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. Author manuscript; available in PMC: 2011 Feb 23.
Published in final edited form as: Ecol Food Nutr. 2010 Nov 1;49(6):409–430. doi: 10.1080/03670244.2010.524102

Characteristics of Prepared Food Sources in Low-Income Neighborhoods of Baltimore City

SEUNG HEE LEE 1, MEGAN T ROWAN 2, LISA M POWELL 3, SARA NEWMAN 4, ANN CARROLL KLASSEN 5, KEVIN D FRICK 6, JENNIFER ANDERSON 7, JOEL GITTELSOHN 8
PMCID: PMC3043356  NIHMSID: NIHMS271221  PMID: 21359162

Abstract

The food environment is associated with obesity risk and diet-related chronic diseases. Despite extensive research conducted on retail food stores, little is known about prepared food sources (PFSs). We conducted an observational assessment of all PFSs (N = 92) in low-income neighborhoods in Baltimore. The most common PFSs were carry-outs, which had the lowest availability of healthy food choices. Only a small proportion of these carry-outs offered healthy sides, whole wheat bread, or entrée salads (21.4%, 7.1%, and 33.9%, respectively). These findings suggest that carry-out-specific interventions are necessary to increase healthy food availability in low-income urban neighborhoods.

Keywords: food environment, prepared food, restaurants, carry-outs, low-income neighborhoods

BACKGROUND

Obesity and the Food Environment in the United States

Obesity is a leading cause of preventable death in the United States (Gostin 2007) and its prevalence has increased dramatically over the past two decades (Ogden et al. 2006; Wang and Beydoun 2007). Low-income urban African Americans (AA) suffer from obesity and associated chronic diseases at rates higher than national averages (Marshall 2005; Clark and El-Atat 2007; Clark et al. 2001; Grier and Kumanyika 2008). Many urban low-income minorities live in “obesogenic” food environments (Hill and Peters 1998), which include a lack of supermarkets and an abundance of small food stores. (Larson, Story, and Nelson 2009; Morland et al. 2002; Franco et al. 2009; Sloane et al. 2003; Pearce et al. 2007). These areas are also often referred to as food deserts, which have been defined as block groups that are more than one-quarter mile from a supermarket and are comprised of a population in which more than 40 percent are below the poverty line (Center for a Livable Future 2010). Living in these settings is associated with excess energy intake and an increased risk of obesity and chronic diseases (Thompson et al. 2004; Babey et al. 2008).

The Role of Prepared Food Sources in Low-Income AA Settings

In addition to the abundance of small food stores, higher proportions of prepared food sources (PFSs) have been found in predominantly black versus white neighborhoods, and this has been positively associated with racial differences in obesity (Lovasi et al. 2009), neighborhood characteristics (Powell, Chaloupka, and Bao 2007; Franco et al. 2008; Galvez et al. 2008; Morland et al. 2002) and healthy diets (Franco et al. 2009; Moore et al. 2009). While it is difficult to find affordable healthy foods in these settings, high caloric and fatty prepared foods (PFs) are readily available in corner stores and carry-outs (Lee et al. 2010; Cannuscio, Weiss, and Asch 2010; Azuma et al. 2010). Although PFs are generally more costly than those prepared at home, they are still consumed at high rates among those with lower incomes (Guthrie, Lin, and Frazao 2002; French, Harnack, and Jeffery 2000; Kant and Graubard 2004). A recent community food assessment in Baltimore revealed that African American residents spent roughly equal amounts at PFSs as supermarkets, $288 and $274 per month, respectively (Palmer et al. 2007).

Prepared Foods and Associations with Health Outcomes

Within carry-outs and fast-food restaurants, portion sizes have increased extensively to attract customers. Since the 1970s, standard soft drink servings have increased by 49 calories, French fries by 68 calories, and hamburgers by 97 calories (Young and Nestle 2007). The large portion sizes and high calorie and fat content of PFs contribute to many health outcomes associated with obesity (Guthrie, Lin, and Frazao 2002; Young and Nestle 2002; Jeffery et al. 2006; Zoumas-Morse et al. 2001; Nielsen and Popkin 2003; Rolls, Morris, and Roe 2002; Diliberti et al. 2004). Studies have found that frequently eating in PFSs or lower PFS prices are related to higher intake of fat, sodium, and sugar and lower intake of nutrient-dense foods, such as fruits and vegetables (French, Harnack, and Jeffery 2000; Kant and Graubard 2004; McCrory et al. 1999; Beydoun, Powell, and Wang 2009), and as a result, an increased risk for heart disease (Duffey et al. 2007). PF consumption has also been directly linked to three primary indicators of Diabetes Mellitus: high-fasting blood glucose, weight gain, and insulin resistance (Salmeron et al. 1997; Ludwig et al. 1999; Pereira et al. 2005).

