Arsenic and Nonmelanoma Skin Cancer in Slovakia
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Arsenic and Nonmelanoma Skin Cancer in Slovakia

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Part of the EU-funded Project EXPASCAN Exposure to Arsenic and Cancer in Central
Arsenic and Nonmelanoma Skin Cancer in Slovakia

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1. Arsenic and Nonmelanoma Skin Cancer in Slovakia Beate Pesch Environmental Health Research Institute, Germany beate.pesch@uni-duesseldorf.de URL: www.miu.uni-duesseldorf.de/members/1mem.htm NMSC nonmelanoma skin cancer SK Slovakia As arsenic Pesch B, Ranft U, Jakubis P et al. 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. Am J Epidemiol 2002;155:798-809 beate.pesch@uni-duesseldorf.de URL: www.miu.uni-duesseldorf.de/members/1mem.htm NMSC nonmelanoma skin cancer SK Slovakia As arsenic Pesch B, Ranft U, Jakubis P et al. 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. Am J Epidemiol 2002;155:798-809

2. Part of the EU-funded Project EXPASCAN ?Exposure to Arsenic and Cancer in Central & Eastern Europe? www.icconsultants.co.uk/ EXPASCAN.html The case-control study on the risk of environmental arsenic exposure from a coal-burning power plant on the development of nonmelanoma skin cancer is part of the EU-funded project EXPASCAN: Exposure to Arsenic and Cancer in Central and Eastern Europe URL: www.icconsultants.co.uk/ircyl.html Contract No. IC15 CT98 0525 The case-control study on the risk of environmental arsenic exposure from a coal-burning power plant on the development of nonmelanoma skin cancer is part of the EU-funded project EXPASCAN: Exposure to Arsenic and Cancer in Central and Eastern Europe URL: www.icconsultants.co.uk/ircyl.html Contract No. IC15 CT98 0525

3. Mark Nieuwenhuijsen (UK) project co-ordinator Workpackage 1: literature review (M. Nieuwenhuijsen, UK et al.) Workpackage 2: Ecological study (V. Bencko, CZ, et al.) Workpackage 3: Case-control study (U. Ranft, B. Pesch, K. Unfried, D, et al.) Workpackage 4: Urinary As speciation (P. Jakubis, P. Miscovic, SK, et al.) Workpackage 5: As in soil, dust, ash, coal (I. Thornton, T. Keegan, UK, et al.) Workpackage 6: As immission model (R. Colvile, UK, et al.) Workpackage 7: Risk assessment in Romania (E. Cordos, RO, et al.) Workpackage 8: Best industrial practice (P. Docx, R. Rautiu, UK, et al.) Workpackage 9: Synopsis (M. Nieuwenhuijsen, UK, et al.)Mark Nieuwenhuijsen (UK) project co-ordinator Workpackage 1: literature review (M. Nieuwenhuijsen, UK et al.) Workpackage 2: Ecological study (V. Bencko, CZ, et al.) Workpackage 3: Case-control study (U. Ranft, B. Pesch, K. Unfried, D, et al.) Workpackage 4: Urinary As speciation (P. Jakubis, P. Miscovic, SK, et al.) Workpackage 5: As in soil, dust, ash, coal (I. Thornton, T. Keegan, UK, et al.) Workpackage 6: As immission model (R. Colvile, UK, et al.) Workpackage 7: Risk assessment in Romania (E. Cordos, RO, et al.) Workpackage 8: Best industrial practice (P. Docx, R. Rautiu, UK, et al.) Workpackage 9: Synopsis (M. Nieuwenhuijsen, UK, et al.)

