Improving Food Affordability and Health Awareness in Atlanta

Skill-building strategies aimed at improving healthy eating typically target food shopping and preparation but have also targeted food production skills. Skill-building programs have had modest to limited impacts on food safety and nutrition knowledge, and on food shopping, preparation and consumption Greenwell Arnold and Sobal, ; Townsend et al. School and after-school garden programs combined with nutrition education curriculum, for example, have shown promise for improving knowledge, skills and behaviors, including willingness to try new, healthy foods Block et al.

A recent systematic review of community garden programs similarly found modest positive impacts on cooking skills Iacovou et al. There is little evidence on the equity impacts. Public awareness campaigns use organized communication strategies to create awareness in the general population through mass and social media, billboards and other outdoor advertising, and local community settings and events Hawkes, Mass media public information campaigns have been consistently shown to be more successful in improving knowledge and attitudes among women, and more educated and higher SES groups King et al.

The accumulating international evidence highlights that there are structural issues that affect the availability, affordability and acceptability of food, which influence what and how much different social groups eat. To address inequities in healthy eating, policy and action must tackle the systemic problems that generate poor nutrition, and reflect on how our food and social systems are making people sick.

This review highlights however that there is a dearth of evidence on the equity impact of actions across a range of policy domains. The bulk of evidence identified in this review relates to interventions targeting individual-level factors including a considerable number of interventions conducted in daily living environments, particularly in school and workplace settings and that focus on population averages. Well-designed and executed these actions can achieve modest short-term improvements in health-related knowledge and awareness. Alone, they are highly unlikely to be sufficient to reduce inequities in healthy eating, and at worst, may exacerbate existing inequities, with uptake and impact consistently shown to be higher in more advantaged groups.

Focusing on direct action to help people eat more healthily misses the heart of the problem: Unless this oversight is addressed, inequities in healthy eating will persist and possibly increase. Actions that address daily living conditions and the local settings in which people live show some promise in promoting healthy eating among disadvantaged groups. But much more action is needed at the socio-economic, and sociocultural levels, ensuring that actions in these domains are at least sensitive to their impact on diet and nutrition.

INTRODUCTION

The interconnected nature of the determinants of inequities in healthy eating implies the need for an integrated response comprising whole-of government policy and community level action. This requires joined-up action at global, national and local levels bringing together the capacity of multiple sectors. As discussed in other health governance literature Popay et al.

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Health promotion professionals can play an important role in advocating for these mechanisms, and pushing for greater social responsibility in the private sector. Supplementary material is available at Health Promotion International online. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.

Sign In or Create an Account. Close mobile search navigation Article navigation. Addressing inequities in healthy eating Sharon Friel. Abstract What, when, where and how much people eat is influenced by a complex mix of factors at societal, community and individual levels.

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The community engagement objective for this project was to gather community input on priority public health issues and the resulting FFM initiative in Cobb County, Georgia. The objective of the FFM initiative was to increase access to fresh fruits and vegetables among residents of the zip code. In , CDPH and Cobb surveyed county residents with a listed landline or cellular telephone number. Participation was limited to one randomly sampled adult per household.

Most of the 1, respondents were middle-aged mean age, Respondents ranged in educational attainment and household income; A finding from this survey was that most county residents were either overweight Many respondents also reported that obesity and other chronic diseases are serious health concerns for the county CDPH provided minigrants to gatekeeper community groups to recruit participants and contracted with a county university to lead the focus groups.

Adults who lived in Cobb County were recruited online, through announcements, and during one-on-one meetings eg, CDPH clients who came in for services. Four focus groups were conducted in English and 2 in Spanish. In addition to themes about the need for health education, improved access to health care, increased trust in medical providers, reduced barriers to seeking health care, and greater availability of health care services, participants articulated a need for improved access to affordable, healthy food choices Cobb and CDPH used MAPP findings to prioritize intervention strategies that address the community-identified priority of obesity and chronic disease prevention by addressing the lack of access to affordable, healthy foods.

In addition to the MAPP activities, CDPH worked with Cobb to identify health-promoting resources in the county, such as fitness and recreation facilities, health care clinics, and food retailers. These resources were geocoded on an interactive online asset map CDPH and Cobb used this map to identify the zip code as a community with limited access to healthy food options. In , CDPH and the YMCA assembled a community advisory board, consisting of community members and representatives from local businesses and organizations eg, representatives from a local community task force and apartment complexes , to help plan the FFM.

