Fighting Back

Abstract

This study investigated perceptions of stigma stemming from food insecurity experienced by residents of an inner-city community described as a food desert. Sixty inner-city residents were interviewed about their difficulty in providing healthy food for their families. The study measured four kinds of structural barriers which contributed to the experience of stigma. Participants agreed that welfare created a barrier and reported experiencing health disparities, neighborhood stigma, and welfare stigma. Participants who read high-stigma messages agreed more with health-stigma beliefs compared with participants who read low-stigma messages. Low-income White residents perceived more nutritional and neighborhood barriers compared with other racial groups. In spite of these perceptions of being stigmatized, the people included in this study engaged in stigma resistance in their efforts to secure nutritious food for their families.

Keywords

food insecurity stigma food deserts nutritional stigma stigma resistance

This study surveyed a group of inner-city residents about perceived barriers to good nutrition. An experiment was conducted that exposed participants to either a high-stigma message or a low-stigma message in order to examine whether reading these messages prompted participants to perceive inequality in nutritional distribution in their neighborhood compared with more affluent suburbs. A well-established phenomenon across the United States is for full-service grocery stores to relocate away from inner-city neighborhoods to safer, more affluent suburbs where higher profit and less risk is possible (Hilmers, Hilmers, & Dave, 2012). This creates a nutritional challenge for people living in the inner city who often are forced to get most of their food at convenience stores and fast-food chains. Numerous studies have demonstrated that lower socioeconomic status is associated with greater obesity (Black & Macinko, 2008; Nobles, Weintraub, & Adler, 2013; Robert & Reither, 2004). Economic inequality, community disadvantage, and high body mass index combine to contribute to health challenges (Zhang & Wang, 2004). Multiple sources demonstrated that people living in disadvantaged neighborhoods have poorer diets (Hilmers et al., 2012; Kimbro & Denney, 2013).

Household Food Insecurity in Inner-City Neighborhoods

Food insecurity is defined as “limited or uncertain availability of nutritionally adequate and safe foods or limited or uncertain ability to acquire acceptable foods in socially acceptable ways” (Bickel, Nord, Price, Hamilton, & Cook, 2013, p. 28). A 2012 study of availability of food for children in the United States determined that 12% to 15% of Black and Hispanic children in Grades k through 3 were food insecure, compared with 5% of White children of the same age (Kimbro, Denney, & Panchang, 2012). Individual lower socioeconomic status and community disadvantage have been linked to poorer overall health and this is compounded by lack of access and availability to healthy food (Grow et al., 2010; Larson & Story, 2015; Powell, Chaloupka, & Bao, 2007; Umberson, Williams, Thomas, Liu, & Thomeer, 2014).

Food insecurity occurs when people do not have adequate money to buy high-quality food to satisfy their nutritional needs (Martin & Lippert, 2012; Wunderlich & Norwood, 2006). There is limitation even with public food assistance programs in practice. For example, people on public food assistance, in this case the Michigan Bridge card, have money deposited in their card account at the beginning of the month. Many people on assistance report that they eat well for 2 weeks and barely manage for the rest of the month (“Holes in the Mitten,” 2015; Kempson, Keenan, Sadani, Ridlen, & Rosato, 2002).

Robert and Reither (2004) concluded:

Wealthy and predominantly white neighborhoods have over four times the number of large supermarkets compared to poor and predominantly Black neighborhoods. Supermarkets tend to have low food prices and an abundant selection of healthy foods like fresh fruits and vegetables relative to neighborhood groceries and convenience stores. Communities with the lowest SES also have 2.5 times more fast food restaurants than communities with the highest SES. (p. 2422)

Multiple sources demonstrate that people living in disadvantaged neighborhoods have poorer diets (Kimbro & Denney, 2013; Kimbro et al., 2012; Zhang & Wang, 2004). Healthy fresh food tends to be more expensive compared with inexpensive high-calorie processed food (Martin & Lippert, 2012).

Why Study People in Lansing, Michigan?

