Investigating the effect of noise exposure on mental disorders and the work ability index among industrial workers

Abstract

Noise as one of the most common hazardous physical agents in the work environment causes physical and psychological problems in occupied workers. This study aims to investigate the relationship of demographic variables and noise exposure with mental disorder and work ability index in automotive industry workers. This study aims to investigate the effect of noise exposure on mental disorder and work ability index among industry workers. In this descriptive-analytic study, 325 individuals working in auto parts supplier industry who were exposed to different level of noises were investigated. Personnel’s daily exposure to noise for each group was measured based on ISO-9612 standards using calibrated sound level meter model SVANTEK-971. Workers’ mental disorder and work ability index were determined using Kessler Psychological Distress Scale questionnaire and shortened form of work ability index, respectively. Then, collected data were analyzed using SPSS-22. The mean and standard deviation of mental disorder and work ability index for all employees was 23.46 ± 3.45 and 37.43 ± 6.14, respectively. The results of one-way ANOVA and linear regression analysis showed that there is a significant association between noise exposure with mental disorder and work ability index in term of age groups, working groups, and work experience (p-value < .05). Regardless the effect of other variables, it can be stated that for each dB increase in noise exposure cause mental disorder increase by 0.32 and work ability index decrease by 0.157. And among the demographic variables, age was the most influential parameter on mental health and work ability index. According to the results of this study, noise exposure could lead to increased psychological distress and decreased work ability index in workers. The ability to work directly and indirectly through mental disorders can be affected by exposure to industrial noise. Considering severe exposure to noise in some units and the negative impact of noise exposure on mental health and work ability index, it is necessary to improve of controlling and protective measures against noise.

Keywords

Noise exposure;mental health;work ability index

Introduction

Exposure to high levels of noise in workplaces is one of the most common causes of physical and mental illnesses in the industrial community. It affects millions of workers worldwide annually.¹ In addition to hearing loss, exposure to noise may cause many psychological and physical problems, such as lack of concentration, discomfort, fatigue, loss of professional ability, sleep disturbance, nausea and stress, tinnitus, and low efficiency in industrial workers.^2–5 Noise can interfere with the process of verbal communication and conversation, increasing the feeling of personal loneliness.^6,7 Exposure to noise in mental and physical tasks with different cognitive and physical workloads causes fatigue in workers. It also adversely affects their mental states and moods and disrupts one’s adaptation to the workplace and even to the family and community, resulting in productivity deficits.^8–11 Numerous clinical observations and laboratory experiments have revealed that noise decreases performance and efficiency.^3,12–14 In recent years, the Work Ability Index (WAI) has been introduced as an important tool in occupational health research and services to prevent early retirement and work-related disability. Since workers differ in occupational factors, personal characteristics, and lifestyles, this index can be affected in various ways by illness and other occupational factors.^15,16 Ability to work is defined as the degree to which employees are physically or mentally able to adapt to their work needs based on their level of health.¹⁷ Ability to work reflects the interaction between individual characteristics, working conditions, functional capabilities of employees, as well as their health status.¹⁸ Various individual, occupational, lifestyle, and psychosocial factors can influence a person’s ability to do different jobs.¹⁹ In a study aimed at identifying the effect of occupational factors on work ability, Sell et al. indicated that exposure to high level noise is one of the risk factors for decreasing work ability.²⁰

Mental distress is a general term used to describe unpleasant emotions that affect an individual’s level of performance.²¹ Mental disorders are associated with flexible and creative thinking, social behavior, and good physical health so that deficits in each of the above factors lead to varying degrees of mental disorders.²²

The WHO reported that chronic exposure to noise can cause irritation, mental distress, and sleep disturbances. These three factors can affect health and quality of life associated with health.^23,24 A study in Austrian school children aged 11–8 years indicated that there was a dose–response relationship between acoustic exposure and self-reported mental disorders.²⁵ Leventhall stated that prolonged exposure to low-frequency noise may cause physiological psychological damage.²⁶

