986). 

A unique feature of the-.Study is that both industrial hygiene and 

biological monitoring were performed over several successive days for each 

individual studied. Ethoxyacetic acid in the urine was measured by a 

modification of the method of Smallwood et al. (1984). Attempts were also 

made to measure methoxyacetic acid and butoxyacetic acid, however MAA 

was only detected in a single sample. All EAA excretion data were corrected 

for the time between urine collections and variation in the rate of excretion of 

water by dividing the measured EAA concentrations by the concentration of 

creatinine in the urine sample. Data points for whi~h creatinine 

concentrations fell outside the range where this correction was considered 

reliable (0.5 to 3.0 g/liter) were not used. The coefficient of variation of both 

the EAA and the creatinine measurements was about 3-5%. 

In order to express all the infonnation as numerical data, we made a 

number of interpretations of notations in the data set that specific values were 

"less than" a particular number, or "non-detectable": 

i 
l 

-38­

t 

! Table 3.1 

Shipyard Painter Database 


WORKER DAY PRESHFT POSTSHIFT AIRCONC ACTIVITY RESPUSE SKINEX 

NUMBER m&E6A mKE6A mKEE (I•sanding (1 =No (0• none 

g creatinine g crcatinine cubic meter 3 •heavy lifL) respirator) 2-signif.) 

1 3 .99• 6 1.70 3 1 1 

4 5 3 4.10 1 0 1 

5 2 1 2.18 2 0 0 

6 2 -99 -99.00 9·· 9 9 

2 4 36 64 44.01 2 1 1 

5 61 54 16.99 1 1 0 

6 57 44 .60 1 1 0 

7 39 -99 -99.00 9 9 9 

3 4 1 4 5.23 1 1" 1 

5 1 11 56.03 1 1 0 

6 16 13 4.83 1 1 1 

7 7 -99 -99.00 9 9 9 

4 4 14 11 -1 .60 1 1 

5 7 17 2.12 2 I 2 

6 7 -99 3.23 1 1 0 

7 20 -99 -99.00 9 9 9 

5 4 -99 -99 22.94 2 1 1 

5 -99 -99 7.14 2 1 I 

6 -99 -99 -99.00 1 I .o 

' 

6 4 36 38 7.58 2 1 1 

5 47 47 6.38 2 1 1 

6 -99 55 8.30 1 1 0 

7 34 -99 -99.00 9 9 9 

7 3 s 6 2.91 1 1 .o 

4 -99 6 4.79 1 1 1 

s 6 9 6.58 1 ·o 0 

6 8 13 -99.00 9 9 9 

• -99 signifies missing data for the urinary measurements of ethoxyacetic acid and the air 

measurements of ethoxyethanol. . 1 •• 9 signifies missing data for the activity, respirator use, and skin exposure ratings. 
-39­

Table 3.1, Continued 

WORKER 

NUMBER 

DAY PRESHFI' POSTSHIFT 

m~f~A miE86 

g crcatinine · g creatinine 

AIRCONC ACTIVITY RESPUSE 

miEE (l=standing (1 =No 

cubic meier 3 =heavy lift) respirator) 

SKD\"EX 

(0 =none 

2ssignif.) 

8 4 

5 

6 

7 

1 

2 

1 

1 

2 

1 

2 

-99 

1.60 

1.06 

1.55 

-99.00 

1 

2 

1 

9 

1 

1 

1 

9 

1 

1 

1 

9 

9 3 

4 

5 

6 

4 

6 

23 

15 

2 

21 

18 

14 

6.21 

18.89 

8.63 

-99.00 

2 

2 

2 

9 

l 

1 

1 

9 

0 

2 

1 

9 

10 4 

5 

6 

7 

1 

2 

3 

2 

2 

2 

1 

-99 

1.10 

.60 

3.70 

-99.00 

1 

2 

1 

9 

0 

1 

1 

9 

0 

2 

1 

9 

11 4 

5 

6 

7 

12 

13 

12 

9 

14 

12 

-99 

-99 

3.99 

2.43 

1.96 

-99.00 

2 

1 

I 

9 

1 

1 

I 

9 

1 

0 

0 

9 

12 4 

5 

6 

7 

2 

2 

5 

I 

6 

-99 

-99 

-99 

4.40 

.60 

.70 

-99.00 

2 

1 

1 

9 

0 

1 

1 

9 

1 

0 

0 

9 

13 4 

5 

6 

7 

-99 

-99 

-99 

66 

69 

144 

-99 

-99 

39.05 

-99.00 

3.82 

-99.00 

l 

2 

1 

9 

1 

I 

1 

9 

I 

2 

0 

9 

14 4 

5 

6 

7 

46 

31 

36 

24 

47 

45 - 33 

-99 

.'60 

.96 

-99.00 

-99.00 

l 

l 

1 

· 9 

1 

1 

1 

9 

1 

1 

1 

9· 
-40­

Table 3.1, Continued 

WORKER DAY PRESHFT POSTSHIFT AIRCONC ACTIVITY RESPUSE SKINEX 

NUMBER mcEAA m~ Et..~ m!.!EE (lsstanding (I= No (0 =none 

g ett.atinine g c:rcatinine cubic meter 3 •heavy lift.) respirator) 2=signif.) 

15 4 -99 9 7.38 2 1 1 

5 11 15 19.51 1 0 0 

6 -99 9 3.09 1 1 0 

7 9 -99 -99.00 9 9 9 

16 	 3 3 2 .52 3 0 1 

4 3 8 84.34 1 0 0 

5 11 9 7.88 1 1 0 

6 13 11 -99.00 9 9 9 

17 	 4 9 11 6.64 2 0 1 

5 5 14 2.15 2 0 1 

6 11 17 5.74 1 1 0 

7 10 -99 -99.00 9 9 9 

18 	 3 9 -99 79.00 2 0 0 

4 31 23 1.05 1 1 0 

5 13 10 11.52 1 1 0 

6 27 12 -99.00 9 9 9 

19 	 3 2 4 2.19 1 1 0 

4 3 1 2.08 3 -0 1 

5 3 1 .00 2 0 2 

6 1 3 -99.00 9 9 9 

20 	 4 26 26 40.12 2 0 I 

5 66 49 59.20 1 1 1 

6 41 38 9.29 1 1 1 

7 43 -99 -99.00 9 9 9 

21 	 4 -99 20 15.83 1 · 1 . 1 . 

s 29 . .40 38.54 1 1 0 

6 35 .. 30 -99.00 J 	 . 1 0 

22 4 6 3 3.33 2 1 0 

s 5 6 4.42 . 1 1 0

6 	 6 7 -99.00 9 9 9 

I 

f 

I 

I 

t 

I 

I 

i

I 

. 
-41­

lBble 3.1, Continued 

WORKER 

NUMBER 

23 

DAY PRESHFT POSTSHIFT 

m~EAA m11:Eaa 

g creatininc g c:reatininc 

3 12 14 

4 16 10 

5 16 10 

6 16 8 

AIRCONC 

mg EE 

cubic meter 

8.19 

3.13 

7.29 

-99.00 

ACTIVITY RESPUSE 

(I=standing (1 =No 

3 c heavy lift) respirator) 

1 ·1 

2 1 

1 1 

9 9 

SKINEX 

(0 =none 

2=signif.) 

0 

1 

0 

9 

24 4 

5 

6 

7 

1 

2 

5 

1 

1 

5 

2 

-99 

4.11 

2.17 

.99 

-99.00 

1 

1 

1 

9 

1 

1 

1 

9 

1 

0 

0 

9 

25 3 

4 

5 

6 

-99 

. 6 

7 

5 

6 

5 

6 

10 

.92 

1.05 

6.85 

-99.00 

3 

1 

1 

9 

1 

1 

1 

9 

1 

0 

1 

9 

.26 4 

5 

6 

7 

6 

11 

10 

13 

8 

16 

16 

-99 

3.08 

6.27 

9.48 

-99.00 

2 

1 

1 

9 

1 

1 

1 

9 

1 

0 

0 

9 

27 3 

4 

5 

5 

-99 

10 

16 

5 

-99 

7.45 

2.17 

-99.00 

3 

1 

9 

1 

1 

9 

-

1 

0 

9 

28 3 

4 

5 

6 

1 

2 

1 

1 

1 

5 

1 

1 

2.60 

3.21 

3.91 

-99.00 

1 

2 

2 

9 

1 

0 

0 

9 

0 

2 

2 

9 

29 3 

4 

5 

6 

1 

6 

2 

3 

3 

8 

5 

4 

11.64 

3.33 

1.31 

-99.00 

1 

2 

2 

9 

. 1 

1 

1 

9 

0. 

