Residential Magnetic Fields and the Risk of Breast Cancer

Scott Davis1,2, Dana K. Mirick1 and Richard G. Stevens3

1 Program In Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA.
2 Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, WA.
3 Department of Community Medicine, University of Connecticut Health Center, Farmington, CT.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Chronic exposure to 60-Hz magnetic fields may increase the risk of breast cancer by suppressing the normal nocturnal production of melatonin. This population-based case-control study investigated whether such exposure is associated with an increased risk of breast cancer in women aged 20–74 years from the greater Seattle, Washington, area. Cases were diagnosed between November 1992 and March 1995 (n = 813); controls were identified by random digit dialing and were frequency matched by 5-year age groups (n = 793). Exposure was estimated using magnetic field measurements in the home at diagnosis, wiring configuration of all homes occupied in the 10 years prior to diagnosis, and self-reported measures of at-home electric appliance use. Odds ratios and 95% confidence intervals were estimated using conditional logistic regression with adjustment for other potential risk factors. Risk did not increase with measured nighttime bedroom magnetic field level, wiring configuration of the home at diagnosis, weighted summary wire codes of all homes occupied 5 and 10 years prior to diagnosis, or reported use of common household appliances, including bed-warming devices. These data do not support the hypothesis that exposure to residential magnetic fields is associated with an increased risk of developing breast cancer.

breast neoplasms; carcinogens, environmental; electricity; electromagnetic fields; melatonin

Abbreviations: SES socioeconomic status


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
It has been suggested that chronic exposure to 60-Hz magnetic fields may increase the risk of breast cancer by suppressing the normal nocturnal production of melatonin (1Go). Reduced melatonin levels could affect the development of breast cancer either through increased levels of circulating estrogen or through an oncostatic property of melatonin itself (2Go, 3Go). Experimental evidence has emerged over the last 2 decades to indicate that melatonin can be suppressed by electric and magnetic fields, that manipulation of melatonin levels can affect the development of mammary carcinoma in animals, and that exposure to magnetic fields can enhance the development of chemically induced mammary carcinoma in animals (summarized in 4Go, 5Go).

To date, observational studies of both residential and occupational exposures to magnetic fields and the risk of breast cancer have led to conflicting results (reviewed by Caplan et al. (6Go)). Residential studies have relied mostly on characteristics of power lines surrounding current and historical residences as the primary method of estimating exposure (7GoGoGoGoGoGoGoGo–15Go). Several studies have investigated the use of electric bed-warming devices as a potential source of magnetic field exposure. Most have not found an association with breast cancer risk (11Go, 16Go, 17Go), although two analyses by Vena et al. (18Go, 19Go) are suggestive, and subsequent analyses of their data revealed evidence of a possible modest association (20Go). None of these studies of breast cancer and residential magnetic field exposure has used direct measurements of magnetic field levels in the home at diagnosis. The purpose of this study was to investigate whether the risk of breast cancer is associated with exposure to residential magnetic fields by using magnetic field measurements in the home at diagnosis, wiring configuration of all homes occupied in the 10 years prior to diagnosis, and self-reported measures of at-home electric appliance use.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Subject identification
Cases were identified by the Cancer Surveillance System of the Fred Hutchinson Cancer Research Center. Eligible cases were all English-speaking, Caucasian women diagnosed with cancer of the breast (International Classification of Diseases for Oncology codes 174.0–174.9) between November 1992 and March 1995, who at diagnosis were between ages 20 and 74 years and resident of King or Snohomish County. All cases diagnosed in Snohomish County were targeted for enrollment in the study, and a random sample of approximately 30 percent of the cases from King County were targeted such that the case series totaled approximately 800. Sampling of cases in this manner was to ensure representation of urban, suburban, and rural living environments. Because the selection process for controls required that they have a telephone, only cases with a telephone in the home at the time of recruitment were eligible.

Controls were English-speaking, Caucasian women aged 20–74 years with no history of breast cancer and resident in King or Snohomish County. They were selected to be equal in number to the cases and were frequency matched by 5-year age groupings and county of residence. Controls were identified by random digit dialing using a modification of the method described by Waksberg (21Go). If multiple women at one residence were eligible, only one was randomly selected. To ensure that the recall period prior to diagnosis was comparable for cases and controls, a reference date was assigned to each selected control which corresponded to the date of diagnosis for a case identified in the same month. Approximately equal numbers of cases and controls were identified each month and subsequently interviewed and measured within a few weeks of each other to minimize the possibility that any difference in magnetic field levels between cases and controls could be due to seasonal variation. Participation rates for cases and controls are shown in table 1. There were no appreciable differences in participation rates by county.


