This research investigates the intricate relationship between air pollution and respiratory health by integrating real-time air quality data with longitudinal health records. Using sophisticated statistical techniques, including multivariate regression and machine learning algorithms, we analyze the impact of key pollutants—such as PM2.5, PM10, NOx, and SO2—on the prevalence and severity of respiratory conditions. Our study not only identifies significant pollutant-health associations but also introduces a novel predictive model that assesses individual risk based on dynamic air quality metrics and personal health data. The model’s predictive accuracy offers a proactive tool for public health interventions, allowing for targeted health advisories and personalized prevention strategies. The findings enhance our understanding of air pollution’s multifaceted effects on respiratory health, providing crucial evidence to guide effective policy measures and improve health outcomes in affected populations.
- Quote paper
- Ananya S. Padasalgi (Author), Amrutha B. T. (Author), Maanasa M. G. (Author), Smrithi R. Holla (Author), 2024, The Impact of Air Pollution on Respiratory Diseases, Munich, GRIN Verlag, https://www.grin.com/document/1502994
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