Environmental Arsenic Exposure from a Coal-burning Power Plant as a Potential Risk Factor for Nonmelanoma Skin Carcinoma: Results from a Case-Control Study in the District of Prievidza, Slovakia

Beate Pesch1, Ulrich Ranft1, Pavel Jakubis2, Mark J. Nieuwenhuijsen3, Andre Hergemöller1, Klaus Unfried1, Marian Jakubis2, Peter Miskovic4, Tom Keegan3 and the EXPASCAN Study Group

1 Medical Institute for Environmental Hygiene at Heinrich Heine University of Düsseldorf, Düsseldorf, Germany.
2 State Health Institute, Prievidza, Slovakia.
3 Department of Environmental Sciences and Technology, Imperial College of Science, Technology and Medicine, London, United Kingdom.
4 State Health Institute, Banska Bystrica, Slovakia.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 
To investigate the risk of arsenic exposure from a coal-burning power plant in Slovakia on nonmelanoma skin cancer (NMSC) development, a 1996–1999 population-based case-control study was conducted with 264 cases and 286 controls. Exposure assessment was based on residential history and annual emissions (Asres1, Asres2) and on nutritional habits and arsenic content in food (Asnut1, Asnut2). Asres1 was assessed as a function of the distance of places of residence to the plant. Asres2 additionally considered workplace locations. Asnut1 was used to calculate arsenic uptake by weighting food frequencies with arsenic concentrations and annual consumption of food items. Asnut2 additionally considered consumption of local products. Age- and gender-adjusted risk estimates for NMSC in the highest exposure category (90th vs. 30th percentile) were 1.90 (95% confidence interval (CI): 1.39, 2.60) for Asres1, 1.90 (95% CI: 1.38, 2.62) for Asres2, 1.19 (95% CI: 0.64, 2.12) for Asnut1, and 1.83 (95% CI: 0.98, 3.43) for Asnut2. No interaction was found between arsenic exposure and dietary and residential data. Other plant emissions could have confounded the distance-based exposure variables. Consumption of contaminated vegetables and fruits could be confounded by the protective effects of such a diet. Nevertheless, the authors found an excess NMSC risk for environmental arsenic exposure.

arsenic; case-control studies; coal; environmental exposure; metals, heavy; neoplasms; power plants; skin neoplasms

Abbreviations: Asnut1, arsenic uptake calculated by weighting food frequencies with arsenic concentrations and annual consumption of food items; Asnut2, same as Asnut 1 multiplied by a factor for consumption of homegrown food; Asres1, arsenic exposure as a function of the distances of the residences to the coal-burning power plant; Asres2, same as Asres1 plus the distances to work locations; CI, confidence interval; EXPASCAN, EXPosure to ArSenic and CANcer Risk in Central and East Europe; NMSC, nonmelanoma skin cancer; OR, odds ratio


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 
The International Agency for Research on Cancer considers arsenic a human carcinogen (1Go). In 1984, the US Environmental Protection Agency classified oral ingestion of inorganic arsenic as a group A human carcinogen, using skin cancer as the endpoint. Evidence was based mainly on historical cases ascertained as a result of medical treatment, occupational exposure to pesticides, and environmental exposure via drinking water. According to updated scientific data, the US arsenic drinking water standard is in flux (2Go). The health impact of arsenic on the development of nonmelanoma skin cancer (NMSC) from contaminated air and soil is studied less intensively.

The cancer risks associated with combustion of arsenic-rich coal to generate power were investigated as part of the European Union-funded project, EXPosure to ArSenic and CANcer Risk in Central and East Europe (EXPASCAN). In 1999, the arsenic content of samples taken from a Slovak power plant was about 500 µg/g in coal and as high as 1,600 µg/g in fly ash (3Go). The district of Prievidza is highly industrialized and ranks among the most polluted areas of Slovakia. Arsenic emissions from a power plant had been identified as a potential health hazard in the 1970s (4Go), when annual arsenic emissions were as high as 200 metric tons (figure 1). To date, an estimated 3,000 metric tons of arsenic have been emitted. The incidence of NMSC in this district has been the highest in Slovakia, with 90 male and 50 female cases per 100,000 in 1997 (age adjusted to the world standard population (5Go)) (6Go).



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FIGURE 1. Annual arsenic emissions from the Electrarne Novaky power station, Slovakia, 1953–2000 (in metric tons per year (t.a); estimated for 1953–1967 and measured for 1967–2000) (9Go).

