Understanding urban health equity through the study of activity spaces using big data: A case study of Southeast Michigan

A growing body of research has linked social and environmental factors to health outcomes and health equity, with most studies focusing on residential neighborhoods. While activity space—the places people regularly visit—has been increasingly recognized as critical to health, there remains a lack of scalable, quantitative methods to assess its impact on health equity. This study addresses this gap by developing a big-data-driven approach that integrates 5.48 million origin–destination (O–D) pairs from SafeGraph travel data with demographic and environmental datasets to examine health equity in Southeast Michigan. The study assessed the difference between home ranges of residents of Black-/Hispanic-/White-dominant census tracts and measured three health-related aspects of residential and activity spaces with the Mann–Whitney U test ( U ) and Rank-Biserial Correlation ( rrb ). Through a systematic variable selection process, 13 out of 31 variables were selected to construct six indices that present: (1) socioeconomic disadvantages of residents (NDI [Neighborhood Disadvantage Index]/ANDI [Activity Space Neighborhood Disadvantage Index]), (2) access to health-essential resources (HOI [Health Opportunity Index]/AHOI [Activity Space Health Opportunity Index]), and (3) exposure to health disamenities (UEI [Unhealthy Exposure Index]/AUEI [Activity Space Unhealthy Exposure Index]). Results indicate that 91.2% of trips extend beyond residents’ home census tracts, and 73.6% reach beyond immediate neighboring tracts. White-dominant tract residents exhibit significantly larger home range areas (median = 782.3 km 2 ), which is 2.43 and 1.35 times that of Hispanic- and Black-dominant tract residents, respectively, indicating better mobility and affordance to diverse destinations. Furthermore, residents of Hispanic- and Black-dominant tracts experienced significantly higher levels of socioeconomic disadvantage and health risks both at home and in their activity spaces, reinforcing persistent disparities. As evidenced by increased rrb of pairwise U tests between three groups, social and environmental disparities were also intensified in activity spaces (e.g., rrb-NDI White-Black = 0.82 and rrb-ANDI White-Black = 0.92). By comparing the activity space patterns and health indices of different racial groups, this research provides a big-data-empowered and straightforward method to assess social and environmental disparities that contribute to health gaps. These findings provide actionable insights for urban planners to develop health-equity-focused, activity-space-informed policies aimed at mitigating structural inequalities in mobility and environmental exposure.