A New Electromagnetic Exposure Metric: High
Frequency Voltage Transients Associated With
Increased Cancer Incidence in Teachers in a
California School
Samuel Milham, MD, MPH
,{ and L. Lloyd Morgan, BS{
Background In 2003 the teachers at La Quinta, California middle school complained
that they had more cancers than would be expected. A consultant for the school district
denied that there was a problem.
Objectives To investigate the cancer incidence in the teachers, and its cause.
Method We conducted a retrospective study of cancer incidence in the teachers’ cohort in
relationship to the school’s electrical environment.
Results Sixteen school teachers in a cohort of 137 teachers hired in 1988 through 2005
were diagnosed with 18 cancers. The observed to expected (O/E) risk ratio for all cancers
was 2.78 (P¼0.000098), while the O/E risk ratio for malignant melanoma was 9.8
(P¼0.0008). Thyroid cancer had a risk ratio of 13.3 (P¼0.0098), and uterine cancer had
a risk ratio of 9.2 (P¼0.019). Sixty Hertz magnetic fields showed no association with
cancer incidence. A new exposure metric, high frequency voltage transients, did show a
positive correlation to cancer incidence. A cohort cancer incidence analysis of the teacher
population showed a positive trend (P¼7.110
10) of increasing cancer risk with
increasing cumulative exposure to high frequency voltage transients on the classroom’s
electrical wiring measured with a Graham/Stetzer (G/S) meter. The attributable risk of
cancer associated with this exposure was 64%. A single year of employment at this school
increased a teacher’s cancer risk by 21%.
Conclusion The cancer incidence in the teachers at this school is unusually high and is
strongly associated with high frequency voltage transients, which may be a universal
carcinogen, similar to ionizing radiation. Am. J. Ind. Med. 2008. 2008 Wiley-Liss, Inc.
KEY WORDS: high frequency voltage transients; electricity; dirty power; cancer;
school teachers; carcinogen
BACKGROUND
Since the 1979 Wertheimer–Leeper study [Wertheimer
and Leeper, 1979] there has been concern that exposure to
power frequency (50/60 Hz) EMFs, especially magnetic
fields, may contribute to adverse health effects including
cancer. Until now, the most commonly used exposure metric
has been the time-weighted average of the power-frequency
magnetic field. However, the low risk ratios in most studies
suggest that magnetic fields might be a surrogate for a more
important metric. In this paper we present evidence that a
2008 Wiley-Liss, Inc.
Abbreviations: EMF, electromagnetic fields; O, observed cases; E, expected cases; O/E,
risk ratio; p, probability; Hz, Hertz or cycles per second; OSHA, Occupational Safety and
Health Administration; OCMAP, occupational mortality analysis program; AM, amplitude
modulation; GS units, Graham/Stetzer units; G/S meter, Graham/Stetzer meter; MS II, Microsurge
II meter; mG, milligauss; EKG, electrocardiogram; LQMS, La Quinta Middle School.
Washington State Department of Health,Tumwater,Washington
{Retired.
{Retired Electronic Engineer.
*Correspondence to: Samuel Milham, 2318 Gravelly Beach Loop NW, Olympia,WA 98502.
E-mail: smilham2@comcast.net
Accepted 29 April 2008
DOI10.1002/ajim.20598. Published online inWiley InterScience
(www.interscience.wiley.com)
new exposure metric, high frequency voltage transients
existing on electrical power wiring, is an important predictor
of cancer incidence in an exposed population.
The new metric, GS units, used in this investigation is
measured with a Graham/Stetzer meter (G/S meter) also
known as a Microsurge II meter (MS II meter), which is
plugged into electric outlets [Graham, 2005]. This meter
displays the average rate of change of these high frequency
voltage transients that exist everywhere on electric power
wiring. High frequency voltage transients found on electrical
wiring both inside and outside of buildings are caused by an
interruption of electrical current flow. The electrical utility
industry has referred to these transients as ‘‘dirty power.’’