 
A population-based case-control study was conducted to estimate the NMSC risk associated with arsenic exposure from power station emissions in the district of Prievidza, Slovakia; results are reported in this paper. A structured questionnaire was used to obtain detailed exposure and confounder information. Historical airborne arsenic pollution was modeled (7Go), and arsenic was measured in environmental (soil, dust) and biologic (urine) specimens (3Go).


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 
Study population
From October 1999 until June 2000, the investigation took place in the Slovak district of Prievidza. During 1996–1999, 540 NMSC cases were registered at the Department of Pathology of Bojnice Hospital, which serves as the district reporting center for the National Cancer Institute of Slovakia (SK NCI) (8Go). Cases were eligible if 1) they currently resided in this district; 2) they were not older than age 80 years; and 3) the diagnosis of NMSC as a primary, first tumor was confirmed histologically during 1996–1999. From 374 eligible cases, 328 were randomly contacted, and 264 NMSC cases were recruited.

Population controls were frequency matched to cases on gender and age (5-year classes). Controls were ascertained from a random address sample of the mandatory registry of the district. From the 396 persons contacted, 286 controls were enrolled.

Interviews were conducted in person by trained staff. Informed consent for participation in the study was obtained from the study subjects prior to the interview. A standardized questionnaire was used to ascertain demographic characteristics as well as details on occupational and residential history. Furthermore, questions on dietary habits, outdoor activities, skin type, and smoking habits were asked.

Exposure assessment
Assessment of environmental arsenic exposure was based on a subject's residential history. Every place of residence held for at least 1 year since 1953, when the power plant began operating, was classified in one of three categories according to the distance to the plant: <5 km, 5–10 km, >10 km. The cutoffs for these categories were derived from atmospheric dispersion modeling of the historical pollution pattern (7Go). An arsenic (As) exposure variable, Asres1, was calculated as a function of time and distance according to the dispersion model, based on available emission data (9Go) (refer to the Appendix). A second variable, Asres2, was constructed, which additionally considered the locations of the workplaces (refer to the Appendix).

Estimation of a subject's arsenic exposure from oral uptake (Asnut1) was based on the individual frequencies of consumption of 25 dietary items, taking into account the average annual intake (kg x a-1) and the median arsenic concentration (mg x kg-1) of the items (refer to the Appendix). Information on food intake and arsenic concentrations was obtained from the European Union-funded project PHARE (9Go). Recent data on arsenic in drinking water indicated that more than 50 percent of the analyzed samples were below the detection limit (3.7 µg x liter-1), and one village in the study district had concentrations only slightly higher than 10 µg x liter-1. Since no data on past levels could be identified, the assumption of 1 µg x liter-1 was taken from PHARE (9Go). A second assessment of nutritional exposure to arsenic (Asnut2) classified interviewees as highly exposed if they reported a relevant contribution of homegrown products to their food consumption during the period of the highest arsenic emissions (1970–1989). Simply, a factor of two for self-supplier applied to Asnut1 was sufficient to rearrange the distribution such that mostly self-suppliers contributed to the high-exposure category (refer to the Appendix).

Two approaches were applied to assess occupational exposure to arsenic. First, NMSC risks were estimated for ever-held jobs and the longest-held job in potentially high-risk industries. High-risk industries were selected from the database CAREX, which provides industry-specific estimates for exposure to selected agents (10Go). Relevant arsenic exposures were estimated during the manufacture of wood, glass, and chemicals; in the metal basic and processing industries; in the electricity and electronics industry; and in construction. Additionally, power generation, manufacture of building materials from coal ash, coal mining, and farming were considered local high-risk industries. Second, to obtain an agent-specific exposure assessment, a British job-exposure matrix (11Go) was applied, modified for arsenic in the local industries. Risk estimates were calculated using a cumulative measure of exposure by summarizing the product of duration, probability, and the square of intensity over all jobs held, according to an approach published elsewhere (12Go).

Because of the possible nonlinear relation between arsenic exposure and cancer risk, the variables Asres1, Asres2, Asnut1, and Asnut2 were categorized as "low," "medium," and "high" exposure, with the 30th and 90th percentiles of the distribution of the variable in the total study sample as cutoffs. A corresponding categorization as "no," "low," and "high" exposure was used for occupational exposure variables assessed with a job-exposure matrix, with the 90th percentile as the cutoff between low and high exposure.

