Читать книгу Musculoskeletal Disorders - Sean Gallagher - Страница 13

The ability to move about freely can be easily taken for granted, but if one stops to consider the finely tuned coordination of the multiple intricate systems necessary to accomplish even simple movements, both the beauty and remarkable complexity of the musculoskeletal system can be appreciated. Movement requires careful synchronization of a complex structure made of muscle, bone, cartilage, tendon, ligament, and nerve to permit specific movement goals to be achieved. Not only is the musculoskeletal system itself complex, but it is also dependent on other complex systems to supply the resources necessary to accomplish desired movement objectives. These other supporting systems (e.g., nervous, cardiovascular, respiratory, and gastrointestinal) provide nutrition and other resources required by musculoskeletal tissues that allow us to perform tasks or activities that we desire to accomplish (or which may be required of us), and otherwise live our everyday lives. However, despite the remarkable capabilities of the musculoskeletal system, each system component is made of materials that will experience damage when exposed to repeated stress. The accumulation of damage that can result may lead to tissue injury, pain, disability, and/or system dysfunction.

Injuries to the musculoskeletal system result in extraordinary societal impacts and economic costs. In the United States alone, over 73 million adults suffer from chronic low back pain, and the annual cost of treatment and lost wages associated with back pain was estimated at $315 billion (United States Bone and Joint Initiative, 2021). Musculoskeletal disorders (MSDs) also account for a substantial loss of productivity in the workplace. For example, back and neck disorders were associated with 264 million annual lost workdays according to data from 2015 (United States Bone and Joint Initiative, 2021). However, back pain is but one of the many MSDs that lead to these substantial economic, societal, and individual costs. An analysis of work‐related upper extremity disorders in US workers indicated that the 30‐day prevalence of these disorders was 8.2% but ranged as high as 9.9% in the construction industry (Ma et al., 2018). Workers experiencing these disorders typically require more time to recuperate than those experiencing other work‐related illnesses and injuries. For example, US workers with carpal tunnel syndrome (CTS) took a median of 32 days to return to work and those with tendonitis required a median of 15 days of recuperation compared to the median of nine days off for all work‐related injuries and illnesses in the United States for 2014 (Ma et al., 2018).

If we are to effectively combat the enormous societal burden associated with these disorders, it is essential to gain a better understanding of the processes involved with MSD development. Over the past several decades, considerable research has been performed, and a great deal learned about these disorders. However, despite these important advances in our understanding, the identification of specific causal mechanisms that explain exactly how and why these disorders develop has been lacking. To better understand the development of MSDs, we must identify the specific processes that possess causal powers or capacities to bring about changes in the state of musculoskeletal tissues. Identification of such processes or pathways is a central ambition of science and can confer numerous benefits. In the case of MSDs, benefits may include improved risk assessment methods, better injury prevention strategies, and greater insight into physiological and biomechanical processes affecting the development of damage in musculoskeletal tissues.

The purpose of this book is to evaluate a prospective causal mechanism of musculoskeletal tissue damage recently promoted by the authors, to provide evidence in support of this mechanism, and to discuss its rather substantial implications in terms of musculoskeletal tissue damage development, healing, and overall musculoskeletal health (Barbe et al., 2013; Gallagher & Heberger, 2013; Gallagher & Schall, 2017). This mechanism is known as fatigue failure and is the theory that explains how and why damage development occurs in materials subjected to repeated stress. Fatigue failure is not a new theory; in fact, it has a history going back well over a century and a half (Rankine, 1843). However, the application of fatigue failure principles and their role in the development of MSDs have not received much attention until recently. Given that musculoskeletal tissues are materials that are known to experience exposure to repeated stress and that musculoskeletal tissues exhibit damage development, fatigue failure would seem a natural candidate as a causal mechanism to explain the initiation and propagation of damage in musculoskeletal tissues (and the consequent development of MSDs).

