Metropolitan residential segregation and very preterm birth among African American and Mexican-origin women

Social Science & Medicine 98 (2013) 37e45

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Metropolitan residential segregation and very preterm birth among African American and Mexican-origin women Marcus L. Britton a, *, Heeju Shin b a b

Department of Sociology, University of Wisconsin-Milwaukee, NWQ B, Room 7459, 2025 E. Newport Ave., Milwaukee, WI 53211, USA Department of Sociology, University of Wisconsin-Milwaukee, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Available online 5 September 2013

Residential segregation is associated with poor healthdincluding poor birth outcomesdamong African Americans in US cities and metropolitan areas. However, the few existing studies of this relationship among Mexican-origin women have produced mixed results. In this study, the relationship between segregation and very preterm birth was examined with National Center for Health Statistics (NCHS) data on singleton births to African American women (n ¼ 400,718) in 238 metropolitan areas and to Mexican-origin women (n ¼ 552,382) in 170 metropolitan areas. The study evaluated 1) whether residential segregation is positively associated with very preterm birth among both African American and Mexican-origin women and 2) if so, whether exposure to neighborhood poverty accounts for these associations. Results from multi-level analysis indicate that residential segregation is positively associated with very preterm birth among both groups of women. However, this association is robust across different measures of segregation only for African Americans. Conversely, differences across metropolitan areas in average levels of exposure to neighborhood poverty account for the positive association between segregation and very preterm birth among Mexican-origin women, but not among African American women. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: US Residential segregation Very preterm birth Neighborhood poverty

Introduction Metropolitan residential segregation is associated with an increased risk of poor birth outcomes among Black women. This finding has generally been robust across studies that measured different birth outcomes (Bell, Zimmerman, Almgren, Mayer, & Huebner, 2006; Ellen, 2000; Kramer, Cooper, Drews-Botsch, Waller, & Hogue, 2010; Osypuk & Acevedo-Garcia, 2008; but see Walton, 2009), as well as different dimensions of segregation, including both isolation/exposure (Bell et al., 2006; Kramer et al., 2010) and evenness/dissimilarity (Ellen, 2000).1 But despite similar household poverty levels and increasingly similar levels of segregation among Hispanics, the few existing studies of this relationship among Hispanics have produced mixed, inconclusive

* Corresponding author. Fax: þ1 414 229 4266. E-mail addresses: [email protected] (M.L. Britton), [email protected] (H. Shin). 1 Isolation segregation refers to the extent to which members of a given group (e. g., Blacks) typically live in neighborhoods in which the other residents belong to the same group (e.g., in predominantly Black neighborhoods). Dissimilarity (a measure of evenness segregation) measures the extent to which members of one group (e.g., Blacks) are underrepresented in some neighborhoods and overrepresented in others relative to a comparison group (e.g., non-Hispanic Whites) (Iceland et al., 2002). 0277-9536/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.socscimed.2013.08.039

results (Osypuk, Bates, & Acevedo-Garcia, 2010; Walton, 2009). As explained further below, these results are surprising from the perspective of place stratification theory, which emphasizes that racial/ethnic segregation concentrates poverty in minority neighborhoods. This theory suggests that similar levels of poverty and segregation (especially from non-Hispanic Whites) among Blacks and Hispanics should result in similarly high levels of exposure to neighborhood poverty (Massey & Denton, 1993; Massey & Fischer, 2000). In turn, neighborhood poverty exposure should be associated with poor birth outcomes among both groups. The divergent findings for Black and Hispanic women may partially reflect the epidemiological paradox (Markides & Coreil, 1986), in which the risk of poor birth outcomes increases as immigrant groups become acculturated, especially across generations (Collins & David, 2004; Guendelman, Gould, Hudes, & Eskenazi, 1990). Indeed, a number of studies suggest that the health advantages enjoyed by first generation Hispanic immigrants despite their typically low levels of education and limited access to health care may reflect the protective health effects of immigrant enclave neighborhoods (Cagney, Browning, & Wallace, 2007; Finch, Lim, Perez, & Do, 2007; Lee & Ferraro, 2007; Peak & Weeks, 2002). In this study, we analyzed the relationship between the two most widely used measures of metropolitan residential segregation, the isolation and dissimilarity indices, and very preterm birth

