1 Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
2 School of Public Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia.
3 Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
4 Department of Biostatistics, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
5 Current affiliation: Foodborne and Diarrheal Diseases Branch, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA.
Received for publication August 23, 2001; accepted for publication November 14, 2002.
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ABSTRACT |
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electromagnetic fields; occupational exposure; polychlorinated biphenyls; prostatic neoplasms
Abbreviations: Abbreviations: EMF(s), electromagnetic field(s); PCB(s), polychlorinated biphenyl(s).
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INTRODUCTION |
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Among the environmental factors that have been suggested as possible causes of prostate cancer are exposures to electromagnetic fields (EMFs) and polychlorinated biphenyls (PCBs). Electric power systems are the major sources of EMFs (3). PCBs, a mixture of more than 209 different chlorinated biphenyl congeners, were widely used as dielectric fluid from the 1930s to the 1970s and can still be found in some capacitors. Exposures to EMFs and some PCBs (those having dioxin-like effects) may be associated with prostate cancer by their causing a decrease in melatonin levels (4, 5). Melatonin is considered an oncostatic agent that may confer protection by reducing the levels of certain hormones (4, 6, 7). Reduced melatonin levels may result in increased tes-tosterone levels, thereby increasing the cancer risk of tissues that are dependent on this hormone for growth (e.g., the prostate gland) (4). Certain PCBs display estrogenic effects, thus reducing testosterone levels (5, 8, 9). Therefore, PCBs may be associated with a reduction in the growth of prostate tumor cells.
Occupational exposures to EMFs and PCBs have been found to be related to increased risk of leukemia, brain, and breast cancer in adults (10, 11). However, few studies of these exposures using prostate cancer as the outcome have been reported (12). The purpose of this study was to determine whether occupational exposures to EMFs or PCBs might be associated with an increased risk of prostate cancer mortality.
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MATERIALS AND METHODS |
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Cases and controls
Members of the electrical workers cohort were eligible for selection as cases if their underlying cause of death was recorded on the death certificate as prostate cancer (International Classification of Diseases, Ninth Revision, code 185).
Controls were chosen at random from persons in the cohort who were at risk of becoming a case (the risk set) within 1 year of the cases death. Five controls per case were sampled and matched to the case on age at risk (i.e., ±6 months from age at death from prostate cancer). A total of 129 control observations were used as repeated control observations for two, three, or four different cases. Thirty-two cases were also used as controls for prior cases, with two of these repeating twice as controls for different cases.
Assessment of exposures
Exposure to EMFs was determined from a job exposure matrix, which has been described in detail elsewhere (14). Briefly, an occupational classification system was first developed to categorize 25,000 raw job titles. Job titles, determined by the longest-held job during each year of employment, were used to link individual workers to specific exposures. Workers performing similar duties in similar environments were grouped into the same occupational categories. Next, each job title was abstracted from the work history records of the cohort and assigned to one of the 28 occupational categories.
From each of the occupational category cells, workers were randomly selected for personal EMF measurements, which were used to create a job exposure matrix (10). The group average measurement was assigned to individual workers. Cumulative exposure to EMFs was obtained by applying the formula "intensity multiplied by duration and summed across all jobs" and was given in micro-Tesla-years (µT-years) (10, 13).
A panel of industrial hygienists, department managers, and long-term employees assessed the potential for PCB exposure for each of the occupational categories based on their expert judgment as to the likelihood that workers in that category would have direct contact with the agent (10) and the frequency and duration of contact, if it occurred. Actual measurements were not taken. Research personnel and company staff performed walk-through surveys at each company during 1991 and 1992 to further assess exposure to PCBs. Cumulative exposure to PCBs (in hours) was obtained by summing the products of the frequency and duration of exposure over the individuals employment history.
