FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Journal of orthopaedic research : official publication of the Orthopaedic Research Society2001; 19(5); 919-926; doi: 10.1016/S0736-0266(01)00009-2

The prediction of stress fractures using a ‘stressed volume’ concept.

Abstract: This paper addresses an anomaly which exists in the current literature regarding stress fractures. Analysis of the data on fatigue strength of bone samples in vitro would conclude that these fractures should never occur at the strain levels known to occur in vivo. This anomaly can be resolved by including in the analysis the effect of stressed volume, whereby larger volumes of material are expected to have worse fatigue properties. A Weibull analysis was used to predict the probability of failure, Pf; this was an upper-bound prediction because it did not include the effects of remodelling and adaptation. Combining this analysis with a finite element model of the human tibia, we predicted a Pf value of 21% after five weeks of strenuous exercise, which is comparable with reported incidences in military personnel. The high incidence of stress fractures in the cannon bone of racehorses could also be predicted (Pf = 62%, compared to 70% experimentally). The approach can be used to investigate the effect of variables in the exercise regime such as the distance run per day and the use of improved footwear. It can also predict the increased risk of stress fractures in elderly people. The results suggest certain simple rules which may be of clinical value in designing exercise regimes and in understanding the risk factors for this type of injury.
Get Full Text
Publication Date: 2001-09-20 PubMed ID: 11562142DOI: 10.1016/S0736-0266(01)00009-2Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This article presents research into predicting stress fractures in bones using a concept called ‘stressed volume’. By incorporating the volume of stress experienced by the bone into analysis, the researchers provided a method for predicting the likelihood of stress fractures from intense exercise regimes, age, and other factors.

Stress Fractures and ‘Stressed Volume’

  • The paper begins by acknowledging an unexplained issue in current scientific literature about stress fractures. Bone sample studies under laboratory conditions suggest that stress fractures should not occur at the strain levels found in living organisms.
  • To reconcile this inconsistency, the researchers introduced the concept of ‘stressed volume’, which suggests that larger volumes of material (such as bones) would naturally have lower fatigue properties and, therefore, be more prone to stress fractures.

Weibull Analysis and Probability of Failure

  • The researchers used a method called Weibull analysis to predict the probability of failure, denoted as ‘Pf’. This prediction acted as an upper limit because it did not factor in the processes of remodelling and adaptation, which are inherent to living organisms.
  • The probability of failure (Pf) is a measure of the likelihood of a stress fracture occurring in a particular context. In this study, the researchers used a Pf value to determine the likelihood of a stress fracture occurring after five weeks of strenuous exercise.

Findings and Application

  • After applying their methodology to a finite element model of the human tibia (shinbone), the researchers predicted a Pf value of 21% following five weeks of strenuous exercise. This matched the observed incidences of stress fractures in military personnel.
  • Predictions also corresponded with observations in the high percentage of stress fractures in racehorse cannon bones, where the Pf was predicted at 62%, close to the experimentally observed 70%.
  • This new method can be used to study the effects of different exercise variables, such as daily running distance or use of improved footwear, on the likelihood of stress fractures. It can also forecast the increased risk of stress fractures in elderly people.
  • Coupled with previous data, the results of this research can help devise safer exercise regimes and better understand risk factors for stress fractures.

Cite This Article

APA
Taylor D, Kuiper JH. (2001). The prediction of stress fractures using a ‘stressed volume’ concept. J Orthop Res, 19(5), 919-926. https://doi.org/10.1016/S0736-0266(01)00009-2

Publication

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
ISSN: 0736-0266
NlmUniqueID: 8404726
Country: United States
Language: English
Volume: 19
Issue: 5
Pages: 919-926

Researcher Affiliations

Taylor, D
  • Mechanical Engineering Department, Trinity College, Ireland. dtaylor@tcd.ie
Kuiper, J H

    MeSH Terms

    • Animals
    • Fractures, Stress / diagnosis
    • Fractures, Stress / physiopathology
    • Fractures, Stress / veterinary
    • Horses
    • Humans
    • Models, Biological
    • Predictive Value of Tests
    • Stress, Mechanical
    • Tibia / injuries
    • Tibia / physiopathology

