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. Author manuscript; available in PMC: 2021 Jul 23.
Published in final edited form as: Health Place. 2020 Jul 23;64:102392. doi: 10.1016/j.healthplace.2020.102392

My neighborhood has a good reputation: Associations between spatial stigma and health

Emma Tran 1,*, Kim Blankenship 2, Shannon Whittaker 1, Alana Rosenberg 1, Penelope Schlesinger 1, Trace Kershaw 1, Danya Keene 1
PMCID: PMC7456603  NIHMSID: NIHMS1615995  PMID: 32838899

Abstract

Health researchers increasingly recognize the influence of spatial stigma, or negative reputation of place, as a social determinant of health. Drawing from a New Haven-based cohort study (n=251), we assessed the relationships between spatial stigma, self-rated health, and psychological distress using generalized estimating equation models. Adjusting for neighborhood-level poverty and racial composition, those who perceived living in spatially stigmatized neighborhoods were significantly more likely to report severe psychological distress compared to those that did not perceive their neighborhoods to be stigmatized (B=1.09, CI: 0.31, 1.87). Our findings contribute to a growing body of literature that suggests that socially constructed meanings of place may influence health.

Keywords: spatial stigma, place, neighborhood, self-rated health, mental health

INTRODUCTION

An extensive body of literature documents the relationship between place and health. Previous studies have identified, for instance, that places of residence are strongly associated with a variety of physical and mental health outcomes, including chronic cardiovascular conditions, overall mortality, and psychosocial distress (Macintyre & Ellaway, 2003). While the literature connecting health to neighborhoods is robust and longstanding, research focusing on the less tangible, socially constructed meanings of places has emerged only over the last decade (Halliday et al., 2018). In particular, scholars have argued that negative reputations of places can stigmatize place-based identities (Chaix, 2009; Wacquant, 2007). These negative discourses are deeply rooted in persistent stereotypes that link disadvantaged minority groups, particularly Black Americans, to crime, disorder, violence, and poverty (Sampson & Raudenbush, 2005). These pervasive racist beliefs are facilitated and reinforced by structural conditions, such as redlining and economic disinvestment, that historically and contemporarily segregate Black communities into areas of concentrated poverty (Keene & Padilla, 2014; Wacquant et al., 2014). Sociological studies have shown that spatial stigma not only affects residents’ day-to-day life, but also can intersect with other neighborhood-level measures of disadvantage to produce and reproduce social discrediting (Goffman, 1963; Wacquant, 2007).

Though less studied, spatial stigma has also been shown to have detrimental effects on health. Kelaher and colleagues (2010), for example, found that perceptions of spatial stigma among residents of socioeconomically disadvantaged Australian neighborhoods are associated with poor self-rated health. Tabauchi and colleagues (2012) found that perceived geographic discrimination in a disadvantaged area of Osaka, Japan is associated with depressive symptoms. Duncan et al (2016) found that perceptions of neighborhood stigma among public housing residents were linked to increased risk of obesity, overweight and hypertension, and pre-hypertension, as well as higher BMI and higher systolic blood pressure. Other studies have found associations between spatial stigma and a greater risk of depression, anxiety, and overall mental illness (Olsen et al., 2017; Wutich et al., 2014). As the existing literature is limited in scope, these findings highlight the need for more extensive research in order to wholly understand the effects of spatial stigma on health.

To explain the pathways through which spatial stigma can manifest in these health disparities, Keena and Padilla (2018) offer a helpful conceptual framework. First, spatial stigmatization may justify the segregation of some communities that limit access to health-promoting resources. These socio-spatial divisions also play an important role in patterns of investment and disinvestment, determining opportunities available to residents (Macintyre et al., 2002; Wakefield & McMullan, 2005). Second, spatial stigma can have a psychosocial impact on individuals by activating stereotypes (Kallin & Slater, 2014). For example, some residents in spatially stigmatized neighborhoods have reported being refused services in ways that can be detrimental to health. Scholars have found that taxi drivers, food deliverers, home health workers, and police have avoided stigmatized places (Macintyre & Ellaway, 2003; McCormick et al., 2012). Additionally, spatial stigma may be internalized, which can negatively influence self-esteem by attaching feelings of shame to place-based identities (Hatzenbuehler, 2016; Keene & Padilla, 2014).

