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| Year : 2014
| Volume
: 16 | Issue : 72 | Page
: 270-278 |
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| A comparison of occupational and nonoccupational noise exposures in Sweden |
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Richard L Neitzel1, Eva B Svensson2, Stephanie K Sayler3, Johnson Ann-Christin2
1 Department of Environmental Health Sciences and Risk Science Center, University of Michigan, Ann Arbor, MI, USA
2 Department of Clinical Science Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
3 Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI, USA
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| Date of Web Publication | 10-Sep-2014 |
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This study was conducted to evaluate noise exposures and the contributions of occupational and nonoccupational activities among three groups of Swedish workers (office workers, day care workers, and military flight technicians), and to evaluate risk factors for elevated hearing threshold levels. Forty-five subjects were recruited across the three groups. Each subject completed a risk factor questionnaire along with Békésy audiometry at frequencies between 125 and 8000 Hz. Subjects also wore a noise dosimeter continuously for 1 week, and documented their occupational and nonoccupational activities using a time-activity log. Subjects in all groups completed >7400 h of dosimetry, and had weekly exposures between 76 and 81 dBA. Day care workers had the highest daily exposures, and flight technicians had the highest weekly exposures. Most daily and weekly exposures exceeded the 70 dBA exposure limit recommended for prevention of any hearing loss. Subjects' perceptions of their exposures generally agreed well with measured noise levels. Among office workers, exposures were predominately nonoccupational, while among flight technicians nonoccupational and occupational activities contributed roughly equally, and among day care workers occupational exposures were dominant. Extreme exposures and cumulative noise exposure were associated with an increased risk of hearing threshold levels >10 dB hearing level. Effective hearing loss prevention programs may be needed in occupations not historically considered to be at high risk of noise-induced hearing loss (e.g., day care workers). Prevention efforts need to address nonoccupational exposures as well as occupational exposures, as nonoccupational activities may present the dominant risk of noise-induced hearing loss for some workers. Keywords: Exposure assessment, hearing loss risk, noise, nonoccupational, occupational, source apportionment
How to cite this article:
Neitzel RL, Svensson EB, Sayler SK, Ann-Christin J. A comparison of occupational and nonoccupational noise exposures in Sweden. Noise Health 2014;16:270-8 |
| Introduction | |  |
Noise exposure is a ubiquitous but often overlooked occupational and environmental hazard. While the causal relationship between noise and noise-induced hearing loss (NIHL) has been known for hundreds of years, there is increasing evidence that a host of other health effects are associated with exposure to lower levels of noise. These effects include coronary heart disease, [1] hypertension, [2] stress, [3] and sleep disturbance. [4] The personal, social, and economic impacts of NIHL are substantial, and these additional health effects may present an even larger public health burden.
One factor that hampers our understanding of these health effects is inadequate noise exposure assessment. A number of European studies have developed and utilized sophisticated models designed to evaluate community-level exposures to specific sources of noise, and especially road [5] and airport [6] noise. The key shortcoming of these studies is their focus on single sources of noise. Without holistic assessment of exposure from all occupational and nonoccupational activities, these studies cannot evaluate total noise exposure, and this limitation may inadvertently limit our understanding of noise-related health effects. Model-based assessments are certainly useful for determining the fraction of a population at risk of exposure over a given level - for example, the 24-h limit of 70 A-weighted decibels (dBA) recommended by the World Health Organization (WHO) and the US Environmental Protection Agency (EPA) [7],[8] - from a particular source. However, such studies cannot determine the contribution of specific sources of noise to an individual's total exposure. Individual-level dosimetry measurements with simultaneous assessment of activities are needed to adequately assess the contribution of different exposure sources to health risk. Unfortunately, only a few studies [9],[10],[11] have conducted such assessments, and due to study design issues many of these dosimetry-based studies have not been able to explore the contribution of specific occupational and nonoccupational activities to total noise exposure and subsequent health effects.
