Prevalence and determinants of noise-induced hearing loss among workers in the automotive industry in China: A pilot study

Advancing noise management in aviation: Strategic approaches for preventing noise-induced hearing loss

As urbanization and population growth escalate, the challenge of noise pollution intensifies, particularly within the aviation industry. This review examines current insights into noise-induced hearing loss (NIHL) in aviation, highlighting the risks to pilots, cabin crew, aircraft maintenance engineers, and ground staff from continuous exposure to high-level noise. It evaluates existing noise management and hearing conservation strategies, identifying key obstacles and exploring new technological solutions. While progress in developing protective devices and noise control technologies is evident, gaps in their widespread implementation persist. The study underscores the need for an integrated strategy combining regulatory compliance, technological advances, and targeted educational efforts. It advocates for global collaboration and policy development to safeguard the auditory health of aviation workers and proposes a strategic framework to enhance hearing conservation practices within the unique challenges of the aviation sector.

Time Trend of Occupational Noise-induced Hearing Loss in a Metallurgical Plant With a Hearing Conservation Program

Background

This study aimed to analyze the trend of occupational noise-induced hearing loss (ONIHL) in Brazilian workers at a metallurgical plant with a hearing conservation program (HCP), which has been addressed in a previous study.

Methods

All 152 workers in this time series (20032018) participated in the HCP and used personal protective equipment. All annual audiometry records in the company's software were collected from the electronic database. The trend of ONIHL was analyzed with the joinpoint regression model. The hearing thresholds of ONIHL cases at the end of the series were compared with those found in a national reference study.

Results

The binaural mean hearing thresholds at 3, 4, and 6 kHz at the end of the series were higher for ages ≥50 years, exposures ≥85 dB (A), time since admission >20 years, and maintenance workers. Significance was found only in the group divided by age. There was an increasing time trend of ONIHL, though with a low percentage variation for the period (AAPC = 3.5%; p = 0.01). Hearing thresholds in this study differed from the reference one.

Conclusion

Despite the unmet expectation of a stationary trend in the study period, the time pace of ONIHL evolution did not follow what was expected for a population exposed to noise. These findings signal to the scientific community and public authorities that good ONIHL control is possible when HCP is well implemented.

Risk analysis of noise-induced hearing loss of workers in the automobile manufacturing industries based on back-propagation neural network model: a cross-sectional study in Han Chinese population

OBJECTIVES

This study aims to predict the risk of noise-induced hearing loss (NIHL) through a back-propagation neural network (BPNN) model. It provides an early, simple and accurate prediction method for NIHL.

DESIGN

Population based, a cross sectional study.

SETTING

Han, China.

PARTICIPANTS

This study selected 3266 Han male workers from three automobile manufacturing industries.

PRIMARY OUTCOME MEASURES

Information including personal life habits, occupational health test information and occupational exposure history were collected and predictive factors of NIHL were screened from these workers. BPNN and logistic regression models were constructed using these predictors.

RESULTS

The input variables of BPNN model were 20, 16 and 21 important factors screened by univariate, stepwise and lasso-logistic regression. When the BPNN model was applied to the test set, it was found to have a sensitivity (TPR) of 83.33%, a specificity (TNR) of 85.92%, an accuracy (ACC) of 85.51%, a positive predictive value (PPV) of 52.85%, a negative predictive value of 96.46% and area under the receiver operating curve (AUC) is: 0.926 (95% CI: 0.891 to 0.961), which demonstrated the better overall properties than univariate-logistic regression modelling (AUC: 0.715) (95% CI: 0.652 to 0.777). The BPNN model has better predictive performance against NIHL than the stepwise-logistic and lasso-logistic regression model in terms of TPR, TNR, ACC, PPV and NPV (p<0.05); the area under the receiver operating characteristics curve of NIHL is also higher than that of the stepwise and lasso-logistic regression model (p<0.05). It was a relatively important factor in NIHL to find cumulative noise exposure, auditory system symptoms, age, listening to music or watching video with headphones, exposure to high temperature and noise exposure time in the trained BPNN model.

CONCLUSIONS

The BPNN model was a valuable tool in dealing with the occupational risk prediction problem of NIHL. It can be used to predict the risk of an individual NIHL.

