Workplace indoor environmental quality and asthma-related outcomes in healthcare workers.

BACKGROUND: Asthma-related health outcomes are known to be associated with indoor moisture and renovations. The objective of this study was to estimate the frequency of these indoor environmental quality (IEQ) factors in healthcare facilities and their association with asthma-related outcomes among workers. METHODS: New York City healthcare workers (n = 2030) were surveyed regarding asthma-related symptoms, and moisture and renovation factors at work and at home during the last 12 months. Questions for workplace moisture addressed water damage (WD), mold growth (MG), and mold odor (MO), while for renovations they addressed painting (P), floor renovations (FR), and wall renovations (WR). Regression models were fit to examine associations between work and home IEQ factors and multiple asthma-related outcomes. RESULTS: Reports of any moisture (n = 728, 36%) and renovations (n = 1412, 70%) at work were common. Workplace risk factors for asthma-related outcomes included the moisture categories of WD by itself, WD with MO (without MG), and WD with MG and MO, and the renovation category with the three factors P, FR, and WR. Reports of home IEQ factors were less frequent and less likely to be associated with health outcomes. Data analyses suggested that MG and/or MO at work and at home had a synergistic effect on the additive scale with a symptom-based algorithm for bronchial hyperresponsiveness. CONCLUSIONS: The current study determined that moisture and renovation factors are common in healthcare facilities, potentially putting workers at risk for asthma-related outcomes. More research is needed to confirm these results, especially prospective studies.

Peaks, Means, and Determinants of Real-Time TVOC Exposures Associated with Cleaning and Disinfecting Tasks in Healthcare Settings.

Cleaning and disinfecting tasks and product use are associated with elevated prevalence of asthma and respiratory symptoms among healthcare workers; however, the levels of exposure that pose a health risk remain unclear. The objective of this study was to estimate the peak, average, and determinants of real-time total volatile organic compound (TVOC) exposure associated with cleaning tasks and product-use. TVOC exposures were measured using monitors equipped with a photoionization detector (PID). A simple correction factor was applied to the real-time measurements, calculated as a ratio of the full-shift average TVOC concentrations from a time-integrated canister and the PID sample, for each sample pair. During sampling, auxiliary information, e.g. tasks, products used, engineering controls, was recorded on standardized data collection forms at 5-min intervals. Five-minute averaged air measurements (n = 10 276) from 129 time-series comprising 92 workers and four hospitals were used to model the determinants of exposures. The statistical model simultaneously accounted for censored data and non-stationary autocorrelation and was fit using Markov-Chain Monte Carlo within a Bayesian context. Log-transformed corrected concentrations (cTVOC) were modeled, with the fixed-effects of tasks and covariates, that were systematically gathered during sampling, and random effect of person-day. The model-predicted geometric mean (GM) cTVOC concentrations ranged from 387 parts per billion (ppb) for the task of using a product containing formaldehyde in laboratories to 2091 ppb for the task of using skin wipes containing quaternary ammonium compounds, with a GM of 925 ppb when no products were used. Peak exposures quantified as the 95th percentile of 15-min averages for these tasks ranged from 3172 to 17 360 ppb. Peak and GM task exposures varied by occupation and hospital unit. In the multiple regression model, use of sprays was associated with increasing exposures, while presence of local exhaust ventilation, large room volume, and automatic sterilizer use were associated with decreasing exposures. A detailed understanding of factors affecting TVOC exposure can inform targeted interventions to reduce exposures and can be used in epidemiologic studies as metrics of short-duration peak exposures.

Clustering asthma symptoms and cleaning and disinfecting activities and evaluating their associations among healthcare workers.

Asthma is a heterogeneous disease with varying severity and subtypes. Recent reviews of epidemiologic studies have identified cleaning and disinfecting activities (CDAs) as important risk factors for asthma-related outcomes among healthcare workers. However, the complexity of CDAs in healthcare settings has rarely been examined. This study utilized a complex survey dataset and data reduction approaches to identify and group healthcare workers with similar patterns of asthma symptoms, and then explored their associations with groups of participants with similar patterns of CDAs. Self-reported information on asthma symptoms/care, CDAs, demographics, smoking status, allergic status, and other characteristics were collected from 2030 healthcare workers within nine selected occupations in New York City. Hierarchical clustering was conducted to systematically group participants based on similarity of patterns of the 27 asthma symptom/care variables, and 14 product applications during CDAs, separately. Word clouds were used to visualize the complex information on the resulting clusters. The associations of asthma health clusters (HCs) with exposure clusters (ECs) were evaluated using multinomial logistic regression. Five HCs were identified (HC-1 to HC-5), labelled based on predominant features as: "no symptoms", "winter cough/phlegm", "mild asthma symptoms", "undiagnosed/untreated asthma", and "asthma attacks/exacerbations". For CDAs, five ECs were identified (EC-1 to EC-5), labelled as: "no products", "housekeeping/chlorine", "patient care", "general cleaning/laboratory", and "disinfection products". Using HC-1 and EC-1 as the reference groups, EC-2 was associated with HC-4 (odds ratio (OR) = 3.11, 95% confidence interval (95% CI) = 1.46-6.63) and HC-5 (OR = 2.71, 95% CI = 1.25-5.86). EC-3 was associated with HC-5 (OR = 2.34, 95% CI = 1.16-4.72). EC-4 was associated with HC-5 (OR = 2.35, 95% CI = 1.07-5.13). EC-5 was associated with HC-3 (OR = 1.81, 95% CI = 1.09-2.99) and HC-4 (OR = 3.42, 95% CI = 1.24-9.39). Various combinations of product applications like using alcohols, bleach, high-level disinfectants, and enzymes to disinfect instruments and clean surfaces captured by the ECs were identified as risk factors for the different asthma symptoms clusters, indicating that prevention efforts may require targeting multiple products. The associations of HCs with EC can be used to better inform prevention strategies and treatment options to avoid disease progression. This study demonstrated hierarchical clustering and word clouds were useful techniques for analyzing and visualizing a complex dataset with a large number of potentially correlated variables to generate practical information that can inform prevention activities.

