Lag effect of ambient temperature on respiratory emergency department visits in Beijing: a time series and pooled analysis

Abstract

Abstract Background Although the association between ambient temperature and mortality of respiratory diseases was numerously documented, the association between various ambient temperature levels and respiratory emergency department (ED) visits has not been well studied. A recent investigation of the association between respiratory ED visits and various levels of ambient temperature was conducted in Beijing, China. Methods Daily meteorological data, air pollution data, and respiratory ED visits data from 2017 to 2018 were collected in Beijing. The relationship between ambient temperature and respiratory ED visits was explored using a distributed lagged nonlinear model (DLNM). Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of ambient temperature on respiratory ED visits across China. Results The single-day lag risk for extreme cold peaked at a relative risk (RR) of 1.048 [95% confidence interval (CI): 1.009, 1.088] at a lag of 21 days, with a long lag effect. As for the single-day lag risk for extreme hot, a short lag effect was shown at a lag of 7 days with an RR of 1.076 (95% CI: 1.038, 1.114). The cumulative lagged effects of both hot and cold effects peaked at lag 0–21 days, with a cumulative risk of the onset of 3.690 (95% CI: 2.133, 6.382) and 1.641 (95% CI: 1.284, 2.098), respectively, with stronger impact on the hot. Additionally, the elderly were more sensitive to ambient temperature. The males were more susceptible to hot weather than the females. A longer cold temperature lag effect was found in females. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent in general. In the subgroup analysis, a significant difference was found by gender. Conclusions Temperature level, age-specific, and gender-specific effects between ambient temperature and the number of ED visits provide information on early warning measures for the prevention and control of respiratory diseases.

Keywords

• Respiratory diseases
• Emergency department visits
• Ambient temperature
• Meteorological factors
• Distributed lag non-linear model
• Meta-analysis