In order to ensure clean drinking water for all, it is crucial to understand potential upland stressors that compromise the quality of source waters treated by local community water systems (CWSs). Contamination associated with specific types of land cover can result in downstream water quality degradation, which may reduce the effectiveness of treatment by CWSs. Surface mining has been hypothesized as a source of drinking water degradation within the Central Appalachian region, which may result in adverse exposures and health disparities. The purpose of this study was to identify potential correlations between land cover and adverse birth outcomes (ABOs) through the application of watershed epidemiology, an emerging environmental health paradigm. Birth records for the Central Appalachian region were acquired from their respective state health departments from 2001 to 2015: each record contained the mother's street address, outcome variables, and covariates. Records were included in later analyses if they fell within an approximated CWS service area. Contributing land cover to each CWS was determined via previously delineated watersheds that relied on CWS intake points. A binomial generalized linear model was used to compare low birth weight (LBW), term low birth rate (tLBW), and preterm birth (PTB) incidence to CWS source watershed land cover, Safe Drinking Water Act (SDWA) violations, CWS size, and covariates related to the birth records. Source watershed mining and SDWA health based (HB) violations were significantly associated with greater risks for preterm birth (PTB) and low birth weight (LBW). Future work should be conducted to explore upstream flow impacts, address missing data in the birth records, and to more accurately represent CWS service areas to better characterize exposure. / Master of Science / Millions of individuals throughout the world are sickened by waterborne exposures every year. To ensure clean drinking water long-term, it is crucial to understand how human land cover might change the water quality of source watersheds, as this may impact the effectiveness of water treatment and increase adverse human health exposures. The goal of this effort is to understand whether land cover is linked to downstream adverse birth outcomes (ABOs) in Central Appalachia, a region of the United States previously associated with high disease incidence suspected to be partially linked to environmental exposure. Birth records were acquired for the years of 2001 to 2015 from four (VA, WV, TN, KY) respective state health departments. Each record contained the mother's address, outcome variables, and covariates (e.g., race, ethnicity). Births were located within approximate service areas for 140 surface water dependent community water systems (CWS) within the region. Data from each CWS, including weighted land cover proportions for their source watershed, were merged with the birth records according to approximate service areas. Statistical analysis suggested that higher source watershed levels of mining and urban development were associated with higher risks of preterm birth (PTB) and low birth weight (LBW). The number of health based (HB) violations associated with each CWS was also associated with both of these outcomes. Major limitations of this work include birth record data gaps and the lack of publicly available CWS service areas and/or water consumption rates, which does increase the risk of exposure misclassification.

Adverse birth outcomes and adverse childhood experiences (ACE) are concerns in the United States, with potential to impact health indices now and in the future. The purpose of this study was to quantitatively examine the association between maternal exposure to ACE, low birth weight, and county of residence in the Appalachian population using the Life Course Approach as the theoretical framework. A cross-sectional study design and clustering strategy was used to randomly select potential respondents from a data set that was provided by Ohio Department of Health. Self-administered questionnaires were sent to potential respondents to collect information about ACE in the maternal population of Appalachia, Ohio with an overall response rate of 29.5% and 212 total participants. A chi-square analysis was completed and no significant association was found between county of residence and risk of low birth weight. However, statistically significant associations were found between the different types of ACE exposure and low birth weight delivery as well as Appalachian county of residence and exposure to ACE. As the sample of low birth weight deliveries was small, it is recommended that the relationship between ACE exposure and low birth weight be further studied to develop more purposeful health interventions to improve maternal health in Appalachia, Ohio specifically, as well as other rural communities. Reducing rates of adverse birth outcomes and chronic disease burden in Appalachia have potential to reduce health disparities between urban and Appalachian communities, allowing for positive social change for many socioeconomically disadvantaged communities and improving population health.