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(VPTB) among African American and Mexican-origin women. This study had two specific aims. First, we sought to clarify the extent to which the relationships between segregation and VPTB are similar or different among African American and Mexican-origin women. Second, we assessed the extent to which differences across metropolitan areas in average levels of exposure to neighborhood poverty among members of each group account for any positive association between segregation and VPTB among either African American or Mexican-origin women. Our comparison focused on US-born, African American women and Mexican-origin women due to substantial heterogeneity across African-origin and Hispanic subgroups (see Logan & Deane, 2003; Orrenius & Zavodny, 2011). Data from the National Center for Health Statistics (NCHS) 2004 Birth Data file on singleton births to 400,718 African American women in 238 metropolitan areas and 552,382 Mexican-origin women in 170 metropolitan areas were analyzed. The analysis focused on the relationship between segregation and the adverse birth outcome most closely linked to infant mortality, very preterm birth (Kramer et al., 2010). In light of the literature on the epidemiological paradox, we analyzed this relationship in separate models for foreign-born and US-born women of Mexican ancestry. Residential segregation, place stratification, and poor birth outcomes The documented relationship between residential segregation and poor health outcomes among African Americans may reflect the strong association between segregation and heightened exposure to adverse neighborhood conditions (Culhane & Elo, 2005; Osypuk & Acevedo-Garcia, 2010). Sociologists have examined this association from the perspective of place stratification theory (Alba & Logan, 1993). According to this theory, institutionalized and decentralized racism generate and perpetuate racial residential segregation, which, in turn, spatially concentrates household poverty in the neighborhoods inhabited by socioeconomically disadvantaged racial/ethnic groups (Massey & Denton, 1993; Massey & Fischer, 2000). High levels of segregation interact with the relatively high poverty rates among some racial/ethnic groups (e.g., Blacks and Hispanics) to produce even higher levels of exposure to neighborhood poverty among these same groups than one would expect based on their poverty rates alone. In turn, high-poverty neighborhoods provide limited access to a variety of services (e.g., full-service grocery stores and high-quality schools) and increase exposure to violent crime, substandard housing, and pollution (Acevedo-Garcia & Osypuk, 2008; Messer, Kaufman, Dole, Savitz, & Laraia, 2006; Morland, Wing, Diex Roux, & Poole, 2002; Peterson & Krivo, 2010). Thus, residential segregation may contribute to disproportionate exposure to acute and chronic stress, poor air and water quality, and toxins such as heavy metals and pesticides, each of which is linked to an increased risk of adverse birth outcomes (Kramer & Hogue, 2009; Miranda, Maxson, & Edwards, 2009). Similarly, segregation may indirectly encourage risky health behaviors and limit access to adequate healthcare during pregnancy by concentrating poverty in minority neighborhoods (Bell, Zimmerman, Mayer, Almgren, & Huebner, 2007; Perloff & Jaffee, 1999). Given similar levels of poverty and segregation among Blacks and Hispanics, place stratification theory is more difficult to reconcile with the comparatively limited evidence on how metropolitan residential segregation is related to poor birth outcomes among Hispanic women. Overall family poverty rates among both Blacks and Hispanics are on the order of three times higher than the rate of approximately eight percent among non-Hispanic Whites (Orrenius & Zavodny, 2011). Among the Mexican-origin population, the poverty rate among the US-born (18.8 percent) is somewhat

lower than among Mexican immigrants (26.8 percent), but still nearly as high as the rate among Blacks (23.7 percent). Further, Hispanics are nearly as segregated from non-Hispanic Whites as Blacks overall, and sometimes even more so in large metropolitan areas in the West with large Mexican-origin populations (Charles, 2003; Logan, Stults, & Farley, 2004). Similar levels of family poverty and segregation among Blacks and Hispanics are associated with relatively high levels of exposure to neighborhood poverty among both groups (Jargowsky, 2003; Logan, 2011). Moreover, place stratification theory predicts that neighborhood poverty exposure should be particularly similar among African Americans and Mexican immigrants, since poverty rates and levels of segregation from Whites are even higher among Mexican immigrants than among other Hispanics (Iceland, 2009; Orrenius & Zavodny, 2011). Thus, residential segregation should be positively associated with VPTB not only among African American women, but also among Mexican-origin womendespecially Mexican immigrants. In turn, exposure to neighborhood poverty should largely account for these positive associations. But in fact, prior research has produced limited evidence of any substantial association between metropolitan residential segregation and poor birth outcomes among Hispanic women. Walton (2009) found no evidence of a significant association between Hispanic residential isolation and low birthweight among Hispanic women. Conversely, Osypuk, Bates, and Acevedo-Garcia (2010) found a negative association between residential isolation and birth weight among US-born, Mexican Americans, but not among Mexican immigrants. The divergent findings of these studies may reflect their methodological limitations. Walton’s (2009) study pooled results for Hispanic ethnic groups, potentially obscuring a relationship that is specific to Mexican-origin women. Further, studies of Hispanic women have focused primarily on the isolation dimension of segregation (see endnote 1). This may be problematic, since, as Osypuk, Bates and Acevedo-Garcia (2010, p. 558) pointed out, residential isolation measures conflate “residential segregation with population composition” (e.g., the percent Mexican-origin in the metropolitan area). In addition, Kramer et al. (2010) found that the association between Black residential isolation and moderately preterm birth was only half as strong as the corresponding association with VPTB. By conflating birth outcomes of varying severity, prior research may have obscured stronger relationships between segregation and very severe birth outcomes. Immigration, spatial assimilation and birth outcomes Another reason for the limited evidence of a substantial association between residential segregation and adverse birth outcomes among Mexican-origin womendespecially Mexican immigrantsdmay be that the mechanisms producing segregation differ substantially between African American and Mexican-origin populations. Discrimination and “White flight” contribute to both Black and Hispanic residential segregation (Pais, South, & Crowder, 2009; Turner, Ross, Galster, & Yinger, 2002). But spatial assimilation theory emphasizes that chain migration is an important factor contributing to segregation among immigrant groups (Massey, 1985). Chain migration channels new migrants to the places where previous migrants have settled (Bauer, Epstein, & Gang, 2005; Zavodny, 1999). The result may be to concentrate immigrant settlement in enclaves that develop in and around the neighborhoods where the earliest migrants settled (Massey, 1985). As immigrant enclaves become larger, this process is likely to be reinforced by the development of ethnic institutions (e.g., churches and social service agencies) that attract more coethnic immigrants. Consistent with these ideas, rising levels of Hispanic segregation

