Cardiovascular Disease Incidence and Cardiovascular Health Among Diverse Women With Breast and Gynecologic Cancers.

OBJECTIVES: To examine if racial differences in cardiovascular health (CVH) are associated with cardiovascular disease (CVD) disparities among women with breast and gynecologic cancers. SAMPLE & SETTING: The sample consisted of 252 Black women and 93 White women without a self-reported history of cancer or CVD who developed a breast or gynecologic malignancy. Women who developed CVD before their cancer diagnosis were excluded. METHODS & VARIABLES: CVH was classified using metrics of the American Heart Association's Life's Simple 7 framework. Metrics were summed to create a total CVH score (0-7). Associations among race, ideal CVH (score of 5-7), and CVD incidence following cancer diagnosis were estimated with Cox proportional hazards models. RESULTS: Ideal CVH was similar between Black women (33%) and White women (37%). Race and CVH were not associated with CVD incidence. IMPLICATIONS FOR NURSING: In a small sample of women diagnosed with breast and gynecologic cancers, racial disparities in CVH and CVD incidence were not observed. Additional investigation of potential confounders relating to social determinants of health tied to the construct of race is warranted.

Seminar: Scalable Preprocessing Tools for Exposomic Data Analysis.

BACKGROUND: The exposome serves as a popular framework in which to study exposures from chemical and nonchemical stressors across the life course and the differing roles that these exposures can play in human health. As a result, data relevant to the exposome have been used as a resource in the quest to untangle complicated health trajectories and help connect the dots from exposures to adverse outcome pathways. OBJECTIVES: The primary aim of this methods seminar is to clarify and review preprocessing techniques critical for accurate and effective external exposomic data analysis. Scalability is emphasized through an application of highly innovative combinatorial techniques coupled with more traditional statistical strategies. The Public Health Exposome is used as an archetypical model. The novelty and innovation of this seminar's focus stem from its methodical, comprehensive treatment of preprocessing and its demonstration of the positive effects preprocessing can have on downstream analytics. DISCUSSION: State-of-the-art technologies are described for data harmonization and to mitigate noise, which can stymie downstream interpretation, and to select key exposomic features, without which analytics may lose focus. A main task is the reduction of multicollinearity, a particularly formidable problem that frequently arises from repeated measurements of similar events taken at various times and from multiple sources. Empirical results highlight the effectiveness of a carefully planned preprocessing workflow as demonstrated in the context of more highly concentrated variable lists, improved correlational distributions, and enhanced downstream analytics for latent relationship discovery. The nascent field of exposome science can be characterized by the need to analyze and interpret a complex confluence of highly inhomogeneous spatial and temporal data, which may present formidable challenges to even the most powerful analytical tools. A systematic approach to preprocessing can therefore provide an essential first step in the application of modern computer and data science methods. https://doi.org/10.1289/EHP12901.

A scoping review of the concept of resilience among African American women.

Resilience, thriving in the face of adversity, is a critical component of well-being in African American women. However, traditional definitions and approaches to operationalize resilience may not capture race- and gender-related resilience experiences of African American women. A more complete conceptualization of resilience may help facilitate future investigation of the mechanisms through which resilience influences health in this group. Our team conducted a scoping review of the literature published during twenty years, between 2000 and 2019, on resilience and health in African American women. We included a multidisciplinary set of databases (PubMed, CINAHL, PsycINFO, Scopus, Social Work Abstracts, Sociological Abstracts, Academic Search Premier). Using Covidence software a multi-step review process was conducted; 904 abstracts were initially screened for eligibility, 219 full-text studies were screened in stage two, and 22 remaining studies were reviewed for extraction. The studies reviewed revealed limitations of unidimensional approaches to conceptualizing/operationalizing resilience in African American women. The review highlighted culturally-relevant components of resilience including spirituality/religion, strength, survival, active coping, and social support. Findings highlight the importance of operationalizing resilience as a multidimensional construct so it can be optimally included in research designed to investigate the quality of life, cardiovascular risk, and other health outcomes in African American women.

The association between cardiovascular disease and breast and gynecologic cancers among black female patients.

