455426 al of Health and Social Behavior XX(X)Walton 2012
HSBXXX10.1177/0022146512455426Journ
Race, Ethnicity, and Health
Resurgent Ethnicity among Asian Americans: Ethnic Neighborhood Context and Health
Journal of Health and Social Behavior 53(3) 378–394 © American Sociological Association 2012 DOI: 10.1177/0022146512455426 http://jhsb.sagepub.com
Emily Walton1
Abstract In this study I investigate the associations of neighborhood socioeconomic and social environments with the health of Asian Americans living in both Asian ethnic neighborhoods and non-Asian neighborhoods. I use a sample of 1962 Asian Americans from the National Latino and Asian American Study (NLAAS, 200304). Three key findings emerge. First, absolute levels of socioeconomic and social resources do not differ greatly between the Asian ethnic neighborhoods and non-Asian neighborhoods in which Asian Americans live. Second, the ethnic neighborhood context conditions the effects of neighborhood education on health so that higher neighborhood education is related to better self-rated health among Asian Americans only when they live in Asian ethnic neighborhoods. Finally, the social environment, measured by everyday discrimination and social cohesion, does not differ in its health effects for individuals living in Asian ethnic and non-Asian neighborhoods. Together, these findings illuminate the complex ways that racial and ethnic neighborhood concentration impacts health.
Keywords Asian American, ethnic neighborhoods, resurgent ethnicity, segregation, self-rated health
Most racial and ethnic minorities in the United States live in segregated neighborhoods (Iceland 2004; Logan, Stults, and Farley 2004). In addition to being geographically separated from whites, racial and ethnic minorities are systematically separated from health-enhancing resources and opportunities (Logan 2011; Schulz et al. 2002). Indeed, living in neighborhoods with greater ethnic minority concentration is associated with worse overall health and mortality (Williams and Collins 2001). However, research has not fully explored the complex ways in which neighborhoods affect health, especially the ways that living in ethnic neighborhoods might actually be protective, rather than just detrimental to health. Racial and ethnic residential concentration largely results from institutional and interpersonal discrimination that constrains individual choices (Massey and Denton 1993). However, it can also result from individual preferences for living in a
neighborhood that is comfortable and familiar, uncertainty about being an integrationist “pioneer,” and understanding the value of living among a critical mass of people with similar ethnicity (Charles 2005). While the former explanation for residential ethnic concentration leads us to expect harmful health consequences, the latter suggests that there may be benefits to living in ethnically concentrated neighborhoods. Theories that inform contemporary research about the effects of residential ethnic concentration make a distinction between ethnic neighborhoods as materially disadvantaged ghettos (Wilson 1987) 1
Dartmouth College, Hanover, NH, USA
Corresponding Author: Emily Walton, Dartmouth College, Department of Sociology, 6104 Silsby Hall, Hanover, NH 03755 E-mail:
[email protected]
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Walton or as temporary immigrant enclaves (Portes and Bach 1985). But, these theories leave very little room for understanding ethnic neighborhoods as socioeconomically- and socially-successful, semipermanent settlements resulting from preferences for co-ethnic neighbors (Logan, Alba, and Zhang 2002; Wen, Lauderdale, and Kandula 2009). A host of recent studies contradict expectations about the negative health effects of ethnic concentration (Bell et al. 2006; Lee and Ferraro 2007; Walton 2009). This implies that a focus on disadvantage and disorder in ethnic neighborhoods may not capture the inherent complexity and diversity among ethnic neighborhoods, including the positive impact that residence in ethnic neighborhoods might have on health. Studying Asian Americans and their residence in Asian ethnic neighborhoods or non-Asian neighborhoods provides an opportunity to take a fresh look at the impact of co-ethnic residence on health. In particular, Asian ethnic neighborhoods are an appropriate case for investigating heterogeneity in neighborhood effects across contexts because they have greater socioeconomic resources than other residentially concentrated ethnic minority groups (Logan 2011). Asian ethnic neighborhoods have been described as having positive educational and occupational environments that encourage social mobility among residents (Zhou 1992; Zhou and Kim 2006). It may be that when Asian Americans live in Asian ethnic neighborhoods, they also reap the particular benefits of a socioeconomic and social neighborhood environment that is culturally oriented, benefits that may positively affect their health. The overarching goal of this study is to gain a better understanding of the complex links among race, place, and health among Asian Americans. I first describe the socioeconomic, social, and health differences between Asian Americans living in Asian ethnic and non-Asian neighborhoods. Next, I use multilevel analysis to test whether the Asian ethnic neighborhood environment conditions the relationship between neighborhood socioeconomic factors and individual self-rated health. Finally, I examine how the Asian ethnic neighborhood environment conditions the effects of the social environment on self-rated health. I situate the analyses within the theoretical framework of the resurgent ethnicity perspective, which allows for an understanding that social problems do not inherently arise from living among others of the same racial or ethnic group, but rather arise because resources
people need to achieve success in life are not evenly distributed throughout space.
Background Place Stratification in Ethnic Neighborhoods The place stratification perspective is relevant to understanding the effects of disadvantaged neighborhood environments that emerge from and are maintained by individual and institutional discrimination (Charles 2003). Ethnic concentration is seen as a fundamental cause of health disparities because it often leads to a range of socioeconomic and social disadvantages related to worse health (Link and Phelan 1995; Macintyre, Ellaway, and Cummins 2002; Schulz et al. 2002; Williams and Collins 2001). As such, the place stratification perspective aptly theorizes the ways in which disadvantaged neighborhood conditions relate to poorer health outcomes, and this particularly describes the situation in many ethnically concentrated Latino and African American neighborhoods. While place stratification theory has been useful in demonstrating the often negative consequences of racial residential segregation on the health of racial and ethnic minorities, it has not highlighted the diversity of resources in different types of ethnic neighborhoods. In particular, Asian ethnic neighborhoods differ substantially in their material and social resources compared to ethnically concentrated neighborhoods among Latinos and African Americans in the United States. Asian Americans living in ethnic neighborhoods have much lower exposure to poverty and higher household incomes than their Latino and African American counterparts living in ethnic neighborhoods (Logan 2011). Many oncedisadvantaged Asian ethnic neighborhoods established because of discrimination and exclusion at the turn of the twentieth century (Takaki 1989) were rejuvenated with the influx of new immigrants from Asia and investment of domestic and foreign capital that accompanied immigration reform in 1965 (Horton 1995; Li 2009). Today, Asian Americans are forging new ground in suburban and post-suburban pan-ethnic Asian communities, sometimes called ethnoburbs (Li 2009). While these ethnic neighborhoods are home to individuals with high levels of education and income, socioeconomic success does not necessarily imply linguistic and cultural assimilation with mainstream America (Vo and Danico 2004; Wen et al. 2009; Zhou and Kim 2003).