Our knowledge of the relationship between spatial stigma is largely based on a theoretical literature (Keene & Padilla, 2018; Slater, 2017; Wacquant et al., 2014) as well as qualitative data (Collins et al., 2016; Graham et al., 2016; Thomas, 2016) that document residents’ personal experiences with discredited place-based identities. While this literature has created an important foundation to conceptually understand spatial stigma, fewer studies have quantitatively examined the relationship between spatial stigma and health outcomes, as outlined above. Moreover, many of these quantitative findings draw from studies outside the US. Our study expands the existing literature examining the relationship between spatial stigma and health outcomes, psychological distress and self-rated health, by drawing on data from residents across multiple neighborhoods in one US city.

METHODS

Data and Sample Selection

This analysis draws on data from the New Haven-based Justice, Housing and Health Study (JustHouHS), a collaborative study of the American University Department of Sociology, the Yale School of Public Health, and Drexel University. Like many other American cities, New Haven has experienced historical racial and socioeconomic segregation that has precipitated today’s dramatically concentrated pockets of wealth and poverty. These patterns have also largely determined where communities of color live in the city (Seaberry, 2018). Given this high segregation, the structural and symbolic demarcations of New Haven’s 20 neighborhoods are important components of the city’s geography and cultural landscape.

JustHouHS was designed to examine the intersections among mass incarceration, housing policies, and housing stability in producing health risks, as well as detailed data about New Haven’s neighborhood characteristics and experiences. All data collection and recruitment processes were approved by the Yale University Institutional Review Board. JustHouHS’s cohort of 400 New Haven residents were over the age of 18 years. To obtain a low-income sample, participants at screening must also have either 1) identified as homeless, 2) resided in a low-income census tract (where more than 20% of residents live below the federal poverty level), 3) received housing or food assistance within the past year, or 4) received Medicaid. Enrollment took place between September 2017 and March 2018, and participants agreed to participate in waves of the survey every six months for two years. Within the larger study, JustHouHS participants represent each of the city of New Haven’s 20 neighborhoods. A majority of this sample live in neighborhoods identified as having the city’s highest poverty rates (Abraham et al., 2016).

The present paper draws on data from the first follow-up wave of the study, which included 318 respondents (among those who were missing, 30 were incarcerated between baseline and follow-up). We further limit our sample to individuals who resided in New Haven at the time of the follow up survey (N=268), allowing us to incorporate neighborhood-level contextual data. Our final analytic sample (N=251) excluded n=17 individuals who were homeless at the first follow-up and did not report a neighborhood of residence.

Measures

Health Outcomes

Our dependent variables, or health outcomes, included psychological distress, number of days with poor mental health, and self-rated health.

Psychological distress was captured using the Kessler psychological distress scale (K10), a nonspecific measure of distress that has been psychometrically validated. While not a diagnostic tool, a high K10 score can indicate risk for depressive and anxiety disorders. The K10 is a 10-item scale that asks how often during the past 30 days an individual felt (1) “tired out for no good reason,” (2) “nervous,” (3) “so nervous that nothing could calm you down,” (4) “hopeless,” (5) “restless or fidgety,” (6) “so restless that you could not sit still, (7) “depressed,” (8) “that everything was an effort,” (9) “so sad that nothing could cheer you up,” and (10) “worthless.” Responses were scored from 1 point (none of the time) to 5 (all of the time) and summed to yield a total score. Following clinical guidelines, we identified K10 scores of 30 or greater as indication of severe psychological distress, and scores below 29 to indicate lower risk of distress (Jarman et al., 2014; Kessler et al., 2003). As an additional nonspecific measure of distress, our study also included the number of days in the last month that participants felt that their mental health was not good.

