Effects Of Temperature And Its Changes On Respiratory Diseases In Lanzhou

Epidemiological studies have confirmed that temperature and its changes have important impacts on respiratory diseases,but there were significant differences in research results from different regions.High,low,or extreme temperatures were generally considered to be the most important factors leading to morbidity or mortality in populations.Based on the meteorological observation data and the daily visits for respiratory diseases in Lanzhou from January 1,2012 to December 31,2018,a generalized additive model(GAM)was used to establish an exposure-response relationship between temperatures and respiratory disease visits,and to quantify the impact of normal temperature(P25～P75)and extreme low temperatures(P5,P10)on the risk of respiratory diseases.By using the distributed lag non-linear model(DLNM),the delayed and cumulative effects of temperature changes(daily temperature range(DTR)and temperature change between neighboring days(TCN))on respiratory diseases were studied.On this basis,two typical cold wave weather processes were selected,and the impact of cold air processes with different intensities on the risk of respiratory diseases was compared.At last,the Weather Research Forecast model(WRF)was used to numerically simulate these two typical processes to explore the regional differences in the impact of cold waves on the risk of respiratory diseases.The main results are as follows:(1)The exposure response curve between the average temperature and respiratory visits was an inverse "J" type,and the impact of low temperature was greater than that of high temperature.The daily respiratory visits during extreme low temperatures was higher than normal temperatures.In the single-day lag models,extreme low temperatures had short-term and longer-term effects on respiratory diseases.The maximum relative risk(RR)of 1.094(95% CI: 1.071～1.117,P5)and 1.049(95% CI:1.038～1.062,P10)respectively were observed at lag 2(2 days delay).The effect of P5 extreme low temperatures was greater than that of P10 and far greater than normal temperatures.Males and those age under 60 were more affected by P5 extreme low temperatures.In the cumulative lag models,the maximum RR value of P5 and P10 extreme temperatures were found at lag 2 and lag 3,which were 1.058(95% CI:1.034～1.081)and 1.041(95% CI: 1.029～1.054)respectively.Females and those age over 60 were more affected by the cumulative impact of extreme low temperatures.(2)In temperature rise period,the RR of extreme low TCN(P1)was 1.068(95%CI: 1.004～1.136)at lag 2.The maximum RR for extreme high TCN(P99)occurs at lag1(1.035,95% CI: 1.001～1.071)and lag 14(1.035,95% CI: 1.010～1.061).Females and those age over 60 were more susceptible to extreme TCN.In temperature drop period,the RR of extreme high TCN was 1.082(95% CI: 1.021～1.148)at lag 7,and the cumulative RR was 2.011(95% CI: 1.017～3.977)at lag 0～14,among which females and those age over 60 were more vulnerable.(3)Respiratory diseases were affected by extreme high DTR(P99).In temperature rise period,the lag time of extreme high DTR was longer,with a maximum RR of 1.485(95% CI: 1.005～1.094)at lag 1,and males and those age under 60 were more affected.In temperature drop period,the lag time of extreme high DTR was relatively short,with the maximum RR occurring at lag 1,which was 1.201(95% CI: 1.060～1.361).Females and those age under 60 were more affected.Cumulative results indicated that extreme high DTR can increase the risk of respiratory diseases within 0～2 days(RR=1.067,95%CI: 1.004～1.134),especially for those age under 60.Overall,the health effect of extreme high DTR was significantly greater than that of extreme high TCN.(4)The admission index(AI)of respiratory diseases had significantly increased within 0～7 days after cold air and the AI of cold waves were the largest,with a maximum value of 132.26 at lag 7.The number of respiratory visits was 21.2% higher than normal period(95% CI: 12.5%～30.5%).Males and those age over 60 were more affected by the cold waves.The analysis of typical cold wave cases showed the temperature decreases,air pressure and the number of respiratory visits increased after cold waves.The temperature-lowering amplitude in the cold waves from November 27 to 30,2022 was larger than that in the cold wave from October 7 to 9,2017,and the excess risk(ER)and the accumulative excess patient times in two weeks were higher,which were 15.6% and 38978 respectively,with the largest number of excess number of patients in Chengguan District.