Occupation and task as risk factors for asthma-related outcomes among healthcare workers in New York City.

BACKGROUND: Previous studies have suggested an association of asthma onset and exacerbation with cleaning and disinfecting activities in a number of industries, including healthcare. The objective of the current study was to investigate the association of asthma and related outcomes with occupations and tasks in urban healthcare workers in the United States. METHODS: A questionnaire was implemented in a sample of workers from nine healthcare occupations in New York City. We used regression models to examine the association of post-hire asthma, current asthma, exacerbation of asthma, a symptom algorithm for bronchial hyper-responsiveness (BHR-related symptoms), a symptom-based asthma score, and the symptom wheeze with occupation and four healthcare tasks, while adjusting for other risk factors and potential confounders. RESULTS: A total of 2030 participants completed the questionnaire. The task of cleaning fixed surfaces was significantly associated with most outcome variables, including current asthma (odds ratio (OR) = 1.84, 95% confidence interval (CI) 1.26-2.68), moderate exacerbation (OR = 3.10, 95% CI 1.25-7.67), and BHR-related symptoms (OR = 1.38, 95% CI 1.08-1.77). In comparison to nursing assistants, the occupations environmental service workers and registered nurses were at higher risk for current asthma, and licensed practical nurses were at higher risk for moderate exacerbation. Other tasks associated with outcomes were administering aerosolized medications with current asthma and moderate exacerbation, and sterilizing medical equipment with BHR-related symptoms. CONCLUSIONS: These findings add to the growing body of evidence for the association of asthma with cleaning and other activities in healthcare. Further research is especially needed to investigate the association of asthma-related outcomes with exposure metrics based on tasks, products, and chemical exposures in healthcare.

Exposures to Volatile Organic Compounds among Healthcare Workers: Modeling the Effects of Cleaning Tasks and Product Use.

Objectives: Use of cleaning and disinfecting products is associated with work-related asthma among healthcare workers, but the specific levels and factors that affect exposures remain unclear. The objective of this study was to evaluate the determinants of selected volatile organic compound (VOC) exposures in healthcare settings. Methods: Personal and mobile-area air measurements (n = 143) from 100 healthcare workers at four hospitals were used to model the determinants of ethanol, acetone, 2-propanol, d-limonene, α-pinene, and chloroform exposures. Hierarchical cluster analysis was conducted to partition workers into groups with similar cleaning task/product-use profiles. Linear mixed-effect regression models using log-transformed VOC measurements were applied to evaluate the association of individual VOCs with clusters of task/product use, industrial hygienists' grouping (IH) of tasks, grouping of product application, chemical ingredients of the cleaning products used, amount of product use, and ventilation. Results: Cluster analysis identified eight task/product-use clusters that were distributed across multiple occupations and hospital units, with the exception of clusters consisting of housekeepers and floor strippers/waxers. Results of the mixed-effect models showed significant associations between selected VOC exposures and several clusters, combinations of IH-generated task groups and chemical ingredients, and product application groups. The patient/personal cleaning task using products containing chlorine was associated with elevated levels of personal chloroform and α-pinene exposures. Tasks associated with instrument sterilizing and disinfecting were significantly associated with personal d-limonene and 2-propanol exposures. Surface and floor cleaning and stripping tasks were predominated by housekeepers and floor strippers/waxers, and use of chlorine-, alcohol-, ethanolamine-, and quaternary ammonium compounds-based products was associated with exposures to chloroform, α-pinene, acetone, 2-propanol, or d-limonene. Conclusions: Healthcare workers are exposed to a variety of chemicals that vary with tasks and ingredients of products used during cleaning and disinfecting. The combination of product ingredients with cleaning and disinfecting tasks were associated with specific VOCs. Exposure modules for questionnaires used in epidemiologic studies might benefit from seeking information on products used within a task context.

Volatile Organic Compounds (VOCs) in Conventional and High Performance School Buildings in the U.S.

