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2


Dimensions of the Problem

This chapter provides a review of the major databases covering the musculoskeletal disorders in the general population and in the work place. An analytic approach is used to extract relevant information as well as to identify key limitations. The discussion covers both the occurrence of musculoskeletal disorders and the annual costs to society.

MUSCULOSKELETAL DISORDERS IN THE GENERAL POPULATION

Six data sources are available for estimating the extent of the musculoskeletal disorder burden in the general U.S. population—the National Health Interview Surveys (1988 and 1995), the National Health and Nutrition Examination Survey (1976-1988), the Health and Retirement Survey (1992-1994), the Social Security Supplemental Security Income system (1998), the National Ambulatory Medical Care Survey (1989), and two regional surveys. The limitations of these datasets are considerable and are discussed in detail later in the chapter.

It is essential here to note that: (1) there are no comprehensive national data sources capturing medically determined musculoskeletal disorders; (2) almost all of the data regarding musculoskeletal disorders are based on individual self-report in surveys; and (3) the survey data do not and cannot distinguish musculoskeletal disorders that may be associated with work from those likely not associated with work in the study populations, which are comprised primarily of working American adults. From these facts two inferences may be drawn:

    1. Explicitly, these data include work as well as nonwork-related musculoskeletal disorders without distinction. Rates derived from these



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Page 38 2 Dimensions of the Problem This chapter provides a review of the major databases covering the musculoskeletal disorders in the general population and in the work place. An analytic approach is used to extract relevant information as well as to identify key limitations. The discussion covers both the occurrence of musculoskeletal disorders and the annual costs to society. MUSCULOSKELETAL DISORDERS IN THE GENERAL POPULATION Six data sources are available for estimating the extent of the musculoskeletal disorder burden in the general U.S. population—the National Health Interview Surveys (1988 and 1995), the National Health and Nutrition Examination Survey (1976-1988), the Health and Retirement Survey (1992-1994), the Social Security Supplemental Security Income system (1998), the National Ambulatory Medical Care Survey (1989), and two regional surveys. The limitations of these datasets are considerable and are discussed in detail later in the chapter. It is essential here to note that: (1) there are no comprehensive national data sources capturing medically determined musculoskeletal disorders; (2) almost all of the data regarding musculoskeletal disorders are based on individual self-report in surveys; and (3) the survey data do not and cannot distinguish musculoskeletal disorders that may be associated with work from those likely not associated with work in the study populations, which are comprised primarily of working American adults. From these facts two inferences may be drawn: 1. Explicitly, these data include work as well as nonwork-related musculoskeletal disorders without distinction. Rates derived from these

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Page 39 general population sources cannot be considered in any sense equivalent to rates for background, reference, or unexposed groups nor, conversely, as rates for musculoskeletal disorders associated with any specific work or activity. 2. There are no comprehensive data available on occupationally unexposed groups. Given the proportion of adults now in the active workforce in the United States, any such nonemployed group would, by definition, be unrepresentative of the adult population. Table 2.1 summarizes all available information regarding the rates in the general population from the six sources, organized by category: (1) all musculoskeletal disorders, (2) upper extremity disorders (including carpal tunnel syndrome), and (3) disorders of the back. Because there are relatively more data available in the latter category, Table 2.2 and Table 2.3 are included to provide the detailed findings in each of the relevant study groups. The overwhelming thrust of the data reveals that musculoskeletal disorders are very prevalent among adults in the United States, especially after the age of 50, and are a source of an extraordinary burden of disability. According to the 1997 report from the National Arthritis Data Workgroup (Lawrence et al., 1998), a working group of the National Institute of Arthritis and Musculoskeletal and Skin Diseases, 37.9 million people, or 15 percent of the entire U.S. population, suffered from one or more chronic musculoskeletal disorders in 1990. Moreover, given the increase in disease rates and the projected demographic shifts, they estimate a rate of 18.4 percent or 59.4 million people with these disorders by the year 2020. Results of the National Health Interview Survey for 1995 showed a 13.9 percent prevalence of impairment from musculoskeletal disorders (Praemer, Furner, and Rice, 1999). Other estimates were generated from the Health and Retirement Survey (1992-1994), which found a rate of 62.4 percent among men and women between ages 51 and 61 reporting one or more musculoskeletal disorders; 41 percent of these reported work disability as a consequence. Among all disabled workers in that age group, almost 90 percent reported one or more musculoskeletal disorders, making musculoskeletal disorders overwhelmingly the largest reason for disability. According to data from Supplemental Security Income, a program that covers chronically ill as well as previously employed persons, 7.7 percent of people under the age of 65 receiving assistance attribute it to musculoskeletal disorders. This proportion rises to 16.9 percent among adults in their 50s, and to 23.9 percent among adults 60 to 64 years old. Data regarding upper extremity disorders and low back pain are consistent and show that both are important national concerns. Data regarding the former, available from the National Health Interview Survey, show

