Increased Access to Fast Food Ups Community T2D Risk

A higher density of fast-food restaurants was linked to increased incidence of type 2 diabetes (T2D) among U.S. veterans living in the surrounding community, but increased access to supermarkets was associated with lower T2D rates in suburban and rural areas, according to a study of Veteran’s Affairs (VA) health records.

A growing number of studies have found that availability of better neighborhood-level resources—such as the area’s suitability for physical activity and access to healthy food—was associated with a reduced risk for diabetes, while a higher density of less healthy food had the opposite effect. However, these studies have largely been limited to urban areas, which limits the generalizability of these associations to other environments, Rania Kanchi, MPH, of NYU Langone Health in New York, and colleagues explained in JAMA Network Open.

In order to explore these associations across a wider variety of community environments, Kanchi and colleagues used electronic health record (EHR) data from the VA to analyze the impact of neighborhood food environments, specifically the presence of fast-food restaurants and supermarkets, on the risk of T2D among U.S. veterans.

“This cohort study of U.S. veterans is the first, to our knowledge, to prospectively examine the association between neighborhood food environment and type 2 diabetes risk nationally and by community type, using exposure measures tailored to community type,” they wrote. “The availability of fast-food restaurants relative to all restaurants was associated with a higher risk of type 2 diabetes in all community types, whereas supermarkets were associated with a lower type 2 diabetes risk in suburban and rural communities. Our models did not find a significant association between supermarket availability and type 2 diabetes incidence in urban communities.”

For their analysis, Kanchi and colleagues pulled VA data for 4,100,650 U.S. veterans in the U.S. Veterans Administration Diabetes Risk (VADR) cohort who had not been diagnosed with T2D as of Jan. 1, 2008, and who had at least two primary care visits at least 30 days apart in any five-year period between Jan. 1, 2008-Dec. 31, 2016.

The primary study exposures were relative food environment measures, which included five-year mean counts of fast-food restaurants and supermarkets relative to other food outlets at baseline. “The association between food environment and time to incident diabetes was examined using piecewise exponential models with 2-year interval of person-time and county-level random effects stratifying by community types,” they explained.

Mean (SD) age among the study cohort was 59.4 (17.2) years; the majority of participants were non-Hispanic White (76.3%) and male (92.2%). Mean (IQR) duration of follow-up was 5.5 (2.6-9.8) person-years.

During follow-up, 13.2% of the cohort met the criteria for T2D incidence.

“The relative density of fast-food restaurants was positively associated with a modestly increased risk of type 2 diabetes in all community types,” the study authors found. “The adjusted hazard ratio (aHR) was 1.01 (95% CI, 1.00-1.02) in high-density urban communities, 1.01 (95% CI, 1.01-1.01) in low-density urban communities, 1.02 (95% CI, 1.01-1.03) in suburban communities, and 1.01 (95% CI, 1.01-1.02) in rural communities. The relative density of supermarkets was associated with lower type 2 diabetes risk only in suburban (aHR, 0.97; 95% CI, 0.96-0.99) and rural (aHR, 0.99; 95% CI, 0.98-0.99) communities.”

When absolute measures of neighborhood fast-food and supermarket density were used instead of relative measures, the results changed slightly: in high-density urban areas, fast-food density was no longer linked to increased T2D, while increased supermarket density was associated with a lower T2D risk.

Also among the findings:

• Cumulative T2D incidence was highest among those ages 60-79 years (17.0%), followed by those ages 40-59 years (14.9%); incidence was higher among males (13.6%) than females (8.2%); incidence was highest among non-Hispanic Black veterans (16.9%) and lowest among non-Hispanic Asian and Hispanic participants (12.8% each).
• Adults with either disability or low-income but no disability had a higher incidence of T2D (13.7% and 14.1%, respectively) compared to those with neither disability nor low income (11.5%); the proportion of individuals with T2D increased as neighborhood social and economic environment quartiles moved from most advantaged to least advantaged (11.8% vs 14.8%).
• T2D incidence was highest in high-density urban communities (14.3%), followed by low-density urban communities (13.1%) and rural communities (13.2%), and incidence was lowest in suburban communities (12.6%).

The lack of correlation between supermarket availability and T2D incidence in urban environments, they noted, could potentially be explained by increased access to public transportation and cars, particularly in low-density urban communities, “which could increase the ability to access supermarkets, regardless of availability within the residential neighborhoods. Thus, interventions targeting the placement or zoning of supermarkets may be more appropriate in suburban and rural communities.”

Kanchi and colleagues also pointed out that, while the association between relative availability of fast-food and T2D was similar across community types, results from a sensitivity analysis showed that the association was larger in suburban and rural communities compared to low-density urban areas, and it was null in high-density urban areas. One possible reason for this is that, given the high population density in these areas, “the absolute count of food outlets per kilometer may mirror population density, rather than quality of food environment.” And, they added, urban centers tend to have higher socioeconomic status than other areas in high-density urban communities.

“Taken together, our findings suggest that policies specific to fast-food restaurants, such as policies 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,” they wrote. “In urban areas where population and retail density are growing, it will be even more important to focus on these policies.”

In an editorial accompanying the study, Elham Hatef, MD, MPH, of Johns Hopkins Bloomberg School of Public Health in Baltimore, praised the analysis by Kanchi et al, particularly in regard to the methodology and the application of patient EHRs.

“Health information technology (HIT) offers considerable opportunities to advance the health system’s role in positively affecting the health of high-risk populations and achieving good population health,” Hatef explained. “Although health systems are encouraging the uptake of HIT among their practitioners and patients, to advance population health, the application of HIT solutions needs to include the capture, analysis, and dissemination of information on social needs within electronic health records (EHRs). Moreover, to truly have an impact, assessment of individual social needs is not enough. We must also consider place-based [social determinants of health] SDOH and characteristics of the environment where patients live and assess how such factors affect one’s ability to stay healthy and receive care when needed.”

Hatef argued that the study by Kanchi et al is a good example of how HIT can be used to go beyond the mere documentation of clinical diseases and medical interventions and offer a more complete assessment of an individual’s health in order to identify at-risk patients and populations.

“The use of real-time EHR data on a large population of patients, compared with the use of survey data with limited scope and claims data with the time lag, provides a source of high-volume data, the potential of which has not been fully exercised in health care systems,” she wrote. “The advanced HIT tools would enable the health systems to systematically identify social needs and challenges in EHR’s structured and unstructured data (free- text notes), which are arguably one of the major sources of data on social risk factors for a large percentage of the US population. The linkage of such data to 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.”

Study limitations include its observational nature; an inability to capture residual lifestyle confounders based on EHR data; the analysis may not be generalizable to the non-veteran population; an inability to determine how often participants made use of neighborhood stores; and an inability to identify members of the cohort who also received care outside of the VA and may have been diagnosed with diabetes.

1. A higher density of fast-food restaurants was linked to increased incidence of type 2 diabetes (T2D) among U.S. veterans in the surrounding community, but increased access to supermarkets was associated with lower T2D rates in suburban and rural areas.

2. Based on these findings, interventions targeting the placement or zoning of supermarkets may be more appropriate in suburban and rural communities.

John McKenna, Associate Editor, BreakingMED™

Cat ID: 12

Topic ID: 76,12,585,730,12,669,149,60,918