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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields 5 Epidemiology SUMMARY AND CONCLUSIONS The potential association between childhood leukemia and the presence of power lines reported in epidemiologic studies has raised public concern, particularly among parents. In this chapter, over 15 years of epidemiologic research is reviewed, and the key methods used in epidemiology that affect the interpretation of research are considered. Based on an analysis of the epidemiologic literature, the committee makes the following general conclusions: Wire codes1 are associated with an approximate 1.5-fold excess of childhood leukemia, which is statistically significant. Although the literature is not entirely consistent, the combined results from the array of studies that have examined wire codes and related markers of exposure, such as proximity to power lines and calculated magnetic fields from power lines, indicate that an association is present. Biased selection of controls and confounders might have influenced some of the studies, but they are unlikely to account for the overall pattern of association that is identified. Average magnetic fields measured in the homes of children have not been found to be associated with an excess of childhood leukemia or other cancers. 1 Used in the context of epidemiology, a wire code is a carefully documented aid to the epidemiologist to classify homes by their presumed correlation with magnetic fields; this use of the term is not similar to that in standard home construction. A detailed description of the term, as used in epidemiology, is given in Appendix B of this report.
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields Studies that have examined average magnetic fields measured in homes after a diagnosis has been made have all been severely limited by missing data, and no firm conclusions can be drawn from them. The data that have been generated do not support an association between childhood leukemia and magnetic fields, in contrast to the data generated from wire codes. The factors that explain the association between wire codes and childhood leukemia have not been identified. The original and continued interest in wire codes is their presumed correlation with long-term average magnetic fields in homes. However, epidemiologic studies have generated little evidence that average magnetic fields account for the observed association between wire codes and childhood leukemia. Wire codes are not strong predictors of magnetic-field strengths in homes, although they do distinguish very high fields from outdoor wiring from lesser fields reasonably well. Other explanatory factors, such as neighborhood characteristics, other measurements of exposure to electric and magnetic fields, or air pollution, have received even less support, leaving open the question of what accounts for the observed association. Epidemiologic evidence of an association between magnetic fields and childhood cancers (other than leukemia), adult cancers, pregnancy outcome, and neurobehavioral disorders is not, in the aggregate, supported. A number of studies examined health outcomes other than childhood leukemia, and some of them reported positive associations. However, the number of well-designed studies supportive of such an association is not sufficient to conclude that any of the associations are actually present. INTERPRETATION OF EPIDEMIOLOGIC EVIDENCE Epidemiology can be defined as the study of patterns of health and disease in human populations to understand causes and identify methods of prevention. Interpretation of epidemiologic evidence regarding potential causal relations between exposures and health outcomes is a complex process and relies on a wide range of supporting data. No simple checklist can be used to make judgments about the quality of research and the certainty of the results, although a number of considerations might bear favorably or unfavorably on a causal interpretation. As a prelude to the review of epidemiologic studies addressing possible health effects of electric and magnetic fields, some of the key methods used to interpret epidemiologic data are reviewed. For more thorough consideration of these and related principles, see work by Rothman (1986) and Kelsey et al. (1986). Compared with laboratory approaches to the study of health and disease (e.g., toxicology), observational epidemiology has a number of strengths and weaknesses. The principal deficiency of an observational approach is the inability to assign exposure randomly. This inability introduces the possibility of confounding the effect of the exposure of interest by other disease determinants. Because exposures
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields are observed rather than controlled by the investigator, accurate determination of the exposure is more challenging in observational epidemiologic studies than in experimental studies. However, epidemiology has an advantage in addressing the species of ultimate interest, humans, in their natural environment. In addition, environmental exposure conditions that are difficult to duplicate precisely in the laboratory can be studied directly, at least in general terms, through epidemiology. Epidemiology can include studies of exposures that only produce health effects many years later. The complex array of disease cofactors, genetic heterogeneity, and diversity in human populations is virtually impossible to simulate in the laboratory, yet it is an inherent part of epidemiologic inquiry. Given the strengths and weaknesses of epidemiology relative to other approaches, consistent information from various approaches is desirable to enhance confidence that inferences are valid. The notion of assigning causality from an observed association is, in a philosophical sense, complex, and the application of epidemiologic data to determination of causality is particularly problematic. Without randomly assigning the potential causes of interest (e.g., magnetic-field exposure) and observing the resulting health event (e.g., a change in cancer incidence), a mistaken inference that a given exposure causes a specific disease can result from a number of potential errors or misinterpretations. Conversely, even when a true causal relationship is present, it will not always be discerned easily. Ultimately, causal inference is enhanced when a number of noncausal explanations have been carefully postulated, tested, and refuted (U.S. Surgeon-General 1964). No universally accepted threshold exists for determining when the process of establishing causality has ended, as indicated by the few remaining skeptics who assert that the causal effect of tobacco smoking on lung cancer is unproved. In fact, rather than asking the broad unanswerable question "When has a causal inference been established?", a somewhat more practical question can be asked: "When is evidence of a causal association sufficient to take a specific action that presumes such a causal relationship?" In this chapter, published epidemiologic data are reviewed that bear upon the potential association between exposure to low-frequency 60-Hz residential magnetic fields and disease, the potential sources of random and systematic errors common to epidemiologic studies are explored, the possible confounding factors and their potential effects on the findings of the studies are examined, and the effect of these various factors on the conclusions derived from the epidemiologic work is evaluated. The consistency of the results are explored using methods of data pooling, and the criteria for causality will be discussed as they apply to the problem at hand. Potential Sources of Error in Epidemiologic Studies Random Error Random error is perhaps the most easily addressed source of error in scientific studies: results of a given study are subject to variability due solely to random
