Coal Mine Air Pollution and Number of Children Hospitalizations because of Respiratory Tract Infection: A Time Series Analysis.

Yonglin Liu,Juan Liu,Yanhua Shi,Yanmei Qiao,Qiang Wang,Fenglian Chen,Fuyong Jiao,Shamsi Bilal Haider

doi:10.1155/2015/649706

Abstract

To analyze the relationship between levels of air pollution and number of children hospitalizations because of respiratory tract infection in Shenmu County, the data regarding meteorological factors, environmental pollutants, that is SO2 and NO2, Particulate Matter 10 (PM10), and hospitalizations of children less than 16 years of age was collected during the time duration of November 2009 to October 2012. Using SAS 9.3, descriptive data analysis for meteorological and environmental factors and hospital admissions were performed along with main air pollutants determination. Using the statistical software R 3.0.1, a generalized additive Poisson regression model was established, the linear fitting models of the air pollutant concentrations and meteorological factors were introduced considering the lag effect, and the relative risk of the main atmospheric pollutants on children hospitalization was evaluated. The results showed that the primary air pollutant in Shenmu County is PM10 and its Pearson correlation coefficient with Air Pollution Index (API) is 0.917. After control of long term climate trend, “week day effect,” meteorological factors, and impact of other contaminants, it was found that, on the same day and during the lag of 1 to 10 days, PM10 concentrations had no significant effect on children hospitalization rate.

Highlights

Air pollution and respiratory diseases are closely related [1] leading to the increase in hospital admissions and health care burden [2, 3]
We applied the Generalized Additive Model (GAM) extended Poisson regression model to quantitatively evaluate the effects of ambient air pollutants, NO2, Particulate Matter 10 (PM10), and SO2, on the prevalence of respiratory diseases by analyzing the time-series data of air pollutants, meteorological factors, and number of hospitalizations because of respiratory diseases in Shenmu County, Yulin City of China
Atmospheric pollutant concentrations and meteorological factors were fitted into linear models, and considering the lag effects it was determined that the main pollutants and respiratory diseases had significant correlation and relevance

Summary

Introduction

Air pollution and respiratory diseases are closely related [1] leading to the increase in hospital admissions and health care burden [2, 3]. Shenmu County in northern Shaanxi Province has Shenfu Dongsheng coalfield, which is one of the world’s largest coalfield [10], coal mining has produced a serious bituminous type atmospheric pollution [11, 12]. It is necessary to quantitatively evaluate the Shenmu air pollution concentration and its impact on childhood hospitalization due to respiratory diseases, in order to provide the strong basis for the protection of children respiratory health. We applied the Generalized Additive Model (GAM) extended Poisson regression model to quantitatively evaluate the effects of ambient air pollutants, NO2, PM10, and SO2, on the prevalence of respiratory diseases by analyzing the time-series data of air pollutants, meteorological factors, and number of hospitalizations because of respiratory diseases in Shenmu County, Yulin City of China

Methods

Results

Discussion

Conclusion