ArticleEnvironmental health : a global access science source2016
Air pollution modelling for birth cohorts: a time-space regression model.
Article in Environmental health : a global access science source, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Prenatal exposure to air pollution affects autophagy, senescence and remodelling proteins in cord blood.ERJ open research · 2025Article
- Inequalities in urban air pollution in sub-Saharan Africa: an empirical modeling of ambient NO and NOEnvironmental research letters : ERL [Web site] · 2024Article
- High-resolution patterns and inequalities in ambient fine particle mass (PMThe Science of the total environment · 2023Article
- Long-term exposure to PM2.5 and Children's lung function: a dose-based association analysis.Journal of thoracic disease · 2020Article
- Response of cord blood cells to environmental, hereditary and perinatal factors: A prospective birth cohort study.PloS one · 2018Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo 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.
methodsWe 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.
resultsTraffic 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).
conclusionsThis 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.
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