2011 Progress Report: Research Project B: Healthy Pregnancy, Healthy Baby: Studying Racial Disparities in Birth Outcomes

EPA Grant Number: R833293C002
Subproject: this is subproject number 002 , established and managed by the Center Director under grant R833293
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: Southern Center on Environmentally Driven Disparities in Birth Outcomes
Center Director: Miranda , Marie Lynn
Title: Research Project B: Healthy Pregnancy, Healthy Baby: Studying Racial Disparities in Birth Outcomes
Investigators: Williams, Redford , Ashley-Koch, Allison , Auten, Richard , Maxson, Pamela , Miranda , Marie Lynn , Reiter, Jerome , Swamy, Geeta
Current Investigators: Williams, Redford , Ashley-Koch, Allison , Gibson-Davis, Christina , Maxson, Pamela , Miranda , Marie Lynn , Reiter, Jerome , Swamy, Geeta
Institution: Duke University
EPA Project Officer: Callan, Richard
Project Period: May 1, 2007 through April 30, 2012 (Extended to April 30, 2014)
Project Period Covered by this Report: May 1, 2011 through April 30,2012
RFA: Centers for Children’s Environmental Health and Disease Prevention Research (2005) RFA Text |  Recipients Lists
Research Category: Children's Health , Health Effects , Health

Objective:

The central objective of the Healthy Pregnancy, Healthy Baby Study is to determine how the interaction of environmental, social, and host factors contributes to disparities in birth outcomes between African-American and white women in the American South. There are four specific aims:

  1. Conduct a cohort study of pregnant women in Durham, NC designed to correlate birth weight, gestation, and birth weight x gestation with environmental, social, and host factors;
  2. Develop community-level measures of environmental and social factors by inventorying neighborhood quality and the built environment in partnership with local community groups;
  3. Create a comprehensive data architecture, spatially resolved at the tax parcel level, of environmental, social, and host factors affecting pregnant women by linking data from the cohort study and neighborhood assessments with additional environmental and socioeconomic data; and
  4. Determine whether and to what extent differential exposures explain health disparities in birth outcomes by applying innovative spatial and genetic statistical methods to:
    1. Identify environmental, social, and host factors that cluster to predict birth outcomes in the entire sample,
    2. Determine whether these clusters are more or less present in African-American versus white populations and quantify the proportion of health disparities explained by differences in cluster frequency, and
    3. Identify environmental, social, and host factors that cluster to predict birth outcomes within the African-Americanand white sub-samples and compare these clusters across racial groups.

Progress Summary:

As of 4/1/2012, 1889 women have been enrolled in the study. Women are recruited from Duke University Medical Center (DUMC) and Lincoln Community Health Center. Demographic data indicate that we are successfully recruiting women who are most at risk for adverse pregnancy outcomes, particularly low-income, low educational attainment, and non-Hispanic black women.  Data collection is now complete.

All maternal data are georeferenced (i.e., linked to the physical address of the mother) using Esri software. The Healthy Pregnancy/Healthy Baby Study also includes an in-depth neighborhood assessment designed to capture both built environment and community-level social stressors and community resources. The cohort study and neighborhood assessment data are spatially linked to extensive environmental and demographic data at a highly resolved spatial scale. 

Genetic Data and Analysis. This project focused on genetic analysis of candidate genes, specifically those involving human environmental contaminant clearance (heavy metals and environmental tobacco smoke), infection and inflammation (cytokines, chemokines, and bacterial pathogen recognition), maternal stress response (serotonin), and other pathways that have been implicated as potential drivers of health disparities (vascular responsivity). To date, we have genotyped 412 Single Nucleotide Polymorphisms (SNPs) in fifty-two candidate genes. This past year, we focused on completing the genotyping of those SNPs in the samples which had been most recently ascertained.

Psychosocial Indicators. Analyses have been completed on psychosocial influences on birth outcomes. In order to reduce the number of psychosocial variables, cluster analysis has been performed, resulting in three distinct clusters of women. A paper examining the relationship between the built environment as measured through the Community Assessment Project and women’s psychosocial health was published in year 5. Future analyses will continue with a focus on the relationships among psychosocial health, risk behaviors, chemical and non-chemical stressors, and pregnancy outcomes.

Maternal Medical Complications. Fetal health is not only individually determined, but is also influenced by maternal health and well-being. This past year, we put additional emphasis on maternal outcomes.

