Verónica M. Vieira

The C8 Health Project: Design, Methods, and Participants

Background The C8 Health Project was created, authorized, and funded as part of the settlement agreement reached in the case of Jack W. Leach, et al. v. E.I. du Pont de Nemours & Company (no. 01-C-608 W.Va., Wood County Circuit Court, filed 10 April 2002). The settlement stemmed from the perfluorooctanoic acid (PFOA, or C8) contamination of drinking water in six water districts in two states near the DuPont Washington Works facility near Parkersburg, West Virginia. Objectives This study reports on the methods and results from the C8 Health Project, a population study created to gather data that would allow class members to know their own PFOA levels and permit subsequent epidemiologic investigations. Methods Final study participation was 69,030, enrolled over a 13-month period in 2005–2006. Extensive data were collected, including demographic data, medical diagnoses (both self-report and medical records review), clinical laboratory testing, and determination of serum concentrations of 10 perfluorocarbons (PFCs). Here we describe the processes used to collect, validate, and store these health data. We also describe survey participants and their serum PFC levels. Results The population geometric mean for serum PFOA was 32.91 ng/mL, 500% higher than previously reported for a representative American population. Serum concentrations for perfluorohexane sulfonate and perfluorononanoic acid were elevated 39% and 73% respectively, whereas perfluorooctanesulfonate was present at levels similar to those in the U.S. population. Conclusions This largest known population study of community PFC exposure permits new evaluations of associations between PFOA, in particular, and a range of health parameters. These will contribute to understanding of the biology of PFC exposure. The C8 Health Project also represents an unprecedented effort to gather basic data on an exposed population; its achievements and limitations can inform future legal settlements for populations exposed to environmental contaminants.

Exposure to Polyfluoroalkyl Chemicals and Attention Deficit/Hyperactivity Disorder in U.S. Children 12–15 Years of Age

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.

Predictors of PFOA Levels in a Community Surrounding a Chemical Plant

Background Perfluorooctanoic acid (PFOA) is considered a probable human carcinogen by the U.S. Environmental Protection Agency. It does not exist in nature but has been used widely since World War II. It is present in the serum of most Americans at about 4–5 ng/mL, although the routes of exposure remain unknown. Objectives We examined predictors of PFOA in mid-Ohio Valley residents living near a chemical plant that until recently released large quantities of PFOA into the environment, contaminating drinking water. Methods We studied 69,030 residents in six contaminated water districts who participated in a 2005–2006 survey involving a questionnaire and blood tests. Of these, 64,251 had complete data on PFOA and covariates. We also analyzed a subset (71%) for whom we had occupational history. We ran linear regression models to determine serum PFOA predictors. Results Mean PFOA serum level was 83.0 ng/mL (median, 28.2). The most important predictors were current (median for all districts, 38.4; highest district, 224.1) and past (median, 18.6) residence in contaminated water districts, and current (median, 147.8) and past (median, 74.9) employment at the chemical plant (R2 model = 0.55). PFOA was higher for males, those consuming local vegetables, and those using well water rather than public water, and lower for those using bottled water. PFOA was higher at younger and older ages. Conclusions PFOA levels in this population varied with distance of residence from the plant and employment at the plant. Effects of age and sex reflected prior findings. Effects of other demographic and lifestyle covariates were relatively weak.

Method for mapping population-based case-control studies: an application using generalized additive models

BackgroundMapping 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.ResultsGeneralized 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 Akaikes 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.ConclusionOur 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.

Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: An application of generalized additive models to case-control data

BackgroundThe availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed.MethodsWe investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA) using extensive data on covariates and residential history from two case-control studies for 1983–1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk.ResultsMaps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation.DiscussionSpatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of breast cancer on upper Cape Cod. The analysis suggests further investigation of the potential association between breast cancer and pollution plumes based on detailed exposure modeling.

Association between Residences in U.S. Northern Latitudes and Rheumatoid Arthritis: A Spatial Analysis of the Nurses’ Health Study

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.

Private Drinking Water Wells as a Source of Exposure to Perfluorooctanoic Acid (PFOA) in Communities Surrounding a Fluoropolymer Production Facility

Background The C8 Health Project was established in 2005 to collect data on perfluorooctanoic acid (PFOA, or C8) and human health in Ohio and West Virginia communities contaminated by a fluoropolymer production facility. Objective We assessed PFOA exposure via contaminated drinking water in a subset of C8 Health Project participants who drank water from private wells. Methods Participants provided demographic information and residential, occupational, and medical histories. Laboratory analyses were conducted to determine serum-PFOA concentrations. PFOA data were collected from 2001 through 2005 from 62 private drinking water wells. We examined the relationship between drinking water and PFOA levels in serum using robust regression methods. As a comparison with regression models, we used a first-order, single-compartment pharmacokinetic model to estimate the serum:drinking-water concentration ratio at steady state. Results The median serum PFOA concentration in 108 study participants who used private wells was 75.7 μg/L, approximately 20 times greater than the levels in the U.S. general population but similar to those of local residents who drank public water. Each 1 μg/L increase in PFOA levels in drinking water was associated with an increase in serum concentrations of 141.5 μg/L (95% confidence interval, 134.9–148.1). The serum:drinking-water concentration ratio for the steady-state pharmacokinetic model was 114. Conclusions PFOA-contaminated drinking water is a significant contributor to PFOA levels in serum in the study population. Regression methods and pharmacokinetic modeling produced similar estimates of the relationship.

