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Attitudes about electric and magnetic fields: do scientists and other risk experts perceive risk similarly? (Features).

Introduction

Extremely low frequency electric and magnetic fields (EMFs) are produced by power lines, electrical wiring, and electrical equipment. Virtually everyone in a modem society is exposed to EMFs because they occur whenever electricity is used. Turning on a light switch, using electrical appliances, and even turning off an alarm clock are examples of EME exposure sources (U.S. Department of Energy & National Institute of Environmental Health Sciences, 1995). Over the past several years, scientific studies have raised questions about possible adverse health effects linked to EMFs (Coleman, Bell, Taylor, & Zakelj, 1989; Feychting & Ahlbom, 1993; Fulton, Cobb, Preble, Leone, & Forman, 1980; London, Thomas, Bowman, Sobel, Cheng, & Peters, 1991; Myers, Clayden, Cartwright, & Cartwright, 1990; Savitz, Wachtel, Barnes, John, & Tvrdik, 1988; Tomenius, 1986; Wertheimer & Leeper, 1979). Biologically, EMFs create weak electric currents in the bodies of people and animals. Usually, the current is too weak to penetrate cell me mbranes and exists only between the cells, but there is a potential for EMFs to cause biological effects. Some scientists argue that it is impossible for EMEs to have any important effects, but others disagree. The dissenters argue that, just as a trained ear can pick up a familiar voice in a crowd, so might a cell respond to an induced current as a signal, even though the EMF-created current is lower in intensity than the background noise of the body's own natural currents (NIOSH & U.S. Department of Energy, 1996).

Further fueling the debate are opposing reports published by several scientific agencies. Reports by the National Academy of Sciences (NAS) (1996) and the National Cancer Institute (NCI) (Linet et al., 1997) concluded that there is no clear, convincing evidence that exposure to electric power lines and electric power appliances are a threat to human health at the exposure levels typically found in personal residences. The National Institute of Environmental Health Sciences and the U.S. Department of Energy (1999), however, concluded that extremely low frequency (ELF) EME exposure cannot be recognized at this time as entirely safe because there is weak scientific evidence that exposure may pose a leukemia hazard. The report states that although epidemiological evidence suggests this link, mechanistic studies and the animal toxicology literature fail to demonstrate any consistent pattern across studies.

Based on the inconclusiveness of data on EMF effects, what are the perceptions of EMF specialists attending a bioelectromagnetics conference? Several studies have examined perceptions of known health risks among scientists and other government officials (Barke, Jenkins-Smith, & Slovic, 1997; Flynn, Slovic & Mertz, 1994; Johnson & Slovic, 1995; Matthies, Hoeger, & Guski, 2000). These studies have compared risk perceptions by gender and race, but only a few studies have identified other factors, such as job affiliation effects, that may play an important role in shaping risk perceptions (Kivimaki, Kalimo, & Salminen, 1995; Kraus, Malmfors, & Slovic, 1992; Slovic, Malmfors, Krewski, Mertz, Neil, & Bartlett, 1995). This study seeks to identify whether gender, level of education, job type, age, or length of employment may explain differences among experts' perceptions of the risks attributable to EMFs.

Methods

Surveys were sent to 163 participants at the 1997 annual Department of Energy Contractors Meeting on Electric and Magnetic Fields. The survey was distributed via e-mail in March 1998. Approximately one-half of the participants (49 percent, n = 81) returned the survey. The remainder could not be contacted because of invalid addresses (15 percent, n = 24), withdrew from the study because of job reassignments or potential conflicts of interest (e.g., one individual was writing a report to Congress) (5 percent, n=9), or did not respond even after a second survey was sent out (30 percent, n = 49). Additional demographic information is presented in Table 1.

All of the respondents spent some time each week talking about and answering questions regarding electric and magnetic fields. On average, the participants reported spending five hours per week communicating about electric and magnetic fields. In addition, they reported that they were asked between one and 25 questions a week about electric and magnetic fields, with the average being three questions per week.

As part of a larger survey investigating attitudes concerning EMFs, several questions were used to assess independent variables in the present investigation. Participants were asked to indicate their gender and highest level of education (high school degree, undergraduate degree, master's level degree, Ph.D.) using forced-choice response categories. Participants were asked to indicate their job type as workers in either a government, a university, a private, or a utility setting. Age was determined from respondents' listed date of birth, and participants were asked how many years they had been working in the field of bioelectromagnetics. Both of the latter questions were asked in an open-choice response format.

The dependent measure was recorded on a seven-point Likert scale designed to assess respondents' level of agreement with the following statement: "Recent investigations by the National Academy of Sciences and the National Cancer Institute that indicate EMF is not a problem are accurate." Anchors were placed on the response scale ranging from 1, disagree (indicating that EMFs are, in fact, dangerous), to 7, agree (indicating agreement with NAS and NCI statements that EMFs are not a problem, and therefore indicating that EMFs are not dangerous).