Statistical estimation of noise induced hearing loss among the drivers in one of the most polluted cities of India

In the present study, an attempt has been made to assess the impact of vehicular noise upon the 3-wheeler tempo drivers and to know whether there is any relationship between hearing loss and cumulative noise exposure. For this purpose, 3-wheeler tempo drivers (Exposed group) and non-commercial light motor vehicle car drivers (Unexposed group) were chosen as study subjects. Three traffic routes were selected to assess the noise level during waiting and running time in the exposed and unexposed groups. Among all three routes, the highest mean noise level (Leq) was observed on the Chowk to Dubagga route for waiting and en-route noise measurement. It was measured as 84.13 dB(A) and 86.36 dB(A) for waiting and en-route periods of 7.68 ± 3.46 and 31.05 ± 6.6 min, respectively. Cumulative noise exposure was found to be significantly different (p < 0.001) in all age groups of exposed and unexposed drivers. Audiometric tests have been performed over both exposed and unexposed groups. The regression analysis has been done keeping hearing loss among tempo drivers as the dependent variable and age (years) and Energy (Pa2 Hrs) as the independent variable using three different criteria of hearing loss definitions, i.e., World Health Organization, National Institute for Occupational Safety and Health (NIOSH), Occupational Safety and Health Administration criteria. Among these three criteria, the NIOSH criterion of hearing loss best explained the independent variables. It could explain the total variation in dependent variable by independent variable quite well, i.e., 68.1%. The finding showed a linear relationship between cumulative noise exposures (Pa2 Hrs) and the exposed group's hearing loss (dB), i.e., hearing loss increases with increasing noise dose. Based on the findings, two model equations were developed to identify the safe and unsafe noise levels with exposure time.

A risk model for occupational noise-induced hearing loss in workers

BACKGROUND

Occupational hearing loss is one of the most common work-related diseases with various risk factors and considerable negative impacts on both physical and mental well-being of affected workers. Occupational noise-induced hearing loss (ONIHL) has a complex interaction with personal, environmental and occupational factors.

OBJECTIVE

This study aimed to develop a risk model for ONIHL in workers by identifying risk factors and their interactions.

METHODS

The subjects were 605 males in an industrial factory in Arak, Iran. The study took place between 2022 and 2023. The sociodemographic and occupational characteristics were collected by a health technician using questionnaires and medical records. Hearing status was assessed using audiometry by a qualified audiologist. Hearing loss was analyzed by univariate logistic analysis including age, smoking, medical history, type of occupation, and some workplace hazards. The risk model was generated by logistic regression.

RESULTS

Hearing loss in the participants was 44.13% (n = 267). In univariate logistic analysis, age (OR: 2.93,95% CI: 1.848-4.656), smoking (OR: 1.80, 95% CI: 1.224-2.655), work experience (OR: 1.06, 95% CI: 1.016-1.107), previous exposure to noise (OR: 1.60, 95% CI: 1.112-2.312) or vibration (OR: 1.68, 95% CI: 1.150-2.475) and type of occupation (OR: 2.126, 95% CI: 1.055-4.285) were associated with an increased risk of ONIHL (P < 0.05).

CONCLUSION

It was found that vibration exposure, work experience, previous noise exposure, type of occupation as well as age and smoking significantly affected the likelihood of developing ONIHL. This risk model could help management to prevent ONIHL and enhance application-oriented research on the condition.

The role of kurtosis and kurtosis-adjusted energy metric in occupational noise-induced hearing loss among metal manufacturing workers

Background

Noise energy has been well-established to increase the risk of occupational noise-induced hearing loss (NIHL). However, the role of noise temporal structure (expressed by kurtosis) or its combination with energy metrics (e.g., kurtosis-adjusted cumulative noise exposure, adj-CNE) in occupational NIHL was still unclear.

Methods

A cross-sectional survey of 867 Chinese workers, including 678 metal manufacturing workers and 189 workers exposed to Gaussian noise, was conducted. Noise energy metrics, including L_Aeq,8h and CNE, kurtosis (β), and adj-CNE were used to quantify noise exposure levels. Noise-induced permanent threshold shift at frequencies 3, 4, and 6 kHz (NIPTS₃₄₆) and the prevalence of high-frequency NIHL (HFNIHL%) were calculated for each participant. The dose-response relationship between kurtosis or adj-CNE and occupational NIHL was observed.

