Meagre effects of disuse on the human fibula are not explained by bone size or geometry

Summary Fibula response to disuse is unknown; we assessed fibula bone in spinal cord injury (SCI) patients and able-bodied counterparts. Group differences were smaller than in the neighbouring tibia which could not be explained by bone geometry. Differential adaptation of the shank bones may indicate previously unknown mechanoadaptive behaviours of bone. Introduction The fibula supports only a small and highly variable proportion of shank compressive load (−8 to +19 %), and little is known about other kinds of stresses. Hence, whilst effects of habitual loading on tibia are well-known, fibula response to disuse is difficult to predict. Methods Therefore, we assessed fibular bone strength using peripheral quantitative computed tomography (pQCT) at 5 % increments from 5 to 90 % distal-proximal tibia length in nine participants with long-term spinal cord injury (SCI; age 39.2 ± 6.2 years, time since injury 17.8 ± 7.4 years), representing a cross-sectional model of long-term disuse and in nine able-bodied counterparts of similar age (39.6 ± 7.8 years), height and mass. Results There was no group difference in diaphyseal fibula total bone mineral content (BMC) (P = 0.22, 95 % CIs -7.4 % to -13.4 % and +10.9 % to +19.2 %). Site by group interactions (P < 0.001) revealed 27 and 22 % lower BMC in SCI at 5 and 90 % (epiphyseal) sites only. Cortical bone geometry differed at mid and distal diaphysis, with lower endocortical circumference and greater cortical thickness in SCI than able-bodied participants in this region only (interactions both P < 0.01). Tibia bone strength was also assessed; bone by group interactions showed smaller group differences in fibula than tibia for all bone parameters, with opposing effects on distal diaphysis geometry in the two bones (all Ps < 0.001). Conclusions These results suggest that the structure of the fibula diaphysis is not heavily influenced by compressive loading, and only mid and distal diaphysis are influenced by bending and/or torsional loads. The fibula is less influenced by disuse than the tibia, which cannot satisfactorily be explained by differences in bone geometry or relative changes in habitual loading in disuse. Biomechanical study of the shank loading environment may give new information pertaining to factors influencing bone mechanoadaptation

Structural differences in cortical shell properties between upper and lower human fibula as described by pQCT serial scans.A biomechanical interpretation

This study describes the structural features of fibula cortical shell as allowed by serial pQCT scans in 10/10 healthy men and women aged 20–40 years. Indicators of cortical mass (mineral content -BMC-, cross-sectional area -CSA-), mineralization (volumetric BMD, vBMD), design (perimeters, thickness, moments of inertia -MIs-) and strength (Bone Strength Indices, BSIs; polar Strength-Strain Index, pSSI) were determined. All cross-sectional shapes and geometrical or strength indicators suggested a sequence of five different regions along the bone, which would be successively adapted to 1. transmit loads from the articular surface to the cortical shell (near the proximal tibia-fibular joint), 2. favor lateral bending (central part of upper half), 3. resist lateral bending (mid-diaphysis), 4. favor lateral bending again (central part of the lower half), and 5. resist bending/torsion (distal end). Cortical BMC and the cortical/total CSA ratio were higher at the midshaft than at both bone ends (p < 0.001). However, all MIs, BSIs and pSSI values and the endocortical perimeter/cortical CSA ratio (indicator of the mechanostat's ability to re-distribute the available cortical mass) showed a “W-shaped” distribution along the bone, with maximums at the mid-shaft and at both bone's ends (site effect, p < 0.001). The correlation coefficient (r) of the relationship between MIs (y) and cortical vBMD (x) at each bone site (“distribution/quality” curve that describes the efficiency of distribution of the cortical tissue as a function of the local tissue stiffness) was higher at proximal than distal bone regions (p < 0.001). The results from the study suggest that human fibula is primarily adapted to resist bending and torsion rather than compression stresses, and that fibula's bending strength is lower at the center of its proximal and distal halves and higher at the mid-shaft and at both bone's ends. This would favor, proximally, the elastic absorption of energy by the attached muscles that rotate or evert the foot, and distally, the widening of the heel joint and the resistance to excessive lateral bending. Results also suggest that biomechanical control of structural stiffness differs between proximal and distal fibula

