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Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers (1999)

Chapter:Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders

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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
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Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders

Julia Faucett, RN, Ph.D.

UC Northern California Center for Occupational and Environmental Health, and School of Nursing, University of California, San Francisco CA 94143-0608

and Robert A. Werner, MD

University of Michigan, and Veterans Administration Medical Center, Ann Arbor, MI 48105

Multiple occupational risk factors have been proposed for common musculoskeletal disorders. Chief among them are biomechanical factors such as repetition and force. In growing numbers, however, investigators in Europe, Japan, and the United States are reporting associations between non-biomechanical aspects of work and musculoskeletal disorders. Factors related to the way work tasks are organized, integrated, and controlled; the psychological demands of the job as well as demands for production speed and quality; and the structural and social aspects of supervision and coworker relationships are examples. Several measures for evaluating the worksite, the job, and worker perceptions about the job have been developed and are gaining in use. Furthermore, increasing evidence linking these factors with musculoskeletal outcomes has stimulated investigators to propose theoretical models to explain potential causal effects and guide additional research in the field (Bongers et al. 1993; Sauter & Swanson 1996; Armstrong et al. 1993; Smith & Sainfort 1989).

To fully understand the etiology of musculoskeletal disorders, however, it is important to examine physical and health-related factors intrinsic to the individual worker in addition to work-related biomechanical and non-biomechanical factors. Factors such as age, obesity, chronic illness, and anatomical variation for example have been studied to evaluate their contribution to the development of musculoskeletal disease. This paper on non-biomechanical factors thus reviews personal characteristics of the worker in addition to characteristics of the job and work environment. Literature searches were conducted separately to identify studies that investigated key personal and work-related variables for their associations with musculoskeletal disease and related symptoms. Following the request of the Academy, each section includes a discussion of the search strategies and inclusion criteria, summary of relevant research findings, critical examination of research methods that have been used in key or exemplary studies, and an overview of the investigators' conclusions and their plausibility.

Section One: Personal Factors

(Author: Robert Werner)

Articles included in this focused review were selected based upon the following criteria:

  • The study represents a scientific inquiry, not simply commentary or opinion (cross-sectional, longitudinal or experimental design).
Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×
  • The study had a minimum of 30 subjects included.
  • Appropriate statistical analysis, emphasis on including logistic regression or multilinear regression in an attempt to control for other factors
  • The study was published in English.

Medical Conditions: diabetes, rheumatoid arthritis, thyroid disease, connective tissue disorders, vitamin B6 deficiency, pregnancy

Body Mass Index (BMI): Weight, Stature

• Gender

Wrist dimension/Anatomical size and shape of the carpal canal Age

General conditioning: strength, aerobic conditioning Genetics

Table 1 : Non-Biomechanical Risk Factors for CTDs

The search strategy included a MEDLINE search using the qualifier, 'etiology,' or 'epidemiology' with the medical subject headings of: carpal tunnel syndrome (CTS), median nerve injury, cumulative trauma disorders (CTDs), low back pain and repetitive strain disorders. If the study focused on age, gender, medical status, obesity, physical condition, anatomical variation or genetics, it was screened for the above criteria based upon the abstract. The articles selected are not meant to represent an exhaustive list but simply the studies with an adequate scientific basis.

There are many personal co-factors that have been related to the development of CTS and to a lesser extent all CTDs. Obesity (body mass index), square wrist configuration, small carpal canal area, diabetes as well as several other connective tissue disorders and poor general fitness have all been associated with higher prevalence of CTS. The ultimate mechanism of injury is probably ischemia so anything that influences the health of the vascular system may compromise the soft tissues, i.e. nerve, muscle and tendon. Several investigators have suggested that CTDs and specifically CTS are primarily a result of health habits and lifestyle and secondarily to the biomechanical stress. Of the numerous personal co-factors that have been reported, few have been quantified as to the strength of the association. In the instances where the relative risk has been determined, attempts at modeling disease based upon these factors have only explained a small percentage of the variance.

Systemic Disorders

Many systemic disorders place an individual at higher risk for the development of soft tissue injuries. Diabetes and rheumatoid arthritis are the most obvious risk factors affecting the development of overuse syndromes (Stevens et al. 1992; Albers et al. 1996; Atcheson et al. 1998). Rheumatoid arthritis patients as well as those with other connective tissue disorders are at higher risk for development of joint abnormalities as well as muscle and nerve injuries (Stevens

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

1992). Diabetes is well known to be a risk factor for CTS and other compression mononeuropathies (Albers et al. 1996). Stevens et al. (1992) calculated a standardized morbidity ratio for rheumatoid arthritis (3.6), for diabetes (2.3) and for pregnancy (2.5). Thyroid disease and kidney disease also have many connective tissue side effects placing the individual at higher risk for nerve injuries; thyroid disease may also lead to muscle disease. Systemic disease causes the nerves to be more susceptible to compression and ischemia. The biologic plausibility of this association is high and the association is very strong, but these disorders affect a small percentage of active workers. Atcheson et al. (1998) suggest that these disorders are more common among workers diagnosed with CTS compared to other CTDs and may be under recognized in the industrial setting. The studies reviewed in this area use a methodology based upon population based data or large cross-sectional data. There is little bias associated with sample selection and the statistics are appropriate for the sample.

Vitamin B6

In 1973, Ellis and Presley suggested an association between vitamin B6 deficiency and CTS. Over the next 2 decades, several additional reports appeared which suggest that this association is causal in many cases. The impact of these studies on physician understanding and treatment of CTS is substantial. Vitamin deficiency is mentioned in a major textbook of occupational medicine (Keyserling & Armstrong 1992) as a possible CTS risk factor, implying that such deficiency contributes to CTS among workers.

Unfortunately, the studies which demonstrate an association between vitamin B6 status and CTS usually include small numbers of non-randomly selected subjects, frequently rely on non-standard or entirely subjective measures of outcome, and occasionally suffer from serious design flaws. Recent prospective and population based studies have not borne out this relationship (Folker et al. 1978; McCann & Davis 1978; Ellis et al. 1979, 1981, 1982; Amadio 1985; Franzblau et al. 1996). The recent population based studies and large cross-sectional studies are without the selection bias of earlier studies and use appropriate statistical analysis. The recent study by Kensinton et al. (1998) suggesting a relationship between vitamin B6 deficiency, vitamin C, and CTS (among women but not men) has methodological as well as statistical flaws (Franzblau et al. 1998).

