Association Between the Retail Food Environment, Neighborhood Deprivation, and County-Level Dietary Outcomes Among Supplemental Nutrition Assistance Program–Education (SNAP-Ed) Recipients in Kentucky, 2010–2011

Gustafson, Alison; Lewis, Sarah; Perkins, Sarah; Damewood, Melissa; Buckner, Elizabeth; Vail, Ann; Mullins, Janet; Jilcott-Pitts, Stephanie

doi:10.1080/19320248.2013.816993

Cited by 7 publications

(4 citation statements)

References 44 publications

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“…Furthermore, Dun & Bradstreet is the only data source that provides comparable data across the U.S. and historically to 1992, so combining multiple data sources [ 70 ] was not possible. In the absence of high quality empirical data quantifying error in commercial resource databases historically and across diverse metropolitan areas, we did not apply a correction factor as performed in previous neighborhood studies [ 72 ]. Parcel-level data needed to measure land use mix [ 6 – 8 ], an important aspect of walkability, were not collected for this study.…”

Section: Discussionmentioning

confidence: 99%

The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study

et al. 2013

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BackgroundRecent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood. Methods and FindingsWe used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25th to 75th percentile) predicted inter-exam reduction in BMI of 0.09 kg/m2 [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m2 in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m2 in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.ConclusionsFindings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.

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Section: Discussionmentioning

confidence: 99%

The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study

et al. 2013

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“…Improving dietary intake among rural and lower-income populations is a national priority. At the individual level of dietary intake, a host of proximal and distal factors influence purchasing habits and thus what is consumed [ 1 , 2 , 3 ]. Specifically, among lower-income and rural communities, there is strong evidence to suggest that these neighborhoods often lack access to supercenters which constrains residents’ purchasing ability of affordable healthier food items [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

The Impact of a Grocery Store Closure in One Rural Highly Obese Appalachian Community on Shopping Behavior and Dietary Intake

Gillespie

DeWitt

Slone

et al. 2022

IJERPH

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Research has examined how the entry of grocery stores into neighborhoods influences dietary outcomes, yet limited evidence suggests a direct correlation between opening a store and changes in dietary intake. A factor that might influence individuals’ behavior more directly is the closing of a grocery store where residents shop. This study aims to examine how a grocery closure in a rural Appalachian high poverty county is associated with dietary intake. A cohort of n = 152 individuals were recruited to participate in a longitudinal study examining purchasing habits and dietary intake. At time point two, one year later, n = 74 individuals completed the survey via phone. Results indicate those that switched from shopping at a local grocery store to a supercenter significantly increased their dietary intake of fruit (0.2 ± 0.8), fruits and vegetables (1.4 ± 2.7), alcohol (grams) (17.3 ± 54.1), and tomato sauce (0.1 ± 0.3). A local grocery store closure was associated with a change in shopping behavior and dietary intake. Community-level interventions targeting dietary behaviors must account for neighborhood food environment influences, including grocery store availability. Policy aimed at improving food access in rural communities need to consider approaches to improving a variety of food venues with affordable healthy food, while addressing the evolving grocery shopping behaviors of consumers.

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“…25 Gustafson et al reported that shopping at supermarkets was associated with a higher SSB consumption. 48 Many studies have examined the association between fruit and vegetable intake and the community food environment, and the results are generally consistent-those who live near supermarkets, farmer's markets, or healthy food stores consume more 20,21,23,28,49 while those who live near convenience stores and restaurants consume less. 17,49,50 These findings align with the current study's result that SNAP participation was associated with a lower frequency of fruit consumption when respondents did not live near a supermarket.…”

Section: Discussionmentioning

confidence: 95%

“…27 A similar study examined the association of food outlets with macronutrient intakes among SNAP participants and reported SNAP participants had a higher consumption of calories and fat when living in counties with multiple gas stations with food marts compared to participants without access to multiple gas stations. 28 While these studies limited their population to SNAP participants, they did not examine whether these behaviors were different for income-eligible non-participants. SNAP participation increases a household's food budget, 29,30 and thus SNAP participants may purchase and consume different foods than the low-income, non-participating population.…”

Section: Introductionmentioning

confidence: 99%

Participation in the Supplemental Nutrition Assistance Program and Dietary Behaviors: Role of Community Food Environment

Lorts¹,

Tasevska²,

Adams

et al. 2019

Journal of the Academy of Nutrition and Dietetics

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Program (SNAP) is the country's largest nutrition assistance program for low-income populations. While SNAP has been shown to reduce food insecurity, research on the diet quality of program participants is inconsistent. Objective: This study examined if the community food environment is a potential moderator of the association between SNAP participation and eating behaviors. Design: This cross-sectional study utilized participant data from a telephone survey of 2,211 households in four cities in New Jersey. Data were collected from two cross-sectional panels from 2009-10 and 2014. Food outlet data were purchased from commercial sources and classified as supermarkets, small grocery stores, convenience stores, or limited service restaurants. Participants/setting: Analysis is limited to 983 respondents (588 SNAP participants) with household incomes below 130% of the Federal Poverty Level. Main outcome measures: Eating behaviors assessed as frequency of consum ption of fruit, vegetables, salad, and sugar sweetened beverages (SSB). Statistical analysis performed: Interaction and stratified analyses using gamma regression determined the differences in the association between SNAP participation and eating behaviors by the presence or absence of food outlets adjusted for covariates. Results: SNAP participation was associated with a higher frequency of consuming SSB (p<0.05) when respondents lived within ¼-½ mile of a small grocery store, supermarket, and limited service restaurant. SNAP participants who did not live close to a convenience store reported a lower frequency of SSB consumption (p=0.01), while those living more than ½ mile away from a supermarket reported a lower frequency of fruit consumption (p=0.03). Conclusions: This study suggests that the community food environment may play a role in moderating the association between SNAP participation and eating behaviors. While SNAP participation is associated with some unhealthy behaviors, this association may only hold true when respondents live in certain food environments.

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Association Between the Retail Food Environment, Neighborhood Deprivation, and County-Level Dietary Outcomes Among Supplemental Nutrition Assistance Program–Education (SNAP-Ed) Recipients in Kentucky, 2010–2011

Cited by 7 publications

References 44 publications

The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study

The Neighborhood Energy Balance Equation: Does Neighborhood Food Retail Environment + Physical Activity Environment = Obesity? The CARDIA Study

The Impact of a Grocery Store Closure in One Rural Highly Obese Appalachian Community on Shopping Behavior and Dietary Intake

Participation in the Supplemental Nutrition Assistance Program and Dietary Behaviors: Role of Community Food Environment

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