Marielle C. Brinkman

Residential environmental measurements in the national human exposure assessment survey (NHEXAS) pilot study in Arizona: preliminary results for pesticides and VOCs.

A major objective of the National Human Exposure Assessment Survey (NHEXAS) performed in Arizona was to conduct residential environmental and biomarker measurements of selected pesticides (chlorpyrifos, diazinon), volatile organic compounds (VOCs; benzene, toluene, trichloroethene, formaldehyde, 1,3-butadiene), and metals for total human exposure assessments. Both personal (e.g., blood, urine, dermal wipes, 24 h duplicate diet) and microenvironmental (e.g., indoor and outdoor air, house dust, foundation soil) samples were collected in each home in order to describe individual exposure via ingestion, inhalation, and dermal pathways, and to extrapolate trends to larger populations. This paper is a preliminary report of only the microenvironmental and dermal wipe data obtained for the target pesticides and VOCs, and provides comparisons with results from similar studies. Evaluations of total exposure from all sources and pathways will be addressed in future papers. The pesticides and VOCs all showed log-normal distributions of concentrations in the Arizona population sampled, and in most cases were detected with sufficient frequency to allow unequivocal description of the concentration by media at the 90th, 75th, and 50th (median) percentiles. Those combinations of pollutant and media, in which a large fraction of the measurements were below the detection limit of the analysis method used, included trichloroethene, 1,3-butadiene, and formaldehyde in outdoor air; chlorpyrifos and diazinon in outdoor air; and diazinon in dermal and window sill wipes. In general, indoor air concentrations were higher than outdoor air concentrations for all VOCs and pesticides investigated, and VOC levels were in good agreement with levels reported in other studies. In addition, the agreement obtained between co-located VOC samplers indicated that the low-cost diffusional badges used to measure concentrations are probably adequate for use in future monitoring studies. For the pesticides, the median levels found in indoor samples agreed well with other studies, although the levels corresponding to the upper 0.1–1% of the population were considerably higher than levels reported elsewhere, with indoor air levels as high as 3.3 and 20.5 µg/m3 for chlorpyrifos and diazinon, respectively. These data showed excellent correlation (Pearson and Spearman correlation coefficients of 0.998 and 0.998, respectively) between chlorpyrifos in indoor air and in the corresponding dermal wipes, and relatively poor correlation between chlorpyrifos in dust (µg/g or µg/m2) and dermal wipes (Pearson=0.055 µg/g and 0.015 µg/m2; Spearman=0.644 µg/g and 0.578 µg/m2). These data suggest the importance of dermal penetration of semi-volatiles as a route of residential human exposure.

Changes in breath trihalomethane levels resulting from household water-use activities

Common household water-use activities such as showering, bathing, drinking, and washing clothes or dishes are potentially important contributors to individual exposure to trihalomethanes (THMs), the major class of disinfection by-products of water treated with chlorine. Previous studies have focused on showering or bathing activities. In this study, we selected 12 common water-use activities and determined which may lead to the greatest THM exposures and result in the greatest increase in the internal dose. Seven subjects performed the various water-use activities in two residences served by water utilities with relatively high and moderate total THM levels. To maintain a consistent exposure environment, the activities, exposure times, air exchange rates, water flows, water temperatures, and extraneous THM emissions to the indoor air were carefully controlled. Water, indoor air, blood, and exhaled-breath samples were collected during each exposure session for each activity, in accordance with a strict, well-defined protocol. Although showering (for 10 min) and bathing (for 14 min), as well as machine washing of clothes and opening mechanical dishwashers at the end of the cycle, resulted in substantial increases in indoor air chloroform concentrations, only showering and bathing caused significant increases in the breath chloroform levels. In the case of bromodichloromethane (BDCM), only bathing yielded a significantly higher air level in relation to the preexposure concentration. For chloroform from showering, strong correlations were observed for indoor air and exhaled breath, blood and exhaled breath, indoor air and blood, and tap water and blood. Only water and breath, and blood and breath were significantly associated for chloroform from bathing. For BDCM, significant correlations were obtained for blood and air, and blood and water from showering. Neither dibromochloromethane nor bromoform gave measurable breath concentrations for any of the activities investigated because of their much lower tap-water concentrations. Future studies will address the effects that changes in these common water-use activities may have on exposure.

Exogenous and endogenous determinants of blood trihalomethane levels after showering.