4. Objective Estimation of the risk of environmental arsenic exposure from power plant emissions for non-melanoma skin cancer (NMSC) Associate environmental arsenic exposure with effect variables on the skin cancer burden to estimate the risk of arsenic 1)How can the environmental arsenic exposure be assessed and rated? Compare the Slovak arsenic pollution level with other exposure circumstances (2) How can an excess risk for skin cancer be assessed and rated? Compare NMSC incidence in SK with sun-exposed regions at a global scale (3) Choose appropriate study design(s) to estimate the risk of environmental arsenic exposure on the development of skin cancer Associate environmental arsenic exposure with effect variables on the skin cancer burden to estimate the risk of arsenic 1)How can the environmental arsenic exposure be assessed and rated? Compare the Slovak arsenic pollution level with other exposure circumstances (2) How can an excess risk for skin cancer be assessed and rated? Compare NMSC incidence in SK with sun-exposed regions at a global scale (3) Choose appropriate study design(s) to estimate the risk of environmental arsenic exposure on the development of skin cancer

5. Estimation of the risk of environmental arsenic exposure Choose study design(s) Assess exposure Estimate risk Discuss confounders

6. Arsenic and arsenic compounds Environmental Health Criteria (EHC) 2nd edition, 224; 2001 WHO, Geneva www.inchem.org Use the following reference to inform on state-of-the-art evaluation of arsenic and arsenic compounds: Environmental Health Criteria (EHC) Monographs 224 (2001): Arsenic and arsenic compounds. www.inchem.org Use the following reference to inform on state-of-the-art evaluation of arsenic and arsenic compounds: Environmental Health Criteria (EHC) Monographs 224 (2001): Arsenic and arsenic compounds. www.inchem.org

7. Estimate by Distance to the Power Plant Environmental As exposure NMSC incidence Associate As exposure with NMSC risk & control for covariates (1) Has the NMSC incidence been elevated in the vicinity of the plant? - historical incidence measures - current incidence measures (2) Has the arsenic concentration in the environment been elevated in the vicinity of the plant? - historical arsenic pollution (modelling) - current arsenic pollution (measurement in soil, dust, coal ash) (3) How can this possible association assessed with epidemiological studies be validated? - discuss an association of current arsenic exposure in soil and dust with urinary arsenic concentrations (4) discuss potential covariates and confounders(1) Has the NMSC incidence been elevated in the vicinity of the plant? - historical incidence measures - current incidence measures (2) Has the arsenic concentration in the environment been elevated in the vicinity of the plant? - historical arsenic pollution (modelling) - current arsenic pollution (measurement in soil, dust, coal ash) (3) How can this possible association assessed with epidemiological studies be validated? - discuss an association of current arsenic exposure in soil and dust with urinary arsenic concentrations (4) discuss potential covariates and confounders

8. ENO Power Plant (Slovakia) The ENO power plant, located in the center of the district of Prievidza, has been producing energy since 1953 by burning an arsenic-rich coal. The high content of arsenic in the coal (~ 520 ?g/g) and in the fly ash (~860 ?g/g) and the insufficient emission control measures resulted in the pollution of this Slovak region up to 1990 Keegan T, Hong B, Thornton I et al. Assessment of environmental arsenic levels in Prievidza district. J Expo Anal Environ Epidemiol 2002;12:179-85 The district of Prievidza ranks among the highly industrialized and most polluted areas in Central Slovakia. In the vicinity of the power plant, there is a large plant of the chlorine chemistry, also contributing to the environmental pollution of this area. Discuss, if the potential effect of the spatially co-varying exposure by this chemical plant can be disentangled from the power plant effect on skin cancer risk respectively incidence?The ENO power plant, located in the center of the district of Prievidza, has been producing energy since 1953 by burning an arsenic-rich coal. The high content of arsenic in the coal (~ 520 ?g/g) and in the fly ash (~860 ?g/g) and the insufficient emission control measures resulted in the pollution of this Slovak region up to 1990 Keegan T, Hong B, Thornton I et al. Assessment of environmental arsenic levels in Prievidza district. J Expo Anal Environ Epidemiol 2002;12:179-85 The district of Prievidza ranks among the highly industrialized and most polluted areas in Central Slovakia. In the vicinity of the power plant, there is a large plant of the chlorine chemistry, also contributing to the environmental pollution of this area. Discuss, if the potential effect of the spatially co-varying exposure by this chemical plant can be disentangled from the power plant effect on skin cancer risk respectively incidence?