INTRODUCTION: Little is known about whether a breast or gynecologic cancer diagnosis increases long-term cardiovascular disease (CVD) risk among Black females. The purpose of this study was to determine whether a breast or gynecologic cancer diagnosis is associated with CVD risk and identify determinants of subsequent CVD risk among Black females with an incident breast or gynecologic cancer diagnosis. METHODS: Using the Southern Community Cohort Study data from 2002-2016, this study was designed to analyze CVD incidence among Black females without cancer or CVD at enrollment. Cox proportional hazards regression models with or without covariates were used to explore the relationship between a breast or gynecologic cancer diagnosis and CVD risk among women without cancer as well as without CVD at enrollment (N=11,486). In addition, Cox proportional hazards regression models, excluding those who developed CVD before breast and gynecologic cancer diagnosis and those with other types of cancers, were used to assess determinants of CVD risk among breast and gynecologic cancer survivors. RESULTS: Of 11,486 Black females, 531 developed a breast or gynecological cancer (4.6%) over a median follow-up of 140 months (interquartile range: 123-159 months). Compared to women without cancer, women with a breast or gynecological cancers had greater than 20% higher risk of incident CVD during the follow-up period. Without adjusting for covariates, positive association between CVD risk and breast cancer was observed (hazard ratio (HR) = 1.24; 95% confidence interval (CI) = 1.11 - 1.39; p < 0.001); as well as between CVD risk and a gynecological cancer (HR = 1.23; 95% CI = 1.03 - 1.46; p = 0.021). Yet, after adjusting for covariates, CVD risk was only significantly associated with breast cancer (p = 0.001) but not gynecologic cancer. In cancer case-only analyses, CVD risk was significantly increasing with age (p < 0.05). CONCLUSIONS: Like study populations of predominantly White females, our results suggest that, adjusting for covariates, Black females possess a higher risk of CVD following a breast cancer diagnosis compared to women who did not develop breast cancer. Our results suggest a need for active CVD surveillance in the cancer survivorship phase.

The Modifying Role of Resilience on Allostatic Load and Cardiovascular Disease Risk in the Jackson Heart Study.

We examined whether resilience modified associations between allostatic load (AL), a physiological indicator of coping with repeated stressors, and cardiovascular disease (CVD) among 2758 African Americans in the Jackson Heart Study. Baseline AL was quantified using biological measures of metabolic, cardiovascular, and immune markers. We constructed a multidimensional resilience measure using validated questionnaires for social support, social networks, religious experiences, and optimism. Participants were followed until 2016 for stroke, coronary heart disease (CHD), and heart failure (HF). We used multivariable-adjusted, sex-stratified Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between dichotomous AL and CVD. High AL was associated with CHD among women (HR = 1.73, 95% CI = 1.00, 2.99) and HF among women (HR = 1.52, 95% CI = 0.98, 2.37) and men (HR = 2.17, 95% CI = 1.28, 3.68). Among women, resilience did not modify the AL-CVD relationship. Among men, we observed higher stroke risk among men with low resilience (HR = 2.21, 95% CI = 0.94, 5.22) and no association among those with high resilience. Counterintuitively, high AL was associated with greater HF (HR = 5.80, 95% CI = 2.32, 14.47) in the subgroup of men with high resilience. Future studies addressing different facets of resilience are needed to elucidate underlying mechanisms for CVD prevention among African Americans.

Community-level exposomics: a population-centered approach to address public health concerns.

Environmental factors affecting health and vulnerability far outweigh genetics in accounting for disparities in health status and longevity in US communities. The concept of the exposome, the totality of exposure from conception onwards, provides a paradigm for researchers to investigate the complex role of the environment on the health of individuals. We propose a complementary framework, community-level exposomics, for population-level exposome assessment. The goal is to bring the exposome paradigm to research and practice on the health of populations, defined by various axes including geographic, social, and occupational. This framework includes the integration of community-level measures of the built, natural and social environments, environmental pollution-derived from conventional and community science approaches, internal markers of exposure that can be measured at the population-level and early responses associated with health status that can be tracked using population-based monitoring. Primary challenges to the implementation of the proposed framework include needed advancements in population-level measurement, lack of existing models with the capability to produce interpretable and actionable evidence and the ethical considerations of labeling geographically-bound populations by exposomic profiles. To address these challenges, we propose a set of recommendations that begin with greater engagement with and empowerment of affected communities and targeted investment in community-based solutions. Applications to urban settings and disaster epidemiology are discussed as examples for implementation.

