SPH Environmental Health Papers and Presentations

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Neuroimaging markers for studying Gulf-War illness: single-subject level analytical method based on machine learning
(2020-11-20) Guan, Yi; Cheng, Chia-Hsin; Chen, Weifan; Zhang, Yingqi; Koo, Sophia; Krengel, Maxine; Janulewicz, Patricia; Toomey, Rosemary; Yang, Ehwa; Bhadelia, Rafeeque; Steele, Lea; Kim, Jae-Hun; Sullivan, Kimberly; Koo, Bang-Bon
Gulf War illness (GWI) refers to the multitude of chronic health symptoms, spanning from fatigue, musculoskeletal pain, and neurological complaints to respiratory, gastrointestinal, and dermatologic symptoms experienced by about 250,000 GW veterans who served in the 1991 Gulf War (GW). Longitudinal studies showed that the severity of these symptoms often remain unchanged even years after the GW, and these veterans with GWI continue to have poorer general health and increased chronic medical conditions than their non-deployed counterparts. For better management and treatment of this condition, there is an urgent need for developing objective biomarkers that can help with simple and accurate diagnosis of GWI. In this study, we applied multiple neuroimaging techniques, including T1-weighted magnetic resonance imaging (T1W-MRI), diffusion tensor imaging (DTI), and novel neurite density imaging (NDI) to perform both a group-level statistical comparison and a single-subject level machine learning (ML) analysis to identify diagnostic imaging features of GWI. Our results supported NDI as the most sensitive in defining GWI characteristics. In particular, our classifier trained with white matter NDI features achieved an accuracy of 90% and F-score of 0.941 for classifying GWI cases from controls after the cross-validation. These results are consistent with our previous study which suggests that NDI measures are sensitive to the microstructural and macrostructural changes in the brain of veterans with GWI, which can be valuable for designing better diagnosis method and treatment efficacy studies.
The Impact of Contract Operations on Safety in Underground Coal Mines
(Wolters Kluwer, 2016-09) Buessing, Marric Grace; Boden, Leslie
OBJECTIVE: The aim of this study was to test for differences in injury rates for contractor-operated underground coal mines relative to owner-operated mines in Kentucky, controlling for other covariates. METHODS: We used disparities between MSHA contractor data and surface reclamation permit data to identify mines operated by contractors. We then used negative binomial regression to estimate injury rates from 1999 to 2013, controlling for mine and controller characteristics available from MSHA and the Energy Information Administration (EIA). RESULTS: Contractor-operated mines with 15 or fewer full-time equivalent workers (FTEs) had a statistically significant 57% higher covariate-adjusted reported traumatic injury rate than similar mines without contract operators. Larger contractor-operated mines did not have a statistically significant elevated rate. CONCLUSIONS: We detected a significant elevation of traumatic injury rates only among the smallest contractor-operated mines. This increase appears substantial enough to warrant attention.
Tools for Addressing Cumulative Impacts on Human Health and the Environment
(Mary Ann Liebert, 2014) Scammell, Madeleine Kangsen; Montague, Peter; Raffensperger, Carolyn
"Cumulative impacts" refers to the total harm to human health and the environment resulting from combinations of stressors over time. Cumulative impacts are creating three kinds of effects: degraded ecosystems (such as oceans and boreal forests), human diseases, and disproportionately burdened communities, which are the hallmark of environmental injustice. At the heart of the problem lie the modern risk-based regulatory systems of the U.S. and Europe, which are not designed to understand or manage cumulative impacts, and which have permitted an accumulation of harmful activities and effects. Alternative, precautionary regulatory approaches have been recommended but not yet widely implemented. Now some communities, planners and regulators are finding ways to supplement traditional risk-based approaches, using innovative new tools for assessment and decision-making in the face of cumulative impacts, including indexes, mapping, and screening. These efforts both inform policy and serve as exemplary models. Together they point the way toward new, precautionary decision structures aimed at reducing cumulative impacts.
