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ORIGINAL ARTICLES
Year : 2015  |  Volume : 19  |  Issue : 1  |  Page : 14-18
 

Hearing loss in shipyard employees


1 Department of Public Health, Medical School, University of Patras; School of Social Sciences, Hellenic Open University, Patras, Greece
2 Department of Public Health, Medical School, University of Patras; GP Section, General Hospital of Aigio, Aigio, Greece

Date of Web Publication14-May-2015

Correspondence Address:
Thomaella Tsouvaltzidou
Amerikis 30, 26441 Patras
Greece
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0019-5278.157000

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  Abstract 

Background: Noise-induced hearing loss (NIHL) is one of the most prevalent occupational illnesses, with a higher incidence in the heavy industry. Objectives of the Study: The aim of this study is to investigate the prevalence of NIHL in Greece and explore its correlations with other job and individual-related factors. Materials and Methods: Questionnaires were administered, and audiograms were conducted to 757 employees of a shipyard company in Greece, both white- and blue-collar, during the period 2006-2009. A modification of the 1979' equation of the American Academy of Otolaryngology was used to calculate hearing loss. Statistical analysis was conducted by means of the SPSS v. 17. Results: A 27.1% of the employees were hearing handicap. Hearing loss was correlated with age, past medical history of ear disease (Meniere's disease, acoustic neuroma, otosclerosis) or injury, hyperlipidemia, job title and level of education. A few questions on subjective hearing ability and symptoms showed strong discriminatory power of hearing pathology. Conclusions: The results of this study emphasize the burden of disease in the shipyard industry, and the need for continuous monitoring, implementation of preventive measures and hearing conservation programs.


Keywords: Audiograms, blue-collar workers, heavy industry, noise-induced hearing loss, shipyard


How to cite this article:
Alexopoulos EC, Tsouvaltzidou T. Hearing loss in shipyard employees. Indian J Occup Environ Med 2015;19:14-8

How to cite this URL:
Alexopoulos EC, Tsouvaltzidou T. Hearing loss in shipyard employees. Indian J Occup Environ Med [serial online] 2015 [cited 2018 Dec 11];19:14-8. Available from: http://www.ijoem.com/text.asp?2015/19/1/14/157000



  Introduction Top


Hearing loss is the third-most prevalent condition among older adults. [1],[2] A 16% of the hearing loss of >25 decibels hearing loss in adults worldwide and 24% of the cases of hearing difficulty in the United States is being attributable to occupational noise exposures, making it the second most self-reported occupational illness or injury. [3],[4],[5] In Europe, hearing disorders ranked seventh among the most prevalent work-related health problems, close to infectious diseases and skin problems while stress and musculoskeletal, pulmonary or cardiovascular disorders are placed higher in the list. [6] Occupational hearing loss is a condition caused by work-related factors, such as exposure to loud noise, or ototoxic chemicals, that result in hearing impairment. [1],[7]

The cause and effect relationship between noise exposure and hearing loss has been established for many years. [8] Existing studies indicate a link between industry, occupation, and noise-induced hearing loss (NIHL) with a higher prevalence or risk of hearing impairment in the railroad, mining, and metal manufacturing industries. [4],[9],[10] NIHL is caused by acoustic trauma, after a single exposure to an excessive sound, for example an explosion, or is a disease process that occurs gradually over many years of exposure to less intense noise levels and in the majority is due to occupational or industrial exposure (chronic NIHL).

Noise-induced hearing loss research in the Greek heavy industry is hardly being published, and the number of recognized occupational hearing loss cases among exposed workers is very small due to underreporting. [11],[12] High levels of noise and high rates of NIHL have been reported among electro production workers. [13] In a comparative study, employees in the Greek industry reported significantly higher exposure to noise. [14]

The aim of this study is to investigate the prevalence of occupational hearing loss among specific occupational groups of blue- and white-collar workers in a shipyard industry in Greece and to explore the correlations with other job and individual-related factors.


  Materials and methods Top


Study population

The population under study consisted of shipyard employees in Athens, Greece. For this study, 757 employees were assigned into the following eight broad job categories: (i) One category with those exposed to low mean levels of noise, that is, white-collar workers (managers-engineers [civil-, mechanical-, chemical-, metallurgy-, electrical-], draughtsmen, accountants, clerks, computer operators, nurses, electricians with license, inspectors, supervisors, store workers, material suppliers, tool repairs, security men, and fire watchmen); (ii) seven groups of blue collars exposed to medium or high mean levels of noise:

  • Sand (grit) blasters (simon operators) and painters
  • Welders, flame cutters
  • Riggers, propeller fitters, dry-dock laborers
  • Fitters, platters, plate fitters
  • Electric crane operators, chippers, riveters, fork lift operators, CNC operators, diesel cranes operators
  • Carpenters
  • Other blue collar workers (building workers, car washers, scuba divers, dockers, cooling, plumbers, car drivers, ship cleaners, radiomen, car mechanics, technicians, pipe fitters, tugboat personnel, e.g., captain and sailors, practical engineers, etc.).
Data collection

