123,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Musculoskeletal Disorders Hands-on guidance and tools for the prevention of musculoskeletal injuries in the workplace In Musculoskeletal Disorders: The Fatigue Failure Mechanism, a team of accomplished occupational health experts delivers an essential and incisive discussion of how musculoskeletal disorders (MSDs) develop and progress, as well as how they can be prevented and controlled. Offering a novel, evidence-based approach to this costly problem, the book has broad implications for employers, insurers, and other stakeholders in workplace health and safety. The authors identify new risk assessment approaches based on the cumulative effects of exposure to highly variable loading conditions. These new approaches can also be applied to evaluate the efficacy of job rotation scenarios and to quantify exoskeleton efficacy. The complexities associated with fatigue failure in biological environments are also explored in addition to suggested models for understanding how the body maintains musculoskeletal homeostasis. Readers will also find: * Thorough introductions to the material properties of musculoskeletal tissues and the fundamental principles of fatigue failure analysis * In-depth explorations of the structure and function of the musculoskeletal system and up-to-date epidemiological research on MSDs * Comprehensive discussions of validated fatigue failure risk assessment methods, including continuous exposure assessment to better quantify injury risk * Insightful treatments of remodeling and healing processes as they apply to MSD risk, as well as factors that impair the healing process, like stress, obesity, and aging Perfect for occupational and environmental health and safety (OEHS) professionals, Musculoskeletal Disorders: The Fatigue Failure Mechanism will also earn a place in the libraries of ergonomists, physical therapists, biomechanists, industrial hygienists, occupational physicians, orthopedists, and musculoskeletal disorder researchers.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 1085
Veröffentlichungsjahr: 2022
Ähnliche
Table of Contents
Cover
Title Page
Copyright Page
Dedication
Preface
Bibliography
Acknowledgments
About the Authors
1 Introduction
Bibliography
2 Common Musculoskeletal Disorders
Overview
Burden of MSDs
Common Musculoskeletal Disorders
Commonalities Among MSDs
Bibliography
3 Structure and Function of the Musculoskeletal System
A Systems View of the Musculoskeletal System
Connective Tissues: General Overview
Skeletal (Striated) Muscle
Tendon
Cartilage
Bone
Ligament
Joints
Summary
Bibliography
4 Structure and Function of the Nervous System and Its Relation to Pain
Overview
A Systems View of the Nervous System
An Introduction to Cellular Components of the Nervous System
Structure and Function of the Peripheral Nervous System
Interactions of Peripheral Nerves with the Musculoskeletal System
Central Nervous System Components that Interact with the Musculoskeletal System
Pain
Summary
Bibliography
5 Fundamental Biomechanics Concepts
Introduction
Newton's Laws
Biomechanical Modeling
Summary
Bibliography
6 Material Properties of Musculoskeletal and Peripheral Nerve Tissues
Overview
Fundamentals of Materials Science
Material Deformation of Musculoskeletal Tissues
General Characteristics of Deformation in Musculoskeletal Tissues
Material Properties of Musculoskeletal Components
Material Properties of Peripheral Nerves
Summary
Bibliography
7 Fatigue Failure of Musculoskeletal Tissues
Introduction
Ex Vivo
Studies of Fatigue Failure in Musculoskeletal Tissues
In Vivo
Studies of Fatigue Failure
Epidemiological Data
Summary
Bibliography
8 MSDs as a Fatigue Failure Process
Introduction
Prior Models and Approaches
Upper Extremity Risk Assessment Tools
Summary of Prior Models
Considering MSD Risk Factors from the Fatigue Failure Perspective
Benefits of the Fatigue Failure Model
Other Potential Applications of Fatigue Failure
Summary
Bibliography
9 Fundamentals of Fatigue Failure Analysis
Introduction
Fatigue Terminology
Mechanisms of Fatigue Failure
The Stress‐Life (
S
–
N
) Curve
Plastic Strain Fatigue Life Estimation Methods
Cumulative Damage and Residual Strength Models
Effects of Mean Stress on Fatigue Life
Cycle Counting in Variable Amplitude Stress Exposures
Weibull Analysis of Fatigue Life
Creep Loading and Creep‐Fatigue
Summary
Bibliography
10 Fatigue Failure in a Biological Environment
Introduction
Responses of Inert Versus Biological Materials to Stress
Healing of Damaged Tissues
Self‐Healing in Engineered Materials
Factors Influencing Healing Kinetics
