Objective To assess the association of temperature and emergency visits to internal medicine department of a downtown hospital in Shanghai.
Methods Meteorological data including daily temperature, humidity, and air pressure, air pollution data, as well as visits to the emergency internal medicine department in Shanghai Huangpu District Center Hospital were collected from 2009 to 2014. Quasi-Poisson generalized additive model (GAM) for time-series analysis was used to assess the association between daily mean temperature and emergency visits. Distributed lag nonlinear model (DLNM) was built to examine the lag effects of temperature and humidity while other potential time relevant confounders were considered.
Results A J-shaped relationship was found between daily mean temperature and emergency visits to internal medicine department of the studied hospital, which showed that both cold and hot temperatures increased emergency visits, especially the potential effect of cold temperature lasted more than two weeks. The optimum temperature (OT) corresponding to the lowest risk of emergency visits was about 7℃. The relative risks of cold and hot temperatures versus OT were 1.09 (95%CI: 1.03-1.16) and 1.27 (95%CI: 1.08-1.50), respectively. The overall excess risk of the visits associated with 1℃ below OT was 2.43% (95%CI: 0.83%-4.18%) for cold effect and that associated with 1℃ above OT was 0.96% (95%CI: 0.31%-1.64%) for hot effect.
Conclusion Both cold and hot temperatures are associated with increased risk of emergency visits to internal medicine department in Huangpu District. The effect lasts longer for cold temperature.
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