Article Database

Stress During Pregnancy: the Role of Institutional Racism

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Institutional racism, also known as structural racism, can be defined as differential access to resources and opportunities by race as well as policies, laws, and practices that reinforce racial inequity. This study examines how institutional racism in the form of residential redlining (neighbourhood-level racial inequities in mortgage lending) and segregation (geographic separation of groups by race) is associated with self-reported stress among a diverse cohort of pregnant women. Institutional racism was measured by a residential redlining index using Home Mortgage Disclosure Act data and residential segregation using 2000 US Census data. These redlining and segregation indices were linked with data from a pregnancy cohort study (n = 4652), which included individual measures of reported stress. We ran multilevel linear regression models to examine the association between redlining, segregation and reported stress. Hispanic women compared with all other women were slightly more likely to report stress. There was no significant relationship between redlining and stress among this population. However, higher neighbourhood percentage black was inversely associated with stress. This study suggests that some forms of segregation may be associated with reported stress. Future studies should consider how redlining and segregation may provide an understanding of how institutional racism and the neighbourhood context may influence stress and health of populations.

Neighborhood Socioeconomic Disadvantage and Gestational Weight Gain and Loss

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We explored the relationship between neighborhood socioeconomic disadvantage (NSED) and gestational weight gain and loss and if the association differed by race. A census tract level NSED index (categorized as low, mid-low, mid-high, and high) was generated from 12 measures from the 2000 US Census data. Gestational weight gain and other individual-level characteristics were derived from vital birth records for Allegheny County, PA for 2003-2010 (n = 55,608). Crude and adjusted relative risks were estimated using modified multilevel Poisson regression models to estimate the association between NSED and excessive and inadequate gestational weight gain (GWG) and weight loss (versus adequate GWG). Black women lived in neighborhoods that were more likely to be socioeconomically disadvantaged compared to white women. Almost 55% of women gained an excessive amount of weight during pregnancy, and 2% lost weight during pregnancy. Black women were more likely than white women to have inadequate weight gain or weight loss. Mid-high (aRR = 1.3, 95% CI 1.2, 1.3) and high (aRR = 1.5, 95% CI 1.5, 1.6) NSED compared to low NSED was associated with inadequate weight gain while NSED was not associated with excessive weight gain. Among black women, high versus low NSED was associated with weight loss during pregnancy (RR = 1.6, 95% CI 1.1, 2.5). Among white women, each level of NSED compared to low NSED was associated with weight loss during pregnancy. This study demonstrates how neighborhood socioeconomic characteristics can contribute to our understanding of inadequate weight gain and weight loss during pregnancy, having implications for future research and interventions designed to advance pregnancy outcomes.

Factors Associated with Distance and Time Traveled to Cleft and Craniofacial Care

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Institutional Racism, Neighborhood Factors, Stress, and Preterm Birth

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Objective. Racial/ethnic disparities in the risk of preterm birth may be explained by various factors, and previous studies are limited in examining the role of institutional racism. This study focused on the following questions: what is the association between preterm birth and institutional racism as measured by residential racial segregation (geographic separation by race) and redlining (black–white disparity in mortgage loan denial); and what is the association between preterm birth and reported stress, discrimination, and neighborhood quality.

Design. We used data from a clinic-based sample of pregnant women (n = 3462) participating in a stress and pregnancy study conducted from 1999 to 2004 in Philadelphia, PA (USA). We linked data from the 2000 US Census and Home Mortgage Disclosure Act (HMDA) data from 1999 to 2004 and developed measures of residential redlining and segregation.

Results. Among the entire population, there was an increased risk for preterm birth among women who were older, unmarried, tobacco users, higher number of previous births, high levels of experiences of everyday discrimination, owned their homes, lived in nonredlined areas, and areas with high levels of segregation measured by the isolation index. Among black women, living in a redlined area (where blacks were more likely to be denied mortgage loans compared to whites) was moderately associated with a decreased risk of preterm birth (aRR = 0.8, 95% CI: 0.6, 0.99).

Conclusion. Residential redlining as a form institutional racism and neighborhood characteristic may be important for understanding racial/ethnic disparities in pregnancy and preterm birth.

