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

Abstract

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.

Keywords

Hearing disorder risk factors noise work vibration smoking

1 Introduction

Noise typically refers to sounds that are considered unpleasant or unwanted which exerts detrimental effects on a person’s physical or mental health [1, 2]. Exposure to persistent and intense noise has risen concurrently with industrial development and technological progress [3]. Occupational noise-induced hearing loss (ONIHL) is the second most prevailing form of sensorineural hearing loss after age-related hearing loss and also one of the most prevalent work-related diseases in the world [4, 5]. The World Health Organization (WHO) has reported that 16% of people with disabling hearing loss has resulted from work-related noise exposure [6]. A study in 2015 demonstrated that 95.90% of occupational ear, nose and throat diseases in china were attributed to noise-induced hearing loss (NIHL) [7]. Additionally, the number of people with hearing loss is projected to reach 630 million by 2030 and more than 900 million by 2050 [6]. The high costs of industrial noise control, lack of proper management in occupational health and insufficient personnel nationwide are challenges of surveillance of occupational diseases and hazards [8, 9].

ONIHL -as an irreversible impairment- develops slowly, beginning with higher frequencies and gradually spreading to the middle and lower frequencies [5, 10]. Occupational hearing loss is usually bilateral, but occasionally unilateral [11]. Previous studies have focused on the prevalence and ONIHL- related factors [12 –14] and its related diseases in different countries [15 –17]. Hearing loss in workers can result from occupational and environmental risk factors and individual susceptibility. Environmental risk factors include noise, vibration, organic solvents and heavy metals. In addition, occupational factors consist of intensity, frequency and duration of noise exposure. Individual susceptibility consists of factors such as gender, race, age, initial hearing, smoking and health conditions [18].

There have been limited studies on the risk model for ONIHL, for example Pentti Kuronen et al. developed an NIHL risk model for military pilots [19]. Sun et al. also made a risk model for high frequency hearing loss in noise-exposed workers with small number of risk factors in different industries [9]. Currently, there are increasing concerns about health consequences of exposure to work-related noise, particularly hearing loss. It is known that available treatments for this type of hearing loss (hearing aids) do not reverse the disease [5]. Therefore, early prediction and diagnosis of ONIHL in various occupational groups could provide evidence for completely preventing this type of hearing loss. Approaches to assessing occupational noise exposure include questionnaire-based [20] and artificial intelligence methods [21]. Considering the above information, the purpose of this study was to provision of a risk model to determine the predictors of occupational hearing loss and estimate the risk of hearing loss hearing loss in workers exposed to industrial noise.

2 Methods

2.1 Study population

This study was carried out on subjects exposed to occupational noise in a steel factory in Arak, Iran and took place between 2022 and 2023. The participants in this study included 605 workers exposed to industrial sounds. The inclusion criteria were: subjects completing a questionnaire and a health examination voluntarily were aged between 18 and 60 years with at least one year of work experience in industrial environments. Exclusion criteria were: a history of ear trauma or middle/outer ear disease and a history of exposure to toxic drugs and chemicals.

2.2 Data acquiring

After obtaining written informed consent, a trained healthcare technician and a qualified audiologist collected the basic information and audiometric results from workers exposed to noise. The data was subsequently entered into the software for further analysis. The basic data were acquired using research-made questionnaire comprising personal information including gender, date of birth, history of smoking, previous exposure to noise and other occupational hazards (vibration, heat stress, noise level, type of occupation), work experience and medical history. The equivalent sound level (Leq) was measured by using a CASELLA CEL 450 Sound Level Meter (SLM) and a CASELLA CEL 110/2 calibration device.

Pure Tone Audiometry test (PTA) was used for auditory evaluation. According to the standards, the standard limit of sound in work environments is equal to 85 dB. The audiological examination consisted of otoscopy in both ears. Then, hearing thresholds were obtained at 8 different frequencies (0.25,0.5, 1, 2, 3, 4, 6 and 8 kHz) using a clinical audiometer (Madsen Orbiter 922). PTA consisted of air conduction and bone conduction tests for each worker. Hearing thresholds≥25 dB at one or more frequencies above 1 KHz for either ear was considered ONIHL for either ear [22].

Table 1
Demographic and occupational characteristics of noise-exposed workers

variables NH group(N = 338) N (%) HL group(N = 267) N (%) p-value

Leq_8 h (dB A) ≤85 182(53.8%) 130(48.7%) P < 0.001*

>85 156(46.2%) 137(51.3%)

Heat stress history yes 217(64.2%) 177(66.3%) 0.592

no 121(35.8%) 90(33.7%

Previous noise exposure yes 125(37%) 157(58.8%) P < 0.001*

no 213(63%) 110(41.2%)

Vibration exposure yes 84(24.9%) 96(36%) P < 0.001*

no 254(75.1%) 171(64%)

Smoking yes 72(21.3%) 112(41.9%) P < 0.001*

no 266(78.7%) 155(58.1%)