Obesity and the Food Environment in Baltimore City, Maryland

Between 59.2 and 63.1 percent of Baltimore City adults are obese or overweight (Balakrishnan, Fichtenberg, and Ames 2008). Adult obesity prevalence is about 30 percent higher in Baltimore City than in Maryland and nationally (Balakrishnan et al. 2008). The 2005 Youth Risk Behavioral Surveillance Survey found 17.6 percent of Baltimore City youth had BMIs greater than the 95th percentile, as compared to 12.6 percent across Maryland (Eaton et al. 2006).

Among Baltimore City AAs, fruit and vegetable intake is extremely low. In 2008, Behavior Risk Factor Surveillance Survey data showed that 23 percent of AAs ate five or more servings of fruits and vegetables a day, compared to 31 percent of Caucasians (Centers for Disease Control and Prevention 2008). Conversely, Baltimore AAs consume many sugary drinks and fatty foods, and PFs provide more than half of their total calories (Gittelsohn and Sharma 2009).

Little is known about PFSs in low-income urban areas, despite their potential role in the obesity epidemic. Moreover, findings regarding the risks associated with PFs in these settings are inconsistent (Larson, Story, and Nelson 2009; Morland, Wing, and Diez Roux 2002; Mobley et al. 2006; Simmons et al. 2005). Such inconclusive findings may be due to the varying definitions of restaurants, the exclusion of carry-outs in their definition, and a lack of descriptive data associated with varying PFSs. This study addressed this gap by answering the following questions:

  1. What types of PFSs are available in low-income Baltimore census tracts?

  2. What healthy foods do these outlets carry?

  3. How do PFSs differ from each other?

METHODS

Geographical Coverage and Sampling of Areas

We focused our analyses on East and West Baltimore; low-income areas comprised of 40 census tracts. These areas were selected for inclusion because they have been previously defined as food deserts (Antin and Hora 2005; Gittelsohn et al. 2007). Our population statistics are based on Census data aggregated to the neighborhood level, rather than analyzed at the individual census tract level (http://webapps.jhu.edu/census and www.bnia.org), and included comprehensive socioeconomic data on the residents within our target areas.

All neighborhoods included in the sample are approximately 90 percent AA (U.S. Census Bureau 2000). The median of median household income in our sample neighborhoods is lower than the city average ($19,070 versus $30,008). To understand the difference between very-low (VL) and moderately-low (ML)-income neighborhoods, income composition was dichotomized by the average median household income (< $19,070, > $19,070~$27,824) of study neighborhoods.

Data Collection

Data on PFSs within the study area was obtained through ground-truthing (Hosler and Dharssi 2010) and direct observation. Data collectors canvassed the area by car and foot, visually inspecting every street and identifying the location and business status (i.e., in-business, out-of-business, or under renovation) of all PFSs. There were no refusals. This provided an up-to-date list of PFSs, as a discrepancy existed between our list of operating sources and those listed in directories. PFs have been defined as ready-to-eat food items, which are prepared and can be purchased on-site (South Dakota Department of Revenue & Regulation 2010).

To assess food availability within these venues, we used a modified version of the previously validated Nutrition Environment Measures Study in Restaurants (NEMS-R) data collection instrument (Saelens et al. 2007). Our study team developed and utilized similarly refined NEMS instruments for Baltimore Healthy Stores (www.healthystores.org) and Baltimore Eating Zones research (Dennisuk et al. 2010). In contrast to the NEMS-R, which was designed to gather data on all foods and associated prices, our modified version was primarily focused on health promoting foods and features of PFSs. These modifications enabled observers to collect data in less than 10 minutes; an important asset given the large number of PFSs in Baltimore City and store owner resistance to detailed surveying.

