Hearing Loss Data Discussion Instructions: Please read a NIOSH study “Trends in worker hearing loss by industry sector, 1981-2010”, published in the Americ

Hearing Loss Data Discussion Instructions: Please read a NIOSH study “Trends in worker hearing loss by industry sector, 1981-2010”, published in the American Journal of Industrial Medicine (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4557728/pdf/nihms718189.pdf). Using your own words and critical thinking skills, discuss (15 points) Why the prevalence and incidence of hearing loss for all industries combined did not change much during 1981-2010 (about 1-2%), but the adjusted risk decreased significantly (46%)? (15 points) Why the prevalence for hearing loss among workers in Healthcare and Social Assistance were increasing, and what factors may have contributed to? HHS Public Access
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Am J Ind Med. Author manuscript; available in PMC 2015 December 01.
Published in final edited form as:
Am J Ind Med. 2015 April ; 58(4): 392–401. doi:10.1002/ajim.22429.
Trends in Worker Hearing Loss by Industry Sector, 1981–2010
Elizabeth A. Masterson, PhD, CPH, COHC, NIOSH*, James A. Deddens, PhD, NIOSH,
Christa L. Themann, MA, CCC-A, NIOSH, Stephen Bertke, PhD, NIOSH, and Geoffrey M.
Calvert, MD, MPH, NIOSH
National Institute for Occupational Safety and Health (NIOSH), Centers for Disease Control and
Prevention, Cincinnati, Ohio
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Abstract
Background—The purpose of this study was to estimate the incidence and prevalence of hearing
loss for noise-exposed U.S. workers by industry sector and 5-year time period, covering 30 years.
Methods—Audiograms for 1.8 million workers from 1981–2010 were examined. Incidence and
prevalence were estimated by industry sector and time period. The adjusted risk of incident
hearing loss within each time period and industry sector as compared with a reference time period
was also estimated.
Results—The adjusted risk for incident hearing loss decreased over time when all industry
sectors were combined. However, the risk remained high for workers in Healthcare and Social
Assistance, and the prevalence was consistently high for Mining and Construction workers.
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Conclusions—While progress has been made in reducing the risk of incident hearing loss
within most industry sectors, additional efforts are needed within Mining, Construction and
Healthcare and Social Assistance.
Keywords
occupational hearing loss; material hearing impairment; hazardous noise; noise-induced hearing
loss; surveillance; trends; prevalence; incidence
INTRODUCTION
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Occupational hearing loss (OHL) is the most common work-related illness in the United
States [NIOSH, 2013a]. It most often results from chronic exposure to hazardous noise (≥85
dBA) but can be caused by a single instantaneous high noise exposure or exposure to
ototoxic chemicals [Nelson et al., 2005]. Approximately 22 million U.S. workers are
exposed to hazardous noise at work [Tak et al., 2009]. Noise regulations exist in most
industries to prevent or ameliorate hazardous occupational noise. However, noise exposure
*
Correspondence to: Elizabeth A. Masterson, PhD, CPH, COHC, NIOSH, Division of Surveillance, Hazard Evaluations and Field
Studies, National Institute for Occupational Safety and Health, 1090 usculum Avenue, MS-R17, Cincinnati, OH 45226.
EMasterson@cdc.gov.
Conflict of interest statement: The authors have no conflicts of interest to declare.
Disclaimer: The findings and conclusions in this article have not been formally disseminated by the National Institute for
Occupational Safety and Health and should not be construed to represent any agency determination or policy.
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limits and mandated prevention efforts vary by industry [NIOSH, 1998]. Some industries,
such as agriculture, have no noise regulation at all [Suter, 2003]. Hearing loss is permanent,
potentially debilitating, and affects workers both at home and on the job [Hetu et al., 1995;
Morata et al., 2005; Seidman and Standring, 2010]. However, OHL resulting from noise and
ototoxic chemical exposures is entirely preventable [Themann et al., 2013a,b].
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The level of hearing loss deemed acceptable in establishing U.S. noise regulations is based
on preserving hearing for conversational speech, defined by the National Institute for
Occupational Safety and Health (NIOSH) as an average hearing level of 25 dBor less
(better) at the frequencies 1,000, 2,000, 3,000, and 4,000 Hertz (Hz). When hearing ability
exceeds the 25 dB average, a worker is said to have developed a “material hearing
impairment.” No known studies have examined whether current regulations are effectively
preventing material hearing impairment among U.S. workers and few studies have examined
trends in worker hearing loss.