Statistical Methods Development. We developed several new statistical methodologies designed to improve analysis of the Project B data, as well as to advance statistical analysis more broadly. First, we developed and implemented methods for finding important predictors in quantile regression when there are a very large number of covariates. These methods adapted the lasso and elastic net penalties for quantile regression. We applied the methods on a mid-study sample of women to uncover a previously unreported interaction: women who smoke and who have high blood lead levels tend to have babies with lower birth weights. Second, we developed and implemented methods for using factor analysis models in the context of quantile regression. The investigative team believes that many of the predictors can be grouped into underlying factors. Third, we developed and implemented methods for accounting for mid-study changes in measurement scales. These methods were needed because the Project B investigators switched laboratories for measuring blood levels of heavy metals midway through data collection in order to take advantage of finer measurement scales.  Exploratory analysis indicated that the distributions of levels for several exposures were markedly different across the labs, so that analyses based on a simple concatenation of the two labs’ data would be biased. We also developed a Bayesian growth mixture model to jointly examine the associations between longitudinal blood pressure measurements, preterm birth (PTB), and low birthweight (LBW). The model partitions women into distinct classes characterized by a mean arterial pressure (MAP) curve and joint probabilities of PTB and LBW. Each class contains a unique mixed effects model for MAP with class-specific regression coefficients and random effect covariances. To account for the high correlation between PTB and LBW, we introduce a bivariate probit model within each class to capture residual within-class dependence between PTB and LBW. The model permits the association between PTB and LBW to vary by class, so that for some classes, PTB and LBW may be positively correlated, while for others, they may be uncorrelated or negatively correlated.

We also focused statistical methods development on the genetic data. The first statistical innovation involving the genetic data is the adverse sub-population regression (ASPR) for multivariate outcomes with high dimensional predictors. The ASPR is a two component latent class model, with the dominant component corresponding to (presumed) healthy individuals and the risk of falling in the minority component characterized via a logistic regression. The logistic regression model is designed to accommodate high-dimensional predictors, as occur in studies with a large number of gene by environment interactions, through use of a flexible nonparametric multiple shrinkage approach. The Gibbs sampler is developed for posterior computation.

Future Activities:

In the next year, we will focus on data analysis and further statistical methods innovation. Our overall goal is to identify complex interactions among host, social, and environmental contributors. With the data collection complete, we will are well-positioned to examine and identify combinations of factors that lead to health disparities in birth outcomes. We are particularly interested in identifying chemical and non-chemical environmental risk factors given that they are actionable to improve birth outcomes.


