A Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) in Rural South Carolina: Assessing Nutrition Equity and WIC Readiness

A Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) in Rural South Carolina: Assessing Nutrition Equity and WIC Readiness | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) in Rural South Carolina: Assessing Nutrition Equity and WIC Readiness Hadis Dastgerdizad, Theresa Andrasfay, Lovelyn Isiani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8273196/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in BMC Public Health → Version 1 posted 12 You are reading this latest preprint version Abstract Background Rural areas in the southern United States (U.S) experience a disproportionate burden of diet-related disorders, driven by limited access to nutritious and affordable foods. Dollar stores have rapidly grown in these regions —including South Carolina’s Lowcountry—often replacing traditional grocery stores and shaping residents’ nutritional behavior. However, their food environment and their readiness to serve as vendors for the Women, Infants, and Children (WIC) nutrition program remain under-examined. This study addressed this gap using a newly developed Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS), which captures dimensions overlooked by previous assessment tools, particularly given dollar stores’ reliance on shelf-stable and ultra-processed foods. Methods A quantitative, cross-sectional study was conducted in 13-dollar stores across six rural counties in the Lowcountry. All stores were located in rural, high-deprivation areas identified through the Area Deprivation Index (ADI). Food environments of sampled stores were assessed across three domains: (1) Healthy Food Availability (HFA); (2) WIC Readiness; and (3) marketing of healthy versus unhealthy items (e.g., shelf-space allocation). Descriptive statistics, F-tests, and χ²-tests were employed to compare Lowcountry stores with 202-dollar stores from a parallel multi-state assessment. Results Lowcountry’s stores demonstrated limited HFA scores (mean 23 out of a possible 62) and low WIC readiness (mean 51 out of a possible 190). Stores allocated only 12% of the total shelf space to healthy items. None marketed healthy foods at checkout, whereas 100% promoted sugar-sweetened beverages and ultra-processed snacks—patterns consistent with stores in other regions. Although fresh produce availability was slightly higher in the Lowcountry than in a sample of different states, frozen and shelf-stable produce availability was significantly lower. Conclusion Dollar stores in the Lowcountry mirrored national patterns of heavy reliance on ultra-processed foods, reinforcing unhealthy food environments in rural high-poverty settings. Findings provide a policy-actionable framework for expanding WIC vendor eligibility to dollar stores, incentivizing healthy product placement, and regulating marketing to improve nutritional behavior, promote equitable access to nutritious foods, and prevent diet-related chronic disease in rural communities. WIC readiness Rural food environment High-deprivation areas Nutrition equity Nutrition environment measures survey for dollar stores Introduction Nutrition-related chronic disorders, including type II diabetes, obesity, hypertension, and cardiovascular disease, remain leading causes of preventable morbidity and mortality in the United States (U.S) [ 1 – 8 ]. These burdens disproportionally affect low-income, rural, and racially diverse communities, that experience limited access to affordable and nutritious foods [ 9 – 13 ]. South Carolina (SC), with a significant proportion of its land classified as rural, exemplifies these disparities, with adult obesity (36%) and diabetes (13.3%) prevalence exceeding national averages [ 14 – 22 ]. Such disparities underscore the need to move beyond individual behavior change and to investigate structural and environmental inequities [ 5 – 7 , 23 ]. Understanding the characteristics of the community food environments is central to improving dietary patterns and reducing chronic disease disparities among rural communities. Dollar stores, have expanded rapidly across the rural South, serving as a significant source of food [ 24 – 34 ]. Dollar stores significantly influence dietary choices and overall nutritional behaviors in rural populations [ 34 – 42 ], yet they typically offer shelf-stable and ultra-processed foods with minimal fresh options [ 37 , 41 – 43 ]. In many rural areas, the entry of dollar stores often leads to the closure of local grocery stores, further reducing access to healthier food options and aggravating food insecurity [ 44 – 47 ]. In the Lowcountry, high food insecurity and historical marginalization reflect deep structural inequities. [ 18 – 22 , 47 – 50 ]. These inequities are further compounded by recent Supplemental Nutrition Assistance Program (SNAP) benefit reductions, which may reduce support for low-income rural families and increase reliance on the Women, Infants, and Children (WIC) program [ 51 – 52 ]. Despite dollar stores' ubiquity in rural food landscapes and their acceptance of SNAP, they are generally ineligible to serve as WIC vendors because WIC-approved products are not widely available. This presents a critical but understudied gap as expanding WIC authorization to dollar stores could substantially increase access to healthy foods for low-income mothers and children in rural areas, yet little is known about these retailers' WIC-readiness. Most research focuses on urban and suburban food environments, creating critical gaps for rural areas such as the Lowcountry. Furthermore, prior tools such as the Nutrition Environment Measures Survey for Stores (NEMS-S), which were developed for supermarkets and small groceries, are not well-suited to dollar stores [ 53 – 54 ]. These tools also do not assess dollar stores' capacity to meet WIC program standards. The newly developed Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) addresses these limitations by providing a store-format-specific tool designed to assess the availability, visibility, shelf space, and marketing of healthy and unhealthy foods in dollar stores, as well as their readiness to become WIC vendors [ 53 , 55 ].This study is grounded in the Community Nutrition Environment (CNE) and Social-Ecological Models (SEM), which highlight how structural, community, and food-environment factors shape consumer purchasing patterns and dietary behavior [ 56 – 57 ]. Applying these frameworks allows for an integrated assessment of environmental influences—from limited healthy food placement to inadequate WIC-eligible stock—that constrain consumer choice and reinforce rural nutrition inequities. No prior work has jointly assessed the nutrition environment and WIC readiness of rural Lowcountry dollar stores using a validated tool, nor has it compared them across states using standardized metrics. Filling this gap is critical for informing policies to improve healthy food access in underserved rural communities. This study aimed to 1) assess the availability, visibility, marketing, and shelf-space allocation of healthy versus unhealthy foods in 13 rural dollar stores in the Lowcountry using the NEMS-DS tool; 2) evaluate the WIC readiness of these stores; and 3) compare findings from rural Lowcountry stores to those from 202 dollar stores across 10 states, situating local conditions within broader national patterns. By generating this evidence, we aim to guide equitable food access policies and support actionable strategies to reduce diet-related risks in rural communities. Methods Study Design & Setting We conducted a quantitative cross-sectional assessment of the nutrition environments of 13-dollar stores located in six rural counties of the Lowcountry—Allendale, Beaufort, Charleston, Colleton, Hampton, and Jasper counties (Table 1 ). These stores represent a subset of a larger multi-state parallel study that assessed 202 dollar stores across 10 U.S. states, including New York, Texas, Illinois, Florida, Maryland, Georgia, Louisiana, Michigan, Southern California, and South Carolina [ 53 , 55 ]. The broader study applied a standardized protocol and the NEMS-DS to evaluate availability, visibility, and marketing of healthy and unhealthy foods, as well as WIC readiness [ 53 , 55 ] (Appendix A). Dollar stores were identified through publicly available sources and verified through online searches, telephone calls, or in-person visits. For each site, stores were matched to state-level deciles of the Area Deprivation Index (ADI) and categorized as low (1–3), medium (4–6), or high (7–10) deprivation. The ADI is a composite measure of 17 socioeconomic indicators reflecting income, employment, education, housing, and household characteristics [ 58 – 61 ]. In the Lowcountry, stores were intentionally sampled from high-deprivation rural communities where dollar stores are more densely concentrated and where significant structural barriers to healthy food access exist. All stores included in this study were operational at the time of data collection. The University of South Carolina granted an exemption from the Institutional Review Board (IRB). Sampling Strategy We employed a stratified purposive-random sampling approach to ensure representation of selected stores across ADI levels in the Lowcountry while prioritizing rural and high-poverty communities. From the 28 national chain dollar stores (Dollar General, Family Dollar, Dollar Tree) identified in the Lowcountry, 13 were eligible and accessible for assessment. Stores not included were permanently closed (N = 9), temporarily inaccessible, or did not meet the inclusion criteria (N = 6). NEMS-DS assessment was conducted in sampled stores by a trained data collector between January 2024 and December 2024. Measures Neighborhood and store characteristics We collected neighborhood-level sociodemographic characteristics for each store’s census tract or block group. Variables included the racial/ethnic composition of the census tract, the rural/urban classification based on the 2020 U.S. Census, and block group ADI deciles from the 2022 state-level ADI dataset [ 59 – 61 ]. Store characteristics included chain brand, number of checkout counters, and whether SNAP benefits were accepted. Checkout count served as a proxy for customer exposure to point-of-sale marketing and store capacity [ 62 – 63 ]. WIC Readiness The WIC Readiness score assessed the alignment of store offerings with federal WIC food package standards across six categories: fruits and vegetables (fresh and frozen/shelf-stable), fruit juice, grains, dairy and dairy substitutes, proteins, and infant foods and formula. For all non-infant items, a store received points based on the availability of different WIC-eligible varieties: 0 varieties = 0 points; 1–3 varieties = 1 point; 4–6 varieties = 2 points; 7–9 varieties = 3 points; 10–11 varieties = 4 points; 12 + varieties = 5 points. For infant items, 0 varieties = 0 points; 1–2 varieties = 3 points; 3 + varieties = 5 points. Sub-scores received an additional 2 points if at least 30% of store offerings in the category were WIC-eligible. Because subcategories contained differing numbers of items and potential varieties, the maximum potential sub-scores range from 16 points for juice to 53 points for produce. The overall WIC Readiness score ranges from 0 to 190 points. Details of score development are available elsewhere [ 53 ]. The score sheet is included in Appendix B. Healthy Food Availability (HFA) In the original NEMS-S tool, the number of rows or shelf columns is used to count the variety of healthy food items available. The HFA score in NEMS-DS is adapted from this availability component of NEMS-S but modified to reflect the dollar-store format. For subcategories within fruits, vegetables, and juice, 0 points were awarded if there were 0 varieties available; 1 point if 1–2 varieties were available, 2 points if 3–4 varieties were available; and 3 points if at least 5 varieties were available. For subcategories within grains, dairy, and proteins, the scoring depended on the particular item. Still, 0 points were generally awarded if 0 varieties were available, 1 point if at least 1 variety was offered, and some subcategories received an additional point if at least 2 varieties were available. The total HFA score ranged from 0 to 62 points (Appendix C). Marketing and visibility of healthy and unhealthy food items Observers recorded whether selected healthy and unhealthy items—fresh or frozen produce, canned goods, salty snacks, sweet snacks, bottled water, and sugar-sweetened beverages—were displayed at checkout or visible from the store entrance. For each location, we also noted whether at least one healthy (fresh or frozen produce or canned goods) or at least one unhealthy item (salty or sweet snacks) was marketed or visible. Shelf space for healthy and unhealthy food items Raters estimated the linear shelf space for several food and beverage categories in feet using a measurement app on their mobile devices. Healthy shelf space included fresh, frozen, and canned fruits and vegetables; unhealthy shelf space included packaged salty and sweet snacks. We calculated the total healthy shelf space, total unhealthy shelf space, healthy shelf space as a percentage of unhealthy shelf space, and water shelf space a s a percentage of sugar-sweetened beverage shelf space. If healthy and unhealthy items received equal shelf space, these values would be 100%; if healthy items received less shelf space, these values would be lower than 100%. Lower percentages indicate stronger emphasis on calorie-dense, nutrient-poor foods. Statistical Analysis We summarized neighborhood and store-level characteristics using descriptive statistics. For all nutrition environment measures—including WIC readiness, HFA scores, marketing patterns, visibility, and shelf-space allocation—we compared Lowcountry stores (N = 13) with stores from other research sites (N = 202). We conducted chi-squared tests for categorical variables and F tests for numeric variables. Analyses focused on identifying significant differences between rural Lowcountry stores and the broader sample, and on situating findings within a parallel study using NEMS-DS. This comparative approach enables interpretation of whether dollar stores in rural Lowcountry align with, exceed, or lag behind the national sample of dollar stores [ 54 , 59 ]. Results Store-level and neighborhood characteristics are displayed in Table 1 for the 13 Lowcountry stores, compared with 202 stores across other study sites. Most Lowcountry stores were Dollar General (62%) and were located in rural, high-deprivation areas. All Lowcountry stores were classified as rural, compared with only 9% at other sites (p < 0.001). Almost 23% were Family Dollar, and 15% were Dollar Tree; stores in other research sites were more evenly spread across these three brands, but the differences were not statistically significant (Table 1 ). Five (38%) of the Lowcountry stores were located in low ADI neighborhoods, two (15%) in medium ADI neighborhoods, and six (46%) in high ADI neighborhoods; the majority (60%) of stores in other sites were located in high ADI neighborhoods, although differences in ADI level by research site were not statistically significant (Table 1 ). Neighborhood racial compositions varied, with Lowcountry stores located in census tracts with higher percentages of Black residents and lower percentages of Hispanic residents; stores from other sites were located in tracts that had significantly larger Hispanic populations (27% on average) (Table 1 ). All stores in the Lowcountry and 94% of stores in other sites reported accepting SNAP benefits. Stores in the Lowcountry had significantly fewer checkouts than stores at other sites (2.2 vs. 3.4, p < 0.001), suggesting reduced capacity and greater concentration of point-of-sale marketing. Table 1 Store-level and neighborhood characteristics by research site South Carolina (Lowcountry) (N = 13) Other Sites (N = 202) N (%) or Mean, Standard Deviation (SD) N (%) or Mean (SD) p-value County Hampton 3 (23%) Jasper 3 (23%) Allendale 2 (15%) Charleston 2 (15%) Colleton 2 (15%) Beaufort 1 (8%) Store Brand 0.06 Dollar Tree 2 (15%) 83 (41%) Dollar General 8 (62%) 63 (31%) Family Dollar 3 (23%) 56 (27%) ADI level 1 0.07 Low 5 (38%) 29 (14%) Medium 2 (15%) 50 (25%) High 6 (46%) 120 (60%) Urban Status < 0.001 Urban/suburban 0 (0%) 181 (91%) Rural 13 (100%) 18 (9%) Percent non-Hispanic White 47 (20) 38 (33) 0.33 Percent non-Hispanic Black 41 (17) 28 (34) 0.15 Percent Hispanic 7.8 (8.4) 27 (31) 0.03 Percent non-Hispanic other races 3.3 (2.0) 6.7 (8.3) 0.14 Accept SNAP 0.72 No 0 (0%) 13 (6%) Yes 13 (100%) 188 (94%) Number of checkouts 2.2 (0.8) 3.4 (1.2) < 0.001 Note: p-values are from chi-square tests for categorical variables and one-way ANOVA (F-tests) for continuous variables comparing stores in South Carolina to stores in other sites. 