Magnetic Fields and Cancer
Editor's Note: The following letter is a response to an article by
Savitz and Kaune, EHP 101:76-80.
In 1979 Wertheimer and Leeper developed their W-L wire code, based on
power line construction, size, and distance from a residence, as a surrogate
for residential magnetic field exposure (1). This W-L wire code was
applied to data from a 1988 Denver study, and an association was reported
between "high" W-L wire code and childhood cancer (2).
The authors of "Childhood Cancer in Relation to a Modified Residential
Wire Code" (3) use the 1988 Denver data and report a stronger
association between their newly defined "high" wire code and childhood
cancer. However, they report that this new wire code is not more strongly
correlated with measured magnetic fields. (The authors state that both the
W-L wire code and the new wire code can explain only 20% of the magnetic
field variability.) A stronger association with childhood cancer without
a correspondingly stronger correlation with magnetic fields suggests that
factors other than magnetic fields may be involved in the reported wire
code association with childhood cancer.
The authors suggest that their new wire code is less susceptible to classification
error than was present with the W-L wire code and that, had all of the 1988
Denver study homes been classified correctly, the W-L wire code would have
produced a stronger association with childhood cancer. However, a "Back-to-Denver"
(BTD) study, based on a subset of the 1988 Denver homes, found the W-L wire
code classification error rate to be "quite small" (4).
This finding appears to weaken the authors' argument that classification
error resulted in an appreciable reduction in the association between W-L
high wire code and childhood cancer in the 1988 Denver study. The authors
of the BTD study conclude that factors other than magnetic fields may be
responsible for the reported wire code association with childhood cancer
(4).
Explanations exist that suggest the reported stronger childhood cancer
association with the new wire code may be false. For example, the selection
criteria used in the original study (2) caused the case and control
populations to be noncomparable with respect to residential mobility. Specifically,
controls were required to be residentially stable from case diagnosis to
selection as a control but cases were not. Thus, an artificial association
between residential mobility and cancer was created by the subject selection
procedure. This artificial association was shown to be a possible explanation
for at least part of the reported association between W-L high wire code
and childhood cancer (5). An even stronger bias from differential
residential mobility might exist with the new wire code. This possibility
could be tested by restricting the analysis to only those cases and controls
that were residentially stable from diagnosis to matched control selection.
Children that lived in homes in whlch magnetic field measurements were taken
were residentially stable from diagnosis to control selection (2)
and could provide the basis for such a comparison.
Another possible explanation for a false association between wire codes
and cancer is that individual cases may not have been matched with a control
from the same neighborhood. In the 1988 Denver study children with the same
telephone exchange as the case were eligible for selection as controls (2).
The area corresponding to a particular telephone exchange likely does not
correspond to a single neighborhood. For example, in Columbus, Ohio, the
telephone exchange for the oldest neighborhood (developed in the 1800s)
includes modern residential areas that were annexed to the city after 1970.
Neighborhood differences between the cases and controls have the potential
to significantly influence wire code associations because wire codes have
been found to be strongly associated with the age of a neighborhood. For
instance, 50% of the homes in one of the oldest neighborhoods (inner city)
in Columbus were classified as W-L high wire code, while less than 25% of
the homes in two neighborhoods developed within the last 50 years were classified
as W-L high wire code (6). Based on these Columbus data, if cases
from the inner city are matched with controls from newer neighborhoods,
odds ratios exceeding a value of 3.0 could be produced, falsely associating
high wire code with childhood cancer.
Evidence exists that the cases in the 1988 Denver study may be from older
neighborhoods relative to the controls. For example, of the homes classified
as W-L high wire code based on secondary powerline construction, 63% of
the cases and only 33% of the controls had the older "open wire"
construction (7). This finding is suggestive of a failure to match
cases and controls by neighborhood, which could have resulted in the creation
of a false association between W-L high wire code and childhood cancer.
As compared to the W-L wire code, the authors' new wire code appears
to place an even greater proportion of older powerline constructions in
the high wire code category and a greater proportion of newer constructions
in the low category (Table 1). Based on the authors' Table 3, the most important
result may be the movement of spun wire secondaries (present standard construction
which was introduced in Columbus in the 1950s) within 50 feet of a residence
from the W-L "high" category to the new "low" category
(23% of the W-L "high wire code" controls, while only 9% of the
W-L "high wire code" cases were so reclassified). If cases are
from older neighborhoods relative to the controls, application of this new
wire code would likely result in a stronger but false association between
the new high wire code and childhood cancer. Adjustment for age of neighborhood
should remove this possible bias.
In conclusion, the fact that the new wire code is only weakly correlated
with magnetic field measurements (in the same manner as the original W-L
wire code) suggests that the newly reported stronger association with childhood
cancer is likely due to factors other than magnetic fields. Differential
residential mobility and differential residential age are two possible explanations
and are suggestive that the reported association may be false.