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from non-Hispanic Whites have been strongly associated with growth in the foreign-born populations of specific metropolitan areas (Logan et al., 2004). Because segregation of Mexican immigrants at least partially reflects the role that migrants’ ties to coethnic relatives and friends play in producing immigrant enclaves, it may be associated with social supports and health-enhancing norms that protect against poor birth outcomes among Mexican immigrant women. Indeed, first generation immigrants’ health advantages may partially reflect the protective effects of immigrant enclaves (Cagney et al., 2007; Finch et al., 2007; Lee & Ferraro, 2007; Peak & Weeks, 2002). Supports derived from friendship and kinship networks are associated with more favorable physical and mental health (Alegria, Sribney, & Mulvaney-Day, 2006; Cagney et al., 2007) and specifically with more favorable birth outcomes (Weigers & Sherraden, 2001). Latino immigrant enclaves can also foster positive health behaviors such as eating a healthy diet (Reyes-Ortiz, Ju, Eschbach, Kuo, & Gaadwin, 2009), discourage harmful behaviors such as smoking, drug use and binge-drinking (Frank, Cerdá, & Rendón, 2007; Kimbro, 2009), and protect residents from discrimination and prejudice (Viruell-Fuentes, 2007). Consequently, residential isolation among Mexican immigrants may reduce the risk of poor birth outcomes and buffer the effects of concentrated poverty among Mexican immigrant women (Collins & Shay, 1994; Finch et al., 2007). But across generations, some immigrant families not only acculturate, but achieve upward mobility, enabling them to disperse across a wider range of neighborhoods (Massey, 1985). Higher levels of education and household income among nonimmigrant Mexican-origin households are associated with moving out of Latino enclaves and into areas with more non-Hispanic White neighbors (South, Crowder, & Chavez, 2005). Consequently, US-born, Mexican Americans who remain in enclave neighborhoods are disproportionately exposed to the least educated, lowest income segments of the US-born, Mexicanorigin populations of their metropolitan areasdand typically to high proportions of poor Mexican immigrants, as well (Alba, Logan, & Stults, 2000; Logan, 2011). Therefore, relatively high levels of residential segregation should be associated with higher average levels of exposure to neighborhood poverty among US-born, Mexican-origin populations. Moreover, residential segregation among US-born, Mexican Americans is unlikely to reflect the coethnic social ties involved in chain migration among Mexican immigrants. Thus, the adverse consequences of increased poverty exposure associated with segregation among the US-born are less likely to be offset by the social supports and health-enhancing norms that may buffer against these consequences among residentially isolated Mexican immigrants. In summary, spatial assimilation theory predicts that residential isolation among Mexican immigrants will be negatively associated with the risk of VPTB among Mexican immigrant women, reflecting the protective effects of immigrant enclaves. Conversely, higher levels of residential segregation among US-born, Mexican-origin populations should be associated with an increased risk of VPTB among US-born, Mexican-origin women. In turn, place stratification theory suggests that adjusting for differences across metropolitan areas in average levels of exposure to neighborhood poverty should largely account for the positive associations between segregation and VPTB among both US-born, Mexican-origin and African American women.

Data file, which constitutes a census of all US births during that year. Data on metropolitan area characteristics were obtained from the 2000 US Census (Summary Files 1 and 3). To ensure comparability with prior research, our analysis focused on singleton births to African American and Mexican-origin women who resided in metropolitan areas with at least 100,000 total residents and 5000 Black (or Mexican-origin) residents. We omitted cases in which the recorded birthweight was implausible (less than 500 g or more than 6000 g). Finally, we omitted 11,787 records for African American women (2.9 percent) and 32,018 records for Mexican-origin women (5.5 percent) because they were missing data on the dependent variable, maternal characteristics (primarily educational attainment), or both. After imposing the restrictions noted above, data on 400,718 births to African American women in 238 metropolitan areas and 552,382 births to Mexican-origin women (including 199,113 who were born in the United States and 353,269 Mexican immigrants) in 170 metropolitan areas remained. Measures Birth outcomes: The dependent variable was a dichotomous indicator of very preterm birth, set equal to one for all births that took place prior to 32 weeks of gestation. Estimates of gestational age were obtained from the infant’s birth certificate. In over 93 percent of cases for both African American and Mexican-origin women, gestational age estimates were based on the mother’s self-reported date of last normal menstruation. In the remaining cases, a clinician estimated gestational age. Residential segregation: We operationalized isolation/exposure dimension of segregation using the P-star index: * x P y ¼ 100

Data on VPTB and maternal and infant characteristics were taken from the US 2004 National Center for Health Statistics (NCHS) Birth

n X xi yi X ti i¼1

!

where x P *y denotes the exposure of group x to group y, xi is the census tract population of group x, X is the population of group x in the entire metro area, yi is the tract population of group y, ti is the total tract population, and n is the number of tracts in the metropolitan area (Iceland, Weinberg, & Steinmetz, 2002). When groups x and y are different groups, the P-star index measures average levels of residential exposure to group y among members of group x. Conversely, when groups x and y are the same group (i.e., yi ¼ xi), the P-star index measures the level of residential isolation for that group in the focal metropolitan area. Because African and Afro-Caribbean immigrants constitute very small proportions of the population in virtually all US metropolitan areas, our measure of Black residential isolation did not distinguish between US-born and immigrant Black residents. But following Osypuk et al. (2010), our measures of Mexican-origin residential isolation/exposure differentiated between residential exposure to Mexican immigrants and exposure to US-born Mexican-origin residents. Four measures were calculated using the formula given above: exposure to Mexican immigrants among US-born, Mexican-origin residents; residential isolation among the US-born; exposure to US-born, Mexican-origin residents among Mexican immigrants; and Mexican immigrant isolation. We operationalized the evenness dimension using the residential dissimilarity index, focusing specifically on dissimilarity from non-Hispanic Whites:

Method Data

39

x Dw ¼ 100

 n  1X xi wi     2 i¼1 X W

!