Results

Among 867 workers, different types of work had specific and independent noise energy and kurtosis values (p > 0.05). HFNIHL% increased with an increase in exposure duration (ED), L_Aeq,8h, CNE, or kurtosis (p < 0.01), and there were strong linear relationships between HFNIHL% and ED (coefficient of determination [R²] = 0.963), CNE (R² = 0.976), or kurtosis (R² = 0.938, when CNE < 100 dB(A)∙year). The "V" shape notching extent in NIPTS became deeper with increasing kurtosis when CNE < 100 dB(A)∙year and reached the notching bottom at the frequency of 4 or 6 kHz. The workers exposed to complex noise (β ≥ 10) had a higher risk of NIHL than those exposed to Gaussian noise (β < 10) at the frequencies of 3, 4, 6, and 8 kHz (OR > 2, p < 0.01). Moreover, HFNIHL% increased with adj-CNE (p < 0.001). There were strong linear relationships between NIHL and adj-CNE or CNE when β ≥ 10 (R²_adj-CNE > R²_CNE). After CNE was adjusted by kurtosis, average differences in NIPTS₃₄₆ or HFNIHL% between the complex and Gaussian noise group were significantly reduced (p < 0.05).

Conclusion

Kurtosis was a key factor influencing occupational NIHL among metal manufacturing workers, and its combination with energy metrics could assess the risk of NIHL more effectively than CNE alone.

Effectiveness of Kurtosis-Adjusted Cumulative Noise Exposure in Assessing Occupational Hearing Loss Associated With Complex Noise

OBJECTIVES

Occupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases worldwide. Few studies have been reported on applying kurtosis-adjusted noise energy (e.g., kurtosis-adjusted cumulative noise exposure, CNE-K) as a joint indicator for assessing NIHL. This study aimed to analyze the effectiveness of CNE-K in assessing occupational hearing loss associated with complex noise in typical manufacturing industries.

DESIGN

A cross-sectional survey of 1404 Chinese manufacturing workers from typical manufacturing industries was conducted. General demographic characteristics, noise exposure data, and noise-induced permanent threshold shifts (NIPTS) at 3, 4, and 6 kHz (NIPTS 346 ) were collected and analyzed. The role of kurtosis in high-frequency noise-induced hearing loss (HFNIHL) was also analyzed. The degree of overlap of the two logistic curves (i.e., between complex noise CNE-K and HFNIHL%, and between Gaussian noise CNE and HFNIHL%) was used to evaluate the effectiveness of CNE-K, using a stratified analysis based on age, sex, industry, or job type.

RESULTS

The binary logistic regression analysis showed that in addition to age, sex, exposure duration, and Eight-hour Continuous Equivalent A-weighted Sound Pressure Level (L Aeq,8h ), kurtosis was a key factor influencing HFNIHL% in workers (odds ratio = 1.18, p < 0.05), and its odds ratio increased with an increase in kurtosis value. Multiple linear regression analysis demonstrated that the contribution of kurtosis to NIPTS 346 was second to L Aeq,8h . Complex noise led to a higher risk of NIHL than Gaussian noise at frequencies of 3, 4, 6, and 8 kHz after adjusting for age, sex, and CNE ( p < 0.05). As kurtosis increased, the notch in the audiogram became deeper, and the frequency at which the notch began to deepen shifted from 3 to 1 kHz. The logistic curve between complex noise CNE-K and HFNIHL% nearly overlapped with that between Gaussian noise CNE and HFNIHL%, and the average difference in HFNIHL% between the two curves decreased from 8.1 to 0.4%. Moreover, the decrease of average difference in HFNIHL% between the two logistic curves was evident in several subgroups, such as male workers, aged <30 and 30 to 50 years, furniture and woodworking industries and gunning and nailing job types with relatively high kurtosis values.

CONCLUSIONS

Kurtosis, as an indirect metric of noise temporal structure, was an important risk factor for occupational NIHL. Kurtosis-adjusted CNE metric could be more effective than CNE alone in assessing occupational hearing loss risk associated with complex noise.