A Framework for Interfacing and Partnering with Environmental Justice Communities as a Prelude to Human Health and Hazard Identification in the Vulnerable Census Tracts of Columbus, Ohio.

Columbus, Ohio is one of the more prosperous, well-educated, and progressive cities in the United States. However, it ranks as the second worst life expectancy at birth, has a census tract wealth gap (27-year disparity), and one of the higher infant mortality rates in the country. These data suggest that there are likely several high-risk, vulnerable neighborhoods in Columbus with residents experiencing disparate and adverse outcomes. Illustrative of this fact are studies that have examined the social processes and mechanisms through which neighborhood contexts are at the forefront, including exposures to chemical stressors such as particulate matter (PM2.5) as well as non-chemical stressors including violence, social determinants of health, zoning, and land use policies. It is documented that disparate and adverse outcomes are magnified in the vulnerable neighborhoods on the Near East Side as compared to Columbus city proper, Franklin County and/or the state of Ohio. As such, we developed a nuanced community engagement framework to identify potential environmental hazards associated with adverse pregnancy outcomes in those census tracts. The refined framework uses a blended version of traditional community-based participatory research (CBPR) models and is referred to as E6, Enhancing Environmental Endeavors via e-Equity, Education, and Empowerment.

Big Data to Knowledge Analytics Reveals the Zika Virus Epidemic as Only One of Multiple Factors Contributing to a Year-Over-Year 28-Fold Increase in Microcephaly Incidence.

During the 2015-2016 Zika Virus (ZIKV) epidemic in Brazil, the geographical distributions of ZIKV infection and microcephaly outbreaks did not align. This raised doubts about the virus as the single cause of the microcephaly outbreak and led to research hypotheses of alternative explanatory factors, such as environmental variables and factors, agrochemical use, or immunizations. We investigated context and the intermediate and structural determinants of health inequalities, as well as social environment factors, to determine their interaction with ZIKV-positive- and ZIKV-negative-related microcephaly. The results revealed the identification of 382 associations among 382 nonredundant variables of Zika surveillance, including multiple determinants of environmental public health factors and variables obtained from 5565 municipalities in Brazil. This study compared those factors and variables directly associated with microcephaly incidence positive to ZIKV and those associated with microcephaly incidence negative to ZIKV, respectively, and mapped them in case and control subnetworks. The subnetworks of factors and variables associated with low birth weight and birthweight where birth incidence served as an additional control were also mapped. Non-significant differences in factors and variables were observed, as were weights of associations between microcephaly incidence, both positive and negative to ZIKV, which revealed diagnostic inaccuracies that translated to the underestimation of the scope of the ZIKV outbreak. A detailed analysis of the patterns of association does not support a finding that vaccinations contributed to microcephaly, but it does raise concerns about the use of agrochemicals as a potential factor in the observed neurotoxicity arising from the presence of heavy metals in the environment and microcephaly not associated with ZIKV. Summary: A comparative network inferential analysis of the patterns of variables and factors associated with Zika virus infections in Brazil during 2015-2016 coinciding with a microcephaly epidemic identified multiple contributing determinants. This study advances our understanding of the cumulative interactive effects of exposures to chemical and non-chemical stressors in the built, natural, physical, and social environments on adverse pregnancy and health outcomes in vulnerable populations.

Structural and Social Determinants of Health Factors Associated with County-Level Variation in Non-Adherence to Antihypertensive Medication Treatment.