According to the most recent city data report (Lansing Statistics, 2015), Lansing is described as a midsize city of 113,972 residents. The ethnic distribution is 55% White, 23% Black, 13% Hispanic, and 4% Asian. The overall median income is about $36,000 (compared with $53,046 national median income) and the mean detached inner-city house is valued at $32,000 (compared with $188,900 nationally http://www.huffingtonpost.com/2014/03/13/median-home-price2014_n_4957604.html). Even though Lansing is the state capitol, the unemployment rate was 6% in 2015 and many inner-city neighborhoods are filled with run-down, foreclosed, and boarded up houses. For a city of its size, Lansing records higher burglary and property crimes, shootings, and assaults compared with the national averages (http://www.neighborhoodscout.com/mi/lansing/crime/) (). The student–teacher ratio in Lansing schools is 60:1, compared with the national average of 16:1 (http://www.areavibes.com/lansing-mi/education). Similar to the national average, around 24% of the population of Lansing is 18 years of age or younger. There are no full-service grocery stores in inner-city Lansing making it very difficult for inner-city residents to shop for healthy food.

Stigma is defined as “a mark or an attribute that is deeply discrediting” (Goffman, 1963, p. 3). Stigma is an interactive construct between the stigmatized and the stigmatizer. Stigmatizers generally command some kind of social power, while stigmatized individuals are often powerless, further aggravating the negative effects of stigma (Link & Phelan, 2001, 2014). Stigma occurs when some status stands out as different from the accepted norm (Goffman, 1963). Three major behaviors contribute to stigma. (a) Based on the perception that some condition is negative and undesirable, stigmatizers identify a group of people who are in this condition as a social entity different from us who need to be kept separate from us. (b) Stigmatizers believe that there is some physical or social peril associated with this condition. Stigmatizers believe that people with this condition pose both a threat to society and to them personally. (c) Stigmatizers assign blame and responsibility to people with membership in this group for getting themselves in a condition, for example, of poverty or unemployment, and for their inability to rid themselves of this onus (Smith, 2007).

Inner-city residents experience many forms of stigma such as harsher policing (Embrick, 2015; Farmer, Sun, & Starks, 2015; Salinas, James, Mattila, & Harton, 2015), more threat from violence and crime in rundown neglected, often overcrowded neighborhoods (Andersen, Gustat, & Becker, 2015), health inequity (Skinner & Masuda, 2013), the often escalating consequences of structural poverty (Bickel et al., 2013; Gibson, 2011), and less access to nutritious food and knowledge about healthy diet choices (Hilmers et al., 2012; Larson, Story, & Nelson, 2009). Nutritional stigma is defined as the denial of access to healthy food based on the neighborhood where people are forced to live because of their impoverished status. This has been described as “residential segregation” when grocery providers, urban developers, and city planners decline to invest in certain risky neighborhoods which are marginalized and ignored (Kwate, 2008). Inner-city residents are often marginalized and disempowered lacking any meaningful social capital (Alaimo, Reischl, & Allen, 2010). They suffer from power imbalance and structural stigma (Link & Phelan, 2014). Chaudoir, Earnshaw, and Andel (2013) describe how inner-city residents are often invisible to city planners and policy makers and how they suffer from disproportionate exposure to toxins and other health disparities.

Some people may feel powerless to fight nutritional stigma resigning to poor nutrition and accepting health consequences from eating a poor diet (compliance with stigmatized condition) (Scambler & Hopkins, 1986). Other inner-city residents fight the image that they are somehow deserving of reduced access to healthy food and make valiant efforts to get healthy food for themselves and their families (noncompliance and creative solutions for healthy nutrition). They try to improve their own access to nutrition by adopting such strategies as taking the bus together in small groups to the suburbs to get to full-service grocery stores, just as the participants in this study did. They bring portable shopping carts and large plastic containers to the local food pantry or share a ride with others to go to mobile food pantry food distribution events. Some rent a plot in a community garden and share produce with neighbors. While these responses are helpful, they do little to resolve the inequality and burden of systemic nutritional stigma.

Nutritional stigma becomes a compound form of stigma because the same group of people who lack access and affordability to healthy nutrition often experience other forms of stigma (e.g., health disparities, neighborhood and social stigma, welfare stigma; Hilmers et al., 2012). Nutritional stigma when compounded with several other forms of stigma may cause people in this set of circumstances to just give up and stick with unhealthy food as they have no viable alternative available (Larson et al., 2009).

