Sitting, Standing and Moving: Evaluating the impact of health enhancing initiatives

This program of research aimed to inform evaluation of targeted interventions and population-wide initiatives to promote reductions in sitting and increases in standing and moving. The research addressed the following research questions:

1) How effective are current self-report measures, compared to device-based measures, at identifying change in sitting, standing and moving?

2) What improvement in currently available device-based measures can be obtained by applying newer techniques for analysis?

3) Can device-based techniques identify the context of change in sitting, standing and moving?

4) How effective is a newly developed online self-report data collection tool at detecting change in sitting, standing and moving?

Funding Body

National Health and Medical Research Council - Early Career Fellowship

Project outputs and outcomes

The research undertaken in the program showed that there are self-report measures that can detect change in sitting, standing and moving time. More importantly, new self-report measures were developed to measure how sitting time is accumulated and broken up by standing and moving and that these measures can detect change in behavioural interventions.

Evaluation of new and existing machine learning algorithms using accelerometer data showed that these can be used effectively and interchangeably with high accuracy for identifying sitting, standing and stepping when worn on the thigh.

Lastly newer methods of using Bluetooth to identify the context of sitting, standing and moving indoors showed high accuracy for objective measurement of context. Further research in the program has added development of methods using mmWave technology and ecological momentary sampling for identifying context of physical behaviour, which have shown promise for use in future interventions.

Publications that have arisen from the program of research:

1. Clark BK, Brakenridge CL, Healy GN (2022). The Importance of Research on Occupational Sedentary Behaviour and Activity Right Now. International Journal of Environmental Research and Public Health. 19(23):15816. https://doi.org/10.3390/ijerph192315816
2. Clark BK, Stephens SK, Goode AD, Healy GN, Winkler EAH (2021). Alternatives for measuring sitting accumulation in workplace surveys. Journal of Occupational and Environmental Medicine 63(12):p e853-e860 https://doi.org/10.1097/JOM.0000000000002387
3. Giurgiu M, Nissen R, Müller G, Ebner-Priemer UW, Reichert M and Clark BK. (2021), Drivers of Productivity: Being physically active increases yet sedentary bouts and lack of sleep decrease work ability. Scand J Med Sci Sports. 31 (10) 1921-1931. https://doi.org/10.1111/sms.14005
4. Clark BK, Winkler EA, Ahmadi M, Trost SG (2021). Comparison of three algorithms using thigh worn accelerometers for classifying sitting, standing and stepping in free-living office workers. Journal for the Measurement of Physical Behaviour. 4(1): 89-95. https://doi.org/10.1123/jmpb.2020-0019.
5. Clark BK, Hadgraft N, Sugiyama T, Winkler EAH (2019). Measuring time in the office using Bluetooth Sensors: feasibility and validity considerations. Journal for the Measurement of Physical Behaviour. 2 (1): 36-44  https://doi.org/10.1123/jmpb.2018-0046
6. Clark BK, Winkler EA, Brakenridge CL, Trost SG and Healy GN. (2018) Using bluetooth proximity sensing to determine where office workers spend time at work. PLoS One, 13 3: e0193971. https://doi.org/10.1371/journal.pone.0193971  

Impact

The measurement methods developed in this program of research are freely available to researchers and health workers tackling the issues of a sedentary society where people spend too much time sitting and too little time moving, resulting in increased risk of developing chronic diseases and premature mortality.

Having these methods allows the evaluation of whether interventions and strategies to get people to sit less and move more actually work, and it is important to identify what strategies/programs work, so that these can be implemented in the population for improvement in health.

The methods were a mix of inexpensive easy to implement self-report methods and more accurate but more expensive device-based measures providing a range of methods that can be selected depending on the budget and expertise available for projects.