The relationship between temperature and myocardial infarction has not been fully explained. In this study, we identified the threshold temperature and examined the relationship between temperature and emergency admissions due to MI in Korea. Poisson generalized additive model analyses were used to assess the short-term effects of temperature (mean, maximum, minimum, diurnal) on MI emergency visits, after controlling for meteorological variable and air pollution (PM10, NO₂). We defined the threshold temperature when the inflection point showed a statistically significant difference in the regression coefficients of the generalized additive models (GAMs) analysis. The analysis was performed on the following subgroups: geographical region, gender, age (<75 years or ≥75 years), and MI status (STEMI or non-STEMI). The threshold temperatures during heat exposure were for the maximum temperature as 25.5–31.5°C and for the mean temperature as 27.5–28.5°C. The threshold temperatures during cold exposure were for the minimum temperature as −2.5–1.5°C. Relative risks (RRs) of emergency visits above hot temperature thresholds ranged from 1.02 to 1.30 and those below cold temperature thresholds ranged from 1.01 to 1.05. We also observed increased RRs ranged from 1.02 to 1.65 of emergency visits when temperatures changes on a single day or on successive days. We found a relationship between temperature and MI occurrence during both heat and cold exposure at the threshold temperature. Diurnal temperature or temperature change on successive days also increased MI risk.

The relationship between temperature and subarachnoid hemorrhage (SAH) is less studied than that between temperature and myocardial infarction or other cardiovascular diseases. This study investigated the association between daily temperature and risk of SAH by analyzing the hospital admission records of 111,316 SAH patients from 2004 to 2012 in Korea. A Poisson regression model was used to examine the association between temperature and daily SAH hospital admissions. To analyze data and identify vulnerable groups, we used the following subgroups: sex, age, insurance type, area (rural or urban), and different climate zones. We confirmed a markedly higher SAH risk only for people of low socioeconomic status in both hot and cold temperatures; the relative risk (RR) in the Medicaid group was significantly increased and ranged from 1.04 to 1.11 for cold temperatures and 1.10 to 1.11 for hot temperatures. For the National Health Insurance group, the RR was increased to 1.02 for the maximum temperature only. The increased risk for SAH was highest in the temperate zone. An increase above the heat threshold temperature and a decrease below the cold threshold temperature were correlated with an increased risk of SAH in susceptible populations and were associated with different lag effects and RRs.