DOI: 10.1126/science.1102443 

Science 306, 1774 (2004);

Qing Lan, et al.

of Benzene

Hematotoxicity in Workers Exposed to Low Levels

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Hematotoxicity in Workers

Exposed to Low Levels of Benzene

Qing Lan,1

* Luoping Zhang,2* Guilan Li,3 Roel Vermeulen,1

Rona S. Weinberg,4 Mustafa Dosemeci,1 Stephen M. Rappaport,5

Min Shen,1 Blanche P. Alter,1 Yongji Wu,6 William Kopp,7

Suramya Waidyanatha,5 Charles Rabkin,1 Weihong Guo,2

Stephen Chanock,1,8 Richard B. Hayes,1

Martha Linet,1Sungkyoon Kim,5 Songnian Yin,3

Nathaniel Rothman,1. Martyn T. Smith2.-

Benzene is known to have toxic effects on the blood and bone marrow, but its

impact at levels below the U.S. occupational standard of 1 part per million

(ppm) remains uncertain. In a study of 250 workers exposed to benzene,

white blood cell and platelet counts were significantly lower than in 140

controls, even for exposure below 1 ppm in air. Progenitor cell colony

formation significantly declined with increasing benzene exposure and was

more sensitive to the effects of benzene than was the number of mature

blood cells. Two genetic variants in key metabolizing enzymes, myeloperoxidase and NAD(P)H:quinone oxidoreductase, influenced susceptibility to

benzene hematotoxicity. Thus, hematotoxicity from exposure to benzene

occurred at air levels of 1 ppm or less and may be particularly evident among

genetically susceptible subpopulations.

Benzene causes toxicity to the hematopoietic

system (hematotoxicity) and leukemia (1).

Exposure to benzene occurs worldwide to

workers in the oil, shipping, automobile

repair, shoe manufacture, and other industries and to the general public from cigarette

smoke, gasoline, and automobile emissions

(2). In addition to ongoing concern about

health effects at or below the current U.S.

occupational standard of 1 ppm, high environmental exposures in cities (3) have led to

regulatory consideration of the risks posed

by benzene as an air pollutant.

Limitations in previous occupational

studies evaluating hematotoxicity at low

levels of benzene exposure led us to perform

a large cross-sectional study with detailed

exposure assessment that measured lymphocyte subsets and colony formation from

progenitor cells in addition to the standard

blood-count analyses reported in most previous investigations. Because benzene is

thought to lower blood cell counts via

metabolite effects on hematopoietic progenitor cells (4), we also evaluated the influence

of genetic variants in cytochrome P4502E1

(CYP2E1) and myeloperoxidase (MPO),

which metabolize benzene to toxic quinones

and free radicals (5), and NAD(P)H:quinone

oxidoreductase (NQO1), which protects

against this toxicity (6, 7).

We compared 250 benzene-exposed shoe

workers with 140 unexposed age- and sexmatched controls who worked in three

clothes-manufacturing factories in the same

region near Tianjin, China. Subjects were

young (mean T SD: 29.9 T 8.4 years), about

two-thirds were female (table S1), and shoe

workers had been employed an average of

6.1 T 2.9 years. For each subject, individual

benzene and toluene exposure was monitored repeatedly up to 16 months before

phlebotomy, and postshift urine samples

were collected from each subject (8, 9).

Subjects were categorized into four groups

by mean benzene levels measured during the

month before phlebotomy Econtrols, G1 ppm,

1 to G10 ppm, and Q10 ppm (Table 1)^, and

more than 100 of the exposed workers had

exposures below 1 ppm.

All types of white blood cells (WBCs)

measured in the Complete Blood Count and

platelets (9) were significantly decreased in

workers exposed to G1 ppm benzene compared to controls (Table 1). Lymphocyte

subset analysis showed significantly decreased CD4þ–T cells, CD4þ/CD8þ ratio,

and B cells. Hemoglobin concentrations

were decreased only among workers exposed

to Q10 ppm. Tests for a linear trend using

benzene air level as a continuous variable

were significant for platelets and all WBC

measures except monocytes and CD8þ–T

cells (Table 1). Adjustment for a range of

potential confounders had a negligible effect

on the strength of the associations (9).

