Types and spatial contexts of neighborhood greenery matter in associations with weight status in women across 28 U.S. communities.

Excess body weight is a risk factor for many chronic diseases. Studies have identified neighborhood greenery as supportive of healthy weight. However, few have considered plausible effect pathways for ecosystem services (e.g., heat mitigation, landscape aesthetics, and venues for physical activities) or potential variations by climate. This study examined associations between weight status and neighborhood greenery that capture ecosystem services most relevant to weight status across 28 U.S. communities. Weight status was defined by body mass index (BMI) reported for 6591 women from the U.S. Sister Study cohort. Measures of greenery within street and circular areas at 500 m and 2000 m buffer distances from homes were derived for each participant using 1 m land cover data. Street area was defined as a 25 m-wide zone on both sides of street centerlines multiplied by the buffer distances, and circular area was the area of the circle centered on a home within each of the buffer distances. Measures of street greenery characterized the pedestrian environment to capture physically and visually accessible greenery for shade and aesthetics. Circular greenery was generated for comparison. Greenery types of tree and herbaceous cover were quantified separately, and a combined measure of tree and herbaceous cover (i.e., aggregate greenery) was also included. Mixed models accounting for the clustering at the community level were applied to evaluate the associations between neighborhood greenery and the odds of being overweight or obese (BMI > 25) with adjustment for covariates selected using gradient boosted regression trees. Analyses were stratified by climate zone (arid, continental, and temperate). Tree cover was consistently associated with decreased odds of being overweight or obese. For example, the adjusted odds ratio [AOR] was 0.92, 95% Confidence Interval [CI]: 0.88-0.96, given a 10% increase in street tree cover at the 2000 m buffer across the 28 U.S. communities. These associations held across climate zones, with the lowest AOR in the arid climate (AOR: 0.74, 95% CI: 0.54-1.01). In contrast, associations with herbaceous cover varied by climate zone. For the arid climate, a 10% increase in street herbaceous cover at the 2000 m buffer was associated with lower odds of being overweight or obese (AOR: 0.75, 95% CI: 0.55-1.03), whereas the association was reversed for the temperate climate, the odds increased (AOR: 1.19, 95% CI: 1.05-1.35). Associations between greenery and overweight/obesity varied by type and spatial context of greenery, and climate. Our findings add to a growing body of evidence that greenery design in urban planning can support public health. These findings also justify further defining the mechanism that underlies the observed associations.

Data Mining Approaches for Assessing Chemical Coexposures Using Consumer Product Purchase Data.

The use of consumer products presents a potential for chemical exposures to humans. Toxicity testing and exposure models are routinely employed to estimate risks from their use; however, a key challenge is the sparseness of information concerning who uses products and which products are used contemporaneously. Our goal was to demonstrate a method to infer use patterns by way of purchase data. We examined purchase patterns for three types of personal care products (cosmetics, hair care, and skin care) and two household care products (household cleaners and laundry supplies) using data from 60,000 households collected over a one-year period in 2012. The market basket analysis methodology frequent itemset mining (FIM) was used to identify co-occurring sets of product purchases for all households and demographic groups based on income, education, race/ethnicity, and family composition. Our methodology captured robust co-occurrence patterns for personal and household products, globally and for different demographic groups. FIM identified cosmetic co-occurrence patterns captured in prior surveys of cosmetic use, as well as a trend of increased diversity of cosmetic purchases as children mature to teenage years. We propose that consumer product purchase data can be mined to inform person-oriented use patterns for high-throughput chemical screening applications, for aggregate and combined chemical risk evaluations.

Integrating Personal Air Sensor and GPS to Determine Microenvironment-Specific Exposures to Volatile Organic Compounds.