Design and Analysis

In order to determine how gender, highest level of education, job type, age, and length of employment influence perceptions that bioelectromagnetics specialists have of the risks attributable to EMFs, regression analysis was performed with the risk statement as a criterion variable. The order of entry into this analysis was based on previous research demonstrating that gender and education are consistent predictors of risk perceptions (Finucane, Slovic, Mertz, Flynn, & Satterfield, 2000; Lowe, Borland, Stanton, Baade, White, & Balanda, 2000; Barke, Jenkins-Smith, & Slovic, 1997; Johnson & Slovic, 1995; Flynn, Slovic, & Mertz, 1994); the effects of job type, age, and length of employment are not as well documented. Therefore, gender and education were entered into the analysis before job type, age, and length of employment, respectively. Because gender and job type were categorical variables, they were dummy-coded for entry into the analysis with males and government job types serving as the base groups.

Results

Means, standard deviations, and response frequency contingency values are presented in Table 2. In order to simplify the presentation of the data given by the contingency values, categories for age and years of employment were created based upon median splits, and the dependent variable was categorized into three categories comprising those who disagreed (chose from 1 to 3 on the Likert scale), indicated neutrality (chose 4), or agreed (chose from 5 to 7) with the statements that EMFs are not a problem.

The results of regression analysis demonstrated that level of education was a significant predictor of agreement with the NAS and NCI statements that EMFs are not a problem (see Table 3). Participants reporting higher levels of education were more likely to agree with the NAS/NCI statements that EMFs are not a problem. In addition, those who held jobs in the utility industries reported greater agreement with this statement than did those in government positions. Overall, the final equation accounted for nearly 37 percent of the variance in perceptions regarding the accuracy of statements indicating that EMFs are not a problem.

Discussion

The scientists and other risk experts in this study appeared to feel more strongly about risk issues that pertain to their employment characteristics. As previously noted, only a few studies have demonstrated this finding. One such study was conducted among toxicologists in the United States and another among toxicologists in Canada (Slovic et al., 1995; Kraus et al., 1992). The Canadian study indicated that Canadian toxicologists had far lower perceptions of risk for all hazards and more favorable attitudes toward chemicals than did the Canadian public. The public's attitudes toward chemicals were quite negative and showed the same lack of dose-response sensitivity found in the U.S. study.

Scientists and other risk experts in this study appeared to differ about the conclusion of the NAS report and the NCI findings. Those who worked at utility companies, in particular, tended to agree more strongly with the statement that EMFs are not a problem.

Certainly, job affiliation effects may have important implications for risk communication given that if one works in a particular industry, as discerned in this study one's views may be different or biased. This bias may be conveyed to the public, which often is unaware of the characteristics of the presenter and the history of the risk issues.

In previous studies, gender has been found to be an important predictor regarding risk statements. Studies reveal a far greater concern about environmental hazards among women than among men. White males often perceive risks as much smaller and more acceptable than do other groups (DeJoy, 1992; Gutteling, & Wiegman, 1993; Stern, Dietz, & Kalof, 1993). Those findings corroborate the results of the present investigation. Though gender was not a statistically reliable predictor of risk perceptions in this investigation, there is a trend for females to perceive greater risks attributable to EMFs. The relationships between gender and risk perceptions, therefore, deserve further examination.

Although the findings of this paper suggest greater attention should be given to the role of risk perceptions based on employment and demographic characteristics, the sample reporting in this study is small and may not be generalizable to all scientific specialists. Certainly data collected from participants at a bioelectromagnetics conference may or may not be representative of overall scientific opinion. It should also be mentioned that there were trends in the data, that, while not statistically reliable, warrant the re-examination of gender and years of job tenure as potential predictors of risk perceptions in the present context. The small sample size used in the investigation may not have yielded the statistical power needed to demonstrate significance, increasing the likelihood of Type II error.

Conclusion

As issues in environmental health become more complex and uncertain, risk perception and its role in risk communication will undoubtedly play an increasingly important role. Future studies should look at the impact of risk perception on risk communication and determine if messages may be distorted by factors such as job characteristics, gender, and race before a decision can be reached by the recipient of the risk message about the validity of the risk message. Based on the history of risk communication, environmental health professionals should be aware that the public may hesitate to respond to risk messages, depending on the agency or company that is being represented. It is best in the case of an unknown risk to provide all of the data, in a clear and unbiased format, and to let members of the public make their own choice as independent, educated risk consumers.
TABLE 1

Demographic Characteristics

Variable n

Gender

 Male 59
 Female 21
 DNR (a) 1

Job classification

 Engineer 15
 Other 13
 Manager 9
 Professor 8
 Consultant 7
 Scientist 7
 Environmental scientist 5
 Industrial hygienist 5
 Epidemiologist 3
 Environmental inspector 2
 Biologist/biophysicist 2
 Physician 2
 DNR (a) 2
 Toxicologist 1

Sector of employment

 Government 21
 Private 20
 University 16
 Utility 11
 Other 10
 DNR (a) 3

Highest education level

 Ph.D. 38
 Master's degree 24
 Undergraduate degree 12
 High school degree 2
 DNR (a) 5

Age

 50 years or older 42
 Younger than 50 years 33
 DNR (a) 6

Years of employment at
 current job

 Less than 13 years 42
 13 or more years 37
 DNR (a) 2

(a) DNR = did not respond.