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields (i.e., statistical) processes, in addition to other sources of error (i.e., bias). An observed risk of 1.0 or 2.0 relating high wire codes to childhood leukemia might be indicative of a ''true" risk in the neighborhood of 1.0 or 2.0, in the absence of other sources of error attributable to random processes. The impact of random processes decreases as the number of study subjects increases, resulting in narrower confidence intervals for larger studies. Tests of statistical significance address the probability that, conditional on the observed data, the "true" relative risk2 is inconsistent with the relative risks under the null hypothesis. Note that even if the null hypothesis is rejected, the statistical test relates to the association between the variables being tested (i.e., high wire code and leukemia) and not causality. In the light of statistically significant findings, causality in observational epidemiology studies can be inferred only on the basis of design and weight of evidence criteria (see discussion of Hill's criteria below). Many criticize epidemiology as a nonfalsifiable discipline. Although it is true that epidemiologists cannot prove the absence of an effect, they can identify the smallest detectable effect for a given study, and if this smallest detectable effect is sufficiently small, it is tantamount to the absence of an effect. For example, in a study of high wire codes and leukemia in which an odds ratio of 1.01 is obtained, a possible association might not be ruled out, but with appropriate data, the true relative risk could be stated with a certain probability to lie between 0.95 and 1.05. Thus, one can show that if the effect existed, it would be remarkably small and of little significance to the individual or to the public health. In regard to observational epidemiology, it should be remembered that the formal methods of statistical significance testing and construction of confidence intervals attempt to address one and only one question: How likely is it that a valid method of randomly assigning exposures to individuals led to results as extreme or more extreme than those that were obtained, assuming that the null hypothesis is correct? Because random assignment is not a feature of epidemiologic studies, interpretation of statistical significance and confidence-interval boundaries have less of a theoretic foundation (Greenland 1994), and therefore less meaning, than they have in results of randomized experiments. In addition, the relative importance of nonrandom error (bias) is generally much greater than random error as a potential source of erroneous results. Therefore, judgments of evidence and causality take into account all available evidence, the level of statistical significance being only one of many considerations. Information Bias: Misclassification of Disease or Exposure In assigning exposure and disease status to individuals in epidemiologic studies, error, referred to as information bias or misclassification, can arise. Such error has an effect on the measures of association produced by an epidemiologic 2 The relative risk is defined as the ratio of risk in the exposed population to that in the unexposed.
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields study. Diseases like leukemia are subject to relatively little misclassification because false negatives are unlikely given the severity of the disease (although misclassification might depend on the stage of the disease at diagnosis), and false positives are unlikely given the medical scrutiny of suspected cases. For prostate cancer, however, false negatives (failure to diagnose disease that is present) are common, as are false positives (misdiagnosing disease when it is not present), and for health events like miscarriage, false positives (e.g., a late menstrual period that is misinterpreted as an early pregnancy loss), and false negatives (e.g., an early pregnancy loss not recognized by the woman) are also quite common. Exposure misclassification is a pervasive concern in epidemiologic studies on the effects of exposure to electric and magnetic fields. Errors can occur on several levels. In a study of occupational exposures and leukemia, simple errors might occur in assigning the job title. For example, an error in the assignment of "electrical worker" might occur because of erroneous job-title information provided by the coroner or funeral director who fills out a death certificate. When the investigator interprets electrical-worker job titles as "exposed worker" and nonelectrical-worker job titles as "unexposed worker" when examining possible health effects of exposures to electric and magnetic fields, additional error is introduced. If the true historical exposures were known, some of the workers labeled "exposed" based on their job title would not be exposed (e.g., the electrical engineer who almost never works near electric equipment), and some of those labeled "unexposed'' would be exposed (e.g., the janitor who routinely uses equipment with electric motors, such as floor polishers or vacuum cleaners). Any resulting misclassification can produce distortion in the measured association between exposure and disease. If dichotomous exposure comparisons are made, such as for electrical workers versus nonelectrical workers, and if the amount of error in exposure assignment is unrelated to the disease of interest (or vice versa), the direction of the error is predictable: a bias will be evident toward the null value, or an underestimation of any association (Rothman 1986). When exposure is classified into three or more categories, that general principle cannot be assumed to apply, particularly when there is misclassification into nonadjacent categories (Dosemeci et al. 1990). If the errors in exposure assignment described above applied equally to workers who died of leukemia as to workers who died of other causes, the tendency would be to produce measures of association that are closer to the null value (relative risks closer to 1.0) compared with the "true" relative risk. Likewise, because job title is an inherently imperfect marker of exposure and as likely to be similarly imperfect for workers who get leukemia as for other workers, then a bias will be toward the null value when making inferences from job title as a marker of exposure. If, in coding death certificates for leukemia, errors of a similar type and magnitude occur for electrical workers as for nonelectrical workers, the bias will be toward finding no association. When the error is differential (i.e., the quality of exposure assignment differs
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields for diseased and nondiseased persons, or disease assignment differs for exposed and unexposed persons), the error in the association can go in either direction. The direction and magnitude of error in the association depends on the degree of misclassification of exposure or disease. For example, if funeral directors have heard of the hypothesis linking magnetic-field exposure to leukemia, and they preferentially assign the job of "electrician" to persons who died of leukemia, the bias would be toward a spuriously large association. Selection Bias Another potential source of error arises from the constitution of the groups to be compared: those composed of exposed and unexposed subjects in a cohort study or cases and controls in a case-control study. In a cohort study, the primary concern is retaining subjects under observation throughout the study period, because the pattern of losses potentially distorts the comparison of disease rates among exposed versus unexposed subjects. If disease-prone persons were preferentially lost from the exposed group, its disease rate would be biased downward and the relative risk would also be biased downward. Concern with selection bias is much greater in case-control studies, specifically in regard to control selection. In a case-control study, the goal of control selection is to sample from the study base or the population experience that produced the cases (Rothman 1986). If sampling is done successfully, the results will be identical, on average, to those obtained in a cohort study of the same population. In studies of residential magnetic-field exposure and childhood