extremely low-frequency electric and magnetic fields and cancer

Cancer Causes and Control, 2, 267 - 276

PERSPECTIVE

Extremely low-frequency electric and magnetic fields and cancer

Charles Poole and Dimitrios Trichopoulos

(Received 20 March 1991; accepted in revised forrn 20 May 1991)

Key words: Brain cancer, central nervous system cancers, childhood cancer, ELF-EMF, leukemia.

Introduction This paper examines the most relevant epidemiologic data available on the hypothetical role of extremely low-frequency (50-60 Hertz) electric and magnetic fields (ELF-EMF) in the occurrence of cancer. Until 1979, there was no evidence linking ELF-EMF to cancer. That year, Wertheimer and Leeper I reported a substantial excess of high-current electrical wiring configurations near the homes of children in Denver, Colorado (United States), who had died of cancer. Because building materials effectively shield electric fields, but not the corresponding magnetic fields, the latter were considered the exposure of potential biological relevance. Since then, more than 50 epidemiologic studies have examined the association. 2-6

Researchers in this area generally have avoided making causal inferences from data that are inherently weak. Nevertheless, the topic has been sensational- ized 79 and scientific bodies such as the International Agency for Research on Cancer 1° and regulatory authorities such as the US Environmental Protection Agency 1~ have taken a strong interest in it. Our goals are to discuss issues of methodology and interpretation in the most notable epidemiologic studies, to examine the overall epidemiologic coherence of the

evidence, and to consider its biologic plausibility. We focus on leukemia and cancers of the central nervous system. They are the malignancies most frequently mentioned in connection with ELF-EMF and the most common cancers among children, studies of whom have raised some of the most intriguing questions.

Residential studies Most interest in the epidemiologic literature on ELF- EMF and cancer has focused on three case-control studies because of their positive associations between childhood cancers and measures of ELF-EMF exposure. In the first study, Wertheimer and Leeper 1 used only wiring codes to measure exposure. The wiring codes categorize homes by visible features of nearby electrical power lines (e.g., thickness) that are related to current--and therefore the magnetic field strength--and by the proximity of the homes to these lines. Tomenius, 12 in a study of Swedish children, used two measures of exposure: (i) magnetic field measurements taken at the front entrances of dwellings and (ii) estimated proximity of residences to overhead high- voltage transmission lines. Because most distribution

Dr Poole is with the Epidemiology and Biostatistics Section, Boston University School of Public Health, 80 East Concord Street, Boston, MA 02118-2394, USA. Dr Trichopoulos is with the Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. Address correspondence to Dr Poole.

(~ 1991 Rapid Communications of Oxford Ltd Cancer Causes and Control. Vol 2. 1991 267

C. Poole and D. Trichopoulos

Table 1. Relative risks (95 percent confidence intervals) f rom three studies of ch i ldhood leukemia and central nervous system cancers in relat ion to measures of E L F - E M F exposure in dwellings occupied at the t ime of diagnosis or death

Leukemia Central nervous system cancers

Authors (year) Wiring codes Magnetic fields Wiring codes Magnetic fields

Wertheimer and Leeper 1 (1979) Tomenius 12 (1986) Savitz et a113 (1988)

3.0 (1.8- 5.0)' not measured 2.4 (1.1 - 5.1) ~ not measured 1.1 (0.3-4.6) b 0.3 (0.1-1.1) c 4.0 (0.9-27.1) b 3.9 (1.2-17.3) ~ 1.5 (0.9-2.6)' 1.9 (0.7-5.6) a 2.0 (1.1-3.8) ~ 1.0 (0.2-4.8) d

a High-current cflow-current configurations. b < 150 m from overhead 200 kilovolt transmission line cf~> 150 m. c/> 3.0 milligauss cf < 3.0 milligauss at dwelling entrance.

/> 2.0 milligauss cf < 2.0 milligauss inside dwelling, low-power conditions.

lines (the lines that deliver electric power to homes) in Sweden are buried, proximity to transmission lines is the functional equivalent of wiring codes in that country. Savitz et a113-16 studied Denver children and used wiring codes, as did Wertheimer and Leeper, but added in-home measurements of electric and magnetic fields and an assessment of electric appliance use.

Wertheimer and Leeper 1 reported appreciable associations between high-current wiring codes and both leukemia and central nervous system cancers (Table 1). The study, however, failed to meet a few of the methodologic standards of contemporary epidemiologic research. The wiring codes, for instance, were not assigned with the case or control status of the homes masked, though evidence from a small vali- dation study in a later investigation of adult cancers by the same authors suggested an absence of substantial bias. 17 Of greater importance, the control-selection procedure was so complicated that it has eluded critical scrutiny. The control group was not necessarily biased, but its adequacy cannot be evaluated as thoroughly as can control groups selected by simpler and more familiar methods. Wertheimer and Leeper served to inspire subsequent studies in a research area that, justifiably or not, did not even exist prior to their initial report.

Tomenius 12 reported a strong association between central nervous system cancers and both of his measures of ELF-EMF exposure, but no positive associa- ton for leukemia (Table 1). Unfortunately, Tomenius reported all data for specific cancers (including the results summarized in Table 1) in the form of dwelling counts, with variable numbers of dwellings per subject, and not as counts of cases and controls. Also curious was the author's choice of a 3.0 milligauss cut-point to create a dichotomous exposure scale. It led to a very low exposure-prevalence, about one percent among controls, approximately equal to the unavoidably low prevalence of homes within 150 m of high-voltage transmission lines. The 3.0 milligauss cut-point made the estimates of relative risk (RR) very

268 Cancer Causes and Control. Vol 2. 1991

imprecise, as reflected in their extremely wide confidence intervals (Table 1). No more informative pres- entation of the data from the Tomenius study has become available.