Background We previously conducted a study to assess whether household exposures to tap water increased an individual’s internal dose of trihalomethanes (THMs). Increases in blood THM levels among subjects who showered or bathed were variable, with increased levels tending to cluster in two groups. Objectives Our goal was to assess the importance of personal characteristics, previous exposures, genetic polymorphisms, and environmental exposures in determining THM concentrations in blood after showering. Methods One hundred study participants completed a health symptom questionnaire, a 48-hr food and water consumption diary, and took a 10-min shower in a controlled setting. We examined THM levels in blood samples collected at baseline and 10 and 30 min after the shower. We assessed the significance of personal characteristics, previous exposures to THMs, and specific gene polymorphisms in predicting postshower blood THM concentrations. Results We did not observe the clustering of blood THM concentrations observed in our earlier study. We found that environmental THM concentrations were important predictors of blood THM concentrations immediately after showering. For example, the chloroform concentration in the shower stall air was the most important predictor of blood chloroform levels 10 min after the shower (p < 0.001). Personal characteristics, previous exposures to THMs, and specific polymorphisms in CYP2D6 and GSTT1 genes were significant predictors of both baseline and postshowering blood THM concentrations as well as of changes in THM concentrations associated with showering. Conclusion The inclusion of information about individual physiologic characteristics and environmental measurements would be valuable in future studies to assess human health effects from exposures to THMs in tap water.

Increases in tobacco exposure biomarkers measured in non-smokers exposed to sidestream cigarette smoke under controlled conditions

National surveys of the exposure of non-smokers to secondhand smoke based on serum cotinine analyses have consistently identified certain groups within the population including children, males and non-Hispanic Blacks as having relatively greater exposure. Although these differences in mean serum cotinine concentrations probably represent differences in exposure of individuals in their daily lives, it is also possible that metabolic or other differences in response might influence the results. To better define the nature of those findings, we have examined the response of 40 non-smokers including both men and women and African-Americans and whites to sidestream (SS) cigarette smoke generated by a smoking machine under controlled conditions. In this study, participants were exposed to aged, diluted SS smoke (ADSS) generated in an environmental chamber with a mean air nicotine concentration of 140 μg m−3 and 8.6 ppm CO for 4 h. Salivary cotinine was measured every 30 min, and serum cotinine samples were taken prior to, and 2 h after exposure. Urinary nicotine metabolites and NNAL, a tobacco-specific nitrosamine, and 4-aminobiphenyl (4-AB) haemoglobin adducts were also measured prior to and 2 h following the exposure. Under these uniform, controlled conditions, we found a similar response to ADSS smoke exposure among all the participants. In all cases a significant increase in biomarker concentration was noted following exposure, and the short-term increases in salivary cotinine concentration were quite similar at approximately 12 pg ml−1 min−1 among the groups. In this small study, no significant differences by gender or race were seen in the mean increases observed in cotinine, NNAL or 4-AB adducts following 4 h of exposure. Thus, our results are most consistent with a relatively uniform response in tobacco biomarker concentrations following short-term exposure to ADSS tobacco smoke, and suggest that biomarker measurements are capable of effectively indicating increases in exposure among groups of non-smokers.

Role of sweet and other flavours in liking and disliking of electronic cigarettes

Objective To examine the extent to which the perception of sweet and other flavours is associated with liking and disliking of flavoured electronic cigarettes (e-cigarettes). Methods 31 participants (13 females/18 males; 12 sole/19 dual users) vaped 6 commercially available flavours of blu Tanks: Classic Tobacco (CT), Magnificent Menthol (MM), Cherry Crush (CC), Vivid Vanilla (VV), Piña Colada (PC) and Peach Schnapps (PS); all ‘medium’ strength, 12 mg/mL nicotine concentration. For each flavoured e-cigarette, participants first rated liking/disliking on the Labeled Hedonic Scale, followed by perceived intensities of sweetness, coolness, bitterness, harshness and specific flavour on the generalised version of the Labeled Magnitude Scale. The psychophysical testing was conducted individually in an environmental chamber. Results PC was perceived as sweetest and liked the most; CT was perceived as least sweet and liked the least. Across all flavours, liking was correlated with sweetness (r=0.31), coolness (r=0.25), bitterness (r=−0.25) and harshness (r=−0.29, all p<0.001). Specifically, liking was positively correlated with sweetness of PS (r=0.56, p=0.001) and PC (r=0.36, p=0.048); and with coolness of MM, CT and VV (r=0.41–0.52, p<0.05). In contrast, harshness was negatively correlated with liking for CC, PC and PS (r=0.37–0.40, p<0.05). In a multivariate model, sweetness had the greatest positive impact on liking followed by coolness; harshness had the greatest negative impact on liking. Conclusions Our findings indicate that bitterness and harshness, most likely from nicotine, have negative impacts on the liking of e-cigarettes, but the addition of flavourants that elicit sweetness or coolness generally improves liking. The results suggest that flavours play an important role in e-cigarette preference and most likely use.