To better characterize the importance of occupational and nonoccupational noise exposures to risk of NIHL, we evaluated noise exposures in several groups of Swedish workers. The goals of our study were threefold. The first was to assess, in a holistic fashion, total noise exposures over a short period (1 week). The second was to evaluate the contributions of occupational and nonoccupational activities to total noise exposures. The third was to explore the relationship between observed hearing threshold levels (HTLs) and noise exposures and other risk factors.
| Methods | | |
We selected three occupations to evaluate. The first group was office workers, which we expected to have occupational noise exposures of ~60 dBA. [12] The second group was day care workers, with expected exposures of ~70 dBA. [13],[14] The final group was flight technicians employed by the Swedish Air Force, anticipated to have exposures of ~90 dBA [15],[16] Our target sample was 15 workers per group (n = 45).
Office workers employed by the Karolinska Institutet near Stockholm, Sweden, were approached individually during normal work hours. Day care workers employed at 5 day care centers within a single community near Stockholm were approached at scheduled center meetings during normal work hours. Military flight technicians at two Swedish airbases in southern Sweden were approached at scheduled meetings during normal work hours. All potential subjects were given an overview of the study, and interested individuals completed informed consent forms. Study procedures were reviewed and approved by the Regional Ethical Review Board in Stockholm.
Each subject completed a range of procedures. These included a one-time questionnaire; noise dosimetry over a 1-week period; completion of a time-activity log during dosimetry; and otoscopy and audiometry sometime during the 1-week period.
Questionnaire
Subjects completed a 31-item questionnaire, written in Swedish, which collected information concerning demographics; hearing health; perceived hearing ability; job history and work experience; "typical" perceived occupational noise exposure and use of hearing protection devices (HPDs); and noisy leisure time activities and use of HPDs. The questionnaire, as a whole or in parts, has been used previously [17],[18],[19] An English version of the perceived noise item has been used [20] and validated [21] in US workers.
Noise dosimetry
To accomplish our first study goal, evaluation of noise exposures, subjects were issued a Larson Davis 706RC (Larson Davis, USA) dosimeter at the outset of the 1-week study period. Dosimeters data logged average noise levels at 1-min intervals, and were configured with a 70 dBA criterion level, 24 h criterion time, 3 dB time-intensity exchange rate, and 40-110 dB measurement range. Previous assessments have had limited ability to evaluate low-level nonoccupational exposures due to use of a 70-140 dB occupational measurement range. [22] Dosimeters were worn during waking hours, and kept nearby when sleeping or bathing. Dosimeters were recovered by research staff at the end of the 1-week measurement period, and were calibrated pre- and post-measurement.
Time-activity log
Subjects were given a time-activity log, written in Swedish. The log, similar to one we have used previously, [22] allowed subjects to report the timing and duration of their activities during their dosimetry measurement. The log also allowed subjects to report their use of headphones (which would add additional exposure not detected by the dosimeter), their use of HPDs, and their perceived noise levels (via the same item used in the questionnaire). Time-activity log information, combined with dosimetry-derived noise levels, was used to achieve our second study goal, evaluation of the contributions of occupational and nonoccupational activities to total noise exposures.
Otoscopy and audiometry
Otoscopy was performed prior to audiometric testing. Tests on office workers were conducted in an audiometric test booth at the Karolinska Institutet. Tests on day care workers and flight technicians were conducted in quiet rooms at each day care center and airbase, respectively. Background noise levels were not measured but rooms were judged to be very quiet by research staff. Békésy audiometry was conducted using a laptop PC running a program called "Fixfrekvens Békésy Audiogram" (Technical Audiology Department, Karolinska Institutet) an external sound card (UGM96, ESI, Germany), and Sennheiser superaural headphones (HAD200, Sennheiser, Germany). HTLs in dB hearing level (HL) were measured at frequencies between 125 and 8000 Hz. These audiometric data, when combined with dosimetry and questionnaire information, were used to address our third study goal, exploring the relationship between increased HTLs and noise exposures and other risk factors.
