The Correlation Between Socioeconomic Status and Fast Food Restaurant Density Food

Written by:   Lexi Sheldon, Zane Jensen, KyChe Sanders, WenYan Wang, and Sam Distefano


There is currently an obesity crisis in the United States. Outrageously, 35.7% of adults qualify as being obese. While many factors play into this, there could be one in particular not commonly thought about. Obesity rates could potentially be linked the amount of income per household. In any area, the income level of its inhabitants vary considerably. This variation can cause each person’s dietary intake to be completely different from one another. In today’s society, nutritious food options are usually much more expensive while their unhealthy counterparts are cheap and easily manufactured. The creation of fast food restaurants has made poor food choices more accessible. For most living in the city, a few minutes is all one would have to travel to find a fast food establishment. Understandably, these places have become part of a daily diet for many people living throughout the United States. Could one’s intake of fast food be linked to the amount of income one has? For those that have lower incomes, fast food may be their only affordable option. If this is indeed true for a majority of families, it is not a coincidence if fast food locations inhabit these areas more so than others. These companies could be taking advantage of the people in those regions and causing their obesity levels to spike at the same time.

In many parts of the U.S., such as Philadelphia, Alabama, and Washington, fast food restaurants have a monopoly over the areas of poor income. In Philadelphia, a study was done using photos to assess poverty levels of neighborhoods as well as surveys of the residents of these areas. The results showed that the residents were concerned about the amount of supermarkets and the inaccessible transportation to these facilities. This causes them to choose takeout food places and convenience stores. These options are very unhealthy and seem to be more focused in lower income neighborhoods. The people surveyed also revealed that they feel as though they can not change the area they live in and are powerless against the unhealthy food choices and establishments (Cannuscio). In Alabama, 50% of the child population is overweight in some areas. The national average is about 30.6% of children are overweight. A study was conducted here because it is one of the poorest places in the U.S. The goal was to determine if there are higher amounts of fast food places in those areas and if that affects poor nutrient consumption. The median household income in this area is about $21,180 which is a lot lower than the average income of the U.S. which is $53,146. Data was collected on 613 children from ages 4-13. The results showed that children who live in healthier food environments are less likely to become overweight. They also found that the poorest areas are densely populated with fast food places and there usually aren’t healthy options or supermarkets for blocks (Li). In Washington, the same things were found in all of their studies. Fast food restaurants were concentrated in lower income areas in King County, WA (Hurvitz). After reading articles over these studies, it was evident that there is a common trend in the United States.

Overall, there are similarities throughout the U.S. that correspond with theory that income can be related to the fast food restaurant density in an area. Higher income areas tend to have more supermarkets and less fast food while the lower income neighborhoods have just about the opposite. If this is true for other places, is it valid in the city in which one resides? This question peaked interest and caused a separate investigation.


The group of sociologists decided to see if there was a local correlation between income and restaurant density. Omaha, NE is very economically diverse, with areas of high income as well as low income. As a large city, Omaha also has many fast food restaurants. The basis of the project was to ascertain if the majority of fast food locations reside in the lower income areas of the city. This would help to support the theory that lower income families consume more unhealthy options, leading to more obesity within that socioeconomic class. It was determined that there were six large themes that would cover the basis of the research. These included income, obesity, population, racial distribution, poverty level, and restaurant distribution. Income and poverty level, some of the most important themes, were useful in helping the group to understand the variations of median incomes throughout Omaha as well as the levels of poverty. Obesity statistics were needed to recognize the state the population is in when concerning those who are overweight. Racial data was necessary to get a feel for the area and it’s minorities and majorities. To fathom the amount of people the research was concerning and to determine how the wealth is distributed among the area, population numbers throughout the city were obtained. Restaurant numbers were obviously needed to distinguish if they had direct correlation to income. Within these six categories, research from five different areas of the city was organized in order to recognize correlations. These areas included North, South, West, Downtown, and Midtown Omaha. For part of the research, the American Factfinder website was used. This housed current statistics on many of the themes including income, population, racial distribution, and poverty level. In order to find restaurant density in each area, Google Maps was used to locate each location. Additionally, the Douglas County Health Department site and the Centers for Disease Control site had great information on current obesity statistics in the Omaha area. Ample research was collected from each source which allowed the project to commence.