The biologic plausibility is moderate. However, the strength of the relationship is weak except in severely vitamin B6 deficiency (and a severe B6 deficiency is rare). The cross-sectional studies of active workers and population based studies are sound enough to say that there is not a significant relationship between B6 levels and carpal tunnel syndrome.

Pregnancy/Gynecologic History

Pregnancy is considered an independent risk factor (estimated RR of 2.5) for the development of CTS due to increased vasculature and interstitial fluids (Soferman et al. 1964; Gould & Wissinger 1978; Masey et al. 1978; Stevens et al. 1992). These studies have adequate sample size and statistical analysis. This is a strong association with strong biologic plausibility. Fortunately this condition is a time limited and there is usually resolution of symptoms at the end of the pregnancy or shortly thereafter.

Both the use of oral contraceptives and gynecologic surgery have been hypothesized as

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

risk factors for CTS based on epidemiological data, but this has not been consistently identified as a risk factor. (Saborur & Fadel 1970; Jorkquist et al. 1977; Cannon et al. 1981; DeKrom et al. 1990). The biological significance and rational for this is not well established although increased interstitial fluid as a result of hormonal changes is a suggested mechanism. This is a weak association with modest biologic plausibility. These studies are large cross-sectional studies with statistically significant findings in some of the studies but the clinical significance is low.

Body Mass Index (BMI)

Several investigators have reported that individuals with CTS were heavier and shorter than the general population. Cannon et al. (1982) noted that 27% of individuals (8 of 30) with CTS were obese compared to 12% (11 of 90) in a control population; this difference did not reach statistical significance. Dieck and Kelsey (1985) found an increased prevalence of CTS, within an adult female population, among individuals with short stature, greater weight and recent weight gain. The BMI was significantly higher in the CTS group (27 kg/m2 versus 25 kg/m2, p = 0.01). Vessey et al. (1990) found that the risk for CTS among obese women was double that of slender women.

Within an industrial population, Nathan et al. (1992) demonstrated that a higher BMI was associated with a higher prevalence of median mononeuropathy. They found a relative risk of 4.1 for obese individuals compared to slender individuals. This relationship was more pronounced in men (RR = 5.1) than in women (RR = 2.7). This study did have a number of methodological flaws of which the most prominent was an analysis by hand instead of by person. The findings of Werner et al. (1994) support the hypothesis that individuals with a higher BMI are at increased risk for CTS.

In terms of obesity, the pathophysiology that would explain this relationship is not well understood. Letz and Gerr (1994) found the same relationship between obesity and slow conduction of the median nerve across the wrist in a large population based study, but an inverse relationship was found between obesity and other peripheral nerve measures. The conduction velocity of the peroneal, sural and ulnar nerves all tended to improve among subjects who were more obese whereas only the median sensory nerve across the wrist demonstrated slowing. The finding that BMI is correlated with the median but not ulnar sensory distal latencies suggest that the condition of obesity affects the nerves differently. The additional finding that the difference in the latencies is more strongly correlated with BMI than the median latency alone further supports this contention. This was a large cross-sectional study of Vietnam veterans. Its strength lies in the large sample size (>6,000) and the uniform electrodiagnostic testing.

If a causal relationship between obesity and a slowing of median conduction across the wrist exists, it may relate to increased fatty tissue within the carpal canal or to increased hydrostatic pressure throughout the carpal canal in obese individuals compared to normal or slender individuals. The median nerve at the wrist is more compartmentalized than the ulnar, peroneal or sural nerves and may be subjected to compression due to fatty build up within the carpal canal among obese individuals. Conversely, heavier individuals may simply place more mechanical stress on their hands and wrists and thus place the median nerve at higher risk as opposed to some intrinsic change within the carpal canal. The possible association between obesity and the development of early type II diabetes may be a confounder but is not related to

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

the workers' report of diabetes. Alternatively, thinner subjects may be a surrogate of a person's overall conditioning which may in term influence the performance of the median nerve. This is a very strong association and appears to have a dose response relationship. The studies are either case control or large cross-sectional studies with sound statistical analysis. The biologic plausibility is still under question. Whether this is based upon biomechanical or metabolic factors is not known. The pathophysiology that would explain this relationship is not well understood. Although this is a strong relationship with an apparent dose response effect, this factor at best, explains only a small portion of the variance (less than 8%) related to the diagnosis of CTS or electrodiagnostic abnormalities involving the median nerve (Nathan et al. 1994; Werner et al. 1997)

Obesity is also associated with higher prevalence of lumbar back pain and leg symptoms but not thoracic or cervical back pain (Westgaard et al. 1992; Milgrom et al. 1993) These are based upon cross-sectional studies with adequate sample sizes but the population studied by Milgrom et al. was military recruits as opposed to active workers studied by Westgaard et al. Other large, cross-sectional studies of industrial workers did not demonstrate a relationship between low back pain and obesity (Battie et al. 1989; Bigos et al. 1991; Daltroy et al. 1991) A study by Ryden et al. (1989) demonstrated the reverse relationship, women with low body mass were 50% more likely to have back injuries but the 95% confidence interval included 1.0 so it does not reach statistical significance. The strengthen of the association between obesity and other CTDs is weak and the larger studies have not demonstrated a consistent association.

Gender

Gender has been suggested as an independent risk factor for the development of CTS as well as repetitive strain injuries (Tanzer et al. 1959; Kendall et al. 1960; Phillips et al. 1967; Phalen 1972; Stevens et al. 1988). This risk factor is not well explained although historically women had a higher use of the health care system in this may represent another spectrum of higher use. Ashbury (1995) demonstrated an average relative risk for reporting of repetitive strain disorders of 1.5 for women compared to men across all occupations but it was much higher in some occupations: material handling (RR = 6.0), construction (RR = 4.0), processing (RR = 3.5). Female postal workers had twice the relative risk for occupation injuries compared to male postal workers (Zwerling et al. 1993) Bigos et al. (1991) did not demonstrate a relationship between gender and reported low back pain among Boeing workers.

The finding that women were more likely to have a higher prevalence of CTS than men is supported by population-based studies (Stevens et al. 1980, 1992) but differs from the worker compensation based data on CTS reported by Franklin. In the work place, the risk for women is only 10-20% higher than men as opposed to 300% reported in population based studies (Franklin et al. 1991; Werner et al. 1997). It was felt that the carpal canal was smaller in women thus exposing them to more compression of the median nerve. Further investigation of carpal canal dimension among women has not demonstrated any relationship between CTS and canal dimensions (see discussion of carpal canal size below).

