Contribution of hearing conservation program components to the prevention of noise-induced hearing loss (NIHL) Nicholas Heyer -Battelle Thais C. Morata -NIOSH Lynne E. Pinkerton -NIOSH Hyoshin Kim -Battelle Steve Sinclair - UC Northridge

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Contribution of hearing conservation program
components to the prevention of noise-induced
hearing loss (NIHL) Nicholas Heyer
- Battelle Thais C. Morata - NIOSH Lynne E.
Pinkerton - NIOSH Hyoshin Kim - Battelle Steve
Sinclair - UC Northridge Scott E. Brueck
- NIOSH Daniel Stancescu - NIOSH Mary Prince
Panaccio - NIOSH Martha A. Waters
- NIOSH Cherie F. Estill - NIOSH John R. Franks
- NIOSH
The findings and conclusions in this presentation
are those of the authors and do not necessarily
represent the views of the National Institute for
Occupational Safety and Health.
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Study Questions

• Can HCP quality be judged by evaluating their
  component parts?
• Can historical data be useful in conducting such
  evaluations?

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The initial study (1998-2000)

• Historic review of 3 plants
• 2 automotive plants
• 1 food processor
• Covers period from 1970 through 1999

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Four Primary Sources of Data

• Historic noise exposure surveys
• Historic audiometric test records
• Employee work histories
• Survey focus group information on history of
  hearing conservation programs

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8-Hour TWA noise exposure

• Assigned by Job Title
• Used task-based noise surveys from 1990s
• Multiple stage extrapolation to earlier jobs and
  job titles

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Linking noise exposure and NIHL

• Merged historical audiometric testing data with
  work histories (job titles)
• Excellent match for food processor
• Poor match for two automotive plants
• More than half of all audiometric testing
  conducted prior to initial work history
• Possibly due to migration of workers from other
  plants

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Creating HCP component variables

• History based on worker focus groups
• Four historical HCP components created
• use of hearing protective devices (HPD)
• Audiometric testing frequency (calculated)
• Frequency responsiveness of noise monitoring
• Worker education (at shop meetings testing)

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Concerns about the data

• Noise Exposure Accuracy of TWAs
• Multiple stage extrapolation limited data
  points
• Audiometric Thresholds
• Workplace audiograms known to be variable
• Duration of exposure
• Missing work histories loss of data
• Quality measures for HCP components
• Memory based few historical documents

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Cumulative noise exposure

• Leq cumulative measure of equivalent noise
  energy
• 3 dB increase in TWA doubles exposure
• Does not accommodate uncertainty
• Historical estimates of duration better than
  intensity
• Test alternative measure
• Duration of exposure within 5 dB strata
• Weightings determined by the data

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Audiometric threshold

• Not addressing hearing per se
• No need to define a threshold shift
• No censorship of data
• Use a sensitive yet robust measure
• Use most sensitive frequencies
• Incorporate bilateral measures
• Average across multiple thresholds
• Solution
• Average at 3, 4 6 kHz across both ears

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Missing work histories

• Reduced data vs. data uncertainty
• Do missing work histories migration between
  plants?
• Guessing could introduce large errors
  considered too risk
• Conclusion Exclude audiograms with missing work
  histories

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HCP component measures

• Used dichotomous variables for all component
  quality measures
• Used better vs. worse categorization
• Fortunately these varied by time and plant
• Did not necessarily improve over time
• The four components did not necessarily vary
  together

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Unreliable Responders

• Extreme cases of threshold improvement
• Some clustering by facility and time
• Remove person not audiogram
• Average improvement of gt15 dB
• From baseline audiogram
• From immediately preceding audiogram
• 5 of subjects removed

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Analyses
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Time between consecutive audiograms
Unit of Analysis?
Time between Baseline current audiograms
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Unit of Analysis

• Time from Baseline (1st valid) Audiogram
• Reasons
• Better captures cumulative exposure
• Less dependent on accuracy of time cut-points for
  HCP quality measures
• Less dependent on latency of impact

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Two models of cumulative noise exposure

• Variables included
• Intercept dummy variables for plant
• Baseline (time0) hearing threshold average
• Age at time of test (timet)
• Leq Duration of employment
• Results
• Duration of employment better predictor of NIHL
• Majority of noise exposures between 85-95 dB

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Duration of Noise Exposure Stratified by TWA

• Tested stratified model duration of exposure
  within 5 dB TWA groups
• duration at gt95 dB
• duration at lt95 dB
• Baseline test 1 .test 2 .test 3 ..
  test n
• Stratified duration for nth audiometric test
  period for this subject
• Only strata significantly different from total
  exposure duration was for gt95 dB

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Duration of Noise Exposure Stratified by TWA
and years

• Model duration of exposure by TWA and duration
  groups (over x years in red)
• duration at 95 dB
• duration at lt95 dB
• Baseline test 1 .test 2 .test 3 ..
  test n
• Two-way stratified duration for nth audiometric
  test period for this subject
• Observed change in the dose-response relationship
  after 6 years

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Adding terms for HCP quality

