Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis.

Studies of personal solar ultraviolet radiation (pUVR) exposure are important to identify populations at-risk of excess and insufficient exposure given the negative and positive health impacts, respectively, of time spent in the sun. Electronic UVR dosimeters measure personal solar UVR exposure at high frequency intervals generating large datasets. Sophisticated methods are needed to analyze these data. Previously, wavelet transform (WT) analysis was applied to high-frequency personal recordings collected by electronic UVR dosimeters. Those findings showed scaling behavior in the datasets that changed from uncorrelated to long-range correlated with increasing duration of time spent in the sun. We hypothesized that the WT slope would be influenced by the duration of time that a person spends in continuum outside. In this study, we address this hypothesis by using an experimental study approach. We aimed to corroborate this hypothesis and to characterize the extent and nature of influence time a person spends outside has on the shape of statistical functions that we used to analyze individual UVR exposure patterns. Detrended fluctuation analysis (DFA) was applied to personal sun exposure data. We analyzed sun exposure recordings from skiers (on snow) and hikers in Europe, golfers in New Zealand and outdoor workers in South Africa. Results confirmed validity of the DFA superposition rule for assessment of pUVR data and showed that pUVR scaling is determined by personal patterns of exposure on lower scales. We also showed that this dominance ends at the range of time scales comparable to the maximal duration of continuous exposure to solar UVR during the day; in this way the superposition rule can be used to quantify behavioral patterns, particularly accurate if it is determined on WT curves. These findings confirm a novel way in which large datasets of personal UVR data may be analyzed to inform messaging regarding safe sun exposure for human health.

The Epidemiology of Skin Cancer and Public Health Strategies for Its Prevention in Southern Africa.

Skin cancer is a non-communicable disease that has been underexplored in Africa, including Southern Africa. Exposure to solar ultraviolet radiation (UVR) is an important, potentially modifiable risk factor for skin cancer. The countries which comprise Southern Africa are Botswana, Lesotho, Namibia, South Africa, and Swaziland. They differ in population size and composition and experience different levels of solar UVR. Here, the epidemiology and prevalence of skin cancer in Southern African countries are outlined. Information is provided on skin cancer prevention campaigns in these countries, and evidence sought to support recommendations for skin cancer prevention, especially for people with fair skin, or oculocutaneous albinism or HIV-AIDS who are at the greatest risk. Consideration is given to the possible impacts of climate change on skin cancer in Southern Africa and the need for adaptation and human behavioural change is emphasized.

Comparison of GOME-2 UVA Satellite Data to Ground-Based UVA Measurements in South Africa.

Satellite estimates of surface ultraviolet A (UVA) (315-400 nm) from the Global Ozone Monitoring Experiment (GOME)-2 were compared to ground-based measurements at four stations in South Africa for 2015. The comparison of daily exposure and daily maximum irradiance was completed for all-sky and clear-sky conditions. There is a strong linear correlation between the satellite and ground-based data with a correlation coefficient (r) between 0.86 and 0.97 for all-sky conditions. However, at three of the stations the satellite data are underestimated compared to ground-based data with a mean bias error (MBE) between -8.7% and -20.6%. A seasonal analysis indicated that there is a link between the bias in ground-based and GOME-2 UVA and cloud fraction. Factors such as aerosols, surface albedo, altitude and data resolution may contribute to the underestimations found at the three sites. These results indicate that satellite estimates of surface UVA over South Africa do not exhibit the same behavior as other stations around the world and therefore require further validation.