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TABLE 1. Subject identification and participation rates, Greater Seattle, Washington, area, 1992–1995

 
Data collection
An in-person interview was used to ascertain information about known or suspected risk factors for breast cancer. Assessment of magnetic field exposure consisted of three components: 1) interview questions regarding the electrical and heating characteristics of homes in which the subject lived and personal use patterns of a variety of household appliances; 2) 48-hour continuous measurements of magnetic field and light levels in the bedroom of each subject's current residence; and 3) scaled drawings of all electrical hardware and wiring within 140 feet (42.98 m) of the subject's current residence and all previous residences occupied for at least 6 consecutive months within the greater Seattle metropolitan area (King, Pierce, and Snohomish counties). Including historical residences in Pierce County greatly increased the likelihood of mapping most homes occupied in the 10 years prior to diagnosis.

Magnetic field measurements were made in the subject's bedroom using an EMDEX II meter (Enertech Consultants, Campbell, California) set to record broadband (40–800 Hz) and harmonic (100–800 Hz) magnetic fields at 15-second intervals. The meter was placed on the floor at the head of the subject's bed in a location with a measured magnetic field within ±0.05 µT of the field strength measured on the pillow. The meter was left in place for 2 consecutive days. Ambient light was measured during the same time period at 15-second intervals with a commercial light sensor (Graseby Electronics, Orlando, Florida). Trained technicians drew scaled diagrams of all electrical hardware around the subject's current residence and any other residence in which the subject had lived for at least 6 consecutive months during the 10 years prior to diagnosis (reference) in the three-county area noted above. The Fred Hutchinson Cancer Research Center Institutional Review Board approved the procedures for contacting potential participants, obtaining informed consent, and data collection procedures.

Statistical methods
Eight variables were defined a priori to characterize aspects of a subject's exposure to magnetic fields. Three variables characterized exposure to broadband magnetic fields in the bedroom during the two nights of measurements: 1) mean nighttime bedroom magnetic field; 2) proportion of nighttime bedroom magnetic field measurements >=0.2 µT; and 3) short-term variability in the nighttime bedroom magnetic field. Analyses of magnetic field measurements were restricted to nighttime to correspond with the underlying biologic hypothesis that exposure to magnetic fields may increase the risk of breast cancer by reducing the nocturnal secretion of melatonin. To make meaningful comparisons of magnetic field levels in the bedroom at night, a uniform period of nighttime was defined for all subjects as the 7 hours between 10 p.m. and 5 a.m. the following morning. Magnetic field measurements were grouped into 10-minute intervals. For each 10-minute interval, short-term variability in the bedroom magnetic field was assessed in a manner comparable with the "rate-of-change metric" introduced by Yost (22Go) and averaged over the nighttime period. The three exposure variables were highly correlated between the two nights for all subjects, and thus, each variable was calculated for both nights of measurements and then averaged together for analysis. Measured levels of ambient nighttime light intensity were consistently low and lacking in variability (median level = 1.2 lux for both cases and controls); therefore, no further analysis of this measure was conducted.

Wiring configuration around the home was used as a surrogate measure of magnetic field levels inside the home. Wire code category was assigned to each participant's current residence and to every residence in the 10 years prior to diagnosis (reference) that could be mapped, according to the scheme developed by Wertheimer and Leeper (12Go, 23Go). Three variables characterized exposure using this method: 1) the wire code of the house at diagnosis (reference); 2) the weighted summary wire code category of all houses lived in during the 5 years prior to diagnosis (reference); and 3) the weighted summary wire code category of all houses lived in during the 10 years prior to diagnosis (reference). Weighted summary wire codes were calculated as follows: The five wire code categories were ordered according to their respective in-home nighttime mean magnetic field measurements using data from the controls (Very Low Current Configuration = 0.052 µT, UnderGround = 0.064 µT, Ordinary Low Current Configuration = 0.072 µT, Ordinary High Current Configuration = 0.086 µT, Very High Current Configuration = 0.150 µT) and assigned the scale values 1–5 according to this order. These scale values were then used to calculate 5- and 10-year mean wire code values, weighted by the time lived at each residence. The use of 48-hour mean magnetic field measurements instead of nighttime measurements did not change this order. The order is the same as that established by Wertheimer and Leeper (12Go), except for the category UnderGround, which was not distinguished from Very Low Current Configuration in their study.

