24
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Association between store food environment and customer purchases in small grocery stores, gas-marts, pharmacies and dollar stores

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Purchases at small/non-traditional food stores tend to have poor nutritional quality, and have been associated with poor health outcomes, including increased obesity risk The purpose of this study was to examine whether customers who shop at small/non-traditional food stores with more health promoting features make healthier purchases.

          Methods

          In a cross-sectional design, data collectors assessed store features in a sample of 99 small and non-traditional food stores not participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in Minneapolis/St. Paul, MN in 2014. Customer intercept interviews ( n = 594) collected purchase data from a bag check and demographics from a survey. Store measures included fruit/vegetable and whole grain availability, an overall Healthy Food Supply Score (HFSS), healthy food advertisements and in-store placement, and shelf space of key items. Customer nutritional measures were analyzed using Nutrient Databases System for Research (NDSR), and included the purchase of ≥1 serving of fruits/vegetables; ≥1 serving of whole grains; and overall Healthy Eating Index-2010 (HEI-2010) score for foods/beverages purchased. Associations between store and customer measures were estimated in multilevel linear and logistic regression models, controlling for customer characteristics and store type.

          Results

          Few customers purchased fruits and vegetables (8%) or whole grains (8%). In fully adjusted models, purchase HEI-2010 scores were associated with fruit/vegetable shelf space ( p = 0.002) and the ratio of shelf space devoted to healthy vs. less healthy items ( p = 0.0002). Offering ≥14 varieties of fruit/vegetables was associated with produce purchases (OR 3.9, 95% CI 1.2–12.3), as was having produce visible from the store entrance (OR 2.3 95% CI 1.0 to 5.8), but whole grain availability measures were not associated with whole grain purchases.

          Conclusions

          Strategies addressing both customer demand and the availability of healthy food may be necessary to improve customer purchases.

          Trial registration

          ClinialTrials.gov: NCT02774330. Registered May 4, 2016 (retrospectively registered).

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12966-017-0531-x) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references50

          • Record: found
          • Abstract: found
          • Article: not found

          Supermarkets, other food stores, and obesity: the atherosclerosis risk in communities study.

          Obesity is a leading public health concern, and although environmental factors have been hypothesized to play a role in the prevention of obesity, little empirical data exist to document their effects. The purpose of this study was to examine whether characteristics of the local food environment are associated with the prevalence of cardiovascular disease risk factors. A cross-sectional study of men and women participating in the third visit (1993-1995) of the Atherosclerosis Risk in Communities (ARIC) Study was conducted in 2004. The analyses included 10,763 ARIC participants residing in one of the 207 eligible census tracts located in the four ARIC-defined geographic areas. Names and addresses of food stores located in Mississippi, North Carolina, Maryland, and Minnesota were obtained from departments of agriculture. Multilevel modeling was used to calculate prevalence ratios of the associations between the presence of specific types of food stores and cardiovascular disease risk factors. The presence of supermarkets was associated with a lower prevalence of obesity and overweight (obesity prevalence ratio [PR] = 0.83, 95% confidence interval [CI] = 0.75-0.92; overweight PR = 0.94, 95% CI = 0.90-0.98), and the presence of convenience stores was associated with a higher prevalence of obesity and overweight (obesity PR = 1.16, 95% CI = 1.05-1.27; overweight PR = 1.06, 95% CI = 1.02-1.10). Associations for diabetes, high serum cholesterol, and hypertension were not consistently observed. Results from this study suggest that characteristics of local food environments may play a role in the prevention of overweight and obesity.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Obesity prevalence and the local food environment.

            Disparities in access to healthy foods have been identified particularly in the United States. Fewer studies have measured the effects these disparities have on diet-related health outcomes. This study measured the association between the presence of food establishments and obesity among 1295 adults living in the southern region of the United States. The prevalence of obesity was lower in areas that had supermarkets and higher in area with small grocery stores or fast food restaurants. Our findings are consistent with other studies showing that types of food stores and restaurants influence food choices and, subsequently, diet-related health outcomes.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Sources of data for developing and maintaining a nutrient database.

              A nutrient database that contains current, reliable data is a prerequisite for accurate calculation of dietary intakes. Most nutrient databases are expanded from data supplied by the U.S. Department of Agriculture and may include additional foods or nutrients or data from more recent analyses, food manufacturers, or foreign food tables. Guidelines must be established for selection of reliable values from appropriate sources. A system for precise documentation of data sources provides a means for determining whether individual nutrient values were derived from chemical analyses, recipe calculations, or imputations. This article identifies data sources used by the Nutrition Coordinating Center at the University of Minnesota for its nutrient database and describes the procedures used to select and document nutrient values.
                Bookmark

                Author and article information

                Contributors
                (612) 626-7074 , cecaspi@umn.edu
                lenk@umn.edu
                Jennifer.Pelletier@state.mn.us
                tlbarnes@umn.edu
                harna001@umn.edu
                erick232@umn.edu
                nels5024@umn.edu
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                5 June 2017
                5 June 2017
                2017
                : 14
                : 76
                Affiliations
                [1 ]ISNI 0000000419368657, GRID grid.17635.36, Department of Family Medicine and Community Health, Program in Health Disparities Research, , University of Minnesota, ; 717 Delaware St. SE, Minneapolis, MN 55414 USA
                [2 ]ISNI 0000000419368657, GRID grid.17635.36, Division of Epidemiology and Community Health, Suite 300, , University of Minnesota, ; 1300 South 2nd St, Minneapolis, MN 55454 USA
                [3 ]ISNI 0000 0004 0509 1853, GRID grid.280248.4, , Statewide Health Improvement Program, Minnesota Department of Health, ; Saint Paul, MN 55164 USA
                Article
                531
                10.1186/s12966-017-0531-x
                5460502
                28583131
                1f4940e6-e4f5-4ab6-a260-44f54ccd30a4
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 February 2017
                : 26 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: R01DK104348
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100009633, Eunice Kennedy Shriver National Institute of Child Health and Human Development;
                Award ID: U54HD070725
                Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: R25CA163184
                Funded by: FundRef http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR000114
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Nutrition & Dietetics
                community nutrition,customer purchases,healthy eating index,corner stores

                Comments

                Comment on this article