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.

There is a paucity of data on additive manufacturing process emissions and personal exposures in real-world workplaces. Hence, we evaluated atmospheres in four workplaces utilizing desktop "3-dimensional" (3-d) printers [fused filament fabrication (FFF) and sheer] for production, prototyping, or research. Airborne particle diameter and number concentration and total volatile organic compound concentrations were measured using real-time instruments. Airborne particles and volatile organic compounds were collected using time-integrated sampling techniques for off-line analysis. Personal exposures for metals and volatile organic compounds were measured in the breathing zone of operators. All 3-d printers that were monitored released ultrafine and fine particles and organic vapors into workplace air. Particle number-based emission rates (#/min) ranged from 9.4 times 109 to 4.4 times 1011 (n = 9 samples) for FFF 3-d printers and from 1.9 to 3.8 times 109 (n = 2 samples) for a sheer 3-d printer. The large variability in emission rate values reflected variability from the printers as well as differences in printer design, operating conditions, and feedstock materials among printers. A custom-built ventilated enclosure evaluated at one facility was capable of reducing particle number and total organic chemical concentrations by 99.7% and 53.2%, respectively. Carbonyl compounds were detected in room air; however, none were specifically attributed to the 3-d printing process. Personal exposure to metals (aluminum, iron) and 12 different organic chemicals were all below applicable NIOSH Recommended Exposure Limit values, but results are not reflective of all possible exposure scenarios. More research is needed to understand 3- d printer emissions, exposures, and efficacy of engineering controls in occupational 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.

Little is known about emissions and exposure potential from vat polymerization additive manufacturing, a process that uses light-activated polymerization of a resin to build an object. Five vat polymerization printers (three stereolithography (SLA) and two digital light processing (DLP) were evaluated individually in a 12.85 m(3) chamber. Aerosols (number, size) and total volatile organic compounds (TVOC) were measured using real-time monitors. Carbonyl vapors and particulate matter were collected for offline analysis using impingers and filters, respectively. During printing, particle emission yields (#/g printed) ranged from 1.3 +/- 0.3 to 2.8 +/- 2.6 x 10(8) (SLA printers) and from 3.3 +/- 1.5 to 9.2 +/- 3.0 x 10(8) (DLP printers). Yields for number of particles with sizes 5.6 to 560 nm (#/g printed) were 0.8 +/- 0.1 to 2.1 +/- 0.9 x 10(10) and from 1.1 +/- 0.3 to 4.0 +/- 1.2 x 10(10) for SLA and DLP printers, respectively. TVOC yield values (microg/g printed) ranged from 161 +/- 47 to 322 +/- 229 (SLA printers) and from 1281 +/- 313 to 1931 +/- 234 (DLP printers). Geometric mean mobility particle sizes were 41.1-45.1 nm for SLA printers and 15.3-28.8 nm for DLP printers. Mean particle and TVOC yields were statistically significantly higher and mean particle sizes were significantly smaller for DLP printers compared with SLA printers (p < 0.05). Energy dispersive X-ray analysis of individual particles qualitatively identified potential occupational carcinogens (chromium, nickel) as well as reactive metals implicated in generation of reactive oxygen species (iron, zinc). Lung deposition modeling indicates that about 15-37% of emitted particles would deposit in the pulmonary region (alveoli). Benzaldehyde (1.0-2.3 ppb) and acetone (0.7-18.0 ppb) were quantified in emissions from four of the printers and 4-oxopentanal (0.07 ppb) was detectable in the emissions from one printer. Vat polymerization printers emitted nanoscale particles that contained potential carcinogens, sensitizers, and reactive metals as well as carbonyl compound vapors. Differences in emissions between SLA and DLP printers indicate that the underlying technology is an important factor when considering exposure reduction strategies such as engineering controls.

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.

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.

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, alpha-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 alpha-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, alpha-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.