Search Terms Glossary

• Access - Open: Access - Open refers to the free, immediate, online availability of research outputs such as journal articles, databases or books, combined with the rights to use these outputs fully in the digital environment.

• Access - Purchase: Access - Purchase refers to research outputs such as journal articles, databases or books, whose access and/or use requires a license or similar authorization that must be purchased from the owner(s) or authorized vendors of said research outputs.

• Coverage - National: Coverage - National describes food environment data sources that contain units representative of a country or nation, rather than geographies of smaller/larger scale, or other jurisdictions. FEED indexes data sources with national coverage for both the US & Canada.

• Coverage - Subnational: Coverage - Subnational describes food environment data sources that contain units representative of geographies or other jurisdictions existing below the nation- or country- level such as regions, states, catchment areas, and point location. FEED indexes data sources with subnational coverage for both the US & Canada.

• Time - Pre 2000: Time - Pre 2000 describes the temporal coverage of a food environment data source for calendar years occurring prior to the year 2000.

• Time - 2000 to 2009: Time - 2000 to 2009 describes the temporal coverage of a food environment data source for the following calendar years: 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, and 2009.

• Time - 2010 to 2019: Time - 2010 to 2019 describes the temporal coverage of a food environment data source for the following calendar years: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, and 2019.

• Time - 2020 to Present: Time - 2020 to Present describes the temporal coverage of a food environment data source for calendar years ranging from 2020 to the present year.

• Recent Update - 1 Year: Recent Update - 1 Year describes data sources that have been reviewed by the FEED team and updated within the last 365 days.

Domains & Constructs Glossary

• • Availability: Quantity and diversity of food stores or other establishments that can be physically accessed by individuals, often defined within a geographic area. Can also be defined for specific types of food or beverage items in institutional settings such as offices and schools, based on offerings within on-site cafeterias or vending machines [1, 2, 3, 4].

  • Convenience: Qualities of retail and food options that minimize effort needed from consumers to purchase, prepare, and consume food. Includes establishment characteristics beyond availability, such as store hours, delivery services, and food product characteristics, such as shelf-life [2, 3].

  • Accessibility: Qualities and characteristics affecting how readily individuals can purchase and consume food items. Includes both convenience and whether the consumer has sufficient time or transportation mode options to overcome barriers to access. Importantly includes Affordability which depends on both food prices and individual purchasing power [1, 2, 3, 4].

    • • Eligibility and use restrictions for Nutrition Assistance Programs such as the Supplemental Nutrition Assistance Program (SNAP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) are food policy factors related to addressing food insecurity [5]. The acceptance of corresponding payment via Electronic Benefits Transfer (EBT) cards varies [5, 6].

      • Much research has focused on Food Deserts as a limiting factor to healthy food consumption, though area-based sociodemographic factors may be more crucial [7].

  • Acceptability: Agreement between available foods and population food preferences, factoring in taste, culture, customs, and knowledge [1, 3].

  • Food Quality: Perceived and quantifiable characteristics of food products that impact alignment with consumer needs and preferences. For a health-oriented consumer, quality may include density of desired nutrients relative to unhealthy components (e.g., additives, sugar, sodium, or trans fats). Quality can also include freshness and appearance [2], or conversely, the degree to which foods have been processed.

    • • The NOVA classification defines Ultra-Processed Foods as ingredient and meal formulations resulting from extensive industrial-scale processing, often containing artificial colors, flavors, emulsifiers, and other additives [8]. Implications of ultra-processed food intake continues to be examined with both a health and equity lens [9, 10], alongside associated nutrition characteristics and consumption patterns.

  • Food Retail Stores: Commercial locations with food products available, including food to be prepared or consumed off-premises. May include retail locations that are not primarily food retailers, but offer some food items for purchase (e.g., pharmacies, department stores) [3, 11]. Note that classification of food retail stores selling a wide range of items may rely on which items are most salient, as defined by typical consumer intentions, marketing, relative pricing, or shelf space [12]. The classification of a store as healthy or unhealthy has national and cultural context and requires a subjective lens rather than uniformity [13].

