산업경영시스템학회지 (Journal of Korean Society of Industrial and Systems Engineering)

  • 제38권2호
  • /
  • Pages.1-7
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  • 2015
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  • 2005-0461(pISSN)
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  • 2287-7975(eISSN)
한국산업경영시스템학회 (Society of Korea Industrial and System Engineering)
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인체둘레치수를 활용한 체지방율 예측 다중회귀모델 개발

Analysis of Body Circumference Measures in Predicting Percentage of Body Fat

  • 박성하 (한남대학교 산업경영공학과)
  • Park, Sung Ha (Department of Industrial and Management Engineering, Hannam University)
  • 투고 : 2015.02.02
  • 심사 : 2015.05.11
  • 발행 : 2015.06.30
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초록

As a measure of health, the percentage of body fat has been utilized for many ergonomist, physician, athletic trainers, and work physiologists. Underwater weighing procedure for measuring the percentage of body fat is popular and accurate. However, it is relatively expensive, difficult to perform and requires large space. Anthropometric techniques can be utilized to predict the percentage of body fat in the field setting because they are easy to implement and require little space. In this concern, the purpose of this study was to find a regression model to easily predict the percentage of body fat using the anthropometric circumference measurements as predictor variables. In this study, the data for 10 anthropometric circumference measurements for 252 men were analyzed. A full model with ten predictor variables was constructed based on subjective knowledge and literature. The linear regression modeling consists of variable selection and various assumptions regarding the anticipated model. All possible regression models and the assumptions are evaluated using various statistical methods. Based on the evaluation, a reduced model was selected with five predictor variables to predict the percentage of body fat. The model is : % Body Fat = 2.704-0.601 (Neck Circumference) + 0.974 (Abdominal Circumference) -0.332 (Hip Circumference) + 0.409 (Arm Circumference) - 1.618 (Wrist Circumference) + $\epsilon$. This model can be used to estimate the percentage of body fat using only a tape measure.

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참고문헌

  1. Bary, G.A., Complications of Obesity. Annals of Internal Medicine, 1985, Vol. 103, pp. 1052-1062. https://doi.org/10.7326/0003-4819-103-6-1052
  2. Craig, B.N., Congleton, J.J., Kerk, C.J., Amendola, A. A., and Gaines, W.G., Personal and non-occupational risk factors and occupational injury/illness. Am J Ind Med, 2006, Vol. 49, No. 4, pp. 249-260. https://doi.org/10.1002/ajim.20290
  3. Hamilton, M.A., Strawdermana, L., Babski-Reevesa, K., and Hale, B., Effects of BMI and task parameters on joint angles during simulated small parts assembly. International Journal of Industrial Ergonomics, 2013, Vol. 43, No. 5, pp. 417-424. https://doi.org/10.1016/j.ergon.2013.08.003
  4. Kerr, M.S., Frank, J.W., Shannon, H.S., Norman, R.W., Wells, R.P., Neumann, P., and Bombardier, C., Biomechanical and psychosocial risk factors for low back pain at work. American Journal of Public Health, 2001, Vol. 91, No. 7, pp. 1069-1075. https://doi.org/10.2105/AJPH.91.7.1069
  5. Lohman, T.G., Boileau, R.A., aand Massey, B.H., Prediction of Lean Body Weight in Young Boys from Skinfold Thickness and Body Weight. Human Biology, 1975, Vol. 47, pp. 245-262s.
  6. Neter, J., Kuter, M.H., Nachtsheim, C.J., and Wasserman, W., Applied Linear Regression Models. 3rd ed. Burr Ridge, Illinois : Irwin, 1996.
  7. Ostbye, T., Dement, J.M., and Krause, K.M., Obesity and workers' compensation : results from the Duke Health and Safety Surveillance System. Arch Intern Med, 2007, Vol. 167, No. 8, pp. 766-773. https://doi.org/10.1001/archinte.167.8.766
  8. Penrose, K., Nelson, A., and Fisher, A., Generalized Body Composition Prediction Equation for Men Using Simple Measurement Techniques (abstract). Medicine and Science in Sports and Exercise, 1985, Vol. 17, No. 2, p. 189.
  9. Pollack, K.M., Sorock, G.S., Slade, M.D., Cantley, L., Sircar, K., Taiwo, O., and Cullen, M.R., Association between body mass index and acute traumatic workplace injury in hourly manufacturing employees. Am J Epidemiol, 2007, Vol. 166, No. 2, pp. 204-211. https://doi.org/10.1093/aje/kwm058
  10. Pollock, M.L., The Measurement of Body Composition. In P. J. Maud and C. Foster (Eds.), Physiological Assessment of Human Fitness, Champaign, IL : Human Kinetics, 1995, pp. 167-204.
  11. Roche, A.F., Anthropometry and Ultrasound. In A.F. Roche, S.B. Heymsfield, and T.G. Lohman (Eds.). Human Body Composition, Champaign, IL : Human Kinetics, 1996, pp. 167-189.
  12. SAS Institute, Inc., SAS/STAT9.2 User's Guide, Cary, NC : Author; 2009.
  13. Siri, W.E., Body Composition from Fluid Space and Density. In J. Brozek and A. Henschel (Eds.), Techniques for measuring body composition Washington, DC : National Academy of Science, 1961, pp. 223-224.
  14. Trogdon, J.G., Finkelstein, E.A., Hylands, T., Dellea, P.S., and Kamal-Bahl, S.J., Indirect costs of obesity : a review of the current literature. Obes Rev, Vol. 9, No. 5, 2008, pp. 489-500. https://doi.org/10.1111/j.1467-789X.2008.00472.x
  15. University of Arizona, Mathematics Department homepage. http://math.arizona.edu/-jwatkins/505d/body.htm. 2014.