The evidence that fatigue failure is a causal mechanism by which inert (i.e., nonbiological) materials experience cumulative damage is by now beyond dispute (Stephens, Fatemi, Stephens, & Fuchs, 2001). This process is observed in all materials exposed to repeated stress, with each exhibiting the distinctive exponential relationship between stress magnitude and the number of cycles to failure. As we will discuss in this book, there is abundant evidence to suggest the same process occurs in musculoskeletal tissues. However, there are some important differences between inert materials and biological tissues in the response to damage invoked by the fatigue failure process. For example, biological tissues possess the remarkable capacity to sense mechanical loading and to remodel (to a degree) tissues to help them adapt to the stresses they experience. Furthermore, when damage is experienced, there is a healing process by which such damage might be repaired. Thus, the fatigue failure process in living tissues may be considered a modified fatigue failure process in which the competing processes of damage and healing will both be important to the health status of the tissue. Having remodeling and healing processes is quite fortunate as they would be expected to extend the fatigue life of musculoskeletal tissues (i.e., the number of loading cycles that can be experienced prior to failure) well beyond what would be possible in the absence of these processes.

Over the past few decades, numerous methods have been developed to assess the risk of developing various types of MSDs. Some of the more popular methods include the National Institute for Occupational Safety and Health (NIOSH) Lifting Equation (Waters, Putz‐Anderson, Garg, & Fine, 1993), The Liberty Mutual Psychophysical tables (Potvin, Ciriello, Snook, Maynard, & Brogmus, 2021; Snook, 1978; Snook & Ciriello, 1991), The Strain Index (Moore & Garg, 1995), and the Threshold Limit Value for Hand Activity (Rempel, 2018). These methods are discussed in greater detail in Chapter 8. As discussed in that chapter, these MSD models have been validated against MSD prevalence and incidence in several epidemiology studies and have provided much knowledge in terms of improving the risk assessment of MSDs. These risk assessment tools have unquestionably aided in the prevention of untold injuries and disability in workers.

Despite the benefits of these methods, however, there appears much to be gained in applying fatigue failure principles to assess MSD risk. As will be discussed in this book, there are many validated fatigue failure techniques that provide ready solutions to challenging problems that have long been faced by musculoskeletal researchers. The following text provides some of the benefits of applying fatigue failure methods to MSD risk assessment.

 Validated Methods of Cumulative Exposure Assessment. It has been a general assumption of musculoskeletal researchers that it is the totality of exposure that an individual experiences (often involving exposure to several tasks with highly variable loading profiles) that determines the risk of developing MSDs. However, not all current models provide methods of combining the risk associated with the performance of multiple tasks during a workday. Fortunately, the fatigue failure theory has validated methods for assessing the cumulative effects associated with highly variable loading histories, as might be experienced in multitask jobs (Miner, 1945; Palmgren, 1924). This technique (described in detail in Chapter 9) not only allows assessment of the cumulative effects of loading but can also evaluate the proportion of risk associated with each individual task. This provides the ability to identify work tasks most responsible for the overall risk (and most in need of ergonomic intervention). These cumulative exposure techniques have been shown to correlate well with MSD outcomes in fatigue failure‐based risk assessment tools (Gallagher, Sesek, Schall Jr, & Huangfu, 2017; Bani Hani et al., 2021; Gallagher, Schall Jr, Sesek, & Huangfu, 2018).