Daniell et al. [2002] reported that workers’ compensation claims for hearing loss doubled
between 1984 and 1991 and multiplied by twelve by 1998 in Washington State. They
postulated that the large increase was likely due to reporting phenomena. McCall and
Horwitz [2004] reported that workers’ compensation claims decreased in Oregon between
1984 and 1998 following improvements in state occupational safety and health standards.
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Tak and Calvert [2008] examined the overall trend in the prevalence of self-reported hearing
difficulty among workers during 1997–2003 and found that the prevalence slowly decreased
until 2000, but then fluctuated thereafter. Bureau of Labor Statistics (BLS) data has
indicated a gradual reduction in the incidence of Occupational Safety and Health
Administration (OSHA) standard threshold shifts in hearing during 2004–2007 [Hager,
2006, 2007, 2008, 2009]. However, BLS estimates must be interpreted with caution, in part
since certain types of employers are not represented [Leigh and Miller, 1998], and economic
incentives may encourage under-reporting [Leigh and Miller, 1998; Azaroff et al., 2002].
NIOSH established the OHL Surveillance Project in 2009 to address the lack of a national
surveillance program for OHL. Through partnerships with audiometric testing service
providers and others, hereafter referred to as providers, NIOSH collects de-identified worker
audiograms originally completed for regulatory compliance purposes, including historical
audiograms.
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The purpose of this study was to estimate the incidence and prevalence of material hearing
impairment, hereafter referred to as hearing loss, for noise-exposed U.S. workers by industry
sector and time period using NIOSH OHL Surveillance Project data. The risk of incident
hearing loss as compared with a reference time period was also estimated. No previous
studies have examined 30 years of hearing loss prevalence, incidence and risk by industry
sector.
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MATERIALS AND METHODS
Study Design and Population
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This longitudinal study of a retrospective cohort estimated and compared the prevalence and
incidence of U.S. worker hearing loss by industry sector and time period. Worker
audiograms and related information from the NIOSH OHL Surveillance Project were used
and are described in detail by Masterson et al. [2013]. In short, de-identified audiometric
tests previously conducted by providers predominantly for workers exposed to high noise
(≥85 dBA) were shared with NIOSH and assigned arbitrary employee IDs. Male and female
workers ages 18 to 75 years during the years 1981–2010 and meeting study quality
standards (defined below under Audiogram Inclusion and Exclusion Criteria) were included.
We chose this time period because there were insufficient numbers of audiograms prior to
1981 and 2010 was the latest year of data available. The data were analyzed in 5-year blocks
to increase sample size in industry sectors and power to detect trends:
•
1981–1985 (Period 1)
•
1986–1990 (Period 2)
•
1991–1995 (Period 3)
•
1996–2000 (Period 4)
•
2001–2005 (Period 5)
•
2006–2010 (Period 6)
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It was necessary for the estimation of incidence to establish that each worker was free of
hearing loss before he/she could become an incident case. Incidence was therefore counted
beginning in Period 2. After case determination, only the last audiogram for each worker in
each time period was retained for the analyses, and was used to determine worker age. Since
all audiograms were de-identified, this project was determined by the NIOSH Institutional
Review Board to be research not involving human subjects.
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Beginning with 8,597,503 U.S. audiograms for 2,198,124 workers ages 18–75 during 1981–
2010, 2,338,034 audiograms (27%) were eliminated from the analysis due to the quality
deficiencies identified in Table I (additional description in the Audiogram Inclusion and
Exclusion Criteria section). Next, we retained only the last audiogram for each worker in
each time period (3,314,799 audiograms eliminated, no workers eliminated). Our final study
sample contained 2,944,670 audiograms for 1,816,812 workers at 33,572 companies, and
was used for the prevalence analyses. A subset of the sample, 560,320 workers with at least
two valid audiograms, was used for the incidence analyses, detailed under Statistical
Analyses.
Materials
The results of worker audiograms were used to identify hearing loss. Audiometric records
included date of birth, gender, threshold values at frequencies 500, 1,000, 2,000, 3,000,
4,000, 6,000, and 8,000 Hz, and North American Industry Classification System (NAICS)
codes [U.S. Department of Commerce, The Kraus Organization Limited, 2007; U.S. Census
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Bureau, 2011]. NAICS codes range from two-digit to six-digit numbers and industry
specificity increases with each digit. Date of hire and occupation were not available for most
cases. Education, race, income, smoking status, noise and ototoxic chemical exposure
information were also not available.
