Catherine Trask 2008

1. Balancing Efficiencies & Tradeoffs:Evaluating EMG Exposure Assessment for Low Back Injury Risk Factors in Heavy Industry Catherine Trask 2008

2. ‘Solving’ Back Injury • Back injury is a prevalent and expensive problem, particularly in heavy industry

3. Thesis Objectives • How should exposure be measured? • For what duration? • Who should be measured? • How many times should they be measured?

4. Thesis Chapters • How should exposure be measured? • For what duration? • Who should be measured? • How many times should they be measured? • Chapters 4 and 5 • Chapter 6 • Chapter 7 • Chapter 7

5. Thesis Chapters • Introduction to exposure assessment • Introduction to methods • How should exposure be measured? • For what duration? • Who should be measured? • How many times should they be measured? • Chapters 1 • Chapter 2 and 3 • Chapters 4 and 5 • Chapter 6 • Chapter 7 • Chapter 7

6. Introduction to Exposure Assessment

7. Direct Measure using electronic devices Observation by trained experts Self-report by the workers Available Exposure Assessment Methods

8. Direct Measure Observation Self-report Continuum of Methods Wider scope – ‘big picture’ Subjective Inexpensive More people Longer time High-resolution – lots of detail Objective Expensive Few people Short time

9. Data Collection

10. Worker Recruitment • Contacted workers in heavy industry with accepted back injury claims • Contacted employer to gain access to the worksite • Recruited co-workers at each worksite • 126 individuals • Repeated measures • 223 measurement days

11. Direct Measure by electronic devices Observation by trained experts Self-report by the workers The Measurement Day • Measured all methods concurrently • Full shift

12. Self-report Back Injury Risk Factors for Back Injury:Self-Report • Asked for the amount of time in each activity • Used pictographs for most questions • Working Postures Manual Materials Handling

13. Observation Back Injury Risk Factors for Back Injury:Observation • ‘Snapshots’ of 15 variables at 1 minute intervals • Full-shift, excluding breaks • Working Postures Manual Materials Handling

14. Whole body vibration Seat pad accelerometer Inclinometer Back muscle activity EMG Mean 90th % Cumulative RCM Back Injury Risk Factors for Back Injury:Direct Measurement • Working Postures Manual Materials Handling

15. Chapter 4: Measuring low back injury risk factors in challenging work environments: an evaluation of cost and feasibility A version of this chapter has been published. Trask, C., Teschke, K., Village, J., Chow, Y., Johnson, P., Luong, N., and Koehoorn, M. (2007). Evaluating methods to measure low back injury risk factors in challenging work environments. American Journal of Industrial Medicine 50(9):687-96.

16. Cost and Feasibility • Success rate = successful measurement/ attempted measurement • Cost ($CDN) per successful measurement

17. Measurement Success Rates

18. Measurement Costs (per successful measurement)

19. Conclusions • Inverse relationship between cost and feasibility • Industrial environments are demanding on mechanical equipment • Cold, dusty, wet, explosive, • Rough handling/vibration • Consider costs and feasibility when planning field work!

20. Chapter 5: Predicting exposure for mean, 90th percentile, and cumulative EMG activity in heavy industry A version of this chapter has been submitted for publication. Trask, C., Teschke, K., Morrison, J., Village, J., Johnson, P., Koehoorn, M. (2008) Predicting Exposure for Mean, 90th Percentile, and Cumulative EMG Activity in Heavy Industry. Submitted February 2008 to: Applied Ergonomics.

21. Low Back EMG Observation or self report Modeling determinants of exposure %RC = β1(observed variable 1) + β2(observed variable 2) + β3(observed variable 3)…

22. Observation-based Model

23. Self-report Model

24. Model Performance • Observation based model • Self-report based model

25. Conclusion Is this enough to conduct injury research? • Chemical exposure studies often predict 30-60% • Many studies using self-report and observation have found a relationship with back injury in the past • Epidemiology often uses categorical exposure variables, not continuous variables • One can predict some of the variability in EMG by asking a few questions or observing a few exposures • Tradeoff is in measuring more individuals, more times

26. Chapter 6: How long is long enough? Selecting efficient sampling durations for low-back EMG assessment A version of this chapter has been accepted for publication. Trask, C., Koehoorn, M., Village, J., Johnson, P., Teschke, K. (2008) How long is long enough? Evaluating sampling durations for low-back EMG assessment. Journal of Occupational and Environmental Hygiene. Submission number: JOEH-07-0094.R1.

27. Sampling Duration Rationale • Direct measurements were made for a whole shift • Do you really need to measure a whole shift? • How much information is lost if you measure a portion of the shift?

28. Selecting sampling durations • Compared 7 different sampling durations of the same work shift: • Whole shift (5.5 to 7.5 hours) • 4 hours • 2 hours • 1 hour • 10 minute • 2 minute • 2 shifts • Re-sampled post hoc • Randomized start time

29. Whole shift 4 hour 2 hour 1 hour Sampling durations Green = right back muscles Red = left back muscles

30. Absolute error between sampling durations

31. Conclusion • 8% error for 4-hour and 14% error for 2-hour durations: reasonable estimates • 1 hour or less produces very large errors • Balance cost with data precision and sample size • Shorter duration but more workers measured

32. Chapter 7: Optimizing sampling strategies: components of low-back EMG variability in five heavy industries A version of this chapter has been submitted for publication. Trask, C., Teschke, K., Morrison, J., Koehoorn, M. (2007) Optimizing Sampling Strategies: Components of Low-Back EMG Variability in Five Heavy Industries. Submitted February 2008 to: Occupational and Environmental Medicine. Submission number: OEM/2008/039826

33. Components of Variability Rationale • How many individuals? • How many repeats? • (How) should we group measurements? • Grouping schemes make for less attenuation of an exposure-response relationship • Attenuation can be estimated based on the exposure data, even when the response is not measured

34. Response Exposure Sample Exposure-ResponseRelationship Back injury outcome = intercept + β1(exposure variable 1)

35. Grouping Schemes • No grouping • Job title • Company • Industry • Post hoc ranking of industry/job title groups

36. Percentage of true E-R by grouping scheme

37. Workers per group (k) required for 95% of true E-R

38. Conclusion • The post hoc grouping scheme was the most efficient grouping scheme • Lowest estimated attenuation • Lowest number of measurements required • Measurement and recruitment challenges mean one should aim for a larger number of measurements • Attenuation isn't everything when selecting a sampling strategy – want to choose sample size to be robust

39. Summary There are always tradeoffs in exposure assessment • Lots of decisions to make! • How you ‘tip the scales’ toward more samples or more precision depends on the purpose of the study and the characteristics of the population • Contribution is in the ways of framing these questions and starting to quantify the answers

40. Acknowledgements Participating Workers and Worksites WorkSafe BC Michael Smith Foundation for Health Research CIHR Bridge Fellowship Program Mieke Koehoorn Kay Teschke Jim Morrison Judy Village Pete Johnson Jim Ploger Yat Chow Kevin Hong Nancy Luong Melissa Knott James Cooper

41. Questions