Dr Tina Smith

Dr Tina SmithFaculty of Education, Health and Wellbeing (FEHW)

Dr Tina Smith is a Senior Lecturer in Biomechanics.  After receiving a BSc (Hons) Sports Science from the University of Brighton she completed a PhD in biomechanics from Southern Cross University, Australia. Prior to joining the University of Wolverhampton she held academic positions at the University of Hull and University of Roehampton. Her research interests include the biomechanics of activities of daily living in differing populations, and the use of biomechanically derived feedback and exercise interventions to improve musculo-skeletal health and functional performance. Within sport her research includes the biomechanics of sports performance, and the application of biomechanics to the coaching environment.

The associations between sedentary behaviour and impact characteristics on bone health


Significant proportions of adults and children are engaging in sedentary behaviour for prolonged periods of time (DoH, 2010). Sedentary behaviour is generally regarded as having deleterious effects on health although far less is known about its specific effects on bone health (Chastin et al., 2014). Maintaining bone health is important as it reduces the onset and extent of osteoporosis and decreases the risk of fracture due to falling, which is estimated to cost over £1.7 billion / year in the UK (DoH, 1994). Although exercise has been proposed as a method of improving bone health (Guadalupe-Grau et al., 2009), the relationship between physical activity (PA) and bone health is not clear. In addition individuals can participate in recommended amounts of PA and yet spend the majority of time in sedentary, low energy expenditure activities (DoHPAHI&P, 2011). With an increasingly ageing and sedentary population it is therefore important that we understand what happens to bone health due to sedentary behaviour.

It is the impact forces generated as the foot contacts the ground during PA that have the potential to act as a stimulus for bone maintenance and development (Guadalupe-Grau et al, 2009). As impact forces are attenuated as they travel up the body, exploration of the mechanisms related to mechanical loading at the hip and especially the spine require further investigation. These sites are pertinent as most osteoporotic fractures occur in those regions in later life. Exploring these questions will provide evidence upon which to base future interventions that are likely to be of benefit for bone health in sedentary populations.


Sedentary behaviour is not simply a lack of PA but defined as activities requiring low levels of energy expenditure that occur while sitting or lying down (Atkin et al., 2012). An objective and increasingly wider used method of assessing sedentary and active behaviour is via accelerometry (Atkin et al., 2012; Plasqui & Westerterp, 2007; Trost et al., 2005). As well as providing information on activity thresholds of individual’s, accelerometers also provide information in relation to how the activity influences bone health. The properties of bone are regulated through the amount of mechanical loading, frequency of loading and duration of loading endured, which can create an osteogenic effect (Hsieh & Turner, 2001; Turner, 1998).

These variables can be quantified via accelerometry which records the magnitude, rate and duration of accelerations experienced at the site on the body where the accelerometer is worn. Although there is a vast amount of literature where accelerometers have been used to monitor physical activity, there is a lack of studies that use accelerometers to determine the most effective exercise for bone (Jamsa et al., 2011). There have been various approaches used to process the accelerometer data to estimate the osteogenic effect of activity. However very few studies take into account the combination of loading magnitude, frequency and duration using acceleration data in order to determine the osteogenic effects of activity (Chahal et al., 2014; Kelley et al., 2014; Smith et al., 2015).

Current research suggests there is an inverse association of PA with relative risk of hip and vertebral fracture, although the strength of the evidence for the effects of PA on vertebral fracture is considered weak (DoHPAHI&B, 2011). This may be related to the intensity of exercise engaged in as the effects of loading will be attenuated as they travel up the lower limb, thus being weakened by the time they reach the spine and having a lesser effect. There are very few studies that have specifically looked at the effects of PA on the lumbar spine, and only high impact exercise has been shown to improve bone mineral density in the hip (upper femur) and lumbar spine in premenopausal women (Vainionpaa et al., 2005).