cancer, cases have typically constituted a complete roster of all diagnosed children in a specified geographic area and time period. The goal of control selection in such studies is to identify an unbiased sample from the population in that area for the corresponding time period to provide a baseline of exposure prevalence (e.g., prevalence of high-wire-code homes). Any process of control selection that does not yield an accurate indication of the prevalence of high-wire-code homes will yield a biased odds ratio. If high-wire-code homes are underrepresented among controls, then the odds ratio will be biased upward (away from 1.0), and if high-wire-code homes are overrepresented, then the odds ratio will be biased downward. Evaluation of control selection addresses such issues as whether all persons eligible to be cases (i.e., people who, if they became ill, would have been cases) were included in the sampling frame and whether refusal to participate among eligible controls might have altered the prevalence of exposure as compared with controls who were included in the sample. Confounding and Effect Modification Confounding, a mixing of effects between the exposure of interest and extraneous risk factors, is not a product of the design or conduct of the study,
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields but results from a natural association among risk factors. For example, assume that children who use electric blankets are more likely to be ill and, because of that pattern of illness, receive medical X-rays more often than children who do not use electric blankets. If medical X-ray exposures caused an increased risk of childhood leukemia and the exposures were not accounted for in the analysis, electric-blanket use would be falsely implicated as being responsible for an increase in risk that actually would be due to X-ray exposure. The control of confounding is, in principle, easily achieved through statistical methods. For example, measuring X-ray use directly would allow assessment of the association between electric blankets and leukemia among those who did and did not receive X-rays. The results across those strata would be pooled. The potential confounder, X-ray use, could not affect the association of interest within those strata, and therefore the pooled or adjusted result is free of confounding. Obviously, such a solution requires awareness of the potential confounder, accurate assessment of it in the study, and control for it in the analysis. It should be noted that confounding can produce bias in either direction, spuriously increasing or decreasing relative risk, depending on the direction of the association between the exposure, the disease, and the confounder. A different concept, sometimes confused with confounding, is effect modification in which the association between a given exposure and disease is affected by a third variable. For example, if magnetic fields acted as a late-stage carcinogen or promoter of childhood leukemia and parental tobacco smoking acted as an initiator, parental tobacco smoking can be hypothesized to act as an effect modifier of magnetic-field exposure. The relation between magnetic fields and leukemia would be stronger among those children whose parents smoked than among children whose parents did not smoke. In contrast to confounding, this phenomenon is not a source of distortion or bias, and thus not something to be controlled, but rather it is an observation of interest to be described. Although effect modification is reflective of biologic interdependence, it is commonly treated statistically when the association between two variables (exposure and disease) is determined for subgroups defined by a third variable (effect modifier) and is found to differ. Criteria for Causality in Epidemiologic Studies Criteria to assist in the evaluation of whether an association observed in an epidemiologic study is likely to reflect a causal rather than a noncausal association were delineated by Hill (1961) and have been used widely for that purpose, most notably in the U.S. Surgeon-General's report on smoking and health (1964). In his original presentation, Hill carefully stated that his criteria were only general considerations and not, individually or collectively, a checklist or scoring system. As noted above, judgments of causality are not strictly a scientific process but are a subjective interpretation of the accumulation of evidence. At some point, a consensus is reached that sufficient evidence has been accumulated to make
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields some corrective action preferable to no action, indicating an implicit acceptance of a causal association. Nonetheless, the criteria presented by Hill provide useful reminders of issues that are worthy of consideration. Most of the criteria relate to an assessment of the degree to which the data are free from bias of the types described above, as noted by Rothman (1986). Starting with a reported association between exposure and disease, Hill (1961) suggested several criteria to consider in addressing causality. These criteria are discussed below along with caveats regarding their interpretation: Strength of association: If a given exposure and disease are strongly associated (i.e., a large relative risk), then unrecognized confounders are less likely to be responsible for the association. For large relative risks, confounders are presumed to be apparent and already identified as important risk factors. This criterion will not be met if a true cause exists that actually has a very small effect. For example, true causes that only affect persons who are more susceptible because of relatively rare genetic or environmental cofactors would appear as weak associations in an epidemiologic study of a general population. Consistency: If the association is observed in different populations under different circumstances, it is more likely to be a causal relationship and not a product of some methodologic artifact in the study. However, the same error can be made consistently in studies to produce consistent but erroneous results, associations can truly be present under some circumstances but not under others, or inconsistent results can reflect a combination of good and bad studies yielding a mixture of valid and invalid results. Specificity: A cause should lead to a single effect rather than multiple effects; if multiple diseases are associated with a suspected agent, the associations are more likely to be spurious. Hill acknowledges that this criterion is particularly questionable, and an example of an exposure causing only one disease probably does not exist; examples of exposures with multiple effects are tobacco smoke, ionizing radiation, and asbestos fibers. Temporality: The exposure must logically precede the disease in time if the association is causal. This criterion is the only one that must be met. In some instances, the possibility of biologic markers being the consequence rather than the cause of the disease should be considered. For example, biologic markers of exposure, such as serum pesticide concentrations, might be disturbed by the occurrence of the disease itself, thus distorting comparisons of cases and controls. Biologic gradient: A dose-response gradient, in which risk of disease rises with increasing exposure level, is generally more likely to indicate causality than some other pattern of association between exposure and disease. Such an assessment, however, assumes the measurement of a relevant dose indicator. Weiss (1981) discussed in some detail why the presence of such a gradient is supportive of a causal inference, whereas the absence of such a gradient is not sufficient reason for ruling out a causal association. Confounding factors can
