Temperature-related mortality estimates after accounting for the cumulative effects of air pollution in an urban area

Svetlana Stanišić Stojić,Andreja Stojić,Nemanja Stanišić

doi:10.1186/s12940-016-0164-6

Abstract

BackgroundTo propose a new method for including the cumulative mid-term effects of air pollution in the traditional Poisson regression model and compare the temperature-related mortality risk estimates, before and after including air pollution data.ResultsThe analysis comprised a total of 56,920 residents aged 65 years or older who died from circulatory and respiratory diseases in Belgrade, Serbia, and daily mean PM10, NO2, SO2 and soot concentrations obtained for the period 2009–2014. After accounting for the cumulative effects of air pollutants, the risk associated with cold temperatures was significantly lower and the overall temperature-attributable risk decreased from 8.80 to 3.00 %. Furthermore, the optimum range of temperature, within which no excess temperature-related mortality is expected to occur, was very broad, between −5 and 21 °C, which differs from the previous findings that most of the attributable deaths were associated with mild temperatures.ConclusionsThese results suggest that, in polluted areas of developing countries, most of the mortality risk, previously attributed to cold temperatures, can be explained by the mid-term effects of air pollution. The results also showed that the estimated relative importance of PM10 was the smallest of four examined pollutant species, and thus, including PM10 data only is clearly not the most effective way to control for the effects of air pollution.Electronic supplementary materialThe online version of this article (doi:10.1186/s12940-016-0164-6) contains supplementary material, which is available to authorized users.

Highlights

To propose a new method for including the cumulative mid-term effects of air pollution in the traditional Poisson regression model and compare the temperature-related mortality risk estimates, before and after including air pollution data
The number of days with average particles smaller than 10 μm (PM10) concentrations exceeding 50 μg m−3 was in the range from 75 to 155 per year, which is considerably higher than the Air Quality Standard margin (35 exceedances per year), whereas the mean annual nitrogen dioxide (NO2) concentrations did not exceed the value of 40 μg m−3, nor any mean daily sulfur dioxide (SO2) levels higher than the recommended limit of 135 μg m−3 were observed
The proposed method is based on the theoretical premise that there are significant cumulative mid-term effects of air pollution on mortality, which are more stable, and more statistically robust, than the lagspecific effects commonly included in regression models

Summary

Introduction

To propose a new method for including the cumulative mid-term effects of air pollution in the traditional Poisson regression model and compare the temperature-related mortality risk estimates, before and after including air pollution data. Environmental stressors, such as extreme temperature events and air pollution, pose a significant challenge to human societies, to the growing urban population worldwide [1]. The relatively few studies considering the interactive effects of meteorological variables and air pollution on daily mortality have reported inconsistent results [3, 4]. The latest study of Gasparrini et al [9] including more than 74 million deaths recorded in 13 countries and 384 locations showed that cold-related deaths outnumbered

Methods

Results

Conclusion