Grantee Research Project Results
Final Report: Southern Center on Environmentally-Driven Disparities in Birth Outcomes
EPA Grant Number: R833293Center: The Center for Study of Neurodevelopment and Improving Children's Health
Center Director: Murphy, Susan K.
Title: Southern Center on Environmentally-Driven Disparities in Birth Outcomes
Investigators: Miranda , Marie Lynn , Ashley-Koch, Allison , Auten, Richard , Foster, W. Michael , Gelfand, Alan , Gibson-Davis, Christina , Goodall, Jonathan , James, Sherman , Reiter, Jerome , Swamy, Geeta , Williams, Redford , Keating, Martha H. , Maxson, Pamela
Institution: Duke University
EPA Project Officer: Callan, Richard
Project Period: May 1, 2007 through April 30, 2012 (Extended to April 30, 2014)
Project Amount: $7,735,620
RFA: Centers for Children’s Environmental Health and Disease Prevention Research (2005) RFA Text | Recipients Lists
Research Category: Children's Health , Human Health
Objective:
- To develop and operate an interdisciplinary children’s health research center with a focus on understanding how biological, physiological, environmental and social aspects of vulnerability contribute to health disparities;
- To enhance research in children’s health at Duke by promoting research interactions among programs in biomedicine, pediatric and obstetric care, environmental health, and the social sciences and establishing an infrastructure to support and extend interdisciplinary research;
- To develop new methodologies for incorporating innovative statistical analysis into children’s environmental health research and policy practice, with a particular emphasis on spatial, genetic and proteomic analysis;
- To serve as a technical and educational resource to the local community, region, the nation, and to international agencies in the area of children’s health and health disparities; and
- To translate the results of the Center into direct interventions in clinical care and practice.
The SCEDDBO was governed through an Administrative Core that includes an Executive Committee composed of the Director, the two Co-Directors, and the Project Manager; an Internal Steering Committee composed of members of the Executive Committee and the Directors of the Research Projects and the Facility and Community Outreach Cores, as well as a community member and the Director of the Durham County Health Department; and an External Advisory Committee composed of senior environmental health scientists, as well as community representatives, with expertise relevant to SCEDDBO, who provided informal consultation, as well as annual formal evaluation of Center research and outreach activities.
The specific aims of the Administrative Core are to:
a. Provide scientific direction and leadership;
b. Coordinate and foster interactions among research project and facility core investigators;
c. Provide administrative services for the Center;
d. Direct the Young Investigators program; and
e. Represent Duke’s SCEDDBO to the university, the community, the NIH, other Children’s Environmental Health Centers across the United States, and the policy and scientific community interested in children's environmental health more broadly.
In all activities, SCEDDBO emphasized the importance of diversity. The decision to focus on health disparities, the gender and racial diversity of Center leadership, the incorporation of natural, social and biomedical scientists, a commitment to community-based participatory research, and efforts to promote the careers of promising new investigators were all indicative of the importance that we place on fostering environments where all people can prosper.- Spatially link detailed birth record, fetal death certificate, socioeconomic, environmental, tax assessor, community-based and clinical obstetric data at highly resolved scales for the State of North Carolina from 1990 to 2003;
- Refine the concept of fetal growth restriction by (a) developing a joint distribution for birth weight and gestation using bivariate modeling for live births and fetal deaths—both separately and jointly, and (b) defining it in terms of fetal and infant mortality, rather than percentile cut points; and
- Determine whether and to what extent differential exposures to both environmental and social stressors help explain health disparities in fetal growth restriction among (a) African-American women compared to non-Hispanic white and Hispanic women, (b) Older African-American women compared to younger African-American women, (c) Hispanic women compared to non-Hispanic white and African-American women, and (d) foreign-born Hispanic women compared to U.S.-born Hispanic women.
- 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 subsamples and compare these clusters across racial groups.
- To determine whether maternal exposure to airborne particulates (PM) and/or ozone (1st hit) restricts fetal growth and/or postnatal growth, and impairs lung development/function in newborn mice;
- To determine whether PM and/or ozone exposure "reprograms" maternal inflammatory responses;
- To determine whether postnatal (2nd hit) ozone exposure further impairs postnatal somatic and lung development/function following maternal PM and/or ozone exposures;
- To determine whether genetic or developmental susceptibility to airway hyperreactivity exacerbates maternal and/or postnatal exposure effects on postnatal somatic and lung development/function.
- Support the community-based neighborhood assessment being undertaken as part of Projects A and B;
- Partner with nursing programs at Duke-affiliated hospitals to develop and present curricula to nursing students on environmental exposures and maternal and child health outcomes;
- Develop culturally-appropriate advisory materials on environmental contaminants for low-income expectant or nursing mothers with low English proficiency;
- Deliver training to local health department personnel focused on environmental factors related to maternal health and pregnancy outcomes;
- Participate in regional, state and federal policy dialogues to provide decision makers with policy-relevant, science-based information concerning environmental exposures and health disparities related to maternal and child health and well-being; and
- Increase awareness of maternal health and health disparities by facilitating bidirectional exchanges between Center investigators, community members, public health advocacy groups, and policy makers.
