title: Indicators of hypertriglyceridemia from anthropometric measures based on data mining.
abstract: BACKGROUND
  The best indicator for the prediction of hypertriglyceridemia derived from anthropometric measures of body shape remains a matter of debate. The objectives are to determine the strongest predictor of hypertriglyceridemia from anthropometric measures and to investigate whether a combination of measures can improve the prediction accuracy compared with individual measures.
  
  
  METHODS
  A total of 5517 subjects aged 20-90 years participated in this study. The numbers of normal and hypertriglyceridemia subjects were 3022 and 653 females, respectively, and 1306 and 536 males, respectively. We evaluated 33 anthropometric measures for the prediction of hypertriglyceridemia using statistical analysis and data mining.
  
  
  RESULTS
  In the 20-90-year-old groups, age in women was the variable that exhibited the highest predictive power; however, this was not the case in men in all age groups. Of the anthropometric measures, the waist-to-height ratio (WHtR) was the best predictor of hypertriglyceridemia in women. In men, the rib-to-forehead circumference ratio (RFcR) was the strongest indicator. The use of a combination of measures provides better predictive power compared with individual measures in both women and men. However, in the subgroups of ages 20-50 and 51-90 years, the strongest indicators for hypertriglyceridemia were rib circumference in the 20-50-year-old group and WHtR in the 51-90-year-old group in women and RFcR in the 20-50-year-old group and BMI in the 51-90-year-old group in men.
  
  
  CONCLUSIONS
  Our results demonstrated that the best predictor of hypertriglyceridemia may differ according to gender and age.
authors.affiliation: Medical Research Division, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Deajeon 305-811, Republic of Korea.
authors.forename: Bum Ju
authors.initials: BJ
authors.lastname: Lee
authors.affiliation: Medical Research Division, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Deajeon 305-811, Republic of Korea. Electronic address: jupiter-lee@hanmail.net.
authors.forename: Jong Yeol
authors.initials: JY
authors.lastname: Kim
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D057225:Data Mining / Q000379:methods*; D005260:Female; D006801:Humans; D015228:Hypertriglyceridemia / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D056910:Republic of Korea / Q000453:epidemiology; D012189:Retrospective Studies; D012307:Risk Factors; D049629:Waist-Hip Ratio / Q000706:statistics & numerical data*; D055815:Young Adult
keywords: Anthropometry; Data mining; Hypertriglyceridemia; Machine learning; Prediction; Statistical data analysis; Triglycerides