This readme.txt file was generated on <20200814> by <Megan Winkler>


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GENERAL INFORMATION
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1. Title of Dataset: Data to accompany Longitudinal Fruit and Vegetable Sales in Small 
Food Retailers: Response to a Novel Local Food Policy and Variation by Neighborhood 
Socioeconomic Status 


2. Author Information


  Lead Author Contact Information
        Name: Megan R. Winkler
           Institution: University of Minnesota, School of Public Health, Division of Epidemiology and Community Health
           Address: 1300 S. 2nd Street, Suite 300, Minneapolis, MN 55454
	   Email: mwinkler@umn.edu

  Associate or Co-investigator Contact Information
        Name: Kathleen Lenk
           Institution: University of Minnesota, School of Public Health, Division of Epidemiology and Community Health
           Address: 1300 S. 2nd Street, Suite 300, Minneapolis, MN 55454
           Email: lenk@umn.edu

  Associate or Co-investigator Contact Information
        Name: Darin J. Erickson
           Institution: University of Minnesota, School of Public Health, Division of Epidemiology and Community Health
           Address: 1300 S. 2nd Street, Suite 300, Minneapolis, MN 55454
           Email: erick232@umn.edu

  Associate or Co-investigator Contact Information
	Name: Caitlin E. Caspi
           Institution: University of Minnesota, Medical School, Department of Family Medicine and Community Health
           Address: 717 Delaware Street SE, Rm 183, Minneapolis, MN 55414
           Email: cecaspi@umn.edu

  Principal Investigator Contact Information
	Name: Melissa N. Laska 
           Institution: University of Minnesota, School of Public Health, Division of Epidemiology and Community Health
           Address: 1300 S. 2nd Street, Suite 300, Minneapolis, MN 55454
           Email: mnlaska@umn.edu


3. Date of data collection: 2014 - 2017


4. Geographic location of data collection : Minneapolis, MN, and St. Paul, MN, USA 


5. Information about funding sources that supported the collection of the data:
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK104348); Centers 
for Disease Control and Prevention (U48DP005022); National Center for Advancing 
Translational Science (UL1TR000114)


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SHARING/ACCESS INFORMATION
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1. Licenses/restrictions placed on the data: Attribution-NonCommercial-ShareAlike 4.0 
International (CC BY-NC-SA 4.0) [https://creativecommons.org/licenses/by-nc-sa/4.0/]


2. Links to publications that cite or use the data:
Winkler MR, Lenk KM, Erickson DJ, Caspi CE, Laska MN. Longitudinal Fruit and Vegetable 
Sales in Small Food Retailers: Response to a Novel Local Food Policy and Variation by 
Neighborhood Socioeconomic Status. International Journal of Environmental Research and 
Public Health. 2020 Jul 29; 17(15):5480.

http://doi.org/10.3390/ijerph17155480

3. Recommended citation for the data:
Winkler, Megan R; Lenk, Kathleen M; Erickson, Darin J; Caspi, Caitlin E; Laska, 
Melissa N. (2020). Data to accompany Longitudinal Fruit and Vegetable Sales in Small 
Food Retailers: Response to a Novel Local Food Policy and Variation by Neighborhood 
Socioeconomic Status. Retrieved from the Data Repository for the University of 
Minnesota, https://doi.org/10.13020/adr6-3542.



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DATA & FILE OVERVIEW
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1. File List
   A. Filename: Store_winkler_drum_dataset.sas7bdat        
      Short description: SAS data file containing the manager survey and customer 
intercept interview data (summarized to store level) reported in the associated 
publication. Note that store ID numbers are not always numerically sequential because 
a store may have been deemed ineligible or dropped out over time; likewise, some stores 
do not have data for all variables at all time points.      

      *Additional file with the same name in .csv format for preservation and interoperability      


   B. Filename: winkler_STORE_Variables in dataset_DRUM.pdf         
      Short description: Word file that describes the variables included in the SAS 
data file.
        


2. Relationship between files: N/A      




3. Additional related data collected that was not included in the current data package: 
See Laska, Melissa N; Caspi, Caitlin E; Lenk, Kathleen; Moe, Stacey G; Pelletier, 
Jennifer E; Harnack, Lisa J; Erickson, Darin J. (2019). Data to accompany evaluation of 
the first U.S. staple foods ordinance: Impact on nutritional quality of food retailer 
offerings, customer purchases and home food environments. Retrieved from the Data 
Repository for the University of Minnesota, https://doi.org/10.13020/qxtc-sc36.



