European Agency on Safety and Health at Work, 2005). In New Zealand it is difficult to identify exactly how many people are affected by NIHL and how many are ...
Report on ACC/HRC funded research programme
Noise Induced Hearing Loss: Epidemiology and Noise Exposure
PR Thorne, D Welch, A Grynevych, G John, S Ameratunga, J Stewart, K Dirks, W Williams, G Dodd, SC Purdy, G Long, D Black,
Auckland Uniservices Ltd 2011
1|Page
Contents List of Abbreviations ............................................................................................................ 4 Executive Summary ............................................................................................................ 5 1.1 Outline: ..................................................................................................................... 8 1.2 Estimates of Incidence and Prevalence of Occupational NIHL in New Zealand ....... 9 1.3 Noise levels in New Zealand Industries .................................................................. 10 1.4 Hearing Protection Equipment Usage ..................................................................... 11 1.5 Hearing Loss........................................................................................................... 11 1.6 Non-work noise exposure ....................................................................................... 11 1.7 Monitoring of Hearing Loss ..................................................................................... 12 1.8 Summary and Conclusions ..................................................................................... 13 2. Background ................................................................................................................... 15 2.1 Overview and Purpose ........................................................................................... 15 2.2 Noise-Induced Hearing Loss .................................................................................. 15 2.2.1 Occupational NIHL ......................................................................................... 16 2.2.2 Non-work related NIHL ................................................................................... 18 3. Research Objectives ..................................................................................................... 20 4. Research Team ............................................................................................................ 21 5. Incidence and Prevalence of NIHL and Characteristics of Noise Environments in NZ Industries (Objective 1) ................................................................................................. 22 5.1 Introduction ............................................................................................................. 22 5.2 Methodology ........................................................................................................... 23 5.2.1 Exposure estimation ....................................................................................... 23 5.2.2 Relative risks of noise exposure ..................................................................... 25 5.2.3 Updated relative risks ..................................................................................... 27 5.2.4 Prevalence of Hearing Loss ........................................................................... 27 5.2.5 Modelling prevalence of hearing loss to estimate incidence........................... 28 5.2.6 Data Sources ................................................................................................. 28 5.3 Field Measurements ............................................................................................... 29 5.3.1 Interview and Noise exposure history............................................................. 30 5.3.2 Hearing protection use ................................................................................... 31 5.3.3 Noise measurements ..................................................................................... 31 5.3.4 Hearing tests (Otoscopy,Tympanometry and Audiometry) ............................. 32 5.4 Results .................................................................................................................... 33 5.4.1 Initial Estimates of Incidence and Prevalence of NIHL in New Zealand using the WHO Model (Objective 1a) ................................................................................. 33 5.4.2 Estimates of Incidence of NIHL ...................................................................... 41 5.4.3 Estimates of Prevalence of NIHL ................................................................... 43 5.4.4 Trends of NIHL 1986 – 2006 (Objective 1b) ................................................... 43 5.4.5 Summary ........................................................................................................ 48 5.4.6 Noise levels in New Zealand Industries.......................................................... 50 5.4.7 Characteristics of Hearing Loss ..................................................................... 64 5.4.8 Summary ........................................................................................................ 72 5.4.9 Revised Estimates ........................................................................................... 74 5.5 Summary ................................................................................................................. 80 6. Non-work related noise exposure (Objective 2) ............................................................ 81 6.1 Non-work related noise exposure in workers (Objective 2a, b) ................................ 81 6.2 Leisure noise levels ................................................................................................ 87 6.2.1 Nightclubs ...................................................................................................... 87 2|Page
6.2.2 Live Music Events .......................................................................................... 89 6.2.3 Personal Listening Device (PLD) Use ............................................................ 91 6.3 Summary ................................................................................................................ 94 7. Improving Methods for Monitoring of Noise-Induced Hearing Loss Objective 3: Refining the use of otoacoustic emissions as a means of monitoring sub-clinical hearing damage ......................................................................................................................... 96 7.1 Introduction ............................................................................................................ 96 7.2 Methods .................................................................................................................. 98 7.3 Results .................................................................................................................... 99 7.4 Summary .............................................................................................................. 105 7.5 Current research and the next step ...................................................................... 105 8. Discussion................................................................................................................... 106 9. Summary and Conclusions ......................................................................................... 111 10. References ............................................................................................................. 113 11. Appendices ............................................................................................................... 119 Appendix A: Questionnaire .......................................................................................... 119 Appendix B: Leisure Time Noise Exposure ................................................................. 123 123 Appendix C: Prediction of incidence given prevalence using DISMOD II ................... 124
3|Page
List of Abbreviations ACC
Accident Compensation Corporation
dB
Decibel
dBSPL
Decibels (Sound pressure level)
dBA/dB(A)
Decibels (A-weighted sound level)
dBHL
Decibels (Hearing level)
DPOAE
Distortion Product Otoacoustic Emissions
GBD
Global burden of disease
HL
Hearing Level
HPE
Hearing protection equipment
HRC
Health Research Council
ISO
International Organization for Standardization
LAeq
Equivalent continuous A-weighted sound pressure level
LAeq,8h
Eight-hour equivalent continuous A-weighted sound pressure level
LC,peak
C-weighted peak sound pressure level
NIHL
Noise Induced Hearing Loss
NIOSH
National Institute for Occupational Safety and Health
OAE
Otoacoustic Emissions
PAF
Population Attributable Fraction
PLD
Personal listening device
PTA
Pure Tone Average
SLM
Sound level meter
SPL
Sound Pressure Level
WHO
World Health Organisation
4|Page
Executive Summary
This study, funded by the Joint Research Partnership Programme of the Health Research Council (HRC) and the Accident Compensation Corporation (ACC), was undertaken to investigate the epidemiology of Noise-induced Hearing Loss (NIHL) in New Zealand. The study design was based on a modelling approach developed by the Global Burden of Disease working group of the World Health Organisation (WHO) (ConchaBarrientos, Campbell-Lendrum & Steenland, 2004). The model utilised international data, to establish the estimated excess risk of developing hearing loss above agerelated hearing loss given the level and duration of noise exposure in an occupational setting. Using this we identified the proportional attributable fraction for given sectors and occupational settings and then took data from the Census over different years on the participation rates in each sector and occupation, and the prevalence of hearing loss in New Zealand to provide the background data. From these data we developed estimates of the prevalence and incidence of NIHL (hearing loss ≥25dBHLAve1,2,3,4kHz) in different sectors and occupational groups and across census years (1986-2006). We attempted to verify and assess the sensitivities of these estimates with field measurements of noise levels in the workplace and assessment of hearing levels among a sample of workers in different sectors (500 workers and 99 companies across economic sectors). These data then allowed us to refine the estimates and to place them in a New Zealand context by drawing on New Zealand data. Our estimates of the prevalence of NIHL (≥25dBHLAve1,2,3,4kHz) in the workforce, in 2006, range from 29,242 (based on the WHO calculations) to 42,497 (based on New Zealand data collected in this study). This gives an incidence in the workforce ranging from 1077 to 1537 new cases of NIHL in 2006. We extrapolated the data to estimate the prevalence of NIHL (≥25dBHLAve1,2,3,4kHz) in the New Zealand population, in 2006, giving a range from 62,169 (based on the WHO calculations) to 69,613 (based on New Zealand data collected in this study). Since the data reflect Occupational NIHL, the incidence in the New Zealand population would not differ from that in the workforce. Based on these population data it is estimated that between 1.54 and 1.73% of the New Zealand population had a hearing loss solely due to occupational noise exposure. Because age-related hearing loss can add to the NIHL we estimated the number of people who would have only NIHL or some contribution to their total hearing loss from occupational noise exposure at between 2.25% and 2.58% of the population. Estimates are for unprotected noise exposures and are therefore likely to overestimate the prevalence of NIHL. Given the estimated prevalence of hearing loss in the New Zealand population is 10% (Greville, 2005) then we estimate that between 13.5% and 17.5% of the hearing impaired population have an occupational Noise-induced Hearing Loss and a total of 22.5-25.8% of hearing impaired people have some hearing loss from occupational noise exposure. Retrospective estimates using Census data indicates that there has been an increase in the total number of cases of NIHL and a small increase in the incidence rates between 1986 and 2006. The model predicts this on the basis of changes in the participation rates in sectors rather than any changes in the environmental noise levels which are assumed to remain the same across this period. 5|Page
Estimates of future incidence and prevalence were made under the assumption that the current trends in population growth and noisy sector participation would continue. The longest projections, to 2040, suggest that the number of people with NIHL will fall if current workforce trends continue and the rate would be determined by the efficacy of prevention programmes. Based on the noise measurements production workers in Agriculture, Mining, Construction and Manufacturing were exposed to the highest average noise levels (86.3-83.9 dBLAeq in descending order). However, these average levels were lower than what was predicted by the literature or NIOSH (1998) figures. The greatest proportion of workers affected by noise exposure in excess of 85dBA or 90dBA were mostly in Mining, Construction, Agriculture and Manufacturing and these would be the key industries to target for interventions. In the remaining sectors, smaller proportions were exposed to over 85dBA or 90dBA in Transport and Services but no workers in the Finance and Administration Sectors were exposed to levels in excess of 85dB LAeq. The proportion and extent of hearing losses in these sectors tended to be correlated with the expected exposures, except for the construction sector where the losses tended to be worse than predicted. This may relate to the small samples size or could reflect greater impulse noise exposures in this industry. The proportion of males and females exposed in these sectors is similar for Agriculture and Trade, reflecting the nature of the work and participation rates in these sectors. However in all others a higher proportion of males are exposed to damaging levels of noise than females. There is a higher proportion of Māori exposed to noise in all the High and Medium Noise Industries compared with non-Māori, except for Agriculture where the proportions are equivalent. Hearing Protection Equipment (HPE) was used by most workers (80-100%) when the noise levels were in excess of 85dBLAeq and by 100% of those who worked in levels above 90dBLAeq. HPE was used at some time by 50% of all workers interviewed. A large proportion of production workers (67%) did not use HPE; this was greater in the Transport and Agriculture sectors. The use of HPE tended to be equivalent across ages, although very young workers (40 years old) subjects, apart from DIY and music. A much larger proportion of older subjects reported DIY (59.2%, compared to 36.4% of younger subjects). This is largely explained by a much higher proportion taking part in lawn mowing. A greater proportion of younger people reported music related activities (62.3%, compared to 22.4% older subjects), with the largest contributions coming from live music, clubbing and PLDs. People are potentially exposed to high noise levels in many of these leisure activities. Using dosimetry and static noise measurements, noise levels were measured between 100dBLAeq and 108dBLAeq in nightclubs and live music events while PLDs were shown to produce levels up to 100dBA using earbud headphones. Because people spend a long continuous time in loud music (around 2-5hrs per day with a PLD; longer for nightclubs and live music events) these high noise exposures can contribute significantly to the daily noise dose for an individual (e.g., 15 minutes unprotected exposure at a nightclub with noise levels at 100dB is equivalent to 85 dBLAeq for 8 hours). Total lifetime noise exposure contributions from both occupational and non-work related activities was calculated for subjects. Subjects who are currently less than 30 years old were found to have a larger proportion (60%) of their lifetime noise exposure attributed to non-work related activities, compared to older subjects(41-45%). This may be due to a decrease in levels of occupational noise exposure or changes in the types of non-work related activities, possibly the introduction and popularity of PLDs, or greater access to and/or attendance at nightclubs or music concerts. Hearing Protection Equipment (HPE) use during non-work related activities was low. HPE was not used for 68.2% of all reported noisy activities. Reported HPE usage was greatest during DIY activities and firearms use. Not surprisingly, HPE usage was lowest when listening to music, since it is often not possible (for example using PLDs) or is socially undesirable (for example in night clubs or other live music events).