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Journal of Health and Social Behavior 53(3)
Resurgent Ethnicity in Asian Ethnic Neighborhoods
Socioeconomic and Social Environments in Asian Ethnic Neighborhoods
Relevant to understanding ethnic residential concentration among Asian Americans is recent work using the resurgent ethnicity perspective. This perspective emphasizes choice and preference for living among others of similar ethnicity to explain the persistence of ethnic neighborhoods over time, despite social mobility and the dismantling of formal discriminatory practices (Logan et al. 2002; Wen et al. 2009). In their recent examination of resurgent ethnicity, Wen and colleagues (2009) claim that the cultural and economic aspects of race should be decoupled while calling for empirical tests of the circumstances under which living in ethnic neighborhoods can be beneficial. For example, in her description of two Vietnamese neighborhoods, Aguilar-San Juan (2009) argues that ethnic places reinforce group identity and belonging, which allows individuals to “stay Vietnamese” despite showing conventional signs of becoming American, like speaking English, participating in politics, and living in suburban areas. Fugita and O’Brien (1991) show similar findings when examining the persistence of ethnic identity in Japanese American communities. The implication of resurgent ethnicity is that ethnic concentration may be accompanied by health-promoting socioeconomic and social resources. Supporting this idea, a national study of Asian Americans found that those living in more segregated metropolitan areas were more likely to have a baby with healthy birth weight compared to Asian Americans living in more integrated metropolitan settings (Walton 2009). Some research among other racial and ethnic groups demonstrates that there may be beneficial health effects accompanying ethnic concentration. Latinos and African Americans living in more ethnically homogeneous areas lose fewer years of life to heart disease (Franzini and Spears 2003) and perceive fewer barriers to receiving health care (Haas et al. 2004) compared to peers living in less homogeneous areas. Similarly, Lee and Ferraro (2007) report that second- and later-generation Mexican Americans living in ethnically isolated neighborhoods, those in which the likelihood of encountering a white person is low, have fewer physical pain symptoms and report less disability compared to those living in less ethnically isolated neighborhoods.
Socioeconomically, the resurgent ethnicity perspective suggests that racial and ethnic concentration is not necessarily associated with institutional abandonment. There may be greater poverty in ethnically concentrated communities, but there also may be greater socioeconomic heterogeneity, including a greater presence of affluent and well-educated neighbors. Having a higher percentage of affluent or well-educated neighbors is positively related to health (Galea and Ahern 2005; Wen, Browning, and Cagney 2003). Greater human capital among neighborhood adults may lead to a heightened presence of high-quality local institutions because individuals have greater power to advocate for health-enhancing resources in their community. In addition, the presence of affluent and well-educated neighbors may provide the resources necessary to sustain basic neighborhood institutions, like churches, voluntary organizations, and service programs, which improve social relationships and individual well-being (Browning and Cagney 2003). Therefore, consistent with the resurgent ethnicity perspective, my first hypothesis is: Socioeconomic resources, particularly the presence of affluent and highly educated neighbors, will be higher in Asian ethnic neighborhoods compared to non-Asian neighborhoods. Socially, the resurgent ethnicity perspective implies that the ethnic neighborhood need not be synonymous with social disorganization because the ability to exercise choice in one’s ethnic environment may mean that ethnic concentration brings concomitant social benefits. To capture the neighborhood social environment, researchers have used measures of collective efficacy, perceived safety, social exchange, and social contact (Franzini et al. 2005). In this study, I characterize the social environment in terms of everyday discrimination and social cohesion because these psychosocial indicators may be particularly responsive to the ethnic climate of the neighborhood and they have been shown to relate to health status. A growing body of research shows that perceptions of racial discrimination are lower in ethnic neighborhoods because people have fewer opportunities for encounters with whites (Hunt et al. 2007; Pickett and Wilkinson 2008). In the case of a thriving, institutionally complete ethnic neighborhood (Breton 1964), residents would have little
Walton reason to go outside of their neighborhood for work, schooling, shopping, health care, and other business and thus have even fewer opportunities for encountering racial and ethnic discrimination. Experiences of discrimination have repeatedly been shown to relate to poorer health and emotional well-being (Forman, Williams, and Jackson 1997; Gee et al. 2007; Karlsen and Nazroo 2002). Reduced exposure to racial discrimination may be an important pathway through which ethnic neighborhoods can be protective of health (Bécares, Nazroo, and Stafford 2009; Halpern and Nazroo 1999; Smaje 1995). Social cohesion may be higher in ethnically concentrated neighborhoods because people are more likely to interact with and trust those who are like them (McPherson, Smith-Lovin, and Cook 2001). Putnam (2007) argues that as racial diversity increases in the local neighborhood environment, it is accompanied by lower levels of social cohesion because people are more likely to “hunker down,” or turn inward and have less trust of their neighbors. Social cohesion with neighbors may promote healthy behaviors and increase information about and access to health-related services (Kawachi and Berkman 2000). A higher degree of social cohesion with friends and neighbors may also promote the diffusion of health-related information (Viswanath, Steele, and Finnegan 2006). As such, my second hypothesis is: Social resources, particularly lower exposure to discrimination and higher social cohesion, will be greater in Asian ethnic neighborhoods compared to nonAsian neighborhoods. The concentration of a socioeconomically successful ethnic group within a geographically bounded neighborhood may be a way of sustaining a structural environment where activities are oriented toward co-ethnics in a way that is conducive to good health and well-being. Residents of coethnic neighborhoods are likely to be more embedded in bounded social networks, which can promote cooperative behavior and increase the sharing of resources (Coleman 1988). Zhou and Kim (2006) conceptualize the ethnic community as a particular site where culture and structure interact; in their view, the boundaries of the ethnic community contain a common cultural heritage,
381 shared values, and behavioral standards while also containing relevant ethnic institutions, like economic, sociocultural, and religious organizations. This combination of neighborhood socioeconomic resources and the opportunity for residents to invest in cultural institutions or culturally appropriate services might make ethnically concentrated neighborhoods particularly health promoting. These theoretical perspectives provide rationale for my third hypothesis: The Asian ethnic neighborhood context conditions the association between neighborhood socioeconomic resources and health such that Asian Americans will benefit more from neighborhood socioeconomic resources when living in an Asian ethnic neighborhood compared to living in a non-Asian neighborhood. It could be that living in an Asian ethnic neighborhood protects Asian Americans from the harmful health effects of discrimination by providing opportunities for individuals to develop a greater sense of ethnic identity. In a study of Filipino Americans, Mossakowski (2003) found that ethnic identity, as measured by having a sense of ethnic pride, being involved in ethnic practices, and cultural commitment to one’s ethnic group, buffered the effects of racial and ethnic discrimination on depressive symptoms. The influence of social cohesion on health may also be exceptionally strong within the clearly defined boundaries of an ethnic neighborhood, where shared cultural models and value orientations increase the incentive for residents to behave according to community norms (Fukuyama 2000). In an ethnic neighborhood, social cohesion may be particularly predictive of health because co-ethnic ties form a basis upon which residents can build a sense of common identity and community belonging. Having a sense of community belonging has been shown to relate to health-related behavior change, specifically positive changes to exercise (Hystad and Carpiano 2012). These theoretical and empirical perspectives lead to my final hypothesis: Asian ethnic neighborhood context conditions the association between neighborhood social resources and health such that Asian Americans will benefit more from neighborhood social resources when living in an Asian ethnic neighborhood compared to living in a nonAsian neighborhood.