 Biomechanics and Injury Risk. Biomechanical analysis is an important method of evaluating the forces and moments acting on the body due to the performance of physically demanding tasks. However, while this technique allows for the quantification of stresses on the musculoskeletal system, the relationship of calculated forces and moments to actual injury risk has often been missing. For example, a traditional introductory biomechanical problem asks the student to calculate the force required of the elbow flexor muscles to hold a certain load in the hands. For example, it might be calculated that holding a 11.3 kg (25 lbs) weight, the upper arm perpendicular to the floor, and the elbow flexed at 90° require an elbow flexor muscle force of approximately 1,000 N (225 lbs). It is, of course, interesting in itself that the muscle forces required are vastly greater than the load being held. But what if we are interested in estimating the probability of an injury outcome to the elbow flexor tendons if such a load was handled 100 times in a workday? And what if this task were combined with another where 500 repetitions of handling a load of 5 kg (11.0 lbs.) in the same posture? Biomechanical modeling techniques alone cannot answer these questions. However, when used in conjunction with fatigue failure techniques, one can use biomechanical estimates of tissue stress to estimate injury probabilities associated with either mono‐task jobs or combinations of tasks. Chapter 5 discusses the benefits of applying fatigue failure principles to biomechanical analyses to help estimate the fatigue life of tissues experiencing repeated biomechanical stress.

 Damage versus Healing. As indicated earlier, musculoskeletal health is expected to be dependent upon both damage development (due to repeated stress) and healing. As noted long ago by Nash, despite the additional complexity of the presence of a healing component, it is relatively easy to develop an injury model that incorporates both cumulative damage development and healing using a fatigue failure approach (Nash, 1966). This simply involves use of the Palmgren–Miner method (Chapter 9) to ascertain the cumulative damage associated with the experienced variable magnitude loading, and then subtracting out the damage healed over the same time frame. If the rate of cumulative damage is greater than the healing rate, damage will occur; in contrast, if the healing rate equals or exceeds the rate of damage development, no damage would be expected to occur. This model can also be employed to assess risk in conditions associated with impaired healing (such as psychological stress, aging, and obesity), as discussed in Chapter 10. Thus, in contrast to previous models, fatigue failure techniques are well positioned to address important complexities of the biological environment that are important in maintaining musculoskeletal health. This “damage and healing” model may be useful, for example, in assessing the MSD risk associated with factors known to impair the healing process, such as psychological stress, obesity, and aging (Guo & DiPietro, 2010). These and other implications are discussed further in Chapter 10.

 Real‐Time Risk Assessment. The fatigue failure theory also has techniques that could be used as real‐time exposure assessment methods continue to develop and mature (Radwin, 2011). Due to the variable amplitude loading histories experienced by humans in the performance of physical work, a method will be needed to evaluate the risk associated with complex and irregular loading curves. Fortunately, this situation is also encountered in the loading of other materials and methods have been developed to deconstruct complex loading curves into cycles that can then be assessed by fatigue failure models. The consensus technique is known as rainflow analysis (Matsuishi & Endo, 1968). This technique evaluates stress “reversals” (half‐cycles) associated with complex loading histories and derives full cycles for analysis while accounting for the entire load history (Chapter 9). Thus, the fatigue failure approach is well positioned for the future of risk assessment in which complex loading curves derived from real‐time exposure assessment can be rapidly analyzed using validated techniques as discussed further in Chapter 13.

 Cumulative Risk from Different Loading Modalities. Fatigue failure methods also hold the promise of combining the risks associated with diverse loading modalities. For example, imagine a delivery driver who experiences whole‐body vibration from driving across rough roads and then must carry heavy boxes to complete the delivery. Fatigue failure methods hold the promise to combine these two types of repetitive stress into a single measure of risk and provide an estimate of cumulative damage associated with both exposures. Whole‐body vibration is known to be an exposure that imposes repeated stress on the low back (Gallagher & Schall, 2017) as does repetitive compressive loading due to lifting (Brinckmann, Biggemann, & Hilweg, 1988). Since both can be expressed in terms of cumulative damage, fatigue failure techniques could be used to combine these disparate loading modalities to obtain a cumulative measure of overall risk not previously available (Chapter 9).

 Combining Static and Cyclic Loading. MSDs may also be the result of both static and/or dynamic activities. Thus, it would be helpful to have a method of calculating the combined risk associated with a combination of creep (static) loading and cyclic (dynamic) loading. Fortunately, the fatigue failure theory also has a validated method of evaluating the cumulative effects associated with combined static and dynamic loading (Wright, Carroll, Sham, Lybeck, & Wright, 2016). This method allows estimating the proportion of risk associated with dynamic versus static loads overall, as well as the proportion of individual task risks for both types of loading (See Chapters 9 and 13).

