Objective: To investigate the impact of temperature changes between neighboring days (TCN) on the mortality risk of respiratory diseases, so as to provide the evidence for the study of deaths from respiratory diseases caused by climate change. Methods: The monitoring data of deaths from respiratory diseases in Zibo City from 2015 to 2019 were collected from Shandong Provincial Management Information System for Chronic Diseases and Cause of Death Surveillance. The meteorological and air pollutant data of the same period were collected from China Meteorological Data Website and ChinaHighAirPollutants dataset. The effect of TCN on the risk of deaths from respiratory diseases was examined using a generalized additive model combined with a distributed lag non-linear model, and subgroup analyses for gender and age were conducted. The disease burden attributed to TCN at different intervals was assessed by calculating attributable fraction. Results: Totally 11 767 deaths from respiratory diseases were reported in Zibo City from 2015 to 2019, including 6 648 males (56.50%) and 5 119 females (43.50%). There were 1 307 deaths aged <65 years (11.11%), and 10 460 deaths aged 65 years and older (88.89%). A monotonically increasing exposure-response relationship was observed between TCN and deaths from respiratory diseases in the general population, females, and the population aged 65 years and older. The 95th percentile of TCN (P95, 3.84 ℃) reached the peak at a cumulative lagged of day 11 (RR=2.063, 95%CI: 1.261-3.376). The results of subgroup analyses showed greater impacts on females and the population aged 65 years and older, with cumulative lagged effects peaking at day 12 (RR=3.119, 95%CI: 1.476-6.589) and day 11 (RR=2.107, 95%CI: 1.260-3.523). The results of attributional risk analysis showed that next-day warming might increase the attributable risk of deaths from respiratory diseases, and next-day cooling might decrease the attributable risk. Conclusion Next-day warming may increase the mortality risk of respiratory diseases, and has greater impacts on females and the population aged 65 years and older.