Grantee Research Project Results
Final Report: Research Project B: Healthy Pregnancy, Healthy Baby: Studying Racial Disparities in Birth Outcomes
EPA Grant Number: R833293C002Subproject: 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: The Center for Study of Neurodevelopment and Improving Children's Health
Center Director: Murphy, Susan K.
Title: Research Project B: Healthy Pregnancy, Healthy Baby: Studying Racial Disparities in Birth Outcomes
Investigators: Williams, Redford , Miranda , Marie Lynn , Ashley-Koch, Allison , Gibson-Davis, Christina , Swamy, Geeta , Reiter, Jerome , Maxson, Pamela
Institution: Duke University
EPA Project Officer: Callan, Richard
Project Period: May 1, 2007 through April 30, 2012 (Extended to April 30, 2014)
RFA: Centers for Children’s Environmental Health and Disease Prevention Research (2005) RFA Text | Recipients Lists
Research Category: Children's Health , Human Health
Objective:
The central objective of the Healthy Pregnancy, Healthy Baby Study was 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 were four specific aims:
- 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;
- Develop community-level measures of environmental and social factors by inventorying neighborhood quality and the built environment in partnership with local community groups;
- 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
- Determine whether and to what extent differential exposures explain health disparities in birth outcomes by applying innovative spatial and genetic statistical methods to:
- Identify environmental, social, and host factors that cluster to predict birth outcomes in the entire sample;
- 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
- Identify environmental, social, and host factors that cluster to predict birth outcomes within the African-American and white sub-samples and compare these clusters across racial groups.
Summary/Accomplishments (Outputs/Outcomes):
We successfully recruited 1889 women into our prospective cohort study, Healthy Pregnancy, Healthy Baby. Women were recruited from Duke University Medical Center (DUMC) and Lincoln Community Health Center. Demographic data indicate that we were highly successful recruiting women most at risk for adverse pregnancy outcomes, particularly low-income, low educational attainment, and non-Hispanic black women.
The following information was collected from participants in the Healthy Pregnancy, Healthy Baby Study:
- Psychosocial measures: CES-D, perceived stress, self-efficacy, interpersonal support, paternal support, perceived racism, perceived community standing, pregnancy intention, John Henryism Active Coping Scale, NEO Five Factor Inventory of personality.
- Environmental exposure survey measures: short survey on fish consumption, smoking pattern and exposure to second-hand smoke, and drinking water source.
- Maternal and neonatal medical record abstraction: detailed pre-pregnancy medical and social history, antepartum complications, birth outcomes, and neonatal complications.
- Blood samples for genetic and environmental analysis to assess candidate genes related to environmental contaminant (nicotine, cotinine, cadmium, lead, mercury, arsenic, and manganese) metabolism, inflammation, vascular dysfunction, and stress response.
- Cord blood and placental samples currently are being stored for future genetic analysis and evaluation of activity at the maternal-fetal interface.
We also were highly successful in collection of participant-level data as well as biological samples, with greater than 90% attainment of maternal blood sample for genetic and environmental analyses. Collection of cord blood and placental samples, which began in June 2007, also has been successful with approximately 960 delivery samples collected.
All maternal data have been georeferenced (i.e., linked to the physical address of the mother) using Geographic Information System (GIS) software. The Healthy Pregnancy/Healthy Baby Study also included two in-depth neighborhood assessments designed to capture both built environment and community-level social stressors and community resources. In order to increase the participant capture rate (first assessment: 40%), we expanded our second assessment area, successfully capturing approximately 70% of the participants. The cohort study and neighborhood assessment data are spatially linked to extensive environmental and demographic data at a highly resolved spatial scale.
We genotyped the cohort for 412 Single Nucleotide Polymorphisms (SNPs) in 52 genes related to 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 better identify subpopulations among NHB women in our sample, we generated the Illumina African American Admixture Chip, based on 1509 selected SNPs with disparate frequencies in the Yoruban (African) and European (Caucasian) HapMap samples. For the purpose of addressing population stratification, we used clustering algorithms on the Illumina data to identify sub-populations within our NHB women and found that indeed some stratification does exist. Thus, we used the genome-wide percentage of European admixture as a continuous covariate in our candidate gene analyses.