Comorbidities history yes 72(21.3%) 77(28.8%) 0.033*

no 266(78.7%) 190(71.2%)

Age groups <45 years old 300(88%) 182(68.2%) P < 0.001*

45–60 years old 38(11.2%) 85(31.8%)

Type of occupation Office workers 50(14.8%) 13(4.9%) P < 0.001*

Industry sectors workers 288(85.2%) 254(95.1%)

variables		NH group(N = 338) N (%)	HL group(N = 267) N (%)	p-value
Leq_8 h (dB A)	≤85	182(53.8%)	130(48.7%)	P < 0.001*
	>85	156(46.2%)	137(51.3%)
Heat stress history	yes	217(64.2%)	177(66.3%)	0.592
	no	121(35.8%)	90(33.7%
Previous noise exposure	yes	125(37%)	157(58.8%)	P < 0.001*
	no	213(63%)	110(41.2%)
Vibration exposure	yes	84(24.9%)	96(36%)	P < 0.001*
	no	254(75.1%)	171(64%)
Smoking	yes	72(21.3%)	112(41.9%)	P < 0.001*
	no	266(78.7%)	155(58.1%)
Comorbidities history	yes	72(21.3%)	77(28.8%)	0.033*
	no	266(78.7%)	190(71.2%)
Age groups	<45 years old	300(88%)	182(68.2%)	P < 0.001*
	45–60 years old	38(11.2%)	85(31.8%)
Type of occupation	Office workers	50(14.8%)	13(4.9%)	P < 0.001*
Industry sectors workers	288(85.2%)	254(95.1%)

NH: Normal Hearing; HL: Hearing loss; Leq: equivalent acoustic level. *p < 0.05.

2.3 Statistical methods

The characteristics were described by frequency and percentage. Categorical variables were expressed as frequency (%) and compared between all subjects using chi-square tests. To estimate the association between all available risk factors and ONIHL, logistic regression analyses were performed by examining factors such as age, work experience, previous exposure to noise or vibration, Leq, smoking and disease history and occupation type. Occupational hearing loss (HL) was defined as a condition where a hearing threshold≥25 dB at any frequency above 1KHz and Normal Hearing (NH) indicated hearing threshold < 25 dB in each ear. Risk is expressed as odds ratio (OR) and 95% confidence interval (CI). A two-tailed P-value < 0.05 was considered to be statistically significant. All statistical analyses were performed using STATA 12.0 software.

2.4 Ethics statement

The study was approved by the local ethics committee (protocol number IR.ARAKMU.REC.1401.098). All study participants provided informed consent.

3 Results

The study population included 605 workers with a mean age of 38.50±6.74 (36.41±5.68 in NH group vs.41.15±7.05 in HL group). Hearing loss was 44.13% among the participants. Workers in HL group had longer work experience (8.08±4.90 years) than in NH group (6.37±3.82). However, the official daily working schedule was 8 hours per day. Leq at 8 hours was higher in HL group than NH group (83.37±5.78 vs. 81.67±8.24 p < 0.05). The demographic and occupational characteristics of the participants are shown in Table 1.

Workers in industry sectors had higher occupational NHIL than office workers (p < 0.05). Office workers consisted of workers in the health, safety and environment-related positions. Hearing loss increased significantly with age and work experience (p < 0.05). In addition, there was an association between Leq for 8 hours, history of previous noise exposure, vibration exposure, smoking and disease history(p < 0.05). Exceeding the regulations, almost half of the workers were exposed to sound levels greater than 85 dB in 8 hours.

3.1 The risk model for HL in noise-exposed workers

Previous work experience, noise exposure, vibration, smoking and age were the variables included in the final risk model. Further subjecting of the variables to univariate analysis (logistic regression) with NIHL and each of the significant parameters as the outcome variable is shown in Table 2. All variables in the final model were associated with an increased likelihood of HL.

Table 2
Logistic regression analysis of hazardous factors affecting hearing loss

Variables OR p 95% Confidence Interval

Work experience Years 1.06 0.006* 1.016–1.107

Previous noise exposure No 1

Yes 1.60 0.011* 1.112–2.312

Vibration exposure No 1

Yes 1.68 0.007* 1.150–2.475

Smoking No 1

Yes 1.80 0.003* 1.224–2.655

Age Years 1

2.93 0.000* 1.848–4.656

Type of occupation Office 1

Industry sectors workers 2.12 0.035* 1.055–4.285

Variables	OR	p	95% Confidence Interval
Work experience	Years	1.06	0.006*	1.016–1.107
Previous noise exposure	No	1
	Yes	1.60	0.011*	1.112–2.312
Vibration exposure	No	1
	Yes	1.68	0.007*	1.150–2.475
Smoking	No	1
	Yes	1.80	0.003*	1.224–2.655
Age	Years	1
		2.93	0.000*	1.848–4.656
Type of occupation	Office	1
	Industry sectors workers	2.12	0.035*	1.055–4.285

OR odds ratio, SE standard error; P-values were analyzed by logistic regression, with significance at < 0.05.

