Bone-muscle strength indices for the human lower leg

doi:10.1016/S8756-3282(00)00327-6

Bone

Volume 27, Issue 2, August 2000, Pages 319-326

https://doi.org/10.1016/S8756-3282(00)00327-6 Get rights and content

Abstract

This cross-sectional study is based on images from the lower leg as assessed by peripheral quantitative computer tomography (pQCT). Measurements were performed in 39 female and 38 male control subjects and 15 female professional volleyball players, all between 18 and 30 years of age. The images were obtained at shank levels of 4%, 14%, 33%, and 66% from the distal end. Bone and muscle cross-sectional areas, and the bones’ density-weighted area moment of resistance and of inertia were assessed. From these, muscle-bone strength indices (MBSIs) were developed for compression (CI = 100 · bone area/muscle area) and bending (BI = 100 · bone area moment of resistance/muscle area/tibia length). Significant correlations between muscle cross-sectional area and bone were found at all section levels investigated. The strongest correlation for compression was observed in the sections at 14% (correlation coefficient r = 0.74), where 4.10 ± 0.46 cm² bone, on average, was related to 100 cm² muscle. The compression index (CI) at the 14% level was independent of the tibia length. Interestingly, the 15 athletes had significantly greater CIs than the control subjects. This is most probably due to the greater tension development in the athletes. The highest correlation for bending was for anteroposterior bending at 33% of tibia length (r = 0.81), where the area moment of resistance, R, was on, average, 4.21 ± 0.54 cm³/100 cm² muscle/m tibia length. Analysis of the bones’ area moment of inertia showed that buckling is a possible cause of bending at the 33% and 66% levels, but not at the 14% level. No gender differences in MBSI were found. Likewise, age was without significant effect. The data show that bone architecture depends critically on muscle cross section and tension development. Moreover, bone geometry (e.g., the tibia length) influences the geometrical distribution of bone mineral, as it was found that long bones adapted to the same compressive strength are wider than short ones. We conclude that MBSIs offer a powerful diagnostic tool for bone disorders and may contribute to improving the treatment of bone metabolic and other diseases.

Introduction

Bones adapt their strength to the mechanical forces they undergo.2, 18 This is accomplished by either the modeling process,12 which can add net bone, or by remodeling, which can remove bone.13 As a whole, this system works as a “mechanostat,” keeping the strains exerted by external forces within certain limits.11 The external forces arise essentially from muscle contractions. Consequently, exercise-typical, site-specific relations between muscle force and bone geometry have been demonstrated.20, 31

With dual-energy X-ray absorptiometry (DXA), body composition can be assessed and broken down into: (i) bone mineral content (BMC); (ii) fat body mass (FBM); and (iii) lean body mass (LBM), half of which is closely correlated with muscle mass.19 Strong correlations have been observed between LBM and total body BMC.25 In fact, BMC is influenced by an order of magnitude stronger by LBM than by FBM or by height.6

Considered over the whole body, BMC amounts to approximately 5% of LBM, except in premenopausal women, who store 17%–29% more bone mineral per LBM than prepubertal children, postpubertal men, or postmenopausal women.6, 25 It has been hypothesized that this “surplus” of bone mineral is stored at locations where it is not needed mechanically.7

Given the strong interrelationship between muscle force and bone strength, diagnostic indices that quantify these relations may turn out to be valuable tools in the diagnosis of osteoporosis and other bone disorders. This approach has been perceived and assessed in several studies.7, 22, 27 Lately, the term “bone-muscle strength index” (BMSI) has been coined for such quantitative measures (H. M. Frost, personal communication, 1999).

Physiologically, bones are loaded by compression as well as by bending.3, 4 In the lower leg, bending may occur by the horizontal component of the soleus muscle fibers, by eccentric muscle pull, or through buckling under mere compression. Separate BMSIs should therefore be developed for the two strain mechanisms. With adequate tools, peak muscle force can be assessed through a limb’s torque during maximum voluntary contraction and analysis of the muscle levers. Likewise, the potential force development of muscles could also (and may be more objectively) be quantified by their cross-sectional area (CSA).21 Respectively, the bending moment that a certain muscle exerts could be identified by the product of CSA and the length of the lever.