Genetic and Epigenetic Somatic Alterations in Head and Neck Squamous Cell Carcinomas Are Globally Coordinated but Not Locally Targeted
(Public Library of Science, 2010-3-11) Poage, Graham M.; Christensen, Brock C.; Houseman, E. Andres; McClean, Michael D.; Wiencke, John K.; Posner, Marshall R.; Clark, John R.; Nelson, Heather H.; Marsit, Carmen J.; Kelsey, Karl T.
BACKGROUND. Solid tumors, including head and neck squamous cell carcinomas (HNSCC), arise as a result of genetic and epigenetic alterations in a sustained stress environment. Little work has been done that simultaneously examines the spectrum of both types of changes in human tumors on a genome-wide scale and results so far have been limited and mixed. Since it has been hypothesized that epigenetic alterations may act by providing the second carcinogenic hit in gene silencing, we sought to identify genome-wide DNA copy number alterations and CpG dinucleotide methylation events and examine the global/local relationships between these types of alterations in HNSCC. METHODOLOGY/PRINCIPAL FINDINGS. We have extended a prior analysis of 1,413 cancer-associated loci for epigenetic changes in HNSCC by integrating DNA copy number alterations, measured at 500,000 polymorphic loci, in a case series of 19 primary HNSCC tumors. We have previously demonstrated that local copy number does not bias methylation measurements in this array platform. Importantly, we found that the global pattern of copy number alterations in these tumors was significantly associated with tumor methylation profiles (p<0.002). However at the local level, gene promoter regions did not exhibit a correlation between copy number and methylation (lowest q=0.3), and the spectrum of genes affected by each type of alteration was unique. CONCLUSION/SIGNIFICANCE. This work, using a novel and robust statistical approach demonstrates that, although a "second hit" mechanism is not likely the predominant mode of action for epigenetic dysregulation in cancer, the patterns of methylation events are associated with the patterns of allele loss. Our work further highlights the utility of integrative genomics approaches in exploring the driving somatic alterations in solid tumors.
Growth of a Human Mammary Tumor Cell Line Is Blocked by Galangin, a Naturally Occurring Bioflavonoid, and Is Accompanied by Down-Regulation of Cyclins D3, E, and A
(BioMed Central, 2006-3-27) Murray, Tessa J; Yang, Xinhai; Sherr, David H
INTRODUCTION. This study was designed to determine if and how a non-toxic, naturally occurring bioflavonoid, galangin, affects proliferation of human mammary tumor cells. Our previous studies demonstrated that, in other cell types, galangin is a potent inhibitor of the aryl hydrocarbon receptor (AhR), an environmental carcinogen-responsive transcription factor implicated in mammary tumor initiation and growth control. Because some current breast cancer therapeutics are ineffective in estrogen receptor (ER) negative tumors and since the AhR may be involved in breast cancer proliferation, the effects of galangin on the proliferation of an ER-, AhRhigh line, Hs578T, were studied. METHODS. AhR expression and function in the presence or absence of galangin, a second AhR inhibitor, α-naphthoflavone (α-NF), an AhR agonist, indole-3-carbinol, and a transfected AhR repressor-encoding plasmid (FhAhRR) were studied in Hs578T cells by western blotting for nuclear (for instance, constitutively activated) AhR and by transfection of an AhR-driven reporter construct, pGudLuc. The effects of these agents on cell proliferation were studied by 3H-thymidine incorporation and by flow cytometry. The effects on cyclins implicated in mammary tumorigenesis were evaluated by western blotting. RESULTS. Hs578T cells were shown to express high levels of constitutively active AhR. Constitutive and environmental chemical-induced AhR activity was profoundly suppressed by galangin as was cell proliferation. However, the failure of α-NF or FhAhRR transfection to block proliferation indicated that galangin-mediated AhR inhibition was either insufficient or unrelated to its ability to significantly block cell proliferation at therapeutically relevant doses (IC50 = 11 μM). Galangin inhibited transition of cells from the G0/G1 to the S phases of cell growth, likely through the nearly total elimination of cyclin D3. Expression of cyclins A and E was also suppressed. CONCLUSION. Galangin is a strong inhibitor of Hs578T cell proliferation that likely mediates this effect through a relatively unique mechanism, suppression of cyclin D3, and not through the AhR. The results suggest that this non-toxic bioflavonoid may be useful as a chemotherapeutic, particularly in combination with agents that target other components of the tumor cell cycle and in situations where estrogen receptor-specific therapeutics are ineffective.
