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Comparison of associations between mortality and air pollution exposure estimated with a hybrid, a land-use regression and a dispersion model.

Klompmaker, JO; Janssen, N; Andersen, ZJ; Atkinson, R; Bauwelinck, M; Chen, J; de Hoogh, K; Houthuijs, D; Katsouyanni, K; Marra, M; et al. Klompmaker, JO; Janssen, N; Andersen, ZJ; Atkinson, R; Bauwelinck, M; Chen, J; de Hoogh, K; Houthuijs, D; Katsouyanni, K; Marra, M; Oftedal, B; Rodopoulou, S; Samoli, E; Stafoggia, M; Strak, M; Swart, W; Wesseling, J; Vienneau, D; Brunekreef, B; Hoek, G (2021) Comparison of associations between mortality and air pollution exposure estimated with a hybrid, a land-use regression and a dispersion model. Environ Int, 146. p. 106306. ISSN 1873-6750 https://doi.org/10.1016/j.envint.2020.106306
SGUL Authors: Atkinson, Richard William

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Abstract

INTRODUCTION: To characterize air pollution exposure at a fine spatial scale, different exposure assessment methods have been applied. Comparison of associations with health from different exposure methods are scarce. The aim of this study was to evaluate associations of air pollution based on hybrid, land-use regression (LUR) and dispersion models with natural cause and cause-specific mortality. METHODS: We followed a Dutch national cohort of approximately 10.5 million adults aged 29+ years from 2008 until 2012. We used Cox proportional hazard models with age as underlying time scale and adjusted for several potential individual and area-level socio-economic status confounders to evaluate associations of annual average residential NO2, PM2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models. RESULTS: Spatial variability of PM2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO2 and BC ranged from 0.72 to 0.83; correlations for PM2.5 were slightly lower (0.61-0.72). In general, all three models showed stronger associations of air pollutants with respiratory disease and lung cancer mortality than with natural cause and cardiovascular disease mortality. The strength of the associations differed between the three exposure models. Associations of air pollutants estimated by LUR were generally weaker compared to associations of air pollutants estimated by hybrid and dispersion models. For natural cause mortality, we found a hazard ratio (HR) of 1.030 (95% confidence interval (CI): 1.019, 1.041) per 10 µg/m3 for hybrid modeled NO2, a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m3 for LUR modeled NO2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m3 for dispersion modeled NO2. CONCLUSION: Air pollution was positively associated with natural cause and cause-specific mortality, but the strength of the associations differed between the three exposure models. Our study documents that the selected exposure model may contribute to heterogeneity in effect estimates of associations between air pollution and health.

Item Type: Article
Additional Information: © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Dispersion model, Exposure assessment, LUR model, Mortality, NO(2), PM(2.5), PM2.5, NO2, Exposure assessment, LUR model, Dispersion model, Mortality, Environmental Sciences, MD Multidisciplinary
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: Environ Int
ISSN: 1873-6750
Language: eng
Dates:
DateEvent
January 2021Published
14 December 2020Published Online
26 November 2020Accepted
Publisher License: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Projects:
Project IDFunderFunder ID
4954-RFA14-3/16-5Health Effects Institutehttp://dx.doi.org/10.13039/100001160
S/121004 HERACLESRijksinstituut voor Volksgezondheid en MilieuUNSPECIFIED
4973-RFA19-1/20-7Health Effects Institutehttp://dx.doi.org/10.13039/100001160
PubMed ID: 33395948
Web of Science ID: WOS:000604624700007
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/112869
Publisher's version: https://doi.org/10.1016/j.envint.2020.106306

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