There is also a lack of information on the effects of sedentary behaviour on bone health (Chastin et al., 2014). Previous studies have suggested that the time spent in sedentary work increases the risk of an osteoporotic fracture (Cooper et al., 1990) in adults and the amount of time spent watching TV or studying decreases bone mineral content in adolescent boys and girls respectively (Vicente-Rodríguez  et al., 2009; Gracia-Marco et al., 2012). However Gracia-Marco et al. (2012) found that the effects of studying in adolescent girls was mitigated by engagement in PA indicating that the effects of sedentary behaviour can be offset by regular engagement in PA. Yet a similar offset was not evident for adolescent boys who spent time browsing the internet indicating further research on the association between sedentary behaviour and bone health is warranted to determine if sitting is a risk factor (Chastin et al., 2014).


  • To associate sedentary vs. active behaviour with bone health and functional ability
  • To associate mechanical loading at the lumbar spine and hip in sedentary and active individuals with bone mineral density


  1. Analyse functional movement and gait characteristics in a laboratory setting.
  2. Quantify bone characteristics via dual X-ray absorptiometry (DXA) scanning
  3. Develop an algorithm and software to calculate external mechanical loading at the lumbar spine during daily activity from accelerometer data
  4. Determine the associations between sedentary behaviour and functional movement capabilities, gait characteristics, bone health and external mechanical loading of the spine during daily activities.                                                                         


The study employed a cross sectional design to determine differences in bone health, mechanical loading characteristics associated with bone health status, and functional ability between sedentary and active individuals. Fifty-six participants, aged between 30 – 59 years who met the eligibility criteria and gave their informed consent took part in the study.

For each participant, the first testing session took place in the laboratory. Physical characteristics were assessed, and time spent in sedentary behaviour and current physical activity levels were determined using the International Physical Activity Questionnaire. Tests of functional ability and a biomechanical gait assessment were performed.

The second stage of testing took place during free-living conditions. Participants wore an accelerometer (GENEActiv Action, 100 Hz) attached via a strap around the waist at the level of their 4th lumbar vertebrae for a period of seven days. The data extracted allows the external mechanical loading at the lumbar spine during typical daily activity to be estimated.

For the final stage of the testing participants underwent a full body DXA scan. Data quantifying their current bone mineral densities and body composition were obtained.

Summary findings & outcomes

Due to the large datasets, data processing and analysis is ongoing. A summary of the outcomes and findings to date are provided below.

The application of techniques to correct accelerometer data for movement artefacts due to skin and strap mounting have been explored within the current datasets. A previously reported method for correcting data obtained via skin mounted accelerometers (Smeathers, 1989) has been applied to the strap mounted accelerometers used in the study. To date the results indicate that at low levels of acceleration appropriate data can be extracted from the behaviour of the strap mounted system and inputted affectively into established equations for data correction. Further work is needed to validate this technique for higher magnitudes and frequencies of acceleration and therefore its applicability as a data correction method in the current study.

Acceleration data from the free-living condition is being processed using software (GADget) that has been custom written as part of the project. This software incorporates algorithms adapted from Kelley et al. (2014) and Smith et al. (2015) which quantify the magnitude, frequency and duration of mechanical loading at the lumbar spine. The software has the potential to be disseminated to the wider research community on completion of the project.

Preliminary results from a sub-set of sedentary (n = 10, ³ 8hrs sitting time / week day) and non-sedentary (n = 10, < 8hrs sitting time / week day) participants who engaged in low levels of physical activity have been analysed for specific walking gait parameters from the laboratory testing sessions. Differences in walking velocity and peak acceleration at the lumbar spine were tending to significance (p £ 0.1), both being higher in the non-sedentary participants. The remaining analysis will incorporate the entire dataset and investigate further characteristics of gait, the external loading characteristics during daily activity and bone parameters.