Exposure to volatile organic compounds (VOCs) has been an indoor environmental quality (IEQ) concern in schools and other buildings for many years. Newer designs, construction practices and building materials for "green" buildings and the use of "environmentally friendly" products have the promise of lowering chemical exposure. This study examines VOCs and IEQ parameters in 144 classrooms in 37 conventional and high performance elementary schools in the U.S. with the objectives of providing a comprehensive analysis and updating the literature. Tested schools were built or renovated in the past 15 years, and included comparable numbers of conventional, Energy Star, and Leadership in Energy and Environmental Design (LEED)-certified buildings. Indoor and outdoor VOC samples were collected and analyzed by thermal desorption, gas chromatography and mass spectroscopy for 94 compounds. Aromatics, alkanes and terpenes were the major compound groups detected. Most VOCs had mean concentrations below 5 µg/m³, and most indoor/outdoor concentration ratios ranged from one to 10. For 16 VOCs, the within-school variance of concentrations exceeded that between schools and, overall, no major differences in VOC concentrations were found between conventional and high performance buildings. While VOC concentrations have declined from levels measured in earlier decades, opportunities remain to improve indoor air quality (IAQ) by limiting emissions from building-related sources and by increasing ventilation rates.

Measurement and Comparison of Organic Compound Concentrations in Plasma, Whole Blood, and Dried Blood Spot Samples.

The preferred sampling medium for measuring human exposures of persistent organic compounds (POPs) is blood, and relevant sample types include whole blood, plasma, and dried blood spots (DBS). Because information regarding the performance and comparability of measurements across these sample types is limited, it is difficult to compare across studies. This study evaluates the performance of POP measurements in plasma, whole blood and DBS, and presents the distribution coefficients needed to convert concentrations among the three sample types. Blood samples were collected from adult volunteers, along with demographic and smoking information, and analyzed by GC/MS for organochlorine pesticides (OCPs), chlorinated hydrocarbons (CHCs), polychlorinated biphenyls (PCBs), and brominated diphenyl ethers (PBDEs). Regression models were used to evaluate the relationships between the sample types and possible effects of personal covariates. Distribution coefficients also were calculated using physically-based models. Across all compounds, concentrations in plasma were consistently the highest; concentrations in whole blood and DBS samples were comparable. Distribution coefficients for plasma to whole blood concentrations ranged from 1.74 to 2.26 for pesticides/CHCs, averaged 1.69 ± 0.06 for the PCBs, and averaged 1.65 ± 0.03 for the PBDEs. Regression models closely fit most chemicals (R (2) > 0.80), and whole blood and DBS samples generally showed very good agreement. Distribution coefficients estimated using biologically-based models were near one and did not explain the observed distribution. Among the study population, median concentrations of several pesticides/CHCs and PBDEs exceeded levels reported in the 2007-2008 National Health and Nutrition Examination Survey, while levels of other OCPs and PBDEs were comparable or lower. Race and smoking status appeared to slightly affect plasma/blood concentration ratios for several POPs. The experimentally-determined distribution coefficients can be used to compare POP exposures across studies using different types of blood-based matrices.

Association of Environmental Toxins With Amyotrophic Lateral Sclerosis.

IMPORTANCE: Persistent environmental pollutants may represent a modifiable risk factor involved in the gene-time-environment hypothesis in amyotrophic lateral sclerosis (ALS). OBJECTIVE: To evaluate the association of occupational exposures and environmental toxins on the odds of developing ALS in Michigan. DESIGN, SETTING, AND PARTICIPANTS: Case-control study conducted between 2011 and 2014 at a tertiary referral center for ALS. Cases were patients diagnosed as having definitive, probable, probable with laboratory support, or possible ALS by revised El Escorial criteria; controls were excluded if they were diagnosed as having ALS or another neurodegenerative condition or if they had a family history of ALS in a first- or second-degree blood relative. Participants completed a survey assessing occupational and residential exposures. Blood concentrations of 122 persistent environmental pollutants, including organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and brominated flame retardants (BFRs), were measured using gas chromatography-mass spectrometry. Multivariable models with self-reported occupational exposures in various exposure time windows and environmental toxin blood concentrations were separately fit by logistic regression models. Concordance between the survey data and pollutant measurements was assessed using the nonparametric Kendall τ correlation coefficient. MAIN OUTCOMES AND MEASURES: Occupational and residential exposures to environmental toxins, and blood concentrations of 122 persistent environmental pollutants, including OCPs, PCBs, and BFRs. RESULTS: Participants included 156 cases (mean [SD] age, 60.5 [11.1] years; 61.5% male) and 128 controls (mean [SD] age, 60.4 [9.4] years; 57.8% male); among them, 101 cases and 110 controls had complete demographic and pollutant data. Survey data revealed that reported pesticide exposure in the cumulative exposure windows was significantly associated with ALS (odds ratio [OR] = 5.09; 95% CI, 1.85-13.99; P = .002). Military service was also associated with ALS in 2 time windows (exposure ever happened in entire occupational history: OR = 2.31; 95% CI, 1.02-5.25; P = .046; exposure ever happened 10-30 years ago: OR = 2.18; 95% CI, 1.01-4.73; P = .049). A multivariable model of measured persistent environmental pollutants in the blood, representing cumulative occupational and residential exposure, showed increased odds of ALS for 2 OCPs (pentachlorobenzene: OR = 2.21; 95% CI, 1.06-4.60; P = .04; and cis-chlordane: OR = 5.74; 95% CI, 1.80-18.20; P = .005), 2 PCBs (PCB 175: OR = 1.81; 95% CI, 1.20-2.72; P = .005; and PCB 202: OR = 2.11; 95% CI, 1.36-3.27; P = .001), and 1 BFR (polybrominated diphenyl ether 47: OR = 2.69; 95% CI, 1.49-4.85; P = .001). There was modest concordance between survey data and the measurements of persistent environmental pollutants in blood; significant Kendall τ correlation coefficients ranged from -0.18 (Dacthal and "use pesticides to treat home or yard") to 0.24 (trans-nonachlor and "store lawn care products in garage"). CONCLUSIONS AND RELEVANCE: In this study, persistent environmental pollutants measured in blood were significantly associated with ALS and may represent modifiable ALS disease risk factors.

Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA data.

INTRODUCTION: Emission sources of volatile organic compounds (VOCs*) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are known to affect VOC exposures, many personal, environmental, and socioeconomic determinants remain to be identified, and the significance and applicability of the determinants reported in the literature are uncertain. To help answer these unresolved questions and overcome limitations of previous analyses, this project used several novel and powerful statistical modeling and analysis techniques and two large data sets. The overall objectives of this project were (1) to identify and characterize exposure distributions (including extreme values), (2) evaluate mixtures (including dependencies), and (3) identify determinants of VOC exposure. METHODS VOC data were drawn from two large data sets: the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study (1999-2001) and the National Health and Nutrition Examination Survey (NHANES; 1999-2000). The RIOPA study used a convenience sample to collect outdoor, indoor, and personal exposure measurements in three cities (Elizabeth, NJ; Houston, TX; Los Angeles, CA). In each city, approximately 100 households with adults and children who did not smoke were sampled twice for 18 VOCs. In addition, information about 500 variables associated with exposure was collected. The NHANES used a nationally representative sample and included personal VOC measurements for 851 participants. NHANES sampled 10 VOCs in common with RIOPA. Both studies used similar sampling methods and study periods. Specific Aim 1. To estimate and model extreme value exposures, extreme value distribution models were fitted to the top 10% and 5% of VOC exposures. Health risks were estimated for individual VOCs and for three VOC mixtures. Simulated extreme value data sets, generated for each VOC and for fitted extreme value and lognormal distributions, were compared with measured concentrations (RIOPA observations) to evaluate each model's goodness of fit. Mixture distributions were fitted with the conventional finite mixture of normal distributions and the semi-parametric Dirichlet process mixture (DPM) of normal distributions for three individual VOCs (chloroform, 1,4-DCB, and styrene). Goodness of fit for these full distribution models was also evaluated using simulated data. Specific Aim 2. Mixtures in the RIOPA VOC data set were identified using positive matrix factorization (PMF) and by toxicologic mode of action. Dependency structures of a mixture's components were examined using mixture fractions and were modeled using copulas, which address correlations of multiple components across their entire distributions. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) were evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks were calculated for mixtures, and results from copulas and multivariate lognormal models were compared with risks based on RIOPA observations. Specific Aim 3. Exposure determinants were identified using stepwise regressions and linear mixed-effects models (LMMs). RESULTS: Specific Aim 1. Extreme value exposures in RIOPA typically were best fitted by three-parameter generalized extreme value (GEV) distributions, and sometimes by the two-parameter Gumbel distribution. In contrast, lognormal distributions significantly underestimated both the level and likelihood of extreme values. Among the VOCs measured in RIOPA, 1,4-dichlorobenzene (1,4-DCB) was associated with the greatest cancer risks; for example, for the highest 10% of measurements of 1,4-DCB, all individuals had risk levels above 10(-4), and 13% of all participants had risk levels above 10(-2). Of the full-distribution models, the finite mixture of normal distributions with two to four clusters and the DPM of normal distributions had superior performance in comparison with the lognormal models. DPM distributions provided slightly better fit than the finite mixture distributions; the advantages of the DPM model were avoiding certain convergence issues associated with the finite mixture distributions, adaptively selecting the number of needed clusters, and providing uncertainty estimates. Although the results apply to the RIOPA data set, GEV distributions and mixture models appear more broadly applicable. These models can be used to simulate VOC distributions, which are neither normally nor lognormally distributed, and they accurately represent the highest exposures, which may have the greatest health significance. Specific Aim 2. Four VOC mixtures were identified and apportioned by PMF; they represented gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection byproducts, and cleaning products and odorants. The last mixture (cleaning products and odorants) accounted for the largest fraction of an individual's total exposure (average of 42% across RIOPA participants). Often, a single compound dominated a mixture but the mixture fractions were heterogeneous; that is, the fractions of the compounds changed with the concentration of the mixture. Three VOC mixtures were identified by toxicologic mode of action and represented VOCs associated with hematopoietic, liver, and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10(-3) for about 10% of RIOPA participants. The dependency structures of the VOC mixtures in the RIOPA data set fitted Gumbel (two mixtures) and t copulas (four mixtures). These copula types emphasize dependencies found in the upper and lower tails of a distribution. The copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy and performed better than multivariate lognormal distributions. Specific Aim 3. In an analysis focused on the home environment and the outdoor (close to home) environment, home VOC concentrations dominated personal exposures (66% to 78% of the total exposure, depending on VOC); this was largely the result of the amount of time participants spent at home and the fact that indoor concentrations were much higher than outdoor concentrations for most VOCs. In a different analysis focused on the sources inside the home and outside (but close to the home), it was assumed that 100% of VOCs from outside sources would penetrate the home. Outdoor VOC sources accounted for 5% (d-limonene) to 81% (carbon tetrachloride [CTC]) of the total exposure. Personal exposure and indoor measurements had similar determinants depending on the VOC. Gasoline-related VOCs (e.g., benzene and methyl tert-butyl ether [MTBE]) were associated with city, residences with attached garages, pumping gas, wind speed, and home air exchange rate (AER). Odorant and cleaning-related VOCs (e.g., 1,4-DCB and chloroform) also were associated with city, and a residence's AER, size, and family members showering. Dry-cleaning and industry-related VOCs (e.g., tetrachloroethylene [or perchloroethylene, PERC] and trichloroethylene [TCE]) were associated with city, type of water supply to the home, and visits to the dry cleaner. These and other relationships were significant, they explained from 10% to 40% of the variance in the measurements, and are consistent with known emission sources and those reported in the literature. Outdoor concentrations of VOCs had only two determinants in common: city and wind speed. Overall, personal exposure was dominated by the home setting, although a large fraction of indoor VOC concentrations were due to outdoor sources. City of residence, personal activities, household characteristics, and meteorology were significant determinants. Concentrations in RIOPA were considerably lower than levels in the nationally representative NHANES for all VOCs except MTBE and 1,4-DCB. Differences between RIOPA and NHANES results can be explained by contrasts between the sampling designs and staging in the two studies, and by differences in the demographics, smoking, employment, occupations, and home locations. (ABSTRACT TRUNCATED)