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Page 40 TABLE 2.1 General Population Data Sources Disorder Data Source Year Observation Reference All musculoskeletal disorders National Health Interview Survey 1988 37.9 million prevalence (15 percent U.S. population) a Lawrence et al., 1998 1995 13.9 percent impairment, U.S. population Praemer, Furner, and Rice,1999 All musculoskeletal disorders Health and Retirement Survey (1992-1994) 1992-1994 62.4 percent prevalence in 51 to 61 year-olds; 41 percent of these disabled; 90 percent all disabled had musculoskeletal disorders Health and Retirement Survey Yelin, Trupin, and Sebesta, 1999 All musculoskeletal disorders Social Security Insurance Disability 1998 7.7 percent of all disabled Americans on Social Security Insurance (N=4.53 million, with 16.9 percent of all 50 to 59, 23.9 percent of all 60 to 64) Social Security Bulletin Annual Statistics Summary, 1999:360 Upper extremities (all musculoskeletal disorders) (Hand or wrist) National Health Interview Survey 1988 9.4 percent overall prevalence of musculoskeletal disorders; 1.55 percent prevalence carpal tunnel syndrome; 0.4 percent prevalence tendinitis Tanaka et al., 1994, in press

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Page 41 Upper extremities or shoulder impairment National Health Interview Survey 1995 1.74 percent prevalence Praemer, Furner, and Rice, 1999 Upper extremities (carpal tunnel syndrome) Atroshi 1998 14.4 percent prevalent carpal tunnel syndrome (symptoms); 2.7 percent prevalent carpal tunnel syndrome (diagnosis) Atroshi et al., 1999 Marshfield Clinic Approximately 1 incident case per 100 adults/3 years Nordstrom et al., 1997 Back or spine impairment National Health Interview Survey 1995 7.0 percent prevalence Praemer, Furner, and Rice, 1999 Low back pain National Health and Nutrition Examination Survey II – National Health Interview Survey (1976, 1988) 1976-1993 19 to 59 percent prevalence for any See Table 2.2 and Table 2.3 (from Lawrence et al., 1998) Sternbach, 1986 10 to 18 percent frequent Leigh and Sheetz, 1989 Frymoyer et al., 1983 Quality of Employment Survey (1992-1993) a Projected to rise to 59.4 by 2020 or 18.4 percent population.

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Page 42 TABLE 2.2 Annual and Lifetime “Prevalence” of Various Categories of Low Back Pain Category of Back Pain Source and Survey Size Sample Description of Back Pain Prevalence (%) Annual Lifetime Any low back pain Taylor and Curran, 1985 (148) (n = 1,254) Both sexes, age ≥18; national sample (Sternbach, 1986) Any backache in past year 56 Frymoyer et al., 1983 (142) (n = 1,221) Men, age 18 to 55; family practice clinic 70 Olsen et al., 1992 (143) (n = 1,242) Both sexes, ages 11 to 17; urban school district 30 Frequent or persistent low back pain Nagi, Riley, and Newby, 1973 (144) (n = 1,135) Both sexes, ages 18 to 64; citywide population Frequent pain 18 14 Deyo and Tsui-Wu, 1987 (7) (n = 10,404) Both sexes, age >25; national sample (National Health and Nutrition Examination Survey II) Ever had pain >2 weeks 10 Taylor and Curran, 1985 (148) (n = 1,254) Both sexes, age ≥18; citywide sample (Louis Harris Survey Group [Sternbach, 1986]) Pain >30 days in past year 15 Reisbord and Greenland, 1985 (145) (n = 2,792) Both sexes, age >25; national sample (National Health and Nutrition Examination Survey II) Frequent back pain 18 Low back pain with features of sciatica Deyo and Tsui-Wu, 1987 (7) (n = 10,404) Both sexes, age >25; national sample (National Health and Nutrition Examination Survey II, 1976) Pain ≥2 weeks, radiating to leg, increased with cough, sneeze, and deep breathing 1.6 Herniated disc diagnosed by a physician Kelsey, Golden, and Mundt, 1990 (146) Both sexes, ages 7 to 64; national sample (National Health Interview Survey, 1976) Prolapsed disc diagnosed by physician 1.0 Deyo and Tsui-Wu, 1987 (7) (n = 10,404) Both sexes, adults; national sample (National Health and Nutrition Examination Survey II) Ever told by physician they had ruptured disc 2.1

