Measurement of osteogenic exercise – how to interpret accelerometric data?

Abstract

Bone tissue adapts to its mechanical loading environment. We review here the accelerometric measurements with special emphasis on osteogenic exercise. The accelerometric method offers a unique opportunity to assess the intensity of mechanical loadings. We present methods to interpret accelerometric data, reducing it to the daily distributions of magnitude, slope, area, and energy of signal. These features represent the intensity level of physical activities, and were associated with the changes in bone density, bone geometry, physical performance, and metabolism in healthy premenopausal women. Bone adaptations presented a dose- and intensity dependent relationship with impact loading. Changes in hip were threshold dependent, indicating the importance of high-impacts exceeding acceleration of 4 g or slope of 100 g/s as an osteogenic stimulus. The number of impacts needed was 60/day. We also present the daily impact score to describe the osteogenic potential of daily mechanical loading with a single score. The methodology presented here can be used to study musculoskeletal adaptation to exercise in other target groups as well.

Objective Longitudinal Measures of Physical Activity and Bone Health in Older Japanese: the Nakanojo Study

“…This finding is in keeping with known logarithmic response governing the mechanosensitivity of bone to an increased number of loading cycles . Jämsä et al have defined the needed stimuli for bone health at the hip in middle‐aged women: an acceleration of 4 g or a slope of 100 g/s, with a minimum of 60 such impulses, but diminishing returns from impacts in excess of this number. Observations in the rat noted the importance of the grouping of stimuli; six groups of 60 impulses provided a greater osteogenic stimulus than a cluster of 360 impulses at the same intensity …”

Best Practices for Conducting Observational Research to Assess the Relation between Nutrition and Bone: An International Working Group Summary

“…Although there are some reports that higher pedometer-determined activity (step counts) are associated with greater BMD (165, 166), a limitation of these devices is that they do not distinguish between activities of different load magnitude (e.g., walking compared with jumping). In contrast, accelerometers which can be worn at the hip or wrist and measure acceleration [e.g., the change in speed with respect to time (m/s) or multiplies of the acceleration of gravity ( g = 9.81 m/s)] offer a unique approach to provide an estimate of the intensity of mechanical loading of bone (167). Indeed, previous research has shown that accelerometers can be used to quantify the number of daily vertical impacts at different magnitudes and loading rates (167, 168), with higher acceleration levels (> 3.9 g ) found to be associated with increased hip BMD (169, 170).…”

“…In contrast, accelerometers which can be worn at the hip or wrist and measure acceleration [e.g., the change in speed with respect to time (m/s) or multiplies of the acceleration of gravity ( g = 9.81 m/s)] offer a unique approach to provide an estimate of the intensity of mechanical loading of bone (167). Indeed, previous research has shown that accelerometers can be used to quantify the number of daily vertical impacts at different magnitudes and loading rates (167, 168), with higher acceleration levels (> 3.9 g ) found to be associated with increased hip BMD (169, 170). Given the importance of moderate to high magnitude loading to bone, observational and prospective studies should consider using accelerometers when studying the relations between nutrition, exercise, and bone outcomes.…”

Moderate to vigorous physical activity and impact loading independently predict variance in bone strength at the tibia but not at the radius in children

“…We calculated daily MVPA and VPA as the total minutes of MVPA and VPA divided by the number of days of valid wear. As raw accelerometer data is considered a valid measurement of bone loading during physical activity (Jamsa et al 2011), we acquired accelerometer data using the feature extraction tool from the manufacturer's software.…”