1.7 Monitoring of Hearing Loss
Hearing loss from noise exposure is defined audiometrically generally as an elevation of auditory threshold in the high frequency region, particularly as a “notch” in the 36kHz region of the audiogram. However, there can be difficulties ascribing the hearing loss to noise exposure, especially when there is an overlap with other otological conditions or age which can affect similar frequencies in the audiogram. Furthermore, the changes in hearing need to be reasonably substantial before they appear as a significant change in the auditory threshold. Thus using the audiogram to monitor hearing loss in industry is too coarse and insensitive as a measure to inform the efficacy of any prevention or conservation approach. There has been considerable interest in developing more sensitive methods that could identify early changes associated with noise exposure and perhaps assist in distinguishing NIHL from other 12 | P a g e
conditions. As part of such an effort, we have worked with our colleague, Professor Glenis Long in City University New York (CUNY) to further develop their swept tone method for measuring Distortion Product Otoacoustic Emissions (DPOAEs) and are investigating the relationship to NIHL. DPOAEs are generated by the non-linear active processes in the cochlea associated with the function of a population of sensory cells, the outer hair cells. These cells are particularly vulnerable to injury from noise exposure and when they are damaged the DPOAEs from those frequency regions are reduced or absent. Theoretically, the measurement of DPOAEs thus offer a method to objectively assess noise-induced injury. The results of previous studies looking at DPOAEs as a measure of noise injury have been mixed. Issues are the large variability in the DPOAEs from individuals, time taken to measure large number of frequencies and selecting the appropriate parameters to measure as a correlate. Some of the variability may be because for any frequency the DPOAE represents the combination of responses from different sources in the cochlea and these may sum differently in the earcanal and also be variably affected by noise or injury. Professor Long and her group have developed a method that uses swept tones and signal processing techniques to extract the different components of the DPOAE so that they can be analysed individually. She is co-supervising a PhD student, Gavin Coad, at the University of Auckland to investigate the utility of this method to assess cochlear function more specifically and sensitively and thus determine if this could be a suitable method for assessing NIHL. The signal processing techniques have been established in our laboratory and further developed for the project. The DPOAEs have been measured in normally hearing subjects using this method and correlated to other sensitive measures of hearing function. With these foundation data a study is underway to look at the DPOAEs in subjects with and without noise exposure and different levels of hearing loss.
1.8 Summary and Conclusions Noise induced hearing loss is a serious problem in New Zealand, so an understanding of its epidemiology is important; however, classical epidemiological approaches cannot inform us about the rates of NIHL because there is no gold standard to identify a case. To overcome this, a numerical modelling approach was taken to estimate the rates of NIHL based on known population effects of noise exposure, overseas estimates of workplace noise exposure, and New Zealand census data about the workforce profile in each sector and occupational class. We then conducted field research to test whether the noise levels and estimates used were appropriate for application to the New Zealand workforce. Noise levels and audiometric data were gathered from companies and people working in each of New Zealand’s economic sectors: these showed general support for the model estimates, but also allowed the model to be tuned so that it gave more accurate estimates of incidence and prevalence in the New Zealand context. Numbers of people in the population estimated with NIHL from occupational noise exposure ranged from 62,169 (based on the WHO calculations) to 69,613 and remained quite steady in the model over the years from 1986 to 2040: this reflected the changing workforce profile towards quieter, white-collar, employment offsetting the gradual population increase. These rates are for unprotected exposure and therefore are likely to be an overestimate of the occupational NIHL. The longest projections, to 2040, suggest 13 | P a g e
that the number of people with NIHL will fall if current workforce trends continue and the rate would be determined by the efficacy of prevention programmes. The incidence of NIHL has declined slightly over the years and would continue to do so according to forward projections. The calculated incidence in the population would be about 1077 to 1537 new cases of NIHL in 2006. These data provide an estimate of between 1.54 and 1.73% of the New Zealand population has a hearing loss with a contribution from noise exposure. The greatest proportion of workers affected by noise exposure in excess of 85dBA or 90dBA were mostly in Mining, Construction, Agriculture, and Manufacturing and these would be the key industries to target interventions. In the remaining sectors, smaller proportions were exposed to over 85dB or 90dB in Transport and Services. No workers in the Finance and Administration Sectors were exposed to levels in excess of 85dB LAeq. The proportion and extent of hearing losses in these sectors correlated with the expected exposures. The rate of new cases developing in the population is much lower than the rate of new cases to ACC which have increased almost exponentially. The factors that affect the application and acceptance of a claim to ACC are more complex than those modelled in this study to determine estimates of prevalence and incidence. Non-occupational noise exposure is a significant issue and some people are exposed regularly to levels of noise in excess of the dose that would be derived from occupational settings. This seems to be more significant among young adults and tails off with age. These data provide information to develop targeted approaches to ameliorate the effects of leisure noise. The modelling approach has been shown to be effective as a framework to incorporate findings from research. Gradual improvement of these estimates with continued input from future research is therefore anticipated.
14 | P a g e
2. Background 2.1 Overview and Purpose Noise-induced hearing loss (NIHL) is recognised as a significant health and disability issue both in New Zealand and worldwide. Noise exposure can lead to damage in the inner ear and loss of hearing ability, particularly to high frequency sounds; poor speech detection and discrimination; an inability to hear in background noise; and tinnitus. The impact on the individual varies but it can reduce employment options and cause social withdrawal, isolation and depression. The incidence and prevalence of NIHL in NZ is as yet unknown but globally noise is regarded as one of the main causes of hearing loss. The World Health Organisation estimates that over 250 million people have significant hearing loss and that approximately 16% of these cases result from excessive noise (Smith, 2004). There is also a high economic cost. For example, in Australia hearing impairment is estimated to cost $11.6b (1.6% of GDP) annually and NIHL is thought to account for about 30% of this cost (Access Economics Pty Ltd, 2006). The Accident Compensation Corporation (ACC) in NZ reports a steady increase in the number of NIHL claims over recent years at an increasing cost for rehabilitation. The increasing number of claims and the impact of hearing loss on the individual, family/whanau and society led the ACC and HRC in 2007 to jointly facilitate and fund research into NIHL in NZ that will lead to improved interventions and outcomes (Thorne, Ameratunga, Stewart, Reid, Williams, Purdy, Dodd & Wallaart, 2008). Funding was provided from the ACC/HRC partnership programme to investigate the epidemiology and prevention of NIHL in New Zealand. The Occupational Health and Safety Joint Research Portfolio (OH&S JRP) Steering Committee identified that this research was needed to give a better understanding of the nature and extent of NIHL in New Zealand and provide an evidence-based platform to develop interventions. The Committee also identified the need to build research capacity in this area indicating a longterm vision to establish credible research within NZ that will provide an evidence-based approach to interventions and policy to ameliorate the impact of NIHL. The projects described in this report were undertaken to estimate the incidence and prevalence of NIHL and to look at the non-work related noise exposure and methods of monitoring NIHL in the workplace. Other studies were undertaken at Massey University, led by Associate Professor Ian Laird, to look at prevention strategies in the workplace. Collectively, the research and subsequent reports and publications provide a greater understanding of NIHL in New Zealand and offer an important platform for building prevention strategies and policy to reduce the burden of NIHL in this country.
