Improved Methods for Evaluating Noise Exposure and Hearing Loss
dc.contributor.author | Roberts, Benjamin | |
dc.date.accessioned | 2017-06-14T18:33:52Z | |
dc.date.available | NO_RESTRICTION | |
dc.date.available | 2017-06-14T18:33:52Z | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/137069 | |
dc.description.abstract | Noise is one of the most common occupational exposures in the United States; up to 22 million workers are exposed to dangerous noise levels each year. Excessive noise exposure can lead to noise-induced hearing loss (NIHL). Exposure to high levels of noise may also be a contributing factor for a number of non-auditory outcomes, including injuries, cardiovascular disease, stress, and depression. This dissertation research focused on improving our understanding of the relationship between occupational noise exposure and NIHL by completing three distinct but related projects. Project 1 investigated the feasibility of using smart devices (iPods and iPhones) to accurately measure occupational noise in laboratory experiments and real-life workplaces. This project was divided into four experiments, three of which took place in a controlled laboratory setting, and one of which was a field test of the devices in two groups of workers. Experiment 1 demonstrated that certain combinations of applications and microphones could provide measurements within +/ 2.0 A-weighted decibels (dBA) of a reference noise level. Experiment 2 showed that the best-performing microphone and application combinations could provide measurements within +/- 2.0 dBA of a reference level across different generations of devices. Experiment 3 demonstrated that the 8-hr time weighted average (TWA) measured by the smart devices was within +/- 1.5 dBA of a paired noise dosimeter. Finally, experiment 4 determined that, on average, smart devices overestimated workplace exposures by up to 2.2 dBA among workers exposed to highly variable noise. Project 2 developed a job-exposure matrix (JEM) for every occupation in the United States. This was done by collecting data from the government, private, industry and the published literature. From this dataset 748,598 measurements made using the Occupational Health and Safety Administration’s (OSHA) Permissible Exposure Limit (PEL) were used to impute exposures for occupations without measurement data. Each measurement was assigned a job title based on the Bureau of Labor Statistics’ (BLS) standard occupational classification (SOC) system. Because this classification system is hierarchical, it was possible to impute values for SOCs using SOCs where data was available. Of 443 SOCs, 19% and 74% were estimated to have noise exposures >85 dBA and >80 dBA, respectively, although many SOCs had wide credible intervals, indicating a significant amount of uncertainty around the point estimates. Project 3 compared the ability of the OSHA PEL and the National Institute of Occupational Safety and Health’s (NIOSH) Recommended Exposure Limit (REL) to predict NIHL. Noise exposures were estimated for a previously established cohort of construction workers followed for 10 years using both the PEL and REL metrics. These exposure estimates were used in mixed models predicting hearing threshold levels (HTLs). Akaike information criterion (AIC) was calculated to evaluate model fit. The modeled estimates were also compared to hearing loss estimates from an International Organization of Standards (ISO) NIHL model. In all but one instance, the models using the REL were found to have a better model fit. The mixed models predicted more hearing loss than the corresponding ISO model; however, the REL showed closer agreement to the corresponding ISO model than the PEL. The completion of these projects have made it easier to collect and use occupational noise measurements for epidemiological purposes. In addition, this research will help inform best practices for collecting occupational noise measurements to that they can be used to better predict NIHL. | |
dc.language.iso | en_US | |
dc.subject | Occupational Noise | |
dc.subject | Exposure Assessment | |
dc.subject | Industrial Hygiene | |
dc.subject | Noise-induced Hearing Loss | |
dc.subject | Occupational Health | |
dc.subject | Public Health | |
dc.title | Improved Methods for Evaluating Noise Exposure and Hearing Loss | |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Environmental Health Sciences | |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | |
dc.contributor.committeemember | Neitzel, Richard L | |
dc.contributor.committeemember | Mukherjee, Bhramar | |
dc.contributor.committeemember | Park, Sung Kyun | |
dc.contributor.committeemember | Seixas, Noah S | |
dc.subject.hlbsecondlevel | Public Health | |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | |
dc.subject.hlbtoplevel | Health Sciences | |
dc.subject.hlbtoplevel | Science | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/137069/1/bjrobe_1.pdf | |
dc.identifier.orcid | 0000-0001-7451-925X | |
dc.identifier.name-orcid | Roberts, Benjamin; 0000-0001-7451-925X | en_US |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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