Effects of Personal Characteristics on Wound Healing
Summary
Bibliography
11 Injury and Self‐Repair of Musculoskeletal Tissues
Introduction
Injury‐Induced Inflammation
Wound Healing—Physiological Versus Pathological
Unique Injury and Healing Mechanisms and Capacity in Specific Musculoskeletal and Neural Tissues
Effects of Continued Tissue Loading on the Healing Process
Summary
Bibliography
12 Personal Characteristics and MSD Risk
Introduction
Biological Variability
Age
Sex
Body Size and Composition
Fatigue Failure Implications Regarding Personal Characteristics
Summary
Bibliography
13 Using Fatigue Failure Principles to Assess MSD Risk
Introduction
Application of Fatigue Failure Principles to MSD Risk Assessment
General Principles of Fatigue Failure Theory
Fatigue‐Failure Based Risk Assessment Tools
Current and Future Developments
Summary
Bibliography
14 Implications for MSD Prevention
Introduction
The importance of Assessing Cumulative Damage
Identifying and Managing Risky Tasks
Stress Reduction/Cycle Reduction
The Load/Repetition Trade‐off
The Central Role of Tissue Strength
Impaired Healing and the Fatigue Life of Musculoskeletal Tissues
Rest
Job Rotation
Exoskeletons and MSD Prevention
Summary
Bibliography
15 Optimizing Musculoskeletal Health
Introduction
General
Reducing MSD Risk in Occupational Settings
Treatment of Injuries
Summary
Bibliography
16 Status of Knowledge and Unanswered Questions
Introduction
Improved Characterization of Musculoskeletal Tissue Properties
Improved Characterization of the Damage Response to Repeated Stress of Musculoskeletal Tissues
In Vivo
Characterization of the Remodeling and Healing Responses in Musculoskeletal Tissues
Musculoskeletal Stress Thresholds
Musculoskeletal Tissues in the Resting State
Risk Assessment in Epidemiological Studies
Assessing the Risk of Multiple Loading Modes
Dwell and Combination Loading
Summary
Bibliography
Index
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Summary of Common MSDs
Chapter 3
Table 3.1 General Features of Connective Tissues
Table 3.2 Summary of Cells, Subtypes, Extracellular Matrix (ECM), and Funct...
Table 3.3 Summary of Cells, Extracellular Matrix (ECM), Subregions, and Fun...
Table 3.4 Summary of Cells, Extracellular Matrix (ECM), Subtypes, and Funct...
Table 3.5 Summary of Cells, Extracellular Matrix (ECM), Subtypes, and Funct...
Table 3.6 Summary of Cells, Extracellular Matrix (ECM), Subtypes, and Funct...
Table 3.7 Classifications of Joints
Table 3.8 Summary of Non‐Neural Tissues of the Musculoskeletal System
Chapter 4
Table 4.1 Basic Arrangements of Neuronal Cell Bodies and Their Processes
Table 4.2 Examples of Neurotransmitters and Neuropeptides
Table 4.3 Main Types of Neuroglia and Their Properties
Table 4.4 Structure of a Synapse
Table 4.5 Comparison of Exteroreceptors Versus Interoreceptors
Table 4.6 Main Functional Divisions of the CNS that Interact with the Muscu...
Table 4.7 Pain Terminology (Pain, 2018)
Table 4.8 Summary
Chapter 5
Table 5.1 Estimates of Biomechanical Parameters (Elbow Moment, Required Mus...
Chapter 6
Table 6.1 Definitions of Common Material Characteristics
Table 6.2 Anisotropic Loading Responses of the Human Femoral Cortical Bone...
Table 6.3 Tensile Fracture Stress (MPa) of Femoral Condyle Hyaline Cartilag...
Table 6.4 Tensile Fracture Stress (MPa) of Femoral Condyle Hyaline Cartilag...
Table 6.5 Elastic Modulus Values (MPa) for Fibrocartilage in Lateral and Me...
Table 6.6 Ultimate Tensile Strength and Other Characteristics After Tensile...
Table 6.7 Rupture Probability for Weights and Excursions Tested
Table 6.8 Percent Retraction of Whole Nerve, Sheath, and Core
Table 6.9 A Summary of the Material Properties of Musculoskeletal Tissues
Chapter 7
Table 7.1 Cumulative Damage Observed in
Ex Vivo
Tested Tendons at Different...
Table 7.2 Percentage of Motion Segments Failing at Different Numbers of Loa...
Chapter 8
Table 8.1 Example of the influence of Variable Tendon Ultimate Stress on th...
Chapter 9
Table 9.1 Determination of the Percentage of Total Damage for Scenario Abov...
Table 9.2 Calculation of Residual Strength
Table 9.3 Estimates of Cumulative Damage from Rainflow Analysis, Assuming t...
Table 9.4 A Representation of a Hypothesized Tendon Loading History Broken ...
Table 9.5 Fatigue Life Data for Human Extensor Digitorum Longus Tendons and...
Table 9.6 Initial Data Required for Regression to Determine Weibull Plot an...
Table 9.7 Failure Probabilities and Reliability for EDL Tendons as a Functi...
Table 9.8 Estimated Cycles to Failure for Various Levels of Reliability for...
Table 9.9 Fatigue Damage Per Cycle and Creep Damage Per Second at Various P...