1 

0 

9 
I 	

I 

\· 

I 

l 

! 

l I 

I 

I 

I 

i 

i 

1 

I 	

I 

! 

l 

( 

l 

a 

1 

1 

] 

,{ 

-42­

.· Tnble 	3.1, Continued 

WORKER DAY PRESHFT POSTSHIFT AIRCONC ACTIVITY RESPUSE S.KINEX 

:NUMBER .mi: :EAA mi: :EAA mi: :EE (!=standing (I= No (0 =none 

g aeatinine g aeatinine . cubic meaer 3 •heavy lift) respirator) 2asignif.) 

30 3 -99 4 8.95 1 1 0

4 1 4 7.64 2 0 0 

5 5 3 4.08 1 1 0 

6 -99 6 -99.00 9 9 9 

31 	 4 57 47 .23 2 1 1 

5 78 42 1.00 2 1 1 

6 54 -99 .60 1 1 0 

7 39 -99 -99.00 9 9 9 

32 	 3 26 16 7.17 1 1 0 

4 35 . 10 3.02 2 0 2 

5 27 24 5.71 2 0 0 

6 26 20 -99.00 9 9 9 

33 	 4 18 14 ' .23 2 1 0 

5 25 16 10.96 1 1 0 

6 20 13 3.60 1 1 0 

34 	 3 4 13 3.20 1 1 0 

4 2 13 2.11 2 1 1 

5 4 6 ·4.00 1 1 1 

6 2 6 -99.00 9 9 9 

35 	 3 6 5 2.28 1 I 0 


4 5 10 48.61 2 0 0 


5 12 15 2.67 1 0 0 


6 10 .99 -99.00 9 9 9 

36 3 2 3 9.09 1 1 0 

4 2 2 S.04 l 1 0 

5 3 ·s 11.13 '2 1 1 

l 
-43­

o The "not detected" data points resulted when the EAA concentrations 

were too small to be detected by the gas chromatography column. 

Depending on the column used for the sample, the limit of detection 

(LOD) was either 3 or 4 mcg/ml. We halved these numbers, divided 

by the creatinine concentration, and rounded to the nearest whole 

number. 

o The "range" data points (i.e. "less than 5") resulted when the sample 

had an amount ofEAA that was detected, but was below the GC 

columns' level of quantification (LOQ). In this case, we averaged 

the LOD and LOQ (7 and 10 mcg/ml), getting 5 or 7 mcg/ml, then 

proceeded as above. Similarly in the case of the air data, where 

results were express as "less than x", th~ value 0.5x was entered into 

the data base after rounding to the nearest .1 (i.e. "less than 3.1" 

became 1.6). 

With these transformations, the data are shown in Table 3.1.• 

"PRESHlFT" and "POSTSHIFT'' refer to urinary concentrations of EAA/g 

creatinine. "AIRCONC" reflects an 8-hourTime Weighted Average air 

measurement using a personal sampler. For the "ACTIVITY" ratings, "1 " 

reflects mostly standing, "2" indicates moderate climbing over objects, 

bending, and stretching, while "3" indicates heaving lifting and carrying. 

According to. K. McManus it mi.ght be reaonable to assign the "2" rating an 

alveolar ventilation rate about l.SX that prevailing for activity level "1 ";and 

the "3" rating might correspond to approximately a doubling of respiratory 

rate over "1". The skin exposure ratings (SKINEX) were done by visual 

examination of the hands and foreanns at the end of the shift. "Some" dennal 

exposure (rating of "1") corresponded to roughly 10-50% of the hand area 

covered by paint spots. · l 

l 

. ­ • The data were stoled and analysed on the MIT mM mainframe as a FOCUS (Information Build~ 1983) database. 
-44­

3.2 MetbodoJ02y for Inferring Ethoxyetbanol Absorption From 

the Urinary Data and the Alternatjve Models 

The model results presented in Table 2.9 (p. 36 above) show the rates 

of EAA excretion expected for the different models at various times after a 

single 8-hour exposure to 20 mglm3 EE (with total absorption of 

1.213 X 10-3 moles EE). Larger and smaller air concentrations or alveolar 

ventilation rates would be expected to produce proportionately larger or 

smaller absorption and EAA excretion at every time point.• 

There are two steps to using the urinary excretion data to calculate EE 

absorption over a workday: 

(1) Based on the "preshift" EAA excretion rate, calculate the amount of 

EAA excretion that would be expected at the "postshift" collection 

time, and at the next day's preshift collection time in the absence of 

any further exposure. These "carryover" EAA excretion rates are 

then subtracted from the EAA excretion observed at the two 

collection times after the. day's exposure. 

(2) Multiply the remaining EAA excretion (not explained by simple 

continued excretion from the stores of EAA from previous days) 

. by the appropriate constant factor to convert to units of moles EE 

absorbed during the workday. 

To derive the appropriate preshift-to-postshift multipliers for the first 

step, we simply need to observe the ratio of the day 2 postshift EAA excretion 

rates to the day 2 preshift excretion rates. Similarly, the preshift-to-nextday's-preshift multipliers are calculated as the ratio of the day 3 preshift to the 

day 2 preshift: 

• There would be some differences in the pattern ofEAA excretion ifthe EE exposure were 

not (as implicitly 8.ssumed) uniform over the 8 hour period. This would particularly affect 

the EAA excretion rate for the first day's post-shift urine collection. . ..• .~ > (' •· 

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Best Estimate Alternative Less Simple 70-Hr 

Comparison Simplest Model Simplest Model Model Model 

Post/Pre 	 12.39/14.79 14.64/18.08 10.55/12.41 12.13/13.18 

=.838 =.810 . =.850 =.920· 

Nextpre/Pre 	 8.68/14.79 9.6/18.08 7.54/12.41 10.39/13.18 

=.587 ·=.531 =.608 =;788 

Deriving the second factor requires an assumption about when exactly 

.	the urine collected at the pre- and post-shift time points was delivered into the 

bladder. The data listed in Table 2.9 are the instantaneous rates of EAk. 

excretion at panicular time points.• However, the sample delivered 

represents a weighted average of the kidneys' output since the last time the 

worker urinated. For this pwpose we assumed that the urine collections 

represented an average model excretion rate over the previous two hours.•• 

Given this, the multiplicative conversion factors (moles EAA 

absorbedf'excess" mg EAA/g~reatinine in urine) for the second step are 

derived from the each model's day f post-shift and day 2 preshift excretion 

rates, assuming an average of 1.7 g/day of creatinine excretion (ICRP ·~-- ~ 

Reference Man, 1975, p. 355). For example, for the postshift measurement 

for the "Best-Estimate Simplest" model: , · ·:·1 

moles EAA absorbed= "excess" mg EAA/g crcatininine • 

1.213 X JO:l moles EM absorbed• 1.7 g creatininefday • lQQQ u&EAMn& 

(16.79 ug EAA/min)*(1440min/day) 

11: 8.53 X 10-S . 

• • - l ·: 

The corresponding conversion factors for all ~ight situations are: 

•The times listed for the original urinary exaction data ofGrosenekcn et al (1986b)iappcar 

to reflect the midpoints between the adjacent times when urine was collected. Therefore we 

have been fitting our model to what implicitly arc the ongoing rates ofdelivery ofEkA'to 

the bladder. · · . 