Identification of Noise Levels for Skill Training Activities, Equipment, Machines and Power Tools at TVET Institutes in Malaysia

The use of various machines, equipment and power tools at TVET Institute causes the institute's environment to be exposed to noise hazards that are similar to the industry. However, not much data has been published regarding noise exposure at TVET institutes. This study was carried out to document the noise exposure of work activities training in public TVET institutes in Malaysia that implement skill training programs in metal fabrication, furniture manufacturing and automotive maintenance. The identification of excessive noise, task-based noise exposure monitoring and source measurement was conducted. The noise contribution from each work activity to the daily A-weighted noise exposure level and sound pressure level emitted by machines and equipment was documented. The findings of this study recorded 20 activities with task-based noise contribution to the daily A-weighted noise exposure level between 75.3 dB and 95 dB. Based on the findings, the training environment at the TVET institutes has a risk of operating with excessive noise. The documented data can be used in planning the implementation of suitable noise control measures in TVET institutes.

Developing a guideline for measuring workplace non-Gaussian noise exposure based on kurtosis adjustment of noise level in China

Objective

There is no unified standard for measuring workplace non-Gaussian noise (known as complex noise) exposure. This study aimed to develop a draft guideline for measuring workplace non-Gaussian complex noise exposure based on noise temporal structure adjustment.

Methods

Noise exposure level, e.g., the A-weighted sound pressure level normalized to a nominal 8-h working day (L_EX,8h), was adjusted using the temporal structure (expressed by kurtosis) of noise. Noise waveform analysis or the instrument's direct reading was used.

Results

The framework of the draft guideline included measurement metrics, the protocol using kurtosis to adjust L_EX,8h, technical requirements for measuring instruments, measurement steps, data analysis, and measurement recording.

Conclusion

The draft guideline could provide a basis for accurately measuring workers' exposure to non-Gaussian noise.

Epidemiological characteristics of hearing loss associated with noise temporal structure among manufacturing workers

Objective: This study aimed to investigate the epidemiological characteristics of occupational noise-induced hearing loss (NIHL) among manufacturing workers, and to provide evidence for diagnosing and preventing occupational hearing loss caused by complex noise, which is different from Gaussian noise in temporal structure.

Methods: One thousand and fifty manufacturing workers exposed to occupational noise were recruited in a cross-sectional survey. Exposure characteristics and epidemiological distribution of hearing loss and noise exposure metrics (noise energy and kurtosis) were investigated, and the relationship between noise exposure and hearing loss was analyzed. The effects of kurtosis on hearing threshold shift across different frequencies and on NIHL development with exposure duration and noise intensity were also investigated.

Results: Each type of work had specific noise exposure metrics. Noise intensity and kurtosis were independent parameters (r = −0.004, p = 0.885). The prevalence of NIHL and the hearing threshold level had a specific distribution in different types of work. Kurtosis deepened the hearing notch at high frequencies and accelerated the formation of early hearing loss. The effect of exposure duration and noise intensity on the prevalence of high-frequency NIHL (i.e., at 3, 4, 6, and 8 kHz) for manufacturing workers increased with kurtosis in workers with noise exposure duration of less than 10 years and with L_Aeq.8h between 80 and 90 dB(A). Male (OR = 1.557, 95%CI = 1.141–2.124), age (OR = 1.033, 95%CI = 1.014–1.052), exposure duration (OR = 1.072, 95%CI = 1.038–1.107), kurtosis (OR = 1.002, 95%CI = 1.001–1.003), and noise intensity (L_Aeq.8h; OR = 1.064, 95%CI = 1.044–1.084) were risk factors for high-frequency NIHL. The speech-frequency NIHL (i.e., at 0.5, 1, and 2 kHz) risk of workers exposed to manufacturing noise was related to age (OR = 1.071, 95%CI = 1.043–1.100). There were no statistically significant associations between speech-frequency NIHL and sex, noise exposure duration, kurtosis, and noise intensity (L_Aeq.8h).

