Maggie Li, Markus Hilpert, Jenni A. Shearston, Ana Navas-Acien, and Marianthi-Anna Kioumourtzoglou are with the Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY. Jeff Goldsmith is with the Department of Biostatistics, Columbia University Mailman School of Public Health. Jada L. Brooks is with the University of North Carolina School of Nursing, Chapel Hill. Steven N. Chillrud is with the Lamont-Doherty Earth Observatory, Columbia University. Tauqeer Ali is with the Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City. Jason G. Umans is with the Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC. Lyle G. Best and Joseph Yracheta are with Missouri Breaks Industries Research, Inc., Eagle Butte, SD. Aaron van Donkelaar and Randall V. Martin are with the Department of Energy, Environmental & Chemical Engineering, Washington University, St. Louis, MO.
Am J Public Health. 2022 Apr;112(4):615-623. doi: 10.2105/AJPH.2021.306650.
To compare fine particulate matter (PM) concentrations in American Indian (AI)-populated with those in non-AI-populated counties over time (2000-2018) in the contiguous United States. We used a multicriteria approach to classify counties as AI- or non--AI-populated. We ran linear mixed effects models to estimate the difference in countywide annual PM concentrations from well-validated prediction models and monitoring sites (modeled and measured PM, respectively) in AI- versus non-AI-populated counties. On average, adjusted modeled PM concentrations in AI-populated counties were 0.38 micrograms per cubic meter (95% confidence interval [CI] = 0.23, 0.54) lower than in non-AI-populated counties. However, this difference was not constant over time: in 2000, modeled concentrations in AI-populated counties were 1.46 micrograms per cubic meter (95% CI = 1.25, 1.68) lower, and by 2018, they were 0.66 micrograms per cubic meter (95% CI = 0.45, 0.87) higher. Over the study period, adjusted modeled PM mean concentrations decreased by 2.13 micrograms per cubic meter in AI-populated counties versus 4.26 micrograms per cubic meter in non-AI-populated counties. Results were similar for measured PM. This study highlights disparities in PM trends between AI- and non-AI-populated counties over time, underscoring the need to strengthen air pollution regulations and prevention implementation in tribal territories and areas where AI populations live. (. 2022;112(4): 615-623. https://doi.org/10.2105/AJPH.2021.306650).
为了比较美国印第安人(AI)聚居县和非 AI 聚居县的细颗粒物(PM)浓度随时间的变化(2000-2018 年)。我们使用多标准方法将县分类为 AI 或非 AI 聚居。我们运行线性混合效应模型,根据经过充分验证的预测模型和监测站点(分别为模型化和测量 PM)来估计 AI 聚居县和非 AI 聚居县的全县年度 PM 浓度差异。平均而言,AI 聚居县调整后的模型 PM 浓度比非 AI 聚居县低 0.38 微克/立方米(95%置信区间[CI] = 0.23,0.54)。然而,这种差异并不是一成不变的:2000 年,AI 聚居县的模型浓度低 1.46 微克/立方米(95% CI = 1.25,1.68),到 2018 年,浓度高 0.66 微克/立方米(95% CI = 0.45,0.87)。在研究期间,AI 聚居县调整后的模型 PM 平均浓度下降了 2.13 微克/立方米,而非 AI 聚居县下降了 4.26 微克/立方米。测量 PM 的结果也类似。本研究强调了 AI 聚居县和非 AI 聚居县之间 PM 趋势随时间的差异,这凸显了在部落领土和 AI 人口居住地区加强空气污染法规和预防措施实施的必要性。(. 2022;112(4): 615-623. https://doi.org/10.2105/AJPH.2021.306650)。