•• These two-hour average EAA excretion rates for the various models arc: 

Best Estimate A1tcmativc Less Simple 70-Hr 


Tune Simplest Model Simplest Model Model Model 


Day 1 Postshift 16.80 20.33 13.SS 12.39 


Day 2 Prcshift 15.18 	 18.57 12.75 1"3.33 
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Best Estimate Alternative Less Simple 70-Hr 

Comparison Simplest Model Simplest Model Model Model 

Post/Pre 8.53xI0-5 7.04x10-5 10.57xl0-5 11.56xI0-5

Nextpre/Pre 9.43xl0-5 7.7lxl0-5 11.23xlo-5 12.90xio-5 

3.3 Comparison of Model Performance Usjn2 Criterjon#l: 

SimiJarjty of Absorption Calculated From Preshift/Postshift and 

Preshift/Next-Day-Presbjft Data 

3.3.1 Analysis Without Correction for Diurnal Cycles of 

Creatinine Excretion 

· An obvious first step in assessing the models' perfonnance is to ask 

whether the two independent calculations that are possible for a single day's 

exposure un_der each model give reasonably comparable results. Table 3.2 

shows the sum of total calculated EE absorption for all worker-days where 

preshift, postshift, and next-day's-preshift urinary EAA excretion data were 

available. 

As can be seen in Table 3.2, for all of the model variants the 

comparisons are miserable--the total absorption of the workers (on the 77 

days with complete infonnation) calculated from the preshift/postshift data is 

less than a third of the total absorption calculated from the preshift/next-day's 

preshift comparison. These data are, however, based on what turns out to be 

an assumption that is not quite correct--that urinary creatinine is an 

appropriate nonnalizing measure which is comparable between pre-shift and 

post-shift time points. The next section shows how we have managed to do 

better by using available data on diumal changes in creatinine excretion. 
-47­

Teble 3.2 

Total flbsorptlon Eualuated by the Different 

Models Without Correction for Dlurnel Changes In 

Creatlnine Eucretlon 

Moles of EE Absorbed by the Entire Population. Posed on 77 

Person-Doys of Obserpotlon. Where Preshlft. Postshlft. pod NeutDoy's Preshtft Urlnoru ERR Leuels Were 811 Ruoiloble 

Best Estimate Alternative Less Simple 70-Hr · 

Comparison Simplest Model Simplest Model Model Model 

Post/Pre .01472 .01433 .01680 .00944 

Nextpre/Pre ·.04750 .-04362 .05403 .03030 

Ratio of the .310 .328 .311 .312 

two estimates of · 

total absorption 

• "·!'". ~ ( _.. 

.._ - : ... ~ 

! ­

. .,,__.~ ,... ... ·~· _,,_~/'• -~.cf..,.....,.,,.., ,_,...•_ .._ -.. • -:-· !

. ' '""~- 'l 

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- -- ·--..-····--·-·------···-·......--.........---------- ---· ­
-48­

3.3.2 Analysis With Correction for Diurnal Cycles 	of 

Creatinine Excretion . 

As it happens, there is considerable evidence that there are diurnal 

cycles in the urinary excretion of creatinine, and a host of other renal 

functions. Some observations of Lakatua ei al. (1982) are shown in Figure 

3.1. Creatinine excretion is relatively low in the early morning hours just 

after waking (when the "preshift" urine is accumulating) and relatively high 

in evening hours. 

Lakatua et al. (1982) fit a cosine function to their data. Numerical 

evaluation of this function (Table 3.3) indicates that the rate of urinary 

creatinine excretion from 7:00 - 9:00 A.M. averages about 85.6% of the 

overall mean•, whereas from 3:00 - 5:00 P. M. creatinine excretion averages 

about 103.4% of the overall mean. This requires us to make two different 

kinds of corrections to the calculations described in Section 3.2: 

(1) The predicted posiSbift urine concentration in mg EAA/g creatinine 

should be multiplied by 72.07/87.03 = .8281. As the rate of 

creatinine excretion rises during the day from the preshift to the 

postshift urine collection, a constant rate ofEAA excretion in 

mg/hour will translate into a lower rate ofexcretion when 

expressed in mg/g creatinine. The multipliers previously given at 

the top of page 45 for predicting postshift urine concentrations 

from preshift readings in the absence of further exposure therefore 

become: 

Best Estimate Alternative Less Simple 70-Hr 

Comparison Simplest Model Simplest Model Model Model 

Post/Pre .6937 .6705 .704 .7621 

(2) In the fonnulas for the final calculation ofdaily absorption, the 

previously assumed daily rate of creatinine excretion (1.7 g/day) 

should be multiplied by the .8559 and 1.034 factors for the preshift and postshift collections, respectively. The conversion factors 

for translating the excess of obseived over predicted urinary mg/g 

creatinine excretion into moles ofEE absorbed (previously given at 

the top of page 46) therefore become: 

l 	 • 72.07 /84.2 =.8559 

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.Figure 3.1 


Lakatua et al., 1982--Circadian Rhythm in 


Urinary Creatinine EHcretion 


...... c ......, Cfuonotr•"' 

0 .)00 

r ~•O • 1•"'• 

1ool 

~ 

' c 

, "1 

1 60~ 

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\ . \ .., 

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• .... I I 

"00 

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...,_1 

0111e , , 00 or oo 

...... 0 " 

·,, '•"'···· .... 11 ...... 

Chronogram or display of means and standard errors as a 

function of clockhour (leftl. Statistical quotlficetlon of the-same 

date by mean cosinor (right, where the mesor Is the rhythm 

edjusteted ouerell mean and the amplitude Is half the tota'lpredlctable change ell eHpressed In actual measured units. Jhe 

ecrophase Is the crest time of the cosine·curue, best flttlng)o . . \

the date, eHpressed In negatlue degrees, with 3600 equar·'tb 24· 

hours ( 1 so • 1 bour) end -3600 Is equal to local midnight (OO:OO). 

Source: lakatua et el., ( 1982) 	 ...,' _. 

.. .... .. ..... 
,. .... 

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-50­

TABLE 3.3 


Numerical Evaluation of the lakatua et al. ( 1982) Cosine 


ruction for Male Subjects 


MG/HR CRERTININE EHCRETION • 84.2 + 13.00 COS 9 

Where e Is the clock degrees plus 430 

Cock Time 	 Clock 

Degrees 

9 Cose Mg/hr Crcatinine Excrct 

12:00 midnite 0 43 .731 93.7 

l:OOam 15 58 .530 91.1 

2:00 30 73 .292 88.0 

3:00 45 88 .035 84.6 

4:00 60 103 -.225 81.3 

5:00 75 118 -.469 78.1 


6:00 90 133 -.682 75.3 

7:00 105 148 ·- . -.848 73.2 7 :00 - 9:00 A.M. 

8:00 . 120 163 -.956 71.8 Average is 72'.0? mg 

9:00 135 178 -.999 71.2 Crcatinine per hour

10:00 150 193 -.974 71.5 

11:00 165 208 -.883 72.7 

12:00 noon - 180 223 -.731 74.7 

l:OOpm 195 238 -.530 77.3 

2:00 210 ·253 -.292 80.4 

3:00 225 268 -.035 83.7 3:00 - 5:00 P.M. 

4:00 240 283 .225 87.1 Average is 87.03 mg 

5:00 255 298 .469 90.3 Crcatinine per hour 

6:00 270 313 .682 93.1 

7:00 .285 .328 .848 95.2 

8:00 300 343 .956 96.6 

9:00 315 358 .999 97.2 

10:00 330 13 .974 96.9 

11:00 345 28 .883 95.7 

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Best Estimate Alternative Less Simple 70-Hr 

Comparison Simplest Model ..·Simplest Model Model Model 

Post/Pre 8.82xl0-5 7.28xlo-5 10.93xI0-5 11.95xI0-5 

Nextpre/Pre 8.07xl0-5 6.60x10-5 9.61xl0-5 i1:04x10-5 

.. 