Conclusion: The high-frequency NIHL prevalence among manufacturing workers is associated with sex, age, exposure duration, noise intensity, and temporal structure of noise, while the speech-frequency NIHL prevalence is associated with age. Kurtosis strengthens the association of noise exposure duration and noise intensity with high-frequency hearing loss. The influence of noise temporal structure should be considered in the diagnosis and early prevention of occupational hearing loss caused by complex noise.

Hearing loss and hypertension among noise-exposed workers: a pilot study based on baseline data

This study aimed to assess the prevalence of noise-induced hearing loss (NIHL) and hypertension, and the association between NIHL and hypertension using occupational physical examination data of 42,588 noise-exposed workers from local enterprises in Yangzhou between 2015 and 2017. The average binaural high-frequency threshold on average (BHFTA), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were 23.09 ± 11.32 dB, 126.85 ± 15.94 mm Hg and 79.94 ± 11.61 mm Hg. The prevalence of NIHL and hypertension were 24.38% and 25.40%. An increased risk of NIHL and hypertension was observed in the groups of males, aged >35 years, noise exposure time >5 years, noise exposure level >85 dB(A) and smoking. 32.25% NIHL workers had hypertension. NIHL workers were at higher risk of hypertension (adjusted OR = 1.07, 95%CI = 1.02-1.13). This study shows that the noise-exposed workers have high risk of developing NIHL and hypertension.

Analysis of Noise Exposure Level and Influencing Factors of Small and Micro-Scale Enterprises in Beijing, China

Understand the noise exposure level and influencing factors of small and micro-scale enterprises in Beijing, and support the formulation of noise prevention and control policies. Noise hazards in small- and micro-scale enterprises were monitored from May to December 2021 using a combination of questionnaire survey and on-site noise monitoring. The survey included questions on the basic characteristics of the enterprise, the situation of noise protection facilities, and protective equipment. We calculated the equivalent to the sound level of 8 h per day (L_{EX, 8h}) or the equivalent of the sound level of 40 h per week (L_EX,w) and the exceeding rate. Unconditional logistic regression was used to analyze the influencing factors. We recruited 194 enterprises in our study, including 145 small- and 49 micro-scale enterprises. Overall, 9.9% of the noise points exceeded the Chinese national standard, which was 85 dB(A). The detected noise of micro-enterprises significantly (P < .001) exceeded that of small enterprises. This is the first study to examine noise hazards of small and micro-scale enterprises in Beijing in recent years. Our results showed noise hazard prevention in Beijing is grim. It is suggested that the government should strengthen supervision, allocate responsibility to the employer, and guide them to establish and improve the management system for controlling noise hazards, to effectively reduce its impact on the health of workers.

Applying Kurtosis as an Indirect Metric of Noise Temporal Structure in the Assessment of Hearing Loss Associated With Occupational Complex Noise Exposure

OBJECTIVE

The association of occupational noise-induced hearing loss (NIHL) with noise energy was well documented, but the relationship between occupational noise and noise temporal structure is rarely reported. The objective of this study was to investigate the principal characteristics of the relationship between occupational NIHL and the temporal structure of noise.

METHODS

Audiometric and shift-long noise exposure data were collected from 3102 Chinese manufacturing workers from six typical industries through a cross-sectional survey. In data analysis, A-weighted 8-h equivalent SPL (LAeq.8h), peak SPL, and cumulative noise exposure (CNE) were used as noise energy indicators, while kurtosis (β) was used as the indicator of noise temporal structure. Two NIHL were defined: (1) high-frequency noise-induced hearing loss (HFNIHL) and (2) noise-induced permanent threshold shift at test frequencies of 3, 4, and 6 kHz (noise-induced permanent threshold shift [NIPTS346]). The noise characteristics of different types of work and the relationship between these characteristics and the prevalence of NIHL were analyzed.

