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Biomonitoring of human populations exposed to petroleum fuels with special consideration of the role of benzene as a genotoxic component

Report of the EC Environment programme Project EV5V-CT92-0221

Edited by A. Carere and R. Crebelli

ISSN 0394-9311 Serie Relazioni 97/4 DISCLAIMER

Portions of this document may be illegible electronic image products. Images are produced from the best available original document. iSTITUTO SUPERIORS Dl SANITA

Biomonitoring of human populations exposed to petroleum fuels with special consideration of the role of benzene as a genotoxic component

Report of the EC Environment programme Project EV5V-CT92-0221

Edited by Angelo Carere and Riccardo Crebelli Laboratorio di Tossicologia Comparata ed Ecotossicologia

ISSN 0394-9311 Serie Relazioni 97/4 Istituto Superiore di Sanita Biomonitoring of human populations exposed to petroleum fuels with special consideration of the role of benzene as a genotoxic component Report of the EC Environment programme. Project EV5V-CT92-0221 Edited by Angelo Carere and Riccardo Crebelli 1997, iv, 102 p. Sene Relazioni 97/4

In the framework of an EC research programme on the health risks of environmental chemicals, the Istituto Superiore di Sanita co-ordinated, in 1993-1996, a project on the biological effects of benzene and petroleum fuels. Seven laboratories from six European countries collaborated in the biological monitoring of selected populations with occupational exposure to petrochemicals. Several markers of early biological effect were applied together with environmental and personal exposure monitoring techniques. An epidemiological retrospective mortality study was also carried out on Italian filling station attendants. TTie results obtained highlighted an excess of genetic damage in some of the study populations, compared to matched unexposed controls. Even though these results do not allow a reliable risk estimation, the possible prognostic significance of cytogenetic damage for future cancer onset, together with some alerting findings from the mortality study, suggest that low dose exposures to benzene and petroleum fuels may retain some toxicological significance. Key words: Benzene, Biomonitoring, Epidemiology, Exposure monitoring, Petroleum fuels

Istituto Superiore di Sanita Monitoraggio biologico di popolazioni esposte a carburanti, con particolare riguardo agli effetti del benzene. Rapporto del programma di ricerca comunitario Ambiente. Progetto EV5V-CT92-0221. A cura di Angelo Carere e Riccardo Crebelli 1997, iv, 102 p. Serie Relazioni 97/4 (in inglese)

Nell’ambito del programma comunitario Ambiente, 1’Istituto Superiore di Sanita ha coordinate un progetto triennale (1993-1996) sugli effetti della esposizione a benzene e carburanti autoveicolari. Sette laboratory in sei stati europei, hanno partecipato al monitoraggio di popolazioni con esposizione occupazionale a bassi liveili di prodotti petrolchimici. Sono stati analizzati molteplici indicator! di effetti biologic! precoci, con particolare riguardo ai danni cromosomici, insieme a marcatori di esposizione interna, validati e intercalibrati alio scopo. I risultati ottenuti mostrano, in alcune delle popolazioni studiate, un eccesso di danni cromosomici rispetto a popolazioni di contralto non esposte. Una indagine sulle cause di morte di una coorte di gestori di impianti di rifornimento ha segnalato un possibile eccesso di neoplasie. Anche se i risultati ottenuti non permettono una puntuale stima del rischio, in considerazione del possibile valore predittivo delle alterazioni citogenetiche per i! rischio di tumore, e delle indicazioni dello studio di mortalita, si pud ritenere che anche 1’esposizione a basse dost di benzene e altri derivati del petrolio possa avere rilevanza tossicologica. Parole chiave: Benzene, Biomonitoraggio, Carburanti, Epidemiologia, Esposizione

The research project “Biomonitoring of human populations exposed to petroleum fuels with special consideration on the role of benzene as a genotoxic component ” was partially supported by the EC Environment programme under the contract EV5 V-CT92-0221, coordinated by the Istituto Superiore di Sanita. The interest and encouragement of Dr Canice Nolan, Directorate General XII, Science, Research and Development of the European Commission, is gratefully acknowledged. The Editors are indebted with Ms. Francesca Di Bari for her valuable assistance.

CONTENTS

Preface iii

Contributors iv

1. Overview of the project 1

2. Assessment of benzene exposure, early genetic effects, and cancer 6 mortality in Italian filling station attendants

3. Cytogenetic monitoringof Spanish filling station attendants 41

4. Benzene exposure and cytogenetic investigation on Estonian shale oil 56 petrochemical workers

5. Influence of benzene and benzene ralated compounds on cytogenetic 68 damage in human blood lymphocytes (Polish workers)

6. Examination of ras oncoproteins in human plasma from healthy controls 78 and workers exposed to petroleum emissions

7. Monitoring of Hungarian urban areas, oil refinery sites and service 86 stations

8. Conclusions 96

9. Publications arising from the project 99

Ill

PREFACE

Benzene is nowadays an ubiquitary environmental pollutant in European countries. Engine emissions supply the largest contribution to the environmental benzene level, which is a matter of special concern in many high traffic urban areas. Despite the long standing interest of physicians and biologists in the adverse effects of benzene to human health, the consequences of human exposure to low environmental benzene levels are not yet elucidated. This leads to uncertainties in the estimation of actual risks and in the definition of air quality criteria. In 1991 the European Commission launched the “Environment” Programme, to support coordinated research activities of European laboratories in the field of the environment. Airborne pollution, and the resulting health risks to urban populations, were among the priority tasks. In this framework, the Istituto Superiore di Sanita coordinated a collaborative research project on exposure and early biological effects of low benzene exposure. Six partners from five countries, including two non- Member States, joined the project from March 1993 to September 1996. The main results and conclusions of this collaborative endeavour are summarized in this publication. Exposure and early effect markers were assessed on several model populations with moderate to low benzene exposure, providing information on low dose effects which contribute to unravelling the health risks from environmental benzene. The project also provided the opportunity for a fruitful exchange of expertise and collaboration among partners, giving a truly transnational dimension to this coordinated effort, which tackles a priority environmental health problem throughout the European community.

The Editors IV

CONTRIBUTORS

Angelo Carere, Riccardo Crebelli, Andrea Zijno, Paola Leopardi, Francesca Marcon, Cristina Andreoli, Luigi Turrio Baldassarri, - Laboratory of Comparative Toxicology and Ecotoxicology, Istituto Superiore di Sanita, Rome, Italy

Susanna Lagorio, Ivano Iavarone, Sergio Fuselli - Laboratory of Environmental Hygiene, Istituto Superiore di Sanita, Rome, Italy

Francesco Forastiere, Elisabetta Rapid - Epidemiological Unit, Latium regional Health Authority, Rome, Italy

Marco Biocca, Adriana Pasquini - CDS, Centro Documentazione per la Salute, Emilia Romagna Health Authority, Bologna, Italy

Antonio Antoccia, Daniela Cimini, Francesca Degrassi, Mario Fiore, Fabrizio Palitti, Antonella Sgura, Caterina Tanzarella - Centro di Studio di Genetica Evoluzionistica del CNR c/o Dipartimento di Genetica e Biologia Molecolare, Universita “La Sapienza ”, Rome, Italy

Ricardo Marcos, Amadeo Creus, Noel Xamena, Elisabet Carbonell, Maria Pitarque, Gloria Ribas - Universitat Autonoma de Barcelona, Barcelona, Spain

Kimmo Peltonen, Antero Aitio, Tiina Anttinen-Klemetti, Kirsi Autio, Tehri Kuljukka, Lars Nylund, Kaija Pekari, Jordi Surralles, Maqa Sorsa - Finnish Institute of Occupational Health, Helsinki, Finland

Diana Anderson, Jane Hughes - BIBRA International, Carshalton, Surrey, United Kingdom

Antonina Cebulska-Wasilewska, Anna Wierzevvska, Ewa Kasper - Institute of Nuclear Physics, Kracow, Poland

Alan Pinter, Anna Paldy, Eva Vaskovi, Julianna Bacskai, Gabor Mayer, Istvan Vincze - National Institute of Public Health, Budapest, Hungary

Thomas Veidebaum - Estonian Institute of Experimental and Clinical Medicine, Tallin, Estonia 1

1. OVERVIEW OF THE PROJECT

Introduction

Benzene, an established human carcinogen (IARC, 1987 Vol. 1), is currently the fourth-fifth (by tonnes) organic chemical produced worldwide (Fishbein L., 1988). Benzene is an important air pollutant in most large Western and Eastern cities, where it is detectable at levels in the range of tens of micrograms per cubic meter (Fishbein L., 1988 - Wallace L.A., 1989). Epidemiological data on leukemia incidence in benzene exposed workers have been used to derive the unit risk, i.e. the risk for a lifetime exposure to 1 microgram per cubic meter. Current estimates are in the range 4 x 10"6 - 3 x 10"5 the unit risk for leukemia associated to benzene exposure (OMS/WHO, 1987 - EPA, 1994). These figures have been used recently by the Italian National Advisory Committee on Toxicology to make a quantitative estimate of leukemia risks associated with benzene exposure in the general Italian population living in urban areas: according to the hypothesized exposure levels, 36 to 108 new cases are expected for each year (CCTN, 1994). Considering the large number of European citizens living in urban areas, the health consequences of benzene pollution are a matter of serious concern, and the reduction of environmental benzene is regarded as a priority goal in the field of environmental safety. Most environmental benzene comes from the use of gasoline, where it is present in low percent amounts. Even though it can be anticipated that the exposure to petroleum fuels may represent a potential risk factor (Mehlman M.A., 1991), because of the occurrence of known or suspect animal carcinogens (Infante P.F. et al, 1990), the health impact of fuel exposure has not been fully elucidated (Infante P.F. et al, 1990 - Mehlman M.A., 1990 - IARC, 1989). Exposures to gasoline fuel and to exhausts from engines operating on gasoline were considered by the International Agency for Research on Cancer as possibly carcinogenic to humans (IARC, 1989 Vol. 45-46). However, further mechanistic information is required for a better evaluation of possible risks, especially at low dose levels (Mehlman M.A., 1991). Despite the evidence of carcinogenicity in humans and experimental animals (IARC, 1987 Vol. 1-42, Suppl.7), and genotoxicity in vivo (IARC, 1987 Vol. 1-42, Suppl.6), the mechanism of benzene toxicity is far from being fully understood. In this respect, different mechanistic interpretations of the leukemogenic effect of benzene have been suggested, such as a synergism between different metabolites, or a synergism between glutathione-depleting metabolites of benzene and hydroxyl radicals (Yardley-Jones A. etal, 1991 - Snyder R. et al, 1993). Besides the hazard for the general population, the consequences of occupational exposure to benzene are also a cause for concern. In view of its established carcinogenicity, occupational exposure limits to benzene, usually above 1 ppm (3.2 mg/m3) as 8 hours TWA have been established (Garlanda T., 1991). However, the possible risks related to low dose exposures (below 1 ppm), such as those associated with fuel delivery, are not yet elucidated. Epidemiological studies point to a possible 2

increased cancer risk in these workeis (Siemiatycki J. et al, 1987 - Jakobsson R. et al, 1993), which may represent, together with other occupationally exposed populations, a useful human model to evaluate the adverse effects resulting from low dose exposure to petroleum fuels. In this connection, this research project was focused on the analysis of early markers of biological effect in relation to the exposure to benzene and other petrochemical products in several occupationally exposed populations, with the final aim of investigating the risk of irreversible effects arising from exposure to low level benzene and petroleum fuels.

Objectives

The research programme was aimed at: a) assessing exposure of human populations exposed to benzene from petroleum fuels; b) analysing the frequency of indicators of genetic damage in people exposed to petrochemical products; c) evaluating the role of benzene as a genotoxic component of petroleum and its derivatives; d) estimating the risk of different causes of death among those exposed to gasoline vapours. Towards this aim, several intercorrelated activities were carried out by the project partners on the following study populations: 1. Italian filling station attendants; 2. Spanish filling station attendants; 3. Estonian shale oil workers; 4. Polish refinery workers; 5. Residents in the surroundings of the oil refinery at Szazhalombatta, Hungary. Methods and results of these investigations are described in detail in Chapters 2-7. 3

Partners of the project

Coordinator Cl Istituto Superiore di Sanita, Rome (ISS) Principal investigator Angelo Carere

Contractor C2 Centro di Genetica Evoluzionistica, CNR, Rome (CGE) Principal investigator Caterina Tanzarella

Contractor C3 Universitat Autonoma de Barcelona, Barcelona (UAB) Principal investigator Ricardo Marcos

Contractor C4 Finnish Institute of Occupational Health, Helsinki (FIOH) Principal investigator Kimmo Peltonen

Contractor C5 BIBRA International, Carshalton, Surrey (BIBRA) Principal investigator Diana Anderson

Sub-Contractor SCI Institute of Nuclear Physics, Cracow (INF) Principal investigator Antonina Cebulska-Wasilewska

Sub-Contractor SC2 “Johan Bela” National Institute of Public Health, Budapest (NIPH) Principal investigator Alan Pinter 4

Distribution of tasks

The research activities undertaken within the project and the distribution of tasks among partners are illustrated below:

Chapter Study population Type of study Partner

2 Italian filling station attendants Exposure assessment Cl Genotoxicity studies Cl C2 Mortality study Cl*

3 Spanish filling station attendants Exposure assessment C3 and airport workers Genotoxicity studies C3

4 Estonian shale oil petrochemical Exposure assessment C4 workers Cytogenetic survey C4

5-6 Polish refinery workers Cytogenetic survey SCI Serum oncoproteins C5

7 Hungarian urban areas, oil Air monitoring, medical SC2 refinery sites and service surveillance stations

* In collaboration with Epidemiological Unit, Latium regional Health Authority, Rome, and CDS, Emilia Romagna Health Authority, Bologna, Italy

References

FISHBEIN, L. Benzene: uses, occurrence and exposure. In: L.Fishbein & I.K.O’Neill (Eds.) Environmental Carcinogens - Methods of Analysis and Exposure Assessment. Volume 10 - Benzene and Alkylated Benzenes. IARC Scientific Publication n.85, International Agency for Research on Cancer, Lyon, 1988. pp.67 - 96.

GARLANDA T. Exposure limits at working place, Year 1990/1991; Commission of the European Communities, General Directorate Employment, Social Affairs and Education; Health and Safety Directorate. 1991.

INFANTE PF, SCHWARTZ E,. CAHILL R. Benzene in petrol: a continuing hazard. The Lancet 1990, 336: 814-815. 5

International Agency for Research on Cancer. IARC Monographs on the evaluation of the carcinogenic risks to humans. Diesel and gasoline engine exhausts and some nitroarenes. Lyon, IARC, 1989, Vol. 46.

International Agency for Research on Cancer. IARC Monographs on the evaluation of the carcinogenic risks to humans. Genetic and related effects: an updating of selected IARC monographs from volumes l to 42. Lyon: IARC, 1987, Suppl. 6.

International Agency for Research on Cancer. IARC Monographs on the evaluation of the carcinogenic risks to humans. Occupational exposures in petroleum refining; crude oil and major petroleum fuels. Lyon: IARC, 1989, Vol. 45.

International Agency for Research on Cancer. IARC Monographs on the evaluation of the carcinogenic risks to humans. Overall evaluations of carcinogenicity. An updating of IARC Monographs Volumes 1 to 42. Supplement 7. Lyon: IARC, 1987.

JAKOBSSON R., AHLBOM A., BELLANDER T., LUNDBERG I.. Acute myeloid leukemia among petrol station attendants. Arch. Environ. Health 1993; 48: 255-259.

MEHLMAN MA. Benzene health effects: unanswered questions still not addressed. Am J Ind Med 1991; 20: 707-711.

MEHLMAN MA. Dangerous properties of petroleum refining prodyucts: carcinogenicity of motor fuels (gasoline). Teratogenesis, Carcinogenesis, Mutagenesis 1990, 10: 399-408.

National Advisory Committee on Toxicology. “Parere della Commissione Consultiva Tossicologica Nazionale riguardante la stima del rischio di leucemia da benzene da emission! autoveicolari”. Rome, 27 June, 1994.

OMSAVHO. Air quality guidelines, QMS, Copenhagen: 1987.

SIEMIATYCKI, J„ DEWAR R, NADON L„ GERIN M„ RICHARDSON L„ WACHOLDER S. Association between several sites of cancer and twelve petroleum delivered liquids: results from a case- referent study in Montreal. Scand. J. Work Environ. Health 1987; 13: 493-504.

SNYDER R, WITZ G, GOLDSTEIN BD. The toxicology of benzene. Environ Health Persp 1993; 100: 293-306.

State of California - Air Resource Board. Proposed regulation for California 2 reformulated gasoline - Technical support, 1991.

US EPA. IRIS File, US EPA, Washington, 1994.

WALLACE, LA. The exposure of the general population to benzene. Cell Biology and Toxicology 1989, 5: 297-314.

YARDLEY-JONES A, ANDERSON D, PARKE DV. The toxicity of benzene and its metabolism and molecular pathology in human risk assessment. Br J Ind Med. 1991; 48: 437-44. 6

2. ASSESSMENT OF BENZENE EXPOSURE, EARLY GENETIC EFFECTS, AND CANCER MORTALITY IN ITALIAN FILLING STATION ATTENDANTS

Angelo Carere (a), Riccardo Crebelli (a), Andrea Zijno (a), Paola Leopardi (a), Francesca Marcon (a), Cristina Andreoli (a), Sergio Fuselli (a), Ivano Iavarone (a), Susanna Lagorio (a), Luigi Turrio Baldassarri (a), Antonio Antoccia (b), Daniela Cimini (b), Francesca Degrassi (b), Mario Fiore (b), Fabrizio Palitti (b), Antonella Sgura (b), Francesco Forastiere (c), Elisabetta Rapiti (c), Marco Biocca (d), Adriana Pasquini (d).

(a) Istituto Superiore di Sanita, Rome, Italy (b) Centro di Studio di Genetica Evoluzionistica del CNR c/o Dipartimento di Genetica e BiologiaMolecolare, Universita “La Sapienza”, Rome, Italy (c) Epidemiological Unit, Latium regional Health Authority, Rome, Italy (d) CDS, Emilia Romagna Health Authority, Bologna, Italy

This report describes the main results of the research activity carried out by the Istituto Superiore di Sanita (ISS) and its associated partner Centro di Genetica Evoluzionistica, CRN (CGE) in the framework of the research project. Three interrelated studies were undertaken on Italian gasoline station attendants to investigate the health effects of the occupational exposure to petroleum fuels: 1. Exposure assessment surveys 2. Biomonitoring study 3. Mortality study Each of the above studies is described in one separate paragraph. The research lines 1. (exposure assessment) and 3. (mortality study) were performed by the ISS staff in collaboration with the Epidemiological Unit, Latium Regional Health Authority, Rome and CDS, Bologna. The cytogenetic investigation described in paragraph 2 was jointly performed by ISS and CGE. The urinary analysis of 8-hydroxyguanosine, reported in the biomonitoring section, was performed by ISS in collaboration with Dr. Christer Tagesson, Department of Occupational and Environmental Medicine, Linkoping University, Sweden.

2.1. Exposure assessment survey

Two exposure assessment studies among Italian filling station attendants were performed, aimed at describing the exposure profile of this occupational group and at deriving personal exposure indicators for the genotoxicity survey and for the retrospectivemortality study. Design, methods and results of the studies are described in details in the original publications (Lagorio S. et al., 1993 - Lagorio S. et al., 1994 - Lagorio S. et al., 1997) and will be only briefly summarised herein. ERRATUM

The name of Caterina Tanzarella was erroneously omitted from the authors of Chapter p.6. The Editors apologize for this inconvenience. 7

2.1.1 Methods - A first investigation was carried out during the period December 1991 - November 1992 on 111 service stations (Lagorio S. et al., 1993). On each sampling day the attendant recorded the quantity of fuel dispensed by type and the number of vehicles filled. Vapor samples were collected at the breathing zone of the worker during the 8 hours of the workshift by means of charcoal tubes and personal pumps. Concentrations of benzene, toluene and xylenes were determined by GC/FID. The analysis concerned 2109 measurements of the 8h TWA of aromatic hydrocarbons, referring to 703 personal samples from 111 filling station workers. Samples of leaded and unleaded gasoline (24 and 10 respectively) were collected from 27 service stations and analysed, for benzene concentration, by capillary GC/FID. The effect of daily workload indicators and other variables on the log- transformed personal exposures to benzene were evaluated by linear regression analysis. An estimate of the absolute quantity of benzene (g) in the gasoline sold during the sampling day was calculated as the product of the average benzene concentration in the sample of leaded or unleaded gasoline (g/1) times the total amount of fuel dispensed (Lagorio S. etal., 1994). In 1994-95 a subgroup of 12 service stations included in the previous survey, was requested to take part to a second exposure assessment study aimed at evaluating the relationship between personal exposure to benzene and different sources of exposure variability, including individual work practices and background level of atmospheric benzene pollution (Lagorio S. et al., 1997). Each filling station attendant was monitored four times at 2 or 3 month intervals, on randomly selected week-days. On each sampling day, samples of worker ’s breathing zone air, of atmospheric air in the service station proximity, and of leaded and unleaded gasoline (50 ml) were collected. A controlled monitoring strategy was adopted, with a research assistant appointed to supervise the sampling and to record potential exposure modifying events. Samplings of both worker ’s breathing zone air and atmospheric air in the service station proximity were performed by charcoal tubes with annexed personal pumps. In the first sampling series (July 1994) an additional breathing zone air sample per worker was collected by a passive organic vapour monitor. Concentrations of benzene, toluene, xylenes and ethyl benzene in each sample series (breathing zone air, atmospheric air, and fuel) were determined by capillary GC/FID. The arithmetic and geometric means calculated on the entire set of 48 breathing zone air concentrations, along with their standard deviations, were used to describe the exposure profile of the monitored service station attendants as a group. In order to evaluate whether the overall mean exposure was a valid estimate of the individual workers exposure, a one-way ANOVA model with the worker code (twelve levels) as main factor was fitted to the data. The presence of a temporal pattern in the chemical composition of fuels during the study period was examined by regressing the benzene concentration of gasoline samples on a four level dummy variable “sampling series’’, where the first sampling set was taken as reference category. The effects of 8

potentially predictive variables on personal exposures to benzene were evaluated by simple and multiple linear regression analyses.

2.1.2 Results.-First survey (1991-92). Table 1 presents the relevant characteristics of the 111 filling stations included in the environmental survey and of their attendants. The yearly quantity of super premium gasoline sold per employee was higher in small stations. A similar pattern was found for the total quantity of fuel perfull-time employee dispensed during the sampling day. The daily quantity of fuel dispensed during the sampling days (service station averages) was highly correlated to the yearly workload. A mean level of 0.55 mg/m of benzene was measured (Table 2). As the concentrations of toluene and xylenes were highly correlated with the benzene levels (r = 0.87 and r = 0.83, respectively), only analyses referring to benzene are reported. The size of the station, although unrelated to the benzene level, acted as an effect modifier. No single variable was able to predict the benzene level in large stations. In small stations, on the contrary, the quantities of super premium gasoline and motor-bike fuel dispensed and the season remained significant predicting factors in the multivariate analysis; the overall explained variance was 12.3% (Table 3). In the subsample of 27 filling station attendants with available data on benzene concentration in the fuel (Lagorio S. et al., 1994), an increase of 0.01 mg/m3 in the personal benzene exposure per unit increase (100 g) in the absolute quantity of benzene in the fuel sold was estimated (Table 4). Second survey (1994-95) The relevant characteristics of the 12 filling station attendants surveyed are reported in Table 5. Two stations had a shelter covering the refuelling area. No vapour recovery system at the nozzle was available at any of the monitored work places. Table 2 reports the TWA concentrations of benzene and other aromatics in breathing zone air samples. A small degree of heterogeneity in benzene exposure between workers was observed as reflected by the percentile ratio BRo .95 = 2.5 (Table 7). Personal exposures to benzene and other aromatics were highly variable from day-to- day, as suggested by the elevated X. As a consequence, fifty-four repeats of benzene exposure measurements per worker would have been necessary to decrease the expected bias in an hypothetical exposure-response relationship from the observed 60% to 10% (Table 7). Atmospheric concentrations of benzene in the service station proximity were one order of magnitude lower than the concurrently measured personal exposures (Table 8) and there was a moderate correlation between the two measurement series (r = 0.39, pO.Ol). Leaded and unleaded gasoline samples did not differ with regard to their average content of benzene and other aromatics and significant reductions of the benzene concentration in the 1995 fuel samples in comparison with the first sampling series was observed (data not shown). The “daily benzene from dispensed fuel” (g), calculated as the weighted product of benzene concentration in leaded and unleaded gasoline samples (g/1) times the quantity of each type of fuel (Lagorio S. et al., 1993) pumped during the sampling day, was the strongest predictor of the workers ’ intensity of exposure to benzene. When the effects of daily benzene from dispensed fuel, sheltered refuelling area, 9

amount of fuel supplied to the station (with the possible concurrent activation of a vapour recovery system at the underground tank), and background benzene concentrations were simultaneously examined in a multivariate linear regression analysis, almost 70% of workers ’ personal exposure variability was explained by the model (Table 8 ).

