Smartphone data reveals link between fast food establishments and diet-related diseases

How many fast food outlets do you encounter throughout the day and what does that have to do with your health? A lotsays Abigail Horn, senior scientist at USC’s Information Sciences Institute (ISI).

Horn led a multidisciplinary team that included researchers from three USC schools (Viterbi School of Engineering; Dornsife College of Letters, Arts and Sciences; and Keck School of Medicine), MIT, and Sabancı University in Turkey; and worked in collaboration with the Los Angeles County Department of Public Health. They set out to determine whether mobility (i.e., location) data from smartphones could provide a way to measure the dynamic food environments experienced individually by people, at scale across large, diverse populations and in diverse physical environments.

The question was: can we use mobility data to measure people’s visits to food establishments? Because that is a good indicator for eating food at that point of sale. “And then, can we go a step further to see if visits to food establishments observed in mobility data predict people’s rates of dietary illness?”

Abigail Horn, senior scientist at the USC Information Sciences Institute

Location, location, location

“It is well established that the physical environment can affect people’s eating decisions and therefore their diet-related health outcomes, but what we don’t know is the extent to which that is true,” said Horn, assistant professor research in the Daniel J. Epstein Department of Industrial and Systems Engineering at the USC Viterbi School of Engineering.

Physical food environments are the actual spaces where people acquire food. “Food establishments in your neighborhood, or around your workplace, or anywhere on your daily walk. Things like grocery stores, restaurants, or corner markets,” Horn explained.

These environments have been shown to affect people’s diet and therefore health outcomes (including diet-related diseases) in several ways. First, Horn said, “when people have little physical access to healthy foods, that can lead to making unhealthy choices out of convenience or necessity.” And second, “people can receive cues from food environments. So, for example, if throughout the day you see fast food establishments over and over again, that can cue or trigger certain behaviors” (i.e., eating more food fast). .

There are a number of studies that look at the food environments of people’s home neighborhood and associate them with food choices and diet-related illnesses. But the findings have been mixed, as have the results of public health initiatives that have focused on neighborhood food environments.

Horn explained: “In the last decade or so, more than $1 billion has been invested in public health interventions in domestic food environments. This could mean building a grocery store in a food desert. [a home neighborhood with limited access to nutritious food] or supplying that neighborhood’s corner stores with fresh fruits and vegetables.” But, he continued, “there has been no measurable impact on increasing healthy food purchases or people’s health outcomes. So what is going on here?”.

Kayla de la Haye is one of the members of the research team who could help answer that question. De la Haye is director of the Institute for Food System Equity at the USC Dornsife Center for Economic Research and has expertise in public health, nutrition and psychology. “One of my roles in this research was to provide expertise on how people make decisions about what to eat and the consequences of food environments that flood people with unhealthy options and put them at risk for many diet-related diseases, such as obesity and diabetes.”

Looking beyond the neighborhood market

De la Haye has worked with families throughout Los Angeles, from Lancaster to East Los Angeles, helping them with strategies to avoid unhealthy foods and adopt healthier eating habits. She said, “So I brought this real-world knowledge of the challenges Angelenos face in eating a healthy diet to our research project.”

The team knew, from their own experiences and from the experiences of families they had worked with in healthy eating programs, that people don’t just eat in their neighborhood. But they needed data to demonstrate it on a population scale. Horn said: “We think the lack of data showing all the places where people actually go to eat and where they spend the most time might explain why we’re not seeing associations between the neighborhood food environment and diet and eating habits. of people”. health outcomes.”

So they turned to smartphones for data.

For most of us, our smartphone always tracks our location and we probably share that data with various apps. Location data companies aggregate this data (called “mobility data”) and sell it for advertising purposes. But increasingly it is available for research, such as Spectus.ai through its Social Impact Program, through which the data for this study was obtained.

Esteban Moro led the MIT team that would help access and analyze this data. Moro, a research scientist at MIT Connection Science, said: “Our group has extensive experience analyzing and using mobility data on problems such as segregation, transportation, urban planning and commercial activity. We are experts in analyzing large data sets from the human behavior and transforming them into insightful tools for urban problems. Therefore, our main role in this research was to provide and analyze population-wide mobility data on food consumption.”

Gathering all the data

Using census block data for Los Angeles County to indicate neighborhoods of origin and big mobility data to track daily trajectories, the researchers were able to see all the proximity (the “exposures”) that people would have to retail outlets. of food throughout their days.

The team specifically looked at fast food establishments because fast food is commonly consumed and is strongly linked to disease risk. Using “hotspot” data, they identified fast food establishments within Los Angeles County. To integrate the health piece of the puzzle, they accessed survey data from the Los Angeles County Health Department.

“The Los Angeles County Health Department conducts a health survey of the Los Angeles population every three years. We formed a collaboration with them and they were able to share with us anonymized individual-level data on sociodemographics, obesity rates, diabetes and, very importantly, the frequency of fast food consumption for a representative sample of the Los Angeles population,” Horn said.

By analyzing the data, the researchers confirmed that your home neighborhood matters when it comes to your risk of diet-related diseases, but so does your commute—the path you take to run your daily errands, how you get from point A to point B. and to point Z of your day, and what those points are.

The results?

“We know there is a relationship between visits to fast food establishments and fast food consumption, as well as between fast food consumption and diet-related diseases, but wow, this data source does a very good job by capturing that!” Horn said.

Moro explained: “The most surprising result is that the mobility data works as an ‘honest signal’, that is, visits to fast food establishments were a better predictor of individuals’ obesity and diabetes than their food consumption.” rapid self-reported, controlling for other known risks.”

De la Haye emphasized: “This work demonstrates that large-scale mobility data is indeed a valuable indicator of where and what people eat, and their risk of diet-related diseases.”

Why is this so significant?

De la Haye explained: “Measuring what people eat is really difficult. In fact, many large public health surveys and surveillance tools have stopped asking people about their food intake because the data is often unreliable ( (partly because people often forget the details of what they ate, and also because they don’t always want to tell researchers about their less healthy food choices.) So, this gives us a new tool for tracking dietary patterns. , like eating fast food, for large populations, such as residents of cities, counties, or the entire country.”

Whats Next?

“What excites me as a researcher,” Horn said, “is that this opens up mobility data for all kinds of research on the food environment. Things like: Where do people get food at different times of the day? Who are they? When are they most influenced by the options available (or not available) to them? We can really investigate this with big mobility data, because it allows us to look at eating behaviors in new and broad dimensions: at scale across the entire population, across diverse groups of population, diverse environmental settings and over long periods of time.

De la Haye emphasizes the importance of this: “data on the dietary patterns of the population are a powerful tool necessary to develop public health programs and policies and, ultimately, reduce health risks derived from one of the main Causes of Disease and Death in the U.S.: Unhealthy Diets.” “