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Wonwoong Na 2 Articles
Socio-demographic Characteristics and Leading Causes of Death Among the Casualties of Meteorological Events Compared With All-cause Deaths in Korea, 2000-2011
Kyung Eun Lee, Hyung-Nam Myung, Wonwoong Na, Jae-Yeon Jang
J Prev Med Public Health. 2013;46(5):261-270.   Published online September 30, 2013
DOI: https://doi.org/10.3961/jpmph.2013.46.5.261
  • 9,729 View
  • 66 Download
  • 5 Crossref
AbstractAbstract PDF
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.

Summary

Citations

Citations to this article as recorded by  
  • Research Trends in Agenda-setting for Climate Change Adaptation Policy in the Public Health Sector in Korea
    Su-Mi Chae, Daeeun Kim
    Journal of Preventive Medicine and Public Health.2020; 53(1): 3.     CrossRef
  • Effect of typhoons on the Korean national emergency medical service system
    Soo Hyun Park, Won Chul Cha, Giwoon Kim, Tae Rim Lee, Sung Yeon Hwang, Tae Gun Shin, Min Seob Sim, Ik Joon Jo
    Clinical and Experimental Emergency Medicine.2018; 5(4): 272.     CrossRef
  • The Vulnerability of People to Damaging Hydrogeological Events in the Calabria Region (Southern Italy)
    Olga Petrucci, Paola Salvati, Luigi Aceto, Cinzia Bianchi, Angela Pasqua, Mauro Rossi, Fausto Guzzetti
    International Journal of Environmental Research and Public Health.2017; 15(1): 48.     CrossRef
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    Luigi Aceto, Tommaso Caloiero, A.A. Pasqua, Olga Petrucci
    Journal of Hydrology.2016; 541: 510.     CrossRef
  • Disaster epidemiology in Korea
    Ju Ok Park
    Journal of the Korean Medical Association.2014; 57(12): 993.     CrossRef
The Effects of Temperature on Heat-related Illness According to the Characteristics of Patients During the Summer of 2012 in the Republic of Korea
Wonwoong Na, Jae-Yeon Jang, Kyung Eun Lee, Hyunyoung Kim, Byungyool Jun, Jun-Wook Kwon, Soo-Nam Jo
J Prev Med Public Health. 2013;46(1):19-27.   Published online January 31, 2013
DOI: https://doi.org/10.3961/jpmph.2013.46.1.19
  • 11,138 View
  • 116 Download
  • 29 Crossref
AbstractAbstract PDF
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 1℃ after 31.2℃. 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℃), 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℃) was lower than that of the metropolitan cities (32.2℃). 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.

Summary

Citations

Citations to this article as recorded by  
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    International Journal of Hygiene and Environmental Health.2024; 255: 114296.     CrossRef
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    Atmosphere.2023; 14(5): 839.     CrossRef
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    Buildings.2023; 13(11): 2687.     CrossRef
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    International Journal of Environmental Research and Public Health.2022; 19(13): 8087.     CrossRef
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    Barun Mukhopadhyay, Charles A. Weitz
    International Journal of Environmental Research and Public Health.2022; 19(19): 12446.     CrossRef
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    R Kelundapyan, M A Zakaria, V C Segaran
    IOP Conference Series: Materials Science and Engineering.2021; 1144(1): 012026.     CrossRef
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    Hyun-Ju Lee, Woo-Seop Lee, Jong Ahn Chun, Hwa Woon Lee
    Weather and Forecasting.2020; 35(2): 367.     CrossRef
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    Su-Mi Chae, Daeeun Kim
    Journal of Preventive Medicine and Public Health.2020; 53(1): 3.     CrossRef
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    Building and Environment.2019; 150: 108.     CrossRef
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JPMPH : Journal of Preventive Medicine and Public Health