Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

Ailing Jin, Xiang Chen, Xiao Huang, Zhenlong Li, Caitlin E. Caspi, Ran Xu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The community food environment has potential influences on community members’ dietary health outcomes, such as obesity and Type II diabetes. However, most existing studies evaluating such health effects neglect human mobility. In food patrons’ daily travels, certain locations may be preferred and patronized more frequently than others. This behavioral uncertainty, known as the selective daily mobility bias (SDMB), is less explored in community-food-environment research. In this paper, we aim to confirm the existence of the SDMB by systematically exploring the large-scale GPS-based restaurant-visit patterns in the Greater Harford region, Connecticut. Next, we explore the restaurant and neighborhood characteristics that are associated with the restaurant-visit patterns. Our primary results demonstrate that (1) most restaurant customers originate from areas outside of the census tract where the restaurant is located, and (2) restaurants located in socially vulnerable areas attract more customers in total, more customers from local areas, and more customers from other socially vulnerable areas. These results confirm the relevance of the SDMB to the community food environment, and suggest ways that the SDMB can be moderated by an uneven socio-economic landscape. The findings demonstrate the necessity of incorporating human-mobility data into the study of the community food environment.

Original languageEnglish (US)
Article number404
Issue number2
StatePublished - Jan 2023

All Science Journal Classification (ASJC) codes

  • Food Science
  • Nutrition and Dietetics

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