Statistical methods
First, the incidence of NMSC for all eligible cases ascertained in 1996–1999 was analyzed by means of standardized incidence ratios, stratified by distance to the plant (<5 km, 5–10 km, >10 km). The number of expected cases in these strata was calculated from the total incidence of NMSC in the district during this period. Additionally, the number of expected cases was calculated from the age-specific cancer incidence rates in Slovakia during 1996 and 1997 (6Go, 8Go). The method of indirect standardization was outlined by Breslow and Day (5Go), and the confidence limits were approximated by using the Wargenau method (13Go).

Second, the risk estimates for possible confounders, other than age and gender, were calculated as odds ratios by using conditional regression analysis with the PHREG procedure in SAS software, version 8.1 (14Go). All models were conditional on gender and age (dichotomized with age 60 years as the cutoff). To check for confounding, risk factors were inspected for an association with both NMSC development and environmental arsenic exposure.

Third, the risk estimates for environmental arsenic exposure were calculated. The variables Asnut1 and Asnut2 were analyzed in a corresponding conditional regression model controlled for age and gender. For the distance-related variables Asres1 and Asres2, recruitment of controls that did not precisely correspond to the spatial distribution of the general population would have biased the risk estimates. To estimate the selection bias, two series of crude odds ratios were calculated in strata by distance, age, and gender, with the study controls and the general population serving as reference for the cases (table 1). This stratification revealed an oversampling of controls in the exposed region (the distance category <5 km), which would have resulted in underestimation of the risk of environmental arsenic exposure. Because the true distribution of the reference population with respect to age, gender, and distance was known, a resampling procedure could be applied to the control group to correct for the selection bias (the SURVEYSELECT procedure, method URS, in SAS software, version 8.1 (14Go)) (refer to the Appendix). By means of a bootstrap method, adjusted odds ratios, together with their standard errors, were estimated with conditional and unconditional regression models (LOGISTIC procedure in SAS software, version 8.1 (14Go)), which included the distance-based variables Asres1 and Asres2, respectively (refer to the Appendix).


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TABLE 1. Crude odds ratios as estimates of the relative risk of nonmelanoma skin cancer associated with environmental arsenic exposure* in Prievidza District, Slovakia, EXPASCAN study, 1999–2000

 

    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 
NMSC incidence
Table 2 shows the variation in NMSC incidence by distance to the power plant. Compared with NMSC incidence in the district, the incidence was 21 percent higher in the vicinity of the power plant (standardized incidence ratio = 1.21, 95 percent confidence interval (CI): 0.91, 1.60), with a decreasing trend to a standardized incidence ratio of 0.76 (95 percent CI: 0.63, 0.92) in the most distant part. When related to Slovak NMSC incidence, the incidence was 35 percent higher (standardized incidence ratio = 1.35, 95 percent CI: 1.22, 1.50) in the district of Prievidza, with a standardized incidence ratio of 1.64 (95 percent CI: 1.24, 2.17) in the vicinity of the power plant. The observed cases were based on all primary and first NMSC cases; patients with secondary NMSC were excluded. The national rate includes all primary NMSC cases. Therefore, the corresponding standardized incidence ratios calculated from the NMSC incidence in Slovakia underestimated the relative NMSC incidence in the Prievidza District, but the spatial trend of standardized incidence ratios by distance to the plant was not likely to be confounded.


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TABLE 2. Nonmelanoma skin cancer incidence ratios, by distance to the power plant in Prievidza District, Slovakia, with expected cases calculated from the incidence in the district and from the incidence in the country, EXPASCAN study, 1999–2000

 
Basic characteristics of the study population
Demographic and other characteristics of the study population are outlined in tables 3 and 4. Ninety-one percent of the NMSC was basal cell carcinoma in comparison to an average of 84 percent in Slovakia (15Go). Skin sensitivity and ultraviolet radiation exposure were confirmed as NMSC risk factors. A pigmented skin protects against ultraviolet radiation exposure; therefore, persons who are fair skinned, have freckles, sunburn easily, and have light-colored eyes and hair are more prone to develop skin cancer. Tobacco smoking is not an established NMSC risk factor. Ever smoking was associated with an odds ratio of 0.54 (95 percent CI: 0.32, 0.91) for men and an insignificant excess risk of 1.74 (95 percent CI: 0.91, 3.33) for women. Risk estimates, calculated for lifetime cigarette smoking, showed similar effects. A recall bias for this "protective" effect in men has to be considered. Risk estimates for regular versus rare (less than once a week) uptake revealed insignificantly lower odds ratios for fresh fruits (odds ratio (OR) = 0.56, 95 percent CI: 0.29, 1.08) or vegetables (OR = 0.68, 95 percent CI: 0.37, 1.23).