where x DW is the dissimilarity between the distribution of group x across the n census tracts in the metropolitan area and the

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Table 1 Descriptive statistics for individual-level variables. African American Mean/Prop. Very preterm birth Infant sex (Female) Married Under 15 years old Age 15e19 Age 20e24 Age 25e30 Age 30e34 Age 35e39 Over 39 years old Less than 12 years of education 12 years of education 13e15 years of education 16 or more years of education Prior preterm birth # of prior births Smoked during pregnancy Drank during pregnancy Chronic hypertension Preg.-related hypertension Eclampsia Inadequate Intermediate Adequate Adequate Plus n

0.031 0.490 0.270 0.005 0.185 0.342 0.235 0.146 0.070 0.017 0.247 0.377 0.252 0.124 0.017 1.219 0.087 0.006 0.018 0.041 0.004 0.175 0.127 0.388 0.310 400,718

Mexican immigrant SD

1.433

Mean/Prop. 0.012 0.491 0.573 0.001 0.114 0.280 0.288 0.206 0.091 0.019 0.651 0.238 0.069 0.042 0.006 1.308 0.003 0.001 0.003 0.020 0.002 0.173 0.160 0.420 0.247 353,269

U.S. born Mexican SD.

1.309

Mean/Prop. 0.015 0.490 0.507 0.004 0.207 0.345 0.241 0.138 0.053 0.011 0.313 0.390 0.199 0.098 0.008 1.120 0.023 0.004 0.005 0.028 0.002 0.129 0.132 0.427 0.313 199,113

SD

1.268

Note: Missing data indicators for smoking and alcohol consumption during pregnancy and adequacy of prenatal care omitted.

corresponding distribution of non-Hispanic Whites, wi is the nonHispanic White population of the census tract, and W is the nonHispanic White population of the metro area. Because the dissimilarity index incorporates information about the relative shares of each group in each census tract in the metropolitan area, it provides a measure of segregation that is standardized across metropolitan areas where the relative sizes of two groups (e.g., Blacks and Whites) are very different. We calculated the dissimilarity index for each of three groups: Blacks, Mexican immigrants, and US-born, Mexican-origin residents. The dissimilarity index can be interpreted as the percentage of the population of group x (or of nonHispanic Whites) who would have to move to a different census tract in order to achieve complete integration. Poverty exposure: Following Massey and Fischer (2000), we used the exposure index to measure average levels of exposure to neighborhood poverty. The index is calculated in the same manner as the P-star index described above, except that the proportion of residents in group y (yi/ti) is replaced by the tract poverty rate. This absolute neighborhood poverty exposure index was appropriate in models that used isolation/exposure indices to measure segregation. Following urban economists who study of the effects of residential segregation (Ellen, 2000), we employed a closely related measure of relative exposure to neighborhood poverty in models that used the dissimilarity index: * x P RP ¼ 100 * x P RP

n X xi pi X hi i¼1

!  poverty rate

measures the extent to which members of group x are relatively more exposed to neighborhood poverty than residents of the metropolitan area overall by subtracting the overall poverty rate in the metropolitan area from the index of absolute neighborhood poverty exposure described above. This measure was appropriate for use with the dissimilarity index, since the latter expresses the extent to which group x is overrepresented in some neighborhoods within a given metro area relative to the comparison

group (i.e., non-Hispanic Whites), rather than the average absolute level of exposure to or isolation from a comparison group. Additional independent measures: We also included several metropolitan-level controls in our models, including the natural log of population size and median household income (in $1000s). We also controlled for either the Black or Hispanic poverty rate. To adjust for relative size, we controlled for the percentage of each metropolitan area’s population that was Black (or Mexican-origin), but only in models that used the dissimilarity index to measure residential segregation, since the P-star indices were very highly correlated with relative group size. At the individual level, we controlled Census region of residence, maternal age, maternal education, whether the mother was married, number of prior births, prior pre-term delivery, smoking and alcohol consumption during pregnancy, chronic hypertension, hypertension during the pregnancy, and eclampsia (see Table 1 for categories). We also included indicator variables for the following categories on the Kotelchuck Adequacy of Prenatal Care Utilization (APNCU) index: intermediate, inadequate, adequate plus, and missing (reference ¼ adequate; see Kotelchuck, 1994). In addition, we included a control for the sex of the infant. As in most research using the NCHS birth files, we included dummy variables to indicate missing data on smoking and alcohol consumption, since these data are not collected by all states and localities. Analysis We examined the relationships among VPTB, residential segregation and average levels of exposure to neighborhood poverty with two-level random-intercept logistic regression models. These models enabled us to estimate the net associations between VPTB and both metropolitan-level and individual-level characteristics, while adjusting point estimates and standard errors for unobserved heterogeneity across metros (Rabe-Hesketh & Skrondal, 2008). All analyses were conducted with Stata 11. Models were estimated using the xtlogit command.