With these corrections for diurnal changes iii crcatinine excretion, 

Table 3.4 shows the aggregate moles of EE abso~d for the 77 worker-days 

with complete information, as evaluated by the four models.. Clearly, there is 

now much better correspondence for all the models between the two methods 

for estimating each day's absoiption. By this criterion, the 70-hour model 

comes closest to reconciling the data, followed by the "less simple" model.• 

•We should note that for the calcUlations in Table 3.4, we have assumed that the same 

diurnal corrections should be applied to woker'S employed on the day shift as on the night 

shift. (We reasoned that night-shift wo~woold tend to tdapt 1heir'sleep patterns.and 

other diurnal tbythms so tha:4 like day-shift worms, they would awaken a couple ofhours 

before they were due at work.) Ifwe segregate the 37 day-shift worlcer-days in Table 3.4 

from the 39 night-shift worker-days, we find: 

Best Estimate Alternative Less Simple 70-Hr 

Comparison Simplest Model Simplest Model Model Model 

Day-Shift WorJccrs: 

Post/Pre .02156 .01913 .02585 .02286 

Nextprc/Pre .02774 .02558 .03150 .01718 

Ratio of the .7n .748 .821 

two estimates of 

total absorption 

Ni&ht-Shift Woricers: 


Post/Pre .00764 .00685 . •00910 .C1J772 


Nextpre/Pre .01291 .01291 ·.01474 .00875 

Ratio ofthe .S92 .S31 .617 .882 

two estimates of 

total absorption 

It can be seen that restricting the analysis to the day-shift worker-days produces results that 

arc somewhat more favorable for the first three models, and adverse to the 70-hour i;nocicl. 

Overall, however, the differenccs are not large enough to invalidate use of the informacicm 

fer the night-shift worker-days. . _. .-..:• . _ 


. .. ... 
-52­

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.).,. ... .......,.
 ' . 

.. . . ...~;...' ..U . .::-..... -~ ~- .. :,,........,; ... •'"' ~ J <\ ~?;;. I ,.. 'I" . / 

{J .•:,·,~~ ;~-·-·- I\~ e··,. .~';,, 

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Tnble 3.4 

Total Absorption Eunlunted by the Different 

Models With Correction for Dlurnol Changes In 

Crentlnlne Eucretlon 

Moles of EE Absorbed bU the Entire Pooulotton. Posed on 77 

Person-nous of Observation. Where Preshlft. Postshlft. ond NeHtoou's Preshift Urinoru ERA Levels Were All Buoilable 

Best Estimate Alternative Less Simple 70-Hr

Comparison Simplest Model Simplest Model Model Model 

Post/Pre .02919 .02598 .03496 .03058 

Nextpre/Pre .04065 .03733 .04624 .02594 

Ratio of the .718 .696 .756 1.179 

two estimates of 

total absorption 

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-53­

3.4 Comparjson of Model Performance Usin2 Crjterjon#2; 

Stren~th Qf Association Between Ajr Concentratjon Measurements 

and Total Calculated Absorption 

A second criterion we can use to compare the performance of the 

models is the correlation of the moles ofEE estimated to be absorbed .with the 

measured air concentration of EE. Other things being equal, models that 

suggest a relatively strong correlation (and one that is consistent for pre/post . 

and pre/next-pre calculation methods) are more likely to be closer to the truth 

than models for which the correlation is weaker and/or inconsistent. For this 

purpose we perfonned parallel multiple regression analyses between each of 

the models' calculated daily absorption.amounts and two variables 

representing exposure: 

"ADJAIR'.'--The air concentration adjusted for activity level (for days 

on which the activity level was rated as "2", the air concentration was 

multiplied by 1.5; for days in whcih the activity level was rated as "3", 

the air concentration was multiplied by 2.) As we shall see in Section 

4.1 below, this adjusted air concentration shows a better correlation 

with measures of absorption than an unadjusted air concentration. 

"ANYSKIN"-This is a "dummy" variable that is set equal to 1 ifthere 

was either "some" or "much" skin exposure (SKINEX = 1 or2 in Table 

3.1).• . 

The results of these regression analyses are presented in Table 3.S; In 

this·table, "N".is the number of worker-days ofobservation with analyzable 

·data. The "R2" numbers provide an overall index of the proportion of the 

variance of the dependent variable (moles absorbed as estimated by the model 

• We tried a number of multple n:grcssion analyses distinguishing between the 2 and 3 

ratings of skin exposure, and found that all of the evidence for a positive influence of skin 

exposure on EE absoption was attributed to the "2" or "somescskin" rating. As it happened, 

there were only 7 qualifying worker-days with the "3" rating (vs. 31 with the "2" raring) 

and this small amount ofdata was evidently insufficient to reveal a signigicant effect. In the 

light of this result, for purposes of our analysis there is thus no ad~ge in preserving the 

"2" vs "3" distinction. 
Table 3.5 

Regression Analyses Using es the Dependent Uerinble, the

•Moles llbsorbed!' ·Rs Calculated by the Different Models 

for I ndlulduel Workers ·on Specific Days 

.R. Obseruetions on Days Where No Resolrotor Wes Worn 

Comparison Used 

For Calculating 

N R2 Tadjair Tanyskin Intercept AdjAir 

Cocff. 

Skin 

Coeff.

Moles Absorbed (xlo-4) (xl0-5) (xI0"'.4)

BEST ESTIMATE SIMPLEST MODEL 

Post/Pre 63 .313 4.82 1.70 0.90 2.55 2.38 

Nextpre/Pre 62 .191 3.64 0.53 3.03 2.43 0.95 

Ave, BoL'l Above 57 .308 4.75 1.08 1.96 2.49 1.56 

ALTERNATIVE SIMPLEST MODEL 

Post/Pre 63 .323 4.91 1.77 0.92 2.16 2.06 

Nextprc/Prc . 62 .194 - - 3.66 0.62 2.90 2.10 0.97 


Ave, Both Above 57 .314 4.78 1.17 1.88 2.14 1.44 


LESS SIMPLE MODEL 

Post/Pre 63 .308 4.77 1.66 1.01 3.12 2.88 

Ncxtprc/Pre {)2 .189 3.63 0.49 3.39 2.83 1.03

Ave, Both Above 57 .307 4.74 1.05 2.20 2.98 1.82 

SEVENTY HOUR MODEL 

Post/Pre 63 .274 4.42 1.44 0.38 3.19 2.75 

Ncxtpre/Prc 62 .145 3.15 0.07 1.39 2.18 0.13 

Ave, Both Above 57 .260 4.27 0.70 0.97 2.67 1.21 

-54­

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table 3.5, Continued ) 

Regression analyses Using as the Dependent .Variable, the 

•Moles 	11bsorbed• fls Calculated by 1he Different Models 

· for lndluldual Workers Gn Specific Days 

B. Obseruations on Days Where 8 Besoirotor Was Worn 

Comparison Used N R2 Tadjair Tanyskin Intercept AdjAir Skin 

For Calculating · Cocff. Cocff. 

Moles Absorbed (xlo-4) -(xl0-5) (xlQ-4) 

BEST ESTIMATE SIMPLEST MODEL 

Post/Pre 20 .180 1.31 -0.98 2.70 0.56 -2.04 

Ncxtpre/Prc 20 .444 3.67 1.04 -0.89 2.04 3.86 

Ave, Both Above 19 .368 3.03 0.46 0.62 1.41 1.08 

ALTERNATIVE SIMPLEST MODEL 

"Post/Pre 20 .186 ., 1.36 -0.98 2.34 '0.47 . . -1.66 

Ncxtpre/Pre 20 .430 - 3.S7 1.03 -0.Sl 1.68 ~ 3.23 

Ave, Both Above 19 .362 2.99 0.47 0.68 1.17 0.94 

LESS SIMPLE MODEL 

Post/Pre 20 .177 L30 -0.98 '3.28 0.79 .· .. -2.55 

Ncxtpre/Prc 20 .449 3.70 1.04 . -1.18 ·2.42· 4.55 

Ave, Both Above 19 .369 3.02 0.43 0.71 "1.69 1.21 

SEVENTY HOUR MODEL 

Post/Pre · 20 :162 1.18 .:0.98 3.14 '0.7r -2.91 

NcxtprC/Prc 20 .488 00 1.06 - .-2.12 .2.25 ... '3.99 

Avc, Both Above 19 .-363 · 2.96 0.28 :0.18 -1.60 · ~. · 0.76 

n ""YJ 

,;,~, . ., ~ .,,.. ·,,+;, ~, .. " :I!'" - «:"""1. ':I ...., '"'t· ~ ff" 1' ......