Due to the nature of their workplaces, the automotive and automobile parts manufacturing industries are those in which exposure to noise from equipment such as cutting machines, pressing, welding, and milling machines is a global problem. The employees in those industries are at risk of exposures to high levels of noise from these machines and apparatuses. Regarding the special status of the automotive industry and its branches in each country and the high volume of human resources employed in them, paying attention to the employees’ working ability and mental health is highly critical. Identifying the factors affecting employees’ mental health from different perspectives in these industries is vital to maintaining the employees’ ability to work and productivity.^27–29 Therefore, given the aforementioned issues and the special significance of exposure to noise in these industries as a cause of mental disorders, as well as the relationship between mental disorders and the WAI, it can be expected that exposure to noise indirectly affect mental health and lead to loss of ability to work. On the other hand, some studies have shown that ability to work is partly influenced by physical factors in workplaces, such as exposure to noise. As aforementioned, various studies have indicated that noise can reduce one’s performance and efficacy, but no study was conducted to examine the relationship between the WAI in the face of different industrial noise levels directly. The present aimed to investigate the effect of noise exposure with mental disorders and the WAI of different occupational groups in an automobile parts manufacturing industry.

Methodology

Participants and sample size

This cross-sectional descriptive-analytical study was done in an automobile parts manufacturing industry, one of the largest manufacturing companies in the field of supplying and manufacturing automobile parts and assemblies in the year 2018. The present research inclusion criterion consisted of at least 2 years of work experience, while individuals with any record of taking antidepressant medications and those with hearing and non-occupational injuries were excluded from the study.

The research statistical population consisted of all employees of an industrial group (650 individuals). In this study, the Cochran formula (Formula 1) was employed to determine the sample size.

n = \frac{\frac{Z^{2} p q}{d^{2}}}{1 + \frac{1}{N} (\frac{Z^{2} p q}{d^{2}} - 1)} = 242

where

n: sample size

N: size of population

d: permissible error (usually assumed to be 0.05)

z: the value of the normal variable with confidence level α-1

p: the ratio of having the desired attribute

q: The ratio of not having the desired attribute

Considering the population size (650 individuals), the sample size was determined using the Cochran formula as 242 participants. To increase the accuracy of the study, more employees were asked to participate in the study voluntarily. Finally, this study was conducted on 325 employees of this industry group and in six production and office units facing different levels of noise.

Noise exposure measurement

The noise exposure was measured according to equivalent level in each occupational group according to ISO-9612 standard and using SVANTEK-971 Sound analyzer. All measurements were performed in A weighted network A and in the SLOW mode. Also before each measurement, the apparatus was calibrated using the SV33 calibrator. To 8-h equivalent continuous sound pressure level (L_Ep,d)¹, measurements equivalent level of 8 h were made at all traffic locations and stops during the 8-h daily working.

Questionnaires

In the second phase of the study, after determining the employees’ exposure to levels of noise, demographic information questionnaires, the Kessler Psychological Distress Scale (K-10), and the WAI short form (“WAI-r”) were completed in person. The Kessler Psychological Distress Scale for the Identification of Mental Disorders in the General Population was developed by Kessler et al. (2002)³⁰ in two 10-item (K-10) and 6-item (K-6) forms. The questions in both forms range from a five-point Likert scale from “never” to “always” and are scored on a scale of 1–5. Therefore, the maximum score in K-10 is 50, which is classified as follows:

Scores below 20 are probably good and healthy.

Scores in the range 20–24 probably have a mild mental disorders.

Scores in the range 25–29 probably have a moderate mental disorders.

Scores in the range 30–50 probably have a severe mental disorders.

The K-10 form contains 10 questions that do not target a specific psychological disorder, but generally identify the level of anxiety and depressive symptoms that a person has experienced over the past few weeks. Therefore, the Kessler Psychological Distress Scale (K-10) was used in this study. The Persian version of this questionnaire was reviewed by Yaghoubi et al. its validity and reliability were confirmed (Cronbach’s alpha coefficient as 0.93 and Spearman-Brown split-half reliability coefficient as 0.91).^2,31

The Work Ability Index short form (“WAI-r”) consists of seven items, each of which is assessed using one or more questions. This index is calculated with the sum of the points earned for each item. The best possible estimate of the WAI is 49 and the worst is 7. The scoring scale of the questionnaire is such that finally the workers’ work ability is classified into four groups based on the obtained scores:

1- Poor work ability ranges from 7 to 27

2- Moderate work ability ranges from 28 to 36

3- Good work ability ranges from 37 to 43

4- Excellent work ability ranges from 44 to 49

The validity and reliability of the Persian version of the WAI-r were estimated by Mazloumi et al. (2014), for which an acceptable level of validity and reliability was obtained, and using this questionnaire to evaluate the workers’ work ability was proposed in different workplaces, especially industrial ones.¹⁶

Statistical analysis

Finally, the collected data was analyzed using SPSS-22 software. One-way ANOVA was employed to compare the mean of mental disorders and the ability to work among exposure to different levels of noise, age groups, and work experience. Also, the independent-samples t-test was used to compare the level of mental disorder and the ability to work between different groups. The effects of the employees’ noise exposure, age, and work experience on their levels of mental disorders and the WAI were tested separately using simple linear regression analysis. Multiple regression analysis was used to investigate the concurrent effect of these variables on the dependent variable, namely mental disorders and the WAI.

Results

Of the 650 employees in this industry group, 325 volunteered to participate in the study, all of whom were male and full-time workers. 44 (13.5%) of them were in the administrative department, 57 (17.5%) in the pressing unit, 49 (15%) in the cutting unit, 42 (13%) in the mergers and acquisitions unit, 36 (11%) in screw making unit, 45 (14%) in the molding unit (sheet molding and machining), and 52 (16%) in the die casting unit. The employees’ average age and work experience were 36.46 ± 7.18 and 13.26 ± 5.15 years, respectively. 118 employees (36.2%) held undergraduate education and 207 (63.8%) held high school diploma or higher education levels. The results of the acoustics in Table 1 are presented by occupational groups.

Table 1.

Description of the occupational groups in terms of L_Ep,d.

Occupational groups	No. (%)	dBA ± SD.	Comparison with the standard level
Administrative	44 (13.5)	54.3 ± 1.3	In the permitted limit
Merger and acquisitions	42 (13)	78.8 ± 1.6	In the permitted limit
Die casting	52 (16)	82.5 ± 1.5	In the care limit
Molding	45 (14)	84 ± 3.2	In the care limit
Pressing	57 (17.5)	90.5 ± 8.2	Over limit
Cutting	49 (15)	89.3 ± 7.7	Over limit
Screw making	36 (11)	88.5 ± 4.5	Over limit

The results of Table 1 illustrate that those working in the pressing unit with the mean and SD and 90.5 ± 8.2 had the highest noise exposure. Also, the mean and SD of noise exposure of those working in the cutting, screw making units was 89.3 ± 7.7 and 88.5 ± 4.5, respectively. The employees working in the administrative unit had the lowest mean and SD of noise exposure as 54.3 ± 1.3.

Mean and SD of mental disorders for all employees were 23.46 ± 3.45. The workers in the pressing unit with mean and SD as 28.77 ± 2.74, and those in the administrative unit with mean and SD as 16.78 ± 3.22 had the highest and lowest values, respectively. The mean of WAI of the study population was 37.43 ± 6.14 and the mean of highest and lowest scores of WAI was for the employees in the administrative unit with mean and SD as 44.98 ± 2.08 and those in the pressing unit as 53.53 ± 4.55. Table 2 describes the level of mental disorders and the WAI by occupational group and demographic and grounded variables. One-way ANOVA and independent-samples t-test were employed to examine the differences between the mean of mental disorders and noise-induced WAI among demographic variables and occupational groups.

Table 2.

Description of mental disorders and WAI In term of occupational, age, work experience, and education groups.