We then restricted the linear-trend analyses to workers exposed to G10 ppm

benzene, excluding controls and higher

exposed workers, and found that inverse

associations remained for total WBCs (P 0

0.013), granulocytes (P 0 0.02), lymphocytes

1

Division of Cancer Epidemiology and Genetics,

National Cancer Institute (NCI), National Institutes

of Health (NIH), Department of Health and Human

Services (DHHS), Bethesda, MD 20892, USA. 2

School

of Public Health, University of California, Berkeley,

CA 94720, USA. 3

Chinese Center for Disease Control

and Prevention, Beijing, China. 4

New York Blood

Center, Clinical Services, White Plains, NY 10605,

USA. 5

School of Public Health, University of North

Carolina, Chapel Hill, NC 27599, USA. 6

Peking Union

Medical College, Beijing, China. 7

SAIC-Frederick, Inc.,

Frederick, MD 21702, USA. 8

Center for Cancer Research, NCI, NIH, DHHS, Bethesda, MD 20892, USA.

*These authors contributed equally to this work.

.These authors co-supervised this work.

-To whom correspondence should be addressed.

E-mail: martynts@berkeley.edu

Fig. 1. Effect of benzene exposure on (A)

white blood cell (WBC) and granulocyte counts;

(B) colonies from the colony-forming unit–

granulocyte-macrophage (CFU-GM) and burstforming unit–erythroid (BFU-E); and (C) colonies

from the colony-forming unit–granulocyte,

erythroid, macrophage, megakaryocyte (CFUGEMM). Erythropoietin (EPO) was added to half

of the cultures (9). Trends with benzene were

tested by linear regression (WBC, granulocytes),

negative binomial regression (CFU-GM, BFU-E),

and unconditional logistic regression [CFU-GEMM,

categorizing subjects into 0 or more than 0

colonies (92%, 74%, and 40% of subjects had

90 colonies among controls, G10 ppm, and

Q10 ppm, respectively)]. Models were adjusted

for age and sex, and additionally for smoking,

alcohol, recent infections, and body mass index

(BMI) if significant (9). Strong, inverse trends

between benzene and all cell types were present (Ptrend shown). There was a greater proportional decrease in colonies in workers exposed

to Q10 ppm versus controls for CFU-GM, BFU-E,

and CFU-GEMM compared to the decline in

WBCs (P G 0.011, 0.048, and 0.0078, respectively) and for CFU-GM and -GEMM compared

to the decline in granulocytes (P 0 0.026 and

0.0094, respectively) (9).

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(P 0 0.045), B cells (P 0 0.018), and

platelets (P 0 0.0016). To address the

influence of past benzene exposure on these

cell types, we examined workers exposed to

mean benzene G1 ppm over the previous year

(n 0 60), and a subset who also had G40-

ppm-years lifetime cumulative benzene exposure (n 0 50), and found that the above cell

types were decreased compared to controls

(P G 0.05). Finally, to exclude the effect of

other potential exposures on these associations, we identified a group of workers

exposed to G1 ppm benzene with negligible

exposure to other solvents (n 0 30) (fig. S1)

(9) and found decreased levels of WBCs,

granulocytes, lymphocytes, and B cells compared to controls (P G 0.05). These findings,

based on differentiated blood cell counts,

provide evidence of hematotoxicity in workers exposed to benzene at or below 1 ppm.

Because benzene affected nearly all

blood cell types, toxicity to progenitor cells

was suspected. A fraction of hematopoietic

progenitor cells circulate in the bloodstream

in dynamic equilibrium with the bone marrow

and can be cultured in colony-forming assays

to measure their proliferative potential (10).

Using peripheral blood from 29 benzeneexposed workers and 24 matched controls,

we examined the dose-dependent effects

of benzene on different types of progenitor

cell colony formation (CFU-GM, BFU-E,

CFU-GEMM) (9). Highly significant dosedependent decreases in colony formation

from progenitor cells were observed (Fig. 1).

Further, benzene caused a greater proportional decrease in colony formation than in

levels of differentiated WBCs and granulocytes (compare Fig. 1, B and C, to Fig. 1A),

suggesting that early progenitor cells are

more sensitive than are mature cells to the

hematotoxic effects of benzene. This greater

sensitivity of early progenitor cells is in

agreement with previous findings in human

cell cultures and mice (11, 12).

Genetic variation in enzymes responsible

for activating and detoxifying benzene has

been shown to confer susceptibility to benzene poisoning in highly exposed workers

(6, 13, 14). We examined four nonsynonymous single-nucleotide polymorphisms

(SNPs), with probable functional significance,

in the CYP2E1, MPO, and NQO1 genes (9).

