There is a growing literature on the impacts of temperature change between neighboring days (TCN) on human health; however, the direction and magnitude of such impacts remain unclear. TCN is defined as the previous day’s mean temperature subtracted from the current day’s mean temperature. We investigated year-round and season-stratified associations between TCN and total, sex-specific, and age-specific cardiovascular disease (CVD) hospital admissions. We performed two-stage analysis utilizing nationwide CVD hospital admission data (N=4,859,112) from 2002 to 2019 using distributed lag non-linear model, DLNM, in the first stage and meta-regression in the second stage. A positive TCN was associated with elevated CVD hospital admission risk accounting for 192,117 (182,781; 197,192) hospitalizations during the study period. Season-stratified analyses revealed increased risk associated with positive TCN in both cold (November to April) and hot (May to October) seasons. Risk was more pronounced in the cold season (total relative risk [RR]: 1.70 [1.56, 1.86]) with no significant sex-related differences (RR: 1.81 [1.60, 2.06] vs. 1.59 [1.43, 1.78], respectively). Age-specific risk in the cold season was significantly higher among those aged 65 and older (RR: 2.52 [2.25, 2.81]) compared to those aged under 65 (RR: 0.95 [0.84, 1.08]). This study obtained the total, sex-specific, and age-specific CVD hospitalization risk associated with TCN year-round as well as specific to the hot and cold seasons. People over the age of 65 years were the most vulnerable to day-to-day temperature rise in the cold season. Season-specific policies targeting vulnerable populations may prevent adverse health outcomes of temperature fluctuations. This concern will become increasingly important as climate change proceeds.