RISK ASSESSMENT OF DEVELOPING DISTAL UPPER

EXTREMITY DISORDERS BY STRAIN INDEX METHOD

IN AN ASSEMBLING ELECTRONIC INDUSTRY
M. Pourmahabadian*1, J.N. Saraji1, M. Aghabeighi1 and H. Saddeghi-Naeeni2

1) Department of Occup. Health, School of Public Health, Tehran University of Medical Sciences,
Tehran, Iran
2) Department of Art and Technology, School of Architecture and Urban Studies, Iran University
of Science and Technology, Tehran, Iran

Abstract- The strain index (SI) is a substantial advancement and has been devised to analyze
ergonomic risks for distal upper extremity (DUE) disorders. This semi-quantitative tool allows for the
measurement of hazards and does not require unduly lengthy training to begin to use it accurately. Uses
of the strain index include analysis of a current job to assess whether it is safe or hazardous,
quantification of the risks, and assistance in the initial design of a job or in the redesign of a job. The
aim of this study was to assess and analyze risk of developing DUE disorders in different jobs as well as
hazard classification in an assembling electronic industry through SI method. Also, DUE disorders
prevalence, work-related absenteeism and turnover extracted from SI results were compared and
assessed by those obtained by Nordic musculoskeletal questionnaire (NMQ). The findings of this study
showed that more than 50% of investigated jobs are categorized as "hazardous" and there is a
significant difference between SI mean in hazardous and safe jobs (P < 0.0001). In addition, significant
difference was found between prevalence of DUE disorders in "safe" and "hazardous" jobs (P < 0.049).
But, no significant difference (P = 0.3) was obtained between mean absenteeism in "safe" and
hazardous jobs. Also, no significant difference statistically was found between turnover in "safe" and
hazardous jobs (X2 = 0.133, P = 1) and high prevalence of DUE disorders is due to low turnover rate of
workers.
Acta Medica Iranica, 43(5): 347-354; 2005

Key words: Risk factors, risk analysis ergonomics, distal upper extremity, musculoskeletal disorders,
strain index method, Nordic musculoskeletal questionnaire

INTRODUCTION High automation increases those disorders.

Mechanization and automation decrease workload,
Musculoskeletal disorders (MSDs) of upper but increse work pace and forces to be exerted on
extremities are associated with highly repetitive small anatomic elements such as wrist and hand.
occupational activities, especially those involving By utilizing quantitative methods in MSDs
high force, extreme joint postures and exposure to investigations and other related occupational health
vibration. studies in which risk assessment is involved, one of
the assets of the method is to assist the user in
Received: 19 June 2004, Revised: 23 Jan. 2005, Accepted: 14 Feb. 2005
identifying the specific aspect of the job that is
* Corresponding Author: driving the method towards a hazardous assessment
M. Pourmahabadian, Department of Occup. Health, School of Public
Health, Tehran University of Medical Sciences, Tehran, Iran and therefore allows for a targeted approach to best
Tel: +98 21 66954232 eliminate or lower the risk. One of the methods for
Fax: +98 21 66419984
E-mail: pourmahm@sina.tums.ac.ir exposure assessment of musculoskeletal stressors of
Risk assessment and analysis of DUE