• • O • ' ... I.. : ,, .. ~. :' 	 "".,,,.. 

-55­
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in question) that is related by the regression equation to variation in the two 

independent variables (ADJAIR and ANYSKIN). Higher values for R2 

indicate stronger correlations between the dependent and independent 

variables. "Tadjair" and "Tanysk.in" are the ratios of the ADJAIR and 

ANYSKIN regression coefficients to their respective standard errors (T 

values greater than 1.64 indicate that the coefficient is statistically 

significantly different from zero at P < .05 in a one-tailed test• ). The final 

three columns give the absolute values of the regression coefficients · 

themselves. For example, the regression equation for the first line in Table 

3.5A is 

Moles EE absorbed/worker (post/pre comparison)= .90 X I0-4 + 2.44 X io-5 ADJAIR 

+ 2.38 X 10-4 ANYSKIN 

Where ADJAIR is in mg EE/m3 (multiplied by the activity level) and 

ANYSKIN is 1 or 0 as discussed earlier. For each model, data are given using 

as dependent variables ( 1) the mol~s absorbed as calculated from a 

comparison of postshift urine concentrations with preshift, (2) moles . 

absorbed calculated from a comparison of the preshift EAA concentration 

with the next day's preshift, and (3) the average of (1) and (2) for each 

worker-day where urinary EAA excretion data were available for all three 

relevant readings, and air exposure data and skin ratings were also available 

for the day when exposure took place. 

It can be seen in Table 3.5A (without respirators) that all of the models 

show strong and highly statistically significant relationships between adjusted 

air concentrations and the estimates of worker absorption. Moreover,. the 

ADJAIR coefficients as estimated by the models for the post/pre and 

nextpre/pre comparisons are generally consistent with each other. The .. 

seventy-hour model perfonns a little less well in both of these respects than

the other models, but the differences are not dramatic. 

As might be expected, the data for the smaller number of worker-days 

where respirators were used (Table 3.5B) show somewhat weaker and less 

consistent relationships between air exposure and absorbed ethoxyethanol, but 

the relationships are still significant enough to provide meaningful 

• A one-tailed test is appropriate here because we have a strong the.oretical expectation that th~ should be a positive correlation between measures of exposure and ethoxycthanol absorption. 


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infonnation. The ratio of the ADJAIR regression coefficients with and 

without respirators can give us some indication of the factor by which 

respirator use appears to reduce exposu~ via the air route: 

Best Estimate Alternative Less Simple 70-Hr 

Comparison Simplest Model Simplest Model ·· Model Model 

Average of .57 . .55 .66 .60 

post/pre and 

nextpre/pre 

The overall protection factor ofa little less than two-fold is at the lower end 

of the range of results that have been observed in previous studies ofthe field 

efficacy of respirator use.• 

Curiously enough, if we do a similar calculation to assess the apparent 

effect of respirator use on absorption associated with visible skin exposure we 

find:. 

Best Estimate Alternative Less Simple . · 7-0-Hr . 

Comparison Simplest Model Simplest Model Model Model 

6s ,...::.. r:...... 

Average of : ~. ;r. ,.;.' ~' .. 

.69 ~ "' ,. 4 ..... .

.66 .63 

post/pre and 

nextpre/pre 

The implication is that respirator use may provide nearly as much protection from 

our measure of "skin" absorption than from exposure associated with the air route. 

.One possible explanation for this is that the workers who showed visible · 

contamination of their hands and arms may also have spattered some paint on their 

faces, but that the facial contamination was reduced for those who wore.respirators. 

In the light of the effect ofrespirators in teducing absotption via the air 

,route; in order to be able to use all-0f the datain'SUbsequem-analyses, we . ,

define a second adjusted air concentration (ADJ2AIR) in whicll the value of 

. ~ .. . ,·)-~·:i?·--.1 -r·~~ · '!-,1~-~-~~ .•~-·J.:~(-"f··~-r; .. 

• Studies with cadmium particles.have indicatedan average protection factor ofabout 4 · ·. - · ·(Smith, et al.; 1980). Forcoal dust, average ptotection factors for different groups of 

workersranged between 3.and·9 (Harris.et al.~ 1974).·Ollculations we did based on , information on blood lead air lead relationships and~avenge air and blood lead ·--cooc:emraDons in primary lead smelting,'secondaJy lead smelling, andbauery manuf~ 

suggested average protection factors of2-12 (Goble et al.. 1983). ·-· _- . 

•· 

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ADJAIR is multiplied by 0.6 when respirators are used. Multiple regression 

results using this independent variable are shown in Table 3.6. 


3.S Conclusions on Model Performance . .­

Overall, the various comparisons we have made produced no clear 

"winners" or "losers" among our different model variants. The "70-hour" 

model on the whole perfonned somewhat more poorly than the others in 

correlating calculated exposure with air concentrations of EE (with or without 

adjustments for activity and respirator use). However in our judgment, the 

perf onnance was not so drastically worse as to warrant excluding it from 

further consideration. Because the 70-hour model results in a greater 

conversion of EE to activated ethoxyacetaldyde and EAA metabolites, and also 

for a greater persistence of EAA in the body, it may serve in later work to 

provide a plausible high est~te of internal body exposure to testicular toxins. 

Ifwe had to pick a single "best" model based on all the data, on balance 

we would choose the "less simple" model. This is because: , . 	. ""' .. ' 

o It incorporates plausible features used in full physiologically-based 

phannacokinetic models·(blood flows and organ sizes) and is 

therefore inherently somewhat preferable. 

o It fits no worse to the primary Groseneken et al. (1986b) urinary 

EAA excretion data than the "best estimate-simplest" model, and 


somewhat better than the "alternative-simplest" model using the 


logarithmic least-squares criterion. 


o It shows a later peak of urinary EAA excretion than the two 

."simplest" models, which is more in keeping With the peak times 

.observed by Groseneken et al. (1986b and 1987b). · 

o 	 It perfoms slightly better than the two "simplest" ·models in -· 

reconciling the moles '.EE absorbed a5 cal~ted by the iwo methods 

explored in Section 3.3 (comparing post-shift with preshift urinary .

-. · EAA vs.;.comparing next-?af s presbift urinary EAA with prcsl:iift 

. EAA.) .. ...i~ c .... ~ .. : -,~ : .. --\ t:J {t .u. ~~;:i ti~~~~k'~-.:- -:~~J'~ ;..: \flt~.~-
Table 3.6 

Regression 	Rnelyses Using •ROJ2RIR• (60~ Correction of 


Rlr Leuels for Use of Respirators) 


Comparison Used N R2 Tadj2air Tanyskin Intercept Adj2Air Skin 

For Calculating Cocff. Cocff. 

