Individual Estimation of Exposures to Extremely Low Frequency Magnetic Fields in Jobs Commonly Held by Women

J. E. Deadman and C. Infante-Rivard

From the Joint Departments of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine, McGill University, Montréal, Québec, Canada.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Exposures to extremely low frequency (ELF) magnetic fields have not been documented extensively in occupations besides the work environments of electric or telephone utilities. A 1980–1993 study of childhood acute lymphoblastic leukemia (ALL) in Québec, Canada, gathered detailed information about the occupations of 491 mothers of ALL cases and mothers of a similar number of healthy controls. This information was combined with published data on the intensities of ELF magnetic fields associated with sources or work environments to estimate ELF magnetic field exposures for a wide range of jobs commonly held by women. Estimated exposures for 61 job categories ranged from 0.03 to 0.68 µT; the 25th, 50th, and 75th percentiles were 0.135, 0.17, and 0.23 µT, respectively. By job category, the most highly exposed jobs (>0.23 µT) included bakery worker, cashier, cook and kitchen worker, electronics worker, residential and industrial sewing machine operator, and textile machine operator. By work environment, the most highly exposed job categories were electronics worker in an assembly plant (0.70 µT) and sewing machine operators in a textile factory (0.68 µT) and shoe factory (0.66 µT). These results provide new information on expected levels of exposure in a wide range of jobs commonly held by women.

electromagnetic fields; occupational exposure; women

Abbreviations: ALL, acute lymphoblastic leukemia; ELF, extremely low frequency; EMF RAPID, Electric and Magnetic Fields Research and Public Information Dissemination


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Exposures to extremely low frequency (ELF) magnetic fields (3–300 Hz) are ubiquitous, occurring in most occupational, residential, recreational, and transport environments. Thus, even a weak association with adverse health effects could raise substantial public health concerns. The suggestion by Wertheimer and Leeper in 1979 (1Go) that exposure to magnetic fields at the levels found in residences could be associated with an increased risk of leukemia in children instigated intensive research focusing on the nature and intensity of exposures to these fields. In a recent review of the health risks associated with exposure to ELF magnetic fields, a working group of the National Institute of Environmental Health Sciences concluded that there was "limited evidence of an increased risk for childhood leukemias with residential exposure and an increased occurrence of CLL (chronic lymphocytic leukemia) associated with occupational exposure" (2Go, p. 402). Since this National Institute of Environmental Health Sciences review was published, a pooled analysis of 3,203 children with leukemia and 10,338 control children found that for the 99.2 percent of children residing in homes with a geometric mean exposure level of less than 0.4 µT, the relative risk estimates were compatible with no increased risk, while the 0.8 percent of children with geometric mean exposures of more than or equal to 0.4 µT had an approximately twofold increased relative risk (3Go). This finding underscores the importance of identifying environments in which elevated levels of exposure can occur.

While residential exposures can, in some cases, equal the magnitude of certain occupational exposures, the occupational environment presents a greater opportunity for exposure. Extensive surveys of residences in Canada and the United States have found that 3–24 percent of homes have ELF magnetic fields in excess of 0.2 µT, depending on the configuration of wiring and grounding systems and on the extent of electric heating, among other factors (4Go, 5Go). By comparison, the largest known published study of occupational exposures, covering 100 common jobs in Sweden, found that 40 percent of daily mean exposures to ELF magnetic fields exceeded a level of 0.2 µT (6Go). Furthermore, magnetic field exposures in Europe are expected to be lower than those in North America because of higher European mains voltage (voltage at which electricity is used residentially or commercially) and hence lower currents.

In North America, assessment of occupational exposures to ELF magnetic fields has focused primarily on specialized groups of workers such as those in electric utilities (7GoGoGoGo–11Go) and telephone utilities (12Go), most often in men's jobs, and generally has used a job-exposure matrix approach in which exposures are assigned at the level of job title. Beyond these work environments, information on levels of exposure to ELF magnetic fields is very sparse. Although the Swedish exposure study (6Go) provides exposure levels for many common occupations, the values cannot be transposed to North America directly because the power supply voltages are different. There are scattered reports of elevated exposures, such as among sewing machine operators (13Go) and nurses in neonatal intensive care units (14Go), but, for the vast majority of commonly held jobs in North America, exposures to ELF magnetic fields have not been documented.

