Fine particulate matter composition in American Indian vs. Non-American Indian communities

Maggie Li; Vivian Do; Jada L Brooks; Markus Hilpert; Jeff Goldsmith; Steven N Chillrud; Tauqeer Ali; Lyle G Best; Joseph Yracheta; Jason G Umans; Aaron van Donkelaar; Randall V Martin; Ana Navas-Acien; Marianthi-Anna Kioumourtzoglou

doi:10.1016/j.envres.2023.117091

Fine particulate matter composition in American Indian vs. Non-American Indian communities

Environ Res. 2023 Nov 15;237(Pt 2):117091. doi: 10.1016/j.envres.2023.117091. Epub 2023 Sep 6.

Authors

Affiliations

¹ Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA. Electronic address: ml4424@cumc.columbia.edu.
² Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
³ University of North Carolina School of Nursing, Chapel Hill, NC, USA.
⁴ Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA.
⁵ Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA.
⁶ Department of Biostatistics and Epidemiology, Center for American Indian Health Research, Hudson College of Public Health, University of Oklahoma Health Sciences Center, OK, USA.
⁷ Missouri Breaks Industries Research, Inc., Eagle Butte, SD, USA.
⁸ Native BioData Consortium, Eagle Butte, SD, USA.
⁹ MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown/Howard Universities Center for Clinical and Translational Sciences, Washington, DC, USA.
¹⁰ Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO, USA.

PMID: 37683786
PMCID: PMC10591960 (available on 2024-11-15)
DOI: 10.1016/j.envres.2023.117091

Abstract

Background: Fine particulate matter (PM_2.5) exposure is a known risk factor for numerous adverse health outcomes, with varying estimates of component-specific effects. Populations with compromised health conditions such as diabetes can be more sensitive to the health impacts of air pollution exposure. Recent trends in PM_2.5 in primarily American Indian- (AI-) populated areas examined in previous work declined more gradually compared to the declines observed in the rest of the US. To further investigate components contributing to these findings, we compared trends in concentrations of six PM_2.5 components in AI- vs. non-AI-populated counties over time (2000-2017) in the contiguous US.

Methods: We implemented component-specific linear mixed models to estimate differences in annual county-level concentrations of sulfate, nitrate, ammonium, organic matter, black carbon, and mineral dust from well-validated surface PM_2.5 models in AI- vs. non-AI-populated counties, using a multi-criteria approach to classify counties as AI- or non-AI-populated. Models adjusted for population density and median household income. We included interaction terms with calendar year to estimate whether concentration differences in AI- vs. non-AI-populated counties varied over time.

Results: Our final analysis included 3108 counties, with 199 (6.4%) classified as AI-populated. On average across the study period, adjusted concentrations of all six PM_2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific levels in AI- vs. non-AI-populated counties varied over time: sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties before 2011 but higher after 2011 and nitrate levels were consistently lower in AI-populated counties.

Conclusions: This study indicates time trend differences of specific components by AI-populated county type. Notably, decreases in sulfate and ammonium may contribute to steeper declines in total PM_2.5 in non-AI vs. AI-populated counties. These findings provide potential directives for additional monitoring and regulations of key emissions sources impacting tribal lands.

Keywords: Air pollution; American Indian; Environmental health; Environmental justice.

Abstract

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