Poster Session 3


Tuesday, May 24, 2016, 10:00 AM - 12:00 PM

*All posters are available for viewing in the expo hall from Monday 9:00 a.m. through Wednesday 1:00 p.m.


Comparison Measurements of MDI Isocyanate During the Application of Spray Polyurethane Foam Insulation

J. Brown, G. Oishi, O. Shimelis, M. Halpenny, E. Barrey, K. Espenschied, and M. Ye, R&D, Sigma-Aldrich / Supelco, Bellefonte, PA

Objective: Methylene diphenyl diisocyanate (MDI) is a key component used in spray polyurethane foam (SPF) insulation products. Monitoring the airborne isocyanate concentration in the workplace environment is important because exposures can cause respiratory disorders like occupational asthma. Since MDI is fast reacting it’s important the sample collection device is capable of derivatizing MDI into a stable compound until the analysis is performed.

Methods: In this field study, two different types of sampling devices were used to collect air samples while a two component foam was sprayed into 2” x 4” wall cavity. The first sampling device was impregnated with 1-(2-pyridyl) piperazine (1-2PP) and this device is commonly used in the OSHA method 47. The second sampling device was impregnated with Dibutylamine. Both samplers work by derivatizing the isocyanates during sampling process. One study focused on determining the effect of varying the field extraction time (5,10, and 30 minutes). Another study explored the effect of waiting seven days to carry out the analysis. For this study, the 1-2PP samplers were field desorbed within 30 minutes after sampling and stored in a refrigerator. The Dibutylamine samplers were only capped and stored at ambient temperature.

Results: The MDI Concentration decreased by 25%, when the field extraction was carried out at 5 and 30 minutes using the 1-2PP samplers. Whereas, the Dibutylamine samplers showed no significant change in the captured MDI concentration over the same time frame. The study of waiting seven days to conduct the analysis resulted in an average MDI monomer concentration of 2.8 µg/m3 with the 1-2PP samplers, and 19.1 µg/m3 with the Dibutylamine samplers.

Conclusions: The 1-2PP samplers produced lower concentrations of MDI compared to samplers made with Dibutylamine. Different field extraction times did not affect the captured MDI concentration of the Dibutylamine samplers. In both studies the 1-2PP samplers under estimated the concentration of MDI.



Consultation, Sampling Strategy Development and Performance of Industrial Hygiene Personal and Worst-Case Grab Sample Area Monitoring for Identified Hydrocarbons Related to Potential Oilfield Exposures for Routine Tank Gauging Operations

J. Koehn, L. McKelvey, and J. Wiley, JK, Inc., Houston, TX; R. Acker, Ackcellent Consulting, LLC, Monument, CO; D. Deutsch, Apache Corporation, Houston, TX

Situation/Problem: Professional and technical consulting services have been addressed for occupational exposure assessment of specified oilfield personnel in Texas, Oklahoma, and Louisiana related to potential airborne hydrocarbons associated with oil and gas production and processing operations. Sampling strategy development was undertaken for identified Total Volatile Organic Compounds (TVOCs) involving a combination of personal breathing zone and also worst-case area grab samples during tank gauging operations in 2015. Monitoring data with input for an industry specific task force was requested to assist with investigation of potential workplace exposure controls.

Resolution: Specific knowledge of oilfield operations by health and safety personnel is vital for representative assessment of occupational airborne exposures of tank gauging job positions and general work site monitoring within these environments. Published sampling and analytical methods were employed in addition to field site use of calibrated direct-reading instruments to obtain benzene and hydrocarbon exposure data to assess existing work practice controls.

Results: Exposure assessment monitoring for defined airborne chemicals related to the variable oilfield occupational environment involving tank gauging operations is necessary for specific hazard identification and evaluation procedures. Industrial hygiene monitoring results are compared with current OSHA regulatory standards and other published technical recommended guidelines to better assess and manage the existing potential for elevated workplace airborne exposures. Worst-case grab samples with calibrated direct-reading instruments were also recorded for defined field site work activities and noted weather conditions.

Lessons learned: A range of industrial hygiene techniques were utilized to provide workplace assessment and oilfield site investigation of existing hydrocarbon exposures. Specific airborne monitoring procedures involving referenced methodologies along with subsequent data interpretation assisted with outlined HSE evaluation needs and provided data documentation to assess employee protection and proper hazard management. Investigation of further process design and control measures was also conducted for limitation of existing occupational airborne exposures and provision of useful information for employee protection.