- Providing support for the development of environmental and social data layers needed to implement data analyses required for the research projects and the COTC;
- Providing statistical analysis, advice and consulting on the broad range of statistical issues that arise in conjunction with the research projects, with a particular emphasis on data reduction methods and modeling spatial and spatio-temporal data within a Bayesian framework; and
- Providing analysis for the unique needs of genetic data arising from the clinical and animal studies of the Center.
Summary/Accomplishments (Outputs/Outcomes):
Central to SCEDDBO’s mission to determine how environmental, social, and host factors (see Figure 1) jointly contribute to health disparities was the development of an underlying, multi-sourced, detailed data architecture. During the project period, we constructed a large-scale, spatially referenced data warehouse, linking birth record data to social and environmental exposures data. Among women in our sample population, exposure to air pollutants, including PM2.5 and PM10, is associated with poor pregnancy outcomes (Chang et al., 2012; Gray et al., 2010;Vinikoor-Imler et al., 2012). We have helped define meaningful exposure metrics for air pollution and how to incorporate uncertainty in personal exposure estimates derived from monitoring station measurements (Gray et al., 2011). To do so, we constructed a stochastic simulator to directly make predictions of individual level exposure that we related to birth weight (Berrocal et al., 2011). Additional work on air pollution identified windows of vulnerability for pregnant women (Chang et al., 2012; Gray et al., 2010). We re-conceptualized the analysis for binary pregnancy outcomes (e.g., preterm birth) as a time-to-event analysis, enabling us to examine air pollution in a time-varying setting, where exposure is conditional on the length of the entire pregnancy or the third trimester (Chang et al., 2010). To achieve improved estimates of air pollution exposure, we constructed spatial downscalers, fusing monitoring station data with computer model output to better assess environmental exposure at point level spatial resolution (Berrocal et al., 2010a; Berrocal et al., 2010b; Berrocal et al., 2011).
Figure 1. M.L. Miranda, P. Maxon, S. Edwards. 2009. "Environmental
contributors to disparities in pregnancy outcomes." Epidemiologic
Reviews, 31:67-83. PMID: 19846592
Compared to non-Hispanic whites (NHW), non-Hispanic blacks (NHB) are more likely to live in neighborhoods characterized by poverty, elevated levels of environmental contaminants, and poor quality housing (Miranda et al., 2009). In related work on racial residential segregation (which is associated with higher environmental exposures), we observed a detrimental association between a spatial measure of neighborhood level racial residential segregation and pregnancy outcomes (Anthopolos et al., 2011). Racial residential segregation may impact health through the built environment. Using the Community Assessment Project data, we found that higher levels of housing damage, property disorder, tenure, and vacancy are associated with increased likelihood of preterm birth and low birth weight (Miranda, Messer, & Kroeger, 2012).
Statistical methods development has focused on outcome-exposure relationships. We emphasized joint modeling of related outcomes that can borrow strength from each other, such as birthweight and gestational age, which often helps with causal inference interpretation and illuminates subpopulations with differential risk for poor outcomes (Schwartz et al., 2010. See Figure 4). With binary outcomes (e.g., low birth weight and preterm birth) and normal outcomes, we have introduced additional borrowing of information with spatially correlated random effects (Neelon et al., 2012). Given the critical nature of health outcomes defined by distribution tails, such as low birth weight and preterm birth, in addition to the potential for differential covariate effects over the response distribution, we developed a new method to apply quantile regression in a spatial context (i.e., relaxing the assumption that observations in adjacent neighborhoods are independent). Applying this method, we observed differential effects of standard risk factors of birth weight, such as infant sex and birth order, along the birth weight response distribution.
FIgure 4. S. Schwartz, A. Gelfand, and M.L. Miranda. 2010. "Joint Baysian analysis of birthweight and censored gestational age using finite mixture
models." Statistics in Madicine 20; 20(16): 1710-1723.
We recruited and retained 1,800+ women from Duke University Medical Center and Lincoln Community Health Center for our Healthy Pregnancy, Healthy Baby Study. Data on maternal and neonatal medical indicators, psychosocial health, and environmental exposures were obtained. We genotyped the cohort for 412 Single Nucleotide Polymorphisms (SNPs) in 52 genes related to human environmental contaminant clearance, infection and inflammation, maternal stress response, and other potential drivers of health disparities. To better identify subpopulations among NHB women in our sample, we generated the Illumina African American Admixture Chip, based on 1,509 selected SNPs with disparate frequencies in the Yoruban (African) and European (Caucasian) HapMap samples. As an example, we found that race-specific allelic frequencies in the vitamin D receptor (VDR) gene suggest its potential as a gene involved in health disparities (Swamy et al., 2011).
We found that women who live in neighborhoods with higher levels of housing damage, vacancy, and renter-occupied units are more likely to have poor scores on measures of psychosocial health, compared to women with residence in neighborhoods with lower levels of these attributes (Messer et al., 2012). Linking individual psychosocial health to the built environment, we then sought to understand the pathway between psychosocial health and pregnancy. Poor psychosocial health is associated with the likelihood of engaging in health behaviors known to be harmful to pregnancy, like smoking (Maxson & Miranda, 2011; Maxson et al., 2012; Miranda, Edwards, & Myers, 2011; Zhu et al., 2012). Among women for whom we measured levels of polybrominated diphenyl ethers (PBDE) flame retardants, our data suggest that PBDEs may be affecting thyroid regulation throughout pregnancy (Stapleton et al., 2011). In companion work, we observed that maternal behaviors and the presence of electronics were associated with higher levels of PBDEs in maternal cord blood samples (Buttke et al., 2012).