Our other health outcome included self-rated health, a psychometrically valid tool as a proxy to identify objective health status (DeSalvo et al., 2006). Respondents were asked to self-rate their health from 1 (poor), 2 (fair), 3 (good), 4 (very good), to 5 (excellent). We dichotomized these outcomes as “fair or poor” and “good or better” as an approach consistent with that used in many recent studies that have examined social variables as predictors of self-rated health (Manor et al., 2000; Nieminen et al., 2010).

Spatial Stigma

Our primary independent variable captured perceived neighborhood reputation as a measure of spatial stigma. Individuals’ perceptions of the reputation of their neighborhood were dichotomized to “good” or “poor” based on whether they agreed with the following statement: “Generally, this neighborhood has a good reputation.” This question has been used in previous studies to capture spatial stigma (Kelaher et al., 2010).

Neighborhood Context

Neighborhood-level socioeconomic status and racial composition are frequently used to explain observed differences in health outcomes within neighborhoods (Black et al., 2010; Robert & Ruel, 2006; Zhu & Lee, 2008). As such, to strengthen our attempt to independently link spatial stigma to health, our study adjusted for neighborhood-level percent Black and neighborhood-level poverty using data from the US Census Bureau 2016 American Community Survey 5-year estimates. While JustHouHS participants represented all 20 neighborhoods in New Haven at baseline, the participants included in the first follow-up lived in 19.

Demographics

Lastly, our demographic variables included race, age, education, gender, and neighborhood. Respondents’ races were categorized as Black, White, and Other, the latter of which includes Asian, American Indian, and Hispanic individuals. The current study used age of respondent at baseline, categorized into five levels: 18–29 years, 30–39 years, 40–49 years, 50–59 years, and 60 years or older. In addition, respondents were asked about level of education, categorized into three levels: less than high school, high school graduate or GED, and more than high school. Gender was dichotomized to male or female, which excluded a small number of non-binary respondents. Respondents’ addresses were geocoded for neighborhood.

Statistical Analysis

We used bivariate analyses to compare respondents who perceived their neighborhood reputation positively and negatively by age, gender, race, income, and education level. A generalized estimating equation (GEE) was used to estimate the associations between spatial stigma and severe psychological distress (SPD, defined by a K10 score greater than 30); number of days in the past 30 days with poor mental health; and poor-self-rated health (B estimates and 95% confidence intervals). GEEs are commonly used in studies that aim to correlate neighborhood characteristics with individual-level health outcomes by accounting for within-neighborhood nonindependence of health observations (Hubbard et al., 2010). To adjust for this clustering, our GEEs modeled neighborhood-level poverty and neighborhood-level percent Black, both as continuous variables. All analyses were performed using SAS statistical software, version 9.2 (SAS Institute, Cary, NC, USA).

RESULTS

Demographic Characteristics

Our study population included 251 adults, over half of whom were over the age of 40 and nearly half of whom were Black. The sample was 65.7% male, and the mean income was $18,257. Overall, 57.8% of the sample perceived that they live in a neighborhood with poor reputation. No demographic variable, including age, gender, education, race, or income, was significantly related to neighborhood reputation (Table 1). The neighborhoods most frequently reported to have poor reputations matched neighborhoods in New Haven that reported the highest prevalence of poverty (data not shown).

Table 1.

Distribution of demographic variables and their association with neighborhood reputation (N=318)