Personal exposure to volatile organic compounds (VOCs) from indoor sources including consumer products is an understudied public health concern. To develop and evaluate methods for monitoring personal VOC exposures, we performed a pilot study and examined time-resolved sensor-based measurements of geocoded total VOC (TVOC) exposures across individuals and microenvironments (MEs). We integrated continuous (1 min) data from a personal TVOC sensor and a global positioning system (GPS) logger, with a GPS-based ME classification model, to determine TVOC exposures in four MEs, including indoors at home (Home-In), indoors at other buildings (Other-In), inside vehicles (In-Vehicle), and outdoors (Out), across 45 participant-days for five participants. To help identify places with large emission sources, we identified high-exposure events (HEEs; TVOC > 500 ppb) using geocoded TVOC time-course data overlaid on Google Earth maps. Across the 45 participant-days, the MEs ranked from highest to lowest median TVOC were: Home-In (165 ppb), Other-In (86 ppb), In-Vehicle (52 ppb), and Out (46 ppb). For the two participants living in single-family houses with attached garages, the median exposures for Home-In were substantially higher (209, 416 ppb) than the three participant homes without attached garages: one living in a single-family house (129 ppb), and two living in apartments (38, 60 ppb). The daily average Home-In exposures exceeded the estimated Leadership in Energy and Environmental Design (LEED) building guideline of 108 ppb for 60% of the participant-days. We identified 94 HEEs across all participant-days, and 67% of the corresponding peak levels exceeded 1000 ppb. The MEs ranked from the highest to the lowest number of HEEs were: Home-In (60), Other-In (13), In-Vehicle (12), and Out (9). For Other-In and Out, most HEEs occurred indoors at fast food restaurants and retail stores, and outdoors in parking lots, respectively. For Home-In HEEs, the median TVOC emission and removal rates were 5.4 g h-1 and 1.1 h-1, respectively. Our study demonstrates the ability to determine individual sensor-based time-resolved TVOC exposures in different MEs, in support of identifying potential sources and exposure factors that can inform exposure mitigation strategies.

How do natural features in the residential environment influence women's self-reported general health? Results from cross-sectional analyses of a U.S. national cohort.

BACKGROUND: The relationship between health and human interaction with nature is complex. Here we conduct analyses to provide insights into potential health benefits related to residential proximity to nature. OBJECTIVES: We aimed to examine associations between measures of residential nature and self-reported general health (SRGH), and to explore mediation roles of behavioral, social, and air quality factors, and variations in these relationships by urbanicity and regional climate. METHODS: Using residential addresses for 41,127 women from the Sister Study, a U.S.-based national cohort, we derived two nature exposure metrics, canopy and non-gray cover, using Percent Tree Canopy and Percent Developed Imperviousness from the National Land Cover Database. Residential circular buffers of 250 m and 1250 m were considered. Gradient boosted regression trees were used to model the effects of nature exposure on the odds of reporting better SRGH (Excellent/Very Good versus the referent, Good/Fair/Poor). Analyses stratified by urbanicity and regional climate (arid, continental, temperate) and mediation by physical activity, social support, and air quality were conducted. RESULTS: A 10% increase in canopy and non-gray cover within 1250 m buffer was associated with 1.02 (95% CI: 1.00-1.03) and 1.03 (95% CI: 1.01-1.04) times the odds of reporting better SRGH, respectively. Stronger associations were observed for the urban group and for continental climate relative to other strata. Social support and physical activity played a more significant mediation role than air quality for the full study population. DISCUSSION: Findings from this study identified a small but important beneficial association between residential nature and general health. These findings could inform community planning and investments in neighborhood nature for targeted health improvements and potential societal and environmental co-benefits.

Advancing Environmental Epidemiology to Assess the Beneficial Influence of the Natural Environment on Human Health and Well-Being.

Environmental health research can be oriented across a continuum of effects ranging from adverse to cobenefits to salutogenic. We argue that the salutogenic end of the continuum is insufficiently represented in research and as a basis for environmental protection, even though there is growing evidence that the natural environment plays a critical role in blunting adverse effects and promoting human health and well-being. Thus, we advocate for advancing environmental health research through environmental epidemiology that more fully and directly accounts for the salutogenic effects of the natural environment on individual well-being by (1) defining "natural environments" broadly, from pristine natural areas to urban green infrastructure; (2) considering exposure comprehensively to encompass residential, occupational, and recreational settings, local and distant, day-to-day and occasional; (3) doing individual-level assessments that include both health and well-being outcomes and one's experience of nature, including potential mediation by connectedness to nature and individual perceptions and preferences, as well as sociocultural and demographic effect modifiers; and (4) collecting longitudinal and nationally representative data.

Assessment of temperature and ultraviolet radiation effects on sunburn incidence at an inland U.S. Beach: A cohort study.

