Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA.
Nat Commun. 2024 Mar 14;15(1):2291. doi: 10.1038/s41467-024-46425-2.
Poor diets are a leading cause of morbidity and mortality. Exposure to low-quality food environments saturated with fast food outlets is hypothesized to negatively impact diet. However, food environment research has predominantly focused on static food environments around home neighborhoods and generated mixed findings. In this work, we leverage population-scale mobility data in the U.S. to examine 62M people's visits to food outlets and evaluate how food choice is influenced by the food environments people are exposed to as they move through their daily routines. We find that a 10% increase in exposure to fast food outlets in mobile environments increases individuals' odds of visitation by 20%. Using our results, we simulate multiple policy strategies for intervening on food environments to reduce fast-food outlet visits. This analysis suggests that optimal interventions are informed by spatial, temporal, and behavioral features and could have 2x to 4x larger effect than traditional interventions focused on home food environments.
不良饮食是导致发病率和死亡率的主要原因之一。人们假设，接触充斥着快餐店的低质量食品环境会对饮食产生负面影响。然而，食品环境研究主要集中在家庭周边的静态食品环境上，得出的结果也不一致。在这项工作中，我们利用美国的人口规模移动数据，研究了 6200 万人对食品店的访问情况，并评估了人们在日常生活中移动时所接触的食品环境如何影响他们的食物选择。我们发现，移动环境中快餐店暴露率增加 10%，会使个人光顾快餐店的几率增加 20%。利用我们的研究结果，我们模拟了多种干预食品环境以减少光顾快餐店的策略。这项分析表明，最佳干预措施需要考虑空间、时间和行为特征，其效果可能是传统专注于家庭食品环境的干预措施的 2 到 4 倍。
