TY - JOUR
TI - Particulate matter air pollution components and risk for lung cancer
AU - Raaschou-Nielsen, O.
AU - Beelen, R.
AU - Wang, M.
AU - Hoek, G.
AU - Andersen, Z.J.
AU - Hoffmann, B.
AU - Stafoggia, M.
AU - Samoli, E.
AU - Weinmayr, G.
AU - Dimakopoulou, K.
AU - Nieuwenhuijsen, M.
AU - Xun, W.W.
AU - Fischer, P.
AU - Eriksen, K.T.
AU - Sørensen, M.
AU - Tjønneland, A.
AU - Ricceri, F.
AU - de Hoogh, K.
AU - Key, T.
AU - Eeftens, M.
AU - Peeters, P.H.
AU - Bueno-de-Mesquita, H.B.
AU - Meliefste, K.
AU - Oftedal, B.
AU - Schwarze, P.E.
AU - Nafstad, P.
AU - Galassi, C.
AU - Migliore, E.
AU - Ranzi, A.
AU - Cesaroni, G.
AU - Badaloni, C.
AU - Forastiere, F.
AU - Penell, J.
AU - De Faire, U.
AU - Korek, M.
AU - Pedersen, N.
AU - Östenson, C.-G.
AU - Pershagen, G.
AU - Fratiglioni, L.
AU - Concin, H.
AU - Nagel, G.
AU - Jaensch, A.
AU - Ineichen, A.
AU - Naccarati, A.
AU - Katsoulis, M.
AU - Trichpoulou, A.
AU - Keuken, M.
AU - Jedynska, A.
AU - Kooter, I.M.
AU - Kukkonen, J.
AU - Brunekreef, B.
AU - Sokhi, R.S.
AU - Katsouyanni, K.
AU - Vineis, P.
JO - Environment International
PY - 2016
VL - 87
TODO - null
SP - 66-73
PB - Elsevier Ireland Ltd
SN - 0160-4120
TODO - 10.1016/j.envint.2015.11.007
TODO - Air pollution;  Biological organs;  Diseases;  Land use;  Nickel;  Random processes;  Regression analysis;  Sulfur, Cohort studies;  Cox regression;  European Countries;  Land-use regression models;  Lung Cancer;  Particulate Matter;  Particulate matter air pollution;  Random-effect models, Particles (particulate matter), copper;  iron;  nickel;  potassium;  silicon;  sulfur;  vanadium;  zinc;  air pollutant;  particulate matter, atmospheric pollution;  cancer;  carcinogen;  cohort analysis;  health risk;  nickel;  particulate matter;  sulfur, air pollution;  Article;  cancer incidence;  cancer risk;  cohort analysis;  concentration (parameters);  controlled study;  environmental exposure;  follow up;  lung cancer;  particulate matter;  priority journal;  risk assessment;  risk factor;  validation process;  adult;  aged;  air pollutant;  analysis;  clinical trial;  Europe;  exposure;  female;  human;  incidence;  Lung Neoplasms;  male;  middle aged;  multicenter study;  particle size;  particulate matter;  proportional hazards model;  prospective study;  risk, Europe, Adult;  Aged;  Air Pollutants;  Cohort Studies;  Environmental Exposure;  Europe;  Female;  Humans;  Incidence;  Inhalation Exposure;  Lung Neoplasms;  Male;  Middle Aged;  Particle Size;  Particulate Matter;  Proportional Hazards Models;  Prospective Studies;  Risk
TODO - Background: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. Methods: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. Results: The 245,782 cohort members contributed 3,229,220person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m3), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m3), PM10 S (1.58; 1.03-2.44 per 200 ng/m3), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m3) and PM10 K (1.17; 1.02-1.33 per 100 ng/m3). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. Conclusions: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important. © 2015 Elsevier Ltd.
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