Genetic Analysis
The Vitamin D receptor gene (VDR) has a wide variety of functions, including calcium homeostasis and modulating circulating levels. Subtle genetic variation also has been linked to adverse conditions including diabetes, cancer, renal disease, and autoimmune disorders. In multivariable regression modeling, we found a significant association between the VDR variant (rs731236, a coding, synonymous SNP) and preterm birth (p=0.04) for non-Hispanic black (NHB) women in our study population. The odds of having an infant born preterm were 2.9 times higher for women with the CC genotype at this marker compared with women with the TT genotype (p=0.04) and were 3.8 times higher for women with the CC genotype compared with women with the CT genotype (p=0.01). This same association did not hold true among the non-Hispanic white (NHW) women. Furthermore, in addition to six other SNPs within the VDR gene, rs731236 also was associated with infant birthweight among NHB but not NHW women (Swamy, et al., 2011)
The nitric oxide (NO) pathway is critical for managing oxidative damage in a variety of tissues. Reduced levels of endothelial nitric oxide synthase (NOS3) have been previously linked to preeclampsia, a maternal complication associated with preterm birth. Also pertinent to this project is that specific polymorphisms within the inducible nitric oxide synthase (NOS2A) gene have been associated with protection against malaria; thus, there may be population specific selective forces leading to differential allele frequencies for the polymorphisms in these genes. For these reasons, we hypothesized that polymorphisms within the NOS genes may differentially affect risk for preterm birth among African American mothers in our cohort. We examined 57 SNPs in the three nitric oxide synthase genes (NOS1, NOS2A and NOS3) for association with risk for preterm birth in our cohort. We identified 10 SNPs in NOS1 that were nominally associated with risk for preterm birth in our NHW subset of mothers. Only 1 SNP in NOS2A was nominally associated with preterm birth in our NHB subset of mothers. Thus, we did observe differential association with these genes and preterm birth as a function of maternal race. However, we were surprised that the effects that we observed were stronger for the NHW subset rather than the NHB subset.
We also have examined polymorphisms in the G-protein coupled receptor kinase 5 (GRK-5) gene. GRK5 is associated with a pharmacogenomic interaction among African Americans in the setting of cardiovascular disease and response to β-adrenergic receptor (βAR) blockade, which is standard therapy for cardiac failure and ischemia. Because of the association with cardiovascular disease, we hypothesized that GRK-5 genetic variation was associated with hypertensive disorders in pregnancy. We defined hypertensive disorders as chronic hypertension (CHTN=BP>140/90 before 20 wks), preeclampsia (BP>140/90 and proteinuria), and CHTN + superimposed preeclampsia (CHTN with new onset or worsening proteinuria). Haplotype tagging single nucleotide polymorphisms (SNPs) were genotyped for GRK-5 via Taqman assays. Logistic regression was used to examine the relationship between maternal genotype and each hypertensive disorder among the NHB women, adjusting for age, education, insurance, tobacco use, and pre-pregnancy BMI. CHTN was included as a covariate in the model for preeclampsia. In our NHB data set, 125 out of 587 participants (21%) were diagnosed with preeclampsia. Of the 17 SNPs examined, 3 were nominally associated with preeclampsia. For the most significant association with rs10886445 (global p=0.0009), the odds of preeclampsia for NHB women with the CC genotype were 0.28 times that for NHB women with the TT genotype (CI: 0.1429, 0.552). For those NHB women with the CT genotype, the odds of developing preeclampsia were 0.33 times that for NHB women with the TT genotype (CI: 0.1682, 0.656). In addition, rs12416565 (global p=0.003) and rs11198925 (global p=0.02) also were nominally associated. For CHTN, only one marker (rs2420620, global p=0.02) demonstrated nominal association. Similarly, for CHTN+preeclampsia, only one marker (rs10510055, global p=0.02) demonstrated nominal association. Based on these results, we concluded that the GRK-5 gene may play a role in hypertensive disorders of pregnancy, particularly the development of preeclampsia.