BACKGROUND: Increases in outdoor temperature may lead to increases in sunburn, outdoor exposure, and skin cancer in human populations. OBJECTIVE: This study aimed to quantify sunburn incidence and risk for Ohio beachgoers exposed to varying outdoor conditions. METHODS: Sunburn incidence data were obtained through a prospective cohort study at East Fork Lake (Cincinnati, Ohio, USA). Recruitment occurred over 26 weekend days. Beach interviews and follow-up telephone interviews obtained exposure and health information. New sunburns were self-reported 8-9 days post-enrollment. Survey data were paired with ultraviolet radiation (UVR) index and temperature data for statistical analysis. RESULTS: Among 947 beachgoers, new sunburns were reported in 18% of swimmers. Sunburn incidence was associated with temperature (odds ratio = 1.2; 95% CI: 1.1 - 1.4) and UVR index (odds ratio = 1.6; 95% CI: 1.0 - 2.5) in models adjusted for water exposure, arrival time, and beach visit frequency. Some evidence of a temperature+UVR interaction was observed. LIMITATIONS: Exposure and sunburn data were self-reported without clinical diagnosis and date of onset. The follow-up period enabled sunburns to be reported from a variety of days rather than only the beach visit day thereby limiting interpretation. Sun protection behaviors were not evaluated. CONCLUSIONS: Temperature and UVR influence sunburn frequency. Temperature, however was more strongly associated with sunburn in beachgoers than the nearest measured UVR index, suggesting future investigations are needed to better understand how temperature effects sunburn development. Interventions for decreasing sunburn are needed.

Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency.

Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.

Association of Redlining and Natural Environment with Depressive Symptoms in Women in the Sister Study.

BACKGROUND: Improving mental health is recognized as an important factor for achieving global development goals. Despite strong evidence that neighborhood greenery promotes better mental health, there are environmental justice concerns over the distribution of neighborhood greenery. Underlying these concerns are present-day consequences of historical discriminatory financial investment practices, such as redlining which was established by the U.S. Federal Home Owners' Loan Corporation (HOLC) in the 1930s. The impacts of redlining on environmental and health disparities have been researched extensively. However, the influences of redlining on the associations between neighborhood environment and health outcomes have not been fully assessed. OBJECTIVES: The aim of this study was to examine whether associations between residential tree cover and depressive symptoms vary across areas subject to HOLC practices. METHODS: Depressive symptoms were defined by the 10-item Center for Epidemiologic Studies Depression Scale collected during the period 2008-2012 for 3,555 women in the Sister Study cohort residing in cities subject to HOLC practices across the United States. HOLC rating maps were obtained from the Mapping Inequality Project, University of Richmond, with neighborhoods graded as A (best for financial investment, green), B (still desirable, blue), C (declining, yellow), and D (hazardous, red-known as redlined). Tree cover within 500m and 2,000m from residences was estimated using 2011 U.S. Forest Service Percent Tree Canopy Cover. Mixed model using climate zone as the random effect was applied to evaluate the associations with adjustments for potential covariates. Analyses were stratified by HOLC grade. RESULTS: Tree cover was significantly higher in neighborhoods with better HOLC grades. A 10% increase in tree cover was associated with reduced odds of depressive symptoms for the full study population, with adjusted odds ratios (AORs) of 0.93 [95% confidence interval (CI): 0.88, 0.99], and 0.91 (0.85, 0.97) for 500-m and 2,000-m buffer, respectively. Across HOLC grades, the strongest associations were observed in redlined neighborhoods, with respective AORs of 0.72 (95% CI: 0.52, 0.99) and 0.63 (95% CI: 0.45, 0.90) for 500-m and 2,000-m buffer. DISCUSSION: Findings support a remediation strategy focused on neighborhood greenery that would address multiple public health priorities, including mental health and environmental justice. https://doi.org/10.1289/EHP12212.

In vivo phycocyanin flourometry as a potential rapid screening tool for predicting elevated microcystin concentrations at eutrophic lakes.

Current approaches for assessing human health risks associated with cyanotoxins often rely on the quantification of microcystin. Significant limitations of current approaches are cost and time to obtain a result. To address these challenges, a numerical index for screening microcystin risks above the World Health Organization's (WHO) low-risk threshold for microcystin was developed for eutrophic Midwestern U.S. lakes based on water quality results from 182 beach water samples collected from seven Ohio lakes. In 48 (26.4%) samples we observed microcystin concentrations as measured by ELISA that exceeded the 4 µg/L microcystin threshold. A multivariable logistic regression model using practical real-time measures of in vivo phycocyanin (by fluorometry) and secchi depth was constructed to estimate the probability of a beach sample exceeding 4 µg/L microcystin. The final model achieved statistical significance (p = 0.030) as well as good calibration (as measured by the goodness-of-fit test comparing observed to expected counts within deciles of risk based on the model, p = 0.329) and discrimination (as indicated by the area under the receiver-operator-curve (0.795)). These results demonstrate two rapid and practical measures of recreational water quality are effective in identifying "at risk" lake conditions warranting additional management (e.g., advisory and/or advanced testing).