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×
Wrist size/dimension and CTS

A narrow carpal canal, a squarer shape of the wrist and a smaller sized hand have all been associated with a higher prevalence of CTS. Dekel et al. (1980) and Papaioannou et al. (1992) demonstrated that there was an association between a narrow carpal canal, particularly proximally, and the finding of CTS. This is a moderately strong association with high biologic plausibility.

Several studies have demonstrated a relationship between a more square shaped wrist and a finding of median mononeuropathy at the wrist (Johnson et al. 1983; Radecki 1994) but this was not confirmed by other studies (Werner et al. 1997, 1998). The relationship described by Radecki was in a clinic population of referred patients while the population studied by Werner et al. was a random selection of active workers, regardless of symptoms. The pathophysiology of this association, if it exists, has not been demonstrated. A squarer wrist has not been associated with a smaller cross-sectional area although this mechanism has been proposed. This is a relatively weak association with poor biologic plausibility.

Anomalous muscles extending into the carpal canal have been reported as etiologies for carpal tunnel syndrome (Neviaser 1974; Backhouse & Churchill-Davidson 1975; Brown et al. 1984; Cobb et al. 1984; Bauer & Trusell 1992). Muscle variants implicated include the muscle bellies of the flexor superficialis, palmaris longus, lumbrical muscles, abductor digiti quinti and the accessory palmaris longus muscle. These are rare occurrences and do not account for the typical person with CTS. Likewise, there are other space occupying lesions such as lipoma, haemangioma, synovial sarcoma, tendon sheath fibroma, ganglion or calcified mass that have been reported as etiologies of CTS, but these are also rare occurrences. This is a strong association with high biologic plausibility but again represents a rare anatomical variant (Neviaser 1974, Backhouse & Churchill-Davidson 1975).

Aging and CTDs

Increasing age has consistently been associated with slowing of the median nerve across the wrist and with CTS (Nathan et al. 1992; Stetson et al. 1992; Letz & Gerr 1994; Werner et al. 1994; Dyck et al. 1995). These studies have consistently demonstrated a strong association with high biologic plausibility. Tissue repair declines with aging and may be the basis for this relationship.

The association between aging and symptom reporting is not as strong. It is stronger for CTS than for other upper extremity cumulative trauma disorders or low back pain. Burton et al. (1989) demonstrated that a history of chronic low back pain was associated with increasing age. This study looked at prevalence or reported history as opposed to incident cases. Age did not factor into any of the models of limb or back symptoms reported by Westgaard et al. (1992). Many researchers did not find age a significant factor associated with self-reported back pain prevalence or incidence (Riesbold & Greenland 1985; Bigos et al. 1991). Daltroy et al. (1991) demonstrated that younger postal workers were at a higher risk (OR = 3.0, p=0.0001) for back injuries. The association between aging and low back pain and other CTDs is weak. Greater emphasis should be placed upon the larger prospective, longitudinal studies, i.e. Boeing Study, which do not demonstrate an association.

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×
General Fitness

Several studies have demonstrated an association between low aerobic fitness and higher musculoskeletal injury rates (mostly among military personnel) (Milgrom et al. 1993; Shwayhat et al. 1994). There has also been an association between lower exercise levels and a higher prevalence of CTS as well as slowing of the median nerve across the carpal canal (Nathan & Keniston 1993). Most studies demonstrate a close correlation of poor general fitness with higher BMI, alcohol/tobacco use, and older age. Even when general fitness is identified as a significant independent factor (as is the case with CTS) it accounts for a very small component of the variance (3% or less) (Nathan & Keniston 1993). There are conflicting studies that do not demonstrate a relationship between general fitness/exercise level and higher musculoskeletal injuries. (Battie 1989; Franzblau et al. 1996; Milgrom et al. 1986; Westgaard et al. 1993). Battie et al. (1989) demonstrated that active workers (Boeing Study) with greater strength (isometric testing) were at higher risk for reporting low back pain. Also in the Boeing Study, Battie et al. demonstrated that cardiovascular fitness did not predict reporting of low back pain. The association between general fitness and CTS is modest, while the association with low back pain and other CTDs is poor. Due to the numerous co-variates that are associated to general fitness, the strength of the relationship varies. The biologic plausibility is reasonable, although the exact mechanism is unclear. The largest, prospective study (Boeing Study) does not demonstrate a relationship between better fitness and reduced low back pain; it does suggests that stronger individuals are at higher risk. These results should be more heavily weight than some of the smaller cross-sectional studies.

Genetics

There are a limited number of studies that explore the relationship between specific genetic markers and the incidence of CTDs. It is clear that genetics plays a role in the risks associated with gender, obesity, carpal canal size and several connective tissue disorders, but apart from these relationships, the role of genetics in the etiology of CTDs is not well established. There are a few studies suggesting a familial component to the incidence back pain and radiculopathy. Battie et al. (1995), for example, determined that the risk for degenerative disk disease was explained more by genetics and similarities among 115 identical twins than by documentation of physical loads. Richardson (1997) demonstrated that discogenic pain was more common in family members of subjects with discogenic pain than found among families of the subjects without such pain.

Radecki (1994) demonstrated a higher prevalence of carpal canal surgery or clinical history of CTS among family members with a documented slowing of the median nerve at the wrist compared to the families of other patients without slowing of the median nerve. Twenty seven percent of subjects with a documented median mononeuropathy had a positive family history of CTS compared to 13% without evidence median mononeuropathy (p<0.001). The familial occurrence of CTS has usually been reported as a single family or two involving two or three generations. An autosomal dominant inheritance has been postulated. The mechanism for a hereditary etiology for CTS is unclear but may relate to a thicker carpal tunnel ligament, smaller carpal canal or altered geometry or it may be related to obesity. Although the sample sizes in these studies are relatively small, the relationship is robust and suggests a strong

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

association but more study is necessary to establish the strength of the relationship.

Section Two: Work-Related Factors

(Author: Julia Faucett)

Smith and Carayon hypothesized that the organizational, technological, environmental and task-related features of work systems influence workers' responses to their jobs, including their perceptions and performance of work (Smith & Sainfort 1989; Smith & Carayon 1996). Work system factors include organizational job characteristics that may be temporal (e.g. work-rest schedules, shift work); content-related (e.g. job complexity or monotony); social (e.g. solitary work, team work); financial (e.g. piecework, incentive pay); bureaucratic (e.g. multiple middle management levels); or more global (e.g. organizational climate, culture) (Sauter & Swanson 1996). The work stress paradigm suggests that workers' perceptions about work system factors, particularly perceptions that personal attributes and resources are not adequate to cope with work stressors, may result in work strain or detrimental emotional and physical outcomes (Sauter & Swanson 1996). Others have also suggested that the effects of work strain may be buffered by job-related decision control or social support (Johnson 1989; e.g. Karasek et al. 1981). Thus, for example, the worker's perception that the job is characterized by high psychological job demands, low perceived job control, and poor support from supervisors and coworkers increases the risk for job strain and poor health outcomes.