BACKGROUND: Non-adherence to antihypertensive medication treatment (AHM) is a complex health behavior with determinants that extend beyond the individual patient. The structural and social determinants of health (SDH) that predispose populations to ill health and unhealthy behaviors could be potential barriers to long-term adherence to AHM. However, the role of SDH in AHM non-adherence has been understudied. Therefore, we aimed to define and identify the SDH factors associated with non-adherence to AHM and to quantify the variation in county-level non-adherence to AHM explained by these factors. METHODS: Two cross-sectional datasets, the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014-2016 cycle) and the 2016 County Health Rankings (CHR), were linked to create an analytic dataset. Contextual SDH variables were extracted from the CDC-CHR linked dataset. County-level prevalence of AHM non-adherence, based on Medicare fee-for-service beneficiaries' claims data, was extracted from the CDC Atlas dataset. The CDC measured AHM non-adherence as the proportion of days covered (PDC) with AHM during a 365 day period for Medicare Part D beneficiaries and aggregated these measures at the county level. We applied confirmatory factor analysis (CFA) to identify the constructs of social determinants of AHM non-adherence. AHM non-adherence variation and its social determinants were measured with structural equation models. RESULTS: Among 3000 counties in the U.S., the weighted mean prevalence of AHM non-adherence (PDC < 80%) in 2015 was 25.0%, with a standard deviation (SD) of 18.8%. AHM non-adherence was directly associated with poverty/food insecurity (ß = 0.31, P-value < 0.001) and weak social supports (ß = 0.27, P-value < 0.001), but inversely with healthy built environment (ß = -0.10, P-value = 0.02). These three constructs explained one-third (R2 = 30.0%) of the variation in county-level AHM non-adherence. CONCLUSION: AHM non-adherence varies by geographical location, one-third of which is explained by contextual SDH factors including poverty/food insecurity, weak social supports and healthy built environments.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes.

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

The Health Opportunity Index: Understanding the Input to Disparate Health Outcomes in Vulnerable and High-Risk Census Tracts.

The Health Opportunity Index (HOI) is a multivariate tool that can be more efficiently used to identify and understand the interplay of complex social determinants of health (SDH) at the census tract level that influences the ability to achieve optimal health. The derivation of the HOI utilizes the data-reduction technique of principal component analysis to determine the impact of SDH on optimal health at lower census geographies. In the midst of persistent health disparities and the present COVID-19 pandemic, we demonstrate the potential utility of using 13-input variables to derive a composite metric of health (HOI) score as a means to assist in the identification of the most vulnerable communities during the current pandemic. Using GIS mapping technology, health opportunity indices were layered by counties in Ohio to highlight differences by census tract. Collectively we demonstrate that our HOI framework, principal component analysis and convergence analysis methodology coalesce to provide results supporting the utility of this framework in the three largest counties in Ohio: Franklin (Columbus), Cuyahoga (Cleveland), and Hamilton (Cincinnati). The results in this study identified census tracts that were also synonymous with communities that were at risk for disparate COVID-19 related health outcomes. In this regard, convergence analyses facilitated identification of census tracts where different disparate health outcomes co-exist at the worst levels. Our results suggest that effective use of the HOI composite score and subcomponent scores to identify specific SDH can guide mitigation/intervention practices, thus creating the potential for better targeting of mitigation and intervention strategies for vulnerable communities, such as during the current pandemic.

The Effects of Social, Personal, and Behavioral Risk Factors and PM2.5 on Cardio-Metabolic Disparities in a Cohort of Community Health Center Patients.

(1) Background: Cardio-metabolic diseases (CMD), including cardiovascular disease, stroke, and diabetes, have numerous common individual and environmental risk factors. Yet, few studies to date have considered how these multiple risk factors together affect CMD disparities between Blacks and Whites. (2) Methods: We linked daily fine particulate matter (PM2.5) measures with survey responses of participants in the Southern Community Cohort Study (SCCS). Generalized linear mixed modeling (GLMM) was used to estimate the relationship between CMD risk and social-demographic characteristics, behavioral and personal risk factors, and exposure levels of PM2.5. (3) Results: The study resulted in four key findings: (1) PM2.5 concentration level was significantly associated with reported CMD, with risk rising by 2.6% for each µg/m3 increase in PM2.5; (2) race did not predict CMD risk when clinical, lifestyle, and environmental risk factors were accounted for; (3) a significant variation of CMD risk was found among participants across states; and (4) multiple personal, clinical, and social-demographic and environmental risk factors played a role in predicting CMD occurrence. (4) Conclusions: Disparities in CMD risk among low social status populations reflect the complex interactions of exposures and cumulative risks for CMD contributed by different personal and environmental factors from natural, built, and social environments.

Allostatic load in the association of depressive symptoms with incident coronary heart disease: The Jackson Heart Study.