distal upper extremity (DUE) is strain index (SI), epidemiological principles, the SI methodology is
which were proposed by Moore and Garg (1). The SI based on multiplicative interactions among its task
is a semi-quantitative job analysis methodology variables. The SI score represents the product of six
based upon principles of physiology, biomechanics multipliers that correspond to six task variables. The
and epidemiology (2). Its purpose is the six task variables include intensity of exertion,
identification of jobs that place workers at increased duration of exertion, exertions per min, hand/wrist
risk of developing disorders in the DUE (elbow, posture, speed of work and duration of task per day.
forearm, wrist, hand). Application of the SI Intensity of exertion, hand/wrist posture and speed of
methodology results in a numerical score (the SI work are estimated through rating criterions as
score) that, based on interpretation guidelines, presented in tables 1 to 3. Duration of exertion,
predicts whether a job exposes workers to increased exertions per min and duration of task per day are
risk of developing DUE disorders, i.e. if the job is a measured. Based on these estimated or measured
“problem”. Several researches such as More and data, each of the task variables are rated according to
Grag (1, 3) and Hegmann et al. (4) have shown the five ordinal levels using table 4.
application of SI in analyzing jobs for DUE The user finds the column heading corresponding
disorders in different workplaces. Enough evidence to the appropriate task variable, moves down to the
of external validity (generalizibility) and predictive appropriate row within that column, then follows the
validity of this method have also been reported by row to the first column on the left hand side to
Moore et al. (5), Knox et al. (6), Wands et al. (7) identify the appropriate rating. The multipliers for
and Rucker and Moore (8). each task variable are determined from the ratings
This cross-sectional and descriptive-analytical using table 5. The user finds the column heading
study assesses and analyses risk of DUE disorders corresponding to the appropriate task variable and
through both Nordic musculoskeletal questionnaire the row corresponding to the appropriate rating, then
(NMQ) and SI method together with hazard identifies the multiplier at the intersection of the task
classification in an assembling electronic industry. variable column and rating row. The SI score is the
product of the six multipliers.
MATERIALS AND METHODS In this study 25 job groups and 35 jobs of single
task were chosen only for SI assessment (multiple
NMQ was used to determine the prevalence of tasks is not considered and accounted in this
MSDs symptoms (9). NMQ comprises general method) and 69 workers filled out NMQ
information about age, weight, height, smoking questionnaire. In SI method each job was broken
habit, work experience and shift type and also into the tasks and task variables estimated for both
includes body part-specific questions (neck, hands of qualified workers through SI scoring. Risk
shoulders, elbows, forearm, wrist, upper and lower of developing DUE disorders were accounted as
back). A body “map” was also used to make it easier “hazardous” for those having SI criterion more than
for workers to understand and to pinpoint problems 5 for classification jobs in one of both sides (left and
in each body area. right). Jobs in which obtained SI scores were less
Consistent with physiological, biomechanical and than 5 for both sides were accounted as “safe”.

Table 1. Rating criterion for estimation of intensity of exertion (an estimation of the strength required to perform task)
Rating criterion Percent of MS Borg scale* Perceived effects
Light < 10 ≤2 Barely noticeable
Somewhat hard 10-29 3 Noticeable or definite effort
Hard 30-49 4-5 Obvious effort: changes facial expression
Very hard 50-79 6-7 Substantial effort: changes facial expression
Near maximal ≥ 80 >7 Uses shoulder or trunk to generate force
Abbreviation: MS, maximal strength
* Compared to Borg CR-10 scale (10)

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Table 2. Rating criterion for estimation of hand/wrist posture (an estimation of the position of the hand or wrist in comparison with
neural position)
Rating criterion Wrist extension* Wrist flexion* Ulnar deviation* Perceived effects
Very good 0°-10° 0°-5° 0°-10° Perfectly neutral
Good 11°-25° 6°-15° 11°-15° Near neutral
Fair 26°-40° 16°-30° 16°-20° Non-neutral
Bad 41°-55° 31°-50° 21°-25° Marked deviation
Very bad > 60° ≥ 50° > 25° Near extreme
* Derived from Stetson et al. (11).

Table 3. Rating criterion for estimation of speed of work (an estimation of how fast the worker is working)
Rating criterion Compared to motion and time* Perceived effects
Very slow ≤ 80° Extremely relaxed pace
slow 81-90% “taking one’s own time”
Fair 91-100% “normal” speed of motion
Fast 101-115% Rushed, but able to keep up
Very fast > 115% Rushed and barely or unable to keep up
* Derived from Barnes (12).

