Temperature and daily mortality in Suzhou, China: A time series analysis

Abstract

The evidence concerning the association between ambient temperature and mortality is limited in developing countries, especially in China. We assessed the effects of temperature on daily mortality between 2005 and 2008 in Suzhou, China. A Poisson regression model combined with a distributed-lag nonlinear model was used to examine the association between temperature and daily mortality. We investigated effect modification by individual characteristics, including gender, age and educational attainment. We found significant non-linear effects of temperature on total and cardiovascular mortality. Heat effects were immediate and lasted for 1–2days, whereas cold effects persisted for 10days. The relative risk of total morality associated with extreme cold temperature (1st percentile of temperature, −0.3°C) over lags 0–14days was 1.75 [95% confidence interval (CI): 1.43, 2.14)], compared with the minimum mortality temperature (26°C). The relative risk associated with extremely hot temperature (99th percentile of temperature, 32.6°C) over lags 0–3days was 1.43 (95% CI: 1.31, 1.56). We did not observe significant modifying effect by gender, age or educational level. This study showed that exposure to both hot and cold temperatures was associated with increased mortality in Suzhou. Our findings may have implications for developing intervention strategies for extreme cold and hot temperatures.