Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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A study using HGLM on regional difference of the dead due to injuries

손상으로 인한 사망자의 지역별 차이에 대한 HGLM을 이용한 연구

  • Kim, Kil-Hun (Department of Statistics, Pukyong National University) ;
  • Noh, Maeng-Seok (Department of Statistics, Pukyong National University) ;
  • Ha, Il-Do (Department of Asset Management, Daegu Haany University)
  • Received : 2011.01.17
  • Accepted : 2011.03.19
  • Published : 2011.03.31
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Abstract

In this paper, we systematically investigate regional differences of the dead due to injuries in cities, towns and counties about transportation accidents, suicides and fall accidents, which have recently been an important issue of health problems in Korea, The data are from the Annual Report on the Cause of Death Statistics in Korea in 2008. They include the deaths over the age 19 from transportation accidents, suicides and fall accidents with the criterion of the International Statistical Classification of Diseases. Poisson HGLM is applied to estimate the mortality rate under the assumption that the number of deaths follow a Poisson distribution, by considering regions as random effects and by adjusting age, sex and standardized residence tax as fixed effects. Using the results of random effects prediction, the regional differences in cities, counties and towns are marked in disease mapping. The results showed that there were significant regional differences of mortality rates for transportation accidents and suicides, but no significant differences for fall accidents.

본 논문에서는 최근 중요한 문제로 대두되고 있는 손상으로 인한 사망 중 운수사고, 자살, 낙상사고에 의한 사망률에 대한 시 군 구 별 차이를 체계적으로 파악하고자 한다. 2008년 사망원인통계 원시 자료 중 19세 이상이면서, 국제사인분류에 따른 사인이 운수사고, 자살, 낙상사고에 의한 자료만을 추출하여 분석대상으로 고려하였다. 분석모형으로 성별, 연령, 1인당 주민세를 고정효과로 보정하고, 사망자수가 포아송분포를 따른다는 가정 하에 지역효과를 변량효과로 둔 포아송 HGLM 모형을 고려하여 시 군 구 소지역별 효과의 차이를 질병지도로 나타내었다. 분석결과 운수사고, 자살사고로 인한 사망률은 시 군 구 소지역별로 유의한 차이가 나타났지만, 낙상사고로 인한 사망률은 시 군 구 지역별로 유의한 차이가 없는 것으로 나타났다.

Keywords

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