Individual and combined impacts of biome
AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 43:495–506 (2003)
Individual and Combined Impacts of
Biomechanical and Work Organization Factors
in Work-Related Musculoskeletal Symptoms
Grant D. Huang,
1,2
MPH, PhD,
Michael Feuerstein, PhD, MPH,1,2,3 Willem J. Kop,
Kenneth Schor, DO, MPH,4 and Freya Arroyo, BS5
PhD,
2
Background Investigations of work-related low back (LB) and upper extremity (UE)
disorders have increasingly utilized multivariable models that include biomechanical/
physical and work organization factors. However, the nature of any interactive effects is
not well understood.
Methods Using questionnaires, high and low exposure groups for biomechanical/
physical factors, cognitive demands, cognitive processing, interpersonal demands, participatory management, skill discretion, and time pressure for 289 individuals (U.S. Marines)
were identified. Musculoskeletal symptom status was also determined by questionnaire.
Individual and biomechanical–psychosocial combinations were examined in adjusted
multivariable logistic regression analyses.
Results Time pressure was associated with both LB and UE symptoms (odds ratio(s) (OR)
range ¼ 2.13–3.09), while higher biomechanical exposures were risk factors for LB
symptoms (OR ¼ 2.07; 95% confidence intervals (CI): 1.00–4.35) and concurrent LB and
UE symptoms (OR ¼ 2.80; CI: 1.35–5.83). Greater risks for concurrent LB and UE
symptoms were indicated for combinations involving higher biomechanical exposure and:
time pressure (OR ¼ 2.21; CI: 1.19–4.10); cognitive demands (OR ¼ 2.25; CI: 1.23–
4.09); cognitive processing (OR ¼ 2.08; CI: 1.16–3.75); interpersonal demands
(OR ¼ 2.44; CI: 1.35–4.41); participatory management (OR ¼ 2.50; CI: 1.30–4.81).
Results did not suggest any interaction between biomechanical and work organization
factors.
Conclusions While no synergism was indicated, the present findings emphasize the need
to consider both biomechanical factors and specific work organization factors,
particularly time pressure, in reducing musculoskeletal-related morbidity.
Am. J. Ind. Med. 43:495–506, 2003. Published 2003 Wiley-Liss, Inc.y
KEY WORDS: ergonomics; work organization; psychosocial; low back pain; upper
extremity; symptoms; secondary prevention
1
Department of Preventive Medicine & Biometrics, Uniformed Services University of the
Health Sciences, Bethesda, Maryland
2
Department of Medical & Clinical Psychology, Uniformed Services University of the
Health Sciences, Bethesda, Maryland
3
Division of Behavioral Medicine, Department of Psychiatry, Georgetown University
School of Medicine,Washington, District of Columbia
4
Health Services Division, Headquarters, U.S. Marine Corps,Washington, D.C.
5
Safety Division, Headquarters, U.S. Marine Corps,Washington, D.C.
The opinions and assertions contained herein are the private views of the authors and are
not to be construed as being official or as reflecting the views of the Uniformed Services
University of the Health Sciences, the Department of Defense, or the U.S. Marine Corps.
Published 2003 Wiley-Liss, Inc.
y
This article is a US Government work and, as such, is in
the public domain in the United States of America.
Contract grant sponsor: Safety Division, Headquarters, U.S. Marine Corps; Contract grant
number: MIPROLYLR00370.
*Correspondence to: Grant D. Huang, Department of Preventive Medicine & Biometrics,
Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda,
MD 20814. E-mail: ghuang@usuhs.mil
Accepted16 December 2002
DOI 10.1002/ajim.10212. Published online in Wiley InterScience
(www.interscience.wiley.com)
496
Huang et al.
INTRODUCTION
Work-related low back (LB) and upper extremity (UE)
disorders can significantly impact the health, function, and
productivity of workers and organizations [Duquesnoy et al.,
1998; Morse et al., 1998]. Furthermore, considerable financial burdens associated with medical care and indemnity
payments have been attributed to these problems [Feuerstein
et al., 1998; Hashemi et al., 1998]. Using various job analysis
methods, biomechanical and physical exposures such as
heavy work, static work, awkward postures, lifting, twisting
and bending, repetition, excessive force, and vibration have
been established as risks for work-related LB pain and/or UE
symptoms [Bernard, 1997; National Research Council and
Institute of Medicine (NRC/IOM), 2001]. An increasing
number of epidemiological studies have also indicated that
occupational psychosocial factors as well as characteristics
of work and how it is organized, or work organization factors,
are associated with and/or predictive of work-related
musculoskeletal symptoms and disorders [National Research
Council and Institute of Medicine (NRC/IOM), 2001;
Bongers et al., 2002]. While theoretical frameworks and
existing research have highlighted the need for efforts that
simultaneously address biomechanical and work organization stressors in the prevention of work-related musculoskeletal morbidity [Huang et al., 2002], the relative and
combined impacts they have on workers exposed to both
sets of factors are not well understood.
Multivariable models that include both biomechanical/
physical and occupational psychosocial factors have been
used in some investigations of work-related LB and UE
disorders [e.g., Skov et al., 1996; Polyani et al., 1997; Kerr
et al., 2001]. However, fewer studies have examined the
combined and/or interactive effects of these factors. Marras
et al. [2000] reported that the introduction of psychosocial
stressors, in the form of visual feedback suggesting
inadequate performance and criticism, resulted in significant
increases in spinal loadings, muscle responses, and kinetic
responses in a laboratory-based lifting task. Among individuals from various occupations, high exposures to both
physical and psychosocial stressors were found to place one
at a 2.8-fold greater likelihood for the self-report of LB pain
in the past 7 days when compared to workers with low levels
of exposure [Devereux et al., 1999]. In this cross-sectional
study, high physical exposure was defined as the self-report
of: (1) lifting > 16 kg between 1 and 10 times an hour; or
(2) lifting 6–15 kg between 1 and 10 times an hour and
experiencing vibration while sitting more than or equal to
half of the working day. High exposure to psychosocial
stressors was based on three different self-report scales and
defined as having any two of the following: high mental
demands; low job control; low social support. While
Devereux et al. [1999] emphasized the importance of combined exposure to physical and psychosocial stressors in LB
pain, research is still needed to examine work organization
stressors in the context of biomechanical factors in workers
experiencing LB and UE symptoms. Furthermore, given
recent findings that suggest physical and psychosocial factors
share a common variance based, in part, on how work is
organized [MacDonald et al., 2001], studies on musculoskeletal-related outcomes that examine these factors individually and in combination can assist with determining the
nature of any effects.
A few investigations have suggested that biomechanical
and some work organization factors may interact to influence
UE symptoms. A study of office workers by Bergqvist et al.
[1995] indicated that the interaction between working on
a visual display terminal and having limited opportunities
for rest breaks was a risk factor (odds ratio(s) (OR) ¼ 4.8,
confidence intervals (CI): 1.3–18.1) for reporting neck/
shoulder discomfort. In the same study, arm/hand diagnoses
as determined by a physiotherapist were associated with
limited rest break opportunities and lower arm support in
persons who worked more than 20 hr a week. Faucett and
Rempel [1994] also found that decision latitude, job insecurity, supervisor support, and supervisor conflict all independently interacted with relative keyboard height (based on
the cross-product of the scores on the respective variables)
in determining severity of UE numbness in newspaper
employees. These studies suggest that particular job- and
company-level [Shannon et al., 2001] and physical workstation factors may operate in conjunction to impact worker
UE health. However, interpreting such statistical interactions is complex and it is not clear whether any synergism
exists between such biomechanical/physical and work organization factors.
The primary objectives of the present study were to
determine whether different levels of exposures to both
biomechanical/physical and specific work organization
stressors were associated with LB, UE, and concurrent LB
and UE symptoms and whether the magnitudes of any associations indicated any synergism. Additionally, by examining individuals working in jobs previously identified as
having higher rates for musculoskeletal-related clinic visits,
this investigation was conducted with the intent of continuing
on-going efforts by our group to develop a secondary prevention program for these workers.
METHODS
Study Participants
Active duty, enlisted U.S. Marines involved in high-risk
jobs for musculoskeletal-related clinic visits [Huang et al.,
2001] were invited through news bulletins, electronic mail,
and section heads to attend an information session about a
research study on musculoskeletal disorders. Jobs targeted in
the recruitment process were: Image Interpretation; Auditing
Biomechanical and Work Organization Factors
and Accounting; Disbursing; Information and Education;
and Transportation. After providing the details of the study,
which were approved by a university Institutional Review
Board, all individuals deciding to participate were asked
to complete an informed consent form and a questionnaire
that assessed potential risk factors and musculoskeletal
symptoms.
Four hundred individuals were presented with the details
of the study and 307 (76.8%) consented to participate.
Among these consenting individuals, 18 did not meet
eligibility criteria for the study because they indicated
having musculoskeletal symptoms that resulted from a nonwork-related accident/trauma (e.g., sports, traffic accident).
Questionnaire
The questionnaire contained items and scales that: had
reported associations with work-related musculoskeletal
symptoms, disorders, or disability and/or had been used in
previous studies; had acceptable psychometric properties
(e.g., internal consistency, discriminant validity); could be
easily administered (i.e., relatively few items); and suggested
potential areas for modification through intervention efforts.
These items are described in the following sections. Interested readers may contact the primary author for a copy of
the questionnaire.
Biomechanical/physical factors
Exposures to biomechanical/physical risk factors were
assessed by the Job Factors—Description of Work subscale
of the U.S. Air Force Job Requirements and Physical
Demands Survey (JRPD) [Marcotte et al., 1997]. This selfreport measure contains 38 items on the frequency of
exposure to movements, postures, loads, and environmental
factors while performing a work task. Reliability from a
2-week test–retest was found to have a kappa of 0.68 (88%
raw agreement) and adequate validity in relation to worksite
assessments performed by an ergonomist [Marcotte et al.,
1997]. A recent study of office workers (n ¼ 92) also found a
subset of these items to be normally distributed and that
higher levels of exposure were associated with UE pain,
symptom severity, and functional limitations [Dane et al.,
2002].
Work organization
Items used to measure work organization assessed
multiple dimensions of this construct (i.e., scheduling, job
design, management style, interpersonal) [Cooper and
Marshall, 1976; National Institute for Occupational Safety
and Health (NIOSH), 1996]. All items in the survey were
presented without reference to a specific work organization
category.
497
Scheduling. Three questions adapted from the Work
Environment Scale [Moos, 1994] were used to query one’s
ability to relax at work, perceptions of constant pressure to
keep working, and sense of urgency on the job. Two questions
on work breaks and shift work from the Biological scale of
the Multimethod Job Design Questionnaire [Campion, 1988]
were also included.
Job design. Skill discretion and decision authority were
assessed by items from the Job Content Questionnaire
[Karasek et al., 1998]. Additionally, 13 questions obtained
from a prior NIOSH study [Hales et al., 1994] and dealing
with cognitive aspects of the job such as information
processing, memory, and routine associated with one’s job
were used.