Data were collected during the period 2006-2009 as part of the periodic medical examination in the occupational health department. All employees gave their informed consent for their participation. A validated questionnaire consisting of two sections was administered to the subjects. The first section included questions regarding individual and job-related characteristics such as age, duration of employment, specialty, and basic education. The second section involved 17 questions focusing on the hearing capacity of the respondents, their family history concerning hearing loss, their personal history regarding hearing loss-related conditions, such as head injury or acoustic trauma and diseases such as diabetes mellitus, otosclerosis, Meniere's disease, acoustic neuroma, autoimmune diseases, thyroid dysfunctions, meningitis, parotitis, Lyme disease and vertigo, as well as the use of drugs that are implicated of causing ototoxicity (salicylates, aminoglycosides antibiotics, chemotherapeutics and loop diuretics).

Hearing ability was measured at 125, 250, 500, 1000, 2000, 4000, and 8000 Hz for both ears. To determine the average hearing impairment we used a modification of the equation that was developed in 1979 by the American Academy of Otolaryngology, using for our calculation the hearing capacity at 500, 1000, 2000 and 4000 Hz. [15],[16] For each ear, we summed the hearing ability (dBs) at these four frequencies and divided the result by four. From this average value, we subtracted 25 and then multiplied by 1.5%. Finally, we multiplied the result of the better hearing ear by five, added the result of the worse ear and divided the whole by six. The outcome variable that was included in the logistic regression models, expressed the percentage of hearing handicap (HH) and was divided into two categories, the first one including workers with a 0% of hearing loss and the second with hearing loss over 0.1%. An extra cut-off of 5% hearing loss was used in a descriptive analysis.

Statistical analysis

Descriptive analysis took place for the available measurements per occupational category. Logistic regression analysis was performed to evaluate the influence of possible determinants on the occurrence of hearing impairment. Odds ratios (OR) with 95% confidence intervals (CI) were calculated as a measure of association. For the initial selection of potential factors that influence the level of hearing loss, univariate logistic regression analysis was used with a significance level of P < 0.10. Subsequently, all independent variables that showed significant associations were considered for inclusion into the multivariate logistic regression model. Data entry and analyzes were conducted by means of the SPSS v. 17 for Windows statistical package (SPSS Inc. SPSS Statistics for Windows, version 17, SPSS Inc. Chicago, IL, USA, 2008).


  Results Top


[Table 1] demonstrates the individual and job related characteristics of the employees. The great majority was males (n = 727, 96%), technical school graduates (n = 485, 64.1%) and working over 10 years (n = 479, 63.3%). An 85.5% (n = 658) of the participants were blue-collar workers.
Table 1: Individual and job-related characteristics of the study population (n=757)


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After the application of the American Academy of Otolaryngology equation, the percentage of any HH was 27.1%, with an 11.8% being over 5%. The majority (72.9%) of the participants had no hearing impairment [[Table 2]].
Table 2: HH in shipyard employees (n=757)


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[Table 3] presents the multivariate analysis of subjective factors on hearing impairment. Participants' subjective view regarding their hearing ability seemed to be the most important factor with an OR = 4.771 (95% CI = 3.028 − 7.517). The presence of tinnitus or the sense of ringing in subjects' ears, as well as the difficulty in participating in one-to-one conversations revealed strong associations with hearing loss [[Table 3]]. The combination of these four questions seemed to have a strong discriminatory power, with a positive likelihood ratio (+LR) of 4.17, which gradually decreased when one factor was absent. Thereby, the + LR for three factors being present was 2.579, for two factors 2.277 and for a positive answer to only one of these four questions just 1.678 [[Table 4]].
Table 3: Multivariate analysis of subjective factors on hearing impairment


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Table 4: Discriminatory power of subjective factors in hearing ability (i.e., correctly identify employees with HH)


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The stronger aggravating factors for hearing impairment was age, with an OR = 7.541 for workers older than 50 years, and the presence of past medical history (otosclerosis, Meniere's disease or acoustic neuroma) with an OR = 7.586. Other conditions that present a higher risk of developing hearing loss were the hyperlipidemia (OR = 1.787) and ear injury (OR = 2.729). Participants' basic education shows a strong association with hearing deterioration (OR = 4.661 for primary education graduates), as well as their specialty, with sandblasters (OR = 3.523) and crane operators (OR = 3.187) being the most affected working groups. Riggers and other blue-collar workers showed no significant associations with hearing impairment. Workers exposed to low levels of noise had the lowest percentages of HH [[Table 5]].
Table 5: Multivariate analysis of aggravating factors for hearing impairment