In our NHB women, we have examined G*E between genes in the inflammatory pathway and ETS as they relate to infant birthweight and identified several nominal associations, the most significant being rs2069771 in the interleukin-2 gene with cadmium exposure (global p=0.005) and rs9005 in the interleukin 1 receptor antagonist with cadmium exposure (global p=0.006). In addition, also among the NHB women, we have identified G*E interactions between the n-acetyltransferase genes and cadmium exposure predicting maternal preeclampsia and infant outcomes. In particular, rs8190845 in NAT1 interacted with cadmium exposure to predict occurrence of preeclampsia in the mother (global p=0.009). Additionally, rs17126345 , also in NAT1, interacted with cotinine exposure to predict the occurrence of preterm birth, defined as delivery prior to 37 weeks gestation (global p=0.006).
The inflammatory response influences risk for adverse birth outcomes such as low birthweight. Variability in maternal inflammatory response may be exacerbated by exposure to air pollution during pregnancy. We examined how variation in maternal inflammatory genes interacts with air pollution to affect infant birthweight (BWT) in 673 NHB women participating in the Healthy Pregnancy, Healthy Baby Study. Maternal residential address at enrollment was georeferenced, and the distance to the nearest major roadway was calculated as a proxy for traffic-related air pollution exposure. One hundred five haplotype tagging SNPs were genotyped in 20 candidate genes on maternal DNA samples. Linear regression was used to examine the relationship between SNPs and infant BWT, adjusting for infant sex, maternal age, parity, education, insurance, and smoking use. We also examined interactions between SNPs and roadway proximity. Consistent with previous reports, genetic variation in the inflammatory response provided evidence for main effects on infant BWT among NHB women in our study. We provide the first evidence that some of these genes interact with air pollution exposure to influence infant BWT.
Environmental Sampling
Using the maternal environmental blood samples collected on all participants in Project B (R833293C002), we characterized maternal exposures to toxics.
Lead. In addition to documenting the blood lead burdens among a cohort of pregnant women in Durham County, NC, we have been able to characterize current maternal exposures to lead by linking each participant to the tax parcel at which they resided during their pregnancy. We found that both year built and modeled lead exposure risk at participants' residence during pregnancy were not predictive of maternal blood lead levels. Taken in combination with results showing that maternal blood levels increased with age, these findings indicate that maternal blood lead levels are much more likely the result of lead remobilization from historic exposures as opposed to contemporaneous exposures (Miranda, et al., 2010).
Mercury. Using self-reported fish consumption and maternal blood samples, we examined correlates of mercury levels during pregnancy. Higher income and education were associated with greater fish consumption, as well as higher levels of mercury when controlling for fish consumption (Miranda, Edwards, and Maxson, 2011). Our work with mercury led to our collaboration with Women, Infants, and Children (WIC) in North Carolina to craft culturally appropriate messages for Latina women who consume fish caught in North Carolina waters. This project is described under the COTC.
Cadmium. Cadmium is prevalent in the environment and understudied as a developmental toxicant. We conducted an analysis of maternal cadmium exposure and leukocyte DNA methylation patterns in 17 mother-newborn pairs. A methylated cytosine-guanine (CpG) island recovery assay was used to assess more than 4.6 million sites spanning 16,421 CpG islands. Exposure to cadmium and cotinine was classified for each mother-newborn pair according to maternal blood levels. Comparative methylation analysis was performed to identify genes with differential methylation levels. DNA motifs that were overrepresented among the differentially methylated genes were identified. Subsets of genes were identified that showed altered DNA methylation levels in fetal DNA associated with exposure to cadmium (n=61), cotinine (n=366), or both (n=30). In maternal DNA, subsets of cadmium-associated (n=92) and cotinine-associated (n=134) genes were identified. While the gene sets were largely distinct between mothers and newborns, functional similarities at the biological pathway level were identified including transcriptional regulation and apoptosis. Furthermore, conserved DNA motifs with sequence similarity to specific transcription factor binding sites were identified within the CpG islands of the gene sets. This pilot investigation provides evidence for distinct patterns of DNA methylation alterations in fetal and maternal DNA associated with exposure to cadmium. The genes with differential methylation share common motifs at the sequence level suggesting that structural commonalities in DNA sequence may affect environmentally related DNA methylation status (Sanders, et al., 2013). A paper describing risk factors for elevated levels of cadmium during pregnancy is forthcoming (Edwards, et al., forthcoming), and a paper linking cadmium levels with pregnancy outcome has been submitted (Johnson, et al., in submission).