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Page 43 TABLE 2.3 Prevalence of Various Categories of Low Back Pain, by Race, Age, and Sex (percentage) Any in Past Yeara Frequent in Past Yearb Lifetime Occurrence Lasting ≥2 Weeksc On Most Days for 1 Month or Mored Race White 59 19 14 25 Black 46 19 11 20 Other 48 9 21 Age, years 18 to 34 61 14 10 18 to 44 20 35 to 49 53 21 12 50 to 64 56 21 17 45 to 64 30 ≥65 49 18 16 ≥65 29 Sex Male 53 15 14 24 Female 57 20 13 24 aData from Louis Harris Survey Group, 1985 (from Sternbach, 1986). bData from a citywide population survey; see Reisbord and Greenland, 1985. cData from the National Health and Nutrition Examination Survey II, as reported by Deyo and Tsui-Wu (1987). The percentages are estimates because the reported age categories differed slightly from the ranges presented here. Although the decline in lifetime occurrence of low back pain in the highest age category may be surprising, it has several surveys. Possible explanations are patients' limited recall for distant past events, selective mortality (persons with low back pain have shorter survival, perhaps due to associated health habits or socioeconomic circumstances), or a “cohort” effect, in which persons over age 65, for unexplained reasons, had a lower likelihood of low back pain throughout their lives. dData from the National Center for Health Statistics, National Health Interview Survey, 1995, as reported by Praemer, Furner, and Rice (1999). slightly over 9.4 percent of the entire projected U.S. population reporting hand or wrist conditions in 1988; 1.55 percent (1.62 million people) of these are self-reports of carpal tunnel syndrome. Results of the National Health Interview Survey for 1995 showed a 1.74 percent prevalence of impairment from upper extremity or shoulder musculoskeletal disorders (Praemer, Furner, and Rice, 1999). Atroshi et al. (1999) have documented a rate of 14.4 percent for working-age adults with symptoms referable to the wrist, and a physiological and clinical diagnosis could be made for about 3 percent. Nordstrom et al. (1998), studying the catchment area of the Marshfield Clinic, documented 378 new cases of carpal tunnel syndrome among a total population of 55,000 over three years, equaling a new diagnosis for about 1 percent of all adults in the region. Multiple data

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Page 44 sources confirm the high prevalence of low back pain (see Table 2.2 and Table 2.3). Depending on how survey questions are posed, between 19 and 56 percent report having some back pain within a given year, while between 10 and 18 percent report frequent pain or pain lasting more than 2 weeks. Notably, as has been stressed in the low back pain literature, the proportion of these for whom either sciatica is present (suggesting focal anatomic defect) or a herniated disc is diagnosed by a physician is relatively small by comparison. Furthermore, the National Ambulatory Medical Care Survey of 1989, on the basis of a probability sample of all outpatient health care facilities in the United States, ranks musculoskeletal disorders second after respiratory conditions as the most common reason for seeking health care. For 1989, it was estimated that there were 19.9 million visits for low back pain, 8.1 million for neck pain, and 5.2 and 2.7 million for hand and wrist pain, respectively. In summary, data on the general population suggest the following: (1) musculoskeletal disorders, especially low back pain, are very prevalent and a major reason for seeking health care, (2) musculoskeletal disorders represent the most common cause for disability among workers in their 50s and 60s, and (3) projections suggest that these figures are rising, largely because of changes in the demographics of U.S. society and the workforce. WORK-RELATED MUSCULOSKELETAL DISORDERS Information about the distribution of musculoskeletal disorders by type of work across the U.S. workforce is needed in order to estimate the burden of work-related musculoskeletal disorders. However, there is no single, comprehensive surveillance data system that provides the necessary data to link musculoskeletal disorders and work. Without such a system, it is necessary to examine elements of the association, as represented in several incomplete, somewhat overlapping data sources. Several national systems and some systems from smaller or more targeted jurisdictions may contribute to developing a reasonably robust estimate of burden. Elements to be considered are discussed below and shown in Table 2.4. The Annual Survey of Occupational Injuries and Illnesses, which is the responsibility of the U.S. Department of Labor's Bureau of Labor Statistics (BLS), reports annually on the number and incidence of workplace injuries and illnesses in private industry. The private industry workforce covered includes approximately 75 percent of the total workforce, which is estimated to be 135 million (Bureau of Labor Statistics, 2000b). Beginning with the 1992 survey, BLS has collected additional

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Page 45information on more seriously injured or ill workers in the form of worker and case characteristics. Excluded are the self-employed, farms with fewer than 11 employees, private households, and federal, state, and local government agencies. Comparable occupational injury and illness data for railroad activities are provided by the U.S. Department of Transportation's Federal Railroad Administration, and for coal, metal, and nonmetal mining are provided by the U.S. Department of Labor's Mine Safety and Health Administration. The National Center for Health Statistics conducts numerous surveys designed to provide national estimates of the disease burden and health status of the nation. Only the National Health Interview Survey contributes to estimating prevalence by type of work and musculoskeletal disorder. In 1988, these data were collected by a supplemental survey on work and selected musculoskeletal conditions, with self-report of work-relatedness for those conditions. The objective of this survey is to monitor the health of the U.S. population by self-reported health conditions. The survey covers the civilian noninstitutionalized population of the United States. It was used to gather information annually on a sample of approximately 100,000 individuals. The state of Washington provides workers' compensation for two-thirds of the state's workforce, while the other third are covered by employer programs of self-insurance. Through the Washington State Fund, the state maintains data from accepted compensation claims that permit examination of conditions by standard diagnostic codes and by industry. The Federal Employees' Compensation program provides workers' compensation benefits to federal employees, numbering 2.9 million in 1994. Data from the U.S. Department of Labor Office of Workers' Compensation Programs provide detailed coding by the International Classification of Disease (ICD-9) along with other demographic features. There are at least two other potential resources that could contribute to building a proper estimate of the total burden of work-related musculoskeletal disorders. These are medical care utilization data (with proper protection of medical confidentiality) and the National Occupational Exposure Survey undertaken by the National Institute for Occupational Safety and Health. A combination of these national and regional databases could be used to provide improved and more informative estimates of the burden of work-related musculoskeletal disorders. Some combination of them could also serve to provide an improved mechanism for tracking trends at the level at which the role of risk factors themselves could also be closely followed. Tracking systems would inform employers, employees, and relevant government agencies about important trends in both the devel-

