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The Relationship Between the Atmospheric Environment and Road Traffic Fatalities - Shandong Province, China, 2012-2021.

China CDC weekly. 2024 March 30
INTRODUCTION: This study aims to analyze the potential impact of the meteorological environment and air pollutants on road traffic fatalities.

METHODS: Road traffic fatality data in Shandong Province from 2012 to 2021 were obtained from the Population Death Information Registration Management System. Meteorological and air pollutant data for the same period were collected from the U.S. National Oceanic and Atmospheric Administration and the Ecological Environment Monitoring Center of Shandong Province, China. Pearson's correlation and ridge regression were used to analyze the impact of the meteorological environment and air pollutants on road traffic fatalities.

RESULTS: From 2012 to 2021, there were 163,863 road traffic fatality cases. The results of the ridge regression analysis showed that the daily average temperature was negatively correlated with total fatalities and passengers and positively correlated with pedestrians, nonmotorized drivers, and motorized drivers. The daily minimum temperature was negatively correlated with total fatalities and positively correlated with motorized drivers. The daily maximum temperature was positively correlated with both pedestrian and nonmotorized drivers. The daily accumulated precipitation was negatively correlated with pedestrians. Sunshine duration was positively correlated with both nonmotorized and motorized drivers. Inhalable particulate matter (PM10 ) and nitrogen dioxide (NO2 ) were positively correlated with total fatalities, pedestrians, and nonmotorized drivers. Sulfur dioxide (SO2 ) was positively correlated with total fatalities but negatively correlated with nonmotorized drivers, passengers, and motorized drivers.

CONCLUSIONS: Atmospheric factors associated with the occurrence of road traffic fatalities include air temperature, daily accumulated precipitation, sunshine duration, and air pollutants such as PM10 , NO2 , and SO2 .

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