There was a distinct process in which the research was obtained to ensure organization and accuracy. First, scholarly research was found that would back up the claim. Using the Academic Search Complete database, twenty primary sources were found regarding a link between obesity, income, and fast food restaurants. These articles provided background information so an understanding could be possible on the topic. Afterward, secondary data was obtained for a certain part of town by a different member of the group. Information was collected from the secondary sources which were Google Maps, American Factfinder, and the Douglas County Health Department. The material was then looked at and several themes were determined that were reoccuring throughout. The established themes were obesity, income, population, racial distribution, poverty level, and restaurant density. A shared folder was created for each theme with a certain color accompanying it. The information was then color coded by which of the themes it contained and separated out into the folders. This was an effective way of coding which allowed the material to be useful and convenient. The data could then be analyzed to draw meaningful conclusions from it.


Median income levels of each region of Omaha were recorded from the American FactFinder website. Throughout Omaha, the income levels are similar in most areas. They range from about $25,000 to $37,000. There is one area in particular that has a significantly higher median income than the rest. West Omaha has a median income of $108,000. Predictions on which areas had the most wealth were proven otherwise when most of the areas were determined to have the same median income. Income levels have a role in this project because it is referenced when distinguishing between the poorest and richest areas of Omaha. The poorest area, North Omaha with an income level of $25,531. West Omaha, with a median income of $108,378.

Population around the city varies drastically when comparing one area of the city to another. The majority of people live in South Omaha where the population is around 29,000. The fewest number of people live in Downtown Omaha with population totaling 6,102 people. The rest of the areas, North, West, and Midtown, had population numbers that ranged from 7,817 to 12,302 total. The Omaha population seems to not centralize and cluster in one place excessively.Population numbers are pretty evenly distributed between most regions aside from South Omaha.

The poverty levels throughout Omaha were similar to what most would expect who knew the city well. North Omaha had the highest poverty level which was about 42.8% of the people living in that area. Not surprisingly, West Omaha only had a poverty percentage of 19.2% which was the lowest out of the five regions. South Omaha had the next lowest level at 24.5%. Downtown and Midtown both had about a 30% poverty level. These statistics show that there are definite places where the wealth is concentrated, West Omaha, and where it is not, North Omaha. Aside from this however, the wealth seems to distribute itself pretty evenly throughout the rest of the city.

There were similarities when it came to the races in each area. Midtown is 59% White, 20% Black, 14% Hispanic, and 7% Asian. Similarly, Downtown Omaha is 68% White, 18% Black, 10% Hispanic, and 4% Asian. South Omaha is 68% White, 8% Black, 23% Hispanic, and 1% Asian. There were two regions who had opposite minority and majority groups. West Omaha is 93% White, 1% Black, 2% Hispanic, and 4% Asian while North Omaha is 36% White, 55% Black, .3% Asian, and 8.7% Hispanic.

Surprisingly, the restaurants throughout Omaha seem to be evenly dispersed. South Omaha had the largest amount of fast food restaurants, nineteen total, concentrated in that area. Downtown and Midtown had fifteen total restaurants each which was the lowest amount. North Omaha had sixteen restaurants while West Omaha had eighteen.

Astonishing facts were found about the obesity rate as a city. As an overall city, 61% of adults are overweight or obese as well as 28.4% of children that are obese. Out of all the youth throughout Omaha 96.6% of them do not meet the guidelines put out by the federal government for fruit and vegetable consumption. 60% of the children also don’t participate in as much physical activity as is recommended for their age group. These statistics show that obesity is quite a problem in Omaha, NE and it will only continue to get worse. All the children who are obese and don’t follow guidelines will probably never overcome obesity and could pass their bad habits on to their own families when they get old enough. Nationally, 48.1% of African Americans are obese. Hispanics have the next highest percentage, coming to 42.5%. Whites are 34.5% and Asians are 11.7% obese.