  • Food Establishment Classification: Systematic use of criteria to define Food Retail Stores of interest (e.g., supermarkets, convenience stores, fast food outlets). Commonly incorporates standard coding systems and may consider establishment characteristics such as floor space, number of employees, or annual sales [12]. Granular classification requires attention to potential overlap among large (warehouses vs supermarkets) or small (convenience stores vs bodegas) food stores, and among restaurants (national chain fast-food vs other casual, quick service). Adopting or adapting previously published classifications is recommended to increase comparability between studies [12], unless there is scientific justification for creating a new measure. However, when existing classification definitions prove insufficient, prior models can guide tool development and testing [14].

  • Standard Coding Systems: Numeric codes with corresponding labels for retail and other establishments to categorize establishment type, which may be included in establishment-level datasets used to measure the food environment. Comparison to ground-truthed data may aid understanding in how comprehensively such systems reflect food items available. Two common systems are:

    • • Standard Industrial Classification (SIC): Codes of 4 to 8 digits that group together similar establishment types: the first two numbers represent the major industry, the third digit represents subgroups within that industry, and subsequent digits give further specificity [15]. The U.S. government stopped updating codes in 1987, though original codes have since been expanded. Mainly used by the private sector for economics and marketing.

      • North American Industry Classification System (NAICS): A standard created by U.S. government agencies to replace the SIC system, providing more granular classification and used for governmental operations and classifications. NAICS uses a six-digit system; the first two digits represent major sector, third represents subsector, fourth represents industry group, fifth represents industry type, and sixth represents the national industry [15, 16].

  • Store Catchment Area: The geographic area primarily served by a given Food Retail Store. Can be defined in a variety of ways including distance, travel time, or transit accessibility, and will likely be larger in rural and low population density settings [17]. Defining catchment areas is useful for identifying demographics and preferences of customers that inform context-specific measurement of Food Quality, Accessibility, and Acceptability.

  • Neighborhood: A geographically and socially delineated context for individuals’ behavior and environment. These may be defined through distance-based or political boundaries around homes, workplaces, schools, or commuting routes [18, 19]. People spend time in multiple settings; no single geographic unit perfectly characterizes the physical, social, cultural, and policy environments experienced [20].

    • • Both Geographic Extent (entire area throughout which neighborhoods will be measured) and Scale of Measurement (geographic units used for characterization and comparison have implications for errors encountered and feasibility of ground-truthing or other efforts to improve validity. Smaller-scale measurement and projects with a smaller geographic extent may allow more stakeholder involvement, tailoring of existing neighborhood definitions and measures; a larger geographic extent makes such methods less feasible, though still worth considering for a subsample of geographic units.

  • Density-Based Measures: Measures characterizing intensity of food establishment presence within a boundary, potentially relevant to both Availability and Accessibility. Estimates of density commonly use count of establishments within a given category as the numerator, and a defined land area as a denominator. However, retail density measures may present a challenge for interpretation, especially across settings of different urbanicity or within high density settings [19, 21, 22].

  • Ratio-Based Measures: Measures characterizing relative intensity across food establishment categories within a boundary, which may point to their relative Convenience. Commonly relies on binary (e.g., healthy/unhealthy) categorization [23]; estimates commonly include healthy retail establishment (variously defined) counts in the numerator and unhealthy or total food retail in the denominator, leading to challenges in low-density settings where counts in the denominator may equal 0.

  • Longitudinal Measures: Measures which incorporate multiple moments or periods of time, providing a way to examine trends across years or decades. Longitudinal measures of both food environment and dietary or health outcomes allow for examination of temporal sequencing in studies of the food environment on health, an identified gap in the food environment literature [23]. Observed trends over time are more interpretable if based on consistent classification methods and temporally appropriate linked health data [24].

    • • Supermarket Transition or Greenlining: A longitudinal process bringing in Food Retail Stores to an area that emphasize gourmet, healthy, or natural ingredients over Affordability, which may be concurrent with gentrification, urbanization, or related sociodemographic transitions. Such changes may align with Food Quality preferences of only a segment of the population in the store catchment area, with rising food costs exacerbating inequities in food insecurity particularly if concurrent with a shrinking supply of affordable housing and amenities [25].

  • Sociodemographic Indicators: Characteristics of individuals and geographic units that may confound or mediate food environment effects. These are likely to impact where a person lives and how food is acquired, as well as impacting overall health for reasons unrelated to the food environment; commonly include personal and area-based education, income, and wealth, and may also incorporate household composition and area-level patterns by identity groups such as gender, race, and ethnicity, or may combine several area-based measures into a single index variable [19].

  • Food Habits: Food habits refer to the unique and changing behavioral patterns and choices surrounding food consumption developed by individuals or communities over time. These encompass not just what and how we eat but also the cultural and social aspects of food choices and food consumption.

  • Norms/Social Context: Norms and social context are the unspoken rules, shared values, and shared behaviors within a community regarding food. These norms play an important role in Acceptability and Food Quality by influencing the dietary behaviors and preferences that can either drive or impede population health.

  • Home Food Environment: The home food environment comprises the physical and social aspects of homes, where individuals or families prepare, store, and consume their meals. It includes factors such as the Availability of both healthy and less healthy foods, mealtime dynamics, and the influence of household members on each other's food choices.

  • Food Away From Home: Food away from home encompasses all food and beverage options consumed outside of the home, including restaurants, cafes, fast food establishments, and mobile food establishments. Food away from home represents a dynamic aspect of the food environment that affects both Availability and Accessibility and influences several aspects of food choices and food consumption.

References

1. Caspi CE, Sorensen G, Subramanian SV, Kawachi I. The local food environment and diet: a systematic review. Health Place. 2012;18(5):1172-87. DOI: 10.1016/j.healthplace.2012.05.006.

2. Nodari GR, Kennedy G, Herforth A, Downs S, Brouwer I. Background Note on Food Environment: Prepared for the CGIAR A4NH Consultative Food Environment Workshop, Nov 5-7, 2019. London, England (UK); 2020. p. 18. Available from: https://a4nh.cgiar.org/files/2020/03/FINAL-Background-note-on-Food-Environment_Revised.pdf.

3. Turner C, Aggarwal A, Walls H, Herforth A, Drewnowski A, Coates J, et al. Concepts and critical perspectives for food environment research: A global framework with implications for action in low- and middle-income countries. Glob Food Sec. 2018;18:93-101. DOI: 10.1016/j.gfs.2018.08.003.

4. Turner C, Kadiyala S, Aggarwal A, Coates J, Drewnowski A, Hawkes C, et al. Concepts and methods for food environment research in low and middle income countries. London, UK: Agriculture, Nutrition and Health Academy Food Environments Working Group (ANH-FEWG) Innovative Methods and Metrics for Agriculture and Nutrition Actions (IMMANA) Programme 2017.

5. Gustafson A, Lewis S, Perkins S, Wilson C, Buckner E, Vail A. Neighbourhood and consumer food environment is associated with dietary intake among Supplemental Nutrition Assistance Program (SNAP) participants in Fayette County, Kentucky. Public Health Nutr. 2013;16(7):1229-37. DOI: 10.1017/S1368980013000505.

6. Wood BS, Horner MW. Understanding Accessibility to Snap-Accepting Food Store Locations: Disentangling the Roles of Transportation and Socioeconomic Status. Appl Spat Anal Policy. 2015;9(3):309-27. DOI: 10.1007/s12061-015-9138-2.

7.  Turner C, Kadiyala S, Aggarwal A, Coates J, Drewnowski A, Hawkes C, et al. Concepts and methods for food environment research in low and middle income countries. London, England (UK); 2017. p. Available from: https://a4nh.cgiar.org/2017/05/04/anh-academy-launches-technical-brief-on-food-environments/.

8.  Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, et al. Ultra-processed foods: what they are and how to identify them. Public Health Nutr. 2019;22(5):936-41. DOI: 10.1017/S1368980018003762.

9. Gibney MJ, Forde CG, Mullally D, Gibney ER. Ultra-processed foods in human health: a critical appraisal. Am J Clin Nutr. 2017;106(3):717-24. DOI: 10.3945/ajcn.117.160440.

10.  Gibney MJ. Ultra-Processed Foods: Definitions and Policy Issues. Curr Dev Nutr. 2019;3(2):nzy077. DOI: 10.1093/cdn/nzy077.

11.  Lucan SC, Maroko AR, Seitchik JL, Yoon DH, Sperry LE, Schechter CB. Unexpected Neighborhood Sources of Food and Drink: Implications for Research and Community Health. Am J Prev Med. 2018;55(2):e29-e38. DOI: 10.1016/j.amepre.2018.04.011.

12.  Wilkins EL, Morris MA, Radley D, Griffiths C. Using Geographic Information Systems to measure retail food environments: Discussion of methodological considerations and a proposed reporting checklist (Geo-FERN). Health Place. 2017;44:110-7. DOI: 10.1016/j.healthplace.2017.01.008.

13. Vernez Moudon A, Drewnowski A, Duncan GE, Hurvitz PM, Saelens BE, Scharnhorst E. Characterizing the food environment: pitfalls and future directions. Public Health Nutr. 2013;16(7):1238-43. DOI: 10.1017/S1368980013000773.

14. Lake AA, Burgoine T, Greenhalgh F, Stamp E, Tyrrell R. The foodscape: classification and field validation of secondary data sources. Health Place. 2010;16(4):666-73. DOI: 10.1016/j.healthplace.2010.02.004.

15. Henneberry B. SIC Codes vs. NAICS Codes - What's the Difference? New York, NY (US): Thomas Publishing Company; 2021 [cited 2021 November 15]. Available from: https://www.thomasnet.com/articles/other/sic-codes-vs-naics-codes-what-s-the-difference/.

16. Economic Classification Policy Comittee. North American Industry Classification System. (US): Office of Management and Budget; 2022. p. 958. Available from: https://www.census.gov/naics/reference_files_tools/2022_NAICS_Manual.pdf.

17. Brown B. What is a Catchment Area? + Methods & Tools for Your Analysis (US): Safe Graph; 2021 [cited 2021 November 15]. Available from: https://www.safegraph.com/blog/catchment-area.

18. Burgoine T, Monsivais P. Characterising food environment exposure at home, at work, and along commuting journeys using data on adults in the UK. Int J Behav Nutr Phys Act. 2013;10(1):85. DOI: 10.1186/1479-5868-10-85.

19. Sacks G, Robinson E, Cameron AJ. Issues in Measuring the Healthiness of Food Environments and Interpreting Relationships with Diet, Obesity and Related Health Outcomes. Curr Obes Rep. 2019;8(2):98-111. DOI: 10.1007/s13679-019-00342-4.

20. Lytle LA. Measuring the food environment: state of the science. Am J Prev Med. 2009;36(4 Suppl):S134-44. DOI: 10.1016/j.amepre.2009.01.018.

21. Thornton LE, Pearce JR, Kavanagh AM. Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary. International Journal of Behavioral Nutrition and Physical Activity. 2011;8(1):71. DOI: 10.1186/1479-5868-8-71.

22. Rundle A, Neckerman KM, Freeman L, Lovasi GS, Purciel M, Quinn J, et al. Neighborhood food environment and walkability predict obesity in New York City. Environ Health Perspect. 2009;117(3):442-7. DOI: 10.1289/ehp.11590.

23. Thornton LE, Lamb KE, White SR. The use and misuse of ratio and proportion exposure measures in food environment research. Int J Behav Nutr Phys Act. 2020;17(1):118. DOI: 10.1186/s12966-020-01019-1.

24. Hirsch JA, Moore KA, Cahill J, Quinn J, Zhao Y, Bayer FJ, et al. Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology. J Urban Health.

25. Anguelovski I. Healthy Food Stores, Greenlining and Food Gentrification: Contesting New Forms of Privilege, Displacement and Locally Unwanted Land Uses in Racially Mixed Neighborhoods. Int J Urban Reg Res. 2015;39(6):1209-30. DOI: 10.1111/1468-2427.12299.