Polybrominated Diphenyl Ether (PBDE). Our clinical obstetrics work led to a fruitful collaboration with Dr. Heather Stapleton, a leading expert in PBDE research. This work examined PBDE levels in pregnant women and the association with thyroid hormones (Stapleton, et al., 2011) and pregnancy outcomes (Miranda, et al., in submission). In Stapleton, et al. (2011), we found that BDEs 47, 99, and 100 were significantly and positively associated with free and total thyroxine levels and with total triiodothyronine levels above the normal range. The more recent work (by Miranda, et al.) shows that while certain maternal PBDE levels are negatively associated with infant head circumference, the relationship does not appear to be mediated by thyroid hormone levels.
Additional Projects
Residential mobility. With our access to the North Carolina Detailed Birth Record (DBR) in Project A (R833293C001), we have been able to link participants in Project B (R833293C002) with their birth certificate data. Using maternal and infant identifying information, including name, place, and date of birth, we have been able to link 991 (99.9%) of participants who completed the study and had a live birth by December 31, 2008, and 59 (76.6%) of participants who were lost-to-follow-up but with an expected delivery date on or before December 31, 2008. This linkage allowed us to determine who is moving during pregnancy (by comparing the address at enrollment and the DBR address at delivery) and the nature of those moves, including the quality of the new location compared to the previous location (and thus changes in environment or exposure).
Proximity to Roadways. In parallel to the Project A (R833293C001) work with road proximity metrics, we geocoded Project B (R833293C002) participants to the tax parcel level and then calculated the distance to the nearest roadways. We extended the road proximity work in Project A by incorporating the rich set of variables available in Project B, including analysis looking at how psychosocial health and gene-by-environment interactions may influence the impact of traffic-related air pollution on birth outcomes (Miranda, et al., 2013).
Community Assessment Project/Built Environment. The Community Assessment Project (CAP) assessed built environment variables at two times (2008 and 2011) for more than 17,000 and 34,000 tax parcels, respectively, including the home addresses of more than 70% of the participants in the Healthy Pregnancy, Healthy Baby Study (SCEDDBO Project B). Seven scales (housing damage, property disorder, security measures, tenure, vacancy, violent crime, and nuisances) have been constructed at five levels of geography (census block, primary adjacency neighborhood, census block group, census tract and city-defined neighborhoods). Analyses have assessed the relationship between the built environment and maternal psychosocial status (Messer, et al., 2012) and pregnancy outcomes (Miranda, et al., 2012).
Psychosocial Indicators. Analyses have been completed on psychosocial influences on birth outcomes. The relationships among pregnancy intention, psychosocial health, and pregnancy outcomes have been examined, with a paper published (Maxson, et al., 2011). In addition, we have examined pregnancy intention, behavioral choice, and environmental exposures. The influences of psychosocial health and smoking status have been studied, with a resulting publication (Maxson, et al., 2012). In order to reduce the number of psychosocial variables, cluster analysis has been performed, resulting in three distinct clusters of women. Cluster analysis on the personality indices also was performed. A paper examining the relationship between the built environment as measured through the Community Assessment Project and women's psychosocial health was published (Messer, et al., 2012). We will continue analysis 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 also is influenced by maternal health and well-being. We continue our emphasis on maternal outcomes. In particular, we have focused on hypertensive disorders during pregnancy. We have identified factors that affect maternal blood pressure during pregnancy. To make use of all blood pressure readings collected across the pregnancy, we considered a variety of statistical approaches, including latent trajectory and sparse functional data models (Neelon, et al., 2011).
Statistical Methods Development. We developed new statistical methodologies designed to improve analysis of the Project B (R833293C002) data, as well as to advance statistical analysis more broadly. A paper detailing statistical methodology developed in Year 5 for accounting for mid-study changes in measurement scales won the Youden award for the best paper in interlaboratory testing methods this past year (Burgette and Reiter, 2012). 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 data of the two labs would be biased. Using the second lab scale as the standard, so that effectively measurements before the lab switch are treated as missing, we developed general purpose methodology for imputing plausible values of the missing exposure measurements. The methods are based on assumptions about the relative ranks of measurements in the two scales, e.g., a measurement in the 10th percentile in one scale should be at the 10th percentile in the other scale. We implemented this methodology on the Project B data to provide the investigative team with improved data.
In addition, 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 (Burgette, et al., 2012).
