Patterns and trends in OSHA occupational noise exposure measurements from 1979 to 2013

Self-reported occupational noise exposure and hearing protection device use among NHANES participants and the risk of hearing loss

Occupational noise exposure continues to be a prevalent hazard in many industries. While the proliferation of noise dosimeters and wearable devices has made it easier to assess a worker's exposure to noise, many employees exposed to hazardous (i.e., >85 dBA) levels of noise may go their entire career without ever having their personal noise levels measured. In contrast to other occupational exposures, noise is easily perceived by the individual exposed, allowing them to develop subjective judgments regarding its characteristics. To determine whether such self-reported exposures to occupational noise are associated with hearing loss, this analysis used audiometric data and self-reported occupational exposure to loud noise from the National Health and Nutrition Examination Survey (NHANES), which has collected such data from 1999 to May 2020. Linear and logistic regressions models found a statistically significant association between self-reported noise exposure and worsened hearing at the 3, 4, 6, and 8 kHz hearing frequency as well as an elevated odds ratio for the development of hearing loss greater than 25 dB at the 2, 3, and 4 kHz audiometric frequencies. The results of this analysis suggest that in the absence of exposure measurements, workers are likely able to detect exposure to hazardous levels of noise. In these instances, additional measurements should be collected to determine if the workers should be enrolled in a hearing conservation program.

Making a racket in America's fastest growing sport: Evaluation of noise exposure in pickleball

OBJECTIVE

To measure noise exposure present on pickleball courts and assess the risk of noise-induced hearing loss (NIHL) per guidelines put forward by the National Institute of Occupational Safety and Health (NIOSH).

METHODS

Observational study measuring noise levels at multiple recreational pickleball courts in the Richmond, VA area, documenting LAeq, LASmax, and LCpeak at courtside and waiting areas of pickleball courts. Measurements were completed using the NIOSH SLM application on an iPhone 13 with iMM-6 Calibrated Measurement Microphone (equivalent to IEC 61672-1 Class II) that was calibrated using ND-9 Sound Level Calibrator (IEC942 Class I).

RESULTS

Average sound levels recorded at waiting areas adjacent to the courts, measured in LAeq, LASmax, and LCpeak, were 69.1 dBA, 92.0 dBA, and 112.1 dBC, respectively, while courtside measurements were 69.7 dBA, 92.2 dBA, and 115.6 dBC, respectively. These measurements were within NIOSH and OSHA recommendations.

CONCLUSION

The data demonstrates that randomly sampled pickleball courts have noise levels that do not increase risk for NIHL for participants or bystanders alike based on NIOSH guidelines. However, prolonged noise exposure and ambient noise pollution may have other health implications and warrant further investigations.

LEVEL OF EVIDENCE

Level 2.

The Burden of Occupational Noise-Induced Hearing Loss From 1990 to 2019: An Analysis of Global Burden of Disease Data

OBJECTIVES

The relationship between long-term exposure to occupational noise and hearing loss has been extensively documented. We aimed to assess spatial and temporal changes in the burden of occupational noise-induced hearing loss (ONIHL) in 204 countries and territories with varying socio-demographic indexes (SDI) from 1990 to 2019.

DESIGN

Temporal and spatial trends in age-standardized disability-adjusted life year rates (ASDR) for ONIHL were estimated by sex, age, SDI level, country, and geographic region from 1990 to 2019. We used the Joinpoint model to calculate annual average percentage changes to assess such trends and projected trends in ASDR for ONIHL globally and across different income regions from 2020 to 2044 using an age-period-cohort model. We fitted the relationship between ASDR and SDI, ASDR and healthcare access and quality index, respectively.

RESULTS

Overall, the global burden of ONIHL has decreased since 1990, especially in middle and lower SDI regions. In 2019, the global ASDR for ONIHL was 84.23 (95% confidence interval: 57.46 to 120.52) per 100,000 population. From 1990 to 2019, the global ASDR for ONIHL decreased by 1.72% (annual average percentage change = -0.05, 95% confidence interval: -0.07 to -0.03). Our projections showed a decreasing trend in the global ONIHL burden until 2044. ASDR and SDI ( R = -0.8, p < 0.05), ASDR and healthcare access and quality index ( R = -0.75, p < 0.05) showed significant negative correlations.

CONCLUSIONS

The global ONIHL burden has decreased over the past three decades, especially in regions with middle and lower SDI levels. However, the global ONIHL burden still remained severe in 2019, notably among males, the middle-aged and elderly, and regions with lower SDI levels.

