1
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Vienneau D, Stafoggia M, Rodopoulou S, Chen J, Atkinson RW, Bauwelinck M, Klompmaker JO, Oftedal B, Andersen ZJ, Janssen NAH, So R, Lim YH, Flückiger B, Ducret-Stich R, Röösli M, Probst-Hensch N, Künzli N, Strak M, Samoli E, de Hoogh K, Brunekreef B, Hoek G. Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland. Environ Health 2023; 22:29. [PMID: 36967400 PMCID: PMC10041702 DOI: 10.1186/s12940-023-00983-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 03/13/2023] [Indexed: 05/23/2023]
Abstract
BACKGROUND Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise. METHODS Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges. RESULTS During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 1.057 (1.048, 1.067) per 0.5 × 10-5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m3 for PM2.5 and NO2, < 1.5 10-5/m BC and < 53 dB Lden total transportation noise. The O3 association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC). CONCLUSION Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO2, BC and transportation noise.
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Affiliation(s)
- Danielle Vienneau
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland.
- University of Basel, Basel, Switzerland.
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Region Health Service / ASL Roma 1, Rome, Italy
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sophia Rodopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Jie Chen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Richard W Atkinson
- Population Health Research Institute, St George's, University of London, London, UK
| | - Mariska Bauwelinck
- Interface Demography - Department of Sociology, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium
| | - Jochem O Klompmaker
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Bente Oftedal
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Zorana J Andersen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, 1165, Denmark
| | - Nicole A H Janssen
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Rina So
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, 1165, Denmark
| | - Youn-Hee Lim
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, 1165, Denmark
| | - Benjamin Flückiger
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Regina Ducret-Stich
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Martin Röösli
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Nino Künzli
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Maciek Strak
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Kees de Hoogh
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
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2
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Gulliver J, Morley D, Dunster C, McCrea A, van Nunen E, Tsai MY, Probst-Hensch N, Eeftens M, Imboden M, Ducret-Stich R, Naccarati A, Galassi C, Ranzi A, Nieuwenhuijsen M, Curto A, Donaire-Gonzalez D, Cirach M, Vermeulen R, Vineis P, Hoek G, Kelly FJ. Land use regression models for the oxidative potential of fine particles (PM 2.5) in five European areas. Environ Res 2018; 160:247-255. [PMID: 29031214 DOI: 10.1016/j.envres.2017.10.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Revised: 09/22/2017] [Accepted: 10/03/2017] [Indexed: 06/07/2023]
Abstract
Oxidative potential (OP) of particulate matter (PM) is proposed as a biologically-relevant exposure metric for studies of air pollution and health. We aimed to evaluate the spatial variability of the OP of measured PM2.5 using ascorbate (AA) and (reduced) glutathione (GSH), and develop land use regression (LUR) models to explain this spatial variability. We estimated annual average values (m-3) of OPAA and OPGSH for five areas (Basel, CH; Catalonia, ES; London-Oxford, UK (no OPGSH); the Netherlands; and Turin, IT) using PM2.5 filters. OPAA and OPGSH LUR models were developed using all monitoring sites, separately for each area and combined-areas. The same variables were then used in repeated sub-sampling of monitoring sites to test sensitivity of variable selection; new variables were offered where variables were excluded (p > .1). On average, measurements of OPAA and OPGSH were moderately correlated (maximum Pearson's maximum Pearson's R = = .7) with PM2.5 and other metrics (PM2.5absorbance, NO2, Cu, Fe). HOV (hold-out validation) R2 for OPAA models was .21, .58, .45, .53, and .13 for Basel, Catalonia, London-Oxford, the Netherlands and Turin respectively. For OPGSH, the only model achieving at least moderate performance was for the Netherlands (R2 = .31). Combined models for OPAA and OPGSH were largely explained by study area with weak local predictors of intra-area contrasts; we therefore do not endorse them for use in epidemiologic studies. Given the moderate correlation of OPAA with other pollutants, the three reasonably performing LUR models for OPAA could be used independently of other pollutant metrics in epidemiological studies.