A recent study of environmental and genetic risk factors and childhood acute lymphoblastic leukemia (ALL) (15GoGo–17Go), including parental occupation (18Go), gathered self-reported information about the occupations of 491 parents of ALL cases and a similar number of healthy controls. This information included detailed descriptions of general and specific work environments, tasks and their durations, and electrical equipment used in the workplaces. By combining this information with published data on the intensities of ELF magnetic fields associated with these sources or work environments, this study provided a unique opportunity to semiquantitatively estimate ELF magnetic field exposures for a wide range of jobs. The results have the following key features: 1) they provide new information on expected levels of exposure in a range of jobs commonly and contemporarily held by women; 2) they are based on individually reported exposure data as opposed to job titles for groups of workers—often used to create job-exposure matrices—with the former mode expected to improve the precision of exposure estimates (10Go, 19Go, 20Go); and 3Go) they provide practical indications of exposures to ELF magnetic fields in the form of matrices by source of exposure, by work environment, and by job title.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Case-control study
In a study of environmental risk factors and ALL, a major emphasis was to collect detailed data on parental occupation prior to and during pregnancy (18Go). The study used the so-called expert method proposed by Gérin et al. (21Go) to gather occupational exposure information using general as well as job-specific questionnaires to probe for details about each job. Maternal exposures to chemical and physical contaminants during pregnancy were of primary interest. The general study methodology for this case-control study has been outlined elsewhere (15Go). Briefly, ALL cases aged 0–9 years diagnosed between 1980 and 1993 in the province of Québec, Canada, were recruited from tertiary care centers designated by government policy to hospitalize and treat children with cancer in the province. Tracing cases from these hospitals is equivalent to population-based ascertainment. A case was determined to have ALL (International Classification of Diseases, Ninth Revision, code 204.0) on the basis of a clinical diagnosis by an oncologist or a hematologist at the center. Population-based controls matched to the case on age (within 3 months for 95 percent of the pairs), sex, and region of residence at the calendar time of diagnosis were chosen from family allowance files. The family allowance is a government stipend awarded to all families with children living legally in Canada. A total of 510 cases were identified, and interviews were obtained from 491 parents (96.3 percent); 588 controls were recruited to obtain interviews from 493 (83.3 percent) parents. In the end, information on 491 cases and 491 controls was used in the analyses. Information on maternal occupational history was obtained by interviewing mothers by telephone. Interviewers were trained and their work monitored throughout the study.

Extraction of relevant data
The general and job-specific questionnaires were reviewed by one of the authors (J. E. D.), an industrial hygienist unaware of case-control status, to extract information on the following potential determinants of exposure: job title, work environment, magnetic field sources, duration of use or exposure, total hours of work per week, and type of work shift. The questionnaires included detailed descriptions of work tasks and work methods. These were reviewed for any information that would further help identify electrical equipment in the worker's vicinity, hours of use or of exposure per week, or type of work environment. Because the objective was to assign exposures based on ELF magnetic field sources (primarily electrical equipment), work environments, and duration of exposure, this information was noted and compiled into a list of 111 sources (table 1) and 59 work environments (table 2). When more than one source was reported, the one used most frequently was listed first, with up to two other sources listed in decreasing frequency of use. The list of job titles was standardized into a set of 61 titles (table 3).


View this table:
[in this window]
[in a new window]
 
TABLE 1. Local ELF* magnetic field sources, durations of use, and assigned magnetic field exposures, province of Québec, Canada, 1980–1993

 

View this table:
[in this window]
[in a new window]
 
TABLE 2. Occupational environments and assigned ELF* magnetic field exposures, province of Québec, Canada, 1980–1993

 

View this table:
[in this window]
[in a new window]
 
TABLE 3. Job titles and assigned time-weighted average exposures to extremely low frequency magnetic fields, province of Québec, Canada, 1980–1993

 
Data sources for determining magnetic field intensities
The MEDLINE and TOXLINE databases of the National Library of Medicine (Bethesda, Maryland) were searched for published literature on ELF magnetic field levels associated with electrical equipment, work environments, or job titles. A search for other data on ELF magnetic field intensities was carried out by using the data sets available on the Internet Web site of the Electric and Magnetic Fields Research and Public Information Dissemination (EMF RAPID) Program (22Go) and by reviewing measurement campaigns conducted in the province of Québec.

