Supplemental Nutrition Assistance Program (SNAP)-Authorized Grocery,Convenience,Dollar,and Restaurant or Delivery Service Settings Are Associated With Increased Obesity Prevalence in Virginia

Abstract

Purpose:

United States Department of Agriculture Supplemental Nutrition Assistance Program (SNAP) participants use SNAP-authorized stores for dietary purchases. Relationships between obesity prevalence and access to grocery and varied nontraditional (eg, dollar, drug, and convenience) SNAP settings are underexplored. This research aimed to determine the association of a full range of SNAP-authorized stores with obesity prevalence in Virginia.

Design:

The SNAP Retailer Locator was used to cross-sectionally identify authorized stores, and county health ranking information was applied based on store location.

Setting:

Virginia, United States.

Sample:

The SNAP-authorized stores, classified among store categories: grocery or supermarket; drug; mass merchandiser; supercenter; convenience; dollar; club; other; nonfood store; farmers markets; and independent grocery stores.

Measures:

County-level obesity prevalence with income and rurality as potential confounders.

Analysis:

Multiple linear regression was used to determine associations between county-level adult obesity prevalence and available SNAP-authorized store formats (P < .05 a priori).

Results:

Store format was a predictor of obesity prevalence in Virginia in simple and adjusted models (R ² = 0.035, P < .0001 and R ² = 0.434, P < .0001, respectively). Grocery store or supermarket access was associated with obesity. The SNAP-authorized convenience, dollar, and nonfood stores were associated with a 0.3, 0.5, and 1.3 increase in county obesity prevalence, respectively (P < .05).

Conclusions:

Research, practice, and health policy approaches to improve grocery, convenience, dollar, and restaurant or delivery service settings may favorably influence community obesity prevalence in Virginia.

Keywords

Supplemental Nutrition Assistance Program store format obesity

Purpose

The United States Department of Agriculture (USDA) Supplemental Nutrition Assistance Program (SNAP) provides about 40.3 million Americans from low-income households with supplemental income to purchase foods and beverages.¹ The SNAP benefits can be used in a variety of authorized retail outlets, including grocery stores and supercenters (eg, Walmart) and dollar, drug, and convenience formats. These stores are required to stock fresh and shelf-stable groceries among 4 staple food categories (3 varieties with 3 units available in each group).² However, available products aligned with the 2015-2020 Dietary Guidelines for Americans (DGA),³ and the dietary quality of SNAP consumers’ purchases vary among SNAP-authorized food store types.^4
-6

Most investigations have shown weak or no relationship between grocery store access (or nonaccess) and consumer obesity.^7,8 This relationship may vary among communities, and additionally, obesity prevalence related to traditional and nontraditional (eg, dollar, drug, and convenience) SNAP-authorized store access is underinvestigated.^7
-9 Exploring a wide range of store associations with community obesity prevalence can inform future food environment research and guide SNAP-Education (SNAP-Ed) healthy food retail programming.¹⁰ This was the purpose of the presented research, using Virginia as a case study due to authors’ practice site location.

Methods

The SNAP-authorized stores in Virginia were identified in April 2018 using the SNAP Retailor Locator (N = 6469) (fns.usda.gov/snap/retailer-locator). Virginia was selected for the study setting to guide Virginia Cooperative Extension’s statewide SNAP-Ed healthy food retail programming. Stores were coded by format: grocery or supermarket; drug, mass merchandiser; supercenter; convenience; dollar; club; or other (eg, specialty food store, commissary).⁶ Nonfood stores (eg, restaurant and delivery services), farmers markets (included stands), and independent grocery stores (eg, smaller grocers with different business models than corporate/chain stores)¹¹ were also included to classify the full range of SNAP-authorized stores statewide. Google searches assisted in categorization when store names were unfamiliar. Eight stores remained uncategorized using established criteria and were removed from the final data set (n = 6461).

Potential confounding variables were considered: county population and adjacency to metro areas using the 2013 Rural-Urban Continuum Code (RUCC);¹² and median income by county.¹³ US RUCC values range from 1 to 9, with higher numbers indicating increased rurality.¹² County obesity prevalence was the outcome of interest, defined as the percentage of adult residents (>20 years of age) with a self-reported body mass index greater than or equal to 30.¹³ Median income and county obesity prevalence were obtained from county health ranking data.¹³

Analysis

Multiple linear regression analysis was used to predict county adult obesity prevalence based on available SNAP-authorized store formats in Virginia (SPSS version 25, P < .05 a priori). A simple model was used, then meaningful model outcomes prompted an adjusted model that included potential confounders, including income and RUCC.