There are many sources of ‘‘dirty power’’ in today’s
electrical equipment. Examples of electrical equipment
designed to operate with interrupted current flow are light
dimmer switches that interrupt the current twice per cycle
(120 times/s), power saving compact fluorescent lights that
interrupt the current at least 20,000 times/s, halogen lamps,
electronic transformers and most electronic equipment
manufactured since the mid-1980s that use switching power
supplies. Dirty power generated by electrical equipment in a
building is distributed throughout the building on the electric
wiring. Dirty power generated outside the building enters the
building on electric wiring and through ground rods and
conductive plumbing, while within buildings, it is usually the
result of interrupted current generated by electrical appliances
and equipment.
Each interruption of current flow results in a voltage
spike described by the equation V¼Ldi/dt, where Vis the
voltage, L is the inductance of the electrical wiring circuit
and di/dt is the rate of change of the interrupted current. The
voltage spike decays in an oscillatory manner. The oscillation
frequency is the resonant frequency of the electrical circuit.
The G/S meter measures the average magnitude of the rate of
change of voltage as a function of time (dV/dT). This
preferentially measures the higher frequency transients. The
measurements of dV/dT read by the meter are defined as GS
(Graham/Stetzer) units.
The bandwidth of the G/S meter is in the frequency range
of these decaying oscillations. Figure 1 shows a two-channel
oscilloscope display. One channel displays the 60 Hz voltage
on an electrical outlet while the other channel with a 10 kHz
hi-pass filter between the oscilloscope and the electrical
outlet, displays the high frequency voltage transients on the
same electrical outlet [Havas and Stetzer, 2004, reproduced
with permission].
Although no other published studies have measured high
frequency voltage transients and risk of cancer, one study of
electric utility workers exposed to transients from pulsed
FIGURE 1. Oscilloscope display ofdirtypower: 60 Hzelectrical power (channel1)with concurrenthighfrequency voltage transients
(channel2).A10kHzhi-passfilterwasusedonchannel2inordertofilteroutthe60Hzvoltageanditsharmonics.[Colorfigurecanbeviewed
inthe onlineissue,which is available atwww.interscience.wiley.com.]
2 Milham and Morgan
electromagnetic fields found an increased incidence of lung
cancer among exposed workers [Armstrong et al., 1994].
INTRODUCTION
In February 2004, a Palm Springs, California newspaper,
The Desert Sun, printed an article titled, ‘‘Specialist
discounts cancer cluster at school,’’ in which a local tumor
registry epidemiologist claimed that there was no cancer
cluster or increased cancer incidence at the school [Perrault,
2004]. An Internet search revealed that the teacher
population at La Quinta Middle School (LQMS) was too
small to generate the 11 teachers with cancer who were
reported in the article. The school was opened in 1988 with
20 teachers hired that year. For the first 2 years, the school
operated in three temporary buildings, one of which remains.
In 1990, a newly constructed school opened. In 2003, the
teachers complained to school district management that they
believed that they had too many cancers. Repeated requests
to the school administration for physical access to the school
and for teachers’ information were denied.We contacted the
teachers, and with their help, the cancers in the group were
characterized. One teacher suggested using yearbooks to
develop population-at-risk counts for calculating expected
cancers. We were anxious to assess the electrical environment
at the school, since elevated power frequency magnetic
field exposure with a positive correlation between duration of
exposure and cancer incidence had been reported in first floor
office workers who worked in strong magnetic fields above
three basement-mounted 12,000 V transformers [Milham,
1996]. We also wanted to use a new electrical measurement
tool, the Graham/Stetzer meter, which measures high
frequency voltage transients.
The Graham/Stetzer Microsurge II meter measures the
average rate of change of the transients in Graham/Stetzer
units (GS units). Anecdotal reports had linked dirty power
exposure with a number of illnesses [Havas and Stetzer,
2004]. We decided to investigate whether power frequency
magnetic field exposure or dirty power exposure could
explain the cancer increase in the school teachers.
