Evaluation of Occupational, Community and Recreational Noise Exposures


Monday, May 23, 2016, 2:00 PM - 5:00 PM


Development and Translation of a Job Exposure Matrix for Occupational Noise in the US and Canada

R. Neitzel, B. Roberts, K. Sun, R. Long, and S. Ramdas, University of Michigan School of Public Health, Ann Arbor, MI

Objective: Noise-induced hearing loss is highly prevalent in the US and Canada. Noise is increasingly being linked to other nonauditory health effects such as cardiovascular disease, sleep disturbance, and stress. However, our knowledge of noise exposures associated with many US and Canadian occupations is lacking. To address this critical need, we have developed a Job Exposure Matrix (JEM) for noise using full shift noise measurement data contributed by regulatory, industry, research, and peer reviewed literature sources.

Methods: As of September 2015, we have collected 1,136,766 noise measurements representing 436 unique jobs as coded by Bureau of Labor Statistics (BLS) Standard Occupational Classification (SOCs) and 679 unique industries categorized by the 2012 North American Industry Classification System (NAICS). We used mixed effects regression models to estimate exposures for each job in the JEM, and are in the process of translating the estimates from the JEM into a searchable public web interface.

Results: Using the web interface, users can search for information by SOC or NAICS code, or via free field text, in order to obtain estimates of average and maximum exposure, as well as exceedance fractions (e.g., percentage of measurements >85 dBA) for data collected according to the criteria of the US Occupational Safety and Health Administration (OSHA) and, in some instances, the criteria of the US National Institute for Occupational Safety and Health (NIOSH).

Conclusions: This JEM allows, for the first time, quantitative estimation of workplace noise exposures on a national scale in both the US and Canada. This gives industrial hygienists, epidemiologists, occupational health practitioners and other relevant stakeholders a vital tool that could dramatically improve the accuracy and efficiency of noise exposure assessments. This tool also provides the opportunity to assess temporal trends in occupational noise exposures, to benchmark specific industries or jobs, and to focus and guide development of targeted efforts towards noise control and hearing loss prevention.



What Can More Than 30 Years and 700,000 Measurements Tell Us About Noise Exposure in the Mining Industry?

B. Roberts, R. Neitzel, K. Sun, R. Long, and S. Ramdas, University of Michigan School of Public Health, Ann Arbor, MI

Objective: Collect, organize, and analyze over 700,000 noise measurements made by the US Mine Safety and Health Administration (MSHA).

Methods: As part of a larger effort to construct a job exposure matrix (JEM) for occupation noise, records of full-shift personal noise dosimeter measurements were obtained from MSHA through a Freedom of Information Act (FOIA) request. The data was imported into STATA 14 for analysis. Records were excluded if they did not provide an exposure measurement, did not have a valid job title, or had a time-weighted average (TWA) less than 60 dBA or greater than 120 dBA. The 2012 North American Industry Classification System (NAICS) and the Standard Occupational Classification (SOC) System was used to standardize the records by industry type and job title respectively. The first 4 digits of the NAICS code was used to differentiate between different mine types. Occupations were categorized using the first two digits of the SOC code, ranging from 13 to 53. Average noise exposure levels were computed by year and stratified by SOC and NAICS codes. Linear regression was used to predict the average change in noise exposure by year while controlling for mine type and job title.

Results: In total, 716,142 measurements from 1979 to 2014 were collected from MSHA after the exclusion criteria were applied. A total of 61 unique job titles were identified. The overall TWA was 82.3 dBA with a standard deviation of 9.2. Prior to the implementation of MSHA's revised noise standard in 2000, the TWA was 84.8 dBA which was significantly higher (p <0.001) than the TWA of 78.8 dBA after the implementation of the standard. Of the 61 unique job titles, 37 were found to have significantly (p <0.05) lower exposures after the implementation of the new standard. Linear models predicted that the mining sector has become progressively quieter; while a few occupations within the mining sector have remained the same or become louder.

Conclusions: Overall, the mining industry has become less noisy. However, there are some occupations that are still exposed to hazardous levels of noise. The construction of the JEM has made it possible to identify occupations with hazardous noise exposure so that additional sampling and controls can be implemented to protect the worker's hearing.



Descriptive Evaluation of Noise Dosimetry Values in the Defense Occupational and Environmental Health Readiness System—Industrial Hygiene Component (DOEHRS-IH)

L. Whitehead, D. Tucker, D. Gimeno, K. Whitworth, and J. Betancourt, University of TX Health Sci. Ctr. at Houston, Houston, TX; S. Leonard, Hearing Center of Excellence, San Antonio, TX; A. Zhang, Knowesis, Inc., Fairfax, VA; A. Senchak, Walter Reed National Military Medical Center, Bethesda, MD

Objective: Describe noise dosimetry data for active duty military personnel in the Department of Defense (DoD) Defense Occupational and Environmental Health Readiness System-Industrial Hygiene component (DOEHRS-IH).