			Mean of ± SD mental disorders	p-value	Mean of the ± SD WAI	p-value
Mental disorders and the WAI	Total participants		23.46 ± 3.45	<.001*	37.43 ± 6.14	<.001*
	Occupation^a	Administrative unit	16.78 ± 3.22		44.98 ± 2.08
		Mergers and acquisitions unit	21.24 ± 2.58		42.64 ± 2.32
		Die casting unit	23.13 ± 2.61		34.45 ± 5.60
		Molding unit	23.76 ± 2.64		37.98 ± 2.27
		Screw making unit	24.44 ± 2.82		35.78 ± 5.53
		Cutting unit	26.10 ± 3.44		33.65 ± 3.41
		Pressing unit	28.77 ± 2.74		32.53 ± 4.55
	Age^a	Younger than 35 years of age	18.44 ± 3.15	<.001*	42.90 ± 5.50	<.001*
		35–40 years old	24.59 ± 1.78		37.85 ± 4.44
		Over 40 years of age	27.35 ± 2.98		31.54 ± 3.58
	Work experience^a	Less than 10 years	19.66 ± 3.44	<.001*	42.15 ± 6.02	<.001*
		10–20 years	23.08 ± 2.67		26.54 ± 5.45
		More than 20 years	27.64 ± 1.52		32.60 ± 3.78

^aOne-way analysis of variance.

*Significance at 5% error level.

As the results of analysis one-way ANOVA show, the mean of mental disorders and the WAI were significantly different among occupational, age, and work experience groups. The results of independent-samples t-test indicated that the level of education had no significant relationship with mental disorder and the WAI.

The results of investigating the relationship of noise exposure with mental disorders and the WAI are presented in Figures 1 and 2, respectively.

Figure 1.

Mean scores of mental disorders at different levels of exposure to noise of apparatuses.

Figure 2.

Mean scores of the WAI at different levels of exposure to noise of the apparatuses.

As these figures show, with the increase of noise exposure, the employees’ levels of mental disorders enhance, while the WAI decreased. But there were also fluctuations in the downward trend in the WAI.

Multivariate regression analysis was used to evaluate the simultaneous effect of significant independent variables in the analysis of variance such as age, work experience and daily personal voice contact (LEp, d) on mental disorders and the WAI. The results of this analysis are presented in Table 3.

Table 3.

Investigating the simultaneous effects of age, work experience, and Noise exposure on the employees’ mental disorders and the WAI.

	Independent variable	F-value	p-value	B ± SD	Standardized regression coefficient	t-value	p-value
Mental disorders	Fixed	46.45	<.001	35.99 ± 3.96	---	7.22	<0.001
	LEp,d			0.32 ± 0.04	0.32	6.65	<0.001
	Age			0.09 ± 0.12	0.11	3.27	0.038
WAI	Fixed	83.47	<.001	35.99 ± 3.9	---	6.01	<0.001
	Age			−0.59 ± 0.91	−0.61	−5.27	<0.001
	Work experience			−0.44 ± 0.74	−0.43	−4.81	0.009
	LEp,d			−0.14 ± 0.04	−0.15	−3.65	0.035

Although there are many factors affecting mental disorders and the WAI, only four variables (education level, age, work experience, and noise exposure) were investigated and compared in this study. In independent-samples t-test, the education level variable showed no significant relationship with independent variables. Thus, the variable did not enter into the model for simultaneous study of variables in multiple regression. Multiple regression results (see Table 3) indicate that among the independent variables of age, work experience, and exposure to the levels of noise, the noise exposure variable had the most additive effect (standardized regression coefficient as 0.32) on mental disorders. Assuming the other variables included in the model remained constant, per each dB increase in acoustic exposure, the values of mental disorders increased by 0.32. As Table 2 shows, although the mean scores of mental disorders in work experience groups was significantly different, according to the results of multiple regression model, work experience in presence of age and noise exposure had no significant effect on mental disorders. In addition, the effect of age, work experience, and noise exposure on the WAI showed that among the independent variables included in the model, age, and acoustic exposure had the highest and the lowest effects on the WAI, respectively.

