Article Access Statistics | | Viewed | 6913 | | Printed | 195 | | Emailed | 0 | | PDF Downloaded | 23 | | Comments | [Add] | | Cited by others | 8 | |
|

|
|
|
Year : 2015
| Volume
: 17 | Issue : 74 | Page
: 43-47 |
|
Dose - response relationship between noise exposure and the risk of occupational injury |
|
Jin-Ha Yoon1, Jeong-Suk Hong2, Jaehoon Roh1, Chi-Nyon Kim3, Jong-Uk Won1
1 The Institute for Occupational Health; Department of Preventive Medicine; Graduate School of Public Health, Yonsei University College of Medicine, Seoul, Korea 2 Graduate School of Public Health, Yonsei University College of Medicine, Seoul; Korea Occupational Safety and Health Agency, Gyeonggi Bukbu Area Office, Gyeonggi Province, Korea 3 The Institute for Occupational Health; Graduate School of Public Health, Yonsei University College of Medicine, Seoul, Korea
Click here for correspondence address
and email
Date of Web Publication | 19-Jan-2015 |
|
|
 |
|
Many workers worldwide experience fatality and disability caused by occupational injuries. This study examined the relationship between noise exposure and occupational injuries at factories in Korea. A total of 1790 factories located in northern Gyeonggi Province, Korea was evaluated. The time-weighted average levels of dust and noise exposure were taken from Workplace Exposure Assessment data. Apart occupational injuries, sports events, traffic accidents, and other accidents occurring outside workplaces were excluded. The incidences of occupational injury in each factory were calculated by data from the Korea Workers' Compensation and Welfare Services. Workplaces were classified according to the incidence of any occupational injuries (incident or nonincident workplaces, respectively). Workplace dust exposure was classified as <1 or ≥1 mg/m 3 , and noise exposure as <80, 80-89, or >90 dB. Workplaces with high noise exposure were significantly associated with being incident workplaces, whereas workplaces with high dust exposure were not. The odds ratios (95% confidence intervals) derived from a logistic regression model were 1.68 (1.27-2.24) and 3.42 (2.26-5.17) at 80-89 dB and ≥90 dB versus <80 dB. These associations remained significant when in a separate analysis according to high or low dust exposure level. Noise exposure increases the risk of occupational injury in the workplace. Furthermore, the risk of occupational injury increases with noise exposure level in a dose-response relationship. Therefore, strategies for reducing noise exposure level are required to decrease the risk of occupational injury. Keywords: Injury, noise exposure, occupational injury
How to cite this article: Yoon JH, Hong JS, Roh J, Kim CN, Won JU. Dose - response relationship between noise exposure and the risk of occupational injury. Noise Health 2015;17:43-7 |
Introduction | |  |
Many workers worldwide experience fatality and disability caused by occupational injuries. [1] Accordingly, accident causation models for understanding and preventing occupational injury have been proposed. The domino theory of Heinrich [2] is the most commonly used model; Heinrich suggests that injuries occur as a result of multiple errors involving an unsafe environment and unsafe behaviors causing the actual accident.
The components of unsafe environments include hazardous factors such as moving machines during work. [3] The absence of safety guards is a very simple hazard often faced by workers operating machines or equipment. [4],[5] If unsafe behaviors occur in any unsafe environment, the risk of occupational injury increases drastically. The components of human unsafe factors include a lack of motivation, knowledge, training, performance, and safety awareness about accidents. [6]
Some studies suggest that environmental stress such as heat [7] as well as job stress [8] and fatigue [9] are associated with the risk of occupational injury by making workers less aware of safety. The hearing as well as visual impairment can increase the risk of occupational injuries or accident by increasing the human error due to lack of recognition of warning the signal. [10] Human errors also can be occurred in various workplaces without permanent impairment. For example, dust is generated in various workplaces and could be linked to human stress via eye irritation. [11] Excessive noise exposure can disrupt detection of warning signals or trigger fatigue and stress, which are related to safety unawareness and human error as mentioned above. [12] In the workplace of Europe, because the occupational noise exposure was too loud, almost one-third of workers should raise voices to keep a normal conversation [13],[14] while those conversations are important to recognize the warning signals.
