Occupational noise exposure is one of the most frequent hazards present in the workplace; up to 22 million workers have potentially hazardous noise exposures in the US. As a result, noise-induced hearing loss is one of the most common occupational injuries in the United States. Workers in manufacturing, construction, and the military are at the highest risk for hearing loss. Despite the large number of people exposed to high levels of noise at work, many occupations have not been adequately evaluated for noise exposure. The objective of this experiment was to investigate whether or not iOS smartphones and other smart devices (Apple iPhones and iPods) could be used as reliable instruments to measure noise exposures. For this experiment three different types of microphones were tested with a single model of iPod and three generations of iPhones: the internal microphones on the device, a low-end lapel microphone, and a high-end lapel microphone marketed as being compliant with the International Electrotechnical Commission's (IEC) standard for a Class 2-microphone. All possible combinations of microphones and noise measurement applications were tested in a controlled environment using several different levels of pink noise ranging from 60 to 100 dBA. Results were compared to simultaneous measurements made using a Type 1 sound level measurement system. Analysis of variance and Tukey's honest significant difference (HSD) test were used to determine if the results differed by microphone or noise measurement application. Levels measured with external microphones combined with certain noise measurement applications did not differ significantly from levels measured with the Type 1 sound measurement system. Results showed that it may be possible to use iOS smartphones and smart devices, with specific combinations of measurement applications and calibrated external microphones, to collect reliable, occupational noise exposure data under certain conditions and within the limitations of the device. Further research is needed to determine how these devices compare to traditional noise dosimeter under real-world conditions.

ObjectivesNoise is one of the most common exposures, and occupational noise-induced hearing loss (NIHL) is highly prevalent. In addition to NIHL, noise is linked to numerous non-auditory health effects. The Occupational Safety and Health Administration (OSHA) maintains the Integrated Management Information System (IMIS) database of compliance-related measurements performed in various industries across the USA. The goal of the current study was to describe and analyse personal noise measurements available through the OSHA IMIS, identifying industries with elevated personal noise levels or increasing trends in worker exposure over time.MethodsThrough a Freedom of Information Act request, we obtained OSHA’s noise measurements collected and stored in IMIS between 1979 and 2013 and analysed permissible exposure limit (PEL) and action level (AL) criteria measurements by two-digit industry code.ResultsThe manufacturing industry represented 87.8% of the 93 920 PEL measurements and 84.6% of the 58 073 AL measurements. The highest mean noise levels were found among the agriculture, forestry, fishing and hunting industry for PEL (93.1 dBA) and the mining, quarrying and oil and gas extraction group for AL (93.3 dBA). Overall, measurements generally showed a decreasing trend in noise levels and exceedances of AL and PEL by year, although this was not true for all industries.ConclusionsOur results suggest that, despite reductions in noise over time, further noise control interventions are warranted both inside and outside of the manufacturing industry. Further reductions in occupational noise exposures across many industries are necessary to continue to reduce the risk of occupational NIHL.

It is universally recognized that prolonged exposure to high levels of non-impulsive noise will lead to noise-induced hearing loss. These high levels of noise have traditionally been found in an occupational setting, but exposure to high levels of noise is increasingly common in recreational settings. There is currently no established acceptable risk of hearing loss in children. This review assumed that the most appropriate exposure limit for recreational noise exposure in children would be developed to protect 99% of children from hearing loss exceeding 5 dB at the 4 kHz audiometric test frequency after 18 years of noise exposure. Using the ISO 1999:2013 model for predicting hearing loss, it was estimated that noise exposure equivalent to an 8-h average exposure (LEX) of 82 dBA would result in about 4.2 dB or less of hearing loss in 99% of children after 18 years of exposure. The 8-h LEX was reduced to 80 dB to include a 2 dB margin of safety. This 8-h LEX of 80 dBA is estimated to result in 2.1 dB or less of hearing loss in 99% of children after 18 years of exposure. This is equivalent to 75 dBA as a 24-h equivalent continuous average sound level.

Objective To analyze over 700,000 cross-sectional measurements from the Mine Safety and Health Administration (MHSA) and develop statistical models to predict noise exposure for a worker. Design Descriptive statistics were used to summarize the data. Two linear regression models were used to predict noise exposure based on MSHA permissible exposure limit (PEL) and action level (AL) respectively. Two-fold cross validation was used to compare the exposure estimates from the models to actual measurements in the hold out data. The mean difference and t-statistic was calculated for each job title to determine if the model exposure predictions were significantly different from the actual data. Study Sample Measurements were acquired from MSHA through a Freedom of Information Act request. Results From 1979 to 2014 the average noise measurement has decreased. Measurements taken before the implementation of MSHA’s revised noise regulation in 2000 were on average 4.5 dBA higher than after the law came in to effect. Both models produced mean exposure predictions that were less than 1 dBA different compared to the holdout data. Conclusion Overall noise levels in mines have been decreasing. However, this decrease has not been uniform across all mining sectors. The exposure predictions from the model will be useful to help predict hearing loss in workers from the mining industry.