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Affiliation(s)
- John Gulliver
- MRC-PHE Centre for Environment and Health, the Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom.
| | - David Morley
- MRC-PHE Centre for Environment and Health, the Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Chrissi Dunster
- MRC-PHE Centre for Environment and Health, Environmental Research Group (ERG), King's College London, London, United Kingdom
| | - Adrienne McCrea
- MRC-PHE Centre for Environment and Health, the Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Erik van Nunen
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University, Utrecht, The Netherlands
| | - Ming-Yi Tsai
- Swiss Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nicoltae Probst-Hensch
- Swiss Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Marloes Eeftens
- Swiss Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Medea Imboden
- Swiss Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Regina Ducret-Stich
- Swiss Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland; University of Basel, Basel, Switzerland
| | | | - Claudia Galassi
- Unit of Cancer Epidemiology, Citta' della Salute e della Scienza University Hospital and Centre for Cancer Prevention, Turin, Italy
| | - Andrea Ranzi
- Environmental Health Reference Centre, Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, Modena, Italy
| | - Mark Nieuwenhuijsen
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain; CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - Ariadna Curto
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain; CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - David Donaire-Gonzalez
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain; CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - Marta Cirach
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain; CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University, Utrecht, The Netherlands
| | - Paolo Vineis
- MRC-PHE Centre for Environment and Health, the Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Gerard Hoek
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University, Utrecht, The Netherlands
| | - Frank J Kelly
- MRC-PHE Centre for Environment and Health, Environmental Research Group (ERG), King's College London, London, United Kingdom
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3
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van Nunen E, Vermeulen R, Tsai MY, Probst-Hensch N, Ineichen A, Davey M, Imboden M, Ducret-Stich R, Naccarati A, Raffaele D, Ranzi A, Ivaldi C, Galassi C, Nieuwenhuijsen M, Curto A, Donaire-Gonzalez D, Cirach M, Chatzi L, Kampouri M, Vlaanderen J, Meliefste K, Buijtenhuijs D, Brunekreef B, Morley D, Vineis P, Gulliver J, Hoek G. Land Use Regression Models for Ultrafine Particles in Six European Areas. Environ Sci Technol 2017; 51:3336-3345. [PMID: 28244744 DOI: 10.1021/acs.est.6b0592010.1021/acs.est.6b05920.s001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht ("The Netherlands"), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31-50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R2 of local models were similar within, but varied between areas (e.g., 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R2 was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.
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Affiliation(s)
- Erik van Nunen
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
| | - Ming-Yi Tsai
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
- University of Basel , Basel, Switzerland
- Department of Environmental and Occupational Health Sciences, University of Washington , Seattle, Washington United States
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
- University of Basel , Basel, Switzerland
| | - Alex Ineichen
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
- University of Basel , Basel, Switzerland
| | - Mark Davey
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
- University of Basel , Basel, Switzerland
| | - Medea Imboden
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
- University of Basel , Basel, Switzerland
| | - Regina Ducret-Stich
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
- University of Basel , Basel, Switzerland
| | | | | | - Andrea Ranzi
- Environmental Health Reference Centre, Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, Modena, Italy
| | | | - Claudia Galassi
- Unit of Cancer Epidemiology, Citta' della Salute e della Scienza University Hospital and Centre for Cancer Prevention, Turin, Italy
| | - Mark Nieuwenhuijsen
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF) , Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - Ariadna Curto