Three variables were defined to characterize exposure to magnetic fields from the everyday use of household appliances in the 10 years prior to diagnosis (reference): 1) ever use of an electric bed-warming device such as an electric blanket, mattress pad, or water bed heater; 2) hours of use (per year) of an electric bed-warming device, excluding times when the device was used only to warm the bed; and 3) estimated total exposure to magnetic fields from reported at-home use of the following appliances: portable electric heaters, vacuum cleaners, garbage disposals, toasters, mixers, microwave ovens, hair dryers, curling irons, fluorescent lamps, television sets, and personal computers. The appliance variable was constructed as follows: For each appliance, estimated magnetic field exposure was calculated as the product of the subject's reported duration of use and the typical field strength per unit time of each appliance. Published average measured magnetic fields for each appliance (in teslas) were used as the "typical" field strength (24Go). Total exposure from all appliances during the 10 years prior to diagnosis (reference) was computed as the sum of the individual exposures from each appliance.

Initially, a list of factors known or suspected to influence the risk of breast cancer were investigated for use as covariates, using information obtained from the interview. Each potential risk factor was evaluated by itself with the exposure measure of interest and considered to be significant if it was associated with an increased or decreased risk of breast cancer (p <= 0.1, Wald chi-square). All factors that were significant when defined in this manner were included as a group in all final models regardless of individual significance and are listed in the footnotes to the tables.

Odds ratios and 95 percent confidence intervals were used to evaluate relative risks using conditional logistic regression (25Go). All models were conditional on 5-year age strata with no adjustment for any covariates and with adjustment for the group of covariates listed above. All measures of exposure, except for ever use of bed-warming appliances, were analyzed as both continuous and categorical variables to reduce the possibility that an exposure effect (or lack thereof) was dependent on the form of the dose-response relation with breast cancer risk. The results from the crude (unadjusted) and adjusted analyses were essentially the same; therefore, only adjusted odds ratios are presented.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Descriptive characteristics
Table 2 summarizes the completeness of data collection for the three components of exposure assessment. The proportions of cases and controls for which magnetic field measurements, wire code of the home at diagnosis (reference), and appliance usage were obtained were nearly equal. Wire codes of all residences in the 5 and 10 years prior to diagnosis (reference) were obtained for slightly more cases than controls.


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TABLE 2. Completeness of data collection, Greater Seattle, Washington, area, 1992–1995

 
Table 3 shows selected characteristics of the interviewed cases and controls. Estrogen and progesterone-receptor status was obtained for 86 percent of cases. Of the cases for whom hormone-receptor status was obtained, 67 percent were jointly receptor positive, and 19 percent were jointly negative.


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TABLE 3. Selected characteristics of cases and controls, Greater Seattle, Washington, area, 1992–1995

 
Magnetic field measurements
Mean nighttime broadband magnetic field levels were slightly higher for cases than for controls (mean = 0.080 µT for cases and 0.071 µT for controls; p = 0.75, Wilcoxon rank sum test), but were quite low overall. Nearly identical proportions of cases and controls had no nighttime broadband magnetic field measurements of >=0.2 µT (76 and 77 percent, respectively). Nighttime broadband magnetic field levels were slightly more variable for cases than for controls (mean variability = 0.043 µT and 0.038 µT, respectively; p = 0.84, Wilcoxon rank sum test).

Results regarding exposure to nighttime bedroom broadband magnetic fields are displayed in table 4. In summary, there was no association between risk of breast cancer and any of the following: 1) mean magnetic field; 2) proportion of measurements >=0.2 µT; and 3) short-term variability in magnetic field. Mean magnetic field and variability in the magnetic field were also treated as categorical variables, divided into quartiles based on the distributions of all controls with magnetic field measurements. Analyzing either variable in this manner did not materially change the results. The proportion of magnetic field measurements >=0.2 µT was analyzed in two additional ways: 1) as a categorical variable, divided into quartiles based on the distribution among all controls who had at least one measurement >=0.2 µT; and 2) as an indicator variable (yes if the measurement in any interval during the night was >=0.2 µT, no if otherwise). Using either variable, the results did not change appreciably. When the analysis of mean magnetic field was restricted to those subjects who had lived in their current residence for at least 5 years prior to reference date or to those subjects who had lived in their current residence during the entire 10 years prior to reference date, results were unchanged from those presented above (data not shown).