2.2 Noise-Induced Hearing Loss Any sound will cause hearing loss as long as it is loud enough and of sufficient duration. NIHL in the workplace, however, mainly arises from continual exposure to loud sound (noise) above a level of around 80-85dBA and is recognised as an occupational disorder in many work settings (Dobie, 2001). Acute exposure to very loud sound can also lead to rapid damage to the ear and loss of hearing. Loud sound is also a hazard in non-work related environments but in terms of the development of injury and relationship to exposure the distinction between the two contexts is increasingly recognised as artificial and unhelpful (Smith, Sorock, Wellman, Courtney & Prasky, 2006) although it is important from a legislative and prevention viewpoint. The hearing loss occurs because of damage 15 | P a g e
to the hearing organ (cochlea) of the inner ear; mainly the auditory sensory hair cells and their associated nerves (Thorne & Gavin, 1987; Wang, Hirose & Liberman, 2002). The hearing loss is typically binaural and results in a substantial hearing disability (Alberti, 1987; Neuberger, Korpert, Raber, Schwetz & Bauer, 1992). In addition to loss of sensitivity in high frequencies there is a loss of speech discrimination, particularly in background noise and a loss of clarity of high frequency sounds that creates considerable communication difficulties (Hetu & Getty, 2001). People may also have an intolerance to loud sound and complain of tinnitus (Axelsson & Sandh, 1985; Neuberger et al., 1992; Baguley, 2002). Naturally, such a handicap places a significant burden on an individual physically and psychologically, but hearing loss also has substantial social and interpersonal consequences (Jubb-Toohey, 1994; Arlinger, 2003; Williams, 2005a).
2.2.1 Occupational NIHL The severity of the hearing loss and rate at which it develops is defined primarily by the level and duration of the exposure. The New Zealand national standard for occupational exposure to noise is an eight-hour equivalent continuous A-weighted sound pressure level of 85dB LAeq,8h, while the maximum peak level permitted is 140dB LC,peak. This is set in law by Health and Safety in Employment Regulations (1995). With repeated exposure at this level over a working week, only 5% of the exposed population should have a hearing loss greater than 10dB over a working lifetime in addition to any other loss from aging (Standards Australia/Standards NZ, 2005). The risk and severity of hearing loss rises with duration and sound level (Dobie, 1995; 2001). Epidemiological data on NIHL has been collected using various methods including quantitative hearing assessment, self-reports (eg. European Agency on Safety and Health at Work, 2005), questionnaires (eg. Palmer, Griffin & Bendall, 2000 ;Palmer, Coggon, Syddall, Pannett & Griffin, 2001) and the number of people receiving compensation for NIHL (Thorne et al., 2008). Estimates of the incidence and prevalence of NIHL in different countries vary considerably. This variation is due to differences between the populations and their noise exposure, and includes: variations in the audiometric criteria for defining degree of hearing loss; differences in hearing conservation programmes and use of personal hearing protectors; and differences in criteria for attributing the proportion of hearing loss due to noise exposure rather than age or other disease. Based on the WHO definition for substantial or significant hearing loss (> ave 41 dB loss for 0.5, 1, 2 and 4 kHz), an estimated one sixth (16%) of the population with hearing loss worldwide is attributable to occupational noise exposure (WHO, 2002). This figure is corroborated by a USA assessment of the contribution of occupational noise exposure to total deafness rates, giving a range from 7% in developed nations to 21% in developing regions (Nelson, Nelson, Cocha-Barrientos & Fingerhut, 2005). In the USA it is estimated that between 9 and 11 million people have NIHL and 30-40 million are at risk because they work in noisy environments (Crandell, Mills & Gauthier, 2004; NIDCD, 2005). Hearing loss and tinnitus accounts for 10% of the disabilities in the US armed services; the third highest disability (Humes, Joellenbeck & Durch, 2006). Estimates of the prevalence of NIHL in the UK vary from 509,000 (Palmer et al., 2001; Health & Safety Executive (HSE), 2004) to 170,000 people between 35 and 64 years of age according to the Self-reported Work-related Illness (SWI) survey conducted by the UK Health and Safety Executive in 2004-2005. The number of individuals receiving disablement benefit for NIHL in the UK has changed little since late 1990s, following a decline since at least the 1980s.
16 | P a g e
In many jurisdictions, the numbers receiving compensation or rehabilitation costs for NIHL provides information on its extent in the workplace. In Australia, there were 4510 compensation claims for NIHL in 2001/2002 (NOHSAC, 2004). The number of compensation claims has steadily declined over the last decade in many European countries (UK, Germany, Finland [down approx 65%], France and Denmark) although the numbers have stabilised more recently (European Agency on Safety and Health at Work, 2005). Such declines may reflect the success of industry hearing conservation programmes resulting in a decline in NIHL incidence, although they may be due to changes in inclusion criteria for compensation and rehabilitation. Interestingly, workers in many European workplace surveys report increasing concern over workplace noise levels and perception that hearing is affected by noise exposure (Paoli & Merllié, 2001; European Agency on Safety and Health at Work, 2005). In New Zealand it is difficult to identify exactly how many people are affected by NIHL and how many are at risk as there is very limited published data in this country. In 1984 the Department of Health estimated that about 50% of adult hearing loss in NZ was due to noise (Hearing Report, 1984). From 1992 to 1998, there were 2,411 validated cases of NIHL reported to the Notifiable Occupational Diseases System (NODS), a voluntary national register (Driscoll, Mannetje, Dryson, Feyer, Gander & McCracken, 2004). From 1998 to 2000 there were a further 709 notifications (Statistics New Zealand, 2000). While these voluntary reports are not a reliable indication of the prevalence of NIHL, they place it as the second most voluntarily reported occupational disease in the country (after occupational overuse syndrome). McBride, (2005) estimated that 25% of the NZ workforce are affected by noise at work. In our review of the claims for NIHL up to 2006 we showed that the new claims rate for NIHL has been steadily increasing over the previous ten years, with a noticeable increase between 1995-99 and 2000-2004. Agriculture workers, people in trades and machine operators represent the largest groups of claims to ACC. Maori and Pacific peoples are substantially underrepresented in the ACC claims data when compared with their population (Thorne et al., 2008). It is difficult to estimate the effects of occupational risks on the overall health of communities. Although there is growing acceptance of the importance of objective measurements, the health effects of many occupational risk factors have not been quantified. Recognising the need to quantify the disease burden related to occupational noise, and to understand the distribution of the burden within populations, the World Health Organisation has published a report outlining a method for “occupational health professionals to carry out more detailed estimates of the disease burden associated with hearing loss from occupational noise both at national and subnational levels” (Concha Barrientos, 2004 (p. V)). Together with an introductory volume on assessing environmental burden of disease (Pruss-Ustun, 2003) these provide guidelines for the assessment of the burden of disease associated with NIHL and form the basis of the project described here. Essentially the approach involves: 1. Estimating the number of workers in each occupational and sector. 2. Estimating the proportion of workers by occupation and sector exposed to potentially harmful noise. 3. Estimating the relative risk of developing noise induced hearing loss with noise exposure. 4. Calculating the expected prevalence of hearing loss in each occupation and sector by multiplying the exposure rate by the number of workers and computing the proportion with noise induced hearing loss based on the relative risk compared to non-exposed workers. The main approach to NIHL prevention has been through Hearing Conservation Programmes supported by legislation such as the Health and Safety in Employment Act (1995) in New Zealand. Under most legal jurisdictions worldwide, employers must implement a programme when daily noise exposure exceeds a set level (85dB LAeq,8h in 17 | P a g e
NZ). These programmes normally rely on a hierachy of interventions such as a noise survey of the work environment to establish exposure levels and ‘noise hazard areas’, some form of engineering noise control and the issue of HPE and education on their correct use (Bruhl, Ivarsson & Toremalm, 1994; Leinster, Baum, Tong & Whitehead, 1994, see review by Thorne, Reid, Ameratunga, Williams, Dodd & Purdy, 2006). This is undertaken together with regular (annual) and standardised audiometry administered to all noise-exposed personnel, the results of which are monitored to identify any threshold shift to evaluate the effectiveness of the programme (NOHSC, 1991; Williams, 1993). Further detail on use of HPE, design of conservation programmes, and improving worker compliance are available from a number of studies (Melamed, Rabinowitz, Feiner, Weisberg & Ribak, 1996; Milhinch & Dineen, 1997, National Acoustics Laboratories, 1998; Dobie, 2001; Hughson, Mulholland & Cowie, 2002; Lusk, Ronis, Kazanis, Eakin, Hong & Raymond, 2003; Sexias & Nietzel, 2004; El Dib, Verbeek, Atullah, Andriolo & Soares, 2006; Williams, Purdy, Storey, Nakhla & Boon, 2007). Although audiometry is helpful to determine the efficacy of conservation programmes, concern has been expressed about its sole use to identify hearing damage as inner ear injury may occur before a hearing loss is detectable (LePage & Murray, 1993; Williams, 2005a). Furthermore, the likelihood of measuring a significant threshold shift using annual tests is small (Hetu, Tran Quoc & Dugay, 1990). This has encouraged the search for other tests of inner ear damage such as use of otoacoustic emissions (OAEs). These are sounds generated by healthy sensory outer hair cells in the cochlea and are absent or reduced if these cells are not functioning (Kemp, 2002). OAEs can be measured easily and are used clinically as a qualitative index of cochlea function (Kemp, 2002; Shafer, Withnell, Dhar, Lilly, Goodman & Harmon, 2003). There has been interest in using OAE as a measure of noise damage (Attias, Bresloff, Reshef, Horowitz & Furman, 1998; Fraenkel, Freeman & Sohmer, 2003) particularly early damage that may not be manifest as a threshold shift (Le Page et al., 1993; Chan, Wong & McPherson, 2004). Thus OAE testing could be a useful tool in parallel to audiometry to identify individuals who are especially at risk of developing hearing loss (Zhang, Zhang, Zhu, Zheng & Deng, 2004). Unfortunately, these tests are not yet accurate enough and there is considerable variability across subjects. If this variability was reduced OAEs may be a quick and reliable test that could help as an objective screening test for early noise damage. One of our group (Professor Long) has developed a novel method for separating components of one type of OAE, the Distortion Product OAE which we have looked at to see if it can be used to evaluate early hearing damage (Long, Talmadge & Lee, 2008).
