The more fast food restaurants a person lives near in the United States, the more likely they are to develop type 2 diabetes, new research indicates.
The national study of more than 4 million US veterans also found the opposite association with supermarkets in suburban and rural communities, but not others.
“Neighborhood food environment was associated with type 2 diabetes risk among US veterans in multiple community types, suggesting potential avenues for action to address the burden of type 2 diabetes,” say Rania Kanchi, MPH, of the Department of Population Health, New York University Langone Health, and colleagues.
Restriction of fast food establishments could benefit all types of communities, while interventions to increase supermarket availability could help minimize diabetes risk in suburban and rural communities, they stress.
“These actions, combined with increasing awareness of the risk of type 2 diabetes and the importance of healthy diet intake, might be associated with a decrease in the burden of type 2 diabetes among adults in the US,” the researchers add.
The data were published online October 29 in JAMA Network Open.
“The more we learn about the relationship between the food environment and chronic diseases like type 2 diabetes, the more policymakers can act by improving the mix of healthy food options sold in restaurants and food outlets, or by creating better zoning laws that promote optimal food options for residents,” commented Lorna Thorpe, PhD, MPH, professor in the Department of Population Health at NYU Langone and senior author of the study in a press release.
In an accompanying editorial, Elham Hatef, MD, MPH, of the Center for Population Health IT at Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, calls the study “a great example of the capabilities of [health information technology] to provide a comprehensive assessment of a person’s health, which goes beyond just documenting clinical diseases and medical interventions.”
Research Has Large Geographic Breadth
The study is notable for its large geographic breadth, say the researchers.
“Most studies that examine the built food environment and its relationship to chronic diseases have been much smaller or conducted in localized areas,” said Kanchi in the press statement.
“Our study design is national in scope and allowed us to identify the types of communities that people are living in, characterize their food environment, and observe what happens to them over time. The size of our cohort allows for geographic generalizability in a way that other studies do not,” Kanchi continued.
The research included data for 4,100,650 individuals from the Veterans Affairs electronic health records (EHRs) who didn’t have type 2 diabetes at baseline, between 2008 and 2016. After a median follow-up of 5.5 person-years, 13.2% developed type 2 diabetes. Cumulative incidence was greater among those who were older, those who were non-Hispanic Black compared with other races, and those with disabilities and lower incomes.
The proportion of adults with type 2 diabetes was highest among those living in high-density urban communities (14.3%), followed by low-density urban (13.1%), rural (13.2%), and suburban (12.6%) communities.
Overall, a 10% increase in the number of fast food restaurants compared with other food establishments in a given neighborhood was associated with a 1% increased risk for incident type 2 diabetes in high-density urban, low-density urban, and rural communities and a 2% increased risk in suburban communities.
In contrast, a 10% increase in supermarket density compared with other food stores was associated with a lower risk for type 2 diabetes in suburban and rural communities, but the association wasn’t significant elsewhere.
“Taken together, our findings suggest that policies specific to fast food restaurants, such as [those]…restricting the siting of fast food restaurants and healthy beverage default laws, may be effective in reducing type 2 diabetes risk in all community types,” say the authors.
“In urban areas where population and retail density are growing, it will be even more important to focus on these policies,” they emphasize.
Great Example of Capabilities of Health Information Technology
In the editorial, Hatef notes that methodological advances, such as natural language processing and machine learning, have enabled health systems to use real-world data such as the free-text notes in the EHR to identify patient-level risk factors for diseases or disease complications.
Such methods could be further used to “evaluate the associations between social needs and place-based [social determinants of health] and type 2 diabetes incidence and management,” Hatef adds.
And linkage of data from the EHR to such community-level data “would help to comprehensively assess and identify patients likely to experience type 2 diabetes and its complications as a result of their risk factors or characteristics of the neighborhoods where they reside.”
“This approach could foster collaborations between the health systems and at-risk communities they serve and help to reallocate health system resources to those in most need in the community to reduce the burden of type 2 diabetes and other chronic conditions among racial minority groups and socioeconomically disadvantaged patients and to advance population health.”
The study was supported by the Centers for Disease Control and Prevention, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Aging, the Commonwealth Universal Research Enhancement program funded by the Pennsylvania Department of Health, the Urban Health Collaborative at Drexel University, and the Built Environment and Health Research Group at Columbia University. Kanchi and Hatef have reported no relevant financial relationships.
JAMA Netw Open. Published online October 29, 2021.
Miriam E. Tucker is a freelance journalist based in the Washington, DC, area. She is a regular contributor to Medscape, with other work appearing in The Washington Post, NPR’s Shots blog, and Diabetes Forecast magazine. She is on Twitter: @MiriamETucker.
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