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Page 46 TABLE 2.4 Comparison of Data Elements in Major Systems Reporting on Musculoskeletal Disorders at Work Database Population Denominator Exclusions Case Definition BLS Part I 165,000 establishments Hours worked by SIC Small farms, self-employed, private household, government workers OSHA recordable BLS Part I 165,000 establishments Hours worked by SIC Small farms, self-employed, private household, government workers OSHA recordable with at least one missed day NHIS 43,000 households 106,000 persons U.S. population None (sample chosen to represent U.S. population) Self-reported conditions (1988 supplement on musculoskeletal disorders) Washington State Fund 2/3 employers Hours worked Self-insured, self-employed Accepted cases, gender/race Medical claims data Insured populations Difficult to characterize None Algorithms need to be created NOTE: BLS = Bureau of Labor Statistics; ICD = International Classification of Disease; NHIS = National Health Interview Survey; OSHA = Office of Safety and Health Administration; SIC = Standard Industrial Classification; SOC = Standard Occupational Classification. opment and the amelioration of risk factors related to musculoskeletal disorders. Annual Survey of Occupational Injury and Illnesses Survey Structure and Sampling Strategy As interest in the importance of work and musculoskeletal disorders has grown over the past two decades, the most common data reference has been the Annual Report on Injuries and Illnesses provided by the

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Page 47 Case Coding Exposure Factors Timing Demographic Data Severity Measures BLS coding Hours worked in SIC Year None None BLS coding body part, Nature SIC, SOC, event, source Year Age, gender, race, years worked Lost days, restricted workdays, None Occupation: longest, last 12 months last 2 weeks Within last 12 months, Age, gender, race Disability, time away from work ICD9 Occupation NA None Lost time >4 days, costs ICD9 Job-specific information must be matched Algorithm needs to be created for onset Age, gender, race Algorithm needs to be created Bureau of Labor Statistics. Since 1982, the source for these data has been a national sample of private industry reports of injury and illness according to the requirements of the Occupational Safety and Health Administration (OSHA Form 200). This source is therefore limited to employment in the private sector and includes only cases that have been determined to be work-related by the employer, using definitions provided by OSHA. Annually, a stratified random sample of establishments is selected to provide data. (For the mining workforce, the Mine Safety and Health Administration requires that full details of all work-related injuries and illnesses be reported to BLS. Currently, the sample of nonmining establishments is

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Page 48 approximately 165,000, significantly reduced from the sample size of 250,000 establishments selected for the annual survey a decade ago). When an employer is selected to be part of an annual sample, two-part forms are provided for recording and submitting the necessary summary information about occupational injuries and illnesses. In Part I (Summary of Occupational Injury and Illnesses), the employer is instructed to provide information from personnel records and from the Log and Summary of Occupational Injury and Illnesses (OSHA 200) that reports: (a) the size of the establishment, (b) the number of hours worked during the year, (c) the total number of injuries separated into those with and without lost workdays, (d) the total types of illnesses (using OSHA's classification of skin diseases or disorders, dust diseases of the lungs, respiratory conditions due to toxic agents, poisoning, disorders due to physical agents, disorders associated with repeated trauma, and all other occupational illnesses), and (e) the number of illnesses separated into those with and without lost workdays. At the level of this survey, BLS is able to estimate total employment by industry or by occupation, thus permitting the calculation of injury and illness incidence rates. On the basis of reports in Part I, musculoskeletal disorders are identified only by category of illness or “disorders associated with repeated trauma.” For the guidance of those completing the OSHA log and summary, this category is described with the following examples: noise-induced hearing loss; synovitis, tenosynovitis, and bursitis; Raynaud's phenomena; and other conditions due to repeated motion, vibration, or pressure. Thus, while the category includes a case of hearing loss, it is unlikely to include a case of back strain or pain from overexertion. In Part II (Reporting of Cases with Days Away from Work), each establishment covered by OSHA is required to maintain detailed information about each injury and illness on the form entitled Supplemental Record of Occupational Injury and Illnesses (OSHA 101). Since 1992, BLS has requested that each establishment included in the annual sample provide information from this supplemental record for cases reported to result in at least one day away from work. The Mine Safety and Health Administration requires all mines to report the full details of all cases. Information extracted from this supplemental form provides the following details about the lost-time cases: date of event, days away from work, days of restricted work activity, length of service, race, age, gender, and occupation. Three additional details are provided in a descriptive or narrative form: event (what the employee was doing and how the injury occurred); nature (what the injury or illness was), and source (what object or substance directly harmed the employee). These details are then coded according to a BLS-developed system that allows better focus on musculoskeletal disorders, although it is not based on the standard ICD catego-