Chapter 11
Table 11.1 Examples of Mediators of Inflammation
Table 11.2 Examples of Mediators of Tissue Repair (Including Fibrotic Repai...
Table 11.3 Differences Observed Between Normal Ligament Tissue and Repaired...
Table 11.4 Types of Cartilage Damage and Subsequent Events
Table 11.5 Limitations to Articular Cartilage Self‐Repair
Table 11.6 Factors Modifying Bone Self‐Repair, Growth, and Maintenance
Table 11.7 Estimated Healing Times After Acute Injury
Table 11.8 Effects of Repeated Fatigue Loading on Tissue Healing and Repair...
Chapter 12
Table 12.1 Summary of Age‐Related Changes in a Skeletal Muscle
Table 12.2 Example of the Effect of a 200 N Load on a Young Tendon Versus a...
Table 12.3 BMI Values and Corresponding Weight Categories
Chapter 13
Table 13.1 Criteria for Assessment of MSD Risk Assessment Tools
Table 13.2 Crude and Adjusted Odds Ratios for the LiFFT Log CD Measure Vers...
Table 13.3 OMNI‐Res Scale Damage per Cycle (DPC) Estimates from an
In Vitro
Table 13.4 Summary of Crude and Adjusted Logistic Regression Analysis for D...
Table 13.5 Summary of Crude and Adjusted Logistic Regression Analysis Relat...
Chapter 14
Table 14.1 Average Ultimate Compressive Strength for Male and Female Spines...
Table 14.2 Estimates of Cumulative Damage Derived from the Shoulder Tool
Table 14.3 Results of the Cumulative Damage Estimates for The Job Rotation ...
Chapter 15
Table 15.1 Effects of a Sedentary Lifestyle Versus Active Lifestyle on Musc...
Table 15.2 Dietary Factors Necessary for Musculoskeletal Health
Table 15.3 Recommended Sleep Durations
Table 15.4 Suggested Means to Reduce MSD Risk in Occupational Settings
Table 15.5 A Review of Common Pharmacological and Nonpharmacological Treatm...
Chapter 16
Table 16.1 Factors That Favor Bone Anabolic Versus Catabolic Responses
List of Illustrations
Chapter 2
Figure 2.1 A motion segment of the lumbar spine.
Figure 2.2 Focal damage in the intervertebral disc. Fissures of grade 1 (gra...
Figure 2.3 Lumbar vertebrae and their facet (zygopophyseal) joints, which ar...
Figure 2.4 The site of de Quervain’s syndrome is encircled. APL: abductor po...
Figure 2.5 Location of inflamed or injured tissues in the extensor carpi rad...
Figure 2.6 Partial and full tears in supraspinatus tendons, a rotator cuff t...
Figure 2.7 A model for possible early and late events in muscle response to ...
Figure 2.8 Location of the carpal tunnel and path of the median nerve in the...
Chapter 3
Figure 3.1 Loose and adipose connective tissues. (a) Loose connective tissue...
Figure 3.2 Dense irregular connective tissue in the dermis of the skin. (a) ...
Figure 3.3 Extensions of deep fascia around and into individual muscle fiber...
Figure 3.4 Single muscle cells (fiber) showing multinucleated nature and str...
Figure 3.5 Distribution of different myosin heavy chains detected by immunof...
Figure 3.6 Structure of a skeletal muscle.
Figure 3.7 A simplified schematic of a sarcomere is shown. A sarcomere is co...
Figure 3.8 Diagram of the sarcoplasmic reticulum and T‐tubule system of a ma...
Figure 3.9 Vascular anatomy within skeletal muscle. (a) Highly organized vas...
Figure 3.10 The sliding‐filament mechanism.
Figure 3.11 The neuromuscular junction. Adult skeletal muscle is highly orga...
Figure 3.12 Tendon images. (a) Longitudinal tendon section, with examples of...
Figure 3.13 Schematic depicting the hierarchical structure of tendon, with i...
Figure 3.14 Hyaline cartilage. (a and b) Hyaline cartilage in the articular ...
Figure 3.15 Fibrocartilage in the intervertebral discs between the vertebrae...
Figure 3.16 Elastic cartilage.
Figure 3.17 Bone cells. (a) Osteoblasts on the surface of trabeculae (larger...
Figure 3.18 The organization of long bones. (a) Three‐dimensional micro comp...
Figure 3.19 Osteons in cortical bone. (a) The osteocytes canaliculi are visi...
Figure 3.20 Ligaments. (a) A diagram showing the ligament of the knee: later...
Chapter 4
Figure 4.1 Sensory (afferent) nerves send signals from peripheral sensory te...
Figure 4.2 Types of neurons based on shape.
Figure 4.3 Typical multipolar neurons with glial cells that myelinate depict...
Figure 4.4 Peripheral nerve histological sections. (a) A cross‐section of a ...
Figure 4.5 Schwann cells around unmyelinated peripheral nerve axons.
