A Multidimensional Approach to Characterizing Psychosocial Health During Pregnancy.

Objectives Domains of psychosocial health have been separately connected to pregnancy outcomes. This study explores the relationship between five domains of psychosocial health and their joint association with prenatal health and pregnancy outcomes. Methods Women from a prospective cohort study in Durham, North Carolina were clustered based on measures of paternal support, perceived stress, social support, depression, and self-efficacy. Clusters were constructed using the K-means algorithm. We examined associations between psychosocial health and maternal health correlates, pregnancy intention, and pregnancy outcomes using Chi square tests and multivariable models. Results Three psychosocial health profiles were identified, with the first (Resilient; n = 509) characterized by low depression and perceived stress and high interpersonal support, paternal support, and self-efficacy. The second profile (Vulnerable; n = 278) was marked by high depression and perceived stress, and low interpersonal support, paternal support, and self-efficacy. The third profile (Moderate, n = 526) fell between the other profiles on all domains. Health correlates, pregnancy intention, and pregnancy outcomes varied significantly across profiles. Women with the vulnerable profile were more likely to have risky health correlates, have an unintended pregnancy, and deliver preterm. Women with the resilient profile had better birth outcomes and fewer deleterious health correlates, preconception and prenatally. Conclusions We posit that vulnerable psychosocial health, deleterious health correlates, and the stress which often accompanies pregnancy may interact to magnify risk during pregnancy. Identifying and intervening with women experiencing vulnerable psychosocial health may improve outcomes for women and their children.

Assessing the impact of race, social factors and air pollution on birth outcomes: a population-based study.

BACKGROUND: Both air pollution exposure and socioeconomic status (SES) are important indicators of children's health. Using highly resolved modeled predictive surfaces, we examine the joint effects of air pollution exposure and measures of SES in a population level analysis of pregnancy outcomes in North Carolina (NC). METHODS: Daily measurements of particulate matter <2.5 µm in aerodynamic diameter (PM2.5) and ozone (O3) were calculated through a spatial hierarchical Bayesian model which produces census-tract level point predictions. Using multilevel models and NC birth data from 2002-2006, we examine the association between pregnancy averaged PM2.5 and O3, individual and area-based SES indicators, and birth outcomes. RESULTS: Maternal race and education, and neighborhood household income were associated with adverse birth outcomes. Predicted concentrations of PM2.5 and O3 were also associated with an additional effect on reductions in birth weight and increased risks of being born low birth weight and small for gestational age. CONCLUSIONS: This paper builds on and complements previous work on the relationship between pregnancy outcomes and air pollution exposure by using 1) highly resolved air pollution exposure data; 2) a five-year population level sample of pregnancies; and 3) including personal and areal level measures of social determinants of pregnancy outcomes. Results show a stable and negative association between air pollution exposure and adverse birth outcomes. Additionally, the more socially disadvantaged populations are at a greater risk; controlling for both SES and environmental stressors provides a better understanding of the contributing factors to poor children's health outcomes.

Effects of maternal prenatal smoking and birth outcomes extending into the normal range on academic performance in fourth grade in North Carolina, USA.

BACKGROUND: Research has documented the adverse relationship of child cognitive development with maternal prenatal smoking and poor birth outcomes. The potential, however, for maternal prenatal smoking to modify the association between birth outcomes and cognitive development is unclear. METHODS: We linked statewide North Carolina birth data for non-Hispanic white and non-Hispanic black children to end-of-grade test scores in reading and mathematics at fourth grade (n = 65 677). We fit race-stratified multilevel models of test scores regressed on maternal smoking, birth outcomes (as measured by continuous and categorical gestational age and birthweight percentile for gestational age), and their interaction, controlling for maternal- and child-level socio-economic factors. RESULTS: Smoking was consistently associated with decrements in test scores, and better birth outcomes were associated with improvements in test scores, even in clinically normal ranges. Test scores increased quadratically with improving birth outcomes among smoking and non-smoking mothers. Among non-Hispanic white children, the magnitude of the association between gestational age and test scores was larger for children whose mothers smoked during pregnancy compared with the non-smoking group. However, among non-Hispanic black children, birth outcomes did not appear to interact with maternal smoking on test scores. CONCLUSIONS: Maternal prenatal smoking may interact with birth outcomes on reading and mathematics test scores, particularly among non-Hispanic white children. Improvements in birth outcomes, even within the clinically normal range, may be associated with improved academic performance. Pregnancy-related exposures and events exert a significant and long-term impact on cognitive development.

Race, socioeconomic status, and air pollution exposure in North Carolina.