Goals of This Study

Three levels of stigma are examined in this study—barriers, stigmatizing behaviors, and victims’ options for responding to stigma. What barriers and types of stigma do respondents report experiencing? Does the gender and race of participants have any effect on perception of barriers and being stigmatized? Our earlier research on stigma shows that it is often difficult to evoke a response of stigma in controlled research. This study exposed respondents to one of two experimental manipulations—either a description intended to induce high-stigma response or a message which was neutral for inducing stigma. Do these messages have any impact on perception of being stigmatized?

Method

Participants and Procedure

This study was based on a 2 (high-/low-stigma condition) × 2 (male/female participant) × 2 (White/minorities participant) between-subjects, factorial design. Participants with bags of groceries waiting at a bus stop were approached by the researchers. They were asked for their city zip code. Those who lived in the inner city were included in the study. Fifty percent of participants received a questionnaire with a description of high nutritional stigma. A similar description describing low stigma was given to the remaining 50% of participants. Some participants needed the assistance of the researcher to read and go through the survey with them. Initially, participants answered questions about perceived barriers before they read one of the experimental messages. We made sure participants read the stigma induction by asking questions about it for manipulation checks (see the appendix for stigma messages). Following this, participants answered the remaining questions assessing their perception of stigma experience.

Initially, we targeted the Route 1 bus which traveled from inner-city Lansing to a popular full-service discount grocery store in the suburbs. However, it proved difficult to find a sufficient sample of people who met our selection criteria (right zip code and no car). The decision was made to shift our investigation about 10 miles southwest of the original site.

The stores in both locations were built at approximately the same time but the branch in Meridian Township had recently been renovated and represented the state of the art in food presentation with many boutique concessions featured in the grocery area and a large fruit and vegetable display including a lot of organic options at the entry. The branch in south Lansing had cigarettes and alcohol at the entry and was smaller and unrenovated.

Finally, this study was conducted with 60 inner-city residents (28 males, 31 females, 1 gender unidentified) with ages ranging from 24 to 67 and a mean age of 46.23 (SD = 11.2). Thirty-two participants were White and 27 identified as minority. Thirty-one participants (14 males, 17 females) read the high-stigma research message, while 29 participants (14 males, 14 males) read the low-stigma message. There were 14 minorities in each of the two conditions and an approximately equal number of White participants per condition. A total of 55% lived in rented apartments, 13% lived in a rented house, and only 8.3% owned a house or apartment; 91.7% of participants did not have a car; 50% were unemployed and 20% already retired.

Measures

All measures were assessed for validity and reliability. All measures were 5-point Likert-type scales where a score of 1.0 indicated strong disagreement and 5.0 indicated strong agreement. Responses for all measures were averaged into one score, with higher scores indicating higher perception of barriers and more stigma.

Nutrition-related barriers are conceptualized in this study with four dimensions, which was used in previous research: nutritional barriers, health barriers, neighborhood barriers, and welfare barriers (Carr & Friedman, 2005; Scambler & Hopkins, 1986). Nutritional barriers include lack of access and food availability, due to the location of full-service grocery stores; disparities that make it difficult for people living in the inner city to maintain a healthy diet for themselves and their families. Health barriers are defined in this study as regular choice and preference for unhealthy food (James, 2004). Neighborhood barriers describe presence of numerous fast-food eateries and expensive corner convenience stores loaded with unhealthy food, cigarettes, and alcohol (Moore, Diez Roux, Nettleton, & Jacobs, 2008). Welfare barriers refer to the high cost of healthy food challenging the monthly food assistance allotment.

Nutritional barriers were assessed with four items including (a) Fresh fruit and vegetables are not available in stores close to where I live; (b) I have limited storage where I live for fruit and vegetables; (c) I often get food from Quality Dairy or a nearby convenience store; and (d) A very limited selection of fruit and vegetables is available in stores in my neighborhood (α = .67).

Health barriers were measured with four items including (a) My favorite dishes that I love to eat do not include vegetables; (b) I love to eat snacks and fast food; (c) I do not like the taste of vegetables; and (d) Usually I do not eat fruit (α = .60).

Neighborhood barriers were measured with four items including (a) It is difficult for me to get to a full-service grocery store; (b) I have to walk several blocks to the nearest bus stop; (c) I feel my neighbors are not very friendly; and (d) I think my neighborhood is a bit unsafe (α = .66).

