Exploratory analysis of PM2.5 variation trend of Tehran, Iran, in various time series and its relation with cardiovascular mortality rate using R software

Document Type : Original Article


1 Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

2 Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER) AND Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

3 Associate Professor, School of Public Health and Institute of Public Health Research, Tehran University of Medical Sciences, Tehran, Iran


Among the numerous air pollutants, the strongest proof for adverse health effects has been reported for particulate matter (PM). The aim of this study was the exploration of short-term associations of air pollution with mortalities due to cardiovascular diseases (CVD) in Tehran, Iran, based on hospital and census data from 2007 to 2013. This descriptive and analytical research was conducted in 2015. Daily and hourly pollutant concentration was obtained from Tehran Metropolitan Municipality. Mortality rate records were obtained from the Ministry of Health, Central Municipal Cemetery, and Forensic Organization. In this study, data were analyzed using R software. Zoo, Time series, Stats, ts model, and Splines software packages were installed on R platform in order to outline the trend of different variables. The results showed that accidental mortality did not follow a particular trend and non-accidental mortality followed a descending or ascending trend. However, mortality pattern showed a decreasing trend from 2011 until the end of 2012. From the beginning of 2013, mortality pattern showed increasing trend. Moreover, the direct correlation of mortality rate and PM2.5 concentration can be observed in a yearly and weekly time scale. Proof of a determined effect of airborne particles on mortality was found with PM2.5. In addition, it was found that mortality rate shows a strong seasonal pattern, with a peak in winter and a minimum in fall. The peak the mortality rate in winter is most probably due to the spread of infectious diseases such as influenza as well as temperature-related phenomena in cold weather areas. 


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