Validation of a spatiotemporal light exposure model using personal wearable sensors

Keywords: epidemiology, environmental exposure, GIS, exposure model, wearable sensors
Abstract Type: Virtual Paper Abstract

Abstract

Background: Circadian misalignment has been associated with adverse health outcomes including cancer. One potential source of circadian misalignment is from location within a time zone, which we refer to as environmental circadian misalignment (ECM) as it relates to geographic variation in light exposure. The mismatch between sun time and local clock time, and thus timing and duration of light exposure, increases with greater distance moving east to west within a time zone. The objective of this pilot study was to validate a novel spatiotemporal exposure model for ECM using wearable light sensors.

Methods: We recruited 20 individuals in Seattle, WA and Boston, MA to participate in a 2-week study wearing a LYS Button light sensor (spectral range of 350-750 nm). Participants completed a baseline questionnaire collecting information on residential and work locations, demographics, chronotype, occupations, and health status.

Results: We completed data collection for 20 study participants in November 2022. We will present results comparing geospatial-based ECM exposure and personal light sensor-based exposure using linear regression. ECM will be calculated using our new spatiotemporal exposure model that utilizes a geographic information system (GIS) to combine geospatial data on each participant’s geocoded addresses, location within a time zone, elevation, sunrise time, and sunset time. We hypothesize that higher geospatial-based ECM exposure will be associated with higher light sensor-based exposure.

Impact: This new geospatial ECM exposure model can be used in population-based epidemiologic research allowing for comprehensive characterization of geographic variation in light exposure potentially impacting circadian phase.