BACKGROUND: Although studies suggest that exposure to pollutants is associated with race/ethnicity and socio-economic status (SES), many studies are limited to the geographic regions where monitoring stations are located. OBJECTIVES: This study uses modeled predictive surfaces to examine the relationship between air pollution exposure, race/ethnicity, and measures of SES across the entire State of North Carolina. METHODS: The daily predictions of particulate matter <2.5 µm in aerodynamic diameter (PM2.5) and ozone (O3) were determined using a spatial model that fused data from two sources: point air monitoring data and gridded numerical output. These daily predicted pollution levels for 2002 were linked with Census data. We examine the relationship between the census-tract level predicted concentration measures, SES, and racial composition. RESULTS: SES and race/ethnicity were related to predicted concentrations of both PM2.5 and O3 for census tracts in North Carolina. Lower SES and higher proportion minority population were associated with higher levels of PM2.5. An interquartile range (IQR) increase of median household income reduced the predicted average PM2.5 level by 0.10 µg/m3. The opposite relationship was true for O3. An IQR increase of median household income increased the predicted average O3 measure by 0.11 ppb. CONCLUSIONS: The analyses demonstrate that SES and race/ethnicity are related to predicted estimates of PM2.5 and O3 for census tracts in North Carolina. These findings offer a baseline for future exposure modeling work involving SES and air pollution for the entire state and not just among the populations residing near monitoring networks.

The effects of exposure to particulate matter and neighbourhood deprivation on gestational hypertension.

Gestational hypertension, pre-eclampsia and eclampsia are conditions that affect the health of both mothers and infants during and after pregnancy. Recent research indicates the importance of considering environmental, social and individual contributors to poor pregnancy outcomes. Our research examined particulate matter (PM) concentrations as one measure of environmental exposure and neighbourhood quality as one measure of the social environment. We used these measures, as well as maternal characteristics, to predict the risk of gestational hypertension (including pre-eclampsia and eclampsia). North Carolina Detailed Birth Record data for 2000-2003 were obtained and geocoded for all singleton births. Levels of PM(10) and PM(2.5) were determined using air quality data from the US Environmental Protection Agency. Information on a woman's residential neighbourhood was determined from 2000 Census data. Modified Poisson regression models clustered by tract were used to examine the associations between PM levels, neighbourhood deprivation and maternal characteristics with gestational hypertension. Analysis was restricted to women residing within 20 km of a PM monitor. Both PM(10) and PM(2.5) were associated with gestational hypertension; the risk ratios for an interquartile range (IQR) increase in exposure were 1.07 [95% confidence interval (CI) 1.04, 1.11] for PM(10) (IQR: 3.92 µg/m(3)) and 1.11 [95% CI 1.08, 1.15] for PM(2.5) (IQR: 2.24 µg/m(3)). Living in a neighbourhood with increased levels of deprivation was also associated with gestational hypertension. Any smoking during pregnancy, younger age and higher level of education were inversely associated with risk of gestational hypertension. Compared with non-Hispanic White women, non-Hispanic Black women were at higher risk of gestational hypertension, whereas Hispanic women were at lower risk. Increased levels of PM and neighbourhood deprivation, as well as certain individual characteristics, were associated with higher risk of gestational hypertension.

A novel tool for assessing and summarizing the built environment.

BACKGROUND: A growing corpus of research focuses on assessing the quality of the local built environment and also examining the relationship between the built environment and health outcomes and indicators in communities. However, there is a lack of research presenting a highly resolved, systematic, and comprehensive spatial approach to assessing the built environment over a large geographic extent. In this paper, we contribute to the built environment literature by describing a tool used to assess the residential built environment at the tax parcel-level, as well as a methodology for summarizing the data into meaningful indices for linkages with health data. METHODS: A database containing residential built environment variables was constructed using the existing body of literature, as well as input from local community partners. During the summer of 2008, a team of trained assessors conducted an on-foot, curb-side assessment of approximately 17,000 tax parcels in Durham, North Carolina, evaluating the built environment on over 80 variables using handheld Global Positioning System (GPS) devices. The exercise was repeated again in the summer of 2011 over a larger geographic area that included roughly 30,700 tax parcels; summary data presented here are from the 2008 assessment. RESULTS: Built environment data were combined with Durham crime data and tax assessor data in order to construct seven built environment indices. These indices were aggregated to US Census blocks, as well as to primary adjacency communities (PACs) and secondary adjacency communities (SACs) which better described the larger neighborhood context experienced by local residents. Results were disseminated to community members, public health professionals, and government officials. CONCLUSIONS: The assessment tool described is both easily-replicable and comprehensive in design. Furthermore, our construction of PACs and SACs introduces a novel concept to approximate varying scales of community and describe the built environment at those scales. Our collaboration with community partners at all stages of the tool development, data collection, and dissemination of results provides a model for engaging the community in an active research program.