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41

Table 2 Descriptive statistics for metro-level variables and census region of residence. African American

Dissimilarity Isolation Exposure to US born Mexicans Exposure to Mexican immigrants Percent Black/Mexican-origin Black/Latino poverty rate Ln(population) Median household income ($1000s) Poverty exposure index Relative poverty exposure index Census region Northeast Midwest South West # of metros n

Mexican immigrant

US-born Mexican

Mean

SD

Min

Max

Mean

SD

Min

Max

Mean

SD

Min

Max

64.4 52.4

11.8 16.8

28.3 2.7

84.7 79.0

63.2 20.6 17.7

8.2 8.4 10.8

36.2 0.6 0.1

87.8 37.2 47.9

46.1 21.9

9.3 11.1

13.3 0.4

73.3 48.7

19.9 24.1 14.3 44.7 20.7 8.8

9.9 5.5 1.1 7.2 4.5 3.4

0.9 8.1 11.5 29.1 7.9 6.2

50.8 43.9 16.1 74.3 35.9 18.9

21.2 22.0 14.5 45.4 20.7 7.0

16.6 5.5 1.1 8.5 5.7 2.4

0.2 11.4 11.6 24.9 9.0 1.5

76.1 39.2 16.1 74.3 39.1 15.2

15.8 27.1 22.8 14.3 42.7 18.6 3.5

7.2 17.1 5.4 1.2 8.3 5.5 1.5

0.0 0.2 11.4 11.6 24.9 7.6 1.0

30.7 76.1 39.2 16.1 74.3 36.5 15.5

0.23 0.14 0.54 0.08 238 400,718

0.200 0.094 0.376 0.329 170 353,269

0.206 0.094 0.371 0.329 170 199,113

Notes: Means and standard deviations are weighted by the number of births in each metropolitan area (n).

We estimated four main model specifications for each of three groups: African American, Mexican-immigrant, and US-born, Mexican-origin women. For each dimension of segregation, we first estimated baseline models that included only the segregation measure, the metropolitan-level control variables and the mother’s Census region of residence. These models provided an estimate of the total effect of each measure of segregation. We then estimated two models that added different control variables. The first controlled for the neighborhood poverty exposure index, while the second adjusted for individual-level risk factors. Finally, the full model added the poverty exposure index to the fully specified model with all other metropolitan- and individual-level variables. Estimating these three additional specifications enabled us to assess whether differences across metropolitan areas in average levels of exposure to neighborhood poverty could account for any observed positive association between segregation and VPTB, either with or without adjustments for individual-level risk factors. This approach avoided potential overcontrol bias, since individuallevel risk factors may be partially determined by segregation, neighborhood poverty exposure, or both. Results Tables 1 and 2 provide descriptive statistics for African American, Mexican immigrant and US-born, Mexican-origin women. As shown in Table 1, VPTB was slightly less common among Mexican immigrant than among US-born, Mexican-origin women, but over twice as common among African American women. As shown in Table 2, African American and Mexican immigrant women typically lived in metropolitan areas with similarly high levels of residential dissimilarity from non-Hispanic Whites (xDW ¼ 64.4 and 63.2, respectively), while dissimilarity from Whites was substantially less pronounced among US-born, Mexican-origin populations (xDW ¼ 46.1). As indicated by the mean Black isolation score (52.4), African American women typically lived in metros where Black residents lived in majority Black neighborhoods on average. Conversely, Mexican-origin isolation was much less pronounced, with Mexican immigrants typically living in tracts where foreignborn and US-born coethnics combined made up only a little over one-third of their neighbors (20.6 þ 17.7 ¼ 38.3 percent). US-born Mexicans typically lived in neighborhoods with only slightly lower proportions of coethnics (21.9 þ 15.8 ¼ 37.7 percent). As these figures suggest, dissimilarity from Whites among Blacks was much more highly correlated with Black residential isolation (r ¼ 0.68)

than dissimilarity among Mexican-origin residents was with either Mexican immigrant (r ¼ 0.01) or US-born, Mexican American residential isolation (r ¼ 0.07). The results for the baseline random-intercept model predicting VPTB among African American women are shown as Model 1 in Table 3, with the model specifications using the isolation and the dissimilarity indices shown in the top and bottom panels, respectively. The residential isolation model suggested that each standard deviation increase in isolation (about 17 percentage points) corresponded to an increase of approximately seven percent in the predicted odds of VPTB. Model 2 added the neighborhood poverty exposure index. Contrary to the prediction derived from place stratification theory, the neighborhood poverty exposure index was not significantly associated with the risk of VPTB. Moreover, adding this control did not change the coefficient for residential isolation. The association between VPTB and residential isolation was only slightly weaker after adjusting for individual-level risk factors. Similar but somewhat less robust results were obtained in models that used the dissimilarity index to measure segregation. Dissimilarity from non-Hispanic Whites was positively associated with VPTB in the baseline model. Comparing Models 1 and 2, there was a small decrease in the dissimilarity coefficient after controlling for the relative neighborhood poverty exposure index, but adding this measure did not significantly improve model fit. The dissimilarity coefficient became smaller and marginally significant after adjusting for individual-level risk factors (Models 3). Supplementary analyses (not shown) revealed that three individuallevel variables that were significantly predicted by residential dissimilarity and, in turn, significantly positively associated with the risk of VPTB in Model 3 accounted for this decreased association: maternal age, marital status and prenatal care adequacy. Adding the control for the relative poverty exposure index did not significantly improve model fit after adjusting for these individuallevel variables (Model 4).2

2 We also estimated the models without the control for the Black poverty rate (not shown) in order to assess whether the nonsignificant coefficients of the neighborhood poverty exposure indices reflected multicollinearity. Although there was some evidence of multicollinearity with both the poverty rate and the absolute poverty exposure index in the model, omitting the poverty rate did not substantially alter the results. Even without this control, the poverty exposure indices were not significantly associated with VPTB, and the segregation measures remained positively and significantly associated with VPTB after controlling for the poverty exposure indices.

