Three datasets for nutrition environment measures of food outlets located in the Lower Mississippi Delta region of the United States [version 1; peer review: 2 approved]

This data note provides details of a research database containing 266 food outlets located in five rural towns in the Lower Mississippi Delta region of Mississippi, whose nutrition environments were measured from 2016 to 2018.  The food outlet types include grocery stores, convenience stores, full-service restaurants, and fast food restaurants.  The purpose of this publication is to describe the three datasets for external researchers who may be interested in making use of them.  The datasets are available from the USDA National Agricultural Library’s Ag Data Commons under a CC0 1.0 Universal License: https://doi.org/10.15482/USDA.ADC/1503704.


Introduction
The Mississippi River Delta region is among the most socioeconomically disadvantaged areas of the United States (US) with less healthful food environments (e.g., low access to healthful foods, food insecurity) and poorer health outcomes than non-Delta counties in the same states and the nation 1 . Accessibility (location of healthful food outlets near neighborhoods, particularly in low-income and rural areas), availability (healthful options in local food outlets), and affordability (reasonable prices) of nutrient-dense foods are crucial to facilitate adoption of a healthful diet [2][3][4] . To inform future nutrition interventions designed for residents of the Lower Mississippi, the Delta Food Outlets Study was conducted to measure nutrition environments of towns located in this region.

Methods
Delta Food Outlets was an observational study designed to collect data on food outlets located in five rural Lower Mississippi Delta towns of interest to researchers 5 . Food outlet types included grocery stores, convenience stores, full-service restaurants, and fast food restaurants. The study was approved and classified as exempt by the Institutional Review Board of Delta State University. Data collection occurred from March 2016 through September 2018. Grocery stores were identified by referencing two sources -the US Department of Agriculture (USDA) Food and Nutrition Service Supplemental Nutrition Assistance Program (SNAP) retailer locator 6 and the Mississippi State Department of Health Restaurant and Food Facility Inspections website 7 . Convenience stores were identified by referencing three sources -the SNAP retailer locator 6 , the B2B Yellow Pages website 8 , and lists of current privilege licenses obtained from city clerks. Restaurants were identified by referencing the Mississippi State Department of Health Restaurant and Food Facility Inspections website 7 . Food outlets were classified using operational definitions contained in the Economic Research Service's Food Environment Atlas documentation 9 . While the 266 food outlets included in the datasets represent the entire population of these types of food outlets in the five towns, they may not be representative of all such outlets located in rural Lower Mississippi Delta towns.
Nutrition environments of the food outlets were measured using the Nutrition Environment Measures Survey (NEMS) for grocery stores (NEMS-S), convenience stores (NEMS-CS), and restaurants (NEMS-R) 10 . NEMS tools are validated observational measures of retail store nutrition environments that focus on the availability of healthful food choices, quality of fresh produce, and comparative pricing between healthful and less healthful options in 11 common categories 11 . A comprehensive description of the Delta Food Outlets Study methodology and measures has been published elsewhere 5 .
The NEMS tools were recreated as electronic surveys using Snap Surveys software (version 11.20, Snap Surveys Ltd). All data were collected via tablets loaded with Snap Surveys software and stored on the Snap WebHost, an online mobile and secure survey management system. For quality assurance purposes, 25% of the food outlets were randomly selected for duplicate measurement. Discrepancies between measurements were discussed and resolved.
Food outlets were scored using algorithms provided for the NEMS tools. Higher scores indicate a more healthful nutrition environment. To make scores between different types of food outlets comparable, NEMS scores were transformed into ratio scores by dividing each food outlet score by the maximum score possible for that type of outlet. The use of ratio scores was necessary because each NEMS tool has a different possible score range (NEMS-S, -10 to 57; NEMS-CS, -9 to 57; NEMS-R, -7 to 27). The higher the ratio score, the more healthful the nutrition environment. Scoring was performed using SAS® (version 9.4, SAS Institute Inc). This project contains all three datasets -NEMS-C (convenience stores), NEMS-G (grocery stores), and NEMS-R (restaurants) -along with their corresponding data dictionaries.
Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

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There were some places where more detail would have been useful.
What are the characteristics of the towns of interest? Adding in the range of population size of the towns would be helpful. Were there large metropolitan areas that were excluded because this study was intentionally focused on towns? And/or can the authors make any statement in the note about how the towns may not be representative of the larger Lower Mississippi Delta area food environment? Some information like this would be helpful for readers in determining if the dataset is appropriate for use for addressing their research question.

1.
Classifying food retail outlets (i.e., grocery stores vs. convenience stores, restaurants vs. fast food outlets) can be challenging. Potential misclassification of store types is a major topic of discussion in food environment databases. Consider adding in more detail about how food stores were classified. The definitions used for the food retail outlet categories would be helpful (I see they are defined in the longer paper), but even more helpful would be a description of how decisions were made about how to classify a food outlet (e.g., based on one of the food lists, and then verified during data collection in person?).

2.
Relatedly, the authors reference the documentation for the USDA Food Environment Atlas for how stores were classified. However, the link goes to the Atlas, not the documentation, so it's hard to find more information on how stores were classified. It would be helpful to have a direct link.

3.
Is the rationale for creating the dataset(s) clearly described? Yes comparative pricing between healthful and less healthful options in 11 common categories" I know this is well documented in other places, but it would be useful in this Data Note to list one example of each of these and to also list all 11 food categories. You could add parenthetical comments, for example: availability of healthful food choices (e.g, non-fat milk or whole grain bread, etc), quality of fresh produce (as scored on a X-point scale), and…11 common categories. The categories include a, b, c, ….
Then list them all. It's easy to do and gives the reader a better sense of the data.
"Discrepancies between measurements were discussed and resolved." Discussed by whom? The investigators? Graduate student assistants? Just make clear this clear. 3.
"The higher the ratio score, the more healthful the nutrition environment." Can you indicate if the raw scores and the component scores are also available on the database? Either way is fine, but this would be helpful to know because some feel that the overall NEMS measures are like black box numbers that may not be helpful for a specific campaign to increase fruits and vegetables. See, for example, the references below that allow assessment for targeted campaigns to increase fruits and vegetables or decrease empty calorie snack foods. You may wish to include one or both of these references.