Figure 4.6 (a) Stimulus‐induced amplitude‐graded receptor potentials at rece...
Figure 4.7 A schematic view of an idealized action potential that illustrate...
Figure 4.8 Innervation of muscles and tendons. Depiction of an alpha motor n...
Figure 4.9 A Golgi tendon organ. The vertical dashed lines represent the col...
Figure 4.10 A spinal cord cut cross‐sectionally.
Figure 4.11 Diagram of the spinocerebellar tract and anterolateral system (A...
Chapter 5
Figure 5.1 An example of Newton's third law of motion. The worker pushes on ...
Figure 5.2 A 50 N downward force vector created by gravitational acceleratio...
Figure 5.3 Moment example: (a) a 1 kg (9.8 N) load placed 1 m to the right o...
Figure 5.4 Free body diagram of weight‐holding example. Note sign convention...
Figure 5.5 Reactive moment and reactive forces acting at the elbow.
Figure 5.6 Biomechanical analysis including internal (muscle) forces. The mu...
Figure 5.7 Example of the use of the parallel axis theorem. (a) The mass mom...
Figure 5.8 Dynamic biomechanical example.
Chapter 6
Figure 6.1 The displacement of the spring is proportional to the force appli...
Figure 6.2 An undeformed object and the same object under tensile, compressi...
Figure 6.3 Material stress–strain curve.
A =
proportional limit,
B =
...
Figure 6.4 Relationship of stress and strain for a cortical bone at differen...
Figure 6.5 Stress and strain responses of a viscoelastic solid to an increas...
Figure 6.6 Stress‐relaxation response of a viscoelastic solid subjected to a...
Figure 6.7 Hysteresis is evident in cyclic loading of a tendon at various pe...
Figure 6.8 Model of the nonlinear stress–strain relationship in tendon and l...
Figure 6.9 Scanning electron micrographs showing the mechanism of cartilage ...
Figure 6.10 Ultimate stress values for femoral cortical bone samples from ma...
Figure 6.11 Muscle strain response in tetanized and passive states.
Figure 6.12 Physical stresses placed on peripheral nerves. Tensile stress ap...
Figure 6.13 Correlation between biomechanical strain and incidence of endone...
Figure 6.14 Core pullout and force‐strain profiles of core versus sheath. (a...
Chapter 7
Figure 7.1 Fatigue failure data from
ex vivo
testing of human extensor digit...
Figure 7.2 Inferred relationship between the knee pivot landing force (
F
) in...
Figure 7.3 Comparison of
S–N
curves from studies assessing fatigue fai...
Figure 7.4 Fatigue failure responses of spinal motion segments using combine...
Figure 7.5 Grades of progressive internal disc disruption. Bogduk, N., April...
Figure 7.6 Tensile fatigue failure responses of articular cartilage samples ...
Figure 7.7 Multiple regression lines obtained by Carter, D., & Hayes, W. (19...
Figure 7.8 The relationship between strain range and cycles to failure for b...
Figure 7.9 Fatigue life of cortical bone in shear (R
2
= 0.89,
p
< 0.00001). ...
Figure 7.10 Comparison of the fatigue characteristics of trabecular (group 1...
Figure 7.11 Tendon and serum responses to performance of reaching and graspi...
Figure 7.12 Experimental setup used by Fung et al. (2009) in their study of ...
Figure 7.13 Imaging of the progressive tendon damage resulting from exposure...
Figure 7.14 Cartilage responses in the distal radius (wrist) to the performa...
Figure 7.15 Bone responses in the distal metaphysis of the radius to perform...
Figure 7.16 Three levels of eccentric exercise used in Huangfu et al. (2018)...
Figure 7.17 (a) The HF‐LR group demonstrated significant reductions in MIVC ...
Figure 7.18 Expected force‐repetition interaction pattern for cumulative dam...
Figure 7.19 Results of seven cross‐sectional epidemiological studies allowin...
Chapter 8
Figure 8.1 Biomechanical factors used in static biomechanical analysis model...
Figure 8.2 Model of physical risk factors and their role in the fatigue fail...
Chapter 9
Figure 9.1 Cyclic loading regimens: (a) completely reversed cyclic loading; ...
Figure 9.2 Process of fatigue failure in a material, starting from surface n...
Figure 9.3 Stress‐life (
S
–
N
) curve. Low‐cycle fatigue (characterized by repe...
Figure 9.4 Difference in the proportion of time spent in damage nucleation, ...
Figure 9.5 Hysteresis loop.
Figure 9.6 Median life data for extensor digitorum longus tendon. Modified f...
Figure 9.7 Goodman and Gerber estimates of constant fatigue life given the s...
Figure 9.8 Hypothetical tendon loading with a stress amplitude (
S
a
) of 15...
Figure 9.9 The equivalent fully reversed load history to the nonzero mean st...
