Availability of healthier options in traditional and nontraditional rural fast-food outlets

Creel, Jennifer; Sharkey, Joseph R.; McIntosh, Alex; Anding, Jenna; Huber, John C.

doi:10.1186/1471-2458-8-395

Cited by 62 publications

(85 citation statements)

References 38 publications

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“…In the United States, low-income and racial/ethnic minority communities often have more restricted access to grocery stores and a higher concentration of fast food and convenience store outlets [6,7,8]. Moreover, the availability of affordable, quality healthy foods in these “at-risk” neighborhoods tends to be restricted to outlets selling a limited selection of foods that are higher priced and high in fat and calories [4,9].…”

Section: Introductionmentioning

confidence: 99%

Socioeconomic Context and the Food Landscape in Texas: Results from Hotspot Analysis and Border/Non-Border Comparison of Unhealthy Food Environments

Salinas¹,

Abdelbary²,

Klaas³

et al. 2014

IJERPH

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Purpose: The purpose of this paper is to describe the food landscape of Texas using the CDC’s Modified Retail Food Environment (mRFEI) and to make comparisons by border/non-border. Methods: The Modified Retail Food Environment index (mRFEI (2008)) is an index developed by the CDC that measures what percent of the total food vendors in a census track sell healthy food. The range of values is 0 (unhealthy areas with limited access to fruits and vegetables) to (100—Healthy). These data were linked to 2010 US Census socioeconomic and ethnic concentration data. Spatial analysis and GIS techniques were applied to assess the differences between border and non-border regions. Variables of interest were mRFEI score, median income, total population, percent total population less than five years, median age, % receiving food stamps, % Hispanic, and % with a bachelor degree. Results: Findings from this study reveal that food environment in Texas tends to be characteristic of a “food desert”. Analysis also demonstrates differences by border/non-border location and percent of the population that is foreign born and by percent of families who receive food stamps. Conclusions: Identifying the relationship between socioeconomic disparity, ethnic concentration and mRFEI score could be a fundamental step in improving health in disadvantage communities, particularly those on the Texas-Mexico border.

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Section: Introductionmentioning

confidence: 99%

Socioeconomic Context and the Food Landscape in Texas: Results from Hotspot Analysis and Border/Non-Border Comparison of Unhealthy Food Environments

Salinas¹,

Abdelbary²,

Klaas³

et al. 2014

IJERPH

View full text Add to dashboard Cite

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“…Relatively little is published on the validity and reliability of these sources (1) . In a recent review by Kelly and colleagues (2) , methods used to validate the location of food outlets obtained from secondary data range from list cross-referencing (3)(4)(5)(6) to direct observation (7)(8)(9)(10)(11)(12)(13)(14) . Correspondence between sources was reported as percentage match or agreement (6,7,9,10,13,15) , sensitivity (11)(12)(13) or positive predictive value (PPV) (12,13,16) .…”

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confidence: 99%

“…In a recent review by Kelly and colleagues (2) , methods used to validate the location of food outlets obtained from secondary data range from list cross-referencing (3)(4)(5)(6) to direct observation (7)(8)(9)(10)(11)(12)(13)(14) . Correspondence between sources was reported as percentage match or agreement (6,7,9,10,13,15) , sensitivity (11)(12)(13) or positive predictive value (PPV) (12,13,16) . Validation studies reporting correspondence statistics have generally been performed in North America (3,4,6,(9)(10)(11)(12)14,15,17) or the UK (5,7,13,16) .…”

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confidence: 99%

Validation of presence of supermarkets and fast-food outlets in Copenhagen: case study comparison of multiple sources of secondary data

Svastisalee

Due

2012

Public Health Nutr.

