Ozone and daily mortality rate in 21 cities of East Asia: how does season modify the association?

Am J Epidemiol. 2014 Oct 1;180(7):729-36. doi: 10.1093/aje/kwu183. Epub 2014 Aug 19.


Previous studies in East Asia have revealed that the short-term associations between tropospheric ozone and daily mortality rate were strongest in winter, which is opposite to the findings in North America and Western Europe. Therefore, we investigated the season-varying association between ozone and daily mortality rate in 21 cities of East Asia from 1979 to 2010. Time-series Poisson regression models were used to analyze the association between ozone and daily nonaccidental mortality rate in each city, testing for different temperature lags. The best-fitting model was obtained after adjustment for temperature in the previous 2 weeks. Bayesian hierarchical models were applied to pool the city-specific estimates. An interquartile-range increase of the moving average concentrations of same-day and previous-day ozone was associated with an increase of 1.44% (95% posterior interval (PI): 1.08%, 1.80%) in daily total mortality rate after adjustment for temperature in the previous 2 weeks. The corresponding increases were 0.62% (95% PI: 0.08%, 1.16%) in winter, 1.46% (95% PI: 0.89%, 2.03%) in spring, 1.60% (95% PI: 1.03%, 2.17%) in summer, and 1.12% (95% PI: 0.73%, 1.51%) in fall. We found significant associations between short-term exposure to ozone and higher mortality rate in East Asia that varied considerably from season to season with a significant trough in winter.

Keywords: East Asia; air pollution; mortality rate; ozone; season; temperature.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants / adverse effects*
  • Air Pollutants / analysis
  • Air Pollution / adverse effects*
  • Air Pollution / analysis
  • Bayes Theorem
  • Far East / epidemiology
  • Humans
  • Models, Statistical
  • Mortality*
  • Ozone / adverse effects*
  • Ozone / analysis
  • Poisson Distribution
  • Regression Analysis
  • Seasons*
  • Temperature
  • Urban Health / statistics & numerical data*


  • Air Pollutants
  • Ozone