日用化学工业（中英文）2023，Vol.53Issue(12)：1412-1420,9.DOI:10.3969/j.issn.2097-2806.2023.12.008
中国年轻女性油性皮肤分类方法与特点研究
A study on the classification approach and characteristics of oily skin in young Chinese females
摘要
Abstract
Oily skincare is one of the common problems confronting young Chinese females.Currently,skin type characterization is largely based on self-reports and qualitative assessments by dermatologists.Quantitative classification approach for oily skin totally based on the non-invasive skin measurement devices has not been reported in the literatures.In this study,based on box-plot data and machine learning clustering algorithms for 2000 Chinese female subjects(mean aged 25.90±2.61),non-invasive,objective,and quantitative classification approach for oily skin were initially established and compared with dermatologists'empirical results for mutual corroboration.On this basis,this study quantitatively collected data on skin barrier,chromaticity,elasticity,acne and other indicators through a multifunctional probe tester and a facial skin imaging system,analyzed the accompanying characteristics of oily skin and susceptible skin problems,clarified the characteristics of oily skin in young Chinese females,and evaluated the risk level of acne and sensitivity of oily skin,with a view to providing scientific care and guidance for Chinese young females with oily skin groups.The results show that the box-plot classification method based on facial hydro-oil distribution is superior to the other two types of methods.The accompanying characteristics of oily skin are poor barrier,dull complexion,less elasticity,more acne and pores.In addition,the risk of acne-prone skin is significantly higher in oily skin based on odds ratio.关键词
皮肤参数/易感问题/地域分布/风险程度/油性皮肤护理Key words
skin parameters/susceptibility/geographical distribution/odds ratio/oily skincare分类
化学化工引用本文复制引用
杨笑笑,颜欢,尹雅婷,易帆..中国年轻女性油性皮肤分类方法与特点研究[J].日用化学工业（中英文）,2023,53(12):1412-1420,9.基金项目
北京市教委一般科技项目(KM202010011009) （KM202010011009）
北京市优秀人才培养资助青年骨干个人项目(2018000020124G032) （2018000020124G032）