In Asia, almost half of all workers in manufacturing are exposed to noise, and 30-50% of factories have high noise levels exceeding 90 dB. [15] The nonauditory effects of noise include increased sleeplessness and human errors, which are also possible mechanisms linking noise and occupational injury. [16] In the same context of that biological plausibility, there were some investigation about noise exposure and risk of occupational injury, [17],[18],[19] but there is lack of evidences combination exposure of dust and noise on the risk of occupational injury. Therefore, elucidating the association between occupational injury and noise or dust exposure are important topics in occupational safety. The present study assessed 1790 factories to elucidate the associations of noise and dust with occupational injury.
Methods | |  |
Ethics statement
This study used a number of incidents where an injury has occurred in each factory without information about individual cases of workers. The injury cases information of individual workers were de-identified prior to count the injury incident number of each factory. The factory name and other records were also anonymized and de-identified prior to analysis. This study design was approved by the Institutional Review Boards of Yonsei University.
Factories
A total of 1990 factories located in northern Gyeonggi Province, Korea was included in this study. Factories that had no information regarding Workplace Exposure Assessment (WEA) data were excluded. Finally, the data of 1790 factories were analyzed.
Exposure assessments
The WEA is performed more than once per year by certified agencies from the Korea Ministry of Employment and Labor. All WEAs are performed by a certified industrial hygienist. WEAs target various hazardous agents including chemical compounds such as organic solvents, metals, acids, alkalis, gases, and metal working fluids as well as and physical agents like noise, heat, radiation, etc. Noise and dust exposures were measured by personal sampling methods using by dosimeters. One worker per every different job sectors in factories was chosen for personal sampling. After that, the highest value among personal samplings was used to calculate the 8-h time-weighted average (TWA). Because eye irritation occurs as a result of dust exposure exceeding 1 mg/m 3 , [20] a factory was defined as being a high-exposure factory when the TWA of dust exceeded this level. Meanwhile, noise levels of <80, 80-89, and ≥90 dB were categorized as negligible, marginal, and high exposure, respectively. [21]
Occupational injuries
Data from the Korea Workers' Compensation and Welfare Service were used to determine the incidence of occupational injury at each factory in 2010. Injuries that occurred outside the factory, such as business trips by car, injuries from athletic events, and accidents due to natural disasters, were excluded. Among a total of 1790 factories, 375 factories recorded one or more occupational injuries; these factories were defined as "incident workplaces." Meanwhile, factories not recording any occupational injuries were defined as "nonincident workplaces."
Statistical analysis
The χ2 test was used to compare differences between incident and nonincident workplaces. The odds ratios (ORs) and 95% confidence intervals (95% CIs) of workplace incidences were calculated using a multiple logistic regression model. Model I was adjusted for factory size, Model II was adjusted for factory size and work pattern (i.e., daytime or shift work), and Model III was adjusted for factory size, work pattern, and dust exposure. Two-tailed P < 0.05 were considered statistically significant.
Results | |  |
Basic characteristics of factories
Nonincident workplaces included a significantly greater proportion of small factories (i.e., <30 workers) than incident workplaces in [Table 1] (78.59% vs. 60.27%, P < 0.001). There was no difference between nonincident and incident workplaces with respect to the proportion of shift work. Incident workplaces had a significantly greater proportion of high noise exposure (i.e., ≥90 dB) than nonincident workplaces (14.67% vs. 6.93%, P < 0.001). There was no significant difference between nonincident and incident workplaces with respect to dust exposure level. | Table 1: Basic characteristics of factories according to risk of occupational injury
Click here to view |
Association between noise exposure and occupational injury according to dust exposure level
In a separate analysis according to a dust exposure cutoff of <1 mg/m 3 , the incident workplaces had a significantly greater proportion high noise exposure (i.e., ≥90 dB) than nonincident workplaces (16.50% vs. 7.47%, P < 0.001) [Table 2]. This association remained significant with a dust exposure cutoff of ≥1 mg/m 3 (7.69% vs. 5.14%, P = 0.034). | Table 2: Association between noise exposure and incident workplaces according to dust exposure level
Click here to view |
Odds ratios of incident workplaces according to high noise exposure
