Purpose

Air particulate matter with an aerodynamic diameter of 10 µm or less (PM₁₀) is one of the main causes of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study explored the relationship between PM₁₀ by remote sensing and AECOPD in Chaharmahal-o-Bakhtiari province from 2014 to2018.

Method

PM₁₀ concentrations were predicted and validated based on aerosol optical depth (AOD) from 161 images processed by MODIS sensor and ground air quality monitoring station data. Demographic information and spirometric indices of 2038 patients with AECOPD were collected and analyzed from the hospital during the studied periods. SPSS software was used to analyze the relationships between these two categories of information.

Results

There was a significant negative relationship between PM10 and FVC, FVC%, FEV1, FEV1%, FEF25-75, FEV1/FVC, PEF, and FEF25FVC indices (p < 0.05). The results showed that over 2014–2018, the annual mean of PM10 concentrations varied from 35 to 52 µg/m3. The result of the regression model showed that the patient’s age, body mass index (BMI), and PM₁₀ concentrations were the most affecting variables on the two important spirometric indices i.e., FVC% and FEV₁%. The PM₁₀ concentrations and number of AECOPD patients had a similar pattern during the studied period. The women group, age group above 74 years, normal BMI, and non-smoking patients showed the most sensitivity to the PM₁₀ concentrations.

Conclusions

Our findings provide supplementary scientific information on PM₁₀ concentration related to the incidence of AECOPD and as a variable affecting the most important spirometry indicators by providing local decision-makers information needed to set a priority of air pollution control measures as well as health services.

中文翻译：

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环境空气颗粒物 (PM 10 ) 卫星监测和呼吸健康影响评估

目的

空气动力学直径小于或等于10微米的空气颗粒物（PM ₁₀）是慢性阻塞性肺疾病（AECOPD）急性加重的主要原因之一。本研究探讨了2014-2018年Chaharmahal-o-Bakhtiari省的遥感PM ₁₀与AECOPD之间的关系。

方法

根据 MODIS 传感器处理的 161 幅图像和地面空气质量监测站数据的气溶胶光学深度 (AOD) 预测和验证PM _10浓度。在研究期间从医院收集和分析了 2038 名 AECOPD 患者的人口统计信息和肺活量指标。SPSS软件用于分析这两类信息之间的关系。

结果

PM10 与 FVC、FVC%、FEV1、FEV1%、FEF25-75、FEV1/FVC、PEF 和 FEF25FVC 指数呈显着负相关（p < 0.05）。结果显示，2014-2018 年间，PM10 浓度年均值在 35 至 52 µg/m3 之间变化。回归模型的结果表明，患者的年龄、体重指数（BMI）和PM ₁₀浓度是对两个重要的肺活量指标FVC%和FEV ₁ %影响最大的变量。在研究期间，PM _{10浓度和 AECOPD 患者数量具有相似的模式。}女性组、74 岁以上年龄组、正常 BMI 和不吸烟患者对 PM ₁₀浓度最敏感。

结论

_{我们的研究结果提供了与 AECOPD 发病率相关的 PM 10}浓度的补充科学信息，并通过为当地决策者提供设定空气污染控制措施和卫生服务优先级所需的信息，作为影响最重要肺活量指标的变量。