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      Short-term effects of air pollution on daily mortality and years of life lost in Nanjing, China.

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          The deteriorating air quality in Chinese cities is attracting growing public concern. We conducted analyses to quantify the associations between daily changes in ambient air pollution and mortality in Nanjing, China. Daily mortality, air pollution, and meteorological data from 1 January 2009 to 31 December 2013 were collected. Over-dispersed Poisson regression models were used to evaluate the risk of daily non-accidental mortality and years of life lost (YLL) from exposure to respirable particulate matter (PM10) and gaseous pollutants (NO2, SO2). Stratified analysis was conducted to indentify the modifying effect of individual-level factors on the association between air pollutants and mortality. We found that interquartile range (IQR) increases in the two-day average of PM10, NO2 and SO2 were significantly associated with 1.6% [95% confidence interval (CI):0.7%-2.6%], 2.9% (95% CI: 1.7%-4.2%) and 2.4% (95% CI: 1.2%-3.6%) higher rates of non-accidental mortality; and related to YLL increases of 20.5 (95% CI: 6.3-34.8), 34.9 (95% CI: 16.9-52.9) and 30.3 (95% CI: 12.2-48.4) years, respectively; Associations between air pollution and mortality were more pronounced in the warm season than in the cool season. We conclude that the risks of mortality and YLL were elevated corresponding to an increase in current ambient concentrations of the air pollutants, and season may modify the effects of outdoor air pollution in Nanjing.

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          Author and article information

          Sci. Total Environ.
          The Science of the total environment
          Elsevier BV
          Dec 01 2015
          : 536
          [1 ] Institute of Population Research, Peking University, Beijing 100871, China; Institute of Environmental Health and Related Product Safety, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
          [2 ] Department of Environmental and Endemic Diseases Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu 210009, China.
          [3 ] School of Public Health, Yale University, New Haven, CT 06520, USA.
          [4 ] Department of Epidemiology and Biostatistics, School of Population Health, University of Queensland, Brisbane, QLD 4006, Australia.
          [5 ] Department of Epidemiology, Brown University, Providence RI02912, USA.
          [6 ] Institute of Population Research, Peking University, Beijing 100871, China.
          [7 ] Institute of Population Research, Peking University, Beijing 100871, China. Electronic address: Xzheng@pku.edu.cn.


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