Characterization of Naturally Occurring Airborne Diacetyl Concentrations Associated with the Preparation and Consumption of Unflavored Coffee

J. Pierce, A. Abelmann, J. Lotter, C. Comerford, and K. Keeton, Cardno ChemRisk, Chicago, IL; B. Finley, Cardno ChemRisk, Brooklyn, New York, NY

Objective: Diacetyl, a suspected cause of respiratory disorders in some food and flavorings manufacturing workers, is also a natural component of roasted coffee. The purpose of this analysis was to characterize diacetyl exposures that could plausibly occur in a small coffee shop during the preparation and consumption of unflavored coffee.

Methods: The study was conducted in duplicate, with one simulation in the morning and one in the afternoon, each with a total duration of 3 hours. Airborne samples were collected for 3 hr. (long-term) or 15 min. (short-term). Personal (long- and short-term) and area (long-term) sampling was conducted while a barista ground whole coffee beans, brewed, and poured coffee into cups. Simultaneously, long-term personal samples were collected as two participants, the customers, drank one cup of coffee each per hr. Air sampling and analyses were conducted in accordance with the OSHA Method 1012.

Results: Diacetyl was detected in all long-term samples. The long-term concentrations for the barista and area samples were similar, and ranged from 0.013-0.016 ppm; long-term concentrations for the customers were slightly lower and ranged from 0.010-0.014 ppm. Short-term concentrations ranged from below the limit of detection (< 0.0047 ppm) to 0.016 ppm. Mean estimated 8 hr. time-weighted average (8 hr. TWA) exposures for the barista ranged from 0.007-0.013 ppm. These values exceed recommended 8 hr. TWA occupational exposure limits (OELs) for diacetyl and are comparable to long-term personal measurements collected in various food and beverage production facilities. The concentrations measured based on area sampling were comparable to those measured in the breathing zone of the barista. Exceedances of the recommended OELs may also occur for coffee shop workers who do not personally prepare coffee (e.g., cashier, sanitation/maintenance).

Conclusions: These findings suggest that the practicality and scientific basis of the recommended OELs for diacetyl merit further consideration.



Occupational Exposure to Vapor, Gas, Dusts, and Fumes Among Rural Residents

M. Humann, B. Doney, and P. Henneberger, Division of Respiratory Disease Studies, CDC/NIOSH, Morgantown, WV; B. K. Kelly, The University of Iowa, Iowa City, IA

Objective: Occupational histories combined with a job exposure matrix (JEM) can be used to assess work-related exposures when direct measurements are not available. The objectives of this study were to use the occupational histories of adult participants in the Keokuk County Rural Health Study to describe the distribution of jobs among rural residents and their occupational exposures to vapor-gas, dusts, and fumes (VGDF).

Methods: The Keokuk County Rural Health Study was a long-term prospective cohort study of residents living in a rural county in the US state of Iowa. Data collection was conducted in three rounds, each lasting 5 years, between 1994 and 2011. Over the three rounds, 1,893 adult participants completed study questionnaires that included an occupational history documenting all jobs since age 12. US Census 2000 occupational codes were assigned to all reported jobs and combined with a JEM for airflow limitation to yield exposure levels of never/low, medium, or high for total VGDF. We assigned an exposure level for each participant based on the last job in their occupational history.

Results: The combination of the farm, fishing, and forestry occupational group with farmers and farm managers from the management group accounted for 20.5% of participants at last job. The next four most common occupational groups were office and administrative support (14.0%), sales (9.0%), production (7.7%), and education, training, and library (6.3%). The 20.5% of participants in farming, fishing, and forestry jobs was considerably greater than the comparable national figure of 1.3% from the 2000 US Census. For VGDF exposure in last job, the distribution of participants in the high, medium, and never/low exposure categories was 28.1%, 17.8%, and 54.1%, respectively. This is in contrast to findings from a predominantly urban population where the distribution by the same exposure categories based on the last job was 5.3% high, 9.8% medium, and 85.0% never/low.