1 ADI level is based on the state deciles of the Area Deprivation Index (ADI). Deciles 1–3 are categorized as low ADI, 4–6 as medium ADI, and 7–10 as high ADI. WIC readiness scores were low across all stores (Table 2 ). Lowcountry stores had an average score of 51 out of a potential maximum of 190, similar to other sites. However, the distribution of sub-scores differed. Stores in the Lowcountry had substantially lower fruit and vegetable scores (7.3 vs. 13 out of a potential maximum of 53, p < 0.001), driven by limited frozen and shelf-stable produce offerings (4.3 vs. 12 out of a potential maximum of 39, p < 0.001). Although the Lowcountry dollar stores overall scored lower on total WIC readiness and had limited frozen shelf-stable produce, they actually had more fresh fruits and vegetables available than stores in other regions (3 vs. 0.92 out of a potential maximum of 14, p = 0.024). This reflects emerging fresh produce initiatives within some local Dollar General store chains. The remaining WIC sub-scores were generally low compared to the potential maxima and did not differ significantly between the Lowcountry and the other research sites. One notable exception is that stores in the Lowcountry had an average protein sub-score of 12, which is over 70% of the potential maximum of 17. Sub-scores for juice, grains, dairy, proteins, and infant items were uniformly low across regions, with no statistically significant differences (Table 2 ). Table 2 WIC readiness scores by research site Score and potential range South Carolina (Lowcountry) (N = 13) Other Sites (N = 202) Mean (SD) Mean (SD) p-value WIC Readiness Score (0-190) 51.0 (17.5) 51.6 (20.4) 0.92 Fruit and Veg. Sub Score (0–53) 7.3 (7.0) 12.6 (5.2) < 0.001 Fresh Fruit and Veg. (0–14) 3.0 (4.8) 0.92 (3.1) 0.02 Frozen and Shelf-Stable Fruits and Vegetables (0–39) 4.3 (4.1) 11.6 (4.0) < 0.001 Juice Sub Score (0–16) 6.2 (2.0) 6.12 (2.4) 0.88 Grains Sub Score (0–35) 5.0 (2.5) 4.98 (3.5) 0.98 Dairy Sub Score (0–29) 7.6 (2.0) 7.13 (3.3) 0.61 Protein Sub Score (0–17) 12.4 (1.8) 11.2 (3.1) 0.18 Infant Sub Score (0–40) 12.5 (9.4) 9.57 (10.0) 0.31 Note: p-values are from one-way ANOVA (F-tests) comparing stores in South Carolina to stores in other sites. Table 3 presents the average scores on the HFA score and its sub-scores. Stores in the Lowcountry had an average score of 23 (SD = 6.4) out of a potential maximum of 62, with no significant differences in total or sub-category scores compared with other sites. As with the WIC scores, stores typically scored well below the potential maxima on each of the sub-scores, except for the protein category, in which stores in the Lowcountry scored on average 11 (SD = 1.5) out of 15. Overall, HFA scores indicate constrained access to healthy food options, regardless of store location (Table 3 ). Table 3 Healthy food availability scores by research site Score and potential range South Carolina (Lowcountry) (N = 13) Other Sites (N = 202) Mean (SD) Mean (SD) p-value Healthy Food Availability Score (0–62) 22.9 (6.5) 25.6 (5.8) 0.11 Fruit Availability (0–6) 1.1 (1.4) 1.7 (1.1) 0.07 Veg Availability (0–6) 1.9 (2.0) 2.1 (1.0) 0.47 Juice Availability (0–12) 3.1 (1.3) 3.5 (1.5) 0.30 Grain Availability (0–10) 3.0 (1.2) 3.1 (1.6) 0.82 Dairy Availability (0–13) 2.7 (1.3) 3.2 (1.9) 0.39 Protein Availability (0–15) 11.2 (1.5) 12.0 (1.9) 0.11 Note: p-values are from one-way ANOVA (F-tests) comparing stores in South Carolina to stores in other sites. Table 4 shows that checkout marketing patterns strongly favored unhealthy foods. No Lowcountry stores displayed any healthy food items at checkout, and only four stores (31%) displayed bottled water. In contrast, all Lowcountry stores (100%) marketed unhealthy snacks and sugar-sweetened beverages at checkout, closely mirroring patterns in other regions. These findings highlight consistent national trends in the prominence of ultra-processed products at points of sale (Table 4 ). Table 4 Marketing of healthy and unhealthy items at checkout by research site South Carolina (Lowcountry) (N = 13) Other Sites (N = 202) N (%) N (%) p-value At least one healthy item marketed at checkout 0 (0%) 7 (3.5%) 0.50 Fresh produce marketed at checkout 0 (0%) 7 (3.5%) 0.50 Frozen produce marketed at checkout 0 (0%) 1 (0.5%) 0.80 Canned goods marketed at checkout 0 (0%) 0 (0%) At least one unhealthy food marketed at checkout 13 (100%) 195 (97%) 0.50 Salty snacks marketed at checkout 12 (92%) 181 (90%) 0.76 Sweet snacks marketed at checkout 13 (100%) 195 (97%) 0.50 Water marketed at checkout 4 (31%) 111 (55%) 0.09 Sweetened beverages marketed at checkout 13 (100%) 189 (94%) 0.35 Note: p-values are from chi-square tests comparing stores in South Carolina to stores in other sites. Table 5 presents the frequency with which selected food and beverage items were visible from the front entrance. In the Lowcountry, only three stores (23%) had at least one healthy food and bottled water visible from the entrance, while 12 stores (92%) had at least one unhealthy food and a sugar-sweetened beverage visible from the entrance. Visibility patterns were similar in other regions, underscoring consistent reinforcement of unhealthy options upon store entry (Table 5 ). Table 5 Visibility of healthy and unhealthy items from front entrance by research site South Carolina (Lowcountry)(N = 13) Other Sites (N = 202) N (%) N (%) p-value At least one healthy food visible at entrance 3 (23%) 30 (15%) 0.43 Fresh produce visible at entrance 2 (15%) 23 (11%) 0.67 Frozen produce visible at entrance 2 (15%) 22 (11%) 0.62 Canned goods visible at entrance 1 (8%) 25 (12%) 0.62 At least one unhealthy food visible at entrance 12 (92%) 174 (86%) 0.53 Salty snacks visible at entrance 12 (92%) 159 (79%) 0.24 Sweet snacks visible at entrance 12 (92%) 172 (85%) 0.48 Water visible at entrance 3 (23%) 94 (47%) 0.10 Sweetened beverages visible at entrance 12 (92%) 150 (74%) 0.15 Note: p-values are from chi-square tests comparing stores in South Carolina to stores in other sites. The measurements of shelf space allocated to different food and beverage categories are displayed in Table 6 . On average, stores in the Lowcountry have 34 feet (SD = 27 feet) of shelf space stocking healthy food items, including fresh, frozen, and canned fruits and vegetables, while they have an average of 507 feet (SD = 379 feet) of shelf space stocking unhealthy packaged snacks. The average store’s healthy food shelf space is only 12% (SD = 13 percentage points) of that allocated to unhealthy food items. Shelf space for beverages is also heavily weighted toward unhealthy sugar sweetened beverages: stores have a mean of 29 feet (SD = 22 feet) of shelf space for water and 221 feet (SD = 174 feet) of shelf space for sugar sweetened beverages, and the average store devotes approximately one-fifth as much shelf space to water as it does to sugar-sweetened-beverages (s 21%, SD = 27 percentage points) (Table 6 ). Table 6 Shelf space of healthy and unhealthy items by research site South Carolina (Lowcountry) (N = 13) Other Sites (N = 202) Mean (SD) Mean (SD) p-value Total Healthy Food Shelf Space (feet) 34.3 (26.6) 35.7 (31.6) 0.88 Fresh Fruit 4.9 (8.5) 2.1 (7.7) 0.20 Fresh Vegetables 7.1 (12.2) 2.2 (8.2) 0.04 Frozen Fruit 1.7 (3.7) 2.0 (3.4) 0.78 Frozen Vegetables 5.1 (5.6) 4.8 (5.3) 0.83 Canned Fruit 3.9 (4.4) 10.3 (10.8) 0.03 Canned Vegetables 11.6 (6.6) 14.3 (14.2) 0.49 Total Unhealthy Food Shelf Space (feet) 507 (379) 352 (296) 0.07 Salty Snacks 251 (192) 156 (140) 0.02 Sweet Snacks 256 (188) 196 (168) 0.22 Healthy Food Shelf Space as Percent of Unhealthy Food Shelf Space 12.0 (13.1) 22.2 (46.3) 0.43 Water Shelf Space (feet) 29.2 (22.3) 35.2 (32.2) 0.51 Sweetened Beverages Shelf Space (feet) 221 (174) 161 (174) 0.23 Healthy Beverage Shelf Space as Percent Unhealthy Beverage Shelf Space 21.5 (27.4) 36.5 (50.4) 0.29 Note: p-values are from one-way ANOVA (F-tests) comparing stores in South Carolina to stores in other sites. Discussion This study provides one of the first comprehensive assessments of the nutrition environments and WIC readiness of dollar stores in rural, high-deprivation communities of the Lowcountry, SC, using the newly developed NEMS-DS tool [ 53 , 55 ]. By comparing 13 rural stores with 202 dollar stores across 10 states, this study highlights structural barriers to healthy food access within a rapidly expanding retail sector that plays an increasingly central role in community nutrition access in low income rural communities [ 63 – 65 ]. Across all domains—availability, visibility, marketing, and shelf-space allocation—Lowcountry dollar stores reflected a food environment with limited availability of nutritious foods and dominant placement of ultra-processed products, consistent with prior research. Although there was slightly higher availability of fresh produce in some Lowcountry stores_ likely due to Dollar General’s fresh initiatives_ these offerings remained insufficient to counter less-healthful options [ 66 ]. Overall, healthy items accounted for only a small fraction of total shelf space, and unhealthy snacks and sugar-sweetened beverages dominated checkout and entrances displays, patterns known to influence impulse purchasing and dietary behaviors [ 67 – 68 ]. WIC readiness scores were low in both the Lowcountry and comparison sites, indicating that many key WIC food groups, such as fruits, vegetables, and whole grains, remain scarce [ 69 – 70 ]. Although protein items were more available, overall readiness profiles suggest that substantial improvements are needed for dollar stores to meet WIC standards. Given that dollar stores accept SNAP but often not qualify as WIC vendors, this low WIC readiness represents a missed opportunity to improve access to nutrient-dense foods for low-income mothers and children in rural communities [ 71 – 74 ]. The low rate of WIC participation in SC (1.9% in 2024) could also reflect limited access to WIC-authorized stores for redeeming this benefit [ 75 ]. The structural barriers observed in Lowcountry dollar stores have essential implications for nutrition equity. Policy strategies that support stocking healthier and WIC-authorized items in discount stores_ procurement partnerships_ or expand WIC vendor authorization to include dollar stores could enhance equitable access to nutritious foods in rural food deserts. Some studies show effective results employing similar interventions in increasing the availability and access to nutritious products in small urban stores [ 73 – 74 , 76 ]. From a practice standpoint and given the rising number of these stores in remote and rural regions, this study underscores the importance of providing policymakers and public health practitioners with a tool —NEMS-DS —to measure food access challenges within dollar stores (e.g., limited healthy food availability and marketing of unhealthy items at checkouts), enabling the development of tailored interventions and policies with sustainable outcomes [ 73 – 74 , 76 ]. Partnerships with local distributors or farmers that could increase access to nutritious foods by expanding the availability of fresh and culturally relevant produce. These multilevel strategies are consistent with the Community Nutrition Environment and Social-Ecological Models, which emphasize the role of structural and environmental determinants in shaping dietary behavior [ 56 – 57 ]. This study has several strengths, including the use of a validated dollar-store-specific assessment tool, a multisite comparative design, and detailed measures of shelf space, marketing, and visibility. These metrics go beyond typical food environment assessments and provide high-resolution insight into rural nutritional landscapes. Limitations include the small Lowcountry sample, although they represent most operational rural dollar stores in the region. However, the small sample size in the Lowcountry limits our ability to examine variation in the nutritional environment of dollar stores across counties or store types. The NEMS-DS tool is relatively narrow in its measurement of the marketing, visibility, and shelf space of healthy and unhealthy food items, focusing only on produce and packaged snacks. However, many other items could be considered healthy (e.g., proteins and dairy) or unhealthy (e.g., sugar-sweetened cereals). Additionally, this study does not capture transportation barriers, proximity to dollar stores, active community food programs, regional economic conditions, household food preparation capacity, or consumer purchasing behavior—all important determinants of diet quality [ 10 , 26 , 77 – 78 ]. There is also potential measurement error throughout the assessment tool, particularly in the shelf space measures, which relied on a mobile application to estimate shelf space from the mobile phone camera. Technical issues with this measurement application may have also contributed to the relatively high frequency of missing data on shelf-space measures. The present findings advance understanding of how the food environments of dollar stores in rural Lowcountry, SC, may influence access to nutritious foods. Future work could also explore whether corporate commitment to healthier stocking could be translated into sustainable improvements in access to nutritious foods and tracking progress toward becoming a WIC vendor, particularly in rural regions. Finally, integrating NEMS-DS data with sales and qualitative inquiry on consumer behavior could provide a more complete picture of how dollar stores’ food environments could impact diet-related health outcomes in rural settings. Conclusion This study provides one of the first comprehensive assessments of the food environments of rural dollar stores in the Lowcountry of South Carolina using the NEMS-DS tool. The findings show limited availability of nutritious foods, low WIC readiness, and strong promotion of ultra-processed snacks and beverages, reflecting broader inequities in high-poverty rural communities. The study provides evidence for the literature on rural food environments and demonstrates the value of the NEMS-DS for evaluating healthy food access in discount stores. Multi-level strategies—such as policy incentives to expand WIC vendor authorization, more nutritious product placement standards, and strengthened community partnerships—may help improve the nutritional profile of these stores. Enhancing the availability of healthy food in dollar stores offers a promising opportunity to advance food justice and reduce diet-related health disparities in rural areas. Abbreviations ADI: Area Deprivation Index ANOVA: Analysis of Variance BMI: Body Mass Index CNE: Community Nutrition Environment HFA; Health Food Availability IRB: Institutional Review Board NEMS-DS: Nutrition Environment Measure Survey-Dollar Stores NEMS-S: Nutrition Environment Measure Survey-Stores SC: South Carolina SD: Standard Deviation SEM: Social Ecological Model SNAP: Supplemental Nutrition Assistance Program U.S: United States WIC: Women, Infant, Children program Declarations Ethics approval and consent to participate In this study, data were collected using the NEMS-DS observational tool in 13 rural dollar stores to assess the food environment. Therefore, the University of South Carolina determined that the project was exempt from IRB review. Consent to participate was not applicable. Consent for publication Not applicable. Data Availability All data supporting the findings of this study are included within this manuscript. Data from comparison sites are available upon request of the corresponding author and Dr. Rachael Dombrowski, the principal investigator of the related multi-state study. Competing interests The authors declare no competing interests Funding This project was supported by Healthy Eating Research a program of the Robert Wood Johnson Foundation. Authors’ contributions Conceptualization, writing—original draft—and formal analysis, H.D.; data curation and analysis, T.A .and H.D.; tables, T.A.; methodology, H.D.; validation, H.D., T.A.; writing—review and editing, H.D., T.A., L.I. All authors have read and agreed to the published this version of the manuscript. Acknowledgements I would like to express my sincere appreciation to Dr. Rachael Dombrowski, principal investigator of the multi-state study spanning 10 states, for her leadership, guidance, and role in securing funding for this research project. I also extend my gratitude to Mrs. Kari Hill for her contributions to data collection in South Carolina. Additionally, I acknowledge the essential contributions of the Dollar Store Research Work Group—a team of 11 researchers across multiple public health disciplines and U.S. institutions that formed in the summer of 2022. This group collaborated to develop the NEMS-DS tool. References Centers for Disease Control and Prevention. Obesity [Internet]. Atlanta (GA): CDC; [cited 2025 Nov 26]. Available from: https://www.cdc.gov/obesity/index.html Centers for Disease Control and Prevention. Diabetes Data and Statistics [Internet]. CDC. 2024 Centers for Disease Control and Prevention. Diabetes Data & Research [Internet]. Atlanta (GA): CDC; [cited 2025 Nov 26]. Available from: https://www.cdc.gov/diabetes/php/data-research/index.html Gwira JA, Fryar CD, Gu Q. Prevalence of Total, Diagnosed, and Undiagnosed Diabetes in Adults: United States, August 2021-August 2023. NCHS Data Brief. 