Abstract
ISEE-522 Introduction: Small area health studies are part of a monitoring program on environment and health around the international airport Schiphol, the Netherlands, which aims to keep a close watch on the impact on health during the ongoing expansion of Schiphol. To monitor the long-term spatial pattern of disease prevalences and incidences around the airport, we use routinely collected health data from national medical registries on e.g., hospitalization. We wanted to develop a method of environmental noise exposure characterization for use in our small area health studies, that meets the following requirements: (1) the aggregated exposure estimate should be a reasonable predictor of residential exposure levels; (2) it should provide us with sufficient variance in exposure, corresponding to the actual variance in exposure; (3) it should be stable over the years; and (4) its spatial distribution should be in line with the actual exposure distribution. Methods: With use of GIS, noise exposure grid data of air traffic (Lden and Lnight, years 1998-2001) and road traffic (Lden, composite years 2000-2002), in an area of 55 by 55 square kilometers around Schiphol airport, were combined with residential address coordinates, assigning an exposure level to each address. Two noise indicators, based on only residential addresses, were calculated for each 4 digit postal code area (PCA): (1) the average noise level; and (2) the percentage of residential addresses above a certain noise threshold. Analyses of variance were carried out, and maps of the noise indicators on postcode level were produced. Results: Analyses of air and road traffic noise demonstrated different outcomes: within PCAs, road traffic noise showed relatively more variance (44% of total variance) than air traffic noise (3% of total variance), the latter showing large variation between PCAs (97%), as well as within years (98%) compared to between years (2%). For air traffic noise, best results were met with the PCA-average indicators (Cv 11% - 17%), for road traffic noise results were not conclusive. Conclusions: Misclassification in small area exposure indicators can be substantially reduced when the average is derived from individual address estimates, when opposed to surface area averages. Outcomes differ between air and road traffic noise, resulting in lower power in small area health studies on road traffic noise. The spatial distributions of the chosen indicators were satisfactory. The PCA-average indicator is best to use in studies on air traffic noise, for road traffic noise it has to be explored which indicator performs best.
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