Residential Magnetic Field Exposure Research Articles

Exposure to Magnetic Fields and Childhood Leukemia: An Overview of Meta-Analysis

Background: Leukemia is the most common cancer in children. We aimed to evaluate the association between exposure to magnetic fields and childhood leukemia. Materials and Methods: In this overview,the relevant articles evaluating the association between exposure to magnetic fields and childhood leukemia are screened on the electronic databases of Scopus, EMBASE, Cochrane, Web of Science, and Medline until February 10, 2019. Results: The first meta-analysis showed a statistical association between the magnetic field intensity of ≥0.4 μT and ≥0.2 μT and childhood leukemia. The second meta-analysis based on wiring configuration codes resulted in a pooled relative risk estimate of 1.46 (95% CI=1.05-2.04 μT, P=0.024) and 1.59 (95% CI=1.14-2.22 μT, P=0.006) for exposure to 24-h measurements of magnetic fields, indicating a potential effect of residential magnetic field exposure on childhood leukemia. In the third meta-analysis, the odds ratios of exposure categories of 0.1-0.2 μT, 0.2-0.3 μT, and ≥0.3 μT over Conclusion: Three meta-analyses showed a statistical association between magnetic field intensity and childhood leukemia (ranged 0.1-2.36 μT). The results of one study also showed that there was no relationship between exposure to ≥ 0.1 μT and childhood leukemia.

Power frequency magnetic fields and risk of childhood leukaemia: Misclassification of exposure from the use of the ‘distance from power line’ exposure surrogate

A recent study examining the relationship between distance to nearby power lines and childhood cancer risk re-opened the debate about which exposure metrics are appropriate for power frequency magnetic field investigations. Using data from two large population-based UK and German studies we demonstrate that distance to power lines is a comparatively poor predictor of measured residential magnetic fields. Even at proximities of 50 m or less, the positive predictive value of having a household measurement over 0.2 microT was only 19.4%. Clearly using distance from power lines, without taking account of other variables such as load, results in a poor proxy of residential magnetic field exposure. We conclude that such high levels of exposure misclassification render the findings from studies that rely on distance alone uninterpretable.

Residence Near Power Lines and Mortality From Neurodegenerative Diseases: Longitudinal Study of the Swiss Population

The relation between residential magnetic field exposure from power lines and mortality from neurodegenerative conditions was analyzed among 4.7 million persons of the Swiss National Cohort (linking mortality and census data), covering the period 2000-2005. Cox proportional hazard models were used to analyze the relation of living in the proximity of 220-380 kV power lines and the risk of death from neurodegenerative diseases, with adjustment for a range of potential confounders. Overall, the adjusted hazard ratio for Alzheimer's disease in persons living within 50 m of a 220-380 kV power line was 1.24 (95% confidence interval (CI): 0.80, 1.92) compared with persons who lived at a distance of 600 m or more. There was a dose-response relation with respect to years of residence in the immediate vicinity of power lines and Alzheimer's disease: Persons living at least 5 years within 50 m had an adjusted hazard ratio of 1.51 (95% CI: 0.91, 2.51), increasing to 1.78 (95% CI: 1.07, 2.96) with at least 10 years and to 2.00 (95% CI: 1.21, 3.33) with at least 15 years. The pattern was similar for senile dementia. There was little evidence for an increased risk of amyotrophic lateral sclerosis, Parkinson's disease, or multiple sclerosis.