2024;516CS354814. doi.org/10.15620/cdc/165794 . GBD 2021 US Obesity Forecasting Collaborators. National-level and state-level prevalence of overweight and obesity among children, adolescents, and adults in the USA, 1990–2021 and forecasts up to 2050. Lancet. 2024;404(10469):2278–98. doi.org/10.1016/S0140-6736(24)01548-4 . Matthews ED, Kurnat-Thoma EL. US food policy to address diet-related chronic disease. Front Public Health. 2024;12:1339859. doi.org/10.3389/fpubh.2024.1339859 . Folorunsho S, Ajayi V, Sanmori M. Household income and obesity among older adults: the moderating role of race in a longitudinal analysis. BMC Public Health doi. org/10.1186/s12889-025-22910-1 Odoms-Young A, Brown AGM, Agurs-Collins T, Glanz K. Food insecurity, neighborhood food environment, and health disparities: state of the science, research gaps and opportunities. Am J Clin Nutr. 2024;119(3):850–61. doi.org/10.1016/j.ajcnut.2023.12.019 . Emmerich SD, Fryar CD, Stierman B, Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021–August 2023. NCHS Data Brief. 2024;(508):1–8. Available from: https://www.cdc.gov/nchs/products/databriefs/db508.htm Lundeen EA, Park S, Pan L, O’Toole T, Matthews K, Blanck HM. Obesity prevalence among adults living in metropolitan and nonmetropolitan counties—United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(23):653–8. doi.org/10.15585/mmwr.mm6723a1 . Thompson C. Dietary health in the context of poverty and uncertainty around the social determinants of health. Proc Nutr Soc. 2022;81(2):134–40. doi.org/10.1017/S0029665121003657 . Liu Y, Eicher-Miller HA. Food insecurity and cardiovascular disease risk. Curr Atheroscler Rep. 2021;23(6):24. doi.org/10.1007/s11883-021-00923-6 . Centers for Disease Control and Prevention. Data & research — diabetes [Internet]. Prev Chronic Dis. 2023 [cited 2025 Nov 26]. Available from: https://www.cdc.gov/pcd/issues/2023/23_0136.htm Rural Health Information Hub. Rural obesity and weight control [Internet]. 2025 Mar 19 [cited 2025 Oct 22]. Available from: https://www.ruralhealthinfo.org/topics/obesity-and-weight-control#rural-vs-urban USDA Rural Development South Carolina State Office. South Carolina | rural development [Internet]. Columbia (SC): USDA Rural Development; [cited 2025 Nov 5]. Available from: https://www.rd.usda.gov/sc United States Census Bureau. Urban and rural [Internet]. Washington (DC): U.S. Census Bureau; [cited 2025 Nov 5]. Available from: https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html South Carolina Department of Public Health. DPH focused on reducing obesity to help S.C. residents live healthier lives [Internet]. Columbia (SC): South Carolina Department of Public Health; 2024 Sep 16 [cited 2025 Oct 18]. Available from: https://dph.sc.gov/news/dph-focused-reducing-obesity-help-sc-residents-live-healthier-lives United Health Foundation. Obesity in South Carolina [Internet]. 2024 [cited 2025 Oct 18]. Available from: https://www.americashealthrankings.org/explore/measures/Obesity/SC Johnson-Spruill I, Riegel B. The quality of diabetes care to Gullah families of South Carolina. J Natl Black Nurses Assoc. 2008;19(2):20–7. United Health Foundation. Fruit and vegetable consumption in South Carolina. America’s Health Rankings [Internet]. [cited 2025 Oct 18]. Available from: https://www.americashealthrankings.org/explore/measures/fvcombo/SC Centers for Disease Control and Prevention. South Carolina action guide on fruits and vegetables [Internet]. 2018 Sep. Available from: https://www.cdc.gov/nutrition/data-statistics/pdfs/South_Carolina_StateActionGuide_Sept2018_508.pdf American Diabetes Association. The burden of diabetes in South Carolina [Internet]. Arlington (VA): American Diabetes Association; 2023 Sep [cited 2025 Oct 18]. Available from: https://diabetes.org/sites/default/files/2023-09/ADV_2023_State_Fact_sheets_all_rev_South_Carolina.pdf South Carolina Department of Health and Environmental Control. South Carolina state health assessment [Internet]. Columbia (SC): South Carolina Department of Health and Environmental Control. 2023 Dec. Available from: https://dph.sc.gov/sites/scdph/files/media/document/New%20PDFs/SHA-Report-20240521.pdf Sallis JF, Glanz K. Physical activity and food environments: solutions to the obesity epidemic. Milbank Q. 2009;87(1):123–54. doi.org/10.1111/j.1468-0009.2009.00550.x . Madlala SS, Hill J, Kunneke E, Lopes T, Faber M. Adult food choices in association with the local retail food environment and food access in resource-poor communities: a scoping review. BMC Public Health. 2023. 23:1083.doi.org/10.1186/s12889-023-15996-y . Xin J, Zhao L, Wu T, Zhang L, Li Y, Xue H, Xiao Q, Wang R, Xu P, Visscher T, Ma X, Jia P. Association between access to convenience stores and childhood obesity: a systematic review. Obese Rev. 2021;22(Suppl 1):e12908. .doi.org/10.1111/obr.12908 . Atanasova P, Kusuma D, Pineda E, Frost G, Sassi F, Miraldo M. The impact of the consumer and neighborhood food environment on dietary intake and obesity-related outcomes: a systematic review of causal impact studies. Soc Sci Med. 2022. 299:114879.doi.org/10.1016/j.socscimed.2022.114879 . Herforth A, Ahmed S. The food environment, its effects on dietary consumption, and potential for measurement within agriculture–nutrition interventions. Food Sec. 2015;7:505–20. doi.org/10.1007/s12571-015-0455-8 . Okobi OE, Ajayi OO, Okobi TJ, Anaya IC, Fasehun OO, Diala CS, et al. The burden of obesity in the rural adult population of America. Cureus. 2021;13(6):e15770. doi.org/10.7759/cureus.15770 . Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System (BRFSS) [Internet]. Atlanta (GA): CDC; [cited 2025 Nov 26]. Available from: https://www.cdc.gov/brfss/index.html Ganasegeran K, Abdul Manaf MR, Waller LA, Safian N, Mohd Rizal MF, Chiew WL, et al. Impact of commercial food environments on local type 2 diabetes burden: cross-sectional and ecological multimodeling study. JMIR Public Health Surveil. 2025;11:e70045. doi.org/10.2196/70045 . Salois MJ. Obesity and diabetes, the built environment, and the ‘local’ food economy in the United States, 2007. Econ Hum Biol. 2012;10(1):35–42. doi.org/10.1016/j.ehb.2011.04.001 . Gordon-Larsen P. Food availability/convenience and obesity. Adv Nutr. 2014;5(6):809–17. https://doi.org/10.3945/an.114.007070 . Odoms-Young A, Singleton CR, Springfield S, McNabb L, Thompson T. Retail environments as a venue for obesity prevention. Curr Obes Rep. 2016;5(2):184–91. doi.org/10.1007/s13679-016-0219-6 . Marchesi K, Steinbach S, Lopez RA. Dollar store entry affects rural grocery stores more than urban. Amber Waves [Internet]. 2024 May 6. Available from: https://www.ers.usda.gov/amber-waves/2024/may/dollar-store-entry-affects-rural-grocery-stores-more-than-urban Aldrich AZ. Dollar store expansion pushes out independent grocery stores, decreases local employment opportunities. UConn Today [Internet]. 2023 Dec 14. Available from: https://today.uconn.edu/2023/12/dollar-store-expansion-pushes-out-independent-grocery-stores-decreases-local-employment-opportunities/ Feng W, Page ET, Cash SB. Dollar stores and food access for rural households in the United States, 2008–2020. Am J Public Health. 2023;113(3):e1–e9. doi:10.2105/AJPH.2022.307193. Available from: https://ajph.aphapublications.org/doi/full/ 10.2105/AJPH.2022.307193 Patel V. Dollar store food shopping isn’t derailing American diets: study. ABC News [Internet]. 2025 Aug 11 [cited 2025 Oct 18]. Available from: https://abcnews.go.com/Health/dollar-store-food-shopping-derailing-american-diets-study/story Feng W, Fromkin H, Harney JB, Evans R, Gerrity CM, Cash SB. Perspective: food access at dollar stores and its implications for public health—report of a workshop on identifying research priorities. Adv Nutr. 2024;15:100319. https://doi.org/10.1016/j.advnut.2024.100319 . Feng W, Cash S, Page ET. Dollar stores are growing as food retailers in the U.S. Tufts University School of Medicine News [Internet]. 2023 Jan 19. Available from: https://medicine.tufts.edu/news-events/news/dollar-stores-are-growing-food-retailers-us Reimold AE, Hall MG, Ng SW, Taillie LS, Ribisl KM, Charles EL, et al. The Dollar Store Got It Going On: understanding food shopping patterns and policy preferences among dollar store shoppers with low incomes. Curr Dev Nutr. 2024;8(10):104457. https://doi.org/10.1016/j.cdnut.2024.104457 . University of New Mexico, Department of Economics. Food security report 2025 [Internet]. Albuquerque (NM): University of New Mexico, Department of Economics; 2025 [cited 2025 Nov 26]. Available from: https://econ.unm.edu/what-we-do/research/food-security-report-2025-final.pdf Sundermeir SM, Matsuzaki M, Zhang A, Obi JC, Gittelsohn J, Winkler MR. Characterizing the consumer food environment of dollar stores and exploring differences by neighborhood racial composition. J Nutr Educ Behav. 2025;57(10):972–9. doi.org/10.1016/j.jneb.2025.06.007 . Epub 2025 Jul 12. PMID: 40650649; PMCID: PMC12313204. Sarkar C, Webster C, Gallacher J. Are exposures to ready-to-eat food environments associated with type 2 diabetes? A cross-sectional study of 347,551 UK Biobank adult participants. Lancet Planet Health. 2018;2(10):e438–50. 10.1016/S2542-5196(18)30208-0 . Carey L, Investigate Midwest. Study: dollar stores’ entry into rural communities adds to rural grocery challenges [Internet]. ; 2024 Jul 2 [cited 2025 Nov 1]. Available from: https://investigatemidwest.org/2024/07/02/study-dollar-stores-entry-into-rural-communities-adds-to-rural-grocery-challenges AAccordino J, Conte AW. Planning food and place: navigating dollar stores to improve healthy food access. J Am Plan Assoc. 2024;90(2):193–212. doi.org/10.1080/01944363.2023.2214117 . Chenarides L, Cho C, Nayga RM Jr, Thomsen MR. Dollar stores and food deserts. Appl Geogr. 2021;134:102497. doi.org/10.1016/j.apgeog.2021.102497 . Caoui EH, Hollenbeck B, Osborne M. The impact of dollar store expansion on local market structure and food access [Internet]. Toronto (ON): University of Toronto; 2024 Jun 3 [cited 2025 Nov 1]. Available from: https://www.anderson.ucla.edu/sites/default/files/document/2024-09/caoui_hollenbeck_osborne_dollar_stores_food_access.pdf Momtahan M. Maintaining resilience among local food systems: the effects of COVID-19 on the food system in Lowcountry South Carolina [thesis]. Columbia (SC): University of Charleston, South Carolina; 2021. Available from: https://search.proquest.com/openview/4b374f007650397d5f3cee967f18c903/1.pdf U.S. Department of Agriculture, Economic Research Service. Key statistics & graphics — food security in the U.S. [Internet]. 2025 Jan 8 [cited 2025 Nov 26]. Available from: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics Robert Wood Johnson Foundation, University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps [Internet]. [cited 2025 Oct 25]. Available from: https://www.countyhealthrankings.org/ Plata-Nino G. SNAP’s critical role in rural communities — and the consequences of cuts [Internet]. Food Research & Action Center; 2025 Aug 25 [cited 2025 Nov 1]. Available from: https://frac.org/blog/snaps-critical-role-in-rural-communities-and-the-consequences-of-cuts USAFacts. How many people receive SNAP benefits in South Carolina every month? [Internet]. [place unknown]: USAFacts; 2024 [cited 2025 Nov 10]. Available from: https://usafacts.org/answers/how-many-people-receive-snap-benefits-in-the-us-every-month/state/south-carolina/ Kasprzak C, Sundermeir S, Bode B, Gittelsohn J, Singleton C, Kaur R, Hadis D, Racine E, Dombrowski R. The development of a tool to assess dollar store food environments and WIC readiness: the NEMS-DS. J Nutr Educ Behav. Forthcoming. Glanz K, Sallis JF, Saelens BE, Frank LD. Nutrition Environment Measures Survey in stores (NEMS-S): development and evaluation. Am J Prev Med. 2007;32(4):282–9. https://doi.org/10.1016/j.amepre.2006.12.019 . Dombrowski RD, Sundermeir SM, Andrasfay T, Bode B, Kasprzak C, Dastgerdizad H, et al. Assessment of dollar store food environments and their readiness to become WIC vendors. Manuscript submitted for publication; 2025. Glanz K, Sallis JF, Saelens BE, Frank LD. Healthy nutrition environments: concepts and measures. Am J Health Promot. 2005;19(5):330–2. doi.org/10.4278/0890-1171-19.5.330 . Bronfenbrenner U. The ecology of human development: experiments by nature and design. Cambridge (MA): Harvard University Press; 1979. Kind AJH, Buckingham WR. Making neighborhood-disadvantage metrics accessible — the Neighborhood Atlas. N Engl J Med. 2018;378(26):2456–8. https://doi.org/10.1056/nejmp1802313 . University of Wisconsin School of Medicine and Public Health. Area Deprivation Index (v4.0.1) [Internet]. Madison (WI): University of Wisconsin–Madison; 2022 [cited 2025 Nov 1]. Available from: https://www.neighborhoodatlas.medicine.wisc.edu/ U.S. Census Bureau. Urban and rural [Internet]. 2024 Dec 16 [cited 2025 Nov 27]. Available from: https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html U.S. Census Bureau. American Community Survey 5-year estimates [Internet]. Washington (DC): U.S. Census Bureau; 2023 [cited 2025 Nov 1]. Available from: https://www.census.gov/programs-surveys/acs Ejlerskov KT, Stead M, Adamson A, White M, Adams J. Voluntary policies on checkout foods and healthfulness of foods displayed at, or near, supermarket checkout areas: a cross-sectional survey. Public Health Nutr. 2018;21(18):3462–70. https://doi.org/10.1017/S1368980018002501 . Stevens A, Cho C, Çakır M, Kong X, Boland M, Economic Research Service. The food retail landscape across rural America [Internet]. EIB-223. Washington (DC): U.S. Department of Agriculture, ; 2021 Jun. Available from: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics Smith K. 17 problems: how dollar store chains hurt communities [Internet]. Washington (DC): Institute for Local Self-Reliance; 2023 Feb 28 [cited 2025 Nov 27]. Available from: https://ilsr.org/article/independent-business/17-problems/ U.S. Department of Agriculture, Economic Research Service. Rural counties losing share of grocery stores, gaining other types of food retailers [Internet]. 2021 Dec 7 [cited 2025 Nov 27]. Available from: https://www.ers.usda.gov/amber-waves/2021/december/rural-counties-losing-share-of-grocery-stores-gaining-other-types-of-food-retailers Dollar General. Increasing access to fresh food [Internet]. Community Uplift Nominees. Food Marketing Institute; 2025 [cited 2025 Nov 27]. Available from: https://www.fmi.org/get-involved/community-uplift/nominees/view/dollar-general-increasing-access-to-fresh-food Feng W, Page ET, Sun B, Cash SB. The healthfulness of foods purchased at dollar stores: insights from household scanner data from 2008 to 2020. J Acad Nutr Diet. 2025;125(11):1736–e17456. https://doi.org/10.1016/j.jand.2025.07.001 . Barnes TL, Pelletier JE, Erickson DJ, Caspi CE, Harnack LJ, Laska MN. Healthfulness of foods advertised in small and nontraditional urban stores in Minneapolis–St. Paul, Minnesota, 2014. Prev Chronic Dis. 2016;13:160149. Available from: https://www.cdc.gov/pcd/issues/2016/16_0149.htm U.S. Department of Agriculture, Food and Nutrition Service. Special Supplemental Nutrition Program for Women, Infants, and Children (WIC): revisions in the WIC food packages [Internet]. Federal Register. 2024 Apr 18 [cited 2025 Nov 5]. Available from: https://www.federalregister.gov/documents/2024/04/18/2024-07437/special-supplemental-nutrition-program-for-women-infants-and-children-wic-revisions-in-the-wic-food#p-316 Tester JM, Leung CW, Crawford PB. Revised WIC food package and children’s diet quality. Pediatrics. 2016;137(5):e20153557. doi.org/10.1542/peds.2015-3557 . Whaley SE, Ritchie LD, Spector P, Gomez J. Revised WIC food package improves diets of WIC families. J Nutr Educ Behav. 2012;44(3):204–9. doi.org/10.1016/j.jneb.2011.09.011 . Vaughan CA, Collins R, Ghosh-Dastidar M, Beckman R, Dubowitz T. Does where you shop or who you are predict what you eat? The role of stores and individual characteristics in dietary intake. Prev Med. 2017;100:10–6. doi.org/10.1016/j.ypmed.2017.03.015 . Gittelsohn J, Kasprzak CM, Hill AB, Sundermeir SM, Laska MN, Dombrowski RD, DeAngelo J, Odoms-Young A, Leone LA. Increasing healthy food access for low-income communities: protocol of the Healthy Community Stores Case Study Project. BMC Public Health. 