ABSTRACT Spending time outdoors increases children’s physical activity and promotes engagement with nature, which has been shown to have positive benefits on children’s mental, cognitive, and behavioral health. However, outdoor time is difficult to quantify, with most studies relying on self- or caregiver-reported outdoor time. One solution is to use accelerometers equipped with ambient light sensor technology. The light sensor delivers an estimate of light exposure (i.e., lux values) that can be used to objectively quantify children’s outdoor time. Despite the ubiquitous use of accelerometers, most researchers have not taken advantage of this tool. Of the studies that have used ambient light data, analytic approaches have varied. Specifically, studies have used different lux cut points to distinguish between indoor and outdoor time, and have not considered placement of the accelerometer (i.e., hip vs. wrist worn) or the potential error due to seasonality or weather conditions. Therefore, the objective of this project is to develop and disseminate a set of best practices for analyzing accelerometer-derived ambient light data in order to provide an objective assessment of outdoor time in children. The proposed project will analyze secondary data from two NHLBI funded intervention trials targeting physical activity promotion in the child care setting. Both trials included accelerometer data with the ambient light sensor enabled as well as data from the Environment and Policy Assessment and Observation (EPAO) tool, an observational measure that contains detailed time stamped data of the child care day including indoor and outdoor time. In Aim 1, accelerometer data will be harmonized to facilitate comparisons between hip- and wrist-worn devices and then combined with the corresponding EPAO data. In Aim 2, receiver operator characteristic curve analysis will be used to identify the optimal lux cut point to distinguish between indoor and outdoor time, comparing accelerometer lux values to the documented indoor and outdoor time from the EPAO. Then, we will compare how well the identified lux cut point performs in distinguishing outdoor time in wrist vs. hip worn accelerometers. Finally, we will compare how seasonality and different weather conditions (i.e., cloudy vs. clear days) affect lux readings. In Aim 3, we will examine the association between objectively measured outdoor time and children’s physical activity while at child care using the newly developed analytic guidelines. In order to promote consistency in the field, we will disseminate the best practices by developing open source code for other researchers that can be applied to existing datasets and repositories of accelerometer data. Overall, this project will address key measurement gaps in assessing young children’s physical activity and outdoor time. Improving measurement of outdoor time will further add to research into the health impact of spending time outdoors, aid in the identificati...