Residential Magnetic Field Exposure and Childhood Brain Cancer

We conducted a meta-analysis of studies on magnetic field exposure and childhood brain tumors to evaluate homogeneity in the results, to examine reasons for heterogeneity, and to derive a summary effect estimate. Comparison of results from studies of childhood brain cancer and childhood leukemia may also help to assess the potential for selection bias in childhood leukemia studies. We included results from 13 studies. Using an inverse variance-weighted method, summary effect estimates were calculated separately for distance, wire codes, and measured and calculated magnetic fields. Sensitivity analyses were conducted to assess the influence of individual studies, the potential for selection bias, and the possibility of publication bias. With the exception of wire-code studies, results were compatible with homogeneity across studies. The summary odds ratios (95% confidence intervals) were 0.88 (0.57-1.37) for distance <50 m and 1.14 (0.78-1.67) for calculated or measured magnetic fields above 0.2 microT. For measured or calculated exposures above 0.3 or 0.4 microT, the summary odds ratio was 1.68 (0.83-3.43), with no differences by method of exposure assessment. No single study had a substantial effect on the summary estimates. There was no indication of publication bias. With the exception of high cut-point analyses (0.3/0.4 microT), where the possibility of a moderate risk increase cannot be excluded, no increase in childhood brain cancer risk was evident for any of the exposure metrics.

Assessment of Selection Bias in the Canadian Case-Control Study of Residential Magnetic Field Exposure and Childhood Leukemia

The authors evaluated the role of selection bias in the 1999 Canadian case-control study of residential magnetic field exposure and childhood leukemia. They included cases, participating controls, and first-choice nonparticipating controls in their analyses. Exposure was assessed by wire coding, a classification system based on the distribution line characteristics near homes. Although an imperfect measure of magnetic field exposure, wire coding is the only method applicable to nonparticipating subjects. First-choice nonparticipant controls tended to be of lower socioeconomic status than their replacements (non-first-choice participant controls), and lower socioeconomic status was related to higher wire code categories. The odds ratios for developing childhood leukemia in the highest exposure category were 1.6 (95% confidence interval: 1.0, 2.6) when the actual participating controls were used and 1.3 (95% confidence interval: 0.8, 2.1) when the first-choice ideal controls were used, regardless of their participation. Overall, the authors conclude that, although there is some evidence for control selection or participation bias in the Canadian study, it is unlikely to explain entirely the observed association between magnetic field exposure and childhood leukemia. Inherent problems in exposure assessment for nonparticipating subjects, however, limit the interpretations of these results, and the role of selection bias cannot entirely be dismissed on the basis of these results alone.

Low-frequency transient electric and magnetic fields coupling to child body

Much of the research related to residential electric and magnetic field exposure focuses on cancer risk for children. But until now only little knowledge about coupling of external transient electric and magnetic fields with the child's body at low frequency transients existed. In this study, current densities, in the frequency range from 50 Hz up to 100 kHz, induced by external electric and magnetic fields to child and adult human body, were investigated, as in residential areas, electric and magnetic fields become denser in this frequency band. For the calculations of induced fields and current density, the ellipsoidal body models are used. Current density induced by the external magnetic field (1 microT) and external electric field (1 V/m) is estimated. The results of this study show that the transient electric and magnetic fields would induce higher current density in the child body than power frequency fields with similar field strength.

Assessment of non‐response bias in a survey of residential magnetic field exposure in Taiwan

We assessed potential non-response bias in obtaining information on residential extremely low-frequency power frequency magnetic field (MF) in Taiwan. All households occupied by children aged less than 7 years in two study districts, one in an urban town and the other in a rural town, were visited and solicited for on-site measurements in late 2003. The initial response rate was only 32% (33/104, urban) and 60% (61/101, rural). In the same season 1 year later, we performed a second survey of those who declined to be measured at the initial survey and successfully measured another 77 residences (50 and 27 for urban and rural districts, respectively). The two districts were selected mainly because the local public health officers were quite willing to assist the initial survey and to inform residents of the second survey. Except for meteorological conditions, the two surveys came up with very similar findings regarding residential characteristics and power facilities surrounding the houses. The mean residential MF for the urban residences was .121 and .140 micro-Tesla (microT) (P = .620) for the two surveys. The corresponding figures for the rural residences were .119 and .115 microT (P = .802). Although limited in its scope, this study tends to indicate that measurement studies of residential MF are less likely to suffer from serious selection bias if sampling is confined within a small district where people have similar socioeconomic characteristics.

