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).


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 175
--> 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).

OCR for page 175
--> 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

OCR for page 175
--> 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

OCR for page 175
--> 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

OCR for page 175
--> 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).

OCR for page 175
--> 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.

OCR for page 175
--> 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

OCR for page 175
--> 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

OCR for page 175
--> 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.

OCR for page 175
--> 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

OCR for page 175
--> 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

OCR for page 175
--> longitudinal study involving 429 workers. J Medicine, 34, 379-383. Ryden, L.A., Molgaard, C.A., Bobbitt, S., & Conway, J.(1989). Occupational low-back injury in a hospital employee population: an epidemiologic analysis of multiple risk factors of a high-risk occupational group. Spine, 14, 315-20. 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 Occ Env Med , 54, 268-271. Werner RA, Albers JW, Franzblau A, & Armstrong TJ.(1994). The relationship between body mass index and the diagnosis of carpal tunnel syndrome. Muscle Nerve, 17, 632-636 Zwerling, C., Ryan, J., & Schootman, M.(1993). A case-control study of risk factors for industrial low back injury. The utility of preplacement screening in defining high-risk groups. Spine, 18, 1242-7. Zwerling, C., Sprince, N.L., Wallace, R.B., Davis, C.S., Whitten, P.S., & Heeringa, S.G.(1996). Risk factors for occupational injuries among older workers: an analysis of the health and retirement study. AJPH, 86, 1306-9. Gender and CTS Ashbury, F.D.(1995). Occupational repetitive strain injuries and gender in Ontario, 1986 to 1991. J Occup Env Med, 37, 479-85. 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. Franklin, G.M., Haug, J., Heyer, N., Checkoway, H., & Peck, N.(1991). Occupational carpal tunnel syndrome in Washington state, 1984-1988. AJPH, 81, 741-6. Kendall D. (1960) Aetiology, diagnosis, and treatment of paraesthesia in the hands. British Med J3:1633-1640. Phalen G. (1972) The carpal tunnel syndrome: clinical evaluation of 598 hands. Clin Orthop Relat Res; 83:29-40. Phillips R. (1967) Carpal tunnel syndrome as a manifestation of systemic disease. Ann Rheum Dis 26(1): 59-63. 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. Tanzer R. (1959). The carpal tunnel syndrome. J Bone Joint Surg [Am ], 41:626-634. 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. Zwerling, C., Sprince, N.L., Ryan, J., & Jones, M.P.(1993). Occupational injuries: comparing the rates of male and female postal workers. Am J Epid, 138, 46-55. Carpal Canal Size/Wrist shape Backhouse, K.M. & Churchill-Davidson, D.(1975). Anomalous palmaris longus muscle

OCR for page 175
--> producing carpal tunnel-like compression. Hand, 7, 22-24 Bauer, J.M. & Trusell, J.J.(1992). Palmaris profundus causing carpal tunnel syndrome. Orthopaedics, 15, 1348-50. Bleecker, M.L., Bihlman, M., Moreland, R., & Tipton, A.(1985). Carpal tunnel syndrome: role of carpal canal size. Neurology, 35, 1599-1604. Brown, F.E., Morgan, G.J., Taylor, T., et al.(1984). Coexistence of muscle anomalies and rheumatoid arthritis in patients with carpal tunnel syndrome. Clin Exp Rheumatol 2, 297-302. Cobb, T.K., An.K.N., Cooney, W.P. et al. (1984). Lumbrical muscle incursion into the carpal tunnel during finger flexion. J Hand Surg , 4, 434-438. Gelmers, H.(1981). Primary carpal tunnel stenosis as a cause of entrapment of the median nerve. Acta Neurochir, 55, 317-320. Johnson, E.W., Gatens, T., Poindexter, D. et al.(1983). Wrist dimensions: correlation with median sensory latencies . Arch Phys Med Rehabil, 64, 556-557. Masgaradeh, M., Schneck, C.D., Bonakdarpour, A,, Mitra, A., & Conaway, D.(1989). Carpal Tunnel: MR Imaging Part II. Carpal tunnel syndrome. Radiology 171, 749-754. Nakamichi, K. & Tachibana, S.(1995). Small hand as a risk factor for idiopathic carpal tunnel syndrome. Muscle Nerve, 18, 664-666. Neviaser, R.J.(1974). Flexor digitorum superficialis indicis and carpal tunnel syndrome. Hand, 6, 155-156. Radecki, P.(1994). A gender specific wrist ratio and the likelihood of a median nerve abnormality at the carpal tunnel. Am J Phys Med Rehabil, 73, 157-162. 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. Winn, F.J. & Habes, D.J.(1990). Carpal tunnel area as a risk factor for carpal tunnel syndrome. Muscle Nerve, 13, 254-258. 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. Burton, A.K., Tillotson, K.M., & Troup, J.D.(1989). Prediction of low-back trouble frequency in a working population. Spine, 14, 939-946. Cannon, L.J., Bernacki, E.J., & Walter, D.S.(1982). Personal and occupational factors associated with carpal tunnel syndrome. J Occup Med, 23, 255-258. Daltroy, L.H., Larson, M.G., Wright, E.A., Malspeis, S., Fossel, A.H., Ryan, J., Zwerling, C., & Liang, M.H.(1991). A case-control study of risk factors for industrial low back injury: implications for primary and secondary prevention programs. Am J Ind Med, 20, 505-15. deKrom, M.C.T.F.M., Kester, A.D.M., Knipschild, P.G., & Spaans, F.(1990). Risk factors for carpal tunnel syndrome. Am J Epid, 132, 1102-1110. Dieck, G.S. & Kelsey, J.L.(1985). An epidemiologic study of the carpal tunnel syndrome in an

OCR for page 175
--> adult female population. Prev Med, 14, 63-69. Dyck, P.J., Litchy, W.J., Lehman, K.A. et al.(1995). Variables influencing neuropathic endpoints: the Rochester diabetic neuropathy study of healthy subjects. Neurology, 45, 1115-1121. Letz, R. & Gerr, F.(1994). Covariates of human peripheral nerve function: I. nerve conduction velocity and amplitude. Neurotoxicology and Teratology , 16, 95-104. Reisbord, L.S. & Greenland, S.(1985). Factors associated with self-reported back-pain prevalence: a population-based study. J Chr Dis, 38, 691-702. Stetson, D.S., Albers, J.W., Silverstein, B.A., et al.(1992). Effects of age, sex, and anthropometric factors on nerve conduction measures. Muscle Nerve, 15, 1095-1104. Stevens, J.C., Beard, C.M., O'Fallon, W.M., & Kurland, L.T.(1992). Conditions associated with carpal tunnel syndrome. Mayo Clin Proc, 67, 541-548. 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 Battie, M.C., Bigos, S.J., Fisher, L.D. et al.(1989). Isometric lifting strength as a predictor of industrial back pain reports. Spine, 851-856. Battie, M.C., Bigos, S.J., Fisher, L.D., Spengler, D.M., Hansson, T.H., Nachemson, A.L., & Wortley, M.D.(1990). Anthropometric and clinical measures as predictors of back pain complaints in industry: a prospective study. J Spinal Disorders, 3, 195-204. Battie, M.C., Bigos, S.J., Fisher, L.D., Hansson, T.H., Nachemson, A.L., Spengler, D.M., Wortley, M.D., & Zeh, J.(1989). A prospective study of the role of cardiovascular risk factors and fitness in industrial back pain complaints. Spine, 14, 141-7. Milgrom, C., Finestone, A., Lev, B., Wiener, M., & Floman, Y.(1993). Overexertional lumbar and thoracic back pain among recruit: a prospective study of risk factors. J Spine Disorders, 6, 187-93. Milgrom, C., Giladi, M., Stein et al.(1986). Medial tibial pain: a prospective study of its cause among recruits. Clin Orthop, 213, 167-71. Nathan, P.A. & Keniston, R.C.(1993). Carpal tunnel syndrome and its relation to general physical condition. Hand Clinics, 9, 253-261. Nathan, P.A., Keniston, R.C., Lockwood, R.S., & Meadows, K.D.(1996). Tobacco, caffeine, alcohol, and carpal tunnel syndrome in American industry. A cross-sectional study of 1464 workers. J Occup Env Med , 38, 290-298. Shwayhat, A.F., Linenger, J.M., Hofherr, L.K. et al.(1994). Profiles of exercise history and overuse injuries among united states navy sea, air and land recruits. Am J Sports Med, 22,