Welfare barriers were measured with four items including (a) I think fruit and vegetables are too expensive; (b) I cannot afford most fruit and vegetables in the grocery store; (c) Price is my top concern when I shop for X fruit and vegetables; and (d) I would not have enough money to buy fruit and vegetables without my Bridge Card (α = .65).

Perception of the extent of being stigmatized, the dependent variable in this study, was conceptualized to include four dimensions which parallel barriers: nutritional stigma, health stigma, neighborhood stigma, and welfare stigma. Nutritional stigma evaluates perception of unequal access to full-service grocery stores with better, less expensive food (Galvez et al., 2009). Health stigma focuses on perception of poor health linked to inadequate nutrition (Umberson et al., 2014). Neighborhood stigma focuses on the presence of fast-food restaurants and convenience stores in poor neighborhoods (Galvez, Morland, Raines, & Kobil, 2008). Welfare stigma refers social and economic inequality and lack of money to buy healthy whole foods (Blumkin, Margalioth, & Sadka, 2008; Manchester & Mumford, 2009).

Nutritional stigma was measured with four items (α = .74) including (a) It is unfair that no grocery stores are near the place I live in; (b) I feel abandoned because grocery stores refuse to locate near my neighborhood; (c) I feel I should be compensated for not having access to grocery stores; (d) My lack of access to fruit and vegetables is due to absence of grocery stores.

Health stigma was measured with four items (α = .76) including (a) I believe that fewer health care resources have been invested on people like me; (b) I think that good health care is not available to people like me; (c) It is hard for people like me to keep healthy; (d) Many people I know have health problems (e.g., overweight, high blood sugar, heart problems).

Neighborhood stigma was measured with four items (α = .63) including (a) I think there are too many fast-food stores in my neighborhood; (b) Many people get food at a convenience store in my neighborhood; (c) I feel embarrassed to live in my current neighborhood; (d) I think most people who live around me do not have a garden.

Welfare stigma was measured with four items (α = .74) including (a) Many people make a negative judgment about someone who uses a Bridge Card; (b) I feel guilty about not being able to afford vegetable and fruit for my family; (c) People look down on others when they use a Bridge Card; (d) I feel angry if I cannot afford vegetables and fruit. Responses were averaged into one score, with higher scores indicating stronger welfare stigma.

Results

Perceived Barriers and Stigma

A series of one-sample t tests were conducted to examine whether the average scores for perceived barriers and stigma differed from the midpoint of the scale (i.e., 3 on a 5-point scale). On average, participants agreed with welfare barriers, M = 3.28, SD = 0.82, t(58) = 2.57, p < .05, and experienced health stigma, M = 3.28, SD = 0.82, t(58) = 3.96, p < .01, neighborhood stigma, M = 3.40, SD = 0.72, t(58) = 4.29, p < .01, and welfare stigma, M = 3.43, SD = 0.85, t(58) = 3.96, p < .01. Participants disagreed that their health posed a barrier, with a mean significantly below the midpoint of the scale, M = 2.46, SD = 0.94, t(58) = −4.40, p < .01. No differences from the neutral point of the scale were found for nutritional and neighborhood barriers or nutritional stigma. A series of independent-sample t tests were conducted to examine whether average scores on perceived barriers differed between message conditions. The two groups (high vs. low stigma) were not different in perceived barriers before exposure to the message, which is expected by random assignment.

The study also asked whether gender and race of participants significantly predicted participants’ perception of barriers. A series of two-way analyses of variance were conducted with gender and race as fixed factors (both are dummy coded, male = 1, White = 1) and different types of barriers as dependent variables. There was a significant main effect for race on nutritional barriers, F(1, 55) = 7.66, p < .01 partial η² = .12, observed power = .78, and neighborhood barrier, F(1, 55) = 6.75, p < .05 partial η² = .11, observed power = .72. The results suggested that White residents perceived more nutritional barriers (M = 3.34, SD = 0.84) than residents from other racial categories (M = 2.67, SD = 0.99). In addition, White residents also reported more neighborhood barriers (M = 3.21, SD = 0.80) compared with other racial categories (M = 2.61, SD = 0.89; see Figure 1). No main effect of gender or race was found for health barrier and welfare barrier.

Figure 1.

Plot of gender and race on neighborhood barrier.