Characteristic N (%) Neighborhood reputation, n (%)
 p*
Good (n=106) Poor (n=145)
Gender 0.932
 Male 165 (65.7) 70 (66.0) 95 (65.6)
 Female 86 (34.3) 36 (34.0) 50 (34.5)
Age in years 0.263
 18–29 24 (9.6) 11 (10.4) 13 (9.0)
 30–39 51 (20.3) 21 (19.8) 30 (20.7)
 40–49 72 (28.7) 26 (24.5) 46 (31.7)
 50–59 76 (30.3) 31 (29.3) 45 (31.0)
 60+ 28 (11.2) 17 (16.0) 11 (7.6)
Education 0.541
 Less than high school 57 (22.7) 22 (20.8) 35 (24.1)
 High school or GED 120 (47.8) 55 (51.9) 65 (44.8)
 More than high school 74 (29.5) 29 (27.4) 45 (31.0)
Race 0.125
 Black 173 (69.0) 79 (74.5) 94 (64.8)
 White 56 (22.3) 17 (16.0) 39 (26.9)
 Other 22 (8.8) 10 (9.4) 12 (8.3)
Annual income, mean ± SD 18,257 ± 106,644 21,629 ± 137,774 15,715 ± 75,648 0.651
Percent neighborhood-level poverty, mean ± SD 57.8% ± 11.8% 55.2% ± 12.4% 60.0% ± 10.9% 0.003
Percent neighborhood Black 39.8% ± 21.3% 37.5% ± 18.2% 41.6% ± 23.4% 0.157
Open in a new tab

Note: Numbers may not sum to total due to missing data. Columns show column percentages.

*

p-value for x2 test.

The associations between neighborhood reputation and mental health outcomes were statistically significant (Table 2). Among those who perceived that their neighborhood had a poor reputation, 28.3% reported having severe psychological distress, compared to 14.2% of those who perceived that that their neighborhoods had a good reputation (p=0.008). Similarly, those living in neighborhoods perceived to have a poor reputation reported experiencing an average of 7.0 mentally unwell days in the last month, compared to 4.1 days among those living in non-spatially stigmatized neighborhoods (p=0.018). Self-rated health was not significantly differently distributed across different perceptions of neighborhoods.

Table 2.

Unadjusted associations between neighborhood reputation and health

Characteristic N (%) Neighborhood reputation
 p*
Good (n=106) Poor(n=145)
Self-rated health 0.552
 Fair/poor 187 (74.5) 81 (76.4) 106 (73.1)
 Good or better 64 (25.5) 25 (23.6) 39 (26.9)
Psychological distress 0.008
 None to moderate 195 (77.7) 91 (85.9) 104 (71.7)
 Severe 56 (22.3) 15 (14.2) 41 (28.3)
Number of days mental health not good in the last 30 days, mean ± SD 5.8 ± 9.6 4.1 ± 8.2 7.0 ± 10.3 0.018
Open in a new tab

Note: Numbers may not sum to total due to missing data. Columns reflect column percentages.

*

p-value for x2 test.

Generalized Estimating Equation Models

In our generalized estimating equation models, we assessed associations between perceived neighborhood reputation with self-rated health, severe psychological distress (SPD), and days with poor mental health (Table 3). All models adjusted for neighborhood-level poverty and percent neighborhood identifying as Black. Self-rated health was not significantly associated with neighborhood reputation as shown in Model 1. Among those who perceived their neighborhoods to have a poor reputation, participants reported being significantly more likely to have severe psychological distress compared those who perceived their neighborhoods to have a good reputation (B=1.09, CI: 0.31, 1.87) (Model 2). The association between spatial stigma and more days with poor mental health was marginally significant (B=0.51, CI: −0.02, 1.03) (Model 3).

Table 3.

Generalized estimating equation models of factors associated with health outcomes

Characteristic Health outcomes
Model 1: Fair/poor self-rated health vs good
 Model 2: Severe psychological distress vs mild/moderate
 Model 3: Number of days mental health not good in last 30 days
Estimate (95% CI) p Estimate (95% CI) p Estimate (95% CI) p
Neighborhood reputation
 Good 1.00 -- 1.00 -- 1.00 --
 Poor 0.17 (−0.28, 0.62) 0.454 1.09 (0.31, 1.87) 0.006 0.51 (−0.02, 1.03) 0.214
Percent neighborhood-level poverty 0.91 (−1.51, 3.33) 0.460 −1.66 (−4.43, 1.12) 0.241 0.98 (−0.56, 2.52) 0.214
Percent neighborhood Black 0.24 (−0.93, 1.41) 0.690 −0.94 (−2.47, 0.59) 0.230 −1.30 (−2.55, −0.06) 0.040
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*

Models adjusted for neighborhood-level poverty and neighborhood-level percent Black.