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Table 3 Random-intercept logit models predicting very preterm birth among African American women. Variable

Residential isolation Median household income Ln(Population) Black poverty rate Poverty exposure Constant

r Dissimilarity % Black Median household income Ln(Population) Black poverty rate Relative poverty exposure Constant

r

Metropolitan-area-level variables only

Models adjusted for individual-level variables

Model 1

Model 3

Model 2

Model 4

b

se

OR

b

se

OR

b

se

OR

b

se

OR

0.004*** 0.000 0.019 0.004

(0.001) (0.004) (0.017) (0.004)

1.07 1.00 0.98 1.02

0.003*** 0.002 0.012 0.002

(0.001) (0.004) (0.017) (0.004)

1.05 1.01 0.99 1.01

4.503*** 0.003***

(0.299) (0.001)

0.004*** 0.001 0.008 0.006 0.008 4.522***

(0.001) (0.004) (0.018) (0.007) (0.009) (0.299)

1.07 1.01 0.99 1.03 0.96

(0.294) (0.001)

(0.001) (0.004) (0.018) (0.007) (0.009) (0.295) (0.001)

1.07 1.00 0.98 1.02 1.00

3.431*** 0.004***

0.004*** 0.000 0.019 0.004 0.000 3.430*** 0.004***

0.005** 0.002 0.001 0.023 0.003

(0.002) (0.002) (0.004) (0.020) (0.004)

0.003y 0.002 0.001 0.012 0.001

(0.002) (0.002) (0.004) (0.020) (0.004)

1.04 1.02 1.01 0.99 1.01

4.530*** 0.004***

(0.320) (0.001)

0.004 0.002 0.002 0.013 0.002 0.003 4.553*** 0.004***

(0.002) (0.002) (0.004) (0.020) (0.005) (0.008) (0.327) (0.001)

1.05 1.02 1.01 0.99 1.01 0.99

(0.317) (0.001)

(0.002) (0.002) (0.004) (0.020) (0.005) (0.008) (0.324) (0.001)

1.05 1.03 0.99 0.97 1.01 1.01

3.421*** 0.004***

0.004* 0.003 0.002 0.023 0.002 0.002 3.403*** 0.004**

1.06 1.02 0.99 0.97 1.02

Notes: b ¼ logit coefficient. ***p < 0.001. **p < 0.01. *p < 0.05. yp < 0.10. One-tailed tests for focal logit coefficients, two-tailed tests for controls, and likelihood ratio tests for rho (r). se ¼ standard error. OR ¼ odds ratio for a one-standard deviation increase.

dissimilarity and VPTB (i.e., from OR ¼ 1.08 to OR ¼ 1.04, vs. a decrease from 1.09 to 1.05 in Models 1 and 2). And perhaps more fundamentally, the coefficient for the relative poverty exposure index was only marginally significant net of controls for individuallevel risk factors (Model 4). Finally, Table 5 presents the results for US-born, Mexican-origin women. In the baseline model, there was no evidence of a statistically significant association between either residential isolation or residential exposure to Mexican immigrants and VPTB. However, the coefficient for exposure to Mexican immigrants actually became larger and statistically significant after adjusting for individual-level risk factors. We re-estimated all models with individual-level covariates in Tables 3e5 without the prenatal care adequacy measures (not shown). In all other cases, the results were substantively unchanged. But while the Mexican-immigrant exposure coefficient in Table 5 remained positive (b ¼ 0.004) without adjusting for prenatal care adequacy, it was not statistically significant. As explained in the Discussion section below, we

Table 4 presents the corresponding results for Mexican immigrant women. The models presented in Table 4 provided no evidence of a statistically significant association between either Mexican immigrant residential isolation or exposure to US-born, Mexican-origin residents and VPTB among these women. Conversely, models using the dissimilarity measure suggested that segregation was significantly positively associated with VPTB before adjusting for the relative neighborhood poverty exposure index. The predicted odds of VPTB increased by nine percent for each one standard deviation increase in dissimilarity from nonHispanic Whites (about 8 percentage points). But consistent with place stratification theory, adjusting for the relative poverty exposure index resulted in a substantially smaller and nonsignificant association. The point estimate of the association between dissimilarity and VPTB was slightly smaller after adjusting for individual-level risk factors in Model 3. With these adjustments, controlling for the relative poverty exposure index also resulted in a slightly smaller decrease in the estimated association between

Table 4 Random-intercept logit models predicting very preterm birth among Mexican immigrant women. Variables

Metropolitan-area-level variables only Model 1

Residential isolation US-born Mexican exposure Median household income Ln(population) Latino poverty rate Poverty exposure Constant

r Dissimilarity % Mexican-origin Median household income Ln(Population) Latino poverty rate Relative poverty exposure Constant

r

Models adjusted for individual-level variables

Model 2

Model 3

Model 4

b

se

OR

b

se

OR

b

se

OR

b

se

OR

0.003 0.002 0.013** 0.003 0.016**

(0.005) (0.004) (0.005) (0.024) (0.007)

1.03 1.02 0.90 1.00 0.92

0.007 0.001 0.009* 0.038 0.019**

(0.005) (0.004) (0.005) (0.025) (0.008)

1.06 1.01 0.93 0.96 0.90

4.460*** 0.007***

(0.462) (0.003)

0.007 0.001 0.009 0.037 0.018** 0.001 4.443*** 0.007***

(0.005) (0.005) (0.006) (0.026) (0.009) (0.011) (0.480) (0.003)

1.06 1.01 0.93 0.96 0.91 0.99

(0.445) (0.002)

(0.005) (0.004) (0.006) (0.025) (0.008) (0.011) (0.464) (0.002)

1.03 1.03 0.90 1.00 0.92 0.99

3.575*** 0.006***

0.003 0.003 0.013** 0.003 0.016* 0.002 3.554*** 0.006***

0.011*** 0.003 0.014*** 0.028 0.016**

(0.004) (0.002) (0.004) (0.025) (0.007)