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields also follow a dose-response gradient, or the underlying biologic processes might have a threshold or a maximum in their response that obscures the observation of a gradient in risk. Also, the range of exposure under study might be insufficiently broad to cause a dose-response gradient. Plausibility: Plausibility refers to whether the association is supported by scientific studies or information from disciplines other than epidemiology. The assessment of plausibility is a function of current scientific knowledge, which changes as natural processes are more fully understood. Lack of scientific evidence from other disciplines or conflicting information from other disciplines of course does not confirm that the epidemiologic studies are in error; the nonepidemiologic research, in itself, might be absent or flawed. Nonetheless, the interpretations of the data obtained in epidemiologic studies should be based in part on the agreement or disagreement of findings from other disciplines. Coherence: A causal interpretation should not be in conflict with current knowledge about the natural history of the disease. This criterion is virtually the same as plausibility, and the same caveats apply. Experimental evidence: When possible, experimental evidence in the form of randomized trials with prescribed exposures is highly desirable; however, practical considerations can preclude this approach. For example, hazardous exposures that might result in serious adverse health outcomes cannot ethically be tested in this way, although sometimes the removal of an exposure can be randomized to assess possible benefits. Analogy: If other known and accepted causal agents have been found that are similar to the one under evaluation in their manner of action on the biologic system, then the one under evaluation is more likely to be causal. The ability to identify relevant analogies also depends on the imagination of the investigator, but a documented analogy between a known and a hypothesized causal association is useful in drawing a conclusion of causality. There are several arguments that should be considered when placing reliance on such criteria. First, these criteria do not provide a substitute for the careful and independent scrutiny of specific studies and their methods, but unfortunately they might provide a seductive shortcut that can make it tempting to do so. For example, absence of a dose-response gradient can reflect a poorly measured dose, saturation of the dose-response curve, or absence of any causal process. Merely to report that no dose-response relation was found as a means of dismissing an association requires much less effort than trying to distinguish among the possible reasons for the absence of a dose-response gradient and adds little to an understanding of the literature or the underlying phenomenon of interest. In spite of carefully stated caveats (Hill 1961; U.S. Surgeon-General 1964), such lists suggesting criteria for causality encourage a checklist approach to interpreting evidence. Second, most of the criteria indirectly address questions of confounding and
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields bias. It seems preferable to tackle those questions directly by asking whether a given association suffers from distortion due to the study biases. Third, epidemiologic results should be first evaluated on terms inherent within the discipline, referring to qualities of study design, execution, and analysis. After that, insights and knowledge derived from other scientific disciplines relevant to the association in question can most effectively contribute to judgments about causality. CANCER EPIDEMIOLOGY-RESIDENTIAL EXPOSURES Summary of Evidence The studies that have provided empirical evidence relating residential magnetic-field exposure to cancer are summarized in a series of tables in Appendix A (Tables A5-1, A5-2, and A5-3) that address the study methods. Later in this chapter the methodologic issues are critically evaluated, but this section is intended to provide a summary of the study structure (Table A5-1), of the methods used in control selection in case-control studies (Table A5-2), and of the approaches to exposure assessment (Table A5-3). Although the results are divided into studies of childhood and adult cancers, the summaries of the methods used include both types of studies because the study designs are similar. At the time these tables were constructed, 12 studies provided relevant data on childhood leukemia and five provided data on adult cancers. Eleven were conducted in the United States or western Europe, and the majority were published between 1986 and 1993 (Table A5-1). All but two of the reports concerned case-control studies, most of which were based on a comprehensive case ascertainment in a geographically defined population. Exposure assessment was based on some form of coding derived from the physical characteristics and distances of nearby power lines and other electric constructions, with varying sophistication in the classification methods, and a number of studies included measurements of magnetic-field strengths in homes (Table A5-3). Results of the epidemiologic studies are organized into tables that focus on childhood leukemia (Table A5-4), childhood brain tumors (Table A5-5), childhood lymphoma (Table A5-6), other childhood cancers (Table A5-7), childhood cancer in the aggregate (Table A5-8), cohort studies of residential exposure and cancer including all ages (Table A5-9), adult leukemia (Table A5-10), and adult cancers generally (Table A5-11). In each table, the numbers of cases and controls in each group are provided along with the crude and adjusted odds ratios (or other measures of relative risk) with 95% confidence intervals, and the confounders that were considered are noted. The goal in presenting the tables was to provide sufficient information to help readers understand the rationale behind the committee's interpretation and to allow readers to draw their own conclusions. A decision was made early in the committee's deliberations that the body
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields of studies concerning residential exposure to magnetic fields and occurrence of cancer, particularly childhood leukemia, deserve especially detailed scrutiny. Other exposure sources (e.g., appliances or occupation) and other health outcomes (e.g., reproductive or neurobehavioral efforts) are also considered, but not with the same amount of detail. Residential exposures related to power lines and occurrence of childhood cancer have been and continue to be the principal public concern that drives the broader concern for extremely-low-frequency (ELF) electric-and magnetic-field exposure. As the committee recognized early in its review, an association between proximity to certain types of power lines and childhood leukemia has been replicated with increasingly sophisticated study designs and warrants close examination on that basis alone. Finally, the charge to the committee from the U.S. Department of Energy is, "The committee will concentrate on the electric-and magnetic-field frequencies and exposure modalities found in residential settings." Although the exposures found in residential settings share some features with those in occupational environments and those related to electric appliances, warranting some discussion of nonresidential studies, the most relevant literature is that from exposure in residential settings as outlined in the committee's charge. Framework for the Interpretation of Evidence Linking Magnetic Fields to Childhood Cancer In this section, the framework is established for evaluating each of the key linkages pertaining to an association between living in proximity to certain types of electric power lines and childhood cancer; Figure 5-1 is a diagram of the relationships to be discussed; the arrows indicate associations, not causality. If an association between some characteristic of the power lines (as captured by the "wire codes" defined for use in epidemiologic studies) and cancer exists, several factors might be responsible. The association might be explained by magnetic fields produced by power lines, as a number of authors have suggested (Wertheimer and Leeper 1979; Savitz et al. 1988); that factor is designated FIGURE 5-1 Conceptual framework for evaluation of evidence on wire codes, magnetic fields, and childhood cancer.