Methods: Data in DOEHRS-IH, covering from 1995 to 2015, were obtained on 12,072 personal 8-hour dosimetry samples (85/3 dBA rule, threshold = 80 dBA), as recommended by NIOSH and the ACGIH® TLV®. These include any repeat data from Service Members with annual dosimetry. An 84/4 rule was used previously by the Navy, but unless 85/3 results were also reported, these are not included. While DOEHRS-IH uses Similar Exposure Groups, workers performing like processes, these are base-specific and unstandardized. So, initial analyses are for standardized military occupational codes (MOCs, including MOS, AFSC, Ratings, and Navy Officer codes).

Results: Of about 8,000 MOCs, 773 had at least one time weighted average (TWA) value and 362 had 5 or more. Of 12,072 TWAs, 57% are ≥ 80 dBA, and 43% are < 80 dBA, with 17% = 0. The 80 dBA threshold acts as a de facto detection limit, but many MOCs have values < 80 dBA, including some at zero. Arithmetic averages are distorted downward by the zero values, and to some extent by any <80 dBA. For epidemiology, it is not desirable to discard values < 80 dBA, so the whole distribution of exposures is included in averages. Since values near and above 85 dBA are more important for hearing loss, various metrics were considered. The metric used was decibel averaging, in effect averaging of the underlying sound power, of the TWAs within each MOC, although simple arithmetic averaging is more typically used across workers. This statistic deemphasizes low values and emphasizes the high that have the most sound power and hazard. Since there is also an averaging step, some influence is present for the low values. We are also considering the average or proportion of values ≥ 80 (or 85) and are investigating estimation of low values consistent with a lognormal distribution (though that may bias arithmetic averages low). On the dB-average metric, MOCs (5+ TWAs) range from << 80 to 134 dBA with 73% > 85 dBA.

Conclusions: Noise dosimetry data in DOEHRS-IH offer a rich source for research. Data are likely skewed toward MOCs suspected of having high noise, hence there are few or no data for many MOCs not so suspected. Still, many MOCs, especially those suspected of high noise exposures, have sufficient data to characterize the MOC exposures.



Are Noise and Neurotoxic Chemical Exposures Related to Workplace Traumatic Injuries?

C. Estill, S. Wurzelbacher, and T. Morata, CDC/NIOSH, Cincinnati, OH; C. Rice, A. Bhattacharya, and M. Rao, University of Cincinnati, Cincinnati, OH

Objective: The contribution of noise exposure and chemical hazards to traumatic injury is not well understood. The study was conducted to determine if there is a significant relationship between workers’ compensation (WC) injury claim rates and hazardous exposures for companies. Specific aims were to evaluate WC claims for workplaces with noise exposures above and below the occupational exposure limit and to determine the influence of the synergistic effect between ototoxic and neurological chemicals and noise exposure for predicting traumatic injury.

Methods: Noise and chemical exposure data were gathered from WC consultation site visit reports from 2008 to 2012. WC claims from these companies were evaluated for those same years by gathering data from the Ohio Bureau of Workers’ Compensation (OBWC) including the number of employees for each company. Noise exposure measurements were averaged by company/year and matched with company WC claim rates. Claims were evaluated by International Classification of Diseases (ICD) diagnoses code and 90% were considered traumatic injuries using the Barell Matrix method.

Results: Of 222 companies, 40% had noise exposure levels above established OSHA Permissible Exposure Limit (PEL) and about half were evaluated for chemical exposures. Noise exposure was significantly related to trauma claim rates when adjusting for industry, company size, and hearing conservation programs. Likewise, neurotoxic chemical exposure above the OSHA PEL was significantly related to trauma claims when adjusting for industry and company size. When evaluating only those companies and years with both noise and neurotoxic chemical exposure, noise exposure, chemical exposure, and its interaction were significantly related to trauma claims. This relationship was strengthened when limiting to smaller sized companies. The relative risk of a trauma claim was 1.45 for those companies with average noise exposures above 85 dB compared to those with lower noise exposures.

Conclusions: There was an exposure response relationship for companies with higher average noise exposure and having higher relative risk of trauma claims. Workplace managers should consider evaluating safety hazards if they have elevated noise or neurotoxic chemical exposures.