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF) , Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - David Donaire-Gonzalez
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF) , Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - Marta Cirach
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF) , Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain
| | - Leda Chatzi
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
- Swiss Tropical and Public Health (TPH) Institute, University of Basel , Basel, Switzerland
| | - Mariza Kampouri
- Department of Social Medicine, University of Crete , Heraklion, Greece
| | - Jelle Vlaanderen
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
| | - Kees Meliefste
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
| | - Daan Buijtenhuijs
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
| | - David Morley
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London , St Mary's Campus, London, United Kingdom
| | - Paolo Vineis
- Human Genetics Foundation , Turin, Italy
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London , St Mary's Campus, London, United Kingdom
| | - John Gulliver
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London , St Mary's Campus, London, United Kingdom
| | - Gerard Hoek
- Institute for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology (EEPI), Utrecht University , Utrecht, The Netherlands
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4
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van Nunen E, Vermeulen R, Tsai MY, Probst-Hensch N, Ineichen A, Davey M, Imboden M, Ducret-Stich R, Naccarati A, Raffaele D, Ranzi A, Ivaldi C, Galassi C, Nieuwenhuijsen M, Curto A, Donaire-Gonzalez D, Cirach M, Chatzi L, Kampouri M, Vlaanderen J, Meliefste K, Buijtenhuijs D, Brunekreef B, Morley D, Vineis P, Gulliver J, Hoek G. Land Use Regression Models for Ultrafine Particles in Six European Areas. Environ Sci Technol 2017; 51:3336-3345. [PMID: 28244744 PMCID: PMC5362744 DOI: 10.1021/acs.est.6b05920] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Revised: 02/26/2017] [Accepted: 02/28/2017] [Indexed: 05/17/2023]
Abstract
Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht ("The Netherlands"), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160-240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31-50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R2 of local models were similar within, but varied between areas (e.g., 38-43% Turin; 25-31% Sabadell). Robustness of predictions within areas was high (ICC 0.73-0.98). External validation R2 was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93-1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.
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Affiliation(s)
- Erik van Nunen
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
- Phone: +31 30 253 9474; e-mail:
| | - Roel Vermeulen
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
| | - Ming-Yi Tsai
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
- University
of Basel, Basel, Switzerland
- Department
of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington United States
| | - Nicole Probst-Hensch
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
- University
of Basel, Basel, Switzerland
| | - Alex Ineichen
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
- University
of Basel, Basel, Switzerland
| | - Mark Davey
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
- University
of Basel, Basel, Switzerland
| | - Medea Imboden
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
- University
of Basel, Basel, Switzerland
| | - Regina Ducret-Stich
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
- University
of Basel, Basel, Switzerland
| | | | | | - Andrea Ranzi
- Environmental Health
Reference Centre, Regional Agency for Prevention, Environment and
Energy of Emilia-Romagna, Modena, Italy
| | | | - Claudia Galassi
- Unit of
Cancer
Epidemiology, Citta’ della Salute e della Scienza University
Hospital and Centre for Cancer Prevention, Turin, Italy
| | - Mark Nieuwenhuijsen
- ISGlobal, Centre
for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department
of Experimental and Health Sciences, Pompeu
Fabra University (UPF), Barcelona, Spain
- CIBER Epidemiologia
y Salud Pública (CIBERESP), Barcelona, Spain
| | - Ariadna Curto
- ISGlobal, Centre
for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department
of Experimental and Health Sciences, Pompeu
Fabra University (UPF), Barcelona, Spain
- CIBER Epidemiologia
y Salud Pública (CIBERESP), Barcelona, Spain
| | - David Donaire-Gonzalez
- ISGlobal, Centre
