A recent study, spearheaded by Abigail Horn at USC’s Information Sciences Institute, has unveiled a novel approach to understanding the impact of food environments on people’s health.
The research, a collaborative effort involving experts from USC and elsewhere, utilized smartphone mobility data to explore the dynamic food environments experienced by individuals.
The study’s aim was to determine if people’s visits to food outlets, as indicated by their smartphone location data, could predict dietary disease rates.
Horn, a Research Assistant Professor at the USC Viterbi School of Engineering, emphasized the significance of understanding the influence of physical food environments, like grocery stores and fast-food outlets, on people’s dietary choices and consequent health outcomes.
Kayla de la Haye, Director of the Institute for Food System Equity at USC Dornsife, brought her expertise in public health and nutrition to the study.
The research team recognized that people’s eating habits extend beyond their home neighborhoods, encompassing their entire daily routes.
To gather data, the team utilized smartphone location tracking, a method that is often used for advertising purposes but is increasingly available for research. This approach allowed them to monitor where people actually go to eat and spend most of their time.
Esteban Moro from MIT’s Connection Science played a pivotal role in analyzing this mobility data, leveraging his experience in using such data for urban problems.
The study involved tracking daily trajectories of people in Los Angeles County, using census block data to identify home neighborhoods. Focusing on fast-food outlets, the researchers used point of interest data to locate these establishments within the county.
Health-related data, including obesity and diabetes rates as well as fast-food intake frequency, was obtained from the LA County Health Department’s survey.
The results were enlightening. The mobility data accurately captured the relationship between visits to fast-food outlets, fast-food intake, and diet-related diseases.
It was found to be a more reliable predictor of obesity and diabetes than self-reported fast-food intake, highlighting the utility of mobility data as a tool to track dietary patterns in large populations.
The significance of this study lies in its potential to revolutionize how dietary patterns are monitored and understood.
It opens up possibilities for extensive research into various aspects of the food environment, such as the timing and location of food acquisition and its influence on different demographic groups.
In summary, this innovative approach using smartphone mobility data offers a powerful new lens through which to view and understand the connections between our daily movements, food choices, and health outcomes.
This could be a game-changer for public health initiatives and policies aimed at tackling diet-related diseases.
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The research findings can be found in Digital Medicine.