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TABLE 4. Odds ratios for breast cancer and nighttime bedroom broadband magnetic field, Greater Seattle, Washington, area, 1992–1995

 
The analysis of mean nighttime bedroom broadband magnetic field was extended to investigate whether the risk of breast cancer from exposure to magnetic fields might vary within certain subgroups. Menopausal status, age at diagnosis, and estrogen and progesterone-receptor status (cases only) were each investigated as effect modifiers by including interactions between the effect modifier of interest and the mean magnetic field level. Table 5 displays the results of these analyses. In summary, there was no evidence that any particular subgroup of participants might have an increased breast cancer risk from exposure to nighttime bedroom magnetic fields.


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TABLE 5. Odds ratios for breast cancer and mean nighttime bedroom broadband magnetic field (continuous), stratified by menopausal status, age at diagnosis, and estrogen/progesterone receptor status, Greater Seattle, Washington, area, 1992–1995

 
Wire codes
Nearly identical proportions of cases and controls had wire codes of the home at diagnosis (reference) in the highest two categories (23 and 24 percent, respectively). Of the subjects for whom wire codes were obtained for all residences in the 5 years prior to diagnosis (reference), identical proportions of cases and controls were in the highest two categories (22 percent). Of the subjects for whom wire codes were obtained for all residences in the 10 years prior to diagnosis (reference), a slightly higher percentage of cases than of controls were in the highest two categories (21 and 19 percent, respectively).

Table 6 displays the results of analyses of Wertheimer-Leeper wire codes and breast cancer risk. There was no association between the risk of breast cancer and any of the following: 1) wire code of the home at diagnosis (reference); 2) 5-year weighted summary wire code; and 3) 10-year weighted summary wire code. Five- and 10-year weighted summary wire codes were also calculated by using the respective in-home nighttime mean magnetic field level for each wire code category instead of the scale values 1–5 (see Materials and Methods), and results of analyses were essentially unchanged (data not shown). All wire code analyses were repeated, treating the three wire code variables as continuous rather than categorical variables by using the scale value assigned to each wire code category, and results were essentially the same.


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TABLE 6. Odds ratios for breast cancer and residential Wertheimer-Leeper wire code, Greater Seattle, Washington, area, 1992–1995

 
Appliance usage
Among cases, the average total appliance exposure was 0.0128 tesla/year, and among controls, the average exposure was 0.0135 tesla/year. Nearly identical proportions of cases and controls reported ever use of an electric bed-warming device (42 and 43 percent, respectively). Table 7 displays the results of analyses of risk of breast cancer and exposure to magnetic fields from the everyday use of household appliances in the 10 years prior to diagnosis (reference). No association was seen between the risk of breast cancer and 1) total exposure to magnetic fields from household appliance use; 2) ever use of electric bed-warming devices in the 10 years prior to diagnosis (reference); or 3) hours of use per year of electric bed-warming devices. Analyses of total appliance exposure and hours of use of bed-warming devices as categorical variables did not materially change the results.


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TABLE 7. Odds ratios for breast cancer and appliance use in the 10 years prior to diagnosis (reference), Greater Seattle, Washington, area, 1992–1995

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The results of this study do not support the hypothesis that exposure to residential magnetic fields is associated with an increased risk of breast cancer. No association was found with measures of nighttime bedroom mean broadband magnetic field, variability in broadband magnetic field, or proportion of measurements >=0.2 µT. There was no evidence that a particular subgroup of women is more susceptible to the effects of exposure to magnetic fields in the bedroom at night. Additional analyses in which broadband magnetic field measurements were restricted to those in the harmonic frequency range (100–800 Hz) did not change these results (data not shown). Reported use of household appliances, including bed-warming devices, was not associated with an increased risk of breast cancer. There was no association with the wire code configuration of the home at diagnosis or weighted summary measures of wire codes of the homes occupied in the 5 and 10 years prior to diagnosis.

To date, we are aware of no study of breast cancer and residential magnetic field exposure that has used direct measurements of magnetic field levels in the home at diagnosis. Our findings are consistent with those of five studies that investigated reported past use of electric bed-warming devices as a primary exposure measure (11Go, 16GoGoGo–19Go) and with those of five studies that relied on characteristics of power lines surrounding current or historical residences as the primary method to estimate exposure (7GoGoGoGo–11Go).