Thomas L. Jones
American Electric Power
Service Corporation
References
1. Wertheimer N, Leeper E. Electrical wiring configuration
and childhood cancer. Am J Epidemiol 109:273-284(1979).
2. Savitz DA, Wachtel H, Barnes FA, John EM, Tordik JG.
Case-control study of childhood cancer and exposure to 60 Hz magnetic fields.
Am J Epidemiol 128:21-38(1988).
3. Savitz DA, Kaune WT. Childhood cancer in relation to
a modified wire code. Environ Health Perspect 101:76-80(1993).
4. Dovan T, Kaune WT, Savitz DA. Repeatability of measurements
of residential magnetic fields and wire codes. Bioelectromagnetics 14:145-159(1993).
5. Jones, TL, Shih CH, Thurston DH, Ware BJ, Cole P. Selection
bias from differential residential mobility as an explanation for associations
of wire codes with childhood cancer. J Clin Epidemiol 46:545-548(1993).
6. Jones TL, Shih CH, Thurston DH, Ware BJ, Cole P. Residential
wire code associations and implications for case-control study bias. In:
Electricity and magnetism in biology and medicine. San Francisco,
CA:San Francisco Press, 1993; 437-439.
7. Leeper E, Wertheimer N. Savitz D, Barnes F, Wachtel
H. Modification of the 1979 "Denver wire code" for different wire
or plumbing types. Bioelectromagnetics 12:315-318(1991).
Response: Potential Bias in Denver Childhood Cancer Study
Jones makes several points in his letter to that we would like to
address.
The observation that the modified wire code is similar to the Wertheimer-Leeper
code in its relation to measured magnetic fields, yet more strongly related
to cancer, is interpreted as evidence that both wire codes reflect some
exposure other than magnetic fields as the basis for their relation to cancer
risk, but the modified wire code does so more effectively. If the measured
magnetic field were the true gold standard, this reasoning would be valid,
but the real interest is in long-term, historical magnetic field exposure
to occupants of the residence, which is unfortunately not available. If
the modified wire code is superior, then its relation to the gold standard
exposure would presumably be enhanced, but not necessarily the relation
to spot magnetic-field measurements, another imperfect surrogate of exposure.
The "Back to Denver" study (1) is cited to verify that
the Wertheimer-Leeper wire code can be reliably assessed. However, that
study did not directly address the question of which aspects of the coding
system are contributory and which are superfluous, thereby adding only random
error relative to the ideal exposure measure. The greater simplicity of
the new system is one of its expected contributions, allowing less skilled
persons to collect valid data, but we also believe that the approach may
eliminate some distinctions that are not of importance in estimating exposure.
The reduction in misclassification would not be solely due to fewer actual
recording errors but in more accurately and parsimoniously reflecting the
field-determining characteristics of the power lines. A number of alternative
explanations for the wire code-cancer association are considered by Dovan
et al. (1). Unfortunately, the data reported cannot be used to prove
that magnetic fields or some factor other than magnetic fields account for
the observed associations.
In a recent article (2), the hypothesis was put forth that differential
residential mobility accounts for much of the association we observed originally
between wire codes and childhood cancer (3). Jones et al. argue that
1) controls in our study in Denver were restricted to be residentially stable
from the date of the matched case's diagnosis to the time of selection (a
period of 0-9 years, depending on the corresponding case's date of diagnosis);
2) data collected in Columbus, Ohio, demonstrate an association between
residential stability and wire configuration code. Occupants of homes with
wire codes indicative of elevated magnetic fields are less stable; 3) application
of the differential mobility by wire code in the Denver study produces an
odds ratio due to selection bias of around 1.5.
Given that cases were ascertained over an 8-year period (1976-1983),
which preceded data collection (1984-1985), control selection posed a challenge.
If all residents of the study area at the time of selection were considered
eligible, we would have included many children who had moved to the area
subsequent to the corresponding case's age of diagnosis. We chose instead
to restrict controls to those who were present when the case was diagnosed
and remained in the area until the time of selection. We recognized that
this omitted controls who would have been eligible at the time of diagnosis
but who had subsequently moved away, and acknowledge that this constitutes
a potentially important source of selection bias in the study (3).
Data gathered by Jones et al. (2) in a different city and time period
from our study provide a firmer empirical basis for such a concern, but
the question of generalizability from Columbus to Denver cannot be made
with certainty. Organization of cities with respect to land use, socioeconomic
status, and patterns of migration are complex and quite likely to be distinctive,
especially in different regions of the country.
A comprehensive analysis of our data to address the role, if any, of
selection bias related to mobility is underway, but several points raised
by Jones are in error. We restricted controls to be stable from the time
of diagnosis to the time of selection, whereas cases were included whether
stable or mobile during that period. As a result of this requirement, there
was a small imbalance in the prediagnosis period (birth to diagnosis): 82
of 224 interviewed cases remained stable (37%), whereas 81 of 198 interviewed
controls remained stable from birth to diagnosis (41%). Patterns of association
can be examined in several ways to address this concern. The odds ratio
(high versus low wire code) for children who remained stable was lower for
total cancers and leukemias, but not for brain tumors (4: Table 6).