Assignment of ELF magnetic field intensity values
ELF magnetic field intensities for sources and work environments were obtained from the published literature, calculated from EMF RAPID data set number 004, or inferred by analogy with a documented value. The EMF RAPID database provided almost one third of the source intensity estimates and about one quarter of the environmental intensity estimates. Tables 1 and 2 provide the assigned values for sources and environments and the basis for each value.

Magnetic fields diminish rapidly with distance from small sources such as video display terminals, photocopiers, and typewriters. Since study subjects had not been asked about distances from sources, the expected typical distance between the worker and the source was assumed in assigning magnetic field levels using those cited in the literature. If a source was characterized by intermittent use (e.g., typewriters or sewing machines) and the published magnetic field values represented continuous use, field intensities were reduced to approximate average field levels over a common usage cycle. For video display terminals used before 1986, when magnetic field reduction techniques became more common, we assigned a value of 0.37 µT. Video display terminals used after 1986 were assigned a value of 0.25 µT.

Calculation of weekly time-weighted average exposures
For each job held by a subject, a weekly time-weighted average exposure was calculated by multiplying the ELF magnetic field intensity of each identified source by the weekly duration of use. Any remaining work time was multiplied by the background field level assigned to the specific work environment. The products of source and duration and of environment and duration were summed and were divided by the total weekly hours spent at work. For example, one store manager reported working 50 hours a week managing a pet-grooming salon. She mentioned using an electric razor for an average of 30 hours a week (assigned magnetic field value: 2 µT) and a cash register for an average of 10 hours a week (assigned magnetic field value: 0.33 µT). The remaining 10 hours were assigned the background magnetic field value for stores (0.2 µT). Thus, her weekly exposure was estimated as ((30 hours x 2) + (10 hours x 0.33) + (10 hours x 0.2))/50 hours = 1.31 µT.

For 54 percent of the 1,002 jobs (e.g., most waitresses and agricultural workers), local magnetic field sources were not expected to contribute substantially to exposure. In these instances, exposure was presumed to be similar to the background environmental level, and that level was assigned. For jobs in which local sources of magnetic fields were expected to substantially increase exposures above background levels from the work environment but in which the sources or their duration of use had not been reported in the questionnaire, we assigned the arithmetic mean value of the calculated weekly time-weighted average exposure for other workers with the same job title who had reported duration of use of local sources.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
ELF magnetic field sources
Of the 982 maternal occupational histories obtained, 747 included information on employment outside the home during pregnancy. The proportions of mothers of cases and controls who had stayed at home during pregnancy were very similar (23.9 and 23.7 percent, respectively). From the 747 occupational histories, 1,002 jobs were held between 1980 and 1993. Of these, 671 included one or more reported or identifiable source of ELF magnetic fields, and 486 included information on duration of exposure to the source. A total of 111 different types of sources were reported or identified; the most frequent were photocopiers (20 percent), electric typewriters (15 percent), video display terminals (14 percent), cash registers (8 percent), and sewing machines (5 percent) (table 1). We were able to locate data on ELF magnetic field intensities for 86 percent of the reported or identified sources. For the remainder, one of the authors (J. E. D.) inferred magnetic field intensities by analogy with similar sources.

Table 1 lists the frequency with which each source was reported or was identifiable; the minimum, maximum, and mean duration of use of the source or exposure to it; the ELF magnetic field value assigned to the source; and the basis for the estimate. Assigned ELF magnetic field values ranged from 0.1 to 4 µT. The 25th, 50th, and 75th cutpoints of the intensity range were 0.3, 0.5, and 0.94 µT, respectively. Sources for which the assigned ELF magnetic field intensities were less than 0.3 µT included electrocardiogram machines, floor polishing machines, hair dryers, milking machines, telephone switchboards, tractors, and video display terminals (after 1986). Those for which the assigned ELF magnetic field intensities were 0.3–0.5 µT included commercial aircraft (e.g., an arts representative traveling on business), cash registers, keypunch machines, microscopes, residential ovens (e.g., home care workers), photocopiers, posting machines, presses, saws, residential sewing machines, typewriters, and video display terminals (before 1986). Sources for which the assigned intensities were 0.5–0.94 µT included aquarium motors, deep fryers, heat-sealing plates and machines, light tables/viewers, overhead projectors, photocopiers, soldering guns, vacuum cleaners, warping machines, and weaving machines. The highest intensity sources (>0.94 µT) included band saws, electric compressors, electric razors, fluorescent viewing lamps, industrial sewing machines, paper shredders, and ultrasonic cleaners.

Work environments
Type of work environment was identifiable for all 1,002 jobs reviewed, which were classified into 59 categories chosen to reflect possible differences in ELF magnetic fields. The most common work environments were offices (28 percent), residences (10 percent), stores/supermarkets (9 percent), textile factories (7 percent), and restaurants (5 percent). Data on ELF magnetic field intensities associated with specific work environments were located for 22 of the 59 environments identified. For the remainder, magnetic field intensities were estimated by analogy with measured environments. Table 2 lists the frequency of each environment, the assigned ELF magnetic field value, and the basis for the estimate. By intensity, assigned ELF magnetic fields ranged from 0.01 µT (rural outdoors) to 0.32 µT (commercial kitchens). The 25th, 50th, and 75th cutpoints of the intensity range were 0.08, 0.1, and 0.16 µT, respectively. Environments in which the assigned ELF magnetic fields were less than 0.08 µT included electronics factories, nondairy farms, greenhouses, military barracks, outdoors (rural), and primary schools. Environments in which the fields were 0.08–0.16 µT included airports, banks, clinics/hospitals, dairy farms, day care facilities, factories (assembly and food products), hair salons, hotels, laundries, libraries, offices, outdoors (urban), and warehouses. Environments in which the fields were more than 0.16 µT included bakeries, textile or shoe factories, hospital intensive care units, operating rooms, cardiac or emergency areas, commercial and residential kitchens, residences, and supermarkets.

Job titles and estimated exposures
For the 1,002 jobs held by mothers of study subjects during pregnancy, the estimated time-weighted average exposure was 0.2 µT (minimum, 0.01; maximum, 1.45). Time-weighted average exposures in jobs exceeded levels of 0.2, 0.4, and 0.8 µT for 30, 6, and 3.5 percent of cases, respectively. The most prevalent job titles were office worker (18.8 percent), secretary (12.4 percent), teacher (6.1 percent), cashier (4.7 percent), nurse (4.4 percent), sewing machine operator (4.2 percent), waitress (4.2 percent), assembly worker (3.6 percent), textile machine operator and textile worker (3.3 percent), and bank clerk or teller (3.3 percent). When aggregated at the job category level (combining all work environments), the calculated time-weighted average exposures for the 61 categories of job titles ranged from 0.03 to 0.68 µT, with the 25th, 50th, and 75th percentiles as 0.135, 0.17, and 0.23 µT, respectively.

Jobs in the lowest quartile of exposure (<0.135 µT) included agricultural worker, bank clerk, horticultural worker, laundry worker, primary and secondary school teacher, and social worker. Jobs in which exposures were 0.135–0.17 µT included assembly worker, barmaid, dental technician, nurse and hospital technician, and receptionist. Job categories in which exposures were 0.17–0.23 µT included bank teller, hairdresser, restaurant manager and cook, office worker, salesperson, waitress, and food products worker. The most highly exposed jobs (>0.23 µT) included bakery worker, cashier, cook and kitchen worker, electronics worker, residential and industrial sewing machine operator, and textile machine operator.

Time-weighted average exposures for each job category varied, depending on type of work environment (data not shown). When examined at the work environment level, the most highly exposed job categories were electronics worker in an assembly plant (0.70 µT) and sewing machine operator in a textile factory (0.68 µT) and a shoe factory (0.66 µT). Job categories covering the widest variety of work environments were office worker and secretary. For these jobs, exposures varied from 0.14 µT for a secretary in a clinic to 0.34 µT for a secretary in a secondary school.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The results reported here provide a portrait of exposure levels that can be expected in a broad range of jobs commonly held by women. Published exposure data for comparable jobs elsewhere in North America exist mainly for office workers and nurses and indicate exposures ranging from 0.1 to 0.32 µT (7Go, 12Go, 23Go). Our estimated exposures for this group are similar, ranging from 0.10 to 0.28 µT. One study of nurses reported exposures of 0.13 µT in a normal newborn nursery and 0.2 µT in a neonatal intensive care unit (14Go). The nurses in the jobs we reviewed worked in a variety of hospital services but not in neonatal units; exposure estimates ranged from 0.1 to 0.2 µT. An unpublished study (L. Paquet, McGill University) of five common occupations in the province of Québec provides a reference point for two of the jobs assessed here. The study measured ELF magnetic and electric field exposures for cooks, forklift operators, bus drivers, machinists, and textile sewing machine operators during five complete work shifts. The results for cooks and sewing machine operators, based on 45 and 47 days of measurement, respectively, showed arithmetic mean exposures of 0.28 and 0.52 µT. Our estimated values were similar for cooks (0.29 µT) but were slightly higher for sewing machine operators (0.68 µT).

The only known published population-based job-exposure matrix (6Go) was developed from measurements on Swedish workers and includes exposure information on several of the jobs assessed in our study, notably clerical worker, cook, home worker, and nurse. However, these exposures cannot be directly transposed to North America, where electricity is supplied to the end user at a lower voltage than in Europe. The lower voltage is expected to result in higher electric currents and hence higher magnetic fields for equivalent jobs (24Go). As a result, we did not use these data in deriving the estimates reported here.

The methods used thus far to estimate occupational exposures to ELF magnetic fields in epidemiologic studies cover a wide spectrum. At one extreme, job titles are classified into broad exposure categories (25Go) with or without supporting measurements. At the other, personal exposures of the study subjects are measured. When retrospective exposure assessments are required, job-exposure matrices are commonly used to provide more refined estimates of exposure for job titles beyond those obtained through broad classification. Although a job-exposure matrix can improve resolution of the exposure classification compared with a broad categorization of exposures, it assigns an identical exposure to all workers with the same job title. With the Gérin method of exposure assignment, workers are assigned to exposure categories by expert coders (chemists/industrial hygienists) who review detailed information on work activities and work environments (21Go). The exposure estimation method described here is an extension of the Gérin method and is, to our knowledge, the first application to ELF magnetic fields. The work histories on which the estimation is based go beyond job title and job descriptions to focus on the main determinants of exposure: sources, duration of exposure, and work environments. The method requires expert judgment by an exposure coder, but the coder is not required to assign an exposure directly to a worker. Rather, he or she must be able to recognize and classify the person's work environment, the ELF magnetic field sources, and the duration of exposure to them. This information is then used to generate a weekly time-weighted average exposure based on documented or inferred values of ELF magnetic fields for each source or environment.

There are many potential sources of error when any exposure estimation method is used. For example, we assumed a single value of exposure intensity for each work environment or source; in reality, these vary between workplaces. We used self-reported information on exposure durations, which vary for each worker and according to perceptions of what constitutes use of or exposure to a machine. Overall, though, use of information specific to each person should have resulted in a less misclassified exposure assignment than if exposure had been assigned to the worker's job title by using a job-exposure matrix. On the other hand, using reported information on the occupational histories of the mothers of both cases and controls to create a job-exposure matrix could have created a validity problem if some jobs were held by mostly one of the two groups and there was a reporting bias for job title and job description (for example, if nurses were found only among the case group and they tended to overreport potential ELF exposure sources). On the basis of job distribution categories (e.g., blue collar, white collar) and industry distributions, we found no differences between the groups, and both distributions were comparable to those from population surveys of women in this province and in these age groups over this time period (26Go). Substantial bias in job description reporting for a large proportion of study subjects seems unlikely, although it was not measured.

Because duration of exposure is equally as important as intensity in estimating a person's exposure, its inclusion in the estimation process should have improved accuracy. For the duration estimates, we systematically used average weekly durations, which are expected to provide better estimates of the duration of long-term exposure than actual measurements of exposure duration over shorter periods (27Go). Furthermore, when intensity is estimated separately from duration, the exposure coder is required to judge exposure duration only, thus removing a subjective element from the process. When applied by a coder who has expert knowledge of the tasks involved in a job, sources of ELF fields, and specific exposure situations, this method is expected to increase the sensitivity of exposure assignments by identifying unexpected sources or environments in jobs that would have otherwise been considered as belonging to a low-exposure category. Similarly, the specificity of exposure assignments is expected to improve by identifying low exposures in jobs that could have been automatically considered, on the basis of job title alone, highly exposed.

The exposure estimation described in this paper focused on the key determinants of exposure for a person: the work environment and the sources within that environment. Stewart (28Go) has pointed out that deterministic-based modeling of exposures presents a key advantage for studies that rely on interview data. Once the principal determinants of exposure have been identified (e.g., type of source, duration of exposure), it would be necessary to ask questions on those determinants only, many of which could probably be answered by respondents. A campaign of personal measurements would therefore be very useful not only to validate the exposure estimates presented here but also to assess the performance of these and other exposure determinants in predicting exposures to ELF magnetic fields.


    NOTES
 
Correspondence to Dr. Jan-Erik Deadman, Health and Safety Department, Hydro-Québec, 75, boul. René-Lévesque West, 7th Floor, Montréal, Québec, Canada H2Z 1A4 (e-mail: deadman.jan{at}hydro.qc.ca).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Wertheimer N, Leeper E. Electrical wiring configurations and childhood cancer. Am J Epidemiol 1979;109:273–84.[Abstract]
  2. Portier CJ, Wolfe MS, eds. Assessment of health effects from exposure to power-frequency electric and magnetic fields—NIEHS Working Group report. Research Triangle Park, NC: National Institute of Environmental Health Sciences, 1998. (NIH publication no. 98-3981).
  3. Ahlbom A, Day N, Feychting M, et al. A pooled analysis of magnetic fields and childhood leukaemia. Br J Cancer 2000;83:692–8.[ISI][Medline]
  4. Deadman JE, Armstrong BG, McBride ML, et al. Exposures of children in Canada to 60-Hz magnetic and electric fields. Scand J Work Environ Health 1999;25:368–75.[ISI][Medline]
  5. Zaffanella L. Survey of residential magnetic field sources. Vol 1: goals, results and conclusions; vol 2: protocol, data analysis and management. Palo Alto, CA: Electrical Power Research Institute, September 1993 (final report). (Report nos.: TR-102759-V1; TR-102759-V2).
  6. Floderus B, Persson T, Stenlund C. Magnetic field exposures in the work place: reference distribution and exposures in occupational groups. Int J Occup Environ Health 1996;2:226–38.[Medline]
  7. Sahl JD, Kelsh MA, Smith MA, et al. Exposure to 60-Hz magnetic fields in the electric utility work environment. Bioelectromagnetics 1994;14:373–81.[ISI]
  8. Savitz DA, Loomis DP. Magnetic field exposure in relation to leukemia and brain cancer mortality among electric utility workers. Am J Epidemiol 1995;141:123–34.[Abstract]
  9. Thériault G, Goldberg M, Miller AB, et al. Cancer risks associated with occupational exposure to magnetic fields among electric utility workers in Ontario and Québec, Canada, and France: 1970–1989. Am J Epidemiol 1994;139:550–72.[Abstract]
  10. Guénel P, Nicolau J, Imbernon E, et al. Design of a job exposure matrix on electric and magnetic fields: selection of an efficient job classification for workers in thermoelectric power production plants. Int J Epidemiol 1993;22(suppl 2):S16–21.[Abstract]
  11. Miller AB, To T, Agnew DA, et al. Leukemia following occupational exposure to 60-Hz electric and magnetic fields among Ontario electric utility workers. Am J Epidemiol 1996;144:150–60.[Abstract]
  12. Breysse PN, Matanoski GM, Elliott EA, et al. 60 Hertz magnetic field exposure assessment for an investigation of leukemia in telephone lineworkers. Am J Ind Med 1994;26:681–91.[ISI][Medline]
  13. Sobel E, Davanipour Z, Sulkava R, et al. Occupations with exposure to electromagnetic fields: a possible risk factor for Alzheimer's disease. Am J Epidemiol 1995;142:515–24.[Abstract]
  14. Paul M, Hammond SK, Abdollahzadeh S. Power frequency magnetic field exposures among nurses in a neonatal intensive care unit and a normal newborn nursery. Bioelectromagnetics 1994;15:519–29.[ISI][Medline]
  15. Infante-Rivard C, Labuda D, Krajinovic M, et al. Risk of childhood leukemia associated with exposure to pesticides and with gene polymorphisms. Epidemiology 1999;10:481–7.[ISI][Medline]