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data and Methods Individual-level data come from the National Latino and Asian American Study (NLAAS) collected in 2003-04 (Alegría et al. 2004). The NLAAS comprises a nationally representative household sample of Asian American adults. Participants in the NLAAS core sample were identified using a multistage stratified area probability sampling design. These sampling procedures required the construction of weighting corrections to take into account joint probabilities of selection (Heeringa 2004). Trained interviewers administered the NLAAS questionnaire in the participant’s preferred language in a face-to-face interview unless the respondent specifically requested a telephone interview. Interviews were completed with 2,095 Asian adults age 18 or older. The subsample included in the current study is limited to the respondents of Asian descent living in counties containing census-defined metropolitan areas (with a core urban area of 50,000 or more population) and not missing data on any variables in the analyses (N = 1,962). Detailed descriptions of the methods used in NLAAS appear elsewhere (Heeringa et al. 2004; Pennell et al. 2004). I use data from the Census 2000 in two ways. From Summary File 3 (SF3), I gleaned socioeconomic data at the census-tract level for use as contextual variables in hierarchical linear models. I also downloaded Census 2000 TIGER/Line® shapefiles and demographic data from Summary File 1 (SF1) to identify ethnic neighborhood boundaries in 105 nationally representative counties. Counties were explicitly chosen to match those sampled in the NLAAS. I identify geographic “hot spots” consisting of clusters of census tracts with high Asian ethnic density that exhibit spatial autocorrelation with contiguous census tracts, indicated by significant values of the local Moran statistic (Anselin 1995; Logan et al. 2002). An Asian ethnic cluster is composed of a focal census tract and all contiguous tracts with similarly high Asian ethnic concentration relative to the mean concentration in the county. An important aspect of the spatial definition is that to be included in an ethnic cluster, tracts are required to be contiguous to other tracts with similarly high proportions of Asian Americans, and tracts that are geographically isolated in their high concentration are not included.
Journal of Health and Social Behavior 53(3) Logan and colleagues (2002) hypothesized that ethnic neighborhoods with sometimes modest shares of group members may be better able to support an ethnic infrastructure (e.g., sociocultural institutions, social networks, churches) if they are spread out over a larger area of contiguous tracts. The requirement that tracts not be isolated reinforces the idea that clustering of multiple tracts may accentuate the ethnic character of a neighborhood by aggregating more group members in a delineated space. For each county, I used the following procedures to determine whether census tracts were part of Asian ethnic neighborhoods. First, I joined each census tract shapefile with demographic data, constraining the spatial weight structure such that only contiguous census tracts are considered to influence the spatial autocorrelation. I then calculated the local Moran statistic for each census tract based on the proportion of Asians (total population reporting their race as “Asian alone” divided by the total population in the tract) and evaluated the statistical significance. I determined that all tracts with high and significant spatial autocorrelation were part of an Asian ethnic cluster. Each census tract in all counties was then assigned a designation of in or not in an Asian ethnic neighborhood. I merged these neighborhood definitions by census tract with the NLAAS individual-level data. The final number of tracts included in the analysis is 256, where 79 tracts are in Asian ethnic neighborhoods and 177 tracts are not.
Measures Dependent variable. The health status outcome I use is self-rated health. The NLAAS interview asked, “How would you rate your overall physical health—excellent, very good, good, fair or poor?” The variable is reverse coded in the analyses so that 5 = excellent and 1 = poor, in order to interpret positive coefficients as being related to better health status. Self-rated health is a robust indicator of general health status that predicts morbidity, mortality, subsequent disability, and health care utilization (Ferraro and Yu 1995; Gomez et al. 2004; Idler and Benyamini 1997; Mutchler and Burr 1991). Neighborhood-level variables. All analyses are stratified by ethnic neighborhood residence. As described earlier, a respondent’s census tract is
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Walton designated as either in or not in an Asian ethnic neighborhood. I use the term ethnic neighborhoods to refer to the clustered groups of racially concentrated Asian census tracts. I do this with the understanding that the term Asian signifies a racial group whose boundaries are both socially and politically determined. The term ethnic often implies shared language and culture. I focus on a pan-ethnic Asian category and chose to conceptualize ethnicity this way because of the national scale of analyses. Apart from the traditional gateway cities with large sub-ethnic population concentrations, in many cases Asian Americans reside in pan-ethnic Asian neighborhoods. Substantively, pan-ethnicity may reflect solidarity in response to shared experiences of discrimination and categorization by others (Espiritu 1992). Panethnicity is not meant to represent similar origins among Asian sub-ethnic groups. Using a panethnic Asian category to define neighborhood boundaries complicates our interpretation of the effects of ethnic neighborhoods because a shared language and historical background may be inaccurate assumptions at the neighborhood level. I test the direct effects of three continuous census tract-level variables: proportion of the population educated with at least a high school degree, median household income (in thousands of dollars), and proportion of individuals in poverty. I include additional tract-level variables in the descriptive statistics to give a sense of the diversity between neighborhood types. These include summary measures of proportions non-Hispanic white, non-Hispanic black, Hispanic ethnicity alone, and foreign born in the census tract. Individual-level demographic variables. I control for a number of individual factors that may be related to health status. Asian American ethnicity is categorized as a series of dummy variables representing Vietnamese, Filipino, Chinese (reference group in analyses), and Other Asian (Asian Indian, Japanese, Korean, or Other Asian). Family size is measured as the number of individuals living in the household. Marital status is operationalized as a dummy variable representing currently married or cohabiting (1) versus not currently married or cohabiting (0). The respondent’s gender is coded female (1) and male (0). Age is a continuous variable measured in years. Nativity is operationalized as immigrant (1) and US-born (0).
Individual-level socioeconomic variables. Subjective social status is measured by a symbolic ladder with 10 rungs, where the first and tenth rung represent the lowest and highest social status, respectively (Adler et al. 2000). Education is analyzed as a continuous variable measured in years. Household income is the sum of the midpoints of the following income measures: personal, spouse, other family members, social security, government assistance, and other sources. Because of a large number of missing values (270 missing), the household income variable used in these analyses was imputed using hot deck methods based on the variables of ethnicity, gender, age, education, household composition, and employment status. Household income is operationalized in thousands of dollars in order to make interpretation more meaningful. Individual-level psychosocial variables. Everyday discrimination is a scale measuring the frequency of routine experiences of unfair treatment. Respondents indicate how often they experience situations such as being treated with less respect than other people, having people act afraid of them, and being called names or insulted. The scale has been used extensively in the mental health field (Boardman et al. 2001; Mays and Cochran 2001). The scale ranges from 9 to 54, with higher scores representing more incidences of everyday discrimination. In the present sample, the scale has strong internal consistency (α = .91). Social cohesion is a fouritem scale measuring perceptions of trust and neighborliness. Respondents rated the truth of statements regarding: whether people in the neighborhood could be trusted, generally got along with each other, would help out in an emergency, and look out for each other. Responses range from 4 to 16, with higher values indicating more neighborhood social cohesion. The scale has strong internal consistency (α = .82) in the present sample.
Analyses I use hierarchical linear models (HLM) to assess the relationship of neighborhood and individual factors with self-rated health. A hierarchical model explicitly incorporates variables at the individual and neighborhood levels and accounts for the clustering of individuals (Raudenbush and Bryk 2002; Snijders and Bosker 1999). My primary interest is
384 in how neighborhood socioeconomic and individual social variables explain variability in individual self-rated health and how these relationships vary by residence in an Asian ethnic neighborhood. In preliminary analyses, significant variation at the census tract level was found for self-rated health, justifying incorporating neighborhoodlevel variables into the models. The analyses are weighted at the individual level to account for the complex sampling design in the NLAAS. I stratify by Asian ethnic and non-Asian neighborhoods and perform the same set of nested analyses for each. First, self-rated health is regressed on neighborhood socioeconomic variables. Then I include individual control variables representing the known correlates of self-rated health, followed by the addition of individual socioeconomic variables. Next, I add individual-level psychosocial variables (everyday discrimination and social cohesion) to the full individual model one at a time. All continuous variables are centered on their respective grand means. To assess group differences in the coefficients across neighborhood types, I use a two-sample t test (Wooldridge 2009).
