摘要
Abstract
Objective To investigate the influence of diurnal temperature range(DTR)on the daily hospitalization with chronic kidney diseases(CKD).Methods CKD daily inpatient data of four Grade Ⅲ hospitals,four Grade Ⅱ hospitals and one Grade Ⅰ hospital in Urumqi were collected from January 1,2019 to December 31,2020.Meteorological and pollutant data during the same period were collected from six state-controlled monitoring points in the main urban area of Urumqi.A distributed lag no-linear model(DLNM)was used to analyze the relationship between DTR and daily inpatients in CKD,controlling for day of the week effect,holiday effect,long-term trend and other factors,analyzing the relationship between DTR and CKD daily hospitalization.Results The expose-response curves of the number of patients admitted to CKD daily and DTR(with a lag of 0-21 days)showed an"N"shape,and the hospitalization risk of CKD patients increased first and then decreased with the increase of DTR.The influence of low and high DTR on hospitalization of CKD patients has a certain lag effect,while the influence of moderate DTR on hospitalization is small.DTR=5℃,the single-day effect appeared on day 3[RR=1.081,95%CI(1.020,1.145),P＜0.05],and the maximum effect appeared on day 21[RR=1.090,95%CI(1.014,1.173),P＜0.05];the single-day effect of altitude DTR=14℃(P95)occurred on day 4[RR=1.086,95%CI(1.007,1.172),P＜0.05],and the largest effect occurred on day 5[RR=1.089,95%CI(1.009,1.176),P＜0.05],and no statistical difference was found in cumulative lag.The results of stratified analysis by gender,age and season showed that males and CKD patients＜65 years old were more susceptible to DTR,and the change of DTR in cold season and four seasons had a greater impact on hospitalization of CKD patients.Conclusion Men and patients＜65 years of age with CKD are more susceptible to DTR,the focus should be more on protecting the susceptible population from DTR during the cold season and the change in DTR at the turn of seasons.关键词
昼夜温差/慢性肾脏病/分布滞后非线性模型/日住院人次/时间序列分析Key words
Diurnal temperature range/Chronic kidney disease/Distributed lag no-linear model/Daily hospitalizations/Time series analysis