Residential Magnetic Fields, Medication Use, and the Risk of Breast Cancer

Exposure to 60-Hz magnetic fields may increase breast cancer risk by suppressing the nocturnal production of melatonin. The use of medications associated with reduced melatonin levels could modify this relationship. We recontacted participants in a population-based case-control study of residential magnetic field exposure and breast cancer risk and interviewed them regarding medication use during the 10 years before diagnosis. Cases were diagnosed between November 1992 and March 1995, and magnetic field levels were measured in the home at diagnosis. We obtained medication use information by telephone interview from 558 cases and 588 controls. Breast cancer risk was not associated with exposure to residential magnetic fields, regardless of medication use. These results support previous findings that magnetic field exposure does not increase breast cancer risk.

Assessment of Potential Non-response Bias in a measurement Study of Residential Magnetic Field and Contact Voltage Exposures

Assessment of Potential Non-response Bias in a measurement Study of Residential Magnetic Field and Contact Voltage Exposures

Leukemia Attributable to Residential Magnetic Fields: Results from Analyses Allowing for Study Biases

Nearly every epidemiologic study of residential magnetic fields and childhood leukemia has exhibited a positive association. Nonetheless, because these studies suffer from various methodologic limitations and there is no known plausible mechanism of action, it remains uncertain as to how much, if any, of these associations are causal. Furthermore, because the observed associations are small and involve only the highest and most infrequent levels of exposure, it is believed that the public health impact of an effect would be small. We present some formal analyses of the impact of power-frequency residential magnetic-field exposure (as measured by attributable fractions), accounting for our uncertainties about study biases as well as uncertainties about exposure distribution. These analyses support the idea that the public health impact of residential fields is likely to be limited, but both no impact and a substantial impact remain possibilities in light of the available data.

Multiple-Bias Modelling for Analysis of Observational Data

SummaryConventional analytic results do not reflect any source of uncertainty other than random error, and as a result readers must rely on informal judgments regarding the effect of possible biases. When standard errors are small these judgments often fail to capture sources of uncertainty and their interactions adequately. Multiple-bias models provide alternatives that allow one systematically to integrate major sources of uncertainty, and thus to provide better input to research planning and policy analysis. Typically, the bias parameters in the model are not identified by the analysis data and so the results depend completely on priors for those parameters. A Bayesian analysis is then natural, but several alternatives based on sensitivity analysis have appeared in the risk assessment and epidemiologic literature. Under some circumstances these methods approximate a Bayesian analysis and can be modified to do so even better. These points are illustrated with a pooled analysis of case–control studies of residential magnetic field exposure and childhood leukaemia, which highlights the diminishing value of conventional studies conducted after the early 1990s. It is argued that multiple-bias modelling should become part of the core training of anyone who will be entrusted with the analysis of observational data, and should become standard procedure when random error is not the only important source of uncertainty (as in meta-analysis and pooled analysis).

Residential magnetic field exposure and breast cancer risk: a nested case-control study from a multiethnic cohort in Los Angeles County, California.

Some experimental and epidemiologic evidence suggests that residential exposure to power-frequency magnetic fields can increase breast cancer risk. This association was investigated in a nested case-control study of female breast cancer within a cohort of African Americans, Latinas, and Caucasians in Los Angeles County, California. Incident breast cancer was ascertained from 1993 to 1999 by linkage to county and state tumor registries. Controls were selected from a random sample of cohort members without breast cancer at baseline. Exposure was assessed in 1995-2001 by means of wiring configuration coding (an indirect measure of magnetic field exposure that has been associated with increased risk of childhood leukemia in Los Angeles and elsewhere in North America) in all homes occupied over the previous 10 years for 743 cases and 699 controls and by measurement of magnetic fields in the bedroom over a 7-day period for 347 cases and 286 controls. The estimated risk of breast cancer was not higher among women with wiring configuration codes associated with the highest magnetic fields (for a very high current configuration relative to very low, the adjusted odds ratio was 0.76 (95% confidence interval: 0.49, 1.18)). Stronger measured fields were not significantly associated with increased risk. These data suggest that residential magnetic field exposures commonly experienced by US women do not influence risk of breast cancer.