Additionally, we have characterized mercury and lead levels among women in our sample: socioeconomic status is positively related to mercury levels controlling for fish consumption, and lead levels were more likely to stem from remobilization from historical rather than current exposures (Miranda, Edwards, & Maxson, 2011; Miranda, Edwards, Swamy, et al., 2010).
The Healthy Pregnancy, Healthy Baby Study has motivated innovative methods development in the areas of handling missing data and developing differential risk profiles. While the cohort study had a high retention rate (92%), scattered missingness across the many collected variables resulted in a limited number of complete cases. We developed a non-parametric approach for multiple imputation via chained equations that uses sequential regression trees as the conditional models – an approach that we demonstrate can result in more plausible imputations and hence more reliable inferences (Burgette & Reiter, 2010). A second missing data problem that we encountered stemmed from a change in the laboratories used to measure environmental contaminants in maternal blood (Burgette & Reiter, 2012b). To overcome the statistical challenges associated with not having any measurements on both scales, we developed a multiple imputation approach based on rank preservation.
The amount of detailed information in the Healthy Pregnancy, Healthy Baby Study led us to concentrate on ways to distill variables into meaningful summaries in order to construct risk profiles. For example, through Bayesian growth mixture modeling, we differentiated classes of pregnant women according to their mean arterial blood pressure curves and joint probabilities of adverse birth outcomes (Neelon et al., 2011). Such classes may be more clinically relevant than looking at individual risk factors one at a time. With a similar goal but in a quantile regression setting, we developed ways to reduce high dimensional predictor spaces and identify latent factors underlying clusters of observed variables (Burgette et al., 2011; Burgette & Reiter, 2012a; Zhu et al., 2012).
We used animal models to more precisely assess the contributions of joint and sequential perinatal and postnatal environmental stressors on health outcomes. We exposed pregnant mice to a standardized industrial PM by tracheal instillation throughout pregnancy, followed by intermittent ozone exposure to their offspring. Maternal PM treatment induced inflammatory responses in fetal compartments and augmented the effects of ozone on airway hyper-reactivity, a model system for human asthma (Auten et al., 2009). We chose ozone as a criterion air pollutant to model human asthma since childhood exposure has been strongly associated with the development of asthma, and for the strong potential of early life ozone exposure to have life-long health effects (Auten & Foster, 2011). In order to determine if traffic-related air pollutant exposure during pregnancy, already associated with the development of asthma and adverse pregnancy outcomes, could have similar "priming" effects in offspring exposed to ozone, we exposed pregnant mice to inhaled diesel exhaust or to instilled diesel particles. Exposure to diesel via the ambient, physiological route (and by instillation) also caused fetal inflammatory responses (↑fetal lung and placenta pro-inflammatory cytokines) and worsened the effects of ozone on postnatal airway hyperreactivity. Notably, the combined pre-natal exposure of maternal diesel inhalation and postnatal ozone exposure of offspring impaired lung development, while single exposures did not. Furthermore, the effects on airway hyperreactivity persisted to adulthood after ceasing ozone exposure for four weeks, a completely novel finding, consistent with our hypothesized schema of synergies between exposures across the life span (Auten et al., 2012).
Our prenatal air pollution exposure models provoked fetal inflammation (lung, placenta), known to be linked with other adverse health outcomes such as impaired neurological development, so we began a collaboration with Staci Bilbo, (and eventually made her Co-PI on Project C) to examine long-term effects of combined perinatal pollutant exposure and other stressors known to be prevalent in impoverished communities (maternal stress, obesity, exposure to indoor antigens). We secured additional support from the Duke Institute for Brain Sciences to support these preliminary studies. We have since determined that pre-natal diesel exposure in mice during pregnancy, when combined with a high-fat diet provided to adult offspring, produces activated brain microglia, increases anxiety behavior, and impairs cognition (Bolton et al., 2012).
The synergy among the research projects was facilitated by the GIS and Statistical Analysis (GISSA) Core. The GISSA Core allowed for data analysis of the very large amount of data through the use of high-end GIS applications in combination with Bayesian spatial hierarchical modeling and other advanced spatial statistical approaches, thus permitting multi-level analyses. Research Projects A and B both applied a Bayesian spatial hierarchical modeling approach to capture uncertainties in pregnancy outcomes and to elucidate the contributions of economic, sociocultural, and environmental stressors on health disparities in pregnancy outcomes. State-of-the-art GIS methods allowed for sophisticated spatial statistical analyses at highly resolved spatial scales.
The GISSA Core also provided the analysis of the biological response and genetic data generated in Research Projects B and C. The rich source of social, environmental, and host data in Project B, coupled with sophisticated statistical genetic approaches for identifying gene-gene and gene-environment interactions, provided the opportunity to make important discoveries of how these higher order interactions may be working together to promote or prevent adverse birth outcomes. By serving as a central clearinghouse for statistical analysis, the GISSA Core tracked outcomes in each project and used these discoveries to guide the analysis in each of the other projects.