Conclusions: These results suggest that the unique work history (e.g., farming and other manual labor) of rural residents may lead to higher occupational exposures to VGDF. We will be using the assigned occupational exposures in an upcoming study to investigate whether they are associated with decrements in the spirometry of adults living in a rural county, in order to inform strategies for prevention.



Options for the Placement of Breathing Zone Air Samples Inside a Welder’s Helmet

C. Pomerenke, Liberty Mutual Insurance, Boston, MA

Situation/Problem: Breathing zone air sample placement during welding job tasks presents a challenge inside welding helmets. The OSHA Directorate of Compliance Programs states that the correct placement for air samples is near the breathing zone of the employee. Furthermore, the OSHA Technical Manual for Personal Sampling states, “when sampling for welding fumes, the filter cassette must be placed inside the welding helmet to obtain an accurate measurement of the employee’s exposure”. The American Welding Society also recommends placing the sample inside the helmet. The issue is where to place the sample inside the helmet so it doesn’t interfere with the welder’s work and comfort.

Resolution: This study presents two options for the placement of air samples inside a welder’s helmet that are acceptable to working welders. One option is to clip the sample on a bandana that is tied around the neck. The second option is to clip the sample on a welder’s skull cap so it hangs down and along the cheek between the nose and mouth. Employee feedback on the two options indicated they were user-friendly and did not disturb the welder or hinder their job tasks.

Results: Five different welders in 3 separate workplaces were sampled. Side-by-side monitoring was conducted using the bandana and skull cap locations during Gas Metal Arc (GMAW) or MIG welding. NIOSH Method 7303 was followed for air sampling and laboratory analysis. Manganese data was selected for statistical analysis as it is the component of welding fume that is of most concern when welding carbon steel. Statistics computed for the bandana sample data and the skull cap sample data validated this study’s proposed sample locations.

Lessons learned: Secure the bandana sample to the welder’s shirt so it stays securely inside the helmet. Coach the welder to keep the bandana sample tucked inside the welding helmet. Consider the possibility of skin irritation from sweat, dirt and welding fume accumulation on the bandana. One out of five sampled welders mentioned this concern.



A Quantitative Model to Predict Allergic Contact Dermatitis from Wearable Technology Products

A. Singhal, K. Bogen, R. Kalmes, and P. Sheehan, Exponent, Inc., Oakland, CA

Situation/Problem: Wearable products with electronic components are being introduced to consumers without formal biocompatibility testing or health risk assessment. Some products that assess physiological functions involve prolonged skin contact with plastic and metal components under occluded conditions. Recent media reports have described occurrences of skin reactions such as allergic contact dermatitis (ACD) from wearable technology products. These products therefore present a new product stewardship challenge.

Resolution: A quantitative risk assessment model was developed that incorporates estimates of both dermal exposure and ACD elicitation risk. Product prototypes were tested in artificial sweat solution for varying time periods to reflect product-specific dermal exposure use scenarios. Leachates were analyzed for sensitizing metals and organic chemicals to derive potential applied dermal dose or load (in µg/cm2/unit time) per sensitizing chemical. To estimate ACD risk per chemical, a nickel ACD-elicitation risk model was developed using published human patch test nickel data. The reported fraction of sensitized user populations exhibited ACD reactions at specified dermal nickel loads. This nickel distribution was then generalized to predict ACD risk for chemical sensitizers with limited patch test data. Prediction was based on the observation that estimated distribution of population sensitivity to nickel is similar to distributions of patch test dose response data for other sensitizing chemicals.

Results: Results indicate that the sensitizing metals (nickel, chromium, and cobalt), and sensitizing organics (primarily acrylate and epoxy compounds) are leached from a variety of tested wearable product prototypes. Dermal loads were estimated to range from <1 to >50 µg/cm2/week with chemical loads potentially posing a wide range of risks of ACD reaction in sensitized users, with <0.01% to >10% of the sensitized users expected to react.

Lessons learned: This methodology can help manufacturers in identifying components of wearable technology products that pose a high risk of leaching and consequent ACD reactions, in order to make their products biocompatible prior to introduction into consumer markets.