10. ENO plant started operation in 1953. During the operation period, the Megawatt power stepwise increased. Since the 1960ies, emission has been measured. Highest emission levels were measured in the 1970ies. Since the 1980ies, emission control measures were implemented, but with insufficient effect on the arsenic environmental pollution until the 1990ies.ENO plant started operation in 1953. During the operation period, the Megawatt power stepwise increased. Since the 1960ies, emission has been measured. Highest emission levels were measured in the 1970ies. Since the 1980ies, emission control measures were implemented, but with insufficient effect on the arsenic environmental pollution until the 1990ies.

13. Variation of urinary arsenic in samples of the study populatioon by distance to the power plant: higher levels in the vicinity of the power plant indicate that even under the low exposure levels of the 1990ies there is still an impact of the environmental exposure to arsenic on the body burden. Also occupational exposure may contribute to the elevated levels in urine in the vicinity of the plant. What may justify the conclusion that there is likely also an environmental impact?Variation of urinary arsenic in samples of the study populatioon by distance to the power plant: higher levels in the vicinity of the power plant indicate that even under the low exposure levels of the 1990ies there is still an impact of the environmental exposure to arsenic on the body burden. Also occupational exposure may contribute to the elevated levels in urine in the vicinity of the plant. What may justify the conclusion that there is likely also an environmental impact?

14. There is a weak, but significant correlation between urinary and environmental arsenic levels, which supports the hypothesis that environmental exposure to arsenic can contribute to the elevated urinary arsenic levels of subjects living in the vicinity of the power plant.There is a weak, but significant correlation between urinary and environmental arsenic levels, which supports the hypothesis that environmental exposure to arsenic can contribute to the elevated urinary arsenic levels of subjects living in the vicinity of the power plant.

15. Cancer Incidence Analysis Prievidza district versus Slovakia Within Prievidza district by distance to the plant URL: bmj.com/epidem/epid.html Coggon D, Rose G, Barker DJP Epidemiology of the Unitiated. BMJ Publishing Group 1997 Contents 2. Quantifying disease in populations 3. Comparing disease rates URL: bmj.com/epidem/epid.html Coggon D, Rose G, Barker DJP Epidemiology of the Unitiated. BMJ Publishing Group 1997 Contents 2. Quantifying disease in populations 3. Comparing disease rates

16. Comparative Incidence Figures (CIF) Prievidza district versus Slovakia 1975-84 All malignancies 1.1 NMSC 1.6 Lung cancer 1.0 Bladder cancer 0.9 Source: Slovak National Cancer Registry Plesko I (ed.). Atlas vyskytu shubnych nadorov v SSR [In Slovak; Atlas of Cancer Incidence in Slovakia]. Slovakia: Slovenskej Akademie, 1989 CIF, comparative incidence figure, ratio of age-standardized incidence rate of the region under study in comparison to a reference incidence rate (here the incidence at national level) Also lung cancer and bladder cancer are discussed as causally related to arsenic exposure, but both sites are not associated with an elevated cancer incidence in the district of Privievdza if compared to the Slovak average. NMSC incidence in Prievidza district 1997: 90 male and 50 female cases per 100,000 (age-adjusted to the world standard) -> compare this rate with the NMSC incidence in sun-exposed regions such as AustraliaSource: Slovak National Cancer Registry Plesko I (ed.). Atlas vyskytu shubnych nadorov v SSR [In Slovak; Atlas of Cancer Incidence in Slovakia]. Slovakia: Slovenskej Akademie, 1989 CIF, comparative incidence figure, ratio of age-standardized incidence rate of the region under study in comparison to a reference incidence rate (here the incidence at national level) Also lung cancer and bladder cancer are discussed as causally related to arsenic exposure, but both sites are not associated with an elevated cancer incidence in the district of Privievdza if compared to the Slovak average. NMSC incidence in Prievidza district 1997: 90 male and 50 female cases per 100,000 (age-adjusted to the world standard) -> compare this rate with the NMSC incidence in sun-exposed regions such as Australia

