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Smartphone location data used to evaluate risk of diet
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In a new study, a multidisciplinary team set out to see if smartphone mobility data could be used to quantify people's food access at scale across different populations and their corresponding neighborhoods. From there, they hoped to ascertain the inherent risk of diet-related diseases of a variety of populations.
Measuring food access
"The question was: can we use mobility data to measure people’s visits to food outlets? Because that’s a good proxy for eating food at that outlet. And then, can we go a step further to see whether visits to food outlets observed in the mobility data are predictive of people’s dietary disease rates?” said Abigail Horn, a lead scientist at USC’s Information Sciences Institute (ISI).
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Horn explained that it is generally recognized that the physical environment can influence people's eating habits and thus their diet-related health consequences, but that there is no conclusive evidence to either confirm or deny this hypothesis.
The long-held theory relies on two assumptions. First is the fact that when people have low physical access to healthy foods, they may have to resort to unhealthy choices out of convenience or necessity. Second is the premise that unhealthy food environments can cue and induce particular behaviors by mere fact of their ubiquitousness. The more junk food joints you see, the more likely you are to eat at them.
Over a billion dollars have been invested in public health interventions in home food contexts in the last ten years. However, the results of these efforts seem to have been in vain as they have not had a significant enough impact to lower diet-related diseases.
This is partially due to the fact that people don't only eat in their own neighborhoods. The research team understood this from their own experiences. However, they required statistics to demonstrate this fact. So they decided to explore phone data.
A lack of data
“We thought that the lack of data showing all of the places where people actually go to eat and where they’re spending the most time might explain why we’re not seeing associations between the home neighborhood food environment and people’s diet and health outcomes,” said Horn.
The researchers were able to track all of the access people had to food outlets throughout their days by using census block data from Los Angeles County. In this analysis, the team focused on fast-food restaurants since they are widely consumed and highly associated with disease risk.
The researchers were able to demonstrate that home neighborhoods matter when it comes to the risk of diet-related diseases but so do commutes, particularly daily ones.
“We know there is a relationship between fast-food outlet visits and fast-food intake, as well as between fast-food intake and diet-related diseases, but wow, this data source does a really good job of capturing that!” said Horn.
Now the team hopes that their new approach will become a powerful tool used for the development of public health programs and policies.
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