Use of short-term measurements for assessing temporal variability of residential ELF magnetic field exposure.

In this study, we introduced and tested a new approach to characterize residential magnetic field (MF) exposure. Short-term 20-min MF measurements were obtained by a person who carried out instantaneous spot measurements in residences. Compared to spot measurements, the 20-min measurement could potentially improve exposure assessment, because it contains information of temporal variations of MF, which have been suggested as biologically important characteristics of MF exposure. We have used this new exposure assessment method on a study of maternal MF exposure and reproductive outcomes. To validate the new method, the exposure of 30 subjects was measured with a more accurate "gold standard" method (24 h personal exposure measurements). The measures of validity used were the Spearman correlation coefficient (r), sensitivity, and specificity. We evaluated the validity of the 20-min measurements for estimating several different exposure metrics for the entire 24 h measurement period or for the hours spent at home: arithmetic mean, median, percentage of time above 0.15 microT, standard deviation, rate of change metric, standardized rate of change metric, constant field metric, and three metrics for the occurrence of high-peak exposures. The 20-min measurement was modestly associated with standard deviation and the rate of change metric, but gave very little information of other metrics of temporal variation. The 20-min measurement can also be used for assessing exposure metrics such as arithmetic mean and median, but it does not seem to offer any advantages compared to traditional 'spot' measurements. The 20-min measurement was not useful for assessing occurrence of high-peak exposures. We conclude that the 20-min measurement is useful for estimating some aspects of MF temporal variability.

Interpreting Epidemiologic Research: Lessons From Studies of Childhood Cancer

In recent years, the public has shown concern about trends in incidence rates, the occurrence of clusters, and the role of certain environmental exposures in the cause of childhood cancers. A front-page news story in the New York Times 1 stimulated a dramatic upswing of public anxiety about these issues. Hearings by the US Senate Environment and Public Works Committee on a cluster of 11 childhood acute lymphoblastic leukemia (ALL) cases (since increased to 13) among the 8200 residents of a town in Nevada over a 3-year period led to a featured article in USA Today 2 describing legislation under consideration to enhance the federal government’s role in responding to apparent cancer outbreaks in US communities. Compared with 1.22 million cancers (excluding non-melanoma skin cancers) diagnosed annually among adults in the United States (corresponding to an average annual incidence rate for all cancers of 398 per 100 000 person-years),3 there are only ∼8700 diagnosed per year among children younger than 15 years and 12 400 among children and adolescents younger than 20 years (corresponding to average annual incidence rates of 13.4 per 100 000 and 14.9 per 100 000 person-years, respectively).4 Carcinomas predominate among adults, and the major pediatric tumors are nonepithelial. The most common pediatric neoplasms are the leukemias (representing 30.2% of all cancers diagnosed in children younger than 15 years), brain and central nervous system cancers (21.7%), and lymphomas (10.9%); these 3 categories (together constituting 63%) and the remaining 37% of pediatric malignancies are characterized by substantial histologic and biological diversity.5–7 Instead of the anatomic site-based categories used for adult malignancies, a more appropriate classification system developed for pediatric neoplasms8 was recently updated and designated as the International Classification of Childhood Cancer.9 This article includes 3 components. The first section focuses …

Use of spot measurements for assessing residential ELF magnetic field exposure: A validity study

The purpose of this study was to evaluate residential short term "spot" measurements as surrogates for long term personal magnetic field (MF) exposure. In an epidemiological study on birth weight and pregnancy delay, MF exposure was assessed by taking five spot measurements in each room. For a subsample of 30 subjects 24 h personal MF measurements were made, and the following exposure metrics were calculated: 24 h arithmetic mean, 24 h median, percentage of time above 0.15 microT, and percentage of time above 0.29 microT. The 24 h exposure metrics were used as gold standards, when evaluating the validity of various summary measures calculated from spot measurements for assessing personal exposure. Based on Spearman correlation coefficient (r), specificity and sensitivity, the average of the spot measurements of a residence resulted in least exposure measurement error (misclassification). Also the above bed spot value correlated better with the 24 h metrics than any room average. Spot measurements performed about equally well in predicting different types of exposure metrics.

Measuring temporal variability in residential magnetic field exposures

Considerable interest has developed during the past ten years regarding the hypothesis that living organisms may respond to temporal variability in ELF magnetic fields to which they are exposed. Consequently, methods to measure various aspects of temporal variability are of interest. In this paper, five measures of temporal variability were examined: Arithmetic means (Dmean) and rms values (Drms) of the first differences (i.e., absolute value of the difference between consecutive measurements) of magnetic field recordings; “standardized” forms of Drms, denoted RCMS, obtained by dividing Drms by the standard deviations of the magnetic field data; and mean (Fmean) and rms (Frms) values of fractional first differences. Theoretical investigations showed that Dmean and Drms are virtually unaffected by long-term systematic trends (changes) in exposure. These measures thus provide rather specific measures of short-term temporal variability. This was also true to a lesser extent for Fmean and Frms. In contrast, the RCMS metric was affected by both short-term and long-term exposure variabilities. The metrics were also investigated using a data set consisting of twice-repeated two-calendar-day recordings of bedroom magnetic fields and personal exposures of 203 women residing in the western portion of Washington State. The predominant source of short-term temporal variability in magnetic field exposures arose from the movement of subjects through spatially varying magnetic fields. Spearman correlations between TWA bedroom magnetic fields or TWA personal exposures and five measures of temporal variability were relatively low. Weak to moderate levels of correlation were observed between temporal variability measured during two different sessions separated in time by 3 or 6 months. We conclude that first difference and fractional difference metrics provide specific and fairly independent measures of short-term temporal variability. The RCMS metric does not provide an easily interpreted measure of short-term or long-term temporal variability. This last result raises uncertainties about the interpretation of published studies that use the RCMS metric. Bioelectromagnetics 22:232–245, 2001. © 2001 Wiley-Liss, Inc.

Measuring temporal variability in residential magnetic field exposures

Considerable interest has developed during the past ten years regarding the hypothesis that living organisms may respond to temporal variability in ELF magnetic fields to which they are exposed. Consequently, methods to measure various aspects of temporal variability are of interest. In this paper, five measures of temporal variability were examined: Arithmetic means (D(mean)) and rms values (D(rms)) of the first differences (i.e., absolute value of the difference between consecutive measurements) of magnetic field recordings; "standardized" forms of D(rms), denoted RCMS, obtained by dividing D(rms) by the standard deviations of the magnetic field data; and mean (F(mean)) and rms (F(rms)) values of fractional first differences. Theoretical investigations showed that D(mean) and D(rms) are virtually unaffected by long-term systematic trends (changes) in exposure. These measures thus provide rather specific measures of short-term temporal variability. This was also true to a lesser extent for F(mean) and F(rms). In contrast, the RCMS metric was affected by both short-term and long-term exposure variabilities. The metrics were also investigated using a data set consisting of twice-repeated two-calendar-day recordings of bedroom magnetic fields and personal exposures of 203 women residing in the western portion of Washington State. The predominant source of short-term temporal variability in magnetic field exposures arose from the movement of subjects through spatially varying magnetic fields. Spearman correlations between TWA bedroom magnetic fields or TWA personal exposures and five measures of temporal variability were relatively low. Weak to moderate levels of correlation were observed between temporal variability measured during two different sessions separated in time by 3 or 6 months. We conclude that first difference and fractional difference metrics provide specific and fairly independent measures of short-term temporal variability. The RCMS metric does not provide an easily interpreted measure of short-term or long-term temporal variability. This last result raises uncertainties about the interpretation of published studies that use the RCMS metric.