for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department
of Experimental and Health Sciences, Pompeu
Fabra University (UPF), Barcelona, Spain
- CIBER Epidemiologia
y Salud Pública (CIBERESP), Barcelona, Spain
| | - Marta Cirach
- ISGlobal, Centre
for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Department
of Experimental and Health Sciences, Pompeu
Fabra University (UPF), Barcelona, Spain
- CIBER Epidemiologia
y Salud Pública (CIBERESP), Barcelona, Spain
| | - Leda Chatzi
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
- Swiss
Tropical and Public Health (TPH) Institute, University of Basel, Basel, Switzerland
| | - Mariza Kampouri
- Department
of Social Medicine, University of Crete, Heraklion, Greece
| | - Jelle Vlaanderen
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
| | - Kees Meliefste
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
| | - Daan Buijtenhuijs
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
| | - Bert Brunekreef
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
| | - David Morley
- MRC-PHE
Centre
for Environment and Health, Department of Epidemiology
and Biostatistics, Imperial College London, St Mary’s Campus, London, United Kingdom
| | - Paolo Vineis
- Human
Genetics Foundation, Turin, Italy
- MRC-PHE
Centre
for Environment and Health, Department of Epidemiology
and Biostatistics, Imperial College London, St Mary’s Campus, London, United Kingdom
| | - John Gulliver
- MRC-PHE
Centre
for Environment and Health, Department of Epidemiology
and Biostatistics, Imperial College London, St Mary’s Campus, London, United Kingdom
| | - Gerard Hoek
- Institute
for Risk Assessment Sciences (IRAS), division of Environmental Epidemiology
(EEPI), Utrecht University, Utrecht, The Netherlands
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5
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Eeftens M, Meier R, Schindler C, Aguilera I, Phuleria H, Ineichen A, Davey M, Ducret-Stich R, Keidel D, Probst-Hensch N, Künzli N, Tsai MY. Development of land use regression models for nitrogen dioxide, ultrafine particles, lung deposited surface area, and four other markers of particulate matter pollution in the Swiss SAPALDIA regions. Environ Health 2016; 15:53. [PMID: 27089921 PMCID: PMC4835865 DOI: 10.1186/s12940-016-0137-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Accepted: 04/11/2016] [Indexed: 05/17/2023]
Abstract
BACKGROUND Land Use Regression (LUR) is a popular method to explain and predict spatial contrasts in air pollution concentrations, but LUR models for ultrafine particles, such as particle number concentration (PNC) are especially scarce. Moreover, no models have been previously presented for the lung deposited surface area (LDSA) of ultrafine particles. The additional value of ultrafine particle metrics has not been well investigated due to lack of exposure measurements and models. METHODS Air pollution measurements were performed in 2011 and 2012 in the eight areas of the Swiss SAPALDIA study at up to 40 sites per area for NO2 and at 20 sites in four areas for markers of particulate air pollution. We developed multi-area LUR models for biannual average concentrations of PM2.5, PM2.5 absorbance, PM10, PMcoarse, PNC and LDSA, as well as alpine, non-alpine and study area specific models for NO2, using predictor variables which were available at a national level. Models were validated using leave-one-out cross-validation, as well as independent external validation with routine monitoring data. RESULTS Model explained variance (R(2)) was moderate for the various PM mass fractions PM2.5 (0.57), PM10 (0.63) and PMcoarse (0.45), and was high for PM2.5 absorbance (0.81), PNC (0.87) and LDSA (0.91). Study-area specific LUR models for NO2 (R(2) range 0.52-0.89) outperformed combined-area alpine (R (2) = 0.53) and non-alpine (R (2) = 0.65) models in terms of both cross-validation and independent external validation, and were better able to account for between-area variability. Predictor variables related to traffic and national dispersion model estimates were important predictors. CONCLUSIONS LUR models for all pollutants captured spatial variability of long-term average concentrations, performed adequately in validation, and could be successfully applied to the SAPALDIA cohort. Dispersion model predictions or area indicators served well to capture the between area variance. For NO2, applying study-area specific models was preferable over applying combined-area alpine/non-alpine models. Correlations between pollutants were higher in the model predictions than in the measurements, so it will remain challenging to disentangle their health effects.
