Background: Statistics on lung cancer incidences and air pollutants show a strong correlation between air pollutant concentrations and pulmonary diseases. And environmental effects on lung cancer incidences remain highly unknown and uncertain in China.
Objective: This study aims to measure the relationships between different air pollutants and lung cancer incidences in Tianjin.
Methods: One thusand five hundred patients across 27 districts in Tianjin were studied for lung cancer incidences. The patients had come into contact with various air pollutants such as PM2.5, PM10, SO2, NO2, CO, and O3. These pollutants were measured daily and were published via a Geographic Information System across the 27 districts of Tianjin. The air pollutant compositions of environments the patients lived in were determined using the nearest air monitoring station to the patient. And we used rough set theory to measure the relationships between different air pollutants and lung cancer incidences.
Results: Different air pollutants and combinations of pollutants impacted lung cancer incidences differently across different districts, sexes, and lung cancer types in Tianjin.
Conclusions: Based on data analysis and interpretation, rough set theory provided data relationships that were objective and interpretable. The method is simple, general, and efficient, and lays the foundation for further applications in other cities.
Keywords: Air pollutant compositions; geographic information system; lung cancer incidences; rough set theory.