In crude logistic regression analysis [Figure 1], the ORs (95% CIs) of a factory with a noise exposure level of 80-90 and ≥90 dB being an incident workplace were 1.92 (1.45-2.54) and 3.63 (2.41-5.47), respectively, compared to a factory with a noise exposure level <80 dB [Figure 1], [Table 3]. In factories with dust exposure level <1 mg/m 3 , the OR (95% CI) of a factory being incident workplaces with a noise exposure level of 80-90 and ≥90 dB was 1.86 (1.36-2.54) and 3.71 (2.39-5.77), respectively, compared to a factory with a noise exposure level of <80 dB; in factories with a dust exposure level ≥1 mg/m 3 , the respective ORs (95% CIs) were 2.33 (1.18-4.64) and 2.98 (0.97-9.16). | Figure 1: Odds ratios and 95% confidence intervals for occupational injury
Click here to view |
 | Table 3: Multivariate logistic regression models of the association between occupational injury and noise exposure
Click here to view |
The significant association between high noise exposure and incident workplace status remained significant even after adjusting for factory size and work pattern in Model II (OR [95% CI]: 1.72 [1.29-2.30] at 80-89 dB and 3.49 [2.30-5.29] at ≥90 dB). The association also remained significant after adjusting for dust exposure in Model III (OR [95% CI]: 1.75 [1.31-2.33] at 80-89 dB and 3.42 [2.26-5.20] at ≥90 dB).
In a separate analysis according to dust exposure level (i.e., <1 and ≥1 mg/m 3 , respectively), the association between noise exposure level and incident workplace remained significant: 1.72 (1.25-2.37) and 2.03 (1.01-4.10) at 80-89 dB and 3.68 (2.35-5.78) and 2.50 (0.80-7.80) at ≥90 dB.
Discussion | |  |
The results of the present study indicate that high noise exposure in workplaces is significantly associated with the workplace being an incident workplace (i.e., a workplace where occupational injuries occur). Furthermore, the results indicate a dose - response relationship between noise exposure and the risk of occupational injury. Our results support the other previous results reported from the western country [17],[18],[19] to report an association between noise exposure and risk of occupational injury. This study is the first investigation to extend the association between noise exposure and the risk of occupational injury in Asia country. Noise exposure related to occupational injury independently to dust exposure, and there were also no combined effects of dust and noise exposure in the current study.
Noise is the most frequently reported occupational hazard in various workplaces. [14] Noise exposure is linked with various diseases such as hearing loss, cardiovascular disease, and psychological stress. [22],[23],[24] Furthermore, excessive noise exposure can increase the frequency of unsafe behaviors by triggering the fatigue, stress, [16] and reducing amount of attention. [23] Hence, noise decreases safety and increases unsafe behaviors, consequently increasing the risk of occupational injury. Workers with noise induce hearing loss require higher dB warning signal to recognized the sound compare to healthy workers. Because noise exposure worker should wear the hearing protection equipment and warning signals can be drowned out by background noise in unsafe workplaces, noise can exacerbate the unsafe environment by making workers less sensitive to recognize of warnings. Actually, a well-designed retrospective cohort study observed 240,000 person-years reported that over the 12% of occupational accidents are due to a combination effect of noise-induced hearing loss (NIHL) and workplace noise exposure. [19] Some report also confirms the association between noise exposure and risk of occupational injury using by hospital admission data. [17] Our current results, which were derived from workers' compensation data, also supported and extended that association by elucidating dose - response manner. Hence, the present results suggest noise exposure increases the risk of occupational injury possibly by increasing unsafe behaviors within already unsafe environments.
Noise-induced hearing loss could lead to stress and fatigue because workers needed the additional efforts to consent to understand speech-in-noise. Furthermore, NIHL workers had increased anxiety associated with the fear about might missing important information for their safety. Studies involving workers with hearing defects demonstrate that workplaces with high noise exposure (e.g., above 100 dBA) were associated with high risks of occupational injury. [12],[17] However, in Korea, workers who had noise-induced hearing loss with more than average 30 dB loss should be transferred to the workplace with noise <80 dB. In the current study, almost all workers working at the workplace with noise >80 dB noise have no NIHL. Hence, we cannot investigate the interaction between noise exposure and status of NIHL. In addition, other investigation reported that even relatively low level of noise exposure (e.g., 80 dBA) also can disrupt the verbal communication which related to detection of warning-signal in both hearing loss and normal hearing workers, temporally. [25] Hence, even relatively low level of noise exposure also can trigger the stress and fatigues of normal hearing workers, and our current study show factories exposed to 80-89 dB also had increased risk of occupational injury compare the factories exposed to below 80 dB did.
