HEARING LOSS IN AIRCRAFT MAINTENANCE TECHNICIANS

Maya Guest1, May Boggess2

1 Faculty of Health, University of Newcastle, Australia. 2 Department of Statistics, Texas A&M University, College Station, USA

F111, a flying fuel tank

Deseal, then reseal a fuel tank

The fuel tanks were a confined space They were very cramped, with tradespeople

crawling around the braces

Health Concerns

Concerns about various symptoms experienced by workers were raised in early 1999 with symptoms including: memory loss fatigue neurological problems eg. colour vision

Deseal/reseal activities ceased in 2000 The SHOAMP Study

The SHOAMP Study

Aims compare series of general health, medical and

neurophysiological outcomes between F-111 deseal/reseal personnel and appropriate comparisons

Research Question Is there an association between adverse health

status and an involvement in F-111 deseal/reseal activities?

Study Design Retrospective cohort; postal questionnaire & exam

Study Group

Exposed group in Deseal/Reseal program at Amberley

N = 616

Two comparison groups same time, but in non-technical at Amberley

N=406

same time, but in technical at Richmond N=516

Total health exams N=1538

Measuring Hearing Thresholds

Pure-tone audiometry at the frequencies of 0.5, 1, 2, 3, 4, 6, 8 kHz for air conduction

Australian Standard AS1269.4.1998 by trained nurses

Measures threshold dB (smaller is better)

Hearing Threshold result: one person

Hearing Threshold result: one person

How to compare groups?

Treat each frequency separately

Do 95% confidence intervals for each group overlap?

Mean (95% CI) Hearing Thresholds

Distribution of Hearing Thresholds: lower frequencies

Distribution of Hearing Thresholds: higher frequencies

Problems

16 observations on single person will be correlated

Distribution heavily skewed Multiple test correction (eg. Bonferroni)

needed to control overall error rate Other factors need to be controlled for

AGE!

The ISO-7029

The ISO-7029: statistical distribution of hearing thresholds as a function of age provides by gender the expected median value of hearing thresholds relative to the median threshold at the age of 18 years and the statistical distribution above and below the median value for the range of audiometric frequencies from 125 Hz to 8000 Hz for populations of otologically normal persons of given age between 18 and 70 years

ISO 7029 healthy pop.: lower frequencies

ISO 7029 healthy pop.: higher frequencies

Quantile model?

Mean regression: coefficients estimated by minimizing the sum of the squares of the residuals

Quantile regression: coefficients estimated by minimizing the sum of the absolute values of the residuals

Quantile model?

Mean regression: 1821 Gauss showed it was ML, least variance IF residuals are normal.

Quantile regression: 1818 Laplace showed it had smaller variance than mean for certain distributions with long tails.

Central Limit Theorem is not a cure all.

Statistical Analysis: quantile model to compare to normal population Response: hearing threshold (dB) Explanatory variables:

Frequency, Age Posting category, Rank category Alcohol consumption category, Smoking status Diabetes status SSRI’s (anti-depressants), malaria medication Ringing in the ears Exposure group, civilian solvent exposure

Bootstrap standard errors: correlation within person.

Statistical Analysis: quantile model to compare to normal population Statistically significant explanatory variables:

Frequency, Age Smoking status, Diabetes status SSRI’s (anti-depressants) Ringing in the ears Exposure group

Clinically significant variables: Frequency Age

Result table------------------------------------------------------------------------------ | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+----------------------------------------------------------------_Ifrequen~10 | -1.051308 .3152126 -3.34 0.001 -1.669113 -.4335024_Ifrequen~15 | -.6029429 .3331257 -1.81 0.070 -1.255857 .0499715_Ifrequen~20 | -1.881937 .3809262 -4.94 0.000 -2.628539 -1.135336_Ifrequen~30 | .8669362 .4485159 1.93 0.053 -.0121388 1.746011_Ifrequen~40 | 7.536735 .4582282 16.45 0.000 6.638624 8.434846_Ifrequen~60 | 8.997418 .3901236 23.06 0.000 8.23279 9.762046_IfreXg~40_2 | -2.720623 .9044762 -3.01 0.003 -4.493363 -.9478817_IfreXg~60_2 | -2.208105 .8227658 -2.68 0.007 -3.820696 -.5955134_IfreXg~80_2 | -3.32165 .7481134 -4.44 0.000 -4.787925 -1.855374 age | -.4541155 .2376783 -1.91 0.056 -.9199565 .0117254 age2 | .006715 .002729 2.46 0.014 .0013662 .0120638 frequency | .2533864 .1252859 2.02 0.043 .0078305 .4989422 fa | -.0225578 .0058333 -3.87 0.000 -.0339908 -.0111248 fa2 | .0004074 .000067 6.08 0.000 .0002761 .0005387_Ismoke_ca~3 | 1.7394 .5696168 3.05 0.002 .6229713 2.855828 diabetes | 5.374096 1.413524 3.80 0.000 2.60364 8.144552 ssri | 5.298353 1.240201 4.27 0.000 2.867604 7.729102 ringing | 3.350579 .4439917 7.55 0.000 2.480371 4.220787 _cons | 18.82656 4.990258 3.77 0.000 9.045838 28.60729------------------------------------------------------------------------------

Predicted hearing median threshold

Predicted hearing median threshold

Predicted hearing median threshold

Predicted hearing median threshold

Conclusion

Need to reconsider noise exposure limits if workers are additionally exposed to chemicals

Need to reconsider the efficacy of hearing protectors in combined exposures

Take home message

No one-size-fits all in statistics

Central Limit Theorem is not a cure-all

The TUNRA Study TeamPrincipal Investigators

Catherine D’Este, Associate Professor in Biostatistics, Centre for Clinical Epidemiology & Biostatistics, The University of Newcastle.

John Attia, Senior Lecturer in Epidemiology, Centre for Clinical Epidemiology & Biostatistics, The University of Newcastle; Academic Consultant, Hunter Area Health Service

Anthony Brown, Director of Primary Health Care and Population Health, Macquarie Area Health Service; Conjoint Associate Professor, Environmental and Occupational Health, The University of Newcastle.

Julie Byles, B.Med, PhD, Professor and Director, Centre for Research and Education in Ageing (CREA), Faculty of Health, The University of Newcastle.

Associate Investigator Robert Gibberd, Associate Professor,

Centre for Clinical Epidemiology & Biostatistics, The University of Newcastle.

CEO of TUNRA Ltd Soozy Smith, PhD, TUNRA Ltd, The

University of Newcastle.

Project Support Meredith Tavener, Project Manager. Richard Gibson, Associate Lecturer in

Biostatistics (Research), Centre for Clinical Epidemiology & Biostatistics, The University of Newcastle, Project Statistician.

Maya Guest,. Research Higher Degree candidate, PhD Fellow for SHOAMP.

Questions/Thank you etc.