Adverse birth outcomes among nulliparous vs. multiparous women.

OBJECTIVES: Previous studies indicate that nulliparous women (i.e., women having no previous births) are at higher risk for adverse birth outcomes than multiparous women (i.e., women having had at least one previous birth). We examined whether part of the difference in adverse outcome rates is attributable to nulliparous women with poor pregnancy outcomes being less likely (through choice or fecundity differences) to have a subsequent live birth within the same time period as nulliparous women without adverse outcomes. METHODS: Using deterministic matching, we linked nulliparous women from the North Carolina Detailed Birth Record to subsequent births. We employed statistical and simulation-based analyses to estimate first birth outcome rate differences between nulliparous women who did have a subsequent live birth vs. those who did not. Our Markov simulations focused on preterm birth (PTB). RESULTS: Among nulliparous women who were not linked to a second birth, maternal age-adjusted rates of multiple adverse outcomes were all statistically higher compared with rates for linked women. These results also held in race/ethnicity-specific analyses. Simulations found that the relative risk of PTB associated with a history of PTB was underestimated if some women who would have been at risk for PTB did not experience a second birth. CONCLUSIONS: The observed differences in rates of adverse outcomes between nulliparous and multiparous women are partly attributable to higher-risk women not having a subsequent live birth, either by choice or due to fecundity differences.

Seasonality of poor pregnancy outcomes in North Carolina.

BACKGROUND: Seasonal variation in poor pregnancy outcomes has not received the same level of research attention and rigor as has the well-established seasonal variation in births. METHODS: In this analysis of data from the 2001-2005 North Carolina Detailed Birth Record, we use season of conception as a proxy for environmental or other risk factors. We model the continuous pregnancy outcome of birth weight percentile for gestational age by use of linear regression. We use logistic regression to model the binary pregnancy outcomes of low birth weight (< 2500 g), preterm birth (< 37 weeks), and small for gestational age (< 10th percentile of birth weight for gestational age). RESULTS: We found significant seasonal patterns in poor pregnancy outcomes. Our results suggest that, in North Carolina, seasonal patterns are most pronounced among non-Hispanic white women living in urban areas. LIMITATIONS: The present study is limited by the restricted set of maternal and pregnancy variables available in this data set. Richer data, potentially including psychosocial and activity measures of the women, would allow us to more ably discern what is driving the seasonal patterns we observed. The pronounced increased risk associated with a spring season of conception provides an important clue for determining the true causative factors. CONCLUSIONS: Poor pregnancy outcomes in North Carolina follow a clear seasonal pattern based on timing of conception, with patterns most pronounced among non-Hispanic white women living in urban areas. These seasonal patterns are suggestive of causative environmental factors and certainly warrant additional research.

Use of spatial analysis to support environmental health research and practice.

Recent advances in spatial statistics and geographic information systems provide innovative platforms for diagnosing environmental health problems and for developing interventions. This article discusses when and where spatial techniques can most effectively be deployed to address environmental health issues, especially as they relate to environmental justice concerns.

Cadmium levels in a North Carolina cohort: Identifying risk factors for elevated levels during pregnancy.

The objectives of this study were to examine cadmium (Cd) levels and relationships to demographics in an observational, prospective pregnancy cohort study in Durham County, North Carolina. Multivariable models were used to compare blood Cd levels across demographic characteristics. The relative risk of having a blood Cd level that exceeds the US national median (0.32 µg/l) was estimated. Overall, >60% of the women had an elevated (>0.32 µg/l) blood Cd level. Controlling for confounding variables, smoking was associated with 21% (95% CI: 15-28%) increased risk for an elevated blood Cd level. High Cd levels were also observed in non-smokers and motivated smoking status-stratified models. Race, age, education, relationship status, insurance status and cotinine level were not associated with risk of elevated Cd levels among smokers; however, older age and higher cotinine levels were associated with elevated Cd levels among non-smokers. Taken together, more than half of pregnant women in this cohort had elevated blood Cd levels. Additionally, among non-smokers, 53% of the women had elevated levels of Cd, highlighting other potential sources of exposure. This study expands on the limited data describing Cd levels in pregnant populations and highlights the importance of understanding Cd exposures among non-smokers. Given the latent health risks of both smoking and Cd exposure, this study further highlights the need to biomonitor for exposure to toxic metals during pregnancy among all women of child-bearing age.