Audiogram Inclusion and Exclusion Criteria
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Study audiograms were originally collected for non-research purposes and could contain
incomplete or inaccurate information [Laurikkala et al., 2000]. The entire audiogram was
excluded if the gender, year of birth, NAICS code or geographical region was missing and
this information could not be imputed from another audiogram for the same worker. Missing
birth months and days were imputed as July and 15, respectively, and July 1 was imputed if
both fields were missing. By restricting the age range to 18–75, audiograms with unlikely
birth years were excluded. Audiometric results for ears with missing thresholds at
frequencies necessary for calculations of hearing loss or evaluations of quality were
excluded.
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Utilizing methods developed by senior NIOSH audiologists, we excluded audiograms that
did not meet additional quality standards or displayed attributes indicating that hearing loss
may be due to pathology or non-occupational factors. These methods and their rationale are
described in detail in Masterson et al. [2013]. Briefly, we removed audiograms with
threshold values depicting negative slope in either ear, indicating that background noise may
have been excessive during testing, or the presence of middle ear pathology [Suter, 2002].
We also eliminated audiograms for ears with unlikely threshold values suggesting the
presence of testing errors, and excluded the affected ear for audiograms with threshold
values of “no response at maximum value”. If large inter-aural differences were identified
such that a threshold at a given frequency in one ear differed by 40 dB or more from a
threshold at the same frequency in the other ear, then the entire audiogram was excluded.
Differences of this magnitude are rarely due primarily to occupational noise exposure
[Arslan and Orzan, 1998], and without proper masking, inaccurate thresholds may be
recorded for the poorer ear [Martin, 2009].
Statistical Analysis
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The independent variables were time period and industry sector. Industry sectors were the
NIOSH Occupational Research Agenda industry sectors [NIOSH, 2013b] with two
modifications due to small group sizes: (i) Public Safety was combined with Services, and
(ii) Oil and Gas Extraction was combined with Mining. The worker’s industry sector was
based on the assigned NAICS code. The outcome was hearing loss, using the NIOSH
definition of material hearing impairment: A pure-tone average threshold across frequencies
1,000, 2,000, 3,000 and 4,000 Hz of 25 dB or more in either ear [NIOSH, 1998]. After
determining incident cases (discussed below), audiograms for years 1981–1985 (Period 1)
were combined and the last audiogram for each worker was retained. This process was
repeated for the other time periods to ensure each worker was only counted once during each
time period. A worker could have audiograms in more than one time period.
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Audiograms from Period 1 were used to determine which cases of hearing loss in Period 2
were incident. Workers with hearing loss in Period 1 were not included in Period 2 or later
periods. Workers with hearing loss in Period 2 were not included in Period 3 or later
periods, and this process was repeated for the other time periods. A worker counted as an
incident case had to have a prior audiogram without hearing loss. A worker counted as a
non-case also needed a prior audiogram without hearing loss to ensure all workers had an
equal chance of being an incident case. We also ensured that there were no incident cases
who lost their hearing within their first time period, for example, a worker’s first audiograms
appeared in Period 4 and did not have hearing loss in 1997, but developed a hearing loss by
1999.
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Six descriptive categories were used for worker age. States of worker employment were
condensed into six geographical regions based on the U.S. Embassy region groupings [U.S.
Embassy, 2008]. Providers were assigned arbitrary numbers. SAS version 9.3 statistical
software was utilized for analyses (SAS Institute Inc., Cary, NC).
Prevalence and incidence percentages were estimated for each industry sector and time
period. Probability ratios (PRs) for incident hearing loss were estimated using the SAS®
genmod procedure for log-binomial regression [Spiegelman and Hertzmark, 2005]. PRs
were calculated since some estimates were expected to exceed 10% and odds ratios should
only be utilized for rare outcomes [Deddens and Petersen, 2008], and for ease of
interpretation. The Repeated Statement was used to account for multiple observations for
one worker. The log-binomial regression models did not converge and the copy method was
used to estimate PRs [Deddens and Petersen, 2008].
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The PRs, which identify the risk of becoming an incident case in each time period as
compared with the reference time period, were adjusted for gender, age group, region and
provider. When all industry sectors were combined, the PRs were also adjusted for industry
sector. Confidence intervals were also calculated. The Quasi-Akaike Information Criterion
(QIC) statistics were reviewed to determine if there was a significant interaction among the
patterns of hearing loss for the industry sectors over time.
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Period 2 was designated as the PR reference time period for all industry sectors except
Mining, Quarrying, and Oil and Gas Extraction (hereafter referred to as Mining) and
Healthcare and Social Assistance, due to insufficient sample size in Period 2. Periods 5 and
4 were used as reference time periods for these industry sectors, respectively. A PR >1
indicated that the risk was higher in the current time period than in the reference time period.
A PR
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