Perspectives From Community-Based Doulas and Mothers: Neighborhood Context and Pregnancy

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Barriers to Care for Children with Orofacial Clefts in North Carolina

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A Methodology for Combining Multiple Commercial Data Sources to Improve Measurement of the Food and Alcohol Environment: Applications of Geographical Information Systems

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Commercial data sources have been increasingly used to measure and locate community resources. We describe a methodology for combining and comparing the differences in commercial data of the food and alcohol environment. We used commercial data from two commercial databases (InfoUSA and Dun&Bradstreet) for 2003 and 2009 to obtain infor- mation on food and alcohol establishments and developed a matching process using computer algorithms and manual review by applying ArcGIS to geocode addresses, standard industrial classification and North American industry classification tax- onomy for type of establishment and establishment name. We constructed population and area-based density measures (e.g. grocery stores) and assessed differences across data sources and used ArcGIS to map the densities. The matching process resulted in 8,705 and 7,078 unique establishments for 2003 and 2009, respectively. There were more establishments cap- tured in the combined dataset than relying on one data source alone, and the additional establishments captured ranged from 1,255 to 2,752 in 2009. The correlations for the density measures between the two data sources was highest for alcohol out- lets (r = 0.75 and 0.79 for per capita and area, respectively) and lowest for grocery stores/supermarkets (r = 0.32 for both). This process for applying geographical information systems to combine multiple commercial data sources and develop meas- ures of the food and alcohol environment captured more establishments than relying on one data source alone. This replic- able methodology was found to be useful for understanding the food and alcohol environment when local or public data are limited.

Neighborhood Racial and Socioeconomic Disparities in the Food and Alcohol Environment: Are There Differences by Commercial Data Sources?

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Objectives: This study examined neighborhood racial and socioeconomic disparities and the density of food and alcohol establishments. We also examined whether these disparities differed by data source.

Methods: This study included commercial data for 2003 and 2009 from InfoUSA and Dun and Bradstreet (D&B) in 416 census tracts in Allegheny County, PA. Food and alcohol establishment densities were calculated by using area and population data from the 2000 US census. Differences between InfoUSA and D&B of food and alcohol densities across neighborhood racial and socioeconomic characteristics were tested using correlations and two-way mixed analysis of variance (ANOVA).

Results: There were differences by data source in the association between neighborhood racial and socioeconomic characteristics and food/alcohol establishment density. There was a positive correlation between grocery store/supermarket density and percentage black, poverty, and percentage without a car among D&B data but not in InfoUSA. Alcohol outlet density (AOD) increased as neighborhood poverty increased for both data sources, but the mean difference in AOD between InfoUSA and D&B was highest among neighborhoods with 25-50 % poverty (Cohen’s d -0.49, p < 0.001) compared to neighborhoods with lower or higher poverty (2003 data). Mean grocery store density increased as percentage poverty increased, but only among D&B (2009 data).

Conclusions: Differences in commercial data in the location and numeration of food and alcohol establishments are associated with neighborhood racial and socioeconomic characteristics and may introduce biases concerning neighborhood food and alcohol environments, racial and socioeconomic disparities, and health.

Neighborhood Factors and Six-Month Weight Change Among Overweight Individuals in a Weight Loss Intervention

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The purpose of this study was to examine the neighborhood environment and the association with weight change among overweight/obese individuals in the first six months of a 12-month weight loss intervention, EMPOWER, from 2011 to 2015. Measures of the neighborhood environment included neighborhood racial composition, neighborhood income, and neighborhood food retail stores density (e.g., grocery stores). Weight was measured at baseline and 6 months and calculated as the percent weight change from baseline to 6 months. The analytic sample (N = 127) was 91% female and 81% white with a mean age of 51 (± 10.4) years. At 6 months, the mean weight loss was 8.0 kg (± 5.7), which was equivalent to 8.8% (± 6%) of baseline weight. Participants living in neighborhoods in which 25–75% of the residents identified as black had the greatest percentage of weight loss compared to those living in neighborhoods with < 25% or > 75% black residents. No other neighborhood measures were associated with weight loss. Future studies testing individual-level behavioral weight loss interventions need to consider the influence of neighborhood factors, and how neighborhood-level interventions could be enhanced with individual-level interventions that address behaviors and lifestyle changes.

Neighborhood Racial Composition and Poverty in Association With Pre-Pregnancy Weight and Gestational Weight Gain

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