Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the Contiguous United States

BACKGROUND: Prior research has reported disparities in environmental exposures in the United States, hut, to our knowledge, no nationwide studies have assessed inequality in noise pollution. OBJECTIVES: We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and I)) consider the modifying role of metropolitan level racial residential segregation. METHODS: We used a geospatial sound model to estimate census block group level median (L-50) nighttime and daytime noise exposure and 90th percentile (L-10) daytime noise exposure. Block group variables from the 2006-2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index. RESULTS: Generally, estimated nighttime and daytime noise levels were higher for census block groups with higher proportions of nonwhite and lower-socioeconomic status (SES) residents. For example, estimated nighttime noise levels in urban block groups with 75% vs. 0% black residents were 46.3 A-weighted decibels (dBA) [interquartile range (IQR): 44.3-47.8 dBA] and 42.3 (IBA (IQR: 40.4-45.5 dBA), respectively. In urban block groups with 50% vs. 0% of residents living below poverty, estimated nighttime noise levels were 46.9 dBA (IQR: 44.7-48.5 dBA) and 44.0 dBA (IQR: 42.2-45.5 dBA), respectively. Block groups with the highest metropolitan area segregation had the highest estimated noise exposures, regardless of racial composition. Results were generally consistent between urban and suburban/rural census block groups, and for daytime and nighttime noise and robust to different spatial weight and neighbor definitions. CONCLUSIONS: We found evidence of racial/ethnic and socioeconomic differences in model-based estimates of noise exposure throughout the United States. Additional research is needed to determine if differences in noise exposure may contribute to health disparities in the United Stales.