The incidence of adverse birth outcomes, such as low birth weight and preterm births, has steadily risen in recent years in Canada. Despite the fact that numerous individual and neighbourhood risk factors for low birth weight and preterm births have been identified and various person-oriented intervention strategies have been implemented, uncertainties still exist concerning the role that place and space play in determining adverse birth outcomes. In order to succeed in producing community-oriented health policy and planning guidelines to reduce both the occurrence and inequalities of adverse birth outcomes, the research presented in this thesis provides an approach to examining the pathways of various socio-economic, environmental, and psycho-social risks to LBW and preterm births. Using a modified multilevel binary-outcome mediational analysis method, case studies are conducted within three public health units in Ontario, namely the Wellington-Dufferin-Guelph Health Unit, the Windsor-Essex County Health Unit, and the Halton Region Health Unit. Different pathways are investigated given the available data and the theoretical assumptions of three health inequality pathway models, namely the behavioural model, the psycho-social model, and the materialist model, and the geographical and planning perspectives of health inequalities. A local spatial analysis process is also used to identify spatial clusters of incidence and to assess possible associated reasons in order to support public health polices and planning in community-oriented health interventions. Using Bayesian spatial hierarchical analysis and spatial clustering analysis, local clustering of high risks of adverse birth outcomes and spatial variations of associated individual risks within the study areas are identified. The analysis is framed around five hypotheses that examine personal vs. spatial, compositional vs. contextual, psycho-social vs. material, personal vs. cultural, and global vs. local effects on the determinants of adverse birth outcomes. The results of testing these hypotheses provide evidence to assist with multi-component multi-level community-oriented interventions. Possible improvements of current prenatal care policies and programs to reduce the spatial and social inequalities of adverse birth outcomes are suggested. Potential improvements, including early stage prenatal health education, local healthy food provision, and cross-sector interventions such as the combination of social mixing strategies with bottom-up community-based health promotion programs, are also suggested.

The incidence of adverse birth outcomes, such as low birth weight and preterm births, has steadily risen in recent years in Canada. Despite the fact that numerous individual and neighbourhood risk factors for low birth weight and preterm births have been identified and various person-oriented intervention strategies have been implemented, uncertainties still exist concerning the role that place and space play in determining adverse birth outcomes. In order to succeed in producing community-oriented health policy and planning guidelines to reduce both the occurrence and inequalities of adverse birth outcomes, the research presented in this thesis provides an approach to examining the pathways of various socio-economic, environmental, and psycho-social risks to LBW and preterm births. Using a modified multilevel binary-outcome mediational analysis method, case studies are conducted within three public health units in Ontario, namely the Wellington-Dufferin-Guelph Health Unit, the Windsor-Essex County Health Unit, and the Halton Region Health Unit. Different pathways are investigated given the available data and the theoretical assumptions of three health inequality pathway models, namely the behavioural model, the psycho-social model, and the materialist model, and the geographical and planning perspectives of health inequalities. A local spatial analysis process is also used to identify spatial clusters of incidence and to assess possible associated reasons in order to support public health polices and planning in community-oriented health interventions. Using Bayesian spatial hierarchical analysis and spatial clustering analysis, local clustering of high risks of adverse birth outcomes and spatial variations of associated individual risks within the study areas are identified. The analysis is framed around five hypotheses that examine personal vs. spatial, compositional vs. contextual, psycho-social vs. material, personal vs. cultural, and global vs. local effects on the determinants of adverse birth outcomes. The results of testing these hypotheses provide evidence to assist with multi-component multi-level community-oriented interventions. Possible improvements of current prenatal care policies and programs to reduce the spatial and social inequalities of adverse birth outcomes are suggested. Potential improvements, including early stage prenatal health education, local healthy food provision, and cross-sector interventions such as the combination of social mixing strategies with bottom-up community-based health promotion programs, are also suggested.