The impact of work system factors, and workers' psychological perceptions about those factors, on musculoskeletal outcomes theoretically arises from alterations they produce along multiple pathways: increases in biomechanical strain, physiological vulnerability, or symptom attribution and reporting (Bongers et al. 1993; Sauter & Swanson 1996). Feuerstein et al. (1996, 1997) proposed that workers respond to work system factors, and their appraisals of them, with unique behavioral, cognitive, and physiological reactions. In turn, these reactions, jointly termed ''work style," contribute to the development of musculoskeletal symptoms and disorders. Thus, a managerial decision to increase production demands among data processors may evoke fear in an individual worker that the task may not be completed on time, and lead to faster and harder keying, increased levels of catecholamines and cortisol, and detrimental delays in the awareness of musculoskeletal discomfort.

Search Strategy and Selection Criteria

Research literature was identified for this review using computer assisted searches of the MEDLINE PLUS and PsycINFO databases from 1988 through the first half of 1998. The time constraints set by the Academy did not allow searching for reports through other literature data bases or that were published only in conference proceedings or books. Reports in English that focused on musculoskeletal diseases, cumulative trauma disorders, repetitive strain injury, nerve entrapment or compression syndromes, carpal tunnel syndrome, tendinitis or tenosynovitis, sprains and strains as well as hand, arm, neck, shoulder or back symptoms were initially identified. This set was subsequently searched using keywords related to psychosocial workload, job stress, job demand, mental demand, job control, decision control or latitude, job satisfaction, job security or insecurity, job clarity, social support, work organization, supervision, shiftwork, overload, underload, monotonous work, work pace, work rest breaks, rest breaks, machine pacing, and electronic performance monitoring. After a review of abstracts, over 100 studies that

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

investigated the etiology of musculoskeletal disorders using pertinent non-biomechanical work factors were identified. Seventy studies that could be located were then scored based on the criteria in Table 2. The scoring system led to ties among the highest scoring studies. Twelve studies were finally chosen from among the highest scoring studies as exemplars for review. These twelve were selected to represent a variety of industries. Ten were either cross-sectional or case control studies, two were prospective studies.

Study design: longitudinal (2) vs. cross-sectional or case control (1) vs. other types of reports (0)

Sampling: more than one (1) vs. one worksite represented (0);

Sampling: more than (1) vs. less than 60% response rate (0);

Measurement: reliability and/or validity were (1) or were not (0) investigated for work factors survey;

Measurement: did (1) or did not (0) include measures of physical work load;

Measurement: did (1) or did not (0) include measures of personal factors or non-work activities;

Multimethod approaches: did (1) or did not (0) include multiple techniques to evaluate work setting;

Outcomes: included physical examinations (2) vs. evaluation of specific symptom features (1) vs. general incidence of musculoskeletal symptoms (0);

Outcomes: did (1) or did not (0) evaluate symptoms based on body location (e.g. hand/arm pain, back pain, neck/shoulder pain); and

Outcomes: did (1) or did not (0) blind clinicians doing physicals from data on independent variables.

Table 2: Evaluation criteria for selecting exemplar studies for review.

Summary of Results

The twelve exemplar studies are listed in Table 3 along with significant findings related to selected non-biomechanical work factors. In the main, the findings are drawn from multivariate analyses that controlled for selected physical job demands and workers' personal characteristics. To summarize the results from these studies, non-biomechanical work-related predictors were first placed into six categories based on the name of the factor. Then, studies evaluating factors in each category were reviewed together. The categories were: (1) job demand (included such factors as psychological work load, work pace, deadlines, and fluctuations in work load in addition to job demand), (2) job content (included such factors as requirements for attention and stimulation from the job in addition to job content, (3) job control (included such factors as influence, task flexibility, and control over rest breaks in addition to job control), (4) social relationships at work (included such factors as social support, contact or relationships with coworkers, solitary work, supervisor climate, and supervisor support in addition to social relationships), (5) work role ambiguity , and (6) job satisfaction (included job task enjoyment). Although it may be argued that a factor could be placed into more than one category, this system allowed some comparison among studies that utilized different measures and alternative names for key factors.

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

The above method identified nine studies that investigated job demand or related variables. Seven of these studies (including three that investigated physical examination findings) found significant associations with musculoskeletal outcomes. The eighth study found a significant association for overstrain in a cross-sectional design, but not on follow up ten years later (Leino & Hänninen 1995). Bergqvist et al. (1995b) did not find a significant relationship for work demand. Similarly, five studies (including two that evaluated clinical findings) out of eight that investigated job content or similar variables found significant associations with musculoskeletal outcomes. The sixth study found a significant association for attention demands, but not for job content (Ekberg et al. 1994). Leino and Hänninen (1995) found a significant association in a cross-sectional design, but again not on follow up after ten years. Work content failed to attain significance in the eighth study (Ohlsson et al. 1994). Five studies (including two that evaluated clinical findings) out of nine that investigated job control or related factors found significant associations with musculoskeletal outcomes. The sixth and seventh studies found significant associations for control specifically over temporal aspects of the job, but no associations for general job control or influence (Bergqvist et al. 1995b; Skov et al. 1996). The eighth and ninth studies also found no associations for job control (Ohlsson et al. 1994; Leino & Hänninen 1995). Five studies (including two that evaluated clinical findings) out of seven found significant associations in the expected direction between social relationships and musculoskeletal outcomes. The sixth study found that very high levels of contact with peers were significantly detrimental (Bergqvist et al. 1995b). Skov et al. (1996) did not find a significant relationship between supervisor support and musculoskeletal outcomes. Work role ambiguity was found to be associated with musculoskeletal disorders in two studies. Skov et al. (1996), on the other hand, did not find that musculoskeletal outcomes were significantly associated with role ambiguity or role conflict, but did find a significant association for job insecurity. Additionally, a significant association between job satisfaction and musculoskeletal disorders was found in the Bigos et al.(1991) study of worker compensation claims for back injury, but not in the Leclerc et al. (1998) study of CTS outcomes.