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields a greater potential for increased exposure to electric and magnetic fields, some electrical workers might encounter hazardous chemicals, such as solvents, in their jobs and might be prone to higher rates of leukemia or brain cancer for reasons other than workplace exposures. The obvious test of the hypothesis that exposures to electric and magnetic fields account for the reported increases in risk is to refine the measurement of these fields and assess whether the associations become more pronounced. Over the past several years, a series of publications have examined more refined measurements of exposures to electric and magnetic fields in relation to cancer. Matanoski et al. (1993) studied leukemia other than chronic lymphocytic leukemia among telephone workers in relation to magnetic-field exposures estimated through job titles and a series of measurements. They found little support for increased risk due to increased average fields, but increasing field levels at peak exposure were associated with increased leukemia risk. Floderus et al. (1993) conducted a community-based study of leukemia and brain cancer in Sweden. They evaluated exposure by taking workplace measurements in the employment locations of cases and controls to classify exposure more accurately. On the basis of a quantitative index of magnetic-field exposure, the most highly exposed workers were estimated to have a 3-fold increased risk of chronic lymphocytic leukemia and a 1.6-fold increased risk of total leukemia. Brain-tumor risk was increased by a factor of 1.5 in the highest category. Three studies of electric-utility workers have yielded inconsistent results. A study at Southern California Edison (Sahl et al. 1993) yielded no associations between exposure and leukemia, lymphoma, or brain cancer; all relative risks were less than 1.4. In contrast, a large, well-designed study of utility workers in Canada and France provided evidence for a 2- to 3-fold increased risk of acute myeloid leukemia among men with increased magnetic-field exposure (Theriault et al. 1994). Brain cancer showed much more modest increases (relative risks of 1.5-2.8) with increased magnetic-field exposure. The most recent study (Savitz and Loomis 1995) examined cancer mortality in a large cohort of U.S. electrical workers. Leukemia mortality was not found to be associated with indices of magnetic-field exposure, whereas brain-cancer mortality was associated. Brain-cancer mortality generally was found to increase in relation to accumulative exposure, reaching a relative risk of 2.3-2.5 in the most highly exposed workers. All three studies found no evidence of confounding by the presence of workplace chemicals. A smaller study of Norwegian hydroelectric-power-company workers did not find increased risk associated with estimated magnetic-field exposure, but did report an increased rate of melanoma (Tynes et al. 1994a). Recently, two studies examined cancer among electric-railways workers in Sweden (Floderus et al. 1994) and Norway (Tynes et al. 1994b). Select groups of workers in this industry are believed to have chronic exposure to fields at 16.66 Hz. Tynes et al. (1994b) found no indication of increased leukemia or brain-cancer incidence for any historical period, whereas Floderus et al. (1994)
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields found men who were employed in exposed occupations during the 1960s (but not the 1970s) to have increased leukemia. They suggested that exposure was decreased due to changing work practices in the later time period. Methodologically, these more recent studies are clear improvements on the earlier studies that relied on job titles alone. The investigators developed rather elaborate approaches for classifying exposures more accurately and taking potential confounders into account. In spite of those refinements, the patterns of association have not become more consistent and pronounced, nor have they gone away. The relative risks in the upper categories of 2-3 reported in the high-quality studies of Floderus et al. (1993) and Theriault et al. (1994) cannot be ignored. However, the inconsistency in which cancer types show increased risks, the presence of contradictory studies (e.g., Sahl et al. 1993), and the irregular dose-response gradients make the interpretation problematic. Overall, the most recent studies have increased rather than diminished the likelihood of an association between occupational exposure to electric and magnetic fields and cancer, but they have failed to establish an association with a high degree of certainty. Another avenue of research to be noted is the concern with occupational exposure to electric and magnetic fields and breast cancer. A series of three studies reported an association between electrical occupations and male breast cancer (Tynes and Andersen 1990; Matanoski et al. 1991; Demers et al. 1991), which were similar in character to the initial studies of leukemia and brain cancer. More recently, a report of no association was published (Rosenbaum et al. 1994). Female breast cancer in relation to electrical occupations was evaluated by Loomis et al. (1994) among a large number of decedents in the United States. A modest increase in risk was found for women in electrical occupations, particularly telephone workers, encouraging further evaluation of a potential link between exposure and this common cancer. REPRODUCTION AND DEVELOPMENT Epidemiologic studies of potential adverse reproductive effects of exposure to electric and magnetic fields are limited in quantity and, to some extent, in quality. There are a multiplicity of exposure sources of potential interest (including residential exposures from power lines, occupational exposures from video-display terminals (VDTs), and other exposures from electric appliances, such as electric blankets) as well as a diversity of reproductive health end points (including infertility, miscarriage, congenital defects, growth retardation, and preterm delivery). Most of those areas have been addressed in fewer than three studies, the exception being VDTs in relation to spontaneous abortions. Although grouping data for exposures from all types of sources with the relevant outcomes is tempting for review purposes, comparing studies of similar types of exposures and outcomes without the assumptions required for aggregation is more constructive. The absence of efforts to replicate these studies is the predominant source
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields of uncertainty in this literature. Some excellent reviews of the topic are available (Hatch 1992; Shaw and Croen 1993; Delpizzo 1994). Video-Display Terminals The epidemiologic literature on VDTs was most recently covered in a review by Delpizzo (1994). In the VDT literature, which is large and of reasonably high quality, the evidence is clear that VDT use per se is not associated with increased risk of adverse reproductive outcomes, such as spontaneous abortion, congenital defects, or intrauterine growth retardation. However, the use of VDTs is not synonymous with exposure to extremely-low-frequency electric and magnetic fields. In fact, VDT use is a complex mixture of some increase in exposure primarily to very-low-frequency fields (3-30 kHz), potential psychological stress associated with repetitive tasks, physical inactivity associated with a sedentary job, and a modest increase in exposure to extremely-low-frequency fields (30-300 Hz). Depending on the particular machine, the location of the operator relative to the VDT in use, and the number and location of VDTs surrounding the operator, field exposures are typically in the range of 0.1 to 0.3 µT (Delpizzo 1993). Thus, the sizable literature on VDTs and reproductive outcomes has little value in addressing questions concerning prolonged exposure to increased power-frequency electric and magnetic