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Page 54 The estimated overall prevalence of cases of work-related back pain with at least one lost workday was 4.6 percent of the working population. Furthermore, the proportion of back pain cases reporting lost workdays was 50 percent higher among those who attributed their pain to work than among those who did not. The investigators grouped industries according to the most workdays lost (overall average of 9.2 days for work-related cases) and according to the highest number of workdays lost per lost-workday case. Nationally, back pain of any type was estimated to account for 149 million lost workdays, the majority of which (68 percent) were associated with work-related back pain. The industry with the most lost workdays was construction for men (1.76 million days) and elementary and secondary schools for women (760,000 days). Examining severity of the back pain cases among those with work-related pain, the industry with the highest average lost workdays was the electronic computing equipment industry (29 days/case) for men and the U.S. Postal Service (61 days/case) for women. Both sexes were ranked high for grocery stores, hospitals, banking, and eating and drinking establishments. However, there is substantial variation by gender. For example, in the U.S. Postal Service, men reported average lost workdays of only 1.9 days per case, one-thirtieth of that found among women. Survey Results for Hand Discomfort The survey questions about hand discomfort elicited information about carpal tunnel syndrome, tendinitis and related syndromes, and arthritis. Analyses of these self-reports indicate that annually among working adults: 1. 1.87 million report having carpal tunnel syndrome, of which over one-third report that their health care provider diagnosed their condition as carpal tunnel syndrome and half of these were believed to be work-related (Tanaka et al., 1995, 1997). 2. 588,000 report having tendinitis or related syndromes, of which 28 percent were labeled as work-related by a health care provider (Tanaka, Petersen, and Cameron, in press; Tanaka et al., 1997). 3. Almost 2 million active or recent workers were estimated to have hand-wrist arthritis that caused a major change in work activities, jobs, or missed workdays among almost 20 percent (Dillon, Petersen, and Tanaka, in press, Tanaka et al., 1997). The cases in which one or more of these three disorders confirmed by a health care practitioner were evaluated for associations with a number of risk factors, including age, race, gender, and work requiring repetitive

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Page 55bending and twisting. All three conditions were significantly more common among those whose work required bending and twisting of the hands and wrists (Dillon, Petersen, and Tanaka, in press; Tanaka, Petersen, and Cameron, in press; Tanaka et al., 1995, 1997). Washington State Workers' Compensation Reports The Washington State Fund provides workers' compensation for two-thirds of the state's workforce, with the other third offered through employer programs of self-insurance. As a result, the state has an unusually complete and uniform data resource for analyzing workers' compensation cases. Particularly important is the fund's access to medical information that permits identifying conditions by ICD code. This facilitates comparisons with similarly coded general medical information. Recently, these data have been used to examine the work experience of those whose conditions of the back and upper extremity qualify for compensation after a determination of work-relatedness (Silverstein and Kalat, 1999). Claims data for 1990 to 1997 concerning back injury claims showed a total of 228,500 cases, for an annual incidence rate of 2.3/100 full-time workers. Gradual-onset back injuries represented two-thirds of the awarded claims, and 60 percent of the lost workdays attributed to back injuries. Claims data for the same period involving upper extremities revealed a total of 254,600 cases for an annual incidence rate of 2.6/100 full-time workers. Gradual-onset upper extremity injuries represented over one-third of the awarded claims and almost half of the lost workdays attributed to upper extremity injuries. Similar incidence rates were found in the review of data from self-insured workers. When age and gender characteristics of the occupational carpal tunnel syndrome cases from this dataset were compared with those reported in population-based studies of carpal tunnel syndrome the results were: Women and men had almost equivalent incidence rates (1.2:1) and onset was at 37 years of age. For the general population, the gender ratio was 3:1 and average age of onset for carpal tunnel syndrome was 51 years (Franklin et al., 1991). Analyses of the Washington State Fund data also provide information about the leading industries in which workers' compensation claims are awarded for back or upper extremity disorders. For gradual-onset back disorders, these are nursing homes, roofing, wood frame building construction, landscaping, and wallboard installation. For upper extremity disorders, these are wood products manufacturing, wholesale meat

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Page 56dealers, nursing homes, and temporary help in assembly work and sawmills. The self-insured companies—the 400 largest in the state—represent a different industrial mix. For gradual-onset conditions, the additional industries of concern were package delivery, bus companies, warehouses, supermarkets, and municipal workers, including schools. U.S.Department of Labor Office of Workers' Compensation Programs The U.S. Department of Labor Office of Workers' Compensation Programs data have been used to examine characteristics of compensated claims for upper extremity disorders. Since this dataset also provides ICD specific diagnostic information, carpal tunnel syndrome can be identified with confidence. Similar to the Washington State Fund report, the range of almost all cases was between ages 31 and 50, but women were a higher proportion of all cases of carpal tunnel syndrome (2.3:1). Data were not available on job or industry equivalents, so gender differences in other likely exposures could not be evaluated (Feuerstein et al., 1998). Medical Claims Data Until recently, it has been uncommon to access general medical claims data to determine the patterns of musculoskeletal disorders among working adults. A collaboration between the United Auto Workers and Chrysler Corporation permitted the development of a successful methodology for examining these data without breaching medical confidentiality. The study reported on employees from five plants chosen to represent a diversity of automotive manufacturing activity (Park et al., 1992). The medical claims data over three years were linked with job histories, permitting examination of rate differences by job or department. These data do not include medical treatment information for any workers' compensation claim. The target conditions for the initial analyses were selected musculoskeletal disorders (carpal tunnel disorder, other musculoskeletal disorders of the upper extremity, rotator cuff syndrome, musculoskeletal disorders of the neck, and musculoskeletal disorders of the back). The findings revealed wide differences when crude incidence rates were examined across departments, especially when departments with suspect biomechanical risks were compared with departments considered as having low or no occupational risk factors for these conditions. Although the current limitations in the use of these data are substantial, the striking finding was the apparent frequent occurrence of musculoskeletal disorders that might prove to be work-related but were not