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Affiliation(s)
- Marloes Eeftens
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
| | - Reto Meier
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Christian Schindler
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Inmaculada Aguilera
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Harish Phuleria
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
- CESE, Indian Institute of Technology Bombay, Mumbai, India
| | - Alex Ineichen
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Mark Davey
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, USA
| | - Regina Ducret-Stich
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Dirk Keidel
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Nino Künzli
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Ming-Yi Tsai
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Socinstrasse 57, P.O. Box 4002, Basel, Switzerland
- University of Basel, Basel, Switzerland
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, USA
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6
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Tsai MY, Hoek G, Eeftens M, de Hoogh K, Beelen R, Beregszászi T, Cesaroni G, Cirach M, Cyrys J, De Nazelle A, de Vocht F, Ducret-Stich R, Eriksen K, Galassi C, Gražuleviciene R, Gražulevicius T, Grivas G, Gryparis A, Heinrich J, Hoffmann B, Iakovides M, Keuken M, Krämer U, Künzli N, Lanki T, Madsen C, Meliefste K, Merritt AS, Mölter A, Mosler G, Nieuwenhuijsen MJ, Pershagen G, Phuleria H, Quass U, Ranzi A, Schaffner E, Sokhi R, Stempfelet M, Stephanou E, Sugiri D, Taimisto P, Tewis M, Udvardy O, Wang M, Brunekreef B. Spatial variation of PM elemental composition between and within 20 European study areas--Results of the ESCAPE project. Environ Int 2015; 84:181-92. [PMID: 26342569 DOI: 10.1016/j.envint.2015.04.015] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Revised: 04/30/2015] [Accepted: 04/30/2015] [Indexed: 05/12/2023]
Abstract
An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements. We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning. PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10. Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.
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Affiliation(s)
- Ming-Yi Tsai
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland; Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands
| | - Marloes Eeftens
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland; Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands
| | - Kees de Hoogh
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland; MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Rob Beelen
- Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands
| | - Timea Beregszászi
- Department of Air Hygiene, National Institute of Environmental Health, Budapest, Hungary
| | - Giulia Cesaroni
- Epidemiology Department, Lazio Regional Health Service, Rome, Italy
| | - Marta Cirach
- Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; IMIM (Hospital del Mar Research Institute), Barcelona, Spain
| | - Josef Cyrys
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology, Neuherberg, Germany; Environmental Science Center, Universität Augsburg, Augsburg, Germany
| | - Audrey De Nazelle
- Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; IMIM (Hospital del Mar Research Institute), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Centre for Environmental Policy, Faculty of Natural Sciences, Imperial College London, London, United Kingdom
| | - Frank de Vocht
- Centre for Occupational and Environmental Health, The University of Manchester, Manchester, England, United Kingdom; School of Social and Community Medicine, University of Bristol, Bristol, England, United Kingdom
| | - Regina Ducret-Stich
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland
| | | | - Claudia Galassi
- AOU Città della Salute e della Scienza - CPO Piemonte, Turin, Italy
| | | | | | - Georgios Grivas
- School of Chemical Engineering, National Technical University of Athens, Greece
| | - Alexandros Gryparis
- Division of Hygiene - Epidemiology, Faculty of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Joachim Heinrich
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Epidemiology, Neuherberg, Germany
| | - Barbara Hoffmann
- IUF Leibniz Research Institute for Environmental Medicine, University of Düsseldorf, Düsseldorf, Germany
| | - Minas Iakovides
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, Greece
| | - Menno Keuken
- TNO, Applied Research Organization, The Netherlands
| | - Ursula Krämer
- IUF Leibniz Research Institute for Environmental Medicine, University of Düsseldorf, Düsseldorf, Germany
| | - Nino Künzli
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland
| | - Timo Lanki
- Department of Environmental Health, National Institute for Health and Welfare (THL), Kuopio, Finland
| | - Christian Madsen
- Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
| | - Kees Meliefste
- Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands
| | - Anne-Sophie Merritt
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Anna Mölter