Analyses
Descriptive analyses were conducted for survey responses and for audiometric test results at individual frequencies and arithmetically averaged across 3, 4, and 6 kHz. Age was analyzed in four categories (< 35, 35 to < 45, 45 to < 55, and >55 years). Differences between groups were evaluated using χ2 analysis for categorical variables and analysis of variance (ANOVA) for continuous variables. Results were considered as significant where P < 0.05. Analyses were performed using SPSS 20.0 (IBM, USA) and Intercooled Stata 12.1 (Stata Corporation, USA).
Dosimetry and time-activity log data were combined for each subject, such that each measured 1-min interval had an assigned activity and perceived noise level, and then merged with audiometric and questionnaire data for analysis. One-min L EQ noise levels were analyzed arithmetically across individuals, exposure groups, activities, and by activity within exposure group. Arithmetic analysis of noise exposures is appropriate where dose does not accumulate within an individual. A 24-hour equivalent continuous average noise exposure (L EQ(24) ) for each 24-h period measured for each subject i and day j, were computed using Equation 1:
where T is the total number of measured minutes for subject i in the jth 24-h day (nominally 1440) and L is the average L EQ for each 1-min interval t. Equation 2 was used to compute a weekly (168 nominal h) L EQ for each subject i:
where N is the total number of measured days (nominally seven) per subject and L is the L EQ(24) for the jth day. The percentage of L EQ(24) exposures >70 dBA (e.g., exceedance fraction) was then calculated for both L EQ(24) and L EQ(168) estimates. A modified version of Equation 2 was also used to compute activity-specific L EQ s (L EQ, a ) for each subject. These levels were computed across all minutes in which each activity j was reported by individual i.
Equation 3 was used to estimate the percentage P of total noise exposure resulting from each of the k specific activities reported by each subject i via their time-activity logs:
where the denominator is the total sound pressure over a given exposure period. Activities reported by subjects were then collapsed to work versus non-work, and these calculations repeated. These fractions were arithmetically averaged across activities and groups.
Arithmetic mean 1-min L EQ levels were computed for each of the five perceived noise categories from subjects' time-activity logs. Cuzik's nonparametric test for trend was used to assess trends in 1-min L EQ levels associated with perceived noise categories.
Cumulative L EQ, Cum noise exposures normalized to a one-year exposure period were estimated using Equation 4:
where T is job tenure (years) reported by questionnaire for subject i, and TR is the reference time of 1 year. These cumulative L EQ exposures were considered as continuous variables, and were also collapsed into four categories (<75, 75 to <85, 85 to <95, and >95 dBA).
Logistic regression was utilized to evaluate the relationship between audiometric HTLs and noise exposures and other risk factors. Several dependent variables were explored in iterations of these models: HL >10 dB HTL at 4 kHz; at 6 kHz; and averaged across 3, 4, and 6 kHz. Separate models were developed for right and left ears. A forward stepwise model selection routine was used, with variables retained where P < 0.10. Covariates considered in the model selection routine included all questionnaire items listed in [Table 1] and continuous or categorical versions of cumulative L EQCi.
| Results | | |
Forty-five subjects were recruited [Table 1]: 15 office workers, 16 day care workers, and 14 flight technicians. The majority of participating flight technicians unexpectedly deployed on maneuvers away from their home base for a portion of their 1-week dosimetry period.
There were significant differences in gender between groups, with the flight technicians being majority male, and the other two groups being majority female [Table 1]. Differences between groups were noted in age and tenure, but these were not statistically significant. Office workers reported lower "typical" perceived occupational noise levels than the other groups. There were also significant differences in use of HPDs at work: 100% of flight technicians, but no office or day care workers, reported regular use during occupational exposures. The groups showed significant differences in involvement in motorsports and use of power saws, as well as in the perceived "good" hearing. There were no differences between groups in self-reported health status, hearing health, risk factors for NIHL or nonoccupational use of HPDs.
Audiometric evaluation
No subjects were excluded from audiometry based on otoscopy. However, audiometry could not be conducted on one day care and one office worker due to scheduling issues. The pattern of mean average HTLs was similar across groups [Table 2]. For all groups, mean HTLs were <10 dB HL below 3 kHz. Day care workers showed the largest HTLs at 8 kHz, and office workers showed the largest average, differences between ears. There were no significant differences in mean audiometric HTLs or HTLs >10 or >20 dB HL at 4, 6 kHz, and averaged across 3, 4 and 6 kHz. Only 1-2 subjects per group had HTLs considered above the range of normal hearing (e.g., ≥20 dB HL) at any frequency. HTLs at 6 kHz were generally worse than those at 4 kHz.