2.1.3 Discussion - Service station employees are a relevant occupational category in Italy: at the 1981 census the fuel retail trade employed 60,869 individuals in 32,034 local units. Most service stations are small size facilities, run by household members, with the manager and his co-workers directly involved in car refuelling. The first environmental survey performed in 1991-92 was based on a random sample of stations, extended across one year in order to take into account both daily and seasonal sources of variability, and the number of determinations was large. These factors allow to extrapolate an index of cumulative exposure which could be considered a valid representation of the current exposure level of this group of workers as a whole. Despite the fact that several aspects of the study were well controlled, there was a high variability in the data that could not be explained by the covariates that were available for the analysis. The overall variance explained by the final multivariate model was only 12.3%. Therefore, a clearly defined categorisation of the subjects in groups with homogeneous and significantly different exposure levels was not achievable. The results of the study, however, suggest that the exposure pattern can be better described in small stations, where other sources of variability are more circumscribed; among subjects working in small stations, the quantity of super premium gasoline and of motor-bike fuel dispensed gave a statistically significant contribution to predict the exposure level. Several factors who might contribute to explain the residual variation in the measured exposure levels, such as different exposure situations, individual variability and measurement errors, were not considered in this study. The average benzene exposure in 1994-95 was lower than in 1992, most likely due to a reduction of daily sales of fuel (the average amount of gasoline dispensed per hour by the 12 service stations was 219 litres in 1992 vs 172 litres in 1994-95, p = 0.015) and to the decreased benzene concentration in dispensed fuel (24 g/1 in 1992, 2.8% v/v, versus 11 g/1 in 1994-95, 1.3% v/v). The relative concentrations of benzene, toluene, xylenes, and ethyl benzene in personal exposure series differed from those observed in the atmospheric air samples, pointing to substantially different pollution sources (gasoline vapoursfor breathing zone air samples and vehicle exhausts for background air samples). We found a strong correlation between benzene concentrations measured in breathing zone air samples concurrently collected by personal pump and passive vapour monitor. We observed a larger contribution of the within-worker in respect to the between- worker component of the overall variance in personal exposures to benzene and other aromatics, as expressed by the large X and by the relatively small bRo.95 values. This finding is consistent with previous studies reporting that day-to-day exposure variability 10

is prominent among outdoor workers and/or in intermittent working processes. Such elevated within-worker exposure variability yields to imprecise estimates of mean personal exposures. Thus, as an input to the planning of further surveillance programs, this study suggests that each subject should be monitored once a week along one year in order to get a precise estimate of his long-term average exposure. An alternative, less costly approach consists of a homogeneous exposure grouping strategy, suggested for reducing the attenuation of dose-response relationships in occupational epidemiology studies. However, the estimated bRo.95 for breathing zone air benzene concentrations, indicating a maximum of a threefold difference in mean individual exposures among the surveyed filling station attendants, implies that an efficient grouping strategy of these workers would be hard to derive in the absence of a priori knowledge about factors affecting exposure. To this regard, our data indicate as potentially relevant grouping variables the amount of gasoline dispensed, the benzene content of fuel, and the level of atmospheric benzene pollution. The occurrence of important exposure modifying events such as fuel deliveries to the station, although effective in increasing the daily average exposure level, might have an impact similar to the contrast of small vs large service stations, given the negative correlation between frequency of deliveries and amount of fuel supplied. As reasonably expected, we also observed a tendency towards increasing exposure levels in relation to the presence of sheltered refuelling areas or to the absence of vapour recovery systems at the underground tanks, although the statistical power of the study was too low to fully clarify these issues. Nevertheless, these findings have potentially relevant implications for the implementation of exposure control measures. In conclusion, filling stations attendants are a group occupationally exposed to aromatic hydrocarbons and these studies provide estimates of their current levels of exposure. From the point of view of the individual long-term average exposure estimation, the observed elevated day-to-day exposure variability calls for a large number of repeated exposure measurements in order to reduce exposure misclassification. A number of relevant exposure determinants, however, were documented, which can be translated in homogeneous exposure grouping strategies.

References LAGORIO S., FORASTIERE F„ IAVARONE I., VANACORE N„ FUSELLI S., CARERE A. Exposure assessment in a historical cohort of filling station attendants. Int J Epidemiol. 1993, 22 (2): s51-s56.

LAGORIO S., FUSELLI S., IAVARONE I., VANACORE N., CARERE A. Benzene exposure in service station attendants and composition of gasoline. Med Lav. 1994,85: 412-421 (English abstract).

LAGORIO S., IAVARONE I., IACOVELLA N., PROIETTO A.R., FUSELLI S., TURRIO BALDASSARRI L., CARERE A. Variability of benzene exposure among filling station attendants. Occup Hyg. 1997, 4: 15-30. 11

Table 1.- Characteristics of the 111 filling stations and their attendants included in the exposure assessment survey, by size of the station (Rome, 1991-92).

Station size Large Small

Variable Obs Mean 95% Cl Obs Mean 95% Cl

Employees (n°) 35 2.4 2.0-2.8 75 1.4 1.3-1.5

Age (yr) 36 43.9 39.8-47.9 73 46.9 44.0-49.8

Length of employment (yr) 36 18.5 14.4-22.5 75 19.9 16.9-23.0 Storage (m3) 34 14.0 12.1-16.0 72 10.8 9.7-11.9

Sales/year SPG (10001) 33 625.5 516.9-734.1 68 554.1 488.0-620.2 Sales/year ULG (10001) 31 36.4 26.0-46.8 38 26.6 20.2-33.0 Sales/year MBF (10001) 18 11.0 7.2-14.8 47 13.9 8.4-19.4

Sales/year D (10001) 6 640.5 379.8-901.2 6 432.0 143.2-720.8 Sales/year fuels (10001) 33 728.1 631.3-933.0 68 616.7 541.9-691.5

Sales/year SPG/fte (10001) 33 316.6 264.6-368.7 68 409.7 357.5-461.9

Vehicles filled/day (n°) 77 77.9 63.5-92.4 148 79.5 72.5-86.4 Sales/day SPG (1001) 217 12.1 11.2-13.0 483 11.9 11.3-12.5 Sales/day ULG (1001) 165 1.7 1.5-2.0 274 1.5 1.4-1.7 Sales/day MBF (10 1) 161 2.5 2.1-2.8 383 3.6 3.3-4.0 Sales/day D (1001) 35 20.0 12.5-27.4 48 13.6 11.3-15.8

Sales/day fuel (1001) 217 16.8 14.8-18.8 485 14.4 13.6-15.1 Sales/day SPG/fte (1001) 215 9.6 8.5-10.8 474 11.3 10.7-11.9

Storage = capacity of the super premium gasoline underground tank; SPG = super premium gasoline; ULG = unleaded gasoline; MBF = motor-bike fuel; D = diesel; fte = full-time employee; OBS = number of observations; MEAN = arithmetic mean; 95% Cl = 95% confidence interval.

Table 2.- Concentrations of some aromatic hydrocarbons in breathing zone air samples (mg/m 3 , 111 filling station attendants, Rome 1991-92). Chemical Obs Mean SD Median Min Max GMean G SD Benzene 703 0.55 2.46 0.11 0.001 28.02 0.12 3.82

Toluene 703 0.70 3.14 0.17 0.040 33.77 0.18 3.41

Xylenes 703 0.32 1.21 0.09 0.003 15.37 0.10 3.31

Mean = arithmetic mean; SD = standard deviation of the arithmetic mean; G-Mean = geometric mean; G SD = geometric standard deviation. 12

Table 3.- Estimated B coefficients from the multiple regression analysis relating logarithmic concentrations of benzene with the sales of fuel during the sampling day and the season in small size stations (486 personal samples from 75 filling station attendants).

Variable B SEB P

Sales of SPG/day (1001) 0.0579 0.009 <0.001

Sales ofMBF/day (101) 0.0418 0.194 0.032

Season Spring reference Summer 0.3467 0.178 0.052 Autumn 0.2998 0.153 0.050

Winter 0.5479 0.152 <0.001

(Constant) -3.1804 0.163 <0.001 R2 = 0.123

SPG = super premium gasoline; MBF = motor-bike fuel sold; B = slope of the regression line; SE B = standard error of the B coefficient; p = significance of Student's t statistic; R2 = coefficient of determination.

Table 4.- Intensity of benzene exposure (yearly averages, 8h TWAs, mg/m 3 ) as a function of the total quantity of benzene in leaded and unleaded gasoline sold during the sampling day (27 service stations). Simple linear regression analysis.

Variabile B ES (B) P Benzene in dispensed gasoline (100 g) 0.0120 0.0024 <0.0001

(Constant) -2.5561 1.1583 R2 = 0.4961 p(F) = <0.0001

Benzene in dispensed gasoline = [benzene concentration in fuel (g/1) - gasoline dispensed during the sampling day (1)/100]; B = slope of the regression line; SE B = standard error of the B coefficient; p = significance of Student's t statistic; R2 = coefficient of determination. Table 5.- Relevant characteristics of filling station attendants and service stations included in the survey(Rome, 1994-95).

Variables Obs Mean SD Min Max GMean GSD Workers: Age (years) 12 44.5 12.0 30 62 43.0 1.3 Length employment (years) 12 24.1 13.6 7 43 19.7 2.0 Service stations: Employees, full-time equivalents (#) 12 1.4 0.5 1 2.5 1.3 1.4 Gasoline dispensed/worker/year (1000 1) 10 529.4 173.1 352.00 880 507.8 1.4 Fuel deliveries/month (#) 12 10 3.3 6 15 9.6 1.4 Gasoline supplied/delivery (10001) 12 7.3 4.0 4 18 6.6 1.6 Workload indices: Vehicles refueled /hour (#) 48 14.5 6.9 2 34 12.8 1.7 Gasoline dispensed/hour (1) 48 171.7 77.7 37 424 154.5 1.6 Exposure modifying events: Gasoline dispensed in Close proximity (%) 48 87% 12% 48% 100% - - Refueling close to the tank (%) 48 93% 6% 76% 100% - - Refueling with vapor leakage (%) 48 10% 6% 0% 21% - - Refueling with spills or overflow (%) 48 48% 12% 27% 81% - - Refueling with splashes on overalls (%) 48 1% 2% 0% 8% - - Refueling with engine control (%) 48 4% 4% 0% 12% - - Gasoline supplied by tankers (1000 1) 8 8.00 4.78 3.00 18.00 6.90 1.77

Obs = number of observations; Mean = arithmetic mean; SD = standard deviation of the arithmetic mean; Min = minimum; Max = maximum; GMean = geometric mean; GSD = standard deviation of the geometric mean. Table 6.- Distribution of exposures to benzene and other aromatics (TWA, pg/m3 ) among filling station attendants (Rome, 1994-95).

Variables Obs Mean SD Min Max GMean GSD

Breathing zone air samples by personal pump:

Benzene 48 315.62 210.28 94 959 262.43 1.82

Toluene 48 565.23 311.74 181 1638 497.70 1.65 Xylene 48 339.02 172.87 115 1099 304.90 1.55 Ethyl benzene 48 71.38 41.71 26 244 62.18 1.67 Breathing zone air samples by passive monitor: Benzene 12 449.17 239.45 221 980 399.41 1.63 Toluene 12 813.00 387.68 399 1693 742.48 1.54 Xylene 12 637.67 198.35 455 1130 614.00 1.31 Ethyl benzene 12 98.75 39.83 58 194 92.76 1.43

Table 7.- Analysis of the variance components (within- and between-worker) for log transformed personal exposure to benzene and other aromatics, and consequences of the misclassification of the worker’s average personal exposure (12 filling station attendants, Rome 1994-95).

Exposure k N bRo.95 wGSD bGSD X l-(b/P) E (k)

Benzene 4 48 2.466 1.754 1.259 5.962 0.60 54 Toluene 4 48 2.339 1.571 1.242 4.340 0.52 39 Xylenes 4 48 1.509 1.541 1.111 17.000 0.81 153

Ethyl benzene 4 48 1.783 1.632 1.159 11.034 0.73 99

k = number of repeated measurements per worker; N = number of total measurements; bRo 95 = ratio of the 97.5th and 2.5th percentiles of the lognormally distributed individual average exposures; WGSD = geometric standard deviation of the within-worker distribution (i.e. differences in exposure levels from day to day); BGSD = geometric standard deviation of the between-worker distribution (i.e. differences in average exposure among workers); X = variance ratio of within- and between-worker variance; b/fi: ratio between observed and true coefficient estimated from the regression of a continuous dependent variable (effect indicator) on an imperfectly measured explanatory variable (exposure indicator); l-(b/(B) = 1- [(l+X/k)-l]: expected bias in the hypothetical regression coefficient; E(k) = [b/(3(l-b/p)-l]X: number of repeats/worker required to reduce the expected bias in the regression coefficient to a maximum of 10% (b/p=0.90), given the observed value of X.

Table 8.- Change in benzene exposure (In pg/m3 ) among filling station attendants per unit increase of different covariates, estimated by multiple linear regression analysis (47 observations, Rome 1994-95).

Variable B SE (B) P Daily benzene from dispensed fuel (In g) 0.5676 0.0863 <0.0001 Sheltered refueling area (yes vs no) 0.5334 0.1390 0.0004

Fuel supplied by tankers (10001) 0.0483 0.0165 0.0056 Vapor recovery system (yes vs no) -0.3288 0.2828 0.2517 Atmospheric benzene (In pg/m3) 0.3154 0.1286 0.0185

(Constant) -0.6319 0.8453 R2 = 0.6977 (pcO.OOOl)

B = slope of the regression line; SE (B) = standard error of the B coefficient; p = significance of the Student’s t statistic; R2 = coefficient of determination; Daily benzene from dispensed fuel = E[( benzene concentration in leaded gasoline x dispensed leaded gasoline) + (benzene concentration in unleaded gasoline x dispensed unleaded gasoline)]; Atmospheric benzene = benzene air concentration 70 m away from the service station, windward. 16

2.2 Biomonitoring study

Exposure to gasoline vapours is classified by the International Agency for Research on Cancer as possibly carcinogenic to humans (IARC, 1989 Vol. 45-46). Previous studies suggested an increase of cytogenetic damages in peripheral lymphocytes of workers in the petrochemical industry (Zhou X. et al., 1986 - Sobti R.C. et al, 1993) and in gasoline station attendants (Hogstedt B. et al., 1991 - Santos-Mello R et al, 1992). However, the occurrence of mixed and variable pattern of exposure, as well as the lack of quantitative information on exposure levels, prevent any firm conclusion from the above studies on the genetic effect of occupational exposure to fuels. In the framework of this research project, an investigation was carried out on the possible association between occupational exposure to fuels and genetic damage, using different experimental approaches such as cytogenetics, FISH, urinary excretion of modified bases, Comet assay. In all cases, the biomonitoring studies were coupled with detailed exposure assessment, in order to unravel the possible association between exposure to benzene and other petrochemicals and biological effects.

2.2.1 Methods.- Gas station attendants from the area of Rome were enrolled in the study. Twenty-three and twelve station male attendants were surveyed in the first and second sampling, respectively. The absence of possible confounders related to health status or life style, such as recent diagnostic X-rays, use of pharmaceutical drugs, smoking habits and high alcohol consumption, was assessed through personal interviews. Age-paired, healthy persons with no occupational exposure to fuels or other chemicals served as controls. Personal exposure to benzene and alkylbenzenes in station attendants was monitored by repeated air samplings in the breathing zone and urinary benzene and trans-muconic acid (t-MA) determinations, as described in the previous section. Blood lead level was measured at the time of blood collection on one spot sample per subject by atomic absorption spectrophotometry. For cytogenetic analyses, whole blood cultures cultures were set up for the analysis of SCEs, chromosomal aberration (CAs) and micronuclei following standard procedures (Degrassi F. et al, 1984 - Surralles J. et al, 1992). Fluorescence in situ hybridization (FISH) techniques were applied on slides prepared from the second blood sampling following procedures previously described (Zijno A. et al., 1996 - Zijno A. et al., 1996). In order to detect the frequency of micronuclei containing whole chromosomes, binucleated cells were hybridized with a biotinylated probe (ONCOR) specific for the alphoid sequences of centromere of all human chromosomes. Specific chromosome missegregation was evaluated by FISH with probes for centromere sequence of the studied chromosomes. Two mixtures, each containing probes for two different chromosomes, were applied on both G0/Gi and binucleated lymphocytes. The tandem labelling procedure (Eastmond D A. et al, 1993) was used to detect and quantify aneuploidy of chromosome 1 and breakage involving the centromeric regions of chromosome 1 in interphase lymphocytes 48 h after PHA stimulation. For this purpose, two different probes for chromosome 1 were used: an alpha satellite biotinylated probe 17

to label the centromeric region (lcen), and a classical satellite digoxigenated probe to label the pericentromeric region (lql2). Slide hybridization was performed according to standard procedures (Rupa D.S. etal, 1997). Small aliquots of blood from individuals enrolled in the second sampling, were used to detect and quantitate DNA single and double strand breaks in unstimulated peripheral lymphocytes by means of the single cell gel electrophoresis (SCGE or Comet) assay with the alkaline protocol (Singh N.P. et al, 1988). One hundred cells per individual, stained with ethidium bromide, were scored under a Leitz fluorescence microscope. Comet tail length was taken as a measure of DNA damage. The Synoptics Casys software (Cambridge, UK) was used for the comet image analysis. A random sample of 65 current filling station attendants was selected, among all service stations, for monitoring of the urinary levels of 8-hydroxyguanosine (8-OHdG). A spot sample of urine was collected during the second half of the workshift. Levels of 8-OHdG were determined by high-performance liquid chromatography (HPLC) with coupled columns according to a published procedure (Tagesson C et al., 1992). The mean values of potentially predictive variables (age, blood lead level, length of employment, smoking habits) and frequency of genetic end-points were compared by one-way analysis of variance. The Pearson x2 test was used to evaluate the statistical significance of the differences in percentages of CAs between exposed and controls. The interrelationships between age and the outcome variables at study were investigated by simple linear correlation analyses. As the frequency of micronuclei was low, the average square root transformation was applied to individual measurements in order to stabilize the variance (Whorton E.B., 1985). The arcsin transformed individual percentages of cells containing chromosomal aberrations were used in these analyses (Yardley-Jones A. et al., 1990). Relative risks (RR) of selected outcomes (prevalence of cells with chromosomal aberrations or with high frequency of SCEs) among "exposed" vs "referents" were estimated as the ratios of the prevalence odds, controlling for potential confounders by logistic regression analysis. Blood lead concentrations were categorised around the 33° (7.5 gg/dl) and the 66° percentiles (10 pg/dl) of the overall distribution, and the lowest exposure class was taken as reference. As to benzene exposure, controls were taken as reference and filling station attendants were categorised around the 50° percentile of the distribution (<0.2 and >0.2 mg/m3). Finally, a multiple linear regression analysis was used to study the effect of several variables on the measured level of 8- OHdG. All analyses were carried out with the SPSS/PC statistical package.

2.2.2. Results.- The relevant characteristics of the subjects participating to the first biomonitoring survey are reported in Table 1 Service station workers showed an average blood lead level significantly higher than referents, in agreement with their expected greater exposure to vehicle exhausts. A non statistically significantly increased prevalence of cells with structural CAs (gaps excluded) was recorded in exposed compared to controls (1.97% vs 1.46 %). However, taking the prevalence of CA positive cells among unexposed control subjects as reference, a significant upward trend of cells with aberrations for the medium and high 18

benzene exposure categories was observed (Table 2). No association between CA frequency and blood lead level was found. SCE frequency was not significantly increased among filling station attendants compared with controls (4.73 vs 4.48 SCE/cell). Neverthless, a statistically significant excess risk of HF-SCE cells (cells with >6 exchanges) was observed among filling station attendants (Table 3). The risk of HF-SCE cells increased at increasing blood lead level (%2 for trend = 27.8, p<0.001), while no clear relationship between prevalence of HF- SCE cells and personal exposure to benzene was found (data not shown). The evaluation of the effects of benzene exposure in the second sampling was mainly focussed on the investigation of chromosome segregation abnormalities and aneuploidy in lymphocytes from 12 gas station attendants and 12 paired controls. Fluorescence in situ hybridization techniques were applied in order to detect (i) centromere positive micronuclei in binucleated lymphocytes cultivated 66 hours, (ii) specific chromosome aneuploidy in mononucleated lymphocytes cultivated 24 hours, (iii) specific chromosome aneuploidy and (iv) missegregation in binucleated lymphocytes cultivated 66 hours. Moreover, the tandem labelling approach was applied for the simultaneous detection of hyperploidy and breakage of chromosome 1 in the sensitive heterochromatic pericentromeric region of lymphocytes cultivated 48 hours after stimulation. The main characteristic of the studied populations are indicated in Table 4. The analysis of binucleated lymphocytes did not reveal any differences in the frequency of total micronuclei and in the percentage of centromere positive micronuclei. These data are summarized in Table 5. Specific chromosome malsegregation was evaluated in interphase cells using FISH methods with chromosome specific centromeric probes on both mononucleated and binucleated lymphocytes. Chromosome malsegregation occurred in vivo was investigated evaluating the frequency of hyperdiploid lymphocytes harvested 24 hours after PHA stimulation. According to the time course of lymphocyte cell cycle in vitro, at this time no mitosis have occurred, so aneuploid cells are only consequent of abnormal chromosome segregation occurred in vivo. Furthermore, in vivo effects were also investigated in binucleated lymphocytes harvested at 66 hours. Binucleated cells containing an even number of signals, higher than the normal chromosome diploid set, were classified as aneuploid binucleated cells arisen by pre-existing aneuploid cells present in the lymphocyte population before PHA stimulation. Data on hyperploidy of chromosomes X, 18, 7 and 11 in mononucleated and binucleated cells, in relation to benzene exposure or smoking habits, are shown in Tables 6 and 7, respectively. No significant difference in the frequency of hyperdiploid cells was observed in the exposed vs control populations or in smoker individuals vs former smokers and non smokers, either in mononucleated or in binucleated cells . It is conceivable that benzene exposure may produce, in quiescent cells, cellular damage able to disturb chromosome segregation after in vitro stimulation. In order to investigate this possibility, chromosome missegregation was studied in vitro in binucleated cells of benzene exposed individuals. Both specific chromosome loss and 19

non-disjunction were determined. The relative susceptibility of chromosomes to undergo missegregation invitro, as detected in binucleated cells, followed the order: chromosome X > chromosome 11 > chromosome 7 > chromosome 8. The analysis of results (Tables 8 and 9) failed to show any differences in relation to the exposure status and smoking habits. Statistical analyses of data highlighted significant correlations between the endpoints investigated. Missegregation in vitro and hyperploidy in binucleated cells for the same chromosomes were strongly correlated each other for both chromosome X (p < 0.001) and chromosome 18 (p < 0.01) and slightly correlated for both chromosome 7 (p = 0.067) and chromosome 11 (p = 0.051). An important factor affecting the outcome of both micronuclei and chromosome missegregation was represented by the age of donor. Regression analysis showed that age significantly affects the fidelity of chromosome segregation in vitro as well as in vivo. Concerning the exposure parameters, no clear correlations was observed between benzene exposure markers (air benzene, urinary trans-muconic acid and urinary benzene) and micronuclei or chromosome missegregation rates. Interestingly, blood lead level was significantly correlated with several cytogenetic end-points (Table 10). Also the analysis of hyperploidy of chromosome 1 in tandem labelled slides did not show exposure related excess of aneuploid types (data not shown). However, the analysis of breakages occurring in the pericentromeric region of chromosome 1 by tandem labelling demonstrated a significant (p<0.01) excess of breaks in cultured lymphocytes of station attendants (Figure 1). Interestingly, the incidence of breaks was significantly correlated to the urinary benzene level (p< 0.001), reinforcing the hypothesis of a mechanistic role for benzene exposure. The extent of DNA damage in unstimulated peripheral lymphocytes was also measured by SCGE in gasoline station attendants enrolled in the second sampling. Significantly greater average comet tail lengths were recorded in exposed compared with control individuals (4.66 vs 2.96 pm), possibly reflecting an excess of DNA strand breaks and/or alkali-labile sites. Moreover, the comparison of the distributions of comets according to tail length highlighted a clear prevalence of heavily damaged cells (with tail lenght >15 pm) among station attendants (Figure 2). A mean level of 1.36 pmol (standard deviation = 0.49) of 8-OHdG per mol of creatinine was measured in the sample of 65 filling station attendants. The excretion was not affected by relevant characteristics of the subject, except the age (Table 11). A statistically significant increase of 8-OHdG excretion in relation to increasing personal exposure to benzene was found, adjusting for age, length of employment, smoking habits, and exposure to diagnostic x-rays (Table 12). Remarkably, excretion of 8-OHdG was not associated to personal exposure to toluene and xylenes, although the concentrations of the three aromatic hydrocarbons were highly correlated (Lagorio S. et al, 1994).