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TABLE 3. Selected characteristics of nonmelanoma skin cancer cases and controls, Prievidza District, Slovakia, EXPASCAN study, 1999–2000

 

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TABLE 4. Odds ratios for potential confounders of environmental arsenic exposure and nonmelanoma skin cancer, Prievidza District, Slovakia, EXPASCAN study, 1999–2000

 
Occupational exposure to arsenic
Occupational arsenic exposure was considered a potential confounder because a chemical plant and a company that manufactures building materials from coal ash are located in the vicinity of the power station. A large fraction of men had been working as coal miners. Table 5 shows the risk estimates for working in potentially high-risk jobs, but no excess risk was found for being employed as a coal miner or chemical worker. Significant excess risks were estimated for men whose longest-held job was in agriculture (OR = 4.91, 95 percent CI: 1.03, 23.81) and for women ever working in metal processing (OR = 5.01, 95 percent CI: 1.07, 23.56), but these findings were based on small numbers. Occupational exposure to arsenic, assessed by using a modified British job-exposure matrix (11Go), was not associated with NMSC risk (OR = 1.28, 95 percent CI: 0.87, 1.88 for medium exposure and OR = 0.75, 95 percent CI: 0.41, 1.37 for high exposure).


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TABLE 5. Odds ratios for occupational exposure in a priori high-risk jobs and for arsenic exposure* as potential confounders for environmental arsenic exposure and nonmelanoma skin cancer, Prievidza District, Slovakia, EXPASCAN study, 1999–2000

 
Environmental arsenic
Because no strong confounder for environmental arsenic exposure could be found, the logistic regression models for environmental arsenic exposure controlled for age and gender only. The resampling procedure was used to correct for a selection bias, and table 6 presents the risk estimates for Asres1 with and without interaction terms for distance and gender. Without an interaction term, Asres1 was associated with significant excess risks of 1.72 (95 percent CI: 1.42, 2.08) for medium exposure and 1.90 (95 percent CI: 1.39, 2.60) for high exposure. When interactions were included, the interaction term was significant for gender and medium exposure (p < 0.01), with an excess risk for men (OR = 2.41, 95 percent CI: 1.85, 3.14) but not women (OR = 1.28, 95 percent CI: 0.79, 1.99). Incorporation of the location of the workplaces into the model (Asres2) yielded similar effects, and both variables were highly correlated (Spearman correlation coefficient = 0.91, p < 0.0001).


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TABLE 6. Odds ratios for the association of environmental arsenic exposure with the development of nonmelanoma skin cancer in Prievidza District, Slovakia, EXPASCAN study, 1999–2000*

 
Nutrition and drinking habits were assessed by using a semiquantitative food frequency questionnaire. No significant association was found between individual food items and NMSC risk. For arsenic exposure assessed with these dietary data, Asnut1 was not associated with an excess risk (OR = 0.86, 95 percent CI: 0.59, 1.26 for medium oral uptake of arsenic and OR = 1.19, 95 percent CI: 0.64, 2.12 for high oral uptake of arsenic) (table 7). When consumption of local vegetables and fruits was additionally considered (Asnut2), the odds ratio increased to 1.83 (95 percent CI: 0.98, 3.43) for high exposure, with a marginally significant trend for increasing uptake.