A pilot study of workplace dermal exposures to cypermethrin at a chemical manufacturing plant.

Exposure during the manufacture of pesticides is of particular concern due to their toxicity and because little is known about worker exposure, since most studies have focused on end-use application within agriculture or buildings. Even though dermal exposure can be expected to dominate for pesticides, little is known about workplace dermal exposures or even appropriate methods for their assessment. The current study begins to address this gap by evaluating alternative methods for assessing dermal exposure at a chemical manufacturing plant. For this pilot study, eight workers were recruited from a U.S. plant that produced the pesticide cypermethrin. Exposure was evaluated using three approaches: (1) survey assessment (questionnaire), (2) biological monitoring, and (3) workplace environmental sampling including ancillary measurements of glove contamination (interior and exterior). In each case, cypermethrin was quantified by enzyme-linked immunosorbent assay (ELISA). Environmental measurements identified two potential pathways of cypermethrin exposure: glove and surface contamination. Workplace exposure was also indicated by urine levels (specific gravity adjusted) of the parent compound, which ranged from 35 to 253 µg/L (median of 121 µg/L) with no clear trend in levels from pre- to post-shift. An exploratory analysis intended to guide future studies revealed a positive predictive association (Spearman correlation, p ≤ 0.10) between post-shift urine concentrations and a subset of survey questions evaluating worker knowledge, attitudes, and perceptions (KAP) of workplace dermal hazards, i.e., personal protective equipment self-efficacy, and inverse associations with behavior belief and information belief scales. These findings are valuable in demonstrating a variety of dermal exposure methods (i.e., behavioral attributes, external contamination, and biomarker) showing feasibility and providing measurement ranges and preliminary associations to support future and more complete assessments. Although these pilot data are useful for supporting design and sample size considerations for larger exposure and health studies, there is a need for validation studies of the ELISA assay for quantification of cypermethrin and its metabolites in urine.

Mining of Consumer Product Ingredient and Purchasing Data to Identify Potential Chemical Coexposures.

BACKGROUND: Chemicals in consumer products are a major contributor to human chemical coexposures. Consumers purchase and use a wide variety of products containing potentially thousands of chemicals. There is a need to identify potential real-world chemical coexposures to prioritize in vitro toxicity screening. However, due to the vast number of potential chemical combinations, this identification has been a major challenge. OBJECTIVES: We aimed to develop and implement a data-driven procedure for identifying prevalent chemical combinations to which humans are exposed through purchase and use of consumer products. METHODS: We applied frequent itemset mining to an integrated data set linking consumer product chemical ingredient data with product purchasing data from 60,000 households to identify chemical combinations resulting from co-use of consumer products. RESULTS: We identified co-occurrence patterns of chemicals over all households as well as those specific to demographic groups based on race/ethnicity, income, education, and family composition. We also identified chemicals with the highest potential for aggregate exposure by identifying chemicals occurring in multiple products used by the same household. Last, a case study of chemicals active in estrogen and androgen receptor in silico models revealed priority chemical combinations co-targeting receptors involved in important biological signaling pathways. DISCUSSION: Integration and comprehensive analysis of household purchasing data and product-chemical information provided a means to assess human near-field exposure and inform selection of chemical combinations for high-throughput screening in in vitro assays. https://doi.org/10.1289/EHP8610.

Effectiveness of UV-C equipped vacuum at reducing culturable surface-bound microorganisms on carpets.