We developed and implemented methods for using factor analysis models in the context of quantile regression. The investigative team believed that many of the predictors can be grouped into underlying factors. For example, the Project B data contain several variables that measure maternal stress, and arguably we should connect birth outcomes to the underlying factor of stress rather than its individual indicators. As another example, the data contain several imperfect indicators of smoking status, and we wanted to connect birth outcomes to the underyling factor of true smoking status. We implemented the model on a mid-study sample of women from Project B, and we found that the smoking factor was a strong predictor of low birth weight. An article on this research was accepted for publication in Biometrics (Burgette and Reiter, 2012).
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 introduced 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 allowed maternal covariates to influence the class probabilities via a multinomial logit model. For posterior computation, we proposed an efficient Markov chain Monte Carlo algorithm that combines full-conditional Gibbs and Metropolis steps. We applied our model to a sample of 1027 women enrolled in the Healthy Pregnancy, Healthy Baby Study. A manuscript was published at Statistics in Medicine (Neelon, et al., 2011).
We developed new ways of handling missing data in large epidemiological studies in which interaction effects are suspected. The main approach is to adapt regression trees to perform multiple imputation. This approach was used to handle the missing data in Project B. This methodology has the potential to be utilized in a wide range of settings, including outside of epidemiological contexts. An article describing this work has been published in the American Journal of Epidemiology (Burgette, et al., 2010).
The team also examined approaches to performing Bayesian analysis after multiple imputation is used for missing data. This work was motivated by the use of the tree methodology for multiple imputation, because we are estimating Bayesian models with the completed datasets. This research was published in The American Statistician (Zhou, et al., 2010).
Finally, the team developed an approach for assessing sensitivity to unmeasured confounding when using principal stratification. This work was motivated by the presence of several intermediate variables in the prospective study of Project B, e.g., hypertension as an intermediate variable for gestation age. At this point, this work is at a theoretical stage; we have not yet applied it on Project B data. A manuscript on the theory has been published in Statistics in Medicine (Schwartz, et al., 2012).
Statistical Methods Development for Genetics. We also developed statistical methods for the genetic data. The first statistical innovation involving the genetic data is the adverse sub-population regression (ASPR) for multi-variate 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. The method was evaluated with the Project B data and has been published in Statistics in Medicine (Zhu, et al., 2012).
The second innovation involving the genetic data was motivated by our analysis of the admixture data. The current genetic analysis tool that is most widely used (ANCESTRYMAP) is very limited in that it only allows consideration of qualitative, not quantitative, outcomes and does not allow for the incorporation of covariates. Thus, we have extended this method in our project (Zhu, et al., 2012).
One of the statistical innovations that we have been working on is the improvement of methodologies for admixture mapping. To that end, we developed a generalized admixture mapping (GLEAM) approach, a flexible and powerful regression method for both quantitative and qualitative traits, which is able to test for association between the trait and local ancestries in multiple loci simultaneously and adjust for covariates. The new method is based on the generalized linear model and utilizes a quadratic normal moment prior to incorporate admixture prior information. Through simulation, we demonstrated that GLEAM achieves lower type I error rate and higher power than existing methods both for qualitative traits and more significantly for quantitative traits (see Zhu, et al., 2013).