Prevalence of Hearing Loss Among Noise-Exposed US Workers Within the Utilities Sector, 2010-2019

OBJECTIVE

This study's objective was to estimate hearing loss prevalence for noise-exposed US Utilities workers.

METHODS

In this cross-sectional study of a retrospective cohort, audiograms were examined for 1.3 million workers (13,595 within utilities) from 2010-2019. Hearing loss prevalence and adjusted risk as compared with a reference industry were estimated.

RESULTS

The hearing loss prevalence for noise-exposed Utilities workers (25%) was higher than for noise-exposed workers in all industries combined (20%). Some subsectors surpassed the prevalence for all industries combined and/or had adjusted risks significantly higher than the reference industry. The highest prevalence subsectors were Hydroelectric Power Generation (37%) and steam and Air-Conditioning Supply (29%).

CONCLUSIONS

While often overlooked, noise-exposed workers in this sector have among the highest prevalences of hearing loss and significantly higher risks. Increased attention and better hearing conservation strategies are needed.

Evaluating the potential impact of ototoxicant exposure on worker health

Occupational exposure to ototoxicants, substances that can cause hearing loss alone or exacerbate hearing loss when exposure occurs in combination with noise, is a workplace hazard that is poorly understood. A review of existing research indicates that some solvents and heavy metals may be ototoxic, but few studies have attempted to estimate the impact of ototoxicant exposure on the United States worker population. Researchers examined trends in workplace exposure to ototoxicants among workers in the United States by comparing exposure data collected by the Occupational Safety and Health Administration against worker hearing loss data provided by the Bureau of Labor Statistics (BLS) for 2012-2019. The study found that the noise exposure data was strongly correlated to the hearing loss data using Pearson's correlation (p < .001), confirming that the exposure data collected by OSHA is predictive of the risk of occupational illness as reported by BLS. Chi-square analysis indicates that reported hearing loss was more common among industry subsectors with exposure to ototoxicants than those without exposure to ototoxicants. These findings suggest that workers with coexposure to ototoxicants and noise may be at a higher risk of experiencing hearing loss than those exposed to noise alone, and action should be taken to minimize this risk.

Prerequisite for Imputing Non-detects among Airborne Samples in OSHA's IMIS Databank: Prediction of Sample's Volume

INTRODUCTION

The US Integrated Management Information System (IMIS) contains workplace measurements collected by Occupational Safety and Health Administration (OSHA) inspectors. Its use for research is limited by the lack of record of a value for the limit of detection (LOD) associated with non-detected measurements, which should be used to set censoring point in statistical analysis. We aimed to remedy this by developing a predictive model of the volume of air sampled (V) for the non-detected results of airborne measurements, to then estimate the LOD using the instrument detection limit (IDL), as IDL/V.

METHODS

We obtained the Chemical Exposure Health Data from OSHA's central laboratory in Salt Lake City that partially overlaps IMIS and contains information on V. We used classification and regression trees (CART) to develop a predictive model of V for all measurements where the two datasets overlapped. The analysis was restricted to 69 chemical agents with at least 100 non-detected measurements, and calculated sampling air flow rates consistent with workplace measurement practices; undefined types of inspections were excluded, leaving 412,201/413,515 records. CART models were fitted on randomly selected 70% of the data using 10-fold cross-validation and validated on the remaining data. A separate CART model was fitted to styrene data.

RESULTS

Sampled air volume had a right-skewed distribution with a mean of 357 l, a median (M) of 318, and ranged from 0.040 to 1868 l. There were 173,131 measurements described as non-detects (42% of the data). For the non-detects, the V tended to be greater (M = 378 l) than measurements characterized as either 'short-term' (M = 218 l) or 'long-term' (M = 297 l). The CART models were complex and not easy to interpret, but substance, industry, and year were among the top three most important classifiers. They predicted V well overall (Pearson correlation (r) = 0.73, P < 0.0001; Lin's concordance correlation (rc) = 0.69) and among records captured as non-detects in IMIS (r = 0.66, P < 0.0001l; rc = 0.60). For styrene, CART built on measurements for all agents predicted V among 569 non-detects poorly (r = 0.15; rc = 0.04), but styrene-specific CART predicted it well (r = 0.87, P < 0.0001; rc = 0.86).