Moles Absorbed (xlo-4) . (xt0-5) (xI0-4) 

BEST ESTIMATE SIMPLEST MODEL 

·Ave, Both 76 .313 5.71 1.10 1.671 2.45 1.33 

Post/Pre and 

Nextprc/Prc 

ALTERNATIVE SIMPLEST MODEL 


Ave, Both 76 .313 5.10 1.18 1..622 2.09 1.22 


Post/Pre and 


Nextprc/Pre 


LESS SIMPLE MODEL 


Ave, Both 76 .313 5.71 1.06 1.876 2.93 1.54 


Post/Pre and 


Ncxtprr/Prc 
 - - SEVENTY HOUR MODEL 


Ave, Both 76 .279 5.29 . .715 .799 ' 2.67 1.02 


Post/Pre and 


Nextprc/Prc 	

·. -• 

' ,. - . , . • .; J ~ ~ 

i

-59­

I 

I 
I 

-60­

t 

i 

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I 

4. INFERENCES FROM THE MODELS AND THE SHIPYARD 

DATA 

4.1 The Effects of Actiyity Levels on EE Absorution Vja Ajr and 

Dermal Routes 

Table 4.1 shows regression analyses analogous to those in Table 3.6, 

separated by activity level. There were 44 qualifying worker-days at activity 

level I, 30 at activity level 2, and 2 at activity level 3. It can be seen that the 

ADJ2AIR regression coefficients are much larger for the "2" and "3" group 

than for the "I" group. This suggests that at higher activity levels the workers 

are absorbing even more EE than we provided for with the l .5X and 2X 

assumptions for increased ~~eolar ventilation built into the definition of the 

ADJAIR and AJ)J2AlR variables. It can also be seen that the modest 

suggested effect of the "ANYSKIN" variable is stronger for the group rated at 

higher activity levels. 

We are reluctant to increase our assumption about relative vc~ntilation 

rates at the different activity levels as much as would be required to 

accommodate these observations. It seems implausible that the "moderate" 

activity people could be taking in as much as 4-5 times more air than the 

"sedate11 activity people. Pending confinnation, we simply draw the 

conclusions that adjustment for activity levels seems to be helpful in achieving 

overall fits of the models to the data, and that our "Adjusted" air level 

calculations do not seem to be overstatint: the effect of activity on EE 

absorption (they may in fact be somewhat understating it). 

4.2 Relatjve Importance of lnhaJatjon vs Dermal Routes Slf 

Exposure 

Given the total absorption of EE as calculated from our different 

models, what can we say about inhalation vs. dermal absorption in the group 

ofshipyard painters we have been studying? Based on the Groseneken et al. 

(1986a) data and an assumption of 11.41/minute alveolar ventilation 
-61­

Table 4.1 


Regression Analyses For Worker-Days flt Different 


Rctlulty Leuels 


Comparison Used 

For Calculating 

N R2 Tadj2air Tanyskin Intcrc:cpt Adj2Air 

Cocff. 

Skin 

Cocff. 

Moles Absorbe.d (xlo-4) (xl0-5) (xI0-4) 

44 Worker-Days At a Relatively Low Activity Level (l="Sedate"): 

BEST ESTIMATE SIMPLEST MODEL 

Ave. Both 44 .147 2.56 -.54 3.095 1.17 -.73 

Post/Pre and 

Ncxtprc/Prc 

ALTERNATIVE SIMPLEST MODEL 

Ave. Both 44 .150 2.63 -.39 2.805 1.04 -.47 

Post/Pre and 

Nextprc/Pre 

LESS SIMPLE MODEL 

Avc,Boih 44 .144 - 2.s1 -.57 3.604 1.36 -.93 .Post/Pre and 

Nextprc/Pre 

.SEVENTY HOUR MODEL 

Ave, Both 44 .106 1.93 -.91 2.530 1.00 -t.41 

Post/Pre and 

Nextpre/Prc 

32 Worker-Days At Higher Activity Levels ("2" or "3"): 

BEST ESTIMATE SIMPLEST MODEL 

Ave, Both 32 .550 5.84 1.30 -.499 4.09 . 01 

Post/Pre and 

Ncxtprc/Prc 

ALTERNATIVE SIMPLEST MODEL 

Ave, Both 32 .541 5.71 1.36 -.244 3.41 2.68 

Post/Pre and 

Nextprc/Pre 

LESS SIMPLE MODEL 

Ave, Both 32 .556 5.91 1.28 -.729 4.93 53 

Post/Pre and 

Ncxtprc/Pre 

SEVENTY HOUR MODEL 

Ave, Both 76 .552 5.91 .994 -1.575 4.80 2.67 

Post/Pre and 

Ncxtprc/Pre .. c(" -,z. 

: . c t ... :;... - • 1• ; s_~ ._... ...,, ' 

.,,. ,~ ~ . 

., 

:....:..:' -4 ... - ..,... ::i-· -.. -.. ...... , . . ~ . .. *J:;" ,... . --· •. ' " 

~~:.. 1 - ~- ,.,, ;., r_ -• " r •. · · 

.. ..~'. . "..! 1~ .... ~.) . ·-.. 
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-62­

during light work (Brugnone et al., 1980), we implicitly built into all of our 

models a relationship between moles ofEE absorbed and 8-hour 1WA

exposure in mgtm3 of: 

1.211 X10-3 Moles Absorbed 

------------------------------------- = 6.06 X io-5 moles abs/(mg,lm3) 


20 mg EFJm3 (8hour1WA) 


Comparing this with the ADJ2AlR coefficients iii Table 3.6, it can be seen that 

the actual regression relationships derived from the data are weaker than this 

by 2-3 fold. The difference probably results in pan from inaccuracies in the 

measured levels of the independent variables relative to real exposure.• 

We can use the theoretically-defined 6.06 X 10-5 coefficient to evaluate . 

how.much of the total absorption indicated by the models for the worker-days 

studied could have been accounted for by direct air inhalation, and how much 

therefore must remain to be accounted for by dermal absorption. 'The results 

of this calculation for the four moqel variants are shown in rhe second line of

nwnbers in Table 4.2. It can be seen that using this assumption, for aJ!.ofthe 

models, all of the absorbed EE can be accounted for (and then some) by· 

inhalation, and we are not absolutely compelled by the data to attribute any of 

the absorption to the dennal route. 

H we do use the low-biased air regression coefficients in the same kind 

of calculation, we can arrive at a more conservative estimate of the EE 

absorption attributable to direct air inhaltion (third line of numbers in Table

4.2). It can be seen that in all cases on the order of half to two thirds ofthe

total moles absorbed (given in the first line) must be attributed to the air 

route. 

Our best estimate of the relative importance of the air and dei'mal , 

routes comes from comparing the conservative regression-calculated average 

air absorption in the third line, with a similar conservative regression- -·-

calculated figure for the average dennal absorption in the last line ofTable 

.4.2. It can be seen that in all cases, the data surgest that the ait route accounts 

for 3-5 times as much ofthe estimated EE absorption as the dennal route. 

• In regression analyses, inaccuracies in the measurement of the dependent v~b c do.not 

bias the regression equation, but inaccuracies in measuring the independent vanablcs bias 

the result to larger values of the intercept and smaller values of the coefficients ofthe 

independent variables. The positive intcreepts in Table 3.6 (when the actual values should 

be z.ao) provide other evidence of this kind ofbias. 
-63­

Table 4.2 


Moles of EE Rbsorptlon Due to Inhalation Us Other Routes 


·of EHposure In the Shipyard Painter Group 


(Based on 76 Worker-Days with Complete Urinary EHcretion end 

Rir EHposure Dete--Rll Date Rre Moles Absorbed Hto-4) 

Best Estimate Alternative Less Simple 70.Hr 

Simplest Model Simplest Mcxiel Model Mcxiel 

Total Moles 4.53 4.10 S.21 3.70 

Absorbed Per 

Worker-Day 

Moles Absobcd 5.43 S.43 S.43 5.43 

Potentially Attributable 

to Direct Air Inhalation* 

Minimum Moles 2.19 1.87 2.62 2.39 

Absorbed Attributable 

to Direct AirInhalation •• 

Moles EE Absorption -.90 to 2.34 -1.33 to 2.23 -.16 to 2.64 -1.73 to 1.31 

Absarption Remaining 

to be Accounted for 

By Dermal Absorption 

Estimate ofDenna! .67 .61 .77 .51 

Absorption from ANYSIGN ~ .., ~ Regression Coefficient••• 

• This calculation uses the the.oretical relationship between airinhaltion and moles EE . absorbed that was built into the models (assuming complete absorption of EE from alv~lar 

air and an alwolar ventilation rate duringlight work of 11.4 liters/minute). The average 

adjusted air exposure level (A0l2AIR) for the 76 worker-days was 8.96 mg!m3. Assuming 