2021;21:1102. doi.org/10.3390/ijerph19020690 . Gittelsohn J, Rowan M, Gadhoke P. Interventions in small food stores to change the food environment, improve diet, and reduce risk of chronic disease. Prev Chronic Dis. 2012;9:E59. 10.3390/ijerph19020690 . United States Department of Agriculture, Food and Nutrition Service. WIC Program: Total Participation. Washington (DC): USDA Food and Nutrition Service; 2025 [cited 2025 Nov 10]. Available from: https://fns-prod.azureedge.us/sites/default/files/resource-files/26wifypart-8.pdf Odoms-Young A, Bruce MA. Examining the impact of structural racism on food insecurity: Implications for addressing racial/ethnic disparities. Fam Community Health. 2018 Apr/Jun;41 Suppl 2, Food Insecurity and Obesity(Suppl 2 FOOD INSECURITY AND OBESITY):S3–S6. doi.org/10.1097/FCH.0000000000000183 Equal Justice Initiative. One million Black families in the South have lost their farms. Montgomery, AL: Equal Justice Initiative; [cited 2025 Oct 18]. Available from: https://eji.org/news/one-million-black-families-have-lost-their-farms/ Seguin R, Connor L, Nelson M, LaCroix A, Eldridge G. Understanding barriers and facilitators to healthy eating and active living in rural communities. J Nutr Metab. 2014;2014:146502. doi.org/10.1155/2014/146502 . Additional Declarations No competing interests reported. Supplementary Files Appendixes.docx Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 18 Dec, 2025 Reviews received at journal 17 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviews received at journal 11 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers invited by journal 10 Dec, 2025 Editor invited by journal 09 Dec, 2025 Editor assigned by journal 08 Dec, 2025 Submission checks completed at journal 08 Dec, 2025 First submitted to journal 03 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8273196","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559821876,"identity":"1bf7bae7-7cf3-4984-b989-c756f7af8f8d","order_by":0,"name":"Hadis Dastgerdizad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYBACAyA+/KfChoENyDjAwMBMlBbGAzxn0kjTwnyAt+0wjE+EFnOJ5AMHJNjOR/Oxn048wFBhndhASItlz7GEAwY8t3PbeHI3HGA4k05Yi8HxHoMDCRJALQxALYxth4nQcpj/w4EDBudy2/jfArX8I0bL8R6Ggw0JB3LbJEC2NBCj5cwxg8MMB5KBWoC2JBxLNyas5Uby48+M/+xy5/fnbv7wocZalqAWVJBAmvJRMApGwSgYBbgAAGQTSOMjCFRjAAAAAElFTkSuQmCC","orcid":"","institution":"University of Miami","correspondingAuthor":true,"prefix":"","firstName":"Hadis","middleName":"","lastName":"Dastgerdizad","suffix":""},{"id":559821877,"identity":"66d48262-5472-4e04-81ec-f9fa9676a640","order_by":1,"name":"Theresa Andrasfay","email":"","orcid":"","institution":"California State University, San Marcos","correspondingAuthor":false,"prefix":"","firstName":"Theresa","middleName":"","lastName":"Andrasfay","suffix":""},{"id":559821878,"identity":"ec5878bc-5abb-4769-a939-08a5850646e7","order_by":2,"name":"Lovelyn Isiani","email":"","orcid":"","institution":"University of Miami","correspondingAuthor":false,"prefix":"","firstName":"Lovelyn","middleName":"","lastName":"Isiani","suffix":""}],"badges":[],"createdAt":"2025-12-03 18:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8273196/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8273196/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-026-27446-6","type":"published","date":"2026-04-29T15:58:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":98220095,"identity":"2ef671a5-e4cd-4946-a5ca-8c06e6e1b055","added_by":"auto","created_at":"2025-12-15 11:20:57","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171485,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptBMCPublicHealth.docx","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/67eeb5804dba62ee7a8d1f00.docx"},{"id":98433588,"identity":"52fa7f95-8c1a-4978-aaab-25da88abf8f4","added_by":"auto","created_at":"2025-12-17 16:50:55","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6930,"visible":true,"origin":"","legend":"","description":"","filename":"b43f9071376d454f938486675cf90fb9.json","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/d53d936dc00a38e8c7e161a8.json"},{"id":98433864,"identity":"c4e192c1-cf6c-481d-bd03-42a7a73984e3","added_by":"auto","created_at":"2025-12-17 16:51:11","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":121335,"visible":true,"origin":"","legend":"","description":"","filename":"Appendixes.docx","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/7a2339ca9bc32a377a125632.docx"},{"id":98433778,"identity":"e86f09d9-7e53-410f-91d8-10c0013be939","added_by":"auto","created_at":"2025-12-17 16:51:07","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":365067,"visible":true,"origin":"","legend":"","description":"","filename":"b43f9071376d454f938486675cf90fb91enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/fd584876e29b9fc1796a39eb.xml"},{"id":98220096,"identity":"4fe2f21f-dfe3-4127-8060-ea714de01121","added_by":"auto","created_at":"2025-12-15 11:20:57","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/d3c4c5c293d812df71159232.png"},{"id":98220104,"identity":"1310bba1-bd83-43e9-8b8a-b0b47d423213","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":258,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/2f089d954bd760ce40df4999.png"},{"id":98432668,"identity":"65825a0c-5205-4b95-ae3f-56b20b604d63","added_by":"auto","created_at":"2025-12-17 16:49:46","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/7d79f723e3218b298315b4d5.png"},{"id":98220099,"identity":"840847aa-4603-4897-b366-0926a1117c5e","added_by":"auto","created_at":"2025-12-15 11:20:57","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/ede241d0e2dcddebaa1a99ba.png"},{"id":98433996,"identity":"66ad6e31-6690-467c-90e4-ad0a8b3b3606","added_by":"auto","created_at":"2025-12-17 16:51:23","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/fd033c70e4076bdda7eccf1e.png"},{"id":98433825,"identity":"0495900d-d09f-46e3-92c2-619bff1345a7","added_by":"auto","created_at":"2025-12-17 16:51:09","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/9fe855a8a111ac9e735d3d36.png"},{"id":98220101,"identity":"31d05576-ae63-4d67-8f9e-19d7923829b0","added_by":"auto","created_at":"2025-12-15 11:20:57","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/382af7acdc8dd1c4739effb6.png"},{"id":98433776,"identity":"89cad948-4d9c-444b-82de-574291a15c9d","added_by":"auto","created_at":"2025-12-17 16:51:06","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":267,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/b55be5dff4ca5cd5f5d466a6.png"},{"id":98431925,"identity":"cffc09f1-c44c-4d8f-8337-54dce1619c65","added_by":"auto","created_at":"2025-12-17 16:48:38","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":258,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/949321f307a4f76e4ac127a4.png"},{"id":98432387,"identity":"4fc66ec1-9fb6-4975-8354-3ae40e50b3a3","added_by":"auto","created_at":"2025-12-17 16:49:29","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":258,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/b209cf4ffbdce84b28cae33c.png"},{"id":98431857,"identity":"2c3abfcd-f464-41ce-9516-06eef99e39b5","added_by":"auto","created_at":"2025-12-17 16:48:28","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/384fe507cfffb36a9cb6cbd0.png"},{"id":98220117,"identity":"601663b4-a093-498d-994e-c49ce1bb4bcc","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":403,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/3a5aa5ad66e9e939ad392b18.png"},{"id":98433340,"identity":"883b72ca-257d-45ea-b11d-9a12c8f4dbf5","added_by":"auto","created_at":"2025-12-17 16:50:40","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/caa31c18ca05c7844d6479d7.png"},{"id":98431950,"identity":"dd0e8e95-b22e-4e64-8a63-a4759b06d41d","added_by":"auto","created_at":"2025-12-17 16:48:42","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/eca7cce71ff1175ff1000db9.png"},{"id":98220116,"identity":"b9c82447-70e4-4f4f-bf12-68130992db12","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/b4344581ffcf0c396bdde842.png"},{"id":98432692,"identity":"69ab9107-6cd8-49b2-9034-9ddf79900cb7","added_by":"auto","created_at":"2025-12-17 16:49:48","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/c995a889949dfd7b7ce032a1.png"},{"id":98433586,"identity":"02565c80-d094-4bb7-a89e-06fb195f89b1","added_by":"auto","created_at":"2025-12-17 16:50:55","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/0c602e682a464d19f0ce8421.png"},{"id":98220111,"identity":"34fb5bc9-8f00-40f2-a339-4de6720400be","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":406,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/c142924e5df8758a68873417.png"},{"id":98220118,"identity":"5901cb5e-b988-4a04-b6b4-a189270677ca","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":403,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/0ab7be91b6a3a56c30a73259.png"},{"id":98220119,"identity":"088b0028-a596-443b-ab49-0db9a2d77d02","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":403,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/1a5fb84f498677d36499dac8.png"},{"id":98220120,"identity":"9ac0ea7d-57c8-4598-8c84-32484025b0e0","added_by":"auto","created_at":"2025-12-15 11:20:58","extension":"xml","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":372782,"visible":true,"origin":"","legend":"","description":"","filename":"b43f9071376d454f938486675cf90fb91structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/95e74522e1a5435fd7aea848.xml"},{"id":98431539,"identity":"cb38d9ad-a8d5-4b94-8647-c42efe231814","added_by":"auto","created_at":"2025-12-17 16:47:52","extension":"html","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":386211,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/21fd52e449c5e4486a9249f5.html"},{"id":108438038,"identity":"4e9d5b7e-6fd0-4877-91ba-b3c28bf50d73","added_by":"auto","created_at":"2026-05-04 16:05:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":579620,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/3798ad2e-1833-4839-8f5f-249b9e62387c.pdf"},{"id":98432672,"identity":"4e760aab-dba0-4ca1-b80d-24fc07594809","added_by":"auto","created_at":"2025-12-17 16:49:47","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":121335,"visible":true,"origin":"","legend":"","description":"","filename":"Appendixes.docx","url":"https://assets-eu.researchsquare.com/files/rs-8273196/v1/1b3f93f529a1fb3284f38ea5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) in Rural South Carolina: Assessing Nutrition Equity and WIC Readiness","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNutrition-related chronic disorders, including type II diabetes, obesity, hypertension, and cardiovascular disease, remain leading causes of preventable morbidity and mortality in the United States (U.S) [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These burdens disproportionally affect low-income, rural, and racially diverse communities, that experience limited access to affordable and nutritious foods [\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. South Carolina (SC), with a significant proportion of its land classified as rural, exemplifies these disparities, with adult obesity (36%) and diabetes (13.3%) prevalence exceeding national averages [\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18 CR19 CR20 CR21\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Such disparities underscore the need to move beyond individual behavior change and to investigate structural and environmental inequities [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eUnderstanding the characteristics of the community food environments is central to improving dietary patterns and reducing chronic disease disparities among rural communities. Dollar stores, have expanded rapidly across the rural South, serving as a significant source of food [\u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Dollar stores significantly influence dietary choices and overall nutritional behaviors in rural populations [\u003cspan additionalcitationids=\"CR35 CR36 CR37 CR38 CR39 CR40 CR41\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], yet they typically offer shelf-stable and ultra-processed foods with minimal fresh options [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In many rural areas, the entry of dollar stores often leads to the closure of local grocery stores, further reducing access to healthier food options and aggravating food insecurity [\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In the Lowcountry, high food insecurity and historical marginalization reflect deep structural inequities. [\u003cspan additionalcitationids=\"CR19 CR20 CR21\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These inequities are further compounded by recent Supplemental Nutrition Assistance Program (SNAP) benefit reductions, which may reduce support for low-income rural families and increase reliance on the Women, Infants, and Children (WIC) program [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Despite dollar stores' ubiquity in rural food landscapes and their acceptance of SNAP, they are generally ineligible to serve as WIC vendors because WIC-approved products are not widely available. This presents a critical but understudied gap as expanding WIC authorization to dollar stores could substantially increase access to healthy foods for low-income mothers and children in rural areas, yet little is known about these retailers' WIC-readiness. Most research focuses on urban and suburban food environments, creating critical gaps for rural areas such as the Lowcountry. Furthermore, prior tools such as the Nutrition Environment Measures Survey for Stores (NEMS-S), which were developed for supermarkets and small groceries, are not well-suited to dollar stores [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. These tools also do not assess dollar stores' capacity to meet WIC program standards. The newly developed Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) addresses these limitations by providing a store-format-specific tool designed to assess the availability, visibility, shelf space, and marketing of healthy and unhealthy foods in dollar stores, as well as their readiness to become WIC vendors [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].This study is grounded in the Community Nutrition Environment (CNE) and Social-Ecological Models (SEM), which highlight how structural, community, and food-environment factors shape consumer purchasing patterns and dietary behavior [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Applying these frameworks allows for an integrated assessment of environmental influences\u0026mdash;from limited healthy food placement to inadequate WIC-eligible stock\u0026mdash;that constrain consumer choice and reinforce rural nutrition inequities. No prior work has jointly assessed the nutrition environment and WIC readiness of rural Lowcountry dollar stores using a validated tool, nor has it compared them across states using standardized metrics. Filling this gap is critical for informing policies to improve healthy food access in underserved rural communities. This study aimed to 1) assess the availability, visibility, marketing, and shelf-space allocation of healthy versus unhealthy foods in 13 rural dollar stores in the Lowcountry using the NEMS-DS tool; 2) evaluate the WIC readiness of these stores; and 3) compare findings from rural Lowcountry stores to those from 202 dollar stores across 10 states, situating local conditions within broader national patterns. By generating this evidence, we aim to guide equitable food access policies and support actionable strategies to reduce diet-related risks in rural communities.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design \u0026amp; Setting\u003c/b\u003e We conducted a quantitative cross-sectional assessment of the nutrition environments of 13-dollar stores located in six rural counties of the Lowcountry—Allendale, Beaufort, Charleston, Colleton, Hampton, and Jasper counties (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These stores represent a subset of a larger multi-state parallel study that assessed 202 dollar stores across 10 U.S. states, including New York, Texas, Illinois, Florida, Maryland, Georgia, Louisiana, Michigan, Southern California, and South Carolina [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The broader study applied a standardized protocol and the NEMS-DS to evaluate availability, visibility, and marketing of healthy and unhealthy foods, as well as WIC readiness [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] (Appendix A). Dollar stores were identified through publicly available sources and verified through online searches, telephone calls, or in-person visits. For each site, stores were matched to state-level deciles of the Area Deprivation Index (ADI) and categorized as low (1–3), medium (4–6), or high (7–10) deprivation. The ADI is a composite measure of 17 socioeconomic indicators reflecting income, employment, education, housing, and household characteristics [\u003cspan additionalcitationids=\"CR59 CR60\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e–\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In the Lowcountry, stores were intentionally sampled from high-deprivation rural communities where dollar stores are more densely concentrated and where significant structural barriers to healthy food access exist. All stores included in this study were operational at the time of data collection. The University of South Carolina granted an exemption from the Institutional Review Board (IRB).