Browsing by Subject "Consumer products"

Semi-volatile organic compounds (SVOCs) are used in consumer products in a wide variety of applications such as flame retardants, plasticizers, pesticides, preservatives, and fragrances. Due to their extensive use in everyday products, SVOCs are widely detected in indoor environments, and human exposure is common and often chronic. As the wealth of toxicological data examining the negative health impacts of these compounds grows, the need for reliable tools to accurately measure human exposure becomes increasingly more crucial. In the past few decades, external exposure to these compounds have been evaluated through measurements in indoor air, house dust, and hand wipes, all of which have been shown to be associated with internal dose (e.g., concentrations in urine or blood). However, there are significant limitations to using each of these approaches to characterizing exposure. In recent years, silicone wristbands have been used as personal passive samplers for evaluating ambient exposure to a wide array of consumer product and industrial compounds. While over a thousand chemicals have been reported to be detected on the wristbands, very few studies have measured the concentrations on wristbands and determined how well they correlate to established biomarkers of exposure. This dissertation research sought to evaluate the use of silicone wristbands for measuring personal exposure to three classes of SVOCs- organophosphate esters (OPEs), brominated flame retardants (BFRs), and phthalates. The central hypothesis is that wristbands are an effective tool for evaluating personal exposure to SVOCs and provide more accurate measures of exposure compared to tools currently in use.

Within the first aim of this dissertation research, paired samples of polyurethane foam (collected from sofas), house dust, and serum were analyzed for flame retardants (FRs) chemicals and associations were evaluated. The detection of two FR mixtures, PentaBDE and FM 550, in foam was significantly associated with 4 to 6.5 times as high concentrations of their primary components in house dust (p<0.01). These relationships were modified by the size of the sofa footprint within the room and dust-loading rates. PentaBDE in foam was also associated with higher levels of individual PBDE congeners in serum, particularly two of the primary congeners BDE-47 and -153. Participants who lived in a home with a sofa containing PentaBDE had serum BDE-47 levels that were 2.5 times as high as participants whose sofa did not contain PentaBDE (p<0.01). This study was the first to relate a specific FR application in a consumer product with house dust and a known biomarker of exposure.

For the second aim of this research, adult exposure to OPEs and BFRs were evaluated using silicone wristbands. OPEs quantified on the wristbands were significantly associated with metabolites from pooled urine samples, and polybrominated diphenyl ethers (PBDEs) on the wristbands were similarly correlated to PBDE levels in serum (rs=0.4-0.6, p<0.05). Several novel BFR compounds which lack verified biomarkers of exposure were also measured on the wristbands and reported for the first time. These two studies were the first to evaluate FR concentrations on wristbands with known biomarkers and represent two of now four published manuscripts providing evidence that measurements on wristbands are predictive of internal dose.

In the third aim of this research, children’s exposure to OPEs, phthalates, and BFRs were examined using silicone wristbands. The ability of the wristband measurements to predict urinary metabolite levels of OPEs and phthalates was compared to that of hand wipes and house dust. Across the three classes, the children’s wristband concentrations were positively and significantly associated with a number of their corresponding biomarkers in both urine and serum, similar to observations in our adult cohort. For OPEs, phthalates, and PBDEs, the wristbands were found to have similar or an improved utility, compared to hand wipes and dust, for evaluating children’s exposures to these compounds. For instance, one of the OPEs, 4-tertbutylphenyl diphenyl phosphate (4tBPDPP), on wristbands was more strongly correlated to its urinary metabolite, tert-butyl phenyl phenyl phosphate (tb-PPP), compared to that on hand wipes and dust (rs=0.35, p<0.01, compared to rs=0.16 and 0.05 for hand wipes and dust, respectively). For the phthalate benzyl butyl phthalate (BBP), wristbands and hand wipes were similar associated with the urinary metabolite, mono benzyl phthalate (MBzP), but both were stronger than the dust correlation (rs=0.56 for wristbands and hand wipes, p<0.001; rs=0.23 for dust, p<0.05). Similar results were observed among the PBDEs on the three exposure mediums and their serum biomarkers, although the magnitudes of correlation with serum were more similar for wristbands and dust.

Taken together this dissertation research provides some of the first insights on the evaluation of personal exposures to SVOCs using silicone wristbands. It includes six distinct studies evaluating human exposure to sixty-five chemicals from three classes of compounds. Further, this research offers novel contributions to the field of exposure science, evaluating the relationship between wristbands and established biomarkers of exposure and comparing them to the existing tools used in standard exposure assessments. Wristbands have the potential to serve as an inexpensive and non-invasive medium for evaluating human exposure to chemical mixtures, and this work provides support for their use in large-scale research efforts to characterize SVOC exposures. Additional research should continue to assess wristbands for their ability to measure meaningful exposures for additional classes of chemicals, and importantly, identify the pathways of exposure (e.g., dermal absorption, inhalation, etc.) that are captured by the wristbands.

Chemicals in consumer products can influence our risk for developing adverse health conditions. This research addresses knowledge gaps in our ability to evaluate chemical safety, particularly for emerging substances on the market. Acknowledging the need for more high-throughput exposure and hazard models to support risk assessment, computational frameworks leveraging machine learning strategies and "big data" from public databases and mass social data sources were tested.

First, to understand consumer exposure, we require a better understanding of ingredient concentrations in products. A computational framework was developed to estimate chemical weight fractions for consumer products containing emerging substances. Nanomaterial-enabled products were used as a case study to represent such substances with limited physicochemical property data. Feature variables included chemical properties, functional use categories (e.g., antimicrobial), the type of product and its matrix. Weight fractions were classified as low, medium or high using a random forest or nonlinear support vector classifier. Performance of machine learning models was qualitatively compared with that of models from a second framework trained on data-rich, bulk-scale organic chemical product data. Models could roughly stratify material-product observations into weight fraction bins with moderate success. The best model achieved an average balanced accuracy of 73% on nanomaterials product data. Chemical functional use features served as particularly insightful predictors, suggesting that functional use data may be useful in evaluating the safety and sustainability of emerging chemicals. Investment in chemical and product data collection could see continued improvement of such machine learning models.

Shifting focus to the impact of chemicals on consumers, data on personal care products, ingredients, and customer reviews from online retailers and databases was collected to see if certain chemicals might increase risk of adverse reactions to products. The study scope was narrowed to shampoo products for hypothesis testing. Processing steps in the data pipeline included informatics and machine learning methods, namely, natural language processing for interpreting product reviews, text extraction from images of product labels, and feature reduction using chemical structure and ingredient source data. Fifty-one ingredient clusters were identified as having a significant correlation with higher adverse reaction rates in consumers when present in shampoos. Among these, there were a few common plant-based ingredients and synthetic preservatives known for causing skin sensitivity or irritation. In comparison with other constituents, however, the positively correlated ingredient groups had a general lack of published structural, physicochemical property and toxicity data. Results suggest an urgent need for targeted, higher-throughput chemical evaluations to safeguard consumers.

Together, these proof-of-concept studies progress our ability to quantify exposure and hazard of emerging and data-poor substances in consumer products. The outcomes of the computational frameworks can help prioritize potentially problematic substances for additional study to characterize risk.