Carpets are both sinks and sources for exposure to chemicals, allergens, and microbes and consequently influence health, including asthma, allergies, and infectious diseases. Asthmatics, children, and the immune-compromised are particularly vulnerable to health risks resulting from exposure to carpet contaminants. To address this risk, a commercial upright vacuum cleaner with an ultraviolet germicidal lamp (λ=253.7 nm, UVC) has been developed for residential and commercial uses. However, its effectiveness in reducing microbial load on real-world carpets has not been previously demonstrated. Accordingly, the purpose of the current study was to evaluate the effectiveness of a UVC-equipped vacuum in reducing the carpet surface-bound microbial load. This was accomplished by comparing the carpet microbial surface load from pre- to post-treatment of 9 ft(2) in-use carpet sections under three treatment scenarios: 1) UVC alone (UV), 2) the beater-bar plus vacuum (BB+Vac), or 3) a combination of all three (COMB). Each treatment was two minutes in duration. Microbial surface loads were measured by pressing contact plates containing Sabourauds Dextrose agar onto the carpet surface. In-use carpets from three locations were tested in place. The treatment effect was evaluated at two levels. First, we considered the mean reduction in CFU from pre- to post-treatment for each 9 ft(2) carpet grid (n = 4 for each treatment). The second level considered each 1 ft(2) section using a paired analysis (n = 40 to 49 for each treatment). A total of 125 pre/post-sample pairs were collected across the three treatments. Results showed that all three treatments were associated with a reduction in carpet microbial load (p < 0.0001). The COMB yielded the largest reduction of 13 CFU/plate (87% reduction) and was approximately the sum of the individual effects of either UVC (6.6 CFU/plate, 60% reduction, p = 0.009) or BB+Vac (7.3 CFU/plate, 78% reduction, p < 0.0001). We therefore conclude that a UVC-equipped vacuum approximately doubles the unit's effectiveness in reducing surface-bound microbial load, thereby holding promise as a means for decreasing indoor infectious disease risk.

The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency.

The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data. The expanding number of chemicals found in commerce and the environment, coupled with time and resource requirements for traditional toxicity testing and exposure characterization, continue to underscore the need for new approaches. In 2005, EPA charted a new course to address this challenge by embracing computational toxicology (CompTox) and investing in the technologies and capabilities to push the field forward. The return on this investment has been demonstrated through results and applications across a range of human and environmental health problems, as well as initial application to regulatory decision-making within programs such as the EPA's Endocrine Disruptor Screening Program. The CompTox initiative at EPA is more than a decade old. This manuscript presents a blueprint to guide the strategic and operational direction over the next 5 years. The primary goal is to obtain broader acceptance of the CompTox approaches for application to higher tier regulatory decisions, such as chemical assessments. To achieve this goal, the blueprint expands and refines the use of high-throughput and computational modeling approaches to transform the components in chemical risk assessment, while systematically addressing key challenges that have hindered progress. In addition, the blueprint outlines additional investments in cross-cutting efforts to characterize uncertainty and variability, develop software and information technology tools, provide outreach and training, and establish scientific confidence for application to different public health and environmental regulatory decisions.

The longitudinal dependence of black carbon concentration on traffic volume in an urban environment.

The purpose of this study was to evaluate the effect of traffic volume on ambient black carbon (BC) concentration in an inner-city neighborhood "hot spot" while accounting for modifying effects of weather and time. Continuous monitoring was conducted for 12 months at the Baltimore Traffic Study site surrounded by major urban streets that together carry over 150,000 vehicles per day. Outdoor BC concentration was measured with an Aethalometer; vehicles were counted pneumatically on two nearby streets. Meteorological data were also obtained. Missing data were imputed and all data were normalized to a 5-min observational interval (n = 105,120). Time-series modeling accounted for autoregressively (AR) correlated errors. This study found that outdoor BC was positively correlated at a statistically significant level with neighborhood-level vehicle counts, which contributed at a rate of 66 +/- 10 (SE) ng/m3 per 100 vehicles every 5 min. Winds from the SW-S-SE quarter were associated with the greatest increases in BC (376-612 ng/m3). These winds would have entrained BC from Baltimore's densely trafficked central business district, as well as a nearby interstate highway. The strong influence of wind direction implicates atmospheric transport processes in determining BC exposure. Dew point, mixing height, wind speed, season, and workday were also statistically significant predictors. Background exposure to BC was estimated to be 905 ng/m3. The optimal, statistically significant representation of BC's autocorrelation was AR([1:6]) x 288 x 2016, where the short-term AR factor (lags 1-6) indicated that BC concentrations are correlated for up to 30 min, and the AR factors for lags 288 and 2016 indicate longer-term autocorrelations at diurnal and weekly cycles, respectively. It was concluded that local exposure to BC from mobile sources is substantially modified by meteorological and temporal conditions, including atmospheric transport processes. BC concentration also demonstrates statistically significant autocorrelation at several time scales.

Home indoor pollutant exposures among inner-city children with and without asthma.