In conclusion, the analysis of multiple genetic end-points in people with low occupational exposure to benzene (0.1 - 0.5 ppm, i.e. 0.3 - 1.6 mg/m3 as 8 h TWA) and 20

other petroleum components demonstrated the presence of low, but significant excess of chromosome structural damage and DNA breaks in peripheral lymphocytes. No significant effect on chromosome segregation, either in vitro and in vivo, was exerted by chemical exposure. Conversely, chromosome malsegregation rate was significantly associated with the age of subjects, which was confirmed as the most relevant endogenous factor affecting the fidelity of chromosome segregation. The extent of DNA damage related to exposure was low, requiring careful control of possible confounders and matching of exposed and control group for its detection.

References

DEGRASSI F„ FABRI G., PALITTI F„ PAOLETTI A., RICORDY R., TANZARELLA C. Biological monitoring of workers in the rubber industry. I. Chromosomal aberrations and sister-chromatid exchanges in lymphocytes of vulcanizers, Mutation Res. 1984,138: 99-103.

EASTMOND D.A., RUPA D.S., CHEN H., HASEGAWA L.S. Multicolor fluorescence in situ hybridization with centromeric DNA probes as a new approach to distinguish chromosome breakage from aneuploidy in interphase cells and micronuclei. In Springer-Verlag: Chromosome Segregation and Aneuploidy, B.K. Vig (Ed.). Berlin Heidelberg, 1993. pp. 377-390.

HOGSTEDT B., HOLMEN A., KARLSSON A., RAIHLE G„ NILLIUS K„ VESTLUND K. Gasoline pump mechanics had increase frequencies and sizes of micronuclei in lymphocytes stimulated by pokeweed mitogen, Mutation Res. 1991, 263: 51-55.

International Agency for Research on Cancer. Occupational exposures in petroleum refining; crude oil and major petroleum fuels. 1ARC Monographs on the Evaluation of the Carcinogenic Risks to Humans, vol. 45, IARC, Lyon, 1989.

International Agency for Research on Cancer. Diesel and gasoline engine exhausts and some nitroarenes. IARC Monographs on the Evaluation of the Carcinogenic Risks to Humans, vol. 46, IARC, Lyon, 1989.

LAGORIO S., TAGESSON C., FORASTIERE F„ IAVARONE I., AXELSON O., CARERE A. Exposure to benzene and urinary concentrations of 8-hydroxydeoxyguanosine, a biological marker of oxidative damage to DNA. Occup. Environ. Med. 1994, 51: 739-743.

RUPA D.S., HASEGAWA L.S. EASTMOND D A. Detection of chromosomal alterations affecting the lcen-lql2 region in irradiated granulocytes and lymphocytes by multicolour FISH with tandem DNA probes, Mutagenesis 1997, 12: 195-200.

SANTOS-MELLO R., CAVALCANTE B. Cytogenetic studies on gas station attendants, Mutation Res. 1992, 280: 285-290.

SINGH N.P., MC COY M.T., TICE R.R., SCHNEIDER E.L. A simple technique for quantitation of low levels of DNA damage in individual cells, Exp. Cell Res. 1988, 175: 184-191. 21

SOBTI R.C., BHARDWAJ D.K. Cytogenetic damage and occupational exposure: II. exposure to petroleum exhaust, Mutagenesis 1993, 8: 101-3.

SURRALES J„ CARBONELL E„ MARCOS R., DEGRASSI F„ Antoccia A„ TANZARELLA C. A collaborative study on the improvement of the micronucleus test in cultured human lymphocytes, Mutagenesis 1992, 7: 407-410.

TAGESSON C., KALBERG M., LEANDERSSON P. Determination of urinary 8-hydroxyguanosine by couple-column HPLC with electrochemical detection: a noninvasive assay for in vivo oxidative DNA damage in humans. Toxicology Methods 1992, 1: 242-251.

WHORTON E.B. Some experimental design and analysis considerations for cytogenetic studies, Environ. Mutagen. 1985, 7: 9-15.

YARDLEY-JONES A., ANDERSON D„ LOVELL D.P., JENKINSON C.P. Analysis of chromosomal aberrations in workers exposed to low level benzene, British J. Ind. Med. 1990, 47: 48-51.

ZHOU X., LI L., CUI M., YU r., LI L., YAN Z. Cytogenetic monitoring of petrochemical workers, Mutation Res. 1986, 175: 237-242.

ZIJNO A., LEOPARDI P., MARCON F., CREBELLI R. Sex chromosome loss and non-disjunction in women: analysis of chromosome segregation in binucleated lymphocytes. Chromosoma 1996, 104: 461- 467.

ZIJNO A., MARCON F., LEOPARDI P., CREBELLI R Analysis of chromosome segregation in cytokinesis-blocked human lymphocytes: non-disjunction is the prevalent damage resulting from low dose exposure to spindle poisons. 1996. Figure

1: Breaks/1000 cells between Frequency frequencies gasoline of

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>8-12 controls >12-16 >16-20 >20-24 >24-28 Tail Moment values (microns)

Figure 2: Results of the single cell gel electrophoresis assay on a total of 1,200 cells per group. It is shown the distribution of comets according to tail lenght. Undamaged nucleoids, with tail lenght <5 pm, are not shown. 24

Table 1.- Characteristics of filling station attendants and age-matched referents enrolled in the first sampling.

Variable Exposed Controls P N° Mean ±SE Range N° Mean (±SE) Range

Age (years) 23 45.8±2.5 28-64 24 44.2±2.6 22-62 0.652

Benzene (mg/m3) 21 1.5±0.7 0.1-13.1 - - -

Blood lead (pg/dl) 22 10.7±0.8 5.6-19.9 24 8.4± 0.7 2.8-15.0 0.036 Employment (years) 23 22.4±2.3 3-42 - - -

Table 2.- Relative risk (RR) of cells with chromosomal aberrations (CA, gaps excluded) in relation to average yearly exposure to benzene.

Benzene exposure5 CAs RR 95% Cl 0 >1 Total

None 4443 66 4509 1.00 - Low 2019 36 2055 1.21 0.80-1.82 High 1807 43 1850 1.67 1.12-2.48 Total 8269 145 8414

X2 trend = 5.57 p = 0.018

^Benzene exposure: none for referents; low = filling station attendants with <0.2 mg/m3 (8h TWA, average yearly exposure); high = filling station attendants with >0.2 mg/m3. RR = prevalence odds ratio adjusted for age and proliferation index score (PRI) by logistic regression analysis. 95% Cl = 95% confidence interval 25

Table 3.- Relative risk (RR) of cells with high SCE frequency (HF-SCE cells) in station attendants and unexposed referents.

Exposure SCE/cell RR 95% Cl

<6 >6 Total

Controls 1518 577 2095 1.00 .

Exposed 1227 575 1802 1.30 1.12-1.51 Total 2745 1152 3897

RR = prevalence odds ratio adjusted for age and proliferation index score (PRI) by logistic regression analysis. 95% Cl = 95% confidence interval.

Table 4.- Characteristics of the studied populations enrolled in the second sampling

Exposed (N= 12) Controls (N= 12) Total (N= 24)

Age ± S.E. 44.75±3.46 45.33±3.06 45.04±2.26 Smokers 3 2 5 Former smokers 4 3 7 No smokers 5 7 12 t-MA (pg/g creatinine) 116.3±25.6 82.5±20.2 97.9±16.1 Benzene (mg/m3) 0.32±0.03 Employment (years) 24±4 26

Table 5.- Micronucleiand centromere positivemicronuclei in binucleated cells.

Total micronuclei Centromere positive micronuclei - (%<*S.E.) (%±S.E.)

Exposed (N = 12) 13.54±1.34 40.37*3.13 Controls (N= 12) 16.92*1.19 43.77*2.72

Smokers (N = 5) 12.00*1.56 39.00*6.35 Former smokers (N= 7) 14.36*1.74 44.86*1.83 Non smokers (N = 12) 17.08*1.28 41.73*3.12

Total (N = 24) 15.23*0.94 42.07*2.06

Table 6.- Specific chromosome hyperdiploidy in mononucleated cells

Chromosome X Chromosome Chromosome7 Chromosome (%e*S.E.) 18 (%fffcS.E.) 11 (%c*S.E.) (%as.E.)

Exposed (N= 12) 1.75*0.52 2.58*0.52 0.52*0.20 1.31*0.08 Controls (N = 12) 2.42*0.48 4.71*0.88 1.29*0.36 1.62*0.39

Smokers (N= 5) 1.40*0.43 3.40*0.90 0.50*0.39 1.70*0.58 Former (N = 7) 2.79*0.63 3.07*0.69 1.04*0.54 1.81*0.49 smokers Non smokers (N = 12) 1.96*0.57 4.08*0.97 1.00*0.28 1.17*0.30

Total (N = 24) 2.08*0.35 3.65*0.55 0.91*0.22 1.47*0.24 27

Table 7.- Specificchromosome hyperdiploidy in binucleated cells

Chromosome X Chromosome Chromosome 7 Chromosome (%fftS.E.) 18 (%octS.E.) 11 (%o±S.E.) (%«tS.E.)

Exposed (N = 12) 1.17±0.27 0.67±0.21 1.11*0.37 1.62*0.49 Controls (N = 12) 1.29*0.40 0.58±0.27 1.25*0.35 1.64*0.48

Smokers (N = 5) 1.40*0.60 0.40*0.24 1.56±0.69 1.20*0.73 Former (N = 7) 1.07*0.25 0.14±0.09 0.57±0.37 1.90±0.67 smokers Non smokers (N= 12) 1.25*0.40 1.00±0.28 1.38±0.34 1.64*0.48

Total (N = 24) 1.23±0.24 0.62±0.17 1.18±0.25 1.63±0.33

Table 8.- Micronuclei and specific chromosome X and 18 missegregation in binucleated cells

Total Chrom. X Chrom. X Chrom. X Chrom. 18 micronuclei non-disj. loss misseg. misseg. (%dsS.E.) (%o±S.E.) (%«±S.E.) (%«tS.E.) (%ftSM.)

Exposed (N= 12) 7.62±1.15 3.62±0.79 2.25±0.51 5.87±1.20 1.08*0.27 Controls (N= 12) 9.96±1.13 4.83±0.77 2.42±0.50 7.25±1.09 1.62*0.45

Smokers (N = 5) 9.60±0.94 5.20±1.63 3.30±0.77 8.50±2.32 1.80*0.51 Former (N = 7) 9.79±1.78 3.64±1.27 2.57±0.75 6.21±1.81 1.07*0.61 smokers Non smokers (N = 12) 7.87±1.25 4.17±0.55 1.79±0.41 5.96±0.83 1.33*0.35

Total (N = 24) 8.79±0.83 4.23±0.55 2.33±0.35 6.56±0.81 1.35*0.26 28

Table 9.- Micronucleiand specific chromosome 7 and 11 missegregation in binucleated cells

Total Chrom. 7 Chrom. 11 micronuclei misseg. misseg. (%o±S.E.) (%o±S.E.) (%o±S.E.) fS II

Exposed 10.06±1.34 2.29±0.63 3.58±0.66 cs Controls II 12.67±2.11 2.08±0.67 2.92±0.83

Smokers (N = 5) 8.24±0.72 2.40±0.68 4.12±0.88 Former smokers (N = 7) 13.63±2.00 1.86±0.96 3.97±1.21 Non smokers (N = 12) 11.34±2.14 2.29dt0.69 2.47±0.67

Total (N = 24) 11.36±1.25 2.19±0.45 3.25±0.52

Table 10.- p value for correlation between exposure and biological markers

Air benzene Urinary benzene Urinary t-MA Blood lead (mg/m3) (ug/g creatinine) (Ug/g creatinine) (ug/g) Micronuclei 0.44 (-) 0.12 (-) 0.17 0.44 Cen. pos. Mn (-) 0.01 (-) 0.33 0.23 0.02 Miss X (-) 0.01 (-) 0.06 (-) 0.20 0.00 Miss 18 (-) 0.12 (-) 0.01 (-) 0.07 0.00 Miss 7 0.21 (-) 0.27 0.43 0.05 Miss 11 0.07 0.09 0.35 0.27 Hyperp. X (-) 0.01 (-) 0.31 (-) 0.29 0.01 Hyperp. 18 (-) 0.09 (-) 0.12 (-) 0.14 0.00 Hyperp. 7 (-) 0.03 (-) 0.09 (-) 0.03 0.00 Hyperp. 11 (-)0.47 0.36 (-) 0.16 0.05

(-): negative correlation Micronuclei: micronuclei analyzed in binucleated lymphocytes stained by propidium iodide. Cen. pos. Mn.: Percentage of centromere positive micronuclei detected in binucleated lymphocytes. Miss X, 18, 7, 11: Chromosome X, 18, 7, 11 missegragation in binucleated lymphocytes. Hyperp. X, 18, 7,11: ChromosomeX, 18,7,11 hyperdiploidy in binucleated lymphocytes. In bold p value 5 0.05. 29

Table 11.- Arithmetic mean concentrations of urinary 8-hydroxydeoxyguanosine measured among 65 filling station attendants by relevant characteristics of the subjects.

Variable N° (%) Urinary 8-OHdG (SD) P value (pmol/mol creatinine) Age (years): <39 21 (32.3) 1.44 (0.56) 40-54 22 (33.8) 1.13 (0.30) >55 22 (33.8) 1.52 (0.52) 0.020

Length of employment (years): <10 23 (35.4) 1.27 (0.49) >10 42 (64.6) 1.41 (0.49) 0.284

Smoking habits: Non-smokers 22 (33.8) 1.32 (0.50) Ex-smokers 10 (15.4) 1.29 (0.62) Smokers 33 (50.8) 1.41 (0.46) 0.740

Smoking intensity (cigarettes/day): <10 11 (66.2) 1.41 (0.35) >10 22 (33.8) 1.41 (0.51) 0.969

Exposure to x rays (previous 2 y): No 42 (64.6) 1.42 (0.54) Yes 23 (35.4) 1.26 (0.39) 0.218

Overall 65 (100.0) 1.36 (0.49) -

P value is by analysis of variance between groups. 30

Table 12.- Urinary excretion of 8-hydroxydeoxyguanosine (fjmol/mol creatininej by personal exposure to benzene and other relevant characteristics of the subjects (multiple linear regression analysis).

Variable B SE (B) P value Age (years): <40 reference 40-54 -0.417 0.164 0.014 >55 -0.216 0.198 0.281 Lenght of employment (yrs) <10 reference >10 0.312 0.175 0.081

Smoking intensity (cig/day): 0 reference 1-10 0.025 0.019 0.879 >10 0.167 0.144 0.249

Exposure to x rays No reference Yes -0.132 0.122 0.285

Benzene exposure 0.151 0.060 0.014

(Constant) 1.591 0.176 R2 = 0.265

B = slope of the regression line; SE B = standard error of the B coefficient; p value is by Student's t test; Benzene exposure = In of the yearly average benzene concentration (mg/nP); Constant = the B coefficient of the constant represents the estimated intercept value; R2 = coefficient of determination. 31

2.3. Mortality study

The hazard posed by exposure to benzene via gasoline vapours and exhausts is of major concern, due to the great number of workers employed in petroleum distribution trades and to the relevant contribution of such sources to the pollution burden in urban environments (Infante P.F. et al., 1990 - Mehlman M.A. et al., 1991). While in the US and in northern Europe self-service stations predominate, Italy and other southern European countries still employ large numbers of workers in gasoline retail trades. In this section we describe the mortality experience of a cohort of filling station attendants from a region of central Italy.

2.3.1. Methods.- A nation-wide survey of service stations was carried out in Italy in 1980. Detailed data for the Latium Region were obtained and managers who were still alive on 1 January 1981 were considered eligible for the study (2,665 stations and managers out of 3,272 original records; 81.4%). A full description of the study design can be found in the published paper (Lagorio S. et al., 1994), and only a brief summary is presented herein. Follow-up extended from 1981 through 1992. Vital status and causes of death were ascertained through the Registry Office of the municipalities of residence and death (Lagorio S. et al. , 1987). For the calculation of person-years at risk each subject was considered from 1 January 1981 until the end of the study period or date of death. Those lost to follow-up were considered alive by the end of the study period. Standardised Mortality Ratios (SMRs) and their 90% Confidence Intervals (90% Cl) were used to compare the mortality experience of the cohort with that of the Regional population. Information on duration of employment at entry, along with a series of indicators of workload, were available for all cohort members from the 1980 survey. No vapour recovery system has been enforced in Italy, and the relative quantity of fuel sold has remained relatively stable. Due to the characteristics of Italian service stations, the yearly average quantity of gasoline sold per full-time employee may be considered as an indicator of the average intensity of exposure experienced by the manager at refuelling. As observed in an concurrent exposure assessment survey (Lagorio S. et al, 1993) workers in small-size stations with higher sales of super premium gasoline experience higher levels of exposure, and we decided, consequently, to examine in detail this group of workers.

2.3.2. Results.-The distribution of cohort member by demographic characteristics at entry and by vital status at the end of follow-up is shown in Table 1. Relevant features of the 2,665 service stations in 1980, by station size, are described in Table 2. The overall cause-specific SMRs are reported in Table 3. Although cancer mortality was lower than expected, non-significantly increased risks Were found for non-Hodgkin's lymphoma and for esophageal and nervous system cancers among males. Risk of colon and bladder cancers was slightly elevated, while mortality due to lung cancer and leukemia was lower than expected. No kidney cancer death was recorded whereas two cases were expected. Among attendants of small 32

stations (Table 4) the SMRs for esophageal and brain cancer showed increased values compared to the overall findings, reaching statistical significance among males and in the whole sub-cohort, respectively. Moreover, the excesses of blood diseases, soft tissue sarcoma and melanoma were concentrated in this sub-cohort. Among these workers, furthermore, an increased risk of laryngeal cancer was recorded. The excess risk of non- Hodgkin's lymphoma, however, was almost equally distributed among the two sub cohorts (Tables 4 and 5). Attendants of large service stations, on the other hand, showed increased risks of bladder cancer, leukemia, and nervous system diseases (Table 5).

2.3.3. Discussion.- This study represents the first workplace-based cohort of filling station attendants. Comparing the number of subjects in our cohort with the 1981 Italian census estimates of workers in the economic sector "Retail sales of fuels and lubricants" (ISTAT, 1985 Vol. 2-12) it seems that we studied about half of the whole work force employed in gasoline service stations in the Region, namely the self-employed managers, excluding family and salaried workers. We found excess risks, although not statistically significant, for blood diseases, esophageal cancer, nervous system cancer and non-Hodgkin's lymphoma in the whole cohort. Moreover, an increase of the SMRs for these causes of death was found among managers of small stations, along with an excess risk for laryngeal cancer. Managers of large stations, on the other hand, showed increased risks for bladder cancer, leukemia and nervous system diseases. Our findings essentially confirm previously reported excess risks (for a detailed review, see 3, 4) with the remarkable exclusion of kidney cancer, for which no death was recorded. The deficit in mortality from all causes, cardiovascular diseases and respiratory diseases could be ascribed to the relatively low duration of the follow-up, and to the combination of factors generally referred to as "healthy worker effect". The observed excesses of blood and nervous system diseases deserve attention, in view of the exposure to the hematological and neurological toxicants present in gasoline vapours. A major drawback is that the power of this study, for most of the causes of interest, was quite low and the duration of the follow-up might have been insufficient for cancers that have a long induction period. Furthermore, due to the lack of information on employment termination dates, we did not examine the observed excess risks by length of employment, a usual proxy for duration of exposure. Lack of information about smoking habits and alcohol consumption is undoubtedly a weakness of this study. Nevertheless, mortality due to tobacco- and alcohol-related causes of death (lung cancer, respiratory diseases and digestive diseases, particularly cirrhosis of the liver) was not increased in the cohort. In conclusion, filling station attendants are exposed to gasoline vapours containing aromatic hydrocarbons, including benzene. This group of workers seems at risk of cancer at various sites. The observed increased risks are consistent with the hazards to which they are exposed. Due to the power limitations of this study, a precise estimate of the risk for many causes of death is not achievable. Further cohort studies of greater size are warranted. 33

References

INFANTE P.F., SCHWARTZ E., CAHILL R. Benzene in petrol: a continuing hazard (letter). The Lancet 1990, 336: 814-5.

MEHLMAN M.A. Benzene health effects: unanswered questions still not addressed (commentary). Am. J. Ihd. Med. 1991, 20: 707-11.

LAGORIO S., FORASTIERE F„ IAVARONE I., RAPITI E„ VANACORE N„ PERUCCI C.A., CARERE A. Mortality of filling station attendants. Scand. J. Work Environ. Health 1994, 20: 331-338.

LAGORIO S., FORASTIERE F„ MICHELOZZI P., PERUCCI C.A., ALTAVISTA P„ COSTA G., VIGOTTI M.A. Cause of death ascertainment in follow-up studies: comparison of methods avalaible in Italy. Epidemiologia e Prevenzione 1987; 31: 57-61. (English abstract).

LAGORIO S„ FORASTIERE F„ IAVARONE I., VANACORE N„ FUSELLI S„ CARERE A. Exposure assessment in a historical cohort of filling station attendants. Int. J. Epidemiol. 1993; 22 (2): S51-6.

Istituto Centrale di Statistica (1STAT). 6° Censimento generate dell'industria, del commercio, dei servizi e dell'artigianato. 26 Ottobre 1981. Vol. II. Dati sulle caratteristiche strutturali delle imprese e delle unita locali (6th Census of industry, trade and services. October 26th, 1981). Volumes 2-12. Latium Region. Rome: 1ST AT, 1985. 34

Table 1.- Distribution of filling station attendants by gender according to age and length of employment at entry, working time, vital status at the end of the follow-up and person- years of observation.

Men Women Total N % N % N % Age at entry (years) 15-24 67 2.9 11 3.1 78 2.9 25-34 334 14.5 62 17.4 396 14.9 35-44 632 27.4 90 25.2 722 27.1 45-54 704 30.5 102 28.6 806 30.2 55+ 571 24.7 92 25.8 663 24.9 Total 2308 100.0 357 100.0 2665 100.0 Length of employment at entry (years) 1-10 863 39.2 210 63.8 1073 42.4 11-20 897 40.8 85 25.8 982 38.8 439 20.0 34 10.3 473 18.7 Working Time Full-time 1941 92.5 228 81.1 2169 91.2 Part-time 157 7.5 53 18.9 210 8.8 Vital status Alive 1922 83.3 314 88.0 2236 83.9 Deceased 250 10.8 20 5.6 270 10.1 Lost to follow-up 136 5.9 23 6.4 159 6.0 Person-years by age 15-29 785 3.3 113 2.9 898 3.2 30-39 3487 14.5 622 16.1 4109 14.7 40-49 6617 27.5 1020 26.4 7637 27.4 50-59 7228 30.1 1113 28.8 8341 30.0 60-69 4252 17.7 706 18.3 4958 17.8 70 1664 6.9 291 7.5 1954 7.0 Total 24033 100.0 3864 100.0 27897 100.0

Table 2.- Characteristics of the 2665 stations whose managers were enrolled in the cohort study, by station size.

Station size Small Large N Mean N Mean Yearly gasoline sales (liters) 1720 409605 911 544099 Capacity of the underground gasoline tank (m ) 1738 9.64 918 16.08 Number of employees 1683 1.87 898 2.95 Yearly gasoline sales per full-time employee (liters) 1659 264213 889 218573 Table 3.- Mortality of service station attendants from the Latium region (1981-1992) by broad groups of causes of death. (OBS = observed deaths; EXP - expected deaths; SMR = standardized mortality ratio; 90% Cl = 90% confidence interval).