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  Discussion Top


In the present study, a high percentage of heavy industry employees were found to be HH ped especially among specific job titles. Age, educational and medical history were also of importance. The obligation to control noise exposure and to prevent occupational hearing loss is a legislated area, but this study adds to the evidence against the impression that the problem is under control. It is of necessity to revisit these regulated areas by field studies. Although NIHL is a common and preventable occupational illness in the heavy industry, the scarce literature in this domain give evidence that the control measures adapted by industries to ensure that they are adhering to rules regarding hearing prevention are not effective enough and probably there is a lack of hearing conservation programs like in Greece, where very few NIHL cases were recognized officially each year. [10],[13],[14]

In the agreement with other studies, this study recognizes age as one of the most important factors for the inducement of hearing impairment. On the other hand, the strong co-linearity of age with the duration of employment prevents this variable to show a significant association with hearing loss in multiple regression analysis. Age-related hearing loss, as a progressive, permanent bilateral symmetrical sensorineural hearing loss, adds to noise-induced hair cell degeneration of the cochlea. [17],[18] However, on an audiogram, presbycusis will show a gradually downward slopping pattern, a pattern different from that of NIHL, whereas most audiograms in our study show a typical "notch" at 3.000-6.000 Hz for both ears, and this could only partially be attributed to the age effect. [19] In a recent study in noise-exposed industrial workers, distortion-product (DP) otoacoustic emissions and pure-tone audiometry showed high-frequency deterioration with the maximal audiometric changes at 4 and 6 kHz and DP changes at 2 and 3 kHz. [20]

Increased percentages of hearing loss have been confirmed in employees who have been diagnosed with Meniere's disease, otosclerosis or acoustic neuroma. [21],[22] Workers who experienced hearing loss problems in their childhood continue to show high rates of hearing impairment as adults as well, possibly due to under treatment of the underlying cause such as an otitis media or an untreatable disease, for example congenital causes. [23] Hyperlipidemia showed a strong correlation with hearing loss in agreement with other studies, that present hypertriglyceridemia and hypercholesterolemia as aggravating for hearing impairment factors, mainly by causing atherosclerosis, which reduces the oxygen supply of the cochlea by diminishing its vascularity. [24],[25],[26],[27]

As expected, hearing loss in white-collar workers is very low compared to blue collar workers. [28],[29] In our study, specific occupational groups showed the higher level of hearing loss such sand blasters, fitters, and platters. On the other hand crane, operators are not considered as so highly exposed but in fact very often they are being exposed to noises over 90 dB, and they use personal protective equipment (PPE) inconsistently. It seems that the same hold for chemical airborne exposure. Carpenters and welders/flame cutters showed also increased-but not statistically significant - burden, underlying the need for extent monitoring and surveillance. Except the anticipated effect of the workers' job specialty, our study shows additional and significant effect of the educational level. While the first reflects the effect of the level and the duration of noise exposure, the latter possibly reflects the consistent use of PPE, the adherence to health and safety guidelines and organizational issues. It is more common for lower educated groups to be occupied in higher noise level conditions and thereby being prone to developing NIHL. [30]

A worth mentioning finding was that the employees' subjective opinion regarding their hearing ability (consisting of four simple questions) could be taken into account in occupational health practice, as a cost effective screening tool, since a strong discriminatory power with a satisfactory +LR was monitored.

Our study utilized objective and subjective estimates of hearing ability collected in occupational health department, though are considered of very high validity. Our scope was to estimate hearing ability and potential prognostic factors and not to establish a cause-effect relation of NIHL. The equation used was minimally transformed to be very similar to that used to calculate hearing impairment by the Greek state for compensation reasons. Field and personal exposure measurements were not presented due to the very high complexity of the shipyard environment.

Noise-induced hearing loss is completely preventable, but scarcely research on the surveillance and prevention of hearing loss is published. Comprehensive hearing conservation programs by intervening both into the source of noise and in protecting each worker individually with the use of PPE and close surveillance are largely lacking in heavy industry in Greece. As a result, protective and control measures in heavy industry are not evaluated consistently and although laws for workers' protection have been adopted for decades, e.g. in Greece since 1991, only a few studies and reports on audiometric monitoring of workers have ever been published and even less comparative data for evaluating law efficiency are also available. The present study adds to the evidence that the problem is big and uncontrolled. [31],[32] A national education campaign to increase awareness combined with enhanced pressures to industries to adopt preventive and control strategies is of necessity.


  Acknowledgments Top


The authors would like to thank all the employees that participated in the study and the personnel of the occupational health department (registered occupational health nurses Mrs. Drakoulaki K., Fanarisiou I., Foti D., Konstantinou E., Marmarokopou G., Tanagra D., and Mr Tsimopoulos P.) for data collection. Dr. E. C. Alexopoulos, occupational health physician, who acts as guarantor of the study, was affiliated with the HSY Company during the study period.

 
  References Top

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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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