African Americans are at heightened risk for coronary heart disease (CHD), with biologic pathways poorly understood. We examined the role of allostatic load (AL) in the association of depressive symptoms with incident CHD among 2,670 African American men and women in the prospective Jackson Heart Study. Depressive symptoms were quantified using the Center for Epidemiologic Studies Depression Scale (CES-D). Incident CHD was ascertained by self-report, death certificate survey, and adjudicated medical record surveillance. Baseline AL was quantified using biologic parameters of metabolic, cardiovascular, immune, and neuroendocrine subsystems and as a combined meta-factor. Sequential models adjusted for demographic, socioeconomic, and behavioral covariates, stratified to examine differences by sex. Greater depressive symptomatology was associated with greater metabolic, cardiovascular, and immune AL (p-values≤0.036) and AL meta-factor z-scores (p = 0.007), with findings driven by observations among females. Each 1-point increase in baseline depressive symptomatology, and 1-SD increase in metabolic AL, neuroendocrine AL, and AL meta-factor z-scores was associated with 3.3%, 88%, 39%, and 130% increases in CHD risk, respectively (p-values <0.001). Neuroendocrine AL and AL meta-factor scores predicted incident CHD among males but not females in stratified analyses. Metabolic AL partially mediated the association of depressive symptoms with incident CHD (5.79% mediation, p = 0.044), a finding present among females (p = 0.016) but not males (p = 0.840). Among African American adults, we present novel findings of an association between depressive symptomatology and incident CHD, partially mediated by metabolic AL. These findings appear to be unique to females, an important consideration in the design of targeted interventions for CHD prevention.

Stress, Resilience, and Cardiovascular Disease Risk Among Black Women.

BACKGROUND: Empirical data on the link between stress and cardiovascular disease (CVD) risk among black women is limited. We examined associations of stressful life events and social strain with incident CVD among black women and tested for effect modification by resilience. METHODS AND RESULTS: Our analysis included 10 785 black women enrolled in the Women's Health Initiative Observational Study and Clinical Trials cohort. Participants were followed for CVD for up to 23 years (mean, 12.5). Multivariable Cox regression was used to estimate hazard ratios and 95% CIs for associations between stress-related exposures and incident CVD. We included interactions between follow-up time (age) and stressful life events because of evidence of nonproportional hazards. Effect modification by resilience was examined in the sub-cohort of 2765 women with resilience and stressful life events measures. Higher stressful life events were associated with incident CVD at ages 55 (hazard ratio for highest versus lowest quartile=1.80; 95% CI, 1.27-2.54) and 65 (hazard ratio for highest versus lowest quartile=1.40; 95% CI, 1.16-1.68), but not at older ages. Adjustment for CVD risk factors attenuated these associations. Similar associations were observed for social strain. In the sub-cohort of women with updated stressful life events and resilience measures, higher stressful life events were associated with incident CVD in multivariable-adjusted models (hazard ratio=1.61; 95% CI, 1.04-2.51). Resilience did not modify this association nor was resilience independently associated with incident CVD. CONCLUSIONS: In this cohort of older black women, recent reports of stressful life events were related to incident CVD. Resilience was unrelated to incident CVD. CLINICAL TRIALS REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00000611.

Application of the Public Health Exposome Framework to Estimate Phenotypes of Resilience in a Model Ohio African-American Women's Cohort.

We report integration of the United States Environmental Protection Agency's (USEPA) United States Environmental Justice Screen (EJSCREEN) database with our Public Health Exposome dataset to interrogate 9232 census blocks to model the complexity of relationships among environmental and socio-demographic variables toward estimating adverse pregnancy outcomes [low birth weight (LBW) and pre-term birth (PTB)] in all Ohio counties. Using a hill-climbing algorithm in R software, we derived a Bayesian network that mapped all controlled associations among all variables available by applying a mapping algorithm. The results revealed 17 environmental and socio-demographic variables that were represented by nodes containing 69 links accounting for a network with 32.85% density and average degree of 9.2 showing the most connected nodes in the center of the model. The model predicts that the socio-economic variables low income, minority, and under age five populations are correlated and associated with the environmental variables; particulate matter (PM2.5) level in air, proximity to risk management facilities, and proximity to direct discharges in water are linked to PTB and LBW in 88 Ohio counties. The methodology used to derive significant associations of chemical and non-chemical stressors linked to PTB and LBW from indices of geo-coded environmental neighborhood deprivation serves as a proxy for design of an African-American women's cohort to be recruited in Ohio counties from federally qualified community health centers within the 9232 census blocks. The results have implications for the development of severity scores for endo-phenotypes of resilience based on associations and linkages for different chemical and non-chemical stressors that have been shown to moderate cardio-metabolic disease within a population health context.