The modified instrument captured: type of PFS, availability of 44 key healthy foods by category (14 entrees; 12 side dishes; 7 breakfast foods; 3 desserts; 11drinks), features of the food source (e.g., health information posted, diet fountain drink options, salad bar presence), and types of healthy foods offered (e.g., whole wheat bread, low fat/low calorie condiments) (appendix). For the purposes of this study, an “entrée” was defined as a main dish of the meal, and may be a stand-alone item or accompanied by an appetizer, dessert, or side, and a “combo meal” was defined as an entrée meal that includes a side and a beverage.

Nutrition information (e.g., fat, calories) for specific foods and recipes was not captured by this instrument, which limited our ability to define foods as healthy or unhealthy. We, therefore, defined foods as healthy if they were estimated to be lower fat and/or sugar as compared to similar alternatives (i.e., comparable food types-beverage, entrée, side and size). We referenced the USDA National Nutrient Database (www.nal.usda.gov/fnic/foodcomp/search) to obtain standardized nutrient contents for the menu items that were common in the carry-out setting. According to the database, an average grilled chicken sandwich (with no condiments) has approximately 9 grams of fat, while and average roast beef sandwich (with no condiments) has an approximately of 18 grams of fat (www.nal.usda.gov/fnic/foodcomp/search). According to our definition, the chicken sandwich was “healthy,” and was, in turn, listed on our checklist of healthy items. We used the same methodology to classify other foods, which were listed on NEMS-R, as healthy, and included those foods on our modified checklist. Once our list was refined, we fielded it in seven sample PFSs to determine if it captured all healthy items that were common in our target venues. We adjusted the instrument based on our findings.

Four data collectors were trained to use the checklist. Data collection was primarily based on observational recall. To enhance reliability, pairs of researchers collected data and compared findings. As an additional method of data validation, PFS menus were obtained (when available), and photographs of displayed menus were taken (when menus were not available). Store owners/managers were asked to verbally consent to photography. All store owners/managers consented. The availability of health related information within each venue was assessed and recorded in addition to the menu analysis.

Data were collected from 92 PFSs in low-income neighborhoods in Baltimore, between May 2009 and April 2010. Storeowner/manager ethnicity was ascertained through informal verbal interactions. Visual identification was used to define ethnicity when necessary. Ethnic categories included Caucasian, Black, South Asian (e.g., Pakistani), East Asian (e.g., Chinese) and Hispanic.

We used the following inclusion criteria for PFSs: (1) The venue must serve PFs (as previously defined); and (2) the venue type must be listed as a limited-service restaurant by the 2007 North American Industry Classification System (NAICS; North American Industry Classification System 2008), in accordance with the methodology developed by Saelens et al. (2007) and Morland et al. (2002). We further classified PFSs into four categories fitting to the unique food environment of low-income neighborhoods in East and West Baltimore: carry-outs and market vendor; corner stores; fast-food chain restaurants; and sit-down restaurants.

A takeout-only carry-out is a restaurant that does not have tables and/or chairs and sells ready-to-eat foods. In this type of restaurant the patron orders and pays before eating. A carry-out restaurant with tables describes a restaurant with tables and chairs where the purchased food is provided after patrons order and pay. A market vendor is a carry-out that is located within a market, some specializing in specific foods. A corner store with a deli describes a retail food store that sells ready to eat prepackaged foods, such as deli meats and cheeses. A corner store with takeout describes a retail food store that sells foods requiring fryers or food warmers. A fast-food chain restaurant describes a corporation-operated “brand name” fast-food business at which the customer orders and pays before eating. A sit-down restaurant describes an establishment with tables and servers. The patron orders food and is served while seated, and pays after eating (does not include fast-food chain restaurants).

The Johns Hopkins Bloomberg School of Public Health Institutional Review Board approved this study.

Data Management and Analysis

STATA 10.1 (STATACorp, College Station, Texas) statistical software was used to perform descriptive statistics. Pearson’s chi square analyses were performed to test for differences in the availability of healthy foods by income strata, and the Fisher’s exact test was used for cells that had a frequency of five or less.