17. CIF by Distance to the Power Plant cutoff 7.5 km 1977-1991 Basal cell carcinoma 1.6 Squamous cell ca. 1.6 Lung cancer 1.0 Bladder cancer 1.1 EXPASCAN workpackage ?Ecological Study? (Bencko, V., et al.) Within the district, there is a higher incidence of non-melanoma skin cancer, but not of lung or bladder cancer. The comparative cancer incidence figure relates the age-adjusted incidence rate in the vicinity of the plant (< 7.5 km) with the age-adjusted rate in the distant part of the district (>= 7.5 km). Incidence rates are elevated for both basal cell carcinoma and squamous cell carcinoma of the skin. URL: bmj.com/epidem/epid.html Coggon D, Rose G, Barker DJP Epidemiology of the Unitiated. BMJ Publishing Group 1997 Contents 6. Ecological studies Discuss the ?ecological fallacy? of ecological studies!EXPASCAN workpackage ?Ecological Study? (Bencko, V., et al.) Within the district, there is a higher incidence of non-melanoma skin cancer, but not of lung or bladder cancer. The comparative cancer incidence figure relates the age-adjusted incidence rate in the vicinity of the plant (< 7.5 km) with the age-adjusted rate in the distant part of the district (>= 7.5 km). Incidence rates are elevated for both basal cell carcinoma and squamous cell carcinoma of the skin. URL: bmj.com/epidem/epid.html Coggon D, Rose G, Barker DJP Epidemiology of the Unitiated. BMJ Publishing Group 1997 Contents 6. Ecological studies Discuss the ?ecological fallacy? of ecological studies!

18. SIR NMSC (1996-1999) by Distance to the Plant <5km 5-10 km >10km Reference District 1.2 1.1 0.8 0.9- 1.6 1.0-1.3 0.6-0.9 Slovakia 1.6 1.5 1.0 1.2- 2.2 1.3-1.7 0.9-1.3 SIR, standardized incidence ratio Relation of observed cases to expected cases (numerator) calculation of the expected cases with indirect age standardization observed cases are based on 374 eligible cases identified for the case-control study (primary first NMSC) from a total of 541 cases (including secondary cancer cases) Reference populations to calculate the numerator (expected cases): (1) NMSC incidence of the district of Prievida, based on 374 eligible cases (2) NMSC incidence of Slovakia this number includes secondary NMSC, therefore SIR underestimates the ?true? ratio of observed to expected cases Breslow NE, Day NE, eds. Statistical methods in cancer research. Vol. 2. The design and analysis of cohort studies. Oxford, UK: Oxford University Press, 1987 SIR, standardized incidence ratio Relation of observed cases to expected cases (numerator) calculation of the expected cases with indirect age standardization observed cases are based on 374 eligible cases identified for the case-control study (primary first NMSC) from a total of 541 cases (including secondary cancer cases) Reference populations to calculate the numerator (expected cases): (1) NMSC incidence of the district of Prievida, based on 374 eligible cases (2) NMSC incidence of Slovakiathis number includes secondary NMSC, therefore SIR underestimates the ?true? ratio of observed to expected cases Breslow NE, Day NE, eds. Statistical methods in cancer research. Vol. 2. The design and analysis of cohort studies. Oxford, UK: Oxford University Press, 1987

19. Population-based Case-Control Study 264 NMSC cases (1996-99) response rate 80% 286 population controls response rate 72% Matching by sex, age Cases were eligible, if 1) they currently resided in this district 2) they were not older than age 80 years 3) the diagnosis of NMSC as a primary, first tumor was confirmed histologically during 1996-1999 Population controls were ascertained from a random address sample of the mandatory registry of the district and frequency-matched to cases on gender and age (5-year classes). URL: bmj.com/epidem/epid.html Coggon D, Rose G, Barker DJP Epidemiology of the Unitiated. BMJ Publishing Group 1997 Contents 5. Planning and conducting a survey 8. Case-control and cross-sectional studies Cases were eligible, if 1) they currently resided in this district 2) they were not older than age 80 years 3) the diagnosis of NMSC as a primary, first tumor was confirmed histologically during 1996-1999 Population controls were ascertained from a random address sample of the mandatory registry of the district and frequency-matched to cases on gender and age (5-year classes). URL: bmj.com/epidem/epid.html Coggon D, Rose G, Barker DJP Epidemiology of the Unitiated. BMJ Publishing Group 1997 Contents 5. Planning and conducting a survey 8. Case-control and cross-sectional studies

