The “uneven road” to food: Socioeconomic disparities in the mobility burden of food purchasing behavior in major US cities, 2019–2023

Socioeconomic factors contribute to distinct patterns of food-purchasing behaviors, placing a higher burden of mobility on vulnerable, deprived populations. Traditional approaches often overlook the dynamics of human activity as contextual influences, simulating a perceived food environment that contradicts the actual use thereof. The rise of large-scale mobile phone data presents a unique opportunity to capture real behavioral patterns and their mobility implications at a fine-grained level. Using a Time-Weighted Kernel Density Estimation (TWKDE) model on mobile phone data, this study introduces two novel measures - the Spatial Engel’s Coefficient (SEC) index and the Distance-to-Activity Curve (DAC) – to assess the equity of food-purchasing travel across nine U.S. cities over five years, analyzed by socioeconomic status, time period, and location. The findings reveal that lower socioeconomic status is strongly associated with greater mobility burdens in food-purchasing travel. This mobility gap between the highest and lowest socioeconomic groups was further exacerbated during the COVID-19 pandemic, manifesting in the form of spatial segregation of opportunities within cities. This paper contributes to the literature by developing novel activity-based tools that offer a more nuanced understanding of the behavioral characteristics of food-purchasing activities. These empirical insights can help policymakers identify the communities facing the greatest mobility burdens and guide targeted, place-based interventions to promote equity in food access.

• Record URL:
  • https://doi.org/10.1016/j.healthplace.2024.103404
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1353829224002326
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13538292
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zha, Yilun
  • 0000-0002-6361-1349
• Publication Date: 2025-1

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 103404
• Serial:
  • Health & Place
  • Volume: 91
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1353-8292
  • EISSN: 1873-2054
  • Serial URL: http://www.journals.elsevier.com/health-and-place/

Subject/Index Terms

• TRT Terms: Economic and social factors; Grocery stores; Low income groups; Mobility; Transportation equity; Travel behavior; Trip purpose
• Subject Areas: Safety and Human Factors; Society; Transportation (General);

Filing Info

• Accession Number: 01945371
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 10 2025 2:29PM