한국산학기술학회논문지 (Journal of the Korea Academia-Industrial cooperation Society)

  • 제14권11호
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  • Pages.5771-5777
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  • 2013
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  • 1975-4701(pISSN)
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  • 2288-4688(eISSN)
한국산학기술학회 (The Korea Academia-Industrial cooperation Society)
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개인 식품섭취 선호도에 따른 당뇨병 발생 위험도 분석 모델

Diabetes Risk Analysis Model with Personalized Food Intake Preference

  • 전소혜 (연세대학교 의과대학 의학공학교실) ;
  • 김남현 (연세대학교 의과대학 의학공학교실)
  • Jeon, So-Hye (Department of Medical Engineering, Yonsei University) ;
  • Kim, Nam-Hyun (Department of Medical Engineering, Yonsei University)
  • 투고 : 2013.10.10
  • 심사 : 2013.11.07
  • 발행 : 2013.11.30
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초록

최근 만성질환의 증대로 질병의 지속적인 관리에 대한 필요성이 대두되고 있으나 개인 맞춤형 식품섭취와 관련한 분석 연구는 미비하다. 본 연구에서 제시한 당뇨병 발생 위험도 분석 모델은 기존 상품 선호도 연구를 통해 검증된 유사도평가 방법인 피어슨 상관계수 산출을 이용하여 식품 선호도를 산출하고, 유병율 분석 연구 등에 활용된 로지스틱 회귀분석 방법을 이용하여 당뇨병발생 위험도를 제시하였다. 모델의 유의성 평가를 위해 당뇨 진단을 받은 환자 52명(남자: 22명, 여자: 30, 평균연령: 57(${\pm}13.2$)세)과 비교군과 비슷한 연령을 조건으로 무작위 추출된 52명(남자: 17명, 여자: 35, 평균연령: 58(${\pm}9.4$)세)의 t-검정을 통해 0.05 수준에서 유의함을 검증하였다. 이를 통해 식품섭취빈도에 따른 당뇨병 발생 위험도에 차이가 있음(p=0.046)을 확인할 수 있었다. 이 모델을 기반으로 분석된 정보는 스마트폰이나 웹을 이용한 개인 건강관리 시스템에 적용을 통해 새로운 개인 맞춤형 건강관리 방법으로 제시될 수 있다.

The need of continuous management for diseases came to the fore as a chronic disease has increased, however, research related to personalized food intake analysis are insufficient. In diabetes risk analysis model of this study, food preferences are calculated by Pearson correlation coefficient that is proven method to assess the similarity, and diabetes risk is computed as a Logistic regression that was used in prevalence studies. For the Significance evaluation of this model, it was verified through t-test at 0.05 level of 52 comparison subjects and 52 control subjects. Both groups were significantly independent (p=0.046 <0.05). This model is a new way to personalized health management, through the application to healthcare system based on web and mobile.

키워드

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피인용 문헌

  1. PHR Based Diabetes Index Service Model Using Life Behavior Analysis vol.93, pp.1, 2017, https://doi.org/10.1007/s11277-016-3715-9
  2. Design and Implementation of Chronic Disease Risk Analysis System according to Personalized Food Intake Preferences vol.51, pp.3, 2014, https://doi.org/10.5573/ieie.2014.51.3.147