Industrial Engineering and Management Systems

Korean Institute of Industrial Engineers (대한산업공학회)
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Discovering Relationships between Skin Type and Life Style Using Data Mining Techniques: A Case Study of Korea

  • Kim, Taeheung (Department of Industrial Engineering, Sungkyunkwan University) ;
  • Ha, Jihyun (Department of Industrial Engineering, Sungkyunkwan University) ;
  • Lee, Jong-Seok (Department of Industrial Engineering, Sungkyunkwan University) ;
  • Oh, Younhak (Nielsen Company Korea) ;
  • Cho, Yong Ju (Korea Institute of Industrial Technology)
  • Received : 2016.03.01
  • Accepted : 2016.03.08
  • Published : 2016.03.30
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Abstract

With the growing interest in skincare and maintenance, there are increasing numbers of studies on the classification of skin type and the factors influencing each type. This study presents a novel methodology by using data mining, for the determination of the relationships between skin type, lifestyle, and patterns of cosmetic utilization. Eight skin-specific factors, which are moisture, sebum in U-zone (both cheeks), sebum in T-zone (forehead, nose, and chin), pore, melanin, wrinkle, acne, hemoglobin, were measured in 1,246 subjects living in South Korea, in conjunction with a questionnaire survey analyzing their lifestyles and pattern of cosmetic utilization. Using various multivariate statistical methods and data mining techniques, we classified the skin types based on the skin-specific values, determined the relationship between skin type and lifestyle, and accordingly sorted the subjects into clusters. Logistic regression analysis revealed gender-related differences in the skin; therefore, separate analyses were performed for males and females. Using the Gaussian Mixture Modeling (GMM) technique, we classified the subjects based on skin type (two male and four female). Using the ANOVA and decision tree techniques, we attempted to characterize the relationship between each skin type and the lifestyles of the subjects. Menstruation, eating habits, stress, and smoking were identified as the major factors affecting the skin.