RESULTS

Characteristics of PFSs

Table 1 presents the characteristics of 92 PFSs in the East Baltimore City census tracts. In our study setting, there were 72 carry-outs, 11 corner stores with deli/take-out, 2 sit-down restaurants and 7 fast-food chain restaurants. Carry-out restaurants were the most common PFS (77.2%) and sit-down restaurants were the least common (2.2%). Most (95.7%) food sources had a single cash register. The most common owner ethnicity was Asian (65.2%) and 78.3 percent of those owners were Korean (51.1% of all owners). Other owner ethnicities varied (9.8% African American; 5.4% White/Caucasian; 3.2% Hispanic; 6.5% Middle Eastern; 14.1% unidentified). The majority of non-Korean owners sold ethnicity-specific foods. All Hispanic owners (n = 3) carried Hispanic foods and all Chinese-owned venues (n = 9) were Chinese take-outs.

TABLE 1.

Characteristics of PFSs in Low-Income Baltimore City Neighborhoods, N = 92

Type of food sources Total
n %
Carry-out restaurant 72 78.3
 Take-out only 49 53.3
 Carry-out w/tables 8 8.7
 Market style 15 16.3
Corner store 11 12.0
 Corner store w/deli 7 7.6
 Corner store w/take-out 4 4.3
Fast-food chain restaurant 7 7.6
Sit-down restaurant 2 2.2

Health Promoting Factors in PFSs

Healthy features varied between PFSs (tables 2 and 3). Low fat meats were available for sandwiches in 83.7 percent of the PFSs, but only 41.3 percent offered vegetable sandwich toppings. Healthy sides (e.g., cooked greens, side salad, fruits) were offered in 23.9 percent of the PFSs. Reduced portion size items were most commonly offered in the fast-food chain restaurants (85.7%), while only 42.9 percent of carry-outs and 40.0 percent of market vendors provided that option. Only 4.3 percent of restaurants had self-administered coffee/tea stations, where customers could choose the type and quantity of additives. The same low percentage (4.3%) offered the choice of low-fat condiments. Very few PFSs (5.4%) displayed health or nutrition-content signs.

TABLE 2.

Healthy Features of PFSs in Low-Income Baltimore Neighborhoods, N = 92

Healthy choice offered Total
n %
Low-fat meat offered for subs or sandwiches 77 83.7
Reduced-size portions offered on the menu 37 40.2
Vegetable toppings offered for sandwiches 38 41.3
Choice of healthy sides 22 23.9
Whole-wheat bread available for sandwiches 10 10.9
Promotion/advertisement of healthy foods 5 5.4
Health-related signs 5 5.4
Posting of calorie or other nutrition information for foods on the menu 4 4.3
Self-administered condiments 4 4.3

TABLE 3.

Availability of Healthy Foods by Food Source Type in Low-Income Baltimore Neighborhoods, N = 92

n %
Carry-outs Corner stores Sit-down restaurants Fast-food chains Market vendors
n = 57 n = 11 n = 2 n = 7 n = 15
Healthy eating promoting factors
Low-fat meat offered for subs or sandwiches 47
82.5
9
81.8
1
50.0
7
100.0
13
86.7
Reduced-size portions offered on the menu 24
42.1
1
9.1
0
0.0
6
85.7
6
40.0
Vegetable toppings offered for sandwiches 22
38.6
2
18.2
0
0.0
3
42.9
11
73.3
Choice of healthy sides 12
21.1
2
18.2
2
100.0
2
28.6
4
26.7
Advertisement of healthy foods 3
5.3
0
0.0
0
0.0
0
0.0
1
6.7
Whole-wheat bread available for sandwiches 4
7.0
2
18.2
0
0.0
0
0.0
4
26.7
Posting of calorie or other nutrition information for foods on the menu 2
3.5
1
9.1
0
0.0
1
14.3
0
0.0
Designated Healthy menu 7
12.3
0
0.0
0
0.0
0
0.0
1
6.7
Health-related signs 4
7.0
0
0.0
0
0.0
1
14.3
0
0.0
Food
Diet soda 46
80.7
11
100.0
1
50.0
7
100.0
13
86.7
Bottled water 41
73.2
10
90.9
1
50.0
5
71.4
15
100.0
Low-fat sandwich 41
71.9
10
90.9
2
100.0
5
71.4
11
73.3
100% fruit juice 36
64.3
9
81.8
0
0.0
3
42.9
10
66.7
Grilled poultry 31
54.4
6
54.5
1
50.0
4
57.1
9
60.0
Side salad, fresh greens 24
42.1
3
27.3
0
0.0
4
57.1
6
40.0
Cooked greens 20
35.7
0
0.0
2
100.0
2
28.6
3
20.0
Broth-based soup 20
35.1
2
18.2
0 0 8
53.3
Entrée salads 19
33.3
2
18.2
0
0.0
2
28.6
4
26.7
Fruit without syrup 6
10.5
3
27.3
0
0.0
1
14.3
2
13.3