Other aspects of the FFM were determined with community advisory board input eg, market locations, hours, promotion. The FFM sites were the parking lots of 2 apartment complexes and one community recreation center. Each site was open once per week from 5: Each week, YMCA staff and volunteers purchased bulk quantities of 15 different types of fresh fruits and vegetables from a restaurant distributor and packaged them into individual items of approximately equivalent size and value. Examples of items for sale at the market included 2 apples, 1 head of broccoli, and 1 bunch of collard greens.

The University of Georgia Cooperative Extension provided recipes, nutrition information and cooking demonstrations, health assessment and awareness workshops, and referrals to healthy lifestyle programs. Before the market opened, CDPH and YMCA mailed English-language promotional postcards to a commercial mailing list of zip code residents living with children, distributed flyers in English and Spanish, conducted on-site outreach activities at participating apartment complexes, and produced a promotional video of the FFM.

The evaluation of the FFM pilot program was designed using a collaborative approach: The goal of the evaluation was to provide descriptive information about FFM implementation, reach, use, and impact. Because the purpose of this evaluation was to generate information used primarily for program improvement, the Emory institutional review board IRB determined that this project was a nonresearch program evaluation and did not require IRB approval.

Background

Evaluation data sources included a market tracking log and intercept surveys completed by returning market customers. After each market day, YMCA staff recorded the total number of customers and sales using the market tracking log. Because FFM impacts were assessed retrospectively, survey participation was limited to returning customers who could report changes in behavior before and after they began shopping at the FFM.

Market reach was assessed by using standard demographic questions and by asking participants whether they live in the zip code and have any children aged 5 to 12 living at home. Change in perceived access to healthy foods was measured by asking customers to report the extent to which they agreed or disagreed that the FFM made it easier for them and their family to eat a healthy diet or easier or less expensive for them to buy fresh fruits and vegetables. Customers were also asked to report the distance from their homes to the FFM and the distance they traveled from their homes to purchase fresh fruits and vegetables before they began shopping at the FFM.

Responses to these questions were compared to assess whether the FFM decreased the distance customers travel to purchase fresh produce. Change in fruit and vegetable consumption was measured by asking participants to indicate whether they eat fewer, the same amount, or more fruits and vegetables at the time of the survey than they did before they began shopping at the FFM.

The survey also included questions about frequency of shopping at the FFM and satisfaction with various aspects of the FFM eg, location, hours, prices. Of the customers who were invited to take the survey, completed surveys Two surveys were later excluded, because the participants were ineligible one was shopping for the first time and one had taken the survey before , resulting in a final sample size of participants.

Data were analyzed using SAS 9.

A Food Retail-Based Intervention on Food Security and Consumption

During the pilot season, the FFM attracted an average of Customer volume and sales varied across sites. Most survey participants were female The FFM served customers from varied age ranges, income levels, and educational backgrounds; Most FFM customers Nineteen percent of customers were from the FFM priority population: There were no significant differences in the demographic or socioeconomic characteristics of participants on the basis of FFM shopping frequency.

Before they began shopping at the FFM, most customers By contrast, most customers Most customers reported that they strongly agree that the FFM made it easier Most customers reported that they eat more vegetables There were no significant differences in changes in fruit and vegetable consumption on the basis of FFM shopping frequency. Eighty-eight percent of customers reported that they eat most or all of the fruits and vegetables that they purchase at the market data not shown.

Customers reported very high satisfaction levels with the FFM: This case study describes the development, implementation, and evaluation of the FFM, a novel community-based initiative to increase access to healthy foods in Cobb County, Georgia. The USDA recently created a nation-wide food desert locator to bring awareness to the issue and help guide retail-based interventions, but the locator is plagued by poor data quality [ 19 ]. This is but one example of public policy based on inaccurate descriptions of food deserts.

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Consequently, academics have been critical of using this term without carefully contextualizing the issue. She problematizes the concept by indicating that many methodological and conceptual debates exist in defining food deserts:. Donald and Bedore are not alone in their critiques of the concept of food deserts. There is a lack of consensus on the definition, which can result in inconsistency or uncertainty when devising public policy [ 22 ].

Some have suggested abandoning the term altogether in favor of more general terms such as access [ 23 ]. Other researchers suggest that individual-level circumstances such as mobility are a better indicator of difficulties with food access than geographic metrics such as the lack of a grocery store in a community [ 24 ].

Increasing the use of psychometric measures including perceptions, beliefs, and attitudes of consumers may help to more accurately identify the factors involved in healthy eating behavior [ 5 ]. Although disagreement remains in discourse and literature on the extent to which food deserts influence diet or health, living in such an area is at least likely to exacerbate the potential for dietary problems related to poor access to nutritious foods, especially for those with mobility issues.