fields. Only one study (Lindbohm et al. 1992) carefully related the VDT use to electric-and magnetic-field exposure (described below in Workplaces). Residences In contrast to the large number of cancer studies, only two published studies to date address a possible link between residential sources of exposure to electric and magnetic fields and adverse reproductive outcomes. Juutilainen et al. (1993) evaluated the residential magnetic-field exposures of 89 women who had suffered early pregnancy loss (as diagnosed by assays of human chorionic gonadotropin in urine) compared with the exposures of 102 women who had not. Magnetic fields were measured at several locations in the home to classify subjects. After adjustment for cigarette smoking, risk of early pregnancy loss was increased among women who resided in residences with measured fields above around 0.25 µT, particularly above 0.63 µT. On the basis of 6-8 cases of exposure in the highest exposure strata and 2-3 controls, the odds ratios were found to be substantially increased (in the range of 3 to 5) but highly imprecise. As the authors recognized, these results are imprecise and subject to uncertainty related to possible confounding or response bias. Robert (1993) recently evaluated the risk of birth defects in relation to residence in municipalities with and without high-tension power lines. An inverse association was found; the communities without power lines were at higher risk. However, because the estimation of
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields exposure was based on the condition that a power line was anywhere in the community, as opposed to the Wertheimer and Leeper wire codes in which power lines within 150 feet of the home are considered, the assignment at the community level is unlikely to reflect any information about individual exposure. Thus, the study does not contribute to the question of reproductive health effects of exposure to electric and magnetic fields. Electric Appliances Wertheimer and Leeper (1986, 1989) evaluated fetal loss in relation to electric-blanket use in Colorado and ceiling cable-radiant heat in Oregon. Those seasonal field sources were considered particularly useful for study, given that risk could be compared among users of those devices across seasons. Data from the Colorado study were based on birth announcements and a telephone survey, and the data from Oregon were derived from birth certificates. The methodologic details, particularly of the Colorado study (Wertheimer and Leeper 1986), are difficult to interpret, but the authors' conclusion from both studies was that spontaneous abortion risk was greatest in seasons in which uses of the heating devices was increasing. The unconventional design of the study and the pattern in which risk was not highest when exposure was highest diminish the credibility of the overall results, although no clear bias was evident that would have produced the reported pattern. It should also be noted that the Colorado study reported that birth weights were lower among those who used electric blankets, whereas gestational duration was not shortened; this finding was interpreted by the authors as an indication of fetal growth retardation. Another major study of home electric-appliance use addressed congenital defects, specifically oral clefts and neural tube defects, in New York State (Dlugosz et al. 1992). In this well-designed study, the New York State Congenital Malformations Registry served to identify 121 cases with isolated cleft palate, 197 cases with cleft lip with or without cleft palate, and 224 cases with anencephalus or spina bifida. Controls were selected from birth-certificate files. Mailed questionnaires elicited information on electric-blanket and heated-water-bed use along with an array of potential confounding factors. Relative-risk estimates suggested no increase in risk, the odds ratios being 0.8, 0.7, and 0.9 for cleft palate, cleft lip, and neural tube defects, respectively, for electric-blanket use. Uncertainty arises from the reliance on self-reported electric-appliance use several years in the past and the potential bias from nonresponse. For the specific question of electric-blanket and heated-water-bed use in relation to the specific congenital defects studied, the data provided some assurance of no association. The most recent and detailed study of reproductive health consequences of magnetic fields focused on electric-blanket use in relation to fetal growth (Bracken et al. 1995). Women were interviewed and enrolled in this prospective study by 16 weeks of gestation, and subsets of women were assigned to variably detailed
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields magnetic-field-assessment protocols. Multiple exposure sources were considered, including ambient residential fields, electrically heated beds, and wire codes. Among the 2,709 women enrolled, approximately 4% delivered low-birth-weight infants and approximately 7% delivered infants below the tenth percentile of weight for gestational age (labeled as small-for-gestational age). Electrically heated bed use on a daily basis was associated with relative risks on the order of 1.1-1.3 for the two outcomes; the association was not stronger with longer use. No clear associations were seen with the other sources of magnetic fields that were considered, leading the authors to conclude that "risk of low birth weight and intrauterine growth retardation is not increased after electrically heated bed use during pregnancy." For the field types and outcomes examined, the data suggest little or no association. Workplaces The earliest study of exposure to electric and magnetic fields and reproductive health concerned males exposed at high-voltage substations (Nordstrom et al. 1983). Assessment of exposure was based on working in a high-as opposed to low-voltage switchyard. A larger proportion of high-voltage switchyard workers reported having had children with malformations (8%) as compared with other workers (1-3%). The usual proportion is typically about 5%, depending on how narrowly or broadly malformation is defined. Given the poor quality of reporting of malformations, particularly by fathers, and the minimal evidence of electric-and magnetic-field-exposure gradients, this study adds little information. Magnetic-field exposure from VDTs was examined in relation to spontaneous abortion by Lindbohm et al. (1992). Spontaneous abortion cases (191 cases) and live-birth controls (394 controls) were identified among Finnish clerical workers. Exposure to extremely-low-frequency magnetic-fields from VDTs was identified by combining self-reports with measurements of specific VDT units used by the women in the study. Work with VDTs in general showed no association with spontaneous abortion (OR = 1.1), whereas among women who worked with VDTs emitting the highest magnetic-field strength, the odds ratio rose to 3.4. Combining the number of hours of use with the estimated field strength produced by the unit yielded increased risks in relation to exposure to extremely-low-frequency and very-low-frequency magnetic fields. Risk increased steadily from women who used low-field-strength units for brief periods to women who used higher-field-strength units for longer periods; the odds ratios were 1.7 (95% CI = 0.8-3.6) for medium and 3.8 (95% CI = 1.6-8.8) for high relative to low-estimated extremely-low-frequency exposures. Methodologic Issues The methodologic issues for reproductive studies are largely the same as those for childhood cancer studies. The greatest limitation for reproductive studies