Table 4. Rating for the strain index task variable are assigned by finding the row within the column that corresponds to the datum
for each task variable, then recording the rating value listed in the first column (left hand side)
Intensity of Duration of exertion Hand/ wrist Duration per
Rating exertion (percent of cycle) Efforts/ minute posture Speed of work day (hrs)
1 Light < 10 <4 Very good Very slow ≤1
2 Somewhat hard 10-29 4-8 Good Slow 1-2
3 Hard 30-49 9-14 Fair Fair 2-4
4 Very hard 50-79 15-19 Bad Fast 4-8
5 Near maximal ≥ 80 ≥ 20 Very bad Very fast ≥8

Table 5. Multipliers for each strain index task variable are determined by finding the intersection of the appropriate rating row with
the appropriate task variable column
Intensity of Duration of exertion Hand/ wrist Duration per
Rating exertion (percent of cycle) Efforts/ minute posture Speed of work day (hrs)
1 1 0.5 0.5 1.0 1.0 0.25
2 3 1.0 1.0 1.0 1.0 0.5
3 6 1.5 1.5 1.5 1.0 0.75
4 9 2.0 2.0 2.0 1.5 1.0
* *
5 13 3.0 3.0 3.0 2.0 1.5
* If duration of excretion is 100%, then efforts/ minute multiplier should be set to 3.0.

A digital chronometer, Handhart Stops-star 2 5-10 job cycle and then its average was accounted as
model, recorded job observation times and a mean average of total observation time in terms of
goniometer was used for measuring wrist seconds. Also, duration of exertion was calculated
flexion/extension angles at different positions with by measuring the duration of all exertions during an
respect to natural position. Six task variables were observation period, then dividing the measured
measured and calculated based on More and Garg duration of exertion by the total observation time and
method (2). multiplied by 100. Effort per minutes were measured
Total observation times were measured based on by counting the number of exertions occurring

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Risk assessment and analysis of DUE

during an observation period, then dividing the frequencies of DUE disorders and clearly shows that
number of exertions by the duration of observations more than 50% of disorders belong to hand and
period in terms of minutes. The SI computed by SI wrist.
software, a computerized system that is prepared by Table 8 summarizes the data of task variable and
Occupational Health Logic (13). NMQ results were Strain Index scores for each of the 35 jobs in 68
then standardized and together with all obtained SI sides (right and left). It shows the task variables
data analyzed and compared using SPSS software ratings for intensity of exertion, duration of exertion,
version 10.0 on a personal computer. efforts per minute, hand/wrist posture, speed of
work, and as well as duration task per day.
The Strain Index score is also reported along with
RESULTS “hazard” and “safe” classification. The obtained
strain index scores for 68 sides varied from a
Distal upper extremity disorders prevalence data minimum score of 0.5 to a maximum of 18.9.
were collected and analyzed through 69 workers Investigation of the results showed that 20 (57.1%)
based on their jobs and frequencies as presented in jobs were “hazardous” and 15 (42.9%) were to be
table 6. Initial information showed that among 69 “safe” and this mean that the jobs of 46 workers
workers, 46.4% (32 workers) and 53.6% of them (66.7%) are categorized as "hazardous" and 23
were male and female, respectively and mean workers (33.3%) have "safe" jobs in comparison
average of work experience 3.8 years (SD = 3.2) in with Strain Index criterion of 5 as proposed by
the range of 1-17 years. Mean average of age is 29 Moore and Garg (2). Also, the mean average of
years (SD = 5.79) and 30.4% of 69 workers belong Strain Index score for all jobs was 7.3 (range: 1.5-
to age group of less than 25 years whilst 7.2% of 18.9) and this for “hazardous” and “safe” jobs were
them are grouped into > 40 years old. Absence rate 9.3 (SD = 3.61) and 3.3 (SD = 0.8), among 46 and
(x= 1.07, SD= 7.22) and turnover (5.8%) were found 23 workers, respectively. This difference was also
to be low within 1 year and 61 workers (88.4%) statistically significant (P < 0.0001). Chi Square test
work with right hand. Of the 69 workers, 67 (97.1%) showed that no significant difference existed in work
had DUE disorders. turnover between “safe” and “hazardous” jobs
Table 7 represents absolute and relative (X2=0.133, P = 1).