The investigation by Savitz et a113-16 is the most comprehensive, methodologically sound, and com- pletely reported study of childhood cancer and residential ELF-EMF exposure published to date. For brain cancer, which the researchers considered separ- ately from other cancers of the central nervous system, an association was present with wiring codes but not with measured magnetic fields (Table 1). In contrast, leukemia was somewhat more strongly associated with measured magnetic fields than with wiring codes (Table 1). Prenatal electric-blanket use was associated withleukemia(RR = 1.7, 95 percent confidence inter- val [CI] = 0.8-3.6) and brain cancer (RR = 2.5, CI = 1.1-5.5). Associations with postnatal electric- blanket use and use of other electric appliances were weaker or nonexistent.

One of the methodologic problems of the study by Savitz et al is the large amount of missing ELF-EMF measurement data. No magnetic field measurements were obtained for 64 percent of the cases and 20 percent of the controls. The estimated RRs for measured magnetic fields have much broader confidence intervals (Table 1) and consequently are less reliable than the estimates for wiring codes.

Despite the missing data problem with the magnetic field measurements, it was expected that measured field strengths would be superior to wiring codes as indicators of actual exposure. Therefore, under the causal hypothesis, field-strength measurements should have produced substantially higher RR estimates than those obtained with wiring codes. To the contrary, only wiring codes were associated at all with brain cancer. For leukemia, the magnetic-field RR was slightly higher than the wiring-code RR but consider- ably lower than the wiring-code estimate from Wertheimer and Leeper's study I (Table 1). These results are not consistent with the coupling of the

E L F - E M F and cancer

causal hypothesis with the notion that measured fields are superior to wiring codes as an index of etiologically active exposure.

Wertheimer and Leeper had questioned the presumed superiority of measured fields in 1983) s Faced with results that also seemed to refute this premise, or the causal hypothesis, Savitz et al raised additional concerns. They drew analogies, one to a smoking history cfa single urinary-cotinine value as an index of long-term cigarette smoking, 6'13 and another to a food- frequency questionnaire (FFQ) as a better reflection of long-term dietary intake than a 24-hour dietary recall. 6 To extend the latter analogy, we note that a series of 24-hour recalls is better than an FFQ when the time variability of the relevant dietary intake is limited) 9 In two residential studies of ELF-EMF and cancer, several actual measurements of magnetic field strengths were made in selected homes; little variability was observed with day of the week or season of the year) 4'2° Therefore, repeated measurements of magnetic fields could be superior to wire codes as indicators of long-term ELF-EMF exposure. No study, however, has used repeated measurements for comparisons of cancer risk and it is unlikely that any study will obtain measurements over the periods of years or decades that may be pertinent to such comparisons.

Neither present correlations between wiring codes and short-term ELF-EMF measurements (r = 0.40- 0.45), 2°'21 n o r other data such as national power-consumption trends, 22"z3 directly address the crucial question of how present short-term measurements compare with wire codes as indicators of long-term ELF-EMF exposures. More research on wiring codes and measured fields over longer periods of time is needed. In the absence of evidence, wiring codes and short-term measurements should be treated not only as proxies of long-term exposure to ELF-EMF, but also as proxies of one or more potential confounders or selection factors.

Little is known about common risk factors for childhood leukemia and brain tumors. Despite this limited knowledge, Savitz et a113-1s collected information on a host of potential confounders, measured with variable accuracy, and found that none of them, when controlled, appreciably altered the associations between cancer and the ELF-EMF measures. Thus, as in all studies of diseases of largely unknown etiology, the possibility of substantial, uncontrolled confound- ing can be neither dismissed nor invoked as a crucial methodologic flaw.

Socioeconomic status might be a selection factor in the study by Savitz et al, in which the controls were selected by random-digit telephone dialing. In general,

persons of very low socioeconomic status are difficult to identify, contact, and recruit as controls by this method, which was also used in a similar study by Peters et al, 24 not yet published at the time of this writing. A deficit of controls of very low socioeconomic status would produce:

(i) a downward bias in estimates of RR for measures of socioeconomic status, and for factors associated positively with socioeconomic status; and

(ii) an upward bias in RRs estimated for factors associated inversely with socioeconomic status; and

(iii) a concentration of the upward bias such that the RRs would be accentuated in comparatively low socioeconomic strata and close to the null value of 1.0 in the higher socioeconomic groups (i.e., socioeconomic status would look as though it were an effect-modifier).

One might expect socioeconomic status to be related inversely to measures of ELF-EMF in the Denver area if the poorest families have a disproportionate tendency to live in crowded urban areas with relatively little distance between dwellings and the nearest electric power distribution lines. In some metropolitan areas, however, the poorest neighborhoods may not be in the inner city. Moreover, it is not certain that urban residences receive more exposure than suburban and rural residences. Nevertheless, the same study by Savitz et al has produced positive associations between childhood cancer and three additional factors that might be more prevalent in the very low socioeconomic groups: high traffic density near the home;25 parental cigarette smoking; 26 and abstention from breast feeding, v Therefore, the possibility of socio- economically mediated control-selection bias in this study should be seriously considered.