A Bayesian Approach for Summarizing Real-Time Exposure Data with Left Censoring

E. Houseman, Oregon State University, Corvallis, OR; M. Virji, NIOSH, Morgantown, WV

Objective: Direct-reading instruments are valuable tools for measuring exposure. They provide real-time data and valuable information on short-term exposure variability. However, statistical analysis is complicated by autocorrelation among successive measurements, nonstationary time-series, and presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed for analyzing exposure time-series that accounts for nonstationary autocorrelation and LOD issues.

Methods: A spline based approach was used to model nonstationary autocorrelation with relatively few assumptions about autocorrelation structure. Left censoring was addressed by integrating over the left tail of the distribution. The model was fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method was implemented using the rjags package in R and is illustrated by applying it to real-time exposure data. Estimates for covariates from the Bayesian model were compared to those from the frequentist models including linear regression and mixed effects models with different autocorrelation structures. Simulations studies were conducted to evaluate method performance.

Results: Simulation studies with LODs ranging from 0-50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates, e.g., source enclosure, were significant in some frequentist models, but in the Bayesian model their credible intervals contained zero; such discrepancies were observed in multiple datasets. Variance components from the Bayesian model reflected substantial autocorrelation, consistent with the frequentist models. Plots of means from the Bayesian model showed good fit to the observed data.

Conclusions: The proposed Bayesian model out performs the frequentist models in estimating task means, standard deviations and parameter estimates for covariates, thus providing an approach for modeling nonstationary autocorrelation in a hierarchical modeling framework.



Noise Exposure Assessment in a Dog Grooming Operation

R. Higley, G. Gruenwald, and T. Knepper, ESIS, Corona, CA

Situation/Problem: Noise exposures to bathers/groomers in a national pet store chain may exceed the OSHA Action Level. Noise exposures had not been monitored previously. The store needed to determine if bathers/groomers were required to participate in a Hearing Conservation Program per the OSHA Noise Standard. If noise levels did exceed the Action Level of 85 dBA TWA, what methods of noise control are available in order to achieve compliance with the OSHA noise standard.

Resolution: Employees were selected and fitted with Casella CEL 350 noise dosimeters. The noise dosimeters were calibrated before and after the monitoring period. Observations of employee work procedures were made identifying peak noise exposures. Direct sound level measurements were made of specific noise sources. Noise sources were identified as blowers (some with faulty bearings), positioning of the air blower nozzle in relation to the dog, and barking dogs in the kennel area. Administrative controls were also identified to help reduce employee noise exposure. .

Results: Four different stores were visited and a total of 15 employees were evaluated. Two of the fifteen had noise exposures at 85 dBA TWA, other employees were below the Action Level. Recommendations to further reduce noise exposures included the following: Engineering Controls: Replace defective blowers that generated a loud squeal over 90 dBA with newer and/or quieter blowers. Move blowers adjacent to the drying tables located at head height to underneath the tables. Enclose the blower unit to help further reduce noise transmission Provide plastic strips or other barrier material between the kennel area and the bunker to reduce noise from barking dogs. Administrative Controls: Some workers performed more bathing tasks, while other workers performed more grooming tasks (cutting/trimming fur) which is a quiet task. Schedule work so that employees’ work tasks are more equally balanced between bathing and grooming. Train workers to maintain the blower nozzle away from the dog’s body. Placing the air nozzle close to the body generates air turbulence and excessive noise.

Lessons learned: Relatively simple solutions including administrative controls, placement of blowers and barriers to prevent sound transmission are effective in reducing employee noise exposures.



Evaluation of Noise Exposures During High Pressure Washing, Piglet Vaccinating and Room Relocation at a Hog Farrowing Facility

D. Weber, Liberty Mutual Insurance Company, Glastonbury, CT

Situation/Problem: Hog breeding farms require labor intensive operations including thoroughly cleaning animal housing and farrowing rooms, vaccinating each individual piglet and moving piglets from room to room. High pressure power washers are used to clean all farrowing room surfaces including ceilings, walls, floor grates and basins, etc. Additionally, piglets are vaccinated and moved in groups from room to room. Personal Dosimetry revealed selective operations expose workers to high noise levels. Two of three individuals experienced noise above the OSHA PEL of 90 dBA for an eight hour TWA. HC TWA noise exposures during: room pressure washing were up to 99.5 dBA, piglet relocation were up to 86 dBA and piglet vaccination were up to 81 dBA. Excessive occupational noise exposures have been linked to noise induced hearing loss.