Table 6. Absolute and relatively frequencies of workers in each job

Number Relative Number of Relative
Job category of worker frequency (%) Job category worker frequency (%)
VCD3 1 1.4 Screen lamp installment 3 4.3
Rolling pin press 1 1.4 Chassis installment 2 2.9
APT1 3 4.3 RGB installment 3 4.3
Cut and clinch 3 4.3 Final Control 2 2.9
Manual assembling 8 11.6 Horizontal and vertical screen adjustment 2 2.9
Soldering 1 1.4 Screen adjustment and white balance 2 2.9
Wire cutting 2 2.9 Focus and convergence adjustment 2 2.9
Soldering check 4 5.8 Final quality control (QC2) 6 8.7
APT2 2 2.9 Cabinet enclosing 3 4.3
Working 5 7.2 Cleaning whole TV 2 2.9
TV cabinet preparation 2 2.9 Labeling 2 2.9
Power switch Installment 2 2.9 Packing 4 5.8
AV socket installment 2 2.9 Total 69 100

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Table 7. Absolute and relative frequency of DUE disorders Hazardous Jobs Safe Jobs
DUE disorders Number of workers 80
Hand 51 70
Wrist 56 60
58 56.6
Forearm 33 50
Elbow 24

Percent
40 33
Abbreviation: DUE, distal upper extremity.
30 24.6
21.7
Figure 1 shows absolute and relative frequencies 20 15.9 14.5 13.1

of DUE disorders between “hazardous” and “safe” 10

jobs and it is revealed that relative frequencies of 0

Hand Wrist Forearm Elbow
DUE disorders in “hazardous” jobs for hand and
wrist are 58% and 56.6%, respectively and this for Fig. 1. Relative distal upper extremity disorders in various
elbow decreases to 21.7%. part of the body among hazardous and safe jobs.

Table 8. Strain index variables for 35 jobs within TV assembling facilities

Intensity Duration Effort Hand/ Strain Hazard
of of per wrist Speed of Duration index classification
Job category Side exertion exertion minute posture work per day score (H/S)
VCD3 R 1 16.7 6.8 2 3 4 1 S
L 1.4 18 6.8 2 3 4 1.7 S
Rolling pin press R 1 48 12.7 2 3 4 2.25 S
L 1 63.5 19.9 2 3 4 4 S
APT1 R 1.4 50.8 16.4 2 3 4 6.8 H
L 1 51.4 10.2 2 3 4 3 S
Cut and clinch 1 R 1 100 24.8 2 3 4 9 H
L 1 84 22.6 2 3 4 9 H
Cut and clinch 2 R 1 100 27.2 2 3 4 9 H
L 1 100 27.2 2 3 4 9 H
Cut and clinch 3 R 1 84.5 21.4 2 3 4 9 H
L 1.2 100 23.8 2 3 4 11.7 H
Manual assembling 1 R 1.2 61 22.8 2 3 4 7.8 H
L 1 48 19.3 2 3 4 3 S
Manual assembling 2 R 1.24 63.8 13.6 2 3 4 4.2 S
L 1.23 50.6 16.1 2 3 4 5.6 H
Soldering R 1 40.9 13.6 2 3 4 2.25 S
L 1.23 50.2 13.8 2 3 4 4.2 S
Wire cutting R 1.2 92.2 13.8 2 3 4 11.7 H
L 1 92 84.7 2 3 4 1.5 S
Soldering check 1 R 1.1 69.4 2.8 2 3 4 10.8 H
L 1.1 56 65.7 2 4 4 10.8 H
Soldering 2 R 1.03 86 60.2 2 4 4 9.45 H
L 1.06 75 60.2 2 3 4 6.6 H
APT2 R 1 39.5 11.7 2 3 4 2.25 S
L 1.1 56.4 11.7 2 3 4 3.6 S
(continue on next page)