Discussion

According to the results of the present research, the mean scores of mental disorders was 23.46 with SD as 3.45, indicating the possibility of a mild mental disorders in the whole study population. The results of one-way ANOVA showed that the level of mental disorders was different in different occupational groups, so that the level of psychological distress was higher among workers of the cutting and pressing units than in other occupational groups. Administrative employees had the lowest mean scores of mental disorders (see Table 2). Regression results showed that among the independent variables of age, work experience and daily exposure to noise, individual daily exposure to noise had the most significant effect on mental disorders (see Table 3). These results are consistent with Yoon et al. (2014) conducted on different jobs in Korea. He showed that there was a significant relationship between occupational noise disorder and psychological symptoms.³² Bakker et al. (2012) indicated a significant correlation of exposure to wind turbine noise with noise nuisance, mental disorders, and sleep disorder. This relationship was tested as a structural model, showing that exposure to wind turbine noise causes nuisance, sleep disorder, and mental disorders. Also, those who did not hear the turbine noise had no symptoms of mental disorders. The turbine noise with nuisance effects indirectly caused mental disorders.³³ A study conducted by Ahmadi Kanrash et al. in 2019. The results of this study indicate that there was a significant correlation (p < 0.01) between the measured sound intensity and the level of aggression of the studied workers. Exposure to noise in the workplace also increases the level of stress and inappropriate behavior associated with aggression, which is one of the dimensions of mental disorders, which is consistent with the present study.³⁴

Rostami et al. (2013) investigated the effects of noise exposure on the general health of steelworkers showed that noise can be considered a risk factor for mental disorders. The study showed that steelworkers had lower levels of mental health and those exposed to noise had a significant difference in depression than the reference group, so that 36% of workers exposed to noise suffered from at least one mental disorders.³⁵

Although the results of the present study showed a significant difference in mental disorders in age groups and work experience, the results of multiple regression showed that work experience in presence of other variables had no effect on mental disorders. Although unlimited factors are involved in causing and enhancing mental disorders that are outside the scope of the present study, in regression models the contribution of each factors is found to be significant, explaining 32% of variations in mental disorders. In other words, exposure to noise is a major cause of mental disorder among the workers in the automobile parts manufacturing industry compared to age and work experience, as well as constant consideration of all confounding variables. Beutel et al. conducted a cohort study on 15010 individuals to determine the contribution of diverse environmental and occupational resources in noise nuisances. The results showed a linear correlation of depression and anxiety with noise nuisances.⁸ Conceivably, not only noise but also its effects have a synergistic effect on one another to generate psychological effects. According to the regression results, age was also a predictor of mental disorders. This result is consistent with those of Steptoe et al., stating that an increase in age is correlated with an increase in the risk of chronic illnesses. This may justify to some extent the increase in mental disorders in the working population.³⁶

According to the results of the present study, the mean scores and standard deviation of the WAI were 37.4 and 6.72, respectively. The results indicate the WAI is at an acceptable level throughout the sample. Eyvazlou et al. showed that the mean scores and SD of the WAI among the personnel of one of the automobile companies in Iran were 37.67 and 5.87, respectively. Their results confirm the results of the present study.¹⁹

The results of one-way ANOVA indicated that the workers in the cutting and pressing units, those in the age group over 40 years, and those with more than 20 years of work experience had the lowest level of the WAI. Increasing the employees’ work experience and age decreased the WAI. Also, the workers in the pressing and administrative units who had the highest and lowest noise exposure, had the lowest and highest WAI, respectively (see Table 2).

Noweir examined the relationship of noise exposure with performance, disciplinary action, absenteeism, and accidents among textile workers. The results showed that employees exposed to high levels of noise (more than 90 dB) were more absent and less productive than low noise groups (less than 90 dB).³⁷ In their studies, Bergs and Tafalla reported that as the exposure to noise increased, human performance and productivity decreased.^38,39 Those working in the cutting and pressing units had lower levels of the WAI as they had higher noise exposure. The results of the present study are consistent with other studies that show the effect of noise exposure on decreasing productivity and performance because the WAI is a tool that assesses the aforementioned factors such as productivity, performance, absenteeism, and occupational diseases. In fact, the significant effect of noise exposure on work ability can be due to the influence of each of the dimensions of the WAI. In this regard, Akbari et al. (2013) examined the effect of the exposure to levels of noise on employee productivity in the automotive industry and stated that exposure to levels of noise affects human productivity and performance. So, there is a significant negative relationship between exposure to levels of noise and human productivity.²⁷

