基于风险的模型评估交通相关空气污染物的环境正义和冠心病负担。
A risk-based model to assess environmental justice and coronary heart disease burden from traffic-related air pollutants.
机构信息
Center for Healthy Environments & Communities, Department of Environmental & Occupational Health, University of Pittsburgh Graduate School of Public Health, PUBHL-4132, 130 DeSoto Street Pittsburgh, Pittsburgh, PA, 15261, USA.
Allegheny County Health Department, Pittsburgh, PA, USA.
出版信息
Environ Health. 2020 Mar 16;19(1):34. doi: 10.1186/s12940-020-00584-z.
BACKGROUND
Communities need to efficiently estimate the burden from specific pollutants and identify those most at risk to make timely informed policy decisions. We developed a risk-based model to estimate the burden of black carbon (BC) and nitrogen dioxide (NO) on coronary heart disease (CHD) across environmental justice (EJ) and non-EJ populations in Allegheny County, PA.
METHODS
Exposure estimates in census tracts were modeled via land use regression and analyzed in relation to US Census data. Tracts were ranked into quartiles of exposure (Q1-Q4). A risk-based model for estimating the CHD burden attributed to BC and NO was developed using county health statistics, census tract level exposure estimates, and quantitative effect estimates available in the literature.
RESULTS
For both pollutants, the relative occurrence of EJ tracts (> 20% poverty and/or > 30% non-white minority) in Q2 - Q4 compared to Q1 progressively increased and reached a maximum in Q4. EJ tracts were 4 to 25 times more likely to be in the highest quartile of exposure compared to the lowest quartile for BC and NO, respectively. Pollutant-specific risk values (mean [95% CI]) for CHD mortality were higher in EJ tracts (5.49 × 10 [5.05 × 10 - 5.92 × 10]; 5.72 × 10 [5.44 × 10 - 6.01 × 10] for BC and NO, respectively) compared to non-EJ tracts (3.94 × 10 [3.66 × 10 - 4.23 × 10]; 3.49 × 10 [3.27 × 10 - 3.70 × 10] for BC and NO, respectively). While EJ tracts represented 28% of the county population, they accounted for about 40% of the CHD mortality attributed to each pollutant. EJ tracts are disproportionately skewed toward areas of high exposure and EJ residents bear a greater risk for air pollution-related disease compared to other county residents.
CONCLUSIONS
We have combined a risk-based model with spatially resolved long-term exposure estimates to predict CHD burden from air pollution at the census tract level. It provides quantitative estimates of effects that can be used to assess possible health disparities, track temporal changes, and inform timely local community policy decisions. Such an approach can be further expanded to include other pollutants and adverse health endpoints.
背景
社区需要有效地评估特定污染物的负担，并确定最易受影响的人群，以便及时做出明智的政策决策。我们开发了一种基于风险的模型，用于估算宾夕法尼亚州阿勒格尼县环境正义（EJ）和非 EJ 人群中黑碳（BC）和二氧化氮（NO）对冠心病（CHD）的负担。
方法
通过土地使用回归对普查区内的暴露估计值进行建模，并根据美国人口普查数据进行分析。将普查区分为暴露四分位数（Q1-Q4）。使用县卫生统计数据、普查区水平暴露估计值和文献中可用的定量效应估计值，开发了一种用于估算归因于 BC 和 NO 的 CHD 负担的基于风险的模型。
结果
对于这两种污染物，EJ 区（贫困率>20%和/或非白种少数民族比例>30%）在 Q2-Q4 中所占比例相对于 Q1 逐渐增加，在 Q4 中达到最大值。与 BC 和 NO 的最低四分位数相比，EJ 区分别有 4 到 25 倍的可能性处于暴露的最高四分位数。EJ 区的 CHD 死亡率的特定污染物风险值（平均值[95%CI]）高于非 EJ 区（BC 和 NO 分别为 5.49×10[5.05×10-5.92×10]和 5.72×10[5.44×10-6.01×10]）。与非 EJ 区（BC 和 NO 分别为 3.94×10[3.66×10-4.23×10]和 3.49×10[3.27×10-3.70×10]）相比，EJ 区（BC 和 NO 分别为 3.94×10[3.66×10-4.23×10]和 3.49×10[3.27×10-3.70×10]）分别为 3.94×10[3.66×10-4.23×10]和 3.49×10[3.27×10-3.70×10]）。虽然 EJ 区占全县人口的 28%，但它们分别占归因于每种污染物的 CHD 死亡率的约 40%。EJ 区不成比例地偏向于高暴露区，与其他县居民相比，EJ 居民患与空气污染有关的疾病的风险更高。
结论
我们结合了基于风险的模型和空间分辨的长期暴露估计，以在普查区水平上预测空气污染引起的 CHD 负担。它提供了可用于评估可能存在的健康差异、跟踪时间变化和为及时的地方社区政策决策提供信息的影响定量估计。这种方法可以进一步扩展到包括其他污染物和不良健康终点。
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