Management style. Three items from Hales et al. [1994]
were included to determine how much a worker participates
with others in making decisions and/or setting the way things
are performed at work. The ‘‘Feedback from Agents’’
subscale of the Job Diagnostic Survey (JDS) [Hackman
and Oldham, 1974] was also used to ask about the extent
and frequency of feedback one receives from supervisors and
co-workers.
Interpersonal. Three items dealing with the level of
personal interaction required on the job and obtained from
the ‘‘Dealing with Others’’ subscale of the JDS [Hackman
and Oldham, 1974] were incorporated.
In addition to the items on biomechanical/physical
and work organization factors, there were questions related to demographics, health behavior, physical demands,
and individual psychosocial factors. Demographic information obtained were: age; gender; marital status; number
of children supported; education level; rank; length of
service; military occupational specialty (MOS); and length
of time in MOS.
Individuals were asked how often they completed at
least 20 min of non-stop aerobic activity based on a question from U.S. Army Health Risk Appraisal (HRA).
Responses on this item have been found to predict backrelated disability in U.S. Army soldiers [Feuerstein et al.,
1999a]. A modified Borg [1998] CR10 Scale was also used to
assess the physical effort required from one’s job during
a ‘‘typical day’’ [Feuerstein et al., 2001].
The Conflict Subscale of the Family Environment
Scale [Moos and Moos, 1981] was included based on past
research that reported a group of ambulatory chronic LB
pain individuals to have greater levels of family conflict
and general stress and lower levels of family control
[Feuerstein et al., 1985]. One item from the Conflict Subscale, ‘‘Family members sometimes hit each other’’ was not
included because of its potential in incriminating military
personnel.
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Huang et al.
A question from the HRA addressing the frequency that
worries interfered with life was also asked based upon
findings that self-reported worries are associated with backand UE-related disability in U.S. Army soldiers [Huang et al.,
1998; Feuerstein et al., 1999a].
Musculoskeletal symptoms
Symptoms in the lower back, neck, shoulders, elbows/
forearms, and wrists/hands regions were assessed by using a
modified NIOSH symptom survey [Bernard et al., 1994].
Questions addressed type of symptoms, time of first onset,
frequency, duration, intensity, work interference, and associated limited duty within the past 12 months.
Case Definitions
Four separate groups were delineated based on responses to the following questions: (1) do you experience
physical problems in any of the following areas of your body
(i.e., lower back, neck, shoulder, elbows/forearms, wrists/
hands); (2) when did you first notice the problem? An
asymptomatic control group was defined as those individuals
who did not report having any musculoskeletal symptoms in
any location. Symptomatic cases were classified as having
LB symptoms only, UE symptoms only, or both LB and UE
symptoms simultaneously. Additionally, only those individuals who reported having symptoms since beginning work
in their current MOS and who did not report having had
a prior accident/trauma (e.g., sports, traffic accident) to the
region were included as cases for any of the symptomatic
groups.
Analyses
Factor analyses of the work organization items were
conducted to determine whether specific types of work
organization stressors could be empirically delineated and
to determine which items defined them. To maximize
the variances of factor loadings so that unique factors
could be partitioned, a varimax (i.e., orthogonal) rotation
was used with a rotated component matrix [Nunnally and
Bernstein, 1994]. Those factors with component variances
(i.e., eigenvalues) above one were retained for further analyses [Tabachnick and Fidell, 1983; Nunnally and Bernstein,
1994].
A risk stratification procedure was then performed to
categorize study participants as having either ‘‘high’’ or
‘‘low’’ levels of exposure on the JRPD and on each work
organization factor identified by the factor analyses. The
exposure level for a particular variable was determined by
his/her score relative to a median split of the variable’s scores
from the entire sample. This method was used because prior
research has not established cut-off points for delineating risk
levels. With the exception of the participatory management
variable, a ‘‘high’’ level of exposure indicated more adverse
exposure.
For each of the possible biomechanical/work organization factor combinations, study participants were classified
into a low/low, high/low, low/high, or high/high exposure
group. Classifications were based on the individual’s respective exposure level to biomechanical factors and to the
particular work organization variable of interest.
Using logistic regression analyses with case status (i.e.,
LB case/control; UE case/control; LB and UE case/control)
as the dependent variable, each individual biomechanical
(i.e., JRPD) and work organization variable was examined
separately while adjusting for age, gender, education level,
frequency of exercise, perceived exertion, family conflict,
and worries. Collinearity between these control variables
and the independent variables of interest were examined by
computing Pearson correlation coefficients. Subsequently,
each biomechanical/work organization combination was
entered into a multivariable logistic regression model that
adjusted for age, gender, education level, frequency of
exercise, perceived exertion, family conflict, and worries.
Each of the combinations was examined independently
from the other combinations and used the low biomechanical exposure/low work organization combination as the
referent group. For the analysis involving the biomechanical/
participatory management combination, the referent group
was the one with lower biomechanical exposures and
higher levels of participatory management. The magnitudes of association were determined by obtaining OR,
parameter estimates (b coefficients), 95% CI, and significance levels.
Prior to conducting any analyses, all missing data were
replaced by the mode of that respective question. Less than
3% of the total sample had missing data for any given item.
All analyses were performed using SPSS v.10.1 (SPSS,
Chicago, IL).
RESULTS
Subject Characteristics
Distributions of the study participants according to case
status were: 31.1% (n ¼ 90) asymptomatic controls; 20.4%
(n ¼ 59) LB symptoms only cases; 19.7% (n ¼ 57) UE
symptoms only cases; and, 28.7% (n ¼ 83) cases with both
LB and UE symptoms. The demographic characteristics
most commonly reported were: male (88.2%); ‘‘White’’
(51.6%); married (39.8%); some college/other post high
school education (45.7%), and the rank of E-5, Sergeant
(26.6%). Table I more specifically details the demographic
distribution of the sample.
Using the U.S. Department of Defense Primary
Occupational Codes [U.S. Department of Defense, 1997],
Biomechanical and Work Organization Factors
499
TABLE I. Demographic Characteristics
Age (in years), mean (SD)
Gender
Males
Females
Race
White/Caucasian
Black/African American
Hispanic/Latino
Asian
American Indian
Education
H.S. grad/GED
Some college/other post H.S.
2 year degree
4 year degree/college
Some graduate work
Marital Status
Single
Married
Separated
Divorced
Rank
E2, Private First Class
E3, Lance Corporal
E4, Corporal
E5, Sergeant
E6, Staff Sergeant
E7, Gunnery Sergeant
E8, Master Sergeant or First Sergeant
E9,MasterGunnerySergeantorSergeantMajor
Controls
(n ¼ 90)
Back only cases
(n ¼ 59)
Upper extremity (UE)
only cases (n ¼ 57)
BackandUE cases
(n ¼ 83)
Total sample
(n ¼ 289)
26.9 (6.5)
28.0 7.8
26.5 (6.6)
30.3 (7.6)
28.0 (7.2)b
n (%)a
n (%)a
n (%)a
n (%)a
n (%)a
80 (88.9)
10 (11.1)
51 (86.4)
8 (13.6)
52 (91.2)
5 (8.8)
72 (86.7)
11 (13.3)
255 (88.2)
34 (11.8)
46 (51.1)
21 (23.3)
21 (23.3)
2 (2.2)
0 (0)
31 (52.5)
17 (28.8)
9 (15.3)
2 (3.4)
0 (0)
34 (59.6)
12 (21.1)
8 (14.0)
2 (3.5)
0 (0)
38 (45.8)
24 (28.9)
18 (21.7)
1 (1.2)
1 (1.2)
149 (51.6)
74 (25.6)
56 (19.4)
7 (2.4)
1 (0.3)
37 (41.1)
41 (45.6)
7 (7.8)
2 (2.2)
1 (1.1)
29 (49.2)
24 (40.7)
2 (3.4)
4 (6.8)
0 (0)
25 (43.9)
25 (43.9)
1 (1.8)
1 (1.8)
2 (3.5)
32 (38.6)
42 (50.6)
5 (6.0)
1 (1.2)
2 (2.4)
123 (42.6)
132 (45.7)
15 (5.2)
8 (2.8)
5 (1.7)
30 (33.3)
36 (40.0)
4 (4.4)
3 (3.3)
23 (39.0)
26 (44.1)
0 (0)
5 (8.5)
26 (45.6)
17 (29.8)
1 (1.8)
6 (10.5)
30 (36.1)
36 (43.3)
6 (7.2)
2 (2.4)
109 (37.7)
115 (39.8)
11 (3.8)
16 (5.5)
5 (5.6)
18 (20.0)
16 (17.8)
25 (27.8)
12 (13.3)
8 (8.9)
4 (4.4)
2 (2.2)
2 (3.4)
14 (23.7)
10 (16.9)
17 (28.8)
4 (6.8)
4 (6.8)
4 (6.8)
4 (6.8)
3 (5.3)
14 (24.6)
17 (29.8)
8 (14.0)
8 (14.0)
4 (7.0)
3 (5.3)
0 (0)
2 (2.4)
13 (15.7)
7 (8.4)
27 (32.5)
10 (12.0)
12 (14.5)
8 (9.6)
4 (4.8)
12 (4.2)
59 (20.4)
50 (17.3)
77 (26.6)
34 (11.8)
28 (9.7)
19 (6.6)
10 (3.5)
a
Percentage of group; total n for category may not equal total n for group because of missing data.
t-test comparing group to controls: t ¼ 3.15, df ¼171, P < 0.01.
b
the majority of Marines were found to have jobs from
the Functional Support and Administration category. This
finding indicated a consistency with the intended study
recruitment. Specifically, there were 184 (64.2%) individuals in this occupational category which includes the following subcategories: Personnel; Administration; Clerical/
Personnel; Data Processing; Accounting/Finance/Disbursing; Other Functional Support; and, Information and
Education. Other occupational categories (and percent
distribution) were: Service/Supply Handlers (10%); Infantry,
Gun Crews/Seamanship (10%); Communications/Intelligence Specialists (6%); Electrical/Mechanical Equipment
Repairers (5%); Other (3%).
Chi-square tests on gender, race, education level, marital
status, rank, and MOS indicated no significant differences
between controls and any of the symptomatic case groups.
Only the group with concurrent LB and UE symptom was
found to be significantly older in age than the control group
(t ¼ 3.15, df ¼ 171, P < 0.01).
Work Organization Factors
Factor analyses indicated that five components could be
identified from the work organization items. These components were Job Design, Participatory Management, Time
Pressure, Cognitive Processing, and Interpersonal Demands.
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Huang et al.
Each factor had initial eigenvalues above 1.6. While one
reason for conducting the factor analyses was to reduce the
number of items to be included within a particular work
organization category, the Job Design factor was found to
contain the items from the skill discretion subscale of the Job
Content Questionnaire [Karasek et al., 1998] and from the
cognitive demands section of the NIOSH work survey [Hales
et al., 1994]. Therefore, these items were separated into their
respective subscales to maintain their original integrity.