The unpredictable results forced rethinking of the previous expectations and new conclusions to be formed. The amount of restaurants in an area was previously thought to have a correlation with the income levels of the area. After research was done, this proved to be false and there was no distinction between the two. The poorest area, North Omaha with an income level of $25,531, had a median amount of fast food restaurants totaling at sixteen restaurants. West Omaha, with a median income of $108,378, had eighteen restaurants which was one of the highest throughout the data. Even other parts of Omaha had similar amounts of fast food restaurants. These establishments seem to be very evenly distributed throughout the city. They are not concentrated in low income areas as opposed to higher income regions. This would mean that Omaha’s fast food restaurant density does not contribute to the city’s high levels of obesity.

Unfortunately, this also did not match the scholarly research articles collected at the beginning of the project. Multiple articles, based in the United States, showed that fast food restaurants seemed to be more concentrated in lower income areas and higher income areas had more grocery stores and higher quality food establishments. A study done in numerous places in the U.S. as well as a few places internationally had results similar to what we expected from our project. This article was published in the American Journal of Public Health and tested the same theory that we had proposed. They looked at many areas of the U.S., including New York, Hawaii, Missouri, Texas, and North Carolina. Each one of these areas had correlations between income and fast food restaurants. Lower income areas had few supermarkets and large amounts of fast food establishments. These contrasting factors were also seen internationally in the UK, Canada, New Zealand, Quebec and many other countries. This result, or something similar, was shown in almost all of the primary source articles. It seems as though it is of the majority to have the same characteristics with unhealthy food enterprises. For this reason, it was puzzling to find that Omaha, NE had opposite outcomes than what was expected.

Another conclusion that could be drawn from our research was that African Americans tend to have a lower income in Omaha, NE. North Omaha, with the lowest median income of $25,531, had the largest percentage of African Americans. Blacks were actually the majority compared to other races. The area of Omaha with the largest income, West Omaha, had a majority of Whites residing in that area. 93% of West Omaha is White while only 1% of it is Black. These two areas are opposite in income and race. This helps support the fact that in Omaha, the majority of high income families are White. This is obviously not everyone, but even other races including Hispanics and Asians have very low percentages in West Omaha. Additionally, obesity statistics show that African Americans have the highest percentage among those obese in this country. This race has the lowest income in Omaha, as well as the largest amounts of obesity. This is also noticed in other parts of the United States. This is what initially caused interest in finding a connection between income and restaurant levels because this trend is commonly seen.

Even though the results were unexpected, this means that there is not an issue with where fast food restaurants are located. While they are unhealthy options for food, their location means that Omaha’s citizens are traveling to acquire the food they want. It may not be easiest to consume fast food, but people are still making the decision to eat it and increase their weight. In further studies, it may be beneficial to look at the amount of supermarkets, grocery stores, and nicer restaurants in the areas of Omaha as well. This could give insight on if traveling for food is still necessary. Unfortunately, this is a harder problem to solve. Moving the locations of restaurants is easier to do than force people to choose healthy options when it comes to food and lifestyles. Omaha’s obesity rate will likely increase because people are making the conscious decision to eat fast food. Efforts must be made to change citizen’s minds, and make them think twice when eating poor options. If other places show the same results that Omaha did, obesity may need to have a more complex solution than just eliminating the location of some restaurants. Conquering obesity will be a massive accomplishment considering the many factors that go into it.