Community- and Individual-Level Socioeconomic Status and Breast Cancer Risk: Multilevel Modeling on Cape Cod, Massachusetts

Background Previous research demonstrated increased risk of breast cancer associated with higher socioeconomic status (SES) measured at both the individual and community levels. However, little attention has been paid to simultaneously examining both measures. Objectives We evaluated the independent influences of individual and community SES on the risk of breast cancer using case–control data. Because our previous work suggests that associations may be stronger after including a latency period, we also assessed the effect of community-level SES assuming a 10-year latency period. Methods We obtained individual education for cases and matched controls diagnosed between 1987 and 1993 on Cape Cod, Massachusetts (USA). We acquired community-level SES from census data for 1980 and 1990. Using SES data at diagnosis and 10 years earlier, we constructed models for breast cancer risk using individual-level SES only, community-level SES only, and a multilevel analysis including both. We adjusted models for other individual-level risk factors. Results Women with the highest education were at greater risk of developing breast cancer in both 1980 and 1990 [odds ratio (OR) = 1.17 and 1.19, respectively]. Similarly, women living in the highest-SES communities in 1990 had greater risk (OR = 1.30). Results were stronger in the analyses considering a latency period (OR = 1.69). Adjusting for intragroup correlation had little effect on the analyses. Conclusions Models including individual- or community-level measures of SES produced associations similar to those observed in previous research. Results for models including both measures are consistent with a contextual effect of SES on risk of breast cancer independent of individual SES.

Spatial analysis of adherence to treatment guidelines for advanced-stage ovarian cancer and the impact of race and socioeconomic status

OBJECTIVE To determine the impact of geographic location on advanced-stage ovarian cancer care adherence to the National Comprehensive Cancer Network (NCCN) guidelines in relation to race and socioeconomic status (SES). METHODS Patients diagnosed with stage IIIC/IV epithelial ovarian cancer (1/1/96-12/31/06) were identified from the California Cancer Registry. Generalized additive models were created to assess the effect of spatial distributions of geographic location, proximity to a high-volume hospital (≥20 cases/year), distance traveled to receive care, race, and SES on adherence to NCCN guidelines, with simultaneous smoothing of geographic location and adjustment for confounding variables. Disparities in geographic predictors of treatment adherence were analyzed with the x(2) test for equality of proportions. RESULTS Of the 11,770 patients identified, 45.4% were treated according to NCCN guidelines. Black race (OR=1.49, 95%CI=1.21-1.83), low-SES (OR=1.46, 95%CI=1.24-1.72), and geographic location ≥80 km/50 mi from a high-volume hospital (OR=1.88, 95%CI=1.61-2.19) were independently associated with an increased risk of non-adherent care, while high-volume hospital treatment (OR=0.59, 95%CI=0.53-0.66) and travel distance to receive care ≥32 km/20 mi (OR=0.80, 95%CI=0.69-0.92) were independently protective. SES was inversely associated with location ≥80 km/50 mi from a high-volume hospital, ranging from 6.3% (high-SES) to 33.0% (low-SES) (p<0.0001). White patients were significantly more likely to travel ≥32 km/20 mi to receive care (21.8%) compared to Blacks (14.4%), Hispanics (15.9%), and Asian/Pacific Islanders (15.5%) (p<0.0001). CONCLUSION Geographic proximity to a high-volume hospital and travel distance to receive treatment are independently associated with NCCN guideline adherent care for advanced-stage ovarian cancer. Geographic barriers to standard ovarian cancer treatment disproportionately affect racial minorities and women of low-SES.

Polyfluorinated Compounds in Serum Linked to Indoor Air in Office Environments

We aimed to investigate the role of indoor office air on exposure to polyfluorinated compounds (PFCs) among office workers. Week-long, active air sampling was conducted during the winter of 2009 in 31 offices in Boston, MA. Air samples were analyzed for fluorotelomer alcohols (FTOHs), sulfonamides (FOSAs), and sulfonamidoethanols (FOSEs). Serum was collected from each participant (n = 31) and analyzed for 12 PFCs including PFOA and PFOS. In air, FTOHs were present in the highest concentrations, particularly 8:2-FTOH (GM = 9920 pg/m(3)). FTOHs varied significantly by building with the highest levels observed in a newly constructed building. PFOA in serum was significantly correlated with air levels of 6:2-FTOH (r = 0.43), 8:2-FTOH (r = 0.60), and 10:2-FTOH (r = 0.62). Collectively, FTOHs in air significantly predicted PFOA in serum (p < 0.001) and explained approximately 36% of the variation in serum PFOA concentrations. PFOS in serum was not associated with air levels of FOSAs/FOSEs. In conclusion, FTOH concentrations in office air significantly predict serum PFOA concentrations in office workers. Variation in PFC air concentrations by building is likely due to differences in the number, type, and age of potential sources such as carpeting, furniture, and/or paint.