Subsequent analyses examined skill discretion and cognitive
demands as separate variables.
The components delineated from the factor analyses, the
specific questionnaire items that comprised each factor,
factor loadings, initial eigenvalues, and percent variance are
given in Table II.
Cronbach’s alphas for each of the identified work
organization factors are given in Table III. As shown,
most work organization factors had adequate reliabilities
with Cronbach’s coefficient alphas ranging from 0.71 to
0.83 [Nunnally and Bernstein, 1994]. The cognitive processing factor had a modest Cronbach’s coefficient alpha
of 0.60.
TABLE II. FactorAnalyses of Work Organization Items
Factor loading
Job designa
Skill discretion
My job requires that I learn new things
My job requires me to be creative
My job requires a high level of skill
I get to do a variety of different things on my job
I have an opportunity to develop my own special skills
Cognitive demands
My job requires me to make many decisions
To do my job well, I have to be able to do a lot of things mentally at the same time
My job requires me to remember a great deal of information for brief periods of time
My job often requires me to learn new procedures
My job requires me to remember many different things
Participatory management
To what extent do supervisors or co-workers let you know how well you are doing on the job
The supervisors and co-workers on this job almost never give me any ‘‘feedback’’about how well
I am doing in my work
Supervisors often let me know how well they think I am performing on the job
How much do you take part with others in making decisions that affect you?
How much do you participate with others in helping set the way things are done on your job
How much do you decide with others what part of a task you will do
Time pressure
In my group, people cannot afford to relax
In our group, there is constant pressure to keep working
In my group,there is a sense of urgency about everything
Cognitive processing
I can easily see or hear the information I have to use in my job
The information I receive is organized for me in ways that seem natural and easy to deal with
I can perform the activities associated with my job without thinking about them
Most of the decisions I make are routine and easy to make
In my job,there are set rules that I follow over and over again
Interpersonal demands
To what extent does your job require you to work closely with other people
The job requires a lot of cooperative work with other people
a
b
Initial eigenvalue
Varianceb (%)
8.63
18.0
4.78
9.9
2.79
5.8
1.82
3.8
1.61
3.4
0.696
0.691
0.720
0.720
0.731
0.510
0.562
0.526
0.721
0.660
0.665
0.546
0.644
0.689
0.673
0.668
0.714
0.736
0.659
0.441
0.462
0.478
0.567
0.716
0.564
0.672
The job design factor was separated into the two original scales (skill discretion and cognitive demands) from which the items came.
Cumulative variance ¼ 40.9.
Biomechanical and Work Organization Factors
TABLE III. Internal Consistency of Work OrganizationVariables
Work organization factor
Cronbach’s alpha
Cognitive demands
Cognitive processing
Interpersonal demands
Participatory management
Skill discretion
Time pressure
0.827
0.604
0.709
0.777
0.797
0.816
Biomechanical and Work
Organization Associations With
Musculoskeletal Symptoms
Table IV reports the OR, 95% CI, and levels of
significance for having musculoskeletal symptoms when
501
one had the more adverse level of exposure to a particular
biomechanical/physical or work organization variable. These
figures are the results after adjusting for age, gender,
education level, frequency of exercise, perceived exertion
at work, worries, and family conflict. Pearson correlation
coefficients indicated relatively low (r ¼ 0.02–0.25) associations between control variables and the biomechanical and/
or work organization variables of interest. Most of these
correlations were not statistically significant. Table IV also
provides the number of cases and controls within each level
of exposure.
The findings indicate that a high level of exposure to
biomechanical factors was a significant risk factor for those
with LB symptoms only (OR ¼ 2.07; 95% CI: 1.00–4.35)
and with both LB and UE symptoms (OR ¼ 2.80; CI: 1.35–
5.83). Among the work organization stressors, only time
pressure (OR ¼ 2.13–3.09) was a consistent risk factor across
TABLE IV. Biomechanical and Work Organization Risk Factors for Musculoskeletal Symptoms
Back symptoms(n ¼149)
Variable: level of exposure
Biomechanical exposure
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Cognitive demands
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Cognitive processing
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Interpersonal demands
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Participatory management
Low exposure
N low exposure (cases/controls)
N high exposure (cases/controls)
Skill discretion
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Time pressure
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
UE symptoms (n ¼147)
Back and UE symptoms (n ¼173)
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
2.07 (1.00^4.35)
32/35
27/55
0.05
1.76 (0.82^3.77)
31/35
26/55
0.15
2.80 (1.35^5.83)
48/35
35/55
0.01
1.32 (0.64^2.79)
27/36
32/54
0.45
1.36 (0.66^2.82)
27/36
30/54
0.40
2.20 (1.11^4.37)
47/36
36/54
0.03
0.68 (0.33^1.42)
23/42
36/48
0.31
0.63 (0.29^1.35)
22/42
35/48
0.23
1.77 (0.91^3.42)
49/42
34/48
0.09
0.80 (0.39^1.64)
29/46
30/44
0.54
1.26 (0.60^2.64)
33/46
24/44
0.54
1.48 (0.75^2.90)
55/46
28/44
0.26
1.56 (0.73^3.33)
27/54
32/36
0.25
1.56 (0.71^3.44)
25/54
32/36
0.27
2.32 (1.13^4.73)
37/54
46/36
0.02
1.35 (0.65^2.79)
34/45
25/45
0.42
0.75 (0.36^1.58)
26/45
31/45
0.45
1.28 (0.65^2.50)
43/45
40/45
0.47
2.96 (1.35^6.47)
36/35
23/55
0.01
3.09 (1.39^6.88)
35/35
22/55
0.01
2.13 (1.04^4.37)
44/35
39/55
0.04
After adjusting for age, gender, education level, exercise, physical demands, life-interfering worries, and family conflict.
502
Huang et al.
all case groups. Low participatory management (OR ¼ 2.32;
CI: 1.13–4.73) and cognitive demands (OR ¼ 2.20; CI:
1.11–4.37) were also found to be individual risk factors, but
only for those with both LB and UE symptoms.
For control variables, age was a significant (P < 0.05)
risk factor for LB symptoms only (OR ¼ 1.07 per year;
CI: 1.01–1.13) in the model including time pressure and for
concurrent LB and UE symptoms (OR ¼ 1.1; CI: 1.04–1.18)
in all logistic regression models. Family conflict was a
significant risk factor for LB symptoms only (OR ¼ 1.3;
CI: 1.05–1.68) and UE symptoms only (OR range: 1.2–1.3;
CI: 1.04–1.61) for all models.
Table V provides the OR and 95% CI computed from the
logistic regression analyses for all biomechanical/work
organization combinations after adjusting for age, gender,
education level, health behavior, perceived exertion at work,
life-interfering worries, and family conflict. Only the
combination of high biomechanical exposure and high levels
of time pressure was significantly associated with musculoskeletal symptoms in all groups (OR ¼ 2.21 (LB and UE);
OR ¼ 2.61 (LB only); OR ¼ 2.90 (UE only)). Other significant combinations only placed one at greater risks for
having concurrent LB and UE symptoms and included high
biomechanical exposure and: low participatory management
(OR ¼ 2.50; CI: 1.30–4.81); high interpersonal demands
(OR ¼ 2.44; CI: 1.35–4.81); high cognitive demands (OR ¼
2.25; CI: 1.23–4.09); and high cognitive processing (OR ¼
2.08; CI: 1.16–3.75).
Age was found to be a significant (P < 0.05) risk
factor for LB symptoms only (OR ¼ 1.1; CI: 1.00–1.14)
for the models involving the combinations with biomechanical exposure/time pressure and biomechanical exposure/
cognitive processing combinations. Age (OR ¼ 1.1; CI:
1.06–1.20) was also a significant risk factor for concurrent
LB and UE symptoms in all models with the biomechanical/
work organization combination. Significant OR for family
conflict (OR range ¼ 1.3–1.4) were found for LB symptoms
only in all models and for UE symptoms only in all models
except that involving the combination of biomechanical exposure/participatory management.
TABLE V. Biomechanical Exposure and Work Organization Combinations Associated With Musculoskeletal Symptoms
Back symptoms (n ¼149)
Variables: level biomechanical exposure/
level work organization
Biomechanical exposure and cognitive demands
High/low
Low/high
High/high
Biomechanical exposure and cognitive processing
High/low
Low/high
High/high
Biomechanical exposure and interpersonal demands
High/low
Low/high
High/high
Biomechanical exposure and participatory management
High/high
Low/low
High/low
Biomechanical exposure and skill discretion
High/low
Low/high
High/high
Biomechanical exposure and time pressure
High/low
Low/high
High/high
OR (95% CI)
1.31 (0.69^2.49)
0.79 (0.40^1.57)
1.54 (0.81^2.96)
1.53 (0.80^2.90)
0.39 (0.19^0.84)
1.59 (0.81^3.12)
1.53 (0.83^2.83)
0.65 (0.35^1.19)
1.33 (0.69^2.57)
0.90 (0.47^1.75)
0.67 (0.34^1.32)
2.34 (1.19^4.63)
1.41 (0.73^2.70)
0.91 (0.50^1.64)
1.54 (0.82^2.92)
0.63 (0.29^1.35)
1.00 (0.48^2.09)
2.61 (1.39^4.91)
P
0.26
0.41
0.50
0.19
0.10
0.20
0.02
0.18
0.28
0.18
0.16
0.39
0.09
0.76
0.25
0.01
0.19
0.31
0.74
0.18
0.02
0.23
0.99
0.01
UE symptoms (n ¼147)
OR (95% CI)
1.15 (0.60^2.18)
0.86 (0.43^1.74)
1.50 (0.77^2.93)
1.62 (0.83^3.17)
0.46 (0.21^1.00)
1.25 (0.63^2.49)
0.87 (0.43^1.77)
0.65 (0.34^1.26)
1.93 (1.02^3.65)
1.05 (0.53^2.08)
0.93 (0.49^1.78)
1.67 (0.85^3.30)
1.61 (0.87^3.00)
0.75 (0.41^1.39)
1.06 (0.53^2.11)
0.46 (0.20^1.07)
1.05 (0.50^2.21)
2.90 (1.49^5.66)
After adjusting for age, gender, education level, exercise, physical demands, life-interfering worries, and family conflict.