Correlating Worker Position Through Time with Noise Exposure Measurements for the Prioritization of Noise Source Mitigation

J. Leasure, Associates In Acoustics, Austin, TX

Situation/Problem: Noise dosimetry reports the total noise exposure a worker experiences during their shift, with some instruments reporting sound levels through time. Frequently, workers are active in multiple areas throughout a shift with no records kept of time spent at any location. Other than consideration of the worker's responsibilities, there are few clues for identifying the noise sources responsible for a worker's noise exposure. Blanket noise control policies that seek to reduce noise levels throughout a facility are effective in controlling exposure, but can be inefficient when resources are devoted to mitigating noise sources that are unimportant to actual exposure.

Resolution: Three techniques were employed at a manufacturing facility to determine the most important locations in terms of worker noise exposure. During their shift, workers wore noise dosimeters recording noise levels at 1 second intervals and carried a device used to map their position in time through variation in ambient Wi-Fi signals. Simultaneously, the surveyor measured ambient noise levels throughout the work area and observed the activities of each worker, measuring the time spent in key locations. The 1-second intervals were compared to a noise contour map created from the ambient noise measurements to calculate the exposure accumulated by workers in certain high-noise areas. Notes from activity observations were used to create a map estimating the time workers spent in high-noise areas. A map of worker position and noise exposure was created by the Wi-Fi location system.

Results: Results from the three methods were generally in agreement. They identified short-duration entries into an enclosed area containing high noise sources as the primary cause of exposure for workers who exceeded the PEL. Previous to the study, it was unclear whether the majority of exposure was from activities in the enclosure or elsewhere.

Lessons learned: Measuring, observing, or calculating a worker's movements through a facility in time creates the opportunity to correlate position with measured noise levels. Position, noise, and time data can be combined to create noise exposure maps that identify areas where noise exposure occurs, either for an individual worker or for any subset of members of a shift. Estimates of noise level reduction achieved by mitigation in high-exposure areas can be used to predict the expected reduction in worker noise exposure from implementation of mitigation, which provides a clearer view of its cost-benefit.



Exploration of Potential Applications for Noise Relative Risk Visualization Tools

E. Jones, ExxonMobil Biomedical Sciences, Inc., Annandale, NJ

Situation/Problem: When evaluating whether hearing loss is potentially work related, information characterizing occupational and nonoccupational exposures is routinely collected. A straightforward approach was needed to consistently interpret this information and inform understanding of how exposures from each category may contribute to overall noise exposure risks.

Resolution: A noise relative risk visualization tool was developed to aid understanding of the contribution of occupational exposures to overall noise exposure risks. The tool is based on the equal energy hypothesis of noise induced hearing loss, building on a conceptual approach presented at AIHce by RM Burton, et. al in 2013. Within the tool, measured or estimated average noise exposure levels (in decibels, dBA) are converted to Sound Pressure Level (Pascals), weighted by estimated exposure duration, and summed to estimate a cumulative noise exposure intensity for the scenario of interest. The relative contribution of various noise sources or categories of noise sources can then be compared using simple data visualizations, such as pie charts.

Results: Preliminary testing of the tool was completed using historical Injury and Illness management information. Based on preliminary testing, the tool provided a consistent approach to analyze this information and data visualizations facilitated comparison of relative noise exposure risks. Further testing of this application is planned, and other potential applications for the visionalization approach have been identified. For example, it could also be used to estimate the potential impact of short term noise exposures on long term average exposures, which can be beneficial when developing exposure monitoring strategies or prioritizing risk mitigation projects. The tool could also be used to communicate relative noise exposure risks to managers and potentially exposed individuals.

Lessons learned: The limitations and sensitivities of both the visualization tools and the underlying concepts must be well understood to avoid biasing or misapplying tool results. Therefore, training is recommended to educate users on key concepts and limitations.



Case Study: Industrial Facility Community Noise

P. Murphy, Associates in Acoustics, Los Angeles, CA

Situation/Problem: An industrial facility has received numerous noise complaints from a nearby residence in a new housing development. Despite the facility’s initial noise mitigation efforts, noise complaints continue.

Resolution: An exterior noise survey was conducted to document the existing noise levels at the industrial facility, to locate the noise sources triggering the complaints, and to determine if the facility is in compliance with the local noise ordinance. The survey consisted of noise level measurements recorded at the facility’s property line, near exterior noise sources and at strategic reference locations. The survey revealed the industrial facility was noncompliant with the local noise code, of which they were unaware. Noise sources causing noncompliance and triggering noise complaints from neighbors were verified using frequency spectral analysis and outdoor sound propagation calculations. Noise control methods were recommended for the offending exterior noise sources.

Results: Exterior noise propagation calculations confirm that the facility will comply with the local noise ordinance and reduce noise complaints following the implementation of noise mitigation recommendations for offending noise sources. These efforts will avoid noise related legal issues with the local jurisdiction and establish a good neighbor approach towards residential neighbors. The industrial facility has not received noise complaints since the implementation of noise mitigation recommendations on the offending exterior noise sources.