OCR for page 175
--> 835-840. Westgaard, R.H., Jensen, C., & Hansen, K.(1993). Individual and work-related risk factors associated with symptoms of musculoskeletal complaints. Int Arch Occup Environ Health, 64, 405-13. Genetics and CTDs Battie, M.C., Videman, T., Gibbons, L.E., Fisher, L.D., Manninen, H., & Gill, K.(1995). 1995 Volvo Award in clinical sciences. Determinants of lumbar disc degeneration. A study relating lifetime exposures and magnetic resonance imaging findings in identical twins. Spine, 20, 2601-2612. Danta, G.(1975). Familial carpal tunnel syndrome with onset in childhood. J Neurol Neurosurg Psychiatry, 38, 350-355. Radecki, P.(1994). The familial occurrence of carpal tunnel syndrome. Muscle Nerve, 17, 325-330. Richardson, J.K.(1997). A familial predisposition toward lumbar disc injury. Spine, 22, 1487-1493. 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. Bernard, B., Sauter, S., Petersen, M., Fine, L., & Hales, T. (1993). HETA 90-013-2277: Los Angeles Times . Cincinnati OH: National Institute for Occupational Safety and Health. 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.

OCR for page 175
--> 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. Bergqvist, U., Wolgast, E., Nilsson, B., & Voss, M. (1995). The influence of VDT work on musculoskeletal disorders. Ergonomics, 38, 754-762. Billette, A., Carrier, M., & Bernier, M. (1990). The social organization of work and health problems: A study of word processing secretaries in large bureaucracies . Work With Display Units, 89, 257-271. Bongers, P. M., De Winter, C. R., Kompier, M. A., & Hildebrandt, V. H. (1993). Psychosocial factors at work and musculoskeletal disease. Scand J Work Environ. Health, 19, 297-312. Brisson, C., Vezina, M., & Vinet, A.(1992). Health problems of women employed in jobs involving psychological and ergonomic stressors: The case of garment workers in Quebec. Women and Health, 18, 49-65. DeJoy, D., Murphy, L. R., & Gershon, R. M. (1995). Safety climate in health care setting. Advances in Industrial Ergonomics and Safety , 7, 923-929. Feuerstein, M. (1996). Workstyle: Definition, empirical support, and implications for prevention, evaluation, and rehabilitation of occupational upper extremity disorders. In S.D. Moon