Geocoding large population-level administrative datasets at highly resolved spatial scales.

Using geographic information systems to link administrative databases with demographic, social, and environmental data allows researchers to use spatial approaches to explore relationships between exposures and health. Traditionally, spatial analysis in public health has focused on the county, zip code, or tract level because of limitations to geocoding at highly resolved scales. Using 2005 birth and death data from North Carolina, we examine our ability to geocode population-level datasets at three spatial resolutions - zip code, street, and parcel. We achieve high geocoding rates at all three resolutions, with statewide street geocoding rates of 88.0% for births and 93.2% for deaths. We observe differences in geocoding rates across demographics and health outcomes, with lower geocoding rates in disadvantaged populations and the most dramatic differences occurring across the urban-rural spectrum. Our results suggest highly resolved spatial data architectures for population-level datasets are viable through geocoding individual street addresses. We recommend routinely geocoding administrative datasets to the highest spatial resolution feasible, allowing public health researchers to choose the spatial resolution used in analysis based on an understanding of the spatial dimensions of the health outcomes and exposures being investigated. Such research, however, must acknowledge how disparate geocoding success across subpopulations may affect findings.

Proximity to roadways and pregnancy outcomes.

Adverse birth outcomes are associated with exposure to air pollution during pregnancy. Road proximity is a simple, widely available metric for capturing local variation in exposure to traffic-related air pollution. We characterized maternal exposure to traffic-related air pollution during pregnancy using residential proximity to major roadways among 2004-2008 singleton births in NC. Controlling for maternal race, age, education, nativity, marital status, and tobacco use, and season of birth, parity, infant sex, and Census tract-level urbanization and income, we evaluated the association between road proximity and pregnancy outcomes using generalized linear mixed models with a random intercept for each Census tract. Birth weight, birth weight percentile for gestational age, gestational hypertension, and small-for-gestational age were not associated with road proximity; however, women residing within 250 m of a major roadway were at 3-5% increased odds of low birth weight, preterm birth, and late preterm birth compared with women residing beyond 250 m (P<0.05). Our analyses demonstrate an association between proximity to major roadways and pregnancy outcomes using a large sample. Road proximity may represent a relatively straightforward method for assessing maternal risk from exposure to traffic-related air pollution, with results offering guidance for studies that can more accurately characterize air pollution exposures.

The built environment and childhood obesity in Durham, North Carolina.

The relationship between childhood obesity and aspects of the built environment characterizing neighborhood social context is understudied. This study evaluates the association between 7 built environment domains and childhood obesity in Durham, North Carolina. Measures of housing damage, property disorder, vacancy, nuisances, and territoriality were constructed using data from a 2008 community assessment. Renter-occupied housing and crime measures were developed from public databases. The authors linked these measures to 2008-2009 Duke University Medical Center pediatric preventive care visits. Age- and sex-specific body mass index percentiles were used to classify children as normal weight (>5th and ≤85th percentile), overweight (>85th and ≤95th percentile), or obese (>95th percentile). Ordinal logistic regression models with cluster-corrected standard errors evaluated the association between weight status and the built environment. Adjusting for child-level socioeconomic characteristics, nuisances and crime were associated with childhood overweight/obesity (P < .05). Built environment characteristics appear important to childhood weight status in Durham, North Carolina.

Psychosocial differences between smokers and non-smokers during pregnancy.

Despite the well-established adverse birth and childhood health outcomes associated with maternal smoking, smoking rates among pregnant women remain high. Psychosocial health attributes, including anxiety, depression, perceived stress, self-efficacy, and personality characteristics, have especially important roles in smoking behavior. Understanding who smokes during pregnancy and what factors influence this behavior choice may be key to improving the effectiveness of smoking cessation intervention programs. We use data from a prospective cohort study of pregnant women to understand the psychosocial health profiles of women who choose to smoke during pregnancy compared to the profiles of women who do not smoke or successfully quit smoking during pregnancy. Multinomial logistic regression analyses on 1518 non-Hispanic black and non-Hispanic white women assessed the association between smoking status and psychosocial health while controlling for demographic characteristics. Higher levels of perceived stress, depression, neuroticism, negative paternal support, and perceived racism among non-Hispanic blacks were associated with higher odds of being a smoker than a non-smoker (p<0.05). Higher levels of self-efficacy, extraversion, agreeableness, conscientiousness, interpersonal support, positive paternal support, and perceived social standing were associated with lower odds of being a smoker than a non-smoker (p<0.05). Our analysis indicates that women who smoked during pregnancy experienced a more negative constellation of psychosocial adversities than women who did not smoke. Given the psychosocial needs and personality profiles experienced by smokers, more attention to the psychosocial strengths and weaknesses of these women may allow for more tailored smoking cessation programs, enhancing both the short- and long-term effectiveness of such interventions.