Overall, the results did not match the previous speculations when concerning the correlations between income and fast food restaurant density. Not every place in the United States, or even internationally, has the same characteristics or correlations. So although surprising, it was not impossible for Omaha to show distinctive outcomes. As a result, this makes Omaha unique in comparison to most places. This uniqueness also makes a solution more challenging and complicated. No matter the results, the obvious still stands. Obesity is a detriment to society and it is up to the population to make change in this world. When so much of the population is overweight or obese, bigger actions should be taken to lower this percentage. Around 300,000 people die each year from the obesity epidemic. That is a considerable amount considering it is not impossible to reverse the effects of weight gain. While it may not be simple, there is not just one solution to this problem. There are numerous things each person can do to stay on top of their weight and not contribute to the obesity percentage in the United States. No one is alone in this, and help is there for those who need it. Society can overcome this epidemic if everyone works together in order to ensure our society is a better place for everyone.

Works Cited:

Cannuscio, Carolyn C., Eve E. Weiss, and David A. Asch. “The Contribution Of Urban Foodways To Health Disparities.” Journal Of Urban Health 87.3 (2010): 381-393. Academic Search Complete. Web. 10 Oct. 2016.

Centers for Disease Control and Prevention. Centers for Disease Control and Prevention, 2016.

Data Access and Dissemination Systems (DADS). “American FactFinder.” U.S. Census Bureau.

“Google Maps.” Google Maps.

Hilmers, Angela, David C. Hilmers, and Jayna Dave. “Neighborhood Disparities in Access to Healthy Foods and Their Effects on Environmental Justice.” American Journal of Public Health 102.9 (2012): 1644-654. Web.

Hurvitz, Philip M., Anne V. Moudon, Colin D. Rehm, Laura C. Streichert, and Adam Drewnowski. “Arterial Roads and Area Socioeconomic Status Are Predictors of Fast Food Restaurant Density in King County, WA.” Int J Behav Nutr Phys Act International Journal of Behavioral Nutrition and Physical Activity 6.1 (2009): 46. Web.

Kerr, J., Frank, L., Sallis, J. F., Saelens, B., Glanz, K., & Chapman, J. (2012). Predictors of trips to food destinations. International Journal Of Behavioral Nutrition & Physical Activity, 958-67. doi:10.1186/1479-5868-9-58

Li, Y., et al. “Childhood Obesity And Community Food Environments In Alabama’s Black Belt Region.” Child: Care, Health & Development 41.5 (2015): 668-676. Academic Search Complete. Web. 9 Oct. 2016.

Mellor, Jennifer M., Carrie B. Dolan, and Ronald B. Rapoport. “Child Body Mass Index, Obesity, And Proximity To Fast Food Restaurants.” International Journal Of Pediatric Obesity 6.1 (2011): 60-68. Academic Search Complete. Web. 4 Dec. 2016.

Oyewole, P. (2007). Fast Food Marketing and the African American Consumers: The Impact of Socio-Economic and Demographic Characteristics. Journal Of International Consumer Marketing, 19(4), 75-108. doi:10.1300/J046v19n0405

Reitzel, Lorraine R., et al. “Density And Proximity Of Fast Food Restaurants And Body Mass Index Among African Americans.” American Journal Of Public Health 104.1 (2014): 110-116. Academic Search Complete. Web. 4 Dec. 2016.

Svastisalee, Chalida M., Bjørn E. Holstein, and Pernille Due. “Fruit And Vegetable Intake In Adolescents: Association With Socioeconomic Status And Exposure To Supermarkets And Fast Food Outlets.” Journal Of Nutrition & Metabolism (2012): 1-9. Academic Search Complete. Web. 7 Oct. 2016.

Thornton, Lukar E, Robert W Jeffery, and David A Crawford. “Barriers To Avoiding Fast-Food Consumption In An Environment Supportive Of Unhealthy Eating.” Public Health Nutrition 16.12 (2013): 2105-2113. Academic Search Complete. Web. 4 Dec. 2016.

“Welcome to the Douglas County Health Department.” Home – Douglas County Health Department.