The Latino Health Insurance Program: A Pilot Intervention for Enrolling Latino Families in Health Insurance Programs, East Boston, Massachusetts, 2006-2007
(Centers for Disease Control and Prevention, 2009-9-15) Abreu, Milagros; Hynes, H. Patricia
BACKGROUND. Thirteen percent of Latinos in Massachusetts lack health insurance, the highest rate of any ethnic or racial group. Families without health insurance are more likely to be in poor or fair health, to lack a regular medical provider, and to not have visited a medical provider in the past year. CONTEXT. The Latino Health Insurance Program is designed as a response both to the high rate of uninsurance among Latinos in Boston and to the multiple obstacles that keep Latino parents from applying for insurance for their families. METHODS. In 2006, we designed and implemented a culturally competent model of health insurance outreach, education, enrollment and maintenance, and referral for primary care and social services for Latino families. CONSEQUENCES. Year 1 results of the Latino Health Insurance Program are promising. Six community members were hired and trained as case managers. A total of 230 children and adults were enrolled or re-enrolled in health insurance programs and received other needed services. Retention was near 100% after 1 year. INTERPRETATION. The Latino Health Insurance Program may serve as a model health insurance access program that can be adapted by community-based organizations and also can be incorporated into public agency programs for Latinos and other immigrant and minority groups. The program continues to serve East Boston residents and was expanded in 2008.
Assessment of Neuropsychological Trajectories in Longitudinal Population-Based Studies of Children
(BMJ Publishing Group, 2008-12-5) White, R. F.; Campbell, R.; Echeverria, D.; Knox, S. S.; Janulewicz, P.
This paper provides a strategy for the assessment of brain function in longitudinal cohort studies of children. The proposed strategy invokes both domain-specific and omnibus intelligence test approaches. In order to minimise testing burden and practice effects, the cohort is divided into four groups with one-quarter tested at 6-monthly intervals in the 0–2-year age range (at ages 6 months, 1.0, 1.5 and 2.0 years) and at annual intervals from ages 3–20 (one-quarter of the children at age 3, another at age 4, etc). This strategy allows investigation of cognitive development and of the relationship between environmental influences and development at each age. It also allows introduction of new domains of function when age-appropriate. As far as possible, tests are used that will provide a rich source of both longitudinal and cross-sectional data. The testing strategy allows the introduction of novel tests and new domains as well as piloting of tests when the test burden is relatively light. In addition to the recommended tests for each age and domain, alternative tests are described. Assessment methodology and knowledge about child cognitive development will change over the next 20 years, and strategies are suggested for altering the proposed test schedule as appropriate.
A power comparison of generalized additive models and the spatial scan statistic in a case-control setting
(2010-7-19) Young, Robin L.; Weinberg, Janice; Vieira, Verónica; Ozonoff, Al; Webster, Thomas F.
BACKGROUND. A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. RESULTS. This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. CONCLUSIONS. The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic.
Spatial analysis of learning and developmental disorders in upper Cape Cod, Massachusetts using generalized additive models
(BioMed Central, 2010-2-12) Hoffman, Kate; Webster, Thomas F.; Weinberg, Janice M.; Aschengrau, Ann; Janulewicz, Patricia A.; White, Roberta F.; Vieira, Verónica M.