Figure 9.10 (a) Tendon stress history for 30‐s work task; (b) Rainflow algor...
Figure 9.11 Graphical depiction of the results of a spectrum loading history...
Figure 9.12 Weibull plot for the EDL tendon fatigue loaded at 20% UTS.
Figure 9.13 Example of a load history containing four loading cycles combine...
Chapter 10
Figure 10.1 Data on fatigue microcrack damage to bone and subsequent healing...
Figure 10.2 Simple model of the interplay between the kinetics of damage and...
Figure 10.3 Material healing process in an engineered polymer.
Figure 10.4 Stress Intensity Factor (
K
) associated with a loading regimen.
K
Figure 10.5 Fatigue life for healing agents with different healing kinetics ...
Figure 10.6 Fatigue crack growth at a high material healing rate for two dif...
Figure 10.7 Introduction of rest periods can extend the fatigue life of a ma...
Figure 10.8 Mechanisms associated with the impaired healing response resulti...
Figure 10.9 Effect of aging on the healing process.
Figure 10.10 Effects of obesity on healing.
Figure 10.11 An individual‐level model of the relationship of damage versus ...
Chapter 11
Figure 11.1 Relative time course of inflammatory cell, fibroblast recruitmen...
Figure 11.2 Time‐course of the initiation and resolution of acute inflammati...
Figure 11.3 M1 (pro‐inflammatory) versus M2 (anti‐inflammatory) macrophage p...
Figure 11.4 A model depicting the long‐term effects of repeated tissue infla...
Figure 11.5 A summary of the inflammation, proliferation, and remodeling pha...
Figure 11.6 A comparison of the function of M1 and M2 macrophage phenotypes ...
Figure 11.7 Graphical representation of the morphological features in a heal...
Figure 11.8 Phases and main events after muscle injury. The typical acute ph...
Figure 11.9 Persistent inflammation with continued task performance. Pro‐inf...
Figure 11.10 Phases of cartilage repair. The mechanisms underlying the degen...
Figure 11.11 Primary initiating events of cartilage degeneration, contributo...
Figure 11.12 Examples of microcracks in forearm bone occurring as a conseque...
Figure 11.13 Phases of bone repair after a fracture.
Figure 11.14 Fracture healing is a temporally defined process. (a) Fracture,...
Figure 11.15 Main steps of Wallerian degeneration and nerve regeneration. Th...
Figure 11.16 Main steps in the Wallerian degeneration.
Figure 11.17 Schematic diagram demonstrating that interactions of force, rep...
Chapter 12
Figure 12.1 Differences in areal bone mineral density in males and females t...
Figure 12.2 Grading of osteoporosis damage accumulation. See text for grade ...
Chapter 13
Figure 13.1 Proper measurement of the maximum horizontal distance during a s...
Figure 13.2 Graphical user interface for the LiFFT.
Figure 13.3 A screenshot of a LiFFT analysis for a mono‐task job.
Figure 13.4 An example of a multi‐task lifting job analysis using LiFFT.
Figure 13.5 Probability of high‐risk job for low back disorders (Zurada et a...
Figure 13.6 Dose‐response relationships between the LiFFT Log CD measure and...
Figure 13.7 A screenshot of the DUET tool analysis of a mono‐task job.
Figure 13.8 A screenshot of the DUET tool for analyzing a multi‐task job.
Figure 13.9 Dose‐response relationships observed between DUET's Log CD measu...
Figure 13.10 Proper measurement of the distance from the shoulder joint to t...
Figure 13.11 Illustration of measuring the lever arm for the left and right ...
Figure 13.12 For pushing and pulling tasks, the lever arm may be a vertical ...
Figure 13.13 A screenshot of ‘The Shoulder Tool’ for analyzing a monotask jo...
Figure 13.14 Analysis of a monotask two‐handed lift with even weight distrib...
Figure 13.15 A screenshot of The Shoulder Tool for analyzing a multi‐task jo...
Figure 13.16 Logistic regression models for The Shoulder Tool Log CD measure...
Chapter 15
Figure 15.1 Systemic and local risk factors for osteoarthritis.
Figure 15.2 Conceptual model of the factors that impact tissue health in mus...
Figure 15.3 The multifactorial determinants of elderly nerve and musculoskel...
Chapter 16
Figure 16.1 Model of musculoskeletal tissue thresholds.
Guide
Cover Page
Title Page
Copyright
Dedication
Preface
Acknowledgments
About the Authors
Table of Contents
Begin Reading
Index
WILEY END USER LICENSE AGREEMENT
Pages
iii
iv
vi
ix
x
xi
xiii
xv
1
2
3
4
5
6
7
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
375
376
377
378
379
380
381
382
383
384
385
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
415
416
417
418
419
420
421
422
423
424
425
426
427
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
Musculoskeletal Disorders
The Fatigue Failure Mechanism
Sean Gallagher
Auburn University, Auburn, AL, USA
Mary F. Barbe
Temple University, Philadelphia, PA, USA
This edition first published 2022© 2022 by John Wiley & Sons, Inc.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
The right of Sean Gallagher and Mary F. Barbe to be identified as the authors of this work has been asserted in accordance with law.