Although we did not assess unhealthy foods using our checklists, high-fat foods such as fried chicken wings, fried lake trout, hamburgers and submarine sandwiches were commonly listed on the PFSs menus, which were derived from data collectors’ notes and photographs at our research venues. More than 78.3 percent of PFSs advertise at least one combo meal and 41.7 percent have more than 11. Fried sides were automatically included with entrées in 56.5 percent of PFSs.

Availability of Healthy Foods by Type of Prepared Food Source

Table 3 shows the availability of healthy foods by type of PFS. Healthy menus were found in 8.7 percent of PFSs; all of these venues were Chinese carry-outs that offered steamed/boiled entrees. A lower-fat meat sandwich option was the most commonly offered healthy food (fast-food chains 100%, carry-outs 82.5%, market vendors 86.7%, corner stores 81.8%, and sit-down restaurants 50%). A choice of vegetable toppings was available in 73.3 percent of market vendors, 42.9 percent of the fast-food chain restaurants, 38.6 percent of carry-outs; only 18.2 percent of corner stores offered the choice. Whole wheat sandwich bread was the least available healthy food (less than 11 percent of food sources). Healthy sides were available in all sit-down restaurants and were rarely available in carry-outs and corner stores (21.1% and 18.2%, respectively).

Availability of Healthy Foods by Income Status

Availability of healthy foods was significantly different between ML and VL strata (table 4). VL had significantly more availability of grilled/baked poultry, stir-fried vegetables, turkey burger, side salads, and corn sides than ML. On the other hand, ML had significantly more availability of scrambled/fried eggs, peanut butter and jelly, oatmeal, fresh fruit, and low fat milk than VL.

TABLE 4.

Availability of Foods by Income Strata within the Low-Income Baltimore Neighborhoods (N = 92)

Healthier Foods Very low-income neighborhoods (VL) n = 46
Moderately low-income neighborhoods (ML) n = 46
χ2 p
n % n %
Entrée
 Low-fat meat for sandwich (turkey, chicken) 32 69.6 37 80.4 1.449 .229
 Grilled/baked poultry 32 69.6 19 41.3 7.4357 .006*
 Broth-based soup 18 39.1 13 28.3 1.2163 .27
 Entrée salad 14 30.4 13 28.3 0.1355 .713
 Grilled/baked seafood 10 21.7 6 13.0 1.2105 .271
 Stir-fry incl. vegetables 9 19.6 3 6.5 3.45 .063
 Turkey burger 6 13.0 2 4.3 2.1905 .139
Breakfast
 Scrambled/fried eggs 17 37.0 27 58.7 4.3561 .037*
 Peanut butter and jelly 0 0.0 3 6.5 3.1011 .078
 Oatmeal 0 0.0 4 8.7 4.1818 .041*
 Whole-wheat toast 3 6.5 1 2.2 2.0115 .366
Sides
 Salads/fresh leafy greens 22 47.8 15 32.6 2.2152 .137
 Cooked greens (kale, collard greens) 14 30.4 13 28.3 0.0529 .974
 Coleslaw 11 23.9 6 13.0 1.8039 .179
 Baked/mashed potato 8 17.4 9 19.6 0.0722 .788
 Corn side 10 21.7 5 10.9 1.9913 .158
 Fruits 4 8.7 9 19.6 2.2395 .135
Other
 Diet soda 37 80.4 41 89.1 1.348 .246
 Bottled water 39 84.8 34 73.9 1.6583 .198
 100% fruit juice 31 67.4 27 58.7 1.5486 .461
 Unsweetened tea 8 17.4 11 23.9 0.597 .44
 Low-fat milk (2%, 1%, skim) 1 2.2 5 10.9 4.7143 .095

Note. The median of median household income ($19,070; range $11,276–$27,824) provided the cut-off between very-low (VL) and moderately-low (ML) income levels.

*

p < .05.

