A general model to predict individual exposure to solar UV by using ambient irradiance data.

TitreA general model to predict individual exposure to solar UV by using ambient irradiance data.
Publication TypeJournal Article
Year of Publication2015
AuthorsVernez, D, Milon, A, Vuilleumier, L, Bulliard, J-L, Koechlin, A, Boniol, M, Doré, JF
JournalJournal of Exposure Science and Environmental Epidemiology
Volume25
Issue1
Pagination113-118
Date Published01/2015
DOI10.1038/jes.2014.6
ISSN1559-064X
Mots-clésBiological, Models, Occupational Exposure, Risk Factors, Theoretical, Ultraviolet Rays
Abstract

Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.

Notes

Publication types: Journal Article Publication Status: ppublish

Alternate URL

http://www.ncbi.nlm.nih.gov/pubmed/24496216?dopt=Abstract

First publication date (online)

02/2014

WOS ID (UT)

000346431500017

Alternate JournalJ Expo Sci Environ Epidemiol
Citation Key / SERVAL ID3532
Peer reviewRefereed
PubMed ID24496216
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