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Page 57identified as such with respect to workers' compensation claims. There are two implications. The first is that workers' compensation records are likely to be very incomplete for estimating the relative importance and distribution of musculoskeletal disorders related to work. Second, study of the incidence or prevalence of work-related musculoskeletal disorders in the general population is likely to include a large number of conditions that are not recognized as work-related. National Occupational Exposure Survey The National Occupational Exposure Survey was designed by NIOSH to provide data descriptive of health and safety conditions in the work environment in the United States. Almost 4,500 facilities were visited to evaluate working conditions and potential exposures to workplace risks in most types of work settings in the country. Among the factors identified were (1) potential exposure to whole body and segmental vibration and (2) work conditions associated with passive or awkward postures, lifting, arm or shoulder transport movements, hand-wrist manipulation, finger manipulations, and machine-paced work. Although the survey was carried out in the early 1980s and may be outdated in some regards, it offers data to better characterize work factors related to musculoskeletal disorders in specific jobs in a wide variety of workplaces. One analysis of these data indicated that hand-wrist manipulations were observed almost as frequently as continuous noise exposure. Using these data, an estimated 2.2 million workers were exposed to continuous noise and 2.0 million workers to hand-wrist manipulations (Wegman and Fine, 1990). DATA ON ECONOMIC COSTS Data are available on the cost of musculoskeletal disorders in the general population. A 1999 report from the American Academy of Orthopaedic Surgeons (Praemer, Furner, and Rice, 1999) estimates the total cost of all musculoskeletal conditions in the United States at $215 billion in 1995. Included are the direct treatment cost that accounted for 41 percent of the 1995 total; morbidity costs, the value of reduced or lost productivity, 52 percent; and mortality costs, 7 percent, based on a 4 percent discount rate of the value of productivity forgone in future years as a result of premature mortality in 1995. These figures include occupationally as well as nonoccupationally related disorders. There is a wealth of information on the direct cost to workers' compensation insurers for claims filed in the 50 states as well as in the federal compensation system. Data from two states, Washington and Wisconsin, have been extensively analyzed in relation to musculoskeletal disorders

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Page 58 (Silverstein and Kalat, 1999; Boden and Galizzi, 1999). Moreover, Liberty Mutual has undertaken a series of studies looking at the costs per musculoskeletal disorder by type, as well as in the aggregate. Using the figure derived above from BLS for reported musculoskeletal disorder-like illnesses or injuries involving lost work time of about 1 million cases, and the average direct cost in workers' compensation per case estimate of over $8,000, one may estimate a minimal direct cost for compensation of $8 billion. However, using the proportion of all workers' compensation expenditures related to musculoskeletal disorders (about one-third) and the total workers' compensation cost in the United States of $55 billion (National Academy of Social Insurance, 2000), the estimate for direct workers' compensation costs would be closer to $20 billion. Economic assessment of the actual cost for these compensated claims is higher, of course, since there are many indirect costs to employers, the affected individuals, and society. These include lost productivity, uncompensated lost wages, personal losses, such as household services, administration of the programs, lost tax revenues, social security replacement benefits, and so forth (Morse et al., 1998; Boden and Galizzi, 1999). Estimating the additional costs associated with these uncompensated components yields estimates of total costs associated with reported musculoskeletal disorders as high as $45 to $54 billion, a figure around 0.8 percent of the nation's gross domestic product. As noted above, there is substantial reason to think that a significant proportion of musculoskeletal disorders that might be attributable to work are never reported as such. Morse and his colleagues (1998) in Connecticut, using a population-based phone survey, estimated that about 1 in 10 working-age adults suffers from a condition that would meet qualification for work-related musculoskeletal disorders of the neck, arm, wrist, or hand, and that in over 20 percent of these a physician had made such a diagnosis by report. However, only 10 percent of these workers had accepted workers' compensation claims, which would suggest a very high rate of underreporting. Moreover, these investigators found additional hidden costs associated with work-related musculoskeletal disorders in their survey, including losses of homes and cars, divorces, and job dislocations. The Health and Retirement Survey, which is a population-based survey of adults ages 51 to 61 (Yelin, 1997; Yelin, Trupin, and Sebesta, 1999), approached the question differently, comparing direct markers of economic function in workers with and without musculoskeletal disorders in their population. On average, workers with musculoskeletal disorders earned approximately $3,000 less per person than those without, after adjusting for all other health and social differences. Given the high prevalence of musculoskeletal disorders in adults ages 51 to 61 (62 percent in