Results Sample Description Table 1 summarizes the descriptive statistics for the entire sample of Asian American adults and also stratified by residence in an Asian ethnic or non-Asian neighborhood. At the individual level, to account for clustering of individuals within census tracts I used multilevel bivariate assessments for all significance tests of differences between Asian ethnic and non-Asian neighborhoods. In terms of socioeconomic context, Asian ethnic neighborhoods have significantly higher median household income while proportions of adults (age 25+) with a high school degree and residents in poverty do not vary across neighborhood types. Asian ethnic neighborhoods are about 28 percent Asian compared to 11 percent Asian in the nonAsian neighborhoods. In terms of the racial and ethnic composition beyond Asian, there are higher percentages of whites in non-Asian neighborhoods (51 percent white) compared to Asian ethnic neighborhoods (38 percent white). Proportions of black and Hispanic individuals do not differ
Journal of Health and Social Behavior 53(3) between Asian ethnic and non-Asian neighborhoods (black 8 percent to 10 percent; Hispanic 21 percent to 23 percent). Asian ethnic neighborhoods do have higher percentages of foreign-born individuals (34 percent) compared to non-Asian neighborhoods (25 percent). Levels of self-rated health do not significantly differ at the bivariate level by Asian ethnic neighborhood residence. In other words, without consideration of other neighborhood- or individual-level characteristics, it appears that living in an Asian ethnic neighborhood among others of similar ethnicity is neither protective nor harmful for health status. We can see that most ethnic subgroups are not distributed evenly across neighborhood types. Vietnamese and Chinese Americans are overrepresented in Asian ethnic neighborhoods, Other Asian Americans (includes Indian, Korean, Japanese, and other Asian ethnic groups) are underrepresented in Asian ethnic neighborhoods, and Filipino Americans do not differ in their distribution across neighborhood types. At the individual level, there are no other statistically significant demographic or socioeconomic differences across neighborhood types. In terms of the social environment, individuals experience more everyday discrimination when living in a non-Asian neighborhood, but social cohesion does not systematically differ across neighborhood types. Table 2 reports the results of multilevel analyses that regress self-rated health on neighborhood and individual characteristics, stratified by Asian ethnic neighborhood residence. I first ran null models containing no predictors, to determine the amount of variability in self-rated health explained by a common intercept and random individual- and neighborhood-level variation. In these models, the intraclass correlation (ICC) was .064 in Asian ethnic neighborhoods and .057 in non-Asian neighborhoods, indicating that 6.4 percent and 5.7 percent of the variation in self-rated health in the models is due to between-neighborhood differences, while most of the variation in self-rated health is due to individual-level factors. Model 1a presents the associations of neighborhood socioeconomic characteristics with health status within Asian ethnic neighborhoods. In Asian ethnic neighborhoods, having a larger proportion of the neighborhood population with at least a high
385
.15 21.49 .10 .26 .16 .20 .17 .16
SD .27 15.60 .00 .01 .00 .00 .01 .00
.98 132.50 .49 .98 .98 .94 .75 .72
Minimum Maximum
1.01 .43 .43 .45 .42 1.64 .46 .50 14.67 .42 1.90 3.37 9.86 6.51 2.45
3.46
.24 .25 .29 .23 2.87 .70 .51 40.97 .78
5.80 13.72 81.68
16.07 12.64
SD
9 4
0 0 –2
0 0 0 0 1 0 0 18 0
1
52 16
10 17 1125
1 1 1 1 13 1 1 95 1
5
Minimum Maximum
All Neighborhoods (N = 1,962)
Mean
.78 50.88 .13 .47 .09 .22 .27 .16
Mean
15.65 12.67
5.74 13.56 82.33
.26 .25 .32 .17 2.88 .72 .51 41.65 .79
3.46
Mean
.78 55.27 .12 .38 .08 .21 .34 .28
Mean .32 15.60 .00 .04 .00 .02 .07 .02
.97 132.50 .49 .89 .68 .74 .68 .72
Minimum Maximum
6.38 2.44
1.90 3.49 89.94
.44 .43 .47 .38 1.57 .45 .50 14.95 .41
1.02
SD
9 4
1 0 –1
0 0 0 0 1 0 0 18 0
1
46 16
10 17 1103
1 1 1 1 9 1 1 95 1
5
Minimum Maximum
Asian Ethnic Neighborhoods (n = 880)
.14 25.45 .10 .22 .11 .16 .16 .18
SD
Asian Ethnic Neighborhoods (n = 79)
16.41 12.63
5.85 13.84 81.16
.22 .25 .26 .27 2.86 .69 .52 40.43 .77
3.46
.16 19.22 .08 .27 .17 .22 .17 .12
SD .27 18.19 .00 .01 .00 .00 .01 .00
.98 116.30 .42 .98 .98 .94 .75 .63
Minimum Maximum
6.59 2.46
1.90 3.27 91.64
.42 .43 .44 .45 1.70 .46 .50 14.42 .42
1.00
SD
9 4
0 0 –2
0 0 0 0 1 0 0 18 0
1
52 16
10 17 1125
1 1 1 1 13 1 1 88 1
5
Minimum Maximum
Non-Asian Neighborhoods (n = 1,082) Mean
.76 48.92 .12 .51 .10 .23 .25 .11
Mean
Non-Asian Neighborhoods (n = 177)
Note: Significant Difference refers to statistically significant differences between Asian ethnic and non-Asian neighborhoods, calculated by an independent sample t test. *p < .05. **p < .01. ***p < .001.