Review of Methods

The exemplars chosen for review were selected from among the most carefully designed studies in this field of research. They included workers from a wide diversity of industries: fish processing, construction, manufacturing, sales, newspaper and office work. Community wide studies were also represented. Sample sizes tended to be substantial and adequately representative, outcome measures often included findings from blinded physical examinations in addition to self reported symptoms, and predictor variables were generally assessed using questionnaires with previously investigated psychometrics. Furthermore, for the majority of the studies, potential confounders including the physical aspects of the job and workers' personal characteristics were concomitantly investigated. Additionally, all of the studies included comparisons with subjects who did not have the outcome of interest.

The limitations of these studies are related primarily to design and to measurement. Longitudinal studies of non-biomechanical work factors are sparse in number, yet only prospective studies will allow investigation of temporal relationships between cause and effect. Prospective studies, however, are not without their own pitfalls (Frese & Zapf 1988). The vast majority of studies surveyed workers to collect data on non-biomechanical work factors because

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

they are likely to have the most immediate information about their jobs, and survey techniques are relatively efficient and inexpensive. Additionally, data on workers' perceptions may only be gathered using self reports. Such surveys, however, introduce potential recall bias for the workers who have developed persistent musculoskeletal symptoms or related clinical diagnoses. Observer assessments are thought to offer more objective, if not unbiased, evaluations of the work system. For these reasons, the use of multiple methods to assess the work environment was considered a strength in this review. Multiple survey measures of predictor variables may also be used to strengthen study designs. None of the cross-sectional studies in this set of exemplars, however, fully utilized the multitrait-multimethod approaches that have been recommended (Campbell & Fiske 1959; Frese & Zapf 1988).

Overall, where there were significant associations between the six categories of work factors and musculoskeletal outcomes, they typically indicated modest to moderate increases in risk for the worker with a poorer work environment. Additionally, the strength of the associations varied from study to study, often depending upon whether the outcome measure was symptoms or clinical findings. The method for determining the physical job stresses also varied from study to study and this may account for some of the variation in findings for the non-biomechanical work factors. It is of interest that Johansson and Rubenowitz (1994) added a control variable based on whether the worker thought the symptoms were job-related or not, on the grounds that non-occupational musculoskeletal symptoms are common. This added control measure resulted in an increase in the risk for occupational musculoskeletal symptoms attributed to non biomechanical work factors. The increased risk was comparable to that obtained for the association of physical work factors with musculoskeletal symptoms.

Investigators tended to use diverse survey questionnaires to assess non-biomechanical work factors. This diversity of measures makes comparisons across studies difficult and suggests a basis for the conflicts in findings reported above. Scales purportedly measuring the same key factors were occasionally based on differing items. The work control scale, for example, in the Leino and Hänninen (1995) study was based on items about access to information, influence over changes, and satisfaction with management attitudes. By contrast, the job control scale in the LeClerc et al. (1998) study was based on items about work breaks, work pace, and control over work quantity. Similarly, Bigos et al. (1991) obtained their most significant results for a single item, enjoyment of job tasks, that was taken from a scale focusing largely on relationships with coworkers and supervisors. Although most measures had been used in previous studies and investigated for their psychometric qualities, few investigators reported psychometric information about the use of the questionnaire in their current study. In the Holmström et al. (1992) studies, for example, Cronbach's alpha for the psychosocial scales ranged from 0.72 to 0.45—thus from adequate to unacceptably low values. Additionally, although a few studies addressed dose response relationships, overall there were few data to inform us about critical gradations of the non-biomechanical work factors that displayed significant relationships with musculoskeletal outcomes. Several studies addressed unique work factors in addition to the more commonly studied six categories above. Findings related to these unique factors often lack replication in subsequent studies even though they are intriguing. Examples include working against different types of deadlines (Bernard et al. 1993, 1994) or the notion of "just in time" production (LeClerc et al. 1998).

Outcome in addition to predictor measures in the study examples demonstrated a lack of

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

consensus among researchers in the field. Not all studies included clinical findings, although it is important to investigate predictors of both self reports of symptoms and clinical diagnoses because of the implications for related suffering, impairment, and disability. For the studies that employed physical examinations, clinical criteria were often standardized but they differed from study to study, making comparisons difficult. Some studies established scores for clinical findings (e.g. Leino and Hänninen 1995), for example, while others focused on establishing clinical diagnoses (e.g. Hales et al. 1992, 1994).

Finally, there is likely to be a synergistic effect among the non-biomechanical factors and between those factors and the biomechanical factors. Few of the studies above investigated interactions among factors other than for the traditional divisions between genders, age groups, or blue and white collar workers. Although it has been suggested that one pathway by which psychosocial factors may influence musculoskeletal outcomes is through increases in biomechanical load, there is a lack of studies which attempt to specify relationships along this pathway (e.g. Feuerstein et al. 1997; Waerstad et al. 1991). Studies are also needed that link psychosocial work stressors with musculoskeletal outcomes via physiological mechanisms (e.g. Theorell et al. 1991; Lundberg et al. 1989); and via social or individual influences on symptom reporting.

Additional Non-Biomechanical Factors

This review has considered the non-biomechanical work factors most commonly addressed in the occupational health literature. Additional factors considered by individual researchers bear further investigation, but have not been as widely studied nor was there time to fully review these studies. Furthermore, occupational health literature focusing on work stress and general health conditions suggests other risk factors that may be associated with musculoskeletal disorders. The work system paradigm offered by Smith and Carayon (1996) provides a useful scheme to organize some of the topics that have received attention from researchers: (1) Work task: work rest breaks (e.g. Sauter, Swanson, Conway, & Galinsky 1998; Bergqvist et al. 1995a; Kopardekar & Mital 1994; Wood 1997; Henning et al. 1989), task complexity (e.g. Waerstad et al. 1991), and job enrichment; (2) Organization: piecework or incentive pay systems (e.g. Brisson et al. 1992; Vinet et al. 1989; Schleifer 1986), quality improvement teams, and bureaucratic structures (e.g. Billette et al. 1989; Murphy et al. 1997): (3) Technology : the increasing computerization of work (e.g. Amick & Celentano 1991 and multiple investigations of VDT use), machine or otherwise externally driven work pace, and electronic monitoring (e.g. Smith, Carayon, Sanders, Lim & LeGrande 1992; Hales et al. 1994); (4) Work environment: work climate or work culture (e.g. DeJoy et al. 1995; MacIntosh & Gough 1998). There are also extra-organizational factors with the potential to influence reports, diagnoses, and treatment of work-related musculoskeletal symptoms and related disability that initial studies suggest are important to consider. These include regional and other differences in clinical practice (Hadler, 1992; Atcheson et al. 1998) and fluctuations in local economies and job availability (Volinn et al. 1991).