P
0.46
0.68
0.68
0.24
0.23
0.16
0.05
0.53
0.22
0.70
0.21
0.04
0.35
0.88
0.83
0.14
0.44
0.13
0.36
0.87
0.01
0.07
0.90
0.01
Back and UE symptoms
(n ¼173)
OR (95% CI)
1.15 (0.61^2.15)
0.88 (0.46^1.69)
2.25 (1.23^4.09)
1.30 (0.79^2.42)
0.80 (0.43^1.48)
2.08 (1.16^3.75)
1.13 (0.61^2.08)
0.64 (0.35^1.14)
2.44 (1.35^4.41)
1.17 (0.64^2.14)
0.98 (0.52^1.84)
2.50 (1.30^4.81)
1.76 (0.96^3.23)
0.83 (0.46^1.47)
1.69 (0.93^3.81)
1.18 (0.64^2.17)
0.88 (0.44^1.76)
2.21 (1.19^4.10)
P
0.01
0.67
0.71
0.01
0.02
0.42
0.47
0.02
0.02
0.69
0.13
0.01
0.01
0.60
0.95
0.01
0.03
0.07
0.52
0.09
0.02
0.59
0.72
0.01
Biomechanical and Work Organization Factors
DISCUSSION
The present cross-sectional study indicated that increased time pressure was a consistent risk factor for symptoms in
the LB and/or UE regions. Exposure to biomechanical factors
was also associated with LB symptoms and concurrent
symptoms in the LB and UE. Higher levels of cognitive
demands and less participation in management were significant work organization stressors, but only among workers
who experienced both LB and UE symptoms. While most
biomechanical/work organization combinations (i.e., biomechanical exposure and time pressure, cognitive demands,
cognitive processing, interpersonal demand, or participatory
management) placed individuals at greater risk for concurrent LB and UE symptoms, the magnitudes of the associations did not suggest any interactive effect between the
biomechanical/physical and work organization factors. The
findings do provide information on specific work organization stressors that should be targeted in intervention
programs that attempt to reduce biomechanical exposures.
Pressure to continuously work and for such work to
be completed urgently were particularly relevant in the
experience of LB and/or UE symptoms. The risks (OR ¼
2.13–3.09) for musculoskeletal symptoms highlight the need
for targeting this dimension of work organization in intervention efforts. Such efforts take on added importance
considering that the risks were found independent of biomechanical factors. Another cross-sectional study of nurses
reported that the belief that one ‘‘ought to slow down at
work’’ had a prevalence odds ratio (POR) of 1.94 for
self-reported back complaints, while a difficult work rate
(POR ¼ 1.68) and the belief that one ought to slow down at
work (POR ¼ 2.71) were associated with arm or neck complaints [Engels et al., 1996]. Increased time pressure at work
(defined by reduced time to complete job-related goals) and
work/rest schedule were also associated with a greater incidence of UE disorders among customer service representatives at a bank [Ferreira et al., 1997]. Birch et al. [2000]
found that higher time pressure in completing a standardized computer task produced greater EMG activity in the
trapezius, deltoid, infraspinatus, and extensor digitorum
muscle groups in female computer aided design operators.
Additionally, Feuerstein and Fitzgerald [1992] have reported
that fewer opportunities to rest were associated with higher
levels of fatigue in sign language interpreters with UE symptoms. It may be possible that time pressure and associated
increase muscle activity along with a reduced number of rest
breaks may set the stage for increased UE symptoms. This
process is consistent with the concept of a high-risk
workstyle [Feuerstein et al., 1999b]. Research has yet to
determine whether time pressure is associated with greater
loads in the trunk musculature. Nevertheless, perceptions
of and/or actual conditions that require the need to keep
working and to work at a faster pace may be especially
503
problematic since they could lead to overexertion and prevent
one from taking breaks that assist with recovery processes
[e.g., Eastman Kodak Company, 1986].
Studies such as those conducted by Engstrom et al.
[1999], Krause et al. [1998], and Polyani et al. [1997] have
indicated that high levels of ‘‘psychological demands’’ are
associated with work-related musculoskeletal disorders. In
addition, Waersted et al. [1996] have demonstrated through
EMG-recordings that trapezius muscle motor units actively
fire when performing a cognitively demanding choicereaction time task. Results from this investigation support
these past findings and suggest that additional laboratory
investigations on how cognitive/psychological demands lead
to physiological changes and associated reports of pain and
other symptoms should utilize conditions/tasks related to
decision-making, memorization of pertinent information for
performing a job task, and information processing.
Lack of involvement in decision making processes
and feedback were also found to serve as key sources of
job stress that place workers at risk for symptoms irrespective of ergonomic exposures. Such stressors may reflect
a lack of perceived control at work and/or supervisor/
co-worker support. Subsequently, these factors may have
moderating effects on the experience of other job stressors
and may potentially lead to subsequent distress and impact
general physical and psychological health [Spector, 1998].
Past research has found that lack of influence/control over
work [Lagerstrom et al., 1995], decision-making opportunities [Hales et al., 1994], and supervisor/social support
[Lagerstrom et al., 1995; Toomingas et al., 1997] are
associated with greater risks for musculoskeletal pain and
symptoms.
When examining the biomechanical and work organization factor combinations, the magnitude of the risks are not
observed to increase appreciably in comparison to those from
the individual components alone. These findings do not support the notion that work organization factors interact, either
on an additive or a multiplicative scale, with biomechanical/
physical factors [Kleinbaum et al., 1982]. Nevertheless,
the complex nature of work-related musculoskeletal symptoms/disorders certainly warrants further study into more
fully understanding any relationship between risk factors.
MacDonald et al. [2001] have suggested that the effect of
physical and psychosocial stressors on occupational health
outcomes may be rooted in shared common qualities of
work and how it is performed. This suggestion was based
on correlation and factor analyses that indicated that the
physical and psychosocial stressors, repetition and job
control, had a shared variance [MacDonald et al., 2001].
Additionally, it is possible that a worker’s response to job
demands (either physical or psychosocial), or workstyle
[Feuerstein et al., 1999b], may trigger certain physiological
responses that intensify pathological processes in the LB and/
or UE regions. Examples of such physiological processes
504
Huang et al.
include sustained motor unit activity [Lundberg et al., 1999]
and/or elevations in norepinephrine, epinephrine, adrenocorticotropin hormone, and cortisol [Frankenhaeuser and
Lundberg, 1982; Gerra et al., 2001]. Although research is
required to delineate such hypothesized mechanisms, the
present findings provide further direction on conceptualizing
these pathways where investigations should focus.
The present investigation provided additional information into specific dimensions of work organization and
their risks for musculoskeletal symptoms both individually
and when combined with biomechanical/physical stressors.
Nevertheless, interpretation of the results should recognize
the study’s limitations. The cross-sectional methodology can
only give indications of the associations between risk factors
and musculoskeletal symptoms and not cause–effect relationships [Kleinbaum et al., 1982]. Currently, efforts are
underway to examine whether the identified risk factors
predict future clinic visits for a musculoskeletal disorder
as a proxy for severity. Biomechanical/physical and work
organization exposures were also determined through selfreport. While a reporting bias may have occurred, Wiktorin
et al. [1993] have found that self-reported exposures to
various work postures including having one’s head bent in a
forward position, sitting, and lifting had moderate correlations and ‘‘acceptable’’ accuracy with objective measurements from a posimeter, inclinometer, and observation by
an ergonomist. Kasl [1998] also notes that although subjective measurement tools that enable the assessment of
perceptions of environmental conditions are important in
empirical investigations of job stress, objective measures of
the ‘‘actual’’ work conditions may provide a clearer picture
of potential etiological processes and help reduce potential
confounding from influences on subjective reports. Additionally, as with many cross-sectional studies, the possibility
of a ‘‘common instrument bias’’ should be considered since
both exposure and symptoms were measured simultaneously.
Studies [e.g., Wiktorin et al., 1993] have suggested that
individuals with musculoskeletal complaints may tend to
underreport exposures (e.g., lifting). While efforts were
made to separate question items by type (e.g., biomechanical,
work organization, symptoms) and symptoms were assessed
in relation to the past 12 months (versus at the time of
assessment), responses may have been impacted by the use of
a single questionnaire.
The use of a military sample could also lead to questions
about the ability to generalize results to a civilian population.
For example, the organizational climate of the Marine Corps
differs from certain civilian workplaces despite the possibility that the physical work tasks are similar [Katzenbach
and Santamaria, 1999]. Yet, the observation that a majority
of study participants had job tasks with generic job descriptions that were similar to their civilian counterparts [U.S.
Department of Labor, 1991; Headquarters, U.S. Marine
Corps, 1999] provides support that findings should be appli-
cable to both military and civilian workers. The ethnic and
racial diversity of the sample was also a particularly unique
characteristic of this study and are of particular importance given the need to understand health outcomes among
people of different racial and ethnic backgrounds [Dimsdale,
2000]. However, the present study sample was relatively
young (mean age ¼ 28.0 years) and was 88.2% male, reflecting the predominance of males among the enlisted ranks
in the Marine Corps (94.2%) [Division of Public Affairs,
Headquarters Marine Corps, 1999]. The overrepresentation
of young males would suggest that additional studies in both
military and civilian populations be conducted with a particular emphasis on incorporating females to determine
whether gender should be considered more strongly in determining risk and developing workplace interventions.
Since high levels of physical stressors that included
repetitive movements, frequent bending/twisting, sustained awkward postures, and/or inadequate rest/recovery posed
significant risks to individuals for musculoskeletal symptoms, job redesign that decreases such exposures represents a
logical component of prevention/intervention [Chaffin,
1997; Smith and Cohen, 1997]. Given the possible biobehavioral mechanisms related to work-related musculoskeletal disorders previously described, especially in relation to
time pressure, techniques such as programmed rest breaks
and relaxation training might assist in reducing adrenergic
responsivity and facilitate muscle tension release and/or reduce the likelihood for muscular overexertion [Everly, 1989;
van der Hek and Plomp, 1997]. Instruction on problem
solving methods may also assist with reducing elements that
contribute to greater cognitive demands, cognitive uncertainty, or interpersonal demands can be better identified and
actions can be taken to assist with reducing or eliminating
these stressors [D’Zurilla and Chang, 1995].
From an organizational standpoint, operational efforts
should consider facilitating participation in ergonomic redesign and decision-making processes and decreasing work
aspects that may contribute to greater time pressure [Noro,
1999; Nytro et al., 2000]. Based on the present findings,
such participation should be associated with a lesser likelihood for concurrent report of LB and UE symptoms.
Additionally, encouragement by senior management in
addressing work processes and organization would demonstrate a needed emphasis and commitment in efforts aimed
at reducing the occurrence of work-related musculoskeletal
disorders [National Research Council and Institute of Medicine (NRC/IOM), 2001].
The present study highlights the importance of considering both biomechanical and work organizational factors in the occurrence of LB and UE symptoms. While no
synergism was found, these findings suggest a potential
utility in designing intervention programs that address biomechanical exposures such as repetition, awkward positions,
and bending/twisting in addition to work organization factors
Biomechanical and Work Organization Factors
related to scheduling, job design, and interpersonal factors in
addition to time pressure and cognitive demands. Studies that
evaluate such a multifaceted approach among different work
groups are required before further conclusions can be made.
Based on the present study population, such programs would
appear to be of particular benefit to those working in office
environments. These efforts that incorporate both physical
and work characteristics on the job and company/organizational levels considers their impact on musculoskeletal health
can in turn help enhance worker and organizational health,
function, and productivity.
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for use in an office work environment. J Occup Environ Med 44:73–81.
Devereux JJ, Buckle PW, Vlachonikolis IG. 1999. Interactions between
physical and psychosocial risk factors at work increase the risk of back
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353.