Noise exposures
Four measurement days were lost due to dosimeter failures among two subjects. No dosimeters failed post-calibration. A total of 311 valid 24-h dosimetry measurements (totaling 7426 person-hours) were collected. Most measured hours occurred during three activities: Sleep (about 33% of measured time), home (roughly 30%), and work or school (about 20%) (data not shown). Headphone use was uncommon (only 643 total minutes), so measured levels can be considered accurate for virtually all measured minutes.
The highest activity-specific L EQ levels [Figure 1]a were associated with social activities (e.g., shopping, dining, attending social gatherings, etc.) and work activities (e.g., classroom work with children at day care centers, work in an office setting, or work on or near military aircraft for the day care workers, office workers, and flight technicians respectively). Sleep was the quietest activity, though there was substantial variability in noise levels during sleep among flight technicians. Among flight technicians and office workers, social activities had the highest L EQ levels, while work activities had the highest L EQ s for day care workers. Office workers had the lowest median L EQ levels for all activities except exercise, and day care workers the highest. Variability of L EQ levels was low for commuting, home, and shopping. Mean noise levels were significantly different among the three groups overall and for each individual activity (ANOVA, P < 0.05, data not shown). | Figure 1: Measured and estimated noise exposures. Red reference lines indicated recommended 24-h exposure limit. (a) Measured Activity-specifi c LEQ (n = 45 subjects). (b) Measured LEQ(24) (n = 311 days). (c) Measured LEQ(168) (n = 45 subjects). (d) Estimated LEQ, Cum (n = 45 subjects)
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Two hundred and twenty-three weekday and 88 weekend day L EQ(24) measurements were made [Figure 1]b. Day care workers had the highest weekday levels, and office workers the lowest; differences between weekdays were not significant within groups. Saturdays were higher than Sundays, though not significantly so. Noise levels showed relatively little variability between weekdays and between weekend days. However, variability in L EQ(24) levels was much smaller in day care workers than in the other groups. The overall mean L EQ(24) level for weekdays was 75.8 ± 8.8 dBA, compared with 68.2 ± 9.9 dBA for weekend days. Day care workers had the highest overall mean L EQ(24) level (75.8 ± 6.7 dBA), followed by flight technicians (74.9 ± 11.8 dBA) and then office workers (70 ± 9.6 dBA); the differences in mean levels between groups were significant.
Unlike the daily exposures, flight technicians had the highest weekly L EQ(168) exposures [mean 83.5 dBA, [Figure 1]c, and office workers the lowest (mean 75.2 dBA). Weekly L EQ(168) exposures had a mean level of 78.6 ± 8.9 dBA. Variability in L EQ(168) exposures was smallest among day care workers and greatest among flight technicians.
Exceedance fractions were generally high [Table 3]. Nearly, 87% of measurements exceeded 70 dBA. Exceedance fractions were highest among day care workers and lowest for office workers, and were lower on weekends than weekdays. All weekly L EQ(168) values for day care workers exceeded 70 dBA, compared to 87% for flight technicians and 73% for office workers. At the weekly level, about 43% of total exposure came from occupational activities [Table 3]. This percentage ranged from 24% (office workers) to 55% (day care workers). For day care workers and flight technicians, as well as overall, exposure during weekdays was greater for occupational than nonoccupational activities. Among office workers, occupational activities never contributed more than nonoccupational activities on weekdays. Occupational activities during weekend days contributed only a small fraction of exposure. | Table 3: Exceedance fractions and dose contributions from work and nonwork activities
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The relationship between measured mean 1-min L EQ levels and categories of perceived noise from time-activity logs was monotonic and strong for the four lowest categories for office workers and flight technicians (data not shown). The trend was somewhat weaker among day care workers, and failed for all groups at the fifth category. Trends were statistically significant for all three groups and overall.
