The iFit Study

    The iFit study was originally funded by the Hellman Foundation to develop individual-specific statistical models for health-related behaviors and to compare these new methods with traditional sample-based statistics in the accuracy of predicting health outcomes. Participants in this study wear Fitbit wristbands that automatically record their physical activity and sleep for 100 days. During this period of time, they also complete daily dairy surveys to report their diet, stress, and affect. Their weight status and cardiovascular health are tracked longitudinally for 6 months. The goal of the study is to examine whether day-to-day variation in health behaviors better predicts changes in individual health than static measures.

    Thanks to the Human Ecology Seed Grant, we are able to extend the iFit study to incorporate community-level characteristics in our data set. Specifically, using Geographic Information System (GIS) techniques, we extract information on the walkability of participants' residential and non-residential neighbourhoods. Currently, we are working with researchers with expertise in community development, environmental justice, and spatial analysis to study individual health from a multilevel, systematic perspective.
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The research team of the iFit study.