2.2.2 Non-work related NIHL Exposure to loud sound does not occur just in the workplace. Leisure activities such as shooting (Clark, 1991), motorbikes and jet-skiing can involve exposure to very high sound levels (Davis, 1985). In addition toys (Yaremchuk, Dickson, Burk & Shivapuja, 1997) and domestic power tools produce high sound levels and concerts can put both the performer and audience at risk of hearing loss. More recently attention has been placed on the use of PLDs because they produce high sound levels (90-120dBSPL) directly at the ear canal for relatively long periods of time (LePage & Murray, 1998; Williams, 2005b). Apart from the clear impact of shooting on hearing (Clark, 1991; Nondahl, Cruickshanks, Wiley, Klein, Klein & Tweed, 2000) and loud music on performers, the impact of leisure or non-work related noise exposure (in terms of hearing damage) is very poorly understood (Davis, 1985). Calculating the contribution of non-work related exposure to the total NIHL is difficult and some argue that the distinction between hazards (eg noise) at work and in 18 | P a g e
non-work is artificial and unhelpful (Smith et al., 2006). Work and non-work injuries share many similarities offering opportunities for inclusive injury prevention approaches commonly restricted to one or other setting (Smith et al., 2006). What differs are the type of noise environment, personal attitudes and relative hazard contribution. The contributors to work noise are fairly well defined but what constitutes a non-work related noise environment needs clarifying and is constantly changing with technology (eg PLDs), lifestyle and social habits. Whilst it may be relatively straightforward to calculate a lifetime “work” noise exposure, determining a lifetime non-work related exposure is more difficult as it needs to take account of changes in lifestyle for an individual. It has also been noted that the total exposure to non-work noise is potentially a minimal hazard compared with the total occupational noise exposure (Nietzeal, Seixas, Goldman & Daniell, 2004). In summary, NIHL is as an important health and disability issue world-wide and better interventions essential to reduce the burden on the individual and society. As a first step a comprehensive understanding of the epidemiology of NIHL in NZ is required.
19 | P a g e
3. Research Objectives Table 3.1: Agreed objectives
Number
Objective
Section of Report
To determine the prevalence and incidence of NIHL in the New Zealand workplace and characterise the noise Section 5 environments in occupational settings (RFP objectives 1, 3&4)
1
1a
Identify sectors in New Zealand where there is low, moderately high and high noise exposure using existing international and New Zealand data
Sections 5.2, 5.4.
1b
Determine the proportion of the NZ workforce exposed to low, moderately high and high noise levels at each Census 1986-2006 using the World Health Organisation Global Burden of Disease for Occupational Hearing Loss as a model
Sections 5, 5.4.1
1c
Estimate the prevalence of Noise Induced Hearing Loss in each occupational group at 5 time points 1996, 2001, 2006, 2011, 2016, using the data developed in Objectives 1a and b
Sections 5, 5.4.9
1d
Verify noise levels and NIHL prevalence in sectors and determine these where NZ data is unavailable, unreliable or where prevalence estimates and ACC claims data are not aligned
Sections 5, 5.4.6, 5.4.7, 5.4.9
To identify the potential contributions of other occupational hazards and non-work related noise exposure to the incidence and prevalence of NIHL (RFP objective 2)
Section 6
2a
Determine the history of non-work related noise exposure and other ototoxic substances in surveys of workers in Objective 1
Section 6.1
2b
Assess the types and nature of noise exposure in nonwork related environments and determine the potential contribution to NIHL (not budgeted)
Section 6.2
To develop more accurate methods of monitoring hearing damage in the workplace (RFP objective 9).
Section 7
Refine the use of otoacoustic emissions as a means of monitoring sub-clinical hearing damage
Section 7
2
3 3a
20 | P a g e
4. Research Team Table 4.1: Research Investigators and Staff Name
Department
Role
Professor Peter R Thorne
Audiology and Physiology, University of Auckland
Lead Investigator
Professor Shanthi N Ameratunga
Epidemiology and Biostatistics, University of Auckland
Epidemiologist
Dr Kim N Dirks
Epidemiology and Biostatistics, University of Auckland
Physicist and Lead on Leisure Noise
*Dr David Welch
Audiology, University of Auckland
Hearing Scientist and Lead on Modelling Objective
Dr Warwick Williams
National Acoustics Laboratory, Sydney, Australia
Industrial Hearing Loss expertise
Professor Suzanne Purdy
Speech Sciences, University of Auckland
Audiologist
Dr George Dodd
Architecture, University of Auckland
Acoustician
Mrs Joanna Stewart
Epidemiology and Biostatistics, University of Auckland
Statistician
Professor Glenis R Long
Department of Speech and Hearing, City University New York, New York, USA
Auditory Psychophysics
School of Population Health, University of Auckland
Occupational Health Physician
Principal Investigators
Dr David R Black
Staff Stephen Vanderhoorn Mike Liu Dr Gareth John Dr Alla Grynevych
School of Population Health School of Population Health School of Population Health School of Population Health
*Dr Welch was not part of the original team but joined the Section of Audiology in 2008 and took a significant role in this research. Professor Anthony Rodgers was a member of the original team but left the University of Auckland in 2008. 21 | P a g e
5. Incidence and Prevalence of NIHL and Characteristics of Noise Environments in NZ Industries (Objective 1) 5.1 Introduction Estimates of the incidence and prevalence were developed using a targeted modelling approach that made use of existing data to obtain estimates of past, present, and future prevalence, by occupation, gender, age group and ethnicity. We modelled and estimated the disease burden of NIHL in specific occupational groups using an approach developed by the WHO (Concha-Barrientos et al., 2004), which we further developed and modified. This is a quantitative approach for establishing the level of NIHL and modelling the fraction that is attributable to occupational noise, although it has not been used in any jurisdiction. The incidence and prevalence of occupational noise induced hearing loss can be estimated by combining the following: - The proportion of people exposed to the defined noise levels; Occupational noise categories are defined by the A-weighted decibel, dB (A), usually averaged over an 8-hour working day (LAeq,8h ), measured in the workplace. It is known that there is strong association between this and the hazard to human hearing. A daily acceptable noise dose under the New Zealand Health and Safety Regulations 1984 is 90 dB) levels of noise.
NZ industry sources, or NIOSH study (table 2)
2. Determine the distribution of occupations between the nine economic subsectors.
Census data, Statistical New Zealand
12% of workers in the manufacturing subsector are in the professional category, 13% in administration, 10% in clerical, 4% in sales, 1% in service, none in agriculture, 59% in production.
3. Using the tables developed for Step 1 and Step 2, estimate the proportion of the working population exposed to moderately high noise levels for each of the nine economic subsectors, and sum the results.
Derived from the outputs of Steps 1 and 2.
11% × 59%, or 6.5% of production workers in manufacturing in the USA are exposed to noise levels of 85–90 dB. Repeating the calculation for other occupations in manufacturing, and summing, gives a value of 8.8% for all workers in manufacturing exposed to noise levels 85−90 dB.
4. For each gender, determine the proportion of the labour force working in the nine economic subsectors.
Census data, Statistical New Zealand
Approximately 4% of males work in agriculture, 1% in mining, 22% in manufacturing, etc.
5. Determine the proportion of the labour force exposed to elevated noise levels for each of the nine economic subsectors, and sum the values.
Derived from the outputs of Steps 3 and 4.
8.8% of manufacturing workers are exposed to noise levels of 85−90 dB, and 22% of the male labour force works in manufacturing. Multiplying these figures gives 1.9% of the male labour force is exposed to noise levels of 85−90 dB in manufacturing. Repeating for the other economic subsectors, and summing, gives a figure of 6.6% for the proportion of the total male labour force exposed to moderately high noise levels.
6. Determine the overall proportion of the working-age population, 15−64 years old, in the labour force, as well as the corresponding proportions for males and females.
Census data, Statistical New Zealand
87% of males 15–64 years old participate in the labour force.