Journal Articles on this Report : 17 Displayed | Download in RIS Format

Other subproject views: All 51 publications 26 publications in selected types All 26 journal articles
Other center views: All 162 publications 76 publications in selected types All 75 journal articles
Type Citation Sub Project Document Sources
Journal Article Burgette LF, Reiter JP, Miranda ML. Exploratory quantile regression with many covariates: an application to adverse birth outcomes. Epidemiology 2011;22(6):859-866. R833293 (2010)
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  • Abstract from PubMed
  • Abstract: Lippincott Williams & Wilkins-Abstract
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  • Other: Duke-Prepublication Copy PDF
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  • Journal Article Burgette LF, Reiter JP. Nonparametric Bayesian multiple imputation for missing data due to mid-study switching of measurement methods. Journal of the American Statistical Association 2012;107(498):439-449. R833293 (2010)
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  • Full-text: American Statistical Association-Full Text HTML
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  • Abstract: American Statistical Association-Abstract
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  • Other: American Statistical Association-Full Text PDF
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  • Journal Article Burgette LF, Reiter JP. Modeling adverse birth outcomes via confirmatory factor quantile regression. Biometrics 2012;68(1):92-100. R833293 (2010)
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  • Abstract: Wiley-Abstract
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  • Journal Article Buttke DE, Wolkin A, Stapleton HM, Miranda ML. Associations between serum levels of polybrominated diphenyl ether (PBDE) flame retardants and environmental and behavioral factors in pregnant women. Journal of Exposure Science & Environmental Epidemiology 2013;23(2):176-182. R833293 (2011)
    R833293 (Final)
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  • Abstract: Nature-Abstract
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  • Journal Article Chang HH, Reich BJ, Miranda ML. Chang et al. Respond to “Environmental exposures and preterm birth." American Journal of Epidemiology 2012;175(2):111-112. R833293 (2011)
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  • Full-text: AJE-Full Text HTML
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  • Abstract: AJE-Abstract
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  • Journal Article Chang HH, Reich BJ, Miranda ML. Time-to-event analysis of fine particle air pollution and preterm birth: results from North Carolina, 2001-2005. American Journal of Epidemiology 2012;175(2):91-98. R833293 (2010)
    R833293 (2011)
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    R833293C001 (2010)
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  • Full-text: AJE - Full Text HTML
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  • Abstract: AJE - Abstract
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  • Journal Article Chang HH, Reich BJ, Miranda ML. A spatial time-to-event approach for estimating associations between air pollution and preterm birth. Journal of the Royal Statistical Society--Series C (Applied Statistics) 2013;62(2):167-179. R833293 (2011)
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    R834799 (2014)
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    R834799C003 (2014)
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  • Full-text: University of Michigan-Full Text PDF
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  • Abstract: Wiley-Abstract
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  • Journal Article Maxson PJ, Edwards SE, Ingram A, Miranda ML. Psychosocial differences between smokers and non-smokers during pregnancy. Addictive Behaviors 2012;37(2):153-159. R833293 (2011)
    R833293 (Final)
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  • Journal Article Maxson P, Miranda ML. Pregnancy intention, demographic differences, and psychosocial health. Journal of Women's Health 2011;20(8):1215-1223. R833293 (2010)
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  • Abstract: Liebert-Abstract
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  • Journal Article Messer LC, Maxson P, Miranda ML. The urban built environment and associations with women's psychosocial health. Journal of Urban Health 2013;90(5):857-871. R833293 (2011)
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  • Journal Article Miranda ML, Edwards SE, Chang HH, Auten RL. Proximity to roadways and pregnancy outcomes. Journal of Exposure Science & Environmental Epidemiology 2013;23(1):32-38. R833293 (2011)
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  • Full-text: University of Michigan-Full Text PDF
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  • Abstract: Nature-Abstract
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  • Journal Article Neelon B, Swamy GK, Burgette LF, Miranda ML. A Bayesian growth mixture model to examine maternal hypertension and birth outcomes. Statistics in Medicine 2011;30(22):2721-2735. R833293 (2010)
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  • Journal Article Schwartz S, Li F, Reiter JP. Sensitivity analysis for unmeasured confounding in principal stratification settings with binary variables. Statistics in Medicine 2012;31(10):949-962. R833293 (2010)
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  • Journal Article Stapleton HM, Eagle S, Anthopolos R, Wolkin A, Miranda ML. Associations between polybrominated diphenyl ether (PBDE) flame retardants, phenolic metabolites, and thyroid hormones during pregnancy. Environmental Health Perspectives 2011;119(10):1454-1459. R833293 (2011)
    R833293 (Final)
    R833293C002 (2011)
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  • Journal Article Swamy GK, Garrett ME, Miranda ML, Ashley-Koch AE. Maternal vitamin D receptor genetic variation contributes to infant birthweight among black mothers. American Journal of Medical Genetics Part A 2011;155A(6):1264-1271. R833293 (2009)
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  • Journal Article Swamy GK, Edwards S, Gelfand A, James SA, Miranda ML. Maternal age, birth order, and race: differential effects on birthweight. Journal of Epidemiology and Community Health 2012;66(2):136-142. R833293 (2009)
    R833293 (2010)
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  • Journal Article Zhu B, Dunson DB, Ashley-Koch AE. Adverse subpopulation regression for multivariate outcomes with high-dimensional predictors. Statistics in Medicine 2012;31(29):4102-4113. R833293 (2011)
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  • Full-text: ResearchGate-Abstract & Full Text PDF
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  • Abstract: Wiley-Abstract
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  • Supplemental Keywords:

    pregnancy, preterm birth, low birth weight, racial disparity, African American, environmental stressors, gene-environment interactions, psychosocial stressors, genes, single nucleotide polymorphisms, genetic admixture

    Progress and Final Reports:

    Original Abstract
  • 2007
  • 2008
  • 2009 Progress Report
  • 2010 Progress Report
  • 2012
  • Final Report

  • Main Center Abstract and Reports:

    R833293    Southern Center on Environmentally Driven Disparities in Birth Outcomes

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R833293C001 Research Project A: Mapping Disparities in Birth Outcomes
    R833293C002 Research Project B: Healthy Pregnancy, Healthy Baby: Studying Racial Disparities in Birth Outcomes
    R833293C003 Research Project C: Perinatal Environmental Exposure Disparity and Neonatal Respiratory Health
    R833293C004 Community Outreach and Translation Core
    R833293C005 Geographic Information System and Statistical Analysis Core