Geospatial Mapping of Indoor Air Quality and Respiratory Illnesses in an Urban Slum

Cureus. 2023 Feb 12;15(2):e34890. doi: 10.7759/cureus.34890. eCollection 2023 Feb.

Abstract

Introduction Air pollution is a well-recognized determinant of health. The general perception has focused primarily on outdoor pollution, and indoor pollution which may be due to smoking, biomass use, an extension of outdoor pollution, etc. has been neglected. It is therefore imperative to understand the levels of indoor pollution and find out if these are associated with high rates of illnesses, particularly, respiratory diseases. Material and methods This was a cross-sectional study involving 300 houses and 727 participants in an urban slum, selected through simple random sampling. Indoor air quality was assessed using the Prana C -Air Plus air quality monitor (Prana Air, New Delhi, India). The instrument detected formaldehyde, air quality index (AQI), temperature, humidity, PM2.5, PM10 particles, and total volatile organic (TVO) compounds. Socio-demographic details were noted, and geospatial mapping was done using Q-GIS software (www.qgis.org). A questionnaire was used to survey the residents of those houses. Ethical committee clearance was obtained before starting the project. Results The mean distribution of pollution parameters over the entire study area was AQI - 67.4±65.48, PM 2.5 - 37.6±35.82 μg/m3, formaldehyde - 0.09±0.37 mg/m3, PM 10 - 43.9±38.59 μg/m3, TVO compounds - 0.43±2.13 mg/m3, CO2 - 1128.9±323.86 ppm, temperature - 23.7±21.2 degree Celsius, and PM 1 - 24.3±20.5 μg/m3; 2.6% of the participants had respiratory diseases, and a significant association was found between the AQI, TVO compounds and ventilation, and respiratory diseases (p<0.05). Conclusion Indoor air pollution not unlike outdoor pollution can have dramatic health effects and needs to be addressed to lower the overall respiratory disease burden. The AQI, TVOC, and poor ventilation/cross-ventilation are associated with respiratory illnesses. Geospatial mapping shows a concentration of cases in areas of high pollution.

Keywords: air quality index; geospatial mapping; pollution; prana c air plus; slum.