The real socioeconomic profile of childhood cancer in the Denver metropolitan area is not known. It could be assessed with census-tract or block-area statistics in an extension of the analyses of Denver-area incidence rates that Savitz and Zuckerman 2s have already published, using the cases identified for the case-control study. Among all age groups combined, both leukemia and brain tumors are thought generally to be cor- related positively with socioeconomic status. 1° In their case-control comparisons, however, Savitz et al TM

found childhood cancer to be apparently more common in the lower socioeconomic groups. These results could be a reflection of control-selection bias or of a real difference between childhood and adult cancers in their associations with socioeconomic status.

In the data collected by Savitz et al, TM the associ-

Cancer Causes and Control. Vol 2. 1991 269


ations between the ELF-EMF measures and cancer risk were confined largely to the lower socioeconomic strata. (These stratified results are presented for all cancers combined because the bias, if any, would not be expected to vary from cancer to cancer.) The RRs for high-current wiring codes were 1.9 among children from relatively low-income families (annual income < $7,000 per capita) and 1.7 among children with less educated fathers (no college degree), but only 1.2 among children from families with higher incomes and 1.2 among children with highly educated fathers. Mea- sured magnetic fields (using a 1.0 milligauss cut-point) had RRs of 2.0 and 2.2 in the low-income and low- education strata and 0.9 and 0.5 in the high-income and high-education strata, respectively. These results are consistent with the control-selection bias hypothesis.

An additional problem with control selection in the study by Savitz et al is that the random digits were dialed after the close of the study period, up to nine years after the cases' dates of diagnosis. Thus, the controls were restricted to a residentially stable subset consisting of those who, in addition to living in the study area at the time of the random-digit dialing, had also lived there at the time their matched cases were diagnosed. The study included no comparable require- ment for the cases to be living in the study area at the time the controls were selected and, in any event, the occurrence of childhood cancer might well alter a family's propensity to move. The study data con- firmed that, prior to diagnosis, the cases had been more residentially mobile than the controls. If risk factors for childhood cancer are associated with residential mobility, the different eligibility criteria for cases and controls would have produced a bias. The bias would be toward spuriously high RRs if risk factors are more common among children in mobile families, and toward spuriously low RRs if risk factors are more common among children in residentially stable families. If mobility is associated with socioeconomic status, the direction and magnitude of possible control-selection biases becomes even more difficult to predict.

At least three follow-up activities with respect to control-selection are warranted: (i) detailed analyses of available information on the socioeconomic status of the respondents and nonrespondents in the study by Savitz et aI, 1316 and of the association between socioeconomic status and childhood cancer rates in the Denver area as a whole; (ii) a similar analysis in the forthcoming study by Peters et al in the Los Angeles area; z4 and (iii) a consideration in future studies of alternatives to random-digit dialing and to preferential selection of residentially stable controls.

Occupational studies The studies of adult cancers and occupational exposures to ELF-EMF can be classified into proportionate, case-control, and cohort (including retro- spective cohort) studies. The proportionate studies 2938 are, in essence, case-control studies with questionable control groups. 39 The widely-known 'healthy worker' phenomenon 4° (which leads to lower-than-expected rates of death from chronic diseases such as cardio- vascular and cerebrovascular disease in employed groups) is likely to produce an upward bias in effect- estimates from proportionate studies linking specific occupational groups with diseases like leukemia and brain cancer. Data from Lin's study in Tawaian 41 exemplify this bias. Among deceased telecommunication workers, 34 percent died from cancer as compared with only 22 percent in the general population; the corresponding proportional mortality ratio was 1.5 and the mortality odds ratio was 1.8. The ratio of cancer mortality rates, however, was equal to the ,null value of 1.0, with 129 cancer deaths observed and 127.3 expected. Positive associations from the proportionate studies, 2938 therefore, cannot be given much credence.

As with the proportionate studies, many of the investigations reported by the authors as case-control s t u d i e s 33'42-4z w e r e based exclusively on mortality or cancer-registration information generated by routine reporting. Data on exposure and potentially con- founding factors (such as benzene exposure in analyses of leukemia) tends to be highly limited in these studies. Indeed, among the 17 case-control studies that have examined occupational exposures to ELF-EMF, 33'42-57 only f ive 48'51'52'56'5x w e r e both sufficiently large and specifically designed to ascertain exposure to EMF with information more complete (and presumably more valid) than that routinely collected for cancer registration or death certification.

Cohort studies are considered widely to be methodologically superior to case-control investigations of occupational associations because selection bias is less of a concern in cohort studies. Nevertheless, cohort studies often suffer from poor exposure information and dubious comparability between employed groups and general populations. The results of the available cohort studies 4~'ssTs tend not to suggest the existence of an appreciable association between occupational ELF- EMF exposures and adult leukemia or central nervous system cancers.

At present, virtually the entire literature on occupational ELF-EMF exposure and cancer suffers from the potential for selective reporting of 'positive' results and ad hoc aggregation of occupations into 'exposed' groups based on their individual associations with can-


ELF-EMF and cancer

cer. This potential exists because of the large number of cancer studies for which some occupational information already has been collected. It is a relatively simple matter to add a row or column for ELF-EMF to an existing exposure-classification matrix. Investi- gators then may be tempted to use the results to decide whether or not to modify the list of 'exposed' occupations or jobs or to decide whether or not to publish the results. These forms of bias are, in our opinion, more likely among the presently available occupational studies than among the residential studies, since in the latter, considerable resources were devoted to the generation of exposure information for study subjects. The greater the commitment to generating exposure information, the less likely selective reporting or ad hoc aggregation of jobs or occupations will be. Results of formal meta-analyses of the occupational studies on ELF-EMF and cancer are therefore suspect.

