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Research Article

Assessing short-term effects of ambient air pollution on respiratory diseases in Guwahati, India with the application of the generalized additive model

ORCID Icon & ORCID Icon
Pages 1786-1807 | Received 02 Dec 2020, Accepted 22 Mar 2021, Published online: 04 May 2021
 

Abstract

Research studies connecting air pollution and its effect on health are much needed by the policymakers in India. Generalized additive model (GAM) was applied to quantify the effect of air pollutants on hospital visits related to respiratory diseases for an Indian city, Guwahati. A total of 6335 patients visited the only medical college and hospital in the city for respiratory diseases during 2016-2018. The multi-pollutant GAM models indicate the existence of synergistic effects of particulate matter less than 2.5 µm in diameter (PM2.5), nitrogen dioxide (NO2), and carbon monoxide (CO) on hospital visits of the patients due to respiratory diseases. The ambient PM2.5 concentrations have a strong link with hospital visits in all 6 single lag days. However, the effect of CO on hospital visits due to respiratory diseases was more robust. The percent change of hospital visits associated with each 1 unit increase in CO concentrations at lag 1 day was 15.7% (RR = 1.157; 95% CI 0.929, 1.442), which was enhanced to as high as 40.8% (RR = 1.408; 1.130,1.755) at lag3. The rise of each 10 units of concentrations of PM2.5 and 1 unit of CO at cumulative lag0-6 day was associated with the percentage change in hospital visits of 6.67% and 62.36% respectively. Single-pollutant GAM models indicate that the risk percentage of PM2.5 causing respiratory disease increased in combination with other pollutants.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

This study was supported by the Graduate School Thesis Grant, Chulalongkorn University, Bangkok, Thailand. The authors also thank the State Pollution Control Board, Assam, and Regional Meteorological Department, Guwahati, for air pollution and meteorological information, respectively.

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