20. Statistical Power ? = 5% one-sided ?= 20% (power 80%) controls exposed to As=10% N cases = 264 N controls = 286 RR to be detected >= 1.9 http://calculators.stat.ucla.edu/powercalc/binomila/case-control/ b-case-control-power.php The fraction of the exposed controls was estimated to correspond to the 10% of the population of the district living in the vicinity of the emission source (< 5 km from ENO plant). Which parameter of the statistical power calculation is the limiting factor? -> the cases occurring in the observation perion in this selected district How can the power be improved? -> (1) increase the matching factor, but: The available budget allowed only a 1:1 frequency matching. -> (2) One-sided test can be taken into account, because a protective efffect of arsenic exposure on skin cancer development can likely be excluded. http://calculators.stat.ucla.edu/powercalc/binomila/case-control/ b-case-control-power.php The fraction of the exposed controls was estimated to correspond to the 10% of the population of the district living in the vicinity of the emission source (< 5 km from ENO plant). Which parameter of the statistical power calculation is the limiting factor? -> the cases occurring in the observation perion in this selected district How can the power be improved? -> (1) increase the matching factor, but: The available budget allowed only a 1:1 frequency matching. -> (2) One-sided test can be taken into account, because a protective efffect of arsenic exposure on skin cancer development can likely be excluded.

21. NMSC Risk Estimation Logistic regression conditional on age, gender: Odds Ratio (OR), 95% CI Potential confounders: occupational As exposure smoking All logistic regression models were conditional on age (dichotomized with age 60 years as cutoff) and gender. Software SAS, version 8.1, procedures PHREG LOGISTIC OR, odds ratio CI, confidence intervalAll logistic regression models were conditional on age (dichotomized with age 60 years as cutoff) and gender. Software SAS, version 8.1, procedures PHREG LOGISTIC OR, odds ratio CI, confidence interval

22. Occupational As exposure (Job-Exposure Matrix) Occupational exposure to arsenic is considered a potential confounder for environmental arsenic exposure. A large fraction of the population works has been working as coal miners of an arsenic-rich coal. But the uptake of arsenic from coals remains yet to be determined. Occupational exposure to arsenic was estimated with a British job-exposure matrix (JEM): Pannett B, Coggon D, Acheson ED. A job-exposure matrix for use in population based studies in England and Wales. Br J Ind Med 1985; 42:777-83 Modifications were performed with respect to (1) the local occupational exposure conditions (arsenic rich coal and coal ash) (2) arsenic exposure according to CAREX International Information System on Occupational Exposure to Carcinogens, URL:www.occuphealth.fi/list/data/CAREX see also: Pesch B et al. Int J Epidemiol 2000;29:1014-24 and discuss pros and cons of job-exposure matrices Occupational exposure to arsenic is considered a potential confounder for environmental arsenic exposure. A large fraction of the population works has been working as coal miners of an arsenic-rich coal. But the uptake of arsenic from coals remains yet to be determined. Occupational exposure to arsenic was estimated with a British job-exposure matrix (JEM): Pannett B, Coggon D, Acheson ED. A job-exposure matrix for use in population based studies in England and Wales. Br J Ind Med 1985; 42:777-83 Modifications were performed with respect to (1) the local occupational exposure conditions (arsenic rich coal and coal ash) (2) arsenic exposure according to CAREX International Information System on Occupational Exposure to Carcinogens, URL:www.occuphealth.fi/list/data/CAREX see also: Pesch B et al. Int J Epidemiol 2000;29:1014-24 and discuss pros and cons of job-exposure matrices