DISCUSSION

Among the limitations of our work is the fact that samples may have been collected on different workers and processes within each inspection, each with its own V. Furthermore, we lack measurement-level predictors because classifiers were captured at the inspection level. We did not study all substances that may be of interest and did not use the information that substances measured on the same sampling media should have the same V. We must note that CART models tend to over-fit data and their predictions depend on the selected data, as illustrated by contrasting predictions created using all data vs. limited to styrene.

CONCLUSIONS

We developed predictive models of sampled air volume that should enable the calculation of LOD for non-detects in IMIS. Our predictions may guide future work on handling non-detects in IMIS, although it is advisable to develop separate predictive models for each substance, industry, and year of interest, while also considering other factors, such as whether the measurement evaluated long-term or short-term exposure.

Beware the Grizzlyman: A comparison of job- and industry-based noise exposure estimates using manual coding and the NIOSH NIOCCS machine learning algorithm

Recently, the National Institute for Occupational Safety and Health (NIOSH) released an updated version of the NIOSH Industry and Occupation Computerized Coding System (NIOCCS), which uses supervised machine learning to assign industry and occupational codes based on provided free-text information. However, no efforts have been made to externally verify the quality of assigned industry and job titles when the algorithm is provided with inputs of varying quality. This study sought to evaluate whether the NIOCCS algorithm was sufficiently robust with low-quality inputs and how variable quality could impact subsequent job estimated exposures in a large job-exposure matrix for noise (NoiseJEM). Using free-text industry and job descriptions from >700,000 noise measurements in the NoiseJEM, three files were created and input into NIOCCS: (1) N1, "raw" industries and job titles; (2) N2, "refined" industries and "raw" job titles; and (3) N3, "refined" industries and job titles. Standardized industry and occupation codes were output by NIOCCS. Descriptive statistics of performance metrics (e.g., misclassification/discordance of occupation codes) were evaluated for each input relative to the original NoiseJEM dataset (N0). Across major Standardized Occupational Classifications (SOC), total discordance rates for N1, N2, and N3 compared to N0 were 53.6%, 42.3%, and 5.0%, respectively. The impact of discordance on the major SOC group varied and included both over- and under-estimates of average noise exposure compared to N0. N2 had the most accurate noise exposure estimates (i.e., smallest bias) across major SOC groups compared to N1 and N3. Further refinement of job titles in N3 showed little improvement. Some variation in classification efficacy was seen over time, particularly prior to 1985. Machine learning algorithms can systematically and consistently classify data but are highly dependent on the quality and amount of input data. The greatest benefit for an end-user may come from cleaning industry information before applying this method for job classification. Our results highlight the need for standardized classification methods that remain constant over time.

Time-Trends of U.S. Occupational Noise Standard Violations by OSHA Region and Industry Type 1972 to 2019

OBJECTIVE

We examined time-trends in Occupational Noise Standard violations by OSHA region and industry type over 48 years.

METHODS

Along with descriptive analysis of original data, negative binomial regression and Poisson regression were applied to the analysis of 1972 to 2019 and 1972 to 2012 data, respectively.

RESULTS

A small annual decrease in violation units over the periods was revealed. The three analyses produced differing timetrends. The manufacturing industry had more violations, and Region 4 had the most violations. Regarding numbers of units, the 10 regions and 2 industries were jointly significant. Some interaction between regions and industry types appeared in both regressions.

CONCLUSIONS

OSHA should specify how many regions report noise violations each year to ensure accurate identification of noise-related health risks to American workers. Further time-trend studies are needed for specific regions and industry types.

Toward a better understanding of nonoccupational sound exposures and associated health impacts: Methods of the Apple Hearing Study

Globally, noise exposure from occupational and nonoccupational sources is common, and, as a result, noise-induced hearing loss affects tens of millions of people. Occupational noise exposures have been studied and regulated for decades, but nonoccupational sound exposures are not well understood. The nationwide Apple Hearing Study, launched using the Apple research app in November 2019 (Apple Inc., Cupertino, CA), is characterizing the levels at which participants listen to headphone audio content, as well as their listening habits. This paper describes the methods of the study, which collects data from several types of hearing tests and uses the Apple Watch noise app to measure environmental sound levels and cardiovascular metrics. Participants, all of whom have consented to participate and share their data, have already contributed nearly 300 × 10⁶ h of sound measurements and 200 000 hearing assessments. The preliminary results indicate that environmental sound levels have been higher, on average, than headphone audio, about 10% of the participants have a diagnosed hearing loss, and nearly 20% of the participants have hearing difficulty. The study's analyses will promote understanding of the overall exposures to sound and associated impacts on hearing and cardiovascular health. This study also demonstrates the feasibility of collecting clinically relevant exposure and health data outside of traditional research settings.

