OBJECTIVES: This study investigated the socio-demographic characteristics and medical causes of death among meteorological disaster casualties and compared them with deaths from all causes. METHODS: Based on the death data provided by the National Statistical Office from 2000 to 2011, the authors analyzed the gender, age, and region of 709 casualties whose external causes were recorded as natural events (X330-X389). Exact matching was applied to compare between deaths from meteorological disasters and all deaths. RESULTS: The total number of deaths for last 12 years was 2 728 505. After exact matching, 642 casualties of meteorological disasters were matched to 6815 all-cause deaths, which were defined as general deaths. The mean age of the meteorological disaster casualties was 51.56, which was lower than that of the general deaths by 17.02 (p<0.001). As for the gender ratio, 62.34% of the meteorological event casualties were male. While 54.09% of the matched all-cause deaths occurred at a medical institution, only 7.6% of casualties from meteorological events did. As for occupation, the rate of those working in agriculture, forestry, and fishery jobs was twice as high in the casualties from meteorological disasters as that in the general deaths (p<0.001). Meteorological disaster-related injuries like drowning were more prevalent in the casualties of meteorological events (57.48%). The rate of amputation and crushing injury in deaths from meteorological disasters was three times as high as in the general deaths. CONCLUSIONS: The new information gained on the particular characteristics contributing to casualties from meteorological events will be useful for developing prevention policies.
Adult ; Age Factors ; Aged ; *Cause of Death ; Demography ; Disasters/*statistics & numerical data ; Female ; Humans ; Male ; Middle Aged ; Republic of Korea/epidemiology ; Sex Factors ; Socioeconomic Factors

Aged ; Air Pollutants ; Humans ; Mortality ; Ozone ; Particulate Matter ; Seasons ; Seoul ; Vascular Diseases

PURPOSE: The aim of this study was to examine characteristics of health-related victims identified through the Surveillance System of Heat-related Illness (SSHI) based on emergency department (ED) visits. METHODS: Between July 1 and September 3 of 2011, 443 heat-related patients were reported by 396 of the 461 EDs participating in the SSHI. Heat-related illness included heat (sun) stroke, heat cramp, heat syncope, and heat exhaustion. A hot day was defined as a day above 30degrees C of daily maximum temperature in locations of provincial and metropolitan government offices. We used chi square test for identification of risk factors associated with Heat-related illness in the workplace and heat-related illness heat (sun) stroke. RESULTS: Heatwave, defined as lasting three or more hot days, occurred three times during this period. The daily average number of heat-related patients reported during the heatwave period was 15.7 per day, more than four times the usual rate. The daily maximum temperature showed positive correlation with occurrence of heat-related illness. Heat exhaustion was the most frequent cause (46.0%), with approximately 70% of all cases occurring between noon and 6 p.m. The number of people suffering from heat-related illness while outdoors was three times greater than that of those who experienced it indoors. Work-related occurrence comprised 56.7% of all cases. All six deaths occurred during the heatwave period and were work-related. CONCLUSION: Working conditions, outdoor activities, and old age may be associated with health-related illnesses. A surveillance system that monitors emergency room visits may be useful in assessment of adverse health effects of summer heatwaves.
Climate Change ; Emergencies ; Heat Exhaustion ; Heat Stress Disorders ; Heat Stroke ; Hot Temperature ; Humans ; Infrared Rays ; Korea ; Local Government ; Risk Factors ; Stress, Psychological ; Syncope

OBJECTIVES: This study was conducted to investigate the relationship between heat-related illnesses developed in the summer of 2012 and 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 1degrees C after 31.2degrees 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 (30.4degrees C), and the RR was the highest in the > or =65 age group (1.863, 1.755 to 1.978). The threshold temperature of the provinces (30.5degrees C) was lower than that of the metropolitan cities (32.2degrees 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.
Adolescent ; Adult ; Age Factors ; Aged ; Aged, 80 and over ; Child ; Child, Preschool ; Cities ; Female ; Heat Stroke/*epidemiology ; Humans ; Incidence ; Linear Models ; Male ; Middle Aged ; Patients/*statistics & numerical data ; Republic of Korea/epidemiology ; Seasons ; Sex Factors ; Temperature ; Young Adult