Exposure to and deposition of fine and ultrafine particles in smokers of menthol and nonmenthol cigarettes

Introduction: Research on the deposition of mainstream smoke particulate in the respiratory tract of smokers is needed to understand how exposure may vary based on cigarette menthol content. Methods: We conducted a nine-participant crossover study in which smokers were randomly assigned to cigarettes differing primarily in menthol content. Participants smoked the test cigarettes ad libitum for one week, provided spot urine samples, and then smoked four test cigarettes in a laboratory session; this was repeated for the other test cigarette in week two. Fine and ultrafine particulate matter in exhaled breath were characterized, and smoking behavior was monitored. Participant-specific mainstream smoke, generated using each participant’s topography data, was characterized. During home smoking, participants collected their spent test cigarette butts for estimates of mouth-level exposures (MLE) to mainstream nicotine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). Results: Participant-specific mainstream smoke NNK was higher (39%) and daily MLE to NNK was also higher (52%) when participants smoked the menthol cigarette. Nicotine was not significantly different. Participants retained more ultrafine particulate (43%) and fine particulate benzo(a)pyrene (43%) when smoking the menthol cigarette. There were no significant differences in the levels of urinary biomarkers for nicotine, NNK, or pyrene. Conclusion: This study demonstrates the use of noninvasive real-time techniques to measure exposure differences between cigarettes differing primarily in menthol content. Differences between NNK exposure, ultrafine particle and benzo(a)pyrene deposition, and smoking behavior were observed. Additional research using these techniques with cigarettes that differ only in menthol content is required to unequivocally attribute the exposure differences to presence or absence of menthol.

Design and Evaluation of a Breath-Analysis System for Biological Monitoring of Volatile Compounds

To ensure the health and safety of workers, integrated industrial hygiene methodologies often include biological monitoring of the workers to help understand their exposure to chemicals. To this end, a field-portable breath-analysis system was developed and tested to measure selected solvents in exhaled air. The exhaled breath data were evaluated using a physiologically based pharmacokinetic (PBPK) model to relate exposure to tissue dose. The system was designed to monitor workers every time they entered or left a work environment—a vast improvement over current 8-hour integrated monitoring strategies. The system combines (1) chemical dosimeters to measure airborne contaminant levels (analyzed in the field/workplace); (2) real-time breath analysis to quantitate exposure; and 3) PBPK models to estimate internal target tissue dose. To evaluate the system, field tests were conducted at two locations: (1) at an incinerator in Tennessee monitoring benzene and toluene exposures; and (2) a waste repackaging faci...

The influence of physicochemical properties on the internal dose of trihalomethanes in humans following a controlled showering exposure

Although disinfection of domestic water supply is crucial for protecting public health from waterborne diseases, this process forms potentially harmful by-products, such as trihalomethanes (THMs). We evaluated the influence of physicochemical properties of four THMs (chloroform, bromodichloromethane, dibromochloromethane, and bromoform) on the internal dose after showering. One hundred volunteers showered for 10 min in a controlled setting with fixed water flow, air flow, and temperature. We measured THMs in shower water, shower air, bathroom air, and blood samples collected at various time intervals. The geometric mean (GM) for total THM concentration in shower water was 96.2 μg/l. The GM of total THM in air increased from 5.8 μg/m3 pre shower to 351 μg/m3 during showering. Similarly, the GM of total-blood THM concentration increased from 16.5 ng/l pre shower to 299 ng/l at 10 min post shower. THM levels were significantly correlated between different matrices (e.g. dibromochloromethane levels) in water and air (r=0.941); blood and water (r=0.845); and blood and air (r=0.831). The slopes of best-fit lines for THM levels in water vs air and blood vs air increased with increasing partition coefficient of water/air and blood/air. The slope of the correlation plot of THM levels in water vs air decreased in a linear (r=0.995) fashion with increasing Henrys law constant. The physicochemical properties (volatility, partition coefficients, and Henrys law constant) are useful parameters for predicting THM movement between matrices and understanding THM exposure during showering.

Identification of New and Distinctive Exposures from Little Cigars.