The spatial variability of three indicators of learning and developmental disability (LDD) was assessed for Cape Cod, Massachusetts. Maternal reports of receiving special education services, attention deficit hyperactivity disorder, and educational attainment were available for a birth cohort from 1969-1983. Using generalized additive models and residential history, maps of the odds of LDD were produced that also controlled for known risk factors. While results were not statistically significant, they suggest that children living in certain parts of Cape Cod were more likely to have a LDD. The spatial variation may be due to variation in the physical and social environment.
A multilevel non-hierarchical study of birth weight and socioeconomic status
(BioMed Central, 2010-7-9) Young, Robin L.; Weinberg, Janice; Vieira, Verónica; Aschengrau, Ann; Webster, Thomas F.
BACKGROUND. It is unclear whether the socioeconomic status (SES) of the community of residence has a substantial association with infant birth weight. We used multilevel models to examine associations of birth weight with family- and community-level SES in the Cape Cod Family Health Study. Data were collected retrospectively on births to women between 1969 and 1983 living on Cape Cod, Massachusetts. The sample included siblings born in different residences with differing community-level SES. METHODS. We used cross-classified models to account for multiple levels of correlation in a non-hierarchical data structure. We accounted for clustering at family- and community-levels. Models included extensive individual- and family-level covariates. SES variables of interest were maternal education; paternal occupation; percent adults living in poverty; percent adults with a four year college degree; community mean family income; and percent adult unemployment. RESULTS. Residual correlation was detected at the family- but not the community-level. Substantial effects sizes were observed for family-level SES while smaller magnitudes were observed for community-level SES. Overall, higher SES corresponded to increased birth weight though neither family- nor community-level variables had significant associations with the outcome. In a model applied to a reduced sample that included a single child per family, enforcing a hierarchical data structure, paternal occupation was found to have a significant association with birth weight (p = 0.033). Larger effect sizes for community SES appeared in models applied to the full sample that contained limited covariates, such as those typically found on birth certificates. CONCLUSIONS. Cross-classified models allowed us to include more than one child per family even when families moved between births. There was evidence of mild associations between family SES and birth weight. Stronger associations between paternal occupation and birth weight were observed in models applied to reduced samples with hierarchical data structures, illustrating consequences of excluding observations from the cross-classified analysis. Models with limited covariates showed associations of birth weight with community SES. In models adjusting for a complete set of individual- and family-level covariates, community SES was not as important.
Spatial-temporal analysis of breast cancer in upper Cape Cod, Massachusetts
(BioMed Central, 2008-8-13) Vieira, Verónica M.; Webster, Thomas F.; Weinberg, Janice M.; Aschengrau, Ann
INTRODUCTION. The reasons for elevated breast cancer rates in the upper Cape Cod area of Massachusetts remain unknown despite several epidemiological studies that investigated possible environmental risk factors. Data from two of these population-based case-control studies provide geocoded residential histories and information on confounders, creating an invaluable dataset for spatial-temporal analysis of participants' residency over five decades. METHODS. The combination of statistical modeling and mapping is a powerful tool for visualizing disease risk in a spatial-temporal analysis. Advances in geographic information systems (GIS) enable spatial analytic techniques in public health studies previously not feasible. Generalized additive models (GAMs) are an effective approach for modeling spatial and temporal distributions of data, combining a number of desirable features including smoothing of geographical location, residency duration, or calendar years; the ability to estimate odds ratios (ORs) while adjusting for confounders; selection of optimum degree of smoothing (span size); hypothesis testing; and use of standard software. We conducted a spatial-temporal analysis of breast cancer case-control data using GAMs and GIS to determine the association between participants' residential history during 1947–1993 and the risk of breast cancer diagnosis during 1983–1993. We considered geographic location alone in a two-dimensional space-only analysis. Calendar year, represented by the earliest year a participant lived in the study area, and residency duration in the study area were modeled individually in one-dimensional time-only analyses, and together in a two-dimensional time-only analysis. We also analyzed space and time together by applying a two-dimensional GAM for location to datasets of overlapping calendar years. The resulting series of maps created a movie which allowed us to visualize changes in magnitude, geographic size, and location of elevated breast cancer risk for the 40 years of residential history that was smoothed over space and time. RESULTS. The space-only analysis showed statistically significant increased areas of breast cancer risk in the northern part of upper Cape Cod and decreased areas of breast cancer risk in the southern part (p-value = 0.04; ORs: 0.90–1.40). There was also a significant association between breast cancer risk and calendar year (p-value = 0.05; ORs: 0.53–1.38), with earlier calendar years resulting in higher risk. The results of the one-dimensional analysis of residency duration and the two-dimensional analysis of calendar year and duration showed that the risk of breast cancer increased with increasing residency duration, but results were not statistically significant. When we considered space and time together, the maps showed a large area of statistically significant elevated risk for breast cancer near the Massachusetts Military Reservation (p-value range:0.02–0.05; ORs range: 0.25–2.5). This increased risk began with residences in the late 1940s and remained consistent in size and location through the late 1950s. CONCLUSION. Spatial-temporal analysis of the breast cancer data may help identify new exposure hypotheses that warrant future epidemiologic investigations with detailed exposure models. Our methods allow us to visualize breast cancer risk, adjust for known confounders including age at diagnosis or index year, family history of breast cancer, parity and age at first live- or stillbirth, and test for the statistical significance of location and time. Despite the advantages of GAMs, analyses are for exploratory purposes and there are still methodological issues that warrant further research. This paper illustrates that GAM methods are a suitable alternative to widely-used cluster detection methods and may be preferable when residential histories from existing epidemiological studies are available.
Method for Mapping Population-Based Case-Control Studies: An Application Using Generalized Additive Models
(BioMed Central, 2006-6-9) Webster, Thomas; Vieira, Verónica; Weinberg, Janice; Aschengrau, Ann
BACKGROUND. Mapping spatial distributions of disease occurrence and risk can serve as a useful tool for identifying exposures of public health concern. Disease registry data are often mapped by town or county of diagnosis and contain limited data on covariates. These maps often possess poor spatial resolution, the potential for spatial confounding, and the inability to consider latency. Population-based case-control studies can provide detailed information on residential history and covariates. RESULTS. Generalized additive models (GAMs) provide a useful framework for mapping point-based epidemiologic data. Smoothing on location while controlling for covariates produces adjusted maps. We generate maps of odds ratios using the entire study area as a reference. We smooth using a locally weighted regression smoother (loess), a method that combines the advantages of nearest neighbor and kernel methods. We choose an optimal degree of smoothing by minimizing Akaike's Information Criterion. We use a deviance-based test to assess the overall importance of location in the model and pointwise permutation tests to locate regions of significantly increased or decreased risk. The method is illustrated with synthetic data and data from a population-based case-control study, using S-Plus and ArcView software. CONCLUSION. Our goal is to develop practical methods for mapping population-based case-control and cohort studies. The method described here performs well for our synthetic data, reproducing important features of the data and adequately controlling the covariate. When applied to the population-based case-control data set, the method suggests spatial confounding and identifies statistically significant areas of increased and decreased odds ratios.
Epidemiologic Approaches to Assessing Human Cancer Risk from Consuming Aquatic Food Resources from Chemically Contaminated Water
(National Institute of Environmental Health Sciences, 1991) Ozonoff, D; Longnecker, M P
Epidemiologic approaches to assessing human cancer risk from consuming fish from contaminated waters must confront the problems of long latency and rarity of the end point (cancer). The latency problem makes determination of diet history more difficult, while the low frequency of cancer as an end point reduces the statistical power of the study. These factors are discussed in relation to the study designs most commonly employed in epidemiology. It is suggested that the use of biomarkers for persistent chemicals may be useful to mitigate the difficulty of determining exposure, while the use of more prevalent and timely end points, such as carcinogen-DNA adducts or oncogene proteins, may make the latency and rarity problems more tractable.
