## DOI: 10.1126/science.1102443 , 1774 (2004); 306 Science et al. Qing Lan, 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, 1 

### Sungkyoon Kim, 5 

### Songnian Yin, 3



### Nathaniel Rothman, 1 

### . Martyn T. Smith 2 

### .-

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 matureblood 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, automobilerepair, 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 detailedexposure assessment that measured lymphocyte subsets and colony formation from progenitor cells in addition to the standardblood-count analyses reported in most previous investigations. Because benzene is thought to lower blood cell counts viametabolite 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 shoeworkers 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, individualbenzene 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 E controls, G 1 ppm,
1 to G 10 ppm, and Q 10 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 G 1 ppm benzene compared to controls (Table 1). Lymphocytesubset analysis showed significantly decreased CD4 þ–T cells, CD4 þ /CD8 þ ratio, and B cells. Hemoglobin concentrations were decreased only among workers exposed to Q 10 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 CD8 þ –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 G 10 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

9 0 colonies among controls, G 10 ppm, and
Q 10 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 trendsbetween benzene and all cell types were present (Ptrend shown). There was a greater proportional decrease in colonies in workers exposed

to Q 10 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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### 1774on March 12, 2009www.sciencemag.orgDownloaded from(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 G 1 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 ofother potential exposures on these associations, we identified a group of workers exposed to G 1 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 inlevels 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 hasbeen 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 B at 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 G 1 ppm (Ptrend 0 0.003). Compared to a mean T SD
WBC count of 5980 T 1420 cells/ m l among subjects with neither B at risk [ genotype, the

WBC count was 5480 T 1120 cells/ m l among subjects with either B at risk [ genotype ( P 0 0.006) and 4900 T 1240 cells/m l ( P 0 0.039) for both genotypes, in subjects exposed to G 1 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 465C 9 T SNP is less clear, but it may increase alternativesplicing and lower expression, thereby enhancing benzene hematotoxicity, as we observed.
The other two SNPs E CYP2E1 –1053C 9 T (rs2031920) and NQO1 609C9 T (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 hematotoxiceffects of benzene and suggested that exposure to G 5 ppm benzene could result inhematologic suppression. Occupational exposure decreased WBCs in petrochemical workers exposed to G 10 ppm benzene ( 17 ), and Qu et al . reported that WBCs and othercell types were decreased in workers exposed to G 5 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 CD4 þ /CD8 þ 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) G 1 ppm (109) 1 to G 10 ppm (110) Q 10 ppm (31) P for G 1 ppm vs. controls y P trend , all subjects z `

Benzene exposure Benzene air level (ppm) ¬ G 0.04 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) G 0.0001 G 0.0001 Granulocytes 4110 (1410) 3360 (948) 3480 (1170) 2790 (750) G 0.0001 G 0.0001 Lymphocytes .. 2130 (577) 1960 (541) 1960 (533) 1800 (392) 0.018 0.0014

CD4 þ –T cells 742 (262) 635 (187) 623 (177) 576 (188) 0.003 0.019

CD8 þ –T cells 553 (208) 543 (212) 564 (229) 549 (160) 0.75 0.97

CD4 þ /CD8 þ 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)  10 3 214 (48.8)  10 3 200 (53.4)  10 3 172 (44.8)  10 3 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 G 1 ppm, by linear regression on ln of each endpoint. - P trend using ln air benzene as a continuous variable. All statistically significant endpoints were inversely associated with benzene exposure. ` Comparison of subjects Q 10 ppm versus controls for endpoints without statistically significant trends: CD8 þ –T cells, P 0 0.31; monocytes, P 0 0.0006; hemoglobin P G 0.0001. ¬ Benzene air level is the arithmetic mean ( T SD) 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. P Urinary benzene (mean T SD) and mean individual air levels of benzene were strongly correlated (Spearman r 0 0.88, P G 0.0001). L Unadjusted mean ( T SD ) cells/m l blood. **Supplementary analyses are shown in the SOM Text. .. Absolute count. 

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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 linkedindividual air-monitoring data to the endpoints measured. Further, we showed thatbenzene 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-inducedlowering 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. Stone 5

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 thewell-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 theiractivities. Similarly, questions about timeuse and about the subjective experience ofspecific 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 encompassesall 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, involveshigh 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 witha 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 providean accurate picture of the experience associated with activities (e.g., commuting) andcircumstances (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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