{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T13:26:49Z","timestamp":1791293209478,"version":"4.1.0"},"reference-count":43,"publisher":"American Chemical Society (ACS)","issue":"11-12","license":[{"start":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T00:00:00Z","timestamp":1514505600000},"content-version":"vor","delay-in-days":1554,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Background: Although research has shown that low socioeconomic status (SES) and minority communities have higher exposure to air pollution, few studies have simultaneously investigated the associations of individual and neighborhood SES with pollutants across multiple sites.<\/jats:p>\n                  <jats:p>Objectives: We characterized the distribution of ambient air pollution by both individual and neighborhood SES using spatial regression methods.<\/jats:p>\n                  <jats:p>Methods: The study population comprised 6,140 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Year 2000 annual average ambient PM2.5 and NOx concentrations were calculated for each study participant\u2019s home address at baseline examination. We investigated individual and neighborhood (2000 U.S. Census tract level) SES measures corresponding to the domains of income, wealth, education, and occupation. We used a spatial intrinsic conditional autoregressive model for multivariable analysis and examined pooled and metropolitan area\u2013specific models.<\/jats:p>\n                  <jats:p>Results: A 1-unit increase in the z-score for family income was associated with 0.03-\u03bcg\/m3 lower PM2.5 (95% CI: \u20130.05, \u20130.01) and 0.93% lower NOx (95% CI: \u20131.33, \u20130.53) after adjustment for covariates. A 1-SD\u2013unit increase in the neighborhood\u2019s percentage of persons with at least a high school degree was associated with 0.47-\u03bcg\/m3 lower mean PM2.5 (95% CI: \u20130.55, \u20130.40) and 9.61% lower NOx (95% CI: \u201310.85, \u20138.37). Metropolitan area\u2013specific results exhibited considerable heterogeneity. For example, in New York, high-SES neighborhoods were associated with higher concentrations of pollution.<\/jats:p>\n                  <jats:p>Conclusions: We found statistically significant associations of SES measures with predicted air pollutant concentrations, demonstrating the importance of accounting for neighborhood- and individual-level SES in air pollution health effects research.<\/jats:p>\n                  <jats:p>Citation: Hajat A, Diez-Roux AV, Adar SD, Auchincloss AH, Lovasi GS, O\u2019Neill MS, Sheppard L, Kaufman JD. 2013. Air pollution and individual and neighborhood socioeconomic status: evidence from the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect 121:1325\u20131333;\u2002http:\/\/dx.doi.org\/10.1289\/ehp.1206337<\/jats:p>","DOI":"10.1289\/ehp.1206337","type":"journal-article","created":{"date-parts":[[2013,9,27]],"date-time":"2013-09-27T13:43:55Z","timestamp":1380289435000},"page":"1325-1333","source":"Crossref","is-referenced-by-count":248,"title":["Air Pollution and Individual and Neighborhood Socioeconomic Status: Evidence from the Multi-Ethnic Study of Atherosclerosis (MESA)"],"prefix":"10.1021","volume":"121","author":[{"given":"Anjum","family":"Hajat","sequence":"first","affiliation":[{"name":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana V.","family":"Diez-Roux","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara D.","family":"Adar","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy H.","family":"Auchincloss","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gina S.","family":"Lovasi","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Columbia University, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marie S.","family":"O\u2019Neill","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA"},{"name":"Department of Environmental Health Sciences and Risk Science Center, University of Michigan, Ann Arbor, Michigan, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianne","family":"Sheppard","sequence":"additional","affiliation":[{"name":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA"},{"name":"Department of Biostatistics, University of Washington, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel D.","family":"Kaufman","sequence":"additional","affiliation":[{"name":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2013,9,27]]},"reference":[{"key":"2026080601015445600_micit1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1111\/j.1749-6632.2009.05337.x","article-title":"Health disparities across the lifespan: meaning, methods, and 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