Registered OfficeJohn Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA
Editorial OfficeJohn Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA
For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.
Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand. Some content that appears in standard print versions of this book may not be available in other formats.
Limit of Liability/Disclaimer of WarrantyIn view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
Library of Congress Cataloging‐in‐Publication Data applied for:
ISBN: 9781119640042
Cover image: © MDGRPHCS/ShutterstockCover design by Wiley
To Dad and Mom, who set a high bar; to Nancie for her constant love and support; and to Drew and Brendon for being wonderful and thoughtful sons.
Sean Gallagher
To my parents, who taught me how to dream; to Hugh, the love of my life, for his continued aid and support; and to Susan, my twin and other half of my soul, for always being my best friend, companion, and muse.
Mary F. Barbe
Preface
During the course of my [SG’s] doctoral work with Dr. William S. Marras, I became familiar with the work of researchers such as Adams, Cyron, Hutton, and Brinckmann who had performed ex vivo studies examining the effects of repeated stress on fatigue failure of spinal motion segments (Adams & Hutton, 1985; Brinckmann, Biggemann, & Hilweg, 1988; Cyron & Hutton, 1978). When the time came to select a dissertation topic, the option of performing an ex vivo fatigue failure study on spines at different levels of forward flexion was offered and I accepted the opportunity. The results of our research showed once again that spines subjected to repeated stress exhibited a classic fatigue failure response, and that the relationship is also affected by the degree of flexion of the motion segments adopted (Gallagher et al., 2007).
This research added to the existing body of evidence that cadaveric spinal motion segments fail in accordance with the mechanism of fatigue failure. However, though ex vivo fatigue failure data (on various musculoskeletal tissues) had been accumulating for some time, the implications of this mechanism regarding tissue damage were generally neither reflected in the development of musculoskeletal risk assessment tools nor in epidemiological studies examining musculoskeletal disorder risk factors. It is not entirely clear why this is the case, but it is the author's belief that researchers were reluctant to assume that this process would work in a similar manner in the setting of a complex biological system. This is understandable as no real evidence existed at that time that such a process was actually taking place in vivo.
One day in 2011, I had just finished giving a fatigue‐based presentation to some of my NIOSH colleagues in Pittsburgh and was walking out of the conference room door when I suddenly realized that the S–N curve (which governs the fatigue failure response of materials) would predict a specific pattern of interaction between the risk factors of force and repetition and that the interaction predicted would look exactly like the interaction observed in the classic studies by Silverstein et al. for carpal tunnel syndrome and by Armstrong et al. for hand‐wrist tendinitis (Armstrong, Fine, Goldstein, Lifshitz, & Silverstein, 1987; Silverstein, Fine, & Armstrong, 1987).
This result strongly suggested that a fatigue failure process might indeed be occurring in vivo. This finding piqued my curiosity and I then performed (with my NIOSH collaborator John Heberger) a systematic review of epidemiology studies in the ergonomics literature that had tested for a force‐repetition interaction. The goal was to examine whether studies that had tested the interaction found a pattern indicative of a fatigue failure process (like the aforementioned studies). Results of this review showed only twelve studies in the literature that reported results of a statistical test for the interaction of force and repetition (or which provided data by which such an interaction could be examined). Of these, ten provided data indicative of the predicted pattern, one that tested for such an interaction consisted only high force tasks (where the test for interaction was meaningless), and in the other, the relationship was not present (Gallagher & Heberger, 2013). Overall, the results of this systematic review provided compelling evidence that many musculoskeletal disorder (MSD) outcomes exhibited a pattern of force and repetition that would suggest that a fatigue failure process might be an important etiological factor. This appeared to be the case across a wide range of disorders and joints.
Concurrent with the development of this paper, I met Mary Barbe, whose novel rat model provided additional support that fatigue failure of musculoskeletal tissues occurs in vivo. Her research demonstrated that damage to tendons, bone, and cartilage all followed the fatigue failure predicted force‐repetition pattern (Barbe et al., 2013). The same was true for many cytokines, whose expression appears to be tied to the amount of damage occurring in musculoskeletal tissues (Barr, Barbe, & Clark, 2004). Since that time, we have continued to collaborate on numerous papers and projects.
In 2018, I asked Mary if she would be willing to collaborate on a book dealing with the fatigue failure model of MSD development. The idea was to provide evidence that fatigue failure was occurring in musculoskeletal tissues and to examine the diverse implications of fatigue failure occurring in a complex biological setting. As will be seen in this book, this process (a modified fatigue failure process) is likely influenced by numerous physiological and psychological factors, all of which would be expected to play important roles in maintaining musculoskeletal health.