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Table 8. Strain index variables for 35 jobs within TV assembling facilities (continued)
Intensity Duration Effort Hand/ Strain Hazard
of of per wrist Speed of Duration index classification
Job category Side exertion exertion minute posture work per day score (H/S)
Working R 1.02 66 20.1 2 3 4 6.18 H
L 1.05 29.2 15.1 2 3 4 2.16 S
TV cabinet preparation R 1.23 59 16.9 2 4 4 8.4 H
L 1 53 16.9 2 4 4 6 H
power switch installment R 1.2 66.6 28.3 2 4 4 11.7 H
L 1 47 22.7 2 4 4 6.75 H
AV socket installment R 1.5 93.4 27.8 2 3 4 17.1 H
L 1 70.4 17.1 2 3 4 4 S
screen lamp installment R 2.16 49.7 13.3 3 3 4 11.5 H
L 1.2 22.7 11.8 2 3 4 1.95 S
chassis installment R 1.54 86.9 18.4 3 3 4 18 H
L 1 41.5 9.2 2 3 4 2.25 S
RGB1 installment R 1 68 22.4 2 4 4 9 H
L 1.06 47 15.3 2 4 4 4.95 S
RGB2 installment R 1 62.4 10.7 2 3 4 3 S
L 1 61 13.6 2 3 4 3 S
Final control R 1 35.3 8.4 1 3 4 1.5 S
L 1 11.9 6.3 1 3 4 1 S
Horizontal and vertical R 1 24.8 21.1 2 2 4 3 S
screen adjustment L 1 8.4 8.4 2 2 4 0.5 S
Screen adjustment and R 1 55.3 17.5 2 3 4 4 S
white balance L 1 62 13.1 2 3 4 3 S
Focus and convergence R 1 28.3 13.4 2 3 4 1.5 S
adjustment L 1 52.8 17.5 2 3 4 4 S
Quality control (QC1-2) R 1 49.9 28.6 2 3 4 4.5 S
L 1 11.5 6.5 2 3 4 1 S
Cabinet enclosing 1 R 1.23 93 34.3 2 3 4 18.9 H
L 1 67.6 17.1 2 3 4 4 S
Cabinet enclosing 2 R 1.27 87 16.4 2 3 4 9 H
L 1 15.7 18 1 3 4 4 S
Final quality control R 1 53.4 18 2 3 4 4 S
(QC2)1 L 1 16.8 3.7 2 3 4 0.5 S
Final quality control R 1.1 35 12.1 2 3 4 2.7 S
(QC2)2 L 1 30.5 12.1 2 3 4 2.25 S
Cleaning whole TV R 1 89 16 2 3 4 6 H
L 1 67 9.1 2 3 4 3 S
Labeling R 1 32 15.2 2 3 4 3 S
L 1 65 21.7 2 3 4 6 H
Packing 1 R 1.1 42 18.6 2 3 4 3.6 S
L 1 22 15.5 2 3 4 2 S
Packing 2 R 1 37 14.7 2 3 4 2.25 S
L 1 28 14.7 2 3 4 1.25 S
Abbreviations: R, right; L, left; H, hazardous; S, safe.

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DISCUSSION questionnaire with obtained SI data (P ≤ 0.0001) in

“hazardous” jobs clearly highlighted the validation
A cross-sectional and descriptive analytical study of SI in job risk assessment as “safe” and
of risk assessment and analysis of developing DUE “hazardous” at TV assemblers; they are also in good
disorders was conducted in an assembling electronic agreement with previous works (1-4).
industry. DUE disorders prevalence data were In conclusion, the findings of current study
collected among 69 workers through NMQ showed that 20 jobs were hazardous and 15 jobs
questionnaire and SI as proposed by Moore and Garg were safe. Results of statistical test clearly revealed
(3) was applied for 25 job groups and 35 jobs’ risk that there is a significant difference between mean SI
assessment and hazard classification. in hazardous and safe jobs. Also significant
Investigation of the results of two methods of difference was observed between DUE disorder
NMQ and SI which were applied to this study can be prevalence in safe and hazardous jobs. Comparison
categorized into the following: between mean SI data and DUE disorders, work-
related absenteeism and turnover showed that there
NMQ method results was a good association between SI data and DUE
Results showed that in spite of DUE disorders disorders prevalence results obtained by NMQ
among female assemblers being higher than male questionnaire. Thus, it can be concluded that the SI
workers, no significant difference was observed has a good validity in assessing of DUE disorders
statistically. Also, during 1 year, absenteeism rate risk assessment.
and turnover among workers were found to be low.
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