Musculoskeletal Disorders. Sean Gallagher
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