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×
Conclusion

This review has considered research on non-biomechanical factors that may influence the development of occupational musculoskeletal symptoms and disorders. Over time there has been considerable improvement in study design and implementation as these topics have drawn the attention of researchers and policy makers. Furthermore, findings from well-designed studies demonstrate increasing consistency. The findings from this review suggest that some personal factors may play a role, albeit a modest one, in the development of CTS. In terms of the broader category of musculoskeletal disorders, non-biomechanical occupational factors appear to have significant associations with health outcomes, even after controlling for personal factors and biomechanical work factors. Although the time to produce this report was limited, it is doubtful that these overall conclusions would have differed in a more extensive review. The findings about exposure to non-biomechanical in addition to biomechanical factors in the work setting, affirm that these disorders are complex and multifactorial.

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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
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Aging and CTDs

Bigos, S.J., Battie, M.C., Spengler, D.M., Fisher, L.D., Fordyce, W.E., Hansson, T., Nachemson, A.L., & Zeh, J.(1992). A longitudinal, prospective study of industrial back injury reporting. Clinical Orthopaedics & Related Research, 21-34.

Bigos, S.J., Battie, M.C., Spengler, D.M., et al.(1991). A prospective study of work perceptions and psychosocial factors affecting the report of back injury. Spine, 16, 1-6.

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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

adult female population. Prev Med, 14, 63-69.

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Stevens, J.C., Sun, S., Beard, C.M., O'Fallon, W.M., & Kurland, L.T.(1988). Carpal tunnel syndrome in Rochester, Minnesota, 1961-1980. Neurology , 38, 134-138.


Vessey, M.P., Villard-Mackintosh, L., & Yeates, D.(1990). Epidemiology of carpal tunnel syndrome in women of childbearing age. Findings in a large cohort study. Int J Epidemiol, 19, 655-659.


Werner, R.A., Albers, J.W., Franzblau, A., & Armstrong, T.J.(1997). The influence of body mass index and work activity in determining the prevalence of median mononeuropathy at the wrist. J Occup Env Med, 54, 268-271.

Werner, R.A., Albers, J.W., Franzblau, A., & Armstrong, T.J. (1994). The relationship between body mass index and the diagnosis of carpal tunnel syndrome. Muscle Nerve, 17, 632-636.

Physical Conditioning

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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
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835-840.

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Genetics and CTDs

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Non-biomechanical Work Factors-Exemplar Studies

Bergqvist, U., Wolgast, E., Nilsson, B., & Voss, M. (1995b). Musculoskeletal disorders among visual display terminal workers: individual, ergonomic, and work organizational factors. Ergonomics, 38(4), 763-76.

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Bernard, B., Sauter, S., Fine, L., Petersen, M., & Hales, T. (1994). Job task and psychosocial risk factors for work-related musculoskeletal disorders among newspaper employees. Scand J Work Environ Health, 20(6), 417-26.

Bigos, S. J., Battie, M. C., Spengler, D. M., Fisher, L. D., Fordyce, W. E., Hansson, T., Nachemson, A. L., & Zeh, J. (1992). A longitudinal, prospective study of industrial back injury reporting. Clinical Orthopaedics and Related Research (279), 21-34.


Ekberg, K., Bjorkqvist, B., Malm, P., Bjerre-Kiely, B., Karlsson, M., & Axelson, O. (1994). Case-control study of risk factors for disease in the neck and shoulder area. Occup Environ Med, 51(4), 262-6.


Hales, T. R., Sauter, S. L., Peterson, M. R., Fine, L. J., Putz-Anderson, V., Schleifer, L. R., Ochs, T. T., & Bernard, B. P. (1992). HETA 89-299-2230: US West Communications . Cincinnati OH: National Institute for Occupational Safety and Health.

Hales, T. R., Sauter, S. L., Peterson, M. R., Fine, L. J., Putz-Anderson, V., Schleifer, L. R., Ochs, T. T., & Bernard, B. P. (1994). Musculoskeletal disorders among visual display terminal users in a telecommunications company. Ergonomics, 37(10), 1603-21.

Holmström, E., Moritz, U., & Engholm, G. (1995). Musculoskeletal disorders in construction workers. Occup Med, 10(2), 295-312.

Holmström, E. B., Lindell, J., & Moritz, U. (1992a). Low back and neck/shoulder pain in construction workers: occupational workload and psychosocial risk factors. Part 1: Relationship to low back pain. Spine, 17(6), 663-71.

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
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Holmström, E. B., Lindell, J., & Moritz, U. (1992b). Low back and neck/shoulder pain in construction workers: occupational workload and psychosocial risk factors. Part 2: Relationship to neck and shoulder pain. Spine, 17(6), 672-7.

Johansson, J., & Rubenowitz, S. (1994). Risk indicators in the psychosocial and physical work environment for work-related neck, shoulder, and low back symptoms: A study among blue- and white-collar workers in eight companies . Scand J Rehab Med, 26, 131-142.


Lagerström, M., Wenemark, M., Hagberg, M., & Hjelm, E. W. (1995). Occupational and individual factors related to musculoskeletal symptoms in five body regions among Swedish nursing personnel. Int Arch Occup Environ Health, 68(1), 27-35.

Leclerc, A., Franchi, P., Cristofari, M. F., Delemotte, B., Mereau, P., Teyssier-Cotte, C., & Touranchet, A. (1998). Carpal tunnel syndrome and work organization in repetitive work: a cross sectional study in France. Study Group on Repetitive Work. Occup Environ Med, 55(3 ), 180-7.

Leino, P. I., & Hänninen, V. (1995). Psychosocial factors at work in relation to back and limb disorders. Scand J Work Environ Health , 21(2), 134-42.


Ohlsson, K., Hansson, G. A., Balogh, I., Strömberg, U., Palsson, B., Nordander, C., Rylander, L., & Skerfving, S. (1994). Disorders of the neck and upper limbs in women in the fish processing industry. Occup Environ Med, 51(12), 826-32.


Skov, T., Borg, V., & Ørhede, E. (1996). Psychosocial and physical risk factors for musculoskeletal disorders of the neck, shoulders, and lower back in salespeople. Occup Environ Med, 53(5), 351-6.

Non-biomechanical Work Factors - Other References

Amick III, B. C., & Celentano, D. D. (1991). Structural determinants of the psychosocial work environment: Introducing technology in the work stress framework. Ergonomics, 34, 625-646.

