Association of short-term exposure to air pollution with mortality in a middle eastern tourist city

Abstract

This study investigated the association of short-term exposure to PM 10 , PM 2.5 , NO 2 , O 3 , and CO with daily all-cause, cardiovascular, ischemic heart disease (IHD), cerebrovascular, and respiratory deaths in Mashhad, a tourist megacity in Iran (2014Iran ( -2018. A distributed-lag-day, nonlinear model (DLNM) and generalized additive model (GAM) based on the quasi-Poisson distribution were used to explore the exposure-lag-day-response associations. The average (± standard deviation) concentrations of PM 10 , PM 2.5 , NO 2 , O 3 , and CO were 67.1 (± 35.5), 29.6 (± 14.2), 57.3 (± 24.1), 55.9 (± 16.9), and 1907.6 (± 1362.7) μg/m 3 , respectively. NO 2 was associated with IHD mortality in lag-days 0 to 0-7, and lag-day 1. The relative risks (RRs) for a 10 μg/m 3 increase in NO 2 ranged from 1.01 (95% CI 0.93, 1.11) at lag-day 0 to 1.04 (95% CI 0.94, 1.16) and 1.03 (95% CI 0.93, 1.14) for lag-day 0-1 (cumulative) and lag-day 1 (non-cumulative), respectively. For all-cause mortality, cumulative exposure to PM 2.5 for lag-day 0-7 (1.07, 95% CI 1.00, 1.15) and non-cumulative exposure to NO 2 at lag-day 6 (1.02, 95% CI 1.00, 1.03) were significant. Exposure to PM 10 (per 10 μg/m 3 ) was significantly associated with respiratory mortality at several lag-days. Adjusting for Ramadan did not significantly affect the results. PM 10 had significant associations with respiratory mortality of people > 65 years old, and men for several lag-days. For IHD, NO 2 affected older people, and men and women over different lagdays. Results of multi-pollutant models were similar to the single-pollutant model outcomes. In conclusion, NO 2 and PM 10 had more significant relationships with adverse health outcomes than the other pollutants.

Effect of short-term exposure to air pollution on COVID-19 mortality and morbidity in Iranian cities

“…For averaging, only the days were used that had a minimum of 75% (18 h in 24 h) available data. These criteria were applied to ensure that a representative exposure will be attributed to the population [9,14]. The number of valid monitors after applying the criteria are presented in the Supplementary Materials (Table S1).…”

“…Therefore, a distributed-lag, nonlinear model (DLNM) and a generalized additive model (GAM) based on the quasi-Poisson distribution were used [14,15]. We modelled daily number of COVID-19 cases or deaths against one air pollutant at a time (PM 2.5 , PM 10 , NO 2 , or O 3 ), air temperature, and time variables.…”

“…These two variable were included to adjust for the effect of day of week and holidays on the number of confirmed cases and deaths. Although Ramadan occurred during the study period (April to May), it was not included in the model since prior work showed it had no direct effects on mortality [14].…”