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields and cancer studies concerns exposure assessment. The evolution of cancer epidemiology studies has progressed far more, however, than reproductive studies because refinements are being made successively in the studies. At least one major reproductive study is in progress at the California Department of Health Services directed by Dr. Shanna Swan. The study in progress and recently completed ones use the most sophisticated exposure assessment methods available to investigate spontaneous abortion, late fetal loss, fetal-growth retardation, and preterm delivery. Given the relatively short time course of pregnancy and the relatively high frequency of some adverse outcomes, the opportunity to monitor exposure prospectively or at least closer in time to the development of reproductive effects is much greater than that for cancer. The newer studies include home measurements as well as reports of appliance use and measurements. Given how limited previous studies of reproductive effects have been, these new results could completely change the picture in ways that cannot be predicted. Confounding is a somewhat greater concern for reproductive health outcomes than for childhood cancer, largely because so much more is known about risk factors. Across many reproductive outcomes (with the exception of many congenital malformations), there are strong associations with social class, mother's age, tobacco use, and, to a lesser extent, alcohol and illicit drug use. The more sophisticated studies take such factors into account, and failure to do so could easily lead to confounding of such sources of electric-and magnetic-field exposures as electric blankets or residence in high-exposure homes. Selection bias is a concern here as well, but the source population can be defined unambiguously with greater ease from birth records or prenatal care records. Potential for recall bias and response bias are also relevant to interpreting reproductive studies, particularly because such exposures as electric blankets are increasingly perceived by the public as potentially harmful. These perceptions could affect reporting by women who have had an adverse outcome (recall bias) or affect their willingness to participate in the study at all (response bias). LEARNING AND BEHAVIOR The scientific literature on the association between exposure to power-frequency electric and magnetic fields and behavior includes a series of studies that relate exposure to a wide range of outcomes, including suicides, depressive symptoms, headaches, and neuropsychologic performance. In general, the studies of behavioral outcomes used potentially biased designs and obtained results that are inconsistent and of poor quality. Few studies used a validated measurement instrument to assess subjective symptoms, opportunity for misclassification of exposure and outcome was ample, most did not adjust adequately for confounding (especially demographics), and few used expsoure measurements with adequate temporal and spatial resolution. Nonetheless, the consistent lack of association seen in this set of studies is notable. The committee reviewed the details of these
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields studies, as has Paneth (1993). Note that this section does not consider studies of acute effects (e.g., see Stollery 1986; Gamberale et al. 1989; Cook et al. 1992) nor reports of hypersensitivity to electric or magnetic fields because they are beyond the committee's charge. Suicide Suicide was the first outcome evaluated in modern studies of exposure to electric and magnetic fields and behavioral response. It is listed on death certificates and medical records and thus particularly amenable to evaluation. One set of studies conducted in England compared exposures to high-voltage electric-power transmission lines (equal to or greater than 32 kV) among 598 suicides and 598 randomly selected electoral-register controls (Reichmanis et al. 1979; Perry et al. 1981). The first study used magnetic-field exposures calculated from transmission-line configurations to compare subjects, and the second used measured magnetic fields as well as a variety of other metrics. In the study by Reichmanis et al. (1979), exposures to electric and magnetic fields were calculated at all residences of subjects. Values for case and control residences then were compared among three categories of increasing exposure. The overall results showed statistically significant differences among the suicide cases and the controls, although no exposure-effect trend was observed. Next, cases and controls were ranked individually by exposure, and a paired comparison was conducted. The control exposure values were statistically significantly higher than the cases' exposure, suggesting that suicide subjects were more likely to live in lower-level electric-and magnetic-field environments than controls. The authors were equivocal in their interpretation of those results, but noted that the data are consistent with the notion that exposure to electric and magnetic fields does not induce suicide. In the study by Perry et al. (1981), the same data were compared on the basis of additional exposure metrics: (1) type of residence, (2) distance from school, major road, church, or open water, and (3) doorstep measured magnetic field. No significant differences were found for metrics 1 or 2. However, a statistically significant number of cases compared with controls were found to be at or above the median doorstep-exposure value of 0.04 µT (0.4 mG) (52% vs. 43%), and, overall, case homes had statistically significantly higher measured magnetic-field exposures than control homes. As noted by the authors, the median magnetic field was measured at 0.04 µT, whereas that calculated in the study of Reichmanis et al. (1979) was 0.005 µT, suggesting that transmission lines might not have been the main source of exposure. That discrepancy also provides a possible explanation for the disparate results of the two studies. Commenting on those studies, Bonnell et al. (1983) pointed out that suicide rates vary several-fold by gender, age, socioeconomic status, and urban or rural character, but none of these potential confounding variables was adjusted for. In
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields addition, measurements were made only once, measurements were taken on the doorstep rather than in the living space, measurement takers were not blinded to the house status, and measurements were taken many years after the occurrence of the event. Further, Bonnell et al. (1983) questioned the potential biases in the control-selection procedure (e.g., mobility). Smith (1983) noted an additional potential problem of confounding in that the correlation between the number of suicides and the average exposure in the homes of the suicide cases was negative, a condition that might indicate an association between lower socioeconomic status of suicide cases and the tendency of persons of lower socioeconomic status to use less electricity because of its cost. Suicide cases were also assessed as part of a cohort mortality follow-up study conducted by McDowall (1986). McDowall reported no evidence of an increased rate of suicide among those living within 50 m of a substation or 30 m of an overhead line. Baris and Armstrong (1990) reviewed British occupational mortality data on the proportion of deaths from suicide among electrical workers. They found that the category composed of all electrical occupations did not show excess suicides, but the categories of radio, radar, and television technicians showed excess proportion of death from suicide in 1970-1972 and 1979-1983. The categories of telegraph and radio operators showed excess suicides in 1970-1972 but a deficit proportion of suicides in 1979-1983. Baris and Armstrong (1990) noted the imperfections in their exposure data and, because only age was adjusted for, the possibility of uncontrolled confounding. Overall, they concluded that their results were negative. Nondifferential misclassification of both exposure and outcome might have introduced bias. Depression The first reported studies of the association between residential proximity to power lines and depression were by Dowson et al. (1988) and Perry and colleagues (Perry and Pearl 1988; Perry et al. 1989). Dowson et al. (1988) conducted a study in England among people living near 132-kV overhead power lines. They compared that population with a population living away from overhead lines and closely matched in house type. The study was designed to assess recurrent diseases, health decline during the previous year, and work-time lost due to illness; adjustments were made for age, sex, social status, and duration of residence. The residents near power lines were younger, they reported more days off from work, had more headaches or migraines, and suffered more depression. Adjusting for sex and years of residence did not alter the results. Perry and Pearl (1988) studied hospital admissions among residents of multistory buildings and found no statistically significant differences in overall incidence of heart disease, drug overdoses, and psychiatric problems among those living near and those living away from electric cables, but a statistically significant