7. Determine the overall population exposure by adjusting the proportion of the labour force exposed to elevated noise levels for the participation of the population in the labour force.
Derived from the outputs of Steps 5 and 6.
22% of workers in the production occupational category of the manufacturing economic subsector are exposed to noise above 85 dB. Half of these (11%) are exposed to noise levels of 85–90 dB (the remaining half are exposed to >90 dB).
The value of 6.6% for the proportion of the male labour force exposed to noise levels of 85–90 dB is adjusted by multiplying this figure by the participation of males in the labour force (87%). The result is that 5.7% of the male population 15–64 years old is exposed to moderately high noise levels.
24 | P a g e
5.2.2 Relative risks of noise exposure The GBD working group for occupational health risks developed a set of relative risk estimates (Table 5.2) comparing risk of hearing impairment in the occupational noise exposed population with risk for the general unexposed population (i.e. impairment that would be expected to result from ageing) (Nelson et al., 2005). They report these relative risks of hearing loss at 41 dBHL for the two exposure levels considered in their model. For the purposes of our national burden of disease study, estimates were also derived for relative risks of hearing loss at >25 dBHL (see section below). Given the lack of available NZ epidemiological data on hazards of noise exposure, we followed the WHO recommendation.
Table 5.2(a): Proportion of workers in each occupational category and economic sub-sector exposed a to noise levels >85 dB(A) Occupation Category Economic subsector
Professional
Administrative
Clerical
Sales
Services
Agriculture
Productionb
Agriculture
0.05
0.05
0.05
0.12
0.12
0.2
0.2
Mining
0.05
0.05
0.05
0.12
0.12
0.2
0.85
Manufacturing
0.05
0.05
0.05
0.12
0.12
0.2
0.22
Electricity
0.05
0.05
0.05
0.12
0.12
0.2
0.15
Construction
0.05
0.05
0.05
0.12
0.12
0.2
0.18
Trade
0.02
0.02
0.02
0.12
0.12
0.2
0.13
Transportation
0.02
0.02
0.02
0.12
0.12
0.2
0.12
Financec
0.02
0.02
0.02
0.12
0.12
0.2
0.02
Services
0.02
0.02
0.02
0.12
0.12
0.2
0.03
a Source: NIOSH (1998). b Figures shown in normal typeface are derived by expert judgement. Figures in italics are derived by extrapolation from the most relevant subsector in the production worker survey. Figures in bold indicate direct measurements. c Based on a figure of 1.5% for the proportion of “business services” workers exposed to noise.
25 | P a g e
Table 5.2(b): Proportion of workers in each occupational category and economic sub-sector exposed to noise levels 85-90 dBA Occupation Category Economic subsector
Professional
Administrative
Clerical
Sales
Services
Agriculture
Production
Agriculture
0.05
0.05
0.05
0.09
0.09
0.14
0.1
Mining
0.05
0.05
0.05
0.09
0.09
0.14
0.43
Manufacturing
0.05
0.05
0.05
0.09
0.09
0.14
0.11
Electricity
0.05
0.05
0.05
0.09
0.09
0.14
0.08
Construction
0.05
0.05
0.05
0.09
0.09
0.14
0.09
Trade
0.02
0.02
0.02
0.09
0.09
0.14
0.07
Transportation
0.02
0.02
0.02
0.09
0.09
0.14
0.06
Finance
0.02
0.02
0.02
0.09
0.09
0.14
0.01
Services
0.02
0.02
0.02
0.09
0.09
0.14
0.02
Table 5.2(c): Proportion of workers in each occupational category and economic sub-sector exposed to noise levels >90 dBA Occupation Category Economic subsector
Professional
Administrative
Clerical
Sales
Services
Agriculture
Production
Agriculture
0
0
0
0.03
0.03
0.06
0.1
Mining
0
0
0
0.03
0.03
0.06
0.43
Manufacturing
0
0
0
0.03
0.03
0.06
0.11
Electricity
0
0
0
0.03
0.03
0.06
0.08
Construction
0
0
0
0.03
0.03
0.06
0.09
Trade
0
0
0
0.03
0.03
0.06
0.07
Transportation
0
0
0
0.03
0.03
0.06
0.06
Finance
0
0
0
0.03
0.03
0.06
0.01
Services
0
0
0
0.03
0.03
0.06
0.02
26 | P a g e
5.2.3 Updated relative risks After discussion within the research team it was decided to update the relative risk estimates linking noise and hearing loss in the WHO model to provide more relevance to the New Zealand situation. Estimated excess risks of developing hearing loss given age, duration and level of exposure were used directly from the updated NIOSH model (Kemp, 1978). This takes the form of a logistic regression equation for developing a hearing loss of >25 dBHL. Expected risks for the general unexposed population (i.e. impairment that would be expected to result predominately from ageing) were derived from the ISO 19901999 international standard model, which is based on ISO 7029 (Shera, 2004). The ISO standard reports means and standard deviations for the non-noise exposed population and these were used to estimate the probability in the unexposed population to develop a hearing loss of 25 dB mostly associated with ageing. In this way expected risk for each age group was obtained by taking a weighted average of these probabilities across four frequencies (1000Hz, 2000Hz, 3000Hz and 4000Hz). The overall expected risk was obtained by averaging the expected risks between males and females and the relative risk re-estimated using the following equation and shown in Table 5.3:
Table 5.3: Updated relative risks Age (yrs) RR Expected risk Excess risk
RR
Exp Lev
22.5
37.5
52.5
65
75
25, >41, dbHL
5
New Zealand life tables and population data
Incidence of prevalence of hearing loss as well as prevalence of NIHL using DISMODI and DISMODII
6
Expected risk
World Health Organisation (2002)
Greville (2005) Wilson et al., (1999)
World Health Organisation (2002) ISO (1999) International Standard
Relative Risks, PAFs 7
Excess risks
Prince, Stayner, Smith & Gilbert (1997)
28 | P a g e
5.3 Field Measurements Once the modelling had been undertaken and the estimates discussed within the research team and with some input from Stakeholders, noise and hearing loss data were collected from selected sectors and companies to verify and revise the estimates (Objective 1b-d). These studies were approved by the University of Auckland Human Subjects Ethics Committee (Reference Number 2009/283) Ninety-nine companies were visited across the different economic subsectors (Table 5.5). Companies were randomly selected from the Auckland area and invited to take part in the NIHL study. The Auckland area was selected for convenience and because it includes a wide range of industry. Companies were initially contacted by telephone. 500 workers were recruited from within the companies investigated. They were selected randomly, on the basis of availability, and the sample consisted of a mixture of production workers (N=407) and non-production workers (eg. clerical and administrative staff (N=93)). Additional data on personal noise exposure levels in agriculture, were obtained from Dr David McBride from a separate study on Southland farmers (82 production workers). Additional data on personal noise exposure levels in mining were obtained from a drilling rig (4 production workers). Noise levels produced by industrial equipment were also measured, which together with noise data obtained from an Acoustics Consulting Company, Marshall Day Acoustics, is contained in a large database of noise levels which has been developed as an outcome to this study. Table 5.5: Profile of companies visited and employees tested Employees tested Companies visited
Production
Non-production
6
99*
2
0***
4**
0
Construction
3
15
4
Manufacturing
37
188
18
Transportation, Electric, Gas, Sanitary Services
9
43
9
Trade
14
50
5
Finance and Public Administration
7
8
35
Services
23
86
20
TOTAL
99
493
93
Economic Subsector Agriculture Mining
* Including additional data for 82 production workers, for whom only dosimetry data are available ** Including additional data for 4 production workers, for whom only dosimetry data are available *** Data from a drilling rig
Company visits and data collection took place over a two day period. The first day involved contact with the company, selection of employees for inclusion in the study, noise 29 | P a g e
exposure questionnaires for the selected employees, together with hearing protection assessment, and noise level measurements of equipment. On the second day hearing tests and personal noise exposure monitoring was undertaken. During an initial meeting with the company representative, a description of the NIHL study and details of the data collection procedures were provided and written consent was obtained. This was followed by a tour of the premises and identification of a quiet room for hearing tests and interviews. 5.3.1 Interview and Noise exposure history A list of employees was provided by the company and up to 10 were selected at random for inclusion in the research. Selected employees were interviewed individually to obtain their job title, gender, age, ethnic group, and information about any known hearing problems and current hearing disability. Known hearing problems were recorded as congenital, conductive, age-related, NIHL or other. Current hearing disability and presence of tinnitus were assessed with a set of multiple choice questions. Ethnicity was coded according to the New Zealand 2006 Census protocol (Statistics New Zealand, 2006). Participants were asked to select as many ethnicity options as they felt applied to them, and if the ‘Other’ option was selected, they were asked to specify the ethnicity. (See Appendix A for the interview protocol). In the second part of the interview, employees were asked to recall their lifetime exposure to noise in the workplace and in their leisure time (Appendix A). This took the form of a visual time-line, which was incrementally filled in as the employee recalled his/her noise exposure, beginning at the present day and moving backwards through time. For workplace noise exposure, the employee described: - The type of job undertaken over that period - Whether the job was considered noisy (and if so, over what proportion of the day did the noise occur). A particular job was considered noisy if the employee reported that it was necessary to shout to make themselves heard when one metre away from another person - If any instantaneous sharp sounds (like something banging, falling down, etc) occurred during their shift, to identify impulse noise exposure - The proportion of time hearing protection was worn when it was noisy. Workplace noise exposure of the day for each year was coded into four categories; the number of years when daily noise exposure was approximately 0%, 25%, 50%, 75%, and 100%. In cases where the employee worked for part of a year, the yearly noise exposure was weighted to one complete year. For example working for only 6 months in one year, with a noise exposure 50% of the time would be coded as 25% noise exposure for that year. Impulse noise was coded as a binary measure, either 1 (employee had been exposed to impulse noise) or 0 (employee had not been exposed to impulse noise). The percentage of time hearing protection was used when exposed to noise was coded as the number of years hearing protection was worn 0%, 25%, 50%, 75%, and 100% of the time that it was noisy. 30 | P a g e
