Outlier Diagnostics and Resolution to determine Obesity Status in the Korean National Health Insurance Research Database

국민건강보험공단 자료에서 비만실태 파악을 위한 이상치 진단 및 해결

  • 김동욱 (국민건강보험공단일산병원) ;
  • 윤호순 (국민건강보험공단일산병원)
  • Received : 2017.06.13
  • Accepted : 2017.08.09
  • Published : 2017.09.28


This study was analyzed obesity status by divided into six classification based on the body mass index(BMI) established by World Health Organization-Western Pacific Regional Office(WHO-WPRO) through National Health Insurance Service(NHIS). In the middle of process, problems of outlier solved by presenting the median repeated interpolation. Unlike linear and Lagrange interpolation, median repeated interpolation may be useful in multiple outlier contained dataset. As a result, we found that extreme low and obesity weight gradually increased and the frequency of normal body weight gradually decreased. Especially, the increase of obesity in men and women of lower age group is increasing. Overall, this study suggests that national measures need to be taken before health problems arising from obesity can spread to other social problems.




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