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields increase in depression and personality defects was found among those living near the cables. Gender and age were similarly distributed in each case and control group and could not have introduced confounding. Banks (1988) criticized the exposure characterization and argued that the proximity method used was likely to have misclassified many subjects. Perry et al. (1989), responding to critics, conducted a larger case-control study of discharge diagnosis or cause of death of patients in local hospitals with spot measurements of magnetic fields. They again found a statistically significant association between depressive illness and high magnetic-field exposures. The myocardial infarction results were null, in agreement with the earlier study, which showed a statistically nonsignificant increase in myocardial infarction. Issues of possible confounding and selection bias still were not addressed adequately. Two recent studies incorporated a validated measurement of depression (e.g., the CES-D scale) in their study designs. Poole and Kavet (1993) conducted a telephone interview survey of 382 persons to assess the prevalence of depressive symptoms and headache in relation to visual proximity of residence to overhead power lines. They found a statistically significant positive association for depressive symptoms but not for headaches or migraines. Adjustment for demographic factors did not account for the observed effects. As noted by the authors, the assessment of exposure was crude. The overall participation rate was 69%. McMahan et al. (1994) studied depression in women living adjacent to and one block away from overhead transmission lines in Orange County, California. Field measurements of magnetic fields were used to confirm exposure classifications. Confounders considered were age, income, education, and length of residence. Personal interviews of 152 women (61%) were conducted on the subject of depression. Questions were also asked about general health, life events, family history, health habits, occupation, and home life. Depression (CES-D score above median) was positively associated with shorter tenure at residence, less education, younger age, nonwhite ethnicity, and higher income and negatively associated with living near a power transmission line, although none of the reported associations was statistically significant. Two other studies investigated the association between occupational exposures to electric fields and depressive symptoms. Broadbent et al. (1985) interviewed 390 electric-power transmission and distribution workers. Electric fields were measured for 287 subjects. No significant associations were found between electric-field exposure and headaches, depression, or related conditions. Savitz et al. (1994) analyzed data from the Vietnam Experience Study. Using the Diagnostic Inventory Survey and the Minnesota Multiphasic Personality Inventory, they compared results for 183 electrical workers and 3,861 nonelectrical workers. Electrical workers did not show increased depression or depressive symptoms overall, although electricians were approximately twice as likely to be depressed, but this association was not statistically significant.
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields Headaches Headache frequency was reported mainly in conjunction with other symptoms. Dowson et al. (1988) reported more headaches and migraines among people living near 132-kV overhead power lines than among those in a comparison population living away from overhead lines. Poole and Kavet (1993) did not find an association between reported headache frequency and living within sight of an overhead line. Broadbent et al. (1985) found no association between headache frequency and electric-field exposure. In a study designed to follow up results from Dowson et al. (1988), Haysom et al. (1990) used a standardized questionnaire to investigate the incidence of self-reported headaches and migraines. Subjects lived on large estates adjacent to overhead power lines in Southampton, England, Large estates were used in the study to control for age and social status and to allow for a wide range of exposures by including houses close to (less than 100 m) and far from (greater than 100 m) the power lines. The study group comprised 592 adults classified as exposed and 592 classified as unexposed. Of those subjects determined to be eligible, response rates were similar among exposed (63.5%) and unexposed (66.2%). A lower rate of headache was reported by subjects living 100 m or more from the power lines, although a chi-squared analysis showed the results were not statistically significant. The highest rate of headache was reported by the group living 50-100 m from the power lines. Reported migraines showed a similar pattern and were statistically significant, both for indices of severity and frequency. Finally, the incidence of headaches was more pronounced near a 400-kV power line than a 132-kV power line, although this difference also was not statistically significant. No explanation or postulated physiologic mechanism is given for the findings. Neuropsychologic Performance Two studies of occupational exposures to electric and magnetic fields and neuropsychologic effects were conducted. Knave et al. (1979) conducted a matched (age, location, and length of employment) cross-sectional study of exposed and unexposed workers. Exposed workers performed better on memory tests, one-hand manual dexterity tests, reaction-time tests, and perceptual speed tests. However, these subjects also were more educated, and the authors speculated that the educational difference could be responsible for the performance difference. Baroncelli et al. (1986) conducted a cross-sectional study of railroad workers. They compared results of a variety of laboratory and performance tests among those exposed to electric and magnetic fields. Reaction times and anxiety tests showed no statistically significant differences among four exposure categories.
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Possible Health Effects of Exposure to Residential Electric and Magnetic Fields Summary The results of studies of neurobehavioral responses to exposure to electric and magnetic fields are inconsistent and of mixed quality. The exposure measurements used—job titles, calculated fields, spot measurements and visual proximity—all have known limitations and are likely to result in substantial misclassification. A range of symptoms for clinically relevant outcomes were reported in the studies, and only some of the studies used standardized instruments to assess their occurrence. Hospital and medical records are likely to result in incomplete ascertainment and are likely biased by educational level and socioeconomic status of the subject.
Representative terms from entire chapter: