Sustainable Communities Index

Indicator PR.6.a Food Market Score

Why Is This An Indicator Of Health and Sustainability?

Local food environments influence the options households and individuals have. Access to healthy food choices is directly correlated to obesity and diabetes rates, which occur in higher rates among people living in low-income communities with worse food environments.^a

Supermarkets may provide access to a greater variety of cheaper and healthier foods, including fresh fruits and vegetables. This access helps to facilitate healthier dietary choices. Research has found that the presence of a supermarket in a neighborhood predicts higher fruit and vegetable consumption and a reduced prevalence of overweight and obesity.^b,c  As a result, problems of under- and over-nutrition are often attributed to lack of access to supermarkets.^d,e  Low-income, minority communities typically have fewer supermarkets and grocery stores than higher SES neighborhoods with primarily White residents, and they therefore disproportionately suffer from problems of over- and under-nutrition.^f,g,h

Farmers' markets provide another source of community access to fresh, locally produced fruits, vegetables and other food products. This in turn may support recommended daily consumption of fruits and vegetables. Markets may be particularly important in areas poorly served by full service supermarkets.

Methods

Food Retail Locations

Food retail data can be obtained from business listing providers like Dun and Bradstreet and InfoUSA. For San Francisco, data was downloaded the California Department of Public Health's Network for a Healthy California - GIS Map Viewer for the following categories: General Grocery; Convenience Group; Meat Markets; Fruit and Vegetable Markets; Warehouse/Club Stores. This data had previously undergone cleaning by the State to create the previously listed simplified fields. Farmers’ markets can be obtained by the local licensing body. The following NAICS codes can be used to create these categories:

General Grocery = 445110; Convenience Group = 445120; Meat Markets = 445210; Fruit and Vegetable Markets = 445230 & 445230; Warehouse/Club Stores = 452990; Drug Stores = 446110 (if these commonly carry a range of grocery items). It can also be useful to examine stores that fall into the category of “Specialty Food Stores” (NAICS 445299) because natural food stores that carry a variety of grocery items may fall into this category.

A general review of the selected establishments should be done because there are known classification validity issues with business data. Manual validation of all retailers in the "General Grocery" category can be conducted because this is deemed to be an essential subset of food retailers where accuracy would be most important. General Grocery retailers can be manually validated by entering the address of the establishment into Google Maps and using Streetview to view the storefront. If there appears to be no storefront (i.e. a residential property or warehouse), an internet search using the establishment's name and address can be performed to see if the food retail establishment exists. If the establishment appears to not exist or is a food shipping warehouse it can be excluded from the dataset. Other establishments that did not appear to have a primary purpose of selling food from both the appearance of the storefront and internet search results can also removed from the data set.

For the remaining establishments, an internet search can be conducted using Google and Yelp.com to validate that establishments should indeed be considered grocery stores. In San Francisco, most establishments could be found on Yelp. The key words "produce," "vegetable," "fruit," "meat," "fish," "grocery store," and "supermarket" can be used when searching Yelp establishment reviews. Yelp user photos of the inside of the store, if there are any, can be viewed. If reviewers generally refer to the store as a grocery store or supermarket, or if reviewers mentioned purchasing produce, fruits and vegetables, or fresh meat or fish, the store should remain in the grocery category. If most users refer to the store as a "liquor store," "convenience store," or "corner store" and the primary items reviewers mention purchasing are alcohol, tobacco, beverages, and snacks, and the storefront contains numerous advertisements for alcohol and tobacco, then the store can be recategorized as "Convenience Group." If there are no Yelp reviews for the establishment, but the storefront is covered in advertising for alcohol and tobacco, then the store can also be reclassified to "Convenience Group." In San Francisco, this resulted in 215 stores being recoded from "General Grocery" to "Convenience Group." Based on store fronts and reviews, 3 stores were recoded as "Fast Food, Pizza, Sandwiches," 2 as "Fruit/Vegetable Market," 3 as "Restaurant," 3 as "Meat/Fish/Poultry," 20 as "Single Category/Other," including deli, bakery, beverage, and specialty food shops.

After examining the cleaned results for “General Grocery,” known missing stores can be added to the dataset. In San Francisco, 11 supermarkets that were not present in the data, but were either listed on our previous supermarket list (and were confirmed to still be in business) or were known to have recently have opened (e.g. Fresh and Easy) were manually added. Stores in the general grocery category should be further classified into supermarkets and other grocery. All well know chain supermarkets including are classified as supermarkets. Other stores in the general grocery category, which ave 5,000 sqft. or more, make $1 million or more in annual sales, are part of a local chain, or have 6-20 employees and gross between $500k-1 million in sales can also be added. Square footage requirements can be adjusted as appropriate for the local retail landscape (in dense cities supermarkets may utilize much smaller floor spaces). Other stores which are known to be supermarkets, but have either missing or incorrect data can be manually reclassified. In San Francisco, 2 additional markets that did not fit this criteria, but were known to carry the array of goods that supermarkets carry, were also coded as supermarkets: Mania Oriental Market and Bryan’s Grocery.

Stores are then mapped to illustrate the distribution of supermarkets/club stores, grocery stores, produce stores, meat/fish stores, farmers’ markets, and convenience stores throughout the city.

Food Market Score

This prepared list of food stores is used to create the Food Market Score. To calculate the Food Market Scores, the distance from each residential intersection (intersections within 100 meters of residential lots) to each retail food store school within 1 mile of the intersection is calculated. A distance of < 0.25 miles is given a score of 1, while distances between 0.25-0.49 miles are given a score of 0.9 and distances between 0.5-1.0 miles are given a score of 0.75.

Each store is then given a score based on its type. To come up with scores for store types, a survey of store stock can be completed at a sample of stores from different neighborhoods in the city (contact for survey form). In San Francisco the Inner Richmond, Outer Sunset, Outer Mission, Downtown/Civic Center, Mission, and Marina neighborhoods were sampled. These neighborhoods were chosen because they represented a range of incomes and residential densities, and also because less food retail research had been previously conducted in them. The store survey looks at the variety of healthy, whole foods available in each surveyed store. The survey contains sections for produce, dairy, whole grains, and protein. The produce section represents 51% of the total possible points (59 points possible), while the dairy, whole grains, and protein sections account for 10%, 19%, and 20% of the points respectively. In San Francisco, the median final scores by store type were as follows: supermarket – 57, produce market – 51.5, other grocery – 41.5, meat/seafood market – 20, and convenience/liquor store – 14. It is worth noting that only independent supermarkets may be surveyed, because it can be assumed that a large chain would certainly receive all points. Farmers’ markets were given 29.5 points based on the assumption that they would get the full produce credit, but points for other sections were not given to account for the fact that farmers’ markets have limited hours. Large pharmacies can also be included, if they accept federal nutrition program benefits. The median score for drug stores in San Francisco was 24.2. To arrive at the final store type scores, the median score for each store type should be divided by the median supermarket score. In San Francisco the final scores are as follows: supermarket – 1, produce market – 0.9, other grocery – 0.72, farmers’ market – 0.51, pharmacy – 0.41, meat/seafood market – 0.35, and convenience/liquor store – 0.25.

For each intersection the distance scores are then multiplied by the store type scores for each food retail store within 1 mile of the intersection. In the case of convenience and liquor stores, only stores within ¼ mile are considered because it was judged that residents would not travel further than that to go to a convenience store. The products of the distance score and the store type score were then summed for each intersection by store type. To account for the overabundance of some store types skewing the results, a score cap is applied to each store type. After applying the caps, an intersection will receive no more points than the equivalent of 3 stores within ¼ mile – 3 points for supermarkets, 2.7 points for produce stores, and 2.16 points for other grocery stores. For meat and seafood markets, pharmacies, and convenience and liquor stores, the top number of points an intersection can receive from each store type is 0.7, 0.82, and 0.5 respectively – the equivalent of 2 stores within ¼ mile. There was is score cap for farmers’ markets.

Each intersection’s capped scores by store type are then summed to come up with the food market score. The intersection food market scores were then normalized onto a scale of 0 to 100 and then interpolated across the surface of San Francisco using inverse distance weighting. Neighborhood average scores are calculated using zonal statistics on the resulting raster file.

Limitations

Due to the constant turnover of businesses and the error present in all purchased business list, the data will most likely contain errors. There are likely additional establishments that exist but are not included or some may no longer exist or may be coded incorrectly.

The presence of a food retail establishment within a neighborhood does not equate to access. Many factors affect access to retail food sources, including cost, hours of operation, the presence of physical barriers including major roads, highways, buildings and gates, perceived and actual safety, transportation, cultural preferences, etc.