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Eastman Kodak Company. 1986. Ergonomic design for people at work.
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Engels JA, van der Gulden JW, Senden TF, van’t Hof B. 1996.
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Engstrom T, Hanse JJ, Kadefors R. 1999.
Individual and Combined Impacts of
Biomechanical and Work Organization Factors
in Work-Related Musculoskeletal Symptoms
Grant D. Huang,
1,2
MPH, PhD,
Michael Feuerstein, PhD, MPH,1,2,3 Willem J. Kop,
Kenneth Schor, DO, MPH,4 and Freya Arroyo, BS5
PhD,
2
Background Investigations of work-related low back (LB) and upper extremity (UE)
disorders have increasingly utilized multivariable models that include biomechanical/
physical and work organization factors. However, the nature of any interactive effects is
not well understood.
Methods Using questionnaires, high and low exposure groups for biomechanical/
physical factors, cognitive demands, cognitive processing, interpersonal demands, participatory management, skill discretion, and time pressure for 289 individuals (U.S. Marines)
were identified. Musculoskeletal symptom status was also determined by questionnaire.
Individual and biomechanical–psychosocial combinations were examined in adjusted
multivariable logistic regression analyses.
Results Time pressure was associated with both LB and UE symptoms (odds ratio(s) (OR)
range ¼ 2.13–3.09), while higher biomechanical exposures were risk factors for LB
symptoms (OR ¼ 2.07; 95% confidence intervals (CI): 1.00–4.35) and concurrent LB and
UE symptoms (OR ¼ 2.80; CI: 1.35–5.83). Greater risks for concurrent LB and UE
symptoms were indicated for combinations involving higher biomechanical exposure and:
time pressure (OR ¼ 2.21; CI: 1.19–4.10); cognitive demands (OR ¼ 2.25; CI: 1.23–
4.09); cognitive processing (OR ¼ 2.08; CI: 1.16–3.75); interpersonal demands
(OR ¼ 2.44; CI: 1.35–4.41); participatory management (OR ¼ 2.50; CI: 1.30–4.81).
Results did not suggest any interaction between biomechanical and work organization
factors.
Conclusions While no synergism was indicated, the present findings emphasize the need
to consider both biomechanical factors and specific work organization factors,
particularly time pressure, in reducing musculoskeletal-related morbidity.
Am. J. Ind. Med. 43:495–506, 2003. Published 2003 Wiley-Liss, Inc.y
KEY WORDS: ergonomics; work organization; psychosocial; low back pain; upper
extremity; symptoms; secondary prevention
1
Department of Preventive Medicine & Biometrics, Uniformed Services University of the
Health Sciences, Bethesda, Maryland
2
Department of Medical & Clinical Psychology, Uniformed Services University of the
Health Sciences, Bethesda, Maryland
3
Division of Behavioral Medicine, Department of Psychiatry, Georgetown University
School of Medicine,Washington, District of Columbia
4
Health Services Division, Headquarters, U.S. Marine Corps,Washington, D.C.
5
Safety Division, Headquarters, U.S. Marine Corps,Washington, D.C.
The opinions and assertions contained herein are the private views of the authors and are
not to be construed as being official or as reflecting the views of the Uniformed Services
University of the Health Sciences, the Department of Defense, or the U.S. Marine Corps.
Published 2003 Wiley-Liss, Inc.
y
This article is a US Government work and, as such, is in
the public domain in the United States of America.
Contract grant sponsor: Safety Division, Headquarters, U.S. Marine Corps; Contract grant
number: MIPROLYLR00370.
*Correspondence to: Grant D. Huang, Department of Preventive Medicine & Biometrics,
Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda,
MD 20814. E-mail: ghuang@usuhs.mil
Accepted16 December 2002
DOI 10.1002/ajim.10212. Published online in Wiley InterScience
(www.interscience.wiley.com)
496
Huang et al.
INTRODUCTION
Work-related low back (LB) and upper extremity (UE)
disorders can significantly impact the health, function, and
productivity of workers and organizations [Duquesnoy et al.,
1998; Morse et al., 1998]. Furthermore, considerable financial burdens associated with medical care and indemnity
payments have been attributed to these problems [Feuerstein
et al., 1998; Hashemi et al., 1998]. Using various job analysis
methods, biomechanical and physical exposures such as
heavy work, static work, awkward postures, lifting, twisting
and bending, repetition, excessive force, and vibration have
been established as risks for work-related LB pain and/or UE
symptoms [Bernard, 1997; National Research Council and
Institute of Medicine (NRC/IOM), 2001]. An increasing
number of epidemiological studies have also indicated that
occupational psychosocial factors as well as characteristics
of work and how it is organized, or work organization factors,
are associated with and/or predictive of work-related
musculoskeletal symptoms and disorders [National Research
Council and Institute of Medicine (NRC/IOM), 2001;
Bongers et al., 2002]. While theoretical frameworks and
existing research have highlighted the need for efforts that
simultaneously address biomechanical and work organization stressors in the prevention of work-related musculoskeletal morbidity [Huang et al., 2002], the relative and
combined impacts they have on workers exposed to both
sets of factors are not well understood.
Multivariable models that include both biomechanical/
physical and occupational psychosocial factors have been
used in some investigations of work-related LB and UE
disorders [e.g., Skov et al., 1996; Polyani et al., 1997; Kerr
et al., 2001]. However, fewer studies have examined the
combined and/or interactive effects of these factors. Marras
et al. [2000] reported that the introduction of psychosocial
stressors, in the form of visual feedback suggesting
inadequate performance and criticism, resulted in significant
increases in spinal loadings, muscle responses, and kinetic
responses in a laboratory-based lifting task. Among individuals from various occupations, high exposures to both
physical and psychosocial stressors were found to place one
at a 2.8-fold greater likelihood for the self-report of LB pain
in the past 7 days when compared to workers with low levels
of exposure [Devereux et al., 1999]. In this cross-sectional
study, high physical exposure was defined as the self-report
of: (1) lifting > 16 kg between 1 and 10 times an hour; or
(2) lifting 6–15 kg between 1 and 10 times an hour and
experiencing vibration while sitting more than or equal to
half of the working day. High exposure to psychosocial
stressors was based on three different self-report scales and
defined as having any two of the following: high mental
demands; low job control; low social support. While
Devereux et al. [1999] emphasized the importance of combined exposure to physical and psychosocial stressors in LB
pain, research is still needed to examine work organization
stressors in the context of biomechanical factors in workers
experiencing LB and UE symptoms. Furthermore, given
recent findings that suggest physical and psychosocial factors
share a common variance based, in part, on how work is
organized [MacDonald et al., 2001], studies on musculoskeletal-related outcomes that examine these factors individually and in combination can assist with determining the
nature of any effects.
A few investigations have suggested that biomechanical
and some work organization factors may interact to influence
UE symptoms. A study of office workers by Bergqvist et al.
[1995] indicated that the interaction between working on
a visual display terminal and having limited opportunities
for rest breaks was a risk factor (odds ratio(s) (OR) ¼ 4.8,
confidence intervals (CI): 1.3–18.1) for reporting neck/
shoulder discomfort. In the same study, arm/hand diagnoses
as determined by a physiotherapist were associated with
limited rest break opportunities and lower arm support in
persons who worked more than 20 hr a week. Faucett and
Rempel [1994] also found that decision latitude, job insecurity, supervisor support, and supervisor conflict all independently interacted with relative keyboard height (based on
the cross-product of the scores on the respective variables)
in determining severity of UE numbness in newspaper
employees. These studies suggest that particular job- and
company-level [Shannon et al., 2001] and physical workstation factors may operate in conjunction to impact worker
UE health. However, interpreting such statistical interactions is complex and it is not clear whether any synergism
exists between such biomechanical/physical and work organization factors.
The primary objectives of the present study were to
determine whether different levels of exposures to both
biomechanical/physical and specific work organization
stressors were associated with LB, UE, and concurrent LB
and UE symptoms and whether the magnitudes of any associations indicated any synergism. Additionally, by examining individuals working in jobs previously identified as
having higher rates for musculoskeletal-related clinic visits,
this investigation was conducted with the intent of continuing
on-going efforts by our group to develop a secondary prevention program for these workers.
METHODS
Study Participants
Active duty, enlisted U.S. Marines involved in high-risk
jobs for musculoskeletal-related clinic visits [Huang et al.,
2001] were invited through news bulletins, electronic mail,
and section heads to attend an information session about a
research study on musculoskeletal disorders. Jobs targeted in
the recruitment process were: Image Interpretation; Auditing
Biomechanical and Work Organization Factors
and Accounting; Disbursing; Information and Education;
and Transportation. After providing the details of the study,
which were approved by a university Institutional Review
Board, all individuals deciding to participate were asked
to complete an informed consent form and a questionnaire
that assessed potential risk factors and musculoskeletal
symptoms.
Four hundred individuals were presented with the details
of the study and 307 (76.8%) consented to participate.
Among these consenting individuals, 18 did not meet
eligibility criteria for the study because they indicated
having musculoskeletal symptoms that resulted from a nonwork-related accident/trauma (e.g., sports, traffic accident).
Questionnaire
The questionnaire contained items and scales that: had
reported associations with work-related musculoskeletal
symptoms, disorders, or disability and/or had been used in
previous studies; had acceptable psychometric properties
(e.g., internal consistency, discriminant validity); could be
easily administered (i.e., relatively few items); and suggested
potential areas for modification through intervention efforts.
These items are described in the following sections. Interested readers may contact the primary author for a copy of
the questionnaire.
Biomechanical/physical factors
Exposures to biomechanical/physical risk factors were
assessed by the Job Factors—Description of Work subscale
of the U.S. Air Force Job Requirements and Physical
Demands Survey (JRPD) [Marcotte et al., 1997]. This selfreport measure contains 38 items on the frequency of
exposure to movements, postures, loads, and environmental
factors while performing a work task. Reliability from a
2-week test–retest was found to have a kappa of 0.68 (88%
raw agreement) and adequate validity in relation to worksite
assessments performed by an ergonomist [Marcotte et al.,
1997]. A recent study of office workers (n ¼ 92) also found a
subset of these items to be normally distributed and that
higher levels of exposure were associated with UE pain,
symptom severity, and functional limitations [Dane et al.,
2002].
Work organization
Items used to measure work organization assessed
multiple dimensions of this construct (i.e., scheduling, job
design, management style, interpersonal) [Cooper and
Marshall, 1976; National Institute for Occupational Safety
and Health (NIOSH), 1996]. All items in the survey were
presented without reference to a specific work organization
category.
497
Scheduling. Three questions adapted from the Work
Environment Scale [Moos, 1994] were used to query one’s
ability to relax at work, perceptions of constant pressure to
keep working, and sense of urgency on the job. Two questions
on work breaks and shift work from the Biological scale of
the Multimethod Job Design Questionnaire [Campion, 1988]
were also included.
