Novel approach to analysing large data sets of personal sun exposure measurements

Abstract

Personal sun exposure measurements provide important information to guide the development of sun awareness and disease prevention campaigns. We assess the scaling properties of personal ultraviolet radiation (pUVR) sun exposure measurements using the Wavelet Transform (WT) spectral analysis to process long-range, high frequency personal recordings collected by electronic UVR dosimeters designed to measure erythemal UVR exposure. We analyzed the sun exposure recordings of schoolchildren, farmers, marathon runners and outdoor workers in South Africa, and construction workers and work site supervisors in New Zealand. We found scaling behavior in all the analysed pUVR datasets. We found that the observed scaling changes from uncorrelated to long-range correlated with increasing duration of sun exposure. Peaks in the WT spectra that we found suggest the existence of characteristic times in sun exposure behavior that were to some extent universal across our dataset. Our study also showed that WT measures enable group classification, as well as distinction between individual UVR exposures, otherwise unattainable by conventional statistical methods.