Department of Civil Engineering, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan, 32001, Taiwan.
Environ Geochem Health. 2022 Nov;44(11):3967-3990. doi: 10.1007/s10653-021-01136-1. Epub 2021 Nov 13.
Air pollution has become a major concern worldwide. Many epidemiological studies have proved relationships between fine particulate matter (PM) and various diseases, but most studies only use short-term and models for specific groups to derive relationships with acute diseases. This makes it difficult to understand long-term exposure, nonlinear relationships, and spatial-temporal health risks regarding chronic diseases. Therefore, this study proposed to analyze and map PM exceedance probability from long-term spatial-temporal monitoring data using radial basis function estimation. We then constructed and compared multiple linear regression and generalized additive models to investigate linear and nonlinear relationships between long-term average PM concentration, PM potential probability for exceeding the standard, and standardized mortality for the top ten causes of death in all towns and villages in Taiwan nationally from 2010 to 2017. Linear models indicate that increasing PM concentration increased malignant neoplasm, pneumonia, and chronic lower respiratory disease mortalities; chronic liver diseases; and cirrhosis; whereas heart diseases and esophagus cancer mortality decreased. For the nonlinear model results, it can be found that there were also significant nonlinear relationships between PM concentration and malignant mortalities for neoplasm, heart disease, diabetes; and trachea, bronchus, lung, liver, intrahepatic bile duct, and esophagus cancer. Thus, long-term exposure to PM may be a significant risk factor for multiple acute and chronic diseases. Results from this study can be directly applied worldwide to provide air quality and health management references for governments, and important information on long-term health risks for local residents in the study area.
空气污染已成为全球关注的主要问题。许多流行病学研究已经证明了细颗粒物 (PM) 与各种疾病之间的关系，但大多数研究仅使用短期和特定人群的模型来推导出与急性疾病的关系。这使得人们难以理解慢性疾病的长期暴露、非线性关系和时空健康风险。因此，本研究提出了一种分析和绘制来自长期时空监测数据的 PM 超标概率的方法，使用径向基函数估计。然后，我们构建并比较了多元线性回归和广义加性模型，以研究 2010 年至 2017 年台湾全国所有乡镇长期平均 PM 浓度、PM 超标概率和十大死因标准化死亡率之间的线性和非线性关系。线性模型表明，PM 浓度的增加会增加恶性肿瘤、肺炎和慢性下呼吸道疾病的死亡率；慢性肝病和肝硬化；而心脏病和食道癌的死亡率则下降。对于非线性模型的结果，可以发现 PM 浓度与恶性肿瘤、心脏病、糖尿病以及气管、支气管、肺、肝、肝内胆管和食道癌的死亡率之间也存在显著的非线性关系。因此，长期暴露于 PM 可能是多种急性和慢性疾病的重要危险因素。本研究的结果可以直接在全球范围内应用，为政府提供空气质量和健康管理参考，并为研究区域的当地居民提供重要的长期健康风险信息。