An interaction effect of gender and race was significant on nutritional barriers, F(1, 55) = 4.86, p < .05, partial η² = .08, observed power = .58 (see Figure 2). Significant interactions were further probed by splitting the data by gender. Female, White residents reported more nutritional barriers (M = 3.59, SD = 0.94) than female, non-White residents (M = 2.43, SD = 1.16), t(29) = 3.07, p < .01. The difference between White and non-White residents for nutritional barriers disappeared for male participants, t(26) = 0.52, ns; see Figure 2.

Figure 2.

Plot of gender and race on nutritional barrier.

Message Condition, Perceived Barriers, and Stigma

The study also asked whether exposure to stigma messages, participants demographics (i.e., gender and race), and perceived barriers predicted stigma beliefs related to nutrition, health, neighborhood, and welfare (see Table 1). We expected that the high-stigma message would result in a response of higher stigma compared with the low-stigma message. To examine these assumptions, a series of hierarchical linear regressions were conducted. Before conducting the regressions, message conditions (high-stigma message = 1, low-stigma message = 0), gender (male = 1, female = 0), and race (White = 1, minorities = 0) were dummy coded. The dummy coded variables were then entered into Step 1, and the four types of barriers were entered into Step 2. Since these four variables were only weakly or moderately correlated with each other, there was not much concern for multicollinearity. Nutritional, health, neighborhood, and welfare stigma were entered as dependent variables in each regression models. The results are detailed in Table 2.

Table 1.

Descriptive Statistics and Zero-Order Correlations Among Variables.

	M	SD	Mess	Gender	Race	NutriB	HealthB	NeighB	WelB	NutriS	HealthS	NeighS
Mess	1.48	0.50
Gender	1.53	0.50	−.06
Race	1.46	0.50	.03	.08
NutriB	3.04	0.96	−.05	.01	−.37**
HealthB	2.48	0.94	−.03	−.06	−.22	.16
NeighB	2.94	0.89	−.04	−.02	−.34**	.40**	.46**
WelB	3.28	0.82	.01	.24	.00	.31*	.15	.37**
NutriS	2.96	0.85	−.04	.23	−.11	.27*	.10	.58**	.38**
HealthS	3.43	0.84	−.28*	.14	−.328*	.49**	−.02	.45**	.56**	.65**
NeighS	3.40	0.72	−.11	.17	−.36**	.40**	−.04	.39**	.39**	.41**	.71**
WelS	3.44	0.83	−.09	.29*	−.23	.25	.02	.33**	.52**	.49**	.71**	.75**

Note. Mess = Message condition; NutriB = Nutritional Barrier; HealthB = Health Barrier; NeighB = Neighborhood Barrier; WelB = Welfare Barrier; NutriS = Nutritional Stigma; HealthS = Health Stigma; NeighS = Neighborhood Stigma; WelS = Welfare Stigma.

Table 2.

Regression Estimates on Four Types of Stigma.

	Nutritional Stigma			Health Stigma			Neighborhood Stigma			Welfare Stigma
	B	SE	ΔR²	B	SE	ΔR²	B	SE	ΔR²	B	SE	ΔR²
Step 1			.10			.20**			.16*			.14*
Message	.04	.22		.43*	.20		.12	.18		.14	.21
Gender	−.29	.16		−.39**	.15		−.41**	.13		−.43**	.15
Race	.31^†	.16		.40**	.15		.41**	.13		.43**	.15
Step 2			.34**			.41**			.24**			.24**
Nutritional_B	−.02	.10		.20*	.09		.14	.09		.01	.11
Health_B	−.19	.11		−.25**	.09		−.20*	.10		−.12	.11
Neighborhood_B	.56**	.13		.27*	.11		.24*	.11		.16	.13
Welfare_B	.18	.12		.41**	.11		.19	.10		.44**	.12
Model	F(7, 52) = 5.68, R² = .43, p < .01			F(7, 51) = 11.29, R² = .61, p < .01			F(7, 51) = 4.71, R² = .39, p < .01			F(7, 52) = 4.40, R² = .37, p < .01

Note. N = 59. High-stigma message = 1; low-stigma message = 0; Male = 1, Female = 0; White = 1, other minority = 0; Nutritional_B = Nutritional Barrier; Health_B = Health Barrier; Neighbor_B = Neighborhood Barrier; Welfare_B = Welfare Barrier; SE = standard error.

p < .05. **p < .01. ^†p = .06.