Qualitative Environmental Health Research: An Analysis of the Literature, 1991-2008
(National Institute of Environmental Health Sciences, 2010-08) Scammell, Madeleine Kangsen
BACKGROUND. Recent articles have advocated for the use of qualitative methods in environmental health research. Qualitative research uses nonnumeric data to understand people's opinions, motives, understanding, and beliefs about events or phenomena. OBJECTIVE. In this analysis of the literature, I report the use of qualitative methods and data in the study of the relationship between environmental exposures and human health. DATA SOURCES. A primary search on ISI Web of Knowledge/Web of Science for peer-reviewed journal articles dated from 1991 through 2008 included the following three terms: qualitative, environ*, and health. Inclusion and exclusion criteria are described. DATA EXTRACTION. Searches resulted in 3,155 records. Data were extracted and findings of articles analyzed to determine where and by whom qualitative environmental health research is conducted and published, the types of methods and analyses used in qualitative studies of environmental health, and the types of information qualitative data contribute to environmental health. DATA SYNTHESIS. Ninety-one articles met inclusion criteria. These articles were published in 58 different journals, with a maximum of eight for a single journal. The results highlight a diversity of disciplines and techniques among researchers who used qualitative methods to study environmental health, with most studies relying on one-on-one interviews. Details of the analyses were absent from a large number of studies. Nearly all of the studies identified increased scientific understanding of lay perceptions of environmental health exposures. DISCUSSION AND CONCLUSIONS. Qualitative data are published in traditionally quantitative environmental health studies to a limited extent. However, this analysis demonstrates the potential of qualitative data to improve understanding of complex exposure pathways, including the influence of social factors on environmental health, and health outcomes.
Association between Residences in U.S. Northern Latitudes and Rheumatoid Arthritis: A Spatial Analysis of the Nurses' Health Study
(National Institute of Environmental Health Sciences, 2010-07) Vieira, Verónica M.; Hart, Jaime E.; Webster, Thomas F.; Weinberg, Janice; Puett, Robin; Laden, Francine; Costenbader, Karen H.; Karlson, Elizabeth W.
BACKGROUND. The etiology of rheumatoid arthritis (RA) remains largely unknown, although epidemiologic studies suggest genetic and environmental factors may play a role. Geographic variation in incident RA has been observed at the regional level. OBJECTIVE. Spatial analyses are a useful tool for confirming existing exposure hypotheses or generating new ones. To further explore the association between location and RA risk, we analyzed individual-level data from U.S. women in the Nurses' Health Study, a nationwide cohort study. METHODS. Participants included 461 incident RA cases and 9,220 controls with geocoded addresses; participants were followed from 1988 to 2002. We examined spatial variation using addresses at baseline in 1988 and at the time of case diagnosis or the censoring of controls. Generalized additive models (GAMs) were used to predict a continuous risk surface by smoothing on longitude and latitude while adjusting for known risk factors. Permutation tests were conducted to evaluate the overall importance of location and to identify, within the entire study area, those locations of statistically significant risk. RESULTS. A statistically significant area of increased RA risk was identified in the northeast United States (p-value = 0.034). Risk was generally higher at northern latitudes, and it increased slightly when we used the nurses' 1988 locations compared with those at the time of diagnosis or censoring. Crude and adjusted models produced similar results. CONCLUSIONS. Spatial analyses suggest women living in higher latitudes may be at greater risk for RA. Further, RA risk may be greater for locations that occur earlier in residential histories. These results illustrate the usefulness of GAM methods in generating hypotheses for future investigation and supporting existing hypotheses.
San Antonio Statement on Brominated and Chlorinated Flame Retardants
(National Institute of Environmental Health Sciences, 2010-12) DiGangi, Joseph; Blum, Arlene; Bergman, Åke; de Wit, Cynthia A.; Lucas, Donald; Mortimer, David; Schecter, Arnold; Scheringer, Martin; Shaw, Susan D.; Webster, Thomas F.