Development and initial validation of the Chinese Version of the Noise Exposure Questionnaire (C-NEQ)

BACKGROUND

With a high prevalence of noise-induced hearing loss (NIHL), the noise survey tools for identifying individuals with high risk of NIHL are still limited. This study was aimed to translate and develop a Chinese version of noise exposure questionnaire (C-NEQ), and validate its reliability and reproducibility.

METHODS

This study was conducted from May 2020 to March 2021 in China. The questionnaire was translated from the original NEQ and adapted into Chinese culture using the method according to the International Test Committee. Content validity was evaluated by our expert group. Construct validity and reliability of the C-NEQ was determined through estimating the confirmatory factor analysis and Cronbach's alpha in a cross-sectional analysis among 641 Chinese speaking adults, respectively. The retest reproducibility of the C-NEQ was analyzed by using the intra-group correlation coefficient (ICC) in a follow-up analysis among 151 participants.

RESULTS

The C-NEQ comprises ten items covering four domains: occupational, housework, transport and recreational noise exposure. The annual noise exposure (ANE) was calculated as the protocol of original NEQ. A total of 641 adult participants (aged 26.9 ± 10.1 years, 53.4% males) completed the C-NEQ. The average time for completing the C-NEQ was 4.4 ± 3.0 min. Content validity indicated high relevance of the C-NEQ. The confirmatory factor analysis indices illustrated that the items of the C-NEQ were suitable with the data in the study. For the internal reliability, the Cronbach's α coefficients of the total items and four domains (occupational, housework, transport, and recreational noise exposure) were 0.799, 0.959, 0.837, 0.825, and 0.803, respectively. Among them, 151 participants (aged 36.1 ± 11.1 years, 65.6% males) completed the retest of the C-NEQ 1 month after the first test. The ICC value of total ANEs between the first test and the second test was 0.911 (P < 0.001).

CONCLUSIONS

In this study, we have validated the C-NEQ with adequate reliability and reproducibility for quantifying an individual's annual daily noise exposure, which provides an effective fast-screen tool for researches and clinics to identify those individuals with high risks of NIHL within the short time duration (no more than five minutes) among Chinese population.

Global, regional, and national burden of age-related hearing loss from 1990 to 2019

The global distribution and temporal trend of age-related hearing loss (ARHL) are unknown, and we aimed to investigate magnitudes and temporal trends of ARHL burden and its influencing factors at the national, regional, and global levels. Based on the information of Global Burden of Disease Study 2019, we calculated the estimated annual percentage change to quantify the global, regional, and national temporal trends of age-standardized rates (ASRs) of ARHL by gender, age, and severity. The number of prevalent cases and disability-adjusted life years (DALYs) of ARHL increased from 751.50 million and 22.01 million in 1990 to 1456.66 million and 40.24 million in 2019, respectively. Except for a few countries such as Niger and Burkina Faso, the age-standardized prevalence rate and age-standardized DALYs rate showed a downward trend in most countries and regions. Mild ARHL accounted for the largest proportion in all ARHL, and only mild ARHL showed an upward trend in ASRs. In most regions, the proportion of ARHL disease burden attributable to occupational noise showed a downward trend in the past 30 years. In 2019, ARHL disease burden attributable to occupational noise declined with the increase of socio-demographic index in countries. Although the ASR of ARHL in most parts of the world is declining, the absolute disease burden of ARHL is still heavy. Understanding the real-time disease burden of ARHL and its temporal trend is of great significance for formulating more effective preventive measures and reducing the ARHL burden.

The comprehensive audiological evaluation in young violinists: the medial olivocochlear system, high frequency thresholds, and the auditory figure ground test

PURPOSE

The aim of this study was to examine whether the medial olivocochlear hearing system functions, the high frequency hearing thresholds and speech discrimination in noise performance can guide us in assessing the risk of hearing loss among violinists. It is aimed to investigate possible hearing damage that is not reflected in pure tone hearing thresholds in violinists.

METHODS

The participants (n = 50) who have normal hearing and the ages of 18-30 were included in this study in two groups: violinists and controls who are unrelated to music. High frequency audiometer, auditory figure ground test (AFG) for speech discrimination in noise performance, Distortion Product Otoacoustic Emission (DPOAE) and contralateral suppression on DPOAE for medial olivocochlear system function tests were applied to all participants as well as routine audiological tests.