The regression for nutritional stigma was statistically significant, F(7, 52) = 5.68, R² = .43, p < .01, with race and neighborhood barrier predicting nutritional stigma. After controlling for message exposure and gender, White residents perceived stronger nutritional stigma (M = 3.02, SD = 0.79) than minority residents (M = 2.84, SD = 0.89). The more inner-city residents experienced neighborhood barriers, the more strongly they perceived nutritional stigma (β = .59, t = 4.41, p < .01).

The regression for health stigma was statistically significant, F(7, 51) = 11.29, R² = .61, p < .01, with message condition, gender, race, and all four type of barriers predicting health stigma. Health stigma was higher for residents who read a high-stigma message (M = 3.64, SD = 0.71), were female (M = 3.52, SD = 0.93), and were White (M = 3.66, SD = 0.72) compared with residents who read the low-stigma message (M = 3.22, SD = 0.92), were male (M = 3.30, SD = 0.73), and were non-Whites (M = 3.12, SD = 0.89). Health stigma was positively associated with nutritional (β = .23, t = 2.32, p < .05), neighborhood (β = .29, t = 2.57, p < .05), and welfare barriers (β = .40, t = 4.13, p < .01), but was negatively associated with health barriers (β = −.28, t = −2.79, p < .01).

The regression for neighborhood stigma was statistically significant, F(7, 51) = 4.71, R² = .39, p < .01, with gender, race, health, and neighborhood barrier predicting neighborhood stigma. After controlling for message exposure and participants’ race, female residents (M = 3.52, SD = 0.80) perceived stronger neighborhood stigma than male residents (M = 3.27, SD = 0.62). In addition, White residents (M = 3.63, SD = 0.65) perceived stronger neighborhood stigma than non-White residents (M = 3.12, SD = 0.73). Neighborhood stigma was positively associated with neighborhood barriers (β = .29, t = 2.11, p < .05) and was negatively associated with health barriers (β = −.27, t = −2.16, p < .05).

The regression for welfare stigma was statistically significant, F(7, 52) = 4.40, R² = .37, p < .01, with gender, race, and welfare stigma predicting welfare stigma. Female residents (M = 3.65, SD = 0.87) perceived stronger neighborhood stigma than male residents (M = 3.27, SD = 0.62). White residents (M = 3.60, SD = 0.91) perceived stronger welfare stigma compared with female residents (M = 3.20, SD = 0.75). Welfare stigma was positively associated with welfare barriers (β = .43, t = 3.34, p < .01).

Discussion

This study investigated perceived barriers and stigma related to nutritional access. Inner-city participants reported that relying on welfare posed a barrier for them. They expressed the belief that the high cost of a healthy diet interfered with good nutrition. Interestingly, participants clearly disagreed that their health posed a barrier. Many admitted that they did not eat fast food and that they did not like to eat fruits or vegetables. Participants agreed that they had limited health care access, problems in their neighborhood environment, and reliance on social welfare. However, they did not feel stigmatized in terms of nutrition availability in general.

Gender and race showed some significant results for barriers. White residents perceived more nutritional barriers and neighborhood barriers compared with other groups. Female, White inner-city residents reported the highest nutritional barriers, whereas female, non-White residents reported the lowest. The influence of ethnicity and gender was interesting but needs further in-depth examination and explanation in future research. Participants showed awareness of their stigmatized status based on their neighborhood and economic disadvantage. Nutritional stigma was related to neighborhood barriers as well. The more inner-city residents agreed that their neighborhood had barriers, the more strongly they reported nutritional stigma. A surprising finding is that neighborhood stigma was negatively predicted by health barriers. The more health barriers one felt, the less stigma they perceived about their neighborhood environment. This finding needs further examination.

One unexpected finding from this study is that females in general reported more stigma compared with males, although males perceived more health stigma than females. Additionally, White residents also scored higher across all stigma dimensions than non-White minorities. Message condition was a significant predictor only for health stigma. Participants who read high-stigma messages reported experiencing more health stigma compared with participants who read low-stigma messages. Stigma-loaded message might remind or reinforce feelings of being stigmatized and lead to further negative cognitive or affectional reactions.