Two genotypes significantly influenced WBC

counts in benzene-exposed workers, MPO

–463GG (rs2333227) (P 0 0.04) and NQO1

465CT (rs4986998) (P 0 0.014) (table S2).

In exposed subjects who carry either one (n 0

191) or both of the Bat risk[ genotypes (n 0

11), there was a strong gene-dosage effect

(Ptrend 0 0.004) (table S3), which was also

present among those exposed to G1 ppm

(Ptrend 0 0.003). Compared to a mean T SD

WBC count of 5980 T 1420 cells/ml among

subjects with neither Bat risk[ genotype, the

WBC count was 5480 T 1120 cells/ml among

subjects with either Bat risk[ genotype (P 0

0.006) and 4900 T 1240 cells/ml (P 0 0.039)

for both genotypes, in subjects exposed to G1

ppm. Neither genotype was associated with

WBC count in controls, either separately (table

S2) or in combination (Ptrend 0 0.94) (table

S3), and the trends in exposed workers and

controls were significantly different from each

other (test for interaction, P 0 0.03). Subjects

with the MPO –463GG genotype have

normal expression and had a greater decrease

in WBC counts from benzene exposure

compared to individuals with the GA or AA

genotypes (the latter two being associated

with reduced expression) (15). The functional

significance of the NQO1 465C9T SNP is

less clear, but it may increase alternative

splicing and lower expression, thereby enhancing benzene hematotoxicity, as we observed.

The other two SNPs ECYP2E1 –1053C9T

(rs2031920) and NQO1 609C9T (rs1800566)^

were not significantly related to WBCs

(table S2).

There have been numerous studies of

benzene-induced hematotoxicity (www.epa.

gov/iris/toxreviews/0276-tr.pdf), but few

have been able to study effects at low levels

of exposure. Ward et al. (16) found no

evidence of a threshold for hematotoxic

effects of benzene and suggested that exposure to G5 ppm benzene could result in

hematologic suppression. Occupational exposure decreased WBCs in petrochemical

workers exposed to G10 ppm benzene (17),

and Qu et al. reported that WBCs and other

cell types were decreased in workers exposed to G5 ppm benzene (18). In contrast,

Collins et al. (19, 20) and Tsai et al. (21) did

not detect decreased blood cell counts based

Table 1. Peripheral blood cell counts in relation to benzene exposure level.

There are up to 418 observations on 390 unique subjects (140 controls and

250 benzene-exposed workers). Data were obtained from 28 exposed

subjects in both years (2000 and 2001) and are treated as independent

observations in the summary data shown, distributing into benzene

category on the basis of exposure level in the year that the blood sample

was collected. Statistical analyses were adjusted for repeated measures by

generalized estimating equations (22). Models were adjusted for age, sex,

current smoking, current alcohol drinking, BMI, recent infections, and, where

appropriate, ln toluene air level (which can competitively inhibit benzene’s

metabolism) (9). Data shown here are from all subjects except one benzeneexposed subject with data for only CD4þ/CD8þ ratio; two benzene-exposed

subjects and one control with no benzene urine data; and two controls with

no BMI data.

Subject category

(n)*

Controls

(140)

G1 ppm

(109)

1 to G10 ppm

(110)

Q10 ppm

(31)

P for G1 ppm

vs. controlsy

Ptrend,

all subjectsz`

Benzene exposure

Benzene air level (ppm)¬ G0.04 0.57 (0.24) 2.85 (2.11) 28.73 (20.74)

Benzene urine (mg/liter)P 0.382 (1.24) 13.4 (18.3) 86.0(130) 847(1250)

Peripheral blood cell counts L

White blood cells (WBC)** 6480 (1710) 5540 (1220) 5660 (1500) 4770 (892) G0.0001 G0.0001

Granulocytes 4110 (1410) 3360 (948) 3480 (1170) 2790 (750) G0.0001 G0.0001

Lymphocytes.. 2130 (577) 1960 (541) 1960 (533) 1800 (392) 0.018 0.0014

CD4þ–T cells 742 (262) 635 (187) 623 (177) 576 (188) 0.003 0.019

CD8þ–T cells 553 (208) 543 (212) 564 (229) 549 (160) 0.75 0.97

CD4þ/CD8þ ratio 1.46 (0.58) 1.26 (0.41) 1.22 (0.45) 1.09 (0.35) 0.015 0.024

B cells 218 (94) 186 (95) 170 (75) 140 (101) 0.003 0.0002

NK cells 586 (318) 558 (299) 566 (271) 415 (188) 0.56 0.0044

Monocytes 241 (92) 217 (97) 224 (93) 179 (74) 0.018 0.28

Platelets 230 (59.7)  103 214 (48.8)  103 200 (53.4)  103 172 (44.8)  103 0.023 0.0002