• HCP quality term entered separately for each
  component
• Duration in Worse quality HCP
  (red) does not add to term
• Duration in Better
  quality HCP
• Baseline test 1 .test 2 .test 3 ..
  test n
• Duration in Better quality HCP for nth
  audiometric test period for this subject
• Interaction terms yielded incoherent results

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Results
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NIHL model with/without HPD use

• Base Model HPD Model
• Variables Coeff Coeff
• Intercept -1.89 -2.18
• Plant X -1.02 0.62
• Plant Y -0.39 -0.03
• Reflecting Individual Characteristics
• Baseline Threshold -0.03 -0.03
• Age at Test 0.08 0.08
• Reflecting NIHL
• Duration at lt95dB / lt6 (years) 0.60
  0.77
• Duration at gt95dB / lt6 (years) 0.82
  1.04
• Duration at lt95dB / gt6 (years) 0.52
  0.79
• Duration at gt95dB / gt6 (years) 0.44
  0.69
• Better HPD Use (Years) ----- -0.31
• Coefficients directly reflect average threshold
  change per variable unit
• plt0.05 plt0.01 plt0.001
  plt0.0001

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Hearing Protective Devices

• HPD programs effective in reducing NIHL
• Reported enforcement of HPD policies
• Did not use information on types of devices
• No consensus on relative effectiveness of
  different devices
• Dependent on use and acceptance of the various
  devices

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NIHL model with/without quality audiometric
monitoring

• Base Model HPD Model
• Variables Coeff Coeff
• Intercept -1.89 -2.18
• Plant X -1.02 0.85
• Plant Y -0.39 -0.43
• Reflecting Individual Characteristics
• Baseline Threshold -0.03 -0.03
• Age at Test 0.08 0.08
• Reflecting NIHL
• Duration at lt95dB / lt6 (years) 0.60
  0.54
• Duration at gt95dB / lt6 (years) 0.82
  0.77
• Duration at lt95dB / gt6 (years)
  0.52 0.44
• Duration at gt95dB / gt6 (years) 0.44 0.31
• Better Audiometric Monitoring (Years)
  ----- 0.13
• Coefficients directly reflect average threshold
  change per variable unit
• plt0.05 plt0.01 plt0.001
  plt0.0001

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Audiometric Testing

• Apparent reverse association (more testing, more
  threshold change detected)
• Used mean time between tests
• Need better descriptors
• Possibly due to artifacts
• People with poor hearing may resist initial
  testing
• Longer term employees supervisors may resist
  testing

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NIHL model with/without better noise monitoring

• Base Model HPD Model
• Variables Coeff Coeff
• Intercept -1.89 -2.09
• Plant X -1.02 0.48
• Plant Y -0.39 -0.31
• Reflecting Individual Characteristics
• Baseline Threshold -0.03 -0.03
• Age at Test 0.08 0.08
• Reflecting NIHL
• Duration at lt95dB / lt6 (years) 0.60
  0.64
• Duration at gt95dB / lt6 (years) 0.82
  0.83
• Duration at lt95dB / gt6 (years) 0.52
  0.53
• Duration at gt95dB / gt6 (years) 0.44
  0.43
• Better Noise Monitoring (Years) ----- -0.13
• Coefficients directly reflect average threshold
  change per variable unit
• plt0.05 plt0.01 plt0.001
  plt0.0001

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Noise Monitoring

• Apparent effect - BUT
• Noise Exposure coefficients basically same
• Larger change in plant coefficient
• No variation by time within plants
• Only one plant had a better program
• Conclusion Effect due to confounding

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NIHL model with/without better worker training

• Base Model HPD Model
• Variables Coeff Coeff
• Intercept -1.89 -1.87
• Plant X -1.02 -0.99
• Plant Y -0.39 -0.47
• Reflecting Individual Characteristics
• Baseline Threshold -0.03 -0.03
• Age at Test 0.08 0.08
• Reflecting NIHL
• Duration at lt95dB / lt6 (years) 0.60
  0.63
• Duration at gt95dB / lt6 (years) 0.82
  0.84
• Duration at lt95dB / gt6 (years) 0.52
  0.54
• Duration at gt95dB / gt6 (years)
  0.44 0.43
• Better Worker Training (Years) ----- -0.04
• Coefficients directly reflect average threshold
  change per variable unit
• plt0.05 plt0.01 plt0.001
  plt0.0001

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Worker Training

• Weak non-significant association
• None of the programs were very satisfactory
• Sporadic at best
• Better could only be used as a relative term
• Conclusion not enough variability

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Conclusions
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Usefulness of historic data

• Were able to obtain interpretable results
• Achieved some detail in modeling noise
• Effect of HPD use clearly demonstrated
• However, limitations included
• Lack of variation
• No quality programs for some components
• Sometimes no variation in time within plants
• Lack of good measures
• Need more details in quality and time frame

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Modeling approach

• Leq may not be suitable for historic studies
• Too dependent on accuracy of TWA
• Stratified duration shows possibilities
• Explained much more NIHL
• Shape of dose response could be explored
• Useful for other time dependent variables
• E.g. Quality components

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Future Studies

• More recent HCPs should have
• Better and more detailed records
• More variation with good quality programs
• Able to study more components

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