Influence of geocoding quality on environmental exposure assessment of children living near high traffic roads.
BACKGROUND
The widespread availability of powerful geocoding tools in commercial GIS software and the interest in spatial analysis at the individual level have made address geocoding a widely employed technique in epidemiological studies. This study determined the effect of the positional error in street geocoding on the analysis of traffic-related air pollution on children.


METHODS
For a case-study of a large sample of school children in Orange County, Florida (n = 104,865) the positional error of street geocoding was determined through comparison with a parcel database. The effect of this error was evaluated by analyzing the proximity of street and parcel geocoded locations to road segments with high traffic volume and determining the accuracy of the classification using the results of street geocoding. Of the original sample of 163,886 addresses 36% were not used in the final analysis because they could not be reliably geocoded using either street or parcel geocoding. The estimates of positional error can therefore be considered conservative underestimates.


RESULTS
Street geocoding was found to have a median error of 41 meters, a 90th percentile of 100 meters, a 95th percentile of 137 meters and a 99th percentile of 273 meters. These positional errors were found to be non-random in nature and introduced substantial bias and error in the estimates of potential exposure to traffic-related air pollution. Street geocoding was found to consistently over-estimate the number of potentially exposed children at small distances up to 250 meters. False positives and negatives were also found to be very common at these small distances.


CONCLUSIONS
Results of the case-study presented here strongly suggest that typical street geocoding is insufficient for fine-scale analysis and more accurate alternatives need to be considered.
Zandbergen
Paul A
PA
Department of Geography, University of South Florida, Tampa, FL 33620, USA. zandberg@cas.usf.edu
D000393:Air Pollutants / Q000032:analysis*; D004781:Environmental Exposure / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods*; D005431:Florida; D040362:Geographic Information Systems; D006801:Humans; D011237:Predictive Value of Tests; D014505:Urban Population; D001335:Vehicle Emissions / Q000032:analysis*
D000393:Air Pollutants; D001335:Vehicle Emissions