Results

Store format was identified as a meaningful predictor of obesity prevalence in Virginia (R ² = 0.035, P < .0001). After adjustment, store format remained a predictor (R ² = 0.434, P < .0001). Grocery store or supermarket access was associated with obesity and served as the reference group in this study. Specifically, grocer or supermarket access was associated with a county obesity prevalence of 28.6%. The SNAP-authorized convenience, dollar, and nonfood stores were associated with a 0.3, 0.5, and 1.3 increase in county obesity prevalence, respectively (P < .05; see Table 1).

Table 1.

Supplemental Nutrition Assistance Program (SNAP)-Authorized Stores Predicting County Obesity Prevalence in Virginia.

Predictors	Simple model		Full model
Predictors	β^a	P	β^a	Standard error	T	P	β (95% CI)
Grocery^b	28.604	.000	37.631	0.189	199.356	.000	37.261 to 38.001
Drug	−0.105	.638	−0.020	0.170	−0.116	.908	−0.354 to 0.314
Club	−0.680	.295	0.041	0.498	0.082	.935	−0.936to 1.017
Convenience^c	1.462	.000	0.326	0.126	2.577	.010	0.078 to 0.574
Dollar^b	1.964	.000	0.447	0.158	2.829	.005	0.137 to 0.0756
Supercenter	0.350	.268	0.033	0.242	0.135	.892	−0.442 to 0.507
Mass merchandiser	1.216	.33	0.091	0.436	0.209	.835	−0.764 to 0.946
Independent grocer	1.817	.000	0.357	0.224	1.592	.111	−0.083 to 0.797
Specialty	−0.043	.850	−0.179	0.174	−1.031	.302	−0.520 to 0.161
Nonfood store^c	3.103	.000	1.287	0.592	2.172	.030	0.126 to 2.448
Farmers market	1.174	.000	0.152	0.243	0.624	.532	−0.325 to 0.629
Rural-Urban Continuum Code^b	–	–	−0.305	0.020	−14.973	.000	−0.345 to 0.265
Median county income^b	–	–	0.000	0.000	−65.178	.000	0.000

^a County obesity prevalence, defined as the percentage of adult residents (>20 years of age) with a self-reported body mass index greater than or equal to 30.¹³

^b P < .01, adjusted model.

^c P < .05, adjusted model.

Both RUCC and median county income were also associated with obesity. An increase in county rurality was associated with a 0.31 decrease in obesity prevalence, while median county income was not associated with any change from obesity prevalence indicated by the reference category used (Table 1).

Discussion

Prior research has established a strong relationship between store access and consumer obesity in socioeconomically disadvantaged areas,⁹ which is why it is particularly important to understand such access for SNAP consumers. This study adds to existing literature by characterizing the relationship between obesity prevalence and a wider range of SNAP-authorized stores. While some measures of healthy food access focus on distance to supermarkets, as in the USDA Economic Research Service’s Food Access Research Atlas,¹⁴ the results of this study indicate the need to account for other, nontraditional retail formats when considering how access to foods might influence populations' dietary choices and obesity. Results have important research, practice, and health policy implications.

As shown in this study, community obesity rates are related to access to food based on store type, specifically among grocery, convenience, dollar, and restaurant or delivery service sites. These settings may be characterized by a lack of products aligned with the DGA⁴ and/or disproportionate marketing of dietary products high in saturated fats, added sugar, and sodium to influence consumer purchases,⁸ which is consistent with literature characterizing food swamps and obesity.¹⁵ However, few studies have focused on measuring the availability and affordability of options aligned with the DGA^4,5 and none characterize or compare marketing properties¹⁶ among such nontraditional SNAP-authorized stores. These topics should be the focus of future food store research.

The SNAP-Ed partners have increasingly focused efforts on facilitating healthy retail programming in stores in underserved communities.^10,11 Directing SNAP-Ed resources to formats identified in this research as associated with consumer obesity may be an important step to improve community health outcomes. Likewise, investing in small, independent grocers to facilitate their financial success within communities may be both an important practice and policy approach as small grocers were not associated with obesity prevalence in this research.

Last, incentives to entice supermarkets to operate in underserved neighborhoods may improve healthy food access but do not address the association between other food retail outlets and obesity. More complex policy solutions may be needed to improve the dietary quality of SNAP participants.

Limitations

This research is limited by the combination of different database measures to explore obesity relationships. Associations between SNAP-authorized store format and obesity in the state of Virginia may not be generalizable to other US states, given obesity prevalence varies by US region.¹⁷ However, Virginia serves as a viable example of how county health rankings can be combined with store format data to guide food environment research, practice, and policy solutions.