Office workers had a mean cumulative L EQ, Cumi exposure of 77.5 ± 12.5 dBA, lower than day care workers (79.6 ± 4.7 dBA) and flight technicians (82.5 ± 7.5 dBA) [Figure 1]d. As with L EQ(168) exposures, variability in L EQ, Cumi was smallest among day care workers and greatest among flight technicians. When continuous exposures were collapsed into four categories, 13 of 15 (87%) office workers were in categories 1 (<75 dBA) or 2 (75 to <85 dBA), 14 of 16 (88%) day care workers were in category 2, and 11 of 14 (79%) of flight technicians were in categories 3 (85 to <95 dBA) or 4 (>95 dBA) (data not shown).
Risk factors for elevated hearing thresholds
Risk factors were not varied across frequencies or between ears within frequency in our logistic regression analyses [Table 4]. Only two factors, extreme noise exposure and categorized L EQ,Cumi exposure, appeared in models at all frequencies. Extreme noise exposure was protective in the left ear, but was a significant risk factor in the right ear. Cumulative L EQ,Cumi was a significant risk factor for the 4 kHz and average 3, 4, and 6 kHz models. Categorized age was a significant risk factor at 6 kHz and average 3, 4, and 6 kHz. Job tenure was also a significant factor at 4 and 6 kHz. Overall, the models indicated that extreme noise exposure (an indicator of possible acoustic trauma) and chronic noise exposures were consistent risk factors for elevated HTLs.
| Discussion | | |
This study provides useful insights into noise exposures, the contributions of occupational and nonoccupational activities towards total exposure, and risk of NIHL for three diverse groups of Swedish workers (office workers, day care workers, and flight technicians). Our analyses suggest that most workers in these groups are exposed above limits recommended to prevent NIHL in the public, that nonoccupational exposures can contribute a substantial fraction of total exposure, that workers' perceived exposures are highly correlated with measured exposures, and that workers with even moderate exposures may be at risk of elevated hearing thresholds from noise.
The first aim of our study was to characterize noise exposures among the three groups of workers assessed. The occupational exposures of the groups did not meet our expectations. While we anticipated work exposures of approximately 60, 70 and 85 dBA for the office workers, day care workers, and flight technicians, respectively, observed exposures were around 70, 82, and 84 dBA. Group exposure levels were ordered as expected but showed smaller-than-expected separation. The unexpectedly high occupational exposures among day care workers compared to the expected levels is likely a reflection of noisy activities associated with children (e.g., noisy play, singing or playing of musical instruments, shouting, speech, etc.,), whereas the unexpectedly high occupational exposures among office workers may be due to the social and meal gatherings which are common in Swedish office environments.
The vast majority (about 88%) of weekly average exposures-and a slightly lower fraction of L EQ(24) exposures - exceeded the WHO/EPA 24-h exposure limit of 70 dBA. This finding is remarkably consistent with other dosimetry studies on urban dwellers in the United States (70% exceedance), [10] Spain (84% exceedance), [9] and China (85% exceedance). [11] L EQ(24) exposures among these various studies have ranged from 74.9 [9] to 79 dBA, [10] again quite consistent with our mean L EQ(24) of 73.6 dBA. This consistency increases our confidence in the generalizability of our findings, and also suggests similarities in total noise exposures in diverse urban environments around the globe.
The noise levels and contribution of exposures associated with various occupational and nonoccupational activities generally agree with previous dosimetry-based studies. The levels measured by Diaz and Pedrero [9] on workers in Madrid are similar to those measured here for home, shopping, sleep, and commuting, though weekend days were noisier than weekdays, in contrast to our findings. Nonoccupational activities assessed by Diaz and Pedrero contributed about 65% of total noise dose, which compares well to the nearly 58% nonoccupational contribution measured here. Zheng et al. [11] found that, on average, work contributed about 70% of total noise dose for office workers and teachers in Beijing, compared to 24 and 55%, respectively, in the current study. Levels for sleep are lower here than previously reported in the US [22] and China. [11] This is due at least in part to our low measurement range (40-110 dB) and absence of a 70 or 80 dBA threshold level, which more accurately captured low-level exposures, but which may have resulted in censoring of very high exposures.