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSampling Strategy\u003c/b\u003e We employed a stratified purposive-random sampling approach to ensure representation of selected stores across ADI levels in the Lowcountry while prioritizing rural and high-poverty communities. From the 28 national chain dollar stores (Dollar General, Family Dollar, Dollar Tree) identified in the Lowcountry, 13 were eligible and accessible for assessment. Stores not included were permanently closed (N = 9), temporarily inaccessible, or did not meet the inclusion criteria (N = 6). NEMS-DS assessment was conducted in sampled stores by a trained data collector between January 2024 and December 2024.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasures\u003c/b\u003e \u003cem\u003eNeighborhood and store characteristics\u003c/em\u003e We collected neighborhood-level sociodemographic characteristics for each store’s census tract or block group. Variables included the racial/ethnic composition of the census tract, the rural/urban classification based on the 2020 U.S. Census, and block group ADI deciles from the 2022 state-level ADI dataset [\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e–\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Store characteristics included chain brand, number of checkout counters, and whether SNAP benefits were accepted. Checkout count served as a proxy for customer exposure to point-of-sale marketing and store capacity [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e–\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWIC \u003cem\u003eReadiness\u003c/em\u003e The WIC Readiness score assessed the alignment of store offerings with federal WIC food package standards across six categories: fruits and vegetables (fresh and frozen/shelf-stable), fruit juice, grains, dairy and dairy substitutes, proteins, and infant foods and formula. For all non-infant items, a store received points based on the availability of different WIC-eligible varieties: 0 varieties = 0 points; 1–3 varieties = 1 point; 4–6 varieties = 2 points; 7–9 varieties = 3 points; 10–11 varieties = 4 points; 12 + varieties = 5 points. For infant items, 0 varieties = 0 points; 1–2 varieties = 3 points; 3 + varieties = 5 points. Sub-scores received an additional 2 points if at least 30% of store offerings in the category were WIC-eligible. Because subcategories contained differing numbers of items and potential varieties, the maximum potential sub-scores range from 16 points for juice to 53 points for produce. The overall WIC Readiness score ranges from 0 to 190 points. Details of score development are available elsewhere [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The score sheet is included in Appendix B. \u003cem\u003eHealthy Food Availability (HFA)\u003c/em\u003e In the original NEMS-S tool, the number of rows or shelf columns is used to count the variety of healthy food items available. The HFA score in NEMS-DS is adapted from this availability component of NEMS-S but modified to reflect the dollar-store format. For subcategories within fruits, vegetables, and juice, 0 points were awarded if there were 0 varieties available; 1 point if 1–2 varieties were available, 2 points if 3–4 varieties were available; and 3 points if at least 5 varieties were available. For subcategories within grains, dairy, and proteins, the scoring depended on the particular item. Still, 0 points were generally awarded if 0 varieties were available, 1 point if at least 1 variety was offered, and some subcategories received an additional point if at least 2 varieties were available. The total HFA score ranged from 0 to 62 points (Appendix C).\u003c/p\u003e\u003cp\u003e\u003cem\u003eMarketing and visibility of healthy and unhealthy food items\u003c/em\u003e Observers recorded whether selected healthy and unhealthy items—fresh or frozen produce, canned goods, salty snacks, sweet snacks, bottled water, and sugar-sweetened beverages—were displayed at checkout or visible from the store entrance. For each location, we also noted whether at least one healthy (fresh or frozen produce or canned goods) or at least one unhealthy item (salty or sweet snacks) was marketed or visible.\u003c/p\u003e\u003cp\u003e\u003cem\u003eShelf space for healthy and unhealthy food items\u003c/em\u003e Raters estimated the linear shelf space for several food and beverage categories in feet using a measurement app on their mobile devices. Healthy shelf space included fresh, frozen, and canned fruits and vegetables; unhealthy shelf space included packaged salty and sweet snacks. We calculated the total healthy shelf space, total unhealthy shelf space, healthy shelf space as a percentage of unhealthy shelf space, and water shelf space \u003cem\u003ea\u003c/em\u003es a percentage of sugar-sweetened beverage shelf space. If healthy and unhealthy items received equal shelf space, these values would be 100%; if healthy items received less shelf space, these values would be lower than 100%. Lower percentages indicate stronger emphasis on calorie-dense, nutrient-poor foods.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical Analysis\u003c/b\u003e We summarized neighborhood and store-level characteristics using descriptive statistics. For all nutrition environment measures—including WIC readiness, HFA scores, marketing patterns, visibility, and shelf-space allocation—we compared Lowcountry stores (N = 13) with stores from other research sites (N = 202). We conducted chi-squared tests for categorical variables and F tests for numeric variables. Analyses focused on identifying significant differences between rural Lowcountry stores and the broader sample, and on situating findings within a parallel study using NEMS-DS. This comparative approach enables interpretation of whether dollar stores in rural Lowcountry align with, exceed, or lag behind the national sample of dollar stores [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003eStore-level and neighborhood characteristics are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for the 13 Lowcountry stores, compared with 202 stores across other study sites. Most Lowcountry stores were Dollar General (62%) and were located in rural, high-deprivation areas. All Lowcountry stores were classified as rural, compared with only 9% at other sites (p \u0026lt; 0.001). Almost 23% were Family Dollar, and 15% were Dollar Tree; stores in other research sites were more evenly spread across these three brands, but the differences were not statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Five (38%) of the Lowcountry stores were located in low ADI neighborhoods, two (15%) in medium ADI neighborhoods, and six (46%) in high ADI neighborhoods; the majority (60%) of stores in other sites were located in high ADI neighborhoods, although differences in ADI level by research site were not statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Neighborhood racial compositions varied, with Lowcountry stores located in census tracts with higher percentages of Black residents and lower percentages of Hispanic residents; stores from other sites were located in tracts that had significantly larger Hispanic populations (27% on average) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All stores in the Lowcountry and 94% of stores in other sites reported accepting SNAP benefits. Stores in the Lowcountry had significantly fewer checkouts than stores at other sites (2.2 vs. 3.4, p \u0026lt; 0.001), suggesting reduced capacity and greater concentration of point-of-sale marketing.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStore-level and neighborhood characteristics by research site\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSouth Carolina (Lowcountry)\u003c/p\u003e\u003cp\u003e(N = 13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOther Sites\u003c/p\u003e\u003cp\u003e(N = 202)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eN (%) or Mean, Standard Deviation (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eN (%) or Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCounty\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHampton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJasper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllendale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharleston\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eColleton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeaufort\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStore Brand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDollar Tree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDollar General\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily Dollar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eADI level\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban/suburban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePercent non-Hispanic White\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePercent non-Hispanic Black\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePercent Hispanic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePercent non-Hispanic other races\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccept SNAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of checkouts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: p-values are from chi-square tests for categorical variables and one-way ANOVA (F-tests) for continuous variables comparing stores in South Carolina to stores in other sites.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eADI level is based on the state deciles of the Area Deprivation Index (ADI). Deciles 1–3 are categorized as low ADI, 4–6 as medium ADI, and 7–10 as high ADI.\u003c/p\u003e\u003cp\u003eWIC readiness scores were low across all stores (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Lowcountry stores had an average score of 51 out of a potential maximum of 190, similar to other sites. However, the distribution of sub-scores differed. Stores in the Lowcountry had substantially lower fruit and vegetable scores (7.3 vs. 13 out of a potential maximum of 53, p \u0026lt; 0.001), driven by limited frozen and shelf-stable produce offerings (4.3 vs. 12 out of a potential maximum of 39, p \u0026lt; 0.001). Although the Lowcountry dollar stores overall scored lower on total WIC readiness and had limited frozen shelf-stable produce, they actually had more fresh fruits and vegetables available than stores in other regions (3 vs. 0.92 out of a potential maximum of 14, p = 0.024). This reflects emerging fresh produce initiatives within some local Dollar General store chains. The remaining WIC sub-scores were generally low compared to the potential maxima and did not differ significantly between the Lowcountry and the other research sites. One notable exception is that stores in the Lowcountry had an average protein sub-score of 12, which is over 70% of the potential maximum of 17. Sub-scores for juice, grains, dairy, proteins, and infant items were uniformly low across regions, with no statistically significant differences (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWIC readiness scores by research site\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScore and potential range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSouth Carolina (Lowcountry)\u003c/p\u003e\u003cp\u003e(N = 13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOther Sites\u003c/p\u003e\u003cp\u003e(N = 202)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWIC Readiness Score (0-190)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(20.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit and Veg. Sub Score (0–53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFresh Fruit and Veg. (0–14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrozen and Shelf-Stable Fruits and Vegetables (0–39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJuice Sub Score (0–16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGrains Sub Score (0–35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDairy Sub Score (0–29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein Sub Score (0–17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfant Sub Score (0–40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: p-values are from one-way ANOVA (F-tests) comparing stores in South Carolina to stores in other sites.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the average scores on the HFA score and its sub-scores. Stores in the Lowcountry had an average score of 23 (SD = 6.4) out of a potential maximum of 62, with no significant differences in total or sub-category scores compared with other sites. As with the WIC scores, stores typically scored well below the potential maxima on each of the sub-scores, except for the protein category, in which stores in the Lowcountry scored on average 11 (SD = 1.5) out of 15. Overall, HFA scores indicate constrained access to healthy food options, regardless of store location (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHealthy food availability scores by research site\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScore and potential range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSouth Carolina (Lowcountry)\u003c/p\u003e\u003cp\u003e(N = 13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOther Sites\u003c/p\u003e\u003cp\u003e(N = 202)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthy Food Availability Score (0–62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFruit Availability (0–6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVeg Availability (0–6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJuice Availability (0–12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGrain Availability (0–10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDairy Availability (0–13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein Availability (0–15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: p-values are from one-way ANOVA (F-tests) comparing stores in South Carolina to stores in other sites.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that checkout marketing patterns strongly favored unhealthy foods. No Lowcountry stores displayed any healthy food items at checkout, and only four stores (31%) displayed bottled water. In contrast, all Lowcountry stores (100%) marketed unhealthy snacks and sugar-sweetened beverages at checkout, closely mirroring patterns in other regions. These findings highlight consistent national trends in the prominence of ultra-processed products at points of sale (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMarketing of healthy and unhealthy items at checkout by research site\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSouth Carolina (Lowcountry)\u003c/p\u003e\u003cp\u003e(N = 13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOther Sites\u003c/p\u003e\u003cp\u003e(N = 202)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAt least one healthy item marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFresh produce marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrozen produce marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCanned goods marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAt least one unhealthy food marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalty snacks marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSweet snacks marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSweetened beverages marketed at checkout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: p-values are from chi-square tests comparing stores in South Carolina to stores in other sites.