The COTC provided key support by developing community partnerships and leading the community outreach and translation effort. COTC materials have been disseminated widely throughout the community, and the COTC has met often with community groups and local agencies. In collaboration with the nursing programs at Duke and UNC Schools of Nursing, COTC designed and regularly delivered a comprehensive curriculum to nursing students on environmental exposures and maternal and child health outcomes. The COTC also developed a partnership with nutritionists in the NC Supplemental Nutrition Program for Women, Infants, and Children (WIC), developing advisory materials on mercury fish consumption for Latino families. In addition, the COTC partnered with the GISSA Core to offer no-cost GIS training to public health personnel. COTC also collaborated with a variety of regional, state, and federal advisory groups, SCEDDBO Director Marie Lynn Miranda served on the EPA's Children's Health Protections Advisory Committee (CHPAC).
Partnerships
A rich set of active relationships among community, campus, and organizational partners formed the basis for our center. First, we emphasized the connections among Duke, UNC, and U-M. Second, community partners and SCEDDBO investigators collaborated to improve environmental health in low-income areas throughout Durham County and across NC. These partnerships were and continue to be based on mutual interest in the effects of the environment on young children and pregnant women, as well as how environmental and social stressors interact to affect maternal and child health.
As a concrete example of our partnership approach, Durham Congregations, Associations, and Neighborhoods (Durham CAN) conducted a neighborhood audit that consisted of having volunteers take a block by block inventory of neighborhood problems, including broken or missing sidewalks, missing streetlights, roads in disrepair, litter, sewage and drainage problems, abandoned homes, and vacant/ overgrown lots. GISSA Core personnel converted the neighborhood audits into map-based visuals. Durham CAN used these maps in presentations to community groups, the Durham City Council, the Durham County Commissioners, and local government offices to negotiate improved conditions in target neighborhoods. In mapping the neighborhood audits for Durham CAN, we noted some clear problems with inter-coder reliability when comparing the audits across large sections of the city. We subsequently discussed joint work to improve the neighborhood audit. This collaborative effort formed the basis for the Community Assessment Project (see COTC).
During the project period, community partners and SCEDDBO investigators had multiple opportunities to explore mutual interests in designing projects that generate results that can be applied directly in the community. Our collective community-based experience convinced us that health disparities, particularly as they affect children, still represent the most important policy challenge in low income and minority communities. As we have jointly witnessed the disproportionate exposures to environmental contaminants, as well as the poor quality of the built environment and associated social stressors, we became convinced that real change in our communities requires an integrated understanding of environmental, social, and host factors.
Website. The Administrative Core provided material on SCEDDBO to the EPA for uploading to the EPA children’s centers website. In addition, we updated our SCEDDBO website, linked off the website for the Children’s Environmental Health Initiative (cehi.snre.umich.edu). We used our secure internal website that allowed for discussion boards, email communication, and document storage associated with the work of each of the SCEDDBO components.
Dissemination. SCEDDBO work was disseminated in a multitude of ways over the seven years of the project. Highlights are presented here; each project summary has a relevant list of publications and presentations.
Dr. Miranda brought her perspective on geospatial analysis and its usefulness in assessing and analyzing public health issues via her participation in the US Centers for Disease Control and Prevention’s Geospatial Science and Healthy Communities Expert Panel, held in Atlanta, GA, in May 2008.
SCEDDBO offered a well-attended mini-symposium at the EPA in the Research Triangle Park in January 2009, designed to present EPA employees with a synopsis of the work that SCEDDBO does, emphasizing the environmental contributors to disparities in birth outcomes. Dr. Miranda represented the scientific mission of SCEDDBO as part of the USEPA’s BOSC review of the agency’s human health research program in January 2009. Specifically, Dr. Miranda co-authored and presented with Ms. Devon Payne Sturgess (USEPA) a poster regarding Long Term Goal 3 entitled “Differential Vulnerability to Environmental Contaminants and Adverse Outcomes during Early Childhood.” This poster was well-received and SCEDDBO was commented on very favorably by the BOSC review panel in its written report.
Dr. Miranda represented the scientific mission of SCEDDBO as part of the GEI Exposure Biology Program in August, 2009. Specifically, Dr. Miranda presented a talk entitled “Combining Population Clinical, and Animal Models to Assess Exposure and Effects.” Dr. Miranda also presented a talk at the USEPA’s “Strengthening Environmental Justice Research and Decision-Making” conference. This talk was entitled, “Using GIS to Support EJ Results” and represented the broad work of the Children’s Environmental Health Initiative, including work done under the auspices of SCEDDBO.
In addition, Dr. Miranda was the keynote speaker at our Nurses Conference, Environmental Considerations in Nursing Practice in May, 2010. She also spoke at the Environmental Health Summit in September, 2010. SCEDDBO also co-sponsored a symposium “The Social Context of Environmental Exposures in Children” in March, 2011. Speakers from Harvard, the United States Environmental Protection Agency, the National Institute of Child Health and Human Development, and Duke University discussed the role of the social context of environmental exposures in children. The symposium was well attended and garnered much positive feedback.
