A CASE-CROSSOVER AND TIME-SERIES STUDY OF AMBIENT AIR POLLUTION AND DAILY MORTALITY IN SHANGHAI, CHINA

Abstract

ISEE-110 Abstract: In this study, we used both case-crossover and time-series approaches to assess the relationship between ambient air pollution and daily mortality from June 2000 to December 2001 in Shanghai, the largest city of China. Different control periods (unidirectional and bi-directional control samplings) were used for the case-crossover analysis. In the time-series analysis, semi-parametric generalized additive model (GAM) was used to allow for the highly flexible long-term and seasonable trends, as well as nonlinear weather variables. As a result, both bi-directional case-crossover and time-series analyses revealed a significant association between air pollutants (PM10, SO2 and NO2) level and daily mortality of total & cause-specific causes. Using a bi-directional six control sampling approach, the results from a conditional logistic regression model controlling for weather conditions showed that an increase of each 10 ug/m3 over a 48-hr moving average of PM10, SO2 and NO2 corresponds to 1.003 (95% CI 1.001–1.005), 1.016 (95% CI 1.011–1.021), and 1.020 (95% CI 1.012–1.027) relative risk of total non-accident mortality, respectively. For the time-series analysis, an increase of 10 ug/m3 of PM10, SO2 and NO2 corresponds to 1.003 (95% CI 1.001–1.005), 1.014 (95% CI 1.008–1.020), and 1.015 (95% CI 1.008–1.022) relative risk of total non-accidental mortality, respectively. The association between air pollution and mortality for COPD and cardiovascular causes was found to be stronger than that for all-causes in both analyses. Our study provides evidence that the current air pollution levels continue to have an adverse effect on the population health in Shanghai and strengthen the rationale for limiting levels of air pollution in outdoor air.