Vedovato and Monteiro investigated the relationship between the physical conditions of workplaces (noise), the psychological needs of work, personal characteristics, and health on the WAI. The most important factors in reducing the WAI were age, gender, illness, sleeping less than 6 h, and work experience of more than 20 years. In their study, participants who worked in a noisy environments were less likely to work than participants in environments with less noise.⁴⁰

In a clinical trial, Nassiri et al. studied the effects of noise on human performance, with the results showing that exposure to high levels of noise had a significant and significant effect on reducing human performance.¹⁴ Results of multiple regression indicated that among the independent variables of age, work experience, and daily exposure to noise, age, and work experience had more negative effects on the WAI (Table 3). However, in the present study, individuals with exposure to the higher levels of noise had lower scores of the WAI than the other groups. But as Figure 2 shows, there are fluctuations in this figure as well. For example, in the group working in the die casting and casting unit, although they are less exposed to noise than the two groups working in the screw making and molding units, they have lower the WAI than the other two groups. Many factors such as working conditions, work organization, and workers’ individual characteristics affect the WAI.^15,19 In view of the researchers’ observations, exposure to the chemical and its adverse effects die casting can cause this fluctuation and difference in the WAI compared to the other two groups.

As Eyvazlou et al. showed, among the employees of the automotive industry, their WAI decreased significantly as their age increased. There was also a significant negative relationship between work experience and the WAI. These results are consistent with the results of the present study.¹⁹ Mazloumi et al. reported a significant correlation of the mean scores of the WAI with age and work experience. They showed that the mean scores of the WAI was significantly affected by age (especially after age 45).⁴¹ This is because with age and work experience, the incidence of complaints and occupational diseases increases due to exposure to occupational hazards, which in turn reduces their WAI.

In the present study, it can be said that in addition to physical problems, noise, as one of the most common harmful factors in workplaces can cause many adverse effects on employees’ mental health.^42–44 Moreover, there is a strong relationship between mental disorders and the WAI.⁴⁵ Mental health is one of the most important causes of the reduction in the WAI. As a result, it can be expected that noise exposure may directly or indirectly affect the reduction in the WAI.^20,45 The results of Geidi et al. showed that mental health accounted for 47% of the variations in the WAI.⁴⁵ Studies have also shown that exposure to sound causes psychological and physiological changes, including blood pressure and levels of aggression. In addition, the results of a study by Hosseinabadi et al. in 2019 showed that systolic and diastolic blood pressure and DNA damage in the noise exposure group It was significantly higher than the control group, so sound can affect psychological and physiological changes.^46,47

Therefore, mental disorder can have a negative and significant effect on employees’ WAI and subsequently their job performance. Also, the increase in the rate of mental disorders and the decrease in the WAI due to aging can be considered as the occurrence of various illnesses and physical weakness over time. In addition to mental disorders, age, and work experience, there are several other factors interfering with the WAI that were beyond the scope of the present study.

Conclusion

Overall, the results of this study indicated that there was a significant difference between the mean scores of mental disorders and WAI among occupational, age, work experience, and noise exposure groups. Employees with exposure to higher levels of noise have higher levels of mental disorders and lower WAI than those exposed to lower levels of noise. The ability to work directly and indirectly can be affected by exposure to industrial noise. Therefore, the decrease in working ability due to noise exposure may result in a mismatch of occupational needs with one’s abilities. As a result, mental and physical disorders are highly expected. Therefore, considering the obtained results and the employees’ exposure to noise in the automobile parts manufacturing industry, implementing hearing conservation programs and adopting measures and techniques of engineering-technical and noise management control in some units seem to be necessary so as to keep employees safe against adverse physical and psychological consequences.

Footnotes

Acknowledegments

This study has been extracted from a Master’s Thesis, funded and supported by Tehran University of Medical Sciences under ethics code IR.TUMS.SPH.REC.1397.071. We are obliged to thanks officials of this University and the managers and directors of the automobile parts manufacturing industry.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study , funded and supported by Tehran University of Medical Sciences.

ORCID iD

Seyed Hojat Mousavi Kordmiri

Note

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