Job design. Skill discretion and decision authority were
assessed by items from the Job Content Questionnaire
[Karasek et al., 1998]. Additionally, 13 questions obtained
from a prior NIOSH study [Hales et al., 1994] and dealing
with cognitive aspects of the job such as information
processing, memory, and routine associated with one’s job
were used.
Management style. Three items from Hales et al. [1994]
were included to determine how much a worker participates
with others in making decisions and/or setting the way things
are performed at work. The ‘‘Feedback from Agents’’
subscale of the Job Diagnostic Survey (JDS) [Hackman
and Oldham, 1974] was also used to ask about the extent
and frequency of feedback one receives from supervisors and
co-workers.
Interpersonal. Three items dealing with the level of
personal interaction required on the job and obtained from
the ‘‘Dealing with Others’’ subscale of the JDS [Hackman
and Oldham, 1974] were incorporated.
In addition to the items on biomechanical/physical
and work organization factors, there were questions related to demographics, health behavior, physical demands,
and individual psychosocial factors. Demographic information obtained were: age; gender; marital status; number
of children supported; education level; rank; length of
service; military occupational specialty (MOS); and length
of time in MOS.
Individuals were asked how often they completed at
least 20 min of non-stop aerobic activity based on a question from U.S. Army Health Risk Appraisal (HRA).
Responses on this item have been found to predict backrelated disability in U.S. Army soldiers [Feuerstein et al.,
1999a]. A modified Borg [1998] CR10 Scale was also used to
assess the physical effort required from one’s job during
a ‘‘typical day’’ [Feuerstein et al., 2001].
The Conflict Subscale of the Family Environment
Scale [Moos and Moos, 1981] was included based on past
research that reported a group of ambulatory chronic LB
pain individuals to have greater levels of family conflict
and general stress and lower levels of family control
[Feuerstein et al., 1985]. One item from the Conflict Subscale, ‘‘Family members sometimes hit each other’’ was not
included because of its potential in incriminating military
personnel.
498
Huang et al.
A question from the HRA addressing the frequency that
worries interfered with life was also asked based upon
findings that self-reported worries are associated with backand UE-related disability in U.S. Army soldiers [Huang et al.,
1998; Feuerstein et al., 1999a].
Musculoskeletal symptoms
Symptoms in the lower back, neck, shoulders, elbows/
forearms, and wrists/hands regions were assessed by using a
modified NIOSH symptom survey [Bernard et al., 1994].
Questions addressed type of symptoms, time of first onset,
frequency, duration, intensity, work interference, and associated limited duty within the past 12 months.
Case Definitions
Four separate groups were delineated based on responses to the following questions: (1) do you experience
physical problems in any of the following areas of your body
(i.e., lower back, neck, shoulder, elbows/forearms, wrists/
hands); (2) when did you first notice the problem? An
asymptomatic control group was defined as those individuals
who did not report having any musculoskeletal symptoms in
any location. Symptomatic cases were classified as having
LB symptoms only, UE symptoms only, or both LB and UE
symptoms simultaneously. Additionally, only those individuals who reported having symptoms since beginning work
in their current MOS and who did not report having had
a prior accident/trauma (e.g., sports, traffic accident) to the
region were included as cases for any of the symptomatic
groups.
Analyses
Factor analyses of the work organization items were
conducted to determine whether specific types of work
organization stressors could be empirically delineated and
to determine which items defined them. To maximize
the variances of factor loadings so that unique factors
could be partitioned, a varimax (i.e., orthogonal) rotation
was used with a rotated component matrix [Nunnally and
Bernstein, 1994]. Those factors with component variances
(i.e., eigenvalues) above one were retained for further analyses [Tabachnick and Fidell, 1983; Nunnally and Bernstein,
1994].
A risk stratification procedure was then performed to
categorize study participants as having either ‘‘high’’ or
‘‘low’’ levels of exposure on the JRPD and on each work
organization factor identified by the factor analyses. The
exposure level for a particular variable was determined by
his/her score relative to a median split of the variable’s scores
from the entire sample. This method was used because prior
research has not established cut-off points for delineating risk
levels. With the exception of the participatory management
variable, a ‘‘high’’ level of exposure indicated more adverse
exposure.
For each of the possible biomechanical/work organization factor combinations, study participants were classified
into a low/low, high/low, low/high, or high/high exposure
group. Classifications were based on the individual’s respective exposure level to biomechanical factors and to the
particular work organization variable of interest.
Using logistic regression analyses with case status (i.e.,
LB case/control; UE case/control; LB and UE case/control)
as the dependent variable, each individual biomechanical
(i.e., JRPD) and work organization variable was examined
separately while adjusting for age, gender, education level,
frequency of exercise, perceived exertion, family conflict,
and worries. Collinearity between these control variables
and the independent variables of interest were examined by
computing Pearson correlation coefficients. Subsequently,
each biomechanical/work organization combination was
entered into a multivariable logistic regression model that
adjusted for age, gender, education level, frequency of
exercise, perceived exertion, family conflict, and worries.
Each of the combinations was examined independently
from the other combinations and used the low biomechanical exposure/low work organization combination as the
referent group. For the analysis involving the biomechanical/
participatory management combination, the referent group
was the one with lower biomechanical exposures and
higher levels of participatory management. The magnitudes of association were determined by obtaining OR,
parameter estimates (b coefficients), 95% CI, and significance levels.
Prior to conducting any analyses, all missing data were
replaced by the mode of that respective question. Less than
3% of the total sample had missing data for any given item.
All analyses were performed using SPSS v.10.1 (SPSS,
Chicago, IL).
RESULTS
Subject Characteristics
Distributions of the study participants according to case
status were: 31.1% (n ¼ 90) asymptomatic controls; 20.4%
(n ¼ 59) LB symptoms only cases; 19.7% (n ¼ 57) UE
symptoms only cases; and, 28.7% (n ¼ 83) cases with both
LB and UE symptoms. The demographic characteristics
most commonly reported were: male (88.2%); ‘‘White’’
(51.6%); married (39.8%); some college/other post high
school education (45.7%), and the rank of E-5, Sergeant
(26.6%). Table I more specifically details the demographic
distribution of the sample.
Using the U.S. Department of Defense Primary
Occupational Codes [U.S. Department of Defense, 1997],
Biomechanical and Work Organization Factors
499
TABLE I. Demographic Characteristics
Age (in years), mean (SD)
Gender
Males
Females
Race
White/Caucasian
Black/African American
Hispanic/Latino
Asian
American Indian
Education
H.S. grad/GED
Some college/other post H.S.
2 year degree
4 year degree/college
Some graduate work
Marital Status
Single
Married
Separated
Divorced
Rank
E2, Private First Class
E3, Lance Corporal
E4, Corporal
E5, Sergeant
E6, Staff Sergeant
E7, Gunnery Sergeant
E8, Master Sergeant or First Sergeant
E9,MasterGunnerySergeantorSergeantMajor
Controls
(n ¼ 90)
Back only cases
(n ¼ 59)
Upper extremity (UE)
only cases (n ¼ 57)
BackandUE cases
(n ¼ 83)
Total sample
(n ¼ 289)
26.9 (6.5)
28.0 7.8
26.5 (6.6)
30.3 (7.6)
28.0 (7.2)b
n (%)a
n (%)a
n (%)a
n (%)a
n (%)a
80 (88.9)
10 (11.1)
51 (86.4)
8 (13.6)
52 (91.2)
5 (8.8)
72 (86.7)
11 (13.3)
255 (88.2)
34 (11.8)
46 (51.1)
21 (23.3)
21 (23.3)
2 (2.2)
0 (0)
31 (52.5)
17 (28.8)
9 (15.3)
2 (3.4)
0 (0)
34 (59.6)
12 (21.1)
8 (14.0)
2 (3.5)
0 (0)
38 (45.8)
24 (28.9)
18 (21.7)
1 (1.2)
1 (1.2)
149 (51.6)
74 (25.6)
56 (19.4)
7 (2.4)
1 (0.3)
37 (41.1)
41 (45.6)
7 (7.8)
2 (2.2)
1 (1.1)
29 (49.2)
24 (40.7)
2 (3.4)
4 (6.8)
0 (0)
25 (43.9)
25 (43.9)
1 (1.8)
1 (1.8)
2 (3.5)
32 (38.6)
42 (50.6)
5 (6.0)
1 (1.2)
2 (2.4)
123 (42.6)
132 (45.7)
15 (5.2)
8 (2.8)
5 (1.7)
30 (33.3)
36 (40.0)
4 (4.4)
3 (3.3)
23 (39.0)
26 (44.1)
0 (0)
5 (8.5)
26 (45.6)
17 (29.8)
1 (1.8)
6 (10.5)
30 (36.1)
36 (43.3)
6 (7.2)
2 (2.4)
109 (37.7)
115 (39.8)
11 (3.8)
16 (5.5)
5 (5.6)
18 (20.0)
16 (17.8)
25 (27.8)
12 (13.3)
8 (8.9)
4 (4.4)
2 (2.2)
2 (3.4)
14 (23.7)
10 (16.9)
17 (28.8)
4 (6.8)
4 (6.8)
4 (6.8)
4 (6.8)
3 (5.3)
14 (24.6)
17 (29.8)
8 (14.0)
8 (14.0)
4 (7.0)
3 (5.3)
0 (0)
2 (2.4)
13 (15.7)
7 (8.4)
27 (32.5)
10 (12.0)
12 (14.5)
8 (9.6)
4 (4.8)
12 (4.2)
59 (20.4)
50 (17.3)
77 (26.6)
34 (11.8)
28 (9.7)
19 (6.6)
10 (3.5)
a
Percentage of group; total n for category may not equal total n for group because of missing data.
t-test comparing group to controls: t ¼ 3.15, df ¼171, P < 0.01.
b
the majority of Marines were found to have jobs from
the Functional Support and Administration category. This
finding indicated a consistency with the intended study
recruitment. Specifically, there were 184 (64.2%) individuals in this occupational category which includes the following subcategories: Personnel; Administration; Clerical/
Personnel; Data Processing; Accounting/Finance/Disbursing; Other Functional Support; and, Information and
Education. Other occupational categories (and percent
distribution) were: Service/Supply Handlers (10%); Infantry,
Gun Crews/Seamanship (10%); Communications/Intelligence Specialists (6%); Electrical/Mechanical Equipment
Repairers (5%); Other (3%).
Chi-square tests on gender, race, education level, marital
status, rank, and MOS indicated no significant differences
between controls and any of the symptomatic case groups.
Only the group with concurrent LB and UE symptom was
found to be significantly older in age than the control group
(t ¼ 3.15, df ¼ 171, P < 0.01).
Work Organization Factors
Factor analyses indicated that five components could be
identified from the work organization items. These components were Job Design, Participatory Management, Time
Pressure, Cognitive Processing, and Interpersonal Demands.
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Huang et al.
Each factor had initial eigenvalues above 1.6. While one
reason for conducting the factor analyses was to reduce the
number of items to be included within a particular work
organization category, the Job Design factor was found to
contain the items from the skill discretion subscale of the Job
Content Questionnaire [Karasek et al., 1998] and from the
cognitive demands section of the NIOSH work survey [Hales
et al., 1994]. Therefore, these items were separated into their
respective subscales to maintain their original integrity.