Hemoglobin (g/dl) 14.5 (1.6) 14.7 (1.5) 14.5 (1.7) 13.6 (1.6) 0.12 0.29

*The 28 subjects studied in both the first (2000) and second (2001) year of the study are categorized based on the exposure assessment in 2000. .Controls versus exposed G1

ppm, by linear regression on ln of each endpoint. -Ptrend using ln air benzene as a continuous variable. All statistically significant endpoints were inversely associated with

benzene exposure. `Comparison of subjects Q10 ppm versus controls for endpoints without statistically significant trends: CD8þ–T cells, P 0 0.31; monocytes, P 0 0.0006;

hemoglobin P G 0.0001. ¬Benzene air level is the arithmetic mean (TSD) of an average of two measurements per subject collected during the month before phlebotomy (9). This

time period was chosen because granulocytes have relatively short half-lives in peripheral blood. PUrinary benzene (mean T SD) and mean individual air levels of benzene were

strongly correlated (Spearman r 0 0.88, P G 0.0001). LUnadjusted mean (TSD) cells/ml blood. **Supplementary analyses are shown in the SOM Text. ..Absolute count.

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on routine monitoring of workers exposed to

low levels of benzene.

The present study showed that total

WBCs, granulocytes, lymphocytes, B cells,

and platelets significantly declined with

increasing benzene exposure and were lower

in workers exposed to benzene at air levels

of 1 ppm or less compared to controls. Our

findings are particularly robust because we

carried out extensive exposure assessment

over a 16-month period (8) and linked

individual air-monitoring data to the endpoints measured. Further, we showed that

benzene exposure decreased colony formation from myeloid progenitor cells, and that

these progenitors were more sensitive to

benzene toxicity than were mature WBCs.

Finally, genetic variation in MPO and NQO1

conferred susceptibility to benzene-induced

lowering of WBC counts. Although confirmation of these findings in other studies is

needed, these data provide evidence that

benzene causes hematologic effects at or

below 1 ppm, particularly among susceptible

subpopulations.

References and Notes

1. M. Aksoy, Environ. Health Perspect. 82, 193 (1989).

2. G. L. Gist, J. R. Burg, Toxicol. Ind. Health 13, 661

(1997).

3. V. Simon et al., Sci. Total Environ. 334–335, 177

(2004).

4. B. I. Yoon et al., Exp. Hematol. 29, 278 (2001).

5. D. Ross, Eur. J. Haematol. Suppl. 60, 111 (1996).

6. N. Rothman et al., Cancer Res. 57, 2839 (1997).

7. A. K. Bauer et al., Cancer Res. 63, 929 (2003).

8. R. Vermeulen et al., Ann. Occup. Hyg. 48, 105

(2004).

9. Materials and methods are available as supporting

material on Science Online.

10. L. Kreja, K. M. Greulich, T. M. Fliedner, B. Heinze, Int.

J. Radiat. Biol. 75, 1241 (1999).

11. M. T. Smith et al., Carcinogenesis 21, 1485 (2000).

12. D. J. Abernethy, E. V. Kleymenova, J. Rose, L. Recio,

B. Faiola, Toxicol. Sci. 79, 82 (2004).

13. J. Wan et al., Environ. Health Perspect. 110, 1213

(2002).

14. J. N. Xu et al., Zhonghua Lao Dong Wei Sheng Zhi Ye

Bing Za Zhi 21, 86 (2003).

15. C. C. Winterbourn, M. C. Vissers, A. J. Kettle, Curr.

Opin. Hematol. 7, 53 (2000).

16. E. Ward et al., Am. J. Ind. Med. 29, 247 (1996).

17. B. Zhang, Zhonghua Yu Fang Yi Xue Za Zhi 30, 164

(1996).

18. Q. Qu et al., Am. J. Ind. Med. 42, 275 (2002).

19. J. J. Collins et al., J. Occup. Med. 33, 619 (1991).

20. J. J. Collins, B. K. Ireland, P. A. Easterday, R. S. Nair,

J. Braun, J. Occup. Environ. Med. 39, 232 (1997).

21. S. P. Tsai et al., Regul. Toxicol. Pharmacol. 40, 67

(2004).