Imaging of the Muscle-Bone Relationship

Muscle can be assessed by imaging techniques according to its size (as thickness, area, volume, or alternatively, as a mass) and architecture (fiber length and pennation angle), with values used as an anthropometric measure or a surrogate for force production. Similarly, the size of the bone (as area or volume) can be imaged using MRI or pQCT, although typically bone mineral mass is reported. Bone imaging measures of mineral density, size, and geometry can also be combined to calculate bone’s structural strength—measures being highly predictive of bone’s failure load ex vivo. Imaging of muscle-bone relationships can, hence, be accomplished through a number of approaches by adoption and comparison of these different muscle and bone parameters, dependent on the research question under investigation. These approaches have revealed evidence of direct, mechanical muscle-bone interactions independent of allometric associations. They have led to important information on bone mechanoadaptation and the influence of muscular action on bone, in addition to influences of age, gender, exercise, and disuse on muscle-bone relationships. Such analyses have also produced promising diagnostic tools for clinical use, such as identification of primary, disuse-induced, and secondary osteoporosis and estimation of bone safety factors. Standardization of muscle-bone imaging methods is required to permit more reliable comparisons between studies and differing imaging modes, and in particular to aid adoption of these methods into widespread clinical practice

Hip and spine bone mineral density are greater in master sprinters, but not endurance runners compared with non-athletic controls

Summary: We examined bone density in older athletes and controls. Sprinters had greater hip and spine bone density than endurance athletes and controls, whereas values were similar in the latter two groups. These results could not be explained by differences in impact, muscle size or power between sprint and endurance athletes. Purpose: We examined the relationship between prolonged participation in regular sprint or endurance running and skeletal health at key clinical sites in older age, and the factors responsible for any associations which we observed. Methods: We recruited 38 master sprint runners (28 males, 10 females, mean age 71 ± 7 years), 149 master endurance runners (111 males, 38 females, mean age 70 ± 6 years) and 59 non-athletic controls (29 males, 30 females, mean age 74 ± 5 years). Dual X-ray absorptiometry was used to assess hip and spine bone mineral density (BMD), body composition (lean and fat mass), whilst jump power was assessed with jumping mechanography. In athletes, vertical impacts were recorded over 7 days from a waist-worn accelerometer, and details of starting age, age-graded performance and training hours were recorded. Results: In ANOVA models adjusted for sex, age, height, body composition, and jump power, sprinter hip BMD was 10 and 14% greater than that of endurance runners and controls respectively. Sprinter spine BMD was also greater than that of both endurance runners and controls. There were no differences in hip or spine BMD between endurance runners and controls. Stepwise regression showed only discipline (sprint/endurance), sex, and age as predictors of athlete spine BMD, whilst these variables and starting age were predictive of hip BMD. Conclusions: Regular running is associated with greater BMD at the fracture-prone hip and spine sites in master sprinters but not endurance runners. These benefits cannot be explained by indicators of mechanical loading measured in this study including vertical impacts, body composition or muscular output

The influence of muscular action on bone strength via exercise

Mechanical stimuli influence bone strength, with internal muscular forces thought to be the greatest stressors of bone. Consequently, the effects of exercise in improving and maintaining bone strength have been explored in a number of interventional studies. These studies demonstrate a positive effect of high-impact activities (i.e. where large muscle forces are produced) on bone strength, with benefits being most pronounced in interventions in early pubertal children. However, current studies have not investigated the forces acting on bones and subsequent deformation, preventing the development of optimised and targeted exercise interventions. Similarly, the effects of number and frequency of exercise repetitions and training sessions on bone accrual are unexplored. There are conflicting results as to gender effects on bone response to exercise, and the effects of age and starting age on the osteogenic effects of exercise are not well known. It also appears that exercise interventions are most effective in physically inactive people or counteracting conditions of disuse such as bed rest. Bone strength is only one component of fracture risk, and it may be that exercise resulting in improvements in, e.g., muscle force/power and/or balance is more effective than those whose effects are solely osteogenic. In summary, exercise is likely to be an effective tool in maintaining bone strength but current interventions are far from optimal. © Springer Science+Business Media 2013

Exploring Metropolitan Housing Price Volatility

This paper uses GARCH models and a panel VAR model to analyze possible time variation of the volatility of single-family home value appreciation and the interactions between the volatility and the economy, using a large quarterly data set that covers 277 MSAs in the U.S. from 1990:1 to 2002:2. We find evidence of time varying volatility in about 17% of the MSAs. Using volatility series estimated with GARCH models, we find that the volatility is Granger-caused by the home appreciation rate and GMP growth rate. On the other hand, the volatility Granger-causes the personal income growth rate but the impact is not economically significant. Copyright Springer Science + Business Media, LLC 2006Home value appreciation, Housing price volatility, Urban economy, Panel VAR,