Atkin, A.J., Gorely, T., Clemes, S.A., Yates, T., Edwardson, C., Brage, S., Salmon, J., Marshall, S.J. & Biddle, S.J.H. (2012) Methods of Measurement in epidemiology: Sedentary Behaviour. International Journal of Epidemiology, 4, 1460–1471.

Chahal, J., Lee, R. & Luo, J. (2014) Loading dose of physical activity is related to muscle strength and bone density in middle-aged women. Bone, 67, 41-45.

Chastin, S., Mandrichenko, O. & Skelton, D. (2014) The frequency of osteogenic activities and the pattern of intermittence between periods of physical activity and sedentary behaviour affects bone mineral content: the cross-sectional NHANES study. BMC Public Health, 14(4).

Cooper, C., Wickham, C. & Coggon, D. (1990) Sedentary work in middle life and fracture of the proximal femur. British Journal of Industrial Medicine, 47, 69–70.

Department of Health (DoH) (1994) Department of Health Advisory Group on Osteoporosis Report. London: Department of Health.

Department of Health (DoH) (2010) Sedentary Behaviour and Obesity: Review of the Current Scientific Evidence. London: Department of Health.

Department of Health, Physical Activity, Health Improvement and Protection (DoHPAHI&P) (2011) Start Active, Stay Active: A Report on Physical Activity from the Four Home Countries. London: Department of Health.

Gracia-Marco, L., Rey-López, J.P., Santaliestra-Pasías, A.M., Jiménez-Pavón, D., Díaz, L.E., Moreno, L.A. & Vicente-Rodríguez, G. (2012) Sedentary behaviours and its association with bone mass in adolescents: the HELENA cross-sectional study. BMC Public Health, 12, 971.

Guadalupe-Grau, A., Fuentes, T., Guerra B. & Calbet J.A. (2009) Exercise and bone mass in adults. Sports Medicine, 39(6), 439-68.

Hsieh, Y. & Turner, C.H. (2001) Effects of loading frequency on mechanically induced bone formation.Journal of Bone Mineral Research, 16(5), 918-923.

Jamsa, T., Ahola, R. & Korpelainen, R. (2011) Measurement of osteogenic exercise – how to interpret accelerometric data? Frontiers in Physiology, 2, Article 73.

Kelley, S., Hopkinson, G., Strike, S., Luo, J. & Lee, R. (2014) Anaccelerometry-based approach to assessing loading intensity of physical activity on bone. Research Quarterly for Exercise and Sport, 85, 245-250.

Plasqui, G. & Westerterp, K.R. (2007) Physical activity assessment with accelerometers: An evaluation against doubly labelled water. Obesity, 15(10), 2371-2379.

Smeathers, J.E. (1989) Transient vibrations caused by heel strike.Proceedings of the Institute of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 203, 181-186.

Smith, T., Reeves, S., Huber, J., Halsey, L. & Luo, J. (2015) Relationship Between Loading Intensity and Dose of Physical Activity with Age and BMI when Recorded by Accelerometry and Questionnaire: Potential Implications for Bone Health. The 25th Congress of the International Society of Biomechanics.Glasgow, Scotland, 12th – 15th July, 2015. 

Trost, S.G., Mciver, K.L. & Pate, R.R. (2005) Conducting accelerometer-based activity assessments in field-based research. Medicine and Science in Sports & Exercise, 37(S11), S531-S543. 

Turner, C.H. (1998) Three rules for bone adaptation to mechanical stimuli. Bone, 23(5), 399-407.

Vainionpaa, A.,Korpelainen, R., Leppaluto, J. &Jamsa, T. (2005) Effects of high-impact exercise on bone mineral density: a randomized controlled trial in premenopausal women. Osteoporosis International, 16: 191–197. 

Vicente-Rodríguez, G., Ortega, F.B., Rey-López, J.P., España-Romero, V., Blay, V.A., Blay, G., Martín-Matillas, M. & Moreno, L.A. (2009) Extracurricular physical activity participation modifies the association between high TV watching and low bone mass. Bone, 45, 925–930.