Balancing Efficiencies & Tradeoffs: Evaluating EMG Exposure Assessment for Low Back Injury Risk...
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Balancing Efficiencies & Tradeoffs:Balancing Efficiencies & Tradeoffs:
Evaluating EMG Exposure Evaluating EMG Exposure Assessment for Low Back Injury Risk Assessment for Low Back Injury Risk
Factors in Heavy IndustryFactors in Heavy Industry
Catherine Trask 2008Catherine Trask 2008
Back injury is a prevalent and expensive problem, particularly in heavy industry
‘‘Solving’ Back InjurySolving’ Back Injury
How should exposure be measured?
For what duration? Who should be
measured? How many times should
they be measured?
Thesis ObjectivesThesis Objectives
Thesis ChaptersThesis Chapters
Chapters 4 and 5
Chapter 6 Chapter 7 Chapter 7
How should exposure be measured?
For what duration? Who should be
measured? How many times should
they be measured?
Thesis ChaptersThesis Chapters
Chapters 1
Chapter 2 and 3 Chapters 4 and 5
Chapter 6 Chapter 7 Chapter 7
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?
Introduction to Exposure Introduction to Exposure AssessmentAssessment
Available Exposure Available Exposure Assessment MethodsAssessment Methods
Direct Measure
using electronic devices
Observation
by trained experts
Self-report
by the workers
Continuum of MethodsContinuum of Methods
High-resolution – lots of detail
Objective
Expensive
Few people
Short time
Wider scope – ‘big picture’
Subjective
Inexpensive
More people
Longer time
Direct Measure Observation Self-report
Data CollectionData Collection
Worker RecruitmentWorker 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
The Measurement DayThe Measurement Day
Direct Measure
by electronic devices
Observation
by trained experts
Self-report
by the workers
Measured all methods concurrently Full shift
Back Back InjuryInjuryManual Materials
Handling
Risk Factors for Back Risk Factors for Back Injury:Injury:
Self-ReportSelf-Report
Working
Postures
Asked for the amount of time in each activity Used pictographs for most questions
Self-report
Back Back InjuryInjuryManual Materials
Handling
Risk Factors for Back Risk Factors for Back Injury:Injury:
ObservationObservation
Working
Postures
‘Snapshots’ of 15 variables at 1 minute intervals Full-shift, excluding breaks
Observation
Back Back InjuryInjury
Manual Materials Handling
Risk Factors for Back Injury:Risk Factors for Back Injury:Direct MeasurementDirect Measurement
Working
Postures
Inclinometer
Whole body
vibration
Seat pad accelerometer
Mean90th %
CumulativeRCM
EMGBack
muscle activity
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, 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 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 low back injury risk factors in challenging work environments. American Journal of Industrial Medicine 50(9):687-96.Industrial Medicine 50(9):687-96.
Cost and FeasibilityCost and Feasibility
Success rate = successful measurement/ attempted measurement
Cost ($CDN) per successful measurement
Measurement Success Measurement Success RatesRates
41.9%
61.9%
89.2%97.8% 99.6%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
Vibration EMG Inclinometer Interview Observation
measurement method
su
ce
ss
ra
te (
%)
Measurement Costs Measurement Costs (per successful (per successful measurement)measurement)
$544.76
$320.91
$192.05
$21.70
$213.52
$0.00
$100.00
$200.00
$300.00
$400.00
$500.00
$600.00
Vibration EMG Inclinometer Interview Observation
measurement method
cost
per
mea
sure
($C
DN
)
ConclusionsConclusions
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!
A version of this chapter has been submitted for publication. Trask, C., Teschke, K., 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 Morrison, J., Village, J., Johnson, P., Koehoorn, M. (2008) Predicting Exposure for Mean, 90th Percentile, and Cumulative EMG Activity in Heavy Industry. Submitted Mean, 90th Percentile, and Cumulative EMG Activity in Heavy Industry. Submitted February 2008 to: Applied Ergonomics.February 2008 to: Applied Ergonomics.
Chapter 5: Predicting exposure for Chapter 5: Predicting exposure for mean, 90th percentile, and cumulative mean, 90th percentile, and cumulative
EMG activity in heavy industryEMG activity in heavy industry
Modeling determinants of Modeling determinants of exposure exposure
%RC = %RC = ββ1(observed variable 1) + 1(observed variable 1) + ββ2(observed 2(observed variable 2) + variable 2) + ββ3(observed variable 3)…3(observed variable 3)…
0
20
40
60
80
100
120
140
0 10 20 30 40 50 60 70
Low Back EMG
Observation or self report
Observation-based ModelObservation-based Model
Variable Mean EMG (in %RC)
β (slope) p
Intercept (average for all subjects) 19.8
Standing (% time) 0.115 <0.001*
Trunk position >60o (% time) 0.612 .0018*
4.5-10kg load in hands (% time) 0.910 <0.001*
10-20 kg load in hands (% time) 0.325 .0641
Self-report ModelSelf-report Model
Variable Mean EMG (in %RC)
Β (slope) p
Intercept (average of subjects) 33.4
Sitting (% time) -0.181 0.0023*
Industry
Construction industry 14.8 0.0054*
Forestry industry 13.3 0.0109*
Wood product industry 4.44 0.369
Warehousing industry 8.75 0.1024
Transportation industry 0 Reference
Model PerformanceModel Performance
variance explained,
47%
not explained,
53%
Self-report based modelSelf-report based model Observation based model Observation based model
variance explained,
36%not
explained, 64%
ConclusionConclusion
Is this enough to conduct injury research?Is this enough to conduct injury research? Chemical exposure studies often predict 30-60% Chemical exposure studies often predict 30-60% Many studies using self-report and observation have Many studies using self-report and observation have
found a relationship with back injury in the pastfound a relationship with back injury in the past Epidemiology often uses categorical exposure Epidemiology often uses categorical exposure
variables, not continuous variablesvariables, not continuous variables One can predict some of the variability in EMG by One can predict some of the variability in EMG by
asking a few questions or observing a few asking a few questions or observing a few exposuresexposures
Tradeoff is in measuring more individuals, more Tradeoff is in measuring more individuals, more timestimes
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.
