Background: Land Use Regression models (LUR) are useful to estimate the spatial variability of air pollution in urban areas. Few studies have evaluated the stability of spatial contrasts in outdoor nitrogen dioxide (NO2) concentration over several years. We aimed to compare measured and estimated NO2 levels 12 years apart, the stability of the exposure estimates for members of a large cohort study, and the association of the exposure estimates with natural mortality within the cohort. Methods: We measured NO 2 at 67 locations in Rome in 1995/96 and 78 sites in 2007, over three one-week-long periods. To develop LUR models, several land-use and traffic variables were used. NO2 concentration at each residential address was estimated for a cohort of 684,000 adults. We used Cox regression to analyze the association between the two estimated exposures and mortality. Results: The mean NO2 measured concentrations were 45.4 μg/m3 (SD 6.9) in 1995/96 and 44.6 μg/m3 (SD 11.0) in 2007, respectively. The correlation of the two measurements was 0.79. The LUR models resulted in adjusted R2 of 0.737 and 0.704, respectively. The correlation of the predicted exposure values for cohort members was 0.96. The association of each 10 μg/m3 increase in NO2 with mortality was 6 % for 1995/96 and 4 % for 2007 LUR models. The increased risk per an inter-quartile range change was identical (4 %, 95 % CI:36 %) for both estimates of NO2. Conclusions: Measured and predicted NO2 values from LUR models, from samples collected 12 years apart, had good agreement, and the exposure estimates were similarly associated with mortality in a large cohort study. © 2012 Cesaroni et al.; licensee BioMed Central Ltd.
CITATION STYLE
Cesaroni, G., Porta, D., Badaloni, C., Stafoggia, M., Eeftens, M., Meliefste, K., & Forastiere, F. (2012). Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study. Environmental Health: A Global Access Science Source, 11(1). https://doi.org/10.1186/1476-069X-11-48
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