Environmental noise may affect hearing and a variety of non-auditory disease processes. There is some evidence that, like other environmental hazards, noise may be differentially distributed across communities based on socioeconomic status. We aimed to a) predict daytime noise pollution levels and b) assess disparities in daytime noise exposure in Chicago, Illinois. We measured 5-minute daytime noise levels (Leq, 5-min) at 75 randomly selected sites in Chicago in March 2019. Geographically based variables thought to be associated with noise were obtained and used to fit a noise land-use regression model to estimate the daytime environmental noise level at the centroid of the census blocks. Demographic and socioeconomic data were obtained from the City of Chicago for the 77 community areas, and associations with daytime noise levels were assessed using spatial autoregressive models. Mean sampled noise level (Leq, 5-min) was 60.6 dBA. The adjusted R2 and root mean square error of the noise land use regression model and the validation model were 0.60 and 4.67 dBA and 0.51 and 5.90 dBA, respectively. Nearly 75% of city blocks and 85% of city communities have predicted daytime noise level higher than 55 dBA. Of the socioeconomic variables explored, only community per capita income was associated with mean community predicted noise levels and was highest for communities with incomes in the 2nd quartile. Both the noise measurements and land-use regression modeling demonstrate that Chicago has levels of environmental noise likely contributing to the total burden of environmental stressors. Noise is not uniformly distributed across Chicago; it is associated with proximity to roads and public transportation and is higher among communities with mid-to-low incomes per capita, which highlights how socially and economically disadvantaged communities may be disproportionately impacted by this environmental exposure.

Last modified

• 05/01/2024

Creator

• Conroy, Lorraine M.
• Huang, Yu-Kai
• Mitchell, Uchechi A.
• Jones, Rachael M.

Subject

• Environmental Sciences

Language

• English

Identifier

• https://doi.org/10.7278/S50D-SPT1-FNHH

Keyword

• noise
• land use regression
• health disparities
• geospatial data
• environmental exposure

Date created

• 2019-03-01 to 2019-03-31

Location

• Chicago, Illinois, United States

Resource type

• Dataset

Source

• Library of Congress Subject Headings (LCSH)

License

• CC BY NC - Allows others to use and share your data non-commercially and with attribution.