Chapter 6: How long is long enough? Chapter 6: How long is long enough? Selecting efficient sampling durations Selecting efficient sampling durations
for low-back EMG assessmentfor low-back EMG assessment
Sampling Duration RationaleSampling 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?
Selecting sampling durationsSelecting sampling durations
Compared 7 different sampling durations of the same work shift:
Whole shift (5.5 to 7.5 hours)4 hours2 hours1 hour10 minute2 minute2 shifts
Re-sampled post hocRandomized start time
Sampling durationsSampling durations
Whole shift
4 hour
1 hour
2 hour
Red = left back musclesGreen = right back muscles
Absolute errorAbsolute error between sampling durations between sampling durations
1.64789991.0148922 1.4294942
2.43776282.94
1.4
3.03
5.55.33
1.8
4.7
9.3
7.14
2.4
6.2
14.8
10.3
4.2
9.1
20.9
13.2
4.7
11.4
25.2
0
5
10
15
20
25
30
mean 10 %ile 50 %ile 90%ile
ab
so
lute
err
or
in %
RC
full shift - 2 shifts full shift - 4 hours full shift - 2 hours
full shift - 1 hours full shift - 10min full shift - 2min
ConclusionConclusion
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
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
Chapter 7: Optimizing sampling Chapter 7: Optimizing sampling strategies: components of low-back strategies: components of low-back
EMG variability in five heavy EMG variability in five heavy industriesindustries
How many individuals? How many repeats? (How) should we group
measurements?
Components of Variability Components of Variability RationaleRationale
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
Sample Exposure-Sample Exposure-ResponseResponse
Relationship Relationship Back injury outcome = intercept + Back injury outcome = intercept + ββ1(exposure variable 1)1(exposure variable 1)
0
20
40
60
80
100
120
140
0 10 20 30 40 50 60 70
Response
Exposure
Grouping SchemesGrouping Schemes
No grouping No grouping Job titleJob title CompanyCompany IndustryIndustry Post hoc ranking of Post hoc ranking of
industry/job title groupsindustry/job title groups
Percentage of true E-R Percentage of true E-R by grouping schemeby grouping scheme
0.876 0.895 0.906 0.9220.993
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Grouping byCompany
No Grouping Grouping byJob
Grouping byIndustry
Post hocGrouping
att
en
ua
tio
n f
ac
tor
Workers per group (k) Workers per group (k) required for 95% of true required for 95% of true
E-RE-R
Grouping strategyNumber
of groups
25% repeats
50% repeats
100% repeats
Grouping by Industry 5 58.6 44.3 26.4
Grouping by Company 31 143.5 104.7 58.5
Grouping by Job 24 13 10.3 6.9
Post hoc Grouping 5 3.3 2.7 1.9
ConclusionConclusion
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
SummarySummary
There are always tradeoffs in exposure assessmentThere are always tradeoffs in exposure assessment
Lots of decisions to make!Lots of decisions to make! How you ‘tip the scales’ toward more samples How you ‘tip the scales’ toward more samples
or more precision depends on the purpose of or more precision depends on the purpose of the study and the characteristics of the the study and the characteristics of the populationpopulation
Contribution is in the ways of framing these Contribution is in the ways of framing these questions and starting to quantify the answersquestions and starting to quantify the answers
AcknowledgementsAcknowledgements
Participating Workers and WorksitesParticipating Workers and Worksites
WorkSafe BCWorkSafe BC
Michael Smith Foundation for Health ResearchMichael Smith Foundation for Health Research
CIHR Bridge Fellowship ProgramCIHR Bridge Fellowship Program
Mieke Koehoorn Mieke Koehoorn
Kay TeschkeKay Teschke
Jim MorrisonJim Morrison
Kevin HongKevin Hong
Nancy LuongNancy Luong
Melissa KnottMelissa Knott
James CooperJames Cooper
Judy VillageJudy Village
Pete JohnsonPete Johnson
Jim PlogerJim Ploger
Yat ChowYat Chow
QuestionsQuestions