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Objective: We examined the quality of food outlet addresses provided by secondary sources and determined whether they could be physically located in the field. Design: Addresses of food outlets in fourteen school districts in the northern part of Copenhagen were obtained from multiple business locators. We geocoded 202 addresses using a geographic information system and cross-referenced the sources against each other using a validation grid. Physical presence was determined via street survey. We applied gamma statistics and calculated positive predictive value, sensitivity and percentage agreement to assess the overall correspondence between our test of physical presence and each source of secondary information. Setting: The study took place within city boundaries of Copenhagen, Denmark. Subjects: Food outlets within fourteen school districts within Copenhagen. Results: Positive predictive value between field results and secondary sources indicated good to excellent correspondence (range: 0?81-0?98), comparable with other studies. Gamma coefficients indicated low to high positive correspondence (range: 0?23-0?98). Conclusions: Despite moderately high correspondence between secondary sources of address information and field observation, the findings illustrate that the use of combined sources is recommended.

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“…Some researchers argue that supermarkets in developing countries typically provide cheap, processed and junk foodstuffs, which suggests that the growth of supermarkets is a driver of the transition towards diets high in energy and nutrient-poor foods (15,16) . Likewise, fast food is gaining popularity among younger generations and is widely spreading over both traditional and *Corresponding author: Email xiaoyong.zhang@wur.nl r The Authors 2011 non-traditional food outlets (17,18) . Since entering China in the 1980s, the fast-food industry in China has attained an annual growth rate of 15 %.…”

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confidence: 99%

Impacts of fast food and the food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

Zhang

Lans

Dagevos

2011

Public Health Nutr.

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Objective: To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. Design: A multilevel latent class cluster model was applied to identify consumer segments based not only on their individual preferences for fast food, salty snack foods, and soft drinks and sugared fruit drinks, but also on the food retail environment at the community level. Setting: The data came from the China Health and Nutrition Survey (CHNS) conducted in 2006 and two questionnaires for adults and communities were used. Subjects: A total sample of 9788 adults living in 218 communities participated in the CHNS. Results: We successfully identified four consumer segments. These four segments were embedded in two types of food retail environment: the saturated food retail environment and the deprived food retail environment. A three-factor solution was found for consumers' dietary knowledge. The four consumer segments were highly associated with consumers' dietary knowledge and a number of sociodemographic variables. Conclusions:The widespread discussion about the relationships between fastfood consumption and overweight/obesity is irrelevant for Chinese segments that do not have access to fast food. Factors that are most associated with segments with a higher BMI are consumers' (incorrect) dietary knowledge, the food retail environment and sociodemographics. The results provide valuable insight for policy interventions on reducing overweight/obesity in China. This study also indicates that despite the breathtaking changes in modern China, the impact of 'obesogenic' environments should not be assessed too strictly from a 'Western' perspective. KeywordsChina Obesity Food retail environment Multilevel latent class clusterIn recent years, growing scholarly attention (1)(2)(3) has been paid to the relationships between food retail environments (e.g. access, availability and price) and obesity. Fast food is high in energy and low in micronutrient density, and fast-food consumption may contribute to the obesity epidemic (4)(5)(6) . Although research on the possible interactions between obesity and characteristics of the food environment is at an early stage and the evidence is currently too weak to draw firm conclusions (7) , US studies suggest that the food environment influences a healthy diet and obesity levels in North America (8)(9)(10) .The clearly observable presence of processed foods, fast-food restaurants, supermarkets and other food outlets as factors determining the rising prevalence of overweight and obesity is a topic of research that is particularly relevant in the context of developed countries. Similar to the changing food retailing landscape in the postWorld War II era in Western countries (11,12) , the food retailing sector in China is experiencing dramatic changes half a century later. Over the past decade, supermarkets have been spreading faster in China...

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Availability of healthier options in traditional and nontraditional rural fast-food outlets

Cited by 62 publications

References 38 publications

Socioeconomic Context and the Food Landscape in Texas: Results from Hotspot Analysis and Border/Non-Border Comparison of Unhealthy Food Environments

Socioeconomic Context and the Food Landscape in Texas: Results from Hotspot Analysis and Border/Non-Border Comparison of Unhealthy Food Environments

Validation of presence of supermarkets and fast-food outlets in Copenhagen: case study comparison of multiple sources of secondary data

Impacts of fast food and the food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

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