- Centre for Occupational and Environmental Health, The University of Manchester, Manchester, England, United Kingdom; Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA
| | - Gioia Mosler
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Mark J Nieuwenhuijsen
- Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; IMIM (Hospital del Mar Research Institute), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Harish Phuleria
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland; Centre for Environmental Science and Engineering, Indian Institute of Technology Bombay Powai, Mumbai 400076, India
| | - Ulrich Quass
- Air Quality & Sustainable Nanotachnology, IUTA Institut für Energie- und Umwelttechnik e.V., Duisburg, Germany
| | - Andrea Ranzi
- Regional Reference Centre on Environment and Health, ARPA Emilia Romagna, Modena, Italy
| | - Emmanuel Schaffner
- Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, 4002 Basel, Switzerland; University of Basel, 4003 Basel, Switzerland
| | - Ranjeet Sokhi
- Centre for Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire, College Lane, Hatfield, United Kingdom
| | - Morgane Stempfelet
- French Institute for Public Health Surveillance (InVS), Saint-Maurice Cedex, France
| | - Euripides Stephanou
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, Greece
| | - Dorothea Sugiri
- IUF Leibniz Research Institute for Environmental Medicine, University of Düsseldorf, Düsseldorf, Germany
| | - Pekka Taimisto
- Department of Environmental Health, National Institute for Health and Welfare (THL), Kuopio, Finland
| | - Marjan Tewis
- Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands
| | - Orsolya Udvardy
- Department of Air Hygiene, National Institute of Environmental Health, Budapest, Hungary
| | - Meng Wang
- Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands; Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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7
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Beelen R, Stafoggia M, Raaschou-Nielsen O, Andersen ZJ, Xun WW, Katsouyanni K, Dimakopoulou K, Brunekreef B, Weinmayr G, Hoffmann B, Wolf K, Samoli E, Houthuijs D, Nieuwenhuijsen M, Oudin A, Forsberg B, Olsson D, Salomaa V, Lanki T, Yli-Tuomi T, Oftedal B, Aamodt G, Nafstad P, De Faire U, Pedersen NL, Östenson CG, Fratiglioni L, Penell J, Korek M, Pyko A, Eriksen KT, Tjønneland A, Becker T, Eeftens M, Bots M, Meliefste K, Wang M, Bueno-de-Mesquita B, Sugiri D, Krämer U, Heinrich J, de Hoogh K, Key T, Peters A, Cyrys J, Concin H, Nagel G, Ineichen A, Schaffner E, Probst-Hensch N, Dratva J, Ducret-Stich R, Vilier A, Clavel-Chapelon F, Stempfelet M, Grioni S, Krogh V, Tsai MY, Marcon A, Ricceri F, Sacerdote C, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Tamayo I, Amiano P, Dorronsoro M, Katsoulis M, Trichopoulou A, Vineis P, Hoek G. Long-term exposure to air pollution and cardiovascular mortality: an analysis of 22 European cohorts. Epidemiology 2014; 25:368-78. [PMID: 24589872 DOI: 10.1097/ede.0000000000000076] [Citation(s) in RCA: 190] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. METHODS Data from 22 European cohort studies were used. Using a standardized protocol, study area-specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and 10 μm to 2.5 μm (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. RESULTS The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87-1.69) per 5 μg/m and for PM10, 1.22 (0.91-1.63) per 10 μg/m. CONCLUSION In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.
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Affiliation(s)
- Rob Beelen
- From the aInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; bDepartment of Epidemiology, Lazio Regional Health Service, Rome, Italy; cDanish Cancer Society Research Center, Copenhagen, Denmark; dCenter for Epidemiology and Screening, Department of Public Health, University of Copenhagen, CSS, København K, Denmark; eMRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, United Kingdom; fUniversity College London, CeLSIUS, London, United Kingdom; gDepartment of Hygiene, Epidemiology, and Medical Statistics, Medical School, University of Athens, Athens, Greece; hJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; iInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; jIUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany, and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany; kInstitute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; lNational Institute for Public Health and the Environment, Bilthoven, The Netherlands; mCentre for Research in Environmental Epidemiology (CREAL), Barcelona, and Parc de Recerca Biomèdica de Barcelona-PRBB (office 183.05) C. Doctor Aiguader, Barcelona, Spain; nConsortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Melchor Fernández Almagro 3-5, Madrid, Spain; oDivision of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; pNational Institute for Health and Welfare, Kuopio, Finland; qNorwegian Institute of Public Health, Oslo, Norway; rInstitute of Health and Society, University of Oslo, Oslo, Norway; sInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; tDepartm
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