Analyzing the Relationship between PM 2.5 Levels and Respiratory Disease Incidence in Health Zone 8 of Thailand Using Machine Learning Techniques

Abstract

This study aims to examine the correlation between fine particulate matter (PM 2.5) concentrations and the prevalence of respiratory disorders in Health Zone 8, encompassing provinces in northeastern Thailand, including Loei, Nong Khai, Nong Bua Lam Phu, Udon Thani, Nakhon Phanom, and Sakon Nakhon. This research utilizes secondary data sources, including air quality and PM 2.5 levels from the Pollution Control Department, as well as respiratory disease patient data from the Health Data Center (HDC) of the Ministry of Public Health, spanning from January 1, 2023, to December 31, 2023. The data analysis employs Machine Learning (ML) methodologies to investigate the correlation between PM 2.5 concentrations and the prevalence of respiratory illnesses. Descriptive statistics elucidate the status of PM 2.5 pollution and respiratory disease prevalence, whereas machine learning approaches are utilized to construct models that examine the determinants influencing respiratory disease incidence across various regions and temporal contexts. The results of this research will improve comprehension of PM 2.5 pollution's effects on public health and furnish critical data for devising and implementing effective strategies for monitoring, preventing, and mitigating air pollution challenges in Health Zone 8.