Environmental risk factors and amyotrophic lateral sclerosis (ALS): a case-control study of ALS in Michigan.

An interim report of a case-control study was conducted to explore the role of environmental factors in the development of amyotrophic lateral sclerosis (ALS). Sixty-six cases and 66 age- and gender-matched controls were recruited. Detailed information regarding residence history, occupational history, smoking, physical activity, and other factors was obtained using questionnaires. The association of ALS with potential risk factors, including smoking, physical activity and chemical exposure, was investigated using conditional logistic regression models. As compared to controls, a greater number of our randomly selected ALS patients reported exposure to fertilizers to treat private yards and gardens and occupational exposure to pesticides in the last 30 years than our randomly selected control cases. Smoking, occupational exposures to metals, dust/fibers/fumes/gas and radiation, and physical activity were not associated with ALS when comparing the randomly selected ALS patients to the control subjects. To further explore and confirm results, exposures over several time frames, including 0-10 and 10-30 years earlier, were considered, and analyses were stratified by age and gender. Pesticide and fertilizer exposure were both significantly associated with ALS in the randomly selected ALS patients. While study results need to be interpreted cautiously given the small sample size and the lack of direct exposure measures, these results suggest that environmental and particularly residential exposure factors warrant close attention in studies examining risk factors of ALS.

Modeling and analysis of personal exposures to VOC mixtures using copulas.

Environmental exposures typically involve mixtures of pollutants, which must be understood to evaluate cumulative risks, that is, the likelihood of adverse health effects arising from two or more chemicals. This study uses several powerful techniques to characterize dependency structures of mixture components in personal exposure measurements of volatile organic compounds (VOCs) with aims of advancing the understanding of environmental mixtures, improving the ability to model mixture components in a statistically valid manner, and demonstrating broadly applicable techniques. We first describe characteristics of mixtures and introduce several terms, including the mixture fraction which represents a mixture component's share of the total concentration of the mixture. Next, using VOC exposure data collected in the Relationship of Indoor Outdoor and Personal Air (RIOPA) study, mixtures are identified using positive matrix factorization (PMF) and by toxicological mode of action. Dependency structures of mixture components are examined using mixture fractions and modeled using copulas, which address dependencies of multiple variables across the entire distribution. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) are evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks are calculated for mixtures, and results from copulas and multivariate lognormal models are compared to risks calculated using the observed data. Results obtained using the RIOPA dataset showed four VOC mixtures, representing gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection by-products, and cleaning products and odorants. Often, a single compound dominated the mixture, however, mixture fractions were generally heterogeneous in that the VOC composition of the mixture changed with concentration. Three mixtures were identified by mode of action, representing VOCs associated with hematopoietic, liver and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10(-3) for about 10% of RIOPA participants. Factors affecting the likelihood of high concentration mixtures included city, participant ethnicity, and house air exchange rates. The dependency structures of the VOC mixtures fitted Gumbel (two mixtures) and t (four mixtures) copulas, types that emphasize tail dependencies. Significantly, the copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy, and performed better than multivariate lognormal distributions. Copulas may be the method of choice for VOC mixtures, particularly for the highest exposures or extreme events, cases that poorly fit lognormal distributions and that represent the greatest risks.

