Advancing neighborhood exposure assessment with GPS-based mobility data: toward theoretically driven standardized approaches in population Health Research.

Abstract

Global positioning system (GPS) data capture fine-scale spatial and temporal mobility, enabling more precise, individualized assessments of neighborhood exposures than residential address-based measures. Despite growing use, there is little consensus on how to define and quantify GPS-based exposures, highlighting the need for theory-informed approaches. This study demonstrates how GPS data can enhance neighborhood exposure assessment, address spatial misclassification, and inform future research on mobility and neighborhood environments. We integrated theoretical frameworks from psychology, sociology, and geography into GPS-based research using data from two cohort studies: the Neighborhoods and Networks (N2) Study and the Trying to Understand Relationships, Networks, and Neighborhoods among Trans Women of Color (TURNNT) Study. The final GPS analytic sample was 649 participants. We constructed GPS-based neighborhood exposure measures, including direct exposure to specific locations and neighborhood psychosocial exposures, and compared these metrics with conventional residential address-based measures. We also derived GPS-based mobility measures to characterize individual mobility patterns. GPS-based measures captured higher variability in neighborhood exposures compared with residential-based measures. GPS-derived mobility measures further characterized individual mobility patterns, providing additional context for understanding exposure beyond residential location. Accounting for spatial and temporal dimensions offers a robust foundation for future studies with more precise spatially relevant health interventions.