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TABLE 7. Odds ratios as estimates of the risk of environmental arsenic exposure on the development of nonmelanoma skin cancer in Prievidza District, Slovakia, EXPASCAN study, 1999–2000*

 
To check for an interaction between the two exposure measures from dietary and residential data, a conditional regression model was applied to Asres1, Asnut2 (both as categorical variables) and to the product of Asres1 and Asnut2 as the interaction term, in which the low, medium, and high exposure categories were quantified as 1, 2, and 3, respectively. When the resampling procedure was used to correct for the selection bias, the risk of environmental arsenic exposure was found to be independently represented by "arsenic-contaminated environment" (Asres1) and "arsenic-contaminated food" (Asnut2). Both exposure variables were not correlated (Spearman correlation coefficient = -0.01, p < 0.90).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 
NMSC incidence in the study region
Whereas most cancer registries exclude NMSC, the National Cancer Institute of Slovakia provides NMSC incidence rates since 1968, and Prievidza District has ranked the highest in Slovakia (16Go). A historical cancer database for this district showed that NMSC incidence rates represented 73 males and 58 females within 7.5 km of the power plant but 45 males and 39 females per 100,000 population (world standard (5Go)) in the distant region during 1977–1991 (3Go). Age-adjusted incidence rates for both squamous cell carcinoma and basal cell carcinoma of the skin were elevated in the vicinity of the power plant, but lung and bladder cancer rates were not (3Go).

On the basis of all eligible NMSC cases in 1996–1999 ascertained for this study, an increased NMSC incidence in the vicinity of the power plant (<5 km) was confirmed in comparison to the distant part (>10 km) of the district. In the most-populated medium region (5–10 km), NMSC incidence was also high in men of productive age (<60 years), indicating a possible residual confounding of occupational exposure, which was supported by a significant interaction between gender and medium distance for Asres1 and Asres2. When the spatial trend in NMSC incidence was attributed to environmental arsenic exposure, confounding by the emission of large quantities of other agents from the power plant as well as from a nearby chemical plant could not be excluded.

Study design and exposure assessment
To investigate the risk of arsenic exposure in Prievidza District, Slovakia, on NMSC development and to control for potential confounders, a population-based case-control study was conducted with 264 cases and 286 controls. For these study subjects, information on residential and workplace history and on dietary habits was used to assess environmental exposure to arsenic from the emissions of a coal-burning power plant.

A basic concern in epidemiologic studies is potential selection bias in recruiting study subjects. In the present study, response rates (80 percent for cases, 72 percent for controls) were similar or even better than those for other population-based studies (17Go). Controls were enrolled from a random address sample of the district population, but the spatial distribution of the last places of residence of the ascertained controls did not correspond to that of the general population. Because of the small numbers in the strata by distance, gender, and age, a variation by chance should be considered. For cases, we found no indication of an analogous mismatch between the spatial distributions of enrolled patients and all eligible cases. Deviations in the spatial distribution of the places of residence introduced a serious estimation bias for distance-related exposure variables. Because about half of the study population occupied their current homes for about 30 years, this "immobile" population could not dilute such a bias during a lifetime residential history. Therefore, a resampling procedure for the control sample, stratified by distance, age, and gender with respect to the "true" population figures, was applied to calculate "corrected" risk estimates. The age- and gender-adjusted odds ratios closely resembled the standardized incidence ratio estimates from the incidence study.

The pathways by which a population could have been exposed to arsenic were many and varied (18Go). Non-differential exposure misclassification, resulting from difficulties in estimating complex exposure patterns, can bias risk estimates toward the null value. Crude categorization of the study region into three areas based on distance is associated with loss of specificity. The individual arsenic dose for a study subject cannot be assessed precisely by means of a questionnaire or by using environmental data, particularly for past exposure. Therefore, air pollution modeling, different environmental data (arsenic emission data, arsenic in food items), and different exposure assessment approaches (distance-related measures, oral-uptake measures) were applied to obtain conclusive evidence with respect to the cancer incidence analysis and other results of the project. Arsenic levels in soil, although now low, were higher in the vicinity of the plant (geometric mean, 43 mg/kg) and fell by 40 percent after a distance of 5 km (3Go). Current arsenic concentrations in garden soils correlated with urinary arsenic concentrations in interviewees (Pearson's correlation coefficient = 0.21, p = 0.01) (3Go). A historical hair analysis of children during the period of the greatest arsenic emissions showed threefold higher arsenic concentrations in the vicinity of the plant (19Go).

Oral exposure via drinking water and contaminated food is considered the most important pathway of inorganic arsenic exposure for NMSC development. Asnut1 was calculated as the oral uptake of arsenic based on the individual frequencies of consumption, the arsenic concentrations in food items, and the annual amounts of these items consumed. The reliability of food frequency data is limited (20Go, 21Go). The arsenic concentrations in food, as provided in proj-ect PHARE, were for total arsenic (9Go). Annual consumption data were estimated for the population of central Slovakia, which includes the study region. This index was not associated with an excess risk for arsenic. Limited reliability of these data could have driven the risk estimate toward the null value; furthermore, a diet rich in fruits and vegetables can be protective and thus have masked an adverse arsenic effect. Asnut1 reflects probably more the protective effects of a healthful diet (milk, potatoes, fruits, and vegetables contribute to this variable considerably) than contamination with inorganic arsenic.