The association of increased rurality with lowered obesity prevalence in this research was unanticipated, as rural residents are often documented to experience higher obesity prevalence than urban counterparts.¹⁸ The relationships between obesity, community socioeconomic status, location (ie, rurality), and store format are complex and warrant additional attention among diverse contexts.

So What? (Implications for Health Promotion Practitioners and Researchers)

What is already known on this topic?

The food environment influences consumer obesity and research within this scope has largely focused on traditional grocery formats.

What does this article add?

This research focused on a wide range of nontraditional store formats, tailored to SNAP-authorized settings, to understand associations with obesity prevalence in Virginia.

What are the implications for health promotion practice or research?

Approaches to improve SNAP-authorized grocery, convenience, dollar, and restaurant or delivery service settings may favorably influence obesity prevalence in Virginia.

Footnotes

Authors’ Note

Bailey Houghtaling initiated and led the research. Sarah Misyak and David Kniola contributed to methodological design, analyses, and results reporting and interpretation based on topic expertise in public health programming/evaluation and statistical methods, respectively. Bailey Houghtaling wrote the manuscript with contributions and edits from all authors who have approved the final manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Bailey Houghtaling

References

Oliveira

. The Food Assistance Landscape: FY 2018 Annual Report. US Department of Agriculture, Economic Research Service; 2019.

US Department of Agriculture. Enhancing Retailer Standards in the Supplemental Nutrition Assistance Program (SNAP); Final Rule. Food and Nutrition Service; 2016.

US Department of Health and Human Services and US Department of Agriculture. 2015–2020 Dietary Guidelines for Americans. 8th Edition. Accessed December 2015. http://health.gov/dietaryguidelines/2015/guidelines/

Racine

Batada

Solomon

Story

. Availability of foods and beverages in Supplemental Nutrition Assistance Program-authorized dollar stores in a region of North Carolina. J Acad Nutr Diet. 2016;116(10):1613–1620.

Racine

Kennedy

Batada

Story

. Foods and beverages available at SNAP-authorized drugstores in sections of North Carolina. J Nutr Educ Behav. 2017;49(8):674–683.

Volpe

Kuhns

Jaenicke

. Store Formats and Patterns in Household Grocery Purchases. Economic Research Service; 2017.

Ver Ploeg

Wilde

. How do food retail choices vary within and between food retail environments? Food Policy. 2018;79:300–308. https://www-sciencedirect-com-443.web.bisu.edu.cn/science/article/abs/pii/S0306919218301283

Hollis-Hansen

Vermont

Zafron

Seidman

Leone

. The introduction of new food retail opportunities in lower-income communities and the impact on fruit and vegetable intake: a systematic review. Transl Behav Med. 2019;9(5):837–846.

Chen

Creger

Howard

Judd

Harrington

Fontaine

. Association of community food environment and obesity among US adults: a geographical information system analysis. J Epidemiol Commun Health. 2019;73(2):148–155.

10.

US Department of Agriculture. Supplemental Nutrition Assistance Program Education Plan Guidance. Food and Nutrition Service; 2019.

11.

Houghtaling

Serrano

Dobson

, et al. Rural independent and corporate Supplemental Nutrition Assistance Program (SNAP)-authorized store owners’ and managers’ perceived feasibility to implement marketing-mix and choice-architecture strategies to encourage healthy consumer purchases. Transl Behav Med. 2019;9(5):888–898.

12.

US Department of Agriculture. Rural-Urban continuum codes. Published 2013. Updated May 10, 2018. Accessed July 7, 2016. http://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx

13.

Population Health Institute. County health rankings–Virginia. University of Wisconsin. Published March 2018. Accessed April 28, 2018. https://www.countyhealthrankings.org/app/virginia/2018/overview

14.

US Department of Agriculture. Food access research atlas. Economic Research Service. Updated October 31, 2019. Accessed June 8, 2020. https://www.ers.usda.gov/data-products/food-access-research-atlas/

15.

Cooksey-Stowers

Schwartz

Brownell

. Food swamps predict obesity rates better than food deserts in the United States. Int J Environ Res Public Health. 2017;14(11):1–20. doi:10.3390/ijerph14111366

16.

Kerr

Sallis

Bromby

Glanz

. Assessing reliability and validity of the GroPromo Audit Tool for evaluation of grocery store marketing and promotional environments. J Nutr Educ Behav. 2012;44(6):597–603.

17.

Sung

Etemadifar

. Multilevel analysis of socio-demographic disparities in adulthood obesity across the United States geographic regions. Osong Public Health Res Perspect. 2019;10(3):137–144.

18.

Befort

Nazir

Perri

. Prevalence of obesity among adults from rural and urban areas of the United States: findings from NHANES (2005-2008). J Rural Health. 2012;28(4):392–397.