Self-assessments of "typical" occupational noise exposure levels generally showed good agreement with 1-min L EQ and L EQ(24) exposure levels. These findings are generally consistent with the performance of this self-report noise scale in US workers, [20],[21] as well as musicians [23] and others, [24] and suggest that self-report can be a useful measure of noise levels over short (i.e., days to weeks) and possibly longer periods.
Our second aim was to evaluate the contributions of occupational and nonoccupational activities to total exposure. The average individual received 57.5% of their weekly exposure from nonoccupational activities. The distribution of exposure differed between groups: Office workers received about 76% of their exposure from nonoccupational activities, flight technicians about 52%, and day care workers about 45%. On weekend days the vast majority of exposure was from nonoccupational activities, and weekend days had lower L EQ(24) noise exposures than weekdays. These results suggest that workers with low occupational exposure, such as office workers, may receive the majority of their exposure from nonoccupational activities, but also suggest that workers with somewhat higher occupational exposures can still receive a majority of their exposure from nonoccupational activities. This finding is consistent with our recent study of noise in New York City. [25]
We noted statistically significant (though generally small) differences in mean nonoccupational L EQ levels between groups, suggesting that workers may have systematic differences in the way in which they are exposed during nonoccupational activities. Nevertheless, certain aspects of nonoccupational exposure were shared among all groups: For example, sleep and time at home had the lowest mean L EQ levels, while social activities had the highest, consistent with other dosimetry-based studies. [11],[22]
Our third and final aim was to evaluate the association between noise exposure and other risk factors for NIHL and elevated hearing thresholds. We noted that HTLs were generally worse at 6 kHz than at 4 kHz, a finding that highlights the need to include 8 kHz HTLs in any audiometric analysis in order to confirm that the audiometric configuration is consistent with NIHL, e.g., that a "noise notch" is present. Risk factors that were consistently associated with elevations in HTLs included extreme noise exposures, categorized cumulative L EQC exposure, age category, and job tenure. Our model results were likely influenced by two factors. First, most subjects had normal HTLs - that is, thresholds <10 dB at all test frequencies, - which resulted in diminished power to evaluate risk factors for elevated HTLs. Second, we observed unexpected differences in ages between the three groups. Group-mean ages co-varied with HTLs, raising the possibility that age-related hearing loss could dominate any observed changes in hearing. However, age was never a significant factor in our regression analyses, although tenure in current job, which was somewhat correlated with age (Pearson correlation 0.61), did appear in several models. This suggests that our analytical procedures were sufficiently robust to partition out the effects of aging and noise exposure on hearing. Our results also suggest that individuals with noise exposures below the occupational exposure limit of 85 dBA currently enforced by most developed nations may still be at risk of noise-related changes in hearing. This is consistent with previous findings by the National Institute for Occupational Safety and Health estimating that about 12% of workers with a lifetime of 85 dBA daily L EQ exposures will suffer a material hearing impairment, [26] implying that levels <85 dBA may still represent a hearing hazard.
This study had a number of limitations. Our cross-sectional study design meant that we could not evaluate the causal relationship between noise exposure, other risk factors, and NIHL. However, the consistency of associations between noise exposure and hearing thresholds >10 dB HL suggests that current measures of noise exposure can be used to estimate risk of NIHL. The generalizability of our study results may be limited. Our results are likely representative for workers in Sweden and similarly developed Western European nations, and can probably also be generalized to the United States and Canada. However, these findings may not be representative of exposures in rural areas or in developing nations, where occupational and nonoccupational noise levels, and even the types of activities conducted by individuals, may be quite different. The small sample size limits our statistical power, although our analysis benefitted from the rich level of detail resulting from the measurement of noise levels, activities, and perceived noise levels at 1-min intervals. It should be noted that, as with any study involving diary reporting by subjects, measurement error in reporting of activity timing and duration by subjects is unavoidable, and may be substantial. Finally, our treatment of HPD use was crude: We categorized HPD users as "regular" or otherwise, but small differences in the use time of HPDs have been demonstrated to have large effects on accumulated noise dose. [27],[28] This crude treatment of HPD use likely introduced additional measurement error into our exposure estimates for flight technicians.