The chemical speciation of arsenic is important for its health effects. Most food items contain more inorganic than organic arsenic (22Go). Organic arsenic was found to be less toxic than inorganic arsenic, but the impact of the methyl-ated compounds on carcinogenesis has been revised (23Go). Additional consideration of the consumption of local food, which may have been contaminated by arsenic emissions from the power plant, increased the odds ratio, and a dose-response trend was found. In the analysis of urinary arsenic concentrations, persons living in the vicinity of the power plant had significantly higher total urinary arsenic concentrations (3Go). In addition, persons who reported consuming homegrown fruits and vegetables had significantly higher levels of urinary monomethylarsonic acid.

Whereas the impact of arsenic in drinking water has been the focus of many epidemiologic studies on NMSC conducted thus far (2Go, 24Go), to our knowledge historical data on arsenic concentrations in the drinking water of Prievidza District are missing. Therefore, on the basis of recent measurements, average exposure to an arsenic concentration of 1 µg x liter-1 in drinking water was assumed for the past. Note that the drinking water supply comes from outside the region.

No interaction was found between the exposure variables Asres1 and Asnut2. Therefore, dietary and residential data yielded independent effects.

Confounding
In a cancer incidence study, a risk estimation of environmental arsenic exposure by distance to the point source is not likely to be affected by spatial recruitment bias, which can arise in a case-control study. On the other hand, such an ecologic analysis is based on current residence information only and can be confounded by spatially covarying factors. Therefore, this case-control study was conducted to obtain historical information on environmental risk factors as well as information on potential confounders.

Occupational exposures are the most likely confounders for environmental arsenic. There is a concentration of potentially high-risk industries—a chemical plant and a company manufacturing building materials from coal ash—in the direct vicinity of the power plant; these companies employ 30 percent of the local population of productive age. About 16 percent of the power plant employees lived in this region environmentally exposed to arsenic, and, in power plant workers, urinary arsenic concentrations were found to be higher than those in the general population (9Go). In our study, 10 cases (3.8 percent) and seven controls (2.4 percent) ever worked in the power plant. Exposures to arsenic in known high-risk industries as well as in local coal mining, coal burning for power generation, and the use of coal ash in manufacturing building materials were not associated with a significant excess risk. In particular, coal mining, the longest-held job for 18 percent of both male cases and controls, was not associated with an excess risk, but the arsenic speciation in coal and the environment may be different. Furthermore, ever working in the chemical industry was not found to be associated with NMSC. There was an increased NMSC risk associated with farming for men, but not women, but this finding was based on a small number of cases. Occupational exposures to lead, cadmium, organic solvents, and paints were not found to be associated with development of NMSC. On the other hand, the higher NMSC incidence in males compared with females, as well as the high incidence of NMSC in males in the distance category 5–10 km, may indicate residual confounding.

Tobacco smoking is not an established NMSC risk factor, and there are conflicting results in the literature (25GoGoGo–28Go). Tobacco mainstream smoke contains only small amounts of arsenic (29Go). On the basis of the present study data, smoking was associated with an insignificant excess risk for women and a reduced risk for men. Interpreting the reduced risk as a protective effect seems not to be justified; instead, a recall bias must be taken into account. The majority of cases were interviewed at the dermatologic outpatient service; controls were interviewed at home. Cases were invited by their dermatologists for an interview, which could have contributed to such a bias. Similar results for beer consumption (not shown) supported this potential recall bias for male cases.

Skin sensitivity and ultraviolet radiation exposure were associated with a significant NMSC risk, but neither the prevalence of sensitive skin nor the risk varied consistently by distance to the power plant. A confounder or effect modifier for environmental arsenic could not be identified.