Lessons learned: Facilities should conduct an exterior noise survey to ensure compliance with code and establish good neighbor practices. Noise mitigation of exterior equipment may be required to bring the facility into compliance and to avoid complaints. Lack of equipment maintenance is often a primary cause of elevated noise levels. The industrial facility should establish a routine inspection, service and maintenance schedule for all exterior noise producing equipment. Once in compliance, noise surveys should be conducted twice per year.



Noise Control for Portable Ventilation Blowers

D. Chute, Atrium Environmental Health and Safety Services, LLC, Reston, VA

Situation/Problem: Portable Ventilation Blowers (PVB) used in manufacturing and construction present many noise control challenges. In addition to the noise generated by motors, fans and air movement, noise control in many work environments is complicated by noise and vibration conductive mounting surfaces, frequent relocation, rugged handling and irregular maintenance. Experience, observation and testing has suggested that several practical control options such as vibration isolators, acoustical jackets, duct silencers and enclosure partitions have the potential to offer feasible noise reduction solutions. No published studies or reports were found to demonstrate how these noise control strategies may be achieved in practice.

Resolution: This work included a review of PVB in use in two major shipyards, with selection of the two largest and most commonly used models for follow up testing, treatment and evaluation. This was a year-long study with multiple field evaluations and collaboration between the research team, the site health and safety and facilities maintenance staff. Treatments tested included: outlet and inlet silencers (mufflers), acoustical jackets, spring and rubber type vibration isolation mounts and acoustical curtains.

Results: Noise reduction treatments, applied both individually and in combination, yielded significant noise reduction benefits without measureable impacts on airflow or ventilation performance. Some treatment combinations yielded measured noise reductions as much as 10 to 12 decibels. In addition, variability in the frequency and content of maintenance practices were cited as a key factor in the wide range of baseline noise levels generated by the same model of PVBs at the same site.

Lessons learned: Practical and cost effective noise reduction for PVB is readily achievable through the application of basic isolation and vibration control treatments. Regular maintenance and repair may also provide further ongoing noise control benefits.



Indoor Hockey Officials’ Noise Exposure, Temporary Hearing Loss, and Effect of Helmet Visor Length on Exposure to Whistle Noise

K. Adams and W. Brazile, Environmental & Radiological Health Sciences, Colorado State University, Fort Collins, CO

Objective: Noise exposure and hearing thresholds of hockey officials in amateur and collegiate hockey leagues were measured to assess the impact of hockey game noise on hearing sensitivity. In addition, the effect of the hockey helmet visor length on the level of whistle noise to which hockey officials are exposed was evaluated to determine if visors may introduce a reflective plane for the whistle noise, resulting in increased noise exposure.

Methods: Twenty-nine hockey officials participated in the study. Personal noise dosimetry was conducted to determine if officials were overexposed to noise, as per ACGIH® recommendations. Pure tone audiometry was used to measure the hearing thresholds of officials before and after officiating hockey games to determine if there was a 10 dB or greater decrease in hearing sensitivity. Audiometry was conducted in both ears at 500, 1000, 2000, 3000, 4000, 6000 and 8000 Hertz. In addition, noise generated from whistle blowing was measured in the left ear of the Knowles Electronic Manikin for Acoustic Research for each of three helmet configurations: without visor, 2.75” visor, and 4.0” visor.

Results: Mean personal noise exposure level was 92 dBA (SD=2.2) using ACGIH® sampling parameters. Hearing threshold shifts of 10 dB or greater were observed in 86% of sampled officials, with statistically significant differences between pre- and post-game hearing thresholds observed in both ears at 2000, 3000 and 4000 Hz. Mean peak whistle noise levels measured at the ear of the manikin without a visor and with the 2.75” and 4.0” length visors were 117 dB (SD<1), 117 dB (SD<1) and 121 dB (SD=1), respectively. Measured peak noise levels were significantly different between the helmet configuration with the long (4.0”) visor and the other helmet configurations (p<0.05), but were not significantly different between the helmet without a visor and with the shorter, 2.75” visor (p>0.05).

Conclusions: The results suggest that indoor hockey officials experienced temporary hearing loss after officiating games. Further temporary threshold shift research may identify hockey officials at larger venues and those officiating other sports are at increased risk of noise induced hearing loss. Manikin study results suggest that longer visors may act as a reflective plane for whistle noise and increase hockey official’s noise exposure. Understanding that longer visors may increase the noise exposure from whistle noise may provide insight for better design of helmet visors in the future.​