| Conclusions | | |
Our study confirms that Swedish office workers, day care workers, and military flight technicians have moderate noise exposures (weekly L EQ(168) values between 76 and 81 dBA). The vast majority of measured days and weekly exposures for individual subjects exceeded the 70 dBA exposure limit recommended by WHO and EPA for prevention of NIHL. Among office workers, noise exposures were driven primarily by nonoccupational exposures, while among flight technicians nonoccupational and occupational activities contributed roughly equally to total noise exposure, and among day care workers the majority of exposure came from occupational activities. Nonoccupational noise levels differed between the three groups, but perceptions of noise exposure generally agreed well with dosimetry data across all groups. Extreme noise exposures and categorized cumulative L EQ noise exposure were consistently found to be associated with increased risk of elevated HTLs at the frequencies most vulnerable to noise, whereas age was not consistently a significant risk factor.
Additional study of groups with more clearly defined and separated noise exposures is necessary to confirm these findings. Also, additional study of the risk of noise-related hearing loss among workers with noise exposures between 75 and 85 dBA appears warranted. Overall, these results suggest that effective hearing loss prevention programs remain essential among workers in occupations traditionally considered highly noise-exposed (e.g., flight technicians), but should also be considered for occupations not historically thought to be noisy (e.g., day care workers). Our study also suggests that hearing loss prevention efforts should address nonoccupational activities in addition to occupational exposures.
| References | | |
| 1. | 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. 
|
| 2. | Bodin T, Albin M, Ardö J, Stroh E, Ostergren PO, Björk J. Road traffic noise and hypertension: results from a cross-sectional public health survey in southern Sweden. Environ Health 2009;8:38.
|
| 3. | Hébert S, Lupien SJ. Salivary cortisol levels, subjective stress, and tinnitus intensity in tinnitus sufferers during noise exposure in the laboratory. Int J Hyg Environ Health 2009;212:37-44.
|
| 4. | de Kluizenaar Y, Janssen SA, van Lenthe FJ, Miedema HM, Mackenbach JP. Long-term road traffic noise exposure is associated with an increase in morning tiredness. J Acoust Soc Am 2009;126:626-33.
|
| 5. | Matheson M, Clark C, Martin R, van Kempen E, Haines M, Barrio IL, et al. The effects of road traffic and aircraft noise exposure on children's episodic memory: the RANCH project. Noise Health 2010;12:244-54.
[PUBMED]  |
| 6. | Jarup L, Dudley ML, Babisch W, Houthuijs D, Swart W, Pershagen G, et al. Hypertension and Exposure to Noise near Airports (HYENA): Study design and noise exposure assessment. Environ Health Perspect 2005;113:1473-8.
|
| 7. | EPA. Information on levels of environmental noise requisite to protect public health and welfare with an adequate margin of safety. EPA Report 550/9-74-004; 1974.
|
| 8. | WHO. Birgitta Berglund, Thomas Lindvall, Dietrich H Schwela, editors. Guidelines for Community Noise. Geneva: World Health Organization; 1999.
|
| 9. | Diaz C, Pedrero A. Sound exposure during daily activities. Appl Acoust 2006;67:271-83.
|
| 10. | Flamme GA, Stephenson MR, Deiters K, Tatro A, van Gessel D, Geda K, et al. Typical noise exposure in daily life. Int J Audiol 2012;51 Suppl 1:S3-11.
|
| 11. | Zheng D, Cai X, Song H, Chen T. Study on personal noise exposure in China. Appl Acoust 1996;48:59-70.
|
| 12. | Robinson GS, Casali JG. Speech communications and signal detection in noise. In: Berger EH, Royster LH, Royster JD, Driscoll DP, Layne ML, editors. The Noise Manual. 5 th ed., Ch. 14: US: American Industrial Hygiene Association; 2000. p. 567-600.
