Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 8, 13 November 2023


Open Access | Article

Effect of PM2.5 air pollution on the incidence of respiratory diseases: A Python-based data analysis

Weiping Yan * 1
1 Hangzhou New Channel -Huaer Xinda school

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 8, 70-75
Published 13 November 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Weiping Yan. Effect of PM2.5 air pollution on the incidence of respiratory diseases: A Python-based data analysis. TNS (2023) Vol. 8: 70-75. DOI: 10.54254/2753-8818/8/20240361.

Abstract

Air pollution is a global problem and a serious threat to public health. According to the World Health Organization, 99 percent of the world's population lives in places where air quality guideline standards are exceeded, resulting in 4.2 million premature deaths each year. Air pollution not only leads to respiratory diseases such as respiratory infections, asthma, and chronic obstructive pulmonary disease (COPD), but is also associated with chronic non-communicable diseases such as lung cancer, cardiovascular disease, and diabetes. This study analysed the relationship between the air quality index (AQI) and the incidence of respiratory diseases and found a positive correlation, i.e., the worse the air quality, the more respiratory diseases. This result is consistent with other studies and with the mechanism of the adverse effects of air pollution on the respiratory system. Therefore, this study is important for raising public awareness of the hazards of air pollution and promoting air quality improvement and respiratory health protection. This study also provides valuable information for environmental policy makers to help them consider the impacts of air quality on public health more comprehensively. This study used randomly generated data, so the results may not fully reflect what happens in the real world. Future studies need to use real environmental and health data to validate and extend our findings and provide a more sophisticated model for scenario simulation and analysis.

Keywords

Air Pollution, Air Quality Index, Respiratory Diseases, Linear Regression; Python

References

1. Healthcare Male. Air pollution and respiratory diseases[J]. Healthcare Male,2019(8):215.

2. World Health Organisation. Outdoor air quality and health [EB/OL]. (2018-05-02)[2022-12-19]. https://www.who.int/zh/news-room/fact-sheets/detail/ambient-%28outdoor%29-air-quality-and-health.

3. World Health Organisation. Nine in ten people worldwide breathe polluted air [EB/OL]. (2018-05-02)[2022-12-19]. https://www.who.int/zh/news/item/02-05-2018-9-out-of-10-people-worldwide-breathe-polluted-air-but-more- countries-are-taking-action.

4. sd3212. overview: reducing the burden of respiratory disease due to air pollution [N/OL]. Clove, (2016-12-20) [2022-12-19]. http://chest.dxy.cn/article/506947?trace=hot.

5. ZHANG Y,ZHANG Y,ZHOU M,et al.Burden of mortality and disease attributable to multiple air pollutants in China: a provincial-level analysis[J].The Lancet Planetary Health, 2020,4(9):e376-e386.

6. Huang Suqing.Strategies for using Python programming language in big data analysis[J]. Wireless Internet Technology,2023,20(08):98-100.

7. Zhu Yao. Research on the right-of-way adaptation for people and vehicles in old city streets based on Python data analysis--Taking Guanqian Street in Suzhou as an example[C]// Proceedings of the Architectural Society of China.2022-2023 China Architectural Society. China Architecture Industry Press,2023:505-512.DOI:10.26914/c.cnkihy.2023.019949.

8. Machine Learning; Report Summarises Machine Learning Study Findings from ITMO University (Feature Selection Algorithms as One of the Python Data Analytical Tools)[J]. Robotics & Machine Learning,2020.

9. Shen J. Research and implementation of data analysis visualisation based on Python[J]. Science and Technology Information,2023,21(02):14-17+54.DOI:10.16661/j.cnki.1672-3791.2206-5042-9371.

10. E. P,N. V,S. A, et al. P266 - An EBAMP accredited Python data analysis course for medical physicists[J]. Physica Medica,2021,92(S).

11. Zichun T. Use Python Data Analysis to Gain Insights from Airbnb Hosts[J]. Advances in Mathematical Physics,2021,2021.

12. Machine Learning; Report Summarises Machine Learning Study Findings from ITMO University (Feature Selection Algorithms as One of the Python Data Analytical Tools)[J]. Robotics & Machine Learning,2020.

13. World Health Organisation. Air Pollution [EB/OL]. https://www.who.int/zh/health-topics/air-pollution

14. LI Xiaojuan, ZHANG Zhi, ZHAO Yufang, et al. Research progress on the effects of air pollution on respiratory diseases[J]. China Medicine Herald, 2019, 16(2): 1-4.

15. World Health Organisation. How air pollution damages our health [EB/OL]. https://www.who.int/zh/news-room/spotlight/how-air-pollution-is-destroying-our-health

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 2nd International Conference on Modern Medicine and Global Health
ISBN (Print)
978-1-83558-111-7
ISBN (Online)
978-1-83558-112-4
Published Date
13 November 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/8/20240361
Copyright
13 November 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated