摘要：Objectives. Although differential exposure by socioeconomic position (SEP) to hazardous waste and lead is well demonstrated, there is less evidence for particulate air pollution (PM), which is associated with risk of death and illness. This study determined the relationship of ambient PM and SEP across several spatial scales. Methods. Geographic information system-based, spatio-temporal models were used to predict PM in the Northeastern United States. Predicted concentrations were related to census tract SEP and racial composition using generalized additive models. Results. Lower SEP was associated with small, significant increases in PM. Annual PM10 decreased between 0.09 and 0.93 micrograms per cubic meter and PM2.5 between 0.02 and 0.94 micrograms per cubic meter for interquartile range increases in income. Decrements in PM with SEP increased with spatial scale, indicating that between-city spatial gradients were greater than within-city differences. The PM–SEP relation in urban tracts was not substantially modified by racial composition. Conclusions. Lower compared with higher SEP populations were exposed to higher ambient PM in the Northeastern United States. Given the small percentage change in annual PM2.5 and PM10, SEP was not likely a major source of confounding in epidemiological studies of PM, especially those conducted within a single urban/metropolitan area. Although exposure to some pollutants, such as lead, is clearly associated with race/ethnicity and socioeconomic position (SEP), there is less evidence for particulate air pollution (PM). Further, a key issue in epidemiological studies of air pollution was whether findings were confounded or modified by SEP. 1 – 6 Previous studies generally found lower SEP areas to have higher air pollutant exposures, specifically to total suspended particles in Hamilton, Ontario 7 , 8 and to traffic pollution. 9 These studies relied on existing PM monitoring networks, which generally limited their focus to single urban areas. As a result, the spatial scale for which confounding or effect modification by SEP is most important is not well understood. In this study, recently developed and validated air pollution models were used to predict annual PM10 and PM2.5 levels across the Northeastern United States. The study examined whether areas with lower SEP were associated with higher annual PM pollution levels and whether the associations of SEP and PM exposure were consistent across multiple spatial scales.
