Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou

Abstract

Background: Although many studies have documented health effects of ambient temperature, little evidence is available in subtropical or tropical regions, and effect modifiers remain uncertain. We examined the effects of daily mean temperature on mortality and effect modification in the subtropical city of Guangzhou, China. Methods: A Poisson regression model combined with distributed lag non-linear model was applied to assess the non-linear and lag patterns of the association between daily mean temperature and mortality from 2003 to 2007 in Guangzhou. The case-only approach was used to determine whether the effect of temperature was modified by individual characteristics, including sex, age, educational attainment and occupation class. Results: Hot effect was immediate and limited to the first 5 days, with an overall increase of 15.46% (95% confidence interval: 10.05% to 20.87%) in mortality risk comparing the 99th and the 90th percentile temperature. Cold effect persisted for approximately 12 days, with a 20.39% (11.78% to 29.01%) increase in risk comparing the first and the 10th percentile temperature. The effects were especially remarkable for cardiovascular and respiratory mortality. The effects of both hot and cold temperatures were greater among the elderly. Females suffered more from hot-associated mortality than males. We also found significant effect modification by educational attainment and occupation class. Conclusions: There are significant mortality effects of hot and cold temperatures in Guangzhou. The elderly, females and subjects with low socioeconomic status have been identified as especially vulnerable to the effect of ambient temperatures.