METHODS
After the school administration (Desert Sands Unified
School District) had refused a number of requests to assist in
helping us evaluate the cancers reported by the teachers, we
were invited by a teacher to visit the school after hours to
make magnetic field and dirty power measurements. During
that visit, we noted that, with the exception of one classroom
near the electrical service room, the classroom magnetic field
levels were uniformly low, but the dirty power levels were
very high, giving many overload readings. When we reported
this to Dr. Doris Wilson, then the superintendent of schools
(retired December, 2007), one of us (SM) was threatened
with prosecution for ‘‘unlawful.. trespass,’’ and the teacher
who had invited us into the school received a letter of
reprimand. The teachers then filed a California OSHA
complaint which ultimately lead to a thorough measurement
of magnetic fields and dirty power levels at the school by the
California Department of Health Services which provided
the exposure data for this study. They also provided
comparison dirty power data from residences and an office
building, and expedited tumor registry confirmation of
cancer cases.
Classrooms were measured at different times using
3 meters: an FW Bell model 4080 tri-axial Gaussmeter, a
Dexsil 310 Gaussmeter, and a Graham-Stetzer (G/S) meter.
The Bell meter measures magnetic fields between 25 and
1,000 Hz. The Dexsil meter measures magnetic fields
between 30 and 300 Hz. The G/S meter measures the
average rate of change of the high frequency voltage
transients between 4 and 150 KHz.
All measurements of high frequency voltage transients
were made with the G/S meter. This meter was plugged into
outlets, and a liquid crystal display was read. All measurements
reported were in GS units. The average value was
reported where more than one measurement was made in a
classroom.
We measured seven classrooms in February 2005 using
the Bell meter and the G/S meter. Later in 2005, the teachers
measured 37 rooms using the same meters. On June 8, 2006,
electrical consultants for the school district and the
California Department of Health Services (Dr. Raymond
Neutra) repeated the survey using the G/S meter and a Dexsil
320 Gaussmeter, measuring 51 rooms.We used results of this
June 8, 2006 sampling in our exposure calculations, since all
classrooms were sampled, multiple outlets per room were
sampled, and an experienced team did the sampling.
Additionally, GS readings were taken at Griffin Elementary
school near Olympia,Washington, and Dr. Raymond Neutra
provided GS readings for his Richmond California office
building and 125 private California residences measured in
another Northern California study.
All the cancer case information was developed by
personal, telephone, and E-mail contact with the teachers or
their families without any assistance from the school district.
The local tumor registry verified all the cancer cases with the
exception of one case diagnosed out of state and the two cases
reported in 2007. The out-of state case was verified by
pathologic information provided by the treating hospital. The
teachers gathered population-at-risk information (age at
hire, year of hire, vital status, date of diagnosis, date of death,
and termination year) from yearbooks and from personal
contact. The teachers also provided a history of classroom
assignments for all teachers from annual classroom assignment
rosters (academic years 1990–1991 to 2006–2007)
generated by the school administration. The school administration
provided a listing of school employees, including
High Frequency Voltage Transients and Cancer 3
the teachers, to the regional tumor registry after the teachers
involved the state health agency by submitting an OSHA
complaint. The information we obtained anecdotally from
the teachers, yearbooks, and classroom assignment rosters
was nearly identical to that given to the tumor registry. None
of the cancer cases were ascertained initially through the
cancer registry search.
Published cancer incidence rates by age, sex, and race
for all cancers, as well as for malignant melanoma, thyroid,
uterine, breast, colon, ovarian cancers, and non-Hodgkin’s
lymphoma (NHL) were obtained from a California Cancer
Registry publication [Kwong et al., 2001].We estimated the
expected cancer rate for each teacher by applying year, age,
sex, and race-specific cancer incidence rates from hire date
until June 2007, or until death. We then summed each
teacher’s expected cancer rate for the total cohort.