    Citations

    This article has been cited 16 times.
    1. Sinclair J, Lynch H, Chockalingam N, Taylor PJ. Effects of Obesity on Medial Tibiofemoral Cartilage Mechanics in Females-An Exploration Using Musculoskeletal Simulation and Probabilistic Cartilage Failure Modelling. Life (Basel) 2023 Jan 18;13(2).
      doi: 10.3390/life13020270pubmed: 36836627google scholar: lookup
    2. Sinclair J, Huang G, Taylor PJ, Chockalingam N, Fan Y. Effects of Running in Minimal and Conventional Footwear on Medial Tibiofemoral Cartilage Failure Probability in Habitual and Non-Habitual Users. J Clin Med 2022 Dec 9;11(24).
      doi: 10.3390/jcm11247335pubmed: 36555951google scholar: lookup
    3. Guerriere KI, Castellani CM, Popp KL, Bouxsein ML, Hughes JM. Unraveling the physiologic paradoxes that underlie exercise prescription for stress fracture prevention. Exp Biol Med (Maywood) 2022 Oct;247(20):1833-1839.
      doi: 10.1177/15353702221112108pubmed: 35983839google scholar: lookup
    4. Staab JS, Kolb AL, Tomlinson RE, Pajevic PD, Matheny RW Jr, Hughes JM. Emerging evidence that adaptive bone formation inhibition by non-steroidal anti-inflammatory drugs increases stress fracture risk. Exp Biol Med (Maywood) 2021 May;246(9):1104-1111.
      doi: 10.1177/1535370221993098pubmed: 33641442google scholar: lookup
    5. Unnikrishnan G, Xu C, Baggaley M, Tong J, Kulkarni S, Edwards WB, Reifman J. Effects of body size and load carriage on lower-extremity biomechanical responses in healthy women. BMC Musculoskelet Disord 2021 Feb 24;22(1):219.
      doi: 10.1186/s12891-021-04076-0pubmed: 33627093google scholar: lookup
    6. Miller RH, Krupenevich RL. Medial knee cartilage is unlikely to withstand a lifetime of running without positive adaptation: a theoretical biomechanical model of failure phenomena. PeerJ 2020;8:e9676.
      doi: 10.7717/peerj.9676pubmed: 32844066google scholar: lookup
    7. Hughes JM, Popp KL, Yanovich R, Bouxsein ML, Matheny RW Jr. The role of adaptive bone formation in the etiology of stress fracture. Exp Biol Med (Maywood) 2017 May;242(9):897-906.
      doi: 10.1177/1535370216661646pubmed: 27496801google scholar: lookup
    8. Khandaker M, Ekwaro-Osire S. Weibull analysis of fracture test data on bovine cortical bone: influence of orientation. Int J Biomater 2013;2013:639841.
      doi: 10.1155/2013/639841pubmed: 24385985google scholar: lookup
    9. Idhammad A, Abdali A. On a new law of bone remodeling based on damage elasticity: a thermodynamic approach. Theor Biol Med Model 2012 Nov 29;9:51.
      doi: 10.1186/1742-4682-9-51pubmed: 23194460google scholar: lookup
    10. Taylor D, Dirks JH. Shape optimization in exoskeletons and endoskeletons: a biomechanics analysis. J R Soc Interface 2012 Dec 7;9(77):3480-9.
      doi: 10.1098/rsif.2012.0567pubmed: 22977103google scholar: lookup
    11. Middleton KM, Goldstein BD, Guduru PR, Waters JF, Kelly SA, Swartz SM, Garland T Jr. Variation in within-bone stiffness measured by nanoindentation in mice bred for high levels of voluntary wheel running. J Anat 2010 Jan;216(1):121-31.
      doi: 10.1111/j.1469-7580.2009.01175.xpubmed: 20402827google scholar: lookup
    12. Taylor D. Theoretical modelling in bioengineering: 12th Haughton Lecture of the Royal Academy of Medicine in Ireland. Ir J Med Sci 2008 Mar;177(1):1-8.
      doi: 10.1007/s11845-007-0108-9pubmed: 18074166google scholar: lookup
    13. Currey JD. Bone architecture and fracture. Curr Osteoporos Rep 2005 Jun;3(2):52-6.
      doi: 10.1007/s11914-005-0004-zpubmed: 16036102google scholar: lookup
    14. Wang Z, Mondry A. Volume-based non-continuum modeling of bone functional adaptation. Theor Biol Med Model 2005 Feb 28;2:6.
      doi: 10.1186/1742-4682-2-6pubmed: 15733328google scholar: lookup
    15. Lee TC, Mohsin S, Taylor D, Parkesh R, Gunnlaugsson T, O'Brien FJ, Giehl M, Gowin W. Detecting microdamage in bone. J Anat 2003 Aug;203(2):161-72.
      doi: 10.1046/j.1469-7580.2003.00211.xpubmed: 12924817google scholar: lookup
    16. Sinclair J, Zhang G. Toe-In and Toe-Out Walking Patterns and Lateral Wedge Insoles: A Musculoskeletal Simulation and Probabilistic Modelling Assessment of Medial Tibiofemoral Cartilage Mechanics. Life (Basel) 2025 Oct 28;15(11).
      doi: 10.3390/life15111677pubmed: 41302102google scholar: lookup
    Subscribe to our newsletter
    Join 99,727 horse owners like you who receive our email updates on horse health and nutrition.