Resolution: Management investigated lower noise power washer guns, modified work schedules, limiting duration of power washing by any individual and continued to include exposed workers in hearing conservation program

Results: Attempts to identify suitable replacement power washer units proved unsuccessful. The employer’s main focus was to ensure their hearing conservation program was adequate and to strive to schedule a rotational work schedule limiting any employee’s daily operation of a power washer to an hour or less per day to reduce PEL TWA exposures to below 90 dBA.

Lessons learned: No suitable quieter pressure wash guns were identified. Worker rotation was a means of lowering an individual’s noise exposure on days that pressure washing is performed. Worker rotation does not reliably reduce worker exposures to below 85 dBA for a full shift TWA. In order to reduce worker noise exposures to below the PEL of 90 dBA on days when power washing is performed, workers are limited to one (1) hour or less of pressure washing. In general, limiting the power washing duration to one hour per person per day is estimated to result in noise exposures ranging from 84 dBA to 88 dBA TWA. A two hour power washing operating limit is estimated to result in a TWA exposure range of 87 dBA to 91 dBA.



Evaluation of Noise in a Division 1 College Football Stadium

M. Valigosky, A. Ames, J. Taylor, F. Akbar-Khanzadeh, and S. Milz, University of Toledo, Toledo, OH

Objective: Noise exposure during spectator sporting events has the ability to impact event workers, event participants and spectators. Noise exposures can impact communication efforts and cause temporary and permanent hearing loss. The current study characterized noise exposure of workers and spectators during Division I college football games. The stadium is a medium sized college football stadium in Northwest Ohio, with a current seating capacity of 26,248.

Methods: Noise levels were measured during three Division 1 college football games in 2014 to determine whether the noise levels exceeded standards and guidelines. Noise levels were measured using a set of dosimeters (Larson Davis Spark 705+) placed throughout the football stadium to characterize noise generated by the cannon, the band, the students section, field level game noise and stadium level crowd noise. Dosimeters were programmed to record noise for the entire length of the football game (at one minute intervals), using ACGIH® and OSHA dosimeter parameters. The dosimeters were calibrated using a Larson Davis CAL150. Data from the instruments were uploaded to Blaze software and exported for analysis in SPSS.

Results: The findings suggested significant variations in noise levels depending on monitoring location and attendance. The minute average noise levels [Mean±SD (Min-Max)] in terms of Leq (dBA) during nonscoring were: student section, 85.3±5.4 (73.5-102.5); home team 50-yard line, 86.1±3.9 (77.5-99.6); visiting team 50-yard line, 83.9±3.8 (73.8-94.1); and stadium center of home team, 84.6±3.4 (75.9-98.1). The minute average noise levels [Mean±SD (Min-Max)] in terms of Leq (dBA) during scoring were: student section, 95.1±4.6 (84.9-100.1); home team 50-yard line, 92.4±3.6 (88.3-100.2); visiting team 50-yard line, 89.2±2.8 (83.6-93.6); and stadium center of home team, 92.0±3.1 (85.0-96.1). A canon is fired after every home touchdown and field goal. Peak noise levels during canon fire were: student section, 132.3; home team 50-yard line 130.0; visiting team 50-yard line, 135.2; and stadium center of home team, 130.0.

Conclusions: During nonscoring time, the student section and home team 50-yard line mean noise levels were above the ACGIH® TLV® for noise (85 dBA). All locations after scoring were above the ACGIH® TLV® for noise. Peak noise levels during canon fire, at all locations, were below the WHO guidelines for peak noise (140 dBA).



Environmental Noise Evaluation After Implementation of Controls near a Higher Education Research Facility

A. Ames, M. Valigosky, C. Barber, F. Akbar-Khanzadeh, and S. Milz, University of Toledo, Toledo, OH

Objective: Controls were installed at two noise sources at a higher education facility after results of a 2013 study suggested a possible noncompliance with the city’s noise ordinances based on measurements at a residential property line. The current study investigated whether noise at the higher education site was reduced after implementation of controls, with a resulting effect on local neighborhoods.