RESULTS

The noise waveform shape, with a specific noise kurtosis, was unique to each type of work. Approximately 27.92% of manufacturing workers suffered from HFNIHL, with a mean NIPTS346 of 24.16 ± 14.13 dB HL. The Spearman correlation analysis showed that the kurtosis value was significantly correlated with the difference of peak SPL minus its LAeq.8h across different types of work (p < 0.01). For a kurtosis-adjusted CNE, the linear regression equation between HFNIHL% and CNE for complex noise almost overlapped with Gaussian noise. Binary logistic regression analysis showed that LAeq.8h, kurtosis, and exposure duration were the key factors influencing HFNIHL% (p < 0.01). The notching extent in NIPTS at 4 kHz became deeper with the increase in LAeq.8h and kurtosis. HFNIHL% increased most rapidly during the first 10 years of exposure. HFNIHL% with β ≥ 10 was significantly higher than that with β < 10 (p < 0.05), and it increased with increasing kurtosis across different CNE or LAeq.8h levels. When LAeq.8h was 80 to 85 dB(A), the HFNIHL% at β ≥ 100 was significantly higher than that at 10 ≤ β < 100 or β < 10 (p < 0.05 and p < 0.01, respectively).

CONCLUSIONS

In the evaluation of hearing loss caused by complex noise, not only noise energy but also the temporal structure of noise must be considered. Kurtosis of noise is an indirect metric that is sensitive to the presence of impulsive components in complex noise exposure, and thus, it could be useful for quantifying the risk for NIHL. It is necessary to re-evaluate the safety of permissible exposure limit of 85 dB(A) as noise with a high kurtosis value can aggravate or accelerate early NIHL.

Surveillance of Noise Exposure Level in the Manufacturing Industry - China, 2020

Introduction

Occupational noise exposure is a widespread issue in the manufacturing industry in China. Since 2019, the National Surveillance System for Occupational Hazards in the workplace was established to understand different occupational hazards, especially occupational noise, in workplaces in China.

Methods

Both environmental and individual noise exposure levels were measured for 19,378 enterprises according to the Work Plan for Surveillance of Occupational Hazards in the Workplace (2020) issued by National Health Commission of the People's Republic of China. Median and interquartile range (IQR) were calculated to describe the distribution of the noise exposure level by industry classification, enterprise-scale, and ownership type of the enterprise.

Results

Overall, 25.14% of the individual noise exposure samples exceeded the Chinese national standard among the selected enterprises. The overall median of environmental noise exposure level was 82.8 dB(A) in selected enterprises, while the median of individual noise exposure level was 81.3 dB(A). The individual noise exposure level in the manufacture of metal products, manufacture of motor vehicles, mini-sized enterprises, collective enterprises and private enterprises was relatively high.

Conclusion

Occupational noise is still one of the occupational hazards that cannot be ignored in the manufacturing industry, especially in mini-sized and private enterprises. The risk of noise exposure in the target industry is still high and will pose a threat to the health of workers.

[Self-reported hearing impairment and occupational exposure to hazardous noise and ototoxic agents: a population-based study]

This study's objective was to estimate the association between self-reported hearing impairment and occupational exposure to hazardous noise and ototoxic agents in Brazilian workers. This was a cross-sectional study with data from the Brazilian National Health Survey (PNS-2013). The dependent variable was self-reported hearing impairment, and three principal exposures were analyzed: noise, industrial dust, and chemical substances. Logistic regression was performed, estimating crude and adjusted odds ratios (OR) with 95% confidence intervals (95%CI). The principal exposure variables were adjusted for each other and by covariables sex, age, workplace, time on the job, and hypertension. 36,442 workers participated in the study. Higher prevalence of hearing impairment was seen in workers exposed to industrial dust (9.9%) (p < 0.001). The older the worker and the longer the time on the job, the higher the prevalence of hearing impairment (p < 0.001). In the adjusted analysis, workers exposed to noise showed 1.65 higher odds of reporting difficulty hearing, when compared to unexposed individuals (p < 0.001). The same was true for workers exposed to industrial dust (OR = 1.36) (p = 0.012). No association was observed between the outcome and exposure to chemical substances (p = 0.120). There was an association between hearing impairment and occupational exposure to noise and industrial dust in Brazilian workers. This emphasizes the importance of strengthening public policies for hearing health and the development of measures for prevention and auditory monitoring in the workplace.

Hearing Loss and Associated Factors Among Noise-Exposed Workers in Palm Oil Mills

Introduction

Almost 90% of the reported occupational diseases in Sabah, Malaysian Borneo were due to hearing loss. The manufacturing industry was the main contributor to this problem. This study aims to identify the prevalence and associated factors for hearing loss among workers in the palm oil manufacturing industry in Sabah.