For leisure time noise exposure, the employee described: All noisy activities he/she was involved in, for how long and how often (e.g., raced cars, 2hrs every month). As an aid to memory, and as an example, employees were shown a list of leisure activities considered to be noisy (Appendix B). Employees could choose from the list but were reminded that the list was not exhaustive and that any other activity they thought relevant should also be mentioned. Exposure to sudden, very loud noises (e.g. shooting) as an indicator of exposure to impulse noise. Whether any hearing protection was worn during each activity Leisure time noise exposure was calculated and coded into two categories: the number of years when noise exposure was less than 2hrs per week and number of years greater than or equal to 2hrs per week. Exposure for part of a year was weighted to one complete year. For example, noise exposure for 4hrs per week over 6 months would be coded as noise exposure for 2 hrs per week over one year. 5.3.2 Hearing protection use The type and class of HPE worn by employees was recorded. In addition, the attenuation effectiveness of foam disposable earplugs was assessed on a subgroup of participants using the VeriPRO system (VeriPRO, provided by Sperian). Employees were tested with the earplugs they routinely wear at work and were asked to insert the earplugs as they normally do. The attenuation of other types of hearing protector could not be tested with this system. It should be noted that those employees who scored low attenuation or who could be observed to be fitting the ear plugs incorrectly, were shown a short training video on plug fitting after the test. 5.3.3 Noise measurements Sound level measurements: Noise levels from a selection of machinery and workplace environments were assessed using a sound level meter (Solo SLM, 01dB-Metravib). The sound level meter was calibrated before measurements, and also at the end of each day (measurements were considered valid if the two calibration checks differed by less than 0.5dB). Sound measurements were taken at a distance 1m from the source of the noise, with the sound level meter positioned on a tripod, unless it was not practically possible to do so in which case the measurement distance was recorded. For each machine, the duration of measurement was chosen to obtain a recording that was representative of the typical noise produced by the selected machine, while being used to perform a typical job or process. If machinery was not constantly running, it was possible in some instances to have the machine switched on and a sample job performed to take a noise measurement. When this was not the case, measurements were taken with the machine on but no work undertaken. Noise levels associated with individual machines were measured in the absence of significant extraneous noise but if this was not possible, sound level measurements were not performed. All data were entered into a database including name of machine, manufacturer, model, year of production, function of machine, job being performed while measurement was taken, distance of source of noise from sound level 31 | P a g e
meter (m), length of measurement (hh:mm:ss), LAeq (equivalent continuous A weighted sound level, dB), LC,peak (peak sound level, in C weighted dB). Personal noise exposure: Personal noise exposure over an entire work shift was assessed using a dosimeter (CEL350 dBadge, Casella) for each employee. Following the hearing test, a dosimeter was calibrated and attached to the shoulder of the employee. Then the measurement run was started and the device was locked to prevent any tampering. The dosimeter was set to display ISO parameters, including LAeq and LC,peak. The employee wore the dosimeter for the whole of the shift for that day while performing all tasks associated with their usual working day. Infrequently, the employee noted the need to remove the dosimeter (e.g., when lifting heavy objects on the shoulder). In these cases, the employee was told to reattach the device as soon as the job was completed. A note of this, together with the time the dosimeter was removed and approximate duration, were recorded, but none were of significant duration (the maximum was120 minutes) and employees kept the dosimeter close by while it was removed so that it was still measuring relevant ambient noise levels. The dosimeter recording was stopped at the end of the shift by the researchers. 5.3.4 Hearing tests (Otoscopy,Tympanometry and Audiometry) Hearing tests were conducted at the start of the working day, before exposure to noise had occurred. However, since it was not appropriate to have employees wait for the hearing test rather than begin work, each employee was called as soon as possible after the start of their shift (up to two employees only could be tested at the same time). Each hearing test lasted a maximum of 10 minutes. Where employees were exposed to noise before the hearing test, a note of this was made together with the source of noise and duration. Otoscopy (HEINE mini3000 fiber optic otoscope) on both ears was performed to determine if the ear canal was clear of any obstruction and to check for excess cerumen or abnormalities (e.g., perforated ear drum). The state of the ear canal and eardrum was recorded. Tympanometry was performed on both ears using a portable tympanometer (MT10, Interacoustics). A note was made of compliance (ml), volume of ear canal (ml), gradient (ml), middle ear pressure (daPa) and tympanogram type. Based on the compliance and pressure data, a tympanogram type was assigned to each ear using standard criteria of compliance at 0.3 ml and pressure at -100daPa to classify tympanograms as Type A, B or Type C respectively. Pure-tone audiometry was conducted in the quietest room that could be provided by the company (identified on day 1). To assess level of background noise, a 5 minute sound level measurement (LAeq) was taken with the Solo sound level meter, before conducting the hearing tests. Pure tone audiometric screening (Amplitude T4, Otovation) was performed at 1, 2, 3, 4, 6 and 8 kHz (air conduction thresholds only). Insertphones were used in all cases, except when excessive cerumen was observed during otoscopy. In these cases, supra-aural headphones were used to avoid the possibility of compacting cerumen in the ear canal. The audiometer was calibrated for both headphones and insertphones. 32 | P a g e
5.4 Results 5.4.1 Initial Estimates of Incidence and Prevalence of NIHL in New Zealand using the WHO Model (Objective 1a) Prevalence and Incidence of Hearing Loss: The prevalence of hearing loss (greater than 25dBHL and of any cause) in the New Zealand population with respect to age and sex is shown in Figure 5.1. As expected hearing loss is greater among males and increases markedly above the age of 55yrs and with a greater rate in males than females. (a)
(b)
Figure 5.1: Prevalence of a) mild (≥25dBHL) and b) moderate or greater (≥41dBHL) hearing loss by age and gender
33 | P a g e
Hearing loss was modelled as a progressive condition. Thus cases of moderate hearing loss at a given age are modelled as cases of mild hearing loss incident at an earlier age. DISMODII was used to model incident cases of hearing loss at levels 25 dBHL and 41 dBHL from the prevalences for these levels (Figure 5.3.1). Death rates for people with hearing loss were assumed to be the same as the general population. Estimates of hearing loss incidence (Figure 5.3.2) show how the incidence of hearing loss is distributed across age, sex and severity. The majority of annual cases of mild hearing loss are developed in the relatively younger (45-69) age groups, while most of the moderate cases are occurring in the older age groups (70-80+). Once again, the rates and severity are greater in males than females. (a)
(b)
Figure 5.2: Incidence, per 100,000 population, of a) mild (≥25 dBHL) and b) moderate or greater (≥41 dBHL) hearing loss by age and gender
34 | P a g e
Exposure to Noise: After applying the original WHO model for occupational noise exposure to the NZ census data from 2006, it is clear that mining is the noisiest sector with 55% of workers in that sector exposed to noise greater than 85dBA. This is followed by agriculture (18% of workers), manufacturing (15% of workers) and construction (15 % of workers) sectors (Table 5.6). This is further disaggregated by gender and ethnicity in the tables and figures that follow. Table 5.6: The proportion of the working population exposed to moderately high (85-90dBA) and high (90+dB) noise levels for each economic sub-sector (2006 Census data). *NEI: not elsewhere included Exposure Industry
90dB) noise levels for each economic sub-sector in 2006 Exposure dBA
Total workforce
Industry
85-90
>90
N
% workforce
Agriculture
12.4%
6.2%
90519
8.6%
Mining
30.9%
29.3%
3642
0.4%
Manufacturing
9.1%
7.3%
159126
15.2%
Electrical
6.1%
2.7%
4263
0.4%
Construction
8.4%
7.3%
128205
12.2%
Trade
5.2%
2.7%
216768
20.7%
Transport
4.6%
3.4%
65895
6.9%
Finance
2.4%
0.5%
160992
15.3%
Services
4.0%
1.1%
120360
11.5%
Education
2.3%
0.4%
38028
3.6%
NEI*
2.5%
1.6%
62025
5.9%
1049823
100.0%
Table 5.7(b): The estimated proportion of the working female population exposed to moderately high (85-90dB) and high (>90dB) noise levels for each economic sub-sector in 2006 Exposure dBA
Total workforce
Industry
85-90
>90
N
%
Agriculture
11.6%
5.4%
47289
5.1%
Mining
10.7%
6.4%
513
0.1%
Manufacturing
7.9%
5.0%
67023
7.2%
Electrical
5.3%
0.5%
1824
0.2%
Construction
6.0%
1.5%
19332
2.1%
Trade
5.4%
1.9%
223608
23.9%
Transport
3.4%
1.2%
33699
3.6%
Finance
2.5%
0.3%
156873
16.8%
Services
3.8%
0.9%
235629
25.2%
Education
2.3%
0.2%
101097
10.8%
NEI*
2.6%
1.5%
49071
5.2%
935958
100.0%
36 | P a g e
(a)
(b)
Figure 5.3: Percentage of workforce exposed to a) 85-90dBA and b) >90dBA by age and gender
In general, it is estimated that more Māori are exposed to higher noise levels than nonMāori. In particular, the model predicts that there would be significantly higher proportions of Māori exposed to noise within the agriculture, manufacturing, and construction mining sectors compared with non-Māori (Table 5.8, Figure 5.4).