TABLE 2

Mean Response Values and Frequency of Responses by Agreement with the
Survey Statement Submitted to Participants (a)

 Response Frequencies

 Mean (SD) Disagree Neutral Agree

Gender

 Male 3.29 (2.08) 32 4 19
 Female 2.74 (2.00) 14 1 4
 Total 3.15 (2.06) 46 5 23

Education

 High school 1.00 (0.00) 2 0 0
 4-year degree 3.25 (2.22) 7 0 5
 M.S. degree 3.46 (2.21) 14 1 9
 Ph.D. 3.06 (1.92) 20 4 8
 Total 3.17 (2.06) 43 5 22

Job type

 Government 2.26 (1.63) 16 1 2
 Private 3.21 (1.90) 12 2 5
 University 2.69 (2.06) 9 2 2
 Utility 5.45 (1.37) 1 0 10
 Total 3.21 (2.06) 38 5 19

Age

 <50 years 3.77 (2.08) 14 2 14
 50+ years 2.82 (1.99) 28 3 8
 Total 3.23 (2.07) 42 5 22

Years of employment

 Less than 13 3.58 (2.16) 22 1 17
 13 or more 2.70 (1.85) 23 4 6

 Total 3.18 (2.06) 45 5 23

(a) The survey statement read as follows: "Recent investigations by the
National Academy of Sciences and the National Cancer Institute that
indicate EMF is not a problem are accurate."

TABLE 3

Ordinary Least Squares Multiple Regression Analysis Predicting Agreement
with Survey Statement Submitted to Participants (a)

Variables Beta SE Beta Standardized p
 Beta

Gender -0.98 0.54 -0.21 .07
Education 0.97 0.31 0.41 <.01
Univ. vs. gov. job type 0.81 0.67 0.16 .23
Private vs. gov. job type 0.95 0.57 0.22 .10
Utility vs. gov. job type 4.05 0.69 0.75 <.01
Age -0.01 0.02 -0.06 .64
Years at present job -0.06 0.03 -0.24 .05
Constant 0.60 1.36 .66
Multiple R 0.67
[R.sup.2] 0.45
Adjusted [R.sup.2] 0.37
Standard error (SE) 1.63

F = 5.79.

df = 7.50.

p <.001.

(a) The survey statement read as follows: "Recent Investigations by the
National Academy of Sciences and the National Cancer Institute that
indicate EMF is not a problem are accurate."


REFERENCES

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Gutteling, J.M., & Wiegman, O. (1993). Gender-specific reactions to environmental health hazards in the Netherlands. Sex Roles, 28(7-8), 433-447.

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Kivimaki, M., Kalimo, R., & Salminen, S. (1995). Perceived nuclear risk, organizational commitment, and appraisals of management: A study of nuclear power plant personnel. Risk Analysis, 15(3), 391-395.

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Myers, A., Clayden, A.D., Cartwright, R.A., & Cartwright, S.C. (1990). Childhood cancer and overhead powerlines: A case-control study. British Journal of Cancer, 62(1008), 1-14.

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NIOSH, National Institute of Environmental Health Sciences, & U.S. Department of Energy. (1996). EMF in the workplace: Questions and answers: Electric and magnetic fields associated with the use of electric power. Washington, DC: U.S. Government Printing Office.

National Institute of Environmental Health Sciences & U.S. Department of Energy. (1999). NIEHS report on health effects from exposure to power-line frequency electric and magnetic fields (NIH Publication Number 99-4493, pp. 1-67). Prepared in response to the 1992 Energy Policy Act (PL 102-486, Section 2118). Washington, DC: U.S. Government Printing Office.

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Slovic, P., Malmfors, T., Krewski, D., Mertz, C.K., Neil, N., & Bartlett, S. (1995). Intuitive toxicology II expert and lay judgments of chemical risks in Canada. Risk Analysis, 15(6), 661-675.

Stern, P.C., Dietz, T., & Kalof, L. (1993). Value orientations, gender, and environmental concerns. Environment and Behavior, 25(3), 322-348.

Tomenius, L. (1986). 50 Hz electromagnetic field environment and the incidence of childhood tumors in Stockholm County. Bioelectromagnetics, 7(2), 191-207.

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Corresponding Author: Shari McMahan, Associate Professor, Health Science, Division of Kinesiology and Health Promotion, California State University-Fullerton, PO. Box 6870, Fullerton, CA 92834-6870. Email: <smcmahan@fullerton.edu>.
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Author:Meyer, Jon'a
Publication:Journal of Environmental Health
Geographic Code:1USA
Date:Dec 1, 2002
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