In contrast, three other studies have reported an increased risk of breast cancer associated with exposure to residential magnetic fields using characteristics of wiring configuration as the primary exposure metric. Wertheimer and Leeper (12Go, 13Go) found an increase in breast cancer risk among women who lived in homes classified as having a high-current configuration; however, the coder of all addresses was aware of the case-control status of the subjects. A study in New York State found slightly increased age-adjusted incidence rates of breast cancer among women who resided in census tracks containing 138-kV transmission lines at the time of diagnosis (14Go). However, women living in these census tracks had higher average income levels and more localized staging of breast cancer. More recently, Feytching et al. (15Go) reported an association between magnetic field exposure as estimated from surrounding residential power lines and breast cancer risk among young women (age <50 years at diagnosis). The highest risk was observed in the young cases with ER+ tumors, based on six exposed cases and one exposed control.

In interpreting the current findings, two methodological issues should be considered. First, could bias in the selection or enrollment of participants account for the lack of association observed? This seems unlikely for several reasons. First, response rates for cases and controls were similar and were relatively high. Second, participants did not differ from nonparticipants in terms of wire code distribution, which was determined for the current residences of 380 nonparticipants. Furthermore, the distribution of wire code among nonparticipants did not differ by case-control status. Consequently, an analysis of wire code and breast cancer risk among nonparticipants found no association. Third, the low proportions of participant cases and controls in the highest wire code category do not differ substantially from those of several studies conducted in other US cities that used the Wertheimer-Leeper categorization scheme, including one in which the study area spanned nine states (12Go, 26GoGo–28Go). Finally, cases and controls did not differ appreciably in socioeconomic status (SES) (the two groups had nearly identical income and education levels, and all subjects were required to have a telephone). This could, in fact, suggest that controls of higher SES were overselected, as it is generally established that breast cancer occurs more frequently in women of higher SES. However, based on earlier work in the Seattle area (29Go) that assessed the relation between indicators of SES and wire code and the potential impact of differential participation of low- and high-SES controls, overrepresentation of higher SES controls would tend to inflate the odds ratio, perhaps up to 25 percent, rather than attenuate it. Furthermore, this study found no relation between indicators of SES and mean nighttime magnetic field levels or wire code categories (data not shown).

Of more concern is the likelihood of exposure misclassification. Measured nighttime bedroom magnetic field levels in the home at diagnosis, or wiring configuration of the current residence, may not accurately reflect past exposure. To better capture historical exposure, summary measures of the wire codes of all homes 5 and 10 years prior to diagnosis were also analyzed, but wiring configuration around the home may not be an accurate measure of magnetic field exposure inside the home. This study found a low correlation between wire code and 24-hour measured magnetic fields inside the home (Spearman rank correlation coefficient = 0.26; p < 0.0001). Exposure assessment is further complicated by the fact that it remains unclear when the most etiologically relevant time of exposure occurs. If cumulative exposure over many years is the relevant measure, or if there exists a "window" in the development or progression of the disease during which exposure is most important, then measures of the types used in this study may be of limited use in distinguishing persons at different exposure levels.

Finally, this study had relatively few participants at high levels of exposure. More than 90 percent of both cases and controls had mean nighttime magnetic field levels of less than 0.16 µT. Similarly, the majority of both cases and controls were in the lowest two categories of wire code of the home at diagnosis and the weighted summary measures of the homes occupied in the 5 and 10 years prior to diagnosis. Although the primary focus of this study was residential magnetic field exposure, occupational data were collected during the in-person interview to estimate potential exposure to magnetic fields in the workplace. However, of the 1,129 subjects employed outside the home at reference date, only 10 worked in jobs with probable high exposure to magnetic fields, and only 12 worked in jobs with possible high exposure.

It may be that a particular subgroup of women is more susceptible to the effects of magnetic field exposure. Melatonin has been shown experimentally to be both oncostatic and cytotoxic to estrogen-receptor-positive tumor cells in vitro (3Go, 30Go, 31Go), suggesting that women who develop estrogen-receptor-positive breast cancer may be more sensitive to the effects of reduced melatonin levels. Premenopausal women may be more susceptible to the effects of chronic reduction in melatonin levels than postmenopausal women, whose ovarian estrogen production has effectively ceased. This study found no association between risk of breast cancer and exposure to magnetic fields in either of these subgroups; however, the smallest relative risk that could be detected with 80 percent power was 1.9 for the subgroup of premenopausal subjects, and 2.3 for the subgroup of premenopausal estrogen progesterone-receptor-positive subjects, when comparing the first with the fourth quartile of mean nighttime bedroom magnetic field.