In summary, the following problems prevent firm etiologic conclusions from being drawn from the occupational studies:

(i) the effect-estimates from the proportionate studies tend to be biased upward by the 'healthy worker' phenomenon;

(ii) the poor quality of the exposure information in virtually all of the studies makes it difficult to rely on 'negative' results from any of them;

(iii) information on potential confounders such as occupational benzene exposure is often absent or highly limited; and

(iv) the occupational literature is susceptible to selective reporting and ad hoc aggregation of jobs and occupations, depending on the results obtained.

Epidemiologic coherence Coherence of the epidemiologic evidence can be an important element of causal inference; it refers to the consistency of the epidemiologic patterns that are, or should be, attributed to the same etiologic influences. As shown below, there is little, if any, such coherence with respect to childhood cancers, even though many researchers seem to agree that the strongest evidence concerning hypothetical causation by ELF-EMF comes from the childhood cancer studies.

Virtually all investigators agree that the ascertain- ment of true relevant exposure in ELF-EMF studies is subject to considerable misclassification. Nondiffer- ential misclassification generates systematic under- estimation of the RR. Thus, it can be inferred that the RRs linking ELF-EMF to childhood cancers, if truly

elevated, in fact should be much higher than the empirically derived RRs, unless the latter have been biased upward by other methodologic shortcomings such as control-selection bias.

It is not possible to estimate the true values of sensitivity and specificity of the widely used exposure vari- ables (wiring codes, spot measurements of magnetic fields, etc.) in epidemiologic studies of ELF-EMF. The true, biologically relevant (e.g., time-weighted) exposure, if any, is not known. Nevertheless, upper limits on the magnitude of these parameters can be 'guestimated,' approximately and indirectly, with the use of existing information.

Savitz et al ~3-Js created dichotomous exposure scales in many analyses by defining the 'exposed' groups as i> 2.0 milligauss for measured magnetic fields and as the combination of 'high' and 'very high' categories of wiring configuration codes (Table 1). Proportional interpolations of some of the detailed data from this study (reference 14, table iii. G1) allow estimation of the sensitivity and the specificity of the proxy measure of elevated magnetic fields (with actual magnetic field measurements as the putative standard), as well as the prevalence of magnetic field measurements ~ 2 milligauss. The estimates under conditions of low power use are: sensitivity 0.51; specificity, 0.80; prevalence, 0.11.

It would be surprising if the validity of either of the two proxy measures (wiring codes and short-term ELF-EMF measurements) with respect to the etiologically relevant exposure were superior to these values. Under these conditions, and assuming nondifferential misclassification probabilities between cases and controls, a true RR of about five would be underesti- mated 76-77 on average to an observed RR of 1.5, whereas a true RR of about 10 would be under- estimated on average to an observed RR of 1.9. An alternative approach 19'78'79 requires some additional normality assumptions and allows the calculation of the true (corrected for misclassification) RR as:

true RR = exponent [ln (observed RR)/r2],

where r 2 is the squared correlation coefficient between true exposure and observed exposure. Studies by Kaune et al 2° and Barnes et a123 indicate that r is unlikely to exceed 0.6 and may indeed be between 0.4 and 0.5. Assuming an observed RR of 1.5 and r = 0.55, the true RR would be 3.8, whereas an observed RR of 2.0 would correspond to a true RR of 9.9.

Exposure to ELF-EMF is almost universal today in industrialized nations. Environmental magnetic fields from electric utility facilities are produced by the currents carried on the transmission and distribution lines

Cancer Causes and Control. Vol 2. 1991 271


and, therefore, may be estimated by the power trans- ported? 2 National power consumption has increased exponentially in this century, with a four-fold increase in the US between 1950 and 1987, 23 but the spatial patterns of the increase have been irregular and unpre- dictable. Trends in new transmission and distribution line construction and in the proximity of homes to lines are complicating factors. The proportional con- tribution of industry to the trends in total consumption also needs to be taken into account. Thus, use of trends in per capita electricity consumption to reflect trends in per capita residential ELF-EMF exposure of children is highly speculative. Nevertheless, if a rapidly increasing and widespread exposure were associated strongly (RR on the order of five to 10) with childhood cancers (the noninherited causes of which have inherently short latency periods), and if no strong countervailing trends in other risk factors have occurred, we would be witnessing an observable epidemic of childhood cancers.

There is little, if any, evidence of such an epidemic. Between 1950 and 1987 the reported incidence of childhood cancers increased by 28 percent, 8° but the validity of the apparent trend has been disputed by some 81'82 who suspect a secular increase of coverage and completeness of registration. In Connecticut, s° where the registration system has long been considered adequate, the incidence rates (per 100,000 per year) of total childhood (0-14 years) cancers and leukemia were 12.6 and 4.0 in 1950-54 and again 12.6 and 4.0 in 1975-79. The geographic distribution of childhood cancer internationally s3 also is not supportive of a major epidemic produced by increased exposures to ELF-EMF. Ecologic correlations are, of course, difficult to interpret; nevertheless, it is important to remember that widespread exposures characterized by high RRs can generate strong ecologic correlations.l°'s4

Epidemiologic evidence and biological plausibility Postulated mode of carcinogenic action of ELF-EMF

There is overwhelming evidence that ELF-EMF do not have initiating carcinogenic properties. They do not cause gene mutations and they have not been implicated in de novo induction of tumorsY 5 Most researchers agree that if ELF-EMF are involved in carcinogenesis at all, they are more likely to act as tumor-growth stimulators) The ELF-EMF effects (calcium efflux from chick brain tissue s6'87 and inhi- bition of melatonin synthesis ss) that have been shown to occur at field strengths comparable to those experi- enced by humans, are not suspected to influence the


initiation or (early) promotion phases of carcinogenic processes. Radio frequency radiation is also conjec- tured to act as a tumor growth stimulator, but not as an initiator. 89

Associations have been reported between childhood cancer and paternal occupations believed to entail elevated ELF-EMF exposure. 9°-95 These associations are even less biologically plausible than the associations with measures of exposure to the children themselves. The putatively causal mechanism would have to involve injury to the paternal germ cell or genome and not tumor growth enhancement--which is the only remotely plausible mechanism at present for linking childhood cancer to personal exposure.