Methods: A temporary L-shaped wood barrier was installed on the North (N) roof of a research building near the strobic exhaust fans. Absorbers were placed on a ground level condensing unit abutting the research building. Dosimeters (Larson Davis Spark 705+) were used to measure noise levels around the sources and at the property line of the higher education site. Four days of sampling were performed during August and September 2015. Using ACGIH® and OSHA parameters, the dosimeters recorded noise at one minute intervals, for 24 hours a day. The dosimeters were calibrated​​​ daily (Larson Davis CAL150). Recorded data were uploaded to Blaze software and exported for analysis in SPSS.

Results: The findings indicated significant variations in noise levels depending on monitoring location and time of day. An intermittent source is present, a generator that runs a weekly 20 min test. The minute average noise levels [Mean±SD (Min-Max)] in terms of Leq (dBA) of daytime noise (generator off), can be summarized as follows: property line, 63.3±3.0 (54.6-85.3); N roof, 71.6±5.1 (60.6-98.6); and condensing unit, 63.3±5.2 (51.4-92.5). The minute average noise levels [Mean±SD (Min-Max)] in terms of Leq (dBA) of nighttime noise (generator off) can be summarized as follows: property line, 63.1±1.1 (61.2-70.6); N roof, 66.2±0.4 (65.3-69.2); and condensing unit, 59.6±1.1 (54.8-66.5). Compared to the precontrol study, mean noise levels (dBA) with the generator off demonstrated a reduction in daytime (nighttime) levels: -9.6 (-13.8) at the N roof (barrier), -22.9 (-26.2) at the condensing unit (absorbers) and -0.3 (-2.4) at the property line.

Conclusions: Based on the noise ordinance for the city, noise levels within a residential area must not exceed 60 dBA between 7 am and 10 pm or 55 dBA between 10 pm and 7 am. While implemented controls have reduced noise levels at the source, the noise levels measured at the residential property line continue to be affected by the noise emissions. Additional controls are recommended to achieve continuous compliance.



Sound Level Area Assessments Using Noise Mapping

G. Battista and M. Sheehan, West Chester University, West Chester, PA; R. Morrison, The Dow Chemical Co., Collegeville, PA

Objective: Noise is a ubiquitous hazard in workplaces and work induced hearing loss is one of the most prevalent occupational illnesses. Commissioning of a new plant provides challenges for protecting employees and contractors especially in the building’s mechanical spaces. The purpose of this study was to evaluate baseline sound levels within the mechanical areas of a new facility by using noise mapping to assist in the identification of sources and areas needing exposure controls.

Methods: The methods used in this study included measuring noise with a calibrated sound level meter at several locations within seven mechanical areas once per month over a four-month period. Building diagrams of mechanical areas were reformatted with a grid and were used by the surveyor for data collection/notation. Measurements were inputted into a company designed mapping tool which created color coded maps of noise levels within these areas for each sampling date. Outside weather conditions were also noted to assist with noise source interpretation. Spatial and temporal comparisons of sound levels were made using the Kruskal-Wallace ANOVA.

Results: The results provided visual images of sources and excessive noise locations. A visual assessment of the four monthly noise maps for each mechanical area indicated variations in sound levels over time as different mechanical systems were operating due to weather conditions. Statistical analysis indicated differences among the different mechanical areas and that month two was significantly different from months three and four.

Conclusions: Our conclusions were: 1) sources (e.g. steam leaks) were defined for each area for each month and these were prioritized for remediation; 2) some sources were related to outside weather conditions; 3) locations were defined that required immediate actions to reduce potential exposure (warning signage/ demarcation and provision of necessary personal protective equipment);and  4) this company’s noise mapping tool is an effective way to focus attention on areas and sources needing noise reduction strategies. We recommend that industrial hygienists: 1) incorporate mapping technologies into their evaluations of workplace noise and 2) take multiple area noise measurements of mechanical rooms throughout the commissioning process and throughout the year in plants that are operating This will characterize the sound levels in mechanical areas, identify sources and reduce potential exposure to workplace noise.