Outcome variable Self-rated health (5 = excellent) Demographic variables Vietnamese Filipino Chinese Other Asian Family size (persons) Married or cohabiting Female Age (years) Immigrant Socioeconomic variables Subjective social status Education (years) Household income (thousands) Psychosocial variables Everyday discrimination Social cohesion
Individual Level
Proportion with education ≥ 12 years Median family income (thousands) Proportion in poverty Proportion white Proportion black Proportion Hispanic Proportion foreign born Proportion Asian
Neighborhood Level
All Neighborhoods (N = 256)
Table 1. Descriptive Statistics for the Full Sample and Stratified by Asian Ethnic Neighborhood Type
* ** *** **
Significant Difference
* *** *** ***
Significant Difference
386 school degree is associated with better individual health. The ICC in Model 1a is reduced to .014, indicating that the three neighborhood indicators account for a substantial portion of the betweenneighborhood variance. A comparable analysis in non-Asian neighborhoods (Model 1b) demonstrates that having a greater percentage of residents with higher levels of education in the neighborhood is not associated with individual health status. The ICC for Model 1b is .048, not much lower than .057 in the unconditional model, confirming that these neighborhood factors are less predictive of health in general and do not account for much of the between-neighborhood variation in self-rated health in the non-Asian neighborhoods. An independent two-sample t test reveals that the education coefficients significantly differ between Models 1a and 1b in their relationship with better self-rated health (Model 1a: b = 2.242, p < .001; Model 1b: b = –.237, p > .05; t = 1.360, p < .05). In Models 2a and 2b I add individual-level demographic characteristics (ethnicity, family size, marital status, gender, age, and nativity) to the analyses. The addition of demographic characteristics results in a reduction of the strength and magnitude of the neighborhood education effect; however, having a higher proportion of highly educated individuals in the neighborhood is still positively related to better health in Asian ethnic neighborhoods. Model 2b also results in a diminution of the nonsignificant education coefficient. Model 3a additionally controls for individual socioeconomic characteristics, resulting in a further attenuation of the strength and magnitude of neighborhood-level education; however, it remains significantly positive in its association with better health. Model 3b, a mirror analysis of Model 3a in non-Asian neighborhoods, results in an increase in the magnitude and strength of the negative neighborhood poverty association with good health, an association that almost reaches statistical significance (p < .10). This same relationship is not present in Asian ethnic neighborhoods, and the differences in poverty coefficients are statistically significant (Model 3a: b = .156, p > .05; Model 3b: b = –1.170, p < .10; t = 1.468, p < .05). Interestingly, while neighborhood-level education is associated with good health in Asian ethnic neighborhoods, individual-level education is not
Journal of Health and Social Behavior 53(3) associated with good health in either type of neighborhood. Table 3 investigates the relationships of psychosocial indicators of the social environment with self-rated health, stratified by ethnic neighborhood type. In Model 1a we can see that for individuals living in Asian ethnic neighborhoods, everyday discrimination is not directly related to health status. Though everyday discrimination is marginally related to worse self-rated health in non-Asian neighborhoods, an independent two-sample t test reveals that the discrimination coefficients do not significantly differ between Models 1a and 1b in their relationship with self-rated health (Model 1a: b = –.004, p > .05; Model 1b: b = –.009, p < .10; t = .640, p > .05). Examining the effects of social cohesion in Model 2a, we can see that it is not significantly related to self-rated health in Asian ethnic neighborhoods. Model 2b demonstrates that higher levels of social cohesion are associated with better self-rated health in non-Asian neighborhoods. However, an independent two-sample t test again reveals that the social cohesion coefficients do not significantly differ between Models 2a and 2b in their relationship with self-rated health (Model 2a: b = .019, p > .05; Model 2b: b = .031, p < .05; t = .640, p > .05). Also, when including social cohesion in Model 2b, the coefficient for proportion of neighborhood poverty is reduced, moving from marginally significant to not significant at p < .10, indicating that the relationship of neighborhood poverty with worse individual health in non-Asian neighborhoods is partially mediated by social cohesion.
Discussion Adopting a resurgent ethnicity perspective for this study has allowed for an investigation of some of the potential benefits of living in ethnic neighborhoods. Focusing on the residential experiences of Asian Americans provides a novel perspective for understanding the resources and opportunities that are present in ethnic neighborhoods and their health effects. This study demonstrates that levels of socioeconomic and social resources are very similar for Asian Americans living in different ethnic neighborhood contexts. However, these
387
Note: Omitted Asian ethnic category is Chinese. † p < .10. *p < .05. **p < .01. ***p < .001.
.013 .964 .014 2,492.269
1.437** (.509) –.001 (.003) .066 (.591)
2.242*** (.418) –.004 (.003) –.149 (.772)
.010 .892 .011 2,448.407
.241* (.110) .361** (.130) .352* (.142) .010 (.022) .155 (.088) –.149 (.081) –.015*** (.003) –.079 (.098)
3.273*** (.149)
B (SE)
Model 2a
3.467*** (.046)
B (SE)
Intercept Neighborhood-level variables Proportion education ≥ 12 years Median family income (thousands) Proportion in poverty Individual-level variables Vietnamese Filipino Other Asian Family size Married or cohabiting Female Age Immigrant Subjective social status Education (years) Household income (thousands) Neighborhood-level variance Individual-level variance Intraclass correlation Deviance
Model 1a
B (SE)
Model 3a
(.499) (.002) (.479)
.237 .001 –.737
B (SE)
Model 3b
3.287*** (.090) (.327) –.057 (.317) –.246 (.279) (.003) .000 (.003) –.001 (.003) (.867) –1.068 (.793) –1.170† (.766) –.047 (.089) .041 (.086) .193** (.071) .148* (.067) .249*** (.068) .213** (.065) –.003 (.019) .010 (.018) .128* (.065) .078 (.065) –.074 (.062) –.091 (.057) –.011*** (.003) –.009*** (.002) .026 (.074) .065 (.069) .134***(.021) .003 (.010) –.000 (.000) .031 .016 .933 .890 .032 .018 3,064.482 3,026.365
3.275*** (.095)
B (SE)
Model 2b
Non-Asian Neighborhoods
3.457*** (.039)
B (SE)
Model 1b
.329** (.094) .303** (.117) .337* (.132) .009 (.024) .074 (.087) –.142 (.080) –.013*** (.003) –.047 (.093) .096*** (.024) .009 (.014) .001* (.001) .006 .049 .852 .954 .007 .048 2,427.395 3,071.243
1.028* –.002 .156
3.300*** (.136)
Asian Ethnic Neighborhoods
Table 2. Hierarchical Linear Models of the Effects of Neighborhood- and Individual-Level Factors on Self-Rated Health (1 = Poor, 5 = Excellent), Stratified by Ethnic Neighborhood Type
388 .006 .853 .007 2437.344
(.006)
–.004
.006 .852 .007 2427.395
(.499) (.491) (.468)
1.021* –.002 .140
1.028* (.499) –.002 (.002) .156 (.479)
.006 .851 .007 2434.016
.019
(.017)
1.013* (.503) –.002 (.003) .136 (.481)
3.297*** (.135)
B (SE)
Model 2a
.016 .890 .018 3026.365
–.246 (.279) –.001 (.003) –1.170† (.766)
3.287*** (.090)
B (SE)
Model 3b (from Table 2)
.016 .888 .018 3033.563
–.009†
–.235 –.001 –1.176†
(.005)
(.278) (.003) (.754)
3.312*** (.090)
B (SE)
Model 1b
B (SE)
Model 2b
.016 .886 .017 3028.809
3.291*** (.089) –.281 (.282) –.000 (.003) –1.061 (.760) .031* (.013)
Non-Asian Neighborhoods
Note: All models control for Asian American ethnicity, family size, marital status, gender, age, nativity, subjective social status, education, and household income. † p < .10. *p < .05. **p < .01. ***p < .001.