37 | P a g e
Table 5.8(a): The proportion of the working non-Māori (population exposed to moderately high (8590dBA) and high (>90dBA) noise levels for each economic sector. Data for males and females have been collapsed Exposure dBA
Total workforce
Industry
85-90
>90
N
%
Agriculture
12.2%
5.8%
121686
6.9%
Mining
27.0%
24.9%
3435
0.2%
Manufacturing
8.6%
6.3%
195438
11.1%
Electrical
5.7%
1.9%
5421
0.3%
Construction
8.0%
6.4%
127803
7.3%
Trade
5.2%
2.3%
396927
22.6%
Transport
4.1%
2.6%
86148
4.9%
Finance
2.4%
0.4%
293694
16.7%
Services
3.8%
0.9%
314571
17.9%
Education
2.3%
0.2%
122874
7.0%
NEI*
2.6%
1.6%
92412
5.3%
1760409
100.0%
Table 5.8(b): The proportion of the working Māori population exposed to moderately high (8590dBA) and high (>90dBA) noise levels for each economic sector. Data for males and females have been collapsed Exposure
Total workforce
Industry
85-90
>90
N
%
Agriculture
12.1%
6.4%
16122
7.2%
Mining
35.1%
34.1%
720
0.3%
Manufacturing
9.9%
8.6%
30711
13.6%
Electrical
6.4%
3.7%
666
0.3%
Construction
8.6%
7.6%
19734
8.8%
Trade
5.9%
2.8%
43449
19.3%
Transport
4.7%
3.6%
13446
6.0%
Finance
2.6%
0.7%
24171
10.7%
Services
4.1%
1.1%
41418
18.4%
Education
2.3%
0.4%
16251
7.2%
NEI*
2.3%
1.6%
18684
8.3%
225372
100.0%
38 | P a g e
(a)
(b)
Figure 5.4: Percentage of the Māori and non-Māori workforce exposed to a) 85-90dBA and b) >90dBA in different sectors
Population Attributable Fractions: Population Attributable Fractions (PAFs) were calculated from the expected rates of hearing loss by age in a non noise-exposed sample (ISO1990:1999) in comparison with the rates of hearing loss in a noise-exposed sample (Prince et al., 1997). The tables of PAFs (Tables 5.9 and 5.10) show the estimated percentage of hearing loss in the NZ population that can be attributed to exposure to occupational noise. Estimates are presented by age, sex, and sector. For example, almost 90% of hearing loss in male workers aged 15-29 and 30% aged 45-59 working within the three major sectors with highest noise levels (agriculture, manufacturing and construction) can be attributed to occupational noise. The higher proportion in younger people reflects the fact that occupational noise exposure is virtually the only cause of hearing loss at younger ages. There is a clear attenuation of the PAF by age: it should be emphasised that this relates to the probability of having a hearing loss due to noise exposure relative to other causes of 39 | P a g e
hearing loss at each age and does not reflect the numbers who have existing NIHL at each of these ages. Table 5.9: Population attributable fractions by age and sector for males Age Economic Sector
15 – 29
30 - 44
45 - 59
60 - 69
70 - 79
80+
Agriculture
89.5%
78.5%
28.6%
10.5%
6.9%
0.0%
Mining
97.3%
93.9%
61.3%
30.7%
21.9%
0.0%
Manufacturing
90.2%
79.7%
29.1%
10.4%
6.8%
0.0%
Electrical
79.4%
62.3%
15.4%
5.1%
3.3%
0.0%
Construction
90.1%
79.5%
28.6%
10.1%
6.7%
0.0%
Trade
78.8%
61.3%
14.7%
4.8%
3.1%
0.0%
Transport
81.3%
65.1%
16.3%
5.3%
3.4%
0.0%
Finance
46.6%
27.1%
4.4%
1.4%
0.9%
0.0%
Services
65.0%
44.2%
8.5%
2.8%
1.8%
0.0%
Education
43.9%
25.0%
4.0%
1.3%
0.8%
0.0%
NEI*
67.7%
47.3%
8.7%
2.7%
1.7%
0.0%
Unemployed
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
Table 5.10: Population attributable fractions by age and sector for females Age Economic Sector
15 - 29
30 - 44
45 - 59
60 - 69
70- 79
80+
Agriculture
88.3%
76.3%
26.2%
9.5%
6.2%
0.0%
Mining
89.4%
78.3%
27.9%
10.1%
6.6%
0.0%
Manufacturing
86.7%
73.6%
22.9%
7.9%
5.1%
0.0%
Electrical
57.7%
36.7%
7.3%
2.5%
1.6%
0.0%
Construction
72.1%
52.5%
11.6%
3.9%
2.5%
0.0%
Trade
74.5%
55.5%
12.4%
4.1%
2.6%
0.0%
Transport
65.5%
44.8%
8.4%
2.7%
1.7%
0.0%
Finance
42.6%
24.1%
3.9%
1.3%
0.8%
0.0%
Services
60.6%
39.6%
7.3%
2.4%
1.5%
0.0%
Education
37.0%
20.0%
3.3%
1.1%
0.7%
0.0%
NEI*
67.1%
46.6%
8.6%
2.6%
1.7%
0.0%
Unemployed
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
40 | P a g e
5.4.2 Estimates of Incidence of NIHL Combining NZ population data with the estimates of PAFs (Table 5.9, 5.10) allows estimation of hearing loss incidence (Figure 5.2). These estimates for 2006 can be further disaggregated by gender and sector (Figures 5.5-5.8).
Figure 5.5: NIHL cases per 100k by sector (Male ≥25 dBHL)
Figure 5.6: Total number of NIHL cases by sector (Male ≥25 dBHL)
41 | P a g e
Figure 5.7: NIHL cases per 100k by sector (Female ≥25 dBHL)
Total Number of NIHL Cases by Industry (Female ≥25 dBHL)
Agriculture Mining Manufacturing Electrical Construction Trade Transport Finance Services Education NEI Unemployed
Figure 5.8: Total number of NIHL cases by sector (Female ≥25 dBHL)
42 | P a g e
5.4.3 Estimates of Prevalence of NIHL The prevalence of NIHL (≥25 dBHL) in 2006 was modelled by age and gender, based on the above results (Table 5.11 and 5.12). Table 5.11: Prevalence of NIHL by age and gender (≥25 dBHL hearing loss) *workforce only 25+ dBHL
Age 15-29
Gender Male Prevalence of Number of NIHL, rate per NIHL cases 100,000* 879 210
Female Prevalence of Number of NIHL NIHL, rate per cases 100,000* 401 94
30-44
5541
1270
1592
334
45-59
16952
4309
2513
614
60-69
12881
7526
1596
890
70-79
8611
8078
1234
1029
80+
3863
8135
865
1045
Total
48728
3095
8202
484
Table 5.12: Prevalence of NIHL by age and gender (≥41 dBHL hearing loss) *workforce only 41+ dBHL
Gender Male
Female Prevalence of Number of NIHL NIHL, rate per cases 100,000* 31 7
Age
Number of NIHL cases
15-29
57
Prevalence of NIHL, rate per 100,000* 14
30-44
195
45
109
23
45-59
1998
508
416
102
60-69
2181
1274
365
204
70-79
1666
1563
287
239
80+
782
1646
207
250
Total
6879
437
1415
83
5.4.4 Trends of NIHL 1986 – 2006 (Objective 1b) Using the model, changes in incidence of NIHL between 1986 and 2006 were estimated for the workforce and these are shown in Table 5.13 and Figure 5.9. Although the total number of new cases had increased over this 20yr period, because of the increased population the rate of increase (per 100,000) was estimated to have declined from 176 per 100,000 to 115 per 100,000 during this period. The age specific incidence rates were estimated to have decreased by 10 – 30% for males (Table 5.13).