In a previous study of magnetic fields and nocturnal melatonin levels in the Seattle area, a small, measurable association between higher nighttime bedroom magnetic field level and lower nocturnal melatonin concentrations was observed (32Go). It remains unclear whether the observed effect is substantial enough to affect one's risk of developing breast cancer. Furthermore, the association between nocturnal melatonin levels and magnetic field exposure was observed primarily in those subjects who reported using medications that are associated with reduced melatonin levels. Information on medication use was not collected as part of the present study. Participants are currently being recontacted to collect this information for the 10 years prior to the reference date.

Although this study found no association between various indicators of exposure to residential magnetic fields and the risk of breast cancer, it may be that chronic disruption of the normal daily cycle of melatonin production is indeed related to the development of breast cancer, but that other factors are more directly responsible for such effects. One such possibility is exposure to light at night, which has repeatedly been shown to reduce nocturnal melatonin levels (5Go) and is a characteristic of industrialized society closely related to the use of electric power. Analyses of exposure to light at night, including both residential exposure and occupational exposure from shift work, are currently under way and may provide additional insight regarding the hypothesis that prompted this study.


    ACKNOWLEDGMENTS
 
Supported by grant R01CA55844 from the National Cancer Institute.

The authors thank the following persons for their valuable contributions to this work: Norma Logan, project management; Elizabeth Carosso, data management; Lynette Beaulaurier, Yves Jaques, Cathy Kirkwood, Linda Messent, Betsy Peters, and Mark Reames, data collection; and Peggy Adams Myers, contract administration. They are indebted to Dr. David Thomas and Dr. Suresh Moolgavkar for their helpful advice and their reviews of earlier versions of this manuscript.