RESULTS

The high frequency hearing thresholds were obtained higher in violinists compared to the controls. In violinists, the AFG test scores and the suppression amount at 1 kHz were lower than the controls. In addition, DPOAE responses at 4-6 kHz were obtained lower in violinists (p < 0.05).

CONCLUSION

The reason for high frequency hearing loss, decreased DPOAE response amplitudes, and poor medial olivocochlear function in violinists can be explained by the long-term exposure to high-level noise caused by the violin, one of the closest musical instruments. Routine and comprehensive audiological follow-up is crucial for musicians.

Analysis of Early Biomarkers Associated With Noise-Induced Hearing Loss Among Shipyard Workers

IMPORTANCE

It is important to determine what frequencies and auditory perceptual measures are the most sensitive early indicators of noise-induced hearing impairment.

OBJECTIVES

To examine whether hearing loss among shipyard workers increases more rapidly at extended high frequencies than at clinical frequencies and whether subtle auditory processing deficits are present in those with extensive noise exposure but little or no hearing loss.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study collected audiometric data (0.25-16 kHz), survey questionnaires, and noise exposure levels from 7890 shipyard workers in a Shanghai shipyard from 2015 to 2019. Worsening hearing loss was evaluated in the group with hearing loss. Speech processing and temporal processing were evaluated in 610 participants with noise exposure and clinically normal hearing to identify early biomarkers of noise-induced hearing impairment. Data analysis was conducted from November to December 2020.

MAIN OUTCOMES AND MEASURES

Linear regression was performed to model the increase in hearing loss as function of cumulative noise exposure and compared with a group who were monitored longitudinally for 4 years. Auditory processing tests included speech-in-noise tests, competing sentence tests, dichotic listening tests, and gap detection threshold tests and were compared with a control group without history of noise exposure.

RESULTS

Of the 5539 participants (median [interquartile range (IQR)] age, 41.0 [34.0-47.0] years; 3861 [86.6%] men) included in the cross-sectional analysis, 4459 (80.5%) were hearing loss positive and 1080 (19.5%) were hearing loss negative. In younger participants (ie, ≤40 years), the maximum rate of increase in hearing loss was 0.40 (95% CI, 0.39-0.42) dB per A-weighted dB-year (dB/dBA-year) at 12.5 kHz, higher than the growth rates of 0.36 (95% CI, 0.35-0.36) dB/dBA-year at 4 kHz, 0.32 (95% CI, 0.31-0.33) dB/dBA-year at 10 kHz, 0.31 (95% CI, 0.30-0.31) dB/dBA-year at 6 kHz, 0.27 (95% CI, 0.26-0.27) dB/dBA-year at 3 kHz, and 0.27 (95% CI, 0.27-0.28) dB/dBA-year at 8 kHz. In the 4-year longitudinal analysis of hearing loss among 403 participants, the mean (SD) annual deterioration in hearing was 2.70 (2.98) dB/y at 12.5 kHz, almost twice as that observed at lower frequencies (eg, at 3kHz: 1.18 [2.15] dB/y). The auditory processing scores of participants with clinically normal hearing and a history of noise exposure were significantly lower than those of control participants (eg, median [IQR] score on speech-in-noise test, noise-exposed group 1 vs control group: 0.63 [0.55-0.66] vs 0.78 [0.76-0.80]; P < .001).

CONCLUSIONS AND RELEVANCE

These findings suggest that the increase in hearing loss among shipyard workers was more rapid at 12.5 kHz than at other frequencies; workers with clinically normal hearing but high cumulative noise exposure are likely to exhibit deficits in speech and temporal processing.

Effect of Unmeasured Time Hours on Occupational Noise Exposure Assessment in the Shipbuilding Process in Korea