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the frequency with which selected food and beverage items were visible from the front entrance. In the Lowcountry, only three stores (23%) had at least one healthy food and bottled water visible from the entrance, while 12 stores (92%) had at least one unhealthy food and a sugar-sweetened beverage visible from the entrance. Visibility patterns were similar in other regions, underscoring consistent reinforcement of unhealthy options upon store entry (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVisibility of healthy and unhealthy items from front entrance by research site\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSouth Carolina (Lowcountry)(N = 13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOther Sites\u003c/p\u003e\u003cp\u003e(N = 202)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAt least one healthy food visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFresh produce visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrozen produce visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCanned goods visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAt least one unhealthy food visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalty snacks visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSweet snacks visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSweetened beverages visible at entrance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: p-values are from chi-square tests comparing stores in South Carolina to stores in other sites.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eThe measurements of shelf space allocated to different food and beverage categories are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. On average, stores in the Lowcountry have 34 feet (SD = 27 feet) of shelf space stocking healthy food items, including fresh, frozen, and canned fruits and vegetables, while they have an average of 507 feet (SD = 379 feet) of shelf space stocking unhealthy packaged snacks. The average store’s healthy food shelf space is only 12% (SD = 13 percentage points) of that allocated to unhealthy food items. Shelf space for beverages is also heavily weighted toward unhealthy sugar sweetened beverages: stores have a mean of 29 feet (SD = 22 feet) of shelf space for water and 221 feet (SD = 174 feet) of shelf space for sugar sweetened beverages, and the average store devotes approximately one-fifth as much shelf space to water as it does to sugar-sweetened-beverages (s 21%, SD = 27 percentage points) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eShelf space of healthy and unhealthy items by research site\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSouth Carolina (Lowcountry)\u003c/p\u003e\u003cp\u003e(N = 13)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOther Sites\u003c/p\u003e\u003cp\u003e(N = 202)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Healthy Food Shelf Space (feet)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFresh Fruit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFresh Vegetables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrozen Fruit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrozen Vegetables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCanned Fruit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(4.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(10.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCanned Vegetables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(14.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Unhealthy Food Shelf Space (feet)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e507\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(379)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(296)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalty Snacks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(192)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(140)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSweet Snacks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(188)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(168)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthy Food Shelf Space as Percent of Unhealthy Food Shelf Space\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(13.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(46.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater Shelf Space (feet)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(22.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSweetened Beverages Shelf Space (feet)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(174)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(174)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthy Beverage Shelf Space as Percent Unhealthy Beverage Shelf Space\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(50.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: p-values are from one-way ANOVA (F-tests) comparing stores in South Carolina to stores in other sites.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides one of the first comprehensive assessments of the nutrition environments and WIC readiness of dollar stores in rural, high-deprivation communities of the Lowcountry, SC, using the newly developed NEMS-DS tool [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. By comparing 13 rural stores with 202 dollar stores across 10 states, this study highlights structural barriers to healthy food access within a rapidly expanding retail sector that plays an increasingly central role in community nutrition access in low income rural communities [\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e–\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Across all domains—availability, visibility, marketing, and shelf-space allocation—Lowcountry dollar stores reflected a food environment with limited availability of nutritious foods and dominant placement of ultra-processed products, consistent with prior research. Although there was slightly higher availability of fresh produce in some Lowcountry stores_ likely due to Dollar General’s fresh initiatives_ these offerings remained insufficient to counter less-healthful options [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Overall, healthy items accounted for only a small fraction of total shelf space, and unhealthy snacks and sugar-sweetened beverages dominated checkout and entrances displays, patterns known to influence impulse purchasing and dietary behaviors [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e–\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. WIC readiness scores were low in both the Lowcountry and comparison sites, indicating that many key WIC food groups, such as fruits, vegetables, and whole grains, remain scarce [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e–\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Although protein items were more available, overall readiness profiles suggest that substantial improvements are needed for dollar stores to meet WIC standards. Given that dollar stores accept SNAP but often not qualify as WIC vendors, this low WIC readiness represents a missed opportunity to improve access to nutrient-dense foods for low-income mothers and children in rural communities [\u003cspan additionalcitationids=\"CR72 CR73\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e–\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. The low rate of WIC participation in SC (1.9% in 2024) could also reflect limited access to WIC-authorized stores for redeeming this benefit [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe structural barriers observed in Lowcountry dollar stores have essential implications for nutrition equity. Policy strategies that support stocking healthier and WIC-authorized items in discount stores_ procurement partnerships_ or expand WIC vendor authorization to include dollar stores could enhance equitable access to nutritious foods in rural food deserts. Some studies show effective results employing similar interventions in increasing the availability and access to nutritious products in small urban stores [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e–\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. From a practice standpoint and given the rising number of these stores in remote and rural regions, this study underscores the importance of providing policymakers and public health practitioners with a tool —NEMS-DS —to measure food access challenges within dollar stores (e.g., limited healthy food availability and marketing of unhealthy items at checkouts), enabling the development of tailored interventions and policies with sustainable outcomes [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e–\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePartnerships with local distributors or farmers that could increase access to nutritious foods by expanding the availability of fresh and culturally relevant produce. These multilevel strategies are consistent with the Community Nutrition Environment and Social-Ecological Models, which emphasize the role of structural and environmental determinants in shaping dietary behavior [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e–\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This study has several strengths, including the use of a validated dollar-store-specific assessment tool, a multisite comparative design, and detailed measures of shelf space, marketing, and visibility. These metrics go beyond typical food environment assessments and provide high-resolution insight into rural nutritional landscapes. Limitations include the small Lowcountry sample, although they represent most operational rural dollar stores in the region. However, the small sample size in the Lowcountry limits our ability to examine variation in the nutritional environment of dollar stores across counties or store types. The NEMS-DS tool is relatively narrow in its measurement of the marketing, visibility, and shelf space of healthy and unhealthy food items, focusing only on produce and packaged snacks. However, many other items could be considered healthy (e.g., proteins and dairy) or unhealthy (e.g., sugar-sweetened cereals). Additionally, this study does not capture transportation barriers, proximity to dollar stores, active community food programs, regional economic conditions, household food preparation capacity, or consumer purchasing behavior—all important determinants of diet quality [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e–\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. There is also potential measurement error throughout the assessment tool, particularly in the shelf space measures, which relied on a mobile application to estimate shelf space from the mobile phone camera. Technical issues with this measurement application may have also contributed to the relatively high frequency of missing data on shelf-space measures. The present findings advance understanding of how the food environments of dollar stores in rural Lowcountry, SC, may influence access to nutritious foods. Future work could also explore whether corporate commitment to healthier stocking could be translated into sustainable improvements in access to nutritious foods and tracking progress toward becoming a WIC vendor, particularly in rural regions. Finally, integrating NEMS-DS data with sales and qualitative inquiry on consumer behavior could provide a more complete picture of how dollar stores’ food environments could impact diet-related health outcomes in rural settings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides one of the first comprehensive assessments of the food environments of rural dollar stores in the Lowcountry of South Carolina using the NEMS-DS tool. The findings show limited availability of nutritious foods, low WIC readiness, and strong promotion of ultra-processed snacks and beverages, reflecting broader inequities in high-poverty rural communities. The study provides evidence for the literature on rural food environments and demonstrates the value of the NEMS-DS for evaluating healthy food access in discount stores. Multi-level strategies—such as policy incentives to expand WIC vendor authorization, more nutritious product placement standards, and strengthened community partnerships—may help improve the nutritional profile of these stores. Enhancing the availability of healthy food in dollar stores offers a promising opportunity to advance food justice and reduce diet-related health disparities in rural areas.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADI: Area Deprivation Index\u003c/p\u003e\n\u003cp\u003eANOVA: Analysis of Variance\u003c/p\u003e\n\u003cp\u003eBMI: Body Mass Index\u003c/p\u003e\n\u003cp\u003eCNE: Community Nutrition Environment\u003c/p\u003e\n\u003cp\u003eHFA; Health Food Availability\u003c/p\u003e\n\u003cp\u003eIRB: Institutional Review Board\u003c/p\u003e\n\u003cp\u003eNEMS-DS: Nutrition Environment Measure Survey-Dollar Stores\u003c/p\u003e\n\u003cp\u003eNEMS-S: Nutrition Environment Measure Survey-Stores\u003c/p\u003e\n\u003cp\u003eSC: South Carolina\u003c/p\u003e\n\u003cp\u003eSD: Standard Deviation\u003c/p\u003e\n\u003cp\u003eSEM: Social Ecological Model\u003c/p\u003e\n\u003cp\u003eSNAP: Supplemental Nutrition Assistance Program\u003c/p\u003e\n\u003cp\u003eU.S: United States\u003c/p\u003e\n\u003cp\u003eWIC: Women, Infant, Children program\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003eIn this study, data were collected using the NEMS-DS observational tool in 13 rural dollar stores to assess the food environment. Therefore, the University of South Carolina determined that the project was exempt from IRB review. Consent to participate was not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003eAll data supporting the findings of this study are included within this manuscript. Data from comparison sites are available upon request of the corresponding author and Dr. Rachael Dombrowski, the principal investigator of the related multi-state study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was supported by Healthy Eating Research a program of the Robert Wood Johnson Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, writing\u0026mdash;original draft\u0026mdash;and formal analysis, H.D.; data curation and analysis, T.A .and H.D.; tables, T.A.; methodology, H.D.; validation, H.D., T.A.; writing\u0026mdash;review and editing, H.D., T.A., L.I. All authors have read and agreed to the published this version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e I would like to express my sincere appreciation to Dr. Rachael Dombrowski, principal investigator of the multi-state study spanning 10 states, for her leadership, guidance, and role in securing funding for this research project. I also extend my gratitude to Mrs. Kari Hill for her contributions to data collection in South Carolina. Additionally, I acknowledge the essential contributions of the Dollar Store Research Work Group\u0026mdash;a team of 11 researchers across multiple public health disciplines and U.S. institutions that formed in the summer of 2022. This group collaborated to develop the NEMS-DS tool.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. Obesity [Internet]. Atlanta (GA): CDC; [cited 2025 Nov 26]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/obesity/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/obesity/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. Diabetes Data and Statistics [Internet]. CDC. 2024 Centers for Disease Control and Prevention. Diabetes Data \u0026amp; Research [Internet]. Atlanta (GA): CDC; [cited 2025 Nov 26]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/diabetes/php/data-research/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/diabetes/php/data-research/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGwira JA, Fryar CD, Gu Q. Prevalence of Total, Diagnosed, and Undiagnosed Diabetes in Adults: United States, August 2021-August 2023. NCHS Data Brief. 2024;516CS354814. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.15620/cdc/165794\u003c/span\u003e\u003cspan address=\"10.15620/cdc/165794\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGBD 2021 US Obesity Forecasting Collaborators. National-level and state-level prevalence of overweight and obesity among children, adolescents, and adults in the USA, 1990\u0026ndash;2021 and forecasts up to 2050. Lancet. 2024;404(10469):2278\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/S0140-6736(24)01548-4\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(24)01548-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMatthews ED, Kurnat-Thoma EL. US food policy to address diet-related chronic disease. Front Public Health. 2024;12:1339859. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.3389/fpubh.2024.1339859\u003c/span\u003e\u003cspan address=\"10.3389/fpubh.2024.1339859\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFolorunsho S, Ajayi V, Sanmori M. Household income and obesity among older adults: the moderating role of race in a longitudinal analysis. BMC Public Health doi.