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BioMed Research International
Volume 2016 (2016), Article ID 2935163, 8 pages
Research Article

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

1Center of Respiratory Disorders, Children’s Hospital, Chongqing Medical University, Chongqing 400014, China
2Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China
3Department of Medical Statistics, Chongqing Medical University, Chongqing 400046, China
4Center for Asthma Prevalence and Education, Capital Institute of Pediatrics, Beijing 100020, China
5Institute of Environmental Health and Related Products Safety, Chinese Center for Disease Control and Prevention, Beijing 100021, China

Received 20 April 2016; Revised 29 June 2016; Accepted 30 June 2016

Academic Editor: Taiyoun Rhim

Copyright © 2016 Juanjuan Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China’s urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (, p < 0.05). Furthermore, results had shown that hours of sunshine (β = 0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China.