In 2012, Dr. Miranda gave the plenary address at ISEE in Columbia, South Carolina. Her talk, “Of Mice, Maps, and Moms: Air quality impacts on human health,” discussed SCEDDBO’s geospatial work on air pollution and its effects on pregnancy outcomes. In July 2013, she presented the keynote address, “It takes a village: Integrated methods for addressing environmental health disparities,” at the NIEHS sponsored Environmental Health Disparities and Environmental Justice conference in RTP, North Carolina.
Identification of training opportunities. The Administrative Core worked with all of the other SCEDDBO components to identify key training opportunities for investigators and other research staff. Through this effort, we developed greater expertise in remotely sensed data, air pollution modeling, centering models of patient care, spatial statistics, and information science. These opportunities included both intensive short course and semester long coursework for several research staff, as well as travel to professional meetings for the graduate students and postdoctoral associates supported on the SCEDDBO grant. In addition, Dr. Alan Gelfand, Director of the GISSA Core, delivered a 2-day intensive short course on spatial statistics that was widely attended by SCEDDBO investigators and research staff. We also offered training workshops through our Community Outreach and Translation Core, with administrative support provided through the Administrative Core.
New Collaborations. As part of our mission to both support the work of young investigators and advance the research mission of SCEDDBO, we began new collaborations with Dr. Staci Bilbo, Assistant Professor, Department of Psychology and Neuroscience, Duke University and Dr. Rebecca Fry, Associate Professor, Gillings Global School of Public Health, UNC. Our work with Dr. Bilbo focuses on new mouse models to explore the joint impact of environmental and social stressors on birth and developmental outcomes. Our work with Dr. Fry explores gene expression and epigenetic changes associated with in utero metals exposures, with a particular emphasis on cadmium. In addition, we established a CDC-funded collaboration with Dr. Heather Stapleton, Associate Professor, Nicholas School of the Environment, Duke University. This study leveraged our ongoing clinical obstetrics project to assess in utero exposures to brominated flame retardants, as well as the relationship between brominated flame retardant body burden and maternal thyroid function. Multiple papers were published on this collective work (Bolton et al., 2013; Edwards et al., in press; Stapleton et al., 2011; Sanders et al., 2013; Buttke et al., 2013).
National Service. Duke hosted the Children’s Environmental Health Centers’ monthly conference calls for several years, 2007-2013. SCEDDBO investigators also helped organize the October 2010 and 2013 Children’s Centers conferences. In addition, Dr. Miranda served as a standing member of the Children’s Health Protection Advisory Committee. Dr. Miranda also served as a chartered member of the NIH’s Infectious Diseases, Reproductive Health, Asthma and Pulmonary Conditions (IRAP) Study Section. Multiple SCEDDBO investigators helped to review proposals for federal funding agencies, as well as review manuscripts for peer-reviewed journals.Project A (C001): Mapping Disparities in Birth Outcomes
Environmental Research 126: 152-158. PMID: 23850144.
Figure 3. R. Anthopolos, S.A. James, A.E. Gelfand, and M.L. Miranda. 2011. "A spacial measure of
neighborhood-level racial isolation applied to low birthweight, preterm birth, and birthweight in North Carolina."
Spacial and Spacio Temporal Epidemiolgy 2(4): 235-246. PMID: 22748223.
Figure 4. S. Schwartz, A. Gelfand, and M.L. Miranda. 2010. "Joint Bayesian analysis of birthweight and
censored gestational age using finite mixture models." Statistics in Medicine 20; 20(16): 1470 - 1723.
Figure 5. E. Tassone, M.L. Miranda, and A. Gelfand. 2010. "Disaggreagted spacial modeling
for areal unit catagorical data." Journal of the Royal Statistical Society: Series C (Applied Statistics)
59, Part, pp. 175-190. PMID: PMC2999915.
Figure 6. Spacial layout of racial isolation of blacks and poor quality built environment, census
block level, Community Assessment Project area, Durham, North Carolina.
- 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 secondhand smoke, and drinking water source.
- Maternal and neonatal medical record abstraction: detailed prepregnancy 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 are currently being stored for future genetic analysis and evaluation of activity at the maternal-fetal interface.
