PM2.5 Is Insufficient to Explain Personal PAH Exposure.

To understand how chemical exposure can impact health, researchers need tools that capture the complexities of personal chemical exposure. In practice, fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure, but do not capture total chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. In this study, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a 7-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons. Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

Predicting personal PAH exposure using high dimensional questionnaire and wristband data.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are a class of pervasive environmental pollutants with a variety of known health effects. While significant work has been completed to estimate personal exposure to PAHs, less has been done to identify sources of these exposures. Comprehensive characterization of reported sources of personal PAH exposure is a critical step to more easily identify individuals at risk of high levels of exposure and for developing targeted interventions based on source of exposure. OBJECTIVE: In this study, we leverage data from a New York (NY)-based birth cohort to identify personal characteristics or behaviors associated with personal PAH exposure and develop models for the prediction of PAH exposure. METHODS: We quantified 61 PAHs measured using silicone wristband samplers in association with 75 questionnaire variables from 177 pregnant individuals. We evaluated univariate associations between each compound and questionnaire variable, conducted regression tree analysis for each PAH compound and completed a principal component analysis of for each participant's entire PAH exposure profile to determine the predictors of PAH levels. RESULTS: Regression tree analyses of individual compounds and exposure mixture identified income, time spent outdoors, maternal age, country of birth, transportation type, and season as the variables most frequently predictive of exposure.

Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration.

Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.

Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration.

Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.

Impact of acute temperature and air pollution exposures on adult lung function: A panel study of asthmatics.

BACKGROUND: Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM2.5) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. METHODS AND FINDINGS: Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV1)), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM2.5, DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM2.5, but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM2.5, had a significant association with FEV1. When DBGT and PM2.5 exposures were placed in the same model, the strongest association between cumulative PM2.5 exposures and the use of rescue bronchodilator was identified at the 0-24 hours (OR = 1.030; 95% CI = 1.012-1.049; p-value = 0.001) and 0-48 hours (OR = 1.030; 95% CI = 1.013-1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (ß = 3.257; SE = 0.879; p-value>0.001) and 0-6 hours (ß = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV1. No significant interactions between DBGT and PM2.5 were observed for rescue bronchodilator use or FEV1. CONCLUSIONS: Short-term increases in PM2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV1). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM2.5 and DBGT on lung function in asthmatics.

Evaluating predictive relationships between wristbands and urine for assessment of personal PAH exposure.

During events like the COVID-19 pandemic or a disaster, researchers may need to switch from collecting biological samples to personal exposure samplers that are easy and safe to transport and wear, such as silicone wristbands. Previous studies have demonstrated significant correlations between urine biomarker concentrations and chemical levels in wristbands. We build upon those studies and use a novel combination of descriptive statistics and supervised statistical learning to evaluate the relationship between polycyclic aromatic hydrocarbon (PAH) concentrations in silicone wristbands and hydroxy-PAH (OH-PAH) concentrations in urine. In New York City, 109 participants in a longitudinal birth cohort wore one wristband for 48 h and provided a spot urine sample at the end of the 48-hour period during their third trimester of pregnancy. We compared four PAHs with the corresponding seven OH-PAHs using descriptive statistics, a linear regression model, and a linear discriminant analysis model. Five of the seven PAH and OH-PAH pairs had significant correlations (Pearson's r = 0.35-0.64, p ≤ 0.003) and significant chi-square tests of independence for exposure categories (p ≤ 0.009). For these five comparisons, the observed PAH or OH-PAH concentration could predict the other concentration within a factor of 1.47 for 50-80% of the measurements (depending on the pair). Prediction accuracies for high exposure categories were at least 1.5 times higher compared to accuracies based on random chance. These results demonstrate that wristbands and urine provide similar PAH exposure assessment information, which is critical for environmental health researchers looking for the flexibility to switch between biological sample and wristband collection.

Development of an environmental health tool linking chemical exposures, physical location and lung function.

BACKGROUND: A challenge in environmental health research is collecting robust data sets to facilitate comparisons between personal chemical exposures, the environment and health outcomes. To address this challenge, the Exposure, Location and lung Function (ELF) tool was designed in collaboration with communities that share environmental health concerns. These concerns centered on respiratory health and ambient air quality. The ELF collects exposure to polycyclic aromatic hydrocarbons (PAHs), given their association with diminished lung function. Here, we describe the ELF as a novel environmental health assessment tool. METHODS: The ELF tool collects chemical exposure for 62 PAHs using passive sampling silicone wristbands, geospatial location data and respiratory lung function measures using a paired hand-held spirometer. The ELF was tested by 10 individuals with mild to moderate asthma for 7 days. Participants wore a wristband each day to collect PAH exposure, carried a cell phone, and performed spirometry daily to collect respiratory health measures. Location data was gathered using the geospatial positioning system technology in an Android cell-phone. RESULTS: We detected and quantified 31 PAHs across the study population. PAH exposure data showed spatial and temporal sensitivity within and between participants. Location data was used with existing datasets such as the Toxics Release Inventory and the National Oceanic and Atmospheric Administration (NOAA) Hazard Mapping System. Respiratory health outcomes were validated using criteria from the American Thoracic Society with 94% of participant data meeting standards. Finally, the ELF was used with a high degree of compliance (> 90%) by community members. CONCLUSIONS: The ELF is a novel environmental health assessment tool that allows for personal data collection spanning chemical exposures, location and lung function measures as well as self-reported information.