Cause of death (IXICD) Men Women Total

OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl

Infectious diseases (001-009) 0 1.8 - - 1 0.1 769 39-3649 1 1.9 52 3-247 Malignant neoplasms (140-208) 78 99.6 78 64-95 5 8.9 56 22-119 83 108.5 77 63-92 Esophagus (150) 4 1.7 241 82-551 0 0.1 - - 4 1.7 234 80-535 Colon (153) 6 5.3 113 49-224 0 0.6 - - 6 5.9 102 44-201 Liver (155) 3 5.8 52 14-135 0 0.5 - - 3 6.2 48 13-125 Pancreas (157) 2 3.6 55 10-173 1 0.3 303 15-1438 3 4.0 76 21-195 Larynx (161) 3 2.9 105 29-272 0 0.0 - - 3 2.9 105 29-270

Lung(162) 29 32.3 87 64-123 0 0.8 - - 29 34.1 85 61-116 Bladder (188) 6 4.9 122 53-242 0 0.1 - - 6 5.0 120 52-236

Kidney (189) 0 2.3 - - 0 0.1 - - 0 2.4 - Nervous system (190-2) 5 2.6 195 77-411 1 0.3 400 20-1898 6 2.8 214 93-421

Non-Hodgkin's lymphoma (200, 3 1.7 173 47-448 0 0.2 - - 3 1.9 158 43-408 202)

Leukemia (204-8) 2 3.3 61 11-192 0 0.3 - - 2 3.6 56 10-175

Blood (280-289) 1 0.8 127 6-601 1 0.1 1111 57-5271 2 0.9 227 40-715

Nervous system (320-359) 4 4.4 92 31-210 0 0.5 - - 4 4.8 83 28-190 Table 3 - continued

Cause of death (IXICD) Men Women Total

OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl

Circulatoiy system (390-459) 97 114.7 85 71-210 6 9.6 62 27-123 103 124.3 83 70-98

Respiratoiy system (460-519) 14 19.4 72 44-113 0 1.0 - - 14 20.4 69 41-107 Accidents and Violence (800- 21 14.7 143 96-205 1 1.0 96 5-456 22 15.8 140 94-199 999)

All Causes (001-999) 250 297.6 84 76-93 20 25.3 79 52-115 270 322.9 84 76-92 0> Table 4.- Mortality of small service station attendants (1981-1992) by selected causes of death. (OBS = observed deaths; EXP = expected deaths; SMR = standardized mortality ratio; 90% Cl = 90% confidence interval).

Cause of death (IXICD) Men Women Total

OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl

Malignant neoplasms (140-208) 60 68.6 87 70-108 3 5.99 51 14-133 63 74.4 85 68-104

Esophagus (150) 4 1.1 351 120-803 0 0.0 - - 4 1.2 342 117-782 Colon (153) 5 3.7 136 54-286 0 0.4 - - 5 4.1 123 48-258 Pancreas (157) 2 2.5 80 14-252 1 0.2 476 24-2259 3 2.7 111 30-286 Larynx (161) 3 2.0 153 42-396 0 0.0 - - 3 2.0 152 42-394 Lung(162) 22 22.7 97 63-138 0 0.5 ■ - - 22 23 3 95 64-135 Connective tissue (171) 1 0.1 833 43-3953 0 0.0 - - 1 0.1 769 39-3649 Melanoma (172) 1 0.5 204 10-968 0 0.0 - - 1 0.6 182 9-863 Bladder (188) 4 3.5 116 40-265 0 0.1 - - 4 3.5 113 39-259 Kidney (189) 0 1.6 - - 0 0.1 - - 0 1.6 - -

Nervous system (190-2) 4 1.7 233 79-532 1 0.2 625 32-2965 5 1.9 266 105-559 Lympho-hematopoietic (200-8) 2 4.6 44 8-138 0 0.4 - - 2 5.0 40 7-126 Non-Hodgkin's lymphoma (200, 2 1.2 171 30-538 o 0.1 - - 2 1.3 156 28-492 202)

Leukemia (204-8) 0 2.3 - - 0 0.2 - - 0 2.5 - -

Blood (280-289) 1 0.6 182 9-863 1 0.1 1667 85-7907 2 0.6 323 57-1015 Table 4 - continued

Cause of death (IXICD) Men Women Total

OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl

Nervous system (320-359) 1 3.1 33 2-155 0 0.3 - - 1 3.4 30 2-140 Circulatory system (390-459) 70 80.7 87 70-106 2 6.5 31 5-97 72 87.2 83 67-100 Respiratory system (460-519) 7 13.9 50 24-95 0 0.7 - - 7 14.6 48 23-90 Accidents and violence (800- 13 9.9 132 78-209 0 0.7 - - 13 10.6 123 73-195 999)

All causes (001-999) 178 207.2 86 76-97 13 16.9 77 45-122 191 224.2 85 75-96 Table 5.- Mortality of the large service station attendants from the Latium region (1981-1992) by selected causes of death. (OBS = observed deaths; EXP = expected deaths; SMR = standardized mortality ratio; 90% Cl = 90% confidence interval).

Cause of death (IXICD) Men Women Total

OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl

Malignant neoplasms (140-208) 18 31.0 58 37-86 2 3.0 67 12-211 20 34.0 59 39-85

Esophagus(150) 0 0.5 - - 0 0.0 - - 0 0.5 - - Colon (153) 1 1.6 62 3-293 0 0.2 - - 1 1.8 55 3-261 Pancreas (157) 0 1.1 - - 0 0.1 - - 0 1.3 - - Larynx (161) 0 0.9 - - 0 0.0 - - 0 0.9 - - Lung(162) 7 10.5 67 31-125 0 0.3 - - 7 10.8 65 30-122

Connective tissue (171) 0 0.1 - - 0 0.0 - - 0 0.1 - -

Melanoma (172) 0 0.3 - - 0 0.0 - - 0 0.3 - - Bladder (188) 2 1.4 139 25-437 0 0,1 - - 2 1.5 134 24-423 Kidney (189) 0 0.7 - - 0 0.1 - - 0 0.8 - -

Nervous system (190-2) 1 0.9 116 6-552 0 0.1 - - 1 0.9 106 5-505 Lympho-hematopoietic (200-8) 3 2.1 142 39-366 0 0.2 - 3 2.3 128 35-331 Non-Hodgkin's lymphoma (200, 202) 1 0.6 179 9-847 0 0.1 - - 1 0.6 161 8-765

Leukemia (204-8) 2 1.0 196 35-617 0 0.1 - - 2 1.1 177 31-557

Blood (280-289) 0 0.3 - - 0 0.0 - - 0 0.3 - -

Nervous system (320-359) 3 1.3 231 63-596 0 0.2 - - 3 1.5 204 56-527 Table 5 - continued

Cause of death (IXICD) Men Women Total

OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl OBS EXP SMR 90% Cl

Circulatory system (390-459) 27 34.0 80 56-110 4 3.1 129 44-296 31 37.1 84 61-113 Respiratory system (460-519) 7 5.5 127 59-238 0 0.3 - - 7 5.9 120 56-225 Accidents and violence (800-999) 8 4.9 165 82-297 1 0.3 294 15-1395 9 5.2 173 90-302 All causes (001-999) 72 90.4 80 65-97 7 8.3 84 39-158 79 98.8 80 66-94 41

3 CYTOGENETIC MONITORING OF SPANISH FILLING STATION ATTENDANTS

Ricardo Marcos, Amadeo Creus, Noel Xamena, Elisabet Carbonell, Maria Pitarque, Jordi Surralles, Gloria Ribas Universitat Autdnoma de Barcelona, Barcelona, Spain

The main contribution to the project given by the Universitat Autdnoma de Barcelona, was the cytogenetic study of two human populations occupationally exposed to petroleum fuel derivatives, as well as their comparison with matched control populations. In addition, in vitro genotoxicity of some of the petrol components was also evaluated. The results obtained are summarized in this section. The studied populations were: 1) workers from different petrol stations from Barcelona city and its surroundings and 2) workers from the Barcelona Airport. A group constituted by administrative workers of the Universitat Autdnoma de Barcelona was used as a control group. The first task of the study was to prepare an adequate questionnaire to collect relevant information about confounding factors that can affect the different cytogenetic parameters to be analysed, as well as information concerning potential exposure at the workplace. Taking into account the special relevance of benzene as a genotoxic component of petrol, the exposure to this compound must be related to its concentration in the different fuels. Although a few years ago in European countries benzene levels in fuels was of about 5%, several legal requirements have reduced this concentration to about 1% in presently sold fuels. The analysis of the two most widely used types of commercial petrol in Spain, performed within this work by GC-MS, indicated a content of 1.1 and 0.7 % v/v in super and unleaded gasoline, respectively.

To assess the possible genotoxicity of commercial petrol, we carried out in vitro experiments using cultured human lymphocytes to evaluate the genetic damage induced by samples from the two types of commercial petrol quoted above. Peripheral lymphocytes from three donors were used to evaluate the genotoxicity of different concentrations of fuels by means of the sister-chromatid exchanges (SCE) and the micronucleus (MN) tests. The commercial petrol samples were diluted in methanol (1%) and 0.05 ml of the different dilutions were added to the 5 ml cultures 24 hours after the initiation of both types of cultures (SCE and MN). The data obtained in the SCE study are presented in Tables 1 and 2. The results show a significant inverse relationship between petrol concentration and proliferative index (PRI), an indicator of cell-cycle delay, which decreased in a dose related way with both samples of commercial petrol tested. With reference to genotoxicity, the results obtained show that both types of commercial petrol samples are able to induce SCE in human lymphocytes treated in vitro. Taking into account that a similar positive response 42

was obtained with both leaded and unleaded samples, it is conceivable that other petrol components, beyond lead, are responsible for the detected genotoxic effect. In addition, it must be pointed out that this positive result was detected without the use of an external source of metabolic activation, which would suggest that the genotoxic components are other than benzene, which is believed to be a proximate genotoxic agent, requiring metabolic activation. The results obtained in the study of MN induction are presented in Tables 3 and 4. The assay was carried out with two donors, and the results show that both leaded and unleaded commercial petrol samples are unable to induce micronuclei in cultured human lymphocytes in vitro. Taking into account that the MN assay detects both clastogenic and aneugenic effects, these results would indicate the lack of ability of the petrol samples assayed to induce such types of genetic damage in this assay, carried out only without metabolic activation. The biomonitoring study of the petrol attendance workers was conducted over 52 workers from 11 petrol stations. The characteristics of the petrol stations participating in this study are indicated in Table 5. To evaluate the exposure to different environmental hydrocarbons with particular significance from the genotoxic point of view, we used passive personal dosimeters to determine the levels of benzene, toluene and xylenes. The results obtained after an 8 hour exposure (the normal workshift) are indicated in Table 6. In addition to the above external exposure measurements, information on internal exposure to aromatic hydrocarbons was provided by the analysis of urinary levels of phenol, hippuric and methyl hippuric acid. The results presented in Table 7 indicate significant increases of urinary phenol in exposed workers over controls, possibly related to benzene exposure. Taking into account that some of the petrol components exert severe blood diseases, heamatological analysis from blood samples of petrol attendance workers have been conducted. The results are indicated in Table 8. The comparison of data on station attendants with those of the reference population, indicates no significant differences for any of the haematological parameters analysed. The in vivo study on the genotoxic effects induced by petrol exposure was carried out using blood samples from petrol station attendants and healthy donors used as control. Sister-chromatid exchanges and micronuclei were the genetic endpoints analysed. Tables 9 and 10 show the data obtained in the SCE study. No difference between exposed and controls was observed for SCE frequency and the proliferative rate index (PRI) (Table 9). A higher incidence of cells with high frequency of SCE (MFC, above either the 95th or 75th percentile) was observed among station workers, but the difference did not attain statistical significance. Table 10 shows the different explanatory variables that, at priori, could affect the expression of the SCE parameters. The results obtained indicate that only cigarette smoking was a significant source of variability in the population studied. 43

Tables 11 and 12 present data on the analysis of micronuclei in binucleated lymphocytes. No significant difference was observed between petrol station attendants and controls for either the total number of micronuclei (MN), the number of binucleated cells with micronuclei (BNMN), or the cytokinesis bloock proliferation index (CBPI) (Table 11). When different possible sources of variation were taken into account (Table 12), there were no indications, in our study, that the frequency of micronuclei was affected by factors such as alcohol drinking, cigarette smoking, duration of employment, etc. Taking into account that benzene metabolites are excreted by the urine, if some of them have genotoxic activity, urothelial cells which are in close contact with them could show genetic damage. Thus, an additional investigation was carried out to determine the incidence of micronuclei in exfoliated urothelial cells of exposed workers and controls. The results summarized in Tables 13 and 14 show that there are no significant differences between the two groups. The second group of people exposed to petroleum derivatives consisted in workers from Barcelona Airport. These workers assist planes during charge and descharge, including the activity of filling up the plane’s tanks. The characteristics of this group are indicated in Table 15. Data on personal exposure to benzene, toluene and xylenes, are indicated in Table 16. Very low exposure levels were measured, much lower than those detected in the central streets of Barcelona. On the other hand, it is conceivable that these workers are exposed to engine exhausts, which have also been reported to have genotoxic activity. The results of the cytogenetic survey on airport workers are shown in Tables 17 and 18. No significant difference in either SCE and MN frequencies were observed in airport workers compared to unexposed controls. Taking into account the negative results of cytogenetic assays in both groups of occupationally exposed workers, a novel sensitive method assay (the single cell gel electrophoresis or comet assay) was used for further studies in vitro and in vivo. For the in vivo study, comet tail length as well as the proportion of damaged nuclei was determined in lymphocytes from a group of workers from Barcelona Airport. These results are presented in Table 19. The results indicate a non significant excess of DNA damage, measured both with the tail length and GDI, in airport workers compared to controls. Finally, in vitro experiments were carried out to assess the genotoxicity of benzene and toluene using the comet assay. This study was conducted with and without external metabolic activation (S9 mix). Both chemicals induced a positive response at the highest concentration tested both with and without S9 mix (data not shown). The final conclusion from this work is that although studies conducted in vitro show that both commercial petrol and individual components such as benzene and toluene are genotoxic, there was no genotoxic damage detectable in the occupationally exposed populations investigated. This would suggest that perhaps the exposure levels analysed are too low to exert a significant genotoxic effect, or that the extent of damage induced is below the detection limit of the experimental methods used. 44

Table 1.- Sister-chromatid exchanges induced by leaded petrol (super) in human lymphocytes

Donor Cone, (pl/ml) PRI N SCE/cell ± SE HFC A Control 1.67 50 9.20 ± 0.65 1 Methanol 1% 1.76 50 9.38 ± 0.52 0 0.019 1.71 50 8.50 ± 0.44 0 0.039 1.64 50 9.04 ± 0.56 0 0.078 1.70 50 10.62 ± 0.53* 1 0.156 1.71 50 11.42 ±0.65** 2 0.312 1.59* 50 14.12 ±0.82*** 9“ MMC (0.2 uM) - 50 31.40 ± 1.07*** B Control 2.19 50 8.66 ± 0.53 0 Methanol 1% 108 50 10.44 ± 0.49 1 0.019 1.96 50 9.10 ± 0.51 0 0.039 2.06 50 11.28 ±0.60 2 0.078 1.94 50 10.44 ±0.61 3 0.156 1.84 50 13.30 ±0.70*** 5

0.312 1.19*** - - - MMC (0.2 uM) - 37 26.81 ± 1.22* “ C Control 2.53 50 7.24 ±0.51 0 Methanol 1% 2.31 50 8.82 ±0.47 1 0.019 1.93*** 70 10.33 ±0.53* 1 0.039 1.82*** 50 11.44 ±0.66** 1 0.078 1.91*** 50 11.28 ±0.68“ 2 0.156 1.79*** 50 11.94 ±0.60*" 1

0.312 - - - - MMC (0.2 pM) 50 32.96 ± 0.97***

100 cells were scored to determine the PRI values SE, standard error; t-test for SCE; F-Fischer test for HFC (*p<0.05; “p<0.01; ***p<0.001). Significance is determined with respect to methanol 45

Table 2.- Sister-chromatid exchanges induced by unleaded petrol in human lymphocytes

Donor Cone, (pl/ml) PRI N SCE/cell ± SE MFC A Control 1.67 50 9.20 ± 0.65 1 Methanol 1% 1.76 50 9.38 ±0.52 0 0.019 1.96 50 9.68 ±0.51 0 0.039 1.94 50 7.78 ± 0.50 0 0.078 1.65 50 10.64 ± 0.54* 0 0.156 1.81 50 12.18 ±0.64*" 3 0.312 1.53* 40 13.88 ±0.64*** 5* MMC (0.2 pM) - 50 31.40 ± 1.07*** B Control 2.19 50 8.66 ±0.53 0 Methanol 1% 2.08 50 10.44 ± 0.49 1 0.019 2.13 50 11.62 ±0.63 5 0.039 2.13 50 10.24 ±0.52 1 0.078 2.03 50 10.68 ± 0.57 2 0.156 2.04 50 10.84 ± 0.65 2 0.312 1.53*** 48 12.73 ± 0.74** 6 MMC (0.2 pM) 37 26.81 ± 1.22"" C Control 2.53 50 7.24 ±0.51 0 Methanol 1% 2.13 50 8.82 ± 0.47 I 0.019 1.68*** 29 9.45 ±0.66 0 0.039 1.46*** 50 12.02 ±0.61*** 3 0.078 1.67*** 50 11.50 ±0.53*** 0 0.156 1.67*** 60 12.80 ±0.71*** 5 0.312 1.42*** 39 12.74 ± 0.98*** 6 MMC (0.2 pM) 50 32.96 ±0.97***

100 cells were scored to determine PRI values SE, standard error; t-test for SCE; F-Fischer test (*p<0.05; "p<0.01; ***p<0.001). Significance is determined with respect to metlianol. 46

Table 3.- Induction ofMNin human lymphocytes after a 48h treatment with leaded petrol (super)

Donor Concentration CBPI N Distribution of BN cells according MN BNMN (Hl/ml) to MN (%o) 0 1 2 3 >3 A Control 1.92 1000 996 4 0 0 0 4 4 Methanol 1% 1.88 1000 989 11 0 0 0 11 11 0.019 1.81 1000 988 11 1 0 0 13 12 0.039 1.76 1000 993 7 0 0 0 7 7 0.078 1.74*** 1000 987 12 0 0 1 16 13 0.156 1.63*** 1000 991 7 1 1 0 12 9 0.312 - T ------MMC (0.4nM) 1.75** 1000 914 83 3 0 0 89**' 86*** B Control 2.03 1000 986 12 2 0 0 16 14 Methanol 1% 1.87 1000 989 10 1 0 0 12 11 0.019 1.48*** 725 706 16 2 0 1 25" 26.2* 0.039 1.92* 1000 990 10 0 0 0 10 10 0.078 1.87 1000 991 9 0 0 0 9 9 0.156 1.75*** 1000 992 7 1 0 0 9 8 0.312 - t ------MMC (0.4pM) 1.60*** 1000 935 63 1 1 0 68*** 65***

MN, total MN; BNMN, binucleated cells with MN; t = 100% toxicity. Exact Fischer’s test for BNMN. Kastenbaum and Bowman for MN (*p<0.05; **p<0.01; ***p<0.001). Significance is determined with respect to methanol. 47

Table 4.- Induction ofMN in human lymphocytes after a 48h treatment with unleaded petrol

Donor Concentration CBPI N Distribution of BN cells MN BNMN (pl/ml) according to MN (%o) 0 1 2 3 >3 A Control 1.92 1000 996 4 0 0 0 4 4 Methanol 1% 1.88 1000 989 11 0 0 0 11 11 0.019 1.84 1000 993 4 2 0 1 12 7 0.039 1.85 1000 992 8 0 0 0 8 8 0.078 1.77** 1000 993 7 0 0 0 7 7 0.156 1.57*** 1000 990 8 1 1 0 13 10 0.312 - t ------MMC 1.75** 1000 914 83 3 0 0 89"" 86""" (0.4jxM) B Control 2.03 1000 986 12 2 0 0 16 14 Methanol 1% 1.87 1000 989 10 1 0 0 12 11 0.019 1.39*** 1000 984 15 1 0 0 17 16 0.039 1.62*** 1000 986 14 0 0 0 14 14 0.078 1.71*** 1000 986 13 1 0 0 15 14 0.156 1.76*** 1000 987 13 0 0 0 13 13 0.312 1.27*** 751 733 16 2 0 0 20" 24" MMC 1.60*** 1000 935 63 1 1 0 68'" 65"" (0.4pM)

MN, total MN; BNMN, binucelated cells with MN; t = 100% toxicity. Exact Fischer’s test for BNMN. Kastenbaum and Bowman for MN (*p<0.05; "p<0.01; *"p<0.001). Significance is determined with respect to methanol.

Table 5.- General characteristics of the 11 petrol stations collaborating in the study n. of employees 7-12 n. of car filled-up daily 1000-1500 n. of tank charges 1/day (average) average amount of petrol dealt (1/day): three stars 15,000 unleaded 5,000

diesel oil 5,000 total 25,000 48

Table 6.- Concentration of some aromatic hydrocarbons (mg/m 3 ) after 8 hours exposure (Personal organic monitor 3M- 3500)

Station Benzene Toluene Xylenes

1 0.57 0.96 0.48

2 0.62 2.07 1.00

3 0.30 0.52 0.29

4 1.13 1.82 0.94

5 0.65 0.97 0.72

6 1.55 2.37 1.43

7 1.02 2.07 1.30

8 0.61 1.14 0.56

9 0.68 1.66 0.85

10 1.83 2.08 0.95

11 1.00 1.76 1.26

Mean±SE 0.91±0.14 1.58 ±0.18 0.89 ±0.11

Table 7.- Phenol and hyppuric acid levels in urine of the petrol station workers (mg/g creatinine)

Exposed Controls

Phenol 5.06 ±0.51* 3.73 ±0.53

Hyppuric acid 433.08 ± 42.94 376.51 ±48.35

* Significantly different from control (U- test). Methyl hyppuric values were below the detectable level (< 20 mg/1). 49

Table 8.- White blood cell count in petrol station attendants and controls

White blood cells (%) Mean ± SE Exposed Controls

Eutrophils 58.36 ±0.98 56.73 ± 0.97

Eosinophils 2.14 ±0.20 2.48 ±0.23

Basophils 0.66 ± 0.04 0.75 ± 0.04

Lymphocytes 30.63 ± 0.89 31.87 ±0.85

Monocytes 6.36 ±0.19 6.62 ±0.15

Differences between exposed and controls are not statistically significant (Mann-Whitney (/-test).