43 | P a g e
Table 5.13(a): Number of new cases of hearing loss greater than 25dBHL in 1986 and 2006. NB: the number of unemployed has been removed from the denominator for comparability Gender Male Age 456059 69
25+ dBHL
Year
1529
3044
Number of NIHL cases
1986 1996 2006
178 130 129
478 455 480
1117 1001 1370
Incidence of NIHL, rates per 100,000*
1986 1996 2006
56 49 50
151 136 134
533 427 429
7079
80+
1529
3044
Female Age 45- 6059 69
87 87 178
5 6 12
0 0 0
69 61 57
72 79 86
57 67 87
236 191 195
84 69 65
0 0 0
29 26 24
32 28 26
44 34 29
7079
80+
14 19 42
1 2 4
0 0 0
94 80 65
55 49 41
0 0 0
Table 5.13(b): Number of new cases of hearing loss greater than 41dBHL in 1986 and 2006. NB: the number of unemployed has been removed from the denominator for comparability Gender Male Age 45- 6059 69
7079
80+
1529
3044
Female Age 45- 6059 69
41+ dBHL
Year
1529
3044
Number of NIHL cases
1986 1996 2006
14 11 10
8 7 8
220 197 269
36 36 74
7 9 16
0 0 0
3 3 3
3 3 4
28 32 42
Incidence of NIHL, rates per 100,000*
1986 1996 2006
5 4 4
3 2 2
105 84 84
98 79 81
119 97 92
0 0 0
1 1 1
1 1 1
21 16 14
7079
80+
3 4 9
0 1 2
0 0 0
19 16 13
29 26 22
0 0 0
44 | P a g e
Figure 5.9: Incidence (number of new cases and rate/100,000 population) relative to age, shown for each Census year from 1986 to 2006
As the change in workforce is the most logical explanation for the change in incidence over the 20 year period from 1986 and 2006 the changes in the size and the nature of the workforce were also analysed for this period. This showed that the number of people in the workforce increased by about 500,000 between 1986 and 2006 but in relative terms, there has been a clear trend away from significantly noisy sectors such as agriculture and manufacturing (though not construction), towards less noisy sectors such as trade and finance (Figure 5.10). Additionally overall there was a substantial change in number of people in the production vs non-production workforce (Figure 5.12).
45 | P a g e
(a)
(b)
Figure 5.10: The total number (a) and proportion (b) of total workforce by sector
46 | P a g e
(a)
(b)
Figure 5.11: The proportion of total workforce by sector for males (a) and females (b)
Figure 5.12: Total workforce by occupation. NB: The NZ occupational classification system changed from 1986-2006. Occupational groupings were therefore altered to maximize consistency over the years.
47 | P a g e
5.4.5 Summary The first part of the study involved the use of the WHO model (Concha-Barrientos et al., 2004) to make estimates of the incidence and prevalence of NIHL in the New Zealand population and workforce. The model utilises international data, predominately the NIOSH (1998) data to establish the estimated excess risk of developing hearing loss from noise exposure given age, duration and level of exposure. In setting up the model and adapting it to the New Zealand situation we identified some key factors in the model that needed consideration and modification. Firstly we updated the relative risk estimates linking noise and hearing loss in the WHO model to provide more relevance to the New Zealand situation by using the ISO 1990-1999 international standard for the unexposed population (i.e. impairment that would be expected to result predominately from ageing). The ISO standard reports means and standard deviations for the non-noise exposed and otologically normal population and these were used to estimate the probability in the unexposed population of developing a hearing loss of 25 dBHL that would be mostly associated with ageing. In this way expected risk for each age group was obtained by taking a weighted average of these probabilities across four frequencies (1000Hz, 2000Hz, 3000Hz and 4000Hz), the same frequencies used in the WHO model and a threshold level that equates to a clinical hearing loss in New Zealand. This ISO standard is used in determinations of the extent of noise and age-related hearing loss in claims for ACC and therefore seemed appropriate for the New Zealand situation. An algorithm from Prince et al. (1997) was used to determine the relative risk of noise-induced hearing loss. This was used because it took into account the level of exposure as well as duration. The key model estimates are as follows: 1. Prevalence and incidence of hearing loss: the model shows the greater prevalence with age rising rapidly after 45-54 years of age in males and a decade later in females. The incidence of clinical (mild) hearing loss increase substantially after the age of 45 for males and 60 for females and then steadily increases in severity with age. The ability to model patterns of hearing loss in the population was an unexpected benefit of the model that was not developed further but could be a useful tool for analysing demographic patterns of hearing loss for service and policy development. 2. Key noisy sectors: Mining, Agriculture, Manufacturing and Construction are the major sectors in which there is a high proportion of workers exposed to noise levels over 85dBA (28%, 12%, 9%, 8% respectively). Among these Mining stands out as the sector with the highest exposure rates over 90dBA followed equally by the other three main sectors. These four sectors could therefore be classed as the High Noise Industries. The next group of sectors are Electrical, Trade, Transport and Services where there is a lower proportion of workers exposed to noise above 85dBA (4-5%) but relatively far smaller proportions exposed to noise over 90dBA. These sectors could be classed as Medium Noise Industries. Caution needs to be considered around the Services sector as this contains noisy environments (e.g. panelbeating) and low noise environments (e.g. libraries) and so may need to be subdivided into different noise subsectors. The other sectors Finance and Education would be classed as low noise sectors as fewer people (2%) are exposed to levels over 85dBA and less than 0.5% to noise over 90dBA. 48 | P a g e
3. Key noisy sectors, gender and ethnicity differences: The proportion of males and females exposed in these sectors is similar for Agriculture and Trades, reflecting the nature of the work and participation rates in these sectors. However, in all others a higher proportion of males are exposed to damaging levels of noise than females. There is a higher proportion of Māori exposed to noise in all the High and Medium Noise Industries compared with non-Māori, except for Agriculture where the proportions are equivalent. 4. Incidence and Prevalence of NIHL in Industries: It is estimated that prevalence rates of NIHL (cases/100,000) for males and females is greatest among the High Noise Industries in the order of Mining, Construction, Manufacturing and Agriculture. Given the participation rates in these sectors the total number of NIHL cases is greatest in Manufacturing and Construction, followed by Agriculture and Trades. 5. Trends in Incidence and Prevalence: Analysing data retrospectively and prospectively using Census data and population projections indicates that there has been an increase in the total number of cases of NIHL but a decline in the incidence rates between 1986 and 2006. The model predicts this on the basis of changes in the participation rates in sectors rather than any changes in the environmental noise levels which are assumed to remain the same across this period. Although the workforce has increased substantially (500,000workers) in this 20yr period there has been a major shift away from noisy sectors and an increase in the white collar workforce. The data are estimates only based on model predictions which themselves are based on a number of assumptions. These are discussed later in the general discussion. The next step of the project was to assess the validity of the estimates by sampling noise levels and hearing loss in the key sectors identified by the model predictions.
49 | P a g e
5.4.6 Noise levels in New Zealand Industries To verify the model predictions the research group and stakeholders consulted to determine the possible accuracy and gaps in these data. The major areas of concern were the appropriateness of the noise level criteria (85 and 90 dBA), and also the predictions of risk in the Finance sector (2%) and white-collar workers in other sectors (5%), which seemed too high given the experience of the group. In addition there was discussion around the differences that may exist between large and small companies, the latter dominating the New Zealand commercial sector. From this the group decided to gather data from all sectors and occupations including the “low noise” ones and also to investigate noise levels in relationship to company size. Dosimetry: Dosimetry was performed on a total of 529 employees (including 82 Southland farmers from a separate study by Dr David McBride) and was undertaken as close as possible over a whole working shift. Of these, most recording times were 7 hrs or longer (N=280; 52.9%, Figure 5.13), and the LAeq8hr was calculated from these data (Figure 5.13). Shorter recording times were often used by necessity because it was impractical to access all employees at once at the start of their shift.
Figure 5.13: Histogram of dosimeter recording times (rounded to the nearest hour)
The LAeq ranged from below 65dB to 113.3dB for all the employees tested across all sectors. The LCpeak ranged from 107.4dB to above 146.7dB (Figure 5.14). These two measures of noise exposure were highly correlated (r=0.732, p85dB)
(LAeq>90dB)
age85 dB(A) measured in production/agricultural workers in the agriculture, manufacturing and construction sectors in our study were notably higher than those estimated by the WHO. This had the effect of appropriately inflating the rates of exposure and thus NIHL in these sectors. The end result of these corrections was that the final predictions were quite similar between the original WHO version and ours, but now the losses are better apportioned to sectors. Furthermore, the new data enable better estimates to be made of future levels of NIHL incidence and prevalence (Objective 1C). A strong effect of the changing workforce profile was observed in that the number of New Zealanders with NIHL can be predicted to decrease from approximately 70000 in 2006 to approximately 45000 in 2040. This predicted decrease is despite the expected increase in the overall population, and due solely to reduction in occupational exposure due to the reduction in participation rate in noisy sectors. Other interventions may, of course, decrease this expected level further. Neither the original WHO model nor our revised versions shed any light on the ACC claims rate. This is not surprising given the number of social factors that may have influenced the ACC claims.
80 | P a g e
6. Non-work related noise exposure (Objective 2) In order to understand the contributors to non-work related noise hazards we have made measurements of noise in leisure environments and activities, for example the use and effect of PLDs, and have analysed the leisure noise exposure contribution in the workers studied in the Study 1.
6.1 Non-work related noise exposure in workers (Objective 2a, b) All 500 participants who were interviewed in Study 1 were asked about their leisure time noise exposure and HPE protection practices for each year of their life. Of these, 498 (99.6%) provided information on noisy leisure activities they were involved in, for how long and how often (e.g. raced cars, 2hrs every month between 1967 and 1975), if any impulse noise occurred, and whether any hearing protection was worn during the activity. Overall, 128 (25.7%) of participants reported no important exposure to leisure noise during their lifetimes, and 285 (57.2%) reported never having averaged two hours or more of leisure noise exposure per week. The 213 (42.8%) who had averaged two hours or more of leisure time noise exposure reported a wide range of years of such exposure (Min=0.5, Max=48, Mean=11.4, SD=9.4). There was a correlation between total years of any leisure noise exposure and age (Fig. 6.1a, r=0.427, p