Material and Methods

A cross-sectional study was done among 312 respondents from five palm oil mills in Sabah from January to April 2019. Audiometric tests, validated questionnaires and sound level meters were used. Chi-square test and independent t-test were conducted to determine the associated factors for hearing loss.

Results

75% (n = 234) of the respondents were diagnosed with hearing loss. Most of them were male (96.2%) with a mean age of 44.4 (SD 9.8) years, mean duration of employment of 16.2 (SD 9.7) years and mean noise exposure of 96.1 (SD 4.8) dB(A). The significant factors associated with hearing loss were older age (p = 0.001), married (p = 0.001), blue-collar jobs (p = 0.003), smoking (p = 0.001), works with noisy machinery (p = 0.005), lower level of noise exposed (p = 0.015), longer duration of employment (p = 0.001), and longer overtime hours per week (p = 0.001).

Conclusion

The prevalence of hearing loss among workers in the noise-exposed palm oil industries was high. Annual audiometry testing and job rotation from noise-exposed workstations were recommended. A smoking cessation program may help but reduction of noise from the source by engineering control is still the best method.

Verifying earplug attenuation and evaluating the effectiveness of one-on-one training along with earplug fit testing at nine facilities in China

BACKGROUND

The purpose of this study was twofold: (1) to measure the personal attenuation ratings (PARs) in Chinese workers wearing hearing protection devices (HPDs), to evaluate the effectiveness of the single number rating (SNR), the noise reduction rating (NRR), and the associated derated values of earplugs; and (2) to evaluate the effectiveness of one-on-one training along with earplug fit testing on PAR improvement.

METHODS

Noise exposure measurements, one-on-one training, and fit tests to measure earplug attenuation were conducted at nine manufacturing facilities located in eastern China from 2016 to 2017. 503 workers participated in the study. Ninety-three percent were male. 199 workers were provided one-on-one training.

RESULTS

Before training, 14% and 15% of the workers achieved the attenuation predicted by the manufacturer's SNR and NRR, 56% and 65% exceeded the derated SNR and NRR, respectively. Following one-on-one training, mean PAR improved significantly by 15 dB (p < 0.01); 26% of the workers achieved SNR and NRR, 79% and 91% met the associated derated values, respectively.

CONCLUSIONS

Labeled noise attenuation ratings and their derated values overestimated the actual level of attenuation among workers wearing HPDs. One-on-one training along with earplug fit testing contributed to improved PARs.

Evaluating the Effectiveness of Earplugs in Preventing Noise-Induced Hearing Loss in an Auto Parts Factory in China

A survey was administered to 385 noise-exposed workers from an auto parts factory and 1268 non-noise-exposed health department employees in China. Individual 8 h A-weighted equivalent sound levels (LAeq,8h), earplug personal attenuation ratings (PARs), and pure-tone audiometric tests were performed. The average LAeq,8h of noise-exposed workers was 87 dB (A) with a mean PAR of 7 dB. The prevalence of high-frequency hearing loss was 65% for noise-exposed workers and 33% for the non-noise-exposed employees. The use of earplugs had no observable effect on the prevalence of high-frequency hearing loss of the study participants (OR 0.964, 95% CI 0.925-1.005, p = 0.085). No significant relationship between the effectiveness offered by earplug use and high-frequency hearing thresholds at 3, 4, and 6 kHz was found (t = -1.54, p = 0.125). The mandatory requirement of earplug use without individualized training on how to wear HPDs correctly had no detectable effect on the prevention of hearing loss at the auto parts factory. The hearing conservation program at the surveyed factory was not effective. Periodic hearing tests, earplug fit testing, expanding the offer of different types of hearing protection, and employee education about the importance of protecting their hearing were recommended to the occupational health and safety program.

