A New Electromagnetic Exposure Metric

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


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 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


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


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].


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.


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


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.


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.


4 Milham and Morgan

measure. This is a highly statistically significant excess over

expectation (Poisson P¼3.1410


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


TABLE III. Cancer Risk by Duration ofEmployment

Time at school Average time Teachers %of teachers




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).


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


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


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.


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).


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.


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


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.


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



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.


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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