Other variables
In the original cohort, sunlight exposure was ascertained in only three of the five companies: the Tennessee Valley Authority, Pacific Gas and Electric, and Virginia Power. The original exposure values were reassigned for a later study, using the top 10 job titles within each company-specific occupational category, and workers were classified as frequently exposed, intermittently exposed, and unexposed to sunlight (15). For our study, the age-matched association for sunlight exposure and prostate cancer mortality and assessment of confounding were conducted only for these three companies. Two types of variables for sunlight were created: 1) any chronic exposure versus no chronic exposure and 2) cumulative years of chronic exposure to sunlight. Physical activity had also been assessed, and a job-exposure matrix was developed using the top 10 job titles within each company-specific occupational category for the Tennessee Valley Authority, Pacific Gas and Electric, and Virginia Power (15). Each occupational category was classified as active or sedentary. Using information on the Tennessee Valley Authority, Pacific Gas and Electric, and Virginia Power, we imputed values for the other two electric utility companies, Carolina Power and Light Company and the Philadelphia Electric Company, and conducted analyses on all five companies. A variable for physical activity was also created as a continuous variable. This variable gave us the cumulative years of physically active work over the duration of employment in the company. Race was classified as White versus non-White. Socioeconomic status was determined from job at the time of hiring and was categorized into upper white-collar, lower white-collar, upper blue-collar, and lower blue-collar. Active work status was dichotomized as having worked during the cases last 2 years of employment with the company versus not having worked during that period.
Potential confounders of the association between EMF or PCB exposure and risk of prostate cancer also included being exposed to light at night and shift work, since these exposures affect pineal function and therefore levels of melatonin (16, 17). Documents describing the duties associated with the various jobs within these electric utility companies revealed that only the occupational category of power plant operator consistently required workers for shift duty (three rotating 8-hour shifts). The occupational category of power plant operator was used as a surrogate for shift work and controlled for in these analyses. It was not possible to interview workers or their family members to obtain information on other possible confounding factors, such as diet, smoking status, and alcohol consumption.
Analytical methods
The goal in statistical modeling was to find the most unbiased exposure-disease relation. Conditional logistic regression was used to analyze these data (18, 19). Multivariate analyses were performed using the PHREG procedure in SAS (version 6.12) (20).
Exposure-response relations were evaluated by categorizing cumulative exposures to EMFs and PCBs. EMF and PCB exposures were divided into deciles and coded as dummy variables. The age-matched and weighted odds ratios (obtained by multiplying the inverse of the variance by the age-matched odds ratio) were plotted against the deciles. For PCBs, categorization started at the 20th percentile because values below that cutpoint were all zero.
Both EMF exposures and PCB exposures were analyzed in categorical and dichotomous forms. When categorized, exposures were divided at the following percentiles: <25, 25<50, 50<75, 75<90, and 90. The top quartiles contained the widest ranges of exposure for EMFs (2.613.3 µT) and PCBs (62056,606 hours), making such categorization necessary. Descriptive statistics and age-matched odds ratios were obtained for the associations between EMFs, PCBs, and each covariate and prostate cancer death. Confounding was assessed through the use of logistic models containing EMF exposure (and then PCB exposure) and each covariate separately. Covariates causing a change of at least 10 percent in the estimated odds ratio for the main exposure variable were considered confounders.
Effect modification was assessed by fitting a model containing variables for EMF exposure and PCB exposure, followed by a model containing EMFs, PCBs, an interaction term (EMFs x PCBs), and all identified confounders. Exposures to PCBs and EMFs were dichotomized at the 90th percentile for this analysis. The presence or absence of effect modification was determined by use of the log likelihood ratio test, with a threshold p value of 0.25 to account for the decreased power in effect modification analyses. The interaction contrast ratio, also known as the "relative excess risk for interaction," was calculated as an additional description of effect modification (21).
Cumulative exposure was examined with lag periods of 0, 5, 10, and 15 years to account for the latency period of prostate cancer. EMF exposure and PCB exposure were both dichotomized at the 90th percentile, and "high exposure" refers to exposures above that cutpoint.
The main exposures, potential confounders, and potential effect modifiers were entered into the multivariate model. All models were nested relative to the relevant comparison model, and variables that did not contribute to the model were deleted. Regression diagnostic procedures were performed on the final models to determine whether any problems related to collinearity existed.