Subsequent analyses examined skill discretion and cognitive
demands as separate variables.
The components delineated from the factor analyses, the
specific questionnaire items that comprised each factor,
factor loadings, initial eigenvalues, and percent variance are
given in Table II.
Cronbach’s alphas for each of the identified work
organization factors are given in Table III. As shown,
most work organization factors had adequate reliabilities
with Cronbach’s coefficient alphas ranging from 0.71 to
0.83 [Nunnally and Bernstein, 1994]. The cognitive processing factor had a modest Cronbach’s coefficient alpha
of 0.60.
TABLE II. FactorAnalyses of Work Organization Items
Factor loading
Job designa
Skill discretion
My job requires that I learn new things
My job requires me to be creative
My job requires a high level of skill
I get to do a variety of different things on my job
I have an opportunity to develop my own special skills
Cognitive demands
My job requires me to make many decisions
To do my job well, I have to be able to do a lot of things mentally at the same time
My job requires me to remember a great deal of information for brief periods of time
My job often requires me to learn new procedures
My job requires me to remember many different things
Participatory management
To what extent do supervisors or co-workers let you know how well you are doing on the job
The supervisors and co-workers on this job almost never give me any ‘‘feedback’’about how well
I am doing in my work
Supervisors often let me know how well they think I am performing on the job
How much do you take part with others in making decisions that affect you?
How much do you participate with others in helping set the way things are done on your job
How much do you decide with others what part of a task you will do
Time pressure
In my group, people cannot afford to relax
In our group, there is constant pressure to keep working
In my group,there is a sense of urgency about everything
Cognitive processing
I can easily see or hear the information I have to use in my job
The information I receive is organized for me in ways that seem natural and easy to deal with
I can perform the activities associated with my job without thinking about them
Most of the decisions I make are routine and easy to make
In my job,there are set rules that I follow over and over again
Interpersonal demands
To what extent does your job require you to work closely with other people
The job requires a lot of cooperative work with other people
a
b
Initial eigenvalue
Varianceb (%)
8.63
18.0
4.78
9.9
2.79
5.8
1.82
3.8
1.61
3.4
0.696
0.691
0.720
0.720
0.731
0.510
0.562
0.526
0.721
0.660
0.665
0.546
0.644
0.689
0.673
0.668
0.714
0.736
0.659
0.441
0.462
0.478
0.567
0.716
0.564
0.672
The job design factor was separated into the two original scales (skill discretion and cognitive demands) from which the items came.
Cumulative variance ¼ 40.9.
Biomechanical and Work Organization Factors
TABLE III. Internal Consistency of Work OrganizationVariables
Work organization factor
Cronbach’s alpha
Cognitive demands
Cognitive processing
Interpersonal demands
Participatory management
Skill discretion
Time pressure
0.827
0.604
0.709
0.777
0.797
0.816
Biomechanical and Work
Organization Associations With
Musculoskeletal Symptoms
Table IV reports the OR, 95% CI, and levels of
significance for having musculoskeletal symptoms when
501
one had the more adverse level of exposure to a particular
biomechanical/physical or work organization variable. These
figures are the results after adjusting for age, gender,
education level, frequency of exercise, perceived exertion
at work, worries, and family conflict. Pearson correlation
coefficients indicated relatively low (r ¼ 0.02–0.25) associations between control variables and the biomechanical and/
or work organization variables of interest. Most of these
correlations were not statistically significant. Table IV also
provides the number of cases and controls within each level
of exposure.
The findings indicate that a high level of exposure to
biomechanical factors was a significant risk factor for those
with LB symptoms only (OR ¼ 2.07; 95% CI: 1.00–4.35)
and with both LB and UE symptoms (OR ¼ 2.80; CI: 1.35–
5.83). Among the work organization stressors, only time
pressure (OR ¼ 2.13–3.09) was a consistent risk factor across
TABLE IV. Biomechanical and Work Organization Risk Factors for Musculoskeletal Symptoms
Back symptoms(n ¼149)
Variable: level of exposure
Biomechanical exposure
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Cognitive demands
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Cognitive processing
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Interpersonal demands
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Participatory management
Low exposure
N low exposure (cases/controls)
N high exposure (cases/controls)
Skill discretion
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
Time pressure
High exposure
N high exposure (cases/controls)
N low exposure (cases/controls)
UE symptoms (n ¼147)
Back and UE symptoms (n ¼173)
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
2.07 (1.00^4.35)
32/35
27/55
0.05
1.76 (0.82^3.77)
31/35
26/55
0.15
2.80 (1.35^5.83)
48/35
35/55
0.01
1.32 (0.64^2.79)
27/36
32/54
0.45
1.36 (0.66^2.82)
27/36
30/54
0.40
2.20 (1.11^4.37)
47/36
36/54
0.03
0.68 (0.33^1.42)
23/42
36/48
0.31
0.63 (0.29^1.35)
22/42
35/48
0.23
1.77 (0.91^3.42)
49/42
34/48
0.09
0.80 (0.39^1.64)
29/46
30/44
0.54
1.26 (0.60^2.64)
33/46
24/44
0.54
1.48 (0.75^2.90)
55/46
28/44
0.26
1.56 (0.73^3.33)
27/54
32/36
0.25
1.56 (0.71^3.44)
25/54
32/36
0.27
2.32 (1.13^4.73)
37/54
46/36
0.02
1.35 (0.65^2.79)
34/45
25/45
0.42
0.75 (0.36^1.58)
26/45
31/45
0.45
1.28 (0.65^2.50)
43/45
40/45
0.47
2.96 (1.35^6.47)
36/35
23/55
0.01
3.09 (1.39^6.88)
35/35
22/55
0.01
2.13 (1.04^4.37)
44/35
39/55
0.04
After adjusting for age, gender, education level, exercise, physical demands, life-interfering worries, and family conflict.
502
Huang et al.
all case groups. Low participatory management (OR ¼ 2.32;
CI: 1.13–4.73) and cognitive demands (OR ¼ 2.20; CI:
1.11–4.37) were also found to be individual risk factors, but
only for those with both LB and UE symptoms.
For control variables, age was a significant (P < 0.05)
risk factor for LB symptoms only (OR ¼ 1.07 per year;
CI: 1.01–1.13) in the model including time pressure and for
concurrent LB and UE symptoms (OR ¼ 1.1; CI: 1.04–1.18)
in all logistic regression models. Family conflict was a
significant risk factor for LB symptoms only (OR ¼ 1.3;
CI: 1.05–1.68) and UE symptoms only (OR range: 1.2–1.3;
CI: 1.04–1.61) for all models.
Table V provides the OR and 95% CI computed from the
logistic regression analyses for all biomechanical/work
organization combinations after adjusting for age, gender,
education level, health behavior, perceived exertion at work,
life-interfering worries, and family conflict. Only the
combination of high biomechanical exposure and high levels
of time pressure was significantly associated with musculoskeletal symptoms in all groups (OR ¼ 2.21 (LB and UE);
OR ¼ 2.61 (LB only); OR ¼ 2.90 (UE only)). Other significant combinations only placed one at greater risks for
having concurrent LB and UE symptoms and included high
biomechanical exposure and: low participatory management
(OR ¼ 2.50; CI: 1.30–4.81); high interpersonal demands
(OR ¼ 2.44; CI: 1.35–4.81); high cognitive demands (OR ¼
2.25; CI: 1.23–4.09); and high cognitive processing (OR ¼
2.08; CI: 1.16–3.75).
Age was found to be a significant (P < 0.05) risk
factor for LB symptoms only (OR ¼ 1.1; CI: 1.00–1.14)
for the models involving the combinations with biomechanical exposure/time pressure and biomechanical exposure/
cognitive processing combinations. Age (OR ¼ 1.1; CI:
1.06–1.20) was also a significant risk factor for concurrent
LB and UE symptoms in all models with the biomechanical/
work organization combination. Significant OR for family
conflict (OR range ¼ 1.3–1.4) were found for LB symptoms
only in all models and for UE symptoms only in all models
except that involving the combination of biomechanical exposure/participatory management.
TABLE V. Biomechanical Exposure and Work Organization Combinations Associated With Musculoskeletal Symptoms
Back symptoms (n ¼149)
Variables: level biomechanical exposure/
level work organization
Biomechanical exposure and cognitive demands
High/low
Low/high
High/high
Biomechanical exposure and cognitive processing
High/low
Low/high
High/high
Biomechanical exposure and interpersonal demands
High/low
Low/high
High/high
Biomechanical exposure and participatory management
High/high
Low/low
High/low
Biomechanical exposure and skill discretion
High/low
Low/high
High/high
Biomechanical exposure and time pressure
High/low
Low/high
High/high
OR (95% CI)
1.31 (0.69^2.49)
0.79 (0.40^1.57)
1.54 (0.81^2.96)
1.53 (0.80^2.90)
0.39 (0.19^0.84)
1.59 (0.81^3.12)
1.53 (0.83^2.83)
0.65 (0.35^1.19)
1.33 (0.69^2.57)
0.90 (0.47^1.75)
0.67 (0.34^1.32)
2.34 (1.19^4.63)
1.41 (0.73^2.70)
0.91 (0.50^1.64)
1.54 (0.82^2.92)
0.63 (0.29^1.35)
1.00 (0.48^2.09)
2.61 (1.39^4.91)
P
0.26
0.41
0.50
0.19
0.10
0.20
0.02
0.18
0.28
0.18
0.16
0.39
0.09
0.76
0.25
0.01
0.19
0.31
0.74
0.18
0.02
0.23
0.99
0.01
UE symptoms (n ¼147)
OR (95% CI)
1.15 (0.60^2.18)
0.86 (0.43^1.74)
1.50 (0.77^2.93)
1.62 (0.83^3.17)
0.46 (0.21^1.00)
1.25 (0.63^2.49)
0.87 (0.43^1.77)
0.65 (0.34^1.26)
1.93 (1.02^3.65)
1.05 (0.53^2.08)
0.93 (0.49^1.78)
1.67 (0.85^3.30)
1.61 (0.87^3.00)
0.75 (0.41^1.39)
1.06 (0.53^2.11)
0.46 (0.20^1.07)
1.05 (0.50^2.21)
2.90 (1.49^5.66)
After adjusting for age, gender, education level, exercise, physical demands, life-interfering worries, and family conflict.
