Protocol - Food Swamp
Description
Specific Instructions
If current address (see PhenX Demographics domain, Current Address measure) has been collected for a study respondent, then it is possible to use geocoding to link the address of a study participant to his or her local neighborhood (a geographic area), typically by a census-defined unit, such as a census block group or a census tract or by ZIP Code.
Availability
Protocol
Traditional Retail Food Environment Index
Accessing Food Store Data at the County Level
All county-level food-store data is sourced from the Food Environment Atlas found at https://www.ers.usda.gov/data-products/food-environment-atlas/data-access-and-documentation-downloads/. An excel file can be downloaded to further extract data at a county level.
According to the U.S. Census Bureau, County Business Patterns, the following food environment variables are defined as:
Grocery Stores - The number of supermarkets and grocery stores in the county. Grocery stores include establishments generally known as supermarkets and smaller grocery stores primarily engaged in retailing a general line of food, such as canned and frozen foods; fresh fruits and vegetables; and fresh and prepared meats, fish, and poultry.
Fast Food Restaurants - The number of limited-service restaurants in the county. Limited-service restaurants include establishments primarily engaged in providing food services where patrons generally order or select items and pay before eating. Food and drink may be consumed on premises, taken out, or delivered to the customer’s location.
Convenience Stores/Food Marts - The number of convenience stores in the county. Establishments known as convenience stores or food marts are primarily engaged in retailing a limited line of goods that include soda, snack foods, etc.
Calculating the Traditional Retail Food Environment Index
After downloading the data for a given county, the traditional Retail Food Environment Index may then be calculated as follows:
Traditional Retail Food Environment Index (RFEI) =
(Fast Food / Limited Service Establishments + Convenience Stores) / (Grocery Stores / Super Markets)
Additional information may be found in the related publication at: https://dx.doi.org/10.3390%2Fijerph14111366
The RFEI can be categorized as following:
800 m buffer:
below 3.0
3.0 – 4.9
5.0 and above
1600 m buffer
below 6.0
6.0 – 9.9
10.0 and above
The number indicates the times greater of unhealthy food access (i.e. a RFEI of 3 indicates there are 3 times more unhealthy food retailers vs healthy food retailers in a given radius). A higher RFEI has been correlated with a higher obesity rate compared to a lower RFEI.
Personnel and Training Required
Knowledge of census data products and websites, such as the U.S. Census Bureau website (https://www.census.gov/programs-surveys/cbp.html) and the ability to use U.S. Department of Agriculture products and websites, such as the Food Environment Atlas (https://www.ers.usda.gov/data-products/food-environment-atlas/go-to-the-atlas)
The extracted data will need to be manipulated, and the traditional RFEI needs to be calculated.
Equipment Needs
Access to a desktop or laptop computer with Internet access to download data from the Food Environment Atlas (https://www.ers.usda.gov/data-products/food-environment-atlas/go-to-the-atlas). Optional statistical analysis can be executed using Stata/SE software.
Requirements
Requirement Category | Required |
---|---|
Major equipment | No |
Specialized training | No |
Specialized requirements for biospecimen collection | No |
Average time of greater than 15 minutes in an unaffected individual | No |
Mode of Administration
Secondary Data Analysis
Lifestage
Infant, Toddler, Child, Adolescent, Adult, Senior, Pregnancy
Participants
Not applicable; derived from publicly available secondary data
Selection Rationale
The traditional Retail Food Environment Index is an objective measure of food swamps that is easy to calculate and has been shown to be correlated with county-level obesity rates.
Language
English
Standards
Standard | Name | ID | Source |
---|
Derived Variables
None
Process and Review
Not applicable
Protocol Name from Source
Traditional Retail Food Environment Index (RFEI)
Source
Cooksey-Stowers, K., Schwartz, M. B., & Brownell, K. D. (2017). Food swamps predict obesity rates better than food deserts in the United States. International Journal of Environmental Research and Public Health, 14(11), 1366.
General References
California Center for Public Health Advocacy, PolicyLink, & the UCLA Center for Health Policy Research. (2008, April). Designed for disease: The link between local food environments and obesity and diabetes. Retrieved from https://escholarship.org/uc/item/9zc7p54b
Cooksey-Stowers, K., Schwartz, M. B., & Brownell, K. D. (2017). Food swamps predict obesity rates better than food deserts in the United States. International Journal of Environmental Research and Public Health, 14(11), 1366.
Economic Research Service (ERS), U.S. Department of Agriculture (USDA). (2019). Data access and documentation downloads. Retrieved from
Economic Research Service (ERS), U.S. Department of Agriculture (USDA). (2019). Food Environment Atlas. Retrieved from https://www.ers.usda.gov/data-products/food-environment-atlas/go-to-the-atlas/
McGuirt, J. T., Jilcott Pitts, S. B., & Gustafson, A. (2018). Association between spatial access to food outlets, frequency of grocery shopping, and objectively-assessed and self-reported fruit and vegetable consumption. Nutrients, 10(12), 1974.
Murphy, M., Badland, H., Jordan, H., Koohsari, M. J., & Giles-Corti, B. (2018). Local food environments, suburban development, and BMI: A mixed methods study. International Journal of Environmental Research and Public Health, 15(7), 1392.
Lucan, S. C., Maroko, A. R., Seitchik, J. L., Yoon, D. H., Sperry, L. E. & Schechter, C. B. (2018). Unexpected neighborhood sources of food and drink: Implications for research and community health. American Journal of Preventive Medicine, 55(2), e29–e38.
Spence, J. C., Cutumisu, N., Edwards, J., Raine, K. D., & Smoyer-Tomic, K. (2009). Relation between local food environments and obesity among adults. BMC Public Health, 9, 192. doi: 10.1186/1471-2458-9-192
Protocol ID
290501
Variables
Export VariablesVariable Name | Variable ID | Variable Description | dbGaP Mapping | |
---|---|---|---|---|
PX290501_Food_Swamp_Environment_Convenient_Store | ||||
PX290501030000 | The number of convenience stores in the more | N/A | ||
PX290501_Food_Swamp_Environment_Fast_Food_Restaurants | ||||
PX290501020000 | The number of limited-service restaurants in more | N/A | ||
PX290501_Food_Swamp_Environment_Grocery_Store | ||||
PX290501010000 | The number of supermarkets and grocery more | N/A |
Measure Name
Food Swamp
Release Date
May 11, 2020
Definition
“Food swamp” describes areas with a high density of establishments selling high-calorie fast food and junk food relative to healthier food options.
Purpose
Food swamps have a statistically significant effect on increased adult obesity.
Keywords
Retail Food Environment Index, RFEI, Social Determinants of Health, fast food restaurants, grocery stores
Measure Protocols
Protocol ID | Protocol Name |
---|---|
290501 | Food Swamp |
Publications
Bartholomew, T. S., et al. (2024) Project CHARIOT: study protocol for a hybrid type 1 effectiveness-implementation study of comprehensive tele-harm reduction for engagement of people who inject drugs in HIV prevention services Addiction Science & Clinical Practice. 2024 March; 19(1). doi: 10.1186/s13722-024-00447-9
Davidson, J., et al. (2022) From Genes to Geography, from Cells to Community, from Biomolecules to Behaviors: The Importance of Social Determinants of Health. Biomolecules. 2022 December; 12(10): 7. doi: 10.3390/biom12101449