OCR for page 175
--> and S.L. Sauter (Eds.). Beyond Biomechanics. Psychosocial Aspects of Musculoskeletal Disorders in Office Work. London: Taylor & Francis. Feuerstein, M., Carosella, A.M., Burrell, L.M., Marshall, L., & DeCaro, J. (1997). Occupational upper extremity symptoms in sign language interpreters: prevalence and correlates of pain, function, and work disability . J Occup Rehab, 7, 187-205. Frese, M., & Zapf, D. (1988). Methodological issues in the study of work stress: Objective vs. subjective measurement of work stress and the question of longitudinal studies. In C. L. Cooper and R. Payne (Eds.), Causes, Coping and Consequences of Stress at Work, Chichester, New York: John Wiley. Hadler, N. M. (1992). Arm pain in the workplace: A small area analysis. Journal of Medicine. 34, 113-119. Henning, R. A., Sauter, S. L., Salvendy, G., & Krieg Jr., E. F. (1989). Microbreak length, performance, and stress in a data entry task. Ergonomics, 32, 855-864. Johnson, J. V. (1989). Control, collectivity and the psychosocial work environment. In S. K. Sauter, J. J. Hurrell, Jr. and C. L. Cooper (Eds.), Job Control and Worker Health. New York: John Wiley and Sons. Karasek, R., Baker, D., Marxer, F., Ahlbom, A., & Theorell, T. (1981). Job decision latitude, Job demands, and cardiovascular disease. AJPH , 71, 694-705. Kopardekar, P., & Mital, A. (1994). The effect of different work-rest schedules on fatigue and performance of a simulated directory assistance operator's task. Ergonomics, 37, 1697-1707. Lundberg, U., Granqvist, M., Hansson, T., Magnusson, M., & Wallin, L. (1989). Psychological and physiological stress responses during repetitive work at an assembly line. Work & Stress, 3, 143-153. Macintosh, M., & Gough, R. (1998). The impact of workplace change on occupational health and safety: A study of four manufacturing plants. Human Factors and Ergonomics in Manufacturing, 8, 155-175.). Murphy, L., Grosch, J., Gershon, R., & DeJoy, D. (1997). Safety climate and injuries: The case of occupational exposure to HIV. In P. Seppala, T. Luopajarvi, C-H Nygard, and M. Mattila (Eds.). Proceedings of the 13th Triennial Congress of the International Ergonomics Association , From Experience to Innovation, IEA '97 . Helsinki, Finland: Finnish Institute of Occupational Health. Sauter, S., Swanson, N., Conway, F., Galinsky, T., & Lim, S.Y. (1997, April 13-16, 1997). Redesign of rest-breaks and musculoskeletal discomfort in video display terminal work. Paper presented at the Marconi Research Conference, Marshall, CA. Sauter, S. L., & Swanson, N. G. (1996). An ecological model of musculoskeletal disorders in office work.. In S.D. Moon and S.L. Sauter (Eds.). Beyond Biomechanics: Psychosocial Aspects of Musculoskeletal Disorders in Office Work. London: Taylor & Francis. Schleifer, L. M. (1987). An evaluation of mood disturbances and somatic discomfort under slow computer-response time and incentive-pay conditions. Work With Display Units, 86, 793-802. Smith, M.J., Carayon, P., Sanders, K.J., Lim, Soo-Yee and LeGrande, D. (1992). Employee stress and health complaints in jobs with and without electronic performance monitoring. Applied Ergonomics, 1, 17-28. Smith, M.J. (1997). Psychosocial aspects of working with video display terminals (VDTs) and

OCR for page 175
--> employee physical and mental health. Ergonomics, 40, 1002-1015. Smith, M.J., & Sainfort, P.C. (1989). A balance theory of job design for stress reduction. Intl J Ind Ergo, 4, 67-79. Smith, M.J., & Carayon, P.C. (1996). Work organization, stress and cumulative trauma disorders. In S. Moon and S. Sauter (Eds.), Beyond Biomechanics: Psychosocial Aspects of Cumulative Trauma Disorders. London: Taylor & Francis. Theorell, T., Harms-Ringdahl, K., Ahlberg-Hulten, G., & Westin, B. (1991). Psychosocial job factors and symptoms from the locomotion system—A multicausal analysis. Scand J Rehab Med, 23, 165-173. Vinet, A., Vezina, M., Brisson, C., & Bernard, P. M. (1989). Piecework, repetitive work and medicine use in the clothing industry. Social Science and Medicine, 28, 1283-1288. Waersted, M., & Bjorklund, R. A. (1991). Shoulder muscle tension induced by two VDU-based tasks of different complexity. Ergonomics , 34, 137-150. Wood, D. D. (1997). Minimizing fatigue during repetitive jobs: Optimal work-rest schedules. Human Factors and Ergonomics Society, 39, 83-101. Volinn E., Van Koevring, D., & Loeser, J.D. (1991). Back sprain in industry: The role of socioeconomic factors in chronicity. Spine, 16, 542-8.

OCR for page 175
--> 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)

OCR for page 175
--> 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)

OCR for page 175
--> 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      

OCR for page 175
--> 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)