The Effects of Temperature on Heat-related Illness According to the Characteristics of Patients During the Summer of 2012 in the Republic of Korea
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Objectives: This study was conducted to investigate the relationship between heat-related illnesses developed in the summer of 2012and temperature. Methods: The study analyzed data generated by a heat wave surveillance system operated by the Korea Centers for Disease Control and Prevention during the summer of 2012. The daily maximum temperature, average temperature, and maximum heat index were compared to identify the most suitable index for this study. A piecewise linear model was used to identify the threshold temperature and the relative risk (RR) above the threshold temperature according to patient characteristics and region. Results: The total number of patients during the 3 months was 975. Of the three temperature indicators, the daily maximum temperature showed the best goodness of fit with the model. The RR of the total patient incidence was 1.691 (1.641 to 1.743) per 1°C after 31.2°C. The RR above the threshold temperature of women (1.822, 1.716 to 1.934) was greater than that of men (1.643, 1.587 to 1.701). The threshold temperature was the lowest in the age group of 20 to 64 (30.4°C), and the RR was the highest in the ≥65 age group (1.863, 1.755 to 1.978). The threshold temperature of the provinces (30.5°C) was lower than that of the metropolitan cities (32.2°C). Metropolitan cities at higher latitudes had a greater RR than other cities at lower latitudes. Conclusions: The influences of temperature on heat-related illnesses vary according to gender, age, and region. A surveillance system and public health program should reflect these factors in their implementation.
Abstract
Objectives: This study was conducted to investigate the relationship between heat-related illnesses developed in the summer of 2012and temperature. Methods: The study analyzed data generated by a heat wave surveillance system operated by the Korea Centers for Disease Control and Prevention during the summer of 2012. The daily maximum temperature, average temperature, and maximum heat index were compared to identify the most suitable index for this study. A piecewise linear model was used to identify the threshold temperature and the relative risk (RR) above the threshold temperature according to patient characteristics and region. Results: The total number of patients during the 3 months was 975. Of the three temperature indicators, the daily maximum temperature showed the best goodness of fit with the model. The RR of the total patient incidence was 1.691 (1.641 to 1.743) per 1°C after 31.2°C. The RR above the threshold temperature of women (1.822, 1.716 to 1.934) was greater than that of men (1.643, 1.587 to 1.701). The threshold temperature was the lowest in the age group of 20 to 64 (30.4°C), and the RR was the highest in the ≥65 age group (1.863, 1.755 to 1.978). The threshold temperature of the provinces (30.5°C) was lower than that of the metropolitan cities (32.2°C). Metropolitan cities at higher latitudes had a greater RR than other cities at lower latitudes. Conclusions: The influences of temperature on heat-related illnesses vary according to gender, age, and region. A surveillance system and public health program should reflect these factors in their implementation.
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