23. Cigarette Smoking Packyears: product of the duration of smoking (in years) and the numbers of cigarettes smoked per day divided by a package size of 20 cigarettes, summarized for different smoking periods What would justify to assume tobacco smoke as confounder or covariate? Consider (1) Tobacco smoke contains only small amounts of arsenic. (2) Smoking is a habit which may not vary spatially such as air pollution with arsenic. (3) How likely is a true ?protective effect?? A recall bias of the cases cannot be excluded. Whereas controls were mainly interviewed at home, cases were invited by their dermatologist to be interviewed at a dermatological outpatient service. Similar results for alcohol consumption support this potential bias (underreporting among cases) Packyears: product of the duration of smoking (in years) and the numbers of cigarettes smoked per day divided by a package size of 20 cigarettes, summarized for different smoking periods What would justify to assume tobacco smoke as confounder or covariate? Consider (1) Tobacco smoke contains only small amounts of arsenic. (2) Smoking is a habit which may not vary spatially such as air pollution with arsenic. (3) How likely is a true ?protective effect?? A recall bias of the cases cannot be excluded. Whereas controls were mainly interviewed at home, cases were invited by their dermatologist to be interviewed at a dermatological outpatient service. Similar results for alcohol consumption support this potential bias (underreporting among cases)

24. Skin Type & UV Exposure Skin type and UV exposure are considered the most important risk factors for skin cancer. Compare the risk estimates for the skin characteristics (OR around 2) with the risk other risk factors for cancer, such as smoking for lung cancer (OR around 20). What may explain the relatively low risk estimates for the skin? This may be due to the geographical location and climate in this part of Central Europe. Sun light exposure is much lower than in Australia and many other geographical regions.Skin type and UV exposure are considered the most important risk factors for skin cancer. Compare the risk estimates for the skin characteristics (OR around 2) with the risk other risk factors for cancer, such as smoking for lung cancer (OR around 20). What may explain the relatively low risk estimates for the skin? This may be due to the geographical location and climate in this part of Central Europe. Sun light exposure is much lower than in Australia and many other geographical regions.

25. Fresh Vegetables & Fruits A regular consumption of fresh vegetables and fruits is associated with a protective effect, which is non-significant due to the limited power of the study for rare exposures (only a few persons do not eat fruits and vegetables regularly, i.e. less than once per week).A regular consumption of fresh vegetables and fruits is associated with a protective effect, which is non-significant due to the limited power of the study for rare exposures (only a few persons do not eat fruits and vegetables regularly, i.e. less than once per week).

26. Exposure Assessment and Risk Estimation for Environmental Arsenic Dietary habits Residential history The pathways of arsenic uptake (oral, inhalative and/or dermal) are not known with certainty. For skin cancer, oral uptake is considered the main route. The pathways of arsenic uptake (oral, inhalative and/or dermal) are not known with certainty. For skin cancer, oral uptake is considered the main route.

27. Arsenic Exposure from Dietary Habits AsNut1 = S w(f )* I(f) 25 food items f: w(f) food frequencies I(f) annual As intake AsNut2 = AsNut1 * s if self-support s= 2, else 1 Nutrition and drinking habits were assessed by using a semiquantitative food frequency questionnaire. The exposure to arsenic was calculated by weighting the frequency categories of food intake as follows times/week weight < 1 0 1 1 1-3 2 4-7 3 For each food item, the content of arsenic per kg was taken from the final report of the EC-funded project PHARE, together with the average annual consumption (kg). Asres2 considers additionally self-suppliers with vegetables and fruits as highly exposed to environmental arsenic. How reliable are food frequency data? Nutrition and drinking habits were assessed by using a semiquantitative food frequency questionnaire. The exposure to arsenic was calculated by weighting the frequency categories of food intake as follows times/week weight < 1 0 1 1 1-3 2 4-7 3 For each food item, the content of arsenic per kg was taken from the final report of the EC-funded project PHARE, together with the average annual consumption (kg). Asres2 considers additionally self-suppliers with vegetables and fruits as highly exposed to environmental arsenic. How reliable are food frequency data?

28. Arsenic Exposure with Dietary Habits If self-supplier with local fruits and vegetables,which may have been contaminated with arsenic from the power plant emissions, are additionally rated as high-exposed, there is a significant NMSC excess risk. Note that persons who reported consuming homegrown vegetables and fruits had elevated urinary concentrations of monomethylarsonic acid (data not shown). If self-supplier with local fruits and vegetables,which may have been contaminated with arsenic from the power plant emissions, are additionally rated as high-exposed, there is a significant NMSC excess risk. Note that persons who reported consuming homegrown vegetables and fruits had elevated urinary concentrations of monomethylarsonic acid (data not shown).