Addressing extrema and censoring in pollutant and exposure data using mixture of normal distributions.

BACKGROUND: Volatile organic compounds (VOC), which include many hazardous chemicals, have been used extensively in personal, commercial and industrial products. Due to the variation in source emissions, differences in the settings and environmental conditions where exposures occur, and measurement issues, distributions of VOC concentrations can have multiple modes, heavy tails, and significant portions of data below the method detection limit (MDL). These issues challenge standard parametric distribution models needed to estimate the exposures, even after log-transformation of the data. METHODS: This paper considers mixture of distributions that can be directly applied to concentration and exposure data. Two types of mixture distributions are considered: the traditional finite mixture of normal distributions, and a semi-parametric Dirichlet process mixture (DPM) of normal distributions. Both methods are implemented for a sample data set obtained from the Relationship between Indoor, Outdoor and Personal Air (RIOPA) study. Performance is assessed based on goodness-of-fit criteria that compare the closeness of the density estimates with the empirical density based on data. The goodness-of-fit for the proposed density estimation methods are evaluated by a comprehensive simulation study. RESULTS: The finite mixture of normals and DPM of normals have superior performance when compared to the single normal distribution fitted to log-transformed exposure data. The advantages of using these mixture distributions are more pronounced when exposure data have heavy tails or a large fraction of data below the MDL. Distributions from the DPM provided slightly better fits than the finite mixture of normals. Additionally, the DPM method avoids certain convergence issues associated with the finite mixture of normals, and adaptively selects the number of components. CONCLUSIONS: Compared to the finite mixture of normals, DPM of normals has advantages by characterizing uncertainty around the number of components, and by providing a formal assessment of uncertainty for all model parameters through the posterior distribution. The method adapts to a spectrum of departures from standard model assumptions and provides robust estimates of the exposure density even under censoring due to MDL.

Determinants of personal, indoor and outdoor VOC concentrations: an analysis of the RIOPA data.

Community and environmental exposure to volatile organic compounds (VOCs) has been associated with a number of emission sources and activities, e.g., environmental tobacco smoke and pumping gasoline. Such factors have been identified from mostly small studies with relatively limited information regarding influences on VOC levels. This study uses data from the Relationship of Indoor Outdoor and Personal Air (RIOPA) study to investigate environmental, individual and social determinants of VOC concentrations. RIOPA included outdoor, indoor and personal measurements of 18 VOCs from 310 non-smoking households and adults in three cities and two seasons, and collected a wide range of information pertaining to participants, family members, households, and neighborhoods. Exposure determinants were identified using stepwise regressions and linear mixed-effect models. Most VOC exposure (66 to 78% of the total exposure, depending on VOC) occurred indoors, and outdoor VOC sources accounted for 5 (d-limonene) to 81% (carbon tetrachloride) of the total exposure. Personal exposure and indoor measurements had similar determinants, which depended on the VOC. Gasoline-related VOCs (e.g., benzene, methyl tertiary butyl ether) were associated with city, residences with attached garages, self-pumping of gas, wind speed, and house air exchange rate (AER). Odorant and cleaning-related VOCs (e.g., 1,4-dichlorobenzene and chloroform) also were associated with city and AER, and with house size and family members showering. Dry-cleaning and industry-related VOCs (e.g., tetrachloroethylene and trichloroethylene) were associated with city, residence water supply type, and dry-cleaner visits. These and other relationships were significant, explained from 10 to 40% of the variation, and are consistent with known emission sources and the literature. Outdoor concentrations had only two common determinants: city and wind speed. Overall, personal exposure was dominated by the home setting, although a large fraction of VOC concentrations were due to outdoor sources. City, personal activities, household characteristics and meteorology were significant determinants.

In utero exposure to environmental lead and manganese and neurodevelopment at 2 years of age.

