Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study

Giulia Cesaroni,Daniela Porta,Francesco Forastiere,Marloes Eeftens,Massimo Stafoggia,Chiara Badaloni,Kees Meliefste

doi:10.1186/1476-069x-11-48

Abstract

BackgroundLand 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.MethodsWe measured NO2 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.ResultsThe 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:3–6 %) for both estimates of NO2.ConclusionsMeasured 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.

Highlights

Land Use Regression models (LUR) are useful to estimate the spatial variability of air pollution in urban areas
We linked subjects to the Regional Mortality Registry, and collected the date of death and the underlying cause of death (coded to the International Classification of Diseases (ICD) revision 9). We evaluated their vital status until December 2006 and analysed the association between Nitrogen dioxide (NO2) exposure and natural mortality (ICD-9 < 800), taking into account individual characteristics and area-based socioeconomic position, as a surrogate measure of lifestyles and access to health services
When we considered the quintiles of the two distributions as the relevant exposures, we obtained very similar results of increased mortality from natural causes with increasing quintiles of NO2 at residence (HR = 1.10, 95%CI:1.06-1.13 in the 5th quintile compared to the 1st for 1995/96 estimates, and HR = 1.11, 95%CI:1.07-1.14 in the 5th quintile compared to the 1st for 2007 estimates)

Summary

Introduction

Land Use Regression models (LUR) are useful to estimate the spatial variability of air pollution in urban areas. 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. Few studies has challenged this assumption, by comparing the performance of land use regression models over long time periods with measured and predicted levels of pollutants within the same area [18,19]. There are no available studies that have evaluated the performance of the exposure estimates from land use regression models taken several years apart for a resident population, or have investigated the association with mortality

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