A higher density of food stores carrying less healthy options is associated with a higher prevalence of obesity, according to a report from the Urban Institute.
“We find that areas of higher obesity prevalence are more likely to have greater exposure to the types of food stores likely to offer less healthy options, even when controlling for differences across counties,” Elaine Waxman, MPP, PhD, senior fellow at the institute’s income and benefits policy center, and colleagues wrote in the study. “The association between obesity and unhealthy food establishments holds true in both rural and non-rural areas.”
Importance of the Food Environment
The researchers decided to perform the study because “with the rapid rise in obesity, a lot of attention focused on individual interventions — medications they can take, surgeries they can have, and ways to modify the diet,” Waxman told MedPage Today in a phone interview.
“Those are all important parts of the response, but they lose sight of the structural issues,” Waxman continued. “So we worked on this to call attention to issues such as, if your food environment is more typically the less healthy options, that constrains your ability to make better choices for yourself. It’s part of realizing that individual blaming is not productive for the people experiencing obesity, nor is it a productive frame for creating public policy.”
The authors looked at obesity 2017 and 2018 data in the Obesity Factor Track Surveillance System, a telephone survey that collects information about chronic conditions. “To report county-level information, we used the CDC’s PLACES 2021 release, an effort to release information uniformly on a large scale for local areas,” they noted.
The information on food stores is 2019 data from Data Axle, a national database of about 25 million businesses. The authors looked at variation in the number of establishments per 1,000 residents at the county level and distinguished between different types of food businesses, including grocery stores, other grocery (including specialty food) stores, convenience stores, warehouse clubs, dollar stores, other departments stores (including Walmart, Target, and others selling food), pharmacies, and gas stations. They excluded stores that didn’t sell food.
“We do not include farmer’s markets in our analysis, although they can be important supplemental sources of healthy food offerings in local communities,” they noted. “Because the majority of food purchases in the US are made in store settings, we have prioritized our analysis of these establishments.”
They also didn’t focus much on restaurants. “What we decided to do was focus on this brief on how people can buy food to prepare it at home,” Waxman said. “That’s one thing people will hear from their healthcare providers: ‘What can you prepare at home?'” However, the report does include a map showing what the relationship between obesity and food establishment density looks like when restaurants are added to the mix of food establishments, she noted.
Lower Food Business Density in Urban Areas
Obesity, though widespread in the US, varies greatly by place, the investigators said. “The highest obesity rates in the US are concentrated in Southern counties, particularly those in parts of Texas, Louisiana, Mississippi, Kentucky, and West Virginia. In contrast, the lowest obesity rates are concentrated in Western counties, especially those in Colorado and parts of of Wyoming, California, and Nevada.”
The investigators found that the highest rate of food establishments per 1,000 residents were in the nation’s more rural midsection, from North Dakota through Texas and in parts of Maine, Idaho, and Oregon. Those places with the fewest food establishments per 1,000 residents, by contrast, were mostly in more population-dense areas. For example, a median rural county would have 9 retail food businesses for a population of 5,732, or about 1.57 retail food businesses per 1,000 residents. On the other hand, a median non-rural county would have 42 retail food establishments for a population of 36,971, or roughly 1.14 food establishments per 1,000 residents.
Combining data on food businesses with obesity data, the researchers found that “on average, counties with high obesity rates have more food establishments per 1,000 residents (1.40), while counties with middle obesity rates have 1.29, and those with low obesity rates have fewer obesity rates establishments for their size of population (1.11). These differences are statistically significant in our regression analysis even after controlling for other county-level characteristics.”
The counties with high obesity rates generally also have a bigger variety of stores, they found. “The difference in the number of dollar stores between high- and low-obesity areas is particularly large — with high-obesity areas averaging 0.24 dollar stores per 1,000 residents and low-obesity areas averaging only 0.09 dollar stores per 1,000 residents.”
Waxman said she was surprised at “the extent of the difference in what we call healthy versus unhealthy types of food outlets and high and low obesity rates. We’re not trying to say anything causal about that, because that’s a long and complicated discussion, but what we want to say is, ‘Hey, if we want to look at the highest-obesity areas, what we’re noticing is that they’re more likely to have unhealthy food establishments'” — loosely defined as places that sell mostly packaged and highly processed foods.
Dollar Stores: Challenges and Opportunities
Dollar stores represent both a challenge and an opportunity, the authors wrote. “Although dollar stores are less likely to offer healthier food items like fruits and vegetables, a recent study found that, when available, these items were often priced lower than at surrounding grocery stores. The researchers suggested that dollar stores could be considered potential community assets for building affordable access to healthier foods.
One chain, Dollar General, has promoted a strategy for increasing healthier food options in its stores, although the plan does not reach a majority of its outlets in the near term, they pointed out. “Dollar stores may be among the few business entities willing to locate in areas with limited demand, so it is important to consider what role they can play in increasing affordable, healthy food access in the future.”
Clinicians can use the study as a reminder of the varied contributors to their patients’ diets, Waxman said. “Healthcare professionals are often in the position of advising patients to eat better, and often there’s not enough recognition in the healthcare sector of what the barriers are — that might be affordability and also just what’s in your environment. It’s not enough to think of it as an individual health issue — it is also a population[-wide] issues.”
In that regard, “there are definitely communities where healthcare systems have begun to step up in areas of affordable housing, recognizing that’s an important source of stability, and to get people on SNAP [Supplemental Nutrition Assistance Program, formerly known as food stamps],” she said. “And if you’re in a rural hospital or serving a community of color where [food] options are limited, you can be in the conversation about what the community response is.”
Policymakers can also come to this issue in several ways, Waxman said. For example, the US Department of Agriculture operates the Gus Schumacher Nutrition Incentive Program (GusNIP), a competitive grant program that pays states and localities to increase the value of SNAP benefits when used to purchase fruits and vegetables. Although many GusNIP programs are already in areas with high rates of obesity, other such areas don’t have the program yet, he said.
Healthy food financing investments to bring in stores selling healthy food is another option, and local lawmakers can also consider adopting zoning laws that favor healthy food establishments over unhealthy ones, as some places have done.