BACKGROUND AND OBJECTIVE: Manganese, lead, arsenic and mercury are common neurotoxic metals in the environment. Nonetheless, the relationship between prenatal exposure to low doses of neurotoxic metals and neurodevelopment in children is not clear. The objective of this study was to explore the relationship between in utero exposure to environmental neurotoxic metals and neurodevelopment at 2 years of age. METHODS: The population of this study came from the Taiwan Birth Panel Study. We included 230 pairs of non-smoking mothers without any occupational exposure and their singleton full-term children. The information about exposure during pregnancy was obtained using a structured questionnaire, and the manganese, lead, arsenic and mercury levels in umbilical cord blood samples were analyzed using inductively coupled plasma mass spectrometry. We used the Comprehensive Developmental Inventory for Infants and Toddlers (CDIIT) to evaluate the developmental status of each child at 2 years of age, and we examined the association of in utero exposure to environmental metals and neurodevelopment using linear regression models. RESULTS: The median concentrations of manganese, lead, arsenic and mercury in the cord blood samples in this study were 47.90 µg/L (range, 17.88-106.85 µg/L), 11.41 µg/L (range 0.16-43.22 µg/L), 4.05 µg/L (range, 1.50-12.88 µg/L) and 12.17 µg/L (range, 1.53-64.87 µg/L), respectively. After adjusting for maternal age, infant gender, environmental tobacco smoke during pregnancy and after delivery, Home Observation for Measurement of the Environment Inventory results, and arsenic and mercury levels in cord blood, we found that manganese and lead levels above the 75th percentile had a significant adverse association with the overall (ß=-7.03, SE=2.65, P=0.0085), cognitive (ß=-8.19, SE=3.17, P=0.0105), and language quotients (ß=-6.81, SE=2.73, P=0.0133) of the CDIIT. CONCLUSIONS: In utero exposure to environmental manganese and lead may have an adverse association with neurodevelopment at 2 years of age, and there is an interaction effect between the manganese and lead levels in the cord blood that could aggravate the effect.

Extreme value analyses of VOC exposures and risks: A comparison of RIOPA and NHANES datasets.

Extreme value theory, which characterizes the behavior of tails of distributions, is potentially well-suited to model exposures and risks of pollutants. In this application, it emphasizes the highest exposures, particularly those that may be high enough to present acute or chronic health risks. The present study examines extreme value distributions of exposures and risks to volatile organic compounds (VOCs). Exposures of 15 different VOCs were measured in the Relationship between Indoor, Outdoor and Personal Air (RIOPA) study, and ten of the same VOCs were measured in the nationally representative National Health and Nutrition Examination Survey (NHANES). Both studies used similar sampling methods and study periods. Using the highest 5 and 10% of measurements, generalized extreme value (GEV), Gumbel and lognormal distributions were fit to each VOC in these two large studies. Health risks were estimated for individual VOCs and three VOC mixtures. Simulated data that matched the three types of distributions were generated and compared to observations to evaluate goodness-of-fit. The tail behavior of exposures, which clearly neither fit normal nor lognormal distributions for most VOCs in RIOPA, was usually best fit by the 3-parameter GEV distribution, and often by the 2-parameter Gumbel distribution. In contrast, lognormal distributions significantly underestimated both the level and likelihood of extrema. Among the RIOPA VOCs, 1,4-dichlorobenzene (1,4-DCB) caused the greatest risks, e.g., for the top 10% extrema, all individuals had risk levels above 10-4, and 13% of them exceeded 10-2. NHANES had considerably higher concentrations of all VOCs with two exceptions, methyl tertiary-butyl ether and 1,4-DCB. Differences between these studies can be explained by sampling design, staging, sample demographics, smoking and occupation. This analysis shows that extreme value distributions can represent peak exposures of VOCs, which clearly are neither normally nor lognormally distributed. These exposures have the greatest health significance, and require accurate modeling.

Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: time-series and time-stratified case-crossover analyses with threshold effects.

BACKGROUND: Asthma morbidity has been associated with ambient air pollutants in time-series and case-crossover studies. In such study designs, threshold effects of air pollutants on asthma outcomes have been relatively unexplored, which are of potential interest for exploring concentration-response relationships. METHODS: This study analyzes daily data on the asthma morbidity experienced by the pediatric Medicaid population (ages 2-18 years) of Detroit, Michigan and concentrations of pollutants fine particles (PM2.5), CO, NO2 and SO2 for the 2004-2006 period, using both time-series and case-crossover designs. We use a simple, testable and readily implementable profile likelihood-based approach to estimate threshold parameters in both designs. RESULTS: Evidence of significant increases in daily acute asthma events was found for SO2 and PM2.5, and a significant threshold effect was estimated for PM2.5 at 13 and 11 µg m(-3) using generalized additive models and conditional logistic regression models, respectively. Stronger effect sizes above the threshold were typically noted compared to standard linear relationship, e.g., in the time series analysis, an interquartile range increase (9.2 µg m(-3)) in PM2.5 (5-day-moving average) had a risk ratio of 1.030 (95% CI: 1.001, 1.061) in the generalized additive models, and 1.066 (95% CI: 1.031, 1.102) in the threshold generalized additive models. The corresponding estimates for the case-crossover design were 1.039 (95% CI: 1.013, 1.066) in the conditional logistic regression, and 1.054 (95% CI: 1.023, 1.086) in the threshold conditional logistic regression. CONCLUSION: This study indicates that the associations of SO2 and PM2.5 concentrations with asthma emergency department visits and hospitalizations, as well as the estimated PM2.5 threshold were fairly consistent across time-series and case-crossover analyses, and suggests that effect estimates based on linear models (without thresholds) may underestimate the true risk.