Occupational noise is known to be one of the most hazardous risk factors, frequently exceeding the exposure limit thus causing hearing loss and other health outcomes among many field workers in various industries and workplaces. This study aims to characterize the levels of occupational noise exposure during the daily working hours and break periods (sampling preparation and lunch break), identify work-related characteristics affecting the noise exposure levels when including or excluding the break periods and finally determine the most effective approach for occupational noise exposure assessment by using the Korean and U.S. OSHA’s guidelines. A total of 1575 workers employed by a large shipbuilding company participated in this study, and the historical exposure datasets of noise dosimeters, collected from 2016 to 2018, were classified by characteristics. A threshold level (TL) for the noise dosimeter was set as a value of 80 dBA during the break periods, including the preparation time for sampling instruments and one hour for the lunch break. The shipbuilding workers were exposed to high levels of occupational noise during the break periods, especially for those working in heating, grinding, and power processes in the painting-related departments. Out of 1575 samples, most cases were related to the preparation time (N = 1432, 90.9%) and lunch break (N = 1359, 86.9%). During the break time, the levels of noise exposure were measured depending on task-specific characteristics. When including the break time, the noise levels increased by approximately 1 dBA during the break, combining 0.8 dBA in the lunch hours and 0.2 dBA for the preparation of the sampling instrument. When excluding the break time, the levels of noise exposure collected using a Korean Occupational Safety and Health Administration (KOSHA) guide tended to be underestimated compared to those using the U.S. OSHA method. When including the break times, the proportion of noise exposure levels exceeding the compliance exposure limit declined from 37.9% to 34.5%, indicating that the break times might affect the decrease in the noise exposure levels. Taken together, shipbuilding workers could possibly be exposed to much greater amounts of noise exposure during break times in the shipbuilding processes, and the noise exposure levels in the department of painting were high. Therefore, it is recommended that industrial hygienists collect exposure monitoring data of occupational noise one hour after their job tasks begin and then consecutively monitor the noise exposure levels for at least 6 h including the break periods for each day.

Factors associated with notification of noise-induced hearing loss in Brazil, 2013-2015: an ecological study

OBJECTIVE

To investigate factors associated with the notification of noise-induced hearing loss (NIHL), on the Notifiable Health Conditions Information System (SINAN) in Brazil.

METHODS

This was an ecological study to estimate the proportion of municipalities that had notified NIHL. Logistic regression models were used to identify associated factors.

RESULTS

Between 2013-2015, 277 (5.0%) municipalities notified NIHL. Notification was more prevalent among municipalities in an Occupational Health Referral Center (CEREST) coverage area (OR=1.62 - 95%CI 1.02;2.59) or those that had a CEREST in their territory (OR=4.37 - 95CI% 2.75;6.93), those that were closer to the state capital (OR=1.43 - 95%CI 1.06;1.92) and those with a high human development index (OR=2.35 - 95%CI 1.16;4.75). Among the municipalities located in a CEREST coverage area, notification was more frequent when there was a speech-language-hearing professional in the team (OR=1.96 - 95%CI - 1.47;2.63) and when employee turnover was low (OR=1.88 - 95%CI 1.40;2.52).

CONCLUSION

Contextual factors influence NIHL notification, particularly the presence of CERESTs and their qualification.

An overview of occupational noise-induced hearing loss among workers: epidemiology, pathogenesis, and preventive measures

Occupational noise-induced hearing loss (ONIHL) is the most prevalent occupational disease in the world. The goal of this study was to review the epidemiology, pathogenesis, and preventive measures of ONIHL among workers and provide evidence for the implementation of control measures. Literature studies were identified from the MEDLINE, PubMed, Embase, Web of Science, and Google Scholar using the search terms “noise-induced hearing loss” “prevalence”, “pathogenesis”, and “preventive measures”. The articles reviewed in this report were limited from 2000 to 2020. Articles that were not published in the English language, manuscripts without an abstract, and opinion articles were excluded. After a preliminary screening, all of the articles were reviewed and synthesized to provide an overview of the current status of ONIHL among workers. The mechanism of ONIHL among workers is a complex interaction between environmental and host factors (both genetic and acquired factors). The outcomes of noise exposure are different among individual subjects. Clinical trials are currently underway to evaluate the treatment effect of antioxidants on ONIHL. Noise exposure may contribute to temporary or permanent threshold shifts; however, even temporary threshold shifts may predispose an individual to eventual permanent hearing loss. Noise prevention programs are an important preventive measure in reducing the morbidity of ONIHL among workers.

Analysis of Occupational Safety and Health Administration (OSHA) noise standard violations over 50 years: 1972 to 2019

INTRODUCTION

Noise exposure has long been an occupational health concern and has been an important area of focus of the Occupational Safety and Health Administration (OSHA) since its founding. Nevertheless, it remains unclear what effects OSHA's noise standards have had on employer efforts to reduce risks. Consequently, a review of OSHA noise standard violations was performed to clarify the violation trends between 1972 and 2019.

METHODS

Using the OSHA Information System, researchers identified 119 305 violations involving four noise standards between 1972 and 2019: 29 CFR 1910.95, occupational noise exposure in general industry; 1926.52, occupational noise exposure in construction; 1926.101, hearing protection in construction, and 1904.10, recording criteria for cases involving occupational hearing loss. Violation frequencies of noise standard subparagraphs and relationships to factors such as industry differences were analyzed using descriptive statistics and t tests.

