1. 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

2. F111, a flying fuel tank

3. Deseal, then reseal a fuel tank The fuel tanks were a confined space They were very cramped, with tradespeople crawling around the braces

4. 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

5. 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

6. 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

7. 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)

8. Hearing Threshold result: one person

10. How to compare groups? Treat each frequency separately Do 95% confidence intervals for each group overlap?

11. Mean (95% CI) Hearing Thresholds

12. Distribution of Hearing Thresholds: lower frequencies

13. Distribution of Hearing Thresholds: higher frequencies

14. 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!

15. 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

16. ISO 7029 healthy pop.: lower frequencies

17. ISO 7029 healthy pop.: higher frequencies

18. 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

19. 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.

20. 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.

21. 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

22. 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 ------------------------------------------------------------------------------

23. Predicted hearing median threshold

27. 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

28. Take home message No one-size-fits all in statistics Central Limit Theorem is not a cure-all

29. The TUNRA Study Team Principal 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.

30. Questions/Thank you etc.