An Exploratory Analysis of Sociodemographic Characteristics with Ultrafine Particle Concentrations in Boston, MA

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2022 Mar 30

PMID 35353820

Authors

Katherine L Thayer

Kevin Lane

Matthew C Simon

Doug Brugge

Christina H Fuller

Affiliations

Soon will be listed here.

Abstract

Little is known of the relationship between exposure to the smallest particles of air pollution and socio-demographic characteristics. This paper explores linkages between ultrafine particle (UFP) concentrations and indicators of both race/ethnicity and socioeconomic status in Boston, Massachusetts, USA. We used estimates of UFP based on a highly-resolved land-use regression model of concentrations. In multivariate linear regression models census block groups with high proportions of Asians were associated with higher levels of UFP in comparison to block groups with majority White or other minority groups. Lower UFP concentrations were associated with higher homeownership (indicating higher SES) and with higher female head of household (indicating lower socioeconomic status). One explanation for the results include the proximity of specific groups to traffic corridors that are the main sources of UFP in Boston. Additional studies, especially at higher geographic resolution, are needed in Boston and other major cities to better characterize UFP concentrations by sociodemographic factors.

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References

Jimenez M, Osypuk T, Arevalo S, Tucker K, Falcon L . Neighborhood socioeconomic context and change in allostatic load among older Puerto Ricans: The Boston Puerto Rican health study. Health Place. 2015; 33:1-8. PMC: 4409499. DOI: 10.1016/j.healthplace.2015.02.001. View

Hajat A, Hsia C, ONeill M . Socioeconomic Disparities and Air Pollution Exposure: a Global Review. Curr Environ Health Rep. 2015; 2(4):440-50. PMC: 4626327. DOI: 10.1007/s40572-015-0069-5. View

Simon M, Patton A, Naumova E, Levy J, Kumar P, Brugge D . Combining Measurements from Mobile Monitoring and a Reference Site To Develop Models of Ambient Ultrafine Particle Number Concentration at Residences. Environ Sci Technol. 2018; 52(12):6985-6995. PMC: 8371457. DOI: 10.1021/acs.est.8b00292. View

Oberdorster G . Pulmonary effects of inhaled ultrafine particles. Int Arch Occup Environ Health. 2001; 74(1):1-8. DOI: 10.1007/s004200000185. View

Grineski S, Collins T, Morales D . Asian Americans and disproportionate exposure to carcinogenic hazardous air pollutants: A national study. Soc Sci Med. 2017; 185:71-80. PMC: 5523857. DOI: 10.1016/j.socscimed.2017.05.042. View

Weichenthal S, Van Ryswyk K, Goldstein A, Bagg S, Shekkarizfard M, Hatzopoulou M . A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach. Environ Res. 2016; 146:65-72. DOI: 10.1016/j.envres.2015.12.016. View

Weichenthal S, Van Ryswyk K, Goldstein A, Shekarrizfard M, Hatzopoulou M . Characterizing the spatial distribution of ambient ultrafine particles in Toronto, Canada: A land use regression model. Environ Pollut. 2015; 208(Pt A):241-248. DOI: 10.1016/j.envpol.2015.04.011. View

Clougherty J, Kheirbek I, Eisl H, Ross Z, Pezeshki G, Gorczynski J . Intra-urban spatial variability in wintertime street-level concentrations of multiple combustion-related air pollutants: the New York City Community Air Survey (NYCCAS). J Expo Sci Environ Epidemiol. 2013; 23(3):232-40. DOI: 10.1038/jes.2012.125. View

Cohen A, Brauer M, Burnett R, Anderson H, Frostad J, Estep K . Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015. Lancet. 2017; 389(10082):1907-1918. PMC: 5439030. DOI: 10.1016/S0140-6736(17)30505-6. View

10.

Maantay J . Asthma and air pollution in the Bronx: methodological and data considerations in using GIS for environmental justice and health research. Health Place. 2005; 13(1):32-56. DOI: 10.1016/j.healthplace.2005.09.009. View

11.

Mannocci A, Ciarlo I, DEgidio V, Del Cimmuto A, De Giusti M, Villari P . Socioeconomic Deprivation Status and Air Pollution by PM and NO: An Assessment at Municipal Level of 11 Years in Italy. J Environ Public Health. 2019; 2019:2058467. PMC: 6335678. DOI: 10.1155/2019/2058467. View

12.

Chakraborty J, Maantay J, Brender J . Disproportionate proximity to environmental health hazards: methods, models, and measurement. Am J Public Health. 2011; 101 Suppl 1:S27-36. PMC: 3222485. DOI: 10.2105/AJPH.2010.300109. View

13.

Patton A, Collins C, Naumova E, Zamore W, Brugge D, Durant J . An hourly regression model for ultrafine particles in a near-highway urban area. Environ Sci Technol. 2014; 48(6):3272-80. PMC: 4347899. DOI: 10.1021/es404838k. View

14.

Abernethy R, Allen R, McKendry I, Brauer M . A land use regression model for ultrafine particles in Vancouver, Canada. Environ Sci Technol. 2013; 47(10):5217-25. DOI: 10.1021/es304495s. View

15.

Ohlwein S, Kappeler R, Kutlar Joss M, Kunzli N, Hoffmann B . Health effects of ultrafine particles: a systematic literature review update of epidemiological evidence. Int J Public Health. 2019; 64(4):547-559. DOI: 10.1007/s00038-019-01202-7. View

16.

Patton A, Zamore W, Naumova E, Levy J, Brugge D, Durant J . Transferability and generalizability of regression models of ultrafine particles in urban neighborhoods in the Boston area. Environ Sci Technol. 2015; 49(10):6051-60. PMC: 4440409. DOI: 10.1021/es5061676. View

17.

Kumar P, Morawska L, Birmili W, Paasonen P, Hu M, Kulmala M . Ultrafine particles in cities. Environ Int. 2014; 66:1-10. DOI: 10.1016/j.envint.2014.01.013. View

18.

Shmool J, Kubzansky L, Newman O, Spengler J, Shepard P, Clougherty J . Social stressors and air pollution across New York City communities: a spatial approach for assessing correlations among multiple exposures. Environ Health. 2014; 13:91. PMC: 4240877. DOI: 10.1186/1476-069X-13-91. View

19.

Calderon-Garciduenas L, Reynoso-Robles R, Gonzalez-Maciel A . Combustion and friction-derived nanoparticles and industrial-sourced nanoparticles: The culprit of Alzheimer and Parkinson's diseases. Environ Res. 2019; 176:108574. DOI: 10.1016/j.envres.2019.108574. View

20.

Gray S, Edwards S, Miranda M . Race, socioeconomic status, and air pollution exposure in North Carolina. Environ Res. 2013; 126:152-8. DOI: 10.1016/j.envres.2013.06.005. View