Exploratory multivariate spectroscopic study on human skin.

Skin Res Technol

Coloplast Research, Coloplast A/S, Bakkegaardsvej 406A, DK-3050 Humlebaek, Denmark.

Published: May 2003

Background/aims: Spectroscopy on human skin is a field that is being adopted increasingly because of its rapidity and high reproducibility. Infrared reflectance (IR), near-infrared reflectance (NIR), and fluorescence spectroscopy have previously been applied to human skin in vivo to compare healthy and sick skin, including skin cancer, atopy, and leprosy. Exploratory data analysis/chemometrics is a tool for evaluating multivariate data such as spectroscopic measurements. The objective of this study was to explore the spectral variance spanned by people with normal integument, and to demonstrate the advantages of multivariate analysis to skin research.

Methods: IR, NIR and fluorescence spectroscopy have been carried out in vivo on 216 volunteers' forearms before and after four tape strippings. The subjects were asked to fill in a questionnaire regarding factors suspected to influence the measurement results. Principal Component Analysis (PCA) was used to investigate whether the population can be divided into groups on the basis of their skin chemistry. Unless otherwise stated, the results are from the measurements prior to stripping.

Results: In contrast to IR and fluorescence spectra, NIR spectra proved able to detect gender differences. By use of PCA, classifications on male and female subjects were observed from the IR and NIR measurements, and as an indication from the fluorescence measurements. The NIR and fluorescence measurements varied between elderly and young subjects. The largest variance in the fluorescence landscapes was seen between pigmented and non-pigmented skin. No connection was found between the spectroscopic measurements and smoking or drinking habits.

Conclusions: Future spectroscopic skin investigations should be balanced as regards to gender and age, as these can possibly affect the measurement results. Chemometrics proved to be superior to traditional attempts of interpreting the spectra.

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Source
http://dx.doi.org/10.1034/j.1600-0846.2003.00014.xDOI Listing

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