BACKGROUND: Evidence for environmental causes of asthma is limited, especially among African Americans. To look for systematic differences in early life domestic exposures between inner-city preschool children with and without asthma, we performed a study of home indoor air pollutants and allergens. METHODS: Children 2-6 years of age were enrolled in a cohort study in East Baltimore, Maryland. From the child's bedroom, air was monitored for 3 days for particulate matter 0.05]. Settled dust allergen levels (cat, dust mite, cockroach, dog, and mouse) were also similar in bedrooms of asthmatic and control children. CONCLUSIONS: Exposures to common home indoor pollutants and allergens are similar for inner-city preschool children with and without asthma. Although these exposures may exacerbate existing asthma, this study does not support a causative role of these factors for risk of developing childhood asthma.

Methods and measurements for estimating human dermal uptake of volatile organic compounds and for deriving dermal permeability coefficients.

ABSTRACT Water contamination of public drinking and recreational waters with volatile organic compounds (VOCs) is widespread, resulting in human exposure through multiple routes. Although dermal absorption is of considerable importance, there is great uncertainty in the dermal permeability coefficient (K(P)) for many VOCs due to the methods by which they are derived. We present a human in vivo experimental approach for the measurement of VOC dermal uptake from water contaminated at environmentally relevant concentrations and for determination of K(P). Dermal permeability was estimated from 11 adult subjects following immersion of their hand and forearm into a sealed 4.8-L Plexiglas cylinder containing 100 mug/L each of chloroform, 1,1,1-trichloroethane (111-TCA), and toluene and 400 mug/L of methyl tertiary butyl ether (MTBE) in water. Uptake was determined by measuring the decrease in VOC water concentration during the exposure. A control glass arm accounted for nondermal losses. The concentration of VOCs was determined by solid-phase microextraction (SPME) and analysis with gas chromatography/mass spectrometry. For the eight male and three female adult subjects, on average there was a dermal uptake-attributed 13.5%, 14.9%, 20.8%, and 7.3% decrease in the concentration after 1 h exposure for chloroform, 111-TCA, toluene, and MTBE, respectively. The resulting mean K(P) (standard deviation) was estimated to be 0.166 (0.108), 0.167 (0.107), 0.250 (0.064), and 0.109 (0.157) cm/h for the respective analytes. The experimental K(P) values presented here exceed the previously published model-estimated K(P) values by factors ranging from 6 to 57, suggesting that the published model-estimated K(P) values may underestimate actual VOC dermal absorption from water.

Urinary biomarkers of 1,3-butadiene in environmental settings using liquid chromatography isotope dilution tandem mass spectrometry.

Although, 1,3-butadiene is a known human carcinogen emitted from mobile sources, little is known about traffic-related human exposure to this toxicant. This pilot study was designed to characterize traffic-related environmental exposure to 1,3-butadiene and evaluate its urinary mercapturic acids as biomarkers of exposure in these settings. Personal air samples and multiple urine samples were collected on two separate occasions from three groups of individuals that differed by spatial proximity as well as intensity of traffic: (i) toll collectors, (ii) urban-weekday and (iii) suburban-weekend group. Air samples were analyzed using thermal desorption followed by GC/MS and urine samples were analyzed using isotope dilution liquid chromatography tandem mass spectrometry (ID-LC-MS/MS) for two mercapturic acids of 1,3-butadiene: monohydroxy-3-butenyl mercapturic acid (MHBMA) and 1,2-dihydroxybutyl mercapturic acid (DHBMA). Exposure differed between groups (p<0.05) with median values of 2.38, 1.62 and 0.88 microg/m(3) for toll collectors, the urban-weekday group and the suburban-weekend group, respectively. A refined ID-LC-MS/MS method enabled detection of MHBMA, previously detected only in occupational settings, with high frequency. MHBMA and DHBMA were detected in 95 and 100% of urine samples at levels (mean+/-S.D.) of 9.7+/-9.5, 6.0+/-4.3 and 6.8+/-2.6 ng/mL for MHBMA and 378+/-196, 258+/-133 and 306+/-242 ng/mL for DHBMA for the three different groups, respectively. Mean biomarker levels were higher among the toll collectors compared to the other two groups, however, the differences were not statistically significant (p>0.05). This study is the first to evaluate 1,3-butadiene biomarkers for subtle differences in environmental exposures. However, additional research will be required to ascertain whether the lack of statistical association observed here is real or attributable to unexpectedly small differences in exposure between groups (<1 microg/m(3)), non-specificity of the biomarker at low exposure, and/or small sample size.