RESULTS

The most commonly violated noise standard was 1910.95 in manufacturing. Such violations rose between 1972 and 1985 and then declined steadily. Whether in general industry or construction, four noise standards were most-frequently cited: lack of feasible administrative or engineering controls (1910.95[b] and 1926.52[d]) and inadequate hearing conservation program (1910.95[c] and 1926.52[b]). These violations were more highly penalized (mean = $1036.50) than other subparagraph violations (mean = $915.80). Programmed and unprogrammed inspections generated similar violation quantities except between 1980 and 1985, when programmed inspections exhibited a sharp spike in violations.

CONCLUSION

The study identified trends in OSHA noise standard violations and possible explanations for those trends. The study findings can support development of more practical noise-exposure protection policy.

A Quantitative General Population Job Exposure Matrix for Occupational Noise Exposure

Occupational noise exposure is a known risk factor for hearing loss and also adverse cardiovascular effects have been suggested. A job exposure matrix (JEM) would enable studies of noise and health on a large scale. The objective of this study was to create a quantitative JEM for occupational noise exposure assessment of the general working population. Between 2001–2003 and 2009–2010, we recruited workers from companies within the 10 industries with the highest reporting of noise-induced hearing loss according to the Danish Working Environment Authority and in addition workers of financial services and children day care to optimize the range in exposure levels. We obtained 1343 personal occupational noise dosimeter measurements among 1140 workers representing 100 different jobs according to the Danish version of the International Standard Classification of Occupations 1988 (DISCO 88). Four experts used 35 of these jobs as benchmarks and rated noise levels for the remaining 337 jobs within DISCO 88. To estimate noise levels for all 372 jobs, we included expert ratings together with sex, age, occupational class, and calendar year as fixed effects, while job and worker were included as random effects in a linear mixed regression model. The fixed effects explained 40% of the total variance: 72% of the between-jobs variance, −6% of the between-workers variance and 4% of the within-worker variance. Modelled noise levels showed a monotonic increase with increasing expert score and a 20 dB difference between the highest and lowest exposed jobs. Based on the JEM estimates, metal wheel-grinders were among the highest and finance and sales professionals among the lowest exposed. This JEM of occupational noise exposure can be used to prioritize preventive efforts of occupational noise exposure and to provide quantitative estimates of contemporary exposure levels in epidemiological studies of health effects potentially associated with noise exposure.

Motor vehicle towing: An analysis of injuries in a high-risk yet understudied industry

OBJECTIVES

National fatality rates for commercial tow truck operators exceed those of other first responders who also perform traffic incident management services. The objectives of the current study are to (1) characterize causal factors associated with injuries among commercial tow truck operators engaged in roadside assistance through analysis of coded and free text data obtained from U.S. Occupational Safety and Health Administration (OSHA) investigation files, and (2) utilize supplemental data sources to analyze environmental factors for injuries in which commercial tow truck operators were struck by roadway traffic.

METHODS

Searches of OSHA's online IMIS database were performed to identify investigations of incidents in which tow truck operators were injured while performing roadside assistance duties. Freedom of Information Act (FOIA) requests were submitted to obtain full investigation files for each case. Coded and narrative text analyses were performed to identify causal themes across the identified cases.

RESULTS

One-hundred and six cases of tow truck operators being killed or severely injured were identified in IMIS; 41 FOIA requests for related investigation documents were fulfilled. Two major event type themes were identified which accounted for 9 in 10 of the cases identified. These were (1) 'struck-by' incidents, which were primarily injuries resulting from contact with roadway traffic, rolling vehicles and equipment or other non-motorized objects; and (2) 'caught-in or -between' incidents, which were primarily injuries resulting from being pinned beneath and between vehicles and being caught in moving parts.

CONCLUSIONS

The towing industry should provide initial and refresher safety training on vehicle loading and unloading, defensive techniques when exposed to traffic on roadways, and proper wheel chocking and braking procedures. States should include tow trucks as a first responder vehicle type in their "Move Over" laws and implement public awareness campaigns to protect all first responders, including tow truck operators.