Biomedical plausibility

Biomedical plausibility is an important consideration in interpreting epidemiologic studies. As a general principle, the stronger the empirical association, the less a causal interpretation depends on the identifi- cation of a credible pathophysiologic mechanism. Strong, reproducible associations from well-designed studies can stand on their own and may reshape our understanding of the underlying biomedical processes. In contrast, weak or inconsistent associations can be interpreted etiologically with confidence when the experimental or other biomedical evidence is overwhelming. The association between ELF-EMF and cancer represents neither of these situations, however. A weaker statistical association between childhood cancer and measures of residential magnetic-field exposure has been reported in the study with the best methodology 13-16 than in some of the previous studies; 1'12 the occupational studies are even less consistent with each other; and a plausible biologic mechanism is not presently at hand.

An ELF-EMF and cancer link: plausible or conceivable ?

Conceivability and plausibility are very different con- cepts and have very different implications when judged in conjunction with empirical findings. A plausible finding is one that is based on solid biomedical grounds, whereas an association can be thought of as biologically conceivable when it is not impossible or absurd. The notion that ELF-EMF can cause cancer is not impossible or absurd but is hardly plausible, though research on conceivable biologic mechanisms has been conducted for only a few years.

Some studies indicate that ELF-EMF, under controlled laboratory conditions, may affect biological phenomena. These effects may, in some way, influence known or suspected post-initiation mechanisms of

ELF-EMF and cancer

carcinogenesis, s'21 In most experiments, the fields were of relatively high intensity, producing induced tissue currents on the order of 10 microamperes per square centimeter (~tA/cm 2) compared with 10 ~* vA/cm 2 induced by a typical domestic 60 Hertz magnetic field exposure. Further, some of the postulated effects (e.g., delay of the mitotic cell cycle) could be either carcinogenic or anti-carcinogenic (if anything). Finally, we must face the lack of reproducibility of these results between laboratories, a severe limitation on the inter- pretability of this evidence at present.

It has also been suggested that ELF-EMF, this time at field strengths comparable to those of some human environmental exposures, produce nocturnal sup- pression of melatonin synthesis and affect calcium efflux from chick brain tissues. 86"8s These findings may be interpreted as indicating that ELF-EMF are biologically active but do not of necessity imply that they are carcinogenic.

Finally, it has been suggested that the induction of bone repair and growth stimulation (in acquired bone nonunions secondary to trauma) by pulsed electromagnetic fields (PEMF), 96'97 should be considered as indirect evidence of the potential carcinogenicity of these fields. The evidence for therapeutic effectiveness is based on "improperly designed clinical studies "96 but nevertheless is considered real and attributable to magnetically induced electric currents. 96'97 However, the effects of PEMF cannot be equated with the effects ELF-EMF. Furthermore, human, animal, and in vitro studies indicate that, after application of PEMF, the effective exposure range corresponds to current densi- ties between one and 10 ~tA/cm 2, that there is a lower threshold level, and that no mutagenic (genotoxic) effects have been demonstrated. 96 As previously noted, a typical domestic, 60 Hertz, magnetic exposure will produce in a human a current density of less than 10 4 ~tA/cm 2.

Conclusion Research on cancer and ELF-EMF has been ongoing for slightly more than a decade: less time than it took for the link between cigarette smoking and lung cancer, which entailed a much stronger association and a vastly easier exposure to measure, to become 'estab- lished' as causal. In this early 'discovery stage' of research, investigators should have the freedom to engage in freewheeling and imaginative speculation, research, and debate without fear of being branded as alarmists or participants in a cover-up. Unfortunately, the news-media attention and regulatory interest that this topic has attracted have been detrimental to scientific progress. Pressures are placed unfairly on scien-

tists to take firm positions for or against causality, and to defend those positions, long before an adequate base of observation and theory exists to warrant such decisiveness.

The hypothetical carcinogenicity of ELF-EMF represents an intriguing scientific problem and a potentially important public health issue but, at this stage, nothing more. It clearly is not possible to exon- erate ELF-EMF. In order to do so, very large and valid studies showing very little or no association between ELF-EMF and cancer would be needed. 98 This con- dition is not presently fulfilled. On the other hand, the empirical evidence linking ELF-EMF to cancer is weak and inconsistent. Causal interpretations are not supported by available biologic data. This is an area in which more and better research, and an atmosphere conducive to dispassionate inquiry, are clearly needed.

References

1. Wertheimer N, Leeper E. Electrical wiring configurations and childhood cancer. AmJ Epidemio11979; 109: 273-84.

2. Savitz DA, Calle EE. Leukemia and occupational exposure to electromagnetic fields: review of epidemiological surveys. J Occup Med 1987; 29: 47-51.

3. Ahlbom A. A review of the epidemiologic literature on magnetic fields and cancer. Scand J Work Environ Health 1988; 14: 337-43.

4. Coleman M, Beral V. A review of epidemiological studies of the health effects of living near or working with electricity generation and transmission equipment. IntJ Epidemiol 1988; 17: 1-13.

5. Nair I, Morgan G, Florig HK. Biological Effects of Power Frequency Electric and Magnetic Fields. Washington, DC: Office of Technology Assessment, 1989.

6. Savitz DA, Pearce NE, Poole C. Methodological issues in the epidemiology of electromagnetic fields and cancer. Epidemiol Rev 1989; 11: 59-78.

7. Brodeur P. Currents of Death: Power Lines, Computer Terminals, and the Attempt to Cover up Their Threat to Your Health. New York: Simon and Schuster, 1989.

8. Becker RO, Selden G. The Body Electric: Electromag- netism and the Foundation of Life. New York: William Morrow and Company, 1985.

9. Huber P. Electrophobia. Forbes 4 September 1989: 313. 10. Tomatis L, ed. Cancer: Causes, Occurrence and Control.

Lyon: International Agency for Research on Cancer, 1990; IARC Sci. Pub. No. 100: 164.

11. Pool R. Flying blind: The making of EMF policy. Science 1990; 250: 23-5.

12. Tomenius L. 50-Hz electromagnetic environment and the incidence of childhood tumors in Stockholm County. BioeIectromagnetics 1986; 7: 191-207.

13. Savitz DA, Wachtel H, Barnes FA,John EM, TvrdikJG. Case-control study of childhood cancer and exposure to 60-Hz magnetic fields. Am J Epidemiol 1988; 128: 21-38.

Cancer Causes and Control. Vo12. 1991 273


14. Savitz DA. Case-control Study of Childhood Cancer and Residential Exposure to Electric and Magnetic Fields. Contractor's Final Report, New York State Power Lines Project, Contract 218217, 30 March 1987.

15. Savitz DA. Supplement to the Contractor's Final Report: Case-control Study of Childhood Cancer and Residential Exposure to Electric and Magnetic Fields. New York State Power Lines Project, Contract 218217, 28 March 1988.

16. Savitz DA, John EM, Kleckner RC. Magnetic field exposure from electrical appliances and childhood cancer. ArnJ Epiderniol 1990; 131: 763-73.

17. Wertheimer N, Leeper E. Adult cancer related to electrical wires near the home. Int J Epiderniol 1982; 11: 345-55.

18. Wertheimer N, Leeper E. Health effects of power lines (Letter). Science 1983; 222: 712-3.

19. Willett WC. Nutritional Epidemiology. New York: Oxford University Press, 1989.

20. Kaune WT, Stevens RG, Callahan NJ, Severson RK, Thomas DB. Residential magnetic and electric fields. Bioelectromagnetics 1987; 8: 315-35.

21. Barnes F, Wachtel H, Savitz D, et al. Use of wiring configuration and wiring codes for estimating externally generated electric and magnetic fields. Bioelectrornag- netics 1989; 10: 13-21.

22. World Health Organization. Environmental Health Criteria 35: Extremely Low Frequency (ELF) Fields. Geneva: WHO, 1984.

23. Edison Electric Institute. Historical Statistics of the Elec- tric Utility Industry through 1970. EEI Publication No. 73-74, 1974.

24. Blakeslee S. Electric currents and leukemia show puzz- ling links in new study. The New York Times 8 February 1991: A16.

25. Savitz DA, Feingold L. Association of childhood cancer with residential traffic density. Scand J Work Environ Health 1989; 15: 360-3.

26. John EM, Savitz DA, Sandier DP. Prenatal exposure to parents' smoking and childhood cancer. ArnJ Epiderniol 1991; 133, 123-32.

27. Davis MK, Savitz DA, Graubard BI. Infant feeding and childhood cancer. Lancet 1988; ii: 365-8.

28. Savitz DA, Zuckerman DL. Childhood cancer in the Denver metropolitan area. Cancer 1987; 59: 1539-42.

29. Peterson GR, Milham SJ. Occupational Mortality in the State of California 1959-61. Cincinnati, OH: National Institute for Occupational Safety and Health, 1980, DHEW (NIOSH) Pub. No. 80-104.

30. Milham S Jr. Mortality from leukemia in workers exposed to electrical and magnetic fields (Letter). New EngIJ Med 1982; 307: 249.

31. Wright WJ, Peters JM, Mack TM. Leukemia in workers exposed to electrical and magnetic fields (Letter). Lancet 1982; ii: 1160-1.

32. Coleman M, Bell J, Skeet R. Leukemia incidence in electrical workers (Letter). Lancet 1983; i: 982-3.

33. McDowall M. Leukemia mortality in electrical workers in England and Wales (Letter). Lancet 1983; i: 246.

34. Swerdlow AJ. Epidemiology of eye cancer in adults in England and Wales, 1962-1977. Arn J Epiderniol 1983; 118: 294-300.

35. Calle EE, Savitz DA. Leukemia in occupational groups with presumed exposure to electrical and magnetic fields (Letter). New EnglJ Med 1985; 313: 1476-7.

36. Milham S. Jr Silent keys: leukemia mortality in amateur radio operators (Letter). Lancet 1985; i: 812.

37. Milham S. Jr Mortality in workers exposed to electromagnetic fields. Environ Health Perspec 1985; 62: 297-300.

38. GaUagher RP, McBride ML, Band PR, SpinelliJJ, Threl- fall WJ, Yang P. Occupational electromagnetic field exposure, solvent exposure, and leukemia (Letter). J Occup Med 1990; 32: 64-5.

39. Miettinen OS, Wang JD. An alternative to the proportionate mortality ratio. Arn J EpidernioI 1981; 114: 144-8.

40. Wang JD, Miettinen OS. Occupational mortality studies. Principles of validity. Scand J Work Environ Health 1982; 8: 153-8.