Dust from welding fumes, iron oxide, and crystalline silica, as well as organic dust, are generated in various workplaces. [26] Excessive exposure to dust irritates the eyes and respiratory system, increasing unsafe behaviors. [11] Furthermore, excessive dust exposure can coincide with unsafe environments that include hazardous machinery. However, there was no significant relationship between dust exposure and the risk of occupational injury in the present study. In this study, the risk of occupational injury was linked to noise exposure even after adjusting for dust exposure in the multivariate logistic regression analyses as well as a separate analysis, which may indicate they coincide in unsafe work environments. Hence, the association between noise exposure and occupational injury after adjusting for dust exposure suggests that noise exposure affects occupational injury after adjusting for unsafe environments.
The association between factory size and the risk of occupational injury is controversial: Inverse, [27] positive, [28] and U-shaped [29] associations have been reported. In the present study, there was a positive association between factory size and the risk of occupational injury. Therefore, the risk of occupational injuries in large factories may have been overestimated; consequently, the present results cannot be compared to those of previous studies that include the incidence rate of occupational injuries. Furthermore, almost 90% of factories included in the present study had <50 workers. Therefore, because the present results were based on small factories, the positive association between factory size and the risk of occupational injury cannot be generalized to larger factories.
This study has several limitations. First, because we used workplace average level of noise exposure and incident cases based on each factory, there was no exposure or injury information for individual workers. We have no information about personal protective equipment for noise and dust exposure. Hence, the workers in a given factory may have varying exposure levels; it is difficult to generalize the results to individual workers. Regardless, it is possible that the workers in the present study could share unsafe environments with their coworkers, because the factories were relatively small (i.e., <50 workers). Although different dust types have different toxicity and severity of irritation, we have no information of dust characteristic in the current study. We have no information about personal protective equipment for noise and dust exposure. Hence, more comprehensive exposure assessments were needed to clarify the association between dust exposure and risk of occupational injury. Furthermore, the dose-response effects of noise exposure in the multiple logistic regression analyses strengthen the relationship between noise exposure and the risk of occupational injury in the present study. In addition, safety education programs, such as training intervention of behavioral modification or provide guideline and information to enable the worker protect them self from unsafe environment, are factors associated with prevention strategy against to human unsafe behaviors, [30] while the systematic regulation of hazardous materials is associated with unsafe environments. [30] Furthermore, organizational and cultural factors are important components of unsafe environments that directly or indirectly influence unsafe behaviors. [31] Although working patterns (i.e., daytime and shift work) were controlled for in the analyses, other risk factors, such as workers age, length of experience in the specific work setting, industrial sector as well as organizational and cultural factors, were not included due to a lack of information. Because we used workers' compensation data to detect incident of occupational injury, nondeclaration of injury incident was a possible problem in the current study. Therefore, further studies including comprehensive exposure assessment and injury detection strategy with examination of additional risk factors for occupational injury are required to elucidate the association between noise exposure and the risk of occupational injury.
Conclusion | |  |
The present study indicates that noise exposure increases the risk of occupational injury regardless of dust exposure level. Furthermore, there is a dose-response relationship between noise exposure and the risk of occupational injury. However, investigations including individual-level data are required to elucidate these findings.
