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

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. Cardiometabolic diseases (CMDs) are prevalent in the United States (US). The most recent data shows that 41.9%¹, 47%², and 38.1% of the adults in the US are obese, have hypertension, and have high cholesterol, respectively. Rising levels of CMDs in the country are inseparable from structural changes in the food systems, including economic policies which drove the rapid expansion of fast food chains, technical advances that popularized ultra-processed foods, and the exurbanization process that decentralized residential communities. These policy and urban changes ultimately induced an uneven foodscape with detrimental health consequences, primarily the development of CMDs⁵⁻¹². As such, national food and health initiatives have taken strides to evaluate food access disparities using food environment measures, including the Food Access Research Atlas and the modified retail food environment index (mRFEI), as evidence when designing policy interventions to improve diet-related health outcomes¹³. However, the connection between such food environment measures and CMDs remains far from conclusive¹⁴⁻¹⁵. For example, while some studies identified a positive relationship between fast food restaurant accessibility and obesity¹⁶, others found negative¹⁷, null, and mixed relationships¹⁸. Numerous confounding factors may account for such inconsistencies, such as measures of environmental exposures, obesity indicators, and units of analysis¹⁹. One often overlooked aspect is human mobility. Specifically, food environment measures usually rely on a fixed number of retailers within predefined administrative units (e.g., counties, census tracts), assuming that people are exclusively exposed to food retailers within a unit²⁰. In reality, however, consumers’ food procurement activities often extend beyond a single location or a unit²¹. Further, because of tiers of behavioral uncertainties (e.g., food culture, health education, food security status), their food exposure and activities may not mirror the foodscape near their place of residence. These behavioral uncertainties play a more direct role

Ran Xu, Xiao Huang, Kai Zhang, Weixuan Lyu, Debarchana Ghosh, Zhenlong Li, Xiang Chen