Discovery of common chemical exposures across three continents using silicone wristbands.

To assess differences and trends in personal chemical exposure, volunteers from 14 communities in Africa (Senegal, South Africa), North America (United States (U.S.)) and South America (Peru) wore 262 silicone wristbands. We analysed wristband extracts for 1530 unique chemicals, resulting in 400 860 chemical data points. The number of chemical detections ranged from 4 to 43 per wristband, with 191 different chemicals detected, and 1339 chemicals were not detected in any wristband. No two wristbands had identical chemical detections. We detected 13 potential endocrine disrupting chemicals in over 50% of all wristbands and found 36 chemicals in common between chemicals detected in three geographical wristband groups (Africa, North America and South America). U.S. children (less than or equal to 11 years) had the highest percentage of flame retardant detections compared with all other participants. Wristbands worn in Texas post-Hurricane Harvey had the highest mean number of chemical detections (28) compared with other study locations (10-25). Consumer product-related chemicals and phthalates were a high percentage of chemical detections across all study locations (36-53% and 18-42%, respectively). Chemical exposures varied among individuals; however, many individuals were exposed to similar chemical mixtures. Our exploratory investigation uncovered personal chemical exposure trends that can help prioritize certain mixtures and chemical classes for future studies.

Silicone wristbands compared with traditional polycyclic aromatic hydrocarbon exposure assessment methods.

Currently there is a lack of inexpensive, easy-to-use technology to evaluate human exposure to environmental chemicals, including polycyclic aromatic hydrocarbons (PAHs). This is the first study in which silicone wristbands were deployed alongside two traditional personal PAH exposure assessment methods: active air monitoring with samplers (i.e., polyurethane foam (PUF) and filter) housed in backpacks, and biological sampling with urine. We demonstrate that wristbands worn for 48 h in a non-occupational setting recover semivolatile PAHs, and we compare levels of PAHs in wristbands to PAHs in PUFs-filters and to hydroxy-PAH (OH-PAH) biomarkers in urine. We deployed all samplers simultaneously for 48 h on 22 pregnant women in an established urban birth cohort. Each woman provided one spot urine sample at the end of the 48-h period. Wristbands recovered PAHs with similar detection frequencies to PUFs-filters. Of the 62 PAHs tested for in the 22 wristbands, 51 PAHs were detected in at least one wristband. In this cohort of pregnant women, we found more significant correlations between OH-PAHs and PAHs in wristbands than between OH-PAHs and PAHs in PUFs-filters. Only two comparisons between PAHs in PUFs-filters and OH-PAHs correlated significantly (rs = 0.53 and p = 0.01; rs = 0.44 and p = 0.04), whereas six comparisons between PAHs in wristbands and OH-PAHs correlated significantly (rs = 0.44 to 0.76 and p = 0.04 to <0.0001). These results support the utility of wristbands as a biologically relevant exposure assessment tool which can be easily integrated into environmental health studies. Graphical abstract PAHs detected in samples collected from urban pregnant women.

Preparation and performance features of wristband samplers and considerations for chemical exposure assessment.

Wristbands are increasingly used for assessing personal chemical exposures. Unlike some exposure assessment tools, guidelines for wristbands, such as preparation, applicable chemicals, and transport and storage logistics, are lacking. We tested the wristband's capacity to capture and retain 148 chemicals including polychlorinated biphenyls (PCBs), pesticides, flame retardants, polycyclic aromatic hydrocarbons (PAHs), and volatile organic chemicals (VOCs). The chemicals span a wide range of physical-chemical properties, with log octanol-air partitioning coefficients from 2.1 to 13.7. All chemicals were quantitatively and precisely recovered from initial exposures, averaging 102% recovery with relative SD ≤21%. In simulated transport conditions at +30 °C, SVOCs were stable up to 1 month (average: 104%) and VOC levels were unchanged (average: 99%) for 7 days. During long-term storage at -20 °C up to 3 (VOCs) or 6 months (SVOCs), all chemical levels were stable from chemical degradation or diffusional losses, averaging 110%. Applying a paired wristband/active sampler study with human participants, the first estimates of wristband-air partitioning coefficients for PAHs are presented to aid in environmental air concentration estimates. Extrapolation of these stability results to other chemicals within the same physical-chemical parameters is expected to yield similar results. As we better define wristband characteristics, wristbands can be better integrated in exposure science and epidemiological studies.