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Air pollution modelling for birth cohorts: a time-space regression model
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 3565001
Author(s) Proietti, Elena; Delgado-Eckert, Edgar; Vienneau, Danielle; Stern, Georgette; Tsai, Ming-Yi; Latzin, Philipp; Frey, Urs; Röösli, Martin
Author(s) at UniBasel Röösli, Martin
Vienneau, Danielle
Tsai, Ming-Yi
Frey, Urs Peter
Delgado-Eckert, Edgar
Year 2016
Title Air pollution modelling for birth cohorts: a time-space regression model
Journal Environmental Health
Volume 15
Number 1
Pages / Article-Number 61
Mesh terms Air Pollutants, analysis; Air Pollution, analysis; Environmental Exposure, analysis; Humans; Models, Theoretical; Nitrogen Dioxide, analysis; Regression Analysis; Switzerland
Abstract To investigate air pollution effects during pregnancy or in the first weeks of life, models are needed that capture both the spatial and temporal variability of air pollution exposures.; We developed a time-space exposure model for ambient NO2 concentrations in Bern, Switzerland. We used NO2 data from passive monitoring conducted between 1998 and 2009: 101 rural sites (24,499 biweekly measurements) and 45 urban sites (4350 monthly measurements). We evaluated spatial predictors (land use; roads; traffic; population; annual NO2 from a dispersion model) and temporal predictors (meteorological conditions; NO2 from continuous monitoring station). Separate rural and urban models were developed by multivariable regression techniques. We performed ten-fold internal cross-validation, and an external validation using 57 NO2 passive measurements obtained at study participant's homes.; Traffic related explanatory variables and fixed site NO2 measurements were the most relevant predictors in both models. The coefficient of determination (R(2)) for the log transformed models were 0.63 (rural) and 0.54 (urban); cross-validation R(2)s were unchanged indicating robust coefficient estimates. External validation showed R(2)s of 0.54 (rural) and 0.67 (urban).; This approach is suitable for air pollution exposure prediction in epidemiologic research with time-vulnerable health effects such as those occurring during pregnancy or in the first weeks of life.
Publisher BioMed Central
ISSN/ISBN 1476-069X
edoc-URL http://edoc.unibas.ch/43610/
Full Text on edoc Available
Digital Object Identifier DOI 10.1186/s12940-016-0145-9
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/27225793
ISI-Number 000376666500001
Document type (ISI) Journal Article
 
   

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