Inconsistencies in how studies measure food access can mean food-deprived communities are underrepresented in research, a geography professor and researcher said Thursday at a Colloquium Series lecture hosted by ASU’s School of Criminology and Criminal Justice.
Daoqin Tong, associate professor in the University of Arizona School of Geography and Development, said she became intrigued when she began to look into the health issue of food insecurity — more specifically, food deserts.
Food deserts are defined as geographically isolated locations where access to healthy and affordable foods is limited or nonexistent. Food insecurity is when members of a household are not able to get sufficient food for an active and healthy lifestyle.
Tong reviewed former studies done on this subject by research facilities such as the U.S. Department of Agriculture and found the findings were different in each study.
“When we analyze spatial problems, a lot of times, our results depend on the spatial scales we’re using,” Tong said. “You might expect some discrepancies when your analysis is conducted on alternative scales.”
She said some studies would show high-population, low-income and high-minority areas have fewer supermarkets and less access to food. Others would conclude there is no correlation between those neighborhoods and their access to food.
From those observations, Tong said she was left with several research questions that she could focus on in her own study. One question, she said, was how scale impacts the way food access is assessed.
Tong conducted her study in Tucson in Pima County. She said she gathered information on population, income and supermarkets from the Pima County geographic information system.
To examine the data inconsistencies, Tong observed the number of food deserts using two different spatial measurements: census tracts and block groups.
Census tracts are relatively permanent statistical subdivisions of a county according to the U.S Census. Block groups are statistical divisions of census tracts that are generally defined to contain between 600 and 3,000 people.
Tong said she found that the percentage difference between census tract and block group was not significant, ranging from about .5 percent to 1.5 percent. The difference came when she looked at the map version of the experiment.
The map showed the exact areas that were considered a food desert and which were not.
“When I compare the block group and the tract, although the percent is similar, you have to look at the spatial distribution.” Tong said. “Visually, you see the differences.”
Tong explained that due to the census tract being a measurement of much larger scale, the analysis will be different than the block group analysis, which is smaller and more specific.
The block group showed the same land as the census tract, but while the tract would show no food desert, the block group map would. This is because the block group breaks the census tract into two smaller areas, giving a more accurate representation of the area’s food access to population.
Once the study was done, Tong could conclude that spatial measurement does have an impact on food access assessment.
“For the general population, the tract level analysis underestimates the good food access.” Tong said.
These findings have garnered attention for Tong as researchers are becoming aware of the measurement difference that can affect results of studies and how these results are affecting people nationwide.
Alyssa Chamberlain, an associate professor at the school of criminology, said these types of presentations help educate researchers on how to provide the best results.
“I come because I do a lot of research at a macro scale, so understanding how these different units of analysis can bias results is important because you want to put out your research findings and you want them to be legitimate,” Chamberlain said.
Tony Grubesic, director for Center for Spatial Reasoning and Policy Analytics, said examining inconsistencies is essential to passing policies that are helping communities because if the data is wrong the assistance could be going to the wrong people or place.
“Clearly, it’s an important policy issue,” Grubesic said. “Think about all the people that are impacted by this, especially those without the means to really help themselves.”
Grubesic and Tong said although this talk was about food shortage, many other problems, such as healthcare access, could be facing the same inconsistencies. Grubesic said studies like this will start the change to correct them.
“If you can quantify this stuff, then you can start to make positive change for the policies. If you can actually understand that these areas exist, and you can put a number on it that catches lawmakers’ attention, that catches communities’ attention,” he said. “Daoqin has even evidence here that says we can fix the way we’re analyzing stuff and make better policies for everyone.”
Contact the reporter at kaylee.stock@asu.edu.