Making the environmental justice grade: the relative burden of air pollution exposure in the United States.

This paper assesses whether the Clean Air Act and its Amendments have been equally successful in ensuring the right to healthful air quality in both advantaged and disadvantaged communities in the United States. Using a method to rank air quality established by the American Lung Association in its 2009 State of the Air report along with EPA air quality data, we assess the environmental justice dimensions of air pollution exposure and access to air quality information in the United States. We focus on the race, age, and poverty demographics of communities with differing levels of ozone and particulate matter exposure, as well as communities with and without air quality information. Focusing on PM2.5 and ozone, we find that within areas covered by the monitoring networks, non-Hispanic blacks are consistently overrepresented in communities with the poorest air quality. The results for older and younger age as well as poverty vary by the pollution metric under consideration. Rural areas are typically outside the bounds of air quality monitoring networks leaving large segments of the population without information about their ambient air quality. These results suggest that substantial areas of the United States lack monitoring data, and among areas where monitoring data are available, low income and minority communities tend to experience higher ambient pollution levels.

Assessing exposure metrics for PM and birth weight models.

The link between air pollution exposure and adverse birth outcomes is of public health concern due to the relationship between poor pregnancy outcomes and the onset of childhood and adult diseases. As personal exposure measurements are difficult and expensive to obtain, proximate measures of air pollution exposure are traditionally used. We explored how different air pollution exposure metrics affect birth weight regression models. We examined the effect of maternal exposure to ambient levels of particulate matter <10, <2.5 mum in aerodynamic diameter (PM(10), PM(2.5)) on birth weight among infants in North Carolina. We linked maternal residence to the closest monitor during pregnancy for 2000-2002 (n=350,754). County-level averages of air pollution concentrations were estimated for the entire pregnancy and each trimester. For a finer spatially resolved metric, we calculated exposure averages for women living within 20, 10, and 5 km of a monitor. Multiple linear regression was used to determine the association between exposure and birth weight, adjusting for standard covariates. In the county-level model, an interquartile increase in PM(10) and PM(2.5) during the entire gestational period reduced the birth weight by 5.3 g (95% CI: 3.3-7.4) and 4.6 g (95% CI: 2.3-6.8), respectively. This model also showed a reduction in birth weight for PM(10) (7.1 g, 95% CI: 1.0-13.2) and PM(2.5) (10.4 g, 95% CI: 6.4-14.4) during the third trimester. Proximity models for 20, 10, and 5 km distances showed results similar to the county-level models. County-level models assume that exposure is spatially homogeneous over a larger surface area than proximity models. Sensitivity analysis showed that at varying spatial resolutions, there is still a stable and negative association between air pollution and birth weight, despite North Carolina's consistent attainment of federal air quality standards.

Blood lead levels among pregnant women: historical versus contemporaneous exposures.

Blood lead among pregnant women, even at modest levels, may impair offspring cognitive development. We examine whether blood lead levels (BLLs) result from current versus historic exposures, among a cohort of pregnant women. Cumulative logit models were used to characterize the relationship between maternal risk factors and higher BLLs. Maternal blood lead levels more likely result from lead remobilization from historic versus contemporaneous exposures. Even if all lead sources were abated immediately, women and their fetuses would experience lead exposure for decades. This work emphasizes the importance of addressing sources of environmental lead exposure in the United States and internationally.

Environmental justice implications of reduced reporting requirements of the Toxics Release Inventory Burden Reduction Rule.

This paper presents a geographic information systems (GIS) methodology for evaluating the environmental justice implications of the Toxics Release Inventory (TRI) Burden Reduction Rule, which was issued by the U.S. Environmental Protection Agency in December 2006 under the authority of the Emergency Planning and Community Right-to-Know Act of 1986. This rule exempts industrial facilities meeting certain higher reporting thresholds from filing detailed reports about the quantities of chemicals used, released, or managed as waste. Our analytical approach examines demographic characteristics within a 1, 3, and 5 km buffer around a georeferenced facility location, applied on a national, regional, and state scale. The distance-based GIS analysis demonstrates that TRI facilities that are eligible for reduced reporting are more likely to be located in proximity to communities with a higher percentage of minority and low-income residents. The differences are more pronounced for percent minority and percent minority under age 5 in comparison to percent in poverty, and the demographic differences are more apparent at increasingly resolved geographic scales.