1.05 1.05 0.89 0.98 0.91 1.11 1.00

(0.004) (0.002) (0.005) (0.026) (0.008)

1.08 1.07 0.93 0.94 0.91

4.710*** 0.006***

(0.434) (0.002)

0.005 0.004* 0.008* 0.045* 0.019** 0.018y 4.696*** 0.006***

(0.005) (0.002) (0.005) (0.027) (0.008) (0.012) (0.433) (0.002)

1.04 1.07 0.93 0.95 0.90 1.11

(0.405) (0.002)

(0.004) (0.002) (0.004) (0.024) (0.007) (0.010) (0.397) (0.002)

0.009** 0.004* 0.009* 0.054** 0.017**

3.726*** 0.004***

0.006 0.003 0.014*** 0.019 0.018** 0.019* 3.734*** 0.004***

1.09 1.05 0.89 0.97 0.92

Notes: b ¼ logit coefficient. ***p < 0.001. **p < 0.01. *p < 0.05. yp < 0.10. One-tailed tests for focal logit coefficients, two-tailed tests for controls, and likelihood ratio tests for rho (r). se ¼ standard error. OR ¼ odds ratio for a one-standard deviation increase.

M.L. Britton, H. Shin / Social Science & Medicine 98 (2013) 37e45

43

Table 5 Random-intercept logit models predicting birth outcomes among US-born, Mexican-origin women. Very preterm birth

Residential isolation Mexican-immigrant exposure Median household income Ln(Population) Latino poverty rate Poverty exposure Constant

r Dissimilarity % Mexican-origin Median household income Ln(Population) Latino poverty rate Relative poverty exposure Constant

r

Metropolitan-area-level variables only

Models adjusted for individual-level variables

Model 1

Model 3

Model 2

Model 4

b

se

OR

b

se

OR

b

se

OR

b

se

OR

0.004 0.001 0.010* 0.028 0.012

(0.004) (0.005) (0.005) (0.025) (0.009)

1.05 0.99 0.92 0.97 0.94

0.002 0.009* 0.005 0.068*** 0.015*

(0.003) (0.005) (0.005) (0.025) (0.009)

1.02 1.07 0.96 0.92 0.92

3.799*** 0.002

(0.511) (0.002)

0.002 0.009* 0.006 0.068*** 0.014 0.002 3.788*** 0.002

(0.004) (0.005) (0.006) (0.025) (0.014) (0.017) (0.521) (0.002)

1.02 1.07 0.95 0.92 0.93 0.99

(0.510) (0.002)

(0.004) (0.005) (0.006) (0.025) (0.013) (0.017) (0.514) (0.002)

1.06 0.99 0.92 0.97 0.95 0.97

3.215*** 0.002

0.005 0.001 0.010* 0.028 0.009 0.006 3.188*** 0.002

0.011*** 0.000 0.014*** 0.079*** 0.014

(0.003) (0.002) (0.005) (0.028) (0.009)

0.009*** 0.002 0.005 0.091*** 0.011

(0.004) (0.002) (0.005) (0.028) (0.009)

1.09 1.03 0.96 0.90 0.94

3.867*** 0.002y

(0.475) (0.002)

0.006 0.004 0.005 0.079*** 0.014 0.023 3.959*** 0.002y

(0.004) (0.003) (0.005) (0.030) (0.009) (0.020) (0.481) (0.002)

1.06 1.07 0.96 0.91 0.93 1.13

(0.464) (0.002)

(0.003) (0.002) (0.004) (0.026) (0.007) (0.016) (0.415) (0.000)

1.05 1.07 0.88 0.94 0.89 1.31

2.682*** 0.002*

0.005* 0.004* 0.015*** 0.053** 0.021*** 0.049*** 2.858*** 0.000

1.11 1.00 0.89 0.91 0.93

Notes: b ¼ logit coefficient. ***p < 0.001. **p < 0.01. *p < 0.05. yp < 0.10. One-tailed tests for focal logit coefficients, two-tailed tests for controls, and likelihood ratio tests for rho (r). se ¼ standard error. OR ¼ odds ratio for a one-standard deviation increase.

believe that the evidence of a positive association between residential exposure to Mexican immigrants and VPTB in Models 3 and 4 should be interpreted cautiously. Conversely, the bottom panel of Table 5 provides evidence of a significant association between dissimilarity from Whites and VPTB before adjusting for relative neighborhood poverty exposure. A one-standard deviation increase in the dissimilarity index was associated with an 11 percent increase in the predicted odds of VPTB. But this association was substantially smaller after adjusting for the relative poverty exposure index, though it did remain statistically significant even with this control (Model 2). Adjusting for individual-level risk factors also attenuated the association between dissimilarity and VPTB (Model 3), but less dramatically than adjusting for the relative poverty exposure index. With controls for individual-level risk factors in the model, adding the relative poverty exposure index did not significantly improve model fit (Model 4). Discussion This study had two specific aims: First, to measure the associations between metropolitan residential segregation and VPTB among both African American and Mexican-origin women and, second, to assess whether heightened exposure to neighborhood poverty accounts for the positive associations predicted by place stratification theory. African American women in highly segregated metropolitan areas are at increased risk of poor birth outcomes. Arguably the most influential explanation for this finding has been that high levels of racial residential segregation necessarily result in disproportionate exposure to neighborhood poverty among socioeconomically disadvantaged racial/ethnic groups (Massey & Denton, 1993). Yet prior research found little evidence of any such relationship among Hispanic women, particularly among Mexican immigrants, despite the latter’s similarly high poverty rates and levels of segregation from non-Hispanic Whites. Consistent with prior research, the present study found that segregation was robustly associated with VPTB among African American women. But there was little evidence that heightened exposure to neighborhood poverty could substantially account for this association. This finding may reflect the failure of measures of average levels of exposure to concentrated poverty within specific