 Assessing Risks of Job Rotation. Job rotation is a technique sometimes used in industry in an attempt to balance the biomechanical demands associated with different jobs. However, a recent award‐winning article in the journal Ergonomics using fatigue failure techniques demonstrated that job rotation may be more harmful than helpful in terms of the overall MSD risk to a pool of workers (Mehdizadeh et al., 2020). Due to the nature of the fatigue failure risk function, any reduction in risk for higher risk jobs is guaranteed to be smaller than the increase in risk experienced by those in lower‐risk jobs (See Chapter 13). The magnitude of this effect will vary from extremely large, if a single high‐risk job is present in the pool, to small if all jobs are fairly low risk. Such an analysis would be difficult to achieve with some prior models but is straightforward using fatigue failure principles.

 Influence of Personal Characteristics on MSD Risk. Fatigue failure also offers the potential to incorporate certain personal characteristics into risk assessment. As an example, fatigue failure theory stipulates that the ultimate strength of a material determines the number of cycles to failure at different percentages of that strength. If an individual performs a lifting task resulting in a 2,500 N compressive load on the spine, they will incur damage more quickly if they have a spine ultimate strength of 6,000 N (say at age 60) as opposed to 8,000 N (at age 30). Factors such as age, anthropometry, sex, bone mineral density, and others could be considered to develop “personalized” risk assessments that may be more protective for workers based on their individual characteristics. Risks associated with personal characteristics are discussed in Chapter 12.

The preceding examples provide a sampling of the opportunities that may be realized with the use of the fatigue failure approach to MSD risk, many of which would be difficult to realize with previous approaches. There are numerous other useful applications of this model as will be described in detail later in the book.

In summary, fatigue failure is a universally accepted causal mechanism of damage nucleation and propagation for nonbiological materials, and there is ample evidence to suggest that the same process occurs in musculoskeletal tissues. Much of what has been learned regarding the process of material damage resulting from repeated stress appears applicable to the assessment of musculoskeletal risk, and many techniques developed in this theory appear to provide ready solutions to challenging problems faced by musculoskeletal researchers. These include simple methods of estimating the cumulative impact of multiple tasks having highly variable loading conditions. Techniques are also available for assessing cumulative damage associated with complex loading curves that will be useful soon as real‐time exposure assessment methods for MSDs become available. Furthermore, models incorporating the effects of healing and other biological processes critical to musculoskeletal health have been put forth, thus allowing the complexity of the fatigue failure process in the biological environment to be more fully understood.

As indicated by the earlier discussion, there are many topics to be discussed and implications to be addressed when evaluating the effects of a fatigue failure process in a biological environment and the roles of damage and healing in overall musculoskeletal health. We have structured the 16 chapters in a logical order, and the chapters are grouped into four general themes. Chapters 2–5 provide detailed information regarding common MSDs and the components of the musculoskeletal system, including the structure and function of musculoskeletal structures, the material properties of these tissues, and the important role of nerves and the nervous system in the musculoskeletal system. Chapters 6–9 cover fundamental concepts of biomechanics, evidence of fatigue failure processes in musculoskeletal tissues, and fundamental concepts in fatigue failure analytical methods relevant to the assessment of MSD risk. Chapters 10–12 discuss concepts related to the unique aspects of fatigue failure in a biological environment, addressing the body’s healing capacity and the influence of personal characteristics and psychosocial stress on MSD risk. The final four chapters (Chapters 13–16) provide methods for assessing risk using fatigue failure methods, implications for MSD prevention, suggestions for optimizing musculoskeletal health, and assessment of the status of knowledge and the need for future research in this area. We would note that the book need not be necessarily consumed in the order in which it was written, as many chapters can be read on their own without loss of meaning.