Exposure to Polyfluoroalkyl Chemicals and Cholesterol, Body Weight, and Insulin Resistance in the General U.S. Population
(National Institute of Environmental Health Sciences, 2010-02) Nelson, Jessica W.; Hatch, Elizabeth E.; Webster, Thomas F.
BACKGROUND. Polyfluoroalkyl chemicals (PFCs) are used commonly in commercial applications and are detected in humans and the environment worldwide. Concern has been raised that they may disrupt lipid and weight regulation. OBJECTIVES. We investigated the relationship between PFC serum concentrations and lipid and weight outcomes in a large publicly available data set. METHODS. We analyzed data from the 2003-2004 National Health and Nutrition Examination Survey (NHANES) for participants 12-80 years of age. Using linear regression to control for covariates, we studied the association between serum concentrations of perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctane sulfonic acid (PFOS), and perfluorohexane sulfonic acid (PFHxS) and measures of cholesterol, body size, and insulin resistance. RESULTS. We observed a positive association between concentrations of PFOS, PFOA, and PFNA and total and non-high-density cholesterol. We found the opposite for PFHxS. Those in the highest quartile of PFOS exposure had total cholesterol levels 13.4 mg/dL [95% confidence interval (CI), 3.8-23.0] higher than those in the lowest quartile. For PFOA, PFNA, and PFHxS, effect estimates were 9.8 (95% CI, -0.2 to 19.7), 13.9 (95% CI, 1.9-25.9), and -7.0 (95% CI, -13.2 to -0.8), respectively. A similar pattern emerged when exposures were modeled continuously. We saw little evidence of a consistent association with body size or insulin resistance. CONCLUSIONS. This exploratory cross-sectional study is consistent with other epidemiologic studies in finding a positive association between PFOS and PFOA and cholesterol, despite much lower exposures in NHANES. Results for PFNA and PFHxS are novel, emphasizing the need to study PFCs other than PFOS and PFOA.
Using Residential History and Groundwater Modeling to Examine Drinking Water Exposure and Breast Cancer
(National Institute of Environmental Health Sciences, 2010-06) Gallagher, Lisa G.; Webster, Thomas F.; Aschengrau, Ann; Vieira, Verónica M.
BACKGROUND. Spatial analyses of case-control data have suggested a possible link between breast cancer and groundwater plumes in upper Cape Cod, Massachusetts. OBJECTIVE. We integrated residential histories, public water distribution systems, and groundwater modeling within geographic information systems (GIS) to examine the association between exposure to drinking water that has been contaminated by wastewater effluent and breast cancer. METHODS. Exposure was assessed from 1947 to 1993 for 638 breast cancer cases who were diagnosed from 1983 to 1993 and 842 controls; we took into account residential mobility and drinking water source. To estimate the historical impact of effluent on drinking water wells, we modified a modular three-dimensional finite-difference groundwater model (MODFLOW) from the U.S. Geological Survey. The analyses included latency and exposure duration. RESULTS. Wastewater effluent impacted the drinking water wells of study participants as early as 1966. For > 0-5 years of exposure (versus no exposure), associations were generally null. Adjusted odds ratios (AORs) for > 10 years of exposure were slightly increased, assuming latency periods of 0 or 10 years [AOR = 1.3; 95% confidence interval (CI), 0.9-1.9 and AOR = 1.6; 95% CI, 0.8-3.2, respectively]. Statistically significant associations were estimated for ever-exposed versus never-exposed women when a 20-year latency period was assumed (AOR = 1.9; 95% CI, 1.0-3.4). A sensitivity analysis that classified exposures assuming lower well-pumping rates showed similar results. CONCLUSION. We investigated the hypothesis generated by earlier spatial analyses that exposure to drinking water contaminated by wastewater effluent may be associated with breast cancer. Using a detailed exposure assessment, we found an association with breast cancer that increased with longer latency and greater exposure duration.
