UC Irvine

Geographic information systems have proven instrumental in assessing environmental impacts on individual and community health, but numerous methodological challenges are associated with analyses of highly localized phenomena in which spatially misaligned data are used. In a case study based on child care facility and traffic data for the Los Angeles metropolitan area, we assessed the extent of facility misclassification with spatially unreconciled data from 3 different governmental agencies in an attempt to identify child care centers in which young children are at risk from high concentrations of toxic vehicle-exhaust pollutants. Relative to geographically corrected data, unreconciled information produced a modest bias in terms of aggregated number of facilities at risk and a substantial number of false positives and negatives.