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RESULTS |
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There was a positive association between non-White race and prostate cancer mortality (age-matched odds ratio = 3.69; 95 percent CI: 2.69, 5.05) (table 2). White workers had slightly higher mean EMF exposures, while non-White workers had higher mean PCB exposures. For PCB exposure, White workers in the high-exposure group (9.3 percent) were not at increased risk when compared with White workers with lower exposure levels. In contrast, non-White workers in the high PCB-exposure group (17.0 percent) had 1.4 times the risk of their counterparts with lower exposures. We were not able to assess the race-specific odds ratios for high EMF exposure because of very small numbers in this group. However, for low EMF exposures, non-White workers had 3.9 times the risk of prostate cancer as White workers. Non-White workers were more likely than White workers to be employed in one of three occupational categories: services, heavy vehicle operators, and laborers.
The highest level (90th percentile) of cumulative EMF exposure was positively associated with risk of prostate cancer mortality after adjustment for race (table 3). Exposure to PCBs showed no association with prostate cancer mortality. Minor elevations occurred with exposure at the highest levels (
90th percentile) of the 0- and 5-year lag periods, but these findings were not statistically significant (table 4). The relations were similar regardless of the lag period used. The p value for the trend test was 0.05 for EMF exposure and 0.03 for PCB exposure. The variables assessed for confounding were EMFs, PCBs, physical activity, sunlight exposure, having worked as a power plant operator, race, and socioeconomic status. Race was the only confounder of the association of prostate cancer mortality with EMFs and PCBs. The covariates that remained in the final model were EMFs, race, active work status, PCBs, and the interaction term EMFs x PCBs (table 5).
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Joint effect of EMF and PCB exposure
For assessment of possible interaction between EMFs and PCBs, the joint effect of exposure to high levels of both agents was examined. High exposure was defined as exposure equal to or greater than the 90th percentile for each agent (3.7 µT-years for EMFs and
2,122.8 hours for PCBs), and race and active work status were controlled for in the conditional logistic regression model (table 5).
For the 0-year lag, combined exposure to high levels of both agents had an odds ratio of 1.00, while exposure to high levels of EMFs and low levels of PCBs had an odds ratio of 2.02 and exposure to high levels of PCBs and low levels of EMFs had an odds ratio of 1.47. The interaction contrast ratio for the joint effect of EMFs and PCBs was 1.2. Results were similar for the 5-year lag period. However, only a small number of cases (EMFs, n = 35; PCBs, n = 36) had high levels of exposure to both agents, so these results are imprecise.
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DISCUSSION |
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There has been some skepticism concerning the role of EMFs as cancer-causing agents (22). Four studies, including one that included personal EMF measurements, found no association between exposure to EMFs and prostate cancer among electric utility workers (11, 2325). Our study and that by Theriault et al. (24) are most similar in terms of the numbers of cases and the control for potential confounders, yet the findings diverge. Epidemiologic and experimental studies, while finding associations between EMF exposure (occupational and residential) and several cancers (e.g., brain cancer, leukemia), have not consistently identified a single specific cancer site. Moreover, EMF exposure is believed to be related to prostate cancer through its effects on melatonin and testosterone levels (4, 6), but there is no known physiologic effect on prostate function.
Several studies have investigated or reviewed the incidence of other cancers in workers exposed to PCBs, and our literature review found no consistent evidence that occupational exposure to PCBs was related to an increase in mortality from one or more cancers (26, 27).
Non-White race was independently associated with risk of mortality from prostate cancer. Men classified as non-White were more than 3.5 times as likely to die of prostate cancer as Whites. Black race has been documented in previous studies to be strongly associated with prostate cancer incidence and mortality (28, 29). The reasons for the higher incidence of prostate cancer among Black men, when compared with White men, are not known. The more advanced stage of the disease at the time of diagnosis and the less aggressive treatment given to Black patients contribute to the higher mortality rates (30). Black men generally have lower educational attainment, which potentially reduces their awareness of the need for prostate cancer screening and their access to preventive health care (31). Equal medical care for White and Black prostate cancer patients results in equal outcomes for both groups (32).