Using Public Health Data for Soil Pb Hazard Management in Ohio.

OBJECTIVES: To evaluate how frequently elevated soil lead (Pb) hazards (≥400 ppm Pb) were identified in existing blood Pb site investigations in Ohio. DESIGN: This study evaluated 3050 site investigations from the Ohio Department of Health for children with blood Pb levels at or above 10 µg dL that contained bare soil Pb data. SETTING: Data were collected from existing databases maintained by the Ohio Department of Health. PARTICIPANTS: All data were de-identified prior to analysis. The data used included blood Pb level test results for children (18 years or younger) in Ohio, with most data coming from children younger than 6 years. MAIN OUTCOME MEASURES: The main outcome measures were blood Pb levels and identified Pb concentrations in environmental media, including soil, paint, and dust. METHODS: Data were organized and summarized according to county. Summary statistics were generated on the basis of type of environmental media and county. RESULTS: Soil samples were collected in approximately 5% of all blood Pb cases in Ohio between 1999 and 2015. Median bare soil Pb was 1030 mg Pb kg (range, 0-345 021 mg Pb kg soil). Fifty-six of Ohio's 88 counties had at least 1 soil sample above 10 000 ppm (mg Pb kg). Multiple Pb hazards were identified, including bare soil (74% frequency), deteriorated exterior Pb paint (74%), deteriorated interior Pb paint (72%), and settled Pb dust (72%). Bare soil collected from identified dripline areas contained 2638 ppm Pb above soils collected from bare soil play areas (P = .02). Ninety assessments (3%) contained a bare soil hazard, with no other identified hazards. No trend was found comparing county mean or median Pb with county population. Previously identified high-risk counties for elevated blood Pb levels did not have an elevated prevalence of bare soil Pb hazards compared with other counties (P = .64). CONCLUSIONS: Site investigators should anticipate finding and managing elevated bare soil Pb in locations throughout Ohio. When communicating with the public about bare soil Pb hazards, practitioners and policy makers should emphasize the importance of addressing all potential Pb exposure sources. Findings demonstrate the importance of the individual home environment for exposure, as previously identified high-risk counties for elevated blood Pb levels were not different from other counties.

A novel approach to analyzing lung cancer mortality disparities: Using the exposome and a graph-theoretical toolchain.

OBJECTIVES: The aim is to identify exposures associated with lung cancer mortality and mortality disparities by race and gender using an exposome database coupled to a graph theoretical toolchain. METHODS: Graph theoretical algorithms were employed to extract paracliques from correlation graphs using associations between 2162 environmental exposures and lung cancer mortality rates in 2067 counties, with clique doubling applied to compute an absolute threshold of significance. Factor analysis and multiple linear regressions then were used to analyze differences in exposures associated with lung cancer mortality and mortality disparities by race and gender. RESULTS: While cigarette consumption was highly correlated with rates of lung cancer mortality for both white men and women, previously unidentified novel exposures were more closely associated with lung cancer mortality and mortality disparities for blacks, particularly black women. CONCLUSIONS: Exposures beyond smoking moderate lung cancer mortality and mortality disparities by race and gender. POLICY IMPLICATIONS: An exposome approach and database coupled with scalable combinatorial analytics provides a powerful new approach for analyzing relationships between multiple environmental exposures, pathways and health outcomes. An assessment of multiple exposures is needed to appropriately translate research findings into environmental public health practice and policy.

Active Use of Electronic Health Records (EHRs) and Personal Health Records (PHRs) for Epidemiologic Research: Sample Representativeness and Nonresponse Bias in a Study of Women During Pregnancy.