DISCUSSION

Our study aimed to contribute to a growing body of evidence that spatial stigma detrimentally impacts health. Our analysis is unique in its ability to adjust for neighborhood-level contextual factors, which strengthens our hypothesized argument that the stigma of place itself, which is often conflated with objective neighborhood characteristics like poverty, can drive poor health outcomes. We found that those who perceived that their neighborhoods had poor reputations had greater likelihood of reporting severe psychological distress. These results corroborate previous findings that link spatial stigma with greater odds of poor mental health (Olsen et al., 2017). Like other stigmatized identities, spatial stigma may arise or be made evident when individuals who hold discriminatory views about certain places may exhibit derogatory behaviors toward those who reside in said places. Such social interactions may trigger both physiological responses (such as stress and anxiety) and psychological responses (such as coping) among spatially stigmatized residents (Hatzenbuehler, 2016; Kelaher et al., 2010). Over time, these stress-induced responses can compound to produce severe psychological distress (Griffiths et al., 2008).

Scholars have argued that stigmas are powerful because they operate and maintain as both externally validated and internalized structures (Hatzenbuehler, 2016). In the case of spatial stigma, Macintyre and Ellaway (2003) hypothesize that if respondents report perceiving poor neighborhood reputations, it is likely that they are reporting how they perceive outsiders’ opinions of their neighborhood. Our finding, then, may be explained by the following pathway: our respondents’ perceptions of how outsiders view or talk about their neighborhoods is perhaps more salient than their own perception of their neighborhoods. This externally felt stigma may reveal that respondents living in spatially stigmatized places likely have experienced discrimination based on their neighborhood. On the other hand, as Kearns and colleagues (2013) suggest, individuals experiencing low social status due to their place of residence may suffer from ill mental health due not to external reputations of their neighborhoods, but instead from “self-assessments and self-criticism” within the neighborhood. These prior qualitative studies suggest that multiple pathways may play a role in the associations we observe.

In contrast to our findings on mental health, after adjusting for contextual factors, we did not find an association between spatial stigma and self-rated health. Our inability to establish this link may be explained by two different logics: on one hand, Macintyre and Ellaway (2003) theorize that people living in more disadvantaged neighborhoods may have lower expectations of health compared to those living in more privileged neighborhoods, which decreases their self-rated health. On the other hand, spatial stigma may simply not manifest in lower perceived health in our sample of New Haven participants.

As such, it is important to consider the contextual and potentially local nature of our findings with respect to both mental health and self-rated health. As Keene and Padilla (2014) argued, spatial stigma is a phenomenon that has emerged out of global structures of racism and classism to “express in specific local settings.” Stigmatized places have unique sociohistorical and political contexts, which underscore the importance of local knowledge and research (Del Vecchio Good, 1992). For example, New Haven is a case study in the influence of spatial stigma on health in the United States, with a history of racial redlining and segregation across the city’s 20 neighborhoods, each with unique identities, as well as differences in health outcomes, housing stabilities, educational outcomes, and experiences with the carceral system (Abraham et al., 2016). Consequently, spatial stigma may manifest differently in New Haven than it does in even a comparable small metropolitan area, particularly as it intersects with other race- and class-based stigmas to produce health inequities.