41. Lin RS. Cancer mortality patterns among employees of telecommunication industry in Taiwan. (Meeting abstract) Biological effects from electric and magnetic fields, air ions, and ion currents associated with high voltage transmission lines: contractors review. 1-4 November 1987. Kansas City, MO. US Department of Energy and Electric Power Research Institute, 1988.

42. Dubrow R, Wegman DH. Occupational Characteristics of Cancer Victims in Massachusetts, 1971-1973. Cincin- nati, OH: National Institute for Occupational Safety and Health, 1984; DHHS (NIOSH) Pub. No. 84-109.

43. Pearce NE, Sheppard RA, Howard JK, Fraser J, Lilley BM. Leukemia in electrical workers in New Zealand (Letter). Lancet 1985; i: 811-2.

44. Gilman PA, Ames RG, McCawley MA. Leukemia risk among US white male coal miners. J Occup Med 1985; 27: 669-71.

45. Lin RS, Dischinger PC, Conde J, Farrell KP. Occu- pational exposure to electromagnetic fields and the occurrence of brain tumors. J Occup Med 1985; 27: 413-9.

46. Stern FB, Waxweiler RA, Beaumont JJ, et aL A case- control study of leukemia at a naval nuclear shipyard. ArnJ Epiderniol 1986; 123: 980-92.

47. Flodin U, Fredriksson M, Axelson O, Persson B, Har- dell L. Background radiation, electrical work, and some other exposures associated with acute myeloid leukemia in a case-referent study. Arch Environ Health 1986; 41: 77-84.

48. Thomas TL, Stolley PD, Stemhagen A, et aL Brain tumor mortality risk among men with electrical and electronics jobs: a case control study. JNCI 1987; 79: 233-8.

49. Magnani C, Coggon D, Osmond C, Acheson ED. Occupation and five cancers: a case-control study using death certificates. BrJ Ind Med 1987; 44: 769-76.

50. Speers MA, Dobbins JG, Miller VS. Occupational exposures and brain cancer mortality: a preliminary study of East Texas residents. ArnJ Ind Med 1988; 13: 629-38.

51. Obrams GI. Leukemia in Telephone Linemen. Univer- sity of Michigan Dissertation Service, 1988.

52. Preston-Martin S, Mack W, Henderson BE. Risk factors for gliomas and meningiomas in males in Los Angeles County. Cancer Res 1989; 49: 6137-43.

53. Loomis DP, Savitz DA. Brain cancer and leukemia mortality among electrical workers (Abstract). Arn J Epi- derniol 1989; 130: 814.

54. ReifJS, Pearce N, Fraser J. Occupational risks for brain cancer: a New Zealand cancer registry-based study. J


Occup Med 1989; 10: 863-7. 55. Pearce N, Reif J, Fraser J. Case control studies of cancer

in New Zealand electrical workers. IntJ Epidemio11989 18: 55-9.

56. Verreault R, Weiss NS, Hollenbach KA, Strader CH, Daling JR. Use of electric blankets and risk of testicular cancer. AmJ Epidemiol 1990; 131: 759-62.

57. Lewis J. Employment in Electrical Occupations and the Risk of Neurological Tumors. Doctoral dissertation, University of Texas School of Public Health, 1990.

58. Guralnick L. Mortality by Occupation and Cause of Death among Men 20 to 64 Years of Age: United States 1950. US Government Printing Office, 1963: Vital Stat- istics: Special Reports, Vol. 52, No. 3.

59. Wiklund K, Einhorn J, Eklund G. An application of the Swedish Cancer-Environment Registry. Leukemia among telephone operators at the Telecommunications Administration in Sweden. Int J Epidemiol 1981; 10: 373-6.

60. Vager6 D, Olin R. Incidence of cancer in the electronics industry: using the new Swedish Cancer Environment Registry as a screening instrument. BrJ Ind Med 1983; 40: 188-92.

61. Howe GR, Lindsay JP. A follow-up study of a ten- percent sample of the Canadian Labor Force. 1. Cancer mortality in males. JNCI 1983; 70: 37-44.

62. Olin R, Vager6 D, Ahlbom A. Mortality experience of electrical engineers. BrJ Ind Med 1985; 42: 211-2.

63. Blair A, Walrath J, Rogot E. Mortality patterns among U.S. veterans by occupation. I. Cancer.JNC11985; 75: 1039-47.

64. Vfiger6 D, Ahlbom A, Olin R, Sahlsten S. Cancer mor- bidity among workers in the telecommunications industry. BrJ Ind Med 1985; 42: 191-5.

65. Barregard L, Jarvholm B, Ungethum E. Cancer among workers exposed to strong static magnetic fields (Let- ter). Lancet 1985; ii: 892.

66. T6rnqvist S, Norell S, Ahlbom A, Knave B. Cancer in the electric power industry. Br J Ind Med 1986; 43: 212-3.

67. McLaughlin JK, Malker HSR, Blot WJ, et al. Occu- pational risks for intracranial gliomas in Sweden. JNCI 1987; 78: 253-7.

68. Milham S Jr. Increased mortality in amateur radio operators due to lymphatic and hematopoietic malignancies. AmJ Epiderniol 1988; 127: 50-4.

69. Milham S Jr. Mortality by license class in amateur radio operators (Letter). Am J Epidemiol 1988; 128: 1175-6.

70. Liner MS, Malker HSR, McLaughlin JK, et al. Leu- kemias and occupation in Sweden: a registry-based analysis. AmJ Ind Med 1988; 14: 319-30.