Figure 8. Depiction of Tacle Box Sticker
Figure 7. Community Assessment Project Areas
Journal Articles: 76 Displayed | Download in RIS Format
Other center views: | All 163 publications | 77 publications in selected types | All 76 journal articles |
---|
Type | Citation | ||
---|---|---|---|
|
Anthopolos R, James SA, Gelfand AE, Miranda ML. A spatial measure of neighborhood level racial isolation applied to low birthweight, preterm birth, and birthweight in North Carolina. Spatial and Spatio-temporal Epidemiology 2011;2(4):235-246. |
R833293 (2009) R833293 (2010) R833293 (2011) R833293 (Final) R833293C001 (2010) R833293C001 (2011) R833293C001 (Final) |
Exit |
|
Anthopolos R, Edwards SE, Miranda ML. Effects of maternal prenatal smoking and birth outcomes extending into the normal range on academic performance in fourth grade in North Carolina, USA. Paediatric and Perinatal Epidemiology 2013;27(6):564-574. |
R833293 (2012) R833293 (Final) R833293C001 (Final) |
Exit Exit |
|
Anthopolos R, Kaufman JS, Messer LC, Miranda ML. Racial residential segregation and preterm birth: built environment as a mediator. Epidemiology 2014;25(3):397-405. |
R833293 (Final) R833293C001 (Final) |
Exit Exit |
|
Auten RL, Potts EN, Mason SN, Fischer B, Huang Y, Foster WM. Maternal exposure to particulate matter increases postnatal ozone-induced airway hyperreactivity in juvenile mice. American Journal of Respiratory and Critical Care Medicine 2009;180(12):1218-1226. |
R833293 (Final) |
Exit Exit Exit |
|
Auten RL, Foster WM. Biochemical effects of ozone on asthma during postnatal development. Biochimica et Biophysica Acta 2011;1810(11):1114-1119. |
R833293 (2009) R833293 (2010) R833293 (Final) R833293C003 (2010) R833293C003 (Final) |
Exit |
|
Berrocal VJ, Gelfand AE, Holland DM. A bivariate space-time downscaler under space and time misalignment. Annals of Applied Statistics 2010;4(4):1942-1975. |
R833293 (2009) R833293 (Final) R833293C001 (Final) |
Exit Exit Exit |
|
Berrocal VJ, Gelfand AE, Holland DM. A spatio-temporal downscaler for output from numerical models. Journal of Agricultural, Biological, and Environmental Statistics 2010;15(2):176-197. |
R833293 (2009) R833293 (Final) R833293C001 (2009) R833293C001 (Final) |
Exit |
|
Berrocal VJ, Gelfand AE, Holland DM, Burke J, Miranda ML. On the use of a PM2.5 exposure simulator to explain birthweight. Environmetrics 2011;22(4):553-571. |
R833293 (2009) R833293 (2010) R833293 (2011) R833293 (Final) R833293C001 (2010) R833293C001 (2011) R833293C001 (Final) |
Exit |
|
Berrocal VJ, Gelfand AE, Holland DM. Space-time data fusion under error in computer model output: an application to modeling air quality. Biometrics 2012;68(3):837-848. |
R833293 (2011) R833293 (2012) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit Exit |
|
Berrocal VJ, Miranda ML, Gelfand AE, Bhattacharya S. Synthesizing categorical datasets to enhance inference. Statistical Methodology 2013;15:25-45. |
R833293 (2007) R833293 (2012) R833293 (Final) R833293C001 (Final) |
Exit Exit |
|
Block ML, Elder A, Auten RL, Bilbo SD, Chen H, Chen J-C, Cory-Slechta DA, Costa D, Diaz-Sanchez D, Dorman DC, Gold DR, Gray K, Jeng HA, Kaufman JD, Kleinman MT, Kirshner A, Lawler C, Miller DS, Nadadur SS, Ritz B, Semmens EO, Tonelli LH, Veronesi B, Wright RO, Wright RJ. The outdoor air pollution and brain health workshop. NeuroToxicology 2012;33(5):972-984. |
R833293 (2011) R833293 (2012) R833293 (Final) R833293C003 (2011) R833293C003 (Final) |
Exit Exit Exit |
|
Bolton JL, Smith SH, Huff NC, Gilmour MI, Foster WM, Auten RL, Bilbo SD. Prenatal air pollution exposure induces neuroinflammation and predisposes offspring to weight gain in adulthood in a sex-specific manner. FASEB Journal 2012;26(11):4743-4754. |
R833293 (2011) R833293 (Final) R833293C003 (2011) R833293C003 (Final) |
Exit Exit Exit |
|
Bolton JL, Huff NC, Smith SH, Mason SN, Foster WM, Auten RL, Bilbo SD. Maternal stress and effects of prenatal air pollution on offspring mental health outcomes in mice. Environmental Health Perspectives 2013;121(9):1075-1082. |
R833293 (2012) R833293 (Final) R833293C003 (Final) |
|
|
Bolton J, Auten R, Bilbo S. Prenatal air pollution exposure induces sexually dimorphic fetal programming of metabolic and neuroinflammatory outcomes in adult offspring. BRAIN BEHAVIOR AND IMMUNITY 2014;37:30-44. |
R833293 (Final) |
Exit Exit |
|
Brown JS, Graham JA, Chen LC, Postlethwait EM, Ghio AJ, Foster WM, Gordon T. Panel discussion review: session four--assessing biological plausibility of epidemiological findings in air pollution research. Journal of Exposure Science and Environmental Epidemiology 2007;17(Suppl 2):S97-S105. |
R833293 (2007) R833293 (2008) R833293 (Final) R833293C003 (Final) |
Exit Exit |
|
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) |
Exit Exit Exit |
|
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) |
Exit Exit |
|
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) |
Exit Exit Exit |
|
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) |
Exit Exit Exit |
|
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) |
Exit |
|
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) |
Exit Exit Exit |
|
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) |
Exit Exit Exit |
|
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) |
Exit Exit |
|
