1. Arsenic and Nonmelanoma Skin Cancer in Slovakia Beate Pesch Environmental Health Research Institute, Germany

2. Part of the EU-funded Project EXPASCAN ‚Exposure to Arsenic and Cancer in Central & Eastern Europe‘ www.icconsultants.co.uk/ EXPASCAN.html www.icconsultants.co.uk/ EXPASCAN.html

3. PARTNERS Imperial College & IC Consultants, London, UK State Health Institutes, Prievidza, Bankska Bystrica, SK Institute of Hygiene and Epidemiology, Prague, CZ Environmental Health Research Institute, Duesseldorf, D University of Cluj, RO

4. Objective Estimation of the risk of environmental arsenic exposure from power plant emissions for non- melanoma skin cancer (NMSC) Estimation of the risk of environmental arsenic exposure from power plant emissions for non- melanoma skin cancer (NMSC)

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

6. Arsenic and arsenic compounds Environmental Health Criteria (EHC) 2nd edition, 224; 2001 Environmental Health Criteria (EHC) 2nd edition, 224; 2001 WHO, Geneva WHO, Geneva www.inchem.org www.inchem.org

7. Estimate by Distance to the Power Plant n Environmental As exposure n NMSC incidence Associate As exposure with NMSC risk & control for covariates

8. ENO Power Plant (Slovakia)

9. Environmental Arsenic Exposure n Historical As exposure Air pollution modelling Air pollution modelling (Colvile et al. 2001) (Colvile et al. 2001) n Current As exposure Measurement of As in soil, house dust Measurement of As in soil, house dust (Keegan et al. 2002) (Keegan et al. 2002)

10. Arsenic Emissions (tons/year) of the ENO Power Plant, Slovakia 0 100 200 195319601970198019901999 Year As t/a

12. Arsenic (mg/g) in soil 1999 by distance from the plant Distance N Median MinMax < 5 km 404114 134 5-10 km 102 23 9 139 >10km 6820 10 53

15. Cancer Incidence Analysis n Prievidza district versus Slovakia n Within Prievidza district by distance to the plant

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

17. CIF by Distance to the Power Plant cutoff 7.5 km 1977-1991 CIF by Distance to the Power Plant cutoff 7.5 km 1977-1991 Basal cell carcinoma 1.6 Squamous cell ca. 1.6 Basal cell carcinoma 1.6 Squamous cell ca. 1.6 Lung cancer 1.0 Lung cancer 1.0 Bladder cancer 1.1 Bladder cancer 1.1

18. SIR NMSC (1996-1999) by Distance to the Plant 10km 10kmReference District 1.2 1.10.8 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

19. Population-based Case-Control Study n 264 NMSC cases (1996-99) response rate 80% n 286 population controls response rate 72% response rate 72% Matching by sex, age

20. Statistical Power n  = 5% one-sided n  = 20% (power 80%) n controls exposed to As=10% n N cases = 264 n N controls = 286 n RR to be detected >= 1.9

21. NMSC Risk Estimation n Logistic regression conditional on age, gender: Odds Ratio (OR), 95% CI conditional on age, gender: Odds Ratio (OR), 95% CI n Potential confounders: occupational As exposure smoking smoking

22. Occupational As exposure (Job-Exposure Matrix)

23. Cigarette Smoking

24. Skin Type & UV Exposure

25. Fresh Vegetables & Fruits

26. Exposure Assessment and Risk Estimation for Environmental Arsenic n Dietary habits n Residential history

27. Arsenic Exposure from Dietary Habits n AsNut1 = Σ w(f )* I(f) 25 food items f: w(f) food frequencies I(f) annual As intake n AsNut2 = AsNut1 * s if self-support s= 2, else 1

28. Arsenic Exposure with Dietary Habits

29. As Exposure from Residential Data AsRes1 = Σ E(t)* w(d(t),t) for all places of residence: E(t) annual emission w(d(t),t) immission weight

30. Correction of spatial selection bias for distance- related variables AsRes n (1) Random re-sampling of controls SAS Surveyselect n (2) Bootstrap method OR, 95% CI for R=800 re-sampled groups

31. Arsenic Exposure with Residential Data

32. Environmental Arsenic Exposure & NMSC Risk n Elevated NMSC incidence in the vicinity of the plant. n As exposure from dietary and residential data are associated with excess risk. n Residual confounding can not be excluded.