Using the California cancer incidence data, the school
teacher data, and the GS exposure data, we calculated cancer
incidence and risks. A replicate data set was sent to Dr. Gary
Marsh and to Mike Cunningham at the University of
Pittsburgh School of Public Health for independent analysis
using OCMAP software.We calculated cancer risk ratios by
duration of employment and by cumulative GS unit-years of
exposure.We calculated an attributable risk percent using the
frequencies of total observed and expected cancers, and
performed trend tests [Breslowand Day, 1987] for cancer risk
versus duration of employment and cumulative GS unityears
of exposure. Poisson P values were calculated using the
Stat Trek website (Stat Trek, 2007). We also performed a
linear regression of cancer risk by duration of employment
in years and by time-weighted exposure in GS unit-years.
Since neither author had a current institutional affiliation,
institutional review board approval was not possible.
The teachers requested the study, and their participation in
the study was both voluntary and complete. All the active
teachers at the school signed the Cal OSHA request. The
authors fully explained the nature of the study to study
participants and offered no remuneration to the teachers for
participation in the study. The authors maintained strict
confidentiality of all medical and personal information
provided to us by the teachers, and removed personal
identifiers from the data set which was analyzed by the
University of Pittsburgh. Possession of personal medical
information was limited to the two authors. No patientspecific
information was obtained from the tumor registry.
With the individual’s permission we provided the registry
with case information for a teacher with malignant
melanoma diagnosed out of state. The exposure information
was provided by the California Department of Health
Services. The basic findings of the study were presented to
the Desert Sands Unified School District School Board and at
a public meeting arranged by the teachers.
RESULTS
Electrical Measurements
In our seven-room survey of the school in 2005,
magnetic field readings were as high as 177 mG in a
classroom adjacent to the electrical service room. A number
of outlets had overload readings with the G/S meter.
Magnetic fields were not elevated (>3.0 mG) in the interior
space of any of the classrooms except in the classroom
adjacent to the electrical service room, and near classroom
electrical appliances such as overhead transparency projectors.
There was no association between the risk of cancer and
60 Hz magnetic field exposures in this cohort, since the
classroom magnetic field exposures were the same for
teachers with and without cancer (results not shown).
This school had very high GS readings and an
association between high frequency voltage transient
exposure in the teachers and risk of cancer. The G/S meter
gives readings in the range from 0 to 1,999 GS units. The case
school had 13 of 51 measured rooms with at least one
electrical outlet measuring ‘‘overload’’ (2,000 GS units).
These readings were high compared to another school near
Olympia Washington, a Richmond California office building,
and private residences in Northern California (Table I).
Altogether, 631 rooms were surveyed for this study. Only
17 (2.69%) of the 631 rooms had an ‘‘overload’’ (maximum,
2,000 GS units) reading. Applying this percentage to the
51 rooms surveyed at the case school, we would expect
1.4 rooms at the school to have overload GS readings
(0.026951¼1.37). However, thirteen rooms (25%) measured
at the case school had ‘‘overload’’ measurements above
the highest value (1,999 GS units) that the G/S meter can
TABLE I. Graham/StetzerMeter Readings:MedianValues in Schools,Homes and an Office Building
Place Homes Office bldg OlympiaWASchool LQMS Total
No. of rooms surveyed 500 39 41 51 531
Median GS units 159 210 160 750 <270a
Rooms with overload GS
units (2,000)
4 0 0 13* 17
aExcludes homes as specific room data was not available.
*P¼3.14109.
4 Milham and Morgan
measure. This is a highly statistically significant excess over
expectation (Poisson P¼3.1410
9).
We noticed AM radio interference in the vicinity of the
school. Ateacher also reported similar radio interference in his
classroom and in the field near his ground floor classroom. In
May 2007, he reported that 11 of 15 outlets in his classroom
overloaded the G/S meter. An AM radio tuned off station is a
sensitive detector of dirty power, giving a loud buzzing noise in
the presence of dirty power sources even though theAMband is
beyond the bandwidth of the G/S meter.