More pertinent, the magnitude of any bias resulting from restricted residential
mobility must be greatest for the cases diagnosed in the period most remote
form the time of control selection and interview (C. Poole, personal communication),
yet the odds ratios for the more recent period (1980 or later) are much
larger, not smaller, than the odds ratios for the earlier period (4:
Table 6). Finally, consistent with the pattern by calendar time, the wire
code odds ratio for children who had magnetic field measurements (a marker
of having remained residentially stable from diagnosis to selection) was
2.0 (95% CI: 1.0-3.9). For leukemia cases, the corresponding odds ratio
was 3.9 (95% CI: 1.6-9.8). In fact, among cases, the proportion with high
wire code was virtually identical among those who had magnetic field measurements
(20%) and those who did not (19%). Perhaps in Denver, residential stability
and wire configuration code are not related. Furthermore, the patterns of
movement among families with children who have cancer may well differ as
a result of the occurrence of the cancer, making their reasons for movement
distinct from controls (C. Poole, personal communication).
The telephone exchange areas in which cases and controls were matched
covered a sufficiently large geographic area to allow for disparities to
occur in the wire codes. At the extreme, if the areas were sufficiently
homogeneous, the cases and controls would be assured of having identical
wire codes. To the extent that the random-digit dialing procedure is effective,
we chose a control randomly from the same broad section of town as the case.
Assuming the type of heterogeneity within areas Jones describes, the selection
procedure should have provided a representative control. For his scenario
of "all cases in old homes, all controls in new homes" to operate,
cases would have to be unevenly distributed within telephone exchange areas,
and the selection procedure would have to have been systematically biased
or generated a grossly unrepresentative sample in spite of a random selection
mechanism.
Jones argues that the characteristics of the secondary power line construction
indicate an imbalance between cases and controls in age of neighborhood.
In the original Wertheimer-Leeper coding system, homes could not be placed
in the "very high current configuration" category based on secondary
lines (5), and in the modified code, secondary lines cannot result
in an assignment of a home to the high level. Proximity to a primary line
or transmission line is required for such a classification. The secondary
power line characteristics only influence the designation as "low"
versus "medium" in the modified wire code system, and because
the odds ratios for the medium group were near the null, secondary power
line characteristics did not have an important influence on our results.
Age of neighborhood is suggested as another potential basis for a spurious
positive association. Because selection of controls was unlikely to have
been biased by age of the home, Jones implies that residential age acts
as a true confounder of the wire code-cancer association. Many home attributes
and perhaps exposures are related to age of housing, but none are currently
known to be independently related to risk of cancer in children. If, as
suggested, cases tended to come from older homes than controls, an argument
could be made that the association with age of residence is valid but a
reflection of a causal relationship between high wire codes (associated
with older homes), elevated magnetic fields, and childhood cancer.
Future studies clearly should avoid an approach to control selection
that creates such an imbalance in mobility by conducting concurrent case
and control ascertainment, and the data of Jones et al. (2) provide
more forceful justification for doing so. Ideally, such studies would also
consider potential confounders related to the neighborhood plausibly related
to cancer risk. In addition to the evidence within our study results that
such biases do not account for the observed associations, similar results
in studies free of such potential bias (6,7) provide indirect
evidence that any mobility bias is unlikely to have been substantial in
the study in Denver.
David A. Savitz
University of North
Carolina
Chapel Hill, North Carolina
William T. Kaune
EM Factors
Richland, Washington
References
1. Dovan T, Kaune WT, Savitz DA. Repeatability of measurements
of residential magnetic fields and wire codes. Bioelectromagnetics 14:145-
159(1993).
2. Jones TL, Chih CH, Thurston DH, Ware BJ, Cole P. Selection
bias from differential residential mobility as an explanation for associations
of wire code with childhood cancer. J Clin Epidemiol 46:545-548(1993).
3. Savitz DA, Wachtel H, Barnes FA, John EM, Tvrdik JG.
Case-control study of childhood cancer and exposure to 60-Hz magnetic fields.
Am J Epidemiol 128:21-38(1988).
4. Savitz DA, Kaune WT. Childhood cancer in relation to
a modified residential wire code. Environ Health Perspect 101:76-80(1993).
5. Wertheimer N, Leeper E. Adult cancer related to electrical
wires near the home. Int J Epidemiol 11:345-355(1982).
6. Wertheimer N, Leeper E. Electrical wiring configurations
and childhood cancer. Am J Epidemiol 109:273-284(1979).
7. Feychting M. Ahlbom A. Magnetic fields and cancer in
people residing near Swedish high voltage power lines. Stockholm:Karolinska
Institute, 1982.
Last Update: August 21, 1998