    NOTES
 
Reprint requests to Dr. Scott Davis, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North MP-474, P.O. Box 19024, Seattle, WA 98109-1024 (e-mail: sdavis{at}fhcrc.org).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Stevens RG. Electric power use and breast cancer: a hypothesis. Am J Epidemiol 1987;125:556–61.[ISI][Medline]
  2. Cohen M, Lippman M, Chabner B. Role of pineal gland in aetiology and treatment of breast cancer. Lancet 1978;2:814–16.[Medline]
  3. Hill SM, Blask DE. Effects of the pineal hormone melatonin on the proliferation and morphological characteristics of human breast cancer cells (MCF-7) in culture. Cancer Res 1988;48:6121–6.[Abstract]
  4. Stevens RG, Davis S. The melatonin hypothesis: electric power and breast cancer. Environ Health Perspect 1996;104(suppl 1):135–40.[ISI][Medline]
  5. Brainard GC, Kavet R, Kheifets LI. The relationship between electromagnetic field and light exposures to melatonin and breast cancer risk: a review of the relevant literature. J Pineal Res 1999;26:65–100.[ISI][Medline]
  6. Caplan LS, Schoenfeld ER, O'Leary ES, et al. Breast cancer and electromagnetic fields—a review. Ann Epidemiol 2000;10:31–44.[ISI][Medline]
  7. McDowall ME. Mortality of persons resident in the vicinity of electricity transmission facilities. Br J Cancer 1986;53:271–9.[ISI][Medline]
  8. Schreiber G, Swaen G, Meijers J, et al. Cancer mortality and residence near electricity transmission equipment: a retrospective cohort study. Int J Epidemiol 1993;22:9–15.[Abstract]
  9. Li CY, Theriault G, Lin RS. Residential exposure to 60-Hz magnetic fields and adult cancers in Taiwan. Epidemiology 1997;8:25–30.[ISI][Medline]
  10. Verkasalo PK, Pukkala E, Kaprio J, et al. Magnetic fields of high voltage power lines and risk of cancer in Finnish adults: nationwide cohort study. BMJ 1996;313:1047–51.[Abstract/Free Full Text]
  11. Coogan PF, Aschengrau A. Exposure to power frequency magnetic fields and risk of breast cancer in the Upper Cape Cod Incidence Study. Arch Environ Health 1998;53:359–67.[ISI][Medline]
  12. Wertheimer N, Leeper ED. Adult cancer related to electrical wires near the home. Int J Epidemiol 1982;11:345–55.[Abstract]
  13. Wertheimer N, Leeper ED. Magnetic field exposure related to cancer subtypes. Ann N Y Acad Sci 1987;502:43–53.[Abstract]
  14. New York State Department of Health Bureau of Environmental and Occupational Epidemiology. Location of 138 kV electric transmission lines in Nassau and Suffolk Counties, New York, and breast cancer incidence. Albany, NY: New York State Department of Health, 1992:1978–88.
  15. Feychting M, Forssen U, Rutquist LE, et al. Magnetic fields and breast cancer in Swedish adults residing near high-voltage power lines. Epidemiology 1998;9:392–7.[ISI][Medline]
  16. Gammon MD, Schoenberg JB, Britton JA, et al. Electric blanket use and breast cancer risk among younger women. Am J Epidemiol 1998;148:556–63.[Abstract]
  17. Zheng T, Holford TR, Mayne ST, et al. Exposure to electromagnetic fields from use of electric blankets and other in-home electrical appliances and breast cancer risk. Am J Epidemiol 2000;151:1103–11.[Abstract]
  18. Vena JE, Graham S, Hellmann R, et al. Use of electric blankets and risk of postmenopausal breast cancer. Am J Epidemiol 1991;134:180–5.[Abstract]
  19. Vena JE, Freudenheim JL, Marshall JR, et al. Risk of premenopausal breast cancer and use of electric blankets. Am J Epidemiol 1994;140:974–9.[Abstract]
  20. Vena JE, Freudenheim JL, Marshall JR, et al. Re: "Risk of premenopausal breast cancer and use of electric blankets" and "Use of electric blankets and risk of postmenopausal breast cancer. The authors reply." (Letter). Am J Epidemiol 1995;142:1345.[ISI]
  21. Waksberg JE. Sampling methods for random digit dialing. J Am Stat Assoc 1978;73:40–6.[ISI]
  22. Yost MG. Alternative magnetic field exposure metrics: occupational measurements in trolley workers. Radiat Prot Dosimetry 1999;83:99–106.[Abstract]
  23. Wertheimer N, Leeper ED. Electrical wiring configurations and childhood cancer. Am J Epidemiol 1979;109:273–84.[Abstract]
  24. Gauger JR. Household appliance magnetic field survey. IEEE Trans Power Apparatus Systems 1985;PAS-104:2436–44.
  25. Breslow NE, Day NE, eds. Statistical methods in cancer research. Vol 1. The analysis of case-control studies. Lyon, France: International Agency for Research on Cancer, 1980. (IARC scientific publication no. 32).
  26. Kleinerman RA, Kaune WT, Hatch EE, et al. Are children living near high-voltage power lines at increased risk of acute lymphoblastic leukemia? Am J Epidemiol 2000;151:512–15.[Abstract]
  27. Preston-Martin S, Navidi W, Thomas D, et al. Los Angeles study of residential magnetic fields and childhood brain tumors. Am J Epidemiol 1996;143:105–19.[Abstract]
  28. Savitz DA, Wachtel H, Barnes FA, et al. Case-control study of childhood cancer and exposure to 60-Hz magnetic fields. Am J Epidemiol 1988;128:21–38.[Abstract]
  29. Gurney J, Davis S, Schwartz SM, et al. Childhood cancer occurrence in relation to power line configurations: a study of potential selection bias in case-control studies. Epidemiology 1995;6:31–5.[ISI][Medline]
  30. Cos S, Blask DE. Effects of the pineal hormone melatonin on the anchorage-independent growth of human breast cancer cells (MCF-7) in a clonogenic culture system. Cancer Lett 1990;50:115–19.[ISI][Medline]
  31. Shellard SA, Whelan RDH, Hill BT. Growth inhibitory and cytotoxic effects of melatonin and its metabolites on human tumour cell lines in vitro. Br J Cancer 1989;60:288–90.[ISI][Medline]
  32. Davis S, Kaune WT, Mirick DK, et al. Residential magnetic fields, light-at-night, and nocturnal urinary 6-sulfatoxymelatonin concentration in women. Am J Epidemiol 2001;154:591–600.[Abstract/Free Full Text]
Received for publication December 8, 2000. Accepted for publication July 31, 2001.