Analyzing the effects of air pollution on life expectancy in Tehran, Iran

The present paper aims to analyze twenty-one-year long-term data of life expectancy and levels of PM10, PM2.5, CO, O-3, SO2, and NO2 pollutants in Tehran, Iran, to investigate the correlation between air pollution and life expectancy. Data are analyzed using the Pearson correlation coefficient and regression model. The regression analysis of the data used is performed to understand how the level of life expectancy alters by changing any of the above-mentioned pollutants and keeping constant the other independent variables. Enter Method is used for regression analysis. The level of life expectancy in Tehran was 70.18 years in 2000 and increased to 77.53 in 2020. Calculation of 21-year long-term data on air pollution index indicates no uniform and linear trend, but the trend of life expectancy is increasing. According to the adjusted R-squared calculation, it is concluded that 89.1% of the changes in the dependent variable (life expectancy) are explained by independent variables (air pollutants), which is a large value and is considered a fit model. The result of regression analysis of variance for statistical hypotheses also reveals that the Sig value is less than 0.05, thereby confirming the hypothesis of linear correlation between the two variables. However, the correlation coefficient is not a simple linear function, and the increase in life expectancy should be sought in the growth of other control variables such as improved health, treatment, nutrition, and quality of life.