29. As Exposure from Residential Data AsRes1 = S E(t)* w(d(t),t) for all places of residence: E(t) annual emission w(d(t),t) immission weight The distance of the place of residence to the power station is considered a proxy for environmental arsenic pollution. A residual confounding with occupational exposure cannot be ruled out. Every place of residence held for at least 1 year since 1953, when the power plant began operating, was classified according to the distance to the plant < 5 km, 5-10 km, > 10 km. The cutoffs were derived from atmospheric dispersion modelling of the historical pollution pattern. To calculate Asres1, the emission data were weighted by distance and time to estimate the immision burden of a person with respect to places of residence or work. Note that persons living in the vicinity of the power plant had elevated urinary arsenic concentrations. The distance of the place of residence to the power station is considered a proxy for environmental arsenic pollution. A residual confounding with occupational exposure cannot be ruled out. Every place of residence held for at least 1 year since 1953, when the power plant began operating, was classified according to the distance to the plant < 5 km, 5-10 km, > 10 km. The cutoffs were derived from atmospheric dispersion modelling of the historical pollution pattern. To calculate Asres1, the emission data were weighted by distance and time to estimate the immision burden of a person with respect to places of residence or work. Note that persons living in the vicinity of the power plant had elevated urinary arsenic concentrations.

30. Correction of spatial selection bias for distance-related variables AsRes (1) Random re-sampling of controls SAS Surveyselect (2) Bootstrap method OR, 95% CI for R=800 re-sampled groups For distance-related exposure variables, any spatial bias in the recruitment of the study groups (such as a non-random selection of controls with a lower fraction from the distant part) would result in a biased risk estimate. The SAS procedure SURVEYSELECT was applied for a random re-sampling of controls according to the spatial population distibution. A bootstrap method was applied to estimate the odds ratios from 800 re-sampled groups. For distance-related exposure variables, any spatial bias in the recruitment of the study groups (such as a non-random selection of controls with a lower fraction from the distant part) would result in a biased risk estimate. The SAS procedure SURVEYSELECT was applied for a random re-sampling of controls according to the spatial population distibution. A bootstrap method was applied to estimate the odds ratios from 800 re-sampled groups.

31. Arsenic Exposure with Residential Data Arsenic exposure, assessed with the residential history and corrected for a spatial selection bias, was associated with a significant NMSC excess risk.Arsenic exposure, assessed with the residential history and corrected for a spatial selection bias, was associated with a significant NMSC excess risk.

32. Environmental Arsenic Exposure & NMSC Risk Elevated NMSC incidence in the vicinity of the plant. As exposure from dietary and residential data are associated with excess risk. Residual confounding can not be excluded. There is evidence for a NMSC risk of environmental arsenic exposure from coal-burning for power generation without emission measures, which is supported by based on current measurement under lower exposure levels (1) higher arsenic levels in soil samples in the vicinity of the power plant (2) higher urinary arsenic levels in the vicinity of the power plant with respect to the nonmelanoma skin cancer incidence (1) highest incidence among the Slovak districts since registering cancer (2) within the district: higher incidence in the vicinity of the plant arsenic exposure assessed from data of the case-control study was associated with an excess risk based on (1) dietary intake (2) residential history Residual confounding can not excluded (1) emmisions of a nearby chemical plant (2) occupational exposureThere is evidence for a NMSC risk of environmental arsenic exposure from coal-burning for power generation without emission measures, which is supported by based on current measurement under lower exposure levels (1) higher arsenic levels in soil samples in the vicinity of the power plant (2) higher urinary arsenic levels in the vicinity of the power plant with respect to the nonmelanoma skin cancer incidence (1) highest incidence among the Slovak districts since registering cancer (2) within the district: higher incidence in the vicinity of the plant arsenic exposure assessed from data of the case-control study was associated with an excess risk based on (1) dietary intake (2) residential history Residual confounding can not excluded (1) emmisions of a nearby chemical plant (2) occupational exposure


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