DISCUSSION

Several studies have been conducted in restaurants in ethnically and socio-economically diverse populations (Saelens et al. 2007; Lewis et al. 2005; Economos et al. 2009; Hanni et al. 2009). This is one of the first studies, however, to describe the entire PFS environment in a low-income AA urban setting. We found many parallels between this research and our other research on food availability in corner stores in the same Baltimore City neighborhoods (Franco et al. 2008; Moore et al. 2009). For example, within low-income AA neighborhoods in Baltimore City, most food sources (prepared or retail) were Korean owned, had low healthy food availability and low health promoting features (Gittelsohn et al. 2007).

Most PFSs were carry-outs, which had the lowest healthy food availability. Our findings are comparable to other urban low-income settings in the U.S. A recent study conducted in low-income areas in Los Angeles found that fast-food outlets and carry-outs were the most common (30%) retail food outlets (Azuma et al. 2010). In Philadelphia, Chinese take-out restaurants and “stop-and-go” shops (delis that also sell beer) were commonly found in low-income AA neighborhoods (Cannuscio, Weiss, and Asch 2010). These studies categorized and localized PFSs in low-income urban settings but did not investigate PF store content or food offerings. Such data is necessary to develop effective carryout interventions that improve the availability of healthy food options and sustain the purchase of healthy foods through incentives like point of purchase promotions.

Our study found that 33.3 percent of carry-outs and 28.6 percent of fast-food restaurants had entrée salad availability. A NEMS-R study, including Atlanta PFSs (N = 102), produced similar findings for fast-food restaurants with entrée salad availability of 24.5 percent (Saelens et al. 2007). The NEMS-R study, however, did not stratify other PFSs and could not compare healthy food availability of carry-outs. The checklist provided insight into available healthier foods that are popular in low-income urban PFSs. For example, most commonly available cooked greens (string beans, collard greens or kale) and leafy green salads have a lower fat than other commonly offered sides (French fries and macaroni and cheese). Moreover, preparation methods can be modified in future pilot and feasibility trials. The availability of greens, in combination with the adjustment of cooking methods, could provide a low-calorie nutrient-rich alternative to common PFS sides.

We found that carry-outs sell similar foods as fast-food restaurants but had a significantly different physical layout. The majority of carry-outs stored and sold foods behind floor-to-ceiling glass partitions and most carry-out owners and managers spoke little English. These two features could limit the customer’s ability to order a customized healthier meal, or request healthier options. The glass barrier reduces the interaction between customers and storeowners, leaving owners to guess which foods may be popular. Baltimore Healthy Stores intervention observed similar barriers in Korean American owned corner stores during the intervention (Song et al. 2009, 2010). This issue warrants further exploration.

Also, limited space for menus could inhibit the ability of stores to convey nutritional information. Also, lack of equipment such as small refrigerators, could limit their ability to carry healthy items. Most PFSs also lacked self-serve condiment stations. In one of our intervention trials, healthy choices at self-condiment stations, in conjunction with health education, positively influenced consumer dietary habits (Ho et al. 2008).

Our study had several other limitations. While our modified NEMS-R environmental checklist was relatively simple and easy to implement, it did not capture the entire range of healthy or unhealthy components of PFSs. While we attempted to tailor the revised instrument to capture data on food items in specialized food sources (e.g., steamed vegetables at Chinese carry-outs, etc.); we could expand the checklist to be targeted to specific types of PFSs in order to capture the range of healthy and unhealthy options in these varying settings. Our instrument also did not capture enough food pricing data to perform food pricing analyses for a range of menu items. However, our study contributes to the limited literature on availability of foods in PFSs for which there are no standard data on food composition and portion size (i.e., owner defined small, medium and large). Future research is warranted in order to examine these issues.

As the instrument used was observation-based, it was difficult to accurately classify foods as healthy and unhealthy. We relied on assumptions regarding fat, caloric and fiber content of foods. Without direct knowledge of cooking or preparation methods, we cannot be certain that foods are low in fat and calories. We searched the USDA National Nutrient database to obtain standard recipes for the menu items’ caloric and fat content. Although, it is possible that a turkey sandwich can contain higher calories and fat compared to a corned beef sandwich based on the cooking method, we made an assumption that within the same menu category, the cooking method will be the same. Moreover, as opposed to corner stores, which often carry standardized packaged foods (Variyam 2008) that list nutritional information, the serving sizes of prepared foods are unknown and may vary greatly between each respective source. Future work should include analyses of prepared food nutrient content data to provide rationale for the classification of healthy and unhealthy food offerings. Additional studies are also needed to develop a healthy food index, which includes an analysis of cooking/preparation methods and serving sizes, scores based on estimated nutrient content, and ranking, based on a collective analysis of scores, which would be used to compare PFSs. Interventions, which target cooking/preparation methods and serving sizes, should be considered as a means to promote healthy eating in these venues.