This book is the result of our examination of the impact of the fatigue failure process and its interactions with biological and physiological mechanisms affecting musculoskeletal health. The book provides considerable information on the musculoskeletal and nervous systems; the epidemiology of MSDs; evidence that musculoskeletal tissues fail via a fatigue failure process; implications in terms of MSD etiology; remodeling and healing processes; use of fatigue failure methods in risk assessment; and numerous other topics. We hope that our readers will find this book helpful in understanding the etiology of MSDs and, conversely, the importance of the fatigue failure process in the maintenance of musculoskeletal health.
Bibliography
Adams, M., & Hutton, W. (1985). Gradual disc prolapse.
Spine
,
10
, 524–531.
Armstrong, T., Fine, L., Goldstein, S., Lifshitz, Y., & Silverstein, B. (1987). Ergonomics considerations in hand and wrist tendinitis.
The Journal of Hand Surgery
,
12A
, 830–837.
Barbe, M., Gallagher, S., Massicotte, V., Tytell, M., Popoff, S., & Barr‐Gillespie, A. (2013). The interaction of force and repetition on musculoskeletal and neural tissue responses and sensorimotor behavior in a rat model of work‐related musculoskeletal disorders.
BMC Musculoskskeletal Disorders
,
14
, 303.
Barr, A., Barbe, M., & Clark, B. (2004). Work‐related musculoskeletal disorders of the hand and wrist: epidemiology, pathophysiology, and sensorimotor changes.
Journal of Orthopaedic & Sports Physical Therapy.
,
34
, 610–627.
Brinckmann, P., Biggemann, M., & Hilweg, D. (1988). Fatigue fracture of human lumbar vertebrae.
Clinical Biomechanics
,
3
(Suppl. 1), S1–S23.
Cyron, B., & Hutton, W. (1978). The fatigue strength of the lumbar neural arch in spondylolysis.
Journal of Bone and Joint Surgery
,
60B
, 234–238.
Gallagher, S., & Heberger, J. (2013). Examining the interaction of force and repetition on musculoskeletal disorder risk: A systematic literature review.
Human Factors
,
14
, 108–124.
Gallagher, S., Marras, W., Litsky, A., Burr, D., Landoll, J., & Matkovic, V. (2007). A comparison of fatigue failure responses of old versus middle‐aged lumbar motion segments in simulated flexed lifting.
Spine
,
32
, 1832–1839.
Silverstein, B., Fine, L., & Armstrong, T. (1987). Occupational factors and carpal tunnel syndrome.
American Journal of Industrial Medicine
,
11
, 343–358.
Acknowledgments
The authors wish to acknowledge the following individuals who have aided in the process of writing this book:
First, we would like to acknowledge our spouses, Nancie and Hugh, respectively, for their support and tolerance during the development of this book. The demands of writing have unfortunately required them to put up with longish periods of our absence.
Acknowledgment is also due to the Center for Occupational Safety, Ergonomics, and Injury Prevention (COSEIP) team at Auburn University (both faculty and students), who have been integral in the development of the fatigue failure‐based risk assessment tools presented in this book. We would like to thank faculty members Dr. Richard F. Sesek, Dr. Mark C. Schall, Jr., and Dr. Jerry Davis, along with former students (notably Dr. Rong Huangfu and Dr. Dania Bani Hani) for their critical contributions to risk assessment tool development. Other former and current students have contributed to this research including Dr. Tenchi Smith, Dr. Nick Smith, Ivan Nail, Nathan Pool, Bob Sesek, and Yuting Ma.
We would also like to acknowledge the National Institute for Occupational Safety and Health (NIOSH) for the long‐standing funding provided in support of the Deep South Center for Occupational Health and Safety, along with other extramural funding. We also thank the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) and the National Center for Complementary and Integrative Health (NCCIH), which have helped advance our research in this area.
Great thanks is also due to our colleagues who have taken the time to review draft chapters of this book. In particular, we would like to thank Dr. Michael Zabala and Dr. Sa’d Hamasha (both of Auburn University) for their valuable time and assistance rendered in reviewing draft chapters in this book.
Finally, we would like to acknowledge the Wiley book team (especially Summers Scholl, Judy Howarth, Veerabaghu Nagarajan, Judit Anbu Hena Daniel, Rajalakshmi Venkatesaperumal, and Stefani Volk) for their support and patience during the development of this book. Their commitment is deeply appreciated as is their care and attention in the book’s production.