Objectives To describe the creation of a multigenerational linked dataset with social mobility measures for South Carolina (SC), as an example for states in the South and other areas of the country. Methods Using unique identifiers, we linked birth certificates along the maternal line using SC birth certificate data from 1989 to 2014, and compared the subset of records for which linking was possible with two comparison groups on sociodemographic and birth outcome measures. We created four multi-generational social mobility measures using maternal education, paternal education, presence of paternal information, and a summary score incorporating the prior three measures plus payment source for births after 2004. We compared social mobility measures by race/ethnicity. Results Of the 1,366,288 singleton birth certificates in SC from 1989 to 2014, we linked 103,194, resulting in 61,229 unique three-generation units. Mothers and fathers were younger and had lower education, and low birth weight was more common, in the multigenerational linked dataset than in the two comparison groups. Based on the social mobility summary score, only 6.3% of White families were always disadvantaged, compared to 30.4% of Black families and 13.2% of Hispanic families. Moreover, 32.8% of White families were upwardly mobile and 39.1% of Black families were upwardly mobile, but only 29.9% of Hispanic families were upwardly mobile. Conclusions for Practice When states are able to link individuals, birth certificate data may be an excellent source for examining population-level relationships between social mobility and adverse birth outcomes. Due to its location in the Deep South, the multigenerational SC dataset may be particularly useful for understanding racial/ethnic difference in social mobility and birth outcomes.

Infant mortality (IM) rates in the United States remains high. The higher rates of IM among specific groups in the United States is believed to be fueled by the high rates of adverse birth outcomes including low birthweight (LBW) and preterm births (PTB) among these groups. Adverse birth outcomes have also been linked to the presence of hypertensive disorders during pregnancy. The purpose of this cross-sectional study was to explore the association between hypertensive disorders during pregnancy and adverse birth outcomes and the impact of the residential neighborhood of expectant mothers on this association. The life course health development theory guided the framework for this study. Study data were obtained from the 2010 New York City birth records and the 2010 US Census. Descriptive statistics and logistic regression analysis were used to address the 3 research hypotheses of the study. The study found that prepregnancy hypertension (HTN) (AOR: 2.84 & 3.25), gestational HTN (AOR: 2.28 & 3.33) and eclampsia (AOR: 4.41 & 6.70) were significantly associated with PTB and LBW respectively. Neighborhood segregation was not significant for PTB (AOR: 1.01) or LBW (AOR: 1.03). Neighborhood poverty was significant for PTB (AOR: 0.86) but not for LBW (AOR: 1.05). Neighborhood segregation and poverty had significant moderating effects on the prepregnancy HTN (p = 0.00), gestational HTN (p = 0.00), eclampsia (p = 0.00) and PTB and LBW association. Results from this study can help to address disparities in birth outcomes among women of differing races and ethnicities and thereby contribute to positive social change.

Objective: The Affordable Care Act (ACA) has influenced increasing interests in population health and population health outcomes. The purpose of this study was to exemplify the importance of using existing vital statistics data for understanding and monitoring health outcomes and consequentially health disparities at the population level. Data from birth records for two geographic regions from 2009-2014 were compared; low birth weight (LBW) and preterm delivery (PD) were used as surrogates for population health outcomes. Methods: A population-based, multi-year, cross-sectional study design using a pooled dataset of birth records from Tennessee (TN) was the framework for the analyses. A sub-population from North East TN (NE TN) was compared to TN. Logistic regression was used to estimate odds ratios. Attributable risks were calculated to translate the findings from conditional associations to population-level associations to help inform public health policy decision-making. Results: Using birth records (vital statistics), we demonstrated that the period prevalence of cigarette smoking before and during pregnancy remained unchanged with approximately one in three women in NE TN (from 37% in 2009 to 32% in 2014) and one in five women in TN (from 23% in 2009 to 20% in 2014) reporting smoking pre-pregnancy. Multivariate analyses demonstrated that mothers who were at each end of the age spectrum, of very low household income level and reported cigarette smoking pre-pregnancy or during pregnancy had increased risk of a LBW or PD infant. During the years of observation, 39 to 50% of the total incidence of LBW in the group of women who smoked cigarettes prior to pregnancy was attributable to smoking cigarettes. Conclusions: Existing data, such as vital statistics data, should be used routinely to identify geographic areas for which programs or policies can be implemented to reach large portions of populations. Reducing prenatal smoking, for example, has the potential to reduce a large fraction of adverse birth outcomes such as LBW and PD. For the geographic area we evaluated, 39 to 50% of LBW could be prevented by devising population-based smoking cessation programs or policies for women of child-bearing age. With recent emphasis on prevention and well-baby care in the ACA, there is potential to increase attention to this problem, implement evidence-based prevention programs and monitor program effectiveness with existing birth record data. Following this model, we can attain population health goals and address health disparities.