Table 9.- SCE, HFC and PRI values in petrol station attendants and controls

Group Number of SCE HFC 95 PRI subjects (mean±SE) (mean±SE) (mean±SE) Controls Non-smokers 6.99 ±0.24 2.52 ±0.58 2.38 ±0.05 (27) Smokers (18) 7.97 ± 0.56 7.17 ±2.39 2.41 ±0.05

Total (45) 7.38 ±0.27 4.38 ± 1.06 2.39 ±0.04

Exposed Non-smokers 6.97 ± 0.26 2.58 ± 0.78 2.46 ± 0.06 (12) Smokers (30) 8.39 ±0.34 7.62 ± 1.67 2.43 ± 0.03

Total (42) 7.99 ± 0.27 6.18 ± 1.26 2.43 ± 0.03

Ctrl+ Exp. Non-smokers 6.98 ±0.18 2.54 ± 0.46 2.40 ± 0.04 (39)

Smokers (48) 8.39 ±0.34 7.45 ± 1.36 2.47 ± 0.03

HFC, percentage of high frequency cells; PRI, proliferative rate index. 50

Table 10.- Variation in SCE between cells within individuals (standard errors in brackets)

Explanatory variables Estimates % of total variance

Fixed effects

Constant 6.860 (0.345)'**

Occupational exposure -0.151 (0.262)

Duration of employment -0.019 (0.028)

Cigarette smoking 0.067 (0.014)***

Alcohol drinking 0.001 (0.001)

Random effects

Between ages within exposure 0.009 (0.165) 0.05 groups variance 1

Between individuals within ages 2.294 (0.405)*** 12.75 variance 1

Between cells within individuals 15.683 (0.324) 87.20 variance

1 tested by means of Wald test; *** P< 0.001

Table 11. Micronuclei among petrol station attendants and controls

Exposed Controls

Number of subjects 50 43

Age (years) 43.32 ± 1.84 40.53 ± 1.28

Duration of employment (years) 13.24 ± 1.32 -

Total MN 21.04 ± 1.78 24.91 ± 1.78

BNMN 17.72 ± 1.33 20.81 ±1.41

%BN 61.90 ±0.58 59.96 ±1.42

CBPI 2.05 ± 0.02 2.05 ± 0.03

BNMN, binucleated cells with MN; %BN, percentage of binucleated cells; CBPI, cytokinesis block proliferation index.Differences between exposed and controls are not statistically significant (ANCOVA). Table 12.- Analysis of covariance (ANCOVA) for BNMNfrequency

Source of variation Exposed group Control group Total

df Mean F P df Mean F P df Mean F P

square square square

Occupational exposure - - 1 0.0003 0.25 0.616

Age within occupational exposure 32 0.0012 1.76 0.132 24 0.0012 1.63 0.157 56 0.0012 1.63 0.069

Duration of employment 1 0.0002 0.30 0.596 - - 1 0.0001 0.18 0.677

Cigarette smoking 1 0.0008 1.06 0.321 1 0.0000 0.01 0.921 1 0.0006 0.79 0.380

Alcohol drinking 1 0.0005 0.71 0.415 1 0.0016 2.17 0.161 1 0.0001 0.18 0.675

Error 14 0.0007 16 0.0007 32 0.0007 52

Table 13.- Frequencies of micronuclei in exfoliated cells from urine of the petrolattendance workers

Group Subject N Total MN Cells with MN

N %0

Exposed 1 1000 34 20 20.00 2 1000 14 14 14.00

3 1000 2 2 2.00

4 419 9 4 9.55 5 1000 5 5 5.00 6 562 5 3 5.34

7 1000 2 2 2.00

8 1000 8 6 6.00 9 1000 6 5 5.00 10 1000 8 7 7.00

11 684 7 6 8.77

12 825 0 0 0.00 13 451 2 2 4.43 14 1000 7 7 7.00

15 1000 5 5 5.00

Total 12974 104 88 6.74±1.29 53

Table 14.- Frequencies of micronuclei in exfoliated cells from urine of the controls

Group Subject N Total MN Cells with MN

N %

Control 1 547 6 3 5.48 2 1000 14 10 10.00

3 1000 10 5 5.00

4 508 19 8 3.69 5 1000 5 5 5.00 6 643 11 10 15.55 7 599 8 6 10.02

8 885 9 7 7.91

9 1000 8 5 5.00 10 860 5 3 3.49

11 1000 7 6 6.00

12 10 3 3 2.83

Total 10103 105 71 7.02 ± 1.21

Table 15.- Characteristics of the group of workers from Barcelona Airport participating in the study.

Number of subjects: 39 - non-smokers: 22 - smokers: 17 (mean: 19.86 ± 1.72 cigarettes/day)

Age: 34.87 ±1.11 years

Length of employment: 9.77 ± 0.94 years 54

Table 16.- Comparison of the levels of benzene, toluene and xylene levels in different environments.

Benzene (mg/m3) Toluene (mg/m3) Xylenes (mg/m3)

Aiport <0,01 <0,05 <0,06

Petrol stations 0,91 1,58 0,89

Barcelona streets 0,06 0,28 0,14 (centrum)

Table 17.- SCE and PR1 values in airport workers and controls

Group Number of subjects SCE PRI (mean±SE) (mean±SE)

Controls Non-smokers (27) 6.99 ± 0.24 2.38 ± 0.05

Smokers (18) 7.97 ± 0.56 2.41 ±0.05

Total (45) 7.38 ± 0.27 2.39 ± 0.04

Exposed Non-smokers (12) 6.97 ± 0.26 2.13 ±0.03

Smokers (18) 8.71 ±0.30 2.14 ±0.04

Total (30) 8.25 ± 0.24 2.11 ±0.05

PRI, Proliferative rate index 55

Table 18.- Micronuclei among airport workers and controls

Exposed Controls

Number of subjects 39 11

Age (years) 34.37 ± 1.11 47.91 ±4.22

Duration of employment (years) 9.77 ± 0.94 -

Total MN 7.62 ± 0.49 12.90 ± 1.78

BNMN 7.08 ± 0.43 10.60 ± 1.25

%BN 61.21 ± 0.70 60.56 ±1.21

CBPI 1.89 ±0.02 1.95 ± 0.04

BNMN, binucleated cells with MN; %BN, percentage of binucleated cells; CBPI, cytokinesis block proliferation index

Table 19.- Comet assay in airport workers and controls

Tail length Proportion of damaged nuclei GDI

%A %B %C %D %E

Exposed (37 ind.) 45.51 ± 1.55 22.5 52.1 17.8 6.1 1.5 1.11 ±0.06

Controls (5 ind.) 41.36 ±1.41 34.4 40.0 19.6 3.8 2.2 0.99 ±0.19

GDI, genetic damage index; GDI = (B+2C+3D+4E)/(A+B+C+D+E), where A-E indicate ranks of DNA damage 56

4. BENZENE EXPOSURE AND CYTOGENETIC INVESTIGATION OF ESTONIAN SHALE OIL PETROCHEMICAL WORKERS

Antero Aitio, Tima Anttinen-Klemetti, Kirsi Autio, Kivisto H., Tehri Kuljukka, Lars Nylund, Kaija Pekari, Kimmo Peltonen, Jordi Surralles, Maria Sorsa Finnish Instituteof Occupational Health, Helsinki, Finland

The Finnish Institute of Occupational Health (FIOH) participated to the project with biological monitoring studies on Estonian workers engaged in shale oil industry, enrolled through a collaboration with Prof. T.Veidebaum, from the Estonian Institute of Experimental and Clinical Medicine in Tallin, Estonia. Both exposure and cytogenetic surveys were carried out on the occasion of repeated samplings over the years 1994- 1995. The main results obtained are summarized in the following paragraphs.

4.1. Biological monitoring of exposure to benzene in the oil shale plant.

Benzene is a by product in the coke oven industry, but in an Estonian cokery benzene is used as a solvent. Sampling in the British coke oven industry showed 8 h- TWA mean exposure of 0.3 ppm to 4.3 ppm depending of the profession. Some short time sampling showed even exposure levels up to 38.2 ppm for a 50 minute period (Drummonde L. et al. 1988). At coke ovens in Belgium exposure levels of up to 2 ppm were reported (Lauwerys R. et al. 1994). Benzene is now administratively recognised as an environmental carcinogen in the EU community and community has proposed for the working environment 1 ppm 8h- TWA (Council Directive of 28 June 1990). The Treshold Limit Value (TLV) given by The Amerian Conference of Govememental Industiral Hygiene (ACGIH) at present is 0.5 ppm (ACGIH, 1997). Biological monitoring of occupational exposure to benzene has a long tradition and it is well established. Biomonitoring is mainly carried out by determining of the parent compound in breath, blood and urine or by measuring some of the metabolites in the urine. S-Phenyl-N-acetylcysteine, a minor metabolite of benzene resulting from conjugation with glutathione, has been found to be specific and sensitive for benzene exposure. S-Phenyl-N-acetylcysteine is suggested as a marker compound for benzene exposure in Biological Exposure Indices (BEI) with a reference value of 25 |xg/g creatine (ACGIH, 1997). It was estimated that the proportion of benzene taken up by the lungs and excreted in the urine would be around 0.2 % (Van Sittert N. et al., 1993).

4.1.1. Methods.- A total of 90 workers from an Estonian oil shale plant at Kohtla- Jarve and 39 controls from a nearby Iisaku village took part in this study. All the persons participated voluntarily and were well informed about the purpose of the study beforehand. Sampling was conducted at the beginning of March 1994 and in September 57

1994. About ten persons participated in both samplings. Full shift personal air samples were collected from the breathing zone of each worker, and the sampling was performed by using the Perkin-Elmer thermodesorption tubes utilizing passive diffusion. Collected samples were analysed by using Perkin-Elmer ATD 400 thermodesorption equipment connected to a gas chromatograph (Kivisto H. et al., 1997). All the biomonitoring samples were collected and analysed as previously published (Kivisto H. et al, 1997). Shortly, post shift urine samples were collected in glass bottles and an aliquat was transferred in to a head-space vial. Blood samples were collected in heparinized glass tubes and kept in refrigerator before analysis. Urinary S-phenyl-N- acetylcysteine was analysed as described by Maestri et al. with some inhouse modifications (Maestri L. et al, 1993). trans,/raws-Muconic acid in urine was analysed with a modified method of Ducos et al. (Ducos P. et al., 1992 - Aitio A. et al, 1996). The method of Pekari et al. was adopted in the analysis of blood and urine benzene (Pekari K. et al, 1989 - Pekari K et al., 1992). Benzene in exhaled air was sampled and analysed by following the method of Pekari et al. (Pekari K., 1994).

4.1.2. Results.- The external exposure of the control population was assessed in the winter time only, and it showed a very low exposure. As expected the biomarkers analysed in control population also showed a low exposure. If the controls were devided to smokers and nonsmokers the median of all biomarkers were eleveted in the smoker group (Table 1). Tables 2 and 3 summarises the benzene exposure profiles of the workers in the oil shale plant at Kohtlajarve. In general benzene exposure was higher in benzene factory than in cokery. Also the data indicates a higher exposure in winter time than in summer time. If the workers were grouped according to their smoking habits a bit higher level of biomarkers were detected in smokers, but the difference was not statistically significant (Table 4). The correlation between different biomarkers of exposure were good. In benzene factory the good correlation was not affected at low external exposure, which was the case in the cokery. The correlation of the different biomarkers among the benzene factory workers and cokery workers are summarised in tables 5 and 6. Because of a good correlation achieved between the different biomarkers we were able to estimate the amount of various biomarker that corresponds to the 1 ppm TLV value. Blood benzene showed a value of 110 nmol/1, trans, trans-vmcomc acid gave a value of 24 p.mol/1 or 2 mg/g creatine, S-phenyl-N-acetylcysteine gave a value of 56 pg/g creatine, benzene in exhaled air gave a value of 2.7 nmol/1 and benzene in urine gave a value of 492 nmol/1. Because smoking affects clearly to the background excretion of the benzene biomarkers the smoking status of the study population needs to be sorted out if environmental or otherwise low benzene exposure are assessed.

4.1.3 Conclusions.- The benzene exposure level of the workers in the Kohtajarve plant was high. In March 1994 20% and in early September 29% of the samples 58

collected exceeded 1 ppm TLV. Also all the biomarkers used showed clearly elevated levels of exposure. Besides of the exposure assessment data the intervention allowed us to test the correlation of the various biomarkers. Correlation was good between the different biomarkers and the correlation was also good between the air monitoring data and biomarkers. This fact allowed us to calculate the value of the biomarkers which corresponds to a 1 ppm external exposure. The values and its 95% confidence limits in parenthesis are:

• blood benzene 110 nmol/1 (85-128 nmol/1) • trans,trans-muconic acid 3 mg/1 (1.4-4.6 mg/1) 2 mg/g creatinine (1.0-2.5 mg/g) • S-phenyl-N-acetylcysteine 56 pg/g creatinine (41-73 pg/g) • benzene in urine 492 nmol/1 (147-821 nmol/1) • benzene in exhaled air 2.7 nmol/1 (1.6-4.0 nmol/1)

Our data indicates that at low exposure level the best correlation was achieved between air benzene and benzene in blood and urinary trans,tram-m\icori\c acid.

References

AITIO A., PEKARI K., KIVISTO H. Benzene. In: Biological monitoring of chemical exposure in the workplace, 2. WHO, Geneva, Switzerland, 19%. pp. 73-92.

American Conference of Governmental Industrial Hygienists (ACGIH) 1997. Threshold limit values for chemical substances and Physical agents and biological exposure indices. Cincinnati, OH, USA: ACGIH, 1997.

COUNCIL: Council Directive of 28 June 1990 on the protection of workers from risks related to exposure to carcinogens at work (Sixth Individual Directive within the meaning of Article 16(1) of Directive 89/391EEC) (93/394/EEC). Offic. J. Eur. Commun. 1990 July 26, 196: 1-7.

DRUMMONDE L., LUCK R., AFACAN A., WILSON H. Biological monitoring of workers exposed to benzene in the coke oven industry, Br. J. Ind.. Med. 1988, 45: 256-261.

DUCOS P., GAUDIN R., BEL J., et al.. Trans,trans-Muconic Acid, a Reliable Biological Indicator for the Detection of Individual Benzene Exposure Down to the ppm Level. Int. Arch. Occup. Environ. Health 1992, 64: 309-13.

KIVISTO, H„ PEKARI K., PELTONEN K„ SVINHUFVUD J„ VEIDEBAUM T„ SORSA M„ AITIO A. Biological monitoring of exposure to benzene in the production of benzene and in a cokery, Sci. Total Environ. 1997, 199: 49-63.

LAUWERYS R., BUCKET J., ANDRIEN F. Muconic acid in urine: A reliable indicator of occupational exposure to benzene, Am. J. Ind. Med. 1994, 25: 297-300. 59

MAESTRI L„ GHITTORI S„ GRIGNANI E., FIORENTINO M L., IMBRIANI M. Dosaggio di un metabolita del benzene Tacido s-fenilmercapturico urinario (S-PMA), nelVuomo, mediante HPLC. Med. Lavoro 1993, 84: 55-65.

VAN SITTERT N., BOGAARD P., BEULINK G. Application of the urinary S-phenylmercapturic acid test as a biomarker for low level of exposure to benzene in industry. BritJ.Ind. Med. 1993, 50: 460-469.

PEKARI K. Occupational exposure to benzene, toluene, and styrene in Finland as estimated by biological monitoring, Occup.Hyg. 1994, 1: 95-117.

PEKARI K., RIEKKOLA M-L., AITIO A. Simultaneous determination of benzene and toluene in the blood using head-space gas chromatography. J.Chromatogr. 1989,491: 309-320.

PEKARI K„ VAINIOTALO S., HEIKKILA P„ PALOTIE A., LUOTAMO M., RIIHIMAKI V. Biological monitoring of occupational exposure to low levels of benzene. Scand. J. Work. Environ. Health 1992, 18: 317-322. Table 1.- Means (± SD) and medians of different benzene biomarkers among the control group, divided into smokers and nonsmokers.

Non-smokers Smokers All N Mean* sd Median N Mean± sd Median N Mean±sd Median (Range) (Range) (Range)

Benzene in blood 20 5 ± 5 4 20 11 ± 8 9 40 8 ±7 5 (nmol/1) (<3-22) (<3-30)

Muconic acid in urine 20 0.3 ±0.3 <0.3 20 1.4 ±2.2 <0.3 40 0.9 ±1.7 <0.3 (nmol/1) (<0.3-1.1) (<0.3-8.0)

S-phenyl-N-acetylcysteine 20 1.3 ±4 0.3 20 2.8 ±4 0.3 40 2.0 ± 4.0 0.3 in urine pg/g creatinine (<0.3-18) (<0.3-13) Table 2.- Concentrations of benzene in breathing zone air, blood, urine, and exhaled air and muconic acid and S-phenyl-N-acetylcysteine in urine of the workers in shale oil industry and in control population in winter.

Controls Cokery Benzene factory

N Mean ± sd Median N Mean± sd Median N Mean ± sd Median (Range) (Range) (Range) Benzene in the 10 0.009 ± 0.009 18 1.3 ±2.7 0.4 20 1.6 ±3.3 0.6 breathing zone (ppm) 0.009 (0.09-11.7) (0.06-14.7)

Benzene in blood 27 7 ±5.4 4 21 160 ±361 37 25 174 ± 257 87 (nmol/1) (<3-22) (18-1688) (8-1160)

Muconic acid in urine 28 0.8 ± 1.8 0.1 20 11 ± 10 7 18 38 ±62 15 (p.mol/1) (<0.2-8.1) (<0.2-35) (<0.2-210)

S-phenyl-N- 28 2.1 ±4.6 0.3 20 73 + 225 17 20 99 + 232 23 acetylcysteine in urine (<0.3-18) (<0.3-1023) (<0.3-1032) pg/g creatinine

Benzene in exhaled 10 0.1 ±0.1 0.1 * 25 3.8 ±5.6 1.7 air (0.1-0.2) (0.1-25.8) (nmol/1)

Benzene in urine 25 12 ± 13 6 18 372 ± 488 152 14 965 ±1775 159 (nmol/1) (2-45) (22-1746) (10-6253)

* not measured Table 3.- Concentrations of benzene in breathing zone air, blood, urine, and exhaled air and muconic acid and S-phenyl-N-acetylcysteine in urine of the workers in shale oil industry and in control population in autumn.

Controls Cokery Benzene factory N Mean ± sd Median N Mean ± sd Median N Mean ± sd Median (Range) (Range) (Range) Benzene in the * 27 0.3 ±0.2 0.3 21 0.8 ±1.1 0.3 breathing zone (0.03-0.7) (0.03-3.4) (ppm)

Benzene in blood 13 11 ± 9 27 37 ± 22 38 25 89 ±117 35 (nmol/1) (<3-30) (11-89) (12-479)

Muconic acid in 13 0.9 ± 1.4 0.5 27 5.0 ±7.7 2.7 25 17.2 ±32.9 1.1 urine (<0.2-5.4) (<0.2-39) (<0.2-155) ((xmol/1)

S- 13 1.9 ±2.4 0.7 27 15.7 ± 14.6 10.0 25 51.1 ±75.8 11.9 phenylmercapturic (C0.3-8.6) (<0.3-45) (<0.3-301) acid in urine \iglg creatinine

* not measured 63

Table 4.- Means (± SD) and medians of different benzene biomarkers among the benzene plant workers, divided into smokers and non-smokers in winter.

Non-smokers Smokers N Mean ± s Median N Mean ± s Median (Range) (Range) Benzene in the 6 1.1 ±2.0 0.4 14 1.9 ±3.3 0.7 breathing zone (0.03-5) (0.03-15) (ppm) TWA Benzene in blood 6 135 ±196 71 14 184 ± 293 90 (nmol/L) (8-528) (11-1160)

Muconic acid in 6 40 ±77 8 14 37 ±56 15 urine (0.2-178) (0.2-210) (umol/L) S-phenyl-N- 6 71 ±109 24 14 110 ±272 23 acetylcysteine in (0.3-283) (0.3-1032) urine pg/g creatinine

Table 5.- Correlations between the different biomarkers among theworkers in the benzene factory.

U-MA S-PMA U-Benzene Exhaled air benzene Benzene in blood r = 0.86 r = 0.94 r = 0.96 r =0.97 n = 43 n = n = 14 n = 25 U-MA r = 0.84 r = 0.96 r = 0.84 n = 43 n = 14 n = 18 S-PMA r = 0.97 r = 0.91 n = 14 n= 19 U-Benzene r = 0.96 n= 14

Table 6.- Correlations between the different biomarkers among the cokery workers.

U-MA S-PMA U-Benzene Benzene in blood r = 0.57 r = 0.97 r = 0.41 n = 45 n =46 n = 18 U-MA r = 0.50 r = 0.66 n = 47 n= 18 S-PMA r = 0.33 n = 18 64

4.2 Molecular cytogenetic analysis of shale oil petrochemical workers

Buccal epithelium provides an alternative source of tissue for monitoring human exposure to occupational and environmental genotoxins (Stone J.G. et al, 1995). This tissue is on the direct route of air-borne pollutants such as benzene, and it can metabolize proximate carcinogens (Zhang L. et al, 1989). In addition, buccal cells can be rapidly and easily sampled by brushing the buccal mucosa. New molecular cytogenetic techniques allow us to study clastogenic or aneugenic events not only in peripheral lymphocytes but also in buccal cells (Moore L.E et al., 1993a - Titenko-Holland N. et al, 1994). These techniques employ fluorescence in situ hybridization (FISH) to study the contents of MN and the frequency of aneuploid cells. The aim of the present study was to evaluate, by these new molecular cytogenetic methodologies, the possible genotoxic effects of benzene exposure on lymphocytes and buccal cells sampled from a group of Estonian petrochemical workers exposed to benzene. The cytogenetic end points chosen were total MN counts, centromere-positive MN and centromere-negative MN in lymphocytes and buccal cells as well as chromosome 9 numerical abnormalities in buccal cells.

4.2.1. Methods.- Blood samples for the lymphocyte analyses were collected in March 1994 and buccal cell sampling was performed in March 1995. The first collection included 10 controls and 24 exposed individuals, whereas 15 control and 18 exposed persons were included in the second sampling. Personal exposure was assessed as described by Kivisto et al. (Kivisto H. et al, 1997). Buccal cells were sampled by rubbing the inside of the mouth (both cheeks) with a toothbrush. Heparinized blood was obtained by venipuncture and cultured as previously described (Sorsa M. et al, 1994). Lymphocytes were cultured in the presence of cytochalasin-B to block cytokinesis and to identify the cells after the first in vitro division by their binucleated appearance. Centromeric FISH was performed with the SO-aAllCen probe, which hybridizes with highly repetitive alpha satellite DNA present in the centromeres of all human chromosomes. The all-centromeres FISH protocol for lymphocytes was essentially as described previously (Norppa H. et al, 1993 - Surralles J. et al, 1995). For chromosome 9 detection, and all technical details were performed as previously described (Surralles J. et al., 1997).

4.2.2. Results.- The population of workers analysed was chronically exposed to a level of benzene around 0.5-1 ppm. The benzene exposure level in the control population was estimated to be trivial, about 20-100-fold lower than the benzene exposed workers. As illustrated in Table 1, none of the cytogenetic variables studied (total MN stained with DAPI and MGG, May Griinwald Giemsa, C-MN and C+MN) showed increased levels in peripheral lymphocytes of the exposed population. On the contrary, there was a general trend toward lower values among the benzene exposed group when compared with the controls. Age, sex, and alcohol and smoking habits, showed no correlation with the cytogenetic parameters. Both C-MN and C+MN were responsible 65 for the frequency of MN in the control and exposed populations. Pooling data from both populations, approximately 2/3 of total MN in lymphocytes harboured acentric fragments. Cytogenetic data concerning buccal cells are summarized in Table 2. Although there was a general trend towards lower frequencies in the exposed population, none of the cytogenetic end-points analysed (total MN, C-MN, C+MN and chromosome 9 numerical abnormalities) was significantly affected by benzene exposure, age, smoking or alcohol consumption. Similarly to blood cells, about 2/3 of the spontaneous MN in buccal cells derived from acentric fragments. Results on chromosome 9 numerical abnormalities were based on the analysis of 28670 cells. The overall baseline frequency of cells with 3 or more chromosome 9 signals was 0.87 ± 0.32 %. When the controls and exposed individuals were pooled together, there was a slight but non-significant positive correlation between donor age and the frequency of cells with chromosome 9 numerical abnormalities (r = 0.28; P = 0.13).

4.2.3. Discussion.- According to Snyder et al. (1993), there is a need to better define the lower end of dose-response curve for benzene as a human carcinogen. The application of the emerging molecular cytogenetic methods in biologically-based risk assessments may help to clarify the uncertainties in low-dose risk assessment. In this report we used the most advanced FISH methodologies to biomonitor chromosome damage in benzene-exposed humans. The results suggest that benzene at the level of 1 ppm, 8h-TWA does not induce detectable numerical or structural chromosome abnormalities in buccal cells or lymphocytes. Neither the frequency of MN containing chromosomal fragment or whole chromosomes, nor the frequency of buccal cells with chromosome 9 numerical abnormalities showed increased values in the exposed population. On the contrary, the values were lower among the benzene exposed workers in comparison with the control, although this difference was significant only for the analysis of MN using the less accurate MGG staining. In interpreting the present results, one has to remember that the assays applied are new and their actual sensitivity has not been proven. Both the MN and the chromosome 9 numerical abnormalities assays include uncertain aspects which require further elaboration. Because of the genotoxic activity of benzene, no threshold of action can be identified at the present time, which means that with current scientific knowledge, no level of exposure can be determined below which there is no risk.

References

KIVISTO H., Pekari K., Peltonen K., Svinhufvud I, Veidebaum T., Sorsa M., Aitio A. Biological monitoring of exposure to benzene in the production of benzene and in a cokery, The Science of the Total Environment 1997, 199: 49-63. 66

MOORE L.E., TITENKO-HOLLAND N., SMITH M.T. Use of fluorescence in situ hybridization to detect chromosome-specific changes in exfoliated human bladder and oral mucosa cells. Environ. Mol. Mutagen. 1993a, 22: 130-137.

NORPPA H., RENZIL., LINDHOLM C. Detection of whole chromosome in micronuclei of cytokinesis- blocked human lymphocytes by antikinetochore staining and in situ hybridization. Mutagenesis 1993, 6: 519-525.

SNYDER R., WITHZ G., BERNARD D. The toxicology of benzene. Environ. Health Perspect. 1993, 100: 293-306.