22. S. L. Zeger, K. Y. Liang, Biometrics 42, 121 (1986).

23. We thank the participants for taking part in this study.

Supported by NIH grants RO1ES06721, P42ES04705,

and P30ES01896 (M.T.S.), P42ES05948 and P30ES10126

(S.M.R.), and NIH contract N01-CO-12400 with SAICFrederick, Inc. M.T.S. has received consulting and expert

testimony fees from law firms representing both

plantiffs and defendants in cases involving exposure to

benzene. G.L. has received funds from the American

Petroleum Institute for consulting on benzene-related

health research.

Supporting Online Material

www.sciencemag.org/cgi/content/full/306/5702/1774/

DC1

Materials and Methods

SOM Text

Fig. S1

Tables S1 to S3.

References

7 July 2004; accepted 5 October 2004

A Survey Method for Characterizing

Daily Life Experience: The Day

Reconstruction Method

Daniel Kahneman,1 Alan B. Krueger,1,2 David A. Schkade,3

*

Norbert Schwarz,4 Arthur A. Stone5

The Day Reconstruction Method (DRM) assesses how people spend their time

and how they experience the various activities and settings of their lives,

combining features of time-budget measurement and experience sampling.

Participants systematically reconstruct their activities and experiences of the

preceding day with procedures designed to reduce recall biases. The DRM’s

utility is shown by documenting close correspondences between the DRM

reports of 909 employed women and established results from experience

sampling. An analysis of the hedonic treadmill shows the DRM’s potential for

well-being research.

How do people experience the settings and

activities of their lives? How do they use

their time? These questions are usefully

considered together, but there is no generally

accepted method for collecting the relevant

data. Quantitative information about time

use and the frequency and intensity of stress,

enjoyment, and other affective states is

potentially useful to medical researchers for

assessing the burden of different illnesses (1)

and the health consequences of stress (2); to

epidemiologists interested in social and

environmental stressors (3); to economists

and policy researchers for evaluating policies

and for valuing nonmarket activities (4, 5);

and to anyone who wishes to measure the

well-being of society. In particular, economic models that define well-being by the

temporal integral of momentary experienced

utility (6–8) require detailed measures of the

quality and duration of people_s experiences

in daily life.

Information about the allocation of time

in the daily life of the population is a

component of national statistics in several

countries. With rare exceptions (4, 9), timebudget studies have not included measures of

the satisfaction people derive from their

activities. Similarly, questions about timeuse and about the subjective experience of

specific situations are rarely included in surveys of subjective well-being. Instead, these

studies usually rely on global reports of

happiness or satisfaction with life in general,

or with domains such as work and family

(10, 11).

The development of the experience sampling method (ESM) (12) and of ecological

momentary assessment, which encompasses

all momentary phenomena including physiological events (13), marked a notable advance in the measurement of the quality of

people_s lives. Participants in ESM studies

are prompted to record where they are, what

they are doing, and how they feel several

times throughout the day. This technique

provides a rich description of a sample of

moments in respondents_ lives, while avoiding

the distortions that affect the delayed recall

and evaluation of experiences (14). However,

experience sampling is expensive, involves

high levels of participant burden, and provides little information about uncommon or

brief events, which are rarely sampled.

We present a new hybrid approach, the

DRM, which combines a time-use study with

a technique for recovering affective experiences. DRM respondents first revive memories of the previous day by constructing a

diary consisting of a sequence of episodes.

Then they describe each episode by answering questions about the situation and about

the feelings that they experienced, as in

experience sampling. The goal is to provide

an accurate picture of the experience associated with activities (e.g., commuting) and

circumstances (e.g., a job with time pres1

Woodrow Wilson School and Department of Psychology, 2

Woodrow Wilson School and Economics Department, Princeton University, Princeton, NJ 08540, USA.

3

Rady School of Management, University of California,

San Diego, La Jolla, CA 92093–0093, USA. 4

Institute of

Social Research and Department of Psychology,

University of Michigan, Ann Arbor, MI 48106–1248,

USA. 5

Department of Psychiatry and Behavioral

Science, Stony Brook University, Stony Brook, NY

11794–8790, USA.

*To whom correspondence should be addressed.

E-mail: schkade@ucsd.edu

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