Built environments directly influence health, for example through air pollution and noise exposures, and indirectly influence health through changing health-related behaviors, for which physical activity is a major contributor. Nearly all epidemiology studies examining the relationships between long-term built environment related exposures and health have relied solely on residential address. This has severe limitations related to exposure misclassification and bias from residential selection, and does not capture how individuals interact with the built environment. Some studies have conducted GPS monitoring, but these include small populations (<500 people) and short time-periods (one to four weeks) due to cost and logistical constraints. We have been evaluating Google Location History Timeline data (referred to as Google TimeLine, or GTL) as a viable source of long-term passive GPS time activity data for advancing built environment and health research. GTL data is collected from both android and apple smartphones (that have Google maps or other apps installed) for opt-in participants. To-date, no health study has attempted to leverage GTL for improving exposure assessment or epidemiological research. We will develop and evaluate methods to derive built environment exposures from GTL data, using approaches that protect the privacy of study participants and evaluate these methods within a subset of the Washington Twin Registry Study who have already participated in a two-week GPS and accelerometry study. We will also develop approaches to assess physical activity from GTL data, providing a completely novel and objective measure of physical activity levels. If we are successful in developing and evaluating methods to use GTL data for epidemiological research this will completely revolutionize how we study built environment influences on human health.
The characteristics of cities and communities have important impacts on human health, but researchers are limited in how they can assess individuals' exposures to features of the built environment important to health. Here we evaluate and apply Google Timeline Location Data for assessing long-term time-activity based built environment exposures and physical activity levels.
