Department of Biostatistics and Epidemiology, School of Public Health, University of North Texas Health Sciences Center, 3500 Camp Bowie Blvd, Fort Worth, TX 76104, USA.
Department of Geography and the Environment, University of North Texas, 1704 W. Mulberry, Denton, TX 76203, USA.
Int J Environ Res Public Health. 2023 Jan 18;20(3):1807. doi: 10.3390/ijerph20031807.
Environmental air pollution remains a major contributor to negative health outcomes and mortality, but the relationship between socially vulnerable populations and air pollution is not well understood. Although air pollution potentially affects everyone, the combination of underlying health, socioeconomic, and demographic factors exacerbate the impact for socially vulnerable population groups, and the United States Clean Air Act (CAA) describes an obligation to protect these populations. This paper seeks to understand how air pollution monitor placement strategies and policy may neglect social vulnerabilities and therefore potentially underestimate exposure burdens in vulnerable populations. Multivariate logistic regression models were used to assess the association between being in an ozone-monitored area or not on 15 vulnerability indicators. It was found that the odds of not being in an ozone-monitored area (not covered, outside) increased for the predictor mobile homes (OR = 4.831, 95% CI [2.500-9.338] and OR = 8.066, 95% CI [4.390-14.820] for the 10 and 20 km spatial units, respectively) and decreased for the predictor multiunit structures (OR = 0.281, 95% CI [0.281-0.548] and OR = 0.130, 95% CI [0.037, 0.457] for the 10 and 20 km spatial units, respectively) and the predictor speaks English "less than well" (OR = 0.521, 95% CI [0.292-0.931] for 10 km). These results indicate that existing pollution sensor coverage may neglect areas with concentrations of highly vulnerable populations in mobile homes, and future monitoring placement policy decisions must work to address this imbalance.
环境空气污染仍然是负面健康结果和死亡的主要原因，但社会弱势群体与空气污染之间的关系尚未得到很好的理解。尽管空气污染可能影响到每个人，但潜在的健康、社会经济和人口因素加剧了社会弱势群体的影响，而美国清洁空气法（CAA）规定了保护这些群体的义务。本文旨在探讨空气污染监测点位置策略和政策如何忽视社会脆弱性，从而可能低估弱势群体的暴露负担。采用多元逻辑回归模型评估了 15 个脆弱性指标与是否处于臭氧监测区之间的关联。结果发现，处于臭氧监测区（未覆盖、外部）的几率降低，对于预测器移动房屋（OR=4.831，95%CI[2.500-9.338]和 OR=8.066，95%CI[4.390-14.820]，对于 10 和 20km 空间单位）和预测器多单元结构（OR=0.281，95%CI[0.281-0.548]和 OR=0.130，95%CI[0.037，0.457]，对于 10 和 20km 空间单位），以及预测器英语“不太好”（OR=0.521，95%CI[0.292-0.931]，对于 10km）。这些结果表明，现有的污染传感器覆盖范围可能忽略了移动房屋中高度脆弱人群浓度较高的区域，未来的监测点位置决策必须努力解决这一不平衡问题。