Genetic association study between TAB2 polymorphisms and noise-induced-hearing-loss in a Han Chinese population

Noise-induced-hearing-loss(NIHL) is a common occupational disease caused by various environmental and biological factors. To investigate the association between TAB2 and the susceptibility of NIHL of people exposed to occupational environments, a genetic association study was performed on selected companies with 588 cases and 537 healthy control subjects. Five selected single nucleotide polymorphisms (SNPs) in TAB2,incoluding rs2744434, rs521845, rs652921, rs7896, rs9485372, were genotyped after a collection of DNA samples. Evident differences in participants between the case group and the control group reveals the result that people with the TAB2 has a high probability of getting NIHL. The results show that rs521845 is deeply associated with the risk of NIHL and is available for the diagnosis in the future.

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.

Occupational noise-induced hearing loss in China: a systematic review and meta-analysis

OBJECTIVE

Most of the Chinese occupational population are becoming at risk of noise-induced hearing loss (NIHL). However, there is a limited number of literature reviews on occupational NIHL in China. This study aimed to analyse the prevalence and characteristics of occupational NIHL in the Chinese population using data from relevant studies.

DESIGN

Systematic review and meta-analysis.

METHODS

From December 2019 to February 2020, we searched the literature through databases, including Web of Science, PubMed, MEDLINE, Scopus, the China National Knowledge Internet, Chinese Sci-Tech Journal Database (weip.com), WanFang Database and China United Library Database, for studies on NIHL in China published in 1993-2019 and analysed the correlation between NIHL and occupational exposure to noise, including exposure to complex noise and coexposure to noise and chemicals.

RESULTS

A total of 71 865 workers aged 33.5±8.7 years were occupationally exposed to 98.6±7.2 dB(A) (A-weighted decibels) noise for a duration of 9.9±8.4 years in the transportation, mining and typical manufacturing industries. The prevalence of occupational NIHL in China was 21.3%, of which 30.2% was related to high-frequency NIHL (HFNIHL), 9.0% to speech-frequency NIHL and 5.8% to noise-induced deafness. Among manufacturing workers, complex noise contributed to greater HFNIHL than Gaussian noise (overall weighted OR (OR)=1.95). Coexposure to noise and chemicals such as organic solvents, welding fumes, carbon monoxide and hydrogen sulfide led to greater HFNIHL than noise exposure alone (overall weighted OR=2.36). Male workers were more likely to experience HFNIHL than female workers (overall weighted OR=2.26). Age, noise level and exposure duration were also risk factors for HFNIHL (overall weighted OR=1.35, 5.63 and 1.75, respectively).

CONCLUSIONS

The high prevalence of occupational NIHL in China was related to the wide distribution of noise in different industries as well as high-level and long-term noise exposure. The prevalence was further aggravated by exposure to complex noise or coexposure to noise and specific chemicals. Additional efforts are needed to reduce occupational noise exposure in China.

Prevalence and determinants of noise-induced hearing loss among workers in the automotive industry in China: A pilot study

Objective

Data on noise‐induced hearing loss (NIHL) in the automotive industry are rare. This pilot study aimed to investigate the prevalence and determinants of NIHL among workers in the automotive industry in China.

Methods

A cross‐sectional survey was conducted with 6557 participants from the automotive industry. The questionnaire survey was administered, and individual noise exposure level (L_Aeq.8h) and hearing loss level were measured.

Results

Of participants, 96.43% were male; the median age was 27.0 years and 28.82% had NIHL defined as adjusted high‐frequency noise‐induced hearing loss (AHFNIHL). Concerning individual noise levels (L_Aeq.8h), 62.53% exceeded 85 dB(A), which were mainly concentrated in various jobs, including metal cutting, surface treatment, stamping, welding, grinding, assembly, plastic molding, and forging. Each typical noise source generated its own unique temporal waveform shape with the type of non‐Gaussian noise. Of workers, 53.15% regularly used hearing protector devices (HPD), and the proportion of regular HPD use increased with L_Aeq.8h. The trend test showed that the prevalence of AHFNIHL in male workers significantly increased with an increase in L_Aeq.8h at <94 dB(A) and cumulative noise exposure (CNE) in each age group (P < 0.05 or P < 0.01). A logistic regression analysis showed that CNE and HPD usage frequency were important factors contributing to AHFNIHL.

Conclusions

CNE and HPD usage frequency were the determinants for NIHL. Much more human surveys are needed to understand the prevalence and determinants of NIHL in the automotive industry in China.