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References

  1. Asakura, K., Nishiwaki, Y., Milojevic, A., Michikawa, T., Kikuchi, Y., Nakano, M., and Takebayashi, T. (2008), Lifestyle factors and visible skin aging in a population of Japanese elders, Journal of Epidemiology/Japan Epidemiological Association, 19(5), 251-259. https://doi.org/10.2188/jea.JE20090031
  2. Baumann, L. (2008), Understanding and greating various skin types: the Baumann Skin Type Indicator, Dermatologic Clinics, 26(3), 359-373. https://doi.org/10.1016/j.det.2008.03.007
  3. Fitzpatrick, T. B. (1989), The validity and practicality of sun-reactive skin types I through VI, Archives of Dermatology, 124(6), 869-871. https://doi.org/10.1001/archderm.1988.01670060015008
  4. Fur, I. L., Lopez, S., Morizot, F., Guinot, C., and Tschachler, E. (1999), Comparison of cheek and forehead regions by bioengineering methods in women with different self-reported cosmetic skin types, Skin Research and Technology, 5(3), 182-188. https://doi.org/10.1111/j.1600-0846.1999.tb00129.x
  5. Galzote, C., Estanislao, R., Suero, M. O., Khaiat, A., Mangubat, M. I., Moideen, R., and Wang, X. (2013), Characterization of facial skin of various Asian populations through visual and non-invasive instrumental evaluations: Influence of age and skincare habits, Skin Research and Technology, 19(4), 454-465. https://doi.org/10.1111/srt.12069
  6. Kim, J. G., Park, B. S., and Kim, J. S. (2011), Relationships of food habits and life style and skin health of young females, Korean Association of Human Ecology, 20(2), 449-465. https://doi.org/10.5934/KJHE.2011.20.2.449
  7. Kumagai, H., Shioya, K., Kawasaki, K., Horii, I., Koyara, J., Nakayama, Y., Mori, W., and Ohta, S. (1985), Development of a scientific method for classification of facial skin types, Journal of Society of Cosmetic Chemists of Japan, 19(1), 9-19. https://doi.org/10.5107/sccj.19.9
  8. Lee, W., Lee, J., Lee, H., Jun, C.-H., Park, I.-S., and Kang, S.-H. (2014), Prediction of hypertension complications risk using classification techniques, Industrial Engineering and Management Systems, 13(4), 449-453. https://doi.org/10.7232/iems.2014.13.4.449
  9. Luebberding, S., Krueger, N., and Kerscher, M. (2014), Mechanical properties of human skin in vivo: a comparative evaluation in 300 men and women, Skin Research and Technology, 20(2), 127-135. https://doi.org/10.1111/srt.12094
  10. Man, M. Q., Xin, S. J., Song, S. P., Cho, S. Y., Zhang, X. J., Tu, C. X., Feingold, K. R., and Elias, P. M. (2009), Variation of skin surface pH, sebum content and stratum corneum hydration with age and gender in a large Chinese population, Skin Pharmacology and Physiology, 22(4), 190-199. https://doi.org/10.1159/000231524
  11. McLachlan, G. and Peel, D. (2004), Finite mixture models, John Wiley and Sons.
  12. Nouveau-Richard, S., Yang, Z., Mac-Mary, S., Li, L., Bastien, P., Tardy, I., Bouilon, C., Humbert, P., and De Lacharriere, O. (2005), Skin ageing: A comparison between Chinese and European populations: A pilot study, Journal of Dermatological Science, 40(3), 187-193. https://doi.org/10.1016/j.jdermsci.2005.06.006
  13. Park, S. G., Kim, Y. D., Kim, J. J., and Kang, S. H. (1999), Two possible classifications of facial skin type by two parameters in Korean women: Sebum excretion rate (SER) and skin surface relief (SSR), Skin Research and Technology, 5(3), 189-194. https://doi.org/10.1111/j.1600-0846.1999.tb00130.x
  14. Pierard, G. E. (1987), What Does 'Dry Skin' Mean?, International Journal of Dermatology, 26(3), 167-168. https://doi.org/10.1111/j.1365-4362.1987.tb00883.x
  15. Quinlan, J. R. (1993), C4.5: Programs for Machine Learning, Morgan Kaufmann.
  16. Roberts, S. J. (1999), Novelty detection using extreme value statistics, IEE Proceedings-Vision, Image and Signal Processing, 146(3), 124-129. https://doi.org/10.1049/ip-vis:19990428
  17. Rurangirwa, A., Pierard-Franchimont, C., Le, T., Ghazi, A., and Pierard, G. E. (1987), Corroborative evidence that dry skin is a misnomer, Bioengineering and the Skin, 3(1), 35-42.
  18. Sharma, S. (1995), Applied multivariate techniques, John Wiley and Sons.
  19. Tang, T.-I., Zheng, G., Huang, Y., Shu, G., and Wang, P. (2005), A comparative study of medical data classification methods based on decision tree and system reconstruction analysis, Industrial Engineering and Management Systems, 4(1), 102-108.
  20. Tsukahara, K., Fujimura, T., Yoshida, Y., Kitahara, T., Hotta, M., Moriwaki, S., Witt, P. S., Simion, F. A., and Takema, Y. (2003), Comparison of age-related changes in wrinkling and sagging of the skin in Caucasian females and in Japanese females, Journal of Cosmetic Science, 55(4), 351-371.
  21. Tsukahara, K., Sugata, K., Osanai, O., Ohuchi, A., Miyauchi, Y., Takizawa, M., and Kitahara, T. (2007), Comparison of age-related changes in facial wrinkles and sagging in the skin of Japanese, Chinese and Thai women, Journal of Dermatological Science, 47(1), 19-28. https://doi.org/10.1016/j.jdermsci.2007.03.007
  22. Wendling, P. A. and Dell'Acqua, G. (2003), Skin biophysical properties of a population living in Valais, Switzerland, Skin Research and Technology, 9(4), 331-338. https://doi.org/10.1034/j.1600-0846.2003.00040.x
  23. Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., and Steinberg, D. (2008), Top 10 algorithms in data mining, Knowledge and Information Systems, 14(1), 1-37. https://doi.org/10.1007/s10115-007-0114-2
  24. Youn, S. W., Na, J. I., Choi, S. Y., Huh, C. H., and Park, K. C. (2005), Regional and seasonal variations in facial sebum secretions: a proposal for the definition of combination skin type, Skin Research and Technology, 11(3), 189-195. https://doi.org/10.1111/j.1600-0846.2005.00119.x
  25. Zonios, G., Bykowski, J., and Kollias, N. (2001), Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy, Journal of Investigative Dermatology, 117(6), 1452-1457. https://doi.org/10.1046/j.0022-202x.2001.01577.x