Armstrong, T. J., Buckle, P., Fine, L. J., Hagberg, M., Jonsson, B., Kilbom, A., Kuorinka, I. A. A., Silverstein, B. A., Sjogaard, G., & Viikari-Juntura, E. R. (1993). A conceptual model for work-related neck and upper-limb musculoskeletal disorders. Scand J Work Environ . Health, 19, 73-84.


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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

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×

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Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

TABLE 3: Summary of significant findings from reviewed studies (N = 12).

AUTHORS

DESIGN

SAMPLE: INDUSTRY (SIZE = STUDY TOTAL)

MS OUTCOMES

SIGNIFICANT FINDINGS FOR NON-BIOMECHANICAL WORK FACTORS

 

 

 

Back discomfort

None

 

 

 

 

Neck/shoulder discomfort

Limited break opportunity

OR: 2.7 (CI: 1.2-5.9)

 

 

 

Intense neck/shoulder discomfort

None

 

Bergqvist et al. 1995b

Cross sectional

Office work (n = 260)

Tension neck

Limited break opportunity

OR: 7.4 (CI: 3.1-17.4)

 

 

 

Cervical diagnoses

None

 

 

 

 

Shoulder diagnoses

Limited break opportunity

OR: 3.3 (CI: 1.4-7.9)

 

 

 

 

Low task flexibility

OR: 3.2 (CI: 1.2-8.5)

 

 

 

Arm/hand discomfort

Extreme peer contacts

OR: 2.1 (CI: .1- 1.4)

 

 

 

Arm/hand diagnoses

Extreme peer contacts

OR: 4.5 (CI: 1.3-15.5)

 

 

 

Neck symptoms

Hours on deadline

OR: 1.7 (CI: 1.4-3.0)

 

 

 

 

Work variance

OR: 1.5 (CI: 1.1-1.8)

 

 

 

 

Import. of ergon. to mgmt.

OR: 1.4 (C: 1.2-1.9)

Bernard et al. 1993

Cross sectional

Newspaper (n = 1050)

Shoulder symptoms

Job decision making

OR: 1.6 (CI: 1.2-2.1)

 

 

 

 

Job pressure

OR: 1.4 (CI: 1.0-1.9)

 

 

 

Hand/wrist symptoms

Hours on deadline

OR: 1.7 (CI: 1.2-2.3)

 

 

 

 

Supervisor support

OR: 1.4 (CI: 1.1-1.6)

 

 

 

Any hand/wrist diagnoses

Changes in workload

OR: 3.2 (CI: 2.5-4.1)

Bigos et al. 1991

Prospective

Aircraft manufacture (n = 3030)

Back diagnoses

Enjoy job

RR: 1.7 (CI: 1.31-22.21)

 

 

Diverse—community

Neck/shoulder diagnoses

Work pace—medium

OR: 2.5 (CI: 1.0-6.2)

Ekberg et al. 1994

Case control

(cases n = 109; control A n = 136, control B n = 327)

 

—rushed

OR: 3.5 (CI: 1.3-9.4)

 

 

 

 

Work role ambiguity (high)

OR: 16.5 (CI: 6.0-46)

 

 

 

 

Attention demands (high)

OR: 3.8 (CI: 1.4-1 1)

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

AUTHORS

DESIGN

SAMPLE: INDUSTRY (SIZE = STUDY TOTAL)

MS OUTCOMES

SIGNIFICANT FINDINGS FOR NON-BIOMECHANICAL WORK FACTORS

 

 

 

Neck disorders

Job decision making

OR: 4.2 (CI: 2.1-8.6)

 

 

 

 

Lack of production standard

OR: 3.5 (CI: 1.5-8.3)

 

 

 

 

Fear of replace. by computer

OR: 3.0 (CI: 1.5-6.1)

 

 

 

 

Hi inform. process. demand

OR: 3.0 (CI: 1.4-6.2)

Hales et al. 1994

Cross sectional

Telecommunications (n = 573)

 

Task variety

OR: 2.9 (CI: 1.5-5.8)

 

 

 

 

Work pressure

OR: 2.4 (CI: 1.1-5.5)

 

 

 

Shoulder disorders

Fear of replace. by computer

OR: 2.7 (CI: 1.3-5.8)

 

 

 

Elbow disorders

Fear of replace. by computer

OR: 2.9 (CI: 1.4-6.1)

 

 

 

 

Job decision making

OR: 2.8 (CI: 1.4-5.7)

 

 

 

 

Surges in workload

OR: 2.4 (CI: 1.2-5.0)

 

 

 

Hand/wrist disorders

Hi inform. process. demand

OR: 2.3 (CI: 1.3-4.3)

 

 

 

Back symptoms

Qualitative demands

OR: 1.1 (CI: 1.0-1.4)

 

 

 

 

Quantitative demands

OR: 1.3 (CI: 1.2-1.6)

 

 

 

 

Solitary work

OR: 1.1 (CI: 1.0-1.2)

 

 

 

Severe back symptoms

Quantitative demands

OR: 2.0 (CI: 1.2-3.2)

 

 

 

 

Solitary work

OR: 1.5 (CI: 1.2-1.9)

Holmström et al. 1992

Cross sectional

Construction (n = 1773)

 

Understimulation

OR: 2.2 (CI: 1.4-3.3)

 

 

 

Neck/shoulder symptoms

Qualitative demands

OR: 1.2 (CI: 1.0-1.4)

 

 

 

 

Quantitative demands

OR: 1.4 (CI: 1.2-1.7)

 

 

 

 

Solitary work

OR: 1.1 (CI: 1.0-1.2)

 

 

 

Severe neck/shoulder symptoms

Qualitative demands

OR: 1.4 (CI: 1.0-2.0)

 

 

 

 

Quantitative demands

OR: 3.0 (CI: 2.1-4.0)

 

 

 

 

Solitary work

OR: 1.5 (CI: 1.2-1.8)

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

AUTHORS

DESIGN

SAMPLE: INDUSTRY (SIZE = STUDY TOTAL)

MS OUTCOMES

SIGNIFICANT FINDINGS FOR NON-BIOMECHANICAL WORK FACTORS

 

 

 

Work-related back symptom

Blue collar

 

 

 

 

 

Supervisor climate

partial correl.coefficient = 0.18

 

 

 

 

Understimulation

partial correl.coefficient = 0.16

 

 

 

 

Psych. Workload

partial correl.coefficient = 0.35

 

 

 

Work-related neck symptoms

Blue collar

 

 

 

 

 