Cancer Incidence
Three more teachers were diagnosed with cancer in 2005
after the first 11 cancer diagnoses were reported, and another
former teacher (diagnosed out-of-state in 2000) was reported
by a family member employed in the school system. One
cancer was diagnosed in 2006 and two more in 2007. In
the years 1988–2005, 137 teachers were employed at the
school. The 18 cancers in the 16 teachers were: 4 malignant
melanomas, 2 female breast cancers, 2 cancers of the thyroid,
2 uterine cancers and one each of Burkitt’s lymphoma (a type
of non-Hodgkins lymphoma), polycythemia vera, multiple
myeloma, leiomyosarcoma and cancer of the colon,
pancreas, ovary and larynx. Two teachers had two primary
cancers each: malignant melanoma and multiple myeloma,
and colon and pancreatic cancer. Four teachers had died of
cancer through August 2007. There have been no non-cancer
deaths to date.
The teachers’ cohort accumulated 1,576 teacher-years
of risk between September 1988 and June 2007 based on a
12-month academic year.Average age at hire was 36 years. In
2007, the average age of the cohort was 47.5 years.
When we applied total cancer and specific cancer
incidence rates by year, age, sex, race, and adjusted for
cohort ageing, we found an estimate of 6.5 expected cancers,
0.41 melanomas, 0.15 thyroid cancers, 0.22 uterine cancers,
and 1.5 female breast cancers (Table II). For all cancers, the
risk ratio (Observed/Expected¼18/6.5) was 2.78 (P¼
0.000098, Poisson test); for melanoma, (O/E¼4/0.41) was
9.8 (P¼0.0008, Poisson test); for thyroid cancer (O/E¼2/
0.15) was 13.3 (P¼0.0011, Poisson test); for uterine cancer
(O/E¼2/0.22), was 9.19 (P¼0.019, Poisson test).
Table III shows the cancer risk among the teachers by
duration of employment. Half the teachers worked at the school
for less than 3 years (average 1.52 years). The cancer risk
increases with duration of employment, as is expected when
there is exposure to an occupational carcinogen. The cancer risk
ratio rose from 1.7 for less than 3 years, to 2.9 for 3–14 years, to
4.2 for 15þyears of employment. Therewas a positive trend of
increasing cancer incidence with increasing duration of
employment (P¼4.610
10). A single year of employment
at this school increases a teacher’s risk of cancer by 21%.
Using the June 8, 2006 survey data (Table IV), the cancer
risk of a teacher having ever worked in a room with at least
one outlet with an overload GS reading (2000 GS units) and
employed for 10 years or more, was 7.1 (P¼0.00007,
Poisson test). In this group, there were six teachers diagnosed
TABLE II. Risk of Cancer byType AmongTeachers at La Quinta Middle School
Cancer Observed Expected Risk ratio (O/E) P-value
All cancers 18 6.51 2.78* 0.000098
Malignantmelanoma 4 0.41 9.76* 0.0008
Thyroid cancer 2 0.15 13.3* 0.011
Uterus cancer 2 0.22 9.19* 0.019
Female breast cancer 2 1.5 1.34 0.24
All cancers less melanoma 14 6.10 2.30* 0.0025
*P0.05.
TABLE III. Cancer Risk by Duration ofEmployment
Time at school Average time Teachers %of teachers
Cancer
observed
Cancer
expected Risk ratio (O/E) Poisson p
<3 years 1.52 years 68 49.6 4 2.34 1.72 0.12
3^14 years 7.48 years 56 40.9 9 3.14 2.87* 0.0037
15þyears 16.77 years 12 8.8 5 1.02 4.89* 0.0034
Total 137 100 18 6.51 2.78* 0.000098
Positive trend test (Chi square with one degree of freedom¼38.8, P¼4.6110-10).
*P0.05.