  16. Infante-Rivard C, Mathonnet G, Sinnett D. Diagnostic irradiation and polymorphisms in DNA repair genes in childhood leukemia. Environ Health Perspect 2000;108:495–8.[ISI][Medline]
  17. Infante-Rivard C, Krajinovic M, Labuda D, et al. Parental smoking, CYP1A1 genetic polymorphisms and childhood leukemia. Cancer Causes Control 2000;11:547–53.[ISI][Medline]
  18. Infante-Rivard C, Sinnett D. Preconceptual paternal exposure to pesticides and increased risk of childhood leukaemia. (Letter; comment). Lancet 1999;354:1819.
  19. Wenzl TB. Assessment of magnetic field exposures for a mortality study at a uranium enrichment plant. Am Ind Hyg Assoc J 1999;60:818–24.[ISI][Medline]
  20. Stewart P. Exposure assessment in community-based epidemiological studies. Lancet 1999;353:1816–17.[ISI][Medline]
  21. Gérin M, Siemiatycki J, Kemper H, et al. Obtaining occupational exposure histories in epidemiologic case-control studies. J Occup Med 1985;27:420–6.[ISI][Medline]
  22. EMF RAPID Electric and Magnetic Fields Research and Public Information Dissemination Program. Research Triangle Park, NC: National Institute of Environmental Health Sciences, US Department of Health and Human Services, 1999. (http://www.niehs.nih.gov/emfrapid/home.htm).
  23. Schiffman A, Breysse P, Kanchanaraska S, et al. Characterization of extremely low frequency magnetic field exposures of office workers. Appl Occup Environ Hyg 1998;13:776–81.
  24. Skotte JH. Exposure to power-frequency electromagnetic fields in Denmark. Scand J Work Environ Health 1994;20:132–8.[ISI][Medline]
  25. Milham S Jr. Mortality in workers exposed to electromagnetic fields. Environ Health Perspect 1985;62:297–300.[ISI][Medline]
  26. Labour force historical review. Ottawa, Ontario, Canada: Statistics Canada, 2000. (Catalogue #71F0004XCB).
  27. Olsen E. Analysis of exposures using a logbook method. Appl Occup Environ Hyg 1994;9:712–22.
  28. Stewart P. Challenges to retrospective exposure assessment. Scand J Work Environ Health 1999;25:505–10.[ISI][Medline]
  29. EMF in your environment: magnetic field measurements of everyday electrical devices. Washington, DC: US Environmental Protection Agency, Office of Radiation and Indoor Air, 1992. (EPA 402-R-92-008).
  30. US Department of Energy EMF RAPID Engineering Program, RAPID EMF measurements database. Data set number 004, 1999. (Provided by T. Dan Bracken, Inc, Portland, Oregon).
  31. Milham S, Hatfield JB, Tell R. Magnetic fields from steel-belted radial tires: implications for epidemiological studies. Bioelectromagnetics 1999;20:440–5.[ISI][Medline]
  32. Sun WQ, Héroux P, Clifford T, et al. Characterization of the 60-Hz magnetic fields in schools of the Carleton Board of Education. Am Ind Hyg Assoc 1995;56:1215–24.[ISI]
  33. Bowman JD, Garabrant DH, Sobel E, et al. Exposures to extremely low frequency (ELF) electromagnetic fields in occupations with elevated leukemia rates. Appl Ind Hyg 1988;3:189–94.
  34. Nicholas JS, Lackland BT, Butler GC, et al. Cosmic radiation and magnetic field exposure to airline flight crews. Am J Ind Med 1998;34:574–80.[ISI][Medline]
  35. Rosenthal FS, Abdollahzadeh S. Assessment of extremely low frequency (ELF) electric and magnetic fields in microelectronics fabrication rooms. Appl Occup Environ Hyg 1991;6:777–84.
  36. Gauger JR. Household appliance magnetic field survey. IEEE Transactions on Power Apparatus and Systems 1985;104:2436–44.
  37. Héroux P. 60-Hz electric and magnetic fields generated by a distribution network. Bioelectromagnetics 1987;8:135–48.[ISI][Medline]
  38. Maruvada PS, Jutras P. Caractérisation des champs électrique et magnétique dans différents milieux. (Characterization of electric and magnetic fields in different environments). (In French). Québec, Canada: Institut de Recherche d'Hydro-Québec, 1991.
Received for publication March 27, 2001. Accepted for publication August 23, 2001.