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Long-term nonlinear relationship between PM2.5 and ten leading causes of death

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Abstract

Air pollution has become a major concern worldwide. Many epidemiological studies have proved relationships between fine particulate matter (PM2.5) 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 PM2.5 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 PM2.5 concentration, PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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.

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Availability of data and materials

The original data used in this study is open access from Taiwan Environmental Protection Administration (TWEPA) Taiwan Air Quality Monitoring Network (https://airtw.epa.gov.tw/ENG/default.aspx).

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Acknowledgments

This study was supported by the Ministry of Science and Technology (Taiwan): Projects MOST 108-2625-M-008-002, MOST 108-2119-M-008-003, MOST 108-2636-E-008-004, MOST 109-2636-E-008-008 (Young Scholar Fellowship Program), and MOST 108-2638-E-008-001-MY2 (Shackleton Program Grant).

Funding

This study was supported by the Ministry of Science and Technology (Taiwan): Projects MOST 108–2625-M-008–002, MOST 108–2119-M-008–003, MOST 108–2636-E-008–004, MOST 109–2636-E-008–008 (Young Scholar Fellowship Program), and MOST 108–2638-E-008–001-MY2 (Shackleton Program Grant).

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Authors and Affiliations

  1. Department of Civil Engineering, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan, 32001, Taiwan

    Yuan-Chien Lin, Hua-San Shih & Chun-Yeh Lai

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  1. Yuan-Chien Lin
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  2. Hua-San Shih
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  3. Chun-Yeh Lai
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Contributions

YCL designed the experiments and funding acquisition, HSS, and CYL collected data, YCL, HSS, and CYL analyzed the data, and YCL and HSS interpreted the results and wrote the manuscript.

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Correspondence to Yuan-Chien Lin.

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All the authors are from the Department of Civil Engineering, National Central University, Taiwan.

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Lin, YC., Shih, HS. & Lai, CY. Long-term nonlinear relationship between PM2.5 and ten leading causes of death. Environ Geochem Health 44, 3967–3990 (2022). https://doi.org/10.1007/s10653-021-01136-1

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