Abstract：This study assessing the lag and interactive effects between the daily average temperature and relative humidity on respiratory disease (RD) morbidity in Lanzhou, China, using data from daily outpatient visits for RD between 2014 and 2017, and meteorological and pollutant data during the same period analysed with Poisson Generalized Linear Model and Distributed Lag Non-linear Models, the effects are further explored by classifying the RD by gender, age and disease type. The results showed that the temperature and relative humidity on outpatient visits of different populations and types of RD is nonlinear, with a significant lag effect. Relative to 11°C, every 1°C decrease in temperature is associated with 10.98% (95% Confidence interval (CI): 9.87%–12.11%) increase for total RD. Chronic obstructive pulmonary disease is affected only by low temperature, upper respiratory tract infection is affected by both low and high temperatures, and asthma is influenced by high temperature. When the relative humidity is less than 32%, every 1% decrease in relative humidity is associated with 6.00% (95% CI: 3.00%–9.11%) increase for total RD, relative humidity has different effects on the outpatient risk of different types of RD. Meanwhile, temperature and relative humidity have an obvious interactive effect on different types and populations of RD, when both temperature and humidity are at low levels, the higher the number of outpatient visits for RD. When the relative humidity is ≤50% and the temperature is ≤11°C, total RD outpatient visits increases by 4.502% for every 1°C drop in temperature; that is, dry environment with low temperature has the most significant impact on RD.

Keywords:Humidity; Temperature;Time series;Disease

原文链接：https://doi.org/10.1175/WCAS-D-20-0040.1