Correlation Analysis of Particulate Matter Exposure and Respiratory Function Decline using Multivariate Statistical Modeling

Abstract

The progressive deterioration of air quality in urban environments has necessitated a rigorous examination of the relationship between atmospheric pollutants and human health. This study presents a comprehensive correlation analysis focused on the impact of particulate matter, specifically aerodynamic diameters less than 2.5 micrometers and 10 micrometers, on respiratory function decline. Utilizing a large-scale longitudinal dataset comprising 5,000 adult subjects over a five-year period, we employed multivariate statistical modeling to isolate the specific contributions of particulate exposure while controlling for confounding variables such as smoking status, age, body mass index, and occupational hazards. The primary respiratory metrics utilized were Forced Expiratory Volume in one second and Forced Vital Capacity. Our analysis reveals a statistically significant negative correlation between chronic exposure to elevated particulate concentrations and lung function parameters. The application of multivariate linear regression models demonstrated that for every ten-microgram per cubic meter increase in fine particulate matter, there was a quantifiable reduction in expiratory volume, independent of other risk factors. Furthermore, the study identifies a synergistic effect between particulate exposure and tobacco use, suggesting that smokers are disproportionately vulnerable to environmental pollutants. These findings underscore the critical need for stricter air quality standards and provide a robust statistical framework for future epidemiological assessments of environmental respiratory health.