Abstract
While weight-bearing and resistive exercise modestly increases aBMD, the precise relationship between physical activity and bone microstructure, and strain in humans is not known. Previously, we established a voluntary upper-extremity loading model that assigns a person's target force based on their subject-specific, continuum FE-estimated radius bone strain. Here, our purpose was to quantify the inter-individual variability in radius microstructure and FE-estimated strain explained by site-specific mechanical loading history, and to determine whether variability in strain is captured by aBMD, a clinically relevant measure of bone density and fracture risk. Seventy-two women aged 21–40 were included in this cross-sectional analysis. High resolution peripheral quantitative computed tomography (HRpQCT) was used to measure macro- and micro-structure in the distal radius. Mean energy equivalent strain in the distal radius was calculated from continuum finite element models generated from clinical resolution CT images of the forearm. Areal BMD was used in a nonlinear regression model to predict FE strain. Hierarchical linear regression models were used to assess the predictive capability of intrinsic (age, height) and modifiable (body mass, grip strength, physical activity) predictors. Fifty-one percent of the variability in FE bone strain was explained by its relationship with aBMD, with higher density predicting lower strains. Age and height explained up to 31.6% of the variance in microstructural parameters. Body mass explained 9.1% and 10.0% of the variance in aBMD and bone strain, respectively, with higher body mass indicative of greater density. Overall, results suggest that meaningful differences in bone structure and strain can be predicted by subject characteristics.
Highlights
Bone is a mechanosensitive tissue, with a complex structure adapted to habitual mechanical loads
Our primary purpose was to quantify the inter-individual variability in radius microstructure and finite element (FE)-estimated strain explained by site-specific mechanical loading history
Ten enrolled subjects were excluded from analyses due to incomplete physical activity data (n = 3) or High resolution peripheral quantitative computed tomography (HRpQCT) motion artifact (n = 7)
Summary
Bone is a mechanosensitive tissue, with a complex structure adapted to habitual mechanical loads. The National Osteoporosis Foundation recommends that women perform weight-bearing and musclestrengthening exercises throughout their lifespan to reduce the risk of osteoporotic fracture (Cosman et al, 2014) Despite this knowledge, it remains unclear which exercises are most effective at increasing bone strength (Cosman et al, 2014; Janz et al, 2015), and there are no systematic methods to prescribe loading to specific individuals or clinical populations (Warden et al, 2004). Computed-tomography (CT)-based finite element (FE) models have enabled the non-invasive, subject specific estimation of strain throughout a bone volume Using this technology, we previously established a tunable upper-extremity axial loading model in humans (Troy et al, 2013), which uses FE-estimated bone strain (Bhatia et al, 2014) as a basis for prescribing target forces. We have shown that forearm loading magnitude can be voluntarily manipulated to achieve specific strains during this task (Troy et al, 2013), highlighting its potential to answer several important questions about human bone adaptation
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