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Contribution of hearing conservation program components to the prevention of noise-induced hearing loss (NIHL)Nicholas Heyer - BattelleThais C. Morata - NIOSH Lynne E. Pinkerton - NIOSHHyoshin 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.
Study Questions • Can HCP quality be judged by evaluating their component parts? • Can historical data be useful in conducting such evaluations? 2
The initial study (1998-2000): • Historic review of 3 plants • 2 automotive plants • 1 food processor • Covers period from 1970 through 1999 3
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 4
8-Hour TWA noise exposure • Assigned by Job Title • Used task-based noise surveys from 1990’s • Multiple stage extrapolation to earlier jobs and job titles 5
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 6
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) 7
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 9
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 10
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 11
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 12
14 Analyses
Unit of Analysis? Time between consecutive audiograms Time between Baseline & current audiograms 15
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 16
Two models of cumulative noise exposure • Variables included: • Intercept + dummy variables for plant • Baseline (time=0) hearing threshold average • Age at time of test (time=t) • Leq + Duration of employment • Results • Duration of employment better predictor of NIHL • Majority of noise exposures between 85-95 dB 17
Duration of Noise Exposure – Stratified by TWA • Tested stratified model: duration of exposure within 5 dB TWA groups duration at >=95 dB duration at <95 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 >=95 dB 18
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 <95 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 19
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 20
21 Results
NIHL model with/without HPD use Base Model HPD Model • Variables CoeffCoeff • 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 <95dB / <=6 (years) 0.60**** 0.77**** • Duration at >=95dB / <=6 (years) 0.82**** 1.04**** • Duration at <95dB / >6 (years) 0.52**** 0.79**** • Duration at >=95dB / >6 (years) 0.44*** 0.69**** • Better HPD Use (Years) ----- -0.31**** Coefficients directly reflect average threshold change per variable unit *p<0.05 **p<0.01 ***p<0.001 ****p<0.0001 22
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 23
NIHL model with/without quality audiometric monitoring Base Model HPD Model • Variables CoeffCoeff • 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 <95dB / <=6 (years) 0.60**** 0.54**** • Duration at >=95dB / <=6 (years) 0.82**** 0.77**** • Duration at <95dB / >6 (years) 0.52**** 0.44**** • Duration at >=95dB / >6 (years) 0.44*** 0.31* • Better Audiometric Monitoring (Years) ----- 0.13*** Coefficients directly reflect average threshold change per variable unit *p<0.05 **p<0.01 ***p<0.001 ****p<0.0001 24
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 25
NIHL model with/without better noise monitoring Base Model HPD Model • Variables CoeffCoeff • 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 <95dB / <=6 (years) 0.60**** 0.64**** • Duration at >=95dB / <=6 (years) 0.82**** 0.83**** • Duration at <95dB / >6 (years) 0.52**** 0.53**** • Duration at >=95dB / >6 (years) 0.44**** 0.43*** • Better Noise Monitoring (Years) ----- -0.13**** Coefficients directly reflect average threshold change per variable unit *p<0.05 **p<0.01 ***p<0.001 ****p<0.0001 26
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 27
NIHL model with/without better worker training Base Model HPD Model • Variables CoeffCoeff • 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 <95dB / <=6 (years) 0.60**** 0.63**** • Duration at >=95dB / <=6 (years) 0.82**** 0.84**** • Duration at <95dB / >6 (years) 0.52**** 0.54**** • Duration at >=95dB / >6 (years) 0.44*** 0.43*** • Better Worker Training (Years) ----- -0.04 Coefficients directly reflect average threshold change per variable unit *p<0.05 **p<0.01 ***p<0.001 ****p<0.0001 28
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 29
30 Conclusions
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 31
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 32
Future Studies • More recent HCPs should have • Better and more detailed records • More variation with good quality programs • Able to study more components 33