6.06 X 10-S moles abs/(mg!m3), this leads to an cxpcCtation ofan average ofS.43 X to-4 

moles absorbed EE potentially attributable to direct airinhalation; 

•• Calculated using each model's ADJ2AIR :regression coefficient and the average 

ADJ2AIR value of 8.96 mym3. As discussed inthe text, this is a minimum estimate 

because uncaWnties in the measurement ofair concentrations tend to bW: the :regression coefficient 10 lowec values. '. ; . · , 

...This conservative value is calculated by multiplying the dermal absorption :rcgressioo 

coefficient by the average value of ANYSKIN for the 76 worker-days-.5. It is a 

conservative estimate for the same reason as the analogous set ofestimates for absmption by 

the inhaltion route, and because the qualitative ascertainment ofdermal exposure by 

examining the hands and arms for paint spots is clearly more uncertain, quantitatively, than 

the measurement of air concentrations. On the other hand, it should be noted that for none 

ofthe models was the ANYSKIN statistically significantly diffmt than 0 at the S'li leYd. 
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-64­

4.3 The Possible Effect of Ambient Temparature on EE 

Absorptjon 

In doing some sensitivity analyses with our data, one other result 

appeared for which we do not have a ready explanation. For 12 of the 7 6 

worker-days with complete infonnation covered in Tables 3.6, 4.1 and4.2, 

the industrial hygienists recorded relatively low ·temperatures (in the range of 

35-45 OF.--in contrast to the 70-90 op recorded in other cases). The low 

temperature cases evidently correspond to work outdoors during the 

December period of the study. Because the low ambient temperatures may 

have affected the amount of skin area left uncovered and other work 

practices, we decided to do a set of analyses excluding the 12 low-temperature 

worker days from the data set (Tables 4.3 and 4.4). 

Comparing the regression results in Table 4.3 with those for the full 

data set in Table 3.6 it can be seen.that excluding the low temperature workerdays has improved the correlations as measured by the R values, and the 

indicated statistical significance of the ADJ2AIR coefficients. Ifanything, 

however, the statistical correlation with the ANYSKIN variable has been 

weakened. 

In keeping with this, when we compare the analysis of air-vs-dermal 

absorption in Table 4.4 with that originally presented in Table 4.2, we now 

find that our best estimate of the contribution of the dennal route to overall 

absorption has declined to only about an eighth of th~ contribution of the 

direct air route (the third vs. the fifth line of numbers). 

4.4 Recommendatjons for the Use of Urjnary Metabolite 

Measurements to Infer OveraJJ Exposure in· Workin2 Populations 

The relatively long half-life ofEAA in the body (26-70 hours for our 

various models) means that the use of urinary EAA concentrations to judge 

.ongoing worker exposure is more complex ,than it ordinarily would be . 

......,, :.' '! t .· '.t"' .. l . 
.. :·.:., .... 

·:- t. (f, ~·. • c.,. "" .... .......... ("' ....... 
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L·~ . -~.: ;."'::~.::· ~.~f1.. A • .. ·~~ ... ~ ~··: ~!:'. ;.:,. ..:J:i ·; ..t .

-65­

fable 4.3 

Regression Analyses EHcludlng 12 Worker-Days et Low 

Temperatures 

I .. "'· ~.

Comparison Used 

For Calculating 

N R2 Tadj2air Tanysk:in Intercept Adj2Air 

Coeff. 

Skin 

Coeff. 

Moles Absorbed (xlo-4) (x10-5) (xlo-4) 

BEST ESTIMATE SIMPLEST MODEL 

Ave, Both 64 .418 6.50 .66 1.548 2.75 .787 . 

Post/Pre and 

Nextprc/Prc 

ALTERNATIVE SIMPLEST MODEL 

Ave, Both 64 .431 6.68 .66 1.502 2.37 .664 

Post/Pre and 

Nextpre/Pre 

LESS SIMPLE MODEL 

Ave, Both 64 .412 6.42 .66 1.741 3.26 .951 

Post/Pre and 

Nextpre/Pre 

SEVENTY HOUR MODEL 

Ave.Both 64 .337 5.46 .63 .752 2.81 .917 

Post/Pre and 

Nextpre/Pre 
f 

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-66­

·:'·table 4.4 


Moles of EE ftbsorptlon Due to Inhalation Us -Other Routes 


of EHposure In the Shipyard Painter Group--EHcluding 


Low-Temperature Data Points 


(Besed on 64 Worker-Deys--Rll Data Are Moles Absorbed H Io-4) 

Best Estimate Alternative Less Simple 70-Hr 

Simplest Model Simplesi Mcxiel Mcxiel Mcxiel 

Total Moles 4.48 4.02 5.22 3.80 

Absorbed Per 

Worker-Day 

Moles Absobed 5 .72 5.72 5.72 5.72 

Potentially Attributable 

to Direct Air Inhalation * 

Minimum Moles 2.62 2.26 3.11 2.68 

Absorbed Attributable 

to Direct Air Inhalation •• 

• Moles EE Absmption -1.24 to 1.86 -1.70 to 1.76 -.SO to 2.11 -1.92 to 1.12 

Absorption Remaining 


10 be Accounted for 


By Dermal Absorption 


Estimate ofDcnnal .33 .28 .40 .39 

Absorption from ANYSKIN 

Regression Coefficiem••• 

• This calculation uses the theoretical relationship between airinhaltion and moles EE 

absorbed that was built into the models (assuming complete absorption of EE from alveolar

air and an alveolar ventilation rate during light work of 11.4 litcrs/minute). The average 

adjusted air exposure level (ADJ2AIR) for the 76 worker-days was 9.45 mg!m3. Assuming 

6.06 X 10-5 moles abs/(mg!m3). this leads to an expectation ofan average of 5.43 X lo-4 

moles absorbed EE potentially atttibutable to direct airinhalation. 

~· Calculated using each model's ADJ2AIR regression coefficient and the average 

ADJ2AIR value of8.96 mglm3. As discussed in the text. this is a minimum estimate 


because uncertainties in the measurement ofair concentrations tend to bias the regression 


coefficient to lower values. 
 ...This conservative value is calculated by multiplying the dermal absorption regression 


coefficient by the average value of ANYSKIN for the 76 worker-days-.422. It is a 

conservative estimate for the same reason as the analogous set ofestimates for absorption by

the inhaltion route, and because the qualitative ascertainment ofdermal exposure by . 

examining the hands and arms for paint spots is clearly more unccnain, quantitatively, than 

the measurement of air concenttations. On the otherband. it should be noted thatfor none

ofthe models was the ANYSKIN statistically significantly diff:rcnt than 0 at the S~ level. 
-67­

There is appreciable carryover of EAA from day to day: and it can be 

expected that EAA excretion rates build up in the course of a work-week with 

constant 8-hour exposure on each day. Table 4.5 shows this day to day · 

buildup, and the effects ofexpressing EAA excretion in ug/min vs mg/g 

creatinine, given the diurnal changes in creatinine excretion. 

The data in Table 4.5 can be used to make estimates of the equivalent 8­

hour TWA air exposure for workers exposed to EE and its derivatives by 

both air dennal routes, even ifone only has a single measured value ofEAA 

in the urine for each worker. For example ifone has a pre-shift measurement 

of urinary EAA in mg/g creatinine taken on the third day of the workers' 

work-week (Wednesday), then the estimated average mgtm3 EE exposure on 

the previous two days under our best-estimate ("less simple") model would 

be: 

(urinary mg/g creatinine)*(20 mg/m3 in air)/(20.17 mg/g creatinine) 

= .992 *measured urinary mg/g creatinine 

Other things being equal, of course, it is better to base estimates Of . 

individual daily worker EE exposure on comparisons of urinary EAA output 

per g of creatinine before and after a particular workshift. To avoid p~ole 

complications from inaccuracies in our fonnulas for diurnal changes in 

urinary creatinine output (and possibly EE excretion), and to reduce th~ ~: 

effects of different patterns of exposure during an 8-hour workshift:• 1 we 

recommend basing such calculations on preshift urine collections taken24 

hours apart. Given such data, the calculation can bC done in two steps: 

(1) Predict the second day's preshift urine concenuation in the absence 

pf any exposure during the shift in question--for our prefe~d 

"less simple" model, multiply by .608. ... Subtract the resultftom 

the observed urinary EAA concentration for the ·seeond day'rM 

preshift collection. -· · · · - · · · · , 

• See Table 2.9 on page 36 fcr·the pattern ofexcretion expected after a sinde day's 
 .egposure. Also see Figures 1.2 and 1.3· for the original observations of Grosencken et.al. 


