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PM2.5 and ozone health impacts and disparities in New York City: sensitivity to spatial and temporal resolution

机译：纽约市PM2.5和臭氧对健康的影响和差异：对时空分辨率的敏感性

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Air quality health impact assessment (HIA) synthesizes information about air pollution exposures, health effects, and population vulnerability for regulatory decision-making and public engagement. HIAs often use annual average county or regional data to estimate health outcome incidence rates that vary substantially by season and at the subcounty level. Using New York City as an example, we assessed the sensitivity of estimated citywide morbidity and mortality attributable to ambient fine particulate matter (PM2.5) and ozone to the geographic (county vs. neighborhood) and temporal (seasonal vs. annual average) resolution of health incidence data. We also used the neighborhood-level analysis to assess variation in estimated air pollution impacts by neighborhood poverty concentration. Estimated citywide health impacts attributable to PM2.5 and ozone were relatively insensitive to the geographic resolution of health incidence data. However, the neighborhood-level analysis demonstrated increasing impacts with greater neighborhood poverty levels, particularly for PM2.5-attributable asthma emergency department visits, which were 4.5 times greater in high compared to low-poverty neighborhoods. PM2.5-attributable health impacts were similar using seasonal and annual average incidence rates. Citywide ozone-attributable asthma morbidity was estimated to be 15 % lower when calculated from seasonal, compared to annual average incidence rates, as asthma morbidity rates are lower during the summer ozone season than the annual average rate. Within the ozone season, 57 % of estimated ozone-attributable emergency department for asthma in children occurred in the April–June period when average baseline incidence rates are higher than in the July–September period when ozone concentrations are higher. These analyses underscore the importance of utilizing spatially and temporally resolved data in local air quality impact assessments to characterize the overall city burden and identify areas of high vulnerability.
机译：空气质量健康影响评估（HIA）综合有关空气污染暴露，健康影响和人口脆弱性的信息，以进行监管决策和公众参与。 HIA通常使用县或地区的年度平均数据来估计健康结果发生率，该结果因季节而异，并且在县以下级别上存在很大差异。以纽约市为例，我们评估了估计的全市发病率和死亡率（由环境中的细颗粒物（PM2.5）和臭氧引起）对地理（县与邻里）和时间（季节与年平均）分辨率的敏感性。健康发生率数据。我们还使用了邻里级分析来评估因邻里贫困集中而造成的估计空气污染影响的变化。估计的PM2.5和臭氧对全市范围的健康影响对健康发生率数据的地理分辨率相对不敏感。然而，邻里水平的分析表明，随着邻里贫困水平的提高，影响越来越大，尤其是对PM2.5引起的哮喘急诊就诊而言，高门诊比低贫困邻里高4.5倍。使用季节性和年度平均发病率，可归因于PM2.5的健康影响相似。从季节计算，与年度平均发病率相比，全市臭氧引起的哮喘发病率估计低15％，因为夏季臭氧季节的哮喘发病率低于年度平均发病率。在臭氧季节内，儿童平均臭氧归因于哮喘的急诊科估计有57％发生在4月至6月期间，当时平均基线发病率较高，而7月至9月期间则是臭氧浓度较高。这些分析强调了在当地空气质量影响评估中利用时空分解数据来表征整个城市负担并确定高脆弱性地区的重要性。

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