High Frequency Voltage Transients and Cancer 5
with a total of seven cancers, and four teachers without a
cancer diagnosis, who were employed for 10 or more years
and who ever worked in one of these rooms. Five teachers had
one primary cancer and one teacher had two primary cancers.
These teachers made up 7.3% of the teachers’ population (10/
137) but had 7 cancers or 39% (7/18) of the total cancers. The
10 teachers who worked in an overload classroom for
10 years or more had 7 cancers when 0.99 would have been
expected (P¼6.810
5 Poisson test). The risk ratio for the
8 teachers with cancer and 32 teachers without cancer, who
ever worked in a room with an overload GS reading,
regardless of the time at the school, was 5.1 (P¼0.00003,
Poisson test). The risk ratio for 8 teachers with cancer and 89
teachers without cancer who never worked in a room with an
overload G-S reading was 1.8 (P¼0.047, Poisson test).
Teachers who never worked in an overload classroom also
had a statistically significantly increased risk of cancer.
A positive dose-response was seen between the risk of
cancer and the cumulative GS exposure (Table V). Three
categories of cumulative GS unit-years of exposure were
selected: <5,000, 5,000 to 10,000, and more than 10,000
cumulative GS unit-years. We found elevated risk ratios of
2.0, 5.0, and 4.2, respectively, all statistically significant, for
each category. There was a positive trend of increasing cancer
incidence with increasing cumulative GS unit-years of
exposure (P¼7.110
10). An exposure of 1,000 GS unityears
increased a teacher’s cancer risk by 13%.Working in a
room with a GS overload (2,000 GS units) for 1 year
increased cancer risk by 26%.
An attributable risk percentage was calculated:
(observed cancers-expected cancers)/observed cancers¼
(186.51)/18¼63.8%.
The fact that these cancer incidence findings were
generated by a single day of G/S meter readings made on June
8, 2006 suggests that the readings were fairly constant
over time since the school was built in 1990. For example, if
the 13 classrooms which overloaded the meter on June 8,
2006 were not the same since the start of the study and
constant throughout, the cancer risk of teachers who ever
worked in the overload rooms would have been the same as
the teachers who never worked in an overload room.
Although teachers with melanoma and cancers of the
thyroid, and uterus, had very high, statistically significant
risk ratios, there was nothing exceptional about their age at
hire, duration of employment, or cumulative GS exposure.
However, thyroid cancer and melanoma had relatively short
latency times compared to the average latency time for all
18 cancers. The average latency time between start of
TABLE IV. Cancer inTeachersWho EverTaught in ClassroomsWith at Least One Overload GS Reading (2000 GSUnits) by Duration ofEmployment
Ever in a room
>2,000 GS units
Employed
10þyears Total teachers Cancers observed Cancers expected Risk ratio (O/E) Poisson p
Yes Yes 10 7a 0.988 7.1* 0.00007
Yes No 30 3a 0.939 3.2 0.054
Total 40 10 1.93 5.1* 0.00003
No Yes 19 2 1.28 1.6 0.23
No No 78 6 3.25 1.8 0.063
Total 97 8 4.56 1.8* 0.047
Grand total 137 18 6.49 2.8* 0.000098
aOne teacher had two primary cancers.
*P<0.05.
TABLE V. Observed and Expected Cancers by Cumulative GS Exposure (GSUnit-Years)
Exposure group <5,000 GS unit-years 5,000 to10,000 >10,000 GS unit-years Total
Average GS unit-years 914 7,007 15,483
Cancers obs. 9 4 5 18
Cancers exp. 4.507 0.799 1.20 6.49
Risk ratio (O/E) 2.01* 5.00* 4.17* 2.78*
Poisson p 0.0229 0.0076 0.0062 0.000098
Positive trend test (Chi square with one degree of freedom¼38.0, P¼7.11010).
*P<0.05.
6 Milham and Morgan
employment at the school and diagnosis for all cancers was
9.7 years. The average latency time for thyroid cancer was
3.0 years and for melanoma it was 7.3 years (with three of the
four cases diagnosed at 2, 5, and 5 years).