Supervisor climate

partial correl.coefficient = 0.16

 

 

 

 

Understimulation

partial correl.coefficient = 0.14

 

 

 

 

Psych. Workload

partial correl.coefficient = 0.25

 

 

 

 

White collar

 

Johnasson & Rubenowitz 1994

Cross sectional

Manufacturing (blue collar n = 241; white collar n = 209)

 

Control over work

partial correl.coefficient = 0.17

 

 

 

 

Psych. Workload

partial correl.coefficient = 0.21

 

 

 

Work-related shoulder symptoms

Blue collar

 

 

 

 

 

Control over work

partial correl.coefficient = 0.18

 

 

 

 

Supervisor climate

partial correl.coefficient = 0.16

 

 

 

 

Understimulation

partial correl.coefficient = 0.26

 

 

 

 

Psych. Workload

partial correl.coefficient = 0.27

 

 

 

 

White collar

 

 

 

 

 

Control over work

partial correl.coefficient = 0.17

 

 

 

 

Supervisor climate

partial correl.coefficient = 0.20

 

 

 

 

Understimulation

partial correl.coefficient = 0.22

 

 

 

 

Coworker relations

partial correl.coefficient = 0.24

 

 

 

 

Psych. Workload

partial correl.coefficient = 0.21

 

 

 

Back symptoms

Supervisor support

OR: 1.8 (CI: 1.1-2.8)

 

 

 

Severe back symptoms

None

 

 

 

 

Neck symptoms

Supervisor support

OR: 2.0 (CI: 1.3-3.2)

Lagerström et al. 1995

Cross sectional

Health care (n = 688)

Severe neck symptoms

Work demand

OR: 1.8 (CI: 1.1-2.9)

 

 

 

Shoulder symptoms

Work control

OR: 1.7 (CI: 1.1-2.7)

 

 

 

Severe shoulder symptoms

Work demand

OR: 1.6 (CI: 1.0-2.6)

 

 

 

Hand symptoms

Understimulation

OR: 1.6 (CI: 1.1-2.4)

 

 

 

Severe hand symptoms

None

 

 

Cross sectional with control group

Multiple (exposed to repetitive work n = 1210; non exposed controls n = 337)

CTS

Job control

OR: 1.6 (CI: 1.0-2.4)

Leclerc et al. 1998

 

 

 

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×

AUTHORS

DESIGN

SAMPLE: INDUSTRY (SIZE = STUDY TOTAL)

MS OUTCOMES

SIGNIFICANT FINDINGS FOR NON-BIOMECHANICAL WORK FACTORS

 

 

 

Musculoskeletal morbidity index:

 

 

 

 

 

Cross sectional models

 

 

 

 

 

Symptoms (Model R2 = 0.22)

Overstrain

Beta = 0.21 (p < 0.001)

 

 

 

Work content

Beta = 0.16 (p < 0.001)

 

Leino et al. 1995

Prospective

Manufacturing (n = 411)

Findings (Model R2 = 0.23)

Work content

Beta = 0.13 (p < 0.001)

 

 

 

Overstrain

Beta = 0.12 (p < 0.001)

 

 

 

 

Follow up models

 

 

 

 

 

Symptoms (Model R2 = 0.36)

Social relations

Beta = 0.11 (p < 0.01)

 

 

 

Findings (Model R2 = 0.31)

Social relations

Beta = 0.15 (p = 0.001)

 

 

 

Neck/shoulder symptoms

Work strain

 

 

 

 

 

—medium exposed

OR: 2.5 (CI: 1.2-5.5)

 

 

 

 

control

OR: ns

 

 

 

 

—high exposed

OR: 5.5 (CI: 2.4-12)

 

 

 

 

control

OR: 3.4 (CI: 1.4-7.9)

Ohlsson et al. 1994

Cross sectional with control group

Fish processing (exposed to industrial work n = 206; non-exposed controls n=208)

Neck shoulder diagnoses

Fellowship

 

 

 

 

 

—high exposed

OR: ns

 

 

 

 

control

OR: 3.3 (CI: 1.0-10.8)

 

 

 

 

Work strain

 

 

 

 

 

—medium exposed

OR: 2.9 (CI: 1.1-7.6)

 

 

 

 

control

OR: ns

 

 

 

 

—high exposed

OR: 6.6 (CI: 2.6-17)

 

 

 

 

control

OR: 3.0 (CI: 1.1-8.7)

 

 

 

Hand/elbows—not presented

 

 

 

 

 

Back symptoms

Social contact—next to least

OR: 1.5 (CI: 1.0-2.1)

 

 

 

 

—least

OR: 1.8 (CI: 1.2-2.6)

 

 

 

 

Overwork     —next to most

OR: 1.4 (CI: 1.2-2.0)

 

 

 

 

—most

OR: 2.0 (CI: 1.4-3.0)

 

 

 

Neck symptoms

Work variation—lowest

OR: 1.8 (CI: 1.2-2.7)

Skov et al. 1996

Cross sectional

Sales (n = 1306)

 

Control over time—low

OR: 1.4 (CI: 1.1-1.9)

 

 

 

 

Competition  —high

OR: 1.4 (CI: 1.1-1.9)

 

 

 

Shoulder symptoms

Work demand—highest

OR: 1.5 (CI: 1.0-2.1)

 

 

 

 

Uncertainty of employment

 

 

 

 

 

—next to highest

OR: 1.8 (CI: 1.3-2.5)

 

 

 

 

—highest

OR: 1.5 (CI: 1.0-2.3)

Suggested Citation:"Non-Biomechanical Factors Potentially Affecting Musculoskeletal Disorders." National Research Council. 1999. Work-Related Musculoskeletal Disorders: Report, Workshop Summary, and Workshop Papers. Washington, DC: The National Academies Press. doi: 10.17226/6431.
×
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×
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Estimated costs associated with lost days and compensation claims related to musculoskeletal disorders—including back pains and repetitive motion injuries—range from $13 billion to $20 billion annually. This is a serious national problem that has spurred considerable debate about the causal links between such disorders and risk factors in the workplace.

This book presents a preliminary assessment of what is known about the relationship between musculoskeletal disorders and what may cause them. It includes papers and a workshop summary of findings from orthopedic surgery, public health, occupational medicine, epidemiology, risk analysis, ergonomics, and human factors. Topics covered include the biological responses of tissues to stress, the biomechanics of work stressors, the epidemiology of physical work factors, and the contributions of individual, recreational, and social factors to such disorders. The book also considers the relative success of various workplace interventions for prevention and rehabilitation.

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