TY  - JOUR
AU  - Blesić, Suzana
AU  - du Preez, D. Jean
AU  - Stratimirović, Đorđe
AU  - Ajtić, Jelena
AU  - Ramotsehoa, M. Cynthia
AU  - Allen, Martin W.
AU  - Wright, Caradee Y.
PY  - 2020
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2485
AB  - 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.
PB  - Academic Press Inc Elsevier Science, San Diego
T2  - Environmental Research
T1  - Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis
VL  - 182
DO  - 10.1016/j.envres.2019.108976
ER  - 

@article{
author = "Blesić, Suzana and du Preez, D. Jean and Stratimirović, Đorđe and Ajtić, Jelena and Ramotsehoa, M. Cynthia and Allen, Martin W. and Wright, Caradee Y.",
year = "2020",
abstract = "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.",
publisher = "Academic Press Inc Elsevier Science, San Diego",
journal = "Environmental Research",
title = "Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis",
volume = "182",
doi = "10.1016/j.envres.2019.108976"
}

Blesić, S., du Preez, D. J., Stratimirović, Đ., Ajtić, J., Ramotsehoa, M. C., Allen, M. W.,& Wright, C. Y.. (2020). Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis. in Environmental Research
Academic Press Inc Elsevier Science, San Diego., 182.
https://doi.org/10.1016/j.envres.2019.108976

Blesić S, du Preez DJ, Stratimirović Đ, Ajtić J, Ramotsehoa MC, Allen MW, Wright CY. Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis. in Environmental Research. 2020;182.
doi:10.1016/j.envres.2019.108976 .

Blesić, Suzana, du Preez, D. Jean, Stratimirović, Đorđe, Ajtić, Jelena, Ramotsehoa, M. Cynthia, Allen, Martin W., Wright, Caradee Y., "Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis" in Environmental Research, 182 (2020),
https://doi.org/10.1016/j.envres.2019.108976 . .

TY  - JOUR
AU  - Blesić, Suzana
AU  - Stratimirović, Đorđe
AU  - Ajtić, Jelena
AU  - Wright, Caradee Y.
AU  - Allen, Martin W.
PY  - 2016
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2098
AB  - 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 analysed the sun exposure recordings of school children, farmers, marathon runners and outdoor workers in South Africa, and construction workers and work site supervisors in New Zealand. We found scaling behaviour in all the analysed pUVR data sets. 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 behaviour that were to some extent universal across our data set. Our study also showed that WT measures enable group classification, as well as distinction between individual UVR exposures, otherwise unattainable by conventional statistical methods.
PB  - Nature Publishing Group, New York
T2  - Journal of Exposure Science & Environmental Epidemiology
T1  - Novel approach to analysing large data sets of personal sun exposure measurements
VL  - 26
IS  - 6
SP  - 613
EP  - 620
DO  - 10.1038/jes.2016.43
ER  - 

@article{
author = "Blesić, Suzana and Stratimirović, Đorđe and Ajtić, Jelena and Wright, Caradee Y. and Allen, Martin W.",
year = "2016",
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 analysed the sun exposure recordings of school children, farmers, marathon runners and outdoor workers in South Africa, and construction workers and work site supervisors in New Zealand. We found scaling behaviour in all the analysed pUVR data sets. 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 behaviour that were to some extent universal across our data set. Our study also showed that WT measures enable group classification, as well as distinction between individual UVR exposures, otherwise unattainable by conventional statistical methods.",
publisher = "Nature Publishing Group, New York",
journal = "Journal of Exposure Science & Environmental Epidemiology",
title = "Novel approach to analysing large data sets of personal sun exposure measurements",
volume = "26",
number = "6",
pages = "613-620",
doi = "10.1038/jes.2016.43"
}

Blesić, S., Stratimirović, Đ., Ajtić, J., Wright, C. Y.,& Allen, M. W.. (2016). Novel approach to analysing large data sets of personal sun exposure measurements. in Journal of Exposure Science & Environmental Epidemiology
Nature Publishing Group, New York., 26(6), 613-620.
https://doi.org/10.1038/jes.2016.43

Blesić S, Stratimirović Đ, Ajtić J, Wright CY, Allen MW. Novel approach to analysing large data sets of personal sun exposure measurements. in Journal of Exposure Science & Environmental Epidemiology. 2016;26(6):613-620.
doi:10.1038/jes.2016.43 .

Blesić, Suzana, Stratimirović, Đorđe, Ajtić, Jelena, Wright, Caradee Y., Allen, Martin W., "Novel approach to analysing large data sets of personal sun exposure measurements" in Journal of Exposure Science & Environmental Epidemiology, 26, no. 6 (2016):613-620,
https://doi.org/10.1038/jes.2016.43 . .