Little cigar mainstream smoke is less well-characterized than cigarette mainstream smoke in terms of chemical composition. This study compared four popular little cigar products against four popular cigarette products to determine compounds that are either unique to or more abundant in little cigars. These compounds are categorized as new or distinctive exposures, respectively. Total particulate matter samples collected from machine-generated mainstream smoke were extracted with methylene chloride, and the extracts were analyzed using two-dimensional gas chromatography-time-of-flight mass spectrometry. The data were evaluated using novel data-processing algorithms that account for characteristics specific to the selected analytical technique and variability associated with replicate sample analyses. Among more than 25 000 components detected across the complete data set, ambrox was confirmed as a new exposure, and 3-methylbutanenitrile and 4-methylimidazole were confirmed as distinctive exposures. Concentrations of these compounds for the little cigar mainstream smoke were estimated at approximately 0.4, 0.7, and 12 μg/rod, respectively. In achieving these results, this study has demonstrated the capability of a powerful analytical approach to identify previously uncharacterized tobacco-related exposures from little cigars. The same approach could also be applied to other samples to characterize constituents associated with tobacco product classes or specific tobacco products of interest. Such analyses are critical in identifying tobacco-related exposures that may affect public health.

Determination of nicotine, glycerol, propylene glycol and water in electronic cigarette fluids using quantitative 1H NMR

Electronic cigarettes (e-cigarettes) or electronic nicotine delivery systems allow the user to inhale nicotine without burning or heating tobacco, and their use has been described as safer than tobacco cigarettes and as a means to smoking cessation. As ecigarettes are currently unregulated in the USA, studies have been undertaken to determine whether their use poses any potential health hazards. The fluid (e-liquid) contained within e-cigarettes has been described as containing less than 10wt% water and 50– 99wt% organic solvent. The manufacturer’s labels indicate that they contain water with the organic solvent being 1,2-propylene glycol (PG), and/or vegetable glycerol (VG), referred to here as glycerol as its origin was not verified. The e-liquids usually contain nicotine and flavorings, too. However, the actual chemical composition and amounts of these components vary considerably in individual e-liquids. These factors can play an important role in potential toxic and carcinogenic exposures from e-cigarette use. For example, e-liquids are corrosive to the metal components of the e-cigarette devices and may lead to inhalation of high levels of tin, lead and nickel. Being able to quantitatively determine the composition of the primary carrier solution of an e-liquid is an important aspect for understanding the potential health implications of their use. Because of nicotine’s addictive properties, quantifying its concentration is important for determining the addiction potential of an e-liquid. However, published data indicates that manufacturer’s labeling of e-liquid nicotine content does not necessarily agree with the independently measured nicotine content. Reported analytical methods for e-liquids are predominately based on gas chromatography (GC) and HPLC quantification techniques. However, none of the reported methods has been used to simultaneously determine the amount of water, PG, glycerol and nicotine that may be present in e-liquids in a single analysis. The use of H NMR for the quantitative analysis of e-cigarette chemical components has been reported in a few cases with quantification achieved by comparison to an external calibration curve. None of these methods included the use of an internal standard in the NMR sample for quantification. Each of these used a solvent (D2O, DMSO-d6) in which hydrogen/deuterium exchange can occur, making these solvents unsuitable for determining the amount ofwater present in the e-liquid. Whenwaterwasmeasured, a separate analysis, Karl Fischer coulometric titration, was used. As part of our ongoing investigations into the chemicals contained in e-liquids, we considered H NMR as a single analytical method to identify and quantify the most abundant components, PG, glycerol, water and nicotine. These chemicals were selected because variation in the relative proportions of these components may influence the amount of nicotine, flavorings and the type or amount of byproducts inhaled by the user during vaping. In pursuing H NMR, proper selection of the solvent was critical. Not only did the solvent have to dissolve the e-liquids at a concentration sufficient to readily determine the relatively low concentration of nicotine present in the e-liquid (≤2.4mg/ml), but it could not possess exchangeable protons, which would interfere with determining the amount of water present. Additionally, the residual H solvent signals could not interfere with those of the e-liquid components. To fulfill these requirements, perdeuterated N,N-dimethylformamide (DMF-d7) was selected as the solvent. We also selected to use an internal standard, 1,2,4,5-tetrachloro-3nitrobenzene, to support our quantitation efforts. This solvent and internal standard combination was tested first against a surrogate e-liquid (prepared from HPLC water and/or laboratory-grade PG, glycerol and nicotine) and then applied to e-liquids removed from non-refillable, retail e-cigarettes cartridges as well as those available for refillable e-cigarette cartridges.