INTRODUCTION: With the growing use of electronic medical records, electronic health records (EHRs), and personal health records (PHRs) for health care delivery, new opportunities have arisen for population health researchers. Our objective was to characterize PHR users and examine sample representativeness and nonresponse bias in a study of pregnant women recruited via the PHR. DESIGN: Demographic characteristics were examined for PHR users and nonusers. Enrolled study participants (responders, n=187) were then compared with nonresponders and a representative sample of the target population. RESULTS: PHR patient portal users (34 percent of eligible persons) were older and more likely to be White, have private health insurance, and develop gestational diabetes than nonusers. Of eligible persons (all PHR users), 11 percent (187/1,713) completed a self-administered PHR based questionnaire. Participants in the research study were more likely to be non-Hispanic White (90 percent versus 79 percent) and married (85 percent versus 77 percent), and were less likely to be Non-Hispanic Black (3 percent versus 12 percent) or Hispanic (3 percent versus 6 percent). Responders and nonresponders were similar regarding age distribution, employment status, and health insurance status. Demographic characteristics were similar between responders and nonresponders. DISCUSSION: Demographic characteristics of the study population differed from the general population, consistent with patterns seen in traditional population-based studies. The PHR may be an efficient method for recruiting and conducting observational research with additional benefits of efficiency and cost-cost-effectiveness.

Validation of research trajectory 1 of an Exposome framework: Exposure to benzo(a)pyrene confers enhanced susceptibility to bacterial infection.

The exposome provides a framework for understanding elucidation of an uncharacterized molecular mechanism conferring enhanced susceptibility of macrophage membranes to bacterial infection after exposure to the environmental contaminant benzo(a)pyrene, [B(a)P]. The fundamental requirement in activation of macrophage effector functions is the binding of immunoglobulins to Fc receptors. FcγRIIa (CD32a), a member of the Fc family of immunoreceptors with low affinity for immunoglobulin G, has been reported to bind preferentially to IgG within lipid rafts. Previous research suggested that exposure to B(a)P suppressed macrophage effector functions but the molecular mechanisms remain elusive. The goal of this study was to elucidate the mechanism(s) of B(a)P-exposure induced suppression of macrophage function by examining the resultant effects of exposure-induced insult on CD32-lipid raft interactions in the regulation of IgG binding to CD32. The results demonstrate that exposure of macrophages to B(a)P alters lipid raft integrity by decreasing membrane cholesterol 25% while increasing CD32 into non-lipid raft fractions. This robust diminution in membrane cholesterol and 30% exclusion of CD32 from lipid rafts causes a significant reduction in CD32-mediated IgG binding to suppress essential macrophage effector functions. Such exposures across the lifespan would have the potential to induce immunosuppressive endophenotypes in vulnerable populations.

Revealing Behavioral Learning Deficit Phenotypes Subsequent to In Utero Exposure to Benzo(a)pyrene.

To characterize behavioral deficits in pre-adolescent offspring exposed in utero to Benzo(a)pyrene [B(a)P], timed-pregnant Long Evans Hooded rats were treated with B(a)P (150, 300, 600, and 1200 µg/kg BW) or peanut oil (vehicle) on E14, 15, 16, and 17. Following birth, during the pre-weaning period, B(a)P metabolites were examined in plasma and whole brain or cerebral cortex from exposed and control offspring. Tissue concentrations of B(a)P metabolites were (1) dose-dependent and (2) followed a time-dependence for elimination with ∼60% reduction by PND5 in the 1200 µg/kg BW experimental group. Spatial discrimination-reversal learning was utilized to evaluate potential behavioral neurotoxicity in P40-P60 offspring. Late-adolescent offspring exposed in utero to 600 and 1200 µg/kg BW were indistinguishable from their control counterparts for ability to acquire an original discrimination (OD) and reach criterion. However, a dose-dependent effect of in utero B(a)P-exposure was evident upon a discrimination reversal as exposed offspring perseverated on the previously correct response. This newly characterized behavioral deficit phenotype for the first reversal was not apparent in either the (1) OD or (2) subsequent reversal sessions relative to the respective control offspring. Furthermore, the expression of activity related-cytoskeletal-associated protein (Arc), an experience-dependent cortical protein marker known to be up-regulated in response to acquisition of a novel behavior, was greater in B(a)P-exposed offspring included in the spatial discrimination cohort versus home cage controls. Collectively, these findings support the hypothesis that in utero exposure to B(a)P during critical windows of development representing peak periods of neurogenesis results in behavioral deficits in later life.