An independent analysis of this data set by the
University of Pittsburgh School of Public Health using
OCMAP software supported our findings.
DISCUSSION
Because of access denial, we have no information about
the source, or characterization of the high frequency voltage
transients. We can assume, because the school uses metal
conduit to contain the electrical wiring, that any resultant
radiated electric fields from these high frequency voltage
transients would radiate mainly from the power cords and
from electrical equipment using the power cords within a
classroom.
The school’s GS readings of high frequency voltage
transients are much higher than in other tested places
(Table I). Also, teachers in the case school who were
employed for over 10 years and who had ever worked in a
room with an overload GS reading had a much higher rate of
cancer. They made up 7.3% of the cohort but experienced
39% of all cancers.
The relatively short latency time of melanoma and
thyroid cancers suggests that these cancers may be more
sensitive to the effects of high frequency voltage transients
than the other cancers seen in this population.
In occupational cohort studies, it is very unusual to have
a number of different cancers with an increased risk. An
exception to this is that cohorts exposed to ionizing radiation
showan increased incidence of a number of different cancers.
The three cancers in this cohort with significantly elevated
incidence, malignant melanoma, thyroid cancer and uterine
cancer, also have significantly elevated incidence in the large
California school employees cohort [Reynolds et al., 1999].
These cancer risk estimates are probably low because 23
of the 137 members of the cohort remain untraced. Since
exposure was calculated based on 7 days a week for a year,
this will overstate the actual teachers’ exposure of 5 days
a week for 9 months a year.
We could not study field exposures in the classrooms
since we were denied access to the school.We postulate that
the dirty power in the classroom wiring exerted its effect by
capacitive coupling which induced electrical currents in the
FIGURE 2. Oscilliscope display of 60 Hz current distortedwith high frequencies taken between EKG patches applied to the ankles
of aman standingwith shoes on at a kitchen sink. [Color figure can be viewed in the online issue,which is available atwww.interscience.
wiley.com.]
High Frequency Voltage Transients and Cancer 7
teachers’ bodies. The energy that is capacitively coupled to
the teachers’ bodies is proportional to the frequency. It is this
characteristic that highlights the usefulness of the G/S meter.
High frequency dirty power travels along the electrical
distribution system in and between buildings and through the
ground. Humans and conducting objects in contact with the
ground become part of the circuit. Figure 2 [Havas and
Stetzer, 2004, reproduced with permission] shows an
oscilloscope tracing taken between EKG patches on the
ankles of a man wearing shoes, standing at a kitchen sink.The
60 Hz sine wave is distorted by high frequencies, which
allows high frequency currents to oscillate up one leg and
down the other between the EKG patches.
Although not demonstrated in this data set, dirty power
levels are usually higher in environments with high levels of
60 Hz magnetic fields. Many of the electronic devices which
generate magnetic fields also inject dirty power into the
utility wiring. Magnetic fields may, therefore, be a surrogate
for dirty power exposures. In future studies of the EMFcancer
association, dirty power levels should be studied
along with magnetic fields.
The question of cancer incidence in students who
attended La Quinta Middle School for 3 years has not been
addressed.
CONCLUSION
The cancer incidence in the teachers at this school is
unusually high and is strongly associated with exposure to
high frequency voltage transients. In the 28 years since
electromagnetic fields (EMFs) were first associated with
cancer, a number of exposure metrics have been suggested. If
our findings are substantiated, high frequency voltage transients
are a newand important exposure metric and a possible
universal human carcinogen similar to ionizing radiation.
ACKNOWLEDGMENTS
The authors would like to thank The La Quinta,
California middle school teachers, especially Gayle Cohen.
Thanks also to Eric Ossiander, Dr. Raymond Neutra, Dr.
Gary Marsh and Mike Cunningham and Dr. Louis Slesin.LM
thanks Diana Bilovsky for editorial assistance.
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8 Milham and Morgan