SORSA M., AUTIO K„ DEMOPOULOS N.A., JARVENTAUS H., ROSSNER P„ SRAM R.J., STEPHANOU G., VLACHODIMITROPOULOS D. Human cytogenetic biomonitoring of occupational exposure to 1,3-butadiene. Mutation Res. 1994, 309: 321-326.

STONE J.G., JONES N.J., McGREGOR A.D., WATERS R. Development of a human biomonitoring assay using buccal mucosa: comparison of smoking-related DNA abducts in mucosa versus biopsies. Cancer Res. 1995,55: 1267-1270.

SURRALLES J., AUTIO K., NYLUND L„ JARVENAUS H„ NORPPA H„ VEIDEBAUM T„ SORSA M., PELTONEN K. Molecular cytogenetic analysis of buccal cells and lymphocytes from benzene- exposed workers. Carcinogenesis 1997, 18: 817-823.

SURRALLES J., CATALAN J„ CREUS A., NORPPA H„ XAMENA N„ MARCOS R. Micronuclei induced by alachlor, mitomycin-C and vinblastine in human lymphocytes: presence of centromeres and kinetochores and influence of the staining technique. Mutagenesis 1995, 10: 417-423.

TITENKO-HOLLAND N., MOORE L.E., SMITH M.T. Measurement and characterization of micronuclei in exfoliated human cells by fluorescence in situ hybridization with a centromeric probe, Mutation Res. 1994,312:39-50.

ZHANG L., MOCK D. Gamma-glutamyl transpeptidase activity in superficial exfoliated cells during hamster buccal punch carcinogenesis. Carcinogenesis 1989,10: 857-860. Table 1.- FISH analysis of MN in cultured (72 h) cytokinesis blocked binucleated lymphocytes of benzene-exposed Estonian petrochemical workers and controls.

Donor Sex Age Smokers Overall frequency of Mna Frequency of MN(per 1000) (per 1000) M F Mean ± SD MGG DAPI MN C + MN C-MN analysed control donors (13) 8 5 38±17 4/13 17.00 ± 8.58 23.10 ± 12.17 510 6.83 ±5.11 16.26 ± 7.58

exposed donors (38) 31 7 38±10 27/38 9.23 ± 4.38 19.17 ± 10.03 916 5.80 ± 4.88 12.70 ± 6.53

8 Mean ± SD 3 Table 2.- Analysis of MN and chromosome 9 numerical abnormalities by FISH in buccal cells of benzene-exposed Estonian petrochemical workers and controls.

Donor Age Smokers Frequency and content of MN8 Chromosome 9 analysis Mean Total MN analysed Frequency of MN (%) ± SD No. % Un-MNb C-MN C+MN No. cells hyperploidy %e (Mean ± SD) Total control donors 47±9 5/15 0.218 ±0.181 0.027 ± 0.033 0.120 ±0.116 0.071 ±0.105 11,740 0.92 ± 0.29 analysed (15)

Total exposed donors 37±12 10/18 0.130 ±0.102 0.007 ± 0.022 0.085 ± 0.082 0.037 ± 0.052 16,930 0.70 ± 0.27 analysed (18) 8 Based on the analysis of 1500 cells/donor b MN of unknown origin 68

5. INFLUENCE OF BENZENE AND BENZENE RELATED COMPOUNDS ON CYTOGENETIC DAMAGE IN HUMAN BLOOD LYMPHOCYTES (POLISH WORKERS)

Antonina Cebulska-Wasilewska, Anna Wierzewska, Ewa Kasper Environmental and Radiation Biology Department INP, Krakow, Poland.

This paper presents results from research on genotoxicity to human cells of the benzene and related benzene compounds in emission from petroleum plants. Blood samples from forty-nine persons (twenty-four workers from petroleum plants, twenty-five unexposed controls) of a similar socio-economic status and from the same region in Poland were examined for cytogenetic effects and for any relationship to confounding factors (e g. smoking habit, sex, family cancer history and seasonal influence). Peripheral blood was examined, for chromosome aberrations (CA), sister chromatid exchanges (SCE), high frequency cells (HFC) and proliferative rate index (PRI). These parameters were used as biomarkers of genotoxic anomalies. Results were analyzed by a t-test, one way and multivariate analysis of variance.

5.1. Introduction

Workers in various industrial plants, particularly those in petroleum plants, are exposed to benzene and benzene related compounds as a result of various activities in which benzene is processed, generated or used. Benzene is an important substance widely used in the industry. Most of the population occupationally exposed to these agents are exposed for a long period. Among major sources of environmental exposures are: active and passive smoking, auto exhaust, driving or riding in automobiles. Chronic benzene intoxication modulates immune responses and granulocyte enzyme systems, and leads to thrombocytopenia, leukopenia, and anemia (pancytopenia in some cases). It may trigger the formation of neoplastic diseases in some extreme cases (Parke D.V., 1996, Wallace L , (1996). The aim of this study was to examine levels of cytogenetic effects in samples of peripheralblood of workers from petroleum plants in Poland by comparison with unexposed people and to investigate the relationship to confounding factors exogenous such as smoking habits (unfortunately, still very popular in Poland) or seasonal influences, and endogenous ones (age, sex, family cancer history).

5.2. Materials and Methods

Blood sampling was done between June 1993 and June 1994, among unexposed and occupationally exposed healthy donors subgroups as described previously (Cebulska- Wasilewska et al., 1995). Exposed individuals were from two petroleum plants in Poland. 69

Healthy donors were chosen from an industrial and countryside areas of Southern Poland. The industrial area controls were administrative staff at a petroleum plant and the countryside regions were inhabitants of two neighboring villages with a low level of pollution (Nowicki M. et al., 1990) and a low level of total cancer cases (ZatonskiW., Tyczynski J., 1990). Both groups were interviewed about infectious diseases, drugs, diet, smoking habits and exposure to X-rays during the 2 to 3 months before cytogenetic examination. Blood samples were collected by venipuncture in heparinized tubes and split into two parts. The first was transported to the laboratory of Environmental and Radiation Biology Department in Krakow where samples were processed immediately for the analysis cytogenetic damage. From the second part, blood plasma was separated, by centrifugation, of frozen at -70°C, and then transported in dry ice to the laboratory in BIBRA, UK for testing ras p21 proteins levels (Anderson D. et al., 1996). For cytogenetic analysis cultures from heparinized whole blood samples were incubated at 37°C using Eagle's medium supplemented with 20% fetal calf serum and antibiotics. Lymphocytes were stimulated with LF-7, a Polish substitute for phytohaemagglutin (PHA) (Cebulska-Wasilewska A. et al., 1990, 1992) and then cultured in the case of CA cultures for 48 h, and in case of SCE analysis cells were cultured for 72 h, with the addition of an appropriate amount of 5 -bromo-2-deoxyuridine (BrdU). One and a half hours before the end of culturing, colcemid was added (0.1 ul/ml) to each sample. Fixation and staining were performed by standard cytological procedures for both methods respectively (Carrano A.V., Natarajan A.T. 1988, IAEA 1986). Chromosome and chromatid type aberrations were scored in all metaphases acceptable for diagnosis and expressed as a total aberration frequency including gaps (TAbF), and excluding gaps (AbF). Sister chromatid exchanges (SCE) were screened in each metaphase containing at least 44 chromosomes and high frequency cells (HFC) and proliferative rate index (PRI) were evaluated as reported elsewhere (Anderson D. et al., 1993, 1988). An examination of the mean, median skewness and kurtosis showed that the main variables in the population were normally distributed so the parametric tests, t-test, one way, and multivariate analysis of variance were applied to determine significant differences between two or several variables respectively (Hazard Mumo B, et al., 1986). A significance level lower than .05 is reported as and a level lower than .005 is reported as

5.3. Results

Tables 1 and 2 present main characteristics and results of cytogenetic analysis for persons from exposed and unexposed subgroups under the study. The number of cells analyzed in the first mitosis for chromosome aberrations and in the second mitosis for sister chromatid exchanges are shown as Ml and M2 respectively. There is also presented characteristics of the donors; age, sex, smoking habits, and the means of the effects observed. Among exposed individuals 79% were males and 91% were smokers, among individuals in reference group 50% were males and 64% were smokers. There is observed rather low 70

(8.3%) frequency of exposed individuals for whom the aberration frequency exceeded ±2s the average level of the damage detected in the reference group. However, half of persons (12/24) from exposed group is characterized by the level of aberration frequency without gaps (AbF) equal or higher than 0.50 aberrations/cell (control level ±2s). Table 3 presents summary of comparison between mean values of the effects detected in subgroups according to occupational exposure status. In the exposed group there was observed a statistically significant increase in chromosomal damage (TAbF, AbF) and percent of aberrant cells (AbC). SCE levels were slightly higher in the exposed group, but were not statistically significant by comparison with the unexposed group. There were also no significant differences between exposed and unexposed groups in HFC and PRI levels. Results regarding confounding factors (Table 4), showed that smoking had caused significant increases in all types of damage analyzed except, proliferative index (PRI). Analysis of the aberration of cytogenetic damage due to sex shows that sister chromatid exchanges were found to be significantly sex dependent and HFC were also increased in females but were not significantly different from males. There were no significant differences for CA, AbC, SCE, and HFC levels in subgroups characterized according to cancer history (i.e. cancer cases reported in the immediate family). There were large differences for all the biomarkers in the study in relation to the sampling season. There were statistically significant increases in TAbF, AbF, AbC, SCE, HFC when the blood was collected in Winter. The various biomarkers for the subgroup of non-smoking persons in the relation to the occupational exposure are shown in Table 5. All levels of the cytogenetic damage under the study is much higher in exposed workers. Although size of both samples (nonsmoking exposed workers and unexposed) were extremely small, increases due to exposure observed in effects on TAbF, AbF and HFC were statistically significant.

5.4. Discussion

Our studies have examined the influence of occupational exposure on the various parameters measured in workers from two petroleum plants. The highest level of all biological points studied was observed in the exposed group of workers from petrochemical plants. Results show that the exposed group has statistically significant increases in chromosomal damage, and percent of aberrant cells. Although sample size of the non smoking group in our study was small, a significant increase in a cytogenetic damage due to occupational exposure to benzene or benzene related compounds was observed in nonsmoking people too. A multivariate regression analysis of the results from the whole groups under the study, confirmed a significant casual association, between cytogenetic damage and occupational exposure to benzene related compounds (Table 6). Marked increases in chromosome aberration frequencies in lymphocytes of workers exposed to high levels of benzene have been reported in the literature of (Fomi A. 1996, Major J. et al., 1994, Sorsa M. et al., 1992, Tompa A. et al., 1994). Also studies in petroleum plant in Central part of Poland confirmed an influence of occupational exposure on health conditions of workers (Hubner H. et al., 1991). The other large studies performed in Hungary also showed 71

significantly higher frequencies of chromosomal aberrations for exposed petroleum plants workers, but there was no linear relation between aberration frequencies and the duration of exposure to benzene (Fomi A. 1996, Tompa A. et al., 1994). Such a nonlinear relationship between cytogenetic damage or ras p21 protein levels detected and number of working years (or category of smoking habit) was also observed in our results, an increase in the level of observed cytogenetic damage varied significantly with the duration of occupational exposure, but the relationship was not linear (Anderson D, et al. 1996). Smoking was found to affect significantly various biomarkers both in the exposed and unexposed subgroups. Levels of SCE and RFC detected were also sex dependent. Such a variability with smoking and sex was also found in studies of UK population (Anderson D, et al. 1986, 1988, 1993).

A seasonal influence on genotoxic biomarkers has been already observed by (Perera F. et al, 1992 and by Anderson D. et al, 1986, 1993, 1988) in a UK control population. Our data confirm also that there is some seasonal effect on cytogenetic damage in the whole population (exposed and unexposed sub-groups) and biological effects observed are higher in Winter. There are various possible reasons for such effects. Environmental pollution might be higher in the Winter season due to the intensive combustion of coal for residential heating during the winter months. It is also possible that the effect is caused by different in Winter metabolic efficiencies of individuals to scavenge initial damage from environmental contaminants. The radiomimetic character of benzene toxicity indicated that, as with ionizing radiation, oxygen radicals or reactive oxygen species (ROS) were ultimately involved, and that vitamin C was probably a vital component of the biological defense against ROS and benzene toxicity (Parke D. V. 1996). Cytogenetic damages in this study appeared to be useful biomarkers of genotoxic risk involved to occupational exposure. Smoking and other factors such as age and sex can have an impacton it.

Acknowledgments

Research was partially supported by contract CIPDCT 925100 of the Commission of the European Communities. The able assistance of J.Wiltowska and E.Bartel is greatly appreciated.

References

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ANDERSON D., EDWARDS A.J., GODBERT P., JENKINSON PC. AND BUTTERWORTH K.R. Variability in chromosome aberrations, sister chromatid exchanges and mitogen induced blastogenesis in peripheral lymphocytes from control individuals. Environ. Hlth. Persp. 1993,101 (3): 83-88.

ANDERSON D„ JENKINSON PC., DEWDNEY R.S., FRANCIS A.J., GODBERT P. AND BUTTERWORTH K.R Chromosome aberrations, mitogen induced blastogenesis and proliferative rate index in peripherial lymphocytes from 106 control individuals of the U K. population. Mutation Res. 1988, 204: 407-420.

ANDERSON D., HUGHES J.A., CEBULSKA-WASILEWSKA A, NIANKOWSKA E. AND GRACA B. Ras oncoproteins in human plasma from lung cancer patients and healthy controls. Mutation Res. 1996, 349: 121-126.

ANDERSON D., HUGHES J.A., CEBULSKA-WASILEWSKA A., WIERZEWSKA A., KASPER E. Biological Monitoring of Workers Exposed to Emissions from Petroleum Plants. Env. Health Persp. 1996,104 (3): 609-613.

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CEBULSKA-WASILEWSKA A., WIERZEWSKA A., KASPER E„ PAKA B. AND KOZIARA L. Biomonitoring of a human population exposed to benzene related genotoxic components. Proceedings WHO Workshop "Monitoring of Exposure to Genotoxic Substances", 1995. p. 82-95.

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Table 1- Characteristic of individuals and cytogenetic damage detected in the lymphocytes of exposed to benzene subgroup 1

Samp. Age Sex S Ml M2 TAbF±SE AbF AbC SCE HFC PRI

1 35 M Y 87 74 .046 ± .023 .046 4.6 4:28 0.0 2.50

2 38 F Y 97 75 .021 ± .010 .010 2.1 6.40 2.0 2.42

3 41 F Y 100 75 .070 ±.025 .060 7.0 6.24 2.0 2.16

4 45 M Y 99 74 .000 ± .000 .000 0.0 6.94 10.0 2.24

5 40 M Y 100 79 .020 ±.014 .020 2.0 6.60 2.1 2.27

6 37 M Y 160 62 .006 ±.006 .006 0.6 5.32 2.0 2.46

7 46 M Y 100 74 .020 ± .014 .020 2.0 6.22 4.1 2.20

8 46 M Y 234 75 .047 ±010 .021 4.7 6.18 4.0 2.34

9 36 M N 200 75 .030 ±.012 .030 3.0 5.52 4.0 2.32

10 42 M Y 200 79 .045 ±.014 .040 4.5 6.46 12.0 2.08

11 35 M Y 100 93 .080 ± .025 .060 7.0 7.62 20.0 1.98

12 49 M Y 92 94 .065 ± .024 .054 6.5 6.52 10.0 2.22

13 32 F Y 176 93 .034 ±.010 .017 2.8 6.24 4.0 2.58

14 48 M Y 100 88 .100 ±.028 .080 9.0 5.66 0.0 2.32

15 31 M Y 343 89 .071 ± .020 .056 6.6 8.96 6.4 2.26

16 31 M N 250 93 .082 ± .022 .058 8.2 7.66 5.6 2.28

17 37 M Y 249 93 .067 ±.021 .054 6.7 7.05 1.3 2.13

18 39 M Y 250 97 .055 ± .019 .047 5.5 7.05 4.1 2.16

19 41 M Y 250 91 .075 ±.022 .062 6.7 7.68 4.0 2.21

20 40 M Y 200 94 .105 ±.031 .095 9.0 8.08 14.3 2.14

21 48 M Y 200 91 .075 ± .021 .050 7.5 9.16 6.0 2.31

22 48 F Y 200 90 .095 ± .022 .050 8.5 9.72 12.0 2.50

23 44 F Y 200 91 .065 ± .019 .045 6.0 8.30 10.0 2.34

24 38 M Y 300 98 .063 ± .019 .050 5.8 8.51 12.0 2.30

Ml, M2 - No of cells in the first and second mitosis, respectively, TAbF - total aberration frequency (including gaps) + Standard Error (SE), AbF - aberration frequency (excluding gaps), AbC - percent of aberrant cells, SCE - sister chromatid exchanges per cell, PRI - proliferative rate index (MI+2xMII+3xMIII)/(MI+MII+MIII), HFC - high frequency cells (percent of cells displaying number of exchanges per cell higher than the 95% of the control population distribution) 75

Table 2.- Characteristic of individuals and cytogenetic damage detected in the lymphocytes of healthy and unexposed donors subgroup

Samp. Age Sex S Ml M2 TAbF±SE AbF AbC SCE HFC PRI

1 35 F N 326 74 .015 ± .002 .005 1.5 7.6 4.1 2.47

2 38 M Y 3 49 75 .066 ±.022 .043 6.5 6.2 1.3 2.17

3 41 F N 317 75 .038 ±.016 .021 3.5 7.5 10.7 1.86

4 45 M N 330 74 .037 ±014 .020 3.7 5.8 2.7 2.30

5 40 F N 208 79 .041 ± .015 .019 3.5 7.3 5.1 2.15

6 37 F Y 342 62 .114± .024 .053 10.9 8.0 11.3 2.33

7 46 F Y 354 74 .019 ±002 .003 1.8 7.1 5.4 2.12

8 46 F Y 316 75 .035 ±016 .021 3.5 9.5 22.7 2.43

9 36 M Y 354 75 .013 ± .003 .008 1.1 7.9 12.0 2.28

10 42 F Y 356 79 .048 ±017 .028 4.4 9.1 16.5 2.48

11 35 M N 302 93 .026 ± .006 .013 2.3 6.1 2.2 2.47

12 49 M Y 346 94 011 ± 005 Oil 1.1 7.1 7.4 2.53 .

13 32 M N 276 93 .018 ±.005 .007 1.4 6.6 1.1 2.18

14 48 M Y 225 88 .044 ±.010 .026 4.0 5.6 - 2.40

15 31 M Y 305 89 .036 ±007 .016 3.6 6.3 2.2 2.23

16 31 F Y 305 93 .029 ±.007 .016 2.9 8.4 7.5 2.34

17 37 F Y 305 93 .059 ±.006 .013 5.6 7.7 6.5 2.42

18 39 F N 301 97 .016 ± .004 .006 1.6 6.9 4.1 2.23

19 41 F N 300 91 .023 ± .008 .020 2.3 6.1 2.2 2.56

20 40 M Y 301 94 .013 ±004 .006 1.3 6.4 0.0 2.30

21 48 M Y 307 91 .039 ± .008 .022 3.9 8.1 2.1 2.51

22 48 M Y 299 90 .036 ± .008 .020 3.3 8.5 14.2 2.44

23 44 M Y 303 91 .009 ±005 .009 0.9 7.0 14.4 2.51

24 38 M Y 300 98 .003 ± .003 .003 0.3 5.5 4.4 2.62

25 32 M N 301 95 .010 ± .005 .010 1.0 6.4 0.0 2.67

Ml, M2 - No of cells in the first and second mitosis, respectively, TAbF - total aberration frequency (including gaps) ± Standard Error (SE), AbF - aberration frequency (excluding gaps), AbC - percent of aberrant cells, SCE - sister chromatid exchanges per cell, PRI - proliferative rate index (MI+2xMII+3xMIII)/(MI+MII+MIII), HFC - high frequency cells (percent of cells displaying number of exchanges per cell higher than the 95% of the control population distribution) 76

Table 3. - Mean values of various biomarkers observed in the investigated groups according to occupational exposure status

Ex No Age Ml M2 TAbF AbF AbC SCE PRI HFC /cell /cell % /cell %

0 25 40 7729 2132 .032 .017 3.1 7.0 2.4 6.7

1 24 41 4290 1287 .056** .043** 5.3** 7.2 2.3 7.0

EX - occupational exposure to benzene related compounds: 0 unexposed, 1 - exposed; No - number of individuals investigated, Ml, M2 - No of cells in the first and second mitosis, respectively, TAbF - total aberration frequency (including gaps), AbF - aberration frequency (excluding gaps), AbC - percent of aberrant cells, SCE - sister chromatid exchanges per cell, PRI - proliferative rate index (MI+2xMII+3 xMIII)/(MI+MII+MIII), HFC - high frequency cells (percent of cells displaying number of exchanges per cell higher than the 95% of the control population distribution). A significance level lower than .05 is reported as "*", and a level lower than .005 is reported as

Table 4. - Influence ofconfounding factors on the average levels ofthe biomarkers under the study

Factor No Age TAbF/cell ± SE AbF AbC SCE PRI HFC /cell % /cell %

All 49 41 .044 ±.014 .032 4.1 7.0 2.3 6.3

Ex 0 25 40 032 ± .009** .017** 3.1** 7.0 2.34 6.7

1 24 41 .056 ± .018 .043 5.3 7.2 2.38 7.0

S 0 11 39 .032 ± .010** .019** 2.9* 6.6* 2.31 4.3*

1 38 41 .047 ± .015 .033 4.5 7.2 2.30 7.6

Sex F 16 40 .045 ± .013 .025 4.3 7.5** 2.32 8.5

M 33 41 .043 ± .014 .032 4.1 6.8 2.31 6.1

CiF 0 43 40 .042 ±013 .029 4.0 7.0 2.31 6.6

1 6 40 .054 ±017 .038 5.2 7.2 2.28 8.8

Sn S 24 40 .033 ± 011** .023** 3.2** 6.3** 2.36** 3.0**

W 25 41 .059 ± .018 .040 5.6 8.0 2.24 11.1

S - smoking, 0-nonsmokers, 1 -smokers, F - female, M - male, CiF - 0 = no cancer reported in immediate family, 1 = cancer reported, No - number of individuals, Sn - season, S - Summer, W - Winter, Ml, M2 - No of cells in the first and second mitosis, respectively, TAbF - total aberration frequency (including gaps) + Standard Error (SE), AbF - aberration frequency (excluding gaps), AbC - percent of aberrant cells, SCE - sister chromatid exchanges per cell, PRI - proliferative rate index (MI+2xMII+3xMIII)/(MI+MII+MIII), HFC - high frequency cells (percent of cells displaying number of exchanges per cell higher than the 95% of the control population distribution) 77

Table 5. - The effect of occupational exposure on the biomarkers level in the non-smoking subgroup.

Ex No Age TAbF/cell ± SE AbF AbC SCE PRI HFC /cell % /cell %

23 41 .033 ± .014 .021 .032 6.6 2.32 4.3

0 18 38 .025. ± 009** .014** .023 6.5 2.32 3.6*

1 5 44 .063 ± .018 .049 .063 6.8 2.30 6.9

TAbF - total aberration frequency (including gaps) + Standard Error (SE), AbF - aberration frequency (excluding gaps), AbC - percent of aberrant cells, SCE - sister chromatid exchanges per cell, PRI - proliferative rate index (MI+2xMII+3xMIII)/(MI+MII+MIII), HFC - high frequency cells (percent of cells displaying number of exchanges per cell higher than the 95% of the control population distribution)

Table 6. - Values of the statistically significant regression coefficients after using stepwise multivariate regression analysis for the biomarkers detected under the study

TabF AbF AbC SCE HFC PRI /cell /cell % /cell % Mean .046 .032 4.5 7.1 6.9 2.3 ± SD .033 .023 3.1 1.3 6.6 .17 H .0236 .0229 .0229 n n n Sex n n n 0.49 n n S n n n 0.73 3.49 n Season .0276 .0183 .0252 1.65 8.99 -.118 CIF n n n n n n R .588 .629 .581 .725 .688 .339 r2 .340 .397 .337 .526 .465 .115 F 27.06 34.50 26.68 55.44 44.14 13.78 p value .0000 .0000 .0000 .0000 .0000 .0003

TAbF - total aberration frequency (including gaps), AbF - aberration frequency (excluding gaps), AbC - percent of aberrant cells, SCE - sister chromatid exchanges per cell, PRI - proliferative rate index (MI+2xMII+3xMIII)/(MI+MII+MIII), MFC - high frequency cells (percent of cells displaying number of exchanges per cell higher than the 95% of the control population distribution) SD = Standard Deviation, n = Independent variables excluded by analysis. R, correlation coefficient; R2, proportion of variability explained by variables (factors) accepted; F = variance ratio 78

6. EXAMINATION OF RAS ONCOPROTEINS IN HUMAN PLASMA FROM HEALTHY CONTROLS AND WORKERS EXPOSED TO PETROLEUM EMISSIONS

Diana Anderson, Jane Hughes BIBRA International, Carshalton, Surrey, United Kingdom

6.1 Introduction

Increased ras (p21) protein levels resulting from genetic damage of oncogenes may play a major role in the molecular epidemiology of cancer and could be a possible prognostic biomarker as has been reported for lung cancer patients and colon cancer (Anderson D.et al., 1996b - Perera F.P. et al, 1992). It was shown that 45% of untreated lung cancer patients have an increase in ras (p21) proteins by comparison with 6% in the control population (Anderson D.et al., 1996b). However, oncogenes e g. ras (Brandt-Rauf P.W. et al, 1990 - Brandt-Rauf P.W., 1991), ras and fos (Brandt-Rauf P.W. et al., 1990b) and others (Brandt-Rauf P.W et al., 1989) could also represent potentially significant markers of exposure to occupational or environmental carcinogens (Brandt-Rauf P.W. etal, 1992). Ras is involved with the regulation of cellular proliferation. Ras genes express a protein of 132 amino acids of molecular weight 21KDa, designated as p21. Ras is frequently found to be activated in many human cancers (Bishop J.M., 1991) with mutations in codons 12, 13 and 61 of one of the three ras genes, H-ras and N-ras, thereby converting these genes into active oncogenes. In this study ras (p21) protein levels were examined in plasma from healthy controls and workers exposed to emissions from petroleum plants. Samples were obtained from two petroleum plants in Central and Southern Poland and from a shale-oil petrochemical plant in Kohtla-Jarve, Estonia.

6.2 Methods

Blood samples were collected from workers at both the Polish and Estonian plants. For the Polish samples, two subgroups of unexposed donors were chosen from administrative staff at the petroleum plants and from the region of Southern Poland characterised by a low level of pollution (Nowicki M., 1990) and a low level of total cancer cases (Zatonski W.e/ al., 1990). For the Estonian samples, unexposed controls were compared to workers who had been exposed in the work environment to benzene (B, benzene manufacturing section) and benzene and polyaromatic hydrocarbons (B+PAH, cokery emissions). 79

Screening of serum oncoproteins was carried out by gel electrophoresis, Western blotting and densitometry. Perera et al. (Perera F.P. et al., 1992) suggested a method for determining elevated levels of ras proteins where an increase was greater than two standard deviations above the mean negative control values. This method was adopted in the present studies. The method has already been used to screen plasma samples from workers exposed to 1,3-butadiene in the workplace (Anderson D et al., 1996a) and also in cancer patients (Anderson D. et al., 1996b). The primary antibody used for the detection of p21 proteins in the plasma was an IgG2A monoclonal antibody (supplied by Oncogene Science Inc., New York) raised in mice against a recombinant ras protein. This antibody was able to detect the protein produced by all three members, Harvey, Kirsten and N-ras, of the ras gene family and did not distinguish between normal forms and mutants carrying different amino-acids at position 12. It is defined as a pan-ray antibody The sensitivity of the antibody was detected by electrophoresis of known quantities of purified Kirsten ras protein, a generous gift from Dr H. Paterson, Chester Beatty Laboratories, Institute of Cancer Research, London, UK. Results were analysed both parametrically and non-parametrically using paired, two-sided t-tests and Mann-Whitney tests. Non-parametric statistics were used because there were a number of zero values in the controls and exposed groups so violating a normal distribution.

6.3. Results

Tables 1 and 2 show the ras levels in plasma measured as the optical density of the area under the peak of 21 kDa band for exposed and negative controls of the Polish samples. There were 3 plasma samples in the exposed group and 2 in the negative control group with levels above the mean ± 2 SD of the unexposed control group. Tables 3 and 4 show the ras levels in plasma for exposed and negative controls of the Estonian samples. There were 3 plasma samples in the exposed group and 1 in the unexposed control group with levels above the mean ± 2SD of the unexposed control group. There were no significant differences between the means of the group .

6.4 Discussion

It has been suggested that the presence of elevated levels of ras (p21) proteins could be a positive prognostic marker or biomarker for lung cancer. An elevation of ras (p21) protein levels in adult humans has also been shown to correlate with prior exposure to hazardous chemicals (Brandt-Rauf P.W. et al., 1990 - Brandt-Rauf P,W., 1991 - Brandt-Rauf P.W. et al., 1988). It is possible that exposure of workers to potentially hazardous chemicals such as benzene and benzene-related compounds could 80

lead to raised ras (p21) protein levels, the subsequent detection of which could be considered as a biomarker of exposure and could provide valuable information in any epidemiological study involving exposure to known human carcinogens. Samples screened in this study showed evidence of protein bands running at 21 kDa with varying optical densities (OD). By using the method suggested by Perera et al (Perera F.P. et al, 1992), i.e. comparing the mean of 2 standard deviations of a control group with that of an exposed group, a total of 5 samples (3 exposed and 2 control) were raised in the Polish study and 4 in the Estonian study (3 exposed and 1 control). In the Estonian study 3 of the 4 individuals who had raised levels were sampled on two occasions, but the levels were not elevated on the second occasion. Using the methods outlined in this study, the OD of ras bands plotted against concentration of ras shows a linear response (Anderson D. et al, 1996a). In another study (data not shown), 3 plasma sampleswere run on 4 different gels and in triplicate on each gel. Some variability in the OD of bands of 21 kDa was obtained but the overall assessment of the samples compared to control did not change. Optical densities obtained for Estonian samples 39, 44 and 108, run twice on separate gels in this study, also showed variability but the same results were obtained when compared to the negative controls. The populations examined in this study have not demonstrated a link between exposure to petroleum emissions in the workplace and raised levels of ras (p21) protein in plasma. A previous study which was also part of a CEC collaborative research programme examined samples from workers exposed to 1,3-butadiene and styrene (Anderson D. et al., 1996a) and also showed no significantly increased levels of ras. However, since it was shown that cancer patients did have elevated ras (p21) protein levels (Anderson D. et al, 1996b) it could be useful to repeat the screening procedure on workers with raised levels after a period of time to ascertain whether the increase is sustained or even increased.

References

ANDERSON D„ HUGHES J.A., BRINKWORTH M.H., PELTONEN K„ SORSA M Levels of ras oncoproteins in human plasma from 1,3-butadiene exposed workers and controls. Mutation Res. 1996a, 349: 115-120.

ANDERSON D„ HUGHES J.A, CEBULSKA-WASILEWSKA A., NIZANKOWSKA E„ GRACA B. Oncoproteins in human plasma from lung cancer patients and healthy controls. Mutation Res. 1996b, 349: 121-126.

BISHOP J.M Molecular themes in oncogenesis. Cell 1991,64:235-248.

BRANDT-RAUF P.W. Advances in cancer biomaikers as applied to chemical exposures: the ras oncogene andp21 protein and pulmonary carcinogenesis. JSoc.Occup.Med 1991,33:951-955. 81

BRANDT-RAUF P.W., NIMAN H.L. Serum screening for oncogene proteins in workers exposed to PCBs. BrJIndMed. 1988,45:689-693.

BRANDT-RAUF P.W., NIMAN H.L., SMITH S.T. Correlation between serum oncogene protein expression and the development of neoplastic disease in a worker exposed to carcinogens. J.Roy.Soc.Med. 1990, 83: 594-595.

BRANDT-RAUF P.W., SMITH S., HEMMINKI K„ KOSKINEN H„ VAINIO H. Serum oncoproteins and growth factors in asbestos and silicosis patients. IntJ.Cancer 1992,50:881-885.

BRANDT-RAUF P.W., SMITH S., NIMAN H.L., GOLDSTEIN M.D., FAVATA E. Serum oncogene proteins in hazardous waste workers. J.Soc.Occup.Med. 1989,39:141-143.

BRANDT-RAUF P.W., SMITH S., PERERA F.P., NIMAN H.L., YOHANNAN W„ HEMMINKI K, SANTELLA R.M. Serum oncogene proteins in foundry workers. J.Soc.Occup.Med. 1990b, 40: 11-14.

NOWICKIM Ambient Air Pollution in Poland in 1987 fin Polish). Warszawa Institute of Environmental Protection, 1990.

PERERA F.P., HEMMINKI K„ GRYZBOWSKA E., MOTYKIEWICZ G„ MICHALSKA J., SANTELLA R.M., YOUNG T.L., DICKEY C„ BRANDT-RAUF P.W., DEVIVO I., BLANER W„ TSAI W-Y., CHORAZY M. Molecular and genetic damage in humans from environmental pollution in Poland. Nature 1992, 360:256-258.

ZATONSKIW., TYCZYNSKI J. The geography of cancer in Poland. Arch. Environ. Prot. 1990, 3-4: 17-30. 82

Table 1.- Plasma samples from workers exposed to petroleum/benzene emissions from petroleum plants in Central (POL 1) and Southern (POL 2) Poland - Summary of densitometric data

Peak area 8,1 ” Peak area 3,1”

POL 1 1st dev 2nd dev. POL 2 1st dev 2nd dev

1 3.65 2.44 1 NR 0.90

2 1.91 1.25 2 0.75 0.42

3 2.79 2.00 3 NR 0

4 0 0 4 NR NR

5 0.79 0.48 5 NR NR

6 2.80 2.34 6 0 0

7 0.37 0+ 7 1.50 0.81

8 0.56 0.60 8 1.90 0.90

9 0.39 0 9 0.33 0+

10 NR 0.68 10 2.19 1.41

11 NR 0.68

12 NR 0.67

13 1.61 0.75

14 NR 0.72

Mean + 2 standard deviations of POL 3 = 1.58 Mean + 2 standard deviations of POL 5 = 2.13 Mean + 2 standard deviations of POL 7 = 2.93 Mean + 2 standard deviations of POL 3+5+7 = 2.53

a peak area of band at 21 kD using samples containing 150 mg protein and 2 minute film exposure. b number in bold denotes elevated level of ras oncoprotein compared to "mean + 2 standard deviations" of POL 3+5+7 results 1st dev. first development of blot 2nd dev. second development of blot NR No result 0+ Very weak band, unable to measure optical density 83

Table 2.- Plasma samples from unexposed people in Poland (POL 3, 5 and 7) - Summary of densitometric data

Peak area a,bc

POL 3 1st dev 2nd dev POL 5 Peak area 1,1* POL 7 Peak area"*

1 0.64 0.34 11 1.01 18 1.39

2 0.56 0+ 12 0.69 19 0.77

3 NR 0.22 13 1.60 20 0.44

4 NR NR 14 0 21 1.94

5 NR 0+ 15 0.60 22 0.98

6 NR 0.91 16 1.39 23 1.64

7 NR 1.70 17 1.51 24 0.94

8 NR 0.36 25 0

9 NR 0+ 26 0

10 NR 0.58 27 0.72

28 1.66

29 0.75

30 1.44

31 3.33

32 2.66

33 1.42

65 0

66 0.66

Mean + 2 standard deviations of POL 3 = 1.58 Mean + 2 standard deviations of POL 5 = 2.13 Mean + 2 standard deviations of POL 7 = 2.93 Mean + 2 standard deviations of POL 3+5+7 = 2.53 a peak area of band at 21 kD using samples containing 150 mg protein and 2 minute film exposure. b number in bold denotes elevated level of ras oncoprotein compared to "mean + 2 standard deviations" of POL 3+5+7 results

1st dev. first development of blot 2nd dev. second development of blot NR no result 0+ very weak band, unable to measure optical density 84

Table 3.- Plasma samples from workers exposed to benzene/polyaromatic hydrocarbons from Estonia (EST 2, 4 and 5) - Summary of densitometric data

EST 2 Peak area* -1" EST 2(B) Peak area*' 1’ EST 4 Peak area1* EST 5 (B) Peak area** (B+PAH) (B+PAH)

1 0.35 23 0.91 75 0.72 103 0

2 1.21 24 0.51 76 0.12 104 0.12

3 0.32 25 1.02 78 0.13 105 0.63

4 0.43 26 1.87 79 0.17 106 0.09

5 0 27 0.39 80 0.13 107 0.29

6 2.03 28 0.90 81 0.51 108d 0/0.49

7 0.61 29 0.20 82 0 109 0.21

8 0.94 30 1.49 83 0.88 110 0.29

9 0 31 0 84 0.16 111 0.94

10 0 32 0.73 85 0 112 0.14

11 0.56 33 0.38 86 0 113 0.16

12 0 34 0.51 87 0.11 114 0

13 0 35 0.22 88 0.52 115 0.27

14 1.08 36 0.39 89 0.55 116 0.34

15 0 37 0.25 90 1.49 117 0

16 0 38 0 91 0.64 118 0

17 0 39d 0.65/0.22 92 0.53 119 0

18 0 40 0.19 93 0.68 120 0

19 0.67 41 1.16 94 0.84 121 0.43

20 1.21 42 0.35 95 2.59 122 0.26

21 0.79 43 0.99 96 0.90 123 1.12

22 0 44d 1.25/0 97 0 124 0.22

45 0.26 98 0 126 0.43

46 0 99 0 127 0.67

47 0.38 100 0.49

102 0

Mean + 2 standard deviations of EST 3 = 1.61 Mean + 2 standard deviations of EST 6 = 1.26 Mean + 2 standard deviations of EST 3+6 = 1.50 a peak area of band at 21 kD using samples containing 150 mg protein and 2 minute film exposure. b number in bold denotes elevated level of ras oncoprotein compared to "mean + 2 standard deviations" of EST 3+6 results c Samples were run on two separate gels B Benzene PAH Polyaromatic hydrocaibon 85

Table 4.- Plasma samples from unexposed people from Estonia (EST 3 and 6). Summary of densitometric data

EST 3 Peak area 3,6 EST 6 Peak area a,b

48 0.15 128 0.17

49 0.33 129 0.71

50 0.23 130 0.35

51 0.65 131 1.38

52 0.73 132 0

53 0.66 133 0.19

54 0.45 134 1.16

55 1.26 135 0.29

56 0.80 136 0

57 0.18 137 0.68

58 0.34 138 0

59 0 139 0

61 0.16 140 0.23

62 1.10 141 0.12

63 0.82

64 0.47

65 1.13

66 1.27

67 0

68 0.81

69 0.70

70 1.04

71 2.08

72 0.57

73 0

74 0.44

Mean +• 2 standard deviations of EST 3 1.61 Mean + 2 standard deviations of EST 6 = 1.26 Mean + 2 standard deviations of EST 3+6 = 1.50 1 Peak area of band at 21 kD using samples containing 150 mg protein and 2 minute film exposure. b number in bold denotes elevated levels of ras oncoprotein compared to "mean + 2 standard deviations" of EST 3+6 results. 86

7. MONITORING OF HUNGARIAN URBAN AREAS, OIL REFINERY SITES AND SERVICE STATIONS

Alan Pinter, Anna Paldy, Eva Vaskovi, Julianna Bacskai, Gabor Mayer, Istvan Vincze “Johan Bela” National Instituteof Public Health, Budapest, Hungary

Specific objectives of the activities carried out by the National Institute of Public Health, Budapest, within the project were: i) application of existing methodologies for the monitoring of benzene levels in ambient air in urban and industrial settlements; ii) personal monitoring of benzene exposure in different subjects; iii) epidemiological studies in exposed population. To this aim, three interrelated subprojects were undertaken: 1. Situation analysis of the oil refinery at Szazhalombatta and surrounding settlements 2. Assessment of outdoor benzene exposure within the oil refinery at Szazhalombatta; 3. Exposure assessment to benzene at filling stations in Budapest. The main results of these studies are summarized below.

7.1. Situation analysis of Szazhalombatta and surrounding settlements

1.1.1.Study areas.- Three sites were selected for this study. Szazhalombatta (site 1) is a medium size town with 16.000 inhabitants, 30 km south from Budapest. Two major emission sources are close to the town. The oil refinery with a capacity of 7.0-7.5 milions of tons of crude oil is the biggest in Hungary. Main emitted pollutants are aliphatic and aromatic hydrocarbons, SO2, NOx, and CO. The other is a power plant producing more than 2000 MW of electric energy and using either the heavy fraction of oil refinery or natural gas as alternative source. Main emissions are SO2, NOx, CO and dust containing heavy metals, first of all nickel and vanadium. Air quality of the settlement is determined by these two industries - other sources like traffic and home heating are less important. The second site selected was Csepel island. There are several small villages in this area, of which three were included in the study. The close vicinity of the industries, the ruling wind direction ofNW-SE and the previous measurements of air pollutants substantiated the study area. The population of the three villages amounted to 3.000. Godollo (site 3) is a medium size town with 29.000 inhabitants. It was selected as control area because of the lack of industrial emission sources. One main road crosses the town, which, along with home heating, accounts for the air quality.

1.1.2. Methods.- Inorganic pollutants and aromatic hydrocarbons were monitored with active samplers. In addition, benzene and toluene concentrations were measured at the three study areas, outdoor and indoor, with repeated measurements with passive samplers. A cross sectional study was carried out in the three designed settlements to assess the health status of children, regarded as the most sensitive population. 87

1.1.3. Results.- Outdoor measurements. Three series of measurements were carried out with passive samplers for determination of benzene and toluene concentrations in different places in Szazhalombatta. The measured levels of benzene were generally low, the average concentrations varied between 6.0 and 15.1 pg/m3. There was no statistically significant difference between measuring points either close or far from the traffic (Table 1). Similarly, there was no difference in toluene concentrations. When the results of three sites were compared, again, generally low levels were found and without any differences between the regions (Table 2). Indoor air measurements. The results of the mean values of pollutants in the indoor air are shown in Table 3. There was no significant difference in the mean values of aromatic hydrocarbons. In sites 1 and 2, benzene concentration was in the range of 1.3 - 49.4 pg/m3, whereas in Godolld the range was larger: 1.4 - 183 pg/m3. As regards to formaldehyde and NO2, there was a significant difference between the indoor air concentrations of these pollutants between site 2 (lowest concentration) versus sites 1 and 3. Health status. Summary of the results of lung function tests are shown in Table 4. As regards mean values of the lung function parameters, there was a significant difference between the mean values of I VC and PEF between sites 2 and 3. Concerning lung function parameters relating to physical development and fitness (IVC, FVC), significantly more children had less than 100% of the reference value of IVC in the exposed sites 1 and 2 than in site 3. The correlation was studied between lung function parameters and indoor air pollutants. In site 1, PEF values showed a significant negative correlation with the number of cigarettes smoked by the parents at home (r=0.2424, p=0.045). A large number of clinical laboratory examinations were carried out (Table 5). There was no significant difference in the mean values of WBC, SG, ST RBC, MCV, B lymphocytes, T suppressor lymphocytes. Significant differences were found in the mean values of hematocrite (site 1: 38.86 + 2.73%; site 3: 40.62 + 2.23%; site 2: 38.86 + 3.4%), hemoglobin concentration (site 1: 131.7 + 8.87 g/L, site 3: 135.66 + 6.63 g/L, site 2: 125.77 + 9.53 g/L), and in the rate of T helper lymphocyte subpopulation (site 1: 55.7 + 7.18%, site 2: 52.89 + 7.83%, site 3: 49.5 + 7.24%). The concentration of zinc- protoporphyrine (ZPP), indicating the disturbance of erythropoesis, was significantly higher in site 1 (33.87 + 9.14 pmol/L) and in site 2 (35.78 + 9.02 pmol/L) versus site 3 (29.4 + 9.14 pmol/L). The mean concentration of blood lead was significantly higher in site 3 (7.95 + 3.78 pg/dL) versus site 1 (6.69 + 1.42 pg/dL) and site 2 (6.37 + 1.28 pg/dL). Blood lead level was found above 10 pg/dL in 6 children living in site 3. Low serum iron concentration was found in significantly more children in the site 1 and site 2 than in the Godolld (in site 1 68.5% of the children had serum concentration < 14,4 pmol/L, in site 2, 52.7% and in control site 31.1%). 88

Table 1 - Szazhalombatta Benzene and Toluene Concentrations (pg/m3 ) - passive sampling

Date of 05-09.12.1994 13-16.02.1995 20-26.06.1995 sampling Traffic Traffic Traffic Far Near Far Near Far Near Benzene: 9,1 11,9 0,2 2,0 6,8 7,3 min. Benzene: 17,0 20,6 8,8 11,0 9,9 11,1 max. Benzene: 11,9 15,1 5,1 6,0 8,3 9,1 average Toluene: 9,2 18,3 2,5 7,3 9,6 9,9 min. Toluene: 35,4 35,0 21,5 24,5 26 68,4 max. Toluene: 17,2 23,6 9,1 12,2 15 23,3 average

Table 2.- Szazhalombatta, Csepel Region and Godollo Benzene and Toluene Concentrations

Sampling Szazhalombatta Csepel Region GOdollo site: date 05-09 13-16 20-26 14-17 27.06 03-10 12.1994 02.1995 06.1995 02.1995 03.07.1995 04.1995 Benzene pg/m3 min. 9,1 0,2 6,8 1,1 0,4 4,8 max. 20,6 11,0 11,1 6,2 2,3 8,2 average 13,2 5,5 8,6 3,8 1,0 6,1 Toluene lig/m3 min. 9,2 2,5 9,6 2,9 0,7 6,6 max. 3,5 24,5 68,4 10,0 8,5 24,8 average 19,6 10,6 18,8 6,6 2,3 9,0 Table 3.- Concentrations of indoor air pollutants in the homes of examined children in exposed and control areas

Pollutant Unit Szizhalombatta Cscpel Gtidtilld

X s.d. min-max X s.d. min-max X s.d. min-max

Benzene Mg/m3 8.5 7.73 1.3-41.1 15.64 27.19 1.4-183 8.28 10.48 1.1-49.4

Xylene Mg/m3 20.21 20.86 0.7-112 37.26 45.72 1.9-120 17.36 12.26 0.1-68.6

Toluene Mg/m3 24.97 23.84 1.7-110 24.19 28.46 2.0-116 22.64 21.47 2.7-120

Formaldehy Mg/m3 14.11* 7.93 2.7-37.6 13.73* 9.5 2.7-46.9 9.3 6.93 2.7-27.4 de no2 Mg/m3 30.44* 20.38 4.0-99.9 32.07 22.44 2.1-99.9 19.63 13.28 0.6-57.6

* pcO.05 90

Table 4.- Mean values of lung function parameters

Szazhalombatta Csepel Goddllo

X s.d. X s.d. X s.d.

FEV1 Vs 1.75 0.83 1.80 0.42 1.59 0.57

IVCL 2.12 0.41 2.24 0.31 2.05* 0.31

PEF L/s 3.69 0.82 3.96 0.65 3.41* 0.61

FEV1/IVC 82.99 15.06 80.96 17.4 77.94 24.01

FEVlrel 102.47 18.46 104.31 22.6 97.55 30.6

IVCrel 104.88 13.86 109.03 10.1 105.83 13.47

PEFrel 115.97 20.12 123.38 19.21 111.63* 17.43

FEVl/IVCrel 91.31 16.57 89.07 19.14 85.75 26.42

*P<0.05

FEV1 forced exspiratoiy volume in the 1st second IVCL inspiratory vital capacity PEF peak exspiratoiy flow FEV1/IVC Tiffenau index L/s liter/secundum rel expressed in the percentage of the Hungarian reference values Table 5.- Mean values of laboratory parameters in 3rd and 4th grade school children in exposed (1,2) and in control (3) sites

Parameters Site 1 Site 2 Site 3 unit X s.d. min-max X s.d. min-max X s.d. min-max RBC 106/L 4,69 0,37 3,61-5,90 4,61 0,37 3,61-5,30 4,75 0,34 3,50-5,70

WBC ioV l 6,54 1,92 4,1-16,3 6,82 1,74 4,5-12,8 7,05 1,85 4,1-12,8

ST % 0,68 0,56 0-2 0,84 0,65 0-2 0,76 0,62 0-2

SG % 61,58 6,66 45-73 62 5,15 52-71 60,08 5,48 49-70

B % 31,44 6,97 16-53 33,78 4,7 25-48 32,67 6,29 23-47

Lymphoc. % 55,7* 7,18 42-78 49,48 7,24 19-61 52,89 7,83 18-65 T helper T. suppr. % 12,73 5,04 2-22 16 2,97 11,9-24,26 15,81 11,18 11,9-24,3

HCT % 38,86* 2,73 29,8-45,2 38,86 3,4 30,8-45,0 40,62 2,23 35,0-45,0

HGB g/1 131,07* 8,87 103-156 125,77 9,53 109-153 135,66 6,63 121-150

MCV fl 83,73 3,26 77,4-96,5 82,26 2,81 76,5-89,1 84,33 9,6 10,1-94

SeFe umol/L 13,1 2,3 8,6-19,9 14,4 3,9 7,7-25,6 10,6 4,3 0,3-23,6 transsat % 23,6 5,1 14,5-42,5 24,2 8,1 12,4-51,1 17,3 6,7 0,7-39,4

TRF mg/dL 219,6 24,6 109,9-266,3 236,8 24,9 176-277,7 239,2 36,8 56,7-328,1

ZPP ug/100 33,9 9,1 22-67 35,8 9 21-55 29,4 6,7 16-48 ml 92

7.2. Assessment of outdoor benzene exposure within the oil refinery plant at Szazhalombatta.

Specific objectives of this study were i) to assess the possible use of personal monitors in industrial outdoor environment, and ii) to investigate the relationship between benzene exposure and trans,trans-muconic acid concentration in urine as part of the exposure assessment process.

7.2.1. Methods.- Thirty sampling sites were designated for measuring ambient concentrations in different places - sometimes close to benzene tanks - in the oil refinery of Szazhalombatta. SKC passive samplers were used. Sampling time lasted for 5 days. Four series of measeurements were carried out. For personal monitoring of benzene exposure, a pilot study with 9 volunteers was undertaken. All subjects were interviewed and a questionnaire was filled about personal data, including life style (smoking, alcohol consumption), known diseases, years spent in exposed area, and hours per week in exposure. Benzene exposure was measured with passive monitors, which were worn at the breathing zone for 5-6 hours. Urine samples were collected before and after the working shift and stored at - 20 until analysis. Trans,trans-muconic acid determination was carried out according to Ducos et al (1990).

7.2.2. Results.- Outdoor measurements. Using passive monitors, average benzene concentrations in the oil refinery plant were between 29 and 58 pg/m3, i.e. much lower than the occupational limit value (5,000 pg/m3 in Hungary). Close to the benzene tanks, concentrations were considerably higher, but again lower than the occupational exposure limit. A summary of the results in shown in Table 1. Personal monitoring. There was a consistent difference in samples taken before and after work shift (Table 2). Two workers had high benzene exposure, as measured by passive sampler: in one case this was reflected in high muconic acid excretion, in the other it was not. Even though this pilot study does not allow reliable conclusions on the extent of benzene exposure in oil refinery workers, the methods employed seem to be adequate tools for the monitoring of occupational exposure to low benzene concentrations. 93

Table 1 - Outdoor measurementes within the oil refinery premise - Benzene concentrations (p/m3)

concentrations sampling periods

22-29.03.96 29.02-07.03.96 07-14.03.96 14-21.03.96 average* 58 51 29 29 maximum 273 347 85 134 near to benzene tank 102-273 56-347 25-85 39-134

* 30 sampling points

Table 2.- Benzene exposure and trans-trans - muconic acid concentration in urine in outdoor exposed workers

Sample muconic creatinine muconic acid Difference Benzene acid (ng(nl) (mM/L) (mg/mM (Hg(m3) creatinine) 1.B 10.15 9.4 1.08 1.21 301.55 A 14.67 6.4 2.29

2.B 11.46 8.1 1.42 0.04 26.70 A 9.89 6.8 1.46

3.B 0 8.9 0.00 2.06 13.71 A 10.91 5.3 2.06

4.B 7.18 16.0 0.45 12.6 129.84 A 92.73 7.1 13.06

5.B 1.93 12.1 0.16 1.84 8.86 A 35.41 17.7 2.00

6.B 100.27 32.2 3.10 2.41 18.15 A 188.78 34.2 5.52

7.B 60.02 37.4 1.60 5.17 1.35 A 184.37 27.2 6.78

8.B 11.89 25.1 0.47 0.53 2.39 A 13.422 13.3 1.01

9.B 22.34 27.9 0.80 0.88 0.37 A 48.05 28.6 1.68

B before work A after work 94

7.3. Exposure assessment of workers to benzene at filling stations in Budapest.

The third study carried out within the project concerned the occupational exposure to benzene at filling stations. There are two main types of filling stations at Budapest: stations with traditional filling outfit, or using outfit with recirculation device. A pilot study was initiated to assess benzene exposure in workers attending the two types of filling stations. Fourty-four stations with different technology were selected. Altogether 42 station attendants weared a passive sampler at the level of breathing zone. Samplings were carried out during a 12-hours work-shift and a 12-hours period which reflected travel, indoor and outdoor exposures (home, leisure, etc.,). The results of the pilot study are summarized in Tables 1 and 2. The low number of measurements doses not allow to draw definitive conclusions on the weight of different technologies of filling stations on occupational exposure to benzene. There were large differences between minimum and maximun values; mean values, however, did not differ considerably between the two types of stations. Average benzene concentrations measured not in working shift were 6-8 times lower than during working hours.

Table 1. Benzeneexposure ofpeople, working at filling stations with traditional technique

Exposure Benzene concentration pg/m3 min max mean SD Working 21.1 1029.3 259.0 237.8 hours After work 11.2 969.5 87.5 190.6 Ratio 0.7 32.3 6.1

Table 2.- Benzene exposure ofpeople, Working at filling stations with recirculation technique

Exposure Benzene concentration pg/m3 min max mean SD Working hours 25.7 1669.4 442.9 327.6 After work 18.7 153.4 49.4 52.9 Ratio 1.4 31.5 7.8 95

Overall conclusions

The main results obtained can be summarized as follows: comparing active and passive samplers, it was found that passive samplers can effectively be used for continuous measurements of benzene and toluene in the outdoor and indoor environment. Using passive samplers for outdoor benzene measurements, generally low concentrations were measured in all study areas, including Szazhalombatta, where oil refinery represents a major emission source. Three series of measurements were carried out for determination of benzene concentrations at different sites in Szazhalombatta: average concentrations varied between 6.0 and 15.1 mcg/m3. Samples taken within the oil refinery showed higher values (average 42 mcg/m3), but the difference from other sampling sites was not significant. Other measured pollutants (S02, N02, dust, Ni, V) were found to be well below air quality guideline value and probably do not represent a major environmental health hazard in this region. A preliminary survey of the exposure of people working at filling stations showed consistently higher exposure levels (mean 350 mcg/m3) The cross sectional epidemiological study among children showed slight impaiment of lung function, higher frequency of allergic diseases, a significant impairment of the immune system, and more frequent mild and moderate iron deficiency, possibly related to immunosuppression, among children from Szazhalombatta; a significant more frequent occurrence of iron deficient anemia was found in children from Csepel island. 96

8. CONCLUSIONS

The main findings provided by the research activities reviewed in the previous chapter may be summarised as follows.

• Environmental measurements of air benzene at several sites, including industrial settings, urban areas and fuel service stations, generally displayed relatively low values of benzene pollution, at least in comparison to occupational standards. Average environmental benzene concentrations were in the range 7-51 pg/m3 (Rome, proximity of service stations), and 6-15 pg/m3 (Szazhalombatta, oil refinery plant). • Personal exposure assessment highlighted greater exposure values for people handling petroleum fuels, sometimes above recommended industrial hygiene limits. Personal exposure among filling station attendants averaged 550 pg/m3 in the 1992 Rome survey (range 1-28000 pg/m3), 316 pg/m3 in the 1994-95 Rome survey (range 94-959 pg/m3), 910 pg/m3 in Barcelona (range 570-1830 pg/m3) and 350 pg/m3 in Budapest (range 21-1699 pg/m3). Higher exposure levels were recorded among shale oil workers, both in cokery (mean 3,900 pg/m3) and in the benzene production plant (mean 4,800 pg/m3). In this industrial setting a few individual exposure values above 10 ppm (about 30 mg/m3) were also recorded. • A time trend in occupational exposure levels was observed in the surveys carried out in Rome, with significantly lower average exposure in 1994-1995 compared to 1992. Interestingly, during the period covered by the surveys, benzene content was drastically reduced in gasoline sold in Italy (from 2.8% v/v in 1992 to 1.3% v/v in 1994-1995), in view of the enforcement of the EC Directives on benzene pollution. • Several biomarkers were evaluated for their possible use as internal dosimeters of benzene exposure. An excellent quantitative correlation with personal exposure was observed for some of them. Urinary benzene and urinary t,t-muconic acid showed great promise for acting as useful non-invasive and quantitative biomarkers of exposure even at low (below 1 ppm) benzene concentrations. Their use may help quantify personal exposure and for checking the effectiveness of measurements for the reduction of environmental benzene in a variety of situations. • The health effect of exposure to low levels of benzene and other petrochemical products is not fully elucidated, even though some indication of an excess of DNA damage was obtained in a few studies. The surveys of Italian filling station attendants showed an increase of structural chromosomal aberrations associated with benzene exposure, as well as increased rates of cells with a high incidence of SCE (High Frequency Cells) and DNA single strand breaks and/or alkali labile sites in peripheral lymphocytes. Evidence of an increased prevalence of chromosome breakage in these workers was also provided by tandem fluorescence in situ hybridisation, focussed on a hypersensitive chromosome region. These results were corroborated by the excretion 97

of modified DNA bases, which was correlated to individual exposure to benzene. Furthermore, the survey of Polish petrochemical workers highlighted, beyond the effects of several modulating and confounding factors, an increase of structural chromosome aberrations in exposed workers. No correlation was found in this study group between exposure to petroleum emissions in the workplace and raised levels of ras (p21) protein in plasma. On the other hand, serum oncoproteins may be prognostic biomarkers for cancer onset, rather then for carcinogen exposure. Negative results were reported from studies on the other exposed populations. In the two Spanish populations, one of which experienced very low benzene exposure, a non-significant increase of SCE, but no increase in micronuclei, was detected. The Estonian shale oil workers had relatively higher average benzene exposures, yet no excess of micronuclei nor hyperploidy was detected in their peripheral lymphocytes or buccal cells. These negative results, however, should be interpreted with caution in view of i) the uncertain sensitivity of micronuclei in cultured cells as a biomarker of in vivo exposure, and ii) the expected threshold mechanism for chemically-induced chromosome malsegregation, which makes the induction of aneuploidies unlikely at low exposure levels. However, another recent study, using tandem fluorescence in situ hybridisation, revealed a significant excess of chromosome breaks in peripheral lymphocytes of the same Estonian study subjects. • Even though the causative role of benzene or other petrochemicals in the findings of the cytogenetic surveys cannot be demonstrated, in vitro assays with environmental samples (air particulate matter) and petroleum fuels clearlyhighlighted the presence of genotoxic component(s) which might elicit an adverse effect in exposed subjects. • An increased risk for some neoplasms (oesophagus, brain, non-Hodgkin ’s lymphomas) was suggested by a retrospective cohort study of Italian filling station attendants, with increased relative risks among small station workers who experienced relatively greater exposure to benzene. • A cross sectional epidemiological study carried out in Hungary, suggested increased risks for several pathological parameters, including impairment lung function, a higher frequency of allergic diseases, impairment of the immune system and iron deficiency, for children living in polluted urban areas. • Knowledge of personal exposure levels proved to be mandatory in some of the studies performed in order to unravel the experimental findings. This aspect should receive a high consideration in any forthcoming biomonitoring study on benzene and petrochemicals. Several biomarkers, as shown within this research project, have the potential to work as reliable internal exposure dosimeters. • Uncertainties about the nature, intensity and duration of exposure in the study groups prevent any firm conclusions at the present time. However, the indication of an increased risk of genotoxic effects, provided by the biomonitoring of exposed workers, together with the demonstration of the genotoxicity of crude fuel samples, suggest opportunity for implementing adequate measures to reduce exposure to fuel vapoursduring vehicle refilling, when technically possible. • The environmental surveys confirmed the ubiquity of benzene pollution in urban and 98

industrial areas. Although low, the environmental concentrations were not too far from those which seem to be related to increased genetic damage in occupationally exposed subjects. Considering the widespread human exposure, studies aimed at clarifying the mechanism(s) of pathological effects caused by benzene should be a priority for the sound evaluation of human risk at low doses. In these studies, emphasis should be given to the modulation of the adverse effects of benzene by environmental chemicals and to individual susceptibility factors related to genetic polymorphisms and individual DNA repair. For the time being, it would be wise to recall the established genotoxicity of this human carcinogen, to rely on conservative estimates of risk at low doses and, consequently, to enforce an environmental policy aimed at the progressive reduction of benzene world wide in the near future. 99

PUBLICATIONS ARISING FROM THE PROJECT

ANDERSON D., CEBULSKA-WASILEWSKA A., KASPER E„ WIERZEWSKA A. et al. Factors affecting various biomarkers in lung cancer patients, Proc. Host Factors Environ. Epidem., Krakow, 1995. p. 85-89.

ANDERSON D, CEBULSKA-WASILEWSKA A, HUGHES J., KASPER E. WIERZEWSKA A. Biological monitoring of workers exposed to emissions from petroleum plants. Proc. Host Factors Environ. Epidem., Krakow, 1995. p. 117-127.

ANDERSON, D., YU, T-W., SCHMEZER, P. An investigation of the DNA damaging ability of benzene and its metabolites in human lymphocytes using the Comet assay. Environ. Mol. Mutagen. 1995, 26 (4): 305 314.

ANDERSON D, CEBULSKA-WASILEWSKA A, HUGHES J., KASPER E., WIERZEWSKA A. Biological monitoring of workers exposed to emissions from petroleum plants. Environ. Health Perspect. 1996, 104: 609-613.

ANDERSON D., NIZANKOWSKA E., CEBULSKA-WASILEWSKA A. NIZANKOWSKA E. AND GRACA, B. Ras Oncoproteins in Human Plasma from Lung Cancer Patients and Healthy Controls. Mutation Res. 1996,344: 121-126.

ANDERSON D., TAIN-WEI YU, M.M. DOBRYUSKA, RIBAS G., MARCOS R. The effects in the comet assay of storage condition on human blood. Terat. Carcinogen. Mutagen. 17, 97-102.

ANDERSON D„ HUGHES J.A., VEIDEBAUM T„ PELTONEN K„ SORSA M. Examination of ras (p21) proteins in plasma from workers exposed to benzene emissions from petrochemical plants and healthy controls. Mutation Res. 1997,381: 149-155.

ANDERSON D„ HUGHES J.A., NIZANKOWSKA E„ GRACA B„ CEBULSKA-WASILEWSKA A., WIERZEWSKA A., KASPER E. Factors affecting various biomarkers in untreated lung cancer patients and healthy donors. Environ. Mol. Mutag. 1997, 30: 205 216.

ANDREOLI, C., LEOPARDI, P., CREBELLI, R. Detection of DNA damage in human lymphocytes by single cell gel electrophoresis after in vivo and in vitro exposure to benzene or benzene metabolites. Mutation Res. 1997, 377: 95-104.

ANTOCCIA A, BATTISTONI A, CREBELLI R, DEGRASSI F, DI CHIARA D, FIORE M, LEOPARDI P, MARCON F, MENDITTO A, PALITTI F, TANZARELLA C, ZUNO A, CARERE A. Monitoraggio di addetti alia erogazione di carburanti autoveicolari: monitoraggio citogenetico. II Convegno Nazionale della Societa Italians di Mutagenesi Ambientale, Assisi 27-29 Ottobre 1993. ISTISAN Congress! 1993, vol.32, p.81.

ANTOCCIA A., CARERE A., CREBELLI R., CIMINI D„ DEGRASSI F„ LEOPARDI P„ MARCON F., SGURA A., TANZARELLA C., ZUNO A. FISH techniques to detect chromosome-loss and non disjunction in human lymphocytes 26th EEMS Annual Meeting - Workshop on Chromosome Instability and Cell Cycle Control, Rome, September 3-7, 1996. 100

CARBONELL E., PERIS F., XAMENA N., CREUS A., MARCOS R. Chromosomal aberration analysis in 85 control individuals. Mutation Res. 1996, 370: 29-37

CARERE A, ANDREOLI C, CREBELLIR, IAVARONE I, LAGORIO S, LEOPARDI P, MARCON F, PALITTIF, TANZARELLA C, ZIJNO A. Environmental and cytogenetic monitoring of Italian filling station attendants. J Environ Pathol Toxicol Oncol (in press).

CARERE A, ANTOCCIA A, CREBELLI R, DEGRASSI F, ISACCHI G, IAVARONE I, LAGORIO S, LEOPARDI P, MARCON F, PALITTI F, TANZARELLA C, ZIJNO A. Genetic effects of petroleum fuels: cytogenetic monitoringof gasoline station attendants. Mutation Res. 1995, 332: 17-26.

CARERE A, ANTOCCIA A, CREBELLI R DI CfflARA D, FUSELLI S, IAVARONE I, ISACCHI G, LAGORIO S, LEOPARDI P, MARCON F, MENDITTO A, TANZARELLA C, ZIJNO A. Esposizione a benzene ed effetti genotossici tra gli addetti all ’erogazione di carburanti (Exposure to benzene and genotoxicity indicators among filling station attendants). Epidemiologia e Prevenzione 1995, 19: 105- 119 (English abstract).

CARERE A., CEBULSKA-WASILEWSKA A., TANZARELLA C., MARCOS R, SORSA M., ANDERSON D., PINTER A. Biomonitoring of Human Populations Exposed to Petroleum Fuels with Special Consideration on the Role of Benzene as a Genotoxic Component, Proc. Host Factors Environ. Epidem., Krak6w, 1995. p. 111-115.

CARERE A., CREBELLI R, IAVARONE I., LAGORIO S., LEOPARDI P„ MARCON F„ PALITTI F„ TANZARELLA C., ZIJNO A. Cytogenetic monitoring of filling station attendants. Proceedings of the 1995 ISEE & ISEA Annual Conference. Epidemiology, 1995,6: sl6.

CARERE A., ANTOCCIA A., CIMINI D„ CREBELLI R, DEGRASSI F„ LEOPARDI P. MARCON F., SGURA A., TANZARELLA C., ZIJNO A. Genetic effects of petroleum fuels. II. Analysis of chromosome loss and hyperploidy in peripheral lymphocytes of gasoline station attendants by fluorescence in situ hybridization techniques. Environmental Molecular Mutagenesis, submitted.

CEBULSKA-WASILEWSKA A., WIERZEWSKA A., ANDERSON D. Numerical Chromosome Aberrations in Human Blood Lymphocytes After Exposures to Benzene related Compounds, Proc. Host Factors Environ. Epidem., Krakow, 1995. p. 129-137.

CEBULSKA-WASILEWSKA A., WIERZEWSKA A., KASPER E., PALKA B., KOZIARA L. Biomonitoring of Human Population Exposed to Petroleum fuel with Total Consideration of Benzene Genotoxic Component, Proc. WHO Workshop “Monitoring of Exposure to Genotoxic Substances”, 27- 28 October 1994, Sosnowiec, Poland, 1995. p. 82-95.

CREBELLI R. Benzene exposure and early biomarkers of genotoxicity among gasoline station attendants. Proceedings of the Workshop “Monitoring of exposure to genotoxic substances”, 27-28 October 1994, Sosnowiec, Poland, 1995. p. 53-61.

CREBELLI R, ZIJNO A. Molecular cytogenetic biomonitoring of benzene exposed workers. Proceedings of the workshop “Biomarkers of occupational and environmental exposure to organic genotoxic substances”, 23-24 October 1997, Ustron, Poland, 1997. p. 9-10.

KIVISTO H„ PEKARI K„ PELTONEN K„ SVINHUFVUD J„ VEIDEBAUM T., SORSA M., AITIO A. Biological monitoring of exposure to benzene in the production of benzene and in a cokery. Sci. Total 101

Environ. 1997, 199: 49-63.

LAGORIO S„ FORASTIERE F„ IAVARONE I., RAPITI E„ VANACORE N„ PERUCCI C.A., CARERE A. Mortality of filling station attendants. ScandJ Work Environ Health 1994, 20: 331-338.

LAGORIO S„ FORASTIERE F., IAVARONE I., VANACORE N., FUSELLI S., CARERE A. Exposure assessment in a historical cohort of filling station attendants. Int. J. Epidemiol. 1993, 22 (2): S51-S56.

LAGORIO S., FUSELLI S., IAVARONE I., VANACORE N., CARERE A. Esposizione a benzene tra gli addetti alle stazioni di rifomimento e composizione della benzina (Benzene exposure in service stations and composition of gasoline). Med. Lav. 1994, 85: 412-421 (English abstract).

LAGORIO S., IAVARONE I., IACOVELLA N„ PROIETTO A.R., FUSELLI S„ TURRIO BALDASSARRI L., CARERE A. Variability of benzene exposure among filling station attendants. OccupHyg. 1997,4: 15-30.

LAGORIO S„ TAGESSON C„ FORASTIERE F„ IAVARONE I., AXELSON 0., CARERE A. Exposure to benzene and urinary concentrations of 8-hydroxydeoxyguanosine, a biological marker of oxidative damage to DNA. Occup. Environ. Med. 1994, 51: 739-743.

LAGORIO S., CREBELLI R„ RICCIARELLO R„ CONTI, L„ IAVARONE I., ZONA A., GHITTORI S., CARERE A. Methodological issues in biomonitoring of low level exposure to benzene. Occupational Medicine 1998, in press.

PINTER A. Environmental exposure to benzene with special regards to genotoxic effects, (in preparation).

PITARQUE M., CARBONELL E., CREUS A., MARCOS R. Biomonitoring of a group of airport workers by using the comet assay. (In preparation).

PITARQUE M., CARBONELL E., LAPENA N., MARSA M„ TORRES M„ CREUS A., MARCOS R. No increase in micronucleus frequency in cultured blood lymphocytes from a group of filling station attendants. Mutation Res. 1996, 367: 161-167.

PITARQUE M„ CARBONELL E„ LAPENA N., MARSA M„ VALBUENA A., CREUS A, MARCOS R. SCE analysis in peripheral blood lymphocytes of a group of filling station attendants. Mutation Res. 1997, 390: 153-159.

PITARQUE M., CARBONELL E., XAMENA N., CREUS A, MARCOS R. Genotoxicityof commercial petrol samples in cultured human lymphocytes. Rev. Int. Contam. Amb. 1997, 13: 17-23.

SGURA A., ANTOCCIA A, RAMIREZ M L, MARCOS R., TANZARELLA C., DEGRASSI F. Micronuclei, centromere-positive micronuclei and chromosome nondisjunction in cytokinesis blocked human lymphocytes following mitomycin-C or vinscristine treatment. Mutation Res. 1997, 392: 97-107.

SORSA M, KIVISTO H, PEKARI K, PELTONEN K, VEIDEBAUM T, CARERE A. Biomarkers of benzene exposure in a shale oil petrochemistry plant. International Congress of Toxicology - VII, July 2-6, 1995.

SORSA M., PELTONEN K., KULJAKKA T., VEIDEBAUM T. Biomarkers of benzene exposure in a shale oil petrochemistry plant. In: Horizons in Toxicology: Preparing for the 21st century. VII 102

International Congress in Toxicology, Seattle, 1995.

SURRALLES J., XAMENA N., CREUS A., MARCOS R. The suitability of the micronucleus assay in human lymphocytes as a new biomarker of excision repair. Mutation Res. 1995, 342: 43-59.

SURRALLES J., AUTIO K„ JARVENTAUS H„ NORPPA H„ VEIDEBAUM T„ SORSA M„ PELTONEN K. Molecular cytogenetic analysis of buccal cells and lymphocytes from benzene exposed workers. Carcinogenesis 1997, 18: 817-823.

SURRALLES J., ANTOCCIA A., CREUS A., DEGRASSI F„ PERIS F., TANZARELLA C„ XAMENA N., MARCOS R. The effect of cytochalasin-B concentration on the frequency of micronuclei induced by four standard mutagens. Results from two laboratories. Mutagenesis 194, 9: 347-353.

TURRIO BALDASSARRI L„ CARERE A., FUSELLI S„ IAVARONE I., LAGORIO S., IACOVELLA N. Carburanti autoveicolari come fonte di inquinamento da benzene. In: Frigerio A e Fardini F (Eds). Inquinanti atmosferici primari e secondari. Milano: GSISR, 1996, pp. 43E-53E. Direttore dell'fstituto Superiore di Sanita e Responsabile scientifico: Giuseppe Benagiano

Direttore responsabile: Vilma Alberani

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