The Benefits of Quantifying the Parent Product and Its Urinary Metabolites when Assessing Occupational Exposure to Antineoplastic Drugs

C. Hon, Ryerson University, Toronto, ON, Canada; C. Barzan, University of British Columbia, Vancouver, BC, Canada

Objective: Occupational exposure to antineoplastic drugs has been associated with reproductive toxicities, genetic damage as well as an increased risk of developing cancer. In order to assess healthcare workers’ exposure to antineoplastic drugs, one method that has been employed in studies is to collect urine samples and then quantifying the amount of unmetabolized drug that is voided. However, it has been suggested that this may result in an underestimate of the true body burden. It would be more appropriate to analyze the parent product as well as its urinary metabolites. To our knowledge, this has yet to be demonstrated. The aim of this study was to ascertain the benefits of quantifying cyclophosphamide (CP), a commonly administered antineoplastic drug, and three of its main urinary metabolites with respect to occupational exposure assessment.

Methods: We asked healthcare workers to provide 24-hour urine samples, which were subsequently analyzed using high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). The amount of CP and three of its more stable urinary metabolites (4-ketocyclophosphamide, carboxyphosphamide, and N-dechloroethylcyclophosphamide) was quantified.

Results: We obtained 223 urine samples. The average urinary concentration of CP was 285 ng/24 hours (interquartile range 184 ng/24 hours) while the mean urinary concentration of CP and the three metabolites was 2,158 ng/24 hours (interquartile range 567 ng/24 hours). In addition, only 49% of samples exceeded the LOD for CP when only CP was analyzed; however, when CP and its metabolites were examined, 94% of the samples had at least one analyte at a concentration that exceeded its corresponding LOD.

Conclusions: These findings suggest that analyzing the parent drug and its urinary metabolites would result in improvements concerning the accuracy of body burden levels as well as the proportion of detectable samples, two important factors from an occupational hygiene perspective. We therefore recommend that all future studies, which collect urine samples for exposure assessment purposes, quantify both the parent drug product and several of its urinary metabolites. By doing so, it will allow for more appropriate interpretation of the associated occupational exposure risk.



Development and Administration of a Pilot Environmental Health Survey in Lucas County, Ohio

E. Zgodzinksi, S. Eitniear, G. Bingham, J. Niese, and B. Sherrick, Toledo-Lucas County Health Department, Toledo, OH; A. Ames, M. Valigosky, S. Milz, and F. Akbar-Khanzadeh, University of Toledo, Toledo, OH

Objective: A goal of local public health agencies is to improve the health of their community. The Toledo-Lucas County Health Department collaborated with various stakeholders to undertake the first countywide environmental health assessment in 2015. This assessment is a multistep process to: gather information from residents and employees about environmental conditions and perceptions in Lucas County, reduce exposure to health risks, and educate the public on sources of environmental risk.

Methods: A pilot survey was developed with questions on demographics, perceptions on environmental health issues, including the greatest environmental health issue at different scales (yourself, your family, neighborhood, county, NW Ohio), and how one learns about the issues. The survey was administered online through SurveyMonkey. Participants were recruited via social media (Facebook and twitter); email and at public events.

Results: Result of the pilot data were entered into a database for analysis in SPSS 21. A total of 283 respondents were split into three groups for analysis purposes: Group 1, lives and works in Lucas County (n=187); Group 2, lives in and works outside of Lucas County (n=63); and Group 3, lives outside of Lucas County (n=33). The environmental health conditions were grouped into air (i.e., air pollution, open burning, radon, etc.), water (i.e., drinking water, beach closings, sewage, etc.), land (pesticides/herbicides, nuisance, etc.), and miscellaneous (i.e., food safety, lead, smoking, etc.). The most frequently identified environmental health condition(s) affecting residents of Lucas County: 1) air category were air pollution for Groups 1 (44.4%) & 3 (39.4%) and mold for Group 2 (44.4%); 2) water category were drinking water (59.5%, 58.7%, and 39.4% for Groups 1-3 ) and harmful algal blooms (HABs) (63.1%, 65.1% and 36.4% for Groups 1-3); 3) land category was nuisance, with 50.3% (Group 1), 39.7% (Group 2) and 30.3% (Group 3); and 4) miscellaneous category were mosquitos and ticks for Group 1 (49.2%) and Group 2 (50.8%), and smoking for Group 3 (24.2%). Group 1 cited drinking water and HABs as the greatest environmental health conditions at all scales (yourself, your family, neighborhood, county, NW Ohio).

Conclusions: Perceptions of environmental issues affecting residents of Lucas County were similar among the three groups. Overall, the most frequently identified issues among respondents in all categories were drinking water and HABs.​