Exposure to Polyfluoroalkyl Chemicals and Attention Deficit/Hyperactivity Disorder in U.S. Children 12-15 Years of Age
(National Institute of Environmental Health Sciences, 2010-12) Hoffman, Kate; Webster, Thomas F.; Weisskopf, Marc G.; Weinberg, Janice; Vieira, Verónica M.
BACKGROUND. Polyfluoroalkyl chemicals (PFCs) have been widely used in consumer products. Exposures in the United States and in world populations are widespread. PFC exposures have been linked to various health impacts, and data in animals suggest that PFCs may be potential developmental neurotoxicants. OBJECTIVES. We evaluated the associations between exposures to four PFCs and parental report of diagnosis of attention deficit/hyperactivity disorder (ADHD). METHODS. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999-2000 and 2003-2004 for children 12-15 years of age. Parental report of a previous diagnosis by a doctor or health care professional of ADHD in the child was the primary outcome measure. Perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS) levels were measured in serum samples from each child. RESULTS. Parents reported that 48 of 571 children included in the analysis had been diagnosed with ADHD. The adjusted odds ratio (OR) for parentally reported ADHD in association with a 1-μg/L increase in serum PFOS (modeled as a continuous predictor) was 1.03 [95% confidence interval (CI), 1.01-1.05]. Adjusted ORs for 1-μg/L increases in PFOA and PFHxS were also statistically significant (PFOA: OR = 1.12; 95% CI, 1.01-1.23; PFHxS: OR = 1.06; 95% CI, 1.02-1.11), and we observed a nonsignificant positive association with PFNA (OR = 1.32; 95% CI, 0.86-2.02). CONCLUSIONS. Our results, using cross-sectional data, are consistent with increased odds of ADHD in children with higher serum PFC levels. Given the extremely prevalent exposure to PFCs, follow-up of these data with cohort studies is needed.
Generalized concentration addition predicts joint effects of aryl hydrocarbon receptor agonists with partial agonists and competitive antagonists
(National Institute of Environmental Health Sciences, 2010-05) Howard, Gregory J.; Schlezinger, Jennifer J.; Hahn, Mark E.; Webster, Thomas F.
BACKGROUND. Predicting the expected outcome of a combination exposure is critical to risk assessment. The toxic equivalency factor (TEF) approach used for analyzing joint effects of dioxin-like chemicals is a special case of the method of concentration addition. However, the TEF method assumes that individual agents are full aryl hydrocarbon receptor (AhR) agonists with parallel dose-response curves, whereas many mixtures include partial agonists. OBJECTIVES. We assessed the ability of generalized concentration addition (GCA) to predict effects of combinations of full AhR agonists with partial agonists or competitive antagonists. METHODS. We measured activation of AhR-dependent gene expression in H1G1.1c3 cells after application of binary combinations of AhR ligands. A full agonist (2,3,7,8-tetrachlorodibenzo-p-dioxin or 2,3,7,8-tetrachlorodibenzofuran) was combined with either a full agonist (3,3',4,4',5-pentachlorobiphenyl), a partial agonist (2,3,3',4,4'-pentachlorobiphenyl or galangin), or an antagonist (3,3'-diindolylmethane). Combination effects were modeled by the TEF and GCA approaches, and goodness of fit of the modeled response surface to the experimental data was assessed using a nonparametric statistical test. RESULTS. The GCA and TEF models fit the experimental data equally well for a mixture of two full agonists. In all other cases, GCA fit the experimental data significantly better than the TEF model. CONCLUSIONS. The TEF model overpredicts effects of AhR ligands at the highest concentration combinations. At lower concentrations, the difference between GCA and TEF approaches depends on the efficacy of the partial agonist. GCA represents a more accurate definition of additivity for mixtures that include partial agonist or competitive antagonist ligands.

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