Panel exploring pro and con arguments as to whether EMFs cause childhood brain cancer.

Two groups of epidemiologists were assigned to develop pro and con arguments with regard to a causal explanation for statistical associations sometimes seen between surrogates for occupational and residential electric and magnetic field exposure and brain cancer. The arguments developed were meant to help the Department of Health Services when it prepared its final risk evaluation by a respectful and illuminating review of the possible reasons for concluding either that magnetic fields were or were not likely to be a cause of brain cancer.

A pooled analysis of magnetic fields and childhood leukaemia.

Previous studies have suggested an association between exposure to 50–60 Hz magnetic fields (EMF) and childhood leukaemia. We conducted a pooled analysis based on individual records from nine studies, including the most recent ones. Studies with 24/48-hour magnetic field measurements or calculated magnetic fields were included. We specified which data analyses we planned to do and how to do them before we commenced the work. The use of individual records allowed us to use the same exposure definitions, and the large numbers of subjects enabled more precise estimation of risks at high exposure levels. For the 3203 children with leukaemia and 10 338 control children with estimated residential magnetic field exposures levels < 0.4 μT, we observed risk estimates near the no effect level, while for the 44 children with leukaemia and 62 control children with estimated residential magnetic field exposures ≥ 0.4 μT the estimated summary relative risk was 2.00 (1.27–3.13), P value = 0.002). Adjustment for potential confounding variables did not appreciably change the results. For North American subjects whose residences were in the highest wire code category, the estimated summary relative risk was 1.24 (0.82–1.87). Thus, we found no evidence in the combined data for the existence of the so-called wire-code paradox. In summary, the 99.2% of children residing in homes with exposure levels < 0.4 μT had estimates compatible with no increased risk, while the 0.8% of children with exposures ≥ 0.4 μT had a relative risk estimate of approximately 2, which is unlikely to be due to random variability. The explanation for the elevated risk is unknown, but selection bias may have accounted for some of the increase. © 2000 Cancer Research Campaign

Residential magnetic fields predicted from wiring configurations: II. Relationships to childhood leukemia

Case-control data on childhood leukemia in Los Angeles County were reanalyzed with residential magnetic fields predicted from the wiring configurations of nearby transmission and distribution lines. As described in a companion paper, the 24-h means of the magnetic field's magnitude in subjects' homes were predicted by a physically based regression model that had been fitted to 24-h measurements and wiring data. In addition, magnetic field exposures were adjusted for the most likely form of exposure assessment errors: classic errors for the 24-h measurements and Berkson errors for the predictions from wire configurations. Although the measured fields had no association with childhood leukemia (P for trend=.88), the risks were significant for predicted magnetic fields above 1.25 mG (odds ratio=2.00, 95% confidence interval=1.03-3.89), and a significant dose-response was seen (P for trend=.02). When exposures were determined by a combination of predictions and measurements that corrects for errors, the odds ratio (odd ratio=2.19, 95% confidence interval=1.12-4.31) and the trend (p =.007) showed somewhat greater significance. These findings support the hypothesis that magnetic fields from electrical lines are causally related to childhood leukemia but that this association has been inconsistent among epidemiologic studies due to different types of exposure assessment error. In these data, the leukemia risks from a child's residential magnetic field exposure appears to be better assessed by wire configurations than by 24-h area measurements. However, the predicted fields only partially account for the effect of the Wertheimer-Leeper wire code in a multivariate analysis and do not completely explain why these wire codes have been so often associated with childhood leukemia. The most plausible explanation for our findings is that the causal factor is another magnetic field exposure metric correlated to both wire code and the field's time-averaged magnitude.