Integrating human activity into food environments can better predict cardiometabolic diseases in the United States

Ran Xu, Xiao Huang, Kai Zhang, Weixuan Lyu, Debarchana Ghosh, Zhenlong Li and Xiang Chen ()
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Ran Xu: University of Connecticut
Xiao Huang: Emory University
Kai Zhang: University at Albany, State University of New York
Weixuan Lyu: University of Connecticut
Debarchana Ghosh: University of Connecticut
Zhenlong Li: University of South Carolina
Xiang Chen: University of Connecticut

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract The prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integrate human activity into scalable measures. In this paper, we develop the retail food activity index (RFAI) at the census tract level by utilizing Global Positioning System tracking data covering over 94 million aggregated visit records to approximately 359,000 food retailers across the United States over two years. Here we show that the RFAI has significant associations with the prevalence of multiple cardiometabolic diseases. Our study indicates that the RFAI is a promising index with the potential for guiding the development of policies and health interventions aimed at curtailing the burden of cardiometabolic diseases, especially in communities characterized by obesogenic dietary behaviors.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42667-8

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DOI: 10.1038/s41467-023-42667-8

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