Neighborhood-level variance Individual-level variance Intraclass correlation Deviance
3.312*** (.137)
B (SE)
Model 1a
3.300*** (.136)
B (SE)
Intercept Neighborhood-level variables Proportion education ≥ 12 years Median family income (thousands) Proportion in poverty Individual-level variables Everyday discrimination Social cohesion
Model 3a (from Table 2)
Asian Ethnic Neighborhoods
Table 3. Hierarchical Linear Models of the Effects of Neighborhood- and Individual-Level Factors on Self-Rated Health (1 = Poor, 5 = Excellent) Stratified by Ethnic Neighborhood Type
Walton socioeconomic factors have heterogeneous effects on self-rated health across neighborhood contexts, adding complexity to our understanding of the health effects of ethnic residential concentration. The first hypothesis, that socioeconomic resources would be higher in Asian ethnic neighborhoods, was only partially supported. Median family income is slightly higher in Asian ethnic neighborhoods, but other neighborhood socioeconomic indicators, like educational attainment and poverty status, did not differ based on Asian ethnic neighborhood context. My second hypothesis, predicting that neighborhood social resources would be greater in Asian ethnic neighborhoods, was also only partially supported. Experiences of everyday discrimination were lower in Asian ethnic neighborhoods, but social cohesion did not differ between the two neighborhood types. These surprising findings are supported by a recent study of social cohesion among Mexican Americans in Chicago (Almeida et al. 2009). These authors found that a higher percentage of co-ethnics in the neighborhood was related to greater numbers of social ties in the neighborhood but was not directly related to greater social cohesion; instead, social cohesion was more responsive to other neighborhood-level factors, like neighborhood poverty, residential stability, and the proportion of elderly residents. I found support for my third hypothesis, that the relationship of neighborhood socioeconomic status with health would be conditional on the ethnic neighborhood environment, in the case of educational attainment. Better health is associated with higher neighborhood-level education only when Asian American individuals live in Asian ethnic neighborhoods. Education has repeatedly been shown to affect health directly—by conferring health-promoting habits and skills—and indirectly by providing better work opportunities and economic and social psychological resources and improving health-related behaviors (Elo and Preston 1996; Ross and Wu 1995). One study investigating the relationship of neighborhood education and health found that having more highly educated individuals in the neighborhood relates to better health among all residents, not just the highly educated residents (Galea and Ahern 2005). These authors speculate that presence of more-educated neighbors could bring an improvement in the shared resources available to all residents at the
389 level demanded by the most highly educated residents, like a rising tide lifting all boats. I posit that greater network closure among residents of ethnic neighborhoods could mean that the resources linked to neighborhood education are specifically ethnic in nature and that co-ethnic individuals are in a position to take greater advantage of the resources (Coleman 1988). The first generation of studies on neighborhoods and health worked under the broad assumption that the effects of neighborhood conditions were homogeneous across populations and neighborhood contexts (Small and Feldman 2012). However, the current study suggests that neighborhood effects may be heterogeneous across ethnic neighborhood contexts even within the same racial or ethnic group. This heterogeneity across contexts contributes to a growing body of literature that challenges our assumptions about the effects of residential racial and ethnic concentration. For example, in her study of black and white children, Turley (2003) found that black children did not benefit from higher neighborhood income in predominantly white neighborhoods. It was only in neighborhoods with a higher proportion of black residents that black children benefited from having high-income neighbors, a finding she interpreted to mean that black children are more likely to be influenced by black friends than white friends. The last hypothesis, predicting that the social environmental effects on health would differ according to ethnic neighborhood context, was not supported. The relationship of both everyday discrimination and social cohesion with health does not differ across neighborhood types. Everyday discrimination is not related to self-rated health in Asian ethnic neighborhoods and was only marginally related to self-rated health in non-Asian neighborhoods. Importantly, these findings do not support the perspective that health is better in ethnic neighborhoods because of increased social support or kinship structures, as hypothesized by some scholars who find ethnic neighborhoods relate to better mortality outcomes and self-rated health among Latinos (Eschbach et al. 2004; Patel et al. 2003). Instead, the findings show that social cohesion is significantly related to the health of Asian Americans only in non-Asian neighborhoods. In non-Asian neighborhoods, social cohesion mitigates some of the negative effects of neighborhood
390 poverty on health. These surprising findings warrant further investigation of the circumstances under which social cohesion can benefit health. The findings offered in this study should be considered in light of some limitations. First, the cross-sectional design of the NLAAS makes causal inferences difficult. This is especially problematic for studies of neighborhood health effects because individuals are not randomly selected into neighborhoods, rather individuals may select themselves into certain types of neighborhoods. Recently, some longitudinal work has been devoted to clarifying the nature of causality in the neighborhood socioeconomic context and health relationship, finding that neighborhood disadvantage predicts the onset of fair/poor self-rated health (Glymour et al. 2010). Second, like many other studies involving neighborhood effects, I use census-derived socioeconomic variables, rather than objectively measuring ecological characteristics of neighborhoods. Contextual resources are typically measured by aggregating individual socioeconomic characteristics, which can be taken as markers of neighborhood infrastructure and social conditions. It is particularly important that future studies measure the ways in which the socioeconomic conditions of a neighborhood relate to the social and cultural institutions hypothesized to be more abundant in Asian ethnic neighborhoods. A final limitation is that I combine all Asian Americans into a pan-ethnic category, rather than giving detailed attention to the ways in which residential circumstances may differ along ethnic lines. I recognize and value the differences between ethnic groups subsumed under the broad, socially determined “Asian” category and suggest that future analyses attend to understanding how these differences are manifested in the relationship between ethnic neighborhoods and health. While it is recognized that large-scale Asian immigration has changed the demographic profile of the United States, we do not fully understand how these patterns and trends have shaped how inequality operates in American society. Vertovec (2007), addressing racial and ethnic inequality in Britain, suggests that conventional theories and models may need to be revised or replaced to better capture how immigration changes the dynamic interplay among race and ethnicity with gender, age, and socioeconomic status. This article shows
Journal of Health and Social Behavior 53(3) that our understanding about how place affects health in ethnic neighborhoods may also need revision. Conceptualizing ethnic residential concentration in terms of resources and opportunities allows for a more complex understanding of the socioeconomic and social benefits that accompany a coethnic neighborhood. This study demonstrates that socioeconomic resources in neighborhoods exert beneficial health effects for Asian Americans only in the context of Asian ethnic residential concentration. Understanding the socioeconomic and social factors that are associated with health and the ethnic contexts within which they operate may provide insight into strategies that ensure that ethnically concentrated neighborhoods act as stepping-stones for social mobility and good health, rather than as disadvantaged, disorganized environments that reproduce inequality generation after generation.
Funding The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported in part by the Asian American Center on Disparities Research (National Institute of Mental Health grant: 1P50MH073511-01A2) and by NIH Research Grants MH62207 and MH62209 funded by the National Institute of Mental Health and RWJ DA18715 with generous support from SAMHSA and OBSSR. I also wish to thank the Robert Wood Johnson Foundation Health & Society Scholars program for its financial support.
References Adler, Nancy E., Elissa S. Epel, Grace Castellazzo, and Jeannette R. Ickovics. 2000. “Relationship of Subjective and Objective Social Status With Psychological and Physiological Functioning: Preliminary Data in Healthy White Women.” Health Psychology 19:586– 592. Aguilar-San Juan, Karin. 2009. Little Saigons: Staying Vietnamese in America. Minneapolis: University of Minnesota Press. Alegría, Margarita, David Takeuchi, Glorisa Canino, Naihua Duan, Patrick Shrout, Xiao-Li Meng, William Vega, Nolan Zane, Doryliz Vila, Meghan Woo, Javier Escobar, Keh-Ming Lin, and Fong Gong. 2004. “Considering Context, Place and Culture: The
Walton National Latino and Asian American Study.” International Journal of Methods in Psychiatric Research 13:208–22. Almeida, Joanna, Ichiro Kawachi, Beth E. Molnar, and S. V. Subramanian. 2009. “A Multilevel Analysis of Social Ties and Social Cohesion among Latinos and Their Neighborhoods: Results from Chicago.” Journal of Urban Health 86:745–59. Anselin, Luc. 1995. “Local Indicators of Spatial Association—LISA.” Geographical Analysis 27:93–116. Bécares, Laia, James Nazroo, and Mai Stafford. 2009. “The Buffering Effects of Ethnic Density on Experienced Racism and Health.” Health & Place 15:700– 08. Bell, Janice F., Frederick J. Zimmerman, Gunnar R. Almgren, Jonathan D. Mayer, and Colleen E. Huebner. 2006. “Birth Outcomes among Urban AfricanAmerican Women: A Multilevel Analysis of the Role of Racial Residential Segregation.” Social Science & Medicine 63:3030–45. Boardman, Jason D., Brian K. Finch, Christopher G. Ellison, David R. Williams, and James S. Jackson. 2001. “Neighborhood Disadvantage, Stress, and Drug Use among Adults.” Journal of Health and Social Behavior 42:151–65. Breton, Raymond. 1964. “Institutional Completeness of Ethnic Communities and the Personal Relations of Immigrants.” American Journal of Sociology 70:193–205. Browning, Christopher R. and Kathleen A. Cagney. 2003. “Moving Beyond Poverty: Neighborhood Structure, Social Processes and Health.” Journal of Health and Social Behavior 44:552–71. Charles, Camille Zubrinsky. 2003. “Dynamics of Racial Residential Segregation.” Annual Review of Sociology 29:167–207. Charles, Camille Zubrinsky. 2005. “Can We Live Together? Racial Preferences and Neighborhood Outcomes.” Pp. 45–80 in The Geography of Opportunity: Race and Housing Choice in Metropolitan America, edited by X. d. S. Briggs. Washington, DC: Brookings Institution Press. Coleman, James. 1988. “Social Capital and the Creation of Human Capital.” The American Journal of Sociology 94:S95–120. Elo, Irma T. and Samuel H. Preston. 1996. “Educational Differentials in Mortality: United States, 1979-85.” Social Science and Medicine 42:47–57.
391 Eschbach, Karl, Glenn V. Ostir, Kushang V. Patel, Kyriakos S. Markides, and James S. Goodwin. 2004. “Neighborhood Context and Mortality among Older Mexican Americans: Is There a Barrio Advantage?” American Journal of Public Health 94:1807–12. Espiritu, Yen Le. 1992. Asian American Panethnicity: Bridging Institutions and Identities. Philadelphia: Temple University Press. Ferraro, Kenneth F. and Yan Yu. 1995. “Body Weight and Self-Ratings of Health.” Journal of Health and Social Behavior 36:274–84. Forman, Tyrone A., David R. Williams, and James S. Jackson. 1997. “Race, Place, and Discrimination.” Pp. 237–61 in Perspectives on Social Problems, edited by C. Gardner. Greenwich, CT: JAI Press. Franzini, Luisa, Margaret Caughy, William Spears, and Maria Eugenia Fernandez Esquer. 2005. “Neighborhood Economic Conditions, Social Processes, and Self-rated Health in Low-Income Neighborhoods in Texas: A Multilevel Latent Variables Model.” Social Science & Medicine 61:1135–50. Franzini, Luisa and William Spears. 2003. “Contributions of Social Context to Inequalities in Years of Life Lost to Heart Disease in Texas, USA.” Social Science & Medicine 57:1847–61. Fugita, Stephen S. and David J. O’Brien. 1991. Japanese American Ethnicity: The Persistence of Community. Seattle: University of Washington Press. Fukuyama, Francis. 2000. “Social Capital.” Pp. 98– 111 in Culture Matters: How Human Values Shape Human Progress, edited by L. E. Harrison and S. P. Huntington. New York: Basic Books. Galea, Sandro and Jennifer Ahern. 2005. “Distribution of Education and Population Health: An Ecological Analysis of New York City Neighborhoods.” American Journal of Public Health 95:2198–205. Gee, Gilbert C., Michael S. Spencer, Juan Chen, and David Takeuchi. 2007. “A Nationwide Study of Discrimination and Chronic Health Conditions Among Asian Americans.” American Journal of Public Health 97:1275–82. Glymour, M. Maria, Mahasin Mujahid, Qiong Wu, Kellee White, and Eric J. Tchetgen. 2010. “Neighborhood Disadvantage and Self-Assessed Health, Disability, and Depressive Symptoms: Longitudinal Results from the Health and Retirement Study.” Annals of Epidemiology 20:856–61.
392 Gomez, Scarlett L., Jennifer L. Kelsey, Sally L. Glaser, Marion M. Lee, and Stephen Sidney. 2004. “Immigration and Acculturation in Relation to Health and Health-Related Risk Factors among Specific Asian Subgroups in a Health Maintenance Organization.” American Journal of Public Health 94:1977–84. Haas, Jennifer S., Kathryn A. Phillips, Dean Sonneborn, Charles E. McCulloch, Laurence C. Baker, Celia P. Kaplan, Eliseo J. Perez-Stable, and Su-Ying Liang. 2004. “Variation in Access to Health Care for Different Racial/Ethnic Groups by the Racial/Ethnic Composition of an Individual’s County of Residence.” Medical Care 42:707–14. Halpern, David and James Nazroo. 1999. “The Ethnic Density Effect: Results from a National Community Study of England and Wales.” International Journal of Social Psychiatry 46:34–46. Heeringa, Steven G. 2004. “Technical Sampling Design Documentation: 2002-2003 National Latino and Asian American Study (NLAAS).” Institute for Social Research, Ann Arbor. Heeringa, Steven G., James Wagner, Myriam Torres, Naihua Duan, Terry Adams, and Patricia Berglund. 2004. “Sample Designs and Sampling Methods for the Collaborative Psychiatric Epidemiology Studies (CPES).” International Journal of Methods in Psychiatric Research 13:221–24. Horton, John. 1995. The Politics of Diversity: Immigration, Resistance, and Change in Monterey Park, California. Philadelphia, PA: Temple University Press. Hunt, Matthew O., Lauren A. Wise, Marie-Claude Jipguep, Yvette C. Cozier, and Lynn Rosenberg. 2007. “Neighborhood Racial Composition and Perceptions of Racial Discrimination: Evidence from the Black Women’s Health Study.” Social Psychology Quarterly 70:272–89. Hystad, Perry and Richard M. Carpiano. 2012. “Sense of Community-Belonging and Health-Behaviour Change in Canada” Journal of Epidemiology and Community Health 66:277–83. Iceland, John. 2004. “Beyond Black and White: Metropolitan Residential Segregation in Multi-Ethnic America.” Social Science Research 33:248–71. Idler, Ellen L. and Yael Benyamini. 1997. “Self-Rated Health and Mortality: A Review of Twenty-Seven Community Studies.” Journal of Health and Social Behavior 28:21–37. Karlsen, Saffron and James Y. Nazroo. 2002. “Relation between Racial Discrimination, Social Class, and
Journal of Health and Social Behavior 53(3) Health among Ethnic Minority Groups.” American Journal of Public Health 92:624–31. Kawachi, Ichiro and Lisa F. Berkman. 2000. “Social Cohesion, Social Capital, and Health.” Pp. 174–90 in Social Epidemiology, edited by L. F. Berkman and I. Kawachi. Oxford: Oxford University Press. Lee, Min-Ah and Kenneth F. Ferraro. 2007. “Neighborhood Residential Segregation and Physical Health among Hispanic Americans: Good, Bad, or Benign?” Journal of Health and Social Behavior 48:131–48. Li, Wei. 2009. Ethnoburb: The New Ethnic Community in Urban America. Honolulu: University of Hawai’i Press. Link, Bruce G. and Jo Phelan. 1995. “Social Conditions as Fundamental Causes of Disease.” Journal of Health and Social Behavior 35(Extra Issue):80–94. Logan, John R. 2011. Separate and Unequal: The Neighborhood Gap for Blacks, Hispanics and Asians in Metropolitan America. New York: Russell Sage Foundation. Logan, John R., Richard D. Alba, and Wenquan Zhang. 2002. “Immigrant Enclaves and Ethnic Communities in New York and Los Angeles.” American Sociological Review 67:299–322. Logan, John R., Brian J. Stults, and Reynolds Farley. 2004. “Segregation of Minorities in the Metropolis: Two Decades of Change.” Demography 41:1–22. Macintyre, Sally, Anne Ellaway, and Steven Cummins. 2002. “Place Effects on Health: How Can We Conceptualise, Operationalise, and Measure Them?” Social Science & Medicine 55:125–39. Massey, Douglas S. and Nancy A. Denton. 1993. American Apartheid: Segregation and the Making of the Underclass. Cambridge: Harvard University Press. Mays, Vickie M. and Susan D. Cochran. 2001. “Mental Health Correlates of Perceived Discrimination among Lesbian, Gay, and Bisexual Adults in the United States.” American Journal of Public Health 91:1869–76. McPherson, Miller, Lynn Smith-Lovin, and James M Cook. 2001. “Birds of a Feather: Homophily in Social Networks.” Annual Review of Sociology 27:415–44. Mossakowski, Krysia N. 2003. “Coping with Perceived Discrimination: Does Ethnic Identity Protect Mental Health?” Journal of Health and Social Behavior 44:318–31. Mutchler, Jan E. and Jeffrey A. Burr. 1991. “Racial Differences in Health and Health Care Service Utilization in Later Life: The Effect of Socioeconomic Status.” Journal of Health and Social Behavior 32:342–56.
Walton Patel, Kushang V., Karl Eschbach, Laura L. Rudkin, M. Kristen Peek, and Kyriakos S. Markides. 2003. “Neighborhood Context and Self-Rated Health in Older Mexican Americans.” Annals of Epidemiology 13:620–28. Pennell, Beth-Ellen, Ashley Bowers, Deborah Carr, Stephanie Chardoul, Gina-Qian Cheung, Karl Dinkelmann, Nancy Gebler, Sue Ellen Hansen, Steve Pennell, and Myriam Torres. 2004. “The Development and Implementation of the National Comorbidity Survey Replication, the National Survey of American Life, and the National Latino and Asian American Survey.” International Journal of Methods in Psychiatric Research 13:241–69. Pickett, Kate E. and Richard G. Wilkinson. 2008. “People Like Us: Ethnic Group Density Effects on Health.” Ethnicity & Health 13:321–34. Portes, Alejandro and Robert L. Bach. 1985. The Latin Journey: Cuban and Mexican Immigrants in the United States. Berkeley: University of California Press. Putnam, Robert D. 2007. “E Pluribus Unum: Diversity and Community in the Twenty-First Century.” Scandinavian Political Studies 30:137–74. Raudenbush, Stephen W. and Anthony S. Bryk. 2002. Hierarchical Linear Models: Applications and Data Analysis Methods. Thousand Oaks, CA: Sage. Ross, Catherine E. and Chia-Ling Wu. 1995. “The Links between Educational Attainment and Health.” American Sociological Review 60:719–45. Schulz, Amy J., David R. Williams, Barbara A. Israel, and Lora Bex Lempert. 2002. “Racial and Spatial Relations as Fundamental Determinants of Health in Detroit.” The Milbank Quarterly 80:677–707. Smaje, Chris. 1995. “Ethnic Residential Concentration and Health: Evidence for a Positive Effect?” Policy and Politics 23:251–69. Small, Mario Luis and Jessica Feldman. 2012. “Ethnographic Evidence, Heterogeneity, and Neighbourhood Effects after Moving to Opportunity.” Pp. 57–77 in Neighbourhood Effects Research: New Perspectives, edited by M. van Ham, D. Manley, N. Bailey, L. Simpson, and D. Maclennan. London: Springer. Snijders, Tom and Roel Bosker. 1999. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. Thousand Oaks, CA: Sage.
393 Takaki, Ronald. 1989. Strangers from a Different Shore: A History of Asian Americans. New York: Little, Brown and Company. Turley, Ruth N. Lopez. 2003. “When Do Neighborhoods Matter? The Role of Race and Neighborhood Peers.” Social Science Research 32:61–79. Vertovec, Steven. 2007. “Super-Diversity and Its Implications.” Ethnic and Racial Studies 30:1024–54. Viswanath, Kasisomayajula, Whitney Randolph Steele, and John R. Finnegan Jr. 2006. “Social Capital and Health: Civic Engagement, Community Size, and Recall of Health Messages.” American Journal of Public Health 96:1456–61. Vo, Linda Trinh and Mary Yu Danico. 2004. “The Formation of Post-Suburban Communities: Koreatown and Little Saigon, Orange County.” International Journal of Sociology and Social Policy 24:15–45. Walton, Emily. 2009. “Residential Segregation and Birth Weight among Racial and Ethnic Minorities in the United States.” Journal of Health and Social Behavior 50:427–42. Wen, Ming, Christopher R. Browning, and Kathleen A. Cagney. 2003. “Poverty, Affluence, and Income Inequality: Neighborhood Economic Structure and Its Implications for Health.” Social Science & Medicine 57:843–86. Wen, Ming, Diane S. Lauderdale, and Namratha R. Kandula. 2009. “Ethnic Neighborhoods in Multi-Ethnic America, 1990-2000: Resurgent Ethnicity in the Ethnoburbs?” Social Forces 88:425–46. White, Kellee and Luisa N. Borrell. 2011. “Racial/Ethnic Residential Segregation: Framing the Context of Health Risk and Health Disparities.” Health & Place 17:438–48. Williams, David R. and Chiquita Collins. 2001. “Racial Residential Segregation: A Fundamental Cause of Racial Disparities in Health.” Public Health Reports 116:404–16. Wilson, William Julius. 1987. The Truly Disadvantaged. Chicago: University of Chicago Press. Wooldridge, Jeffrey M. 2009. Introductory Econometrics: A Modern Approach. Mason, OH: South-Western. Zhou, Min. 1992. Chinatown: The Socioeconomic Potential of an Urban Enclave. Philadelphia: Temple University Press. Zhou, Min and Rebecca Kim. 2003. “A Tale of Two Metropolises: New Immigrant Chinese Communities
394 in New York and Los Angeles.” Pp. 124–49 in Los Angeles and New York in the New Millennium, edited by D. Halle. Chicago: University of Chicago Press. Zhou, Min and Susan S. Kim. 2006. “Community Forces, Social Capital, and Educational Achievement: The Case of Supplementary Education in Chinese and Korean Immigrant Communities.” Harvard Educational Review 76:1–29.
Journal of Health and Social Behavior 53(3) Bio Emily Walton is an assistant professor of sociology at Dartmouth College. Her research focuses on understanding the socioeconomic and social neighborhood context of racial and ethnic health disparities. Current projects include an ethnographic investigation of health-related social processes in a multiethnic neighborhood and a study of Asian American ethnic neighborhood change as it relates to health in California.