Thus food deserts should be recognized as a by-product of many social issues, and not merely as geographic gaps in the food environment [ 20 ]. A thorough engagement with community-specific assessment and neighborhood identification is important for practitioners, therefore, to devise and advocate for interventions to improve healthy eating behaviors.

These interventions should also aim toward evaluation designs which can help suggest causality in the food environment. Most ecologic studies of food environments and socioeconomic factors or health-related outcomes have been based on observational or cross-sectional methods. Cross-sectional research is popular among social scientists because data collection is often more accessible than experimental research.

These studies, however, do not suggest causative agents within the environment or eliminate competing explanations for observed environmental traits. Given the lack of causative explanations, there is a need to further evaluate the cause of these indicators of poor health. Because purely scientific experiments are difficult to conduct in the social environment, natural experiments have been advocated as a proxy method [ 26 ].

A natural experiment is a quasi-experimental type of study which takes advantage of an intervention which occurs without researcher control [ 25 ]. But the difficulty in forecasting interventions in time to conduct preliminary assessments often stymies the use of this method. Natural experiments have been used in various research projects on the built environment. For instance, Fitzhugh and colleagues found a significant increase in total physical activity after the improvement of an urban pedestrian greenway [ 27 ]. MacDonald and colleagues found that the addition of a light rail line was associated with reductions in BMI and probability of obesity [ 28 ].

Kapinos and Yakusheva, meanwhile, found that dormitory assignment among college freshman was associated with weight-gain and weight-related behaviors. Each of these research findings demonstrates the influence that local environmental changes can have on the health-related behaviors of individuals [ 29 ].

A Food Retail-Based Intervention on Food Security and Consumption

Despite the call for health researchers to develop more innovative study designs, few studies to date have utilized natural experiments to attempt to isolate causal links between the food environment and health outcomes. Two natural experiments in Leeds and Glasgow, UK, have found conflicting results regarding the impact of new food retail establishments in socioeconomically disadvantaged regions [ 30 , 31 ]. A recent US study also lacked definitive results that an intervention had a measurable impact on diet [ 32 ]. The present research, therefore, advances this literature by following a natural experiment to evaluate the impact of a new food retailer on the food consumption and security of residents in a socioeconomically disadvantaged neighborhood of Flint, Michigan.

In this case, food security refers to whether a respondent has self-reported an instance of lacking food of sufficient quality or quantity within the last year [ 33 ]. This is important because when food security is threatened, the consumption of healthy, fresh foods such as vegetables and fruits—and with it, nutrient intake—declines [ 34 , 35 ].

The addition of a new grocery store, therefore, may help food insecure residents reach healthy food more easily by providing an affordable option within a short distance. As discussed, only three research teams have successfully evaluated natural experiments on food retail interventions, and only the most recent was in the US [ 30 , 31 , 32 ]. The present manuscript, then, will expand on this rarely studied strain of research and contribute the second article to the American context, which is important because of differing cultural attitudes toward urban development. Strict planning policy in the UK has enabled cities to retain a denser urban fabric than in the US [ 36 ], which facilitates active travel and lower obesity rates [ 37 ].

The differences in development patterns and cultural attitudes may also contribute to differences in the influence of neighborhood food shopping on consumption behaviors. It is hypothesized that in a culture where citizens use active travel less frequently, immediate neighborhood shopping opportunities will play a weaker role in shaping diet and, therefore, the addition of a new food retail establishment in a car-dependent community will not have a significant effect on consumption habits.

The effect on food security may, however, be stronger, if food insecure respondents up-take the new food retail establishment. The study area, Flint, Michigan, is a city which has experienced tremendous changes over the past four decades, beginning with disinvestment from car manufacturers in the s. A decline in services and retailers such as grocery stores accompanied this population loss.

Many neighborhoods in Flint exhibit low densities and near complete abandonment by retail and commercial uses. Where retail does exist, grocery stores are easily outnumbered by liquor stores offering junk food and stocking little fresh produce. The evaluation of this intervention on food consumption is important because Flint is one of the least healthy cities in the state of Michigan [ 42 ]. Flint residents consume between 3. Within the study neighborhoods for this research, these statistics are assumed to be worse, since poverty and unemployment are higher than the county average.

It is valuable to consider this past research in the Flint Metropolitan Area so comparisons may be drawn on the two study neighborhoods. Site selection of the control neighborhood was constrained by three factors: First, the intervention neighborhood Carriage Town lies in the center of the city. The small geographic size of the Flint region created the potential for cross-contamination between control and intervention neighborhoods, leaving few suitable candidate neighborhoods.