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eorg/10.1186/s12889-025-22910-1\u003c/span\u003e\u003cspan address=\"10.1186/s12889-025-22910-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOdoms-Young A, Brown AGM, Agurs-Collins T, Glanz K. Food insecurity, neighborhood food environment, and health disparities: state of the science, research gaps and opportunities. Am J Clin Nutr. 2024;119(3):850\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/j.ajcnut.2023.12.019\u003c/span\u003e\u003cspan address=\"10.1016/j.ajcnut.2023.12.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEmmerich SD, Fryar CD, Stierman B, Ogden CL. Obesity and severe obesity prevalence in adults: United States, August 2021\u0026ndash;August 2023. NCHS Data Brief. 2024;(508):1\u0026ndash;8. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/products/databriefs/db508.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/products/databriefs/db508.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLundeen EA, Park S, Pan L, O\u0026rsquo;Toole T, Matthews K, Blanck HM. Obesity prevalence among adults living in metropolitan and nonmetropolitan counties\u0026mdash;United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(23):653\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.15585/mmwr.mm6723a1\u003c/span\u003e\u003cspan address=\"10.15585/mmwr.mm6723a1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThompson C. Dietary health in the context of poverty and uncertainty around the social determinants of health. Proc Nutr Soc. 2022;81(2):134\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1017/S0029665121003657\u003c/span\u003e\u003cspan address=\"10.1017/S0029665121003657\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu Y, Eicher-Miller HA. Food insecurity and cardiovascular disease risk. Curr Atheroscler Rep. 2021;23(6):24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1007/s11883-021-00923-6\u003c/span\u003e\u003cspan address=\"10.1007/s11883-021-00923-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. Data \u0026amp; research \u0026mdash; diabetes [Internet]. Prev Chronic Dis. 2023 [cited 2025 Nov 26]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/pcd/issues/2023/23_0136.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/pcd/issues/2023/23_0136.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRural Health Information Hub. Rural obesity and weight control [Internet]. 2025 Mar 19 [cited 2025 Oct 22]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ruralhealthinfo.org/topics/obesity-and-weight-control#rural-vs-urban\u003c/span\u003e\u003cspan address=\"https://www.ruralhealthinfo.org/topics/obesity-and-weight-control#rural-vs-urban\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUSDA Rural Development South Carolina State Office. South Carolina | rural development [Internet]. Columbia (SC): USDA Rural Development; [cited 2025 Nov 5]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rd.usda.gov/sc\u003c/span\u003e\u003cspan address=\"https://www.rd.usda.gov/sc\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited States Census Bureau. Urban and rural [Internet]. Washington (DC): U.S. Census Bureau; [cited 2025 Nov 5]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html\u003c/span\u003e\u003cspan address=\"https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSouth Carolina Department of Public Health. DPH focused on reducing obesity to help S.C. residents live healthier lives [Internet]. Columbia (SC): South Carolina Department of Public Health; 2024 Sep 16 [cited 2025 Oct 18]. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dph.sc.gov/news/dph-focused-reducing-obesity-help-sc-residents-live-healthier-lives\u003c/span\u003e\u003cspan address=\"https://dph.sc.gov/news/dph-focused-reducing-obesity-help-sc-residents-live-healthier-lives\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited Health Foundation. Obesity in South Carolina [Internet]. 2024 [cited 2025 Oct 18]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.americashealthrankings.org/explore/measures/Obesity/SC\u003c/span\u003e\u003cspan address=\"https://www.americashealthrankings.org/explore/measures/Obesity/SC\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJohnson-Spruill I, Riegel B. The quality of diabetes care to Gullah families of South Carolina. J Natl Black Nurses Assoc. 2008;19(2):20\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited Health Foundation. Fruit and vegetable consumption in South Carolina. America\u0026rsquo;s Health Rankings [Internet]. [cited 2025 Oct 18]. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.americashealthrankings.org/explore/measures/fvcombo/SC\u003c/span\u003e\u003cspan address=\"https://www.americashealthrankings.org/explore/measures/fvcombo/SC\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. South Carolina action guide on fruits and vegetables [Internet]. 2018 Sep. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nutrition/data-statistics/pdfs/South_Carolina_StateActionGuide_Sept2018_508.pdf\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nutrition/data-statistics/pdfs/South_Carolina_StateActionGuide_Sept2018_508.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmerican Diabetes Association. The burden of diabetes in South Carolina [Internet]. Arlington (VA): American Diabetes Association; 2023 Sep [cited 2025 Oct 18]. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diabetes.org/sites/default/files/2023-09/ADV_2023_State_Fact_sheets_all_rev_South_Carolina.pdf\u003c/span\u003e\u003cspan address=\"https://diabetes.org/sites/default/files/2023-09/ADV_2023_State_Fact_sheets_all_rev_South_Carolina.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSouth Carolina Department of Health and Environmental Control. South Carolina state health assessment [Internet]. Columbia (SC): South Carolina Department of Health and Environmental Control. 2023 Dec. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dph.sc.gov/sites/scdph/files/media/document/New%20PDFs/SHA-Report-20240521.pdf\u003c/span\u003e\u003cspan address=\"https://dph.sc.gov/sites/scdph/files/media/document/New%20PDFs/SHA-Report-20240521.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSallis JF, Glanz K. Physical activity and food environments: solutions to the obesity epidemic. Milbank Q. 2009;87(1):123\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1111/j.1468-0009.2009.00550.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1468-0009.2009.00550.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMadlala SS, Hill J, Kunneke E, Lopes T, Faber M. Adult food choices in association with the local retail food environment and food access in resource-poor communities: a scoping review. BMC Public Health. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e23:1083.doi.org/10.1186/s12889-023-15996-y\u003c/span\u003e\u003cspan address=\"23:1083.10.1186/s12889-023-15996-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXin J, Zhao L, Wu T, Zhang L, Li Y, Xue H, Xiao Q, Wang R, Xu P, Visscher T, Ma X, Jia P. Association between access to convenience stores and childhood obesity: a systematic review. Obese Rev. 2021;22(Suppl 1):e12908. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e.doi.org/10.1111/obr.12908\u003c/span\u003e\u003cspan address=\".10.1111/obr.12908\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAtanasova P, Kusuma D, Pineda E, Frost G, Sassi F, Miraldo M. The impact of the consumer and neighborhood food environment on dietary intake and obesity-related outcomes: a systematic review of causal impact studies. Soc Sci Med. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e299:114879.doi.org/10.1016/j.socscimed.2022.114879\u003c/span\u003e\u003cspan address=\"299:114879.10.1016/j.socscimed.2022.114879\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHerforth A, Ahmed S. The food environment, its effects on dietary consumption, and potential for measurement within agriculture\u0026ndash;nutrition interventions. Food Sec. 2015;7:505\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1007/s12571-015-0455-8\u003c/span\u003e\u003cspan address=\"10.1007/s12571-015-0455-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOkobi OE, Ajayi OO, Okobi TJ, Anaya IC, Fasehun OO, Diala CS, et al. The burden of obesity in the rural adult population of America. Cureus. 2021;13(6):e15770. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.7759/cureus.15770\u003c/span\u003e\u003cspan address=\"10.7759/cureus.15770\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention. Behavioral Risk Factor Surveillance System (BRFSS) [Internet]. Atlanta (GA): CDC; [cited 2025 Nov 26]. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/brfss/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/brfss/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGanasegeran K, Abdul Manaf MR, Waller LA, Safian N, Mohd Rizal MF, Chiew WL, et al. Impact of commercial food environments on local type 2 diabetes burden: cross-sectional and ecological multimodeling study. JMIR Public Health Surveil. 2025;11:e70045. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.2196/70045\u003c/span\u003e\u003cspan address=\"10.2196/70045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalois MJ. Obesity and diabetes, the built environment, and the \u0026lsquo;local\u0026rsquo; food economy in the United States, 2007. Econ Hum Biol. 2012;10(1):35\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/j.ehb.2011.04.001\u003c/span\u003e\u003cspan address=\"10.1016/j.ehb.2011.04.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGordon-Larsen P. Food availability/convenience and obesity. Adv Nutr. 2014;5(6):809\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3945/an.114.007070\u003c/span\u003e\u003cspan address=\"10.3945/an.114.007070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOdoms-Young A, Singleton CR, Springfield S, McNabb L, Thompson T. Retail environments as a venue for obesity prevention. Curr Obes Rep. 2016;5(2):184\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1007/s13679-016-0219-6\u003c/span\u003e\u003cspan address=\"10.1007/s13679-016-0219-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarchesi K, Steinbach S, Lopez RA. Dollar store entry affects rural grocery stores more than urban. Amber Waves [Internet]. 2024 May 6. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ers.usda.gov/amber-waves/2024/may/dollar-store-entry-affects-rural-grocery-stores-more-than-urban\u003c/span\u003e\u003cspan address=\"https://www.ers.usda.gov/amber-waves/2024/may/dollar-store-entry-affects-rural-grocery-stores-more-than-urban\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAldrich AZ. Dollar store expansion pushes out independent grocery stores, decreases local employment opportunities. UConn Today [Internet]. 2023 Dec 14. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://today.uconn.edu/2023/12/dollar-store-expansion-pushes-out-independent-grocery-stores-decreases-local-employment-opportunities/\u003c/span\u003e\u003cspan address=\"https://today.uconn.edu/2023/12/dollar-store-expansion-pushes-out-independent-grocery-stores-decreases-local-employment-opportunities/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng W, Page ET, Cash SB. Dollar stores and food access for rural households in the United States, 2008\u0026ndash;2020. Am J Public Health. 2023;113(3):e1\u0026ndash;e9. doi:10.2105/AJPH.2022.307193. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ajph.aphapublications.org/doi/full/\u003c/span\u003e\u003cspan address=\"https://ajph.aphapublications.org/doi/full/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2105/AJPH.2022.307193\u003c/span\u003e\u003cspan address=\"10.2105/AJPH.2022.307193\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel V. Dollar store food shopping isn\u0026rsquo;t derailing American diets: study. ABC News [Internet]. 2025 Aug 11 [cited 2025 Oct 18]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://abcnews.go.com/Health/dollar-store-food-shopping-derailing-american-diets-study/story\u003c/span\u003e\u003cspan address=\"https://abcnews.go.com/Health/dollar-store-food-shopping-derailing-american-diets-study/story\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng W, Fromkin H, Harney JB, Evans R, Gerrity CM, Cash SB. Perspective: food access at dollar stores and its implications for public health\u0026mdash;report of a workshop on identifying research priorities. Adv Nutr. 2024;15:100319. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.advnut.2024.100319\u003c/span\u003e\u003cspan address=\"10.1016/j.advnut.2024.100319\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng W, Cash S, Page ET. Dollar stores are growing as food retailers in the U.S. Tufts University School of Medicine News [Internet]. 2023 Jan 19. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://medicine.tufts.edu/news-events/news/dollar-stores-are-growing-food-retailers-us\u003c/span\u003e\u003cspan address=\"https://medicine.tufts.edu/news-events/news/dollar-stores-are-growing-food-retailers-us\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReimold AE, Hall MG, Ng SW, Taillie LS, Ribisl KM, Charles EL, et al. The Dollar Store Got It Going On: understanding food shopping patterns and policy preferences among dollar store shoppers with low incomes. Curr Dev Nutr. 2024;8(10):104457. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cdnut.2024.104457\u003c/span\u003e\u003cspan address=\"10.1016/j.cdnut.2024.104457\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUniversity of New Mexico, Department of Economics. Food security report 2025 [Internet]. Albuquerque (NM): University of New Mexico, Department of Economics; 2025 [cited 2025 Nov 26]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://econ.unm.edu/what-we-do/research/food-security-report-2025-final.pdf\u003c/span\u003e\u003cspan address=\"https://econ.unm.edu/what-we-do/research/food-security-report-2025-final.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSundermeir SM, Matsuzaki M, Zhang A, Obi JC, Gittelsohn J, Winkler MR. Characterizing the consumer food environment of dollar stores and exploring differences by neighborhood racial composition. J Nutr Educ Behav. 2025;57(10):972\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/j.jneb.2025.06.007\u003c/span\u003e\u003cspan address=\"10.1016/j.jneb.2025.06.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2025 Jul 12. PMID: 40650649; PMCID: PMC12313204.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSarkar C, Webster C, Gallacher J. Are exposures to ready-to-eat food environments associated with type 2 diabetes? A cross-sectional study of 347,551 UK Biobank adult participants. Lancet Planet Health. 2018;2(10):e438\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2542-5196(18)30208-0\u003c/span\u003e\u003cspan address=\"10.1016/S2542-5196(18)30208-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarey L, Investigate Midwest. Study: dollar stores\u0026rsquo; entry into rural communities adds to rural grocery challenges [Internet]. ; 2024 Jul 2 [cited 2025 Nov 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://investigatemidwest.org/2024/07/02/study-dollar-stores-entry-into-rural-communities-adds-to-rural-grocery-challenges\u003c/span\u003e\u003cspan address=\"https://investigatemidwest.org/2024/07/02/study-dollar-stores-entry-into-rural-communities-adds-to-rural-grocery-challenges\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAAccordino J, Conte AW. Planning food and place: navigating dollar stores to improve healthy food access. J Am Plan Assoc. 2024;90(2):193\u0026ndash;212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1080/01944363.2023.2214117\u003c/span\u003e\u003cspan address=\"10.1080/01944363.2023.2214117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChenarides L, Cho C, Nayga RM Jr, Thomsen MR. Dollar stores and food deserts. Appl Geogr. 2021;134:102497. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/j.apgeog.2021.102497\u003c/span\u003e\u003cspan address=\"10.1016/j.apgeog.2021.102497\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaoui EH, Hollenbeck B, Osborne M. The impact of dollar store expansion on local market structure and food access [Internet]. Toronto (ON): University of Toronto; 2024 Jun 3 [cited 2025 Nov 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.anderson.ucla.edu/sites/default/files/document/2024-09/caoui_hollenbeck_osborne_dollar_stores_food_access.pdf\u003c/span\u003e\u003cspan address=\"https://www.anderson.ucla.edu/sites/default/files/document/2024-09/caoui_hollenbeck_osborne_dollar_stores_food_access.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMomtahan M. Maintaining resilience among local food systems: the effects of COVID-19 on the food system in Lowcountry South Carolina [thesis]. Columbia (SC): University of Charleston, South Carolina; 2021. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://search.proquest.com/openview/4b374f007650397d5f3cee967f18c903/1.pdf\u003c/span\u003e\u003cspan address=\"https://search.proquest.com/openview/4b374f007650397d5f3cee967f18c903/1.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Department of Agriculture, Economic Research Service. Key statistics \u0026amp; graphics \u0026mdash; food security in the U.S. [Internet]. 2025 Jan 8 [cited 2025 Nov 26]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics\u003c/span\u003e\u003cspan address=\"https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRobert Wood Johnson Foundation, University of Wisconsin Population Health Institute. County Health Rankings \u0026amp; Roadmaps [Internet]. [cited 2025 Oct 25]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.countyhealthrankings.org/\u003c/span\u003e\u003cspan address=\"https://www.countyhealthrankings.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePlata-Nino G. SNAP\u0026rsquo;s critical role in rural communities \u0026mdash; and the consequences of cuts [Internet]. Food Research \u0026amp; Action Center; 2025 Aug 25 [cited 2025 Nov 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://frac.org/blog/snaps-critical-role-in-rural-communities-and-the-consequences-of-cuts\u003c/span\u003e\u003cspan address=\"https://frac.org/blog/snaps-critical-role-in-rural-communities-and-the-consequences-of-cuts\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUSAFacts. How many people receive SNAP benefits in South Carolina every month? [Internet]. [place unknown]: USAFacts; 2024 [cited 2025 Nov 10]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://usafacts.org/answers/how-many-people-receive-snap-benefits-in-the-us-every-month/state/south-carolina/\u003c/span\u003e\u003cspan address=\"https://usafacts.org/answers/how-many-people-receive-snap-benefits-in-the-us-every-month/state/south-carolina/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKasprzak C, Sundermeir S, Bode B, Gittelsohn J, Singleton C, Kaur R, Hadis D, Racine E, Dombrowski R. The development of a tool to assess dollar store food environments and WIC readiness: the NEMS-DS. J Nutr Educ Behav. Forthcoming.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlanz K, Sallis JF, Saelens BE, Frank LD. Nutrition Environment Measures Survey in stores (NEMS-S): development and evaluation. Am J Prev Med. 2007;32(4):282\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.amepre.2006.12.019\u003c/span\u003e\u003cspan address=\"10.1016/j.amepre.2006.12.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDombrowski RD, Sundermeir SM, Andrasfay T, Bode B, Kasprzak C, Dastgerdizad H, et al. Assessment of dollar store food environments and their readiness to become WIC vendors. Manuscript submitted for publication; 2025.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlanz K, Sallis JF, Saelens BE, Frank LD. Healthy nutrition environments: concepts and measures. Am J Health Promot. 2005;19(5):330\u0026ndash;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.4278/0890-1171-19.5.330\u003c/span\u003e\u003cspan address=\"10.4278/0890-1171-19.5.330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBronfenbrenner U. The ecology of human development: experiments by nature and design. Cambridge (MA): Harvard University Press; 1979.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKind AJH, Buckingham WR. Making neighborhood-disadvantage metrics accessible \u0026mdash; the Neighborhood Atlas. N Engl J Med. 2018;378(26):2456\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1056/nejmp1802313\u003c/span\u003e\u003cspan address=\"10.1056/nejmp1802313\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUniversity of Wisconsin School of Medicine and Public Health. Area Deprivation Index (v4.0.1) [Internet]. Madison (WI): University of Wisconsin\u0026ndash;Madison; 2022 [cited 2025 Nov 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.neighborhoodatlas.medicine.wisc.edu/\u003c/span\u003e\u003cspan address=\"https://www.neighborhoodatlas.medicine.wisc.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Census Bureau. Urban and rural [Internet]. 2024 Dec 16 [cited 2025 Nov 27]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html\u003c/span\u003e\u003cspan address=\"https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Census Bureau. American Community Survey 5-year estimates [Internet]. Washington (DC): U.S. Census Bureau; 2023 [cited 2025 Nov 1]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.census.gov/programs-surveys/acs\u003c/span\u003e\u003cspan address=\"https://www.census.gov/programs-surveys/acs\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEjlerskov KT, Stead M, Adamson A, White M, Adams J. Voluntary policies on checkout foods and healthfulness of foods displayed at, or near, supermarket checkout areas: a cross-sectional survey. Public Health Nutr. 2018;21(18):3462\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S1368980018002501\u003c/span\u003e\u003cspan address=\"10.1017/S1368980018002501\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStevens A, Cho C, \u0026Ccedil;akır M, Kong X, Boland M, Economic Research Service. The food retail landscape across rural America [Internet]. EIB-223. Washington (DC): U.S. Department of Agriculture, ; 2021 Jun. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics\u003c/span\u003e\u003cspan address=\"https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmith K. 17 problems: how dollar store chains hurt communities [Internet]. Washington (DC): Institute for Local Self-Reliance; 2023 Feb 28 [cited 2025 Nov 27]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ilsr.org/article/independent-business/17-problems/\u003c/span\u003e\u003cspan address=\"https://ilsr.org/article/independent-business/17-problems/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Department of Agriculture, Economic Research Service. Rural counties losing share of grocery stores, gaining other types of food retailers [Internet]. 2021 Dec 7 [cited 2025 Nov 27]. Available from:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ers.usda.gov/amber-waves/2021/december/rural-counties-losing-share-of-grocery-stores-gaining-other-types-of-food-retailers\u003c/span\u003e\u003cspan address=\"https://www.ers.usda.gov/amber-waves/2021/december/rural-counties-losing-share-of-grocery-stores-gaining-other-types-of-food-retailers\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDollar General. Increasing access to fresh food [Internet]. Community Uplift Nominees. Food Marketing Institute; 2025 [cited 2025 Nov 27]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fmi.org/get-involved/community-uplift/nominees/view/dollar-general-increasing-access-to-fresh-food\u003c/span\u003e\u003cspan address=\"https://www.fmi.org/get-involved/community-uplift/nominees/view/dollar-general-increasing-access-to-fresh-food\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng W, Page ET, Sun B, Cash SB. The healthfulness of foods purchased at dollar stores: insights from household scanner data from 2008 to 2020. J Acad Nutr Diet. 2025;125(11):1736\u0026ndash;e17456. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jand.2025.07.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jand.2025.07.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarnes TL, Pelletier JE, Erickson DJ, Caspi CE, Harnack LJ, Laska MN. Healthfulness of foods advertised in small and nontraditional urban stores in Minneapolis\u0026ndash;St. Paul, Minnesota, 2014. Prev Chronic Dis. 2016;13:160149. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/pcd/issues/2016/16_0149.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/pcd/issues/2016/16_0149.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eU.S. Department of Agriculture, Food and Nutrition Service. Special Supplemental Nutrition Program for Women, Infants, and Children (WIC): revisions in the WIC food packages [Internet]. Federal Register. 2024 Apr 18 [cited 2025 Nov 5]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.federalregister.gov/documents/2024/04/18/2024-07437/special-supplemental-nutrition-program-for-women-infants-and-children-wic-revisions-in-the-wic-food#p-316\u003c/span\u003e\u003cspan address=\"https://www.federalregister.gov/documents/2024/04/18/2024-07437/special-supplemental-nutrition-program-for-women-infants-and-children-wic-revisions-in-the-wic-food#p-316\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTester JM, Leung CW, Crawford PB. Revised WIC food package and children\u0026rsquo;s diet quality. Pediatrics. 2016;137(5):e20153557. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1542/peds.2015-3557\u003c/span\u003e\u003cspan address=\"10.1542/peds.2015-3557\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhaley SE, Ritchie LD, Spector P, Gomez J. Revised WIC food package improves diets of WIC families. J Nutr Educ Behav. 2012;44(3):204\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/j.jneb.2011.09.011\u003c/span\u003e\u003cspan address=\"10.1016/j.jneb.2011.09.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVaughan CA, Collins R, Ghosh-Dastidar M, Beckman R, Dubowitz T. Does where you shop or who you are predict what you eat? The role of stores and individual characteristics in dietary intake. Prev Med. 2017;100:10\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1016/j.ypmed.2017.03.015\u003c/span\u003e\u003cspan address=\"10.1016/j.ypmed.2017.03.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGittelsohn J, Kasprzak CM, Hill AB, Sundermeir SM, Laska MN, Dombrowski RD, DeAngelo J, Odoms-Young A, Leone LA. Increasing healthy food access for low-income communities: protocol of the Healthy Community Stores Case Study Project. BMC Public Health. 2021;21:1102. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.3390/ijerph19020690\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19020690\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGittelsohn J, Rowan M, Gadhoke P. Interventions in small food stores to change the food environment, improve diet, and reduce risk of chronic disease. Prev Chronic Dis. 2012;9:E59. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph19020690\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19020690\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUnited States Department of Agriculture, Food and Nutrition Service. WIC Program: Total Participation. Washington (DC): USDA Food and Nutrition Service; 2025 [cited 2025 Nov 10]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://fns-prod.azureedge.us/sites/default/files/resource-files/26wifypart-8.pdf\u003c/span\u003e\u003cspan address=\"https://fns-prod.azureedge.us/sites/default/files/resource-files/26wifypart-8.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOdoms-Young A, Bruce MA. Examining the impact of structural racism on food insecurity: Implications for addressing racial/ethnic disparities. Fam Community Health. 2018 Apr/Jun;41 Suppl 2, Food Insecurity and Obesity(Suppl 2 FOOD INSECURITY AND OBESITY):S3\u0026ndash;S6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1097/FCH.0000000000000183\u003c/span\u003e\u003cspan address=\"10.1097/FCH.0000000000000183\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEqual Justice Initiative. One million Black families in the South have lost their farms. Montgomery, AL: Equal Justice Initiative; [cited 2025 Oct 18]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://eji.org/news/one-million-black-families-have-lost-their-farms/\u003c/span\u003e\u003cspan address=\"https://eji.org/news/one-million-black-families-have-lost-their-farms/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeguin R, Connor L, Nelson M, LaCroix A, Eldridge G. Understanding barriers and facilitators to healthy eating and active living in rural communities. J Nutr Metab. 2014;2014:146502. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.1155/2014/146502\u003c/span\u003e\u003cspan address=\"10.1155/2014/146502\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"WIC readiness, Rural food environment, High-deprivation areas, Nutrition equity, Nutrition environment measures survey for dollar stores","lastPublishedDoi":"10.21203/rs.3.rs-8273196/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8273196/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eRural areas in the southern United States (U.S) experience a disproportionate burden of diet-related disorders, driven by limited access to nutritious and affordable foods. Dollar stores have rapidly grown in these regions \u0026mdash;including South Carolina\u0026rsquo;s Lowcountry\u0026mdash;often replacing traditional grocery stores and shaping residents\u0026rsquo; nutritional behavior. However, their food environment and their readiness to serve as vendors for the Women, Infants, and Children (WIC) nutrition program remain under-examined. This study addressed this gap using a newly developed Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS), which captures dimensions overlooked by previous assessment tools, particularly given dollar stores\u0026rsquo; reliance on shelf-stable and ultra-processed foods.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA quantitative, cross-sectional study was conducted in 13-dollar stores across six rural counties in the Lowcountry. All stores were located in rural, high-deprivation areas identified through the Area Deprivation Index (ADI). Food environments of sampled stores were assessed across three domains: (1) Healthy Food Availability (HFA); (2) WIC Readiness; and (3) marketing of healthy versus unhealthy items (e.g., shelf-space allocation). Descriptive statistics, F-tests, and χ\u0026sup2;-tests were employed to compare Lowcountry stores with 202-dollar stores from a parallel multi-state assessment.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eLowcountry\u0026rsquo;s stores demonstrated limited HFA scores (mean 23 out of a possible 62) and low WIC readiness (mean 51 out of a possible 190). Stores allocated only 12% of the total shelf space to healthy items. None marketed healthy foods at checkout, whereas 100% promoted sugar-sweetened beverages and ultra-processed snacks\u0026mdash;patterns consistent with stores in other regions. Although fresh produce availability was slightly higher in the Lowcountry than in a sample of different states, frozen and shelf-stable produce availability was significantly lower.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eDollar stores in the Lowcountry mirrored national patterns of heavy reliance on ultra-processed foods, reinforcing unhealthy food environments in rural high-poverty settings. Findings provide a policy-actionable framework for expanding WIC vendor eligibility to dollar stores, incentivizing healthy product placement, and regulating marketing to improve nutritional behavior, promote equitable access to nutritious foods, and prevent diet-related chronic disease in rural communities.\u003c/p\u003e","manuscriptTitle":"A Nutrition Environment Measures Survey for Dollar Stores (NEMS-DS) in Rural South Carolina: Assessing Nutrition Equity and WIC Readiness","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 11:20:47","doi":"10.21203/rs.3.rs-8273196/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-19T03:51:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T21:51:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23187455306286496350346124980163625665","date":"2025-12-12T16:58:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-11T15:03:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38526490643861741128698338295328888979","date":"2025-12-10T22:29:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81104834212321198742570513836407372441","date":"2025-12-10T14:26:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54484139794066895130439268193391525715","date":"2025-12-10T11:50:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-10T06:52:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T06:44:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T05:05:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-08T05:05:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-12-03T18:39:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1afbd5a-93d6-448a-bcf9-d5c955ef2436","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:05:39+00:00","versionOfRecord":{"articleIdentity":"rs-8273196","link":"https://doi.org/10.1186/s12889-026-27446-6","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2026-04-29 15:58:10","publishedOnDateReadable":"April 29th, 2026"},"versionCreatedAt":"2025-12-15 11:20:47","video":"","vorDoi":"10.1186/s12889-026-27446-6","vorDoiUrl":"https://doi.org/10.1186/s12889-026-27446-6","workflowStages":[]},"version":"v1","identity":"rs-8273196","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8273196","identity":"rs-8273196","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}