Using sensors to assess UV radiation dose and associations with Vitamin D
Topics: Spatial Analysis & Modeling
, Medical and Health Geography
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Keywords: vitamin D, GPS, dynamic exposure, sunlight, mobility, health
Session Type: Virtual Paper
Day: Sunday
Session Start / End Time: 4/11/2021 09:35 AM (Pacific Time (US & Canada)) - 4/11/2021 10:50 AM (Pacific Time (US & Canada))
Room: Virtual 8
Authors:
Suzanne Mavoa, University of Melbourne
Marta M Jankowska, University of California, San Diego
Katie Crist, University of California, San Diego
Raphael Cuomo, University of California, San Diego
Calvin P Tribby, University of Hong Kong
Jiue-An Yang, University of California, San Diego
Steven Zamora, University of California, San Diego
Dorothy D Sears, Arizona State University
Loki Natarajan, University of California, San Diego
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Abstract
Vitamin D is essential for healthy body function, and vitamin D deficiency has been linked with numerous chronic diseases. Sunlight, specifically UVB radiation, is considered the most important source of vitamin D in humans. While coarse estimates of UVB exposure exist, it is challenging to assess individual level exposures. This is in part because the amount of UVB radiation we are exposed to varies according to numerous factors such as time (of day, season), location (latitude), weather (cloud), and individual factors (e.g. skin colour, clothing, sunscreen, mobility patterns). Here we propose a spatiotemporal method to assess individual UVB exposures sufficient to synthesise vitamin D by combining data from a range of sensors (GPS, accelerometers, satellite imagery). We demonstrate the feasibility of the method and perform a sensitivity analysis using a dataset of 140 adults living in San Diego who wore GPS and accelerometers for 7 consecutive days and provided blood samples, providing levels of serum circulating vitamin D. Our spatiotemporal analysis uses GPS/accelerometer data to identify outdoor movement, and then based on the time of day, season, and satellite derived UVB levels we estimate a range of UVB exposure measures. Finally we model relationships between our UVB exposure measures and vitamin D levels and vitamin D deficiency adjusting for age, sex, race, ethnicity, income, household type, work status, dietary vitamin D (mcg), and use of vitamin D and other supplements.