Dadabhoy FZ, Maxson PJ, Huff N, Auten RL. Perinatal exposure to air pollutants had adverse effects on behavioral outcomes in mice. International Journal on Disability and Human Development 2012;11(4):359-368. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Edwards SE, Strauss B, Miranda ML. Geocoding large population-level administrative datasets at highly resolved spatial scales. Transactions in GIS 2014;18(4):586-603. |
R833293 (Final) R833293C001 (Final) |
Exit |
|
Gray SC, Edwards SE, Miranda ML. Assessing exposure metrics for PM and birth weight models. Journal of Exposure Science and Environmental Epidemiology 2010;20(5):469-477. |
R833293 (2008) R833293 (2009) R833293 (2010) R833293 (Final) R833293C001 (2009) R833293C001 (2010) R833293C001 (Final) |
Exit |
|
Gray SC, Gelfand AE, Miranda ML. Hierarchical spatial modeling of uncertainty in air pollution and birth weight study. Statistics in Medicine 2011;30(17):2187-2198. |
R833293 (2010) R833293 (2011) R833293 (Final) R833293C001 (2010) R833293C001 (2011) R833293C001 (Final) |
Exit |
|
Gray SC, Edwards SE, Miranda ML. Race, socioeconomic status, and air pollution exposure in North Carolina. Environmental Research 2013;126:152-158. |
R833293 (2012) R833293 (Final) R833293C001 (Final) |
Exit Exit Exit |
|
Gray SC, Edwards SE, Schultz BD, Miranda ML. Assessing the impact of race, social factors and air pollution on birth outcomes: a population-based study. Environmental Health 2014;13(1):4. |
R833293 (2012) |
Exit Exit Exit |
|
Gregory SG, Anthopolos R, Osgood CE, Grotegut CA, Miranda ML. Association of autism with induced or augmented childbirth in North Carolina Birth Record (1990-1998) and Education Research (1997-2007) databases. JAMA Pediatrics 2013;167(10):959-966. |
R833293 (2012) R833293 (Final) R833293C001 (Final) |
Exit Exit Exit |
|
Gruber A, Maxson P. Disparities in psychosocial health and the built environment during pregnancy. International Journal on Disability and Human Development 2012;11(4):377-385. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Heaton MJ, Gray SC, Gelfand AE. Process modeling for contingency tables with ordered categories. Statistical Modelling 2012;12(3):211-228. |
R833293 (Final) R833293C001 (Final) |
Exit |
|
Henderson K, Maxson P. Obesity intervention strategies and the built environment in Durham, North Carolina. International Journal of Child and Adolescent Health 2009;2(3):Article 8. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Henry H, Anthopolos R, Maxson P. Traffic-related air pollution and pediatric asthma in Durham County, North Carolina. International Journal on Disability and Human Development 2013;12(4):467-471. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Kim JY, Burnett RT, Neas L, Thurston GD, Schwartz J, Tolbert PE, Brunekreef B, Goldberg MS, Romieu I. Panel discussion review: session two--interpretation of observed associations between multiple ambient air pollutants and health effects in epidemiologic analyses. Journal of Exposure Science and Environmental Epidemiology 2007;17(Suppl 2):S83-S89. |
R833293 (2008) R829213 (Final) |
Exit Exit |
|
Koehrn KM, Keating MH. The regulation of agricultural pesticides in North Carolina: implications for migrant farm workers and their families. International Journal of Child and Adolescent Health 2009;2(3):Article 4. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Kroeger GL, Messer L, Edwards SE, Miranda ML. A novel tool for assessing and summarizing the built environment. International Journal of Health Geographics 2012;11:46 (13 pp.). |
R833293 (Final) R833293C004 (Final) |
Exit Exit Exit |
|
Lum K, Gelfand AE. Spatial quantile multiple regression using the asymmetric Laplace process. Bayesian Analysis 2012;7(2):235-258. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit Exit |
|
Martz M, Anthopolos R, Geller M, Maxson P. Pediatric obesity and food access in Durham, North Carolina. International Journal of Child Health and Human Development 2014;7(3). |
R833293 (Final) R833293C004 (Final) |
Exit Exit |
|
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) |
Exit |
|
Maxson PJ. Together we can break the cycle. International Journal on Disability and Human Development 2012;11(4):307-314. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Maxson PJ, Edwards SE, Valentiner EM, Miranda ML. A multidimensional approach to characterizing psychosocial health during pregnancy. Maternal and Child Health Journal 2016;20(6):1103-1113. |
R833293 (Final) |
Exit Exit |
|
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) |
Exit |
|
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) |
Exit |
|
Miranda ML, Keating MH, Edwards SE. Environmental justice implications of reduced reporting requirements for the Toxics Release Inventory Burden Reduction Rule. Environmental Science & Technology 2008;42(15):5407-5414. |
R833293 (Final) R833293C004 (Final) |
Exit Exit Exit |
|
Miranda ML, Maxson P, Edwards S. Environmental contributions to disparities in pregnancy outcomes. Epidemiologic Reviews 2009;31(1):67-83. |
R833293 (2008) R833293 (Final) R833293C001 (Final) |
Exit Exit Exit |
|
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) |
Exit Exit |
|
Miranda ML, Swamy GK, Edwards S, Maxson P, Gelfand A, James S. Disparities in maternal hypertension and pregnancy outcomes: evidence from North Carolina, 1994-2003. Public Health Reports 2010;125(4):579-587. |
R833293 (2008) R833293 (2009) R833293 (2010) R833293 (Final) R833293C001 (2009) R833293C001 (2010) R833293C001 (Final) |
Exit Exit |
|
Miranda ML, Maxson P, Kim D. Early childhood lead exposure and exceptionality designations for students. International Journal of Child Health and Human Development 2010;3(1):77-84. |