Development of a questionnaire to assess worker knowledge, attitudes and perceptions underlying dermal exposure.

OBJECTIVES: Workers' behavior is identified as an important determinant of dermal exposure and is influenced by knowledge, attitudes, and risk perceptions. Because behavior may be a significant predictor of exposure, its assessment provides a means for examining exposure and designing strategies and incentives that encourage worker protective behavior. Currently, there are no psychosocial instruments examining worker knowledge, attitudes, and perceptions with respect to dermal hazards. Accordingly, a questionnaire was developed and tested to provide an instrument for measuring worker knowledge, attitudes, and perceptions. METHODS: The questionnaire was developed on the basis of a literature review and expert consultation. Scales were constructed based on standard methods. Two worker focus groups were used to evaluate worker understanding and content validity of the KAP (knowledge, attitudes, perceptions) questionnaire. The resulting 115-item questionnaire that included scales for knowledge (N=13), attitudes (N=27), perceptions (N=15), behavior (N=8), behavioral intentions (N=15), barriers (N=13), and facilitators (N=5) was tested on 89 workers from 19 facilities. RESULTS: The concepts identified in the focus groups included worker perception of higher risk due to a poor fit and replacement frequency for personal protective equipment and cross-contamination by workers moving into work zones. Field testing of the questionnaire (N=89) yielded Cronbach's alpha reliability scores ranging from 0.87 for the self-efficacy personal protective equipment scale to 0.92 for the overall belief scale, indicating high internal reliability. CONCLUSIONS: Although further testing and refinement is needed, this survey instrument provides an initial and conceptually unique means for evaluating behavioral determinants of worker dermal exposure.

Computational Exposure Science: An Emerging Discipline to Support 21st-Century Risk Assessment.

BACKGROUND: Computational exposure science represents a frontier of environmental science that is emerging and quickly evolving. OBJECTIVES: In this commentary, we define this burgeoning discipline, describe a framework for implementation, and review some key ongoing research elements that are advancing the science with respect to exposure to chemicals in consumer products. DISCUSSION: The fundamental elements of computational exposure science include the development of reliable, computationally efficient predictive exposure models; the identification, acquisition, and application of data to support and evaluate these models; and generation of improved methods for extrapolating across chemicals. We describe our efforts in each of these areas and provide examples that demonstrate both progress and potential. CONCLUSIONS: Computational exposure science, linked with comparable efforts in toxicology, is ushering in a new era of risk assessment that greatly expands our ability to evaluate chemical safety and sustainability and to protect public health. CITATION: Egeghy PP, Sheldon LS, Isaacs KK, Özkaynak H, Goldsmith M-R, Wambaugh JF, Judson RS, Buckley TJ. 2016. Computational exposure science: an emerging discipline to support 21st-century risk assessment. Environ Health Perspect 124:697-702; http://dx.doi.org/10.1289/ehp.1509748.

Socioeconomic and racial disparities in cancer risk from air toxics in Maryland.

We linked risk estimates from the U.S. Environmental Protection Agency's National Air Toxics Assessment (NATA) to racial and socioeconomic characteristics of census tracts in Maryland (2000 Census) to evaluate disparities in estimated cancer risk from exposure to air toxics by emission source category. In Maryland, the average estimated cancer risk across census tracts was highest from on-road sources (50% of total risk from nonbackground sources), followed by nonroad (25%), area (23%), and major sources (< 1%). Census tracts in the highest quartile defined by the fraction of African-American residents were three times more likely to be high risk (> 90th percentile of risk) than those in the lowest quartile (95% confidence interval, 2.0-5.0). Conversely, risk decreased as the proportion of whites increased (p < 0.001). Census tracts in the lowest quartile of socioeconomic position, as measured by various indicators, were 10-100 times more likely to be high risk than those in the highest quartile. We observed substantial risk disparities for on-road, area, and nonroad sources by socioeconomic measure and on-road and area sources by race. There was considerably less evidence of risk disparities from major source emissions. We found a statistically significant interaction between race and income, suggesting a stronger relationship between race and risk at lower incomes. This research demonstrates the utility of NATA for assessing regional environmental justice, identifies an environmental justice concern in Maryland, and suggests that on-road sources may be appropriate targets for policies intended to reduce the disproportionate environmental health burden among economically disadvantaged and minority populations.