Conclusion
Historical and currently measured data on environmental arsenic pollution from a coal-fired power plant in the Slovak district of Prievidza indicate a risk for development of NMSC in the vicinity of this point source. The incidence of NMSC has long been higher in this exposed area in comparison to the distant part of the district. To investigate the association of environmental arsenic exposure with NMSC risk, a population-based case-control study was conducted with 264 cases and 286 controls. A first approach for exposure assessment was distance based, focusing on the history of the places of residence and work and on annual arsenic emissions. A significant excess risk was found for NMSC. The effects of spatially covarying emissions from the power plant and from a nearby chemical plant cannot be disentangled with certainty in risk estimates based on distance-related exposure measures. If assessed on the basis of nutritional habits, consumption of vegetables and fruits possibly contaminated by arsenic may have been masked by the protective effects of such a diet. Historical data on arsenic in drinking water were missing, and recent data showed that levels were mainly less than 10 µg x liter-1. When consumption of food grown in the study region was also considered, high arsenic exposure was associated with a marginally significant excess risk. No interaction between the exposure measures Asres1 and Asnut2 was found. Evidence exists for an impact of environmental arsenic exposure from power plant emissions on NMSC development in the district of Prievidza; evidence is also supported by the higher urinary and soil arsenic levels in the vicinity of the plant reported in the accompanying EXPASCAN studies.


    APPENDIX
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 
Environmental arsenic exposure variables Asres1 and Asres2
For each study subject, the following two environmental exposure variables were calculated:

and

where







In defining Asres2, 40 working hours per week were assumed.


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APPENDIX TABLE 1. Weights used to calculate Asres1* and Asres2* from annual arsenic emission data and with respect to the different operation periods and emission control measures from 1953–2000, by distance to the power plant, Prievidza District, Slovakia, EXPASCAN study

 
Nutritional arsenic variables Asnut1 and Asnut2
For each study subject, the following two nutritional arsenic variables were calculated:

and

where







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APPENDIX TABLE 2. Weights for the different categories of the EXPASCAN food frequency table, Prievidza District, Slovakia

 
Risk estimation for distance-related exposure variables Asres1, Asres2
Resampling procedure to correct for a spatial selection bias
Given 24 strata defined by gender, age (cutoff, 60 years), and distance to the power plant (<5 km, 5–10 km, >10 km), and the "true" population distribution with respect to these strata, unrestricted random samples were drawn from the original study population. For cases, the original sample distribution remained unchanged, but, for controls, the distribution within the distance strata was changed according to the true population distribution, keeping the gender and age distribution unchanged. Appendix table 3 shows an example for male controls in the age class 60 years or more.


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APPENDIX TABLE 3. Example for resampling: stratum of male controls (aged >=60 years) in the EXPASCAN study, Prievidza District, Slovakia

 
Bootstrap method to estimate bias-corrected odds ratios
To the rth resampled sample, the logistic regression model

was applied to estimate the parameter set {0r, 1r, ..., Kr}. Henceforth, the additional procedure was identical to the bootstrap estimation method (30Go); that is, the bias-corrected regression parameter and the variance were estimated as

and

with the number of resamplings R = 800.

The odds ratio and 95 percent confidence interval were calculated as

and


    ACKNOWLEDGMENTS
 
Funding for EXPASCAN was provided by European Union contract IC15 CT98 0525.

Cancer incidence and mortality reports were provided by Dr. Ivan Plesko from the National Cancer Institute of Slovakia.

EXPASCAN study group: V. Bencko, R. Colvile, E. Cordos, P. Docx, E. Fabianova, M. Farago, P. Frank, M. Götzl, J. Grellier, B. Hong, J. Rames, R. Rautiu, E. Stevens, I. Thornton, and J. Zvarova.


    NOTES
 
Correspondence to Dr. Beate Pesch, Medical Institute for Environmental Hygiene at Heinrich Heine University, Auf'm Hennekamp 50, 40225 Düssseldorf, Germany (e-mail: beate.pesch{at}uni-duesseldorf.de).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 APPENDIX
 REFERENCES
 

  1. Some metals and metallic compounds. IARC monographs on the evaluation of carcinogenic risks to humans. Vol 23. Lyon, France: International Agency for Research on Cancer, 1980.
  2. US Environmental Protection Agency. Final rule, "National primary drinking water regulations; arsenic and clarifications to compliance and new source contaminants monitoring." Part VIII. Federal Register 66, no. 14 (January 22, 2001):6876–7066. (http://www.epa.gov/safewater/ars/arsenid_finalrule.htm).
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Received for publication August 21, 2001. Accepted for publication December 26, 2001.