Health effects of ambient air pollution: do different methods for estimating exposure lead to different results?
2014
Abstract Background Spatially resolved exposure models are increasingly used in epidemiology. We previously reported that, although exhibiting a moderate correlation, pregnancy nitrogen dioxide (NO 2 ) levels estimated by the nearest air quality monitoring station (AQMS) model and a geostatistical model, showed similar associations with infant birth weight. Objectives We extended this study by comparing a total of four exposure models, including two highly spatially resolved models: a land-use regression (LUR) model and a dispersion model. Comparisons were made in terms of predicted NO 2 and particle (aerodynamic diameter 10 ) exposure and adjusted association with birth weight. Methods The four exposure models were implemented in two French metropolitan areas where 1026 pregnant women were followed as part of the EDEN mother–child cohort. Results Correlations between model predictions were high (≥ 0.70), except for NO 2 between the AQMS and both the LUR (r = 0.54) and dispersion models (r = 0.63). Spatial variations as estimated by the AQMS model were greater for NO 2 (95%) than for PM 10 (22%). The direction of effect estimates of NO 2 on birth weight varied according to the exposure model, while PM 10 effect estimates were more consistent across exposure models. Conclusions For PM 10 , highly spatially resolved exposure model agreed with the poor spatial resolution AQMS model in terms of estimated pollutant levels and health effects. For more spatially heterogeneous pollutants like NO 2 , although predicted levels from spatially resolved models (all but AQMS) agreed with each other, our results suggest that some may disagree with each other as well as with the AQMS regarding the direction of the estimated health effects.
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