Previous natural experiments were conducted in larger cities, meaning that intervention and control groups could be placed to avoid cross-contamination [ 30 , 31 , 32 ]. Second, Flint is a highly racially segregated city, so few neighborhoods were similar to Carriage Town in ethnic composition Figure 1. Third, Flint is highly bifurcated socioeconomically. Using a distress index developed in past research [ 41 , 46 ], various socioeconomic characteristics were combined into an index to predict areas of high distress Figure 2.

After an evaluation of census data for the city and out-county area [ 47 ] and the information from Figure 1 , Figure 2 , the Beecher district on the north side of the urban area was selected because it was similar to Carriage Town in sociodemographic characteristics, the degree of racial integration, and population density. In contrast to Carriage Town, however, Beecher has been served by a grocery store since well before the study began. The presence of a high proportion of black residents in both of these study neighborhoods is an important consideration because past research from Philadelphia showed that healthy food is more difficult to find in neighborhoods with a high proportion of black residents [ 48 ].

These neighborhoods may therefore yield populations with issues related to accessing healthy food. Data collection spanned two phases: One year is considered an adequate time period over which to observe behavioral change [ 49 ]. Pre-tested questions adapted from the Behavioral Risk Factor Surveillance System BRFSS [ 50 ] were used in a telephone survey of randomly selected residents in the control and intervention neighborhoods Beecher and Carriage Town, respectively.

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Questions covered topics such as: Despite varying results of over- and under-estimation of food consumption found in past research when using brief screeners such as these [ 51 ], this module was used for the sake of comparability to past community surveys. Respondents were also asked to indicate the street intersection nearest to their home. All respondents were at least 18 years old and were the primary shopper for their household.

Respondent selection was determined by the proximity of the resident to the center of the neighborhood. In both neighborhoods the grocery stores were operationalized as the center of the neighborhood see in Figure 1 , Figure 2. A randomized sample of phone numbers were taken from within walking distance of the grocery stores starting within 1, m and subsequently including residences within 1, and 2, m of the store sites.

Based on spatial analysis, the population of each neighborhood was estimated to be around 3, Supposing a household size of 2. Nevertheless, these values are still considered statistically significant for the neighborhoods under study. As well, comparability between neighborhoods is considered more important than generalizability overall for the purpose of this study.

Because of high residential turnover rates in Flint [ 52 ], repeating the study with the same respondents would have been infeasible. Respondents in the second phase, therefore, were asked where they primarily shopped for groceries and, if they had lived in the neighborhood prior to , where they shopped for groceries at that time. This technique controlled for any variation in shopping habits due to drawing from two different samples of the same population.

The respondents are thus also treated as four distinct groups as opposed to two groups studied longitudinally Beecher , Beecher , Carriage Town , and Carriage Town , and statistical analysis reflects this consideration. It was hypothesized that, given the small scale of the store and the many countervailing forces such as entrenched behavioral and cultural practices, dietary habits would not improve significantly due to the addition of the store. Descriptive statistics were compiled for various predictor and outcome variables and compared to past community surveys shown in Table 1.

Statistics are broken down by phase, neighborhood, and food security status. In general, the sample collected for this research was older, was less educated, comprised more black residents, and consumed fewer fruits and vegetables than the samples from past research [ 43 , 44 ]. Respondents from the intervention neighborhood Carriage Town did not vary significantly from respondents in the control neighborhood Beecher in food consumption or self-reported health. Additionally, no significant differences were seen in descriptive statistics when considering both neighborhoods pre- and post-intervention.

The potential for evaluating many relationships especially with regard to food security, food consumption, and geographic access to nutritious foods necessitated further analysis. Bivariate regression analysis was run for all predictor and outcome variables to determine the relevance of multivariate regression analysis for fruit and vegetable consumption or food security as outcome variables.

Several risk factors were evaluated as shown in Table 2 , and significant results are shown with asterisks. Food security FS was negatively correlated with both, suggesting that food insecure respondents were living nearer to both types of food outlets. The absence of multiple non-related significant relationships to either fruit and vegetable consumption or food security, however, nullified the utility of running multivariate analysis.

Still, other variables were highly correlated to one another. Echoing prevailing health research, self-reported good health was positively but not strongly associated with higher food security, higher educational attainment, higher income, lower BMI, and stronger feelings about the importance of healthy foods. Various other relationships were significant, but because multiple regression would not yield useful information for the primary outcome variables of food consumption and food security, analysis turned to additional statistical procedures.