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METHODOLOGICAL INFORMATION
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1. Description of methods used for collection/generation of data: 
The following summary was taken from the following paper: Winkler MR, Lenk KM, Erickson 
DJ, Caspi CE, Laska MN. Longitudinal Fruit and Vegetable Sales in Small Food Retailers: 
Response to a Novel Local Food Policy and Variation by Neighborhood Socioeconomic 
Status. International Journal of Environmental Research and Public Health. 2020 Jul 29; 
17(15):5480. http://doi.org/10.3390/ijerph17155480


Data for this analysis were part of the larger STORE (STaple foods ORdinance Evaluation)
study. The primary objective of STORE was to assess the effects of the Minneapolis 
Staple Foods Ordinance, including overall changes in compliance, the healthfulness of 
the store environments, and customer purchasing in small food stores [9]. Data were 
collected in Minneapolis as well as in an adjacent city, St. Paul, Minnesota, USA, which
served as the study’s comparison (i.e., control) site, across four time points—
pre-ordinance revisions in Fall 2014 and three post-implementation time points, including 
Fall 2015 (ordinance revisions activated, no enforcement), Summer 2016 (early 
enforcement begins), and Fall 2017 (continued monitoring and enforcement). As previously 
described [9], stores were randomly selected based on administrative lists of licensed 
retailers. Stores were excluded from selection if they were supermarkets, authorized as 
a US Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) store, 
and/or a retailer exempt from the ordinance in Minneapolis, as well as comparable stores
in St. Paul. Of the 180 stores (90 Minneapolis, 90 St. Paul) sampled, 23 stores were 
deemed ineligible after a pre-data collection store visit and two stores did not provide 
consent, resulting in 155 stores that consented and participated at one or more study 
time points. 

At each time point, teams of two data collectors visited stores primarily on weekdays 
between 10am and 7pm. Store owners or managers were asked to participate in an 
interviewer-administered manager survey, and customer intercepts were performed with 
manager permission to evaluate customer purchasing. We conducted intercept interviews 
with customers exiting stores and recorded observed food and beverage purchases (details 
on data collection methods, participant eligibility, and participant response rate have 
been published elsewhere) [9,26]. Interviewer-administered manager surveys were 
conducted in the store at a time convenient for the manager [27].

The sample for this analysis included stores that had a manager participate at one or 
more time points (n = 147 stores) and/or stores that had customers that were interviewed
at one or more time points (n = 147 stores; n = 3039 customer interviews conducted 
across 2014–2017; See Supplemental Figure S1). Collectively, 137 stores had both manager 
and customer-level data. As previously reported [27], participating managers self-
reported being predominantly male, non-Hispanic White, in their late thirties, and on 
average had managed and/or owned the store for approximately four years. Customers 
participating in intercept interviews self-reported being predominantly male, non-
Hispanic White or non-Hispanic Black, approximately 40 years old, employed, and shopped 
at the store at least weekly [9].


2. Methods for processing the data:  Data collectors recorded data on hard copy (paper) 
forms while in the field. Hard copies were reviewed for clarity and 
detection/reconciliation of errors and were then manually data entered by a data entry 
service.


3. Describe any quality-assurance procedures performed on the data: Data collectors 
recorded data on hard copy (paper) forms while in the field. Hard copies were reviewed 
for clarity and detection/reconciliation of errors and were then manually data entered 
by a data entry service. Once data entry was complete, an extensive review of and 
quality control checks were administered on a random sample of the data. Any 
discrepancies, errors, or differences found were reconciled prior to inclusion in the 
final data set.


4. People involved with sample collection, processing, analysis and/or submission:
Stacey Moe (study coordinator) and Pamela Carr-Manthe (evaluation coordinator) directly 
oversaw data collection teams. Data were entered through a contract with Northwest 
Keypunch Inc. Bill Baker (data programmer) processed the entered data and led quality 
control checks with Ms. Moe and Ms. Carr-Manthe. Final analyses and analytic datasets 
were prepared by Kath Lenk (senior data analyst). All processes were overseen by 
Melissa Laska (study PI).



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DATA-SPECIFIC INFORMATION FOR: [FILENAME]
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See data dictionary file: winkler_STORE_Variables in dataset_DRUM.pdf