71. Juutilainen J, Pukkala E, Laara E. Results of an epidemiological cancer study among electrical workers in Fin- land.J Bioelectricity 1988: 7: 119-21.

72. De Guire L, Theriault G, Iturra H, Provencher SCD, Case BW. Increased incidence of malignant melanoma of the skin in workers in a telecommunications industry. BrJ Ind Med 1988; 45: 824-8.

73. Guberan E, Usel M, Raymond L, Tissot R, Sweetnam PM. Disability, mortality, and incidence of cancer among Geneva painters and electricians. Br J Ind Med 1989; 46: 16-23.

74. T6rnqvist S, Knave B, Ahlbom A, Persson T. Incidence of leukemia and brain tumours in some "electrical occupations." BrJ Ind Med (in press).

ELF-EMF and cancer

75. Garland FC, Shaw E, Gorham ED, Garland CF, White MR, Sinsheimer PJ. Incidence of leukemia in occupations with potential electromagnetic field exposure in United States Navy personnel. Am J Epidemiol 1990; 132: 293-303.

76. Flegal KM, Brownie C, Haas JD. The effects of exposure misclassification on estimates of relative risk. AmJ Epi- demiol 1986; 123: 736-51.

77. Hsieh C-c, Walter SD. The effect of non-differential exposure misclassification on estimates of the attributable and prevented fraction. Stat in Med 1988; 7: 1073-85.

78. Armstrong BG, Whittemore AS, Howe GR. Analysis of case-control data with covariate measurement error: application to diet and colon cancer. Stat in Med 1989; 8: 1151-63.

79. Rosner B, Willett WC, Spiegelman D. Correction of logistic regression relative risk estimates and confidence intervals for systematic within-person measurement error. Stat in Med 1989; 8: 1051-69.

80. National Institutes of Health. Cancer Statistics Review 1973-87. Rockville, MD: US Department of Health and Human Services, Public Health Service, 1990; NIH Pub. No. 90-2789.

81. Doll R, Peto R. The causes of cancer: quantitative estimates of avoidable risks of cancer in the United States today. JNCI 1981 ; 66: 1191-308.

82. Devesa S, Silverman DT, Young JL, et al. Cancer incidence and mortality trends among whites in the United States, 1947-84.JNCI 1987; 79: 701-70.

83. Parkin DM, Stiller CA, Bieber A, Draper GJ, Terracini B, Young JL eds,. International Incidence of Childhood Cancer. Lyon: International Agency for Research on Cancer, 1988; IARC Sci. Pub. No. 87.

84. Morgenstern H. Uses of ecologic analysis in epidemiologic research. AmJ Public Health 1982; 72: 1336-44.

85. Juutilainen J. Liimatainen A. Mutation frequency in Salmonella exposed to weak 100-Hz magnetic fields. Hereditas 1986; 104: 145-7.

86. Blackman CF, Benane SG, Kinney LS, Joines WT, House DE. Effects of ELF fields on calcium-ion efflux from brain tissue in vitro. Rad Res 1982; 92: 510-20.

87. Blackman CF, Benane SG, Elliott DJ, House DE, Pol- lock MM. Influence of electromagnetic fields on the efflux of calcium ions from brain tissue in vitro: a three- model analysis consistent with the frequency response up to 510 Hz. Bioelectromagnetics 1988; 9: 215-27.

88. Welker HA, Semm P, Willig RP, Commenty JC, Wiltschko W, Volbrath L. Effects of an artificial magnetic field on serotonin in N-acetyltransferase activity and melatonin content of the rat pineal gland. Exp Brain Res 1983; 50: 426-32.

89. Szmigielski S, Szudzinski A, Pletraszek A, Blelec M, Janiak M, Wrembel JK. Accelerated development of spontaneous and benzopyrene-induced skin cancer in mice exposed to 2,450 MHz microwave radiation. Bio- electromagnetics 1982; 3: 179-91.

90. Spitz MR, Johnson CC. Neuroblastoma and paternal occupation. A case-control analysis. Am J Epidemiol 1985 121: 924-9.

91. Wilkins JR, Koutras RA. Paternal occupation and brain cancer in offspring: a mortality-based case-control study. Am J Ind Med 1988; 14: 299-318.

92. Nasca PC, Baptiste MS, MacCubbin PA, et aL An epidemiologic case-control study of central nervous system

Cancer Causes and Control. Vo12. 1991 275


tumors in children and parental occupational exposures. AmJ Epidemiol 1988; 128: 1256-65.

93. Johnson CC, Spitz MR. Childhood nervous system tumors: an asssessment of risk associated with paternal occupations involving use, repair or manufacture of electrical and electronic equipment. Int J Epidemiol 1989; 18: 756-62.

94. Bunin GR, Ward E, Kramer S, Rhee CA, Meadows AT. Neuroblastoma and parental occupation. Am J Epi- demiol 1990; 131: 776-80.

95. Wilkins JR, Hundley VD. Paternal occupational exposure to electromagnetic fields and neuroblastoma in

offspring. AmJ Epidemiol 1990; 131: 995-1008. 96. Food and Drug Administration. Overview of the

Literature on Electrical Bone Repair and Growth Stimu- lation. Rockville, MD: US Department of Health and Human Services, Public Health Service, 1989; HHS Pub. FDA 90-8277.

97. Stuchly MA. Applications of time-varying magnetic fields in medicine. Biomedical Engineering 1990; 18: 89-124.

98. Monson RR. Editorial commentary: epidemiology and exposure to electromagnetic fields. Am J Epidemiol 1990; 131: 774-5.


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