Journal Articles on this Report : 26 Displayed | Download in RIS Format
| Other subproject views: | All 51 publications | 26 publications in selected types | All 26 journal articles |
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| Other center views: | All 163 publications | 77 publications in selected types | All 76 journal articles |
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Burgette LF, Reiter JP. Multiple imputation for missing data via sequential regression trees. American Journal of Epidemiology 2010;172(9):1070-1076. |
R833293 (2008) R833293 (2009) R833293 (2010) R833293 (Final) R833293C002 (2009) R833293C002 (2010) R833293C002 (Final) |
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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) R833293 (2011) R833293 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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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) R833293 (2011) R833293 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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Burgette LF, Reiter JP. Modeling adverse birth outcomes via confirmatory factor quantile regression. Biometrics 2012;68(1):92-100. |
R833293 (2010) R833293 (2011) R833293 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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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) R833293C002 (2011) R833293C002 (Final) |
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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) R833293 (Final) R833293C002 (2011) R833293C002 (Final) |
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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) R833293 (Final) R833293C001 (2010) R833293C001 (2011) R833293C001 (Final) R833293C002 (2011) R833293C002 (Final) R833863 (2011) |
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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) R833293 (2012) R833293 (Final) R833293C001 (2011) R833293C001 (Final) R833293C002 (2011) R833293C002 (Final) R834799 (2014) R834799 (2016) R834799 (Final) R834799C002 (2014) R834799C003 (2013) R834799C003 (2014) |
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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) R833293C002 (2011) R833293C002 (Final) |
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Maxson P, Miranda ML. Pregnancy intention, demographic differences, and psychosocial health. Journal of Women's Health 2011;20(8):1215-1223. |
R833293 (2010) R833293 (2011) R833293 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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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) R833293 (2012) R833293 (Final) R833293C002 (2011) R833293C002 (Final) |
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Miranda ML, Edwards SE, Swamy GK, Paul CJ, Neelon B. Blood lead levels among pregnant women: historical versus contemporaneous exposures. International Journal of Environmental Research and Public Health 2010;7(4):1508-1519. |
R833293 (2008) R833293 (2009) R833293 (2010) R833293 (Final) R833293C002 (2009) R833293C002 (2010) R833293C002 (Final) |
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Miranda ML, Edwards S, Maxson PJ. Mercury levels in an urban pregnant population in Durham County, North Carolina. International Journal of Environmental Research in Public Health 2011;8(3):698-712. |
R833293 (2010) R833293 (Final) R833293C002 (2010) R833293C002 (Final) |
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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) R833293 (2012) R833293 (Final) R833293C001 (2011) R833293C001 (Final) R833293C002 (2011) R833293C002 (Final) R833293C003 (2011) R833293C003 (Final) |
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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) R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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Neelon B, Gelfand AE, Miranda ML. A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores. Journal of the Royal Statistical Societ--Series C (Applied Statistics) 2014;63(5):737-761. |
R833293 (Final) R833293C001 (Final) R833293C002 (Final) |
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Sanders A, Smeester L, Rojas D, DeBussycher T, Wu M, Wright F, Zhou Y-H, Laine J, Rager J, Swamy G, Ashley-Koch A, Miranda ML, Fry R. Cadmium exposure and the epigenome: exposure-associated patterns of DNA methylation in leukocytes from mother-baby pairs. Epigenetics 2014;9(2):212-221. |
R833293 (Final) R833293C002 (Final) |
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Schwartz SL, Gelfand AE, Miranda ML. Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models. Statistics in Medicine 2010;29(16):1710-1723. |
R833293 (2008) R833293 (2009) R833293 (2010) R833293 (Final) R833293C001 (2009) R833293C001 (2010) R833293C001 (Final) R833293C002 (Final) |
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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) R833293 (2011) R833293 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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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) R833293C002 (Final) |
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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) R833293 (2010) R833293 (2011) R833293 (Final) R833293C002 (2010) R833293C002 (2011) R833293C002 (Final) |
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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) R833293 (2011) R833293 (Final) R833293C001 (2010) R833293C001 (Final) R833293C002 (2011) R833293C002 (Final) |
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Zhou X, Reiter JP. A note on Bayesian inference after multiple imputation. The American Statistician 2010;64(2):159-163. |
R833293 (2008) R833293 (2009) R833293 (Final) R833293C002 (2009) R833293C002 (Final) |
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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) R833293 (2012) R833293 (Final) R833293C002 (2011) R833293C002 (Final) |
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Zhu B, Ashley-Koch AE, Dunson DB. Generalized admixture mapping for complex traits. G3--Genes, Genomes, Genetics 2013;3(7):1165-1175. |
R833293 (2012) R833293 (Final) R833293C002 (Final) |
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Miranda ML, Anthopolos R, Wolkin A, Stapleton HM. Associations of birth outcomes with maternal polybrominated diphenyl ethers and thyroid hormones during pregnancy. Environment International 2015;85:244-253. |
R833293 (Final) R833293C002 (Final) |
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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 polymorphismsProgress and Final Reports:
Original AbstractMain Center Abstract and Reports:
R833293 The Center for Study of Neurodevelopment and Improving Children's Health 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
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
51 publications for this subproject
26 journal articles for this subproject
Main Center: R833293
163 publications for this center
76 journal articles for this center
26 journal articles for this subproject
Main Center: R833293
163 publications for this center
76 journal articles for this center