References | |  |
1. | Concha-Barrientos M, Nelson DI, Fingerhut M, Driscoll T, Leigh J. The global burden due to occupational injury. Am J Ind Med 2005;48: 470-81. |
2. | Heinrich HW, Petersen D, Roos NR, Brown J, Hazlett S. Industrial Accident Prevention: A Safety Management Approach. Vol. xii. New York: McGraw-Hill; 1980. p. 468. |
3. | Barreto SM, Swerdlow AJ, Smith PG, Higgins CD. A nested case-control study of fatal work related injuries among Brazilian steel workers. Occup Environ Med 1997;54:599-604. |
4. | Ruff T, Coleman P, Martini L. Machine-related injuries in the US mining industry and priorities for safety research. Int J Inj Contr Saf Promot 2011;18:11-20. |
5. | Caputo AC, Pelagagge PM, Salini P. AHP-based methodology for selecting safety devices of industrial machinery. Saf Sci 2013;53: 202-18. |
6. | Nahrgang JD, Morgeson FP, Hofmann DA. Safety at work: A meta-analytic investigation of the link between job demands, job resources, burnout, engagement, and safety outcomes. J Appl Psychol 2011;96: 71-94. |
7. | Tawatsupa B, Yiengprugsawan V, Kjellstrom T, Berecki-Gisolf J, Seubsman SA, Sleigh A. Association between heat stress and occupational injury among Thai workers: Findings of the Thai Cohort Study. Ind Health 2013;51:34-46. |
8. | Julià M, Catalina-Romero C, Calvo-Bonacho E, Benavides FG. The impact of job stress due to the lack of organisational support on occupational injury. Occup Environ Med 2013;70:623-9. |
9. | Vyas H, Das S, Mehta S. Occupational injuries in automobile repair workers. Ind Health 2011;49:642-51. |
10. | Toppila E, Pyykkö I, Pääkkönen R. Evaluation of the increased accident risk from workplace noise. Int J Occup Saf Ergon 2009;15:155-62. |
11. | van Kampen V, Deckert A, Hoffmeyer F, Taeger D, Brinkmann E, Brüning T, et al. Symptoms, spirometry, and serum antibody concentrations among compost workers exposed to organic dust. J Toxicol Environ Health A 2012;75:492-500. |
12. | Choi SW, Peek-Asa C, Sprince NL, Rautiainen RH, Donham KJ, Flamme GA, et al. Hearing loss as a risk factor for agricultural injuries. Am J Ind Med 2005;48:293-301. |
13. | Lisper HO, Eriksson B. Effects of the length of a rest break and food intake on subsidiary reaction-time performance in an 8-hour driving task. J Appl Psychol 1980;65:117-22. |
14. | Nelson DI, Nelson RY, Concha-Barrientos M, Fingerhut M. The global burden of occupational noise-induced hearing loss. Am J Ind Med 2005;48:446-58. |
15. | Jiho L. Occupational diseases of noise exposed workers. Hanyang Med Rev 2010;30:326-32. |
16. | Smith A. Noise, performance efficiency and safety. Int Arch Occup Environ Health 1990;62:1-5. |
17. | Girard SA, Leroux T, Courteau M, Picard M, Turcotte F, Richer O. Occupational noise exposure and noise-induced hearing loss are associated with work-related injuries leading to admission to hospital. Inj Prev 2014. doi: 10.1136/injuryprev-2013-040828. [Epub ahead of print]. |
18. | Girard SA, Picard M, Davis AC, Simard M, Larocque R, Leroux T, et al. Multiple work-related accidents: Tracing the role of hearing status and noise exposure. Occup Environ Med 2009;66:319-24. |
19. | Picard M, Girard SA, Simard M, Larocque R, Leroux T, Turcotte F. Association of work-related accidents with noise exposure in the workplace and noise-induced hearing loss based on the experience of some 240,000 person-years of observation. Accid Anal Prev 2008;40:1644-52. |
20. | Kjaergaard SK, Pedersen OF. Dust exposure, eye redness, eye cytology and mucous membrane irritation in a tobacco industry. Int Arch Occup Environ Health 1989;61:519-25. |
21. | Lutman ME. What is the risk of noise-induced hearing loss at 80, 85, 90 dB(A) and above? Occup Med (Lond) 2000;50:274-5. |
22. | Nelson DI, Nelson RY, Concha-Barrientos M, Fingerhut M. The global burden of occupational noise-induced hearing loss. Am J Ind Med 2005;48:446-58. |