Sean GallagherMary F. Barbe
About the Authors
Sean Gallagher, PhD, CPE, FAIHA, is the Hal N. and Peggy S. Pennington Professor of Industrial and Systems Engineering at Auburn University. Dr. Gallagher has over 35 years of experience in the field of ergonomics, including having worked for the US Bureau of Mines, the National Institute for Occupational Safety and Health (NIOSH), and Auburn University. He is a Fellow of both the Human Factors and Ergonomics Society and the American Industrial Hygiene Association. Dr. Gallagher is a two‐time recipient of the International Ergonomics Association/Liberty Mutual Medal in Occupational Safety and Ergonomics (2013 and 2018) and a recipient of the 2020 Paper of the Year Award by the journal Ergonomics. He has received various other team‐based awards, including the 2009 Alice Hamilton Award for Excellence in Occupational Safety and Health (Educational Materials Category) and the 2011 HHS Innovates Award (Secretary's Pick).
Mary F. Barbe, PhD, FAAA, is currently a Full Professor at the Center for Translational Medicine at Lewis Katz School of Medicine of Temple University in Philadelphia. She has over 212 peer‐reviewed publications to her credit. She has been involved in research investigating mechanisms and treatments for pain and work‐related musculoskeletal disorders (repetitive strain injuries) in humans and using rat models. She is a Fellow of the American Association of Anatomists (FAAA) and of the American Society of Bone and Mineral Research. She is also the president of the Advances in Mineral Metabolism society for 2021–2023. She is the recipient of the Senior Faculty Research Excellence Award from the Lewis Katz School of Medicine in 2017, the Temple University Faculty Research Award from Temple University in 2019, the Educator Award from the Philadelphia Chapter of the Society for Neuroscience in 2008, the Christian R. and Mary F. Lindback Foundation Award from Temple University for Distinguished Teaching in 2008, and the Excellence in Teaching Award from College of Allied Health Professions in 1997 and 2007. Other awards that she has received include various team‐based awards, including The ISSLS Prize for Lumbar Spine Research 2018 from the International Society for the Study of the Lumbar Spine.
1Introduction
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.
Bibliography
Bani Hani, D., Huangfu, R., Sesek, R., Schall, M. C., Jr., Davis, G. A., & Gallagher, S. (2021). Development and validation of a cumulative exposure shoulder risk assessment tool based on fatigue failure theory.
Ergonomics
,
64
(1), 39–54.
Barbe, M. F., Gallagher, S., Massicotte, V. S., Tytell, M., Popoff, S. N., & Barr‐Gillespie, A. E. (2013). The interaction of force and repetition on musculoskeletal and neural tissue responses and sensorimotor behavior in a rat model of work‐related musculoskeletal disorders.
BMC Musculoskskeletal Disorders
,
14
, 303.
https://doi.org/10.1186/1471‐2474‐14‐303
. PMID: 24156755; PMCID: PMC3924406
Brinckmann, P., Biggemann, M., & Hilweg, D. (1988). Fatigue fracture of human lumbar vertebrae.
Clinical Biomechanics
,
3
(Suppl. 1), S1–S23.
Carter, D., & Hayes, W. (1976). Fatigue life of compact bone—I. Effects of stress amplitude, temperature and density.
Journal of Biomechanics
,
9
, 27–34.
Dong, R., Wu, J., Xu, X., Welcome, D., & Krajnak, K. (2021). A Review of Hand–Arm Vibration Studies Conducted by US NIOSH since 2000.
Vibration
,
4
, 482–528.
Gallagher, S., & Heberger, J. (2013). Examining the interaction of force and repetition on musculoskeletal disorder risk: A systematic literature review.
Human Factors
,
14
, 108–124.
Gallagher, S., Marras, W., Litsky, A., Burr, D., Landoll, J., & Matkovic, V. (2007). A Comparison of fatigue failure responses of old versus middle‐aged lumbar motion segments in simulated flexed lifting.
Spine
,
32
, 1832–1839.
Gallagher, S., & Schall, J. M. (2017). Musculoskeletal disorders as a fatigue failure process: Evidence, implications and research needs.
Ergonomics
,
60
, 255–269.
Gallagher, S., Schall, M., Jr., Sesek, R., & Huangfu, R. (2018). An upper extremity risk assessment tool based on material fatigue failure theory: The distal upper extremity tool (DUET).
Human Factors
,
60
, 1146–1162.
Gallagher, S., Sesek, R., Schall, M., Jr., & Huangfu, R. (2017). Development and validation of an easy‐to‐use risk assessment tool for cumulative low back loading: The Lifting Fatigue Failure Tool (LiFFT).
Applied Ergonomics
,
63
, 142–150.
Gosain, A., & DiPietro, L. (2004). Aging and wound healing.
World Journal of Surgery
,
28
, 321–326.
Guo, S., & DiPietro, L. (2010). Factors affecting wound healing.
Journal of Dental Research
,
89
, 219–229.
Kiecolt‐Glaser, J., Marucha, P., Malarkey, W., Mercado, A., & Glaser, R. (1995). Slowing of wound healing by psychological stress.
Lancet
,
346
, 1194–1196.
Kumar, S. (2001). Theories of musculoskeletal injury causation.
Ergonomics
,
44
, 17–47.