The odds of work experience were 1.06 (95% CI, 1.016–1.107) times higher for workers with hearing loss than NH group. Regarding age, ORs were 2.93 (% 95 CI, 1.848–4.656) for subjects < 45 years in HL group compared with NH group. There were statistically significant ORs;1.60 (95% CI, 1.112–2.312) for workers with previous history of noise exposure, 1.68 (95% CI, 1.150–2.475) for vibration exposure and 1.80 (95% CI, 1.224–2.655) for smokers. Related to type of occupation, OR for workers in industry sectors was 2.126 (95% CI, 1.055–4.285) compared with office workers.

4 Discussion

It has been highlighted that long-term exposure to noise in workers results in ONIHL [23]. According to the results of present study, ONIHL is multi-factorial. There were correlations with the development of ONIHL by some sociodemographic and individual susceptibility variables such as age, smoking and occupational risk factors including work experience, previous noise exposure, vibration exposure and type of occupation.

In this research, 44.13% of workers experienced hearing loss. It was consistent with Solanki et al. (44%) [24], and lower than that of Abraham et al.(58.8%) [25] and Singh et al.(90%) in a steel factory [26]. However, it was higher than the values that reported by Chen et al. (28.82%) [27], Ranga (39%) [28] and Rao et al. (30%) [29]. Comparing ONIHL was challenging due to different criteria of NIHL among workers of various countries, the nature of industry or occupations, and population characteristics. The higher values of hearing loss can be explained by the difference in demographic factors, methodology, lack of proper hearing protection and measurement techniques.

In this study, nearly half of the workers were exposed to average noise levels above 85 dB A over an 8-hour working day. So, hearing conservation program consisting of exposure monitoring, audiometry, hearing protection, employee training, and record keeping is necessary for this group based on OSHA.

The predominant age group was 18 to 45 years in both groups. The occurrence of ONIHL significantly increased with age. It was similar to the findings in Abraham’s study [25]. Noise and age are known as separate causes of hearing loss in workers [25]. The ONIHL tended to rise with noise exposure duration. The pattern was similar to studies conducted in Tanzania [25] and the United States [30]. Long-term noise exposure damages cochlea both mechanically and metabolically, especially hair cells through hypoxia caused by noise-induced capillary vasoconstriction [31].

Smokers had significantly increased odds of developing sensorineural hearing loss. Individual susceptibility factors such as smoking are postulated to aggregate NIHL [5]. It could be explained by the direct ototoxic effects of smoking on the outer hair cells in cochlea, a decrease in the amount of oxygen used by cells resulting from increasing the carboxyhemoglobin in the blood, atherosclerotic change in the end part of cochlear artery in the inner part of higher frequency. Thus, the increase in hearing thresholds is greater at higher frequencies and smoking cessation training for workers appears to be required to prevent the acceleration of NIHL.

It is known that vibration exposure itself or along with noise could result in NIHL and can have notable impacts on physiological responses of the body[32, 33]. Although aspects of vibration impact on hearing are still unknown, its effect on peripheral blood vessels may contribute to the exacerbation of NIHL [33].

The risk model indicated that age (OR = 2.93) and type of occupation (OR = 2.12) had a strong negative effect on ONIHL. Based on the risk model, older workers in industrial sectors with a history of smoking, previous noise or vibration exposure and more work experience are more likely to suffer from ONIHL. This is consistent with previous studies indicating that several factors including loud sounds [31], duration of exposure [34], smoking [23], prior noise exposure [31, 35], vibration [33] and age [23] could influence the development of hearing impairment.

The results obtained in this study showed that the presented model for risk assessment for ONIHL can be effective in risk assessment for ONIHL in noise-exposed workers. More attention should be paid to the relationship between hearing loss and other occupational hazards as well as noise.

The limitations of the present study were its single-center design and the type industry. For this reason, in order to determine the more accurate level of hearing loss as well as more accurate risk assessment, more quantitative studies are needed.

5 Conclusions

This research identified occupational and individual susceptibility risk factors such as isolated exposure to vibration, previous noise exposure, work experience, occupation type, age and smoking in addition to exposure to noise. So, older workers in industry sectors with history of smoking, previous noise exposure, vibration exposure and greater work experience are more likely to experience ONIHL. We believe this risk model can be applied to improve relevant research on ONIHL and management strategies to prevent the condition. Further research is required to investigate the relationship between co-exposure to noise, vibration and other relevant risk factors.

Ethics statement

The study was approved by the local ethics committee (protocol number IR.ARAKMU.REC.1401.098). All study participants provided informed consent.

Funding

This study was supported by Arak University of Medical Sciences. (grant no. 4135).

Conflict of interest

The authors have no conflicts of interest to declare.

Footnotes

Acknowledgments

We would like to express our gratitude to the Research Deputy of Arak University of Medical Sciences for financial support and resources for this research.

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