R833293 (2008) R833293 (Final) R833293C001 (2009) R833293C001 (Final) |
Exit |
|
Miranda ML, Edwards SE, Keating MH, Paul CJ. Making the environmental justice grade: the relative burden of air pollution exposure in the United States. International Journal of Environmental Research and Public Health 2011;8(6):1755-1771. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit Exit Exit |
|
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) |
Exit Exit |
|
Miranda ML, Edwards SE. Use of spatial analysis to support environmental health research and practice. North Carolina Medical Journal 2011;72(2):132-135. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit Exit |
|
Miranda ML, Edwards SE, Myers ER. Adverse birth outcomes among nulliparous vs. multiparous women. Public Health Reports 2011;126(6):797-805. |
R833293 (2010) R833293 (2011) R833293 (Final) R833293C001 (2010) R833293C001 (2011) R833293C001 (Final) |
Exit |
|
Miranda ML, Anthopolos R, Edwards SE. Seasonality of poor pregnancy outcomes in North Carolina. North Carolina Medical Journal 2011;72(6):447-453. |
R833293 (2010) R833293 (2011) R833293 (Final) R833293C001 (2010) R833293C001 (2011) R833293C001 (Final) |
Exit Exit Exit |
|
Miranda ML, Anthopolos R, Hastings D. A geospatial analysis of the effects of aviation gasoline on childhood blood lead levels. Environmental Health Perspectives 2011;119(10):1513-1516. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
|
|
Miranda ML, Edwards SE, Anthopolos R, Dolinsky DH, Kemper AR. The built environment and childhood obesity in Durham, North Carolina. Clinical Pediatrics 2012;51(8):750-758. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit |
|
Miranda ML, Messer LC, Kroeger GL. Associations between the quality of the residential built environment and pregnancy outcomes among women in North Carolina. Environmental Health Perspectives 2012;120(3):471-477. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
|
|
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) |
Exit Exit |
|
Modlin E, Maxson P. Breaking the cycle of maternal depression: an initiative to improve children’s environmental health. International Journal of Child Health and Human Development 2010;3(4):405-411. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
Montagna S, Tokdar ST, Neelon B, Dunson DB. Bayesian latent factor regression for functional and longitudinal data. Biometrics 2012;68(4):1064-1073. |
R833293 (2011) R833293 (2012) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit Exit Exit |
|
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) |
Exit |
|
Neelon B, Anthopolos R, Miranda ML. A spatial bivariate probit model for correlated binary data with application to adverse birth outcomes. Statistical Methods in Medical Research 2014;23(2):119-133. |
R833293 (Final) R833293C001 (Final) |
Exit |
|
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) |
Exit Exit |
|
Ouyang R. The relationship between the built environment and birthweight. Reviews on Environmental Health 2011;26(3):181-186. |
R833293 (Final) R833293C004 (Final) |
Exit |
|
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) |
Exit Exit |
|
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) |
Exit Exit |
|
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) |
Exit |
|
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) |
|
|
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) |
Exit |
|
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) |
Exit |
|
Tassone EC, Miranda ML, Gelfand AE. Disaggregated spatial modelling for areal unit categorical data. Journal of the Royal Statistical Society--Series C (Applied Statistics) 2010;59(1):175-190. |
R833293 (2007) R833293 (2008) R833293 (2009) R833293 (Final) R833293C001 (2009) R833293C001 (Final) |
Exit Exit Exit |
|
Vinikoor-Imler LC, Gray SC, Edwards SE, Miranda ML. The effects of exposure to particulate matter and neighbourhood deprivation on gestational hypertension. Paediatric and Perinatal Epidemiology 2012;26(2):91-100. |
R833293 (2011) R833293 (Final) R833293C001 (2011) R833293C001 (Final) |
Exit Exit |
|
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) |
Exit Exit |
|
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) |
Exit Exit |
|
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) |
Exit Exit Exit |
|
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) |
Exit Exit Exit |
Supplemental Keywords:
Data fusion, meta analysis, disparities, spatial disaggregation, spatial interpolation, spatial modeling, racial residential segregation, built environment, birth outcomes, pregnancy, preterm birth, low birth weight, racial disparity, African American, environmental stressors, gene-environment interactions, psychosocial stressors, genes, single nucleotide polymorphisms, airway hyperreactivity, diesel exhaust particles, air pollution, lung function, epigenetic, innate immunity, Nqo1, neuroinflammation, maternal stress, risk communication, outreach, translation, participatory research, built environment, data fusion, meta analysis, disparities, spatial disaggregation, spatial interpolation, spatial modelingProgress and Final Reports:
Original Abstract 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
- 2012 Progress Report
- 2011 Progress Report
- 2010 Progress Report
- 2009 Progress Report
- 2008 Progress Report
- 2007 Progress Report
- Original Abstract
76 journal articles for this center