This study also had several limitations. First, the sample constituted people who made an effort to purchase nutritional food. This sample could be biased in that this group might feel more barriers and stigmatized than other inner-city residents. That is why they chose to “fight back” actively and strived for a healthier life. Pinel and Bosson (2013) observe: “It may well be that even as stigma consciousness renders targets more vulnerable to the negatives of stigmatization, it also gives them the motivation needed to set the wheels of change into motion” (p. 60). Given Pinel and Bosson’s observation, the current study revealed resistance to stigma in the form of practical steps that people take to combat stigma by getting on the bus and going to the outer reaches of the city to shop at full-service grocery stores. Even though this was time-consuming and somewhat of a burden for the people that we surveyed, these inner-city residents showed a determination to seek the best possible nutrition for their families and to not let themselves fall victim to nutritional exclusion.

Another limitation of the current study is that we did not directly measure coping strategies or ask participants to describe their level of resistance to stigma. Instead, we took an indirect measure of stigma resistance by surveying people who were proactively taking the bus to the edges of the inner city to procure nutritious affordable food for themselves and their families. Their presence at the bus stop at the grocery store indicated their resolve to shop for healthy food in spite of hardship in doing so. In retrospect, we might have further probed their reasons for taking the action that they did. These were labor intensive interviews and people were often distracted by their kids or were rushing to catch the bus. Nonetheless, the researchers on the scene guarded quality control of these precious data. Participants were eager to do our survey and to talk about their concerns about nutrition. Moreover, we did not include any open-ended items in this survey. We might have asked them to describe their experience of the difficulty of making ends meet on public assistance and problems in providing nutrition to their families. Future research could delve into these questions more by including in-depth interviews.

Implications

The results have implications for the structural processes through which stigmatization occurs, and more generally for the stigma-power concept. Research on stigma has revealed much about how stigma was executed in direct person-to-person interactions (e.g., Thompson & Seibold, 1978), but relatively less on how it contributes to the persistence of inequality. Contemporary theories on stigma suggested that inequality is hardwired into the social system via structural level stigmatization (Hatzenbuehler, Phelan, & Link, 2013; Link & Phelan, 2014). Structural stigmatization contributes to the cumulative disadvantages of the stigmatized people via social policy, institutional behavior, and community practices (Link & Phelan, 2001, 2014). The present study responded to a recent call for research on structural stigmatization (Hatzenbuehler & Link, 2014), and examined one novel factor: the deprivation of access to nutritional food due to one’s residency. The lack of nutritional resources significantly contributed to inner-city residents’ barrier perceptions and the feeling of being stigmatized. The more inner-city residents reported neighborhood barrier, the more they felt nutritional, health, and neighborhood stigma. This finding is particularly alarming given that neighborhood barrier was often considered as an obstacle that cannot be easily removed by individual efforts (Roithmayr, 2014). Individuals who want to deal with neighborhood barriers often face high switching costs economically (e.g., expensive housing in nutritionally accessible neighborhoods) and socially (e.g., shrinked size of one’s support network in the original community; Roithmayr, 2014).

More generally, the current findings are in line with the conceptualization of stigma power. Stigma occurs when there is a power imbalance between stigmatizers and the stigmatized (Link & Phelan, 2001). Phelan et al. (2014) further articulated three mechanisms through which stigma power operates: Keep people away, keep people down, and keep people in. Inner-city residents were kept away from accessing nutritional, healthy resources, and as a result, they may be kept down as targets of various stigmatization and potential victims of poor health conditions. If there is no way out, inner-city residents may passively accept their status of having few nutritional resources, and self-rationalize their disadvantaged position. This may explain why participants did not report significant experience of stigma.

Conclusion

Inner-city neighborhoods have been characterized as food deserts where it is difficult to provide a healthy meal for your family (Hilmers et al., 2012). People living in inner-city Lansing, Michigan, do not have a full-service grocery store within easy reach. They have devised creative ways to get around this problem and shop where healthy affordable meat, fruit, and fresh vegetables are available. But these barriers are not without costs to personal time, determination, and experiencing feelings of stigma.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Xiaowen Xu is currently a doctoral student in the Department of Communication at the University of Connecticut. She collected data on this project while working on her MA degree at Michigan State University.

Xun Zhu is a doctoral student in the Department of Communication at Pennsylvania State University. He studies stigma as a social process and is also interested in health stigma.

Mary Bresnahan is a Professor at Michigan State University and studies stigma and bullying.

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