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Page 59their study), this would translate into an income loss nationally for men and women in that age group of over $41 billion. Of course, there is no evidence on the fraction of these individuals that would qualify for a diagnosis of work-related musculoskeletal disorders. Nonetheless, the economic impact of musculoskeletal disorders, when expanded to younger adults, would certainly exceed 1 percent of the nation's gross domestic product. LIMITATIONS OF THE DATA Musculoskeletal Disorders in the General Population It has already been highlighted that the data derived from the general population estimates are intrinsically limited by the absence of any linkage to data that would allow discrimination or apportionment among work and nonwork-related factors. Nor are there any data available that provide musculoskeletal disorder rates in an “unexposed” population, since the exposures of interest are so widespread. Nor are such data capable of being easily developed. There are other intrinsic limitations to the general population data worthy of note. First, as has been mentioned, most available data have been derived from self-report. In other words, these data are not summaries of medical diagnoses but responses of individuals regarding symptoms or their knowledge of a physician's diagnoses. This problem stems in part from the difficulty associated with diagnosis of many of the conditions of concern, such as low back or wrist pain, which are, even in physicians' evaluation, judged largely on patient complaints. While other conditions, such as carpal tunnel syndrome and herniated disc, may be more amenable to specific testing approaches (albeit each with substantial controversy within the medical community), such conditions represent only a small minority of cases of musculoskeletal disorders. This problem is intrinsic to the nature of the musculoskeletal disorders themselves and not amenable to simple scientific or biomedical solution. The paucity of data due to the small number of surveys and the infrequency of their conduct is a limitation that is potentially amenable to solution. Strategies for linking physician diagnoses with other demographic data, as has been done in a very limited way for low back pain (see, e.g., Frymoyer et al., 1983), could provide more reliable indices for estimating the burden of musculoskeletal disorders within different strata of the population. Equally important, linkages between these diagnoses and metrics of exposure to the major risk factors that may be associated with musculoskeletal disorders would theoretically allow direct estimation of the proportion of cases associated with the varying factors, the

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Page 60degree to which these factors covary in relation to the disorders, and the potential proportion that could be prevented by interventions aimed at these specific factors. Currently, none of the existing databases available for the general population offers such a possibility. Finally, it must be reiterated that no databases provide rates of musculoskeletal disorders in representative populations without exposure to the risk factors of concern. Identification of such “unexposed” populations could meaningfully be achieved only within the context of linkage among demographic, health, and work data that is not currently foreseeable. Work-Related Musculoskeletal Disorders Annual Survey of Occupational Injuries and Illnesses The Annual Survey of Occupational Injuries and Illnesses survey is the only resource that currently provides ongoing, consistent reporting of injuries and illnesses that permits examination of trends over time. Therefore, it is the only national resource that can be used for the surveillance goal of tracking trends in injury and illness rates. Trend analysis is useful both to identify new risks and to evaluate efforts to reduce known risks. The survey has limitations that are well recognized. Limitations of Part I 1. The survey represents only private industry, excluding approximately 25 percent of the workforce, primarily government workers, those who are self-employed, those who work on small farms, and those employed in places with fewer than 10 individuals. 2. In order to gain cooperation from the reporting establishments, BLS protects the confidentiality of results by not making them publicly available if (a) the estimates for the industry are based on too few reporting units, (b) average employment in the industry is too small (generally < 10,000), (c) statistical estimates do not meet minimum reliability criteria, or (d) there is any other way that publication might disclose confidential information. 3. The sample size of 165,000 is too small to permit estimates at any level below the national level except for large aggregated industry groupings. This is not the case for the subcategory of mining, since the Mine Safety and Health Administration requires reporting of all injuries and illnesses, not just a sample of these events.

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Page 61 4. The illness coding system is not ICD-based. Rather, it utilizes very crude collapsing of unlike conditions and is determined by a person with no specific training for the task. 5. The demographic characteristics of individuals are not reported, and only industry, not occupation or task, is collected, limiting the description of the injuries and illnesses with adequate specificity. Limitations of Part II In addition to the first three limitations listed for Part I: 1. The greater detail on each injury or illness that is provided in Part II is collected exclusively for lost-time injury or illness cases. OSHA, however, requires this level of detail to be recorded on all injuries and illnesses. BLS has neither the mandate nor the resources to collect and analyze the additional data, although such data would greatly enhance the usability of the database available for surveillance purposes. 2. The more detailed nature and body part coding system is not ICD-based and the narrative is provided by an individual with no specific training for the task. Although the coding is done by trained BLS staff, the inputs are still not adequately standardized. 3. While there are proper demographic characteristics associated with all reports as well as the occupation or task being performed, no comparable denominator data are collected. This prevents the calculation of rates for these better-specified conditions. A recent analysis of workplace fatality rates indicates that it is possible to address this problem (Ruser, 1998.) 4. Data items are suppressed at a national level if the number of cases is fewer than five. National Center for Health Statistics Surveys These surveys provide a number of ways to characterize the health of the U.S. population. The different survey elements allow for the development of a comprehensive measurement of health as self-reported and as diagnosed by health care providers. When these reports are combined, the result is an excellent resource for use to describe the health of the workforce. There are some important limitations that could be corrected, however, as is seen in the NIOSH-funded 1988 supplement to the National Health Interview Survey:

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Page 62 Limitations 1. For the interview surveys (National Health Interview Survey and the National Health and Nutrition Examination Survey), only the job title or industry is collected and then only for the preceding week, month, or 12 months. For the health care records (e.g., the National Ambulatory Medical Care Survey), no data are collected on job or industry. 2. Despite the importance of musculoskeletal disorders in the population (both work-related and nonwork-related), the currently designed surveys collect little detail about these disorders. The added detail in the 1988 NHIS supplement presents a good example of how informative survey data can be when these disorders are better characterized. Workers' Compensation Records and the Washington State Fund The data available from the Washington State Fund are valuable because they have a well-defined population base to which they refer. However, while the Washington State Fund data are among the best, the occupation and industry distribution in one state does not provide an adequate national representation of either those occupations and industries and cannot provide information about occupations and industries not prevalent in Washington. Data based on workers' compensation vary across states as each state applies differing definitions and criteria in determining the conditions that are compensable. The between-state differences are substantial, placing further limits on efforts to derive national estimates of burden from workers' compensation claims. There is evidence that such claims are an underestimate of work-related musculoskeletal disorders, suggesting some limitations of workers' compensation reporting for surveillance and for estimating the national burden of work-related musculoskeletal disorders (Biddle et al., 1998; Morse et al., 1998). While some limitations of the system are administrative, other limitations should be noted. The decision to file a workers' compensation claim is determined by knowledge that the option exists (Sum, 1996). This varies by state and by the education or training of each worker and employer. A decision to file a claim also depends on how likely the claim is to be contested (Herbert, Janeway, and Schecter, 1999), workers' concerns about employer retribution if they file (Speiler, 1994; Pransky et al., 1999; Ochsner et al., 1998), and the alternatives available for payment of medical costs (medical insurance).

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Page 63 National Occupational Exposure Survey The National Occupational Exposure Survey is an important national resource for hazard surveillance providing the data to describe the distribution of ergonomic risk factors by industry and occupation. The survey, however, was last carried out almost 20 years ago and is not likely to represent well the distribution of current exposures. It also does not provide exposure characterization of the risk factors present in emerging industrial sectors. Medical Care Utilization Data Data from medical care records could be particularly valuable in providing much greater detail about the nature, distribution, time course, and disability associated with musculoskeletal disorders. Such data, however, have important limitations: 1. Medical confidentiality mechanisms need to be developed to allow use of these data for surveillance purposes and to protect the individual identity of those whose records are in the system. 2. Although specific diagnostic information is recorded by ICD-9 coding, algorithms will need to be developed to ensure consistency in diagnostic practice across providers and determine reliability. 3. Systems to match information on occupation or employer will need to be developed so that patterns of musculoskeletal disorders among different working groups can be examined. Data on the Economic Costs Since the estimates of cost are contingent on estimates of incidence, severity, and prevalence rates for musculoskeletal disorders and differentiation of work from nonwork-related cases, all of the above limitations apply to these estimates. In addition, there are issues unique to the economic estimates: (1) other than the direct costs of health services and wage offsets, there is no uniformly agreed-on formula for estimating the additional costs of each case, such as domestic productivity, reduced future occupational productivity, reduced educational opportunities for children, etc.; (2) it appears likely that additional costs, over and above health services and wage replacement, accrue not only to victims of musculoskeletal disorders, but also to their employers and to society. These include administrative costs, training of replacement workers, lost tax revenues, utilization of public replacement benefits or assistance, etc.

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Page 64Strategies for assessing these additional costs remain understudied and controversial and are one basis for the wide range of estimates cited above. SUMMARY There are sufficient data regarding the occurrence of musculoskeletal disorders in the general U.S. population, including workers and non-workers, to conclude that the musculoskeletal disorder problem is a major source of short- and long-term disability, with economic losses in the range of 1 percent of the gross domestic product. However, these sources suffer from severe limitations: (1) they use nonstandard criteria for designation of musculoskeletal disorders, making comparison among them impossible; (2) data points are infrequently collected, making analysis of trends or changes impossible; and (3) none is currently structured in such a way as to allow distinctions between musculoskeletal disorders that may be related to work activities and those that are not. BLS and workers' compensation data are sufficient to (1) confirm that the magnitude of the work-related musculoskeletal disorder problem is very large; (2) demonstrate that rates differ substantially between industries and occupations consistent with the assumption that work-related risks are important predictors of musculoskeletal disorders; and (3) document that the rapid growth in the problem or its recognition that occurred in the 1980s has shown a slight decline in the 1990s. These data provide substantial information regarding those musculoskeletal disorders that are considered work related. Moreover, they have been obtained regularly and provide some insight into the relationship between certain kinds of industries and occupations and the rates of musculoskeletal disorders. In these databases, cases have been selected in variable, nonuniform ways that are likely to underrepresent the spectrum of work-related musculoskeletal disorders that occur; musculoskeletal disorders are coded in nonstandard ways, further limiting comparability between data sources; and information available in terms of demographic and occupational risks is very limited. Taken collectively, review of all available data sources underscores the need for more complete, more frequent, and better standardized databases that include, at a minimum, uniform coding of musculoskeletal disorders and sufficient information about industry, occupation, and tasks to allow accurate quantification of the musculoskeletal disorder problem, separation into those aspects that are and those that are not related to work factors, and tracking to determine the effects of interventions as they are undertaken.