The material constants of bone are largely untouched by age, gender, and species,1, 32 but bone as a mechanical structure is crucially dependent on its apparent density. Thus, good prediction of a bone’s ultimate strength and stiffness is possible by quantitative computer tomography (QCT).5, 30 The appropriate resistance measures for compression and for bending are the bone CSA and the area moment of resistance, respectively. For an illustration of the area moment of resistance, see Figure 2.

The present investigation develops BMSI for compression and bending at the human lower leg. To do so, the following hypotheses are tested:

1.
H1: There are significant muscle and bone relationships for indices of compression and bending at the lower leg.
2.
H2: The muscle-bone relationship at the lower leg will depict a gender difference, revealing women to have more bone mineral per muscle tissue than men.
3.
H3: A supposed greater tension production in athletes will affect the muscle-bone relationship as assessed by imaging techniques.

Section snippets

Setup and subjects

Two different groups of subjects were investigated. Group 1 was comprised of 78 female and male whites native to Berlin, between 20 and 30 years of age. Group 2 consisted of 15 female whites who were professional volleyball players in Berlin, all of whom were competing at the highest national or international level. The biometric data of the three groups are given in Table 1. Groups 1 and 2 underwent analysis by peripheral quantitative computer tomography (pQCT). The investigations were

Results

Group 2 was 3.5 years younger than group 1 (p < 0.05). Within group 1, men were significantly taller and heavier than women, and they had a longer tibia. The female athletes’ (group 2) height, weight, and tibia length were indistinguishable from the men in group 1 (see Table 1).

The short-term error values (ESTs) of all variables, measured with pQCT, are given in Table 2. For A_Bone, EST was below 1%, and for A_Muscle it was 1.15%. In the higher moment parameters, errors were between 0.67% and

Discussion

The present data confirm hypothesis H1—that is, the existence of relevant relationships between muscle and bone. The simple observation that A_Bone as well as R_Bone were greater at higher section levels (i.e., with basically the same weight) again indicates that the influence of body weight is comparatively small. In our subjects, more than half of the variation in A_Bone could be attributed to the variation in A_Muscle. Moreover, roughly two thirds of the interindividual variation in R_X33 could

Acknowledgements

The authors are particularly grateful to Birthe Feilke and Hendrikje Börst from our center for clinical recruitment, and also to U. Brandis and J. Dames for their splendid assistance. Very special thanks to the Olympic Training Center in Berlin for cooperation in this and other studies. Last, but not least, we are deeply grateful to our subjects. Without their selfless contribution, this study would not have been possible.

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Original articlesBone-muscle strength indices for the human lower leg

Abstract

Introduction

Section snippets

Setup and subjects

Results

Discussion

Acknowledgements

Bone

Bone

Bone

J Biomech

Mech Ageing Dev

Bone

Bone strength in small mammals and bipedal birdsDo safety factors change with body size?

J Exp Biol

Biomechanics of mammalian terrestrial locomotion

Science

Patterns of strain in the macaque ulna during functional activity

Am J Phys Anthropol

Bone mass is higher in women than in men per unit of muscle mass but bone mechanostat would compensate for the difference in the species

Bone

A cross-sectional study of muscle strength and mass in 45- to 78-yr-old men and women

J Appl Physiol

Bone “mass” and the “mechanostat”A proposal

Anat Rec

Skeletal structural adaptations to mechanical usage (SATMU)1. Redefining Wolff’s law: The bone modeling problem

Anat Rec

Skeletal structural adaptations to mechanical usage (SATMU)2. Redefining Wolff’s law: The remodeling problem

Anat Rec

Wolff’s Law and bone’s structural adaptations to mechanical usageAn overview for clinicians

Angle Orthodont

Isometrisches Muskeltraining

Original articles
Bone-muscle strength indices for the human lower leg