Early hearing slope as a predictor of subsequent hearing trajectory in a noise-exposed occupational cohort

Variations in individual susceptibility to noise-induced hearing loss have been observed among workers exposed to similar ambient noise levels but the reasons for this observation are poorly understood. Many workers are exposed to hazardous levels of occupational noise throughout their entire careers. Therefore, a mechanism to identify workers at risk for accelerated hearing loss early in their career may offer a time-sensitive window for targeted intervention. Using available longitudinal data for an occupationally noise-exposed cohort of manufacturing workers, this study aims to examine whether change in an individual's high frequency hearing level during the initial years of occupational noise exposure can predict subsequent high frequency hearing loss. General linear mixed modeling was used to model later hearing slope in the worse ear for the combined frequencies of 3, 4, and 6 kHz as a function of early hearing slope in the worse ear, age at baseline, sex, race/ethnicity, mean ambient workplace noise exposure, and self-reported non-occupational noise exposure. Those with accelerated early hearing loss were more likely to experience a greater rate of subsequent hearing loss, thus offering a potentially important opportunity for meaningful intervention among those at greatest risk of future hearing loss.

Occupational noise exposure: A review of its effects, epidemiology, and impact with recommendations for reducing its burden

Exposure to hazardous noise is one of the most common occupational risks, both in the U.S. and worldwide. Repeated overexposure to noise at or above 85 dBA can cause permanent hearing loss, tinnitus, and difficulty understanding speech in noise. It is also associated with cardiovascular disease, depression, balance problems, and lower income. About 22 million U.S. workers are currently exposed to hazardous occupational noise. Approximately 33% of working-age adults with a history of occupational noise exposure have audiometric evidence of noise-induced hearing damage, and 16% of noise-exposed workers have material hearing impairment. While the Mining, Construction, and Manufacturing sectors typically have the highest prevalence of noise exposure and hearing loss, there are noise-exposed workers in every sector and every sector has workers with hearing loss. Noise-induced hearing loss is preventable. Increased understanding of the biological processes underlying noise damage may lead to protective pharmacologic or genetic therapies. For now, an integrated public health approach that (1) emphasizes noise control over reliance on hearing protection, (2) illustrates the full impact of hearing loss on quality of life, and (3) challenges the cultural acceptance of loud noise can substantially reduce the impact of noise on worker health.

Audiometric notch for the prediction of early occupational hearing loss and its association with the interleukin-1beta genotype

Objectives

Noise-induced hearing loss (NIHL) is a frequent and irreversible industrial-health problem, the early diagnosis of which can prevent hearing deterioration, especially of speech frequencies. This study aimed to assess hearing impairment in workers occupationally exposed to noise. Audiometric notches and IL-1β gene polymorphisms were evaluated.

Methods

The study included 98 workers employed in a textile factory. Pure-tone audiometric testing was conducted for all workers, using a manual pure-tone diagnostic audiometer, and the noise level was measured at four different work sites in a spinning section. IL-1β gene polymorphism was determined using PCR-RFLP methods.

Results

Workers were exposed to a mean noise level of 105.5 dB. As many as 27.6% of them complained of tinnitus and the majority suffered from some degree of hearing loss in either ear, but none of them exceeded 60 dB. Audiometric notches were detected in either one or both ears. Only 28.6% of workers showed the absence of notches. The TT genotype of IL-1β polymorphisms was dominant in 49% of the workers, whereas TC was predominant in 39.8% and CC in 11.2%. The CC genotype was associated with smoking (54.5%) and audiometric notches (100%). The IL-1β genotype distribution showed no significant difference with or without tinnitus.

Conclusion

This study showed an association between the CC genotype and smoking as well as audiometric notches in workers occupationally exposed to noise. Workers showing audiometric notches should be followed up regularly. Further studies are required to confirm the interrelationship amongst tinnitus, audiometric notches, and IL-1β genotypes.

Occupational Diseases among Workers in Lower and Higher Socioeconomic Positions

Background: To determine differences between workers in lower and higher socioeconomic positions (SEP) in incidences of occupational disease (OD) and incapacity for work due to ODs. Methods: From a Dutch dynamic prospective cohort of occupational physicians (OPs), ODs assessed by OPs were retrieved for lower and higher SEP groups. Results: Among the lower SEP, musculoskeletal disorders, and noise-induced hearing loss (NIHL) comprised two-thirds of the OD diagnoses. Among the higher SEP, stress/burnout comprised 60% of the OD diagnoses. Temporary and permanent incapacity for work due to work-related lower back disorders and repetitive strain injuries differed significantly between workers in lower compared to higher SEP. Conclusions: Occupational diseases occur at a 2.7 higher incidence rate for workers in lower SEP compared with higher SEP. Incapacity for work varies between the type of OD and the level of SEP.