Our checklist was not able to capture accurate pricing information because many PFSs did not have prices posted on the menu or were outdated. Many studies suggest that price may influence consumer behavior (Morland et al. 2002; Jetter and Cassady 2006; Ard et al. 2007; Zenk et al. 2006; Drewnowski and Darmon 2005). Antin and Hora (2005) conducted qualitative research among single mothers in low-income East Baltimore, and found that mothers with fewer than 3 children were eating out more often than mothers with 3 and more children. Overall, informants expressed that convenience and pricing were the most important factors in choosing a store. Without information pertaining to the price of all available foods, it is difficult to present a detailed description of its role in the prepared food environment.

We used neighborhood census data, which combines “some geographical and social aspects” (www.bnia.org), defined by the City Planning Department. This Baltimore City specific data explains low-income areas better than census tracts. In addition, the census data used are 10 years old and the areas may have changed as a result of immigration and the ongoing economic downturn. Since there is a temporal disconnect in the data, similar analyses can be performed after the release of 2010 national census data in near future.

The small sample size and PFS type also limited our ability to detect significant differences between food source types. Within our study setting, there were 11 corner stores, 2 sit-down restaurants and 7 fast-food chain restaurants, which resulted in very small sample sizes to compare with the 72 carry-outs. Despite the small sample sizes, this is the first data available on PFSs in low-income urban settings. Future studies should examine the distribution of PFSs over a greater expanse of Baltimore, and in other urban settings.

In spite of these limitations, our current study adds to previously published literature on PFSs, and can contribute to the development of carry-out interventions. This is especially relevant considering their prominence in low-income AA settings. Previous studies conducted in Baltimore focused on small and medium sized grocery stores (Song et al. 2009), recreation centers (Dennisuk et al. 2010) and schools. There have been a few environmental interventions conducted in restaurants (Albright, Flora, and Fortmann 1990; Horgen and Brownell 2002), department store food service areas (Eldridge et al. 1997) and fast-food restaurants (Wagner and Winett 1988), but their intervention sites were not located in low-income areas. The only previous PFS interventions in low-income areas that have shown some success were conducted by Hanni et al. (Hanni et al. 2009) in Salinas, California, focusing on Hispanic-owned taquerias. The taquerias intervention included a social marketing strategy, providing healthier menu options, to the taqueria owners. Researchers concluded that after participating in the intervention, taqueria storeowners’ perceptions regarding healthy food availability changed. As a result, owners voluntarily offered healthier menu items. However, taqueria owners in Salinas, California, are Latinos serving a Latino community, whereas, in many urban carry-outs, owners are Korean Americans serving an African American community; the latter situation may require a population-specific intervention since the owners’ changes in food preparation practices are not directly benefitting their own community.

Our environmental data on PFSs provided useful insight into the availability of healthy foods in low-income AA neighborhoods in Baltimore City. Additional formative research is needed to understand customers’ and storeowners’ views on healthier prepared foods in order to strengthen interventions in PFSs located in low-income urban AA settings.

Acknowledgments

This work was supported by the Baltimore Diabetes Research and Training Center and the Center for a Livable Future. The authors would like to thank local carry-out owners who were willing to let data collectors observe their store environments.

APPENDIX Prepared Food Sources Environmental Checklist

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Contributor Information

SEUNG HEE LEE, Center for Human Nutrition, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

MEGAN T. ROWAN, Center for Human Nutrition, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA

LISA M. POWELL, Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois, USA

SARA NEWMAN, Center for Human Nutrition, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

ANN CARROLL KLASSEN, Center for Human Nutrition, and Department of Health, Behavior and Society, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

KEVIN D. FRICK, Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA

JENNIFER ANDERSON, Center for Human Nutrition, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

JOEL GITTELSOHN, Center for Human Nutrition, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

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