To this end, public health studies exploring the effects of spatial stigma stand to benefit from more critical multimethod inquiry on the spatial conditions of power and control. First, to more robustly understand why place has such an important effect on health, theories and interventions that wrestle with stigmas must “gaze up” (Tyler & Slater, 2018) in order to contextualize them in discourses of power and domination (Parker & Aggleton, 2003). Spatial stigma must be recognized as a process that reifies boundaries of power as much as it is a tool for dispossessing individuals of their right to space in an age of “advanced marginality” (Wacquant, 2008). By situating spatial stigma as a deliberate process in the reproduction of power and control, researchers and policymakers can better understand how discrimination against residents of certain locales is linked to the workings of social inequality. Some scholars, for example, have begun to understand spatial knowledge from the vantage point of those living in stigmatized areas by triangulating geospatial and interview data, which provides platforms for building narratives around place and health (Felner et al., 2018; Thomas, 2016). Clarifying experiences with spatial stigma may also produce a more appropriate measure that wholly captures how residents of spatially stigmatized places think about and navigate their spaces, as well as how they resist stigma (Halliday et al., 2018, 2020; Thomas, 2016).

Additionally, spatial stigma’s implications for power and control illustrate the need for scholars to expand their epistemological assumptions of space. Politically defined boundaries of spaces, like zip codes and neighborhoods, have guided place-based public health research, but as many studies have revealed, these boundaries 1) may not necessarily map onto how local residents think about and navigate their spaces (Corburn, 2003; Weiss et al., 2007) and 2) may actually reify segregation by reinforcing and justifying racial boundaries (Kramer, 2017). As such, to subvert this stigma, place-based research must challenge generally accepted boundaries of space and seek to incorporate local histories and local knowledge that may shape why certain places are spatially stigmatized.

Limitations and conclusions

Our study findings should be interpreted in light of potential limitations. First, it is possible that individuals who experience greater psychological distress are more likely to report worse neighborhood reputations. As such, this study is limited in its ability to identify a causal or directional link between neighborhoods with poor reputation and poor mental health. Nonetheless, our findings are consistent with a large body of qualitative literature that describes the stressful experience of living in places thought by others to be less worthy of habitation (Collins et al., 2016; Graham et al., 2016; Keene & Padilla, 2010; McCormick et al., 2012; Wakefield & McMullan, 2005). In addition, our sample was not designed to be representative of New Haven, and therefore our findings may not be generalizable within and beyond the city. Future studies should utilize larger, representative samples of city-wide data to identify an independent effect of spatial stigma on health. Additionally, given the contextual nature of spatial stigma, future studies in other cities are important in advancing our understanding of how this phenomenon may shape health and geographic health inequalities. Moreover, our variable for spatial stigma, which asked respondents to which extent they agreed that their neighborhood had a good reputation, represents only one conceptualization, dimension, and measurement of spatial stigma. While this measurement is valuable, it may not appropriately or sufficiently capture how this sample uniquely experiences spatial stigma.

Despite these limitations, our study contributes to a growing literature that continues to clarify the relationship between spatial stigma and health. Our findings, suggesting a link between poor neighborhood reputation and severe psychological distress, provide evidence that research should continue to focus on symbolic meanings of health inequalities. In particular, spatial stigma presents a novel avenue to explore social discourse as a mechanism that maintains and exacerbates neighborhood disparities. Researchers have found that like many urban centers across the nation, structural inequities like poverty and poor quality of affordable housing in New Haven disproportionately afflict low-income communities of color, which have been shown to cluster in certain neighborhoods (Anisfeld et al., 2016, 2016; Ricks, 2018). As local and national conversations center around equitable solutions that target the “triadic nexus” of physical, social, and symbolic space (Wacquant et al., 2014), assessing the relationship between spatial stigma and health can serve as a valuable tool for guiding decision-making and future place-based research.

HIGHLIGHTS.

  • 251 low-income people were asked how their neighborhoods were perceived

  • Spatial stigma was associated with psychological distress, independent of neighborhood

  • Spatial stigma was not related to self-rated health in this sample

  • Socially constructed meanings of place influence health

Acknowledgements

Funding for this study was provided by the National Institute of Mental Health and the National Institute of Allergy and Infectious Diseases (RO1MH110192 Kim M. Blankenship, Ph.D., Principal Investigator). The authors thank study participants for their insights; the study’s Community Advisory Board for their input on study design, implementation, and analysis; and study staff for their assistance with data management.

Footnotes

Declarations of interest: None.

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