Manganese and lead in children's blood and airborne particulate matter in Durban, South Africa.

Despite the toxicity and widespread use of manganese (Mn) and lead (Pb) as additives to motor fuels and for other purposes, information regarding human exposure in Africa is very limited. This study investigates the environmental exposures of Mn and Pb in Durban, South Africa, a region that has utilized both metals in gasoline. Airborne metals were sampled as PM(2.5) and PM(10) at three sites, and blood samples were obtained from a population-based sample of 408 school children attending seven schools. In PM(2.5), Mn and Pb concentrations averaged 17±27 ng m(-3) and 77±91 ng m(-3), respectively; Mn concentrations in PM(10) were higher (49±44 ng m(-3)). In blood, Mn concentrations averaged 10.1±3.4 µg L(-1) and 8% of children exceeded 15 µg L(-1), the normal range. Mn concentrations fit a lognormal distribution. Heavier and Indian children had elevated levels. Pb in blood averaged 5.3±2.1 µg dL(-1), and 3.4% of children exceeded 10 µg dL(-1), the guideline level. Pb levels were best fit by a mixed (extreme value) distribution, and boys and children living in industrialized areas of Durban had elevated levels. Although airborne Mn and Pb concentrations were correlated, blood levels were not. A trend analysis shows dramatic decreases of Pb levels in air and children's blood in South Africa, although a sizable fraction of children still exceeds guideline levels. The study's findings suggest that while vehicle exhaust may contribute to exposures of both metals, other sources currently dominate Pb exposures.

Trends of VOC exposures among a nationally representative sample: Analysis of the NHANES 1988 through 2004 data sets.

Exposures to volatile organic compounds (VOCs) are ubiquitous due to emissions from personal, commercial and industrial products, but quantitative and representative information regarding long term exposure trends is lacking. This study characterizes trends from1988 to 2004 for the 15 VOCs measured in blood in five cohorts of the National Health and Nutrition Examination Survey (NHANES), a large and representative sample of U.S. adults. Trends were evaluated at various percentiles using linear quantile regression (QR) models, which were adjusted for solvent-related occupations and cotinine levels. Most VOCs showed decreasing trends at all quantiles, e.g., median exposures declined by 2.5 (m, p-xylene) to 6.4 (tetrachloroethene) percent per year over the 15 year period. Trends varied by VOC and quantile, and were grouped into three patterns: similar decreases at all quantiles (including benzene, toluene); most rapid decreases at upper quantiles (ethylbenzene, m, p-xylene, o-xylene, styrene, chloroform, tetrachloroethene); and fastest declines at central quantiles (1,4-dichlorobenzene). These patterns reflect changes in exposure sources, e.g., upper-percentile exposures may result mostly from occupational exposure, while lower percentile exposures arise from general environmental sources. Both VOC emissions aggregated at the national level and VOC concentrations measured in ambient air also have declined substantially over the study period and are supportive of the exposure trends, although the NHANES data suggest the importance of indoor sources and personal activities on VOC exposures. While piecewise QR models suggest that exposures of several VOCs decreased little or any during the 1990's, followed by more rapid decreases from 1999 to 2004, questions are raised concerning the reliability of VOC data in several of the NHANES cohorts and its applicability as an exposure indicator, as demonstrated by the modest correlation between VOC levels in blood and personal air collected in the 1999/2000 cohort. Despite some limitations, the NHANES data provides a unique, long term and direct measurement of VOC exposures and trends.

High perinatal seroprevalence of cytomegalovirus in northern Taiwan.

AIM: The living style, health-care system and socio-economic environments have changed substantially in Taiwan over past 20 years. This study was aimed to estimate the current perinatal cytomegalovirus (CMV) seroprevalence in northern Taiwan. METHODS: In a Taiwan Birth Panel Study, 483 pairs of mothers and neonates were prospectively recruited from one tertiary medical center, one local hospital, and two obstetric clinics located in northern Taiwan from April 2004 through January 2005. Sera of their paired maternal and cord blood were tested by an enzyme-linked immunosorbent assay method for CMV IgG and IgM antibodies. Additional data were collected for health measures and epidemiological characteristics through trained interviewers utilising structured questionnaires. RESULTS: Among 483 mothers studied, 93% were Taiwanese, 6.4% were immigrants from the south-eastern Asia and Mainland China, and 0.6% was aborigines. The seropositive rate of CMV IgG and IgM among the mothers was 91.1% and 3.5%, respectively. The immigrant mothers and the mothers younger than 20 years of age had a higher IgM seroprevalence (P < 0.05). Furthermore, 90.8% of the offspring had CMV IgG seropositivity and yet none of the neonates were CMV IgM positive. CONCLUSION: The seroprevalence of CMV among childbearing women is high in northern Taiwan. The immigrant mothers and the teenage mothers appear to have higher seropositivity of CMV IgM.