(1986b and 1987b). 
 •• E.g. high peak,exposures at the biginning or the end ofa work shift, vs a more continuos 


pattern ofexposure. ;e ,
 1 ' . ~ r-

~ 

,, 

... For the 7();.hoormodcl, the factorwould be .788-see'p. '45 above... ~ - :;~ ~!"~·. 
I 

I 

-68­

Table 4.5 

Predicted Urinary EHcretion Of Ethotcyecetlc Reid et Uerious Times 

During Successjve Doitu 8-Hour Occupational EHposure to 5.65 ppm 


EthoHyethenol (20 mg/ m3) 


Tune After "Less Simple Model" Prcdic- '70-Hr Model PrcdicStan of tions (Best Estimate Model). tions (Plausible Upper Bound) Exposure (ugEANmin. (mgEAA/g (ug EAA/min. (mg EANg (min.) excreted) creatinine•) excreted) aeatinine) Day 1 Post-shift 15.73 12.52 12.39 9.86 

(420mint• 

Day 2 Pre-shift 12.67 12.54 13.27 13.14 

(1380 mint•• 

Day 2 Post-shift 24.33 19.37 24.65 19.62 

(1860min) 

Day 3 Pre-shift 20.37 20.17 23.72. 23.48 

(2820min) 

Day 3 Post-shift 30.88. - 24.58 34.32 27.32 

(3300min) 

Day 4 Pre-shift 25.04 24.79 31.96 31.64 

(4260min) 

Day 4 Post-shift 34.85 27.75 41.93 33.38 

(4740min) 

Day 5 Pre-shift 27.88 . 27.60 38.46 38.08 

(5700min) 

Day S Post-shift 37.27 29.67 47.93 38.16 

(6180min) 

4 Day A vc Pre-shift 21.49 21.28 26.85 26.59 

5 Day Ave Post-shift 28.61 22.78 32.24 25.61 

. . 

• Assuming 1.7 g per day ofoverall creatinine excretion. and diurnal changes in crea•fmne · 

exccretion as given by Lakatua et al. (1982)--Sec Table 3.3 on p. SO. This results in 

expected aeatinine excretion mes of (.8559*1700 mg/day)/1440 min/day~ 1.01 mg/min .for the two hours prcc=ding a 9:00 A.M. "preshift0 collection. and (l.034•1700)11440 = 1~6 mg/min for the two hours ~ga 5:00 P .M. "postshift" collection. 

•• The data given here are the expected instantaneous rates of delivery ofethoxyaceticxid 

to the bladder. The 420 minute point is approximately the average rate that might be:seen in 

a urine collection after an 8 hour shift, assuming that the urine has accumulated in the· . 

bladder between the 6- and 8-hour time points after the SWtofthe workday . ... By the same reasoning as given for the post-shift time points. the pre-shift urine:".·. 

samples are assumed to represent a two-hour accumulation of urine that was delivered-to the 

bladder on average 23.hours after the start of the previous day's worbhift. · - · 
-69­

.. ·,.- t, 

(2) Calculate the equivalent 8-hour TWA EE air level in mg!m3 by 

multiplying the "excess" urinary mg EAA/g creatinine by 20 

mg!m3 /12.54 mg EAA/g creatinine =1.59 mgtm3 per mg EAA/g 

creatinine.• · 

It should be s~ssed that because of likely differences among 

individuals in absorption, alveolar ventilation rat~s:• the fraction of absorbed 

EE that is metabolized via ethoxyacetaldehyde to EAA, EAA excretion rates, 

and other factors:•• the "equivalent air absorption" estimates calculated in 

this way may often differ appreciably from measured air exposure levels. We 

believe, however, that for many of these sources of variability•••• the 

"equivalent air absorption" estimates may better reflect the toxicologically 

relevant internal dosage of EAA. 

4.5 Opportunities for Further Work 

The modeling we have done with tbe infonnation available to date has 

left many unanswered questions about the pharmacokinetics of ethoxyetbanol 

and related compounds. For the constroction of full physiologcially-based 

phannacokine.tic models it would be desirable to have: 

(1) Measurements of relevant blood/air and tissue/air partition 

coefficents for EE, ethoxyacetaldehyde, and EAA~ 

(2) In clinical settings such as those used by Grosenekent et al. 

(l986a,b; 1987a,b), measurements of blood concentrations of 

• The analogous multiplyier for the 70 hour model can be derived from the day 2 preshift 

data in Table 4.5. For other models see the second footnote on p. 45 above: · 

••The formulas for "equivalent air concentraticm". assume complete absorption from 

alveolar air, with an alveolar ventilation rate of11.38 liters/minute during light wmk. 

Increased physical exertion during exposure. u well as skin absorption, will be reflected in 

higher estimated "equivalent air concentrations". . . ••• Including anydermal absorption that may be present. .... With the possible exception of differences in EAA excretion rates. Ifan individual · were to excrete EAA more slowly than usual (or expccte.d with our models) the absorbed 

dose might well be underesrimaw.d, when in fact that individual would be expccte.d be 

more susceptible to long term internal buildup ofEAA than others (compare the effects of 

more rapid excretion with the "less simple" model with the slower exaction by the "70--­

hour" model in Table 4.5. 
; - _.:.: .. ... ·~ • ~";.t. ./"'. 

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-70­

ethoxyacetaldehyde and EAA. This might allow more definitive 

estimation of 

(a) rates of the two steps of metabolism for the aldehyde 

dehydrogenase pathway (from EE to ethoxyacetaldeyde, and 

· from ethoxyacetald~hyde to EAA), 

(b) the fraction of EE that is metabolized via the aldehyde 

dehydrogenase vs "other" pathway(s) 

(c) rates of tissue storage and release of ethoxyacetaldehyde, and 

return from storage. (Some aspects of the Groseneken et al. 

1986a,b results suggest that the usual phannacokinetic 

modeling assumption of equilibration between tissue levels 

of EE, ethoxyacetaldehyde, and E~and the levels in 

venous blood exiting the tissues may be leading to 

inaccuracies.) 

(3) Analogous phannacokinetic studies in animal systems where male 

and female reproductive effects have been measured. 

(4) Observations in human workers of the decline in urinary EAA 

excretion rates over several days of no exposure (including diurnal 

fluctuations in excretion). This would both allow resolution of 

.some important uncertainties in the construction of human 

phannacokinetic models, and assessment of human interinidividual 

variability in EAA excretion. 
-71­

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Factory," Brit J. ofIndustrial M~cine, vol 37,.pp.185-188. 

Chapin, R. E. and J.C. Lamb, IV (1984). ''Effects of Ethylene Glycol 

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Rat," Environmental Health Perspecitives, vol 57,pp. 219-224. . 
-72­

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l 

Cheever, K. L., Plotnick, H.B., Richards, D. E., and Weigel, W.W. (1984). 

"Metabolism and Excretion of 2-Ethoxyethanol in the Adult Male Rat," 

Environmental Health Perspectives, vol. 57, pp. 241-248. 

Clapp, D, Zaebst, D, and Herrick, R (1984). "Measuring Exposures to Glycol 

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Creasy, D. M. and Foster, P. M. D. (1984). ''The ·Morphological Development of 

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Molecular Pathology, vol. 40, pp. 169-176. 

Creasy, D. M., Flynn, J.C., Gray, T. J.B., and Butler, W. H. (1985). "A 

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