P
0.46
0.68
0.68
0.24
0.23
0.16
0.05
0.53
0.22
0.70
0.21
0.04
0.35
0.88
0.83
0.14
0.44
0.13
0.36
0.87
0.01
0.07
0.90
0.01
Back and UE symptoms
(n ¼173)
OR (95% CI)
1.15 (0.61^2.15)
0.88 (0.46^1.69)
2.25 (1.23^4.09)
1.30 (0.79^2.42)
0.80 (0.43^1.48)
2.08 (1.16^3.75)
1.13 (0.61^2.08)
0.64 (0.35^1.14)
2.44 (1.35^4.41)
1.17 (0.64^2.14)
0.98 (0.52^1.84)
2.50 (1.30^4.81)
1.76 (0.96^3.23)
0.83 (0.46^1.47)
1.69 (0.93^3.81)
1.18 (0.64^2.17)
0.88 (0.44^1.76)
2.21 (1.19^4.10)
P
0.01
0.67
0.71
0.01
0.02
0.42
0.47
0.02
0.02
0.69
0.13
0.01
0.01
0.60
0.95
0.01
0.03
0.07
0.52
0.09
0.02
0.59
0.72
0.01
Biomechanical and Work Organization Factors
DISCUSSION
The present cross-sectional study indicated that increased time pressure was a consistent risk factor for symptoms in
the LB and/or UE regions. Exposure to biomechanical factors
was also associated with LB symptoms and concurrent
symptoms in the LB and UE. Higher levels of cognitive
demands and less participation in management were significant work organization stressors, but only among workers
who experienced both LB and UE symptoms. While most
biomechanical/work organization combinations (i.e., biomechanical exposure and time pressure, cognitive demands,
cognitive processing, interpersonal demand, or participatory
management) placed individuals at greater risk for concurrent LB and UE symptoms, the magnitudes of the associations did not suggest any interactive effect between the
biomechanical/physical and work organization factors. The
findings do provide information on specific work organization stressors that should be targeted in intervention
programs that attempt to reduce biomechanical exposures.
Pressure to continuously work and for such work to
be completed urgently were particularly relevant in the
experience of LB and/or UE symptoms. The risks (OR ¼
2.13–3.09) for musculoskeletal symptoms highlight the need
for targeting this dimension of work organization in intervention efforts. Such efforts take on added importance
considering that the risks were found independent of biomechanical factors. Another cross-sectional study of nurses
reported that the belief that one ‘‘ought to slow down at
work’’ had a prevalence odds ratio (POR) of 1.94 for
self-reported back complaints, while a difficult work rate
(POR ¼ 1.68) and the belief that one ought to slow down at
work (POR ¼ 2.71) were associated with arm or neck complaints [Engels et al., 1996]. Increased time pressure at work
(defined by reduced time to complete job-related goals) and
work/rest schedule were also associated with a greater incidence of UE disorders among customer service representatives at a bank [Ferreira et al., 1997]. Birch et al. [2000]
found that higher time pressure in completing a standardized computer task produced greater EMG activity in the
trapezius, deltoid, infraspinatus, and extensor digitorum
muscle groups in female computer aided design operators.
Additionally, Feuerstein and Fitzgerald [1992] have reported
that fewer opportunities to rest were associated with higher
levels of fatigue in sign language interpreters with UE symptoms. It may be possible that time pressure and associated
increase muscle activity along with a reduced number of rest
breaks may set the stage for increased UE symptoms. This
process is consistent with the concept of a high-risk
workstyle [Feuerstein et al., 1999b]. Research has yet to
determine whether time pressure is associated with greater
loads in the trunk musculature. Nevertheless, perceptions
of and/or actual conditions that require the need to keep
working and to work at a faster pace may be especially
503
problematic since they could lead to overexertion and prevent
one from taking breaks that assist with recovery processes
[e.g., Eastman Kodak Company, 1986].
Studies such as those conducted by Engstrom et al.
[1999], Krause et al. [1998], and Polyani et al. [1997] have
indicated that high levels of ‘‘psychological demands’’ are
associated with work-related musculoskeletal disorders. In
addition, Waersted et al. [1996] have demonstrated through
EMG-recordings that trapezius muscle motor units actively
fire when performing a cognitively demanding choicereaction time task. Results from this investigation support
these past findings and suggest that additional laboratory
investigations on how cognitive/psychological demands lead
to physiological changes and associated reports of pain and
other symptoms should utilize conditions/tasks related to
decision-making, memorization of pertinent information for
performing a job task, and information processing.
Lack of involvement in decision making processes
and feedback were also found to serve as key sources of
job stress that place workers at risk for symptoms irrespective of ergonomic exposures. Such stressors may reflect
a lack of perceived control at work and/or supervisor/
co-worker support. Subsequently, these factors may have
moderating effects on the experience of other job stressors
and may potentially lead to subsequent distress and impact
general physical and psychological health [Spector, 1998].
Past research has found that lack of influence/control over
work [Lagerstrom et al., 1995], decision-making opportunities [Hales et al., 1994], and supervisor/social support
[Lagerstrom et al., 1995; Toomingas et al., 1997] are
associated with greater risks for musculoskeletal pain and
symptoms.
When examining the biomechanical and work organization factor combinations, the magnitude of the risks are not
observed to increase appreciably in comparison to those from
the individual components alone. These findings do not support the notion that work organization factors interact, either
on an additive or a multiplicative scale, with biomechanical/
physical factors [Kleinbaum et al., 1982]. Nevertheless,
the complex nature of work-related musculoskeletal symptoms/disorders certainly warrants further study into more
fully understanding any relationship between risk factors.
MacDonald et al. [2001] have suggested that the effect of
physical and psychosocial stressors on occupational health
outcomes may be rooted in shared common qualities of
work and how it is performed. This suggestion was based
on correlation and factor analyses that indicated that the
physical and psychosocial stressors, repetition and job
control, had a shared variance [MacDonald et al., 2001].
Additionally, it is possible that a worker’s response to job
demands (either physical or psychosocial), or workstyle
[Feuerstein et al., 1999b], may trigger certain physiological
responses that intensify pathological processes in the LB and/
or UE regions. Examples of such physiological processes
504
Huang et al.
include sustained motor unit activity [Lundberg et al., 1999]
and/or elevations in norepinephrine, epinephrine, adrenocorticotropin hormone, and cortisol [Frankenhaeuser and
Lundberg, 1982; Gerra et al., 2001]. Although research is
required to delineate such hypothesized mechanisms, the
present findings provide further direction on conceptualizing
these pathways where investigations should focus.
The present investigation provided additional information into specific dimensions of work organization and
their risks for musculoskeletal symptoms both individually
and when combined with biomechanical/physical stressors.
Nevertheless, interpretation of the results should recognize
the study’s limitations. The cross-sectional methodology can
only give indications of the associations between risk factors
and musculoskeletal symptoms and not cause–effect relationships [Kleinbaum et al., 1982]. Currently, efforts are
underway to examine whether the identified risk factors
predict future clinic visits for a musculoskeletal disorder
as a proxy for severity. Biomechanical/physical and work
organization exposures were also determined through selfreport. While a reporting bias may have occurred, Wiktorin
et al. [1993] have found that self-reported exposures to
various work postures including having one’s head bent in a
forward position, sitting, and lifting had moderate correlations and ‘‘acceptable’’ accuracy with objective measurements from a posimeter, inclinometer, and observation by
an ergonomist. Kasl [1998] also notes that although subjective measurement tools that enable the assessment of
perceptions of environmental conditions are important in
empirical investigations of job stress, objective measures of
the ‘‘actual’’ work conditions may provide a clearer picture
of potential etiological processes and help reduce potential
confounding from influences on subjective reports. Additionally, as with many cross-sectional studies, the possibility
of a ‘‘common instrument bias’’ should be considered since
both exposure and symptoms were measured simultaneously.
Studies [e.g., Wiktorin et al., 1993] have suggested that
individuals with musculoskeletal complaints may tend to
underreport exposures (e.g., lifting). While efforts were
made to separate question items by type (e.g., biomechanical,
work organization, symptoms) and symptoms were assessed
in relation to the past 12 months (versus at the time of
assessment), responses may have been impacted by the use of
a single questionnaire.
The use of a military sample could also lead to questions
about the ability to generalize results to a civilian population.
For example, the organizational climate of the Marine Corps
differs from certain civilian workplaces despite the possibility that the physical work tasks are similar [Katzenbach
and Santamaria, 1999]. Yet, the observation that a majority
of study participants had job tasks with generic job descriptions that were similar to their civilian counterparts [U.S.
Department of Labor, 1991; Headquarters, U.S. Marine
Corps, 1999] provides support that findings should be appli-
cable to both military and civilian workers. The ethnic and
racial diversity of the sample was also a particularly unique
characteristic of this study and are of particular importance given the need to understand health outcomes among
people of different racial and ethnic backgrounds [Dimsdale,
2000]. However, the present study sample was relatively
young (mean age ¼ 28.0 years) and was 88.2% male, reflecting the predominance of males among the enlisted ranks
in the Marine Corps (94.2%) [Division of Public Affairs,
Headquarters Marine Corps, 1999]. The overrepresentation
of young males would suggest that additional studies in both
military and civilian populations be conducted with a particular emphasis on incorporating females to determine
whether gender should be considered more strongly in determining risk and developing workplace interventions.
Since high levels of physical stressors that included
repetitive movements, frequent bending/twisting, sustained awkward postures, and/or inadequate rest/recovery posed
significant risks to individuals for musculoskeletal symptoms, job redesign that decreases such exposures represents a
logical component of prevention/intervention [Chaffin,
1997; Smith and Cohen, 1997]. Given the possible biobehavioral mechanisms related to work-related musculoskeletal disorders previously described, especially in relation to
time pressure, techniques such as programmed rest breaks
and relaxation training might assist in reducing adrenergic
responsivity and facilitate muscle tension release and/or reduce the likelihood for muscular overexertion [Everly, 1989;
van der Hek and Plomp, 1997]. Instruction on problem
solving methods may also assist with reducing elements that
contribute to greater cognitive demands, cognitive uncertainty, or interpersonal demands can be better identified and
actions can be taken to assist with reducing or eliminating
these stressors [D’Zurilla and Chang, 1995].
From an organizational standpoint, operational efforts
should consider facilitating participation in ergonomic redesign and decision-making processes and decreasing work
aspects that may contribute to greater time pressure [Noro,
1999; Nytro et al., 2000]. Based on the present findings,
such participation should be associated with a lesser likelihood for concurrent report of LB and UE symptoms.
Additionally, encouragement by senior management in
addressing work processes and organization would demonstrate a needed emphasis and commitment in efforts aimed
at reducing the occurrence of work-related musculoskeletal
disorders [National Research Council and Institute of Medicine (NRC/IOM), 2001].
The present study highlights the importance of considering both biomechanical and work organizational factors in the occurrence of LB and UE symptoms. While no
synergism was found, these findings suggest a potential
utility in designing intervention programs that address biomechanical exposures such as repetition, awkward positions,
and bending/twisting in addition to work organization factors
Biomechanical and Work Organization Factors
related to scheduling, job design, and interpersonal factors in
addition to time pressure and cognitive demands. Studies that
evaluate such a multifaceted approach among different work
groups are required before further conclusions can be made.
Based on the present study population, such programs would
appear to be of particular benefit to those working in office
environments. These efforts that incorporate both physical
and work characteristics on the job and company/organizational levels considers their impact on musculoskeletal health
can in turn help enhance worker and organizational health,
function, and productivity.
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