23. | Gan WQ, Davies HW, Demers PA. Exposure to occupational noise and cardiovascular disease in the United States: The National Health and Nutrition Examination Survey 1999-2004. Occup Environ Med 2011;68:183-90. |
24. | Seixas NS, Neitzel R, Stover B, Sheppard L, Feeney P, Mills D, et al. 10-Year prospective study of noise exposure and hearing damage among construction workers. Occup Environ Med 2012;69:643-50. |
25. | Kumar UA, Ameenudin S, Sangamanatha AV. Temporal and speech processing skills in normal hearing individuals exposed to occupational noise. Noise Health 2012;14:100-5.  [ PUBMED] |
26. | Bernstein DM. Increased mortality in COPD among construction workers exposed to inorganic dust. Eur Respir J 2004;24:512. |
27. | Salminen S, Saari J, Saarela KL, Räsänen T. Organizational factors influencing serious occupational accidents. Scand J Work Environ Health 1993;19:352-7. |
28. | Buskin SE, Paulozzi LJ. Fatal injuries in the construction industry in Washington State. Am J Ind Med 1987;11:453-60. |
29. | Leigh JP. Firm size and occupational injury and illness incidence rates in manufacturing industries. J Community Health 1989;14:44-52. |
30. | Khanzode VV, Maiti J, Ray P. Occupational injury and accident research: A comprehensive review. Saf Sci 2012;50:1355-67. |
31. | Seo DC. An explicative model of unsafe work behavior. Saf Sci 2005;43:187-211. |

Correspondence Address: Jong-Uk Won The Institute for Occupational Health, Department of Preventive Medicine, Yonsei University College of Medicine, 50, Yonsei-Ro, Seodaemun-Gu, Seoul 120-749 Korea
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/1463-1741.149578

[Figure 1]
[Table 1], [Table 2], [Table 3] |
|
This article has been cited by | 1 |
Poor adherence to dust, noise and safety regulations predict injury rates in underground coal mines |
|
| Lee S Friedman, Brett Shannon, Leonard H T Go, Yuan Shao, Kirsten S Almberg, Robert A Cohen | | Occupational and Environmental Medicine. 2023; : oemed-2022 | | [Pubmed] | [DOI] | | 2 |
Motivational Interviewing to Encourage Agricultural Producers’ Use of Hearing Protection Devices: A Mixed-Method Feasibility Study |
|
| Laura J. Ridge, Nathan J. Stefanovsky, Keane L. Trautner, Marjorie C. McCullagh | | Workplace Health & Safety. 2022; : 2165079922 | | [Pubmed] | [DOI] | | 3 |
Influencing Factors, Formation Mechanism, and Pre-control Methods of Coal Miners' Unsafe Behavior: A Systematic Literature Review |
|
| Li Yang, Xue Wang, Junqi Zhu, Zhiyuan Qin | | Frontiers in Public Health. 2022; 10 | | [Pubmed] | [DOI] | | 4 |
Occupational noise exposure of utility workers using task based and full shift measurement comparisons |
|
| David Michael Lowry, Lin Fritschi, Benjamin J. Mullins | | Heliyon. 2022; 8(6): e09747 | | [Pubmed] | [DOI] | | 5 |
An evaluation of machine operator exposure to occupational noise during harvesting and extraction operations in Brazilian eucalyptus plantations |
|
| Diego Aparecido Camargo, Rafaele Almeida Munis, Ricardo Hideaki Miyajima, Roldão Carlos Andrade Lima, Danilo Simões | | International Journal of Forest Engineering. 2022; : 1 | | [Pubmed] | [DOI] | | 6 |
Evaluating Occupational Noise Exposure as a Contributor to Injury Risk among Miners |
|
| Abas Shkembi, Lauren M Smith, Sandar Bregg, Richard L Neitzel | | Annals of Work Exposures and Health. 2022; | | [Pubmed] | [DOI] | | 7 |
Fraction of acute work-related injuries attributable to hazardous occupational noise across the USA in 2019 |
|
| Abas Shkembi, Lauren Smith, Benjamin Roberts, Richard Neitzel | | Occupational and Environmental Medicine. 2021; : oemed-2021 | | [Pubmed] | [DOI] | | 8 |
Pregnancy Disorders in Female Workers at the Industrial Area of Sidoarjo, Indonesia |
|
| Firman Suryadi Rahman, Tri Martiana | | Journal of Public Health Research. 2020; 9(2): jphr.2020. | | [Pubmed] | [DOI] | |
|
|
 |
 |
|
|
|