|
| 13. | Sjödin F, Kjellberg A, Knutsson A, Landström U, Lindberg L. Noise exposure and auditory effects on preschool personnel. Noise Health 2012;14:72-82.
|
| 14. | Södersten M, Granqvist S, Hammarberg B, Szabo A. Vocal behavior and vocal loading factors for preschool teachers at work studied with binaural DAT recordings. J Voice 2002;16:356-71.
|
| 15. | Smedje G, Lunden M, Gärtner L, Lundgren H, Lindgren T. Hearing status among aircraft maintenance personnel in a commercial airline company. Noise Health 2011;13:364-70.
[PUBMED] |
| 16. | Kjellberg A, Sköldström B, Andersson P, Lindberg L. Fatigue effects of noise on aeroplane mechanics. Work Stress 1996;10:62-71.
|
| 17. | Morata TC, Johnson AC, Nylen P, Svensson EB, Cheng J, Krieg EF, et al. Audiometric findings in workers exposed to low levels of styrene and noise. J Occup Environ Med 2002;44:806-14.
|
| 18. | Svensson EB, Morata TC, Nylén P, Krieg EF, Johnson AC. Beliefs and attitudes among Swedish workers regarding the risk of hearing loss. Int J Audiol 2004;43:585-93.
|
| 19. | Johnson AC, Morata TC, Lindblad AC, Nylén PR, Svensson EB, Krieg E, et al. Audiological findings in workers exposed to styrene alone or in concert with noise. Noise Health 2006;8:45-57.
[PUBMED] |
| 20. | Neitzel R, Daniell W, Sheppard L, Davies H, Seixas N. Comparison of perceived and quantitative measures of occupational noise exposure. Ann Occup Hyg 2009;53:41-54.
|
| 21. | Neitzel RL, Daniell WE, Sheppard L, Davies HW, Seixas NS. Evaluation and comparison of three exposure assessment techniques. J Occup Environ Hyg 2011;8:310-23.
|
| 22. | Neitzel R, Seixas N, Olson J, Daniell W, Goldman B. Nonoccupational noise: exposures associated with routine activities. J Acoust Soc Am 2004;115:237-45.
|
| 23. | Hagerman B. Musicians' ability to judge the risk of acquiring noise induced hearing loss. Noise Health 2013;15:199-203.
[PUBMED] |
| 24. | Ising H, Babisch W, Kruppa B, Lindthammer A, Wiens D. Subjective work noise: A major risk factor in myocardial infarction. Soz Praventivmed 1997;42:216-22.
|
| 25. | Neitzel RL, Gershon RR, McAlexander TP, Magda LA, Pearson JM. Exposures to transit and other sources of noise among New York City residents. Environ Sci Technol 2012;46:500-8.
|
| 26. | NIOSH. Criteria for a Recommended Standard: Occupational Noise Exposure, Revised Criteria 1998, Report 98-126. US Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Washington, DC, USA, 1998. p. 105.
|
| 27. | Neitzel R, Somers S, Seixas N. Variability of real-world hearing protector attenuation measurements. Ann Occup Hyg 2006; 50:679-91.
|
| 28. | Neitzel R, Seixas N. The effectiveness of hearing protection among construction workers. J Occup Environ Hyg 2005;2:227-38.
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Correspondence Address:
Dr. Richard L Neitzel
Department of Environmental Health Sciences, Risk Science Center, University of Michigan, 6611D SPH Tower, 1415 Washington Heights, Ann Arbor, MI 48109-2029
USA
 Source of Support: This research was funded by grants from the Swedish Council for Working Life and Social Research (FAS Center programme 2006-1526) and AFA insurance (Noise research project 070153). The National Institute for Occupational Safety and Health provided support for the study in the form of loaned noise dosimeters. The authors are indebted to the participants in the study, and to Dr. Per Muhr for his assistance in gaining access to military fl ight technicians., Conflict of Interest: None  | Check |
DOI: 10.4103/1463-1741.140503
[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4] |
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