A primary objective of our study was to investigate the joint effect of exposure to EMFs and PCBs on prostate cancer mortality. However, there was no evidence of synergy between the two agents. Persons who were exposed to high levels of both EMFs and PCBs had lower risks of prostate cancer than workers who were exposed to only one of the agents, and the interaction contrast ratio was less than zero, which is consistent with an interpretation that the effect of exposure to EMFs and PCBs in combination is subadditive or even antagonistic (21). Exposure to EMFs has been shown to cause a reduction in the level of 6-hydroxymelatonin sulfate, a metabolite of melatonin (33). It is possible that the pathway of PCBs with regard to prostate cancer is a factor other than the melatonin pathway, namely the estrogenic pathway. Estrogens may lower levels of testosterone by suppressing the release of luteinizing hormone-releasing hormone, a product of the hypothalamus (34, 35). If exposure to EMFs decreases melatonin levels, thereby raising the concentration of testosterone, and PCBs have the opposite effect, then combined exposures would result in an antagonistic effect with regard to prostate cancer mortality. The preceding findings must be treated with caution, however, because the numbers of cases with high exposures to EMFs and PCBs were small (n = 35 and n = 36, respectively) and the odds ratios were imprecise.
Our study had several strengths. They included personal measurements of EMF exposure, the relatively large sample size, the reduced potential for selection bias (since controls and cases were selected from the same occupational cohort), and the inclusion of important confounders in the analysis. Results of a study done to determine the accuracy of cancer mortality data showed that the listing of prostate cancer as the underlying cause of death on death certificates was reliable (36), so bias due to errors in the coding of underlying cause of death is likely to have been small.
In epidemiologic studies, questions are often raised about uncontrolled confounding. Factors that may be considered potential confounders in the EMF exposure-prostate cancer mortality study and on which data were not available for adjustment are alcohol consumption, cigarette smoking, and diet. However, lack of control for these variables may not necessarily have resulted in validity problems in our study. Substantial confounding requires that the extraneous factor be a strong risk factor for the outcome relative to the effect of the exposure of interest and also be strongly associated with the exposure (21). While alcohol consumption has been reported to reduce the night peak of melatonin, evidence is lacking for an association between alcohol drinking and prostate cancer and between alcohol drinking and EMF exposure or electric utility work (37, 38). Cigarette smoking has been found to be associated with certain manual occupations (39) and may be associated with common jobs in electric utility companies. However, reported associations between smoking and risk of prostate cancer or smoking and EMF exposure have been inconsistent (40). Inconsistencies in associations also exist between diet and prostate cancer. Some studies have reported borderline-to-small associations between consumption of fat and risk of prostate cancer (41) and small inverse associations between consumption of certain vegetables and prostate cancer (42). Socioeconomic status partially controls for alcohol drinking, smoking, and diet, and we did not observe socioeconomic status to be a confounder. Therefore, it is unlikely that alcohol, smoking, or diet caused serious bias in our study.
Exposure to light at night affects the pineal gland by reducing melatonin levels; therefore, it is a potential confounder (17, 43). It was not possible to control for exposure to light at night, but shift work was used as a surrogate for occupational light at night by adjusting for the occupational category of power plant operators (workers rotating 8-hour shifts). To our knowledge, no attempt has been made to control for shift work in previous studies. Analysis did not reveal the occupational category of power plant operator to be a confounder, but the limitations of the variable must be taken into consideration. Crucial information is missing regarding this occupational category. For example, the frequency of shift work and the percentages of jobs within this occupational category that actually involved shift work are unknown. Data were not collected on nonoccupational exposures to EMFs, PCBs, sunlight, and physical activity, and there was no information on previous or subsequent employment. However, lack of control for these exposures can only produce spurious bias if exposure to any of these factors differed between cases and controls. This study found an association between prostate cancer mortality and high occupational exposure to EMFs but very limited evidence of an association between PCBs and prostate cancer mortality. Because of the inconsistency of previous results, additional studies would be needed before exposure to EMFs could be considered an etiologic factor for prostate cancer.
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ACKNOWLEDGMENTS |
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The authors are grateful to the following people for their contributions: for programming support, Dr. Robert Kleckner and Eileen Gregory; for statistical support, Drs. Gary Koch and Juhaeri; and for other support, Dr. Gary Mihlan.
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NOTES |
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REFERENCES |
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