neighborhoods to fully capture the spatial disadvantages that affect African American women in segregated US metropolitan areas. For example, the concentration of disadvantage within predominantly Black neighborhoods only partially explains the extremely high levels of violent crime typical of these neighborhoods in US cities and suburbs (Peterson & Krivo, 2010). Spillover effects from nearby neighborhoods characterized by high levels of concentrated disadvantage and violence also contribute. Future research should investigate whether measures that capture this broader spatial context can account for the relationship between segregation and poor birth outcomes among African American women. Among Mexican immigrant women, dissimilarity from nonHispanic Whites was positively associated with VPTB, but only before adjusting for differences across metropolitan areas in the extent to which Mexican immigrants were disproportionately exposed to neighborhood poverty. Conversely, neither average levels of residential isolation nor exposure to US-born coethnics was significantly associated with these outcomes among Mexican immigrant women. One reason for the disparate results was that, unlike in the case of African Americans, isolation was uncorrelated with dissimilarity from non-Hispanic Whites among Mexican immigrants (r ¼ 0.01). While African Americans lived in majority Black neighborhoods on average, Mexican immigrants typically constituted only a minority of the residents in their neighborhoods (see the isolation measures in Table 2 above). Nonetheless, Mexican immigrants were typically highly segregated in the sense that they were very unevenly distributed across neighborhoods relative to non-Hispanic Whites. And as place stratification theory predicts, residential dissimilarity from non-Hispanic Whites was associated with disproportionate exposure to neighborhood poverty and, consequently, with VPTB. The effect of segregation from Whites was not large, amounting to a few additional very preterm births per thousand. But such relatively small differences can nonetheless have a very substantial impact in a large population. Dissimilarity from Whites was also associated with an increased risk of VPTB among US-born, Mexican-origin women. To a considerable extent, this association reflected the strong relationship between segregation from Whites and disproportionate exposure to neighborhood poverty. Average levels of exposure to Mexican immigrants (though not residential isolation) were also associated with an increased risk of VPTB, but only after adjusting for prenatal

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care adequacy. We suspect this last result may be artifactual. Predicted risk of preterm birth is highly sensitive to different approaches to measuring prenatal care, since most such measures (including the Kotelchuck APNCU index employed here) are systematically related to gestational age (VanderWeele, Lantos, Siddique, & Lauderdale, 2009). Because we only obtained this result after adjusting for prenatal care adequacy, we do not view the positive association we observed between exposure to Mexican immigrants and VPTB as clear evidence that exposure to immigrant coethnics actually increases the risk of poor birth outcomes. On balance then, our results provide qualified support for the predictions derived from place stratification theory. Residential segregation is positively associated with VPTB among both African American and Mexican-origin women, though this finding is more robust across different dimensions of segregation among the former. Among Mexican-origin women, only residential dissimilarity from non-Hispanic Whites is significantly associated with VPTB; the isolation/exposure dimension is not. More surprisingly, differences across metropolitan areas in average levels of exposure to neighborhood poverty are more important in accounting for the association between residential segregation and VPTB among Mexican-origin than among African American women. This finding was particularly unexpected where Mexican immigrant women were concerned. Prior research suggested that exposure to neighborhood poverty would have weaker effects on Mexican immigrant women than on either their US-born coethnics or African American womendand that Mexican immigrant residential isolation might well protect against VPTB among Mexican immigrant women. But in fact, supplementary analyses (not shown) provided little evidence that the positive association between disproportionate exposure to neighborhood poverty and VPTB was significantly weaker among Mexican immigrant women than among their US-born coethnics. This finding contrasts with prior studies that have directly measured the effects of exposure to neighborhood poverty among individual women on low birthweight in specific cities (Collins & Shay, 1994; Finch et al., 2007). Yet it was precisely this positive association between disproportionate exposure to poverty and VPTB that largely accounted for the positive association between dissimilarity from non-Hispanic Whites and this same birth outcome among Mexican-origin women. One reason for the divergent findings may be that the metropolitan-level index of relative poverty exposure captures effects that extend beyond individual neighborhoods (Osypuk & Acevedo-Garcia, 2010). For example, disproportionate exposure to neighborhood poverty in specific metropolitan areas may have a stigmatizing effect on Mexican-origin populations. This may, in turn, lead to heightened levels of prejudice and institutionalized discrimination against Mexican-origin individuals or neighborhoods regardless of their absolute levels of poverty. While such speculations cannot be confirmed without further research, the present study nonetheless clearly established that both residential segregation from non-Hispanic Whites and disproportionate exposure to neighborhood poverty are associated with an increased risk of the very preterm birth among Mexican-origin women. References Acevedo-Garcia, D., & Osypuk, T. L. (2008). Impacts of housing and neighborhoods on health: pathways, racial/ethnic disparities, and policy dimensions. In J. H. Carr, & N. K. Kutty (Eds.), Segregation: The rising costs for America (pp. 197e 236). New York: Routledge. Alba, R. D., & Logan, J. R. (1993). Minority proximity to Whites in suburbs: an